• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1303-1315
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• 2012

In the draft of the IEEE 802.11s standard, a tree topology is established by the proactive tree-building mode of the Hybrid Wireless Mesh Protocol (HWMP). It is used for cases in which the root station (e.g., gateway) is an end point of the majority of the data connections. In the tree topology, the root or central stations (e.g., parent stations) are connected to the other stations (e.g., leaves) that are one level lower than the central station. Such mesh stations are likely to suffer heavily from contention in bottleneck links when the network has a high traffic load. Moreover, the dependence of the network on such stations is a point of vulnerability. A failure of the central station (e.g., a crash or simply going into sleep mode to save energy) can cripple the whole network in the tree topology. This causes performance degradation for end-to-end transmissions. In a connected mesh topology where the stations having two or more radio links between them are connected in such a way that if a failure subsists in any of the links, the other link could provide the redundancy to the network. We propose a scheme to utilize this characteristic by organizing the network into concentric tiers around the root mesh station. The tier structure facilitates path recovery and congestion control. The resulting mode is referred to as Tier-based Proactive Path Selection Mode (TPPSM). The performance of TPPSM is compared with the proactive tree mode of HWMP. Simulation results show that TPPSM has better performance.

• Culinary science and hospitality research
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• v.24 no.2
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• pp.1-7
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• 2018

This study aims to find what attributes of consumer satisfaction are more important when consumers choose coffee shops. Factors when customers choose coffee shops that are considered to be more crucial, such as taste, price, brand, and atmosphere, were tested and also relations between satisfaction and revisit were studied. As a result, factors as 'taste', 'price', 'brand', and 'atmosphere' were found to significantly affect satisfaction; in addition, the path that satisfaction leads to revisit was found to be significant. However, consumers' coffee shop selection attributes differed depending on their psychological consumption value. The path-coefficients from taste and price to satisfaction were more significant in the function-oriented group, meanwhile the path-coefficient from brand to satisfaction was significant in the emotion-oriented group (+) and the function-oriented group (-). The results of this study suggest attributes of selecting coffee shops and provide meaningful implications of consumer value when they choose the attributes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.87-95
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• 2013

In this paper, the outage probability of efficient partial relay selection(EPRS) using only one-hop channel information in multi-hop systems is analyzed in Rayleigh fading channels. In particular, we derive an exact and closed-form expression for the outage probability of decode-and-forward relaying based EPRS. In order to prove the usefulness of EPRS in multi-hop systems, we also analyze the correlation between the end-to-end signal-to-noise ratio(SNR) and the SNR for each hop at an arbitrary relaying path. Furthermore, through numerical investigation, we compare the outage performances for EPRS and the best relay selection using all channel information.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.187-194
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• 2019

This study examined that what attributes of student satisfaction are more important when students use university cafeterias. Factors that are considered to be more crucial when students use a cafeteria, such as menu, taste, price, and cleanliness, were tested. Based on the research of previous studies, it assumed that the selection attributes of students' cafeteria were menu, taste, price, and cleanliness. With 301 surveyed questionnaires, the study was carried out by AMOS 23.0 and the Structural Equation Model was used for examining the hypotheses as statistical method in this study. In consequence of the hypothesis test on the main effect, the factors such as the menu, taste, price and cleanliness were found to significantly affect satisfaction. Then, the moderating role of gender, age and allowance was analyzed. However, students' university cafeteria selection attributes differed depending on their allowance only. The path coefficients from menu to satisfaction were more significant in the group with a smaller allowance, while the path coefficient from price to satisfaction was more significant in the group with a larger allowance. The study analyzed that the effect of selection attribute of students' cafeteria on the satisfaction, and influence of students' allowance, and provide meaningful implications when they choose the attributes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5276-5298
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• 2019

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.103-113
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• 2011

