Search results for: knowledge clustering

Authors: S. S. Bhandari, N. Chakpitak, K. Meksamoot, T. Chandarasupsang

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Under the limitation of investment budget, a utility company is required to maximize the utilization of their existing assets during their life cycle satisfying both engineering and financial requirements. However, utility does not have knowledge about the status of each asset in the portfolio neither in terms of technical nor financial values. This paper presents a knowledge based model for the utility companies in order to make an optimal decision on power transformer with their utilization. CommonKADS methodology, a structured development for knowledge and expertise representation, is utilized for designing and developing knowledge based model. A case study of One MVA power transformer of Nepal Electricity Authority is presented. The results show that the reusable knowledge can be categorized, modeled and utilized within the utility company using the proposed methodologies. Moreover, the results depict that utility company can achieve both engineering and financial benefits from its utilization.

Keywords: CommonKADS, Knowledge Engineering, LifeCycle Management, Power Transformer.

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Authors: Hamid Alalwany, Nabeel A. Koshak, Mohammad K. Ibrahim

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Both knowledge economy and sustainable development are considered key dimensions in the policy action lines of many developed and developing countries. In this context, universities and other higher education institutes have a vital role in developing and sustaining wellbeing communities.

In this paper, the authors’ aim is to address the links between the concepts of innovation and entrepreneurial capacity and knowledge economy, and to utilize the approach of intellectual capital development in building a sustainable knowledge economy.

The paper will contribute to two discourses:

1. Developing a common understanding of the intersection aspects between the three concepts: Knowledge economy, Innovation and entrepreneurial system, and sustainable development.
2. Paving the road towards developing an integrated multidimensional framework for sustainable knowledge economy.

Keywords: Innovation and Entrepreneurial Capacity, Intellectual Capital Development, Sustainable Development, Sustainable Knowledge Economy.

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Authors: Joachim Kimmerle, Johannes Moskaliuk, Ulrike Cress

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The development of Internet technology in recent years has led to a more active role of users in creating Web content. This has significant effects both on individual learning and collaborative knowledge building. This paper will present an integrative framework model to describe and explain learning and knowledge building with shared digital artifacts on the basis of Luhmann-s systems theory and Piaget-s model of equilibration. In this model, knowledge progress is based on cognitive conflicts resulting from incongruities between an individual-s prior knowledge and the information which is contained in a digital artifact. Empirical support for the model will be provided by 1) applying it descriptively to texts from Wikipedia, 2) examining knowledge-building processes using a social network analysis, and 3) presenting a survey of a series of experimental laboratory studies.

Keywords: Individual learning, collaborative knowledge building, systems theory, equilibration.

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Authors: Ani Grubišić, Slavomir Stankov, Branko Žitko

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This paper describes a concept of stereotype student model in adaptive knowledge acquisition e-learning system. Defined knowledge stereotypes are based on student's proficiency level and on Bloom's knowledge taxonomy. The teacher module is responsible for the whole adaptivity process: the automatic generation of courseware elements, their dynamic selection and sorting, as well as their adaptive presentation using templates for statements and questions. The adaptation of courseware is realized according to student-s knowledge stereotype.

Keywords: Adaptive e-learning systems, adaptive courseware, stereotypes, Bloom's knowledge taxonomy.

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Authors: Z. Pooranian, A. Barati, A. Movaghar

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Wireless sensor networks include small nodes which have sensing ability; calculation and connection extend themselves everywhere soon. Such networks have source limitation on connection, calculation and energy consumption. So, since the nodes have limited energy in sensor networks, the optimized energy consumption in these networks is of more importance and has created many challenges. The previous works have shown that by organizing the network nodes in a number of clusters, the energy consumption could be reduced considerably. So the lifetime of the network would be increased. In this paper, we used the Queen-bee algorithm to create energy efficient clusters in wireless sensor networks. The Queen-bee (QB) is similar to nature in that the queen-bee plays a major role in reproduction process. The QB is simulated with J-sim simulator. The results of the simulation showed that the clustering by the QB algorithm decreases the energy consumption with regard to the other existing algorithms and increases the lifetime of the network.

