Search results for: Knowledge sharing network

Authors: H. Zainuddin, F. Hanafi, M. H. Hairi, A. Aman, M.H.N. Talib

Abstract:

This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.

Keywords: Knowledge-based Supplementary Control, Acceleration Feedback, Load Frequency Control, Automatic Generation Control.

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Authors: Mehdi Shami Zanjani, Shohreh Mehrasa, Mandana Modiri

Abstract:

In the current economy of increasing global competition, many organizations are attempting to use knowledge as one of the means to gain sustainable competitive advantage. Besides large organizations, the success of SMEs can be linked to how well they manage their knowledge. Despite the profusion of research about knowledge management within large organizations, fewer studies tried to analyze KM in SMEs. This research proposes a new framework showing the determinant role of organizational dimensions onto KM approaches. The paper and its propositions are based on a literature review and analysis. In this research, personalization versus codification, individualization versus institutionalization and IT-based versus non IT-based are highlighted as three distinct dimensions of knowledge management approaches. The study contributes to research by providing a more nuanced classification of KM approaches and provides guidance to managers about the types of KM approaches that should be adopted based on the size, geographical dispersion and task nature of SMEs. To the author-s knowledge, the paper is the first of its kind to examine if there are suitable configurations of KM approaches for SMEs with different dimensions. It gives valuable information, which hopefully will help SME sector to accomplish KM.

Keywords: Knowledge Management, Knowledge Management Approach, SME, Organizational Dimension.

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Authors: H. O. Barbosa, A. C. R. da Silva, C. M. de Almeida, E. M. dos Santos, F. O. de Sousa, F. B. da S. Souza, F. B. da S. Souza, F. de O. Lima, L. H. Albuquerque, R. F. do Valle Cunha

Abstract:

Software development is intrinsic human-based knowledge-intensive. Due to globalization, software development has become a complex challenge and we usually face barriers related to knowledge management, team building, costly testing processes, especially in distributed settings. In this paper, we present the use of experimental studies to improve our knowledge management process using the Wiki system. According to the results, it was possible to identify learning preferences from our software projects leader team, organize and improve the learning experience of our Wiki, and facilitate collaboration by newcomers to improve Wiki with new contents available in the Wiki.

Keywords: Mobile products, knowledge management process, Wiki system, Global Software Development.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour , Foad Saadi

Abstract:

In this paper back-propagation artificial neural network (BPANN) is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Keywords: Back-propagation artificial neural network(BPANN), prediction, upsetting

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Authors: E. Ahvar, M. Fathy

Abstract:

Ad hoc networks are characterized by multihop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of three routing protocols for mobile ad hoc networks: Dynamic Source Routing (DSR), Ad Hoc On-Demand Distance Vector Routing (AODV), location-aided routing (LAR1).Our evaluation is based on energy consumption in mobile ad hoc networks. The performance differentials are analyzed using varying network load, mobility, and network size. We simulate protocols with GLOMOSIM simulator. Based on the observations, we make recommendations about when the performance of either protocol can be best.

Keywords: Ad hoc Network, energy consumption, Glomosim, routing protocols.

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Authors: Hager Kammoun, Jean Charles Lamirel, Mohamed Ben Ahmed

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In this paper, a model for an information retrieval system is proposed which takes into account that knowledge about documents and information need of users are dynamic. Two methods are combined, one qualitative or symbolic and the other quantitative or numeric, which are deemed suitable for many clustering contexts, data analysis, concept exploring and knowledge discovery. These two methods may be classified as inductive learning techniques. In this model, they are introduced to build “long term" knowledge about past queries and concepts in a collection of documents. The “long term" knowledge can guide and assist the user to formulate an initial query and can be exploited in the process of retrieving relevant information. The different kinds of knowledge are organized in different points of view. This may be considered an enrichment of the exploration level which is coherent with the concept of document/query structure.

Keywords: Information Retrieval Systems, machine learning, classification, Galois lattices, Self Organizing Map.

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Authors: Kejun Zhuang, Zhaohui Wen

Abstract:

In this paper, a tri–neuron network model with time delay is investigated. By using the Bendixson-s criterion for high– dimensional ordinary differential equations and global Hopf bifurcation theory for functional differential equations, sufficient conditions for existence of periodic solutions when the time delay is sufficiently large are established.

