Search results for: traditional knowledge resources classification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17522

Search results for: traditional knowledge resources classification

17132 A Comparative Study of Afghan Traditional and Contemporary Courtyard Housing Regarding Affordable Planning and Sustainability

Authors: Mohammad Saraj Sharifzai, Keisuke Kitagawa, Mohammad Kamil Halimee, Javid Habib, Daishi Sakaguchi

Abstract:

The purpose of this research is to upgrade a pleasing, sustainable and safe shelter in the Afghan urban community. It also aims to maintain traditional housing, which is fitted to its environment, while attempting to upgrade it with new, traditional standards. The three main objectives of this study are to upgrade the traditional courtyard house to become safe and sustainable today and tomorrow; to fit the contemporary house environmentally and culturally, and to suppress or reduce the broad gap between traditional and contemporary housing. The paper tries to exhibit and analyze the sustainably best practices available in both traditional and contemporary courtyard housing in Afghanistan. For instance, the use of thick walls and Tawa-Khana (floor heating system) shows the best sustainable practice in that context.

Keywords: Afghan Traditional Courtyard Housing (ATCH), Afghan Contemporary Courtyard Housing (ACCH), suitability planning, affordable and thermal comfort

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17131 Classification Rule Discovery by Using Parallel Ant Colony Optimization

Authors: Waseem Shahzad, Ayesha Tahir Khan, Hamid Hussain Awan

Abstract:

Ant-Miner algorithm that lies under ACO algorithms is used to extract knowledge from data in the form of rules. A variant of Ant-Miner algorithm named as cAnt-MinerPB is used to generate list of rules using pittsburgh approach in order to maintain the rule interaction among the rules that are generated. In this paper, we propose a parallel Ant MinerPB in which Ant colony optimization algorithm runs parallel. In this technique, a data set is divided vertically (i-e attributes) into different subsets. These subsets are created based on the correlation among attributes using Mutual Information (MI). It generates rules in a parallel manner and then merged to form a final list of rules. The results have shown that the proposed technique achieved higher accuracy when compared with original cAnt-MinerPB and also the execution time has also reduced.

Keywords: ant colony optimization, parallel Ant-MinerPB, vertical partitioning, classification rule discovery

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17130 Optimisation of B2C Supply Chain Resource Allocation

Authors: Firdaous Zair, Zoubir Elfelsoufi, Mohammed Fourka

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The allocation of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players, manufacturers and Click & Mortars that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. Our contribution is a decision support system and tool for improving the allocation of resources in logistics chains e-commerce B2C context. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. In addition, every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource allocation in customized online shopping service mode, which is different from the supply chain resource allocation under traditional manufacturing or service circumstances. Then we realized an optimization model and algorithm for the development based on the analysis of the allocation of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: e-commerce, supply chain, B2C, optimisation, resource allocation

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17129 A Novel Method for Face Detection

Authors: H. Abas Nejad, A. R. Teymoori

Abstract:

Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, etc. in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as the user stays neutral for the majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this work, we propose a light-weight neutral vs. emotion classification engine, which acts as a preprocessor to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at Key Emotion (KE) points using a textural statistical model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a textural statistical model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves ER accuracy and simultaneously reduces the computational complexity of ER system, as validated on multiple databases.

Keywords: neutral vs. emotion classification, Constrained Local Model, procrustes analysis, Local Binary Pattern Histogram, statistical model

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17128 Effectiveness of Technology Enhanced Learning in Orthodontic Teaching

Authors: Mohammed Shaath

Abstract:

