54 research outputs found
Pakistan and Pakistani culture in social studies textbooks approved for Georgia schools, 1967
No full textIndexing of authors according to their domain of expertise
No full textMeasuring the impact and productivity of an author is an important, yet a challenging task. Most of the existing methods for ranking or indexing of authors are based on simple parameters such as publication counts, citation counts and their combinations. These methods are topic independent, hence ignoring the intra-field differences. This study introduces a specific method for indexing of researchers to measure their productivity in a given field of interest, believing that an author can be interested in more than one fields and can have different level of expertise in all these fields. This paper proposes Domain Specific Index (DSI), a novel method for indexing of authors with respect to their fields of interest. Latent Dirichlet Allocation (LDA) is applied to capture the latent topics within text corpora. DSI calculates the standing of an author in all topics of his or her interest by considering topic based citations instead of using overall citations like traditional methods. The citations received by a multi-authored paper are divided among all its co-authors on the basis of their topic probability in that particular field. Results show that instead of giving credit of received citations equally to all co-authors of a paper, if a weight is given with respect to their level of interest in that field, more specific authors in that field will be ranked as top authors
Toward a New Paradigm for Author Name Disambiguation
No full textAuthor Name Disambiguation (AND) has emerged as a significant challenge in the bibliometric context with the growing volume of scientific literature. When citations written by different authors have the same names (polysemy or homonym names), and when an author has different names, there is ambiguity (synonyms or name variants). It is difficult to associate a citation with the correct author. Polysemy and synonyms cause merging and splitting anomalies in the citations. These anomalies affect the quantification of an author’s productivity (bibliometric analysis) and the reliability and quality of the information retrieved. Many techniques for AND have been proposed in the literature; most of them do not go beyond string matching or text matching. Most of the existing work do not consider the context or semantics of the terms used in the citations. In this study, the AND problem is resolved semantically using the deep learning technique on the PubMed dataset. The experimental results show that the proposed method achieves overall (11.72 %, 12.5 %, and 12.1 %) higher precision, recall, and f-measure than the pairwise class classification
Finite element modelling of FRC beams containing PVA and Basalt fibres: A comparative study
No full textManual or electronic? The role of coding in qualitative data analysis
No full textData analysis is the most difficult and most crucial aspect of qualitative research. Coding is one of the significant steps taken during analysis to organize and make sense of textual data. This paper examines the use of manual and electronic methods to code data in two rather different projects in which the data were collected mainly by in-depth interviewing. The author looks at both the methods in the light of her own experience and concludes that the choice will be dependent on the size of the project, the funds and time available, and the inclination and expertise of the researcher
Impact of mutual influence while ranking authors in a co-authorship network
No full textOnline bibliographic databases are providing significant resources to conduct analysis of academic social networks.We believe that work of an author is always influenced by work of his or her co-authors. In this study, we investigatethe impact of productivity and quality of work of an author’s co-authors on his or her ranking along with his owncontribution. We propose mutual influence (MI) based ranking method, which ranks authors based on (1) Publicationsof an author, along with impact of publications of his or her co-authors, (2) Normalized author position based Citationsweight, which is calculated from the citations received by an author with respect to position of his or her name in theco-authors list, (3) MINCC that combines the impact of both factors. A series of experiments has been conducted andresults show that proposed approach has capability to ranks authors in a significant way
Using the Binary Matrices for Modeling the Supply Chain Issues of Virtual Shops: An Evidence from Pakistan
No full textThe study aims at developing a list of supply chain issues in virtual shops and construct a hierarchal model of those supply chain issues with the purpose to prioritize them. It is also geared towards unfolding the inter-relationships of those issues. The research design entails comprehensive review of literature and qualitative analysis following the collection of primary data from panel of experts utilizing Interpretive Structural Modeling (ISM) coupled with Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) as a methodology, this paper intends to probe into the supply chain issues creating bottlenecks in virtual shops’ operations. ISM is conducive to find the influential supply chain issues whereas MICMAC classifies and analyzes the supply chain issues based on their driving and dependence powers. The results of ISM point out that the supply chain issue ‘data centers affected by natural disasters’ is the most influential issue since it occupies bottom level of ISM model whereas supply chain issues ‘long lead time’ and ‘customer unavailability’ occupy top of ISM model being least critical. Results of MICMAC disclosed