Search results for: mining organisation

Authors: Yousuf Nasser Al Khamisi

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Purpose: This paper presents a Knowledge Transfer (KT) Framework in healthcare sectors by applying a systematic literature review process to the healthcare organizations domain to identify enablers and barriers of KT in Healthcare. Methods: The paper conducted a systematic literature search of peer-reviewed papers that described key elements of KT using four databases (Medline, Cinahl, Scopus, and Proquest) for a 10-year period (1/1/2008–16/10/2017). The results of the literature review were used to build a conceptual framework of KT in healthcare organizations. The author used a systematic review of the literature, as described by Barbara Kitchenham in Procedures for Performing Systematic Reviews. Findings: The paper highlighted the impacts of using Knowledge Management (KM) concept at a healthcare organization in controlling infectious diseases in hospitals, improving family medicine performance and enhancing quality improvement practices. Moreover, it found that good-coding performance is analytically linked with a knowledge sharing network structure rich in brokerage and hierarchy rather than in density. The unavailability or ignored of the latest evidence on more cost-effective or more efficient delivery approaches leads to increase the healthcare costs and may lead to unintended results. Originality: Search procedure produced 12,093 results, of which 3523 were general articles about KM and KT. The titles and abstracts of these articles had been screened to segregate what is related and what is not. 94 articles identified by the researchers for full-text assessment. The total number of eligible articles after removing un-related articles was 22 articles.

Keywords: healthcare organisation, knowledge management, knowledge transfer, KT framework

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Authors: Lethamaga Tladi, Ray Kekwaletswe

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This study sought to conceptualise a multi-level framework for the effective use of stock ordering system in small enterprises in a rural area context. The interpretive research methodology has been used to enable the researcher to analyse, in-depth, and the subjective meanings of small enterprises’ employees in using the stock ordering system. The empirical data was collected from 13 small enterprises’ employees as participants through semi-structured interviews and observations. Interpretive Phenomenological Analysis (IPA) approach was used to analyse the small enterprises’ employee’s own account of lived experiences in relations to stock ordering system use in terms of their relatedness to, and cognitive engagement with. A case study of Kgautswane, a rural area in Limpopo Province, South Africa, served as a social context where the phenomenon manifested. Technology-Organisation-Environment Theory (TOE), Technology-to-Performance Chain Model (TPC), and Representation Theory (RT) underpinned this study. In this multi-level study, the findings revealed that; At the organisational level, the effective use of stock ordering system was found to be associated with the organisational performance gains such as efficiency, productivity, quality, competitiveness, and market share. Equally so, at the individual level, the effective use of stock ordering system minimised the end-user’s efforts and time to accomplish their tasks, which yields improved individual performance. The Multi-level framework for effective use of stock ordering system was presented.

Keywords: effective use, multi-dimensions of use, multi-level of use, multi-level research, small enterprises, stock ordering system

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Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

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Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, decision support system, TOPSIS, FAHP, PROMETHEE

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Authors: Avelyno D'Costa, S. K. Shyama, M. K. Praveen Kumar

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The coast of Goa, India receives constant anthropogenic stress through its major rivers which carry mining rejects of iron and manganese ores from upstream mining sites and petroleum hydrocarbons from shipping and harbor-related activities which put the aquatic fauna such as bivalves at risk. The present study reports the pollution status of the Goan coast by the above xenobiotics employing genotoxicity studies. This is further supplemented by the quantification of total petroleum hydrocarbons (TPHs) and various trace metals (iron, manganese, copper, cadmium, and lead) in gills of the estuarine clam, Meretrix ovum as well as from the surrounding water and sediment, over a two-year sampling period, from January 2013 to December 2014. Bivalves were collected from a probable unpolluted site at Palolem and a probable polluted site at Vasco, based upon the anthropogenic activities at these sites. Genotoxicity was assessed in the gill cells using the comet assay and micronucleus test. The quantity of TPHs and trace metals present in gill tissue, water and sediments were analyzed using spectrofluorometry and atomic absorption spectrophotometry (AAS), respectively. The statistical significance of data was analyzed employing Student’s t-test. The relationship between DNA damage and pollutant concentrations was evaluated using multiple regression analysis. Significant DNA damage was observed in the bivalves collected from Vasco which is a region of high industrial activity. Concentrations of TPHs and trace metals (iron, manganese, and cadmium) were also found to be significantly high in gills of the bivalves collected from Vasco compared to those collected from Palolem. Further, the concentrations of these pollutants were also found to be significantly high in the water and sediments at Vasco compared to that of Palolem. This may be due to the lack of industrial activity at Palolem. A high positive correlation was observed between the pollutant levels and DNA damage in the bivalves collected from Vasco suggesting the genotoxic nature of these pollutants. Further, M. ovum can be used as a bioindicator species for monitoring the level of pollution of the estuarine/coastal regions by TPHs and trace metals.