Aims Technological advancements in teaching and learning have made significant improvements over the past decade and have been incorporated in institutions to aid the learner’s experience. This review aims to assess whether Technology Enhanced Learning (TEL) pedagogy is more effective at improving students’ attitude and knowledge retention in orthodontic training than traditional methods. Methodology The searches comprised Systematic Reviews (SRs) related to the comparison of TEL and traditional teaching methods from the following databases: PubMed, SCOPUS, Medline, and Embase. One researcher performed the screening, data extraction, and analysis and assessed the risk of bias and quality using A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR-2). Kirkpatrick’s 4-level evaluation model was used to evaluate the educational values. Results A sum of 34 SRs was identified after the removal of duplications and irrelevant SRs; 4 fit the inclusion criteria. On Level 1, students showed positivity to TEL methods, although acknowledging that the harder the platforms to use, the less favourable. Nonetheless, the students still showed high levels of acceptability. Level 2 showed there is no significant overall advantage of increased knowledge when it comes to TEL methods. One SR showed that certain aspects of study within orthodontics deliver a statistical improvement with TEL. Level 3 was the least reported on. Results showed that if left without time restrictions, TEL methods may be advantageous. Level 4 shows that both methods are equally as effective, but TEL has the potential to overtake traditional methods in the future as a form of active, student-centered approach. Conclusion TEL has a high level of acceptability and potential to improve learning in orthodontics. Current reviews have potential to be improved, but the biggest aspect that needs to be addressed is the primary study, which shows a lower level of evidence and heterogeneity in their results. As it stands, the replacement of traditional methods with TEL cannot be fully supported in an evidence-based manner. The potential of TEL methods has been recognized and is already starting to show some evidence of the ability to be more effective in some aspects of learning to cater for a more technology savvy generation.

Keywords: TEL, orthodontic, teaching, traditional

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17127 Managing HR Knowledge in a Large Privately Owned Enterprise: An Empirical Case Analysis

Authors: Cindy Wang-Cowham, Judy Ningyu Tang

Abstract:

The paper contributes towards the development of scarce literature on HR knowledge management. Drawing literature from knowledge management, the authors define the meaning of HR knowledge and propose that there are social mechanisms in organizations that facilitate the management and sharing of HR knowledge. Instead of investigating the subject in large multinational corporations, the present paper examines it in a large Chinese privately owned enterprise, which has an international standing. The main finding of the case analysis is that communication and feedback plays a pivotal role when managing HR knowledge. Social mechanisms can stimulate the communication and feedback between employees, thus facilitate knowledge exchange.

Keywords: HR knowledge, knowledge management, large privately owned enterprises, China

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17126 Developing Future New Roles for Traditional Birth Attendants in Nigeria

Authors: Hauwau Mohammed

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Research purpose: the integration of Traditional Birth Attendants (TBAs) has long been initiated into healthcare systems. This has been to help improve maternal mortality, particularly in developing countries. Nigeria is seen as one of the countries with a high maternal death rate due to common pregnancy complications and low resources. Communities with challenges of universal coverage of skilled workers rely on TBAs for pregnancy-related services, including delivery. The Sokoto State government has conducted several training programs on a significant number of TBAs to enable a formal integration of relationships with skilled healthcare for women in rural regions. This study aims to explore a standard method and develop an assessment framework for improving TBAs training programs in Sokoto State. Research Design, Methodology & Methods : Using a qualitative design, an interpretive phenomenology approach will be applied to explore the lived-experiences of 28 TBAs, who have undergone a form of training while also examining the strategies used to develop those programs through 8 policymakers and/or program trainers. For the collection stage, a focus group discussion and a face-to-face interview will be conducted, where the latter is for TBAs and the former for policymakers and training officials. Analysis: Data will be analyse through IPA format while using Nvivo to code and catalog personal experiential generated patterns. Secondary review: a scoping review of secondary data from Nigeria was used to map the knowledge gap and the extent of available data. The thematic analytic findings suggested that there are various approaches used to incorporate TBAs into the healthcare system, which include interventional programs targeted at specific health issues. In addition, incentives were used to encourage TBAs to facilitate the frequent use of skilled care for women.

Keywords: traditional birth attendants, Nigeria, training, program

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17125 Enhancing Inservice Education Training Effectiveness Using a Mobile Based E-Learning Model

Authors: Richard Patrick Kabuye

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This study focuses on the addressing the enhancement of in-service training programs as a tool of transforming the existing traditional approaches of formal lectures/contact hours. This will be supported with a more versatile, robust, and remotely accessible means of mobile based e-learning, as a support tool for the traditional means. A combination of various factors in education and incorporation of the eLearning strategy proves to be a key factor in effective in-service education. Key factor needs to be factored in so as to maintain a credible co-existence of the programs, with the prevailing social, economic and political environments. Effective in-service education focuses on having immediate transformation of knowledge into practice for a good time period, active participation of attendees, enable before training planning, in training assessment and post training feedback training analysis which will yield knowledge to the trainers of the applicability of knowledge given out. All the above require a more robust approach to attain success in implementation. Incorporating mobile technology in eLearning will enable the above to be factored together in a more coherent manner, as it is evident that participants have to take time off their duties and attend to these training programs. Making it mobile, will save a lot of time since participants would be in position to follow certain modules while away from lecture rooms, get continuous program updates after completing the program, send feedback to instructors on knowledge gaps, and a wholly conclusive evaluation of the entire program on a learn as you work platform. This study will follow both qualitative and quantitative approaches in data collection, and this will be compounded incorporating a mobile eLearning application using Android.