Keywords: Queen-bee, sensor network, energy efficient, clustering.

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Authors: Francesca Affortunato, Edgardo Bucciarelli, Mariateresa Ciommi, Gianfranco Giulioni

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The paper represents a reflection on how to select proper indicators to assess the progress of regional contexts towards a knowledge-based society. Taking the first research methodologies elaborated at an international level (World Bank, OECD, etc.) as a reference point, this work intends to identify a set of indicators of the knowledge economy suitable to adequately understand in which manner and to which extent the territorial development dynamics are correlated with the knowledge-base of the considered local society. After a critical survey of the variables utilized within other approaches adopted by international or national organizations, this paper seeks to elaborate a framework of variables, named Regional Knowledge Economy Indicators (ReKEI), necessary to describe the knowledge-based relations of subnational socio-economic contexts. The realization of this framework has a double purpose: an analytical one consisting in highlighting the regional differences in the governance of knowledge based processes, and an operative one consisting in providing some reference parameters for contributing to increasing the effectiveness of those economic policies aiming at enlarging the knowledge bases of local societies.

Keywords: Knowledge economy, knowledge society, information society, regional innovation system, territorial competitiveness, local development.

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Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: Band selection, fuzzy C-means, K-means, hyperspectral image.

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Authors: Jing Wu, Wei Lv, Yibing Li, Yuanfan You

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The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.

Keywords: Clustering algorithm, potential function, speech signal, the UBSS model.

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Authors: Nazmona Mat Ali, Kecheng Liu

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Knowledge is a key asset for any organisation to sustain competitive advantages, but it is difficult to identify and represent knowledge which is needed to perform activities in business processes. The effective knowledge management and support for relevant business activities definitely gives a huge impact to the performance of the organisation as a whole. This is because that knowledge have the functions of directing, coordinating and controlling actions within business processes. The study has introduced organisational morphology, a norm-based approach by applying semiotic theories which emphasise on the representation of knowledge in norms. This approach is concerned with the identification of activities into three categories: substantive, communication and control activities. All activities are directed by norms; hence three types of norms exist; each is associated to a category of activities. The paper describes the approach briefly and illustrates the application of this approach through a case study of academic activities in higher education institutions. The result of the study shows that the approach provides an effective way to profile business knowledge and the profile enables the understanding and specification of business requirements of an organisation.

Keywords: Business knowledge, Business process, Norms, Semiotics, Organisational morphology

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Authors: S. Abdallah, A. Khalil, A. Divine

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The purpose of this study was to explore the relationship between knowledge sharing and innovation capability, by examining the influence of individual, organizational and technological factors on knowledge sharing. The research is based on a survey of 103 employees from different organizations in the United Arab Emirates. The study is based on a model and a questionnaire that was previously tested by Lin [1]. Thus, the study aims at examining the validity of that model in UAE context. The results of the research show varying degrees of correlation between the different variables, with ICT use having the strongest relationship with the innovation capabilities of organizations. The study also revealed little evidence of knowledge collecting and knowledge sharing among UAE employees.

Keywords: Knowledge sharing, Organization Innovation, Technology Use, Innovation Capabilities.

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Authors: B. Alajmi, L. Marouf, A. S. Chaudhry

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Knowledge management is considered as an important factor in improving health care services. KM facilitates the transfer of existing knowledge and the development of new knowledge in hospitals. This paper reviews practices adopted by doctors in Kuwait for capturing, sharing, and generating knowledge. It also discusses the perceived impact of KM practices on performance of hospitals. Based on a survey of 277 doctors, the study found that KM practices among doctors in the sampled hospitals were not very effective. Little attention was paid to the main activities that support the transfer of expertise among doctors in hospitals. However, as predicted by previous studies, good km practices were perceived by doctors to have a positive impact on performance of hospitals. It was concluded that through effective KM practices hospitals could improve the services they provide. Documentation of best practices and capturing of lessons learnt for re-use of knowledge could help transform the hospitals into learning organizations.

Keywords: Health Sector, Hospitals, Knowledge Management, Kuwait, Tools and Practices.