Keywords: comet assay, metals, micronucleus test, total petroleum Hydrocarbons

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Authors: Erin Hea-Jin Kim

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This study aims to investigate scholarly communication patterns in Korean studies, which focuses on all aspects of Korea, including history, culture, literature, politics, society, economics, religion, and so on. It is called ‘national study or home study’ as the subject of the study is itself, whereas it is called ‘area study’ as the subject of the study is others, i.e., outside of Korea. Understanding of the structure of scholarly communication in Korean studies is important since the motivations, procedures, results, or outcomes of individual studies may be affected by the cooperative relationships that appear in the communication structure. To this end, we collected 1,798 articles with the (author or index) keyword ‘Korean’ published in 2018 from the Scopus database and extracted the institution and country of the authors using a text mining technique. A total of 96 countries, including South Korea, was identified. Then we constructed a co-authorship network based on the countries identified. The indicators of social network analysis (SNA), co-occurrences, and cluster analysis were used to measure the activity and connectivity of participation in collaboration in Korean studies. As a result, the highest frequency of collaboration appears in the following order: S. Korea with the United States (603), S. Korea with Japan (146), S. Korea with China (131), S. Korea with the United Kingdom (83), and China with the United States (65). This means that the most active participants are S. Korea as well as the USA. The highest rank in the role of mediator measured by betweenness centrality appears in the following order: United States (0.165), United Kingdom (0.045), China (0.043), Japan (0.037), Australia (0.026), and South Africa (0.023). These results show that these countries contribute to connecting in Korean studies. We found two major communities among the co-authorship network. Asian countries and America belong to the same community, and the United Kingdom and European countries belong to the other community. Korean studies have a long history, and the study has emerged since Japanese colonization. However, Korean studies have never been investigated by digital content analysis. The contributions of this study are an analysis of co-authorship in Korean studies with a global perspective based on digital content, which has not attempted so far to our knowledge, and to suggest ideas on how to analyze the humanities disciplines such as history, literature, or Korean studies by text mining. The limitation of this study is that the scholarly data we collected did not cover all domestic journals because we only gathered scholarly data from Scopus. There are thousands of domestic journals not indexed in Scopus that we can consider in terms of national studies, but are not possible to collect.

Keywords: co-authorship network, Korean studies, Koreanology, scholarly communication

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Authors: Trupti Diwan

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Predicting student failure at school has changed into a difficult challenge due to both the large number of factors that can affect the reduced performance of students and the imbalanced nature of these kinds of data sets. This paper surveys the two elements needed to make prediction on Students’ Academic Performances which are parameters and methods. This paper also proposes a framework for predicting the performance of engineering students. Genetic programming can be used to predict student failure/success. Ranking algorithm is used to rank students according to their credit points. The framework can be used as a basis for the system implementation & prediction of students’ Academic Performance in Higher Learning Institute.

Keywords: classification, educational data mining, student failure, grammar-based genetic programming

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Authors: Oluremi I. Bamgbade, Oluwayomi Babatunde

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Governments and nonprofits have been in the support of sustainability as the goal of businesses especially in the construction industry because of its considerable impacts on the environment, economy, and society. However, to measure the degree to which an organisation is being sustainable or pursuing sustainable growth can be difficult as a result of the clear sustainability strategy required to assume their commitment to the goal and competitive advantage. This research investigated the influence of organisational culture and organisational structure in achieving sustainable construction among South African construction firms. A total of 132 consultants from the nine provinces in South Africa participated in the survey. The data collected were initially screened using SPSS (version 21) while Partial Least Squares Structural Equation Modeling (PLS-SEM) algorithm and bootstrap techniques were employed to test the hypothesised paths. The empirical evidence also supported the hypothesised direct effects of organisational culture and organisational structure on sustainable construction. Similarly, the result regarding the relationship between organisational culture and organisational structure was supported. Therefore, construction industry can record a considerable level of construction sustainability and establish suitable cultures and structures within the construction organisations. Drawing upon organisational control theory, these findings supported the view that these organisational internal factors have a strong contingent effect on sustainability adoption in construction project execution. The paper makes theoretical, practical and methodological contributions within the domain of sustainable construction especially in the context of South Africa. Some limitations of the study are indicated, suggesting opportunities for future research.

