Theory of IRE with (α,β,γ) norm”an engineering model for higher education management (HEM) policy administration in india

Impact Factor IF Impact Factor of an indexed journal in a given year is a finite non-negative real number.. The “Impact Factor IF” of an indexed journal in a given year = the average num

an engineering model for solving HEM problems, basically seven major problems which are about: (i) How To Continuously Monitor The Real Time Progress of Research Work of the Ph.D Scholars in the Universities/Institutions in any country by a Common Rule of the ‘Ministry of HRD’ (ii) A New Improved Method for Recruitment of Teachers in Universities (iii) A New Method for Promotion Policy

of Teachers In Universities (iv) How to select the ‘Most Suitable Candidate’ for the various prestigious awards/honors in a country (v) How to restrict the publications of bad quality research papers in fake/ bad journals? (vi) How to select the true experts for every visiting team of NAAC of UGC? and (vii) How

to select the ‘Most Suitable Candidates’ to fill-up the reserved quota It is claimed that if this new theory

be implemented by the ‘Ministry of HRD (MHRD)’ in all its universities/institutions, then a huge amount

of quality-assurance can be achieved in pursuance of Excellence in Higher Education Management & Policy Administration in that Country.

An Engineering Model for Higher

Education Management (HEM) &

Policy Administration in India

Ranjit Biswas

Jamia Hamdard University, India

India, China, France, Germany, Australia, Brazil, Indonesia, Pakistan, Malaysia, USA, UK, Canada, Gulf countries and others in the world India and China are the two giant countries having a large number of in-built talents in every subject area Our model is called an engineering model because of the fact that the model works dynamically on engineering & technology based elements: internet search engines, several databases of heterogeneous big data, intelligent software, computer hardware and distributed systems, mechatronics hardware, Information Technology, Electronics & Communication Engineering, Mechatronics, Fuzzy Logic (Zadeh, 1965), Soft Computing, Big Data (Biswas, 2015a, 2015b), and of course on Mathematics & Statistics of both R-Statistics and NR-Statistics (Biswas, 2016), up to the extent

of Big Data Statistics (Biswas, 2016) Retaining the idea, core logic and philosophy behind its innovation, this model can be easily improved (extended) in future by the growth of various technologies, mainly

of the subject’s computer engineering, information technology and electronics engineering In the giant countries like India, China and other vast countries, every year a very large number of scholars take admissions for higher education, a very large number of students become graduates and post-graduates,

a large number of students enroll for Ph.D study, a large number of teachers retire in universities and institutions, a large number of fresh teachers are recruited in universities and institutions, a large number

of teachers are promoted in universities and institutions, a large number of talents are awarded various prestigious awards/honors, etc and many other academic/research oriented activities which are controlled

by Higher Education Management (HEM) & Policy Administration Consequently, the topic of Higher Education Management (HEM) & Policy Administration in such giant countries is itself a big subject and a major subject for their governments which cater to the overall academic/economic growth of the countries For a hypothetical example, in India (or China) there could be more than 10,000 eligible candidates applying against only ten vacant post of Lecturers in Mathematics advertised in a newspaper There are many other similar HEM functionalities and activities on every day and are of concern to the Government authorities on how to conclude daily work with correct, fair, transparent and successful solutions This is quite naturally not always the situation in small but academically advanced countries like Japan, Finland, Ireland, Poland, Bulgaria, Singapore, etc For the sake of smooth presentation of our new theory entitled “Theory of IRE with (α,β,γ) Norm”, we have identified the country ‘India’ and

we have developed this theory in the context of ‘India’ But the theory can be well extended and cable to other vast countries like China, Brazil, Indonesia, Pakistan, Malaysia, USA, UK, Canada, Gulf countries and in fact to any country in this world be it a small or big, without making any changes in the core philosophy/logic of the theory but incorporating slight customized adjustments in the equivalent nomenclatures of the respective country One basic assumption in the Theory of IRE is that there is

appli-no rounding-off of any numerical results Results of all numerical computations are to be made upto 3 decimal places only Bracket expressions are to be computed with priority, in any complex mathematical

or logical expression in this theory

THE MAJOR PROBLEMS OF MHRD IN INDIA IN HEM

There exists a body of the MHRD which is known as University Grants Commission (UGC) in India, but may be with different nomenclatures in other countries For instance, in Bangladesh, Pakistan, Sri Lanka, Nepal, the body name is UGC whose expanded phrase is also University Grants Commission,

in UK and HK it is also UGC but it stands for the phrase University Grants Committee, etc The main role of UGC is to look after the Higher Education Management (HEM) & Policy Administration in the

country With no loss of generality, we shall use the nomenclature UGC all through in this article, but the literature can be well customized and made compatible for any country incorporating in it the local nomenclatures and terminologies of that country suitably.

In the last three decades in particular, India took a very bold step by allowing for privately run ties in the style of USA, by opening many new IITs, by opening many new NITs offering them the status

universi-of university, by converting many colleges/RECs into universities/NITs This is a major step taken by India for the benefit of the people aspiring for higher studies in UG/PG programmes like B.Sc., B.Tech., M.Sc., LLB, LLM, MBA, M.Pharm, MBBS, BDS, M.Phil., M.Tech., and other Master Programmes and Ph.D etc The today’s concern is not about the top-graded universities/institutions of India which are few only Today’s extreme concern is about most of the other universities in India, in particular the private universities, newly born/converted universities, poorly graded Govt universities, newly born NITs, etc To ensure at least a minimum amount of quality of education at Bachelor Programmes, Master Programmes and Ph.D programmes, the “Ministry of HRD (MHRD)” or UGC may have prescribed across the country yardsticks to such universities (including private Universities and private colleges/institutions) on various quality monitoring parameters viz Teacher-student ratio, faculty qualifications, faculty strength, maximum allowable students strength in a Theory class, in a Lab/Tutorial class, lab requirements, space requirements, etc Consequently, any university/college deviating from the prescribed minimum requirements has to answer to the investigation team of the “Ministry of HRD (MHRD)” of the country Nevertheless, the real ground level scenario in such newly born poor government/private universities/NITs is pathetic The alarming consequences to India (or the concerned country) will be resulted when in future the graduates of the poor institutes will take charge and responsibilities of some office in Government or private organizations, will take decisions, will adopt self-constructed policies, will implement those policies, etc; and the extremely alarming situation will happen when they will become teachers to impart education, knowledge, ethics, morality, character elements, etc because of hidden propagation error of slow but continuous damages However, there could be 0.1% or 0.2% or more number of good graduates produced by them, whose cases are not of our concern

Country’s growth, be it in economy or technology or science or literature or health/medical or tics or law & order or in any major/minor areas, depends always upon the new generation youths who will take charge of the various kind of future responsibilities of the country as well as of the world But excellent quality of graduates/post-graduates cannot be produced until and unless the UG/PG academic programmes be taught by excellent quality teachers

poli-An excellent quality of Syllabus/Schemes/Bye-laws for the UG/PG academic programmes cannot

be designed in universities and institutes until and unless there are excellent quality teachers/experts/scientists available in the universities

An excellent quality of Lectures, Practicals, Assignments, Continuous Evaluation, Question Papers settings, Evaluation of Answer-scripts, Projects, Summer Training, Industrial Training, Internship, etc cannot be delivered/executed in a university/institutes until and unless there are excellent quality teach-ers/experts/scientists available in that university/institute

An excellent quality of Professors, Scientists, Engineers, Doctors, lawyers, IAS/IFS/IPS and other admin officers, Politicians, etc., cannot be produced in the country until and unless there are excellent quality teachers available in the universities and institutes

All these academic responsibilities are directly at the hands of the teachers, experts and scientists in the universities, institutions and research centres or organizations Teachers are the core architects of

future developments of the country The real backbone of a country’s development is thus managed by the Higher Education Management (HEM) & Policy Administration of the country.

The content of this chapter is a proposal to the Ministry of HRD (MHRD) for a huge improvement in the system of Higher Education Management (HEM), for the enhancement of academic quality in higher education in universities/institutions controlled by UGC in India (Biswas, 2015f) corresponding to the most important seven issues in HEM identified to be most prominent in the last three decades basically There are in reality many other problems and sub-problems, issues, etc which can be well controlled if these seven major problems be solved by developing a correct, precise and well documented new theories and models which should work on the basis of actual data of universal coverage

THE SEVEN IMPORTANT PROBLEMS OF MHRD (UGC) IN HEM

Problem 1

A new unique Method on: How to Continuously Monitor the Real Time Progress of Research Work of the Ph.D Scholars in the Universities/Institutions in India by a Common Rule of UGC across all the Universities in India

Proposing a new improved method to Govt of India on: “How to select the ‘Most Suitable Candidate(s)’

to fill-up the reserved quota in academics?”

Problem 7

Proposing a new improved method to MHRD, Govt of India on: “How to select the ‘Most Suitable Candidate(s)’ for the various highly prestigious top awards/honors in India?” (viz India Science Award, Shanti Swarup Bhatnagar Prize, INSA Young Scientists Award, FNA, etc.)

With no loss of generality, we introduce in this chapter the “Theory of IRE with (α,β,γ) Norm” making

it compatible with the vast country ‘India’, but as already mentioned earlier that the theory can be well extended and applicable to other countries too, incorporating the local adjustments Before providing excellent solutions to these seven problems one by one, we introduce a number of new terminologies and new measures in the subject of ‘Higher Education Management’ (HEM) These measures play key roles in our proposed “Theory of IRE with (α,β,γ) Norm”: a new model for almost a complete solution in Higher Education Management & Policy Administration in vast countries like India, China, Brazil, Indo-nesia, Malaysia, USA, UK, France, Germany, Australia, Canada, Gulf countries and others in the world The chapter here is organized with the following 23 Sections (each section having its own subsections):

• INTRODUCTION

• THE MAJOR PROBLEMS OF MHRD IN INDIA IN HEM

• JOURNAL IMPACT FACTOR (IF)

• H-INDEX, G-INDEX, in-INDEX (i10-INDEX) AND OTHER BIBLIOMETRIC INDICATORS

• INTRODUCING THREE NEW BIBLIOMETRICS, AS CORRECTIONS OF THE EXISTING NOTION OF POPULAR BIBLIOMETRICS: H-INDEX, G-INDEX AND iN-INDEX (i10-INDEX)

• INTRODUCING A POWERFUL BIBLIOMETRIC ‘BIBLIOMETRIC INDEX’ (BI) OF A RESEARCHER

• “HEM ENGINEERING CENTRE”: A HIGH COMPUTING CENTRE IN UGC

• INTRODUCING NEW IMPORTANT MEASURES FOR HEM

• JOURNAL PUBLICATIONS INDEX (JPI)

• AN IMPORTANT ISSUE WITH THE IF: SOLUTION BY NORMALIZATION

• ‘SIMPSON AREA’ (SA) OF A RESEARCHER (FOR WHOM LRY ≥5)

• TWIN SUMMARY TABLES FOR EVERY RESEARCHER

• ON PROBLEM STATEMENT 1: HOW TO MONITOR REAL-TIME PROGRESS OF PH.D WORK OF A REGULAR PH.D SCHOLAR IN A UNIVERSITY

• INTRODUCING “FIVE CONDITIONS PH.D RULE OF UGC”

• “THEORY OF IRE WITH (α,β,γ) NORM”

• ON PROBLEM STATEMENT 2: HOW TO RESTRICT POOR RESEARCH PUBLICATIONS

IN BAD/FAKE JOURNALS: A PROPOSAL TO UGC (and to UNESCO)

• ON PROBLEM STATEMENT 3: UGC MODELS FOR ‘RECRUITMENT OF TEACHERS’ IN UNIVERSITIES

• ON PROBLEM STATEMENT 4: THEORY OF IRE WITH “CODED RESERVATION FORMULA” (CRF)

• ON PROBLEM STATEMENT 5: INTERNAL PROMOTION SCHEME FOR TEACHERS IN UNIVERSITIES

• ON PROBLEM STATEMENT 6: ACCREDITATION OF UNIVERSITIES/INSTITUTES IN INDIA: HOW TO SELECT TRUE EXPERTS FOR EVERY VISITING TEAM OF NAAC?

