Search results for: Knowledge Discovery in Database (KDD)

Authors: Jay Ananth

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The drug discovery process currently requires numerous years of clinical testing as well as money just for a single drug to earn FDA approval. For drugs that even make it this far in the process, there is a very slim chance of receiving FDA approval, resulting in detrimental hurdles to drug accessibility. To minimize these inefficiencies, numerous studies have implemented computational methods, although few computational investigations have focused on a crucial feature of drugs: lipophilicity. Lipophilicity is a physical attribute of a compound that measures its solubility in lipids and is a determinant of drug efficacy. This project leverages Artificial Intelligence to predict the impact of a drug’s lipophilicity on its performance by accounting for factors such as binding affinity and toxicity. The model predicted lipophilicity and binding affinity in the validation set with very high R² scores of 0.921 and 0.788, respectively, while also being applicable to a variety of target receptors. The results expressed a strong positive correlation between lipophilicity and both binding affinity and toxicity. The model helps in both drug development and discovery, providing every pharmaceutical company with recommended lipophilicity levels for drug candidates as well as a rapid assessment of early-stage drugs prior to any testing, eliminating significant amounts of time and resources currently restricting drug accessibility.

Keywords: drug discovery, lipophilicity, ligand-receptor interactions, machine learning, drug development

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Authors: Elachouri Mostafa, Fakchich Jamila, Lazaar Jamila, Elmadmad Mohammed, Marhom Mostafa

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Of course, there has been a great growth in scientific information about medicinal plants in recent decades, but in many ways this has proved poor compensation, because such information is accessible, in practice, only to a very few people and anyway, rather little of it is relevant to problems of management and utilization, as encountered in the field. Active compounds are used in most traditional medicines and play an important role in advancing sustainable rural livelihoods through their conservation, cultivation, propagation, marketing and commercialization. Medicinal herbs are great resources for various pharmaceutical compounds and urgent measures are required to protect these plant species from their natural destruction and disappearance. Indeed, there is a real danger of indigenous Arab medicinal practices and knowledge disappearing altogether, further weakening traditional Arab culture and creating more insecurity, as well as forsaking a resource of inestimable economic and health care importance. As scientific approach, the ethnopharmacological investigation remains the principal way to improve, evaluate, and increase the odds of finding of biologically active compounds derived from medicinal plants. As developing country, belonging to the Mediterranean basin, Morocco country is endowed with resources of medicinal and aromatic plants. These plants have been used over the millennia for human welfare, even today. Besides, Morocco has a large plant biodiversity, in fact, its medicinal flora account more than 4200 species growing on various bioclimatic zones from subhumide to arid and Saharan. Nevertheless, the human and animal pressure resulting from the increase of rural population needs has led to degradation of this patrimony. In this paper, we focus our attention on ethnopharmacological studies carried out in Morocco. The goal of this work is to clarify the importance of herbs as platform for drugs discovery and further development, to highlight the importance of ethnopharmacological study as approach on discovery of natural products in the health care field, and to discuss the limit of ethnopharmacological investigation of drug discovery in Morocco.

Keywords: Morocco, medicinal plants, ethnopharmacology, natural products, drug-discovery

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Authors: Attila Simon

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The subject of this research is an element of Mithras' iconography. It is a new element in the series of research begun with the study of the Bull in the Boat motif. The stylized altars represented by the seven adjacent rectangles appear on only a small group of Mithraic reliefs, which may explain why they have received less attention and fewer attempts at decipherment than other motifs. Using Vermaseren's database, CIMRM (Corpus Inscriptionum et Monumentorum Religionis Mithriacae), one collected all the cases containing the motif under investigation, created a database of them grouped by location, then used a comparative method to compare the different forms of the motif and to isolate these cases, and finally evaluated the results. The aim of this research is to interpret the iconographic element in question and attempt to determine its place of origin. The study may provide an interpretation of a Mithraic representation that, to the best of the author's knowledge, has not been explained so far, and the question may generate scientific discourses.

Keywords: roman history, religion, Mithras, iconography

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Authors: Alexander Denzler, Marcel Wehrle, Andreas Meier

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A knowledge base stores facts and rules about the world that applications can use for the purpose of reasoning. By applying the concept of granular computing to a knowledge base, several advantages emerge. These can be harnessed by applications to improve their capabilities and performance. In this paper, the concept behind such a construct, called a granular knowledge cube, is defined, and its intended use as an instrument that manages to cope with different data types and detect knowledge domains is elaborated. Furthermore, the underlying architecture, consisting of the three layers of the storing, representing, and structuring of knowledge, is described. Finally, benefits as well as challenges of deploying it are listed alongside application types that could profit from having such an enhanced knowledge base.