Keywords: in service, training, mobile, e- learning, model

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17124 A Strength Weaknesses Opportunities and Threats Analysis of Socialisation Externalisation Combination and Internalisation Modes in Knowledge Management Practice: A Systematic Review of Literature

Authors: Aderonke Olaitan Adesina

Abstract:

Background: The paradigm shift to knowledge, as the key to organizational innovation and competitive advantage, has made the management of knowledge resources in organizations a mandate. A key component of the knowledge management (KM) cycle is knowledge creation, which is researched to be the result of the interaction between explicit and tacit knowledge. An effective knowledge creation process requires the use of the right model. The SECI (Socialisation, Externalisation, Combination, and Internalisation) model, proposed in 1995, is attested to be a preferred model of choice for knowledge creation activities. The model has, however, been criticized by researchers, who raise their concern, especially about its sequential nature. Therefore, this paper reviews extant literature on the practical application of each mode of the SECI model, from 1995 to date, with a view to ascertaining the relevance in modern-day KM practice. The study will establish the trends of use, with regards to the location and industry of use, and the interconnectedness of the modes. The main research question is, for organizational knowledge creation activities, is the SECI model indeed linear and sequential? In other words, does the model need to be reviewed in today’s KM practice? The review will generate a compendium of the usage of the SECI modes and propose a framework of use, based on the strength weaknesses opportunities and threats (SWOT) findings of the study. Method: This study will employ the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to investigate the usage and SWOT of the modes, in order to ascertain the success, or otherwise, of the sequential application of the modes in practice from 1995 to 2019. To achieve the purpose, four databases will be explored to search for open access, peer-reviewed articles from 1995 to 2019. The year 1995 is chosen as the baseline because it was the year the first paper on the SECI model was published. The study will appraise relevant peer-reviewed articles under the search terms: SECI (or its synonym, knowledge creation theory), socialization, externalization, combination, and internalization in the title, abstract, or keywords list. This review will include only empirical studies of knowledge management initiatives in which the SECI model and its modes were used. Findings: It is expected that the study will highlight the practical relevance of each mode of the SECI model, the linearity or not of the model, the SWOT in each mode. Concluding Statement: Organisations can, from the analysis, determine the modes of emphasis for their knowledge creation activities. It is expected that the study will support decision making in the choice of the SECI model as a strategy for the management of organizational knowledge resources, and in appropriating the SECI model, or its remodeled version, as a theoretical framework in future KM research.

Keywords: combination, externalisation, internalisation, knowledge management, SECI model, socialisation

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17123 Impact of New Media Technologies to News, Social Interactions, and Traditional Media

Authors: Ademola Bamgbose

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The new media revolution, which encompasses a wide variety of new media technologies like blogs, social networking, visual worlds, wikis, have had a great influence on communications, traditional media and across other disciplines. This paper gives a review of the impact of new media technologies on the news, social interactions and traditional media in developing and developed countries. The study points to the fact that there is a significant impact of new media technologies on the news, social interactions and the traditional media in developing and developed countries, albeit both positively and negatively. Social interactions have been significantly affected, as well as in news production and reporting. It is reiterated that despite the pervasiveness of new media technologies, it would not bring to a total decline of traditional media. This paper contributes to the theoretical framework on the new media and will help to assess the extent of the impact of the new media in different locations.

