Search results for: Knowledge discovery in database (KDD)

Authors: M. Bohlouli, M. Analoui

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For complete support of Quality of Service, it is better that environment itself predicts resource requirements of a job by using special methods in the Grid computing. The exact and correct prediction causes exact matching of required resources with available resources. After the execution of each job, the used resources will be saved in the active database named "History". At first some of the attributes will be exploit from the main job and according to a defined similarity algorithm the most similar executed job will be exploited from "History" using statistic terms such as linear regression or average, resource requirements will be predicted. The new idea in this research is based on active database and centralized history maintenance. Implementation and testing of the proposed architecture results in accuracy percentage of 96.68% to predict CPU usage of jobs and 91.29% of memory usage and 89.80% of the band width usage.

Keywords: Active Database, Grid Computing, ResourceRequirement Prediction, Scheduling,

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Authors: Alireza Shirvani, Shadi Ebrahimi Mehrabani

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In this competitive age, one of the key tools of most successful organizations is knowledge management. Today some organizations measure their current knowledge and use it as an indicator for rating the organization on their reports. Noting that the universities and colleges of medical science have a great role in public health of societies, their access to newest scientific research and the establishment of organizational knowledge management systems is very important. In order to explore the Application of Knowledge Management Factors, a national study was undertaken. The main purpose of this study was to find the rate of the application of knowledge management factors and some ways to establish more application of knowledge management system in Esfahan University-s Medical College (EUMC). Esfahan is the second largest city after Tehran, the capital city of Iran, and the EUMC is the biggest medical college in Esfahan. To rate the application of knowledge management, this study uses a quantitative research methodology based on Probst, Raub and Romhardt model of knowledge management. A group of 267 faculty members and staff of the EUMC were asked via questionnaire. Finding showed that the rate of the application of knowledge management factors in EUMC have been lower than average. As a result, an interview with ten faculty members conducted to find the guidelines to establish more applications of knowledge management system in EUMC.

Keywords: Knowledge, knowledge management, knowledge management factors.

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Authors: K. Cormican, G. Coppola, S. Farina

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Knowledge management is a critical component of competitive success in service organizations. Knowledge management centers on creating new knowledge and utilizing existing knowledge. While utilizing existing knowledge relates to input and control and can lead to a reduction in costs; creating new knowledge relates to output and growth and can lead to an increase in revenue. Therefore managers must ensure that they can successfully optimize the knowledge and talent in their organizations. To do this they and must try to develop an environment that promotes the generation, acquisition, transfer and use of valuable knowledge in creative ways. However knowledge management is complex and diverse. Research suggests that organizations in general and SMEs in particular are finding it difficult to implement successful knowledge management initiatives. Our research attempts to understand whether organizations are adopting best practice initiatives in their organizations. This paper presents findings from an exploratory study of 139 SMEs operating in the tourism sector across Europe. The goals of the survey is to assess the level of awareness of knowledge and talent management strategies and methodologies and to determine whether the responding companies implement best practice knowledge management initiatives in their organizations Analysis of the findings from the study are presented and discussed.

Keywords: service sector, small enterprise, success factors, survey

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Authors: Tian Tian, Tian Baoguang

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The paper studies implications between knowledge spillovers and technological innovation capability in the following three aspects: firstly, the paper debates on the effect of knowledge spillover on some perspectives of technological innovation ability; secondly, it discusses how different roles of knowledge spillover affect the technological innovation capability; finally, the paper creates the model of the factors of knowledge spillovers influencing to technological innovation capability. It concludes that knowledge spillovers affect all the main aspects of technological innovation ultimately to impact of technological innovation capabilities.

Keywords: Knowledge Spillover, Technological Innovation Capability, Innovation Cluster, Innovation Network Factors.

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Authors: Ulrich Berger, Yuliya Lebedynska, Veronica Vargas

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The right information at the right time influences the enterprise and technical success. Sharing knowledge among members of a big organization may be a complex activity. And as long as the knowledge is not shared, can not be exploited by the organization. There are some mechanisms which can originate knowledge sharing. It is intended, in this paper, to trigger these mechanisms by using semantic nets. Moreover, the intersection and overlapping of terms and sub-terms, as well as their relationships will be described through the mereology science for the whole knowledge sharing system. It is proposed a knowledge system to supply to operators with the right information about a specific process and possible risks, e.g. at the assembly process, at the right time in an automated manufacturing environment, such as at the automotive industry.