Keywords: granular computing, granular knowledge, hierarchical structuring, knowledge bases

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Authors: Ahmad Aslizadeh, Farid Ghaderi

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Mapping organizational knowledge is an innovative concept and useful instrument of representation, capturing and visualization of implicit and explicit knowledge. There are a diversity of methods, instruments and techniques presented by different researchers following mapping organizational knowledge to reach determined goals. Implicating of these methods, it is necessary to know their exigencies and conditions in which those can be used. Integrating identified methods of knowledge mapping and comparing them would help knowledge managers to select the appropriate methods. This research conducted to presenting a model and framework to map organizational knowledge. At first, knowledge maps, their applications and necessity are introduced because of extracting comparative framework and detection of their structure. At the next step techniques of researchers such as Eppler, Kim, Egbu, Tandukar and Ebner as knowledge mapping models are presented and surveyed. Finally, they compare and a superior model would be introduced.

Keywords: knowledge mapping, knowledge management, comparative study, business and management

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Authors: Akshay Agrawal, Anand K. Srivastava

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The increasing amount of XML datasets available to casual users increases the necessity of investigating techniques to extract knowledge from these data. Data mining is widely applied in the database research area in order to extract frequent correlations of values from both structured and semi-structured datasets. The increasing availability of heterogeneous XML sources has raised a number of issues concerning how to represent and manage these semi structured data. In recent years due to the importance of managing these resources and extracting knowledge from them, lots of methods have been proposed in order to represent and cluster them in different ways.

Keywords: XML, similarity measure, clustering, cluster quality, semantic clustering

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Authors: A. Amidah Amrawaty, M. Saleh S. Ali, Darmawan Salman

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The aim of this study was to identify local and non local knowledge in Bali cattle development, to analyze the contestation between local and non-local knowledge. The paradigm used was constructivism paradigm with a qualitative approach. descriptive type of research using case study method. The study was conducted in four villages subjected to Agropolitan Program, i.e. Palakka, Tompo, Galung and Anabanua in Barru District, province of South Sulawesi. The results indicated that the local knowledge of the farmers were: a) knowledge of animal housing, b) knowledge of the prevention and control disease, c) knowledge of the feed, d) knowledge of breed selection, e) knowledge of sharing arrangement, f) knowledge of marketing, Generally, there are three patterns of knowledge contestation namely coexistence, ‘zero sum game’ and hybridization but in this research only coexistence and zero sum game patterns took place, while the pattern of hybridization did not occur.

Keywords: contestation, local knowledge, non-local knowledge, developing of Bali cattle

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Authors: Deepa Kapoor, Rajshree Singh

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This paper appreciates the emergence and growing importance as a new production factor makes the development of technologies, methodologies and strategies for measurement, creation, and diffusion into one of the main priorities of the organizations in the knowledge society. There are many models for creation and management of knowledge and diverse and varied perspectives for study, analysis, and understanding. In this article, we will conduct a theoretical approach to the type of models for the creation and management of knowledge; we will discuss some of them and see some of the difficulties and the key factors that determine the success of the processes for the creation and management of knowledge.

Keywords: knowledge creation, knowledge management, organizational development, organization learning

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Authors: Yusri Yusof, Chen Wong Keong

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This paper presents the implementation details of a Relational Database Management System of a STEP-technology product model repository. It is able support the implementation of any EXPRESS language schema, although it has been primarily implemented to support mechanical product life cycle applications. This database support the input of STEP part 21 file format from CAD in geometrical and topological data format and support a range of queries for mechanical product life cycle applications. This proposed relational database management system uses entity-to-table method (R1) rather than type-to-table method (R4). The two mapping methods have their own strengths and drawbacks.