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Authors: Teresa L. Ju, Szu-Yuan Sun, Pei-Ju Chao, Chang-Yao Wu

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This study aims to examine the factors affecting knowledge sharing behavior in knowledge-based electronic communities (e-communities) because quantity and quality of knowledge shared among the members play a critical role in the community-s sustainability. Past research has suggested three perspectives that may affect the quantity and quality of knowledge shared: economics, social psychology, and social ecology. In this study, we strongly believe that an economic perspective may be suitable to validate factors influencing newly registered members- knowledge contribution at the beginning of relationship development. Accordingly, this study proposes a model to validate the factors influencing members- knowledge sharing based on Transaction Cost Theory. By doing so, we may empirically test our hypotheses in various types of e-communities to determine the generalizability of our research models.

Keywords: Electronic community, individual behavior, knowledge sharing, transaction cost theory.

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Authors: Kechida Ahmed, Drai Redouane, Khelil Mohamed

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In this paper we present a new approach to detecting a flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image based on texture features. Texture is one of the most important features used in recognizing patterns in an image. The paper describes texture features based on 2D Gabor functions, i.e., Gaussian shaped band-pass filters, with dyadic treatment of the radial spatial frequency range and multiple orientations, which represent an appropriate choice for tasks requiring simultaneous measurement in both space and frequency domains. The most relevant features are used as input data on a Fuzzy c-mean clustering classifier. The classes that exist are only two: 'defects' or 'no defects'. The proposed approach is tested on the T.O.F.D image achieved at the laboratory and on the industrial field.

Keywords: 2D Gabor Functions, flaw detection, fuzzy c-mean clustering, non destructive testing, texture analysis, T.O.F.D Image (Time of Flight Diffraction).

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Authors: Mohammadreza Razzazi, Maryam Bayat

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Selection of the best possible set of suppliers has a significant impact on the overall profitability and success of any business. For this reason, it is usually necessary to optimize all business processes and to make use of cost-effective alternatives for additional savings. This paper proposes a new efficient context-aware supplier selection model that takes into account possible changes of the environment while significantly reducing selection costs. The proposed model is based on data clustering techniques while inspiring certain principles of online algorithms for an optimally selection of suppliers. Unlike common selection models which re-run the selection algorithm from the scratch-line for any decision-making sub-period on the whole environment, our model considers the changes only and superimposes it to the previously defined best set of suppliers to obtain a new best set of suppliers. Therefore, any recomputation of unchanged elements of the environment is avoided and selection costs are consequently reduced significantly. A numerical evaluation confirms applicability of this model and proves that it is a more optimal solution compared with common static selection models in this field.

Keywords: Supplier Selection, Context-Awareness, OnlineAlgorithms, Data Clustering.

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Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

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The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: Degree, initial cluster center, k-means, minimum spanning tree.

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Authors: Novita Verayanti Manalu, Alvin Salim, Esti Yunitasari

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Background: Palliative care is caring holistically for patients and families to improve their quality of life. The approach by a multidisciplinary team requires integrated collaboration based on sufficient knowledge of the principles of palliative care as a whole, especially for nurses. Therefore, this study wants to find out the level of knowledge about palliative care of the nurses along the relationship with attitude and performance. Method: This study applies cross-sectional survey design and allows the respondents to fill two questionnaires to determine the level of knowledge and attitude toward palliative care, while one questionnaire is filled by the head nurse to evaluate nurses’ performance. The relationship was analyzed by Spearman rho’s correlation in alpha < 0.05 by SPSS. Results: The majority of respondents were females, age above 25 years old, and married. Most of the nurses are staff nurses and the ratio of education level is not significantly different. The knowledge level is poor, while the attitude and performance are in adequate level. Knowledge may affect attitude, but it does not happen toward performance. Conclusion: There is a need for increased knowledge about palliative care to improve attitude and work performance. Future researchers might use this finding as reference to conduct further study in improving knowledge of palliative care.

Keywords: Knowledge, attitude, work performance, palliative care.

