• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.25-36
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• 2016

The goal of the SmartGrid is to maximize energy efficiency by exchanging bi-directional real-time power information with the help of ICT(Information and Communication Technology). In this paper, we propose a "JRS-MS" (Joint Routing and Scheduling for Multi-channel SmartGrid) algorithm that uses numerical modeling methods in IEEE 802.11s based STDMA multi-channel SmartGrid NAN networks. The proposed algorithm controls the amount of data transmission adaptively at the link layer and finds a high data-rate path which has the least interference between traffic flows in multi-channel SmartGrid NAN networks. The proposed algorithm improve transmission performance by enhancing network utilization. By comparing the results of performance analysis between the proposed algorithm and the JRS-SG algorithm in the previous paper, we showed that the JRS-MS algorithm can improve transmission performance by maximally utilizing given network resources when the number of flows are increasing in the multi-hop NAN wireless mesh networks.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.1-14
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• 2000

The berth and crane scheduling problem in a container terminal encompasses the whole process of assigning berth to each ship, determining the duration of berthing, assigning container cranes to each ship, and determining the specific start and end time of each crane service, for all the ships scheduled to be arriving at the terminal during a certain scheduling horizon. This problem is basically a constraint satisfaction problem in which cranes and berths should be assigned in such a way that all the spatial and temporal constraints are satisfied without any interference. However, it is also an optimization problem because the requested arrival and departure time should be met for as many of the scheduled ships as possible, while the operation cost of the terminal should be minimized. In this paper, we present an effective and efficient approach to solving this type of problem, which combines constrain satisfaction search and heuristic repair. We first employ a constraint satisfaction search to find a feasib1e solution. Then, the feasible solution is modified to a more optimal one by iteratively applying our heuristic repair operations within the framework of constraint satisfaction search. Experimental results with a real data from Pusan East Container Terminal showed that our approach can derive a schedule of satisfactory quality in a very short time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.778-798
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• 2014

This paper proposes a novel exposed-terminal-eliminated medium access control (ETE-MAC) protocol by combining channel reservation, collision avoidance and concurrent transmissions to improve multi-access performance of the multihop wireless networks. Based on the proposed slot scheduling scheme, each node senses the control channel (CCH) or the data channel (DCH) to accurately determine whether it can send or receive the corresponding packets without collisions. Slot reservation on the CCH can be simultaneously executed with data packet transmissions on the DCH. Therefore, it resolves the hidden-terminal type and the exposed-terminal type problems efficiently, and obtains more spatial reuse of channel resources. Concurrent packet transmissions without extra network overheads are maximized. An analytical model combining Markov model and M/G/1 queuing theory is proposed to analyze its performance. The performance comparison between analysis and simulation shows that the analytical model is highly accurate. Finally, simulation results show that, the proposed protocol obviously outperforms the link-directionality-based dual-channel MAC protocol (DCP) and WiFlex in terms of the network throughput and the average packet delay.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.231-242
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• 2007

The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.83-97
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• 2015

IEEE 802.15.4 is a global standard designed for emerging applications in low-rate wireless personal area networks (LR-WPANs). The standard provides beneficial features, such as a beacon-enabled mode and guaranteed time slots for realtime data delivery. However, how to optimally operate those features is still an open issue. For the optimal operation of the features, this paper proposes a holistic optimization method that jointly optimizes three cross-related problems: cluster-tree construction, nodes' power configuration, and duty-cycle scheduling. Our holistic optimization method provides a solution for those problems so that all the real-time packets can be delivered within their deadlines in the most energy-efficient way. Our simulation study shows that compared to existing methods, our holistic optimization can guarantee the on-time delivery of all real-time packets while significantly saving energy, consequently, significantly increasing the lifetime of the network. Furthermore, we show that our holistic optimization can be extended to take advantage of the spatial reuse of a radio frequency resource among long distance nodes and, hence, significantly increase the entire network capacity.

