Search results for: research data sharing

Authors: Ali Muhammad

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The purpose of this study is to develop and test a theoretical framework which demonstrates the effect of procedural justice on four work outcomes: effective organizational commitmentو organizational trust, organizational citizenship behaviour, and adherence to rules. The new model attempts to explain how procedural justice effects work outcomes. Data were collected from 267 employees working in nine Kuwaiti business organizations. Structural equation modelling was used to analysis the data. A discussion of issues related to procedural justice is presented, as well as recommendations for future research.

Keywords: procedural justice, affective organizational commitment, organizational citizenship behaviour, organizational trust, adherence to rules

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Authors: Huma Javed

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Stylistics is a broad term that is concerned with both literature and linguistics, due to which the significance of the stylistics increases. This research aims to analyze Qaisra Shahraz's short story ‘The Escape’ from the stylistic analysis viewpoint. The focus of this study is on three aspects grammar category, lexical category, and figure of speech of the short story. The research designs for this article are both explorative and descriptive. The analysis of the data shows that the writer has used more nouns in the story as compared to other lexical items, which suggests that story has a descriptive style rather than narrative.

Keywords: The Escape, stylistics, grammatical category, lexical category, figure of speech

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Authors: Lillian Musila, Valerie Oundo, Daniel Erwin, Willie Sang

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Staphylococcus aureus infections are a major cause of nosocomial infections in Kenya. Methicillin resistant S. aureus (MRSA) infections are a significant burden to public health and are associated with considerable morbidity and mortality. At a hospital in Western Kenya two clusters of MRSA cases emerged within short periods of time. In this study we explored whether these clusters represented a nosocomial outbreak by characterizing the isolates using phenotypic and molecular assays and examining epidemiological data to identify possible transmission patterns. Specimens from the site of infection of the subjects were collected, cultured and S. aureus isolates identified phenotypically and confirmed by APIStaph™. MRSA were identified by cefoxitin disk screening per CLSI guidelines. MRSA were further characterized based on their antibiotic susceptibility patterns and spa gene typing. Characteristics of cases with MRSA isolates were compared with those with MSSA isolated around the same time period. Two cases of MRSA infection were identified in the two week period between 21 April and 4 May 2015. A further 2 MRSA isolates were identified on the same day on 7 September 2015. The antibiotic resistance patterns of the two MRSA isolates in the 1st cluster of cases were different suggesting that these were distinct isolates. One isolate had spa type t2029 and the other had a novel spa type. The 2 isolates were obtained from urine and an open skin wound. In the 2nd cluster of MRSA isolates, the antibiotic susceptibility patterns were similar but isolates had different spa types: one was t037 and the other a novel spa type different from the novel MRSA spa type in the first cluster. Both cases in the second cluster were admitted into the hospital but one infection was community- and the other hospital-acquired. Only one of the four MRSA cases was classified as an HAI from an infection acquired post-operatively. When compared to other S. aureus strains isolated within the same time period from the same hospital only one spa type t2029 was found in both MRSA and non-MRSA strains. None of the cases infected with MRSA in the two clusters shared any common epidemiological characteristic such as age, sex or known risk factors for MRSA such as prolonged hospitalization or institutionalization. These data suggest that the observed MRSA clusters were multi strain clusters and not an outbreak of a single strain. There was no clear relationship between the isolates by spa type suggesting that no transmission was occurring within the hospital between these cluster cases but rather that the majority of the MRSA strains were circulating in the community. There was high diversity of spa types among the MRSA strains with none of the isolates sharing spa types. Identification of disease clusters in space and time is critical for immediate infection control action and patient management. Spa gene typing is a rapid way of confirming or ruling out MRSA outbreaks so that costly interventions are applied only when necessary.