Keywords: organisational culture, organisational structure, South African construction firms, sustainable construction

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Authors: Lakmali Anthony, Madeline Gillies

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Purpose: Long-term survivorship in colorectal cancer (CRC) is increasing as mortality decreases, leading to increased focus on patient-reported outcomes such as quality of life (QoL). CRC patients often have decreased QoL even after treatment is complete. This systematic review of the literature aims to identify psychosocial factors associated with decreased QoL in post-treatment CRC patients. Methodology: This systematic review was performed in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations. The search was conducted in MEDLINE, EMBASE, and PsychINFO using MeSH headings. The two authors screened studies for relevance and extracted data. Results: Seventeen studies were identified, including 6,272 total participants (mean = 392, 58% male) with a mean age of 60.6 years. The European Organisation for Research and Treatment of Cancer QLQ-C30 was the most common measure of QoL (n=14, 82.3%). Most studies (n=15, 88.2%) found that emotional distress correlated with poor global QoL. This was most commonly measured with the Hospital Anxiety & Depression Scale (n=11, 64.7%). Other psychosocial factors associated with QoL were lack of social support, body image, and financial difficulties. Clinicopathologic determinants included presence of stoma and metastasis. Conclusion: This systematic review provides a summary of the psychosocial determinants of poor QoL in post-treatment CRC patients, as well as the most commonly reported measures of these. An understanding of these potentially modifiable determinants of poor outcome is pivotal to the provision of quality, patient-centred care in surgical oncology.

Keywords: colorectal cancer, cancer surgery, quality of life, oncology, social determinants

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Authors: Ana Pego

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Environmental technologies were developed for decades. Clean technologies emerged a few years ago. In these perspectives, the use of cleantech technologies has become very important due the fact of new era of environmental feats. As such, the market itself has become more competitive, more collaborative towards a better use of clean technologies. This paper shows the importance of clean technologies in offshore energy sector in Portuguese market, its localization and its impact on economy. Clean technologies are directly related with renewable cluster and concomitant with economic and social resource optimization criteria, geographic aspects, climate change and soil features. Cleantech is related with regional development, socio-technical transitions in organisations. There are an economical and social combinations which allow specialisation of regions in activities, higher employment, reduce of energy costs, local knowledge spillover and, business collaboration and competitiveness. The methodology used will be quantitative (IO matrix for Portugal 2013) and qualitative (questionnaires to stakeholders). The mix of both methodologies will confirm whether the use of technologies will allow a positive impact on economic and social variables used on this model. It is expected a positive impact on Portuguese economy both in investment and employment taking in account the localization of offshore renewable activities. This means that the importance of offshore renewable investment in Portugal has a few points which should be pointed out: the increase of specialised employment, localization of specific activities in territory, and increase of value added in certain regions. The conclusion will allow researchers and organisation to compare the Portuguese model to other European regions in order to a better use of natural and human resources.

Keywords: cleantech, economic impact, localisation, territory dynamics

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Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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Authors: Jeongyeob Hong, Myeonghoon Park, Taeson Yoon

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After the advent of Achaeans which utilize different metabolism pathway and contain conspicuously different cellular structure, they have been recognized as possible materials for developing quality of human beings. Among diverse Achaeans, in this paper, we compared 16s RNA Sequences of four different species of Thermococcus: Achaeans genus specialized in sulfur-dealing metabolism. Four Species, Barophilus, Kodakarensis, Hydrothermalis, and Onnurineus, live near the hydrothermal vent that emits extreme amount of sulfur and heat. By comparing ribosomal sequences of aforementioned four species, we found similarities in their sequences and expressed protein, enabling us to expect that certain ribosomal sequence or proteins are vital for their survival. Apriori algorithms and Decision Tree were used. for comparison.

Keywords: Achaeans, Thermococcus, apriori algorithm, decision tree

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Authors: Merkouche Wassila, Marchand Alain, Renaud Stéphane

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Organizations are facing competitive pressures constraining them to modify their practices and change initial work conditions of employees, however, these modifications have to sustain initial quality of work and engagements toward the workforce. We focus on the importance of promises in the perspective of psychological contract. According to this perspective, employees perceiving a breach of the expected obligations from the employer may become unsatisfied at work and develop organizational withdrawal behaviors. These are negative counterproductive behaviours aiming to damage the organisation according to the principle of reciprocity and social exchange. We present an integrative model of the determinants and manifestations of organizational withdrawal (OW), a set of behaviors allowing the employee to leave his job or avoid his assigned work. OW contains two main components often studied in silos: work withdrawal (delays, absenteeism and other adverse behaviors) and job withdrawal (turnover). We use the systemic micro, meso and macro sociological approach designing the individual at the heart of a system containing individual, organizational, and environmental determinants. Under the influence of these different factors, the individual assesses the type of behavior to adopt. We provide better lighting for understanding OW using both psychological contract approach through the perception of its respect by the organization and job embeddedness approach which explains why the employee does not leave the organization and then remains in his post while practicing negative and counterproductive behaviors such as OW. We study specifically cynicism as a type of OW as it is a dimension of burnout. We focus on the antecedents of cynicism to try to prevent it in the workplace.