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Authors: Amol Bapuso Rajmane, Pradeep M. Patil, Prakash J. Kulkarni

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The Information Retrieval community is facing the problem of effective representation of Web search results. When we organize web search results into clusters it becomes easy to the users to quickly browse through search results. The traditional search engines organize search results into clusters for ambiguous queries, representing each cluster for each meaning of the query. The clusters are obtained according to the topical similarity of the retrieved search results, but it is possible for results to be totally dissimilar and still correspond to the same meaning of the query. People search is also one of the most common tasks on the Web nowadays, but when a particular person’s name is queried the search engines return web pages which are related to different persons who have the same queried name. By placing the burden on the user of disambiguating and collecting pages relevant to a particular person, in this paper, we have developed an approach that clusters web pages based on the association of the web pages to the different people and clusters that are based on generic entity search.

Keywords: Entity resolution, information retrieval, graph based disambiguation, web people search, clustering.

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Authors: A. Mohamed Mydeen, Pallapa Venkataram

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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.

Keywords: Generic knowledge representation, toolkit, toolroom, pervasive computing.

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Authors: A. Rajagopal, S. Somasundaram, B. Sowmya, T. Suguna

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Wireless Sensor Networks (WSNs) enable new applications and need non-conventional paradigms for the protocol because of energy and bandwidth constraints, In WSN, sensor node’s life is a critical parameter. Research on life extension is based on Low-Energy Adaptive Clustering Hierarchy (LEACH) scheme, which rotates Cluster Head (CH) among sensor nodes to distribute energy consumption over all network nodes. CH selection in WSN affects network energy efficiency greatly. This study proposes an improved CH selection for efficient data aggregation in sensor networks. This new algorithm is based on Bacterial Foraging Optimization (BFO) incorporated in LEACH.

Keywords: Bacterial Foraging Optimization (BFO), Cluster Head (CH), Data-aggregation protocols, Low-Energy Adaptive Clustering Hierarchy (LEACH).

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Authors: A. Kowcika, E. Umamaheswari, T.V. Geetha

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In this paper we focus on event extraction from Tamil news article. This system utilizes a scoring scheme for extracting and grouping event-specific sentences. Using this scoring scheme eventspecific clustering is performed for multiple documents. Events are extracted from each document using a scoring scheme based on feature score and condition score. Similarly event specific sentences are clustered from multiple documents using this scoring scheme. The proposed system builds the Event Template based on user specified query. The templates are filled with event specific details like person, location and timeline extracted from the formed clusters. The proposed system applies these methodologies for Tamil news articles that have been enconverted into UNL graphs using a Tamil to UNL-enconverter. The main intention of this work is to generate an event based template.

Keywords: Event Extraction, Score based Clustering, Segmentation, Template Generation.

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Authors: Ying-Hueih Chen, Jyh-Jeng Wu, Shu-Hua Chien, Yui-Chuin Shiah

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Interorganizational knowledge sharing is the major driving force to maximize the operational benefits across supply chain. Trust is considered as the key to facilitate knowledge sharing. This research proposes shared values and relational embeddedness as antecedents of interorganizational trust. Survey based on managers in major industrial parks in Taiwan confirm that trust is enforced when organizations develop shared values and formed social relational embeddedness. Trust leads to interorganizational knowledge sharing. This research has theoretical and practical implications.

Keywords: Shared Goal, Relational Embeddedness, Trust, Knowledge Sharing.

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Authors: Katarzyna Mleczko

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Processes of production of innovative medical tools have interdisciplinary character. They consist of direct and indirect close cooperation of specialists of different scientific branches. The Knowledge they have seems to be important for undertaken design, construction and manufacturing processes. The Knowledge exchange between participants of these processes is therefore crucial for the final result, which are innovative medical products. The paper draws attention to the necessity of feedback from the end user to the designer / manufacturer of medical tools which will allow for more accurate understanding of user needs. The study describes prerequisites of production processes of innovative medical (surgical) tools including participants and category of knowledge resources occurring in these processes. They are the result of research in selected Polish organizations involved in the production of medical instruments and are the basis for further work on the development of knowledge sharing model in interdisciplinary teams geographically dispersed.

