A Mathematical Programming Approach for Imputation of Unknown Journal Ratings in a Combined Journal Quality List

The quality of faculty scholarship and productivity is one of the primary measures for faculty evaluation in most academic institutions. Due to the diversity and interdisciplinary nature of modern academic research fields, it is increasingly important to use journal quality lists, with journal ratings, that offer credible measures of the worth of faculty scholarship. Despite the existence of such metrics, journal lists, by their very nature, exclude some well‐recognized journals. Consequently, academic institutions expend inordinate resources to assess the quality of unrated journals appropriately and equitably across disciplines. The current research proposes mathematical programming models as a path to determining unknown ratings of multiple journal quality lists, using only their known rating information. The objective of the models is to minimize the total number of instances where two journals are rated in opposite order by two different journal quality lists. Computational results based on journal quality list data in https://harzing.com/ indicate that the proposed methods outperform existing imputation algorithms with most realistic test data sets in terms of accuracy, root mean square error, and mean absolute deviation

Discordance Minimization-based Imputation Algorithms for Missing Values in Rating Data

Ratings are frequently used to evaluate and compare subjects in various applications, from education to healthcare, because ratings provide succinct yet credible measures for comparing subjects. However, when multiple rating lists are combined or considered together, subjects often have missing ratings, because most rating lists do not rate every subject in the combined list. In this study, we propose analyses on missing value patterns using six real-world data sets in various applications, as well as the conditions for applicability of imputation algorithms. Based on the special structures and properties derived from the analyses, we propose optimization models and algorithms that minimize the total rating discordance across rating providers to impute missing ratings in the combined rating lists, using only the known rating information. The total rating discordance is defined as the sum of the pairwise discordance metric, which can be written as a quadratic function. Computational experiments based on real-world and synthetic rating data sets show that the proposed methods outperform the state-of-the-art general imputation methods in the literature in terms of imputation accuracy

Application of Copula-Based Markov Model to Generate Monthly Precipitation

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

What motivates people to post comments online?

Cyberbullying, i.e., posting malicious comments online, has been identified as a critical social issue in the online and social media context. As a way to prevent cyberbullying, it is important to promote online prosocial behavior. This study examines what motivates people to post benevolent comments as online prosocial behavior in the online context. For this purpose, we first adopt an exploratory study to identify decision factors in terms of social exchange decision making. We then undertake a main study by developing a theoretical research model based on the identified decision factors. The testing results explain what and how those explored factors affect the posting of benevolent comments online in the social media context. The study has its theoretical contribution in demonstrating the decision factors leading to the posting of benevolent comments by extending the social exchange theory. It also has its practical implications by providing guidance for promoting online prosocial behavior

Clinical Application of DDM/rhBMP-2 in Implant Dentistry

Recombinant human bone morphogenetic protein-2 (rhBMP-2) is well-known osteoinductive growth factors that can be used along with various carriers. Demineralized dentin matrix (DDM) that has osteoinductive and osteoconductive capacities was developed as potential candidate for rhBMP-2 carrier that has its endogenous growth factors and fulfils the requirements such as controlled release kinetics, biocompatibility, biodegradabilities and bone forming capacity. DDM loaded with rhBMP-2 (DDM/rhBMP-2) have been subjected to in vitro, in vivo studies for the purpose of proving the clinical safety and efficacy. Recently the clinical trials and outcomes of DDM/rhBMP-2 have also proved this composite to be safe and efficient in terms of enhanced bone formation, remodeling capacity and reduced concentration of rhBMP-2 in implant dentistry in Korea. This chapter will introduce the clinical application of DDM/rhBMP-2 in implant dentistry based on the related experimental and clinical researches

Some Empirical Evidence on Models of Fisher Relation

The Fisher relation, describing a one-for-one relation between nominal interest rate and expected inflation, underlies many important results in economics and finance. The Fisher relation is a conceptually simple relation, but the empirical evidence of it is more or less complicated with mixed results. Several alternative models with different implications were proposed in empirical literature for the Fisher relation. We evaluate these alternative models for the Fisher relation based on a post-data model determination method. Our result for data from the U.S. and Korea shows that models with both regimes/periods, a regime with nonstationary fluctuations and the other with stationary fluctuations, fit data best for the Fisher relatio