• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.61-69
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• 2012

Smart Grid is the next-generation intelligent power grid that maximizes energy efficiency with the convergence of IT technologies and the existing power grid. Smart Grid is created solution for standardization and interoperability. Smart Grid industry enables consumers to check power rates in real time for active power consumption. It also enables suppliers to measure their expected power generation load, which stabilizes the operation of the power system. Smart industy was ecolved actively cause Wireless communication is being considered for AMI system and wireless communication using ZigBee sensor has been applied in various industly. In this paper, we proposed efficient addressing scheme for improving the performance of the routing algorithm using ZigBee in Smart Grid environment. A distributed address allocation scheme used an existing algorithm has wasted address space. Therefore proposing x, y coordinate axes from divide address space of 16 bit to solve this problem. Each node was reduced not only bitwise but also multi hop using the coordinate axes while routing than Cskip algorithm. I compared the performance between the standard and the proposed mechanism through the numerical analysis. Simulation verify performance about decrease averaging multi hop count that compare proposing algorithm and another. The numerical analysis results show that proposed algorithm reduce multi hop than ZigBee distributed address assignment and another.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.106-115
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• 2003

Diverse multimedia services will be deployed at hand on 3G-and-beyond multi-service CDMA systems in order to satisfy different quality of service (QoS) according to traffic types. In order to use appropriate resources efficiently the call admission control (CAC) as a major resource control mechanism needs to be used to take care of efficient utilization of limited resources. In this paper, we propose a QoS-aware CAC (QCAC) that is enabled to provide service fairness and service differentiation in accordance with priority order and that applies the different thresholds in received power considering different QoS requirements such as different bit error rates (BER) when adopting total received power as the ceil load estimation. The proposed QCAC calculates the different thresholds of the different traffic types based on different required BER applies it for admission policy, and can get service fairness and differentiation in terms of call dropping probability as a main performance metric. The QCAC is aware of the QoS requirement per traffic type and allows admission discrimination according to traffic types in order to minimize the probability of QoS violation. Also the CAC needs to consider the resource allocation schemes such as complete sharing (CS), complete partitioning (CP), and priority sharing(PS) in order to provide fairness and service differentiation among traffic types. Among them, PS is closely related with the proposed QCAC having differently calculated threshold per each traffic type according to traffic priority orders.

• The Journal of Bigdata
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• v.4 no.2
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• pp.159-173
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• 2019

Last-Mile delivery optimization plays a key role in the urban supply chain operation, which is the most expensive and time-consuming and most complicated part of the whole delivery process. The urban consolidation center (UCC) is regarded as a significant asset for supporting customer demand in the last-mile delivery service. It is the key benefit of UCC to improve the load balance of vehicles and to reduce the total traveling distance by finding the better route with the well-organized multi-leg vehicle journey in the urban area. This paper presents the model using multiple scenario analysis integrated with mathematical optimization techniques using Geographic Information System (GIS). The model aims to find the best solution for the distribution network consisted of DC and UCC, which is applied to the case of Ulaanbaatar Mongolia. The proposed methodology integrates two sub-models, location-allocation model and vehicle routing problem. The multiple scenarios devised by selecting locations of UCC are compared considering the general performance and delivery patterns together. It has been adopted to make better decisions the quantitative metrics such as the economic value of capital cost, operating cost, and balance of using available resources. The result of this research may help the manager or public authorities who should design the distribution network for the last mile delivery service optimization using UCC within the urban area.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.822-822
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• 2012

