Search results for: knowledge discovery in database

Authors: Alyona Cerfontyne, Levita D'Souza, Lefteris Patlamazoglou

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Unlike adoption and donor-assisted reproduction, misattributed paternity occurring within the context of spontaneous conception and outside of formally recognised practices of having a child remains largely an understudied phenomenon. In adulthood, to discover misattributed paternity, i.e., that the man you call your father is not related to you genetically, can have profound implications for everyone affected. Until the advent of direct-to-consumer DNA testing 20 years ago, such discoveries were relatively rare. Despite the growing number of individuals uncovering their biogenetic paternity through genetic testing, there is very limited research on misattributed paternity from the perspective of adult children affected by it. No research exists on how to support these individuals through counselling post-discovery. Framed as insider action research, this study aimed to explore the perceived psychosocial consequences of misattributed paternity discoveries and coping strategies used by individuals who discover their misattributed paternity status in adulthood. In total, 12 individuals with misattributed paternity participated in semi-structured interviews in July-August 2022. The collected data was analysed using reflexive thematic analysis. The study’s results indicate that discovering misattributed paternity in adulthood can be likened to a watershed moment forever changing the trajectory of one’s life. Psychological experiences consistent with trauma, as well as grief and loss, re-evaluation of close family relationships, reestablishment of one’s identity, as well as experiencing a profound need to belong are the key themes emerging from the analysis of psychosocial experiences. Post-discovery, individuals with misattributed paternity employ a wide range of emotional and problem-focused coping strategies, amongst which seeking connection with those who understand, searching for information on the new biogenetic family and finding new meanings to life are most prominent. The study contributes both to the academic and practical knowledge of experiences of misattributed paternity and highlights the importance of further research on the topic.

Keywords: discovery of misattributed paternity, misattributed paternity, paternal discrepancy, psychosocial consequences, coping

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Authors: Yener Ekiz

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Knowledge development is a proactive process that covers collection, analysis, storage and distribution of information that helps to contribute the understanding of the environment. To transfer knowledge correctly and fastly, you have to use new emerging information system technologies. Actionable knowledge is only of value if it is understandable and usable by target users. The purpose of the paper is to enlighten how technology eases and affects the process of knowledge development. While preparing the paper, literature review, survey and interview methodology will be used. The hypothesis is that the technology and knowledge development are inseparable and the technology will formalize the DIKW hierarchy again. As a result, today there is huge data. This data must be classified sharply and quickly.

Keywords: DIKW hierarchy, knowledge development, technology

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Authors: Jichan Jang

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Mycobacterium abscessus is a rapidly growing life-threatening mycobacterium with multiple drug-resistance mechanisms. In this study, we screened the library to identify active molecules targeting Mycobacterium abscessus using resazurin live/dead assays. In this screening assay, the Z-factor was 0.7, as an indication of the statistical confidence of the assay. A cut-off of 80% growth inhibition in the screening resulted in the identification of four different compounds at a single concentration (20 μM). Dose-response curves identified three different hit candidates, which generated good inhibitory curves. All hit candidates were expected to have different molecular targets. Thus, we found that compound X, identified, may be a promising candidate in the M. abscessus drug discovery pipeline.

Keywords: Mycobacterium abscessus, antibiotics, drug discovery, emerging Pathogen

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Authors: Wang Zhanquan, Yang Zeping, Gu Chunhua, Zhu Fazhi, Guo Weibin

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Recently, Massive Open Online Courses (MOOCs) are becoming the new trend of education. There are many problems under the environment of Database Principle curriculum teaching process in MOOCs, such as teaching ideas and theories which are out of touch with the reality, how to carry out the technical teaching and interactive practice in the MOOCs environment, thus the methods of database course under the environment of MOOCs are proposed. There are three processes to deal with problem solving in the research, which are problems proposed, problems solved, and inductive analysis. The present research includes the design of teaching contents, teaching methods in classroom, flipped classroom teaching mode under the environment of MOOCs, learning flow method and large practice homework. The database designing ability is systematically improved based on the researching methods.