Keywords: RDBMS, CAD, ISO 10303, part-21 file

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Authors: Iftikhar Tayubi, Tabrej Khan, Rayan Alsulmi, Abdulrahman Labban

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Spider produces a special kind of substance. This special kind of substance is called a toxin. The toxin is composed of many types of protein, which differs from species to species. Spider toxin consists of several proteins and non-proteins that include various categories of toxins like myotoxin, neurotoxin, cardiotoxin, dendrotoxin, haemorrhagins, and fibrinolytic enzyme. Protein Sequence information with references of toxins was derived from literature and public databases. From the previous findings, the Spider toxin would be the best choice to treat different types of tumors and cancer. There are many therapeutic regimes, which causes more side effects than treatment hence a different approach must be adopted for the treatment of cancer. The combinations of drugs are being encouraged, and dramatic outcomes are reported. Spider toxin is one of the natural cytotoxic compounds. Hence, it is being used to treat different types of tumors; especially its positive effect on breast cancer is being reported during the last few decades. The efficacy of this database is that it can provide a user-friendly interface for users to retrieve the information about Spiders, toxin and toxin protein of different Spiders species. SPIDTOXD provides a single source information about spider toxins, which will be useful for pharmacologists, neuroscientists, toxicologists, medicinal chemists. The well-ordered and accessible web interface allows users to explore the detail information of Spider and toxin proteins. It includes common name, scientific name, entry id, entry name, protein name and length of the protein sequence. The utility of this database is that it can provide a user-friendly interface for users to retrieve the information about Spider, toxin and toxin protein of different Spider species. The database interfaces will satisfy the demands of the scientific community by providing in-depth knowledge about Spider and its toxin. We have adopted the methodology by using A MySQL and PHP and for designing, we used the Smart Draw. The users can thus navigate from one section to another, depending on the field of interest of the user. This database contains a wealth of information on species, toxins, and clinical data, etc. This database will be useful for the scientific community, basic researchers and those interested in potential pharmaceutical Industry.

Keywords: siptoxd, php, mysql, toxin

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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Authors: W. S. Besbas, M. A. Artemi, R. M. Salman

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Content based face sketch retrieval can be used to find images of criminals from their sketches for 'Crime Prevention'. This paper investigates the problem of CBIR of face sketch images in transform domain. Face sketch images that are similar to the query image are retrieved from the face sketch database. Features of the face sketch image are extracted in the spectrum domain of a selected transforms. These transforms are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Walsh Hadamard Transform (WHT). For the performance analyses of features selection methods three face images databases are used. These are 'Sheffield face database', 'Olivetti Research Laboratory (ORL) face database', and 'Indian face database'. The City block distance measure is used to evaluate the performance of the retrieval process. The investigation concludes that, the retrieval rate is database dependent. But in general, the DCT is the best. On the other hand, the WHT is the best with respect to the speed of retrieving images.

Keywords: Content Based Image Retrieval (CBIR), face sketch image retrieval, features selection for CBIR, image retrieval in transform domain

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Authors: Efthymios Chondrogiannis, Vassiliki Andronikou, Efstathios Karanastasis, Theodora Varvarigou

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A large amount of data is typically stored in relational databases (DB). The latter can efficiently handle user queries which intend to elicit the appropriate information from data sources. However, direct access and use of this data requires the end users to have an adequate technical background, while they should also cope with the internal data structure and values presented. Consequently the information retrieval is a quite difficult process even for IT or DB experts, taking into account the limited contributions of relational databases from the conceptual point of view. Ontologies enable users to formally describe a domain of knowledge in terms of concepts and relations among them and hence they can be used for unambiguously specifying the information captured by the relational database. However, accessing information residing in a database using ontologies is feasible, provided that the users are keen on using semantic web technologies. For enabling users form different disciplines to retrieve the appropriate data, the design of a Graphical User Interface is necessary. In this work, we will present an interactive, ontology-based, semantically enable web tool that can be used for information retrieval purposes. The tool is totally based on the ontological representation of underlying database schema while it provides a user friendly environment through which the users can graphically form and execute their queries.

Keywords: ontologies, relational databases, SPARQL, web interface

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Authors: Prabhakar Venugopal G.

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Complex environments triggered by globalization have necessitated new paradigms of leadership – complexity leadership that encompasses multiple roles that leaders need to take upon. The success of higher education institutions depends on how well leaders can provide adaptive, administrative and enabling leadership. Complexity leadership seems all the more relevant for institutions that are knowledge-driven and thrive on knowledge creation, knowledge storage and retrieval, knowledge sharing and knowledge applications. In this paper are the elements of globalization, the opportunities and challenges that are brought forth by globalization are discussed. The complexity leadership paradigm in a knowledge-based economy and the need for such a paradigm shift for higher education institutions is presented. Further, the paper also discusses the support the leader requires in a knowledge-driven economy through knowledge management initiatives.