Keywords: communication, media, news, new media technologies, social interactions, traditional media

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17122 Ethnobotanical Study of Medicinal Plants Used by Indigenous People of Community Forest User Groups of Parbat District, Nepal

Authors: Gokul Gaudel, Zhang Wen Hui, Dang Quang Hung, Le Thi Hien, Liang Xiao

Abstract:

The community forests of Nepal serve as a major source of medicinal plants for majority of local people who are dependent on traditional health care system. This study aims to explore the ethnobotanical information of the medicinal plants used by five different community forest user groups of Parbat district of Nepal. The research was conducted during different periods of the year 2015, using semi-structured, open-ended questionnaires, formal and informal interviews, and group discussions. In total 145 different plant species within 77 families were documented, the majority of them being herb were found to be used to treat 84 different ailments. In terms of plant parts use: whole plants, barks, fruits, leaves were found to be in top priorities. Oral administration was the dominant route (57%), followed by both oral and dermal route (29%) and dermal only (14%). Females were found to have 24% more ethnobotanical knowledge than male. The knowledge of ethnobotanical medicinal plants was found excellent on age group 65-75. This study showed that community forests of Parbat district are rich in medicinal plants but the new generation was found less interested in using them. Easy access to modern medicines, lack of documentation and knowledge transfer to young generations are the major causes of diminishing utility of traditional medicinal practices.

Keywords: ailments, community forest, ethnobotany, medicinal plants, Parbat

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17121 Facilitating Knowledge Transfer for New Product Development in Portfolio Entrepreneurship: A Case Study of a Sodium-Ion Battery Start-up in China

Authors: Guohong Wang, Hao Huang, Rui Xing, Liyan Tang, Yu Wang

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Start-ups are consistently under pressure to overcome liabilities of newness and smallness. They must focus on assembling resource and engaging constant renewal and repeated entrepreneurial activities to survive and grow. As an important form of resource, knowledge is constantly vital to start-ups, which will help start-ups with developing new product in hence forming competitive advantage. However, significant knowledge is usually needed to be identified and exploited from external entities, which makes it difficult to achieve knowledge transfer; with limited resources, it can be quite challenging for start-ups balancing the exploration and exploitation of knowledge. The research on knowledge transfer has become a relatively well-developed domain by indicating that knowledge transfer can be achieved through plenty of patterns, yet it is still under-explored that what processes and organizational practices help start-ups facilitating knowledge transfer for new product in the context portfolio entrepreneurship. Resource orchestration theory emphasizes the initiative and active management of company or the manager to explain the fulfillment of resource utility, which will help understand the process of managing knowledge as a certain kind of resource in start-ups. Drawing on the resource orchestration theory, this research aims to explore how knowledge transfer can be facilitated through resource orchestration. A qualitative single-case study of a sodium-ion battery new venture was conducted. The case company is sampled deliberately from representative industrial agglomeration areas in Liaoning Province, China. It is found that distinctive resource orchestration sub-processes are leveraged to facilitate knowledge transfer: (i) resource structuring makes knowledge available across the portfolio; (ii) resource bundling makes combines internal and external knowledge to form new knowledge; and (iii) resource harmonizing balances specific knowledge configurations across the portfolio. Meanwhile, by purposefully reallocating knowledge configurations to new product development in a certain new venture (exploration) and gradually adjusting knowledge configurations to being applied to existing products across the portfolio (exploitation), resource orchestration processes as a whole make exploration and exploitation of knowledge balanced. This study contributes to the knowledge management literature through proposing a resource orchestration view and depicting how knowledge transfer can be facilitated through different resource orchestration processes and mechanisms. In addition, by revealing the balancing process of exploration and exploitation of knowledge, and laying stress on the significance of the idea of making exploration and exploitation of knowledge balanced in the context of portfolio entrepreneurship, this study also adds specific efforts to entrepreneurship and strategy management literature.

Keywords: exploration and exploitation, knowledge transfer, new product development, portfolio entrepreneur, resource orchestration

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17120 Greyscale: A Tree-Based Taxonomy for Grey Literature Published by Fisheries Agencies

Authors: Tatiana Tunon, Gottfried Pestal

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Government agencies responsible for the management of fisheries resources publish many types of grey literature, and these materials are increasingly accessible to the public on agency websites. However, scope and quality vary considerably, and end-users need meta-data about the report series when deciding whether to use the information (e.g. apply the methods, include the results in a systematic review), or when prioritizing materials for archiving (e.g. library holdings, reference databases). A proposed taxonomy for these report series was developed based on a review of 41 report series from 6 government agencies in 4 countries (Canada, New Zealand, Scotland, and United States). Each report series was categorized according to multiple criteria describing peer-review process, content, and purpose. A robust classification tree was then fitted to these descriptions, and the resulting taxonomic groups were used to compare agency output from 4 countries using reports available in their online repositories.