Keywords: burnout, cynicism, job embeddedness, organizational withdrawal, psychological contract

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Authors: Joanna Grzybowska, Magdalena Igras, Mariusz Ziółko

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Association rule learning is an approach for discovering interesting relationships in large databases. The analysis of relations, invisible at first glance, is a source of new knowledge which can be subsequently used for prediction. We used this data mining technique (which is an automatic and objective method) to learn about interesting affects associations in a corpus of emergency phone calls. We also made an attempt to match revealed rules with their possible situational context. The corpus was collected and subjectively annotated by two researchers. Each of 3306 recordings contains information on emotion: (1) type (sadness, weariness, anxiety, surprise, stress, anger, frustration, calm, relief, compassion, contentment, amusement, joy) (2) valence (negative, neutral, or positive) (3) intensity (low, typical, alternating, high). Also, additional information, that is a clue to speaker’s emotional state, was annotated: speech rate (slow, normal, fast), characteristic vocabulary (filled pauses, repeated words) and conversation style (normal, chaotic). Exponentially many rules can be extracted from a set of items (an item is a previously annotated single information). To generate the rules in the form of an implication X → Y (where X and Y are frequent k-itemsets) the Apriori algorithm was used - it avoids performing needless computations. Then, two basic measures (Support and Confidence) and several additional symmetric and asymmetric objective measures (e.g. Laplace, Conviction, Interest Factor, Cosine, correlation coefficient) were calculated for each rule. Each applied interestingness measure revealed different rules - we selected some top rules for each measure. Owing to the specificity of the corpus (emergency situations), most of the strong rules contain only negative emotions. There are though strong rules including neutral or even positive emotions. Three examples of the strongest rules are: {sadness} → {anxiety}; {sadness, weariness, stress, frustration} → {anger}; {compassion} → {sadness}. Association rule learning revealed the strongest configurations of affects (as well as configurations of affects with affect-related information) in our emergency phone calls corpus. The acquired knowledge can be used for prediction to fulfill the emotional profile of a new caller. Furthermore, a rule-related possible context analysis may be a clue to the situation a caller is in.

Keywords: data mining, emergency phone calls, emotional profiles, rules

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Authors: Abdelhalem Shahen

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The world is now experiencing a digital revolution and greatly accelerated technological developments, in addition to the transition from the economy in its traditional form to the digital economy, which has resulted in the emergence of new tools that are appropriate to those developments, and from this, this paper attempts to explore the economic characteristics of the bitcoin currency that circulated recently. Due to the many advantages that distinguish it from money in its traditional forms, which have a range of economic effects. The study found that Bitcoin is among the technological innovations, which contain a set of characteristics that are worth studying, those that make it the focus of attention, such as the digital currency, the peer-to-peer property, Lower and Faster Transaction Costs, transparency, decentralized control, privacy, and Double-Spending, as well as security and Cryptographic, and finally mining.

Keywords: Digital Economics, Digital Currencies, Bitcoin, Features of Bitcoin

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Authors: Eugene Mashapa

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The age of information has witnessed countless unprecedented technological developments, which signal the articulation of succinct technological capabilities that can match these cutting-edge technological trends. These changes have impacted patterns in the production, distribution, and consumption of media content, a space that the Film and Publication Board (FPB) is concerned with. Consequently, the FPB is keen to understand the nature and impact of these technological changes on media content regulation. This exploratory study sought to investigate how content regulators in high and middle-income economies have adapted to the changes in this space, seeking insights into innovations, technological and operational, that facilitate continued relevance during this fast-changing environment. The study is aimed at developing recommendations that could assist and inform the organisation in regulating media content as it evolves. Thus, the overall research strategy in this analysis is applied research, and the analytical model adopted is a mixed research design guided by both qualitative and quantitative research instruments. It was revealed in the study that the FPB was significantly impacted by the unprecedented technological advancements in the media regulation space. Additionally, there exists a need for the FPB to understand the current and future penetrations of 4IR technology in the industry and its impact on media governance and policy implementation. This will range from reskilling officials to align with the technological skills to developing technological innovations as well as adopting co-regulatory or self-regulatory arrangements together with content distributors, where more content is distributed in higher volumes and with increased frequency. Importantly, initiating an interactive learning process for both FPB employees and the general public can assist the regulator and improve FPB’s operational efficiency and effectiveness.