Keywords: Interdisciplinary production processes, knowledge exchange, knowledge sharing, medical tools, user-centered design.

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Authors: Shahrinaz Ismail, Zulhelmi Mohammed, Nur Waheda Md Yusof, Mohd Sharifuddin Ahmad

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The burst of Web 2.0 technology and social networking tools manifest different styles of learning and managing knowledge among both knowledge workers and adult learners. In the Western countries, open-learning concept has been made popular due to the ease of use and the reach that the technology provides. In Malaysia, there are still some gaps between the learners- acceptance of technology and the full implementation of the technology in the education system. There is a need to understand how adult learners, who are knowledge workers, manage their personal knowledge via social networking tools, especially in their learning process. Four processes of personal knowledge management (PKM) and four cognitive enablers are proposed supported by analysed data on adult learners in a university. The model derived from these processes and enablers is tested and presented, with recommendations on features to be included in adult learners- learning environment.

Keywords: Personal knowledge management, adult learners, social network, learning environment.

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Authors: Noor Asilah Nordin, Normala Daud, Wan Ummi Kalsom Meor Osman

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This study applied Theory of Planned Behaviour (TPB) to explain the knowledge sharing behaviour among academic staff at a Public Higher Education Institution (HEI) in Malaysia. The main objectives of this study are; to identify the components that influence knowledge sharing behaviour and to determine the levels of knowledge sharing behaviour among academic staff. A total of 200 respondents were participated in answering questionnaires. The findings of this study revealed that level of perceiving and implementing knowledge sharing behaviour among academic staff at a Public HEI in Malaysia exist but not openly or strongly practiced. The findings were discussed and recommendations for the future research were also addressed.

Keywords: Attitude, Knowledge Sharing Behaviour, Perceived Behavioural Control, Subjective Norm.

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Authors: Chutima Ruanguttamanun

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Despite the relatively large number of studies that have examined the use of appeals in advertisements, research on the use of appeals in green advertisements is still underdeveloped and needs to be investigated further, as it is definitely a tool for marketers to create illustrious ads. In this study, content analysis was employed to examine the nature of green advertising appeals and to match the appeals with the green advertisements. Two different types of green print advertisings, product orientation and organizational image orientation were used. Thirty highly educated participants with different backgrounds were asked individually to ascertain three appeals out of thirty-four given appeals found among forty real green advertisements. To analyze participant responses and to group them based on common appeals, two-step K-mean clustering is used. The clustering solution indicates that eye-catching graphics and imaginative appeals are highly notable in both types of green ads. Depressed, meaningful and sad appeals are found to be highly used in organizational image orientation ads, whereas, corporate image, informative and natural appeals are found to be essential for product orientation ads.

Keywords: Advertising appeals, green marketing, green advertisement, printed advertisement.

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Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik

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Wireless sensor network can be applied to both abominable and military environments. A primary goal in the design of wireless sensor networks is lifetime maximization, constrained by the energy capacity of batteries. One well-known method to reduce energy consumption in such networks is data aggregation. Providing efcient data aggregation while preserving data privacy is a challenging problem in wireless sensor networks research. In this paper, we present privacy-preserving data aggregation scheme for additive aggregation functions. The Cluster-based Private Data Aggregation (CPDA)leverages clustering protocol and algebraic properties of polynomials. It has the advantage of incurring less communication overhead. The goal of our work is to bridge the gap between collaborative data collection by wireless sensor networks and data privacy. We present simulation results of our schemes and compare their performance to a typical data aggregation scheme TAG, where no data privacy protection is provided. Results show the efficacy and efficiency of our schemes.

Keywords: Aggregation, Clustering, Query Processing.