Keywords: Automated manufacturing, knowledge sharing, mereology, risk management, semantic net.

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Authors: F. Bakiri, T. Rexha, A. Mitre

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The aim of our study was to compare knowledge of regarding HPV and cervical cancer in female student of 18 to 26 years old, with or without sexual intercourse. We conducted a questionnaire survey of the students (N=568), in Faculty of Natural Sciences, Tirana, Albania. Sexually experienced students were more likely to have heard of risk factors such as multiple sex partners, sexual intercourse before age 18, having contracted any sexually transmitted diseases, having genital warts, smoking cigarettes, use of oral contraceptive, poor diet or nutrition and using tampons. No significant sexually experience differences were observed in knowledge of the way of transmission of the virus associated with cervical cancer knowledge, the virus associated with cervical cancer knowledge, the prevention of cervical cancer knowledge. On the other hand strong significant sexually experience differences were observed in knowledge of the diagnostic way of cervical cancer and what HPV can cause knowledge.

Keywords: Risk factors, HPV, Cervical cancer, Albanian students.

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Authors: Ferdi Sönmez, Başak Buluz

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Agility in Knowledge Management (AKM) tries to capture agility requirements and their respective answers within the framework of knowledge and learning for organizations. Since it is rather a new construct, it is difficult to claim that it has been sufficiently discussed and analyzed in practical and theoretical realms. Like the term ‘agile learning’, it is also commonly addressed in the software development and information technology fields and across the related areas where those technologies can be applied. The organizational perspective towards AKM, seems to need some more time to become scholarly mature. Nevertheless, in the literature one can come across some implicit usages of this term occasionally. This research is aimed to explore the conceptual background of agility in KM, re-conceptualize it and extend it to business applications with a special focus on e-business.

Keywords: Knowledge management, agility requirements, agility in knowledge management, knowledge.

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Authors: Nor Aziati Abdul Hamid, Juhana Salim

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The main objective of this paper is to contribute the existing knowledge transfer and IT Outsourcing literature specifically in the context of Malaysia by reviewing the current practices of e-government IT outsourcing in Malaysia including the issues and challenges faced by the public agencies in transferring the knowledge during the engagement. This paper discusses various factors and different theoretical model of knowledge transfer starting from the traditional model to the recent model suggested by the scholars. The present paper attempts to align organizational knowledge from the knowledge-based view (KBV) and organizational learning (OL) lens. This review could help shape the direction of both future theoretical and empirical studies on inter-firm knowledge transfer specifically on how KBV and OL perspectives could play significant role in explaining the complex relationships between the client and vendor in inter-firm knowledge transfer and the role of organizational management information system and Transactive Memory System (TMS) to facilitate the organizational knowledge transferring process. Conclusion is drawn and further research is suggested.

Keywords: E-government, IT Outsourcing, Knowledge Management, Knowledge Transfer

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Authors: Asim N., M. Mazhar Manzoor, Shariq A.

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Knowledge is renowned as a significant component for sustaining competitive advantage and gives leading edge in business. This study emphasizes towards proper and effectuate utilization of internal and external (both either explicit or tacit) knowledge comes from stakeholders, highly supportive to combat with the challenges and enhance organizational productivity. Furthermore, it proposed a model under context of IRSA framework which facilitates the organization including flow of knowledge and experience sharing among employees. In discussion section an innovative model which indulges all functionality as mentioned in analysis section.

Keywords: Effective Decision-Making, Internal & ExternalKnowledge, Knowledge Management, Tacit & Explicit Knowledge.

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Authors: M. Takhtravanchi, C. Pathirage

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In the construction industry, project members are conveyor of project knowledge which is, often, not managed properly to be used in future projects. As construction projects are temporary and unique, project members are willing to be recruited once a project is completed. Therefore, poor management of knowledge across construction projects will lead to a considerable amount of knowledge loss; the ignoring of which would be detrimental to project performance. This issue is more prominent in projects undertaken through the traditional procurement system, as this system does not incentives project members for integration. Thus, disputes exist between the design and construction phases based on the poor management of knowledge between those two phases. This paper aims to highlight the challenges of the knowledge management that exists within the traditional procurement system. Expert interviews were conducted and challenges were identified and analysed by the Interpretive Structural Modelling (ISM) approach in order to summarise the relationships among them. Two identified key challenges are the Culture of an Organisation and Knowledge Management Policies. A knowledge of the challenges and their relationships will help project manager and stakeholders to have a better understanding of the importance of knowledge management.