Keywords: Delay, global Hopf bifurcation, neural network, periodicsolutions.

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Authors: Natalia Marulanda Grisales

Abstract:

The most significant changes in the characteristics of consumers have contributed to the development and adoption of methodologies and tools that enable organizations to be more competitive in the marketplace. One of these methodologies is the integration of Knowledge Management (KM) phases and Environmental Management Systems (EMS). This integration allows companies to manage and share the required knowledge for EMS adoption, from the place where it is generated to the place where it is going to be exploited. The aim of this paper is to identify the relationship between KM phases as a tool for the adoption of EMS in HEI. The methodology has a descriptive scope and a qualitative approach. It is based on a case study and a review of the literature about KM and EMS. We conducted 266 surveys to students, professors and staff at Minuto de Dios University (Colombia). Data derived from the study indicate that if a HEI wants to achieve an adequate knowledge acquisition and knowledge transfer, it must have clear goals for implementing an EMS. Also, HEI should create empowerment and training spaces for students, professors and staff. In the case study, HEI must generate alternatives that enhance spaces of knowledge appropriation. It was found that 85% of respondents have not received any training from HEI about EMS. 88% of respondents believe that the actions taken by the university are not efficient to knowledge transfer in order to develop an EMS.

Keywords: Environmental management systems, higher education institutions, knowledge management. training.

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Authors: Nhon Van Do, Nam Hoai Le, Vien Chan Luong

Abstract:

The Model for Knowledge Base of Computational Objects (KBCO model) has been successfully applied to represent the knowledge of human like Plane Geometry, Physical, Calculus. However, the original model cannot easyly apply in inorganic chemistry field because of the knowledge specific problems. So, the aim of this article is to introduce how we extend the Computional Object (Com-Object) in KBCO model, kinds of fact, problems model, and inference algorithms to develop a program for solving problems in inorganic chemistry. Our purpose is to develop the application that can help students in their study inorganic chemistry at schools. This application was built successful by using Maple, C# and WPF technology. It can solve automatically problems and give human readable solution agree with those writting by students and teachers.

Keywords: artificial intelligence, automated problem solving, knowledge base system, knowledge representation, reasoning strategy, education software/educational applications.

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Authors: Tal Ben-Zvi, Donald N. Lombardi

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This study uses a simulation to establish a realistic environment for laboratory research on Accountable Care Organizations. We study network attributes in order to gain insights regarding healthcare providers- conduct and performance. Our findings indicate how network structure creates significant differences in organizational performance. We demonstrate how healthcare providers positioning themselves at the central, pivotal point of the network while maintaining their alliances with their partners produce better outcomes.

Keywords: Social Networks, Decision-Making, Accountable Care Organizations, Performance

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Authors: M. R. Martinez-Torres, S. L. Toral, M. Olmedilla

Abstract:

Typically, virtual communities exhibit the well-known phenomenon of participation inequality, which means that only a small percentage of users is responsible of the majority of contributions. However, the sustainability of the community requires that the group of active users must be continuously nurtured with new users that gain expertise through a participation process. This paper analyzes the time evolution of Open Source Software (OSS) communities, considering users that join/abandon the community over time and several topological properties of the network when modeled as a social network. More specifically, the paper analyzes the role of those users rejoining the community and their influence in the global characteristics of the network.

Keywords: Open source communities, social network analysis, time series, virtual communities.

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Authors: Fengxia Zheng, Shouming Zhong

Abstract:

ANNARIMA that combines both autoregressive integrated moving average (ARIMA) model and artificial neural network (ANN) model is a valuable tool for modeling and forecasting nonlinear time series, yet the over-fitting problem is more likely to occur in neural network models. This paper provides a hybrid methodology that combines both radial basis function (RBF) neural network and auto regression (AR) model based on binomial smoothing (BS) technique which is efficient in data processing, which is called BSRBFAR. This method is examined by using the data of Canadian Lynx data. Empirical results indicate that the over-fitting problem can be eased using RBF neural network based on binomial smoothing which is called BS-RBF, and the hybrid model–BS-RBFAR can be an effective way to improve forecasting accuracy achieved by BSRBF used separately.