• ON PROBLEM STATEMENT 7: HOW TO SELECT THE “MOST SUITABLE CANDIDATE(S)” FOR THE HIGHLY PRESTIGIOUS AWARDS/HONORS IN INDIA?

• CONCLUSION

• REFERENCES

• KEY TERMS AND DEFINITIONS

The “Theory of IRE with (α,β,γ) Norm” is not and cannot be an absolutely frozen theory, except its basic philosophy and architectural logic The implementation of the theory is based upon internet search data, upon the capability of searching with well coverage big data in internet, upon new and new type of updated/improved bibliometrics being developed by the scientists every decade, etc This theory may be regarded as a new area in the subject of “Big Data Statistics” introduced in (Biswas, 2016) The Hadoop and r-Atrain in ADS (Atrain Distributed System) are the most useful models developed in last decades to deal with big data of any 4Vs (Biswas, 2015a; 2015b) The future improvement of the “Theory of IRE with (α,β,γ) Norm” will certainly depends upon: How does the new subject “Big Data Statistics” grow with time, What kind of new soft-computing statistical measures in R-Statistics or NR-Statistics (Biswas, 2016) be developed in future to model excellent kind of new bibliometrics of dynamic nature for the researchers in the world, etc However, the new bibliometrics ‘Hm-index’, ‘Gm-index’ and ‘im10-index’ introduced in this chapter can surely dominate the existing corresponding most popular bibliometrics H-index, G-index and iN-index (i10-index)

We propose that our “Theory of IRE with (α,β,γ) Norm” be considered by the “Ministry of HRD (MHRD)” of the concerned country, for implementation in all the universities or higher level institu-tions across the country The complete theory can be easily implemented by a software-based HEM System of the MHRD (a good HEM software package for the “Theory of IRE with (α,β,γ) Norm” can

be well developed by any good team of programmers, and hence the issue of software development is not discussed in this chapter) JOURNAL IMPACT FACTOR (IF)

We begin with a brief note on the existing notion of Impact Factor (IF) of a journal, the notion which

is uniquely recognized by all the academic universities/institutes across the world

The notion of “Impact Factor (IF)” of a Journal was devised in 1955 by Eugene Garfield, the founder

of the Institute for Scientific Information (ISI) in 1960, now part of Thomson Reuters Impact Factors (IF) are calculated on ‘yearly basis’ for those journals that are indexed in Thomson Reuter’s annual

Journal Citation Reports (JCR) Other related journal-level metrics include: Source normalized impact

per paper (SNIP) which is a factor released in 2012 by Elsevier based on Scopus to estimate impact The PageRank algorithm is a kind of recursive impact factor that gives citations from journals with high impact greater weight than citations from low-impact journals Such a recursive impact factor resembles Google’s PageRank algorithm Before recollecting a brief about IF, we present first of all the meaning

of the simple phrase ‘Core Subject’ which will be used throughout in this chapter

Core Subject

The subjects like Mathematics, Statistics, Botany, Zoology, Sociology, Computer Science (Computer

Engineering), Electronics Engineering, Mechanical Engineering, Law, etc are the core subjects in which

usually bachelor degrees are awarded by universities Usually, the department names in a university ist in the name of core subjects For example, while ‘Computer Science’, ‘Mathematics’, ‘Philosophy’,

ex-‘Zoology’ are core subjects but an area like ‘Computer Network’ or ‘Algorithm’ or ‘Geometry’ will not

be regarded as a core subject in our discussion here They rather example of areas belonging to one or more of the respective core subjects Throughout our discussion in this article, we use the words ‘core subject’ (or ‘subject’, in short) and ‘department name’ as synonyms.

About JCR

Journal Citation Report or JCR is issued by Thomson Reuter Journal Citation Reports (JCR) offers a

systematic and objective means to critically evaluate the world’s leading journals, with quantifiable, statistical information based on citation data By compiling articles’ cited references, JCR Web helps to measure research influence and impact at the journal and category levels, and then shows the relationship between citing and cited journals The JCR is an excellent design of the database of indexed journals It offers the following important information to the researchers of the world:

1 Sort journal data by clearly defined fields: Impact Factor, Immediacy Index, Total Cites, Total Articles, Cited Half-Life, or Journal Title

2 Sort subject category data by clearly defined fields: Total Cites, Median Impact Factor, Aggregate Impact Factor, Aggregate Immediacy Index, Aggregated Cited Half-Life, Number of Journals in Category, Number of Articles in Category

3 View a journal’s impact with a five-year Impact Factor trend graph

4 Understand a journal’s citation influence and prestige with Eigenfactor Metrics — five-year metrics that consider scholarly literature as a network of journal-to-journal relationships

5 Visualize impact factor by journal category with impact factor boxplots

6 Rank journals in multiple categories

7 See how journal self-citations affect impact factor

8 Full integration with ISI Web of Knowledge lets you link from Web of Science to JCR Web; from JCR journal records to ulrichsweb.com and recent Current Contents Connect tables of contents; and to and from your library’s OPAC

Indexed Journal

In our work here, a journal is termed as an ‘indexed journal’ if it is indexed in Thomson Reuter’s annual

Journal Citation Reports (JCR), indexed by SCI/SCIE (Science Citation Index Expanded).

By the term ‘indexed journal’ henceforth in this work, we shall always mean those journals by the

above definition only, i.e which are indexed by SCI/SCIE (Science Citation Index Expanded).

Impact Factor (IF)

Impact Factor of an indexed journal in a given year is a finite non-negative real number It is calculated every year for every indexed journal For a journal its IF varies from year to year; in some year it may rise up, for another year it may fall down But it cannot be a negative number, and is always a finite number A good journal can retain good IF every year by retaining its quality

“Impact Factor” is defined as below:

The “Impact Factor (IF)” of an indexed journal in a given year = the average number of citations (in this journal or in any other indexed journal) received per paper which are published in that journal during the n number of preceding years (where n ≥ 2, but a good value of n is 5 or more).

Thus, IF of a journal for the year Y can be calculated in the year (Y+1) or afterwards, not in the year

Y or before the year Y

For example, if we choose n = 2 and if an indexed Journal has an Impact Factor (IF) of 1.3 in the year 2014, it means that its all the papers published in 2012 and 2013 has received 1.3 citations each on average in 2014 in indexed journals including itself

How to calculate IF of an ‘Indexed Journal’ in a given year?

If the journal is not an indexed journal, there is no question of computing its IF So we consider here only the indexed journals, not the other journals (i.e neither sub-indexed journals or non-indexed journals, the new terminologies which are introduced later in this work)

We explain below the method of computing IF of an indexed journal by an example (with cal data, for the sake of understanding only)

hypotheti-Consider a journal “JOURNAL OF XYZ” The ‘2014 Impact Factor (IF)’ of this journal “JOURNAL

OF XYZ” with n = 2 would be calculated as follows:

• Let A = the number of times “the articles which were published in the JOURNAL OF XYZ during

2012 and 2013” were cited by all indexed journals during 2014

• Let B = the total number of “citable items” published by that journal JOURNAL OF XYZ in 2012 and 2013 Those which are not cited will not be counted (“Citable items” means research papers

or articles, or notes; but not editorials publications or Letters-to-the-Editor, etc There is no antee that a ‘citable item’ will be or have been cited in subsequent years)

guar-Then, the ‘2014 IF’ of the journal ‘JOURNAL OF XYZ’ with two years (n = 2) consideration is equal to = A/B Clearly, IF of any journal in any year is a non-negative real number

It may be noted that “2014 Impact Factor” of a Journal ‘JOURNAL OF XYZ’ are to be calculated

in the year 2015, NOT in the year 2014; because it cannot be calculated until all of the 2014 tions of JOURNAL OF XYZ and of other indexed journals have been investigated and then processed

publica-by the indexing agency JCR Thus impact factor for the nth year can be calculated on (n+1)th year only

or later, not earlier

H-INDEX, G-INDEX, iN-INDEX AND OTHER BIBLIOMETRIC INDICATORS

The H-index is a bibliometric proposed by Jorge Hirsch in 2005 (Hirsch, 2005; Egghe, 2006a, 2006b, 2006c; Jin, 2005, 2006, 2007) A researcher has H-index equal to h if h of his N number of published papers have at least h number of citations each, and the other (N−h) papers have no more than (h-1) number of citations each Thus the H-index is always a non-negative integer The H-index reflects both the number of publications and the number of citations per publication The index is designed to improve upon simple measures such as the total number of citations or publications The index works properly only for comparing researchers working in the same field; citation conventions differ widely among dif-ferent core subjects The h-index “gives an estimate of the importance, significance, and broad impact

of a scientist’s cumulative research contributions” But the H-index has a lot of demerits too

The G-index was suggested by Leo Egghe in 2006 Given a set of publications of a researcher ranked

in decreasing order of the number of citations that they received, the G-index is the largest number such that the top g publications have received together at least g2 citations i.e most cited g papers have been cited g or more times on the average It is doubtful to the world academicians whether G-index is a bet-ter metric than H-index or whether H-index is a better metric than G-index But it is fact that both are good and have their independent in-built significance

The iN-index is the number of articles with N or more citations, where N is a natural number For

N = 10, the i10-index is simply the number of articles with 10 or more citations, the idea being that ten citations means it got looked at Similarly, the i100-index is the number of articles with 100 or more cita-tions, the i500-index is the number of articles with 500 or more citations, etc for different values of N.There are several other bibliometrics which are m-index, c-index, s-index, e-index, RG score, etc defined on the basis of citations, but they are of very particular nature and of limited significance Re-search is going on to find out a kind of absolutely best index metric applicable to all the researchers of all the subjects

How to Calculate H-Index of a Researcher Mr.X?