본 연구는 상류의 개발행위와 더불어 현재 수질관리의 기준이 되는 오염총량관리제를 대상으로 '규모의 경제'의 논리를 따른다는 가정 하에, 지자체간에 협조를 통해 비용을 절감하여 서로 혜택을 볼 수 있도록 상 하류 지자체와 중앙정부 등 관련 당사자들 간의 비용배분 방안을 도출하는 것을 목적으로 하였다. 이를 위해서 광주광역시에 위치한 평동산업단지와 영본B, 영본C를 대상으로 광주, 전남, 중앙정부를 이해당사자로 하여 협조적 상황 하에서 대상 비용배분 문제를 정의하였고, 협조적 게임이론에 근거한 SCRB법 및 샤플리법을 적용하여 비용배분 결과를 제시하였다. 우선 광주와 전남이 각각 삭감해야 할 오염량을 산정하고, 해당 삭감량 만큼 처리하기 위한 하수처리시설의 규모를 설정하였다. 또한 하수처리시설의 건설비와 하수관거 공사비, 유지관리비를 산정하였으며, 하수처리시설의 내용연수인 20년간의 총비용을 2010년 현재가치 기준으로 산정하였다. 상 하류 지자체가 공동으로 대처할 경우 20년간 총비용은 416,311.8 백만원, 개별로 대처할 경우 464,439.6 백만원이며, 공동 대처가 42,359.3 백만원이 절감되므로 양 지자체 모두 협조적 게임에 응할 기본배경은 성립되었다. SCRB법에 의한 지자체별 비용배분율을 산정 결과, 광주 74.24%, 전남 25.76%로 산정되었으며, 2001～2010년 하수도 세입현황을 기준으로 중앙정부의 지원 비율은 10년간 최소 23.98%, 평균 29.22%, 최대 34.17%로, 각각의 비율별로 중앙정부, 광주, 전남의 비용분담액을 도출하였다. 본 논문에서는 개략적으로 비용을 산정하였으나 오염총량관리 사업은 막대한 예산을 필요로 하기 때문에 실제로 두 지자체가 협조하여 비용배분을 하게 된다면 하수처리시설의 수질개선효과, 하수처리시설 위치선정, 사업비용 등을 세밀하게 분석해야 할 것이다. 본 논문은 오염총량관리제에서 제시하는 목표수질을 대상으로 하였으나, 지자체의 정책에 따라 친수활동 증대와 생태 자연환경 개선 등과 같은 수질개선에 따른 간접적인 효과를 고려하여 오염 총량관리제의 목표수질보다 더 나은 수질을 원할 수도 있을 것이다. 협조적 게임의 상황을 복잡하게 하여 해결 가능성이 낮아질 수 있으나, 수질개선에 의한 다양한 효과를 편익으로 산정할 수 있다면 이를 협조적 게임에 적용하여 전반적인 수질개선에 대한 지자체의 적극적 활동을 유도할 수도 있을 것이다.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.35-52
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• 2019

As public services are provided in various forms, including e-government, the level of public demand for public service quality is increasing. Although continuous measurement and improvement of the quality of public services is needed to improve the quality of public services, traditional surveys are costly and time-consuming and have limitations. Therefore, there is a need for an analytical technique that can measure the quality of public services quickly and accurately at any time based on the data generated from public services. In this study, we analyzed the quality of public services based on data using process mining techniques for civil licensing services in N city. It is because the N city's building license complaint service can secure data necessary for analysis and can be spread to other institutions through public service quality management. This study conducted process mining on a total of 3678 building license complaint services in N city for two years from January 2014, and identified process maps and departments with high frequency and long processing time. According to the analysis results, there was a case where a department was crowded or relatively few at a certain point in time. In addition, there was a reasonable doubt that the increase in the number of complaints would increase the time required to complete the complaints. According to the analysis results, the time required to complete the complaint was varied from the same day to a year and 146 days. The cumulative frequency of the top four departments of the Sewage Treatment Division, the Waterworks Division, the Urban Design Division, and the Green Growth Division exceeded 50% and the cumulative frequency of the top nine departments exceeded 70%. Higher departments were limited and there was a great deal of unbalanced load among departments. Most complaint services have a variety of different patterns of processes. Research shows that the number of 'complementary' decisions has the greatest impact on the length of a complaint. This is interpreted as a lengthy period until the completion of the entire complaint is required because the 'complement' decision requires a physical period in which the complainant supplements and submits the documents again. In order to solve these problems, it is possible to drastically reduce the overall processing time of the complaints by preparing thoroughly before the filing of the complaints or in the preparation of the complaints, or the 'complementary' decision of other complaints. By clarifying and disclosing the cause and solution of one of the important data in the system, it helps the complainant to prepare in advance and convinces that the documents prepared by the public information will be passed. The transparency of complaints can be sufficiently predictable. Documents prepared by pre-disclosed information are likely to be processed without problems, which not only shortens the processing period but also improves work efficiency by eliminating the need for renegotiation or multiple tasks from the point of view of the processor. The results of this study can be used to find departments with high burdens of civil complaints at certain points of time and to flexibly manage the workforce allocation between departments. In addition, as a result of analyzing the pattern of the departments participating in the consultation by the characteristics of the complaints, it is possible to use it for automation or recommendation when requesting the consultation department. In addition, by using various data generated during the complaint process and