• Asia pacific journal of information systems
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• v.22 no.1
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• pp.1-27
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• 2012

Asynchronous Learning Networks (ALN) has become a kind of prevalent information systems to supplement or even substitute a traditional classroom face-to-face teaching method. In this paper, we investigate the impacts of types of courses, lecturers' instruction models and computer self-efficacy on the ALN effectiveness in teaching from lecturers' perspective. We conducted survey to professors in various faculties such as School of Computing, Faculty of Arts, Science, Business, Law and Engineering in the National University of Singapore. According to the responses from ninety-eight professors, instruction modes positively influence the usage of ALN; types of course and lecturers' computer-efficacy influence lectures' satisfaction of ALN in teaching. Both the usage of ALN and satisfaction of ALN positively influence the effectiveness of ALN. The results of this study fill the gap of ALN researches in education by examining it from lecturers' perspective and enable schools to improve their implementation of ALN systems based on our findings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4644-4661
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• 2015

Wireless sensor networks are often organized in the form of clusters leading to the new framework of WSN called cluster or hierarchical WSN where each cluster head is responsible for its own cluster and its members. These hierarchical WSN are prone to various routing layer attacks such as Black hole, Gray hole, Sybil, Wormhole, Flooding etc. These routing layer attacks try to spoof, falsify or drop the packets during the packet routing process. They may even flood the network with unwanted data packets. If one cluster head is captured and made malicious, the entire cluster member nodes beneath the cluster get affected. On the other hand if the cluster member nodes are malicious, due to the broadcast wireless communication between all the source nodes it can disrupt the entire cluster functions. Thereby a scheme which can detect both the malicious cluster member and cluster head is the current need. Abnormal energy consumption of nodes is used to identify the malicious activity. To serve this purpose a learning based energy prediction algorithm is proposed. Thus a two level energy prediction based intrusion detection scheme to detect the malicious cluster head and cluster member is proposed and simulations were carried out using NS2-Mannasim framework. Simulation results achieved good detection ratio and less false positive.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.195-200
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• 2002

ART (Adaptive Resonance Theory [1]) neural network and its variations perform non-hierarchical clustering by unsupervised learning. We propose a scheme "arboART" for hierarchical clustering by using several ART1.5-SSS networks. It classifies multidimensional vectors as a cluster tree, and finds features of clusters. The Basic idea of arboART is to use the prototype formed in an ART network as an input to other ART network that has looser distance criteria (Ishihara, et al., [2,3]). By sending prototype vectors made by ART to one after another, many small categories are combined into larger and more generalized categories. We can draw a dendrogram using classification records of sample and categories. We have confirmed its ability using standard test data commonly used in pattern recognition community. The clustering result is better than traditional computing methods, on separation of outliers, smaller error (diameter) of clusters and causes no chaining. This methodology is applied to Kansei evaluation experiment data analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5455-5475
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• 2016

In this article, we model the distributed relay assignment network as a many-to-one matching market with peer effects. We discuss two scenarios for throughput optimization of relay networks: the scenario of aggregate throughput optimization and the scenario of fairness performance optimization. For the first scenario, we propose a Mutual Benefit-based Deferred Acceptance (MBDA) algorithm to increase the aggregate network throughput. For the second scenario, instead of using the alternative matching scheme, a non-substitution matching algorithm (NSA) is designed to solve the fairness problem. The NSA improves the fairness performance. We prove that both two algorithms converge to a globally stable matching, and discuss the practical implementation. Simulation results show that the performance of MBDA algorithm outperforms existing schemes and is almost the same with the optimal solution in terms of aggregate throughput. Meanwhile, the proposed NSA improves fairness as the scale of the relay network expands.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.901-923
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• 2017

Efficient key distribution and management mechanisms as well as lightweight ciphers are the main pillar for establishing secure wireless sensor networks (WSN). Several symmetric based key distribution protocols are already proposed, but most of them are not scalable, yet vulnerable to a small number of compromised nodes. In this paper, we propose an efficient and scalable key management and distribution framework, named KMMR, for large scale WSNs. The KMMR contributions are three fold. First, it performs lightweight local processes orchestrated into upward and downward tiers. Second, it limits the impact of compromised nodes to only local links. Third, KMMR performs efficient secure node addition and revocation. The security analysis shows that KMMR withstands several known attacks. We implemented KMMR using the NesC language and experimented on Telosb motes. Performance evaluation using the TOSSIM simulator shows that KMMR is scalable, provides an excellent key connectivity and allows a good resilience, yet it ensures both forward and backward secrecy. For a WSN comprising 961 sensor nodes monitoring a 60 hectares agriculture field, KMMR requires around 2.5 seconds to distribute all necessary keys, and attains a key connectivity above 96% and a resilience approaching 100%. Quantitative comparisons to earlier work show that KMMR is more efficient in terms of computational complexity, required storage space and communication overhead.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2087-2092
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• 2011