Keywords: Challenges, construction industry, knowledge management, traditional procurement system.

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: Evolving learning, knowledge extraction, knowledge graph, text mining.

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Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao

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The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.

Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.

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Authors: Nur Razia Mohd Suradi, Hema Subramaniam, Marina Hassan, Siti Fatimah Omar

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Knowledge sharing culture contributes to a positive working environment. Currently, there is no platform for the Faculty of Industrial Information Technology (FIIT), Unisel academic staff to share knowledge among them. As it is done manually, the sharing process is through common meeting or by any offline discussions. There is no repository for future retrieval. However, with open source solution the development of knowledge based application may reduce the cost tremendously. In this paper we discuss about the domain on which this knowledge portal is being developed and also the deployment of open source tools such as JOOMLA, PHP programming language and MySQL. This knowledge portal is evidence that open source tools also reliable in developing knowledge based portal. These recommendations will be useful to the open source community to produce more open source products in future.

Keywords: Knowledge management, Portal, ContentManagement, JOOMLA.

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Authors: Nhon Do, Tam Pham

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Knowledge bases are basic components of expert systems or intelligent computational programs. Knowledge bases provide knowledge, events that serve deduction activity, computation and control. Therefore, researching and developing of models for knowledge representation play an important role in computer science, especially in Artificial Intelligence Science and intelligent educational software. In this paper, the extensive deduction computational model is proposed to design knowledge bases whose attributes are able to be real values or functional values. The system can also solve problems based on knowledge bases. Moreover, the models and algorithms are applied to produce the educational software for solving alternating current problems or solving set of equations automatically.

Keywords: Educational software, artificial intelligence, knowledge base systems, knowledge representation.

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Authors: Hafizullah A. Hashim, Aniza. A

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The Spiral development model has been used successfully in many commercial systems and in a good number of defense systems. This is due to the fact that cost-effective incremental commitment of funds, via an analogy of the spiral model to stud poker and also can be used to develop hardware or integrate software, hardware, and systems. To support adaptive, semantic collaboration between domain experts and knowledge engineers, a new knowledge engineering process, called Spiral_OWL is proposed. This model is based on the idea of iterative refinement, annotation and structuring of knowledge base. The Spiral_OWL model is generated base on spiral model and knowledge engineering methodology. A central paradigm for Spiral_OWL model is the concentration on risk-driven determination of knowledge engineering process. The collaboration aspect comes into play during knowledge acquisition and knowledge validation phase. Design rationales for the Spiral_OWL model are to be easy-to-implement, well-organized, and iterative development cycle as an expanding spiral.

Keywords: Domain Expert, Knowledge Base, Ontology, Software Process.

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Authors: Kuribachew Gizaw Tohiye, Monica Garfield

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Personal knowledge management is the aspect of knowledge management that relates to the way in which individuals organize and manage their own set of knowledge. While in that respect, there has been research in this area for the past 25 years, it is at present necessary to speculate upon what research has been done and what we have discovered about this arena of knowledge management. In contrast to organizational knowledge management, which focuses on a firm’s profitability and competitiveness, personal knowledge management (PKM) is concerned with the person’s self-effectiveness, competence and success. People are concerned in managing their knowledge in order to become more efficient in a variety of personal and organizational interests. This study presents a systematic review of PKM studies. Articles with PKM concepts are reviewed with the objective of clearly defining PKM, identifying the benefits of PKM, classifying the tools that enable PKM and finding the research gaps to indicate future research directions in the area. Consequently, we have developed a definition of PKM and identified the benefits of PKM, including an understanding of who seeks PKM and for what. Tools enabling PKM are identified and classified under three categories Web 1.0, 2.0 and 3.0 and finally the research gap and future directions are suggested. Research which facilitates collaboration by using semantic technologies is suggested to be studied further to improve PKM effectiveness.

Keywords: Knowledge management, organizational knowledge management, personal knowledge management, systematic review.

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Authors: Lara Dutil-Fafard, Caroline Rhéaume, Patrick Archambault, Daniel Lafond, Neal W. Pollock

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Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Keywords: Decision support system, event sequence diagram, exploration mission, medical autonomy, scenario-based queries, space medicine.