Let f is the function that corresponds to the number of citations for each publication Consider a researcher

Mr X We compute the H-index of the researcher X as follow:

First we order the values of f in descending order Then, we look for the last position in which f value

is greater than or equal to the position This position h is accepted as the H-index of Mr.X

For example, suppose that the researcher X has 6 publications P1, P2, P3, P4, P5 and P6 with 21,

17, 8, 5, 5 and 2 citations respectively Then, f(P1) = 21, f(P2) = 17, f(P3) = 8, f(P4) = 5, f(P5) = 5 and f(P6) = 2 Clearly the H-index of Mr.X is equal to 5

One major demerit of H-index can now be explained by an example Suppose that another researcher

Y has also 6 publications P1, P2, P3, P4, P5 and P6 with 3100, 2700, 1800, 1500, 5 and 2 citations respectively The data shows an excellence of the researcher Y having huge impact out of his top four publications, unlike the researcher X But the H-index of Mr Y is also equal to 5, the H-index of Mr.X!, i.e the H-index of both the researchers X and Y are appearing equal Thus one cannot compare the researchers X and Y by the values of their respective H-index only

INTRODUCING THREE NEW BIBLIOMETRICS, AS CORRECTIONS

OF THE EXISTING NOTION OF POPULAR BIBLIOMETRICS:

H-INDEX, G-INDEX AND iN-INDEX (i10-INDEX)

The H-index is a good indicator, but it has a lot of weakness too For an instance, consider the tion P1 of the researcher Mr X and the publication P2 of the researcher Mr Y Suppose that P1 is a single-authored paper and P2 is a multiple authored paper (five authors: Mr Y and four co-authors) Also suppose that P1 and P2 both are cited 1000 times so far by various researchers around the world Although both P1 and P2 has 1000 citations, but much more credit goes to Mr X compared to Mr Y This is a very important and significant issue to do justice to the method of estimation of index This logic is missing in the existing notion of H-index, G-index, i10-index and any other existing indices

publica-We introduce below a new and modified version of H-index called by Hm-index, which removes the inner and in-built weakness of the metric H-index caused due to number of co-authors The notation Hmhere stands for ‘H modified’ The Hm-index is constructed considering the philosophy that one paper if authored by a single researcher instead of multiple researchers should cater to full h-index to the author, and if it is multiple authored then the h value is to be shared equally among all the authors But one further level of improvement of the newly introduced Hm-index can be made considering the amount or weight of individual contribution of each author in a multi-authored publication, and proportionately sharing the value of h accordingly Truly speaking, as on today, it is an impossible task.

Introducing ‘Hm-Index’ of a Researcher

Suppose that at a certain day the researcher X has H-index equal to h Consider his top h number of publications (on the basis of number of citations) which are P1, P2, P3, …, Ph Suppose that the publi-cation Pi has ni number of authors (self and (ni – 1) number of co-authors) where ni ≥1 for each i = 1,

2, 3, …,h Then the Hm-index of the researcher X is defined by

as it gives due weightage to the single authored publications, or multiple authored publications ing to the number of authors in the publications In fact, Hm-index is a major correction of the existing popular concept of H-index

accord-Introducing ‘Gm-Index’ of a Researcher

In a similar way, one can define Gm-index Suppose that the researcher X has G-index equal to g sider his top g number of publications (on the basis of number of citations) which are P1, P2, P3, …,

Con-Pg Suppose that the publication Pi has ni number of authors (self and (ni – 1) number of co-authors), where ni ≥1 for each i = 1, 2, 3, …, h Then the Gm-index of the researcher X is defined by

Introducing ‘im10-Index’ of a Researcher

In an analogous way, one can define imN-index and in particular the im10-index of a researcher porating the similar type of corrections in the existing concept of iN-index (i10-index) The ‘H-index’,

incor-‘G-index’ and ‘i10-index’ (and even i5-index) may not be available for the beginners in research (say, for a Ph.D scholar in a university) even if he be an excellent researcher, because of short duration of time Consequently, the ‘Hm-index’, ‘Gm-index’ and ‘im10-index’ too may not exist for the beginners.The notion of Hm-index, Gm-index, im-10 index can be further revised if the piece-wise information about research contributions (weights) of each individual author in multi-authored publications can be known But as on today, probably it is not possible

(Note: There are a number of several metrics for ranking of journals have emerged over the last years in the literature in an effort to broaden the evaluation of scholarly journals (http://www.springer.com/gp/authors-editors/journal-author/journal-author-helpdesk/impact-factor/18684) For example, Eigenfactor, Google Scholar Metrics, SJR, SNIP, etc The Eigenfactor is similar to the notion of Journal Impact Factor, but weeds out journal self-citations The citation frequency as well as the prestige of the journals is taken into account The type of publication and the citation patterns of different disciplines are not considered in Eigenfactor The Google Scholar Metrics summarize the recent citations to many publications One can browse the top 50 publications in several languages, ordered by their five-year h-index and h-median metrics The SJR-SCImago includes the journals and country specific indicators developed from the information contained in the Scopus® database from 1996 onwards This metric does not consider all citations of equal weight; the prestige of the citing journal is taken into account Besides that, self-citations are not included in the calculation of SJR The SNIP (Source-Normalized Impact per Paper) measures a contextual citation impact by weighing citations based on the total number of cita-tions in a core subject It helps to make a direct comparison of sources in different core subjects SNIP especially considers the frequency at which authors cite other papers in their reference lists, the speed

at which citation impact matures All these metrics have a lot of demerits too, besides their own merits).

INTRODUCING A POWERFUL BIBLIOMETRIC

“BIBLIOMETRIC INDEX” (BI) OF A RESEARCHER

The Hm-index, Gm-index and im10-index are corrected versions of the existing popular H-index, G-index and i10-index respectively These new indices are more useful indicators to quantify research talent of a researcher because in these new indices the unfairness part of the existing popular H-index, G-index and

i10-index are removed by their ways of respective constructions But none can be identified as absolutely

best, and at the same time none can be ignored too Each of these indices independently has its own

merit and significance For example, it is very common that two researchers may have equal Hm-index but one may have much higher Gm-index than the other, and conversely The cumulative amount of Hm,

Gm and im-10 indices rather can play a better role than any of the individuals among Hm, Gm and im-10

to measure the research performance of a researcher (who is not a beginner) Consequently, we define a new powerful index called by Bibliometric Index (BI) of a researcher which is defined by:

BI = Hm-index + Gm- index + im10-index

Surely BI is a comprehensive index and better index than Hm, Gm and im-10 indices to compare the research performance of n number of researchers in a given core subject S.

“HEM ENGINEERING CENTRE”: A HIGH COMPUTING CENTRE IN UGC

Although UGC like all other government offices is using computers/softwares for all its daily ing, but there are need of high computing very rich and large labs in a centre in UGC called by “HEM Engineering Centre” with one rich Big Data Computer Lab, with many other IT Labs, one Electronics Lab and other labs, with sufficient number of computers and other engineering equipments and infra-structures This is a mandatory requirement for successful implementation of the engineering model of Higher Education Management (HEM) proposed by us in this chapter The “HEM Engineering Centre” will play a very important role in HEM in a country like India having a large number of universities, institutions and colleges Even as a mandatory requirement, the administration of this “HEM Engineering Centre” is to be controlled by engineers only (preferably IT engineers or software engineers or electron-ics engineers) with the following hierarchy:

function-Director

Associate Director

Assistant Director

Sr Technical Assistant

Technical Assistant, etc

The Director is the overall in charge of the “HEM Engineering Centre,” who must be a very senior and exceptionally talented M.Tech & Ph.D degree holder in Computer/IT/Electronics engineering All data processing job, website maintenance and updates, uploading of all HEM data of national importance, etc are done by the office of the Director The Big Data Computer Lab of the “HEM Engineering Centre” should preferably work in ‘Atrain Distributed System’ (ADS) using the data structures Atrain and Train which are exclusively suitable for big data (Biswas, 2011, 2012, 2013, 2015a, 2015b) The importance

of the huge roles and responsibilities of the Director is one of the major keys of UGC for successful implementation of the “Theory of IRE with (α,β,γ) Norm” in all the universities across the country.For Higher Education Management (HEM) & Policy Administration in vast countries like India, China, France, Germany, Australia, Brazil, Indonesia, Pakistan, Malaysia, USA, UK, Canada, Gulf countries and others in the world, where there are large number of enrollments every year, large number of recruit-ments every year, large number of promotions every year in large number of universities, institutions and colleges, no proper monitoring of quality can be done without a precise and rigid organizational structure of the “HEM Engineering Centre ” The justification behind the requirement of so many man-power (engineers) will be clearly understood while arriving at the end of “Theory of IRE” in this chapter

INTRODUCING NEW IMPORTANT MEASURES FOR HEM

Making excellence in HEM is not an easy task Both India and China have been following traditional style in HEM The government does not have any strong mathematical models in the policy administra-

tion by which a continuous excellence can be achieved correctly, fairly and transparently in HEM with guarantee The existing methods followed are all obsolete methods The proposed Theory of IRE in this article provides a momentum in improving the HEM because of its powerful scientific and engineer-ing construction and a comprehensive architecture Before introducing new important measures for the

‘Theory of IRE’, we define few more terminologies which will be frequently used in our chapter In our proposal here henceforth, by IF (Impact Factor) we mean only the IF of Thomson Reuters, not of any other organizations or agents

‘List of AOIA’ of a Core Subject

Corresponding to every core subject, there are some indexing agents in the world which seem to be growing well, doing well, seem to be promising, but presently not up to the excellence of SCI/SCIE The UGC has an excellent pool of “(α,β,γ) normed Type-1 experts” with respect to some pre-fixed high value of (α,β,γ) corresponding to every subject (but different for different subjects) to give excellent judgment on who are the other indexing agents in the world which seem to be growing well, doing well, seem to be promising, and acceptable temporarily

(Note: the new notion of “(α,β,γ) normed Type-1 experts” in the ‘Theory of IRE’ is explained later

in this article)

The abbreviation AOIA stands for “Acceptable Other Indexing Agents” It is dependent upon the concerned core subject of the area of research This is a list of other indexing agents By the word ‘oth-

er’, we mean here the agents other than the Thomson Reuter’s annual Journal Citation Reports (JCR)

indexed by SCI/SCIE For every core subject, UGC will display a corresponding List of ‘Acceptable

Other Indexing Agents’ (AOIA) in its own website List of AOIA is different for different core subjects UGC will never display the list of journals, but the list of ‘Acceptable Other Indexing Agents’ (AOIA)

in its website UGC will update all these lists every year once in the month of January All the research scholars of all the universities in India may look at the updated list in UGC site in January every year.For a hypothetical example, corresponding to the core subject “Computer Science”, the following list may be displayed by UGC in its own website as its prescribed List of ‘Acceptable Other Indexing Agents’ (List of AOIA) approved by an excellent pool of “(α,β,γ) normed Type-1 experts” in Computer Science identified by UGC