In this paper, we use the earth's magnetic field is measured by the MR device. By analyzing the measured data to determine the direction to implement the system. The construction of the system to determine the direction of neural networks, using input data based on an analysis of the relationship between pattern formation and characteristics of study and related information through a pattern when it is remembered that the output feedback input to associative networks and proves its feasibility for implementation. The entire detection system with regional changes in the Earth's magnetic field to adapt to the environment should aim to build a system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.29-37
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• 2008

Clustering allows hierarchical structures to be built on the nodes and enables more efficient use of scarce resources, such as frequency spectrum, bandwidth, and energy in wireless sensor networks (WSNs). This paper proposes a hierarchical clustering algorithm called EEHC which is more energy efficient than existing algorithms for WSNs, It introduces region node selection as well as cluster head election based on the residual battery capacity of nodes to reduce the costs of managing sensor nodes and of the communication among them. The role of cluster heads or region nodes is rotated among nodes to achieve load balancing and extend the lifetime of every individual sensor node. To do this, EEHC clusters periodically to select cluster heads that are richer in residual energy level, compared to the other nodes, according to clustering policies from administrators. To prove the performance improvement of EEHC, the ns-2 simulator was used. The results show that it can reduce the energy and bandwidth consumption for organizing and managing WSNs comparing it with existing algorithms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.99-109
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• 2020

In the past, conservative concepts have been applied in terms of the characteristic of nuclear power plants(NPPs), resulting in analog-based equipment and closed networks. However, as digital technology has recently been applied to the design, digital-based facilities and communication networks have been used in nuclear power plants, increasing the risk of cybersecurity than using analog-based facilities. Nuclear power plant facilities are divided into a safety system and a non-safety system. It is essential to identify the difference and cope with cybersecurity threats to the safety system according to its characteristics. In this paper, we examine the cybersecurity regulatory guidelines for safety systems in nuclear power plant facilities. Also, we analyze cybersecurity threats to a programmable logic controller of the safety system and suggest cybersecurity requirements be applied to it to respond to the threats. By implementing security functions suitable for the programmable logic controller according to the suggested cybersecurity requirements, regulatory guidelines can be satisfied, and security functions can be extended according to other system requirements. Also, it can effectively cope with cybersecurity attacks that may occur during the operation of nuclear power plants.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.479-491
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• 2008

A "task network" is a type of social network that consists of experts who exchange professional help and advice regarding executing tasks. In this study, we investigate the task network used within the IS department of a national bank in Korea. We identify how this network moderates the influence of computer-mediated communication (CMC) technology on an individual s task performance. Size, density, and centrality were measured as the characteristics of a personal task networks. Size equates to the total number of colleagues who work with a specific member for a certain project. Density is the ratio of the number of actual relationships to the total number of available relationships. Centrality defines whether an individual s position is in the exact center of whole network, and is measured by betweenness centrality, meaning the position one member holds between others in a network. Our findings conclude that the conditions - the larger the size of the task network, the smaller its density and the higher its level of centrality - lead to more benefits of using CMC media. Further, this positive effect of CMC is more noticeable when it provides synchronicity.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.121-129
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• 2014

The trend of an increasing demand for a high-quality user experience, coupled with a shortage of radio resources, has necessitated more advanced wireless techniques to cooperatively achieve the required quality-of-experience enhancement. In this study, we investigate the critical problem of rate splitting in heterogeneous cellular networks, where concurrent transmission, for instance, the coordinated multipoint transmission and reception of LTE-A systems, shows promise for improvement of network-wide capacity and the user experience. Unlike most current studies, which only deal with spectral efficiency enhancement, we implement an optimal rate splitting strategy to improve both spectral efficiency and energy efficiency by exploring and exploiting cooperation diversity. First, we introduce the motivation for our proposed algorithm, and then employ the typical cooperative bargaining game to formulate the problem. Next, we derive the best response function by analyzing the dual problem of the defined primal problem. The existence and uniqueness of the proposed cooperative bargaining equilibrium are proved, and more importantly, a distributed algorithm is designed to approach the optimal unique solution under mild conditions. Finally, numerical results show a performance improvement for our proposed distributed cooperative rate splitting algorithm.