Keywords: classification tree, fisheries, government, grey literature

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17119 How to Incorporate Vernacular Architecture into Practice for Sustainable Development: Case Studies from Kashmir and Kerala, India

Authors: Debanjana Chatterjee

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Vernacular settlements in India often take the form that is dictated by the climate they are in. India, with its vast cultural diversity and various climatic regions, offers a wide range of vernacular architecture. This paper focuses on two main geographical regions: Kashmir and Kerala. They bring together myriad challenges of climatic and social characteristics to incorporate into their vernacular architectures, which are still relevant despite the advent of globalization and modernization. Scholars like William Wurster and Catherine Bauer even claimed that all the traditional buildings in these places have the kind of urbanity, which is dignified and elegant but also lively and human that every architect would like to achieve if they knew how. With modernization, and with a greater ease of construction, a reduction in labor, and the apparent robustness of contemporary construction techniques, people have, however, become increasingly tentative in respect of vernacular architecture. And yet modern architecture has typically led to energize intensive structures without much consideration to the location and surroundings of the structure itself. In contrary, Laurie Baker, the British-born Indian architect, had shown us the way to integrate the knowledge of vernacular when he developed his designs based on the traditional architecture of Kerala, respecting the local climate and environment. This paper also explores his technical creativity in his design of Center for Development Studies (CDS) in Trivandrum. Hence, in order to protect and conserve our rich cultural and architectural heritage, the elements of vernacular should be incorporated into the contemporary planning and architecture for sustainable building design. The provision should be made to incorporate vernacular architecture and traditional knowledge in the policies. Ultimately, the policymakers, planners, and architects should consider this incorporation of traditional vernacular and contemporary sustainability in their work for the betterment of society now.

Keywords: vernacular, architecture, sustainable development, Kashmir and Kerala, climate, Laurie Baker

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17118 Ethnomedicinal Uses of Plants in Bridim Village Development Committee in Langtang National Park, Nepal

Authors: Ila Shrestha

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Bridim Village Development Committee (VDC) is one of the medicinal plants hot spots of Nepal. It is located on a ridge above the lower Langtang Khola, steep and narrow spot in between 1944 m to 4833 m altitude. The study area is homogeneously inhabited by Tamang communities. An investigation on folk herbal medicine on the basis of traditional uses of medicinal plants was done in 2014. The local traditional healers, elder men and women, traders and teachers, were consulted as key informants for documentation of indigenous knowledge on the medicinal plants. It was found that altogether seventy-one medicinal plant species belonging to sixty genera and thirty-three families were used by local people for twenty-seven diseases. Roots of thirty-four species were the most frequently used plant parts and bigger numbers of species were found to be used in fever of ten species. Most medicines were prepared in the form of juice of forty species. The attempt of the study was to document ethno medicinal practices to treat different diseases in the study area for conservation of indigenous knowledge.

Keywords: Bridim village, ethnomedicine, national park, plants

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17117 Classifying and Predicting Efficiencies Using Interval DEA Grid Setting

Authors: Yiannis G. Smirlis

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The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: data envelopment analysis, interval DEA, efficiency classification, efficiency prediction

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17116 Role of Indigenous Women in Securing Sustainable Livelihoods in Western Himalayan Region, India