Keywords: Binomial smoothing (BS), hybrid, Canadian Lynx data, forecasting accuracy.

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Authors: Mohamed Watfa, William Daher, Hisham Al Azar

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The main idea behind in network aggregation is that, rather than sending individual data items from sensors to sinks, multiple data items are aggregated as they are forwarded by the sensor network. Existing sensor network data aggregation techniques assume that the nodes are preprogrammed and send data to a central sink for offline querying and analysis. This approach faces two major drawbacks. First, the system behavior is preprogrammed and cannot be modified on the fly. Second, the increased energy wastage due to the communication overhead will result in decreasing the overall system lifetime. Thus, energy conservation is of prime consideration in sensor network protocols in order to maximize the network-s operational lifetime. In this paper, we give an energy efficient approach to query processing by implementing new optimization techniques applied to in-network aggregation. We first discuss earlier approaches in sensors data management and highlight their disadvantages. We then present our approach “Energy Efficient Indexed Aggregation" (EEIA) and evaluate it through several simulations to prove its efficiency, competence and effectiveness.

Keywords: Sensor Networks, Data Base, Data Fusion, Aggregation, Indexing, Energy Efficiency

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Authors: Defu Zhang, Qingshan Jiang, Xin Li

Abstract:

This paper deals with the application of a well-known neural network technique, multilayer back-propagation (BP) neural network, in financial data mining. A modified neural network forecasting model is presented, and an intelligent mining system is developed. The system can forecast the buying and selling signs according to the prediction of future trends to stock market, and provide decision-making for stock investors. The simulation result of seven years to Shanghai Composite Index shows that the return achieved by this mining system is about three times as large as that achieved by the buy and hold strategy, so it is advantageous to apply neural networks to forecast financial time series, the different investors could benefit from it.

Keywords: Data mining, neural network, stock forecasting.

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Authors: Ashiquer Rahman

Abstract:

The paper focuses on the importance of the knowledge economy and society, emphasizing the significance of the triangle issues (Innovation, Sustainability, and Higher Education) for building a sustainable campus at the university level and preparing students to face the upcoming sustainability challenges in the competitive and sustainable world. Within a framework of the knowledge economy and society, the paper discusses the significance of sustainable campus, triangle issues and potential action plan for the university level. It makes mention of the emergence of a knowledge-based economy and society as well as the necessity of combining innovation, sustainability, and education to create a sustainable campus at the university level. The paper outlines nine significant issues or challenges related to a sustainable campus that have been emphasized, and cross-linked with each other. Optimistically, it will be a milestone in higher education, a pathway to meet the imminent sustainable challenges of the completive world and be able to manage the knowledge economy and societal system

Keywords: Triangle issues, sustainable campus, higher education, knowledge economy, knowledge society.

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Authors: Mohammad Akbarpour, Reza Nasiri Mahalati, Caro Lucas

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The existence of many biological systems, especially human societies, is based on cooperative behavior [1, 2]. If natural selection favors selfish individuals, then what mechanism is at work that we see so many cooperative behaviors? One answer is the effect of network structure. On a graph, cooperators can evolve by forming network bunches [2, 3, 4]. In a research, Ohtsuki et al used the idea of iterated prisoners- dilemma on a graph to model an evolutionary game. They showed that the average number of neighbors plays an important role in determining whether cooperation is the ESS of the system or not [3]. In this paper, we are going to study the dynamics of evolution of cooperation in a social network. We show that during evolution, the ratio of cooperators among individuals with fewer neighbors to cooperators among other individuals is greater than unity. The extent to which the fitness function depends on the payoff of the game determines this ratio.

Keywords: Evolution of cooperation, Iterated prisoner's dilemma, Model dynamics, Social network structure, Intensity of selection.

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Authors: H. El-Madbouly

Abstract:

In this paper, genetic algorithm (GA) is proposed for the design of an optimization algorithm to achieve the bandwidth allocation of ATM network. In Broadband ISDN, the ATM is a highbandwidth; fast packet switching and multiplexing technique. Using ATM it can be flexibly reconfigure the network and reassign the bandwidth to meet the requirements of all types of services. By dynamically routing the traffic and adjusting the bandwidth assignment, the average packet delay of the whole network can be reduced to a minimum. M/M/1 model can be used to analyze the performance.