Keywords: cluster, Kenya, MRSA, spa typing

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Authors: Manirath Wongsim, Chatchawarn Srimontree, Pornpichit Phosri

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Today, the majority of the data innovation may be currently majorly influencing business, what more accepted part of the accountant may be evolving. Information Technology elements have been appearing to be crucial in triggering changes of accountants’ roles. Thus, this study aims to investigate IT competencies among professional accountants to enhance firm performance. This research was conducted with 47 respondents at five organizations in Thailand and used quantitative research. The results indicate that the factor IT competencies for professional accountants in Thai small to medium accounting within the organizational issues defines18 factors. Specifically, these new factors, based on the research findings and the literature, then unique to IT competencies for professional accountants, include ERP software skills and accounting law and legal skills. The evidence in this study suggests that Analytical skills, teamwork skills, and accounting software were ranked as much-needed skills to be acquired by accountants while communication skills were ranked as the most required skills and delegation skills as the least required. The findings of the research’s empirical evidence suggest that organizations should understand appropriate in developing information technology influence competencies for knowledge employees in general and professional accountants in particular and provide assistance in all processes of decision making.

Keywords: IT competencies, IT competences for professional accountants, IT skills for accounting, IT skills in SMEs

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Authors: Lucas Peries, Rolla Monib

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The construction industry plays a vital role in the global economy, contributing billions of dollars annually. However, the industry has been struggling with persistently low productivity levels for years, unlike other sectors that have shown significant improvements. Modular and prefabricated construction methods have been identified as potential solutions to boost productivity in the construction industry. These methods offer time advantages over traditional construction methods. Despite their potential benefits, modular and prefabricated construction face hindrances and limitations that are not present in traditional building systems. Building information modelling (BIM) has the potential to address some of these hindrances, but barriers are preventing its widespread adoption in the construction industry. This research aims to enhance understanding of the shortcomings of modular and prefabricated building systems and develop BIM-based solutions to alleviate or eliminate these hindrances. The research objectives include identifying and analysing key issues hindering the use of modular and prefabricated building systems, investigating the current state of BIM adoption in the construction industry and factors affecting its successful implementation, proposing BIM-based solutions to address the issues associated with modular and prefabricated building systems, and assessing the effectiveness of the developed solutions in removing barriers to their use. The research methodology involves conducting a critical literature review to identify the key issues and challenges in modular and prefabricated construction and BIM adoption. Additionally, an online questionnaire will be used to collect primary data from construction industry professionals, allowing for feedback and evaluation of the proposed BIM-based solutions. The data collected will be analysed to evaluate the effectiveness of the solutions and their potential impact on the adoption of modular and prefabricated building systems. The main findings of the research indicate that the identified issues from the literature review align with the opinions of industry professionals, and the proposed BIM-based solutions are considered effective in addressing the challenges associated with modular and prefabricated construction. However, the research has limitations, such as a small sample size and the need to assess the feasibility of implementing the proposed solutions. In conclusion, this research contributes to enhancing the understanding of modular and prefabricated building systems' limitations and proposes BIM-based solutions to overcome these limitations. The findings are valuable to construction industry professionals and BIM software developers, providing insights into the challenges and potential solutions for implementing modular and prefabricated construction systems in future projects. Further research should focus on addressing the limitations and assessing the feasibility of implementing the proposed solutions from technical and legal perspectives.

Keywords: building information modelling, modularisation, prefabrication, technology

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Authors: Mohammad Abdul Matin

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This research paper aims to investigate the use of cryptocurrency in facilitating cross-border payments, with a specific focus on the case of Bangladesh. With thousands of Bangladeshi living abroad, the demand for efficient and cost-effective remittance channels is high. This paper will examine the current challenges in cross-border payments for Bangladeshi expatriates and explore the potential benefits and barriers to the adoption of cryptocurrency as a solution. Through a combination of literature review, qualitative interviews, and data analysis, the research will provide valuable insights into the opportunities and risks associated with using cryptocurrency for cross-border payments in Bangladesh.