that issues ‘high delivery costs’, ‘long lead time’ and ‘customer unavailability’ are categorized as dependent whereas ‘network errors’ and ‘data centers affected by natural disaster’ are classified as independent. All the other issues are contained into linkage cluster while no supply chain issue is autonomous depicting that all the issues are relevant. Over the past few years, the extent of research on e-commerce logistics and supply chain has been increased. Most of the researches have been conducted to create awareness on the importance of logistics and supply chain in e-commerce industry. But the supply chain issues faced by virtual shops have not been comprehensively identified in any research till date. This study attempt to find those issues and prioritize them. The findings of the study provide understanding of most influential and most influenced supply chain issues so that the practitioners can set their priority actions. This study has contributed theoretically and possess practical implications for the stakeholders of virtual shops as well. In view of the fact that the study is conducted without financial assistance and data is collected from medium-sized panel in a field setting, the study is limited to an extent
Expounding Dynamics of Tacit Knowledge Critical to Credit Decision Making: Juxtaposed Findings of GRA and RIDIT
No full textThis study explores importance of Tacit Knowledge (TK) sharing for formal loan makers in Pakistan. Main objective of the study is to expound, conceptualize and hierarchicalize the factors of TK critical to credit decision making. The study follows positivist approach and overall research design consists of literature review, field survey and data analyses. Data was collected from credit officers of Pakistani banks. Following the triangulation approach for confirmation and comparison of results, multiple techniques viz EFA, GRA and RIDIT were employed. Results of EFA showed that there are eight major dynamics of TK. Findings of GRA revealed that TK about recovery of loans is the most important factor hence occupies the highest GRA rank, whereas, the TK about resources of borrowers occupies the lowest rank. RIDIT analysis showed that TK about multitude of business sectors is the most important factor hence occupies the highest RIDIT rank, whereas, TK about capacity to repay the loans occupies the lowest rank. Juxtaposition of results of GRA and RIDIT revealed that TK gained during recovery of loans is one of the most important factors. It is a seminal study in the area of knowledge management particularly in context of Pakistani banks based on original data collected in field setting. The study gives insight of critical factors of TK, which has high value for credit personnel in banks. The results are useful for decision makers in banks, academicians and researchers
Uncovering the Myths of TQM in Readymade Garment Sector of Pakistan: An Interpretive Structural Modeling Approach
No full textQuality has always been center of gravity for superior competitive advantage. TQM has captured attention of both practitioners and academicians because it is an important management practice for improving performance. This research is aimed to provide insight of the challenges faced by readymade garment industry of Pakistan for implementation of TQM principles. In depth literature, Interpretive Structural Modeling (ISM) and Matriced' Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analyses have been employed to investigate the phenomena under study. Discourse of literature revealed that there are twenty challenges in implementation of TQM. Lack of employee trust in senior management is the most critical challenge to be addressed that occupies bottom of the model. Lack of formalized strategic plan for change and lack of leadership occupy highest position in the model hence attracts least attention. MICMAC analysis revealed that lack of consistency of purposes autonomous, lack of evaluation procedures and benchmark indices and obsolete technology are independent and all other challenges fall in linking quadrant. Whereas no such challenge is exclusively categorized as dependent, however, most of the linking factors have high degree of dependence as well. This study is useful for the organizations which are in process of implementing TQM practices
Spatializing Groundwater Quality Parameters and Their Impacts on Land Value in Khushab City, Punjab, Pakistan: Spatializing Groundwater Quality Parameters and Their Impacts on Land Value in Khushab City, Punjab, Pakistan
No full textThis research was designed to examine the spatial variation in land value in response to ground water quality in Khushab city, Punjab Pakistan. There were four Physical and five chemical parameters such as pH, Electric Conductivity (EC), Calcium (Ca), hardness, Magnesium (Mg), Total Dissolved Solids (TDS) concentration, taste, color and odor were tested for groundwater quality appraisal in the study area. There were one hundred water samples collected from different wells in the study area. Thereafter, the water quality parameters were processed in ArcGIS for analyzing spatial distribution of groundwater quality parameters by using interpolation and geostatistical tools. It was found that all the groundwater parameters were higher than the permissible limit by WHO except pH concentration. It was further revealed that the ground water was unsafe for drinking and domestic purpose. Variation in land price was also studied with special reference to ground water quality. It was concluded that the groundwater quality has a significant effect on land value in the study area. The deteriorated groundwater quality was proved to be a potent determinant for decreasing land price in the study area
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