• Journal of Computing Science and Engineering
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• v.7 no.1
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• pp.53-66
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• 2013

Bounding the worst-case DRAM performance for a real-time application is a challenging problem that is critical for computing worst-case execution time (WCET), especially for multicore processors, where the DRAM memory is usually shared by all of the cores. Typically, DRAM commands from consecutive DRAM accesses can be pipelined on DRAM devices according to the spatial locality of the data fetched by them. By considering the effect of DRAM command pipelining, we propose a basic approach to bounding the worst-case DRAM performance. An enhanced approach is proposed to reduce the overestimation from the invalid DRAM access sequences by checking the timing order of the co-running applications on a dual-core processor. Compared with the conservative approach, which assumes that no DRAM command pipelining exists, our experimental results show that the basic approach can bound the WCET more tightly, by 15.73% on average. The experimental results also indicate that the enhanced approach can further improve the tightness of WCET by 4.23% on average as compared to the basic approach.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.113-122
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• 2009

Since the traditional pattern mining methods only probe unspecified moving patterns that seem to satisfy users' requests among diverse patterns within the limited scopes of time and space, they are not applicable to problems involving the mining of optimal moving patterns, which contain complex time and space constraints, such as 1) searching the optimal path between two specific points, and 2) scheduling a path within the specified time. Therefore, in this paper, we illustrate some problems on mining the optimal moving patterns with complex time and space constraints from a vast set of historical data of numerous moving objects, and suggest a new moving pattern mining method that can be used to search patterns of an optimal moving path as a location-based service. The proposed method, which determines the optimal path(most frequently used path) using pattern frequency retrieved from historical data of moving objects between two specific points, can efficiently carry out pattern mining tasks using by space generalization at the minimum level on the moving object's location attribute in consideration of topological relationship between the object's location and spatial scope. Testing the efficiency of this algorithm was done by comparing the operation processing time with Dijkstra algorithm and $A^*$ algorithm which are generally used for searching the optimal path. As a result, although there were some differences according to heuristic weight on $A^*$ algorithm, it showed that the proposed method is more efficient than the other methods mentioned.

• Research in Plant Disease
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• v.8 no.2
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• pp.84-91
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• 2002

Disease forecasting in Korea was first studied in the Department of Fundamental Research, in the Central Agricultural Technology Institute in Suwon in 1947, where the dispersal of air-borne conidia of blast and brown spot pathogens in rice was examined. Disease forecasting system in Korea is operated based on information obtained from 200 main forecasting plots scattered around country (rice 150, economic crops 50) and 1,403 supplementary observational plots (rice 1,050, others 353) maintained by Korean government. Total number of target crops and diseases in both forecasting plots amount to 30 crops and 104 diseases. Disease development in the forecasting plots is examined by two extension agents specialized in disease forecasting, working in the national Agricul-tural Technology Service Center(ATSC) founded in each city and prefecture. The data obtained by the extension agents are transferred to a central organization, Rural Development Administration (RDA) through an internet-web system for analysis in a nation-wide forecasting program, and forwarded far the Central Forecasting Council consisted of 12 members from administration, university, research institution, meteorology station, and mass media to discuss present situation of disease development and subsequent progress. The council issues a forecasting information message, as a result of analysis, that is announced in public via mass media to 245 agencies including ATSC, who informs to local administration, the related agencies and farmers for implementation of disease control activity. However, in future successful performance of plant disease forecasting system is thought to be securing of excellent extension agents specialized in disease forecasting, elevation of their forecasting ability through continuous trainings, and furnishing of prominent forecasting equipments. Researches in plant disease forecasting in Korea have been concentrated on rice blast, where much information is available, but are substan-tially limited in other diseases. Most of the forecasting researches failed to achieve the continuity of researches on specialized topic, ignoring steady improvement towards practical use. Since disease forecasting loses its value without practicality, more efforts are needed to improve the practicality of the forecasting method in both spatial and temporal aspects. Since significance of disease forecasting is directly related to economic profit, further fore-casting researches should be planned and propelled in relation to fungicide spray scheduling or decision-making of control activities.