Keywords: cryptocurrency, cross-border payments, Bangladesh, remittance, expatriates

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

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Authors: Emily Rivera, Toni DiDona

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The Big Five personality traits is a hierarchical classification of personality traits that applies factor analysis to a personality survey data in order to describe human personality using five broad dimensions: Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness (Fetvadjiev & Van de Vijer, 2015). Research shows that personality constructs underline individual differences in processing conflict and interpersonal relations. (Graziano et al., 1996). This research explores the understudied correlation between the Big Five personality traits and perceived interpersonal conflict in the workplace. It revises social psychological literature on Big Five personality traits within a social context and discusses organizational development journal articles on the perceived efficacy of conflict tactics and approach to interpersonal relationships. The study also presents research undertaken on a survey group of 867 subjects over the age of 18 that were recruited by means of convenience sampling through social media, email, and text messaging. The central finding of this study is that only two of the Big Five personality traits had a significant correlation with perceiving interpersonal conflict in the workplace. Individuals who score higher on agreeableness and neuroticism, perceive more interpersonal conflict in the workplace compared to those that score lower on each dimension. The relationship between both constructs is worthy of research due to its everyday frequency and unique individual psycho-social consequences. This multimethod research associated the Big Five personality dimensions to interpersonal conflict. Its findings that can be utilized to further understand social cognition, person perception, complex social behavior and social relationships in the work environment.

Keywords: five-factor model, interpersonal conflict, personality, The Big Five personality traits

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Authors: Afiq Juazer Rizal, Siti Zaleha Misnan, M. Zairi M. Yusof

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Seismic data is the fundamental tool utilized by exploration companies to determine potential hydrocarbon. However, the importance of seismic trace data will be undermined unless the geo-spatial component of the data is understood. Deriving a proposed well to be drilled from data that has positional ambiguity will jeopardize business decision and millions of dollars’ investment that every oil and gas company would like to avoid. Spatial integrity QC workflow has been introduced in PETRONAS to ensure positional errors within the seismic data are recognized throughout the exploration’s lifecycle from acquisition, processing, and seismic interpretation. This includes, amongst other tests, quantifying that the data is referenced to the appropriate coordinate reference system, survey configuration validation, and geometry loading verification. The direct outcome of the workflow implementation helps improve reliability and integrity of sub-surface geological model produced by geoscientist and provide important input to potential hazard assessment where positional accuracy is crucial. This workflow’s development initiative is part of a bigger geospatial integrity management effort, whereby nearly eighty percent of the oil and gas data are location-dependent.

Keywords: oil and gas exploration, PETRONAS, seismic data, spatial integrity QC workflow

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Authors: Sadeeq Launi

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NGOs, the world over, have been recognized as part of the institutions that complement government activities in providing services to the people, particularly in respect of human development. This study examined the role played by the NGOs in human development in Bauchi State, Nigeria, between 2004 and 2013. The emphasis was on reproductive health and access to education role of the selected NGOs. All the research questions, objectives and hypotheses were stated in line with these variables. The theoretical framework that guided the study was the participatory development approach. Being a survey research, data were generated from both primary and secondary sources with questionnaires and interviews as the instruments for generating the primary data. The population of the study was made up of the staff of the selected NGOs, beneficiaries, health staff and school teachers in Bauchi State. The sample drawn from these categories were 90, 107 and 148 units respectively. Stratified random and simple random sampling techniques were adopted for NGOs staff, and Health staff and school teachers data were analyzed quantitatively and qualitatively and hypotheses were tested using Pearson Chi-square test through SPSS computer statistical package. The study revealed that despite the challenges facing NGOs operations in the study area, NGOs rendered services in the areas of health and education This research recommends among others that, both government and people should be more cooperative to NGOs to enable them provide more efficient and effective services. Governments at all levels should be more dedicated to increasing accessibility and affordability of basic education and reproductive health care facilities and services in Bauchi state through committing more resources to the Health and Education sectors, this would support and facilitate the complementary role of NGOs in providing teaching facilities, drugs, and other reproductive health services in the States. More enlightenment campaigns should be carried out by governments to sensitize the public, particularly women on the need to embrace immunization programmes for their children and antenatal care services being provided by both the government and NGOs.

