Graph Visualization Using the NoSQL Database

The relational database has been a dominant approach for organizing data into formally organized tables for years. Recently, with massive amounts of data being generated, a new type of database called NoSQL has emerged. NoSQL seeks to overcome the drawbacks of SQL, such as fixed schemas, JOIN operations and addresses the scalability problems. In this paper we have reviewed emerging technology called NoSQL and compared it with the traditional relational database. In the first part of the paper, we review the pros and cons of both the technologies and in the second, we tried to address issues involving data visualization. Characteristics such as flexibility, low latency, scalability, schema-less, fast query, and performance are some major advantages of a NoSQL database. To test the properties of NoSQL database, we have developed a graph-visualization application based on Neo4j, a graph database, along with accompanying technologies such as MapReduce and the REST web service

Fair CRISP-DM: Embedding Fairness in Machine Learning (ML) Development Life Cycle

With rapid adoption of machine learning (ML) technologies, the organizations are constantly exploring for efficient processes to develop such technologies. Cross-industry standard process for data mining (CRISP-DM) provides an industry and technology independent model for organizing ML projects’ development. However, the model lacks fairness concerns related to ML technologies. To address this important theoretical and practical gap in the literature, we propose a new model – Fair CRISP-DM which categorizes and presents the relevant fairness challenges in each phase of project development. We contribute to the literature on ML development and fairness. Specifically, ML researchers and practitioners can adopt our model to check and mitigate fairness concerns in each phase of ML project development

Exploring the Time Dimension in the Technology Acceptance Model with Latent Growth Curve Modeling

This paper investigates the dynamics of users’ beliefs and intention to adopt a new technology during the course of its training. It also identifies the relationships among the dynamic elements over a time continuum. As a research method, we introduce latent growth curve modeling to better analyze the dynamics over a longitudinal time horizon. We provide an outline of the method for a research in progress. In addition, we demonstrate the application of latent growth curve modeling to a secondary data set obtained from Venkatesh et al. (2006). The results indicate that those with a higher level of initial behavioral intention to use are likely to have a higher level of initial use of a technology. In addition, those who have a steeper rate of increase in behavioral intention during the implementation are likely to have a steeper increase in their use of the technology

An Equity Perspective on Knowledge Sharing Behaviors in Organizations

Organizations promote knowledge sharing behaviors among their members to derive value from the knowledge embedded within individuals and in other organizational resources. Individuals’ knowledge sharing behavior, however, is a complex phenomenon, influenced by several factors, which has been examined in the prior research using several theoretical perspectives. In spite of the vast body of research, the phenomenon is not fully understood, given that many interacting, external and intrinsic factors can influence individuals’ motivation and ability to participate in knowledge sharing. Among the possible factors, an important set of factors can be equity or fairness perceptions, which can play a role in individuals’ motivation for knowledge sharing. Perceptions of equity have been found to be a good predictor of organizational citizenship behaviors and, organizational citizenship behaviors are known to positively influence knowledge sharing behaviors. However, in the extant literature, the role of equity perceptions in influencing knowledge sharing behaviors has not been examined. In this study, we examine the role of perceptions of equity on knowledge sharing behavior and develop a model for understanding knowledge sharing behaviors from the equity theory perspective

Prevalence and contributing factors of low birth weight babies in institutional delivery

Introductions: Low Birth Weight (LBW) is a sensitive indicator of socio-economic conditions and indirectly measures the health of mother and child. Though, the health situation of Nepal has improved substantially over the years, LBW rate is still high. The present study explores the prevalence and contributing factors of LBW babies delivered in Patan hospital. Methods: The data were collected retrospectively from patients’ record for babies born at Patan Hospital, Patan Academy of Health Sciences, Kathmandu, Nepal. Records were retrieved through systematic randomization and IBM SPSS 15.0 was used for analysis. Non-parametric tests were applied with correlation done between dependent and independent variables. Results: A total of 4395 birth occurred during the study period of which 527 met the study criteria and remaining were of normal birth weight. The prevalence of LBW was 11.99% and the average LBW was calculated as 2074.97 ± 344.425 grams. The factors associated with LBW included preterm babies (Pearson correlation coefficient= 0.554, p= 0.001 < 0.05) and oligohydamnious (Spearman’s correlation coefficient= 0.307, p= 0.019 < 0.05). Conclusions: This study suggests preterm babies and oligohydramnious to be contributing factors of LBW babies. Keywords: amniotic fluid index, intra uterine growth retardation, maternal risk factors, Patan Hospital, retrospective hospital based studyÂ

Examining Leader-Member Exchange as a Moderator of the Relationship between Emotional Intelligence and Creativity of Software Developers

This paper investigates how leader-member exchange (LMX) and emotional intelligence (EI) are associated with employees’ creativity in high-tech firms. We develop a model that considers LMX and EI as predictors of creativity with LMX as a boundary condition for the relationship between EI and creativity. Results reveal that LMX is a strong predictor of creativity. However, EI does not directly affect creativity. More interestingly, the interaction between EI and LMX negatively influences creativity such that EI is detrimental for creativity only when LMX is high. Thus, the role of LMX for employees’ creativity may be paradoxical. Further, the positive role of EI reported in current literature may be overly simplistic, and its role may be contingent on the quality of LMX and the other contex

Examining Leader-Member Exchange as a Moderator of the Relationship between Emotional Intelligence and Creativity of Software Developers

This paper investigates how leader-member exchange (LMX) and emotional intelligence (EI) are associated with employees??? creativity in high-tech firms. We develop a model that considers LMX and EI as predictors of creativity with LMX as a boundary condition for the relationship between EI and creativity. Results reveal that LMX is a strong predictor of creativity. However, EI does not directly affect creativity. More interestingly, the interaction between EI and LMX negatively influences creativity such that EI is detrimental for creativity only when LMX is high. Thus, the role of LMX for employees??? creativity may be paradoxical. Further, the positive role of EI reported in current literature may be overly simplistic, and its role may be contingent on the quality of LMX and the other context.ope