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Authors: Lotfi Admane

Abstract:

This paper presents a model of case based corporate memory named ReCaRo (REsource, CAse, ROle). The approach suggested in ReCaRo decomposes the domain to model through a set of components. These components represent the objects developed by the company during its activity. They are reused, and sometimes, while bringing adaptations. These components are enriched by knowledge after each reuse. ReCaRo builds the corporate memory on the basis of these components. It models two types of knowledge: 1) Business Knowledge, which constitutes the main knowledge capital of the company, refers to its basic skill, thus, directly to the components and 2) the Experience Knowledge which is a specialised knowledge and represents the experience gained during the handling of business knowledge. ReCaRo builds corporate memories which are made up of five communicating ones.

Keywords: Corporate memories, meta-model, reuse, ReCaRo.

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Authors: U. Waqas, M. F. Ahmed, A. Mehmood, M. A. Rashid

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In geophysical exploration surveys, the quality of acquired data holds significant importance before executing the data processing and interpretation phases. In this study, 2D seismic reflection survey data of Fort Abbas area, Cholistan Desert, Pakistan was taken as test case in order to assess its quality on statistical bases by using normalized root mean square error (NRMSE), Cronbach’s alpha test (α) and null hypothesis tests (t-test and F-test). The analysis challenged the quality of the acquired data and highlighted the significant errors in the acquired database. It is proven that the study area is plain, tectonically least affected and rich in oil and gas reserves. However, subsurface 3D modeling and contouring by using acquired database revealed high degrees of structural complexities and intense folding. The NRMSE had highest percentage of residuals between the estimated and predicted cases. The outcomes of hypothesis testing also proved the biasness and erraticness of the acquired database. Low estimated value of alpha (α) in Cronbach’s alpha test confirmed poor reliability of acquired database. A very low quality of acquired database needs excessive static correction or in some cases, reacquisition of data is also suggested which is most of the time not feasible on economic grounds. The outcomes of this study could be used to assess the quality of large databases and to further utilize as a guideline to establish database quality assessment models to make much more informed decisions in hydrocarbon exploration field.

Keywords: Data quality, null hypothesis, seismic lines, seismic reflection survey.

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Authors: Jaqueline M. R. Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge dataset configurations.

Keywords: Brazil, classifiers, data-mining, Image Segmentation, oil well visualization, classifiers.

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Authors: I. Kontorovich, R. Zazkis

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We present a framework of researcher knowledge development in conducting a study in mathematics education. The key components of the framework are: knowledge germane to conducting a particular study, processes of knowledge accumulation, and catalyzing filters that influence a researcher decision making. The components of the framework originated from a confluence between constructs and theories in Mathematics Education, Higher Education and Sociology. Drawing on a self-reflective interview with a leading researcher in mathematics education, Professor Michèle Artigue, we illustrate how the framework can be utilized in data analysis. Criteria for framework evaluation are discussed.

Keywords: Community of practice, knowledge development, mathematics education research, researcher knowledge.

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Authors: M. R. Aghaebrahimi, S. H. Zahiri, M. Amiri

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In this paper a data miner based on the learning automata is proposed and is called LA-miner. The LA-miner extracts classification rules from data sets automatically. The proposed algorithm is established based on the function optimization using learning automata. The experimental results on three benchmarks indicate that the performance of the proposed LA-miner is comparable with (sometimes better than) the Ant-miner (a data miner algorithm based on the Ant Colony optimization algorithm) and CNZ (a well-known data mining algorithm for classification).

Keywords: Data mining, Learning automata, Classification rules, Knowledge discovery.

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Authors: GuoQiang Peng, Yi Sun

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In this paper, based on the work in [1], we further give a general model for acquiring knowledge, which first focuses on the research of how and when things involved in problems are made then describes the goals, the energy and the time to give an optimum model to decide how many related things are supposed to be involved in. Finally, we acquire knowledge from this model in which there are the attributes, actions and connections of the things involved at the time when they are born and the time in their life. This model not only improves AI theories, but also surely brings the effectiveness and accuracy for AI system because systems are given more knowledge when reasoning or computing is used to bring about results.

Keywords: Time, knowledge, model.

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Authors: M. Michael Gromiha, Y. Yabuki, K. Imai, P. Horton, K. Fukui

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We have developed a database for membrane protein functions, which has more than 3000 experimental data on functionally important amino acid residues in membrane proteins along with sequence, structure and literature information. Further, we have proposed different methods for identifying membrane proteins based on their functions: (i) discrimination of membrane transport proteins from other globular and membrane proteins and classifying them into channels/pores, electrochemical and active transporters, and (ii) β-signal for the insertion of mitochondrial β-barrel outer membrane proteins and potential targets. Our method showed an accuracy of 82% in discriminating transport proteins and 68% to classify them into three different transporters. In addition, we have identified a motif for targeting β-signal and potential candidates for mitochondrial β-barrel membrane proteins. Our methods can be used as effective tools for genome-wide annotations.