Keywords: media, regulation, technology, film and publications board

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Authors: Timothy Wale Olaosebikan

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The most active resource in any organization is the manpower. Every other resource remains inactive unless there is competent manpower to handle them. Manpower training is needed to enhance productivity and overall performance of the organizations. This is due to the recognition of the important role of manpower training in attainment of organizational goals. Corporate Compliance conjures visions of an incomprehensible matrix of laws and regulations that defy logic and control by even the most seasoned manpower training professionals. Similarly, corporate compliance can be viewed as one of the most significant problems faced in manpower training process for any organization, therefore, commands relevant attention and comprehension. Consequently, this study investigated the nexus between manpower training and corporate compliance. Collection of data for the study was effected through the use of questionnaire with a sample size of 265 drawn by stratified random sampling. The data were analyzed using descriptive and inferential statistics. The findings of the study show that about 75% of the respondents agree that there is a strong relationship between manpower training and corporate compliance, which brings out the organizational attainment from any training process. The findings further show that most organisation do not totally comply with the rules guiding manpower training process thereby making the process less effective on organizational performance, which may affect overall profitability. The study concludes that formulation and compliance of adequate rules and guidelines for manpower trainings will produce effective results for both employees and the organization at large. The study recommends that leaders of organizations, industries, and institutions must ensure total compliance on the part of both the employees and the organization to manpower training rules. Organizations and stakeholders should also ensure that strict policies on corporate compliance to manpower trainings form the heart of their cardinal mission.

Keywords: corporate compliance, manpower training, nexus, rules and guidelines

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Authors: Atsuko Okazaki, Jurg Ott

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Some genetic diseases (‘digenic traits’) are due to the interaction between two DNA variants. For example, certain forms of Retinitis Pigmentosa (a genetic form of blindness) occur in the presence of two mutant variants, one in the ROM1 gene and one in the RDS gene, while the occurrence of only one of these mutant variants leads to a completely normal phenotype. Detecting such digenic traits by genetic methods is difficult. A common approach to finding disease-causing variants is to compare 100,000s of variants between individuals with a trait (cases) and those without the trait (controls). Such genome-wide association studies (GWASs) have been very successful but hinge on genetic effects of single variants, that is, there should be a difference in allele or genotype frequencies between cases and controls at a disease-causing variant. Frequent pattern mining (FPM) methods offer an avenue at detecting digenic traits even in the absence of single-variant effects. The idea is to enumerate pairs of genotypes (genotype patterns) with each of the two genotypes originating from different variants that may be located at very different genomic positions. What is needed is for genotype patterns to be significantly more common in cases than in controls. Let Y = 2 refer to cases and Y = 1 to controls, with X denoting a specific genotype pattern. We are seeking association rules, ‘X → Y’, with high confidence, P(Y = 2|X), significantly higher than the proportion of cases, P(Y = 2) in the study. Clearly, generally available FPM methods are very suitable for detecting disease-associated genotype patterns. We use fpgrowth as the basic FPM algorithm and built a framework around it to enumerate high-frequency digenic genotype patterns and to evaluate their statistical significance by permutation analysis. Application to a published dataset on opioid dependence furnished results that could not be found with classical GWAS methodology. There were 143 cases and 153 healthy controls, each genotyped for 82 variants in eight genes of the opioid system. The aim was to find out whether any of these variants were disease-associated. The single-variant analysis did not lead to significant results. Application of our FPM implementation resulted in one significant (p < 0.01) genotype pattern with both genotypes in the pattern being heterozygous and originating from two variants on different chromosomes. This pattern occurred in 14 cases and none of the controls. Thus, the pattern seems quite specific to this form of substance abuse and is also rather predictive of disease. An algorithm called Multifactor Dimension Reduction (MDR) was developed some 20 years ago and has been in use in human genetics ever since. This and our algorithms share some similar properties, but they are also very different in other respects. The main difference seems to be that our algorithm focuses on patterns of genotypes while the main object of inference in MDR is the 3 × 3 table of genotypes at two variants.

Keywords: digenic traits, DNA variants, epistasis, statistical genetics

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Authors: Emily Simango, T. Chitura

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Background: Bovine brucellosis is among the most neglected zoonotic diseases in developing countries, where it is endemic and a growing challenge to public health. The development of cost-effective control measures for the disease can only be affirmed by the knowledge of the disease epidemiology and the ability to define its risk profiles. The aim of the study was to document the trend of bovine brucellosis and the control measures adopted following reported cases during the period 2014 to 2019 in South Africa. Methods: Data on confirmed cases of bovine brucellosis was retrieved from the website of the World Organisation of Animal Health (WOAH). Data was analysed using the Statistical Package for Social Sciences (IBM SPSS, 2022) version 29.0. Descriptive analysis (frequencies and percentages) and the Analysis of variance (ANOVA) were utilized for statistical significance (p<0.05). Results: The data retrieved in our study revealed an overall average bovine brucellosis prevalence of 8.48. There were statistically significant differences in bovine brucellosis prevalence across the provinces for the years 2016 and 2019 (p≥0.05), with the Eastern Cape Province having the highest prevalence in both instances. Documented control measures for the disease were limited to killing and disposal of disease cases as well as vaccination of susceptible animals. Conclusion: Bovine brucellosis is real in South Africa, with the risk profiles differing across the provinces. Information on brucellosis control measures in South Africa, as reported to the WOAH, is not comprehensive.