Keywords: problem solving-driven, MOOCs, teaching art, learning flow;

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Authors: Bahadir Aydin

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Today it is difficult to reach accurate knowledge because of mass data. This huge data makes the environment more and more caotic. Data is a main piller of intelligence. There is a close tie between knowledge and intelligence. Information gathered from different sources can be modified, interpreted and classified by using knowledge development process. This process is applied in order to attain intelligence. Within this process the effect of knowledge is crucial. Knowledge is classified as explicit and tacit knowledge. Tacit knowledge can be seen as "only the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose for all organization is to be succesful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. By the help of process the decision-maker can be presented with a clear holistic understanding, as early as possible in the decision making process. Planning, execution and assessments are the key functions that connects to information to knowledge. Altering from the current traditional reactive approach to a proactive knowledge development approach would reduce extensive duplication of work in the organization. By new approach to this process, knowledge can be used more effectively.

Keywords: knowledge, intelligence cycle, tacit knowledge, KIDW

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Authors: Ouassila Labbani-Narsis, Christophe Nicolle

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Building formal ontologies remains a complex process for companies. In the literature, this process is based on the technical knowledge and expertise of domain experts, without further details on the used methodologies. Possible problems of disagreements between experts, expression of tacit knowledge related to high level know-how rarely verbalized, qualification of results by using cases, or simply adhesion of the group of experts, remain currently unsolved. This paper proposes a methodological approach based on knowledge elicitation for the conception of formal, consensual, and shared ontologies. The proposed approach is experimentally tested on industrial collaboration projects in the field of manufacturing (associating knowledge sources from multinational companies) and in the field of viticulture (associating explicit knowledge and implicit knowledge acquired through observation).

Keywords: collaborative ontology engineering, knowledge elicitation, knowledge engineering, knowledge management

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Authors: Daniel Brian Thompson, Subarmaniam Kannan

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The huge weightage of knowledge in this world and within the repository of organizations has already reached immense capacity and is constantly increasing as time goes by. To accommodate these constraints, Big Data implementation and algorithms are utilized to obtain new or enhanced knowledge for decision-making. With the transition from data to knowledge provides the transformational changes which will provide tangible benefits to the individual implementing these practices. Today, various organization would derive knowledge from observations and intuitions where this information or data will be translated into best practices for knowledge acquisition, generation and sharing. Through the widespread usage of Big Data, the main intention is to provide information that has been cleaned and analyzed to nurture tangible insights for an organization to apply to their knowledge-creation practices based on facts and figures. The translation of data into knowledge will generate value for an organization to make decisive decisions to proceed with the transition of best practices. Without a strong foundation of knowledge and Big Data, businesses are not able to grow and be enhanced within the competitive environment.

Keywords: big data, knowledge management, data driven, knowledge creation

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Authors: Vajhollah Ghorbanizadeh, Seyed Mohsen Asadi, Mirali Seyednaghavi, Davoud Hoseynpour

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In the current era, all organizations need knowledge to be able to manage the diverse human resources. Creative, dynamic and knowledge-based Human resources are important competitive advantage and the scarcest resource in today's knowledge-based economy. In addition managers with skills of knowledge management must be aware of human resource management science. It is now generally accepted that successful implementation of knowledge management requires dynamic interaction between knowledge management and human resource management. This is emphasized at systematic approach to knowledge management as well. However human resource management can be complementary of knowledge management because human resources management with the aim of empowering human resources as the key resource organizations in the 21st century, the use of other resources, creating and growing and developing today. Thus, knowledge is the major capital of every organization which is introduced through the process of knowledge management. In this context, knowledge management is systematic approach to create, receive, organize, access, and use of knowledge and learning in the organization. This article aims to define and explain the concepts of knowledge management and human resource management and the importance of these processes and concepts. Literature related to knowledge management and human resource management as well as related topics were studied, then to design, illustrate and provide a theoretical model to explain the factors affecting the relationship between knowledge management and human resource management and knowledge management system approach, for schematic design and are drawn.