AOIA for “Computer Science”: Scopus, Academic Journals Database (Switzerland), Referativnij Zhurnal (Russia), Zentralblatt fur Mathematik (Germany), MathSciNet (American Mathematical Soci-ety), Mathematical Reviews, Ulrich, Zeitschriften, IEEE Xplore

Sub-Indexed Journal

There are some journals in the world in every core subject and seem to be doing well and growing well but presently not ‘indexed journals’ as per our Definition presented earlier If such a journal on a core subject be indexed by any of the corresponding ‘List of AOIA’ prescribed by UGC, then it is called a Sub-Indexed Journal in our Theory of IRE

Non-Indexed Journal

There are a number of journals (having ISSN) which are neither indexed journals nor sub-indexed nals However, they may be indexed by some other agents not listed in the ‘List of AOIA’ of UGC or may not be indexed at all Such a journal is called a Non-Indexed Journal in our Theory of IRE.Unfortunately, most of the journals in the world in any core subject nowadays are of this category, unlike the situation of the preceding century

jour-The next definition is proposed by us with the objective for not blindly discouraging the researchers

to make publications in the sub-indexed journals too (if not in indexed journals) Decision is to be taken

by the researcher himself by doing self-assessment of the quality of the work done

Provisional Impact Factor (PIF)

Only the sub-indexed journals can qualify to possesses PIF, neither indexed journals nor the non-indexed journals The PIF of a sub-indexed journal in a core subject in a given year is equal to the minimum value

of the IF values of all the indexed journals in that core subject in that year The PIF of a sub-indexed journal may vary every year

To check the list of indexed journals and their IF, one could visit the sites:

Which Journals Can Qualify to Possesses an IF?

If a Journal does not qualify to be indexed by Thomson Reuter’s annual Journal Citation Reports (JCR),

then question does not arise of having an ‘IF’ for this journal Only indexed journals can qualify to Thomson Reuter’s to possesses IF There is no question arises like: “Whether an indexed journal can have PIF?” It is an invalid question, because it is not a sub-indexed journal and it already possess IF.However, a journal (not an indexed journal, but either a sub-indexed journal or a non-indexed journal) may carry a value of some kind of so-called IF which it prints on it and which is usually computed by the concerned journal authority itself or by some private unauthorized organization/agent, but those type

of IF are not to be considered to be valid in our ‘Theory of IRE’ here (figure 1) There should not be any confusion in it To get more information about IF and fake IF, one could visit the link: http://www.oajournals.info/impact-factor-2012-list/, and http://fakejournalss.wordpress.com)

WHICH JOURNALS CAN QUALIFY TO POSSESSES AN PIF?

Only the sub-indexed journals can qualify to possesses PIF, neither indexed journals nor the non-indexed journals PIF varies from year to year for every sub-indexed journal

“Impact Factor Score” (IFS) of a Researcher for Every Publication

For a beginner (say, a new researcher or a Ph.D Scholar in a university), the number of citations of their first or second publication may not come into birth during the short tenure of Ph.D scholar which is the beginning year(s) of him Consequently, the Hm, Gm or im10 index are not applicable to his case to quan-tify his research performance, even if he be of an excellent research potential But for such a beginner,

a publication in a “good journal of good IF” certainty guarantees the quality of his publication, at least

a minimum guaranteed amount can be always certified Consequently, a beginner for whom Hm or Gm

or im10 is not available presently which he can use for self-assessment of his own research performance, the IF of the journals is the only authenticated indicator which can guarantee him for his self-satisfaction that his publications are good, because the journals with good IF do always follow a rigorous evaluation/review system by a true implementation procedure involving top quality reviewers/experts in the area concerned With this philosophy in mind we introduce below the notion of “Impact Factor Score” (IFS)

of a Researcher (beginner or senior) corresponding to each publication of him

Impact Factor Score (IFS) is a finite non-negative real number It is a score earned by a researcher (a Ph.D scholar or a senior researcher or a teacher or a Scientist) corresponding to each publication of research paper by him in an indexed or sub-indexed journal Suppose that a research paper P, jointly authored by x number of authors, has been published in an indexed or sub-indexed journal “Journal of ABC” in the year Y Then by virtue of this publication P, each of these x number of authors earns an individual score called by ‘Impact Factor Score’ (IFS) which is equal to the non-negative real number i/x, where i is the IF or PIF of the journal “Journal of ABC” in the year Y It is obvious that an IFS can not be a negative number, and is always a finite non-negative real number IFS plays a very important and a highly significant micro level role in our proposal on “Five Conditions Ph.D Rule of UGC”, which

is proposed in subsequent section here

Figure 1 Three types of journals in a subject S

We explain IFS by a hypothetical example below (not real data):

Suppose that a research paper entitled “A Dynamic Fuzzy Routing Algorithm” has been published

by three authors in an indexed or sub-indexed journal “International Journal of Information Security and Management” details of which is as mentioned below:

Ranjit Biswas, Supriyo De and Bashir Alam, A Dynamic Fuzzy Routing Algorithm, International Journal of Information Security and Management, Vol.8(3) (2009) 214-226

Suppose that the IF or PIF of this indexed or sub-indexed journal “International Journal of tion Security and Management” in the year 2009 is 1.41

Informa-Then by virtue of this publication, the author Ranjit Biswas earns IFS = 1.41/3 = 0.47 in his credit Similarly, the author Supriyo De earns IFS = 0.47 in his credit, and the author Bashir Alam too earns IFS = 0.47 in his credit

However, instead of equal share of IF or PIF among the authors, we also propose for proportionate distribution of the IF corresponding to each publication to define the term “Proportional IF Score (PIFS)” for different authors according to individual contributions We do not recommend that this metric PIFS

be applicable initially to the private universities or to the lower graded Govt universities, in particular while one author be a Ph.D scholar Nevertheless, we present below the definition of PIFS for our future direction of research work only

“Proportional Impact Factor Score” (PIFS) of a

Researcher for Every Publication

Proportional Impact Factor Score or PIFS is a finite non-negative real number It is a score earned by researchers (Ph.D scholars or Professors or Scientists or teachers, etc) corresponding to each publication

of research paper in indexed or sub-indexed journals on the basis of the amount of actual individual contribution of all the authors of the paper Suppose that a research paper P, jointly authored by x num-ber of authors A1, A2, A3, …, Ax has been published in an indexed journal “ABC” in the year Y Suppose that, in this work, the contribution of the author Ai (i = 1, 2, 3, …, x) is wi% Then, by virtue of this publication P, each of these x number of authors Ai earns an individual score called by ‘Proportional Impact Factor Score’ (PIFS) according to his amount of contribution which is equal to the non-negative real number α.wi/100, where α is the IF or PIF of the indexed or sub-indexed journal “ABC” in the year

We explain PIFS by a hypothetical example below (not real data):

Suppose that a research paper entitled “A Dynamic Fuzzy Routing Algorithm” has been published

by three authors in an indexed or sub-indexed journal “International Journal of Information Security and Management” details of which is as mentioned below:

Ranjit Biswas, Supriyo De and Bashir Alam, A Dynamic Fuzzy Routing Algorithm, International Journal of Information Security and Management, Vol.8(3) (2009) 214-226

Suppose that the IF or PIF of the indexed or sub-indexed journal “International Journal of Information Security and Management” in the year 2009 is 1.41 Also suppose that the contribution of the author

Ranjit Biswas in this work is about 50%, the contribution of the author Supriyo De in this work is about

20%, the contribution of the author Bashir Alam in this work is about 30%.

Then by virtue of this publication, the author Ranjit Biswas earns PIFS = 1.41 × 50/100 = 0.705 in his credit Similarly, the author Supriyo De earns PIFS = 1.41 × 20/100 = 0.282 in his credit, and the author Bashir Alam too earns PIFS = 1.41 × 30/100 = 0.423 in his credit

How to Earn IF/PIF from International Conferences?

Many of the International Conferences being of high standard (say, IEEE Conferences) publish the selected excellent papers in indexed or sub-indexed journals too, besides publishing all the accepted papers in their own Proceedings Consequently, by contributing papers in such type of good conferences, a researcher may also earn IF or PIF, if his paper does also come in their list of selected papers for publication in their indexed or sub-indexed journals The ‘Call for Paper’ (CFP) for a good conference always announces the names of the journals where the conference organizer will publish selected papers, besides publishing all the accepted papers in the Conference Proceedings

LRY of a Researcher at a Real Instant of Time D

It is fact in almost 100% cases that for a teacher or a scientist or a statistical officer or a computer engineer

or an economist or holding any post related to academic/research, the research work for him commences after his acquiring of Master degree Exceptional cases are always exceptional, one extraordinary boy may produce a new theory even while studying at his school/bachelor, or in contrast one person may start research and produce a revolutionary theory at the age of 65 without producing any result earlier But in general, ignoring those exceptional cases, for any researcher his research work is expected to start after his Master degree The “Length of Research Years” (LRY) of a researcher is a dynamic value which

is to be computed by a simple straightforward arithmetic It is basically the age of his Master degree Consider together the month and year of final semester/year marksheet(pass) of the Master degree of the researcher denoted by M = (m,y) This paired value M is to be considered as a single entity data and for a given researcher it is obvious that the value M is fixed for him for lifetime

Now consider any date D after the date M In the Theory of IRE, the “Length of Research Years” (LRY) of a researcher at a real instant of time D is the real number N/12 where N is the total number

of months (including the extreme months: the month of M and the month of D) counting from M to D

It is to be noted that the value of LRY of a researcher does not get effected whether he does research or does not do research after his Master degree

JOURNAL PUBLICATIONS INDEX (JPI)

This is true that the quality of research work of a researcher cannot be judged by the IF of the journals only, except that a guarantee about some amount of quality of his publication can be blindly certified Each of the Hm-index, Gm-index, im10-index and surely the BI is rather a good indicator to be considered for adjudging the research performance of the researcher But for a researcher who is the beginner in doing research, in particular for a Ph.D scholar who has just started publishing papers for his Ph.D degree, the Hm-index or Gm-index or im10-index or the BI (or any such index which are based on the

number of citations) cannot be used to estimate the progress of his research work in quality or quantity Nevertheless, a journal of good IF guarantees that any publication in it will be of good quality, at least maintaining a quality of minimum acceptable threshold value For example, a publication in any of the IEEE Transactions, ACM transactions, in NATURE, in SCIENCE, etc will be surely of good quality by default Therefore, for a Ph.D scholar or for a beginner (or even for any senior researcher), publications

in journals of good IF surely ensures the quality of publications, but may not estimate exactly how much

is the quality We here make use of the IF/PIF metric to ensure the progress of a Ph.D research scholar

in our Theory of IRE But we do not even ignore it for the senior or experienced researchers too For senior or experienced researchers, we use it as one input data only, out of the several other input data,

to judge their research potential and talent

Consequently, in this section we define a new measure Journal Publications Index (JPI) for every researcher (beginner or senior) There are three types of JPI for every researcher as below (see figure 2):

1 YJPI, used for evaluating his yearly performance

2 CJPI, used for evaluating his cumulative performance, and

3 AJPI, used for evaluating his average performance

“Yearly Journal Publication Index” (YJPI) of a Researcher at the Year Y

Yearly Journal Publication Index or YJPI of a researcher at the year Y is denoted by the notation (YJPI)Yand is defined by the yearly earned sum total of all the IFS of him at the year (Y-1) By a year, we mean the English calendar year from January to December

Thus, by default the YJPI = 0 in the first year of any researcher in his research career

“Cumulative Journal Publication Index” (CJPI) of a Researcher

Cumulative Journal Publication Index or CJPI is a finite non-negative real number possessed by the searchers (Professors, Scientists, teachers, research scholars, etc) at a given point of time, and is defined by:

re-Figure 2 Three types of JPI for every researcher

CJPI of a researcher at a point of time = Sum of his all IFS earned so far in his research career, at that point of time.

