A Discrimination Index Based on Jain's Fairness Index to Differentiate Researchers with Identical H-index Values

Purpose:This paper proposes a discrimination index method based on the Jain’s fairness index to distinguish researchers with the same H-index.Design/methodology/approach:A validity test is used to measure the correlation of D-offset with the parameters,i.e.H-index,the number of cited papers,the total number of citations,the number of indexed papers,and the number of uncited papers.The correlation test is based on the Saphiro-Wilk method and Pearson’s product-moment correlation.Findings:The result from the discrimination index calculation is a two-digit decimal value called the discrimination-offset(D-offset),with a range of D-offset from 0.00 to 0.99.The result of the correlation value between the D-offset and the number of uncited papers is 0.35,D-offset with the number of indexed papers is 0.24,and the number of cited papers is 0.27.The test provides the result that it is very unlikely that there exists no relationship between the parameters.Practical implications:For this reason,D-offset is proposed as an additional parameter for H-index to differentiate researchers with the same H-index.The H-index for researchers can be written with the format of“H-index:D-offset”.Originality/value:D-offset is worthy to be considered as a complement value to add the H-index value.If the D-offset is added in the H-index value,the H-index will have more discrimination power to differentiate the rank of the researchers who have the same H-index.

Program evaluation and its application to equipment based on super-efficiency DEA and gray relation projection method

For the gray attributes of the equipment program and its difficulty to carry out the quantitative assessment of the equipment program information, the gray relation projection method is simply reviewed. Combining the super-data envelopment analysis（DEA） model and the gray system theory, a new super-DEA for measuring the weight is proposed, and a gray relation projection model is established to rank the equipment programs. Finally, this approach is used to evaluate the equipment program. The results are verified valid and can provide a new way for evaluating the equipment program.

Effect of Intensity Accents on the Detection of IOI Deviations

The effect of intensity accents on detection of temporal irregularities is investigated in a 3×3 behavior experiment with independent variables of inter-onset-interval （IOI） length and intensity. In a 5-beat isochronous sequence, both the length of the third IOI and the intensity of succeeding beat are manipulated to three different levels separately （IOI length： longer Llo, shorter Lsh, or standard Lst. Intensity： louder Ilo, softer Iso, or standard Ist）. Subjects are required to discriminate the third IOI length with different responses respectively. The discrimination sensitivity index （d′） and response criterion （C） are assessed simultaneously for each stimulus condition. Statistical analysis reveals an asymmetric effect of intensity accents on detection of IOI deviations in an isochronous sequence, i.e. the loud accent mainly reduces the sensitivity for both shorter and standard IOIs, and the soft accent might introduce a disturbance into the temporal perception, especially in the detection of the short IOIs. Importantly, when preceding a louder accent, the short IOIs are significantly difficult to detect than the long ones, as consistent with the compensation hypothesis.