Keywords: access to education, human development, NGOs, reproductive health

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Authors: Pragya Paneru

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This paper explores ten primary teachers’ views on gender representation in primary-level textbooks altogether. Data was collected from the teachers who taught in private schools in Kailali and Kathmandu District. This research uses a semi-structured interview method to obtain information regarding teachers’ attitudes toward gender representations in textbook content. The interview data were analysed by using critical skills of qualitative research analysis methods, as suggested by Saldana and Omasta (2018). The findings revealed that most of the teachers were unaware and regarded gender issues as insignificant to discuss in primary-level classes. Most of them responded to the questions personally and claimed that there were no gender issues in their classrooms. Some of the teachers connected gender issues with contexts other than textbook representations, such as school discrimination in the distribution of salary among male and female teachers, school practices of awarding girls rather than boys as the most disciplined students, following girls’ first rule in the assembly marching, encouraging only girls in the stage shows, and involving students in gender-specific activities such as decorating works for girls and physical tasks for boys. The interview also revealed teachers’ covert gendered attitudes in their remarks. Nevertheless, most of the teachers accepted that gender-biased contents have an impact on learners, and this problem can be solved with more gender-centred research in the education field, discussions, and training to increase awareness regarding gender issues. Agreeing with the suggestion of teachers, this paper recommends proper training and awareness regarding how to confront gender issues in textbooks.

Keywords: content analysis, gender equality, school education, critical awareness

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Authors: Nisful Laila, Fatin Fadhilah Hasib, Puji Sucia Sukmaningrum, Achsania Hendratmi

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The purpose of this study is to determine and comparing the level of efficiency of Islamic Banks in Indonesia and United Kingdom during eurozone sovereign debt crisis. This study using a quantitative non-parametric approach with Data Envelopment Analysis (DEA) VRS assumption, and a statistical tool Mann-Whitney U-Test. The samples are 11 Islamic Banks in Indonesia and 4 Islamic Banks in England. This research used mediating approach. Input variable consists of total deposit, asset, and the cost of labour. Output variable consists of financing and profit/loss. This study shows that the efficiency of Islamic Bank in Indonesia and United Kingdom are varied and fluctuated during the observation period. There is no significant different the efficiency performance of Islamic Banks in Indonesia and United Kingdom.

Keywords: data envelopment analysis, efficiency, eurozone crisis, islamic bank

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Authors: Bernard Igoche Igoche, Olumuyiwa Matthew, Peter Bednar, Alexander Gegov

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This study presents an ontology-driven approach for knowledge discovery and validation from admission databases in Nigerian polytechnic institutions. The research aims to address the challenges of extracting meaningful insights from vast amounts of admission data and utilizing them for decision-making and process improvement. The proposed methodology combines the knowledge discovery in databases (KDD) process with a structural causal model (SCM) ontological framework. The admission database of Benue State Polytechnic Ugbokolo (Benpoly) is used as a case study. The KDD process is employed to mine and distill knowledge from the database, while the SCM ontology is designed to identify and validate the important features of the admission process. The SCM validation is performed using the conditional independence test (CIT) criteria, and an algorithm is developed to implement the validation process. The identified features are then used for machine learning (ML) modeling and prediction of admission status. The results demonstrate the adequacy of the SCM ontological framework in representing the admission process and the high predictive accuracies achieved by the ML models, with k-nearest neighbors (KNN) and support vector machine (SVM) achieving 92% accuracy. The study concludes that the proposed ontology-driven approach contributes to the advancement of educational data mining and provides a foundation for future research in this domain.

Keywords: admission databases, educational data mining, machine learning, ontology-driven knowledge discovery, polytechnic education, structural causal model

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Authors: Hantian Wu, Bo Huang, Yuan Zeng

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Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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Authors: Amel Hannech, Mehdi Adda, Hamid Mcheick

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In computer science, the purpose of finding useful information is still one of the most active and important research topics. The most popular application of information retrieval (IR) are Search Engines, they meet users' specific needs and aim to locate the effective information in the web. However, these search engines have some limitations related to the relevancy of the results and the ease to explore those results. In this context, we proposed in previous works a Multi-Space Search Engine model that is based on a multidimensional interpretation universe. In the present paper, we integrate an additional dimension that allows to offer users new research experiences. The added component is based on creating user profiles and calculating the similarity between them that then allow the use of collaborative filtering in retrieving search results. To evaluate the effectiveness of the proposed model, a prototype is developed. The experiments showed that the additional dimension has improved the relevancy of results by predicting the interesting items of users based on their experiences and the experiences of other similar users. The offered personalization service allows users to approve the pertinent items, which allows to enrich their profiles and further improve research.