CJPI is a kind of cumulative score earned by researchers by earning IFS, and hence CJPI of a searcher varies with time It is obvious that CJPI of a researcher is a non-decreasing index because it is

re-a kind of cumulre-ative stre-atistic For re-any resere-archer, his CJPI begins with the vre-alue 0, re-and then it increre-ases with good publications of him in indexed or sub-indexed journals with time The CJPI does not increase

by way of publications in non-indexed journals or in poor journals or by contributing in such type of Seminars/Conferences which cannot add any PIF to the researcher

Thus, for any researcher if we draw his “CJPI - t” graph which is a graph of “CJPI” against the pendent variable ‘time t” where t runs from the value 0 i.e from the initial day of his research, then we can see that it is a continuous non-decreasing step-up graph with

inde-d

dt (CJPI) ≥ 0 at every point of time

For a good researcher, the number of steps will be more in the “CJPI – t” graph For an excellent researcher, there will be one more observation that most of the step-heights will be larger in the graph

A Hypothetical Example

Recollect the previous hypothetical example of publication jointly authored by the three researchers: Ranjit Biswas, Supriyo De and Bashir Alam Suppose that prior to this publication, CJPI of the researcher Ranjit Biswas was 19.21, CJPI of the researcher Supriyo De was 13.89 and the CJPI of the researcher Bashir Alam was 17.63 in their respective credits

Then, by the performance of this publication, the updated CJPI of the researcher Ranjit Biswas is now 19.21 + 0.47 = 19.68, the updated CJPI of the researcher Supriyo De is now 13.89 + 0.47 = 14.36, and the updated CJPI of the researcher Bashir Alam is now 17.63 + 0.47 = 18.10

It is quite obvious that for every researcher,

CJPI (at a year Y) ≥ YJPI (of the year Y or of any preceding year).

If YJPI of a researcher is zero in some year, it means that the researcher could not publish any research paper during the previous year Thus at the end of first n years of research by a researcher (the consecutive years being denoted by Y1, Y2, Y3, …., Y(n-1) and Yn, where Y(i+1) = Yi + 1) the following equality holds:

where (YJPI)Y is the YJPI of the researcher at the year (Y+1) It is obvious that (YJPI)Y1 = 0

Average JPI (AJPI) of a researcher at the year Y

The ‘Average JPI’ (AJPI) of a researcher at the year Y is equal to CJPI

LRY , where LRY is the ‘Length

of Research Years’ of the researcher in the year Y

AN IMPORTANT ISSUE WITH THE IF: SOLUTION BY NORMALIZATION

There are few core subjects in which number of indexed or sub-indexed journals (even, non-indexed journals) in the world are too less (high) compared to the number of good research papers or the amount

of good research work being carried out in those core subjects by the world researchers In some core areas the indexed or sub-indexed journals usually have high IF (PIF), whereas in some core areas the indexed or sub-indexed journals usually does not have high IF (PIF) but have appropriate and reasonable

IF (PIF) Consequently, the researcher of some core areas earn IFS at higher amounts automatically by every publication i.e CJPI of them increases at higher rate of growth; whereas the researcher of other core areas earns IFS at lower amounts by every publication i.e CJPI of them increases not at higher rate of growth but at appropriate rate only This is an unsolved anomaly being faced by the researchers

in the world We propose a new method below to solve this problem by the method of Normalization The Normalization process brings all the subjects in a common scale On imposing normalization, the heterogeneity arising out of nature of various subjects is removed, and all subject areas apparently seem

to be treated by a common thermometer For this first of all we define the term AIF

“Average Impact Factor” (AIF) for a Core Subject S

The list of SCI/SCIE indexed journals (not sub-indexed journals or non-indexed journals) is readymade available in the Thomson Reuters website thomsonreuters.com The total number of SCIE covered journals in 2015 is less than 9000, and SCI covered journals in 2015 is less than 4000

Consider now any particular core subject S in a given year Y Suppose that the number of SCIE indexed journals in the world in this core subject S is n Surely n is not a large number whatever be the core subject S It will be either a two-digit integer or at most a three-digit integer, depending upon the nature of the core subject Since we are considering only SCIE indexed journals here on the subject S

of the year Y, each of them has a unique IF (the IF is available for indexed journals subject-wise in the Thomson Reuters website thomsonreuters.com) Thus, corresponding to these n number of SCI/SCIE indexed journals in the subject S, there are n number of Ifs which are n number of positive real numbers, need not be all distinct always The arithmetic mean of these n data is called the Average Impact Factor (AIF) of the core subject S in the year Y, and is denoted by aY(S) or simply by a(S) The value of a(S) for each subject S will be published by UGC every year (figure 3)

Normalized YJPI of a Researcher

Normalized Yearly Journal Publication Index (or Normalized YJPI) of a researcher at the year Y is defined as below:

Normalized YJPI of the researcher X in the year Y = YJPI

a s( ) , where YJPI of the researcher at the year Y is the yearly earned sum total of all the IFS of him at the year (Y-1)

Normalized CJPI and Normalized AJPI of a researcher at the year Y

Consider a researcher Mr.X in the core subject S Consider a year Y Then the following measures can be regarded as normalized measures in the year Y:

Normalized CJPI of the researcher X in the year Y = CJPI

varia-It is fact that in some core subjects the IF values of almost all the indexed journals are usually low, and in some core subjects the IF values are usually high

Let us suppose that in the year Y we have

CJPI(X) = 5, CJPI (Z) = 6

LRY(X) = 6.2, LRY (Z) = 5.4

Suppose that, in the year Y we have from the UGC data

Figure 3 Normalization of all the three types of JPI (for every researcher)

aY(Mathematics) = 0.4 and aY(Nanoscience) = 0.8

It is quite obvious that whatever be the individual core subjects, both X and Z may not be of equal

or even almost equal talent as a researcher

But there must exist some method for measuring research-talents, for comparing the talents and for ranking of them The beauty of the normalization process is that; it can provide solution to this problem

Therefore, in the year Y considered here, we are in a position to compare the two researchers X and

Z, although they are of different core subjects The researcher X seems to be better researcher than Z

‘SIMPSON AREA’ (SA) OF A RESEARCHER (FOR WHOM LRY ≥5)

The Simpson Area (SA) is a good measure to evaluate the research-talent of a researcher, and applicable

to those only for whom LRY ≥ 5, i.e who have at least 5 completed years of research experience, even

if no research work done during any year after obtaining Master degree It is mentioned earlier that the value of LRY of a researcher does not get effected whether he does research or does not do research after his Master degree

Consider a researcher having n completed year of research experience, where n is an integer (≥5) Construct the following table (table 1) for the researcher:

Table 1

LRY No 1 2 3 ……… (n-1) n

Here the value of n may be odd or even We define Simpson Area of a researcher for odd and even

Here, Residue = sum total of the IFS earned by him during this ongoing incomplete year only (because the researcher has made n completed research years so far, and he is currently at some interim point of his (n+1)th year of his research tenure).

TWIN SUMMARY TABLES FOR EVERY RESEARCHER

Two summary tables are the important key twin tables for a researcher showing all details information about the research performance of him These two dynamic twin tables are:

1 BI Computing Table

2 JPI Computing Table

These twin tables are called Summary Tables of a researcher, which can be updated by the concerned researcher at any time he desires, as many time he needs to do They are called ‘twin tables’ in the sense that whenever these two tables are to be submitted by the researcher to any authority, both must be computed on the same date The date of Search for both the tables must be same (it is strongly recom-mended that whenever a need for submission arises (say, for a job, for an interview, for a fellowship, etc.)

a researcher fill-up both of the twin tables on the same day; the necessary searches will not take much time except few minutes only) However, in case two consecutive days or even three consecutive days are used to fill-up these two tables, the researcher will record the most senior date in both the tables Twin summary tables are not suitable for the beginners (say, for a Ph.D scholar in a university), but they are strongly encouraged to make these twin tables and update them time to time even if some of the items

in these tables cannot be filled-up or if some of the items in these tables are not applicable, and even

if these twin tables are not useful presently for any purpose for them The role of these twin summary tables is highly significant in the ‘Theory of IRE’.

BI Computing Table

The “BI Computing Table” of a researcher contains the information which are required by him to pute his BI This table is to be filled up by the researcher on the concerned date of his interest (say, for applying for a job or for a fellowship or for a promotion or for an award/honor, etc.)

com-Although the h-index can be manually calculated using citation databases or using automatic tools, but there are free or subscription-based databases such as Scopus, Web of Knowledge, etc which provide automated calculators In July 2011 Google offered a simple tool which allows researchers to keep track

of their own citations and also produces an h-index and an i10-index However, there are few specific databases applicable subject-wise, viz INSPIRE-HEP database which can automatically calculate the h-index for researchers working in high energy physics But each database is likely to produce a differ-ent h for the same scholar, because of different coverage For the sake of homogeneity, in the Theory of IRE here we presently use ‘Google Scholar’ only as a common tool for everybody, for all researchers, ignoring any sense of biasness or unbiased with any tool Therefore, the BI of a researcher is presently proposed to be calculated using ‘Google Scholar’ as a common tool across the subjects, across the uni-versities, across the country However, with the discovery of better tools, the choice of database search engine may be updated in future (table 2)

Table 2 BI Computing Table

Rank Title of the Paper

(i) Journal Name:

(ii) Year of Publication:

(iii)Vol., Page No.:

(iv) Publisher:

No of Authors (including self)

No of Citations (in descending order)

2 The common search engine to be used is: Google Scholar

3 The citations of all the papers is to be searched in one day or in two consecutive days.

4 Date of Search (on which data are filled-up by the researcher):

5 LRY on this date of search =

6 All the data in this BI Table are to be filled-up correctly by the researcher on the date of search.

7 Index values (to be calculated from the BI table): Hm-index = xxx, Gm-index = xxx, im10-index = xxx.

8 BI = (Hm-index + Gm-index + im10-index) = xxx.

JPI Computing Table

The following table is called “JPI Computing Table” which is to be filled up by the researcher on the concerned date of his interest (say, for applying for a job or for a fellowship or for a promotion or for

an award/honor, etc.) It contains the information which are required by him to compute his all type of JPI values (Table 3)

With the introduction so far of several new terminologies, new bibliometrics, new indices, new sure parameters, new tables, etc., we are now well equipped to proceed into the depth of the “Theory

mea-of IRE”, to solve the identified seven major problems mea-of HEM, one by one, in the subsequent sections

ON PROBLEM STATEMENT 1: HOW TO MONITOR REAL-TIME PROGRESS

OF PH.D WORK OF A REGULAR PH.D SCHOLAR IN A UNIVERSITY.