Authors: Haresh Sharma, Jaimini Luharia

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The ecology in the Western Himalayan region transforms with the change in altitude. This change is observed in terms of topography, species of flora and fauna and the quality of the soil. The current study focuses on women of indigenous communities of Pangi Valley, which is located in the state of Himachal Pradesh, India. The valley is bifurcated into three different areas –Saichu, Hudan Bhatori, and Sural Bhatori valleys. It is one of the most remote, rugged and difficult to access tribal regions of Chamba district. The altitude of the valley ranges from 2,000 m to 6,000 m above sea level. The Pangi valley is inhabited by ‘Pangwals’ and ‘Bhots’ tribes of the Himalayas who speak their local tribal language called’ Pangwali’. The valley is cut-off from the mainland due to heavy snow and lack of proper roads during peak winters. Due to difficult geographical location, the daily lives of the people are constantly challenged, and they are most of the times deprived of benefits targeted through government programs. However, the indigenous communities earn their livelihood through livestock and forest-based produce while some of them migrate to nearby places for better work. The current study involves snowball sampling methodology for data collection along with in-depth interviews of women members of Self-Help Groups and women farmers. The findings reveal that the lives of these indigenous communities largely depend on forest-based products. So, it creates all the more significance of enhancing, maintaining, and consuming natural resources sustainably. Under such circumstances, the women of the community play a significant role of guardians in conservation and protection of the forests. They are the custodians of traditional knowledge of environment conservation practices that have been followed for many years in the region. The present study also sought to establish a relationship between some of the development initiatives undertaken by the women in the valley that stimulate sustainable mountain economy and conservation practices. These initiatives include cultivation of products like hazelnut, ‘Gucchi’ rare quality mushroom, medicinal plants exclusively found in the region, thereby promoting long term sustainable conservation of agro-biodiversity of the Western Himalayan region. The measures taken by the community women are commendable as they ensure access and distribution of natural resources as well as manage them for future generations. Apart from this, the tribal women have actively formed Self-Help Groups promoting financial inclusion through various activities that augment ownership and accountability towards the overall development of the communities. But, the results also suggest that there’s not enough recognition given to women’s role in forests conservation practices due to several local socio-political reasons. There are not enough research studies done on communities of Pangi Valley due to inaccessibility created out of lack of proper roads and other resources. Also, there emerged a need to concretize indigenous and traditional knowledge of conservation practices followed by women in the community.

Keywords: forest conservation, indigenous community women, sustainable livelihoods, sustainable development, poverty alleviation, Western Himalayas

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17115 Effect of Social Media on Knowledge Work

Authors: Pekka Makkonen, Georgios Lampropoulos, Kerstin Siakas

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This paper examines the impact of social media on knowledge work. It discloses and highlights which specific aspects, areas and tasks of knowledge work can be improved by the use of social media. Moreover, the study includes a survey about higher education students’ viewpoints in regard to the use of social media as a means to enhance knowledge work and knowledge sharing. The analysis has been conducted based both on empirical data and on discussions about the sources dealing with knowledge work and how it can be enhanced by using social media. The results show that social media can improve knowledge work, knowledge building and maintenance tasks in which communication, information sharing and collaboration play a vital role. Additionally, by using social media, personal, collaborative and supplementary work activities can be enhanced. Based on the results of the study, we suggest how knowledge work can be enhanced when using the contemporary information and communications technologies (ICTs) of the 21st century and recommend future directions towards improving knowledge work.

Keywords: knowledge work, social media, social media services, improving work performance

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17114 Ontology-Driven Generation of Radiation Protection Procedures

Authors: Chamseddine Barki, Salam Labidi, Hanen Boussi Rahmouni

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In this article, we present the principle and suitable methodology for the design of a medical ontology that highlights the radiological and dosimetric knowledge, applied in diagnostic radiology and radiation-therapy. Our ontology, which we named «Onto.Rap», is the subject of radiation protection in medical and radiology centers by providing a standardized regulatory oversight. Thanks to its added values of knowledge-sharing, reuse and the ease of maintenance, this ontology tends to solve many problems. Of which we name the confusion between radiological procedures a practitioner might face while performing a patient radiological exam. Adding to it, the difficulties they might have in interpreting applicable patient radioprotection standards. Here, the ontology, thanks to its concepts simplification and expressiveness capabilities, can ensure an efficient classification of radiological procedures. It also provides an explicit representation of the relations between the different components of the studied concept. In fact, an ontology based-radioprotection expert system, when used in radiological center, could implement systematic radioprotection best practices during patient exam and a regulatory compliance service auditing afterwards.

Keywords: knowledge, ontology, radiation protection, radiology

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17113 Exploring the Role of Data Mining in Crime Classification: A Systematic Literature Review

Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

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This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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17112 Feature Weighting Comparison Based on Clustering Centers in the Detection of Diabetic Retinopathy

Authors: Kemal Polat

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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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17111 Rank-Based Chain-Mode Ensemble for Binary Classification

Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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17110 A Strategic Communication Design Model for Indigenous Knowledge Management

Authors: Dilina Janadith Nawarathne

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This article presents the initial development of a communication model (Model_isi) as the means of gathering, preserving and transferring indigenous knowledge in the field of knowledge management. The article first discusses the need for an appropriate complimentary model for indigenous knowledge management which differs from the existing methods and models. Then the paper suggests the newly developed model for indigenous knowledge management which generate as result of blending key aspects of different disciplines, which can be implemented as a complementary approach for the existing scientific method. The paper further presents the effectiveness of the developed method in reflecting upon a pilot demonstration carried out on selected indigenous communities of Sri Lanka.