Keywords: information retrieval, v-facets, user behavior analysis, user profiles, topical ontology, association rules, data personalization

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Authors: Chi-Lun Liu

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Requirements modeling and analysis are important in successful information systems' maintenance. Unified Modeling Language (UML) class diagrams are useful standards for modeling information systems. To our best knowledge, there is a lack of a systems development methodology described by the organism metaphor. The core concept of this metaphor is adaptation. Using the knowledge representation and reasoning approach and ontologies to adopt new requirements are emergent in recent years. This paper proposes an organic methodology which is based on constructivism theory. This methodology is a knowledge representation and reasoning approach to analyze new requirements in the class diagrams maintenance. The process and rules in the proposed methodology automatically analyze inconsistencies in the class diagram. In the big data era, developing an automatic tool based on the proposed methodology to analyze large amounts of class diagram data is an important research topic in the future.

Keywords: knowledge representation, reasoning, ontology, class diagram, software engineering

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Authors: Zelda Jansen Van Rensburg

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Purpose: This study investigates the perceived disparities between Quantity Surveying and Commercial Management in the construction industry, questioning if these differences are substantive or merely semantic. It aims to challenge the conventional notion of Commercial Managers’ superiority by critically evaluating QS and CM roles, exploring CM integration possibilities, examining qualifications for aspiring Commercial Managers, assessing regulatory frameworks, and considering terminology redefinition for global QS professional enhancement. Design: Utilizing mixed methods like literature reviews, surveys, interviews, and document analyses, this research examines the QS-CM relationship. Insights from industry professionals, academics, and regulatory bodies inform the investigation into changing QS roles. Findings: Empirical data highlight evolving roles, showcasing areas of convergence and divergence between QSs and CM. Potential CM integration into QS practice and qualifications for aspiring Commercial Managers are identified. Limitations/Implications: Limitations include potential bias in self-reported data and findings. Nevertheless, the research informs future practices and educational approaches in QS and CM, reflecting the changing roles and responsibilities of Quantity Surveyors. Practical Implications: Findings inform industry practitioners, educators, and regulators, stressing the need to adapt to changing QS roles and integrate CM principles where applicable. Value to the Conference Theme: Aligned with ‘Evolving roles and responsibilities of Quantity Surveyors,’ this research offers insights crucial for understanding the changing dynamics within the QS profession and informs strategies to navigate these shifts effectively.

Keywords: quantity surveying, commercial management, cost engineering, quantity survey

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Victoria Goodall, Paul Fatti, Norman Owen-Smith

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Hidden Markov Models have become popular for the analysis of animal tracking data. These models are being used to model the movements of a variety of species in many areas around the world. A common assumption of the model is that the observations need to have regular time steps. In many ecological studies, this will not be the case. The objective of the research is to modify the movement model to allow for irregularly spaced locations and investigate the effect on the inferences which can be made about the latent states. A modification of the likelihood function to allow for these irregular spaced locations is investigated, without using interpolation or averaging the movement rate. The suitability of the modification is investigated using GPS tracking data for lion (Panthera leo) in South Africa, with many observations obtained during the night, and few observations during the day. Many nocturnal predator tracking studies are set up in this way, to obtain many locations at night when the animal is most active and is difficult to observe. Few observations are obtained during the day, when the animal is expected to rest and is potentially easier to observe. Modifying the likelihood function allows the popular Hidden Markov Model framework to be used to model these irregular spaced locations, making use of all the observed data.

Keywords: hidden Markov Models, irregular observations, animal movement modelling, nocturnal predator

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Authors: Iveta Řepková

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The aim of this paper is to estimate the efficiency of the Slovak commercial banks employing the Data Envelopment Analysis (DEA) window analysis approach during the period 2003-2012. The research is based on unbalanced panel data of the Slovak commercial banks. Undesirable output was included into analysis of banking efficiency. It was found that most efficient banks were Postovabanka, UniCredit Bank and Istrobanka in CCR model and the most efficient banks were Slovenskasporitelna, Istrobanka and UniCredit Bank in BCC model. On contrary, the lowest efficient banks were found Privatbanka and CitiBank. We found that the largest banks in the Slovak banking market were lower efficient than medium-size and small banks. Results of the paper is that during the period 2003-2008 the average efficiency was increasing and then during the period 2010-2011 the average efficiency decreased as a result of financial crisis.