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Authors: Surat Srinoy, Werasak Kurutach, Witcha Chimphlee, Siriporn Chimphlee

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One main drawback of intrusion detection system is the inability of detecting new attacks which do not have known signatures. In this paper we discuss an intrusion detection method that proposes independent component analysis (ICA) based feature selection heuristics and using rough fuzzy for clustering data. ICA is to separate these independent components (ICs) from the monitored variables. Rough set has to decrease the amount of data and get rid of redundancy and Fuzzy methods allow objects to belong to several clusters simultaneously, with different degrees of membership. Our approach allows us to recognize not only known attacks but also to detect activity that may be the result of a new, unknown attack. The experimental results on Knowledge Discovery and Data Mining- (KDDCup 1999) dataset.

Keywords: Network security, intrusion detection, rough set, ICA, anomaly detection, independent component analysis, rough fuzzy .

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Authors: J. Bouchard, B. Prosperi, G. Bavre, M. Daudé, E. Jeandupeux

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Young patients suffering from Cerebral Palsy are facing difficult choices concerning heavy surgeries. Diagnosis settled by surgeons can be complex and on the other hand decision for patient about getting or not such a surgery involves important reflection effort. Proposed software combining prediction for surgeries and post surgery kinematic values, and from 3D model representing the patient is an innovative tool helpful for both patients and medicine professionals. Beginning with analysis and classification of kinematics values from Data Base extracted from gait analysis in 3 separated clusters, it is possible to determine close similarity between patients. Prediction surgery best adapted to improve a patient gait is then determined by operating a suitable preconditioned neural network. Finally, patient 3D modeling based on kinematic values analysis, is animated thanks to post surgery kinematic vectors characterizing the closest patient selected from patients clustering.

Keywords: Cerebral Palsy, Clustering, Crouch Gait, 3-D Modeling.

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Authors: B. Stroetmann, A. Aisenbrey

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The Siemens Healthcare Sector is one of the world's largest suppliers to the healthcare industry and a trendsetter in medical imaging and therapy, laboratory diagnostics, medical information technology, and hearing aids. Siemens offers its customers products and solutions for the entire range of patient care from a single source – from prevention and early detection to diagnosis, and on to treatment and aftercare. By optimizing clinical workflows for the most common diseases, Siemens also makes healthcare faster, better, and more cost effective. The optimization of clinical workflows requires a multidisciplinary focus and a collaborative approach of e.g. medical advisors, researchers and scientists as well as healthcare economists. This new form of collaboration brings together experts with deep technical experience, physicians with specialized medical knowledge as well as people with comprehensive knowledge about health economics. As Charles Darwin is often quoted as saying, “It is neither the strongest of the species that survive, nor the most intelligent, but the one most responsive to change," We believe that those who can successfully manage this change will emerge as winners, with valuable competitive advantage. Current medical information and knowledge are some of the core assets in the healthcare industry. The main issue is to connect knowledge holders and knowledge recipients from various disciplines efficiently in order to spread and distribute knowledge.

Keywords: Business Excellence, Clinical Knowledge, Knowledge Management, Knowledge Services, Learning Organizations, Trust.

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Authors: B. T. Sayed, Nafaâ Jabeur, M. Aref

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Creation and maintenance of knowledge management systems has been recognized as an important research area. Consecutively lack of accurate results from knowledge management systems limits the organization to apply their knowledge management processes. This leads to a failure in getting the right information to the right people at the right time thus followed by a deficiency in decision making processes. An Intranet offers a powerful tool for communication and collaboration, presenting data and information, and the means that creates and shares knowledge, all in one easily accessible place. This paper proposes an archetype describing how a knowledge management system, with the support of intranet capabilities, could very much increase the accuracy of capturing, storing and retrieving knowledge based processes thereby increasing the efficiency of the system. This system will expect a critical mass of usage, by the users, for intranet to function as knowledge management systems. This prototype would lead to a design of an application that would impose creation and maintenance of an effective knowledge management system through intranet. The aim of this paper is to introduce an effective system to handle capture, store and distribute knowledge management in a form that may not lead to any failure which exists in most of the systems. The methodology used in the system would require all the employees, in the organization, to contribute the maximum to deliver the system to a successful arena. The system is still in its initial mode and thereby the authors are under the process to practically implement the ideas, as mentioned in the system, to produce satisfactory results.

Keywords: Knowledge Management Systems, Intranet, Methodology.

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