This research is to select a path planning algorithm to maximize survivability for Unmanned Aerial Vehicle(UAV). An UAV is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are currently employed in many military missions(surveillance, reconnaissance, communication relay, targeting, strike etc.) and a number of civilian applications(communication service, broadcast service, traffic control support, monitoring, measurement etc.). In this research, a mathematical programming model is suggested by using MRPP(Most Reliable Path Problem) and verified by using ILOG CPLEX. A path planning algorithm for UAV is selected by comparing of SPP(Shortest Path Problem) algorithms which transfer MRPP into SPP.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.31-40
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• 2011

Sensor nodes are easily exposed to malicious attackers by physical attacks. The attacker can generate various attacks using compromised nodes in a sensor network. The false report generating application layers injects the network by the compromised node. If a base station has the injected false report, a false alarm also occurs and unnecessary energy of the node is used. In order to defend the attack, a statistical en-route filtering method is proposed to filter the false report that goes to the base station as soon as possible. A path renewal method, which improves the method, is proposed to maintain a detection ability of the statistical en-route filtering method and to consume balanced energy of the node. In this paper, we proposed the secure path cycle method to consume effective energy for a path renewal. To select the secure path cycle, the base station determines through hop counts and the quantity of report transmission by an evaluation function. In addition, three methods, which are statistical en-route filter, path selection method, and path renewal method, are evaluated with our proposed method for efficient energy use. Therefore, the proposed method keeps the secure path and makes the efficiency of energy consumption high.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.69-78
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• 2011

A large-scale sensor network usually operates in open and unattended environments, hence individual sensor node is vulnerable to various attacks. Therefore, malicious attackers can physically capture sensor nodes and inject false reports into the network easily through compromised nodes. These false reports are forwarded to the base station. The false report injection attack causes not only false alarms, but also the depletion of the restricted energy resources in a battery powered network. The statistical en-route filtering (SEF) mechanism was proposed to detect and drop false reports en route. In SEF, the choice of routing paths largely affect the energy consumption rate and the detecting power of the false report. To sustain the secure routing path, when and how to execute the path re-selection is greatly need by reason of the frequent network topology change and the nodes's limitations. In this paper, the regional path re-selection period determination method is proposed for efficient usage of the limited energy resource. A fuzzy logic system is exploited in order to dynamically determine the path re-selection period and compose the routing path. The simulation results show that up to 50% of the energy is saved by applying the proposed method.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.879-888
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• 2013

This paper addresses the vision based local path planning system for obstacle avoidance. To handle the obstacles which exist beyond the field of view (FOV), we propose a Panoramic Environment Map (PEM) using the MDGHM-SIFT algorithm. Moreover, we propose a Complexity Measure (CM) and Fuzzy logic-based Avoidance Motion Selection (FAMS) system to enable a humanoid robot to automatically decide its own direction and walking motion when avoiding an obstacle. The CM provides automation in deciding the direction of avoidance, whereas the FAMS system chooses the avoidance path and walking motion, based on environment conditions such as the size of the obstacle and the available space around it. The proposed system was applied to a humanoid robot that we designed. The results of the experiment show that the proposed method can be effectively applied to decide the avoidance direction and the walking motion of a humanoid robot.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.28-41
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• 1994

An efficient algorithm is proposed to select the proper tools and generate their paths for NC rough cutting of dies and molds with sculptured surfaces. Even though a milling process consists of roughing, semi-finishing, and finishing, most material is removed by a rough cutting process. Therfore it can be said that the rough cutting process occupy an important portion of the NC milling process, and accordingly, an efficient rough cutting method contributes to an efficient milling process. In order work, the following basic assumption is accepted for the efficient machining. That is, to machine a region bounded by a profile, larger tools should be used in the far inside and the region adjacent to relatively simple portion of the boundary while smaller tools are used in the regions adjacent to the relatively complex protion. Thus the tools are selected based on the complexity of the boundary profile adjacent to the region to be machined. An index called cutting path ratio is proposed in this work as a measure of the relative complexity of the profile with respect to a tool diameter. Once the tools are selected, their tool paths are calculated starting from the largest to the smallest tool.