Keywords: data envelopment analysis, efficiency, Slovak banking sector, window analysis

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Authors: Mehrnaz Mostafavi

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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

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Authors: Md Monirul Islam, Shahaduz Zaman, Mosarraf H. Sarker

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Context: Medical waste management (MWM) is a critical sector in Bangladesh due to its impact on human health and the environment. There is a need to assess the current policies and identify the role of policy actors in the policy formulation and implementation process. Research Aim: The study aimed to evaluate the role of policy actors in the medical waste management policy-making process in Bangladesh, identify policy gaps, and provide actionable recommendations for improvement. Methodology: The study adopted a qualitative research method and conducted key informant interviews. The data collected were analyzed using the thematic coding approach through Atlas.ti software. Findings: The study found that policies are formulated at higher administrative levels and implemented in a top-down approach. Higher-level institutions predominantly contribute to policy development, while lower-level institutions focus on implementation. However, due to negligence, ignorance, and lack of coordination, medical waste management receives insufficient attention from the actors. The study recommends the need for immediate strategies, a comprehensive action plan, regular policy updates, and inter-ministerial meetings to enhance medical waste management practices and interventions. Theoretical Importance: The research contributes to evaluating the role of policy actors in medical waste management policymaking and implementation in Bangladesh. It identifies policy gaps and provides actionable recommendations for improvement. Data Collection: The study used key informant interviews as the data collection method. Thirty-six participants were interviewed, including influential policymakers and representatives of various administrative spheres. Analysis Procedures: The data collected was analyzed using the inductive thematic analysis approach. Question Addressed: The study aimed to assess the role of policy actors in medical waste management policymaking and implementation in Bangladesh. Conclusion: In conclusion, the study provides insights into the current medical waste management policy in Bangladesh, the role of policy actors in policy formulation and implementation, and the need for improved strategies and policy updates. The findings of this study can guide future policy-making efforts to enhance medical waste management practices and interventions in Bangladesh.

Keywords: key informant, medical waste management, policy maker, qualitative study

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Authors: Abdolmajid Mosleh, Afzal Ghasimi

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The purpose of this research is to investigate and identify effective factors that can improve the quality of personal performance in industrial companies. In the present study, it was assumed that the hidden variables of talent management could be explained by an important part of the variance in improving the quality of employee performance. This research is targeted in terms of applied research. The statistical population of the research is SAIPA automobile company with a number (N=10291); the sample of 380 people was selected based on the Cochran formula in a random sampling method among employed people. The measurement tool in this research was a questionnaire of 33 items with a control questionnaire that included two talent management departments (talent identification and talent exploitation) and improvements in staff performance (enhancement of technical and specialized capabilities, managerial capability, organizational interaction, and communication). The reliability of the internal consistency method was confirmed by the Cronbach's alpha coefficient and the two half-ways. In order to determine the validity of the questionnaire structure, confirmatory factor analysis was used. Based on the results of the data analysis, the effect of talent management on improving the quality of staff performance was confirmed. Based on the results of inferential statistics and structural equations of the proposed model, it had high fitness.

Keywords: employee performance, talent management, performance improvement, SAIPA automobile manufacturing company

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Authors: Oussedik Lydia, Zaouani-Denoux Souâd

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In an economic context characterized by intense competition and the impact of new technologies, companies have a constant need to adapt to the environment and the changes imposed. This situation leads companies to take training actions to develop employees’ required skills. Further, training is considered as a strategic lever for the company's growth. Accordingly, an increasing number of companies are adopting training to ensure continuous employees qualification. Thus, the aim of this research is to understand the process of training engineering occurring in the context of a company's continuous training, which will help to identify the gaps that can hinder or promote the development of employees' knowledge and skills. The research methodology is based on a mixed-method approach. Interviews and questionnaires are implemented to collect qualitative and quantitative data. The study results can help managers to identify gaps at each stage of training design. Finally, the research findings provide important information to help design a training plan to support the development of employees' knowledge and performance.