Keywords: systemic approach, human resources, knowledge, human resources management, knowledge management

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Authors: Jinseon Song, Yongwan Park

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In this paper, propose method that can user’s position that based on database is built from single camera. Previous positioning calculate distance by arrival-time of signal like GPS (Global Positioning System), RF(Radio Frequency). However, these previous method have weakness because these have large error range according to signal interference. Method for solution estimate position by camera sensor. But, signal camera is difficult to obtain relative position data and stereo camera is difficult to provide real-time position data because of a lot of image data, too. First of all, in this research we build image database at space that able to provide positioning service with single camera. Next, we judge similarity through image matching of database image and transmission image from user. Finally, we decide position of user through position of most similar database image. For verification of propose method, we experiment at real-environment like indoor and outdoor. Propose method is wide positioning range and this method can verify not only position of user but also direction.

Keywords: positioning, distance, camera, features, SURF(Speed-Up Robust Features), database, estimation

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Diabetic nephropathy (DN) is a major complication of diabetes, with fibrosis and propionate metabolism playing critical roles in its progression. Identifying biomarkers linked to these pathways may provide novel insights into DN diagnosis and treatment. This study aims to identify biomarkers associated with fibrosis and propionate metabolism in DN. Analyze the biological pathways and regulatory mechanisms of these biomarkers. Develop a machine learning model to predict DN-related biomarkers and validate their functional roles. Publicly available transcriptome datasets related to DN (GSE96804 and GSE104948) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/gds), and 924 propionate metabolism-related genes (PMRGs) and 656 fibrosis-related genes (FRGs) were identified. The analysis began with the extraction of DN-differentially expressed genes (DN-DEGs) and propionate metabolism-related DEGs (PM-DEGs), followed by the intersection of these with fibrosis-related genes to identify key intersected genes. Instead of relying on traditional models, we employed a combination of deep neural networks (DNNs) and ensemble methods such as Gradient Boosting Machines (GBM) and XGBoost to enhance feature selection and biomarker discovery. Recursive feature elimination (RFE) was coupled with these advanced algorithms to refine the selection of the most critical biomarkers. Functional validation was conducted using convolutional neural networks (CNN) for gene set enrichment and immunoinfiltration analysis, revealing seven significant biomarkers—SLC37A4, ACOX2, GPD1, ACE2, SLC9A3, AGT, and PLG. These biomarkers are involved in critical biological processes such as fatty acid metabolism and glomerular development, providing a mechanistic link to DN progression. Furthermore, a TF–miRNA–mRNA regulatory network was constructed using natural language processing models to identify 8 transcription factors and 60 miRNAs that regulate these biomarkers, while a drug–gene interaction network revealed potential therapeutic targets such as UROKINASE–PLG and ATENOLOL–AGT. This integrative approach, leveraging deep learning and ensemble models, not only enhances the accuracy of biomarker discovery but also offers new perspectives on DN diagnosis and treatment, specifically targeting fibrosis and propionate metabolism pathways.

Keywords: diabetic nephropathy, deep neural networks, gradient boosting machines (GBM), XGBoost

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Authors: Suglo Tohari Luri

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Data analysis is an important aspect of business performance. With the application of artificial intelligence within databases, selecting a suitable database engine for an application design is also very crucial for business data analysis. The application of business intelligence (BI) software into some relational databases such as Neo4j has proved highly effective in terms of customer data analysis. Yet what remains of great concern is the fact that not all business organizations have the neo4j business intelligence software applications to implement for customer data analysis. Further, those with the BI software lack personnel with the requisite expertise to use it effectively with the neo4j database. The purpose of this research is to demonstrate how the Neo4j program code alone can be applied for the analysis of e-commerce website customer visits. As the neo4j database engine is optimized for handling and managing data relationships with the capability of building high performance and scalable systems to handle connected data nodes, it will ensure that business owners who advertise their products at websites using neo4j as a database are able to determine the number of visitors so as to know which products are visited at routine intervals for the necessary decision making. It will also help in knowing the best customer segments in relation to specific goods so as to place more emphasis on their advertisement on the said websites.