Keywords: zoonotic, endemic, Eastern Cape province, vaccination

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Authors: Cleopatra Gittens

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It has been recognized that some social security and national insurance systems in the Eastern Caribbean are experiencing ageing populations and economic and other crises that will present a financial challenge of being unable to pay pension benefits in fifteen to twenty years. This has implications for the fiscal and economic positions of the countries themselves. Hence, organizations would need to address the issue urgently. The study adds to the body of knowledge on social security systems and social security reforms in small island developing states (SIDS). It also makes recommendations for the types of reforms that social security systems in other SIDS can implement given their special circumstances. Secondary research is used to gather financial and other related information on three social security schemes in the Eastern Caribbean. Actuarial and financial reports and other documents of the social security systems are analysed to obtain financial and static data on each of the schemes. The findings show that the three schemes studied are experiencing steady increases in benefit expenditure versus contributions and increasing pensioner to insured ratios. The schemes will deplete their reserves between 2038 and 2050. Two of the schemes have increased their retirement age while the other has not embarked on any reforms. One scheme has made changes to its contribution percentages. Due to their small size, small populations and other unique circumstances, the social security schemes in the identified territories are not likely to be able to take advantage of all of the reform initiatives that the developed world embarked on when faced with similar problems. These schemes will need to make incremental changes that align with the timeframes recommended by the actuarial studies.

Keywords: benefits, pension, small island developing states, social security reform

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Authors: Lakmali Anthony, Madeline Gillies

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Purpose: Decreasing mortality has led to increased focus on patient-reported outcomes such as quality of life (QoL) in breast cancer. Breast cancer patients often have decreased QoL even after treatment is complete. This systematic review of the literature aims to identify psychosocial factors associated with decreased QoL in post-treatment breast cancer patients. Methodology: This systematic review was performed in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations. The search was conducted in MEDLINE, EMBASE, and PsychINFO using MeSH headings. The two authors screened studies for relevance and extracted data. Results: Seventeen studies were identified, including 3,150 total participants (mean = 197) with a mean age of 51.9 years. There was substantial heterogeneity in measures of QoL. The most common was the European Organisation for Research and Treatment of Cancer QLQ-C30 (n=7, 41.1%). Most studies (n=12, 70.5%) found that emotional distress correlated with poor QoL, while 3 found no significant association. The most common measure of emotional distress was the Hospital Anxiety and Depression Scale (n=12, 70.5%). Other psychosocial factors associated with QoL were unmet needs, problematic social support, and negative affect. Clinicopathologic determinants included mastectomy without reconstruction, stage IV disease, and adjuvant chemotherapy. Conclusion: This systematic review provides a summary of the psychosocial determinants of poor QoL in post-treatment breast cancer patients, as well as the most commonly reported measures of these. An understanding of these potentially modifiable determinants of poor outcome is pivotal to the provision of quality, patient-centred care in surgical oncology.

Keywords: breast cancer, quality of life, psychosocial determinants, cancer surgery

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Authors: Taurai T. Chikotie, Bruce W. Watson

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The manifestation of ‘new’ infectious diseases and the re-emergence of ‘old’ infectious diseases now present global problems and Southern Africa has not been spared from such calamity. Although having an organized public health system, countries in this region have failed to leverage on the proliferation in use of Information and Communication Technologies to promote effective disease surveillance. Objective: The objective of this study was to critically review and analyse the crucial variables to consider in the development and implementation of electronic disease surveillance systems in public health within the context of Southern Africa. Methodology: A critical review of literature published in English using, Google Scholar, EBSCOHOST, Science Direct, databases from the Centre for Disease Control (CDC and articles from the World Health Organisation (WHO) was undertaken. Manual reference and grey literature searches were also conducted. Results: Little has been done towards harnessing the potential of information technologies towards disease surveillance and this has been due to several challenges that include, lack of funding, lack of health informatics experts, poor supporting infrastructure, an unstable socio-political and socio-economic ecosystem in the region and archaic policies towards integration of information technologies in public health governance. Conclusion: The Southern African region stands to achieve better health outcomes if they adopt the use of e-disease surveillance systems in public health. However, the dynamics and complexities of the socio-economic, socio-political and technical variables would need addressing to ensure the successful development and implementation of e-disease surveillance systems in the region.