One major weakness of many of the private or newly born/converted universities/NITs is that they do not have even the minimum number of Ph.D qualified teachers because of non-availability, despite re-

Table 3 JPI Computing Table

Sr No. Title of the Paper with details of (i) Journal Name: (ii)Vol., Page

No.:

Year of publication (including self) No of Authors

IF or PIF of the journal (on the year of publication)

1 Journal Publications in JPI Computing Table are to be furnished in ascending chronological order starting from the very first

publication and then in chronological increasing order according to the date of publication of each paper The last published paper will be the bottom most entry here Only those publications which are in indexed and sub-indexed journals are to be recorded Publications in non- indexed journals are not to be recorded in this table.

2 Date of Search (on which data are filled-up by the researcher):

3 LRY on this date of search =

4 All the data in this JPI Table are to be filled-up correctly by the researcher on the date of search.

5 JPI values (to be calculated from the JPI table): CJPI = xxx, AJPI = xxx.

6 Year-wise all YJPI in the format like: (YJPI,Year), till this date on which data are filled-up by the researcher starting from his first year

of research which is assumed in the Theory of IRE to be the year of getting his Master degree, separated by comas For example, if the very first year of a researcher is 2005, then he is to record here all YJPI like: (1.02, 2005), (0.52, 2006), (0.61, 2007), …… etc.:

7 a(S) =

8 SA =

peated advertisement in newspapers or because of low salary structure or because of some other reasons Even if they have Ph.D qualified teachers, it can be observed that most of these Ph.D holders do not possesses good quality Ph.D Most of them do not know how to guide Ph.D scholars because they too did not receive proper guidance from their respective own supervisors during their respective period of pursuing Ph.D Thus the situation is a kind of “error propagation” to the next generation from the present generation receiving from the elder generation But any university, even be weak or of very poor quality,

is free to admit Ph.D scholars, sometimes in a large quantity too, and sometimes with high admission fees Consequently, it is strongly felt that there must be a kind of real-time yardstick to be effective from the very first day of each Ph.D scholar after registration (admission) which all the Ph.D scholars as well as the supervisors and the university officers must be aware of, in order to ensure a minimum qual-ity in the new generation of Ph.D.’s across all the universities in the country in order to bring at least a minimum prescribed amount of quality in every Ph.D.’s It is missing in the existing UGC norms Time has now come to understand that production of poor Ph.D.’s will have both direct and indirect serious consequences to the country’s academic standard and in particular to the quality of future generation teachers upon whom the country will be dependent(!) If teachers are regarded to be the backbone of a country (as said in India), then is it not a very serious type of “error propagation” (forward chain pollu-tion) to the future academicians and hence to the overall growth of the country concerned? This error propagation is never visible directly It is like a very slow poisoning, by damaging silently in a hidden way the future growth of the country In every country, it is the teachers who produce doctors for the future, engineers for the future, teachers for the future, scientists for the future, lawyer for the future, … , etc The “error propagation” (forward chain pollution) penetrating into the stages of a beginner/learner from primary schools to universities is surely a kind of slow-poison to India’s future health at every real field Today apparently we may feel that there is no threat for we Indians in our economic growth But

in case these errors are not properly identified and eradicated at real time, it could be too costly to India

in the year 2020 onwards to give smile to the world as a superpower Repair of damage if identified late will be surely very costly to India

The main objective of this chapter is to introduce an excellent HEM System & Policy Administration for the universities in India (in particular, for the private universities, newly born/converted universities/NITs, poorly graded Govt universities of India) We begin with the first problem (Problem-1) of the seven major problems of MHRD in HEM identified earlier in this article For this we need to develop

a very rich structured method which can help the Ph.D supervisors to monitor very transparently the time-to-time progress of the research work being carried out by their Ph.D scholars, and which can ensure the concerned universities about a precise and quantified amount of excellence in the qualities of the degrees to be conferred The method can ensure the quality of research work and publications of a Ph.D scholar, can provide a simple way for making self-assessment by a research scholar himself about his performance and progress time-to-time, and can also provide a simple way to understand whether the work done so far is sufficient enough in terms of quality and quantity for submission of the thesis The method can easily help the Guides/Supervisors to keep complete control over the performance of research scholars with time during the tenure of guidance by a mercury guided thermometer The exist-ing rules/norms/methods of UGC to monitor real-time progress of Ph.D work of a regular Ph.D scholar

in a university are not rich enough logically or scientifically, rather very much imprecise and hence not fruitful There is no method/norms/rules presently existing with UGC to monitor the universities/institu-tions on the proper assessment about the exact phase of actual completion of research work of a Ph.D scholar which is suitable for submission as a Ph.D thesis as a partial fulfillment for the award of Ph.D

degree There is no minimum standard precisely prescribed or formulated and well documented by UGC

by which a Ph.D scholar can understand by self-assessment that his work is (is not) sufficient enough for submission now in the form of a thesis Sometimes, due to non-availability of a well-constructed norms, a honest Ph.D scholars too depends upon the following two parameters by mistake:

(i) Volume of work done so far and (ii) How many years of Ph.D tenure are completed so far.Even it is fact that in many cases, dishonest or poor performer Ph.D scholars try to exploit these two parameters as their important eligibility criteria to submit their thesis

In this section a very useful and consolidated method called by “Five Conditions Ph.D Rule of UGC” has been introduced which are to be fulfilled by a research scholar as mandatory requirements for submission of his thesis for which the supervisor is the all in all to check/verify all the five constituent conditions individually and finally to validate the eligibility for submission The author is quite sure that

by adopting this proposed “Five Conditions Ph.D Rule of UGC”, the “Ministry of HRD (MHRD)” or the universities can well ensure a minimum standard on the research work carried out by the Ph.D scholars time-to-time, in particular prior to submission of the thesis, and thus MHRD can achieve a huge amount

of homogeneity among the qualities of the Ph.D degrees conferred by different universities across the country Out of the five conditions, the first four conditions are to be fulfilled by the Ph.D scholars (and

to be verified by the supervisors) and the 5th condition is to be fulfilled by the concerned universities

In fact, there is no such model exists in UGC or in the “Ministry of HRD (MHRD)” or in the University Guidelines which can help the Ph.D scholars themselves to measure and keep record continuously and thus to self-assess his research progress with time, which can help the Guides/Supervisors (and hence the concerned universities) to self-assess the minimum standard of a Ph.D thesis to estimate whether

it is eligible for submission It is also fact that although India is having a large number of universities, Engineering Institutions, Medical Institutions, Management Institutions, Law Institutions, etc., but in reality many of them are starving due to acute shortage of quality Guides/Supervisors for Ph.D guid-ance, although there could be a number of long experienced Ph.D teachers and Professors guiding the scholars Nevertheless, our proposed model of “Five Conditions Ph.D Rule of UGC” can standardize the higher education in India up to an excellent limit, can bring a homogeneity in the quality of the future Ph.D.’s across the country up to an amount of very high extent, can ensure the quality of all the future Ph.D.’s to be higher than a minimum quantified prescribed level, in particular while private universities/institutions or newly born/converted universities/NITs or poorly graded Govt universities are concerned

in our country The proposed “Five Conditions Ph.D Rule of UGC” method is not only applicable to the Ph.D scholars but can well be extended to the BS/B.Tech., MS, M.Sc., MBA, M.Pharm, M.Phil or M.Tech or any Master Programme too, where there is an amount of research work required for partial fulfillment of the degree

A Ph.D programme gives a chance to push the frontiers of human knowledge Unfortunately, this prestigious and important degree has fallen prey to commercialism too It is just because of the fact that

a quantified excellent model of a real-time yardstick not prescribed by the “Ministry of HRD (MHRD)”

or by the universities to measure time-to-time the quality of research work being done by the Ph.D scholars in their universities It is extremely shocking fact that this weakness of MHRD/UGC is being exploited by many research scholars, even by many supervisors/guides, by many thesis evaluators, by many thesis reviewers and hence sometimes by the concerned universities too, ultimately This has been

causing a huge damage to the Ph.D quality in India in a very hidden and silent way, in a very able way and like a slow poisoning to the country.

untrace-A researcher (be it a Ph.D scholar or a teacher or a scientist) should certainly agree with the losophy that he/she has grown and reached today this level of height in the academic society with his own subject, and hence it is his moral responsibility that by way of his research work the same subject should also grow and get further height up to some extent And only then a ‘subject’ too will remember the Ph.D scholars or researchers forever

phi-Ph.D Degree by Quality of Research (Not by Publications)

A basic question quite naturally arises: “why publications are required to get a Ph.D degree?” Yes, publications should not be mandatory for submission of Ph.D thesis in a top class university, only a high class of research work is required to enhance the subject sphere by a reasonable amount which au-tomatically will lead to Ph.D degree Truly speaking, there are a number of Nobel Prize winners whose Ph.D thesis did not have any publications But in our theory here we have to ignore such very special cases for the sake of safe-side to maintain our quality which is surely at serious stake presently in India

In this work we solve all the above cited issues by proposing few real-time dynamic yardstick models which can be well imposed in the universities (in particular in the private universities or in newly born/converted universities/NITs) by the “Ministry of HRD (MHRD)”, initially for about ten years at least, and slowly may be revoked thereafter once a stable standard is achieved, however on ‘case to case’ basis

We do also want to say that quality or a minimum quality can be just retained by imposing yardsticks, but true excellence of any university must come from the inside of its heart without carrying any imposed yardstick from the side of UGC or MHRD

Before presenting the “Five Conditions Ph.D Rule of UGC”, we introduce few very useful new indices

“Ph.D Work Index” (PWI) of a Ph.D Scholar

The Ph.D Work Index (PWI) is a finite non-negative real number possessed by each Ph.D research scholar at a given point of time during his tenure of Ph.D work in his university/institute where he is enrolled It is an important measure to ensure the real-time progress of Ph.D scholar with quality re-search work being carried out If one researcher is not a Ph.D scholar, for him the notion of PWI is an invalid quantity, because of the fact that this measure is constructed and introduced here for the Ph.D scholars only, not for other researchers