Keywords: data, engine, intelligence, customer, neo4j, database

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Authors: M. Moslehpour, S. Khorsandi

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As transition to widespread use of IPv6 addresses has gained momentum, it has been shown to be vulnerable to certain security attacks such as those targeting Neighbor Discovery Protocol (NDP) which provides the address resolution functionality in IPv6. To protect this protocol, Secure Neighbor Discovery (SEND) is introduced. This protocol uses Cryptographically Generated Address (CGA) and asymmetric cryptography as a defense against threats on integrity and identity of NDP. Although SEND protects NDP against attacks, it is computationally intensive due to Hash2 condition in CGA. To improve the CGA computation speed, we parallelized CGA generation process and used the available resources in a trusted network. Furthermore, we focused on the influence of the existence of malicious nodes on the overall load of un-malicious ones in the network. According to the evaluation results, malicious nodes have adverse impacts on the average CGA generation time and on the average number of tries. We utilized a Trust Management that is capable of detecting and isolating the malicious node to remove possible incentives for malicious behavior. We have demonstrated the effectiveness of the Trust Management System in detecting the malicious nodes and hence improving the overall system performance.

Keywords: CGA, ICMPv6, IPv6, malicious node, modifier, NDP, overall load, SEND, trust management

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Authors: Devika Tanna

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'Biometrics' means 'life measurement' but the term is usually associated with the use of unique physiological characteristics to identify an individual. It is important to secure the privacy of digital face image that is stored in central database. To impart privacy to such biometric face images, first, the digital face image is split into two host face images such that, each of it gives no idea of existence of the original face image and, then each cover image is stored in two different databases geographically apart. When both the cover images are simultaneously available then only we can access that original image. This can be achieved by using the XM2VTS and IMM face database, an adaptive algorithm for spatial greyscale. The algorithm helps to select the appropriate host images which are most likely to be compatible with the secret image stored in the central database based on its geometry and appearance. The encryption is done using GEVCS which results in a reconstructed image identical to the original private image.

Keywords: adaptive algorithm, database, host images, privacy, visual cryptography

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Authors: Chuen-arom Janthimachai-amorn, Chirawadee Harnrittha

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This study aims to identify the factors facilitating the knowledge management to develop the graduate study programs to achieve success and to identify the approaches in developing the graduate study programs in the Rajbhat Suansunantha University. The 10 respondents were the administrators, the faculty, and the personnel of its Graduate School. The research methodology was based on Pla-too Model of the Knowledge Management Institute (KMI) by allocating the knowledge indicators, the knowledge creation and search, knowledge systematization, knowledge processing and filtering, knowledge access, knowledge sharing and exchanges and learning. The results revealed that major success factors were knowledge indicators, evident knowledge management planning, knowledge exchange and strong solidarity of the team and systematic and tenacious access of knowledge. The approaches allowing the researchers to critically develop the graduate study programs were the environmental data analyses, the local needs and general situations, data analyses of the previous programs, cost analyses of the resources, and the identification of the structure and the purposes to develop the new programs.