Keywords: indigenous knowledge management, knowledge transferring, tacit knowledge, research model, asian centric philosophy

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17109 Spectral Mixture Model Applied to Cannabis Parcel Determination

Authors: Levent Basayigit, Sinan Demir, Yusuf Ucar, Burhan Kara

Abstract:

Many research projects require accurate delineation of the different land cover type of the agricultural area. Especially it is critically important for the definition of specific plants like cannabis. However, the complexity of vegetation stands structure, abundant vegetation species, and the smooth transition between different seconder section stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier. Most of the time, classification distinguishes only between trees/annual or grain. It has been difficult to accurately determine the cannabis mixed with other plants. In this paper, a mixed distribution models approach is applied to classify pure and mix cannabis parcels using Worldview-2 imagery in the Lakes region of Turkey. Five different land use types (i.e. sunflower, maize, bare soil, and cannabis) were identified in the image. A constrained Gaussian mixture discriminant analysis (GMDA) was used to unmix the image. In the study, 255 reflectance ratios derived from spectral signatures of seven bands (Blue-Green-Yellow-Red-Rededge-NIR1-NIR2) were randomly arranged as 80% for training and 20% for test data. Gaussian mixed distribution model approach is proved to be an effective and convenient way to combine very high spatial resolution imagery for distinguishing cannabis vegetation. Based on the overall accuracies of the classification, the Gaussian mixed distribution model was found to be very successful to achieve image classification tasks. This approach is sensitive to capture the illegal cannabis planting areas in the large plain. This approach can also be used for monitoring and determination with spectral reflections in illegal cannabis planting areas.

Keywords: Gaussian mixture discriminant analysis, spectral mixture model, Worldview-2, land parcels

Procedia PDF Downloads 197
17108 Socio-Cultural Factors to Support Knowledge Management and Organizational Innovation: A Study of Small and Medium-Sized Enterprises in Latvia

Authors: Madara Apsalone

Abstract:

Knowledge management and innovation is key to competitive advantage and sustainable business development in advanced economies. Small and medium-sized enterprises (SMEs) have lower capacity and more constrained resources for long-term and high-uncertainty research and development investments. At the same time, SMEs can implement organizational innovation to improve their performance and further foster other types of innovation. The purpose of this study is to analyze, how socio-cultural factors such as shared values, organizational behaviors, work organization and decision making processes can influence knowledge management and help to develop organizational innovation via an empirical study. Surveying 600 SMEs in Latvia, the author explores the contribution of different socio-cultural factors to organizational innovation and the role of knowledge management and organizational learning in this process. A conceptual model, explaining the impact of organizational team, development, result-orientation and structure is created. The study also proposes insights that contribute to theoretical and practical discussions on fostering innovation of small businesses in small economies.

Keywords: knowledge management, organizational innovation, small and medium-sized enterprises, socio-cultural factors

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17107 Medical Knowledge Management since the Integration of Heterogeneous Data until the Knowledge Exploitation in a Decision-Making System

Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal

Abstract:

Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.

Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks

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17106 Feature Extraction and Classification Based on the Bayes Test for Minimum Error

Authors: Nasar Aldian Ambark Shashoa

Abstract:

Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

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17105 Network Traffic Classification Scheme for Internet Network Based on Application Categorization for Ipv6

Authors: Yaser Miaji, Mohammed Aloryani

Abstract:

The rise of recent applications in everyday implementation like videoconferencing, online recreation and voice speech communication leads to pressing the need for novel mechanism and policy to serve this steep improvement within the application itself and users‟ wants. This diversity in web traffics needs some classification and prioritization of the traffics since some traffics merit abundant attention with less delay and loss, than others. This research is intended to reinforce the mechanism by analysing the performance in application according to the proposed mechanism implemented. The mechanism used is quite direct and analytical. The mechanism is implemented by modifying the queue limit in the algorithm.