Keywords: critical review, disease surveillance, public health informatics, Southern Africa

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Authors: Yayun Hsu, Henry Horng-Shing Lu

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This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate cross talk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds since biological information is inherently included in the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning

Procedia PDF Downloads 475

Authors: Saeed Bagherifam, Trevor Brown, Chris Fellows, Ravi Naidu

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Over the last century, rapid urbanization, industrial emissions, and mining activities have resulted in widespread contamination of the environment by heavy metal(loid)s. Arsenic (As) is a toxic metalloid belonging to group 15 of the periodic table, which occurs naturally at low concentrations in soils and the earth’s crust, although concentrations can be significantly elevated in natural systems as a result of dispersion from anthropogenic sources, e.g., mining activities. Bioavailability is the fraction of a contaminant in soils that is available for uptake by plants, food chains, and humans and therefore presents the greatest risk to terrestrial ecosystems. Numerous attempts have been made to establish in situ and ex-situ technologies of remedial action for remediation of arsenic-contaminated soils. In situ stabilization techniques are based on deactivation or chemical immobilization of metalloid(s) in soil by means of soil amendments, which consequently reduce the bioavailability (for biota) and bioaccessibility (for humans) of metalloids due to the formation of low-solubility products or precipitates. This study investigated the effectiveness of two different types of synthetic manganese and iron oxides (birnessite and goethite) for stabilization of As in a soil spiked with 1000 mg kg⁻¹ of As and treated with 10% dosages of soil amendments. Birnessite was made using HCl and KMnO₄, and goethite was synthesized by the dropwise addition of KOH into Fe(NO₃) solution. The resulting contaminated soils were subjected to a series of chemical extraction studies including sequential extraction (BCR method), single-step extraction with distilled (DI) water, 2M HNO₃ and simplified bioaccessibility extraction tests (SBET) for estimation of bioaccessible fractions of As in two different soil fractions ( < 250 µm and < 2 mm). Concentrations of As in samples were measured using inductively coupled plasma mass spectrometry (ICP-MS). The results showed that soil with birnessite reduced bioaccessibility of As by up to 92% in both soil fractions. Furthermore, the results of single-step extractions revealed that the application of both birnessite and Goethite reduced DI water and HNO₃ extractable amounts of arsenic by 75, 75, 91, and 57%, respectively. Moreover, the results of the sequential extraction studies showed that both birnessite and goethite dramatically reduced the exchangeable fraction of As in soils. However, the amounts of recalcitrant fractions were higher in birnessite, and Goethite amended soils. The results revealed that the application of both birnessite and goethite significantly reduced bioavailability and the exchangeable fraction of As in contaminated soils, and therefore birnessite and Goethite amendments might be considered as promising adsorbents for stabilization and remediation of As contaminated soils.

Keywords: arsenic, bioavailability, in situ stabilisation, metalloid(s) contaminated soils

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Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata

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The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system, thus, the proposed solution has been verified. The paper documents how it is possible to apply new discovery knowledge to be used in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.

Keywords: hierarchical process control, knowledge discovery from databases, neural network, process control

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Authors: Hing Hao Chan, Thomas Richard, Masood Mostofi

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The mining industry relies on an estimate of rock strength at several stages of a mine life cycle: mining (excavating, blasting, tunnelling) and processing (crushing and grinding), both very energy-intensive activities. An effective comminution design that can yield significant dividends often requires a reliable estimate of the material rock strength. Common laboratory tests such as rod, ball mill, and uniaxial compressive strength share common shortcomings such as time, sample preparation, bias in plug selection cost, repeatability, and sample amount to ensure reliable estimates. In this paper, the authors present a methodology to derive an estimate of the rock strength from drilling data recorded while coring with a diamond core head. The work presented in this paper builds on a phenomenological model of the bit-rock interface proposed by Franca et al. (2015) and is inspired by the now well-established use of the scratch test with PDC (Polycrystalline Diamond Compact) cutter to derive the rock uniaxial compressive strength. The first part of the paper introduces the phenomenological model of the bit-rock interface for a diamond core head that relates the forces acting on the drill bit (torque, axial thrust) to the bit kinematic variables (rate of penetration and angular velocity) and introduces the intrinsic specific energy or the energy required to drill a unit volume of rock for an ideally sharp drilling tool (meaning ideally sharp diamonds and no contact between the bit matrix and rock debris) that is found well correlated to the rock uniaxial compressive strength for PDC and roller cone bits. The second part describes the laboratory drill rig, the experimental procedure that is tailored to minimize the effect of diamond polishing over the duration of the experiments, and the step-by-step methodology to derive the intrinsic specific energy from the recorded data. The third section presents the results and shows that the intrinsic specific energy correlates well to the uniaxial compressive strength for the 11 tested rock materials (7 sedimentary and 4 igneous rocks). The last section discusses best drilling practices and a method to estimate the rock strength from field drilling data considering the compliance of the drill string and frictional losses along the borehole. The approach is illustrated with a case study from drilling data recorded while drilling an exploration well in Australia.