Keywords: program development, knowledge management, graduate study programs, Rajbhat Suansunantha University

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Authors: Evgeniya Ivanova

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Nowadays, in the literature, there is still no fixed definition of knowledge management that often remains only as an academic discipline. The current market situation is changing very quickly, the need of new technologies is high, and knowledge management is the area that ensures that the know-how has not been lost during market development and adoption. The study examines how knowledge management is being leveraged and practiced in the management consultancy companies and provides not only the tips and best practices of applied knowledge management approaches but also the validation matrix for its successful or unsuccessful implementation. Different knowledge management approaches are explored on the basis of their practical implementation, including related challenges, knowledge sharing process, and barriers that are typical for consulting firms mostly driven by the agile working culture. The relevance of proposed topic is confirmed by the finding that corporate working culture and the exponentially developing technologies have a direct impact on the success of practical implementation of knowledge management.

Keywords: knowledge management, knowledge management in practice, consulting firm, knowledge management success

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Authors: Muhammad Nouman, Fahad Tiwana, Muhammad Irfan, Mohsin Tiwana

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Traffic congestion has been increasing significantly in major metropolitan areas as a result of increased motorization, urbanization, population growth and changes in the urban density. Traffic congestion compromises efficiency of transport infrastructure and causes multiple traffic concerns; including but not limited to increase of travel time, safety hazards, air pollution, and fuel consumption. Traffic management has become a serious challenge for federal and provincial governments, as well as exasperated commuters. Effective, flexible, efficient and user-friendly traffic information/database management systems characterize traffic conditions by making use of traffic counts for storage, processing, and visualization. While, the emerging data collection technologies continue to proliferate, its accuracy can be guaranteed through the comparison of observed data with the manual handheld counters. This paper presents the design of tablet based manual traffic counting application and framework for development of traffic database management system for Pakistan. The database management system comprises of three components including traffic counting android application; establishing online database and its visualization using Google maps. Oracle relational database was chosen to develop the data structure whereas structured query language (SQL) was adopted to program the system architecture. The GIS application links the data from the database and projects it onto a dynamic map for traffic conditions visualization. The traffic counting device and example of a database application in the real-world problem provided a creative outlet to visualize the uses and advantages of a database management system in real time. Also, traffic data counts by means of handheld tablet/ mobile application can be used for transportation planning and forecasting.

Keywords: manual count, emerging data sources, traffic information quality, traffic surveillance, traffic counting device, android; data visualization, traffic management

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Authors: Zuzana Crhová, Karel Kolman, Drahomíra Pavelková

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Knowledge is considered as an important asset which can help organizations to create competitive advantage. The necessity of taking care of these assets is more important in these days – in days of turbulent changes in business environment. Knowledge could facilitate adaption to constant changes. The aim of this paper is to describe how the knowledge sharing can be supported in the manufacturing companies. The methods of case studies and grounded theory were used to present information gained by carrying out semi-structured interviews. Results show that knowledge sharing is supported in very similar ways in respondent companies.

Keywords: case study, human resource management, knowledge, knowledge sharing

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Authors: Nishank Raisinghani

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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

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Authors: Cindy Wang-Cowham, Judy Ningyu Tang

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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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Authors: Syed Asif Hassan, Tabrej Khan

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The use of traditional medicines for the treatment of various diseases as well as maintaining a healthy lifestyle has gained a significant acceptance across the globe. The increasing popularity of Herbal Medicine can be owed to the fact that is relatively inexpensive and has lesser side effects as compared to general medicines. The Kingdom of Saudi Arabia has a rich heritage of herbal medicine for overages. However, the information about essential traditional herbs of Arabian origin and their implication in the treatment of various diseases are not well documented in an organized manner. Therefore, the requirement of a local platform (database system) for herbal medicines of Arab origin is the need of the day. In this context, various questionnaire and surveys were conducted over a period of 6 months. The surveys were targeted to identify a range of herbal remedies used by the communities of Saudi Arabia e.g., pharmacists and local people. The survey leads us to identify many of the mysterious local medicinal herbs used for the treatment of various ailments and thus reveals a unique insight into the natural herbal resource of Saudi Arabia. The information of the herbal medicines will be further used to develop a Saudi herbal database system using the principles of waterfall method. An interactive dynamic electronic web portal of the herbal database system will be built using MySQL and PHP for accessing the information available in the Saudi herbal database system. The web portal will be a step forward in creating awareness among the Arab nationals of their rich herbal heritage.