Keywords: traffic classification, IPv6, internet, application categorization

Procedia PDF Downloads 565
17104 A World Map of Seabed Sediment Based on 50 Years of Knowledge

Authors: T. Garlan, I. Gabelotaud, S. Lucas, E. Marchès

Abstract:

Production of a global sedimentological seabed map has been initiated in 1995 to provide the necessary tool for searches of aircraft and boats lost at sea, to give sedimentary information for nautical charts, and to provide input data for acoustic propagation modelling. This original approach had already been initiated one century ago when the French hydrographic service and the University of Nancy had produced maps of the distribution of marine sediments of the French coasts and then sediment maps of the continental shelves of Europe and North America. The current map of the sediment of oceans presented was initiated with a UNESCO's general map of the deep ocean floor. This map was adapted using a unique sediment classification to present all types of sediments: from beaches to the deep seabed and from glacial deposits to tropical sediments. In order to allow good visualization and to be adapted to the different applications, only the granularity of sediments is represented. The published seabed maps are studied, if they present an interest, the nature of the seabed is extracted from them, the sediment classification is transcribed and the resulted map is integrated in the world map. Data come also from interpretations of Multibeam Echo Sounder (MES) imagery of large hydrographic surveys of deep-ocean. These allow a very high-quality mapping of areas that until then were represented as homogeneous. The third and principal source of data comes from the integration of regional maps produced specifically for this project. These regional maps are carried out using all the bathymetric and sedimentary data of a region. This step makes it possible to produce a regional synthesis map, with the realization of generalizations in the case of over-precise data. 86 regional maps of the Atlantic Ocean, the Mediterranean Sea, and the Indian Ocean have been produced and integrated into the world sedimentary map. This work is permanent and permits a digital version every two years, with the integration of some new maps. This article describes the choices made in terms of sediment classification, the scale of source data and the zonation of the variability of the quality. This map is the final step in a system comprising the Shom Sedimentary Database, enriched by more than one million punctual and surface items of data, and four series of coastal seabed maps at 1:10,000, 1:50,000, 1:200,000 and 1:1,000,000. This step by step approach makes it possible to take into account the progresses in knowledge made in the field of seabed characterization during the last decades. Thus, the arrival of new classification systems for seafloor has improved the recent seabed maps, and the compilation of these new maps with those previously published allows a gradual enrichment of the world sedimentary map. But there is still a lot of work to enhance some regions, which are still based on data acquired more than half a century ago.

Keywords: marine sedimentology, seabed map, sediment classification, world ocean

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17103 Trends, Status, and Future Directions of Artificial Intelligence in Human Resources Disciplines: A Bibliometric Analysis

Authors: Gertrude I. Hewapathirana, Loi A. Nguyen, Mohammed M. Mostafa

Abstract:

Artificial intelligence (AI) technologies and tools are swiftly integrating into many functions of all organizations as a competitive drive to enhance innovations, productivity, efficiency, faster and precise decision making to keep up with rapid changes in the global business arena. Despite increasing research on AI technologies in production, manufacturing, and information management, AI in human resource disciplines is still lagging. Though a few research studies on HR informatics, recruitment, and HRM in general, how to integrate AI in other HR functional disciplines (e.g., compensation, training, mentoring and coaching, employee motivation) is rarely researched. Many inconsistencies of research hinder developing up-to-date knowledge on AI in HR disciplines. Therefore, exploring eight research questions, using bibliometric network analysis combined with a meta-analysis of published research literature. The authors attempt to generate knowledge on the role of AI in improving the efficiency of HR functional disciplines. To advance the knowledge for the benefit of researchers, academics, policymakers, and practitioners, the study highlights the types of AI innovations and outcomes, trends, gaps, themes and topics, fast-moving disciplines, key players, and future directions.AI in HR informatics in high tech firms is the dominant theme in many research publications. While there is increasing attention from researchers and practitioners, there are many gaps between the promise, potential, and real AI applications in HR disciplines. A higher knowledge gap raised many unanswered questions regarding legal, ethical, and morale aspects of AI in HR disciplines as well as the potential contributions of AI in HR disciplines that may guide future research directions. Though the study provides the most current knowledge, it is limited to peer-reviewed empirical, theoretical, and conceptual research publications stored in the WoS database. The implications for theory, practice, and future research are discussed.

Keywords: artificial intelligence, human resources, bibliometric analysis, research directions

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