Keywords: Membrane proteins, database, transporters, discrimination, β-signal.

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Authors: Angelina A. Tzacheva, Jaishree Ranganathan

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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: Actionable pattern discovery, education, emotion, data mining.

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Authors: R. Prabha, N. Ramaraj

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Routing in adhoc networks is a challenge as nodes are mobile, and links are constantly created and broken. Present ondemand adhoc routing algorithms initiate route discovery after a path breaks, incurring significant cost to detect disconnection and establish a new route. Specifically, when a path is about to be broken, the source is warned of the likelihood of a disconnection. The source then initiates path discovery early, avoiding disconnection totally. A path is considered about to break when link availability decreases. This study modifies Adhoc On-demand Multipath Distance Vector routing (AOMDV) so that route handoff occurs through link availability estimation.

Keywords: Mobile Adhoc Network (MANET), Routing, Adhoc On-demand Multipath Distance Vector routing (AOMDV), Link Availability.

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Authors: César Camisón-Zornoza, Beatriz Forés-Julián, Alba Puig-Denia

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The literature has argued that firms based in industrial districts enjoy advantages for creating internal knowledge and absorbing external knowledge as a consequence of to the knowledge flows and spillovers that exist in the district. However, empirical evidence to show how belonging to an industrial district affects the business processes of creation and absorption of knowledge is scarce and, moreover, empirical research has not taken into account the influence of variations in the flows of knowledge circulating in each cluster. This study aims to extend empirical evidence on the effect that the stock of shared competencies in industrial districts has on the business processes of creation and absorption of knowledge, through data from an initial study on 952 firms and 35 industrial districts in Spain.

Keywords: Absorptive capacity, industrial district, knowledge creation, organisational learning

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Authors: Shahrinaz Ismail, Mohd Sharifuddin Ahmad

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This paper presents an analytical framework for an effective online personal knowledge management (PKM) of knowledge workers. The development of this framework is prompted by our qualitative research on the PKM processes and cognitive enablers of knowledge workers in eight organisations selected from three main industries in Malaysia. This multiple-case research identifies the relationships between the effectiveness of four online PKM processes: get/retrieve, understand/analyse, share, and connect. It also establishes the importance of cognitive enablers that mediate this relationship, namely, method, identify, decide and drive. Qualitative analysis is presented as the findings, supported by the preceded quantitative analysis on an exploratory questionnaire survey.

Keywords: Bottom-up approach, knowledge organisation, organisational knowledge management, personal knowledge management, software agent technology.

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Authors: A. Evans, M. McKinley

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Knowledge management (KM) is generally considered to be a positive process in an organisation, facilitating opportunities to achieve competitive advantage via better quality information handling, compilation of expert know-how and rapid response to fluctuations in the business environment. The KM paradigm as portrayed in the literature informs the processes that can increase intangible assets so that corporate knowledge is preserved. However, in some instances, knowledge management exists in a universe of dynamic tension among the conflicting needs to respect privacy and intellectual property (IP), to guard against data theft, to protect national security and to stay within the laws. While the Knowledge Management literature focuses on the bright side of the paradigm, there is also a different side in which knowledge is distorted, suppressed or misappropriated due to personal or organisational motives (the paradox). This paper describes the ethical paradoxes that occur within the taxonomy and deontology of knowledge management and suggests that recognising both the promises and pitfalls of KM requires wisdom.

Keywords: business ethics, data, knowledge, knowledgemanagement, privacy, protection.

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Authors: Tori R. Dodla, Laura A. Jones

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The objective of this study was to propose strategies to improve the efficiency of Knowledge Management Systems (KMS). This study highlights best practices from various industries to create an overall summary of Knowledge Management (KM) and efficiency in organizational performance. Results indicated 11 best practices for maximizing the efficiency of organizational KMS that can be divided into four categories: Designing the KMS, identifying case studies, implementing the KMS, and promoting adoption and usage. Our findings can be used as a foundation for scholars to conduct further research on KMS efficiency.

Keywords: Artificial intelligence, knowledge management efficiency, knowledge management systems, organizational performance.

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