Keywords: Saudi herbal medicine, community survey, database system and design, MySQL, PHP

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Authors: Chander Shekhar, Manoj Kumar

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Present paper deal with the discovery of the stupa’s relics which belongs to the Kushana period. These remains were found during the scientific clearance work at a mound near Brahma-SarovarThanesar, Kurukshetra. This archaeological work was done by Department of Archaeology & Museums Haryana Government. The relics of stupa show that it would have been similar to Assandh and Damekhstupa. As per-Buddhist literature, GoutamBudhha reached Thanesar. In memory of Buddh’s Journey, King Ashoka built a big Stupa at Thanesar on the bank of Sarasvati River. Chinese pilgrim Yuan Chuang also referred a Monastery and stupa near Aujas-ghatof Brahma-sarovar. It may be part of that settlement which was mentioned by Yuan Chuang.

Keywords: archaeology, stupa, buddhism, excavtoin

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Authors: Jisun Lee, Jay Hyoun Kwon

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As an alternative way to compensate the INS (inertial navigation system) error in non-GNSS (Global Navigation Satellite System) environment, geophysical database referenced navigation is being studied. In this study, both gravity gradient and terrain data were combined to complement the weakness of sole geophysical data as well as to improve the stability of the positioning. The main process to compensate the INS error using geophysical database was constructed on the basis of the EKF (Extended Kalman Filter). In detail, two type of combination method, centralized and decentralized filter, were applied to check the pros and cons of its algorithm and to find more robust results. The performance of each navigation algorithm was evaluated based on the simulation by supposing that the aircraft flies with precise geophysical DB and sensors above nine different trajectories. Especially, the results were compared to the ones from sole geophysical database referenced navigation to check the improvement due to a combination of the heterogeneous geophysical database. It was found that the overall navigation performance was improved, but not all trajectories generated better navigation result by the combination of gravity gradient with terrain data. Also, it was found that the centralized filter generally showed more stable results. It is because that the way to allocate the weight for the decentralized filter could not be optimized due to the local inconsistency of geophysical data. In the future, switching of geophysical data or combining different navigation algorithm are necessary to obtain more robust navigation results.

Keywords: Extended Kalman Filter, geophysical database referenced navigation, gravity gradient, terrain

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Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari

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People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Keywords: body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech

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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 21^st century and recommend future directions towards improving knowledge work.

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

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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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Authors: Raquel Mateo Mendaza, Carmen Novo Urraca

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The current paper presents the elaboration of a corpus database that aligns two different corpora in order to simplify the search of information both for researchers and students of Old English. This database comprises the information contained in two main reference corpora, namely the Dictionary of Old English Corpus (DOEC), compiled at the University of Toronto, and the York-Toronto-Helsinki Parsed Corpus of Old English (YCOE). The first one provides information on all surviving texts written in the Old English language. The latter offers the syntactical and morphological annotation of several texts included in the DOEC. Although both corpora are closely related, as the YCOE includes the DOE source text identifier, the main problem detected is that there is not an alignment of texts that allows for the search of whole fragments to be further analysed in terms of morphology and syntax. The database proposed in this paper gathers all this information and presents it in a simple, more accessible, visual, and educational way. The alignment of fragments has been done in an automatized way. However, some problems have emerged during the creating process particularly related to the lack of correspondence in the division of fragments. For this reason, it has been necessary to revise the whole entries manually to obtain a truthful high-quality product and to carefully indicate the gaps encountered in these corpora. All in all, this database contains more than 60,000 entries corresponding with the DOE fragments annotated by the YCOE. The main strength of the resulting product is its research and teaching implications in the study of Old English. The use of this database will help researchers and students in the study of different aspects of the language, such as inflectional morphology, syntactic behaviour of given words, or translation studies, among others. By means of the search of words or fragments, the annotated information on morphology and syntax will be automatically displayed, automatizing, and speeding up the search of data.