Keywords: Bandwidth allocation, Genetic algorithm, ATMNetwork, packet delay.

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Authors: Hisashi Kojima, Masatora Daito

Abstract:

We investigate an asymmetric connections model with a dynamic network formation process, using an agent based simulation. We permit heterogeneity of agents- value. Valuable persons seem to have many links on real social networks. We focus on this point of view, and examine whether valuable agents change the structures of the terminal networks. Simulation reveals that valuable agents diversify the terminal networks. We can not find evidence that valuable agents increase the possibility that star networks survive the dynamic process. We find that valuable agents disperse the degrees of agents in each terminal network on an average.

Keywords: network formation, agent based simulation, connections model.

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Authors: Ryad Zemouri, Paul Ciprian Patic

Abstract:

An adaptive software reliability prediction model using evolutionary connectionist approach based on Recurrent Radial Basis Function architecture is proposed. Based on the currently available software failure time data, Fuzzy Min-Max algorithm is used to globally optimize the number of the k Gaussian nodes. The corresponding optimized neural network architecture is iteratively and dynamically reconfigured in real-time as new actual failure time data arrives. The performance of our proposed approach has been tested using sixteen real-time software failure data. Numerical results show that our proposed approach is robust across different software projects, and has a better performance with respect to next-steppredictability compared to existing neural network model for failure time prediction.

Keywords: Neural network, Prediction error, Recurrent RadialBasis Function Network, Reliability prediction.

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Authors: Qing Lyu, Hang Zhu

Abstract:

Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Keywords: Latency, Fast path assignment, Bottleneck link.

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Authors: Z. Nougrara

Abstract:

In this paper we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We therefore have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Keywords: Satellite image, road network, nodes.

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Authors: Weidong Xia, Malgorzata Kolotylo, Xuan Tan

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This study examines the key factors that influence general practitioners’ learning and transfer of specialized arthritis knowledge and self-care techniques to patients during normal patient visits. Drawing on the theory of planed behavior and using matched survey data collected from general practitioners before and after training sessions provided by specialized orthopedic physicians, the study suggests that the general practitioner’s intention to use and transfer learned knowledge was influenced mainly by intrinsic motivation, organizational learning culture and absorptive capacity, but was not influenced by extrinsic motivation. The results provide both theoretical and practical implications.

Keywords: Empirical study, healthcare knowledge management, patient self-care, physician knowledge transfer.

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Authors: Sultan Noman Qasem

Abstract:

This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: Radial basis function network, Hybrid learning, Multi-objective optimization, Genetic algorithm.

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: Network Intrusion Detection, Machine learning, Artificial Neural Network.

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Authors: Hamid Abdi, Abolfazl Salami, Abolfazl Ahmadi

Abstract:

Programmable logic controllers are the main controllers in the today's industries; they are used for several applications in industrial control systems and there are lots of examples exist from the PLC applications in industries especially in big companies and plants such as refineries, power plants, petrochemical companies, steel companies, and food and production companies. In the PLCs there are some functions in the function library in software that can be used in PLC programs as basic program elements. The aim of this project are introducing and implementing a new function block of a neural network to the function library of PLC. This block can be applied for some control applications or nonlinear functions calculations after it has been trained for these applications. The implemented neural network is a Perceptron neural network with three layers, three input nodes and one output node. The block can be used in manual or automatic mode. In this paper the structure of the implemented function block, the parameters and the training method of the network are presented by considering the especial method of PLC programming and its complexities. Finally the application of the new block is compared with a classic simulated block and the results are presented.

Keywords: Programmable Logic Controller, PLC Programming, Neural Networks, Perception Network, Intelligent Control.