Keywords: globalization, complexity leadership, knowledge management

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Authors: Ilona Mewes, Helena Jenzer, Farshideh Einsele

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Objective: The objective of the study was to integrate two big databases from Swiss nutrition national survey (menuCH) and Swiss health national survey 2012 for data mining purposes. Each database has a demographic base data. An integrated Swiss database is built to later discover critical food consumption patterns linked with lifestyle diseases known to be strongly tied with food consumption. Design: Swiss nutrition national survey (menuCH) with approx. 2000 respondents from two different surveys, one by Phone and the other by questionnaire along with Swiss health national survey 2012 with 21500 respondents were pre-processed, cleaned and finally integrated to a unique relational database. Results: The result of this study is an integrated relational database from the Swiss nutritional and health databases.

Keywords: health informatics, data mining, nutritional and health databases, nutritional and chronical databases

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Authors: Po-Jung Huang, Chi-Ching Lee, Bertrand Chin-Ming Tan, Yuan-Ming Yeh, Julie Lichieh Chu, Tin-Wen Chen, Cheng-Yang Lee, Ruei-Chi Gan, Hsuan Liu, Petrus Tang

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Whole-exome sequencing focuses on the protein coding regions of disease/cancer associated genes based on a priori knowledge is the most cost-effective method to study the association between genetic alterations and disease. Recent advances in high throughput sequencing technologies and proteomic techniques has provided an opportunity to integrate genomics and proteomics, allowing readily detectable mutated peptides corresponding to mutated genes. Since sequence database search is the most widely used method for protein identification using Mass spectrometry (MS)-based proteomics technology, a mutant proteome database is required to better approximate the real protein pool to improve disease-associated mutated protein identification. Large-scale whole exome/genome sequencing studies were launched by National Cancer Institute (NCI), Broad Institute, and The Cancer Genome Atlas (TCGA), which provide not only a comprehensive report on the analysis of coding variants in diverse samples cell lines but a invaluable resource for extensive research community. No existing database is available for the collection of mutant protein sequences related to the identified variants in these studies. CMPD is designed to address this issue, serving as a bridge between genomic data and proteomic studies and focusing on protein sequence-altering variations originated from both germline and cancer-associated somatic variations.

Keywords: TCGA, cancer, mutant, proteome

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Authors: Yusuf Ziya Ayık, Ferhat Kahveci

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Currently, database management systems have various tools such as backup and maintenance, and also provide statistical information such as resource usage and security. In terms of query performance, this paper covers query optimization, views, indexed tables, pre-computation materialized view, query performance analysis in which query plan alternatives can be created and the least costly one selected to optimize a query. Indexes and views can be created for related table columns. The literature review of this study showed that, in the course of time, despite the growing capabilities of the database management system, only database administrators are aware of the need for dealing with archival and transactional data types differently. These data may be constantly changing data used in everyday life, and also may be from the completed questionnaire whose data input was completed. For both types of data, the database uses its capabilities; but as shown in the findings section, instead of repeating similar heavy calculations which are carrying out same results with the same query over a survey results, using materialized view results can be in a more simple way. In this study, this performance difference was observed quantitatively considering the cost of the query.

Keywords: cost of query, database management systems, materialized view, query performance

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Authors: Eugene Okyere-Kwakye

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Knowledge sharing is a practice where individuals commonly exchange both tacit and explicit knowledge to jointly create a new knowledge. Knowledge management literature vividly express that knowledge sharing is the keystone and perhaps it is the most important aspect of knowledge management. To enhance the understanding of knowledge sharing domain, this study is aimed to investigate some factors that could influence employee’s attitude and behaviour to share their knowledge. The researchers employed the social exchange theory as a theoretical foundation for this study. Three essential factors namely: Trust, mutual reciprocity and perceived enjoyment that could influence knowledge sharing behaviour has been incorporated into a research model. To empirically validate this model, data was collected from one hundred and twenty respondents. The multiple regression analysis was employed to analyse the data. The results indicate that perceived enjoyment and trust have a significant influence on knowledge sharing. Surprisingly, mutual reciprocity did not influence knowledge sharing. The paper concludes by highlight the practical implications of the findings and areas for future research to consider.

Keywords: perceived enjoyment, trust, knowledge sharing, knowledge management

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Authors: Yang Bao, Shi Wei Deng, WangQun Lin

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This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.

Keywords: data cleaning, dependency rules, violation data discovery, data repair

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Authors: Laleh Taheri, Noraini C. Pa, Rusli Abdullah, Salfarina Abdullah

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Knowledge plays an important role to the success of any organization. Software development organizations are highly knowledge-intensive organizations especially in their Requirement Elicitation Process (REP). There are several problems regarding communicating and using the knowledge in REP such as misunderstanding, being out of scope, conflicting information and changes of requirements. All of these problems occurred in transmitting the requirements knowledge during REP. Several researches have been done in REP in order to solve the problem towards requirements. Knowledge Audit (KA) approaches were proposed in order to solve managing knowledge in human resources, financial, and manufacturing. There is lack of study applying the KA in requirements elicitation process. Therefore, this paper proposes a KA model for REP in supporting to acquire good requirements.