Keywords: alignment, corpus database, morphosyntactic analysis, Old English

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Authors: Radia Bernaoui, Mohamed Hassoun

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Our survey deals a theme of the measurement of the management knowledge of actors in Algerian agricultural sector, through a study carried out with professionals affiliated to agro-alimentary 'agribusinesses'. Taking into account the creation of a national device of information on the agronomic research in Algeria, the aim is to analyze their informational practices and to assess how they rate the sharing of knowledge and the process of collective intelligence. The results of our study reveal a more crucial need: The creation a suitable framework to the division of the knowledge, to produce 'knowledge shared social' where the scientific community could interact with firms. It is a question of promoting processes for the adaptation and the spreading of knowledge, through a partnership between the R&D sector and the production one, to increase the competitiveness of the firms, even the sustainable development of the country.

Keywords: knowledge management, pole of competitiveness, knowledge management, economy of knowledge, agro-alimentary, agribusiness, information system, Algeria

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Authors: J. Zhang, K. Agyapong-Kodua

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Digital factory based on visual design and simulation has emerged as a mainstream to reduce digital development life cycle. Some basic industrial systems are being integrated via semantic modelling, and products (P) matching process (P)-resource (R) requirements are designed to fulfill current customer demands. Nevertheless, product design is still limited to fixed product models and known knowledge of product engineers. Therefore, this paper presents a rapid reconfiguration method based on semantic technologies with PPR ontologies to reuse known and unknown knowledge. In order to avoid the influence of big data, our system uses a cloud manufactory and distributed database to improve the efficiency of querying meeting PPR requirements.

Keywords: semantic technologies, factory system, digital factory, cloud manufactory

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Authors: Phan Nghiem Vu, Le Tuan Vu, Ta Quang Tai

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Knowledge Management effectively is critical to the survival and advance of a company, especially in company-based industries such as construction. Knowledge management practice is crucial to the survival and progress of a company, especially company-based knowledge such as construction consultancy. Effective knowledge management practices are very significant to the competitive and development of a consulting organization. Hence, the success of knowledge management implementation depends on knowledge capturing and reusing effectively. In this paper, a survey was carried out of engineers and managers with experience in seven construction consulting organizations that provide services on the north-central coast of Vietnam. The main objectives of the survey to finding out how these organizations capture and reuse knowledge and significant barriers to the implementation of knowledge management. A conceptual framework based-on Trello application is proposed to formalize the knowledge-capturing and reusing process within construction consulting companies. It is showed that the conceptual framework could be used to manage both implicit and explicit knowledge effectively in construction consultant organizations.

Keywords: knowledge management, construction consultant organization, knowledge capturing, reusing knowledge, application-based technology

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Authors: Lucy W. Mburu, Richard Karanja, Simon N. Mwendia

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Over recent years, learners have experienced a constant need to access on demand knowledge that is fully aligned with the paradigm of cloud computing. As motivated by the global sustainable development goal to ensure inclusive and equitable learning opportunities, this research has developed a framework hinged on the knowledge-as-a-service architecture that utilizes knowledge from ambient learning systems. Through statistical analysis and decision tree modeling, the study discovers influential variables for ambient learning among university students. The main aim is to generate a platform for disseminating and exploiting the available knowledge to aid the learning process and, thus, to improve educational support on the ambient learning system. The research further explores how collaborative effort can be used to form a knowledge network that allows access to heterogeneous sources of knowledge, which benefits knowledge consumers, such as the developers of ambient learning systems.

Keywords: actionable knowledge, ambient learning, cloud computing, decision trees, knowledge as a service

Procedia PDF Downloads 160