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Authors: Mohammad Soliman, Mohamed A. Abou-Shouk

Abstract:

Knowledge management focuses on the development, storage, retrieval, and dissemination of information and expertise. It has become an important tool to improve performance in tourism enterprises. This includes improving decision-making, developing customer services, and increasing sales and profits. Knowledge management adoption depends on human, organizational and technological factors. This study aims to explore the concept of knowledge management in travel agents in Egypt. It explores the requirements of adoption and its impact on performance in these agencies. The study targets Category A travel agents in Egypt. The population of the study encompasses Category A travel agents having online presence. An online questionnaire is used to collect data from managers of travel agents. This study is useful for travel agents who are in urgent need to restructure their intermediary role and support their survival in the global travel market. The study sheds light on the requirements of adoption and the expected impact on performance. This could help travel agents identify their situation and the determine the extent to which they are ready to adopt knowledge management. This study is contributing to knowledge by providing insights from the tourism sector in a developing country where the concept of knowledge management is still in its infancy stages.

Keywords: Benefits, determinants, Egypt, knowledge management, travel agents.

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Authors: Y. Chaiko

Abstract:

It is important to provide possibility of so called “handover" for the mobile subscriber from GSM network to Wi-Fi network and back. To solve specified problem it is necessary to estimate connection time between base station and wireless access point. Difficulty to estimate this parameter is that it doesn-t described in specifications of the standard and, hence, no recommended value is given. In this paper, the analytical model is presented that allows the estimating connection time between base station and IEEE 802.11 access point.

Keywords: Access point, connection procedure, Wi-Fi network.

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Authors: Jakyoung Kim, Sungwook Jang

Abstract:

The purpose of this study is to examine the research trends of life-long education for people with disabilities using a keyword network analysis. For this purpose, 151 papers were selected from 594 papers retrieved using keywords such as 'people with disabilities' and 'life-long education' in the Korean Education and Research Information Service. The Keyword network analysis was constructed by extracting and coding the keyword used in the title of the selected papers. The frequency of the extracted keywords, the centrality of degree, and betweenness was analyzed by the keyword network. The results of the keyword network analysis are as follows. First, the main keywords that appeared frequently in the study of life-long education for people with disabilities were 'people with disabilities', 'life-long education', 'developmental disabilities', 'current situations', 'development'. The research trends of life-long education for people with disabilities are focused on the current status of the life-long education and the program development. Second, the keyword network analysis and visualization showed that the keywords with high frequency of occurrences also generally have high degree centrality and betweenness centrality. In terms of the keyword network diagram, it was confirmed that research trends of life-long education for people with disabilities are centered on six prominent keywords. Based on these results, it was discussed that life-long education for people with disabilities in the future needs to expand the subjects and the supporting areas of the life-long education, and the research needs to be further expanded into more detailed and specific areas. 

Keywords: Life-long education, people with disabilities, research trends, keyword network analysis.

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Authors: Muhammad Suryanegara, Dendi Wijayatullah, Dadang Gunawan

Abstract:

We review a knowledge extractor model in constructing 3G Killer Applications. The success of 3G is essential for Government as it became part of Telecommunications National Strategy. The 3G wireless technologies may reach larger area and increase country-s ICT penetration. In order to understand future customers needs, the operators require proper information (knowledge) lying inside. Our work approached future customers as complex system where the complex knowledge may expose regular behavior. The hidden information from 3G future customers is revealed by using fractal-based questionnaires. Afterward, further statistical analysis is used to match the results with operator-s strategic plan. The developments of 3G applications also consider its saturation time and further improvement of the application.

Keywords: 3G Killer Applications, Knowledge, Telecommunications Strategy.

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Authors: Zhang Wenbo, Tian Ye, Sun Peigen, Xu Haifeng

Abstract:

According to the mobility of the satellite network nodes and the characteristic of management domain dynamic partition in the satellite network, the login and logout mechanism of the satellite network dynamic management domain partition was proposed in the paper. In the mechanism, a ground branch-station sends the packets of login broadcasting to satellites in view. After received the packets, the SNMP agents on the satellites adopt link-delay test to respond. According to the mechanism, the SNMP primitives were extended, and the new added primitives were as follows: broadcasting, login, login confirmation,delay_testing, test responses, and logout. The definition of primitives, which followed RFC1157 criterion, could be encoded by the BER coding. The policy of the dynamic management domain partition on the basis of the login and logout mechanism, which was supported by the SNMP protocol, was realized by the design of the extended primitives.

Keywords: Satellites Network, network management, communication primitive, SNMP

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