Keywords: bit-rock interaction, drilling experiment, impregnated diamond drilling, uniaxial compressive strength

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Prachi Bhatt

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Motivated workforce is an important asset of an organisation. Intrinsic motivation is one of the key aspects of people operations and performance. Researches have emphasized the significance of internal factors in individuals’ motivation. In the changing business scenario, it is a challenge for the organizations’ leaders to inspire and motivate their workforce. The present study deals with the intrinsic motivation potential of an individual which govern the innate capability of an individual driving him or her to behave or perform in the changing work environment, tasks, teams. Differences at individual level significantly influence differences in levels of motivation. In the above context, the present research attempts to explore behavioral trait dimensions which influence motivational potential of an individual. The present research emphasizes the significance of intrinsic motivational potential and the significance of exploring the differences in the intrinsic motivational potential levels of individuals at work places. Thus, this paper empirically tests the framework of behavioral traits which affects motivational potential of an individual. With the help of two studies i.e., Study 1 and Study 2, exploratory factor analysis and confirmatory factor analysis, respectively, indicated a reliable measure assessing intrinsic motivational potential of an individual. Given the variety of challenges of motivating contemporary workforce, and with increasing importance of intrinsic motivation, the paper discusses the relevance of the findings and of the measure assessing intrinsic motivational potential. Assessment of such behavioral traits would assist in the effective realization of intrinsic motivational potential of individuals. Additionally, the paper discusses the practical implications and furnishes scope for future research.

Keywords: behavioral traits, individual differences, intrinsic motivational potential, intrinsic motivation, motivation, workplace motivation

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Authors: Khadidja Belbachir, Hafida Belbachir

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subsequently the expansion of the physical supports storage and the needs ceaseless to accumulate several data, the sequential algorithms of associations’ rules research proved to be ineffective. Thus the introduction of the new parallel versions is imperative. We propose in this paper, a parallel version of a sequential algorithm “Partition”. This last is fundamentally different from the other sequential algorithms, because it scans the data base only twice to generate the significant association rules. By consequence, the parallel approach does not require much communication between the sites. The proposed approach was implemented for an experimental study. The obtained results, shows a great reduction in execution time compared to the sequential version and Count Distributed algorithm.

Keywords: association rules, distributed data mining, partition, parallel algorithms

Procedia PDF Downloads 392

Authors: Repaul Kanji, Rajat Agrawal

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In this era where issues like climate change and disasters are the topics of discussion at national and international forums, it is very often that humanity questions the causative role of corporates in such events. It is beyond any doubt that rapid industrialisation and development has taken a toll in the form of climate change and even disasters, in some case. Thus, demanding to fulfill a corporate's responsibilities in the form of rescue and relief in times of disaster, rehabilitation and even mitigation and preparedness to adapt to the oncoming changes is obvious. But how can the responsibilities of the corporates be channelised to ensure all this, i.e., develop a resilient society? More than that, which factors, when emphasised upon, can lead to the holistic development of the society. To answer this query, an extensive literature review was done to identify several enablers like legislations of a nation, the role of brand and reputation, ease of doing Corporate Social Responsibility, mission and vision of an organisation, religion and culture, etc. as a tool for building disaster resilience. A questionnaire survey, interviews with experts and academicians followed by interpretive structural modelling (ISM) were used to construct a multi-hierarchy model depicting the contextual relationship among the identified enablers. The study revealed that culture and religion are the most powerful driver, which affects other enablers either directly or indirectly. Taking cognisance of the fact that an idea of separation between religion and workplace (business) resides subconsciously within the society, the study tries to interpret the outcome of the ISM through the lenses of past researches (The Integrating Box) and explores how it can be leveraged to build a resilient society.

Keywords: corporate social responsibility, interpretive structural modelling, disaster resilience and risk reduction, the integration box (TIB)

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Authors: Takalani Tshitangano

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Background: In Limpopo province the rate of new tuberculosis (TB) cases increase daily. The Infection Control (IC) plan is one of the essential actions for TB IC. This study aimed to establish the availability of these plans at health care facilities. Objectives: The objectives were to explore and describe the awareness and knowledge of health care workers (HCWs) of the availability and content of TB IC plan; and to identity the role of infection control committees from the perspective of HCWs. Method: A qualitative approach using a cross-sectional descriptive design was adopted. The target population was all HCWs from the seven hospitals of Vhembe district. A purposive sampling approach was used to select 57 participants. The approval to conduct this study was obtained from the relevant authorities and participants. Data were collected through seven focus group discussions comprising five to 10 members. An unstructured discussion guide was used to collect data, and an open-coding method was used to analyse the data. Lincoln and Guba’s criteria ensured trustworthiness of the study findings. Results: Findings revealed that HCWs were not aware of the availability and the information contained in the TB IC plans. No person was designated as TB IC officer at hospital level. There was lack of a TB IC Committee and teams as well as ineffective utilisation of those that did exist. Conclusions: It was concluded that if the TB IC plans are not available at health care facilities, then the TB IC practices implemented by HCWs vary, resulting in TB nosocomial infection transmission. It was recommended that the World Health Organisation’s TB IC plans be adopted and implemented in Vhembe district.

Keywords: health care workers' awareness, health care workers' knowledge, availability of TB infection control plans, rural hospitals

Procedia PDF Downloads 211