At a given point of time during the tenure of Ph.D research work of a Ph.D scholar, PWI is the sum

of all IFS the scholar has earned during his Ph.D tenure so far, but subject to the condition that the work

is in compliance with his Ph.D Proposal which was officially approved for him by the university DC/BRS or appropriate committee The PWI of a research scholar excludes all IFS earned (if any) by the scholar prior to his admission into the Ph.D programme It does also exclude all IFS earned by the pub-lications which are not relevant to his approved Ph.D Proposal, even if such work been done during his Ph.D tenure The PWI at any given time during the tenure of Ph.D work, if required by the university, must be initially certified by the supervisor which is to be finally approved by university through the Doctoral Committee (DC) meeting of the concerned department and Board of Research Studies (BRS)

of the concerned Faculty of the university

It is therefore obvious that at the time of admission in a Ph.D programme, the PWI of any research scholar is 0, although his CJPI could be a positive number (because, prior to Ph.D admission he may have done few good publications) After that, the PWI improves with time on the basis of his progress

in research work and publications in indexed or sub-indexed journals It is a non-decreasing quantity with respect to time

For any Ph.D scholar, if we draw his “PWI - t” graph which is a graph of ‘PWI’ against the pendent variable ‘time t”, then we can see that it is a continuous non-decreasing step-up graph with

inde-d

dt (PWI) ≥ 0 at every point of time

For a talent Ph.D scholar with good research progress, the number of steps will be more in the “PWI

- t” graph For an excellent research progress of the Ph.D scholar, there will be one more observation that few of the step-heights will be usually large in the graph

The metric PWI has a major significance to an enrolled Ph.D scholar, to his Supervisor/Guide, and

of course to the concerned university/institute The quantity PWI at every point of time helps a research scholar to do self-assessment of his progress of quality work at real time consideration

Difference between PWI and CJPI

The notion of PWI is different from the notion of CJPI Where the CJPI exists for every researcher, the PWI exist only for those researchers who are at this time the Ph.D scholars on enrolment in the univer-sity Thus, it is obvious that CJPI of a Ph.D scholar is always greater than or equal to the PWI of him The PWI of a Ph.D scholar attains its final value once he/she submits his thesis After that the PWI of a Ph.D scholar can never vary, can neither increase nor decrease, and rather it freezes to an absolute value for lifetime of the scholar as a good personal record But this is not true in case of the metric CJPI The CJPI of a researcher gets updated (at least not decreasing) throughout his life

“Thesis Submission Index (TSI) of a Department” in a University/Institution

The ‘Thesis Submission Index’ (TSI) is a measure prescribed by a university in its Ph.D Bye-laws, which could be different for different academic departments (core subjects) of it For example, in a given university the TSI of the Department of Physics may be different from the TSI of the Department of Computer Science of it It is due to the fact that in some fields the IF (PIF) of the indexed or sub-indexed journals are usually low and in some fields the IF (PIF) of the indexed or sub-indexed journals are usu-ally high It is not because of the fault of the scholar or of department or of the university but mainly because of the reason that in some core areas number of indexed or sub-indexed journals are more and

in some core areas number of indexed or sub-indexed journals are less, (considering mathematically per 100 scholars) However, given a department in a university, TSI is fixed for it i.e does not vary on the basis of the nature of the area of research or topics of interest in that subject For example, in the Department of Mathematics the TSI will remain fixed whatever be the area of research, be it “Complex Analysis” or “Optimization Techniques” or “Algebra” or “Fluid Mechanics”, etc TSI is a positive real

number decided/fixed by the university for a department of it, but different TSI values are for different departments.

A Ph.D scholar is eligible to submit his thesis if and only if

1 The PWI of the scholar exceeds the prescribed TSI value of the department (prescribed by its university), and also if

2 The supervisor allows him to submit the thesis, in compliance with the approved “Ph.D Proposal”.Otherwise the scholar has to do more amount of good research work in order to raise his PWI value

to exceed the TSI value of his department in his university (or, at least to become equal) Under no circumstances, a Ph.D scholar is allowed to submit his thesis if PWI < TSI If PWI of a scholar is not sufficient enough, his guide/supervisor should not and cannot allow him to submit the thesis

The guide/supervisor has the full discretion power ‘not to allow’ his scholar to submit his thesis even if PWI of the scholar exceeds the TSI value of the department in the university The Fulfillment

of the condition PWI < TSI does not necessarily mean that the “Ph.D Proposal” is solved completely and satisfactorily It is the guide who will finally decide whether further amount of research work is required or not, for making complete solution to the concerned Ph.D proposal The guide is the all in all to decide about the submission of thesis, but once the inequality PWI ≥ TSI be satisfied, not earlier

“Subject-Wise Minimum Value of TSI” Prescribed by UGC (a

Minimum Requirement for All the Universities/Institutions)

Although a university itself prescribe its own TSI value (different for different core subject), but it does not mean that the university has the freedom/right to choose low or poor values In order to attain at least a minimum amount of homogeneity in the Ph.D degrees in all universities in the country, the UGC will prescribe a “Minimum Value of TSI” department-wise (i.e subject wise) which is applicable across all the universities and across the country However, a university at its own discretion may prescribe a higher value of TSI for its own in the bye-laws Every year in January, UGC will prescribe “Minimum Value of TSI” for each core subject (i.e for each department) for all the Universities/institutions across the country The minimum value of TSA (subject wise) is prescribed by UGC And UGC does also allow the universities to fix their own values, subject to the condition that for a given department the university prescribed TSI values must not be less than the corresponding minimum TSI values prescribed by UGC for the same department in all the universities across the country

However, a university (in particular the excellent universities) is free to fix TSI value for its ments much higher than the minimum values prescribed by UGC in order to maintain a very high qual-ity Ph.D But a top class Professor (Supervisor) may have his own personal TSI value for his subject, but subject to the condition that under no circumstances it can be less than the University TSI value prescribed for his department (core subject) Any TSI value chosen personally by a Supervisor (by his own intellectual choice) for applying to his scholars will be invalid if it is less than the value of the TSI

depart-of his department, prescribed by his university In case a Prdepart-ofessor (supervisor) is having his own valid TSI, he/she may apply his own TSI instead of his department’s TSI while taking decision about allow-ing a scholar of him to submit the Ph.D thesis to the university Even a Professor may apply different

valid TSIs by his own choice to different scholars of him, on case to case basis In a given core subject (say, Mathematics), the value of TSI may be different for different universities, and quite obviously it could be very high for the finest universities in research (like MIT, Harvard, Oxford, Cambridge, IISc Bangalore, ISI Calcutta, etc.).

The TSI values of a given university will signify the weight of the quality of Ph.D.’s being ferred by that university, which is of course department-wise For a given core subject (say, Computer Science) the people will be able to make an initial and preliminary comparison of Ph.D.’s of different universities in India by comparing the TSI values of the universities of their respective core subjects The TSI value will also play an important role to the NAAC accreditation committee of UGC as one of

con-the significant parameters to award con-the grade A or A + or B etc to a university But the minimum value

of TSI prescribed by UGC surely imposes a guaranteed amount of quality of the Ph.D degrees across all the universities in India

Continuous Evaluation by Supervisor

Besides supervising the research work, the guide/supervisor can now, with the help of these new ful continuous evaluation real-time measures make the Ph.D scholar aware of his research progress in

use-a precise quuse-antified form use-about the following informuse-ation use-at the end of every yeuse-ar or even use-at use-any time every year:

1 Whether the research progress is being satisfactory or not?

2 Whether the research progress is going on excellent?

3 Whether the research progress is so poor that it could be alarming?

4 Whether the scholar should be forced to discontinue the Ph.D programme?

5 Whether the progress is so good that that time is now to conclude, and to think about a possible and appropriate stage for writing and typing the thesis

Unfortunately, there is no measure or model specified in India by the “Ministry of HRD (MHRD)”

or UGC which can help the Guides/Supervisors of the universities (in particular, of the private

univer-sities) to take an appropriate quantitative decision on the above five listed points It is absolutely true

that an excellent Guide/Supervisor does not need any measure/model to be specified by the “Ministry

of HRD (MHRD)” Nevertheless, considering the general situation of the country in producing quality Ph.D.’s which is at a serious stake at present, this proposal for “Five Conditions Ph.D Rule of UGC”

is initiated as a genuine solution

Proposition

Suppose that as per bye-laws of a university the minimum working period for submission of Ph.D thesis

by a scholar is n years and the maximum period is z (> n) years in that university, including the work duration, if any Then, from the 2nd year onwards the Ph.D scholar is expected to earn, in average every year, a total amount of IFS which is not less than TSI/(z-1) value, where TSI value is the value prescribed by the university for the department under consideration

Let us admit that in the first year, the Ph.D scholar can earn a small amount of IFS or even nil (If he earns a good amount of IFS in the first year then it is an excellent research progress of him), which is quite natural for every scholar

Therefore, the scholar is having now at most (z-1) years at his hand for completing his research work and publications for completion of his Ph.D degree

Therefore, he has to earn at least an amount of PWI which must be greater than TSI at the end of the last (z-1) years Therefore, the sum total of IFS to be earned every year in average by him must exceed

the value TSI / (z-1) Hence Proved.