Keywords: training engineering, training needs, training plan, competences, continuing training, perception

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Authors: Shalini Priyadarshini

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The notion of performance measurement has held great appeal for the industry and research communities alike. This idea is also true for the construction sector, and some propose that performance measurement and productivity analysis are two separate management functions, where productivity is a subset of performance, the latter requiring comprehensive analysis of comparable factors. Labor productivity is considered one of the best indicators of production efficiency. The construction industry continues to account for a disproportionate share of injuries and illnesses despite adopting several technological and organizational interventions that promote worker safety. Specialty trades contractors typically complete a large fraction of work on any construction project, but insufficient body of work exists that address subcontractor safety and productivity issues. Literature review has revealed the possibility of a relation between productivity, safety and other factors and their links to project, organizational, task and industry performance. This research posits that there is an association between productivity and performance at project as well as organizational levels in the construction industry. Moreover, prior exploration of the importance of safety within the performance-productivity framework has been anecdotal at best. Using structured questionnaire survey and organization- and project level data, this study, which is a combination of cross-sectional and longitudinal research designs, addresses the identified research gap and models the relationship between productivity, safety, and performance with a focus on specialty trades in the construction sector. Statistical analysis is used to establish a correlation between the variables of interest. This research identifies the need for developing and maintaining productivity and safety logs for smaller businesses. Future studies can design and develop research to establish causal relationships between these variables.

Keywords: construction, safety, productivity, performance, specialty trades

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Authors: Saleh Nabiyev

Abstract:

Renewable energy is becoming increasingly important in today's world due to its significant impact on the green economy, ecology, environment, and climate change. Renewable energy sources, such as solar and wind, are clean and sustainable, making them an ideal solution to reduce carbon emissions and mitigate the effects of climate change. The Karabakh region is located in the South Caucasus and covers an area of approximately 11,500 km². The region has a mountainous terrain, which can affect the availability of wind and solar resources. The Karabakh region has significant wind power potential, particularly in its mountainous areas where wind speeds are typically higher. According to a study conducted by the European Commission Joint Research Centre, the average wind speed in the Karabakh region is between 4 and 6 meters per second (m/s) at a height of 50 meters above ground level (AGL). However, wind speeds can be higher in some areas, reaching up to 10 m/s in some mountainous areas. The region also has significant solar power potential, with an average of 2,000 to 2,200 hours of sunshine per year. The region's high altitude and clear skies make it particularly suitable for the development of solar power projects. In this research, the application of satellite images, solar radiation, wind speed and direction, as well as various other materials to determine suitable areas for alternative energy sources, is investigated. The methodology for selecting suitable locations for solar and wind energy consists of four main parts: identification of factors, evaluation of factors, data preparation, and application of suitability analysis. At the end of the research, the territory of the Kalbajar and Lachin districts is suitable for wind energy. The southern plain part of Karabakh is highly evaluated in terms of solar energy potential, especially Jabrayil district. Generally, outcomes taken from this research are essential data for increasing of rational using natural resources, as well as combating climate change.

Keywords: GIS, remote sensing, suitability analysis, solar energy, wind energy

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Authors: Chaudhuri Manoj Kumar Swain, Susmita Das

Abstract:

This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.

Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis

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Authors: Tazeen Fatima

Abstract:

Use of project management in web & software development projects is very significant. It has been observed that even with the application of effective project management, projects usually do not complete their lifecycle and fail. To minimize these failures, key performance indicators have been introduced in previous studies to counter project failures. However, there are always gaps and problems in the KPIs identified. Despite of incessant efforts at technical and managerial levels, projects still fail. There is no substantial approach to identify and avoid these failures in the very beginning of the project lifecycle. In this study, we aim to answer these research problems by analyzing the concept of predictive analytics which is a specialized technology and is very easy to use in this era of computation. Project organizations can use data gathering, compute power, and modern tools to render efficient Predictions. The research aims to identify such a predictive analytics approach. The core objective of the study was to reduce failures and introduce effective implementation of project management principles. Existing predictive analytics methodologies, tools and solution providers were also analyzed. Relevant data was gathered from projects and was analyzed via predictive techniques to make predictions well advance in time to render effective project management in web & software development industry.