Keywords: knowledge audit, requirement elicitation process, KA model, knowledge in requirement elicitation

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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: 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: Amir Taghizadeh Vahed, Adithya Thaduri

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Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

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Authors: Arvind Lal, Chumphila Bhutia, Bidhan Pradhan, Retika Sharma, Monisha Limboo

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There have been many proposals to optimize the students’ management system in higher education. Managing student attendance during lecture periods have become a difficult challenge. Manual calculation of attendance produces errors and wastes a lot of time. This proposed system manages the student’s attendance in a web portal and the records of the attendance will be stored in a database. The attendance of the students will be further forwarded to their HOD (Head OF Department), class teacher and their parents/guardians. This system will use MySQL for the database. The template of the website will be built using HTML and CSS (Cascading StyleSheet) code. JavaScript will be added to improve the use of the system. Student’s details will be stored in the database. Also, it will contain the details of the teachers according to their subjects and the classes they teach. The system will be responsive which can be used in mobile phones. Also, the development of this project will be user-friendly by facilitating with clear and understandable tabs. Hence, this website will be beneficial to institutes.

Keywords: website, student's attendance, MySQL database, HTML, CSS, PHP, JavaScript

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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: Audrey Romero-Pelaez, Juan Carlos Morocho-Yunga

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The increasing amount of open educational resources (OER) published on the web for consumption in teaching and learning environments also generates a growing need to ensure the quality of these resources. The low level of OER discovery is one of the most significant drawbacks when faced with its reuse, and as a consequence, high-quality educational resources can go unnoticed. Metadata enables the discovery of resources on the web. The purpose of this study is to lay the foundations for open educational resources to achieve their first quality star within the Quality4OER Framework. In this study, we evaluate the quality of OER metadata and establish the main guidelines on metadata quality in this context.

Keywords: open educational resources, OER quality, quality metadata

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Authors: Basiru Amuneni

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Astronomy is one domain with a rise in data. Traditional tools for data management have been employed in the quest for knowledge discovery. However, these traditional tools become limited in the face of big. One means of maximizing knowledge discovery for big data is the use of scientific visualisation. The aim of the work is to explore the possibilities offered by emerging creative technologies of Virtual Reality (VR) systems and game engines to visualize multiwavelength datasets. Game Engines are primarily used for developing video games, however their advanced graphics could be exploited for scientific visualization which provides a means to graphically illustrate scientific data to ease human comprehension. Modern astronomy is now in the era of multiwavelength data where a single galaxy for example, is captured by the telescope several times and at different electromagnetic wavelength to have a more comprehensive picture of the physical characteristics of the galaxy. Visualising this in an immersive environment would be more intuitive and natural for an observer. This work presents a standalone VR application that accesses galaxy FITS files. The application was built using the Unity Game Engine for the graphics underpinning and the OpenXR API for the VR infrastructure. The work used a methodology known as Design Science Research (DSR) which entails the act of ‘using design as a research method or technique’. The key stages of the galaxy modelling pipeline are FITS data preparation, Galaxy Modelling, Unity 3D Visualisation and VR Display. The FITS data format cannot be read by the Unity Game Engine directly. A DLL (CSHARPFITS) which provides a native support for reading and writing FITS files was used. The Galaxy modeller uses an approach that integrates cleaned FITS image pixels into the graphics pipeline of the Unity3d game Engine. The cleaned FITS images are then input to the galaxy modeller pipeline phase, which has a pre-processing script that extracts, pixel, galaxy world position, and colour maps the FITS image pixels. The user can visualise image galaxies in different light bands, control the blend of the image with similar images from different sources or fuse images for a holistic view. The framework will allow users to build tools to realise complex workflows for public outreach and possibly scientific work with increased scalability, near real time interactivity with ease of access. The application is presented in an immersive environment and can use all commercially available headset built on the OpenXR API. The user can select galaxies in the scene, teleport to the galaxy, pan, zoom in/out, and change colour gradients of the galaxy. The findings and design lessons learnt in the implementation of different use cases will contribute to the development and design of game-based visualisation tools in immersive environment by enabling informed decisions to be made.

Keywords: astronomy, visualisation, multiwavelenght dataset, virtual reality

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