INTRODUCING “FIVE CONDITIONS PH.D RULE OF UGC” (FOR

ALL THE UNIVERSITIES ACROSS THE COUNTRY)

Now we are in a position to introduce the “Five Conditions Ph.D Rule of UGC” using which a Ph.D scholar can do self-assessment and his supervisor can quantitatively compute and take decision on whether the work of his Ph.D scholar is sufficient and worthwhile in all respect for submission now in thesis form.Suppose that on completion of research work for a period of three to four years, a Ph.D scholar himself feels that it is the time for submission of his thesis Now it is the Supervisor’s intellectual and academic decision to ensure that the work of his scholar done so far is really upto the mark, really in compliance with the approved Ph.D proposal and really sufficient for submission to the university for evaluation But, in order to bring an amount of homogeneity among the class of all supervisors across the country while taking such an important academic and intellectual decision, we propose a consolidated model for UGC which is a complete and sound set of conditions to be mandatorily satisfied by the research scholars as a minimum eligibility norm for submission of thesis But mere fulfillment of the minimum eligibility norm does not provide any right to a scholar to take decision for submission of his Ph.D thesis The fulfilment is a norm for self-assessment and hence for self-satisfaction only for the scholar, and may

be reported to his supervisor as an information just Once the minimum eligibility norm is fulfilled, it

is now the supervisor to take an appropriate decision whether or not to allow the scholar to submit his thesis This set constitute an important and very useful rule called by “Five Conditions Ph.D Rule of UGC” which consists of five number of almost independent conditions Out of these five conditions, the first four conditions are to be satisfied by the Ph.D scholar whereas the last (i.e 5th) condition is

to be satisfied by the concerned university just after the submission of the thesis, but overall check and verification is to be done by the supervisor before allowing him to submit the thesis

The first four necessary conditions which must be mandatorily fulfilled by a Ph.D scholar before a supervisor considers to think whether to allow the scholar to submit his thesis or not, are as mentioned below:

1 Condition-1: Indexed Journal Condition (IJ Condition)

2 Condition-2: TSI Condition

3 Condition-3: Compliance of Ph.D Proposal Condition (CPP Condition)

4 Condition-4: Peripheral Satisfaction Condition (PS Condition) and, if the thesis be submitted

by the scholar (on being allowed by the supervisor), then the fifth condition stated below must be considered and must be fulfilled by the concerned university:

5 Condition-5: Excellent Evaluation Condition (EE Condition)

The above five conditions are explained below:

Condition-1: “Indexed Journal Condition” (IJ Condition)

This condition requires that the publications of the Ph.D scholar must be in indexed and sub-indexed journals only According to this condition, publications in non-indexed journals will not be considered

by the concerned university Because such a publication does not add any value to the IFS of the scholar (We do not want to mean that a publication if accomplished on payment of publication-charge will be necessarily a poor publication Such kind of concept, if any, is surely a wrong concept A number of excellent quality journals of good IF need to generate funds for their noble work! Even, it is fact that top quality journals/transactions of IEEE/ACM too asks for payment of publication-charge in some cases to publish the accepted papers) Instead, it is the amount of IF or PIF of the indexed or sub-indexed journal which reflects and ensures the quality of publications

Unpublished works of the scholar or the materials of publications of the scholar in journals which are neither indexed nor sub-indexed or materials of publications in the Proceedings of the International Conferences etc may be added in the Ph.D thesis, but only for the sake of completeness and soundness

of the content of the thesis, if required However, a good supervisor will always discourage the scholars

to communicate any research work to non-indexed journals or to poor quality journals, but surely he will encourage to participate and contribute in good international conferences which is a good academic value addition for any beginner in research activities or for any level of researchers in fact To enhance the amount of compliance with the approved Ph.D proposal, a research scholar may include in his thesis the publications of him made in the Proceedings of the International Conferences/Seminars for which although there may not be any IF/PIF score The IJ condition is to be checked by the concerned supervisor prior to communicating any work to a journal for publication, because a Ph.D scholar being

a beginner in research may commit mistakes initially

Condition-2: “TSI Condition”

For submission of Ph.D thesis, one of the necessary conditions is that the Ph.D scholar must fulfill the TSI condition which is just a mathematical equation as mentioned below

PWI ≥ TSI

where the PWI is the ‘PWI of the scholar’, and the TSI is the corresponding ‘department TSI’ for the concerned university or a valid TSI personally decided by the supervisor But this is just one of the necessary conditions, not a sufficient condition Clearly, this condition for a scholar is to be checked by his supervisor

A high class Professor (Supervisor) may have his own personal high TSI value for his subject He may apply his own TSI instead of his department’s TSI while taking decision about allowing a scholar

of him to submit the Ph.D thesis to the university Even a Professor may apply different valid TSIs by his own choice to different scholars of him, on case to case basis.

Condition-3: “Compliance of Ph.D Proposal Condition” (CPP Condition)

For every Ph.D research scholar, there is a ‘Ph.D Proposal’ approved by the BRS of the concerned university with which he began the research work for his Ph.D degree The Ph.D scholar has to work

on each and every item of the Ph.D Problem Statements whatever promised in his ‘Ph.D Proposal’

He has to solve the Ph.D proposal completely and correctly Even though the IJ Condition and TSI condition be fulfilled at some point of time, it may happen that the work done so far is not providing the complete solution of the ‘Problem Statement’ as mentioned in the ‘Ph.D Proposal’ or may be that the part of the work done is not in compliance with the approved Ph.D Proposal even if the research work done be excellent Such cases may be termed as non-compliance of the ‘Ph.D Proposal’ even though the work done so far could be excellent in quality and quantity both Under such situation, a scholar is not allowed to submit his thesis It is mandatory to complete the work from A to Z as per the approved Proposal This condition is thus called by “Compliance of Ph.D Proposal Condition” or “CPP Condi-tion” This condition is to be carefully checked and adjudged by the concerned supervisor, and in case the supervisor feels that this condition is not fulfilled then the supervisor will not allow the Ph.D scholar

to submit his thesis

One of the major demerits and faults of the existing evaluation system of Ph.D thesis in India in most of the universities is that the Evaluators (external) of the Ph.D thesis do not check or do not get scope to check the CPP condition The evaluators take it granted by default without looking at the ‘Ph.D Proposal’ based on the fact that ‘the supervisor has allowed the submission of the thesis’

Condition-4: “Peripheral Satisfaction Condition” (PS Condition)

This is an overall compliance condition, regarding other properties of the scholar including the character, behavior, whether defaulter in the university, whether attendance/meetings are fulfilled as per instruc-tions, any indiscipline cases against if any, etc and hence it is not a well-defined or precise condition This condition is to be checked by the supervisor by his best intellectual judgment because he must have overall satisfaction over the scholar’s day-to-day records, activities and performance Let us call this condition to be “Peripheral Satisfaction Condition” or “PS Condition”

Condition-5: “Excellent Evaluation Condition” (EE Condition)

This is the condition to be fulfilled by the concerned university once the thesis is submitted by the scholar We propose that this condition may be finally monitored by the “Ministry of HRD (MHRD)” to countercheck whether ‘excellent evaluation’ has been done as per our definition presented below This condition is one of the most important conditions of the ‘Five Conditions Ph.D Rule of UGC’

Before explaining the “Excellent Evaluation Condition” (EE condition), we introduce a kind of important certificate called by the ‘Thesis Submission Certificate’ On submission of the thesis, the Controller of Examination of the university will issue a simple provisional thesis submission certificate

to the scholar which he keeps for his own record This certificate must mention that it is ‘provisional’, not final The final ‘Thesis Submission Certificate’ he will get from the university while he gets the

Ph.D degree certificate The scholar must retain the ‘Thesis Submission Certificate’ along with his Ph.D degree certificate as a very important document for his career, job, promotion, etc This certificate will carry a good information about the scholar for his future career, as well as to all the recruiters of him in future interview/selection board Thus the initial ‘Thesis Submission Certificate’ is always provisional, not final In few cases there could be more than one, step-wise updated, provisional certificates; but the final one is unique which is an important certificate to the scholar for his life time.

Thesis Submission Certificate

In our ‘Five Conditions Ph.D Rule of UGC’ introduced here, the Thesis Submission Certificate is a Certificate mentioning the value of the ‘university TSI’ and the value of the ‘PWI of the scholar’ as on the date of submission/resubmission of the thesis, as per following format (Table 4)

A copy of this certificate will be forwarded to each of the external and internal evaluators while forwarding the thesis for evaluation However, in case of officially resubmission of the thesis, the cer-tificate may be updated accordingly by the Controller of Examination by updating the latest value of the PWI of the scholar The updated/revised version of this certificate will be forwarded to the evaluator who re-evaluates the thesis (i.e if such a situation arises) The certificate gets finally frozen on the day

of the Viva-Voce while he defends the thesis The final version of the Thesis Submission Certificate is issued to the scholar by the Controller of Examination on successful defend of the thesis by the scholar, not prior to that

The EE Condition consists of two parts as explained below:

Date of submission of the thesis

Date of Re-submission of the thesis (if applicable)

PWI of the scholar

University TSI

Any other information

Comment (if any)

Signature of the Controller of Examination

Part-1: Evaluation by (α,β,γ) Normed Type-1 Experts

A submitted thesis should be evaluated by at least three evaluators who must be (α,β,γ) Normed Type-1 Experts for a suitable value of (α,β,γ) as imposed by the concerned University in the Ph.D bye-laws Obviously, it could be different for different departments (subjects) The thesis (along with the interim Thesis Submission Certificate, the revised version if the case be) is to be forwarded to the evaluators providing at least two months’ time for evaluation

Note: The notion of ‘(α,β,γ) Normed Type-1 Expert’ is introduced here in the next section

Part-2: Fuzzy Evaluation Method

While evaluating a Ph.D thesis (or a Master thesis or a Project dissertation etc.), most of the judgment parameters are not precise parameters but fuzzy parameters Consequently, the existing classical evalu-ation method is an obsolete method and does not provide a complete and fair justice to the evaluation

of the thesis The Fuzzy Evaluation Method is a soft-computing method for evaluation of a Ph.D thesis (or a Master thesis or a Project dissertation etc.), where judgment parameters are answered not only by subjective comments but also awarding fuzzy numbers (fuzzy marks) and/or awarding value (member-ship value) in the closed interval [0,1], by the best intellectual judgment of the appointed (α,β,γ) Normed Type-1 Expert For giving the final comment by the concerned (α,β,γ) Normed Type-1 Expert, the integration of all the intellectual comments is done using fuzzy mathematics and of course according to all the other instructions laid down by the concerned university

An excellent and very precise ‘FUZZY EVALUATION FORMAT’ for evaluation-report is to be designed (could be different for different subjects) by UGC, to be adopted as a common FORMAT across all the universities No university in the country is allowed to use any other format except the common UGC format for evaluation of any Ph.D thesis The format is to be framed by partitioning the global job of evaluation into n number of sub-jobs on the basis of various well defined attributes and parameters so as to cover all aspects of judgment of a thesis by the evaluators who are (α,β,γ) Normed Type-1 Experts Although the format is to be very precise, but the evaluation is to be done using fuzzy logic wherever crisp logic fails (as per prescribed instructions printed on the format) The objective for using fuzzy theory in evaluation is that instead of applying classical two valued logic, the evaluator has

to use the notion of fuzzy numbers (fuzzy marks) and/or membership values lying in the closed interval [0,1] to judge the strength/weakness of the thesis at each and every prescribed attribute or parameter The UGC prescribed format for fuzzy evaluation will have a number of crisp as well as fuzzy attributes, and could have different designs for different faculties like: Engineering, Science, Arts, Humanities, Medicine, Law, Drama, Music, Library Science, etc We propose that all these formats be standard-ized and approved by the “Ministry of HRD (MHRD)” applicable across of the country, by a common format but could be different for different faculties, by a common set of rules, by a common method of integration to award total final score

As mentioned earlier, in order to fulfill the EE Condition of the ‘Five Conditions Ph.D Rule of UGC’, the evaluators must be (α,β,γ) Normed Type-1 Experts for a suitable value of (α,β,γ) as imposed by the concerned university in its Ph.D bye-laws, different for different departments (subjects)

But in reality and quit obviously, many of the Sr Professors or Professors of many faculties (say,

of Arts, Humanities, Drama, Music, etc.) and many of the (α,β,γ) Normed Type-1 Experts may not be