Keywords: project management, predictive analytics, predictive analytics methodology, project failures

Procedia PDF Downloads 347

Authors: Sagar R. Patil, Dinesh R. Gawade, Sudhir N. Divekar

Abstract:

One of the medical devices we found when we visit a hospital care unit such device is ‘patient monitoring system’. This device (patient monitoring system) informs doctors and nurses about the patient’s physiological signals. However, this device (patient monitoring system) does not have a remote monitoring capability, which is necessitates constant onsite attendance by support personnel (doctors and nurses). Thus, we have developed a Remote Wireless Patient Monitoring System using some biomedical sensors and Android OS, which is a portable patient monitoring. This device(Remote Wireless Patient Monitoring System) monitors the biomedical signals of patients in real time and sends them to remote stations (doctors and nurse’s android Smartphone and web) for display and with alerts when necessary. Wireless Patient Monitoring System different from conventional device (Patient Monitoring system) in two aspects: First its wireless communication capability allows physiological signals to be monitored remotely and second, it is portable so patients can move while there biomedical signals are being monitor. Wireless Patient Monitoring is also notable because of its implementation. We are integrated four sensors such as pulse oximeter (SPO2), thermometer, respiration, blood pressure (BP), heart rate and electrocardiogram (ECG) in this device (Wireless Patient Monitoring System) and Monitoring and communication applications are implemented on the Android OS using threads, which facilitate the stable and timely manipulation of signals and the appropriate sharing of resources. The biomedical data will be display on android smart phone as well as on web Using web server and database system we can share these physiological signals with remote place medical personnel’s or with any where in the world medical personnel’s. We verified that the multitasking implementation used in the system was suitable for patient monitoring and for other Healthcare applications.

Keywords: patient monitoring, wireless patient monitoring, bio-medical signals, physiological signals, embedded system, Android OS, healthcare, pulse oximeter (SPO2), thermometer, respiration, blood pressure (BP), heart rate, electrocardiogram (ECG)

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Authors: Phillipa Evans, Christopher Trotter

Abstract:

Aims: This study aims to examine the effectiveness of a practice skills framework implemented in three youth detention centres in Juvenile Justice in New South Wales (NSW), Australia. The study is supported by a grant from and Australian Research Council and NSW Juvenile Justice. Recent years have seen a number of incidents in youth detention centres in Australia and other places. These have led to inquiries and reviews with some suggesting that detention centres often do not even meet basic human rights and do little in terms of providing opportunities for rehabilitation of residents. While there is an increasing body of research suggesting that community based supervision can be effective in reducing recidivism if appropriate skills are used by supervisors, there has been less work considering worker skills in youth detention settings. The research that has been done, however, suggest that teaching interpersonal skills to youth officers may be effective in enhancing the rehabilitation culture of centres. Positive outcomes have been seen in a UK detention centre for example, from teaching staff to do five-minute problem-solving interventions. The aim of this project is to examine the effectiveness of training and coaching youth detention staff in three NSW detention centres in interpersonal practice skills. Effectiveness is defined in terms of reductions in the frequency of critical incidents and improvements in the well-being of staff and young people. The research is important as the results may lead to the development of more humane and rehabilitative experiences for young people. Method: The study involves training staff in core effective practice skills and supporting staff in the use of those skills through supervision and de-briefing. The core effective practice skills include role clarification, pro-social modelling, brief problem solving, and relationship skills. The training also addresses some of the background to criminal behaviour including trauma. Data regarding critical incidents and well-being before and after the program implementation are being collected. This involves interviews with staff and young people, the completion of well-being scales, and examination of departmental records regarding critical incidents. In addition to the before and after comparison a matched control group which is not offered the intervention is also being used. The study includes more than 400 young people and 100 youth officers across 6 centres including the control sites. Data collection includes interviews with workers and young people, critical incident data such as assaults, use of lock ups and confinement and school attendance. Data collection also includes analysing video-tapes of centre activities for changes in the use of staff skills. Results: The project is currently underway with ongoing training and supervision. Early results will be available for the conference.

Keywords: custody, practice skills, training, youth workers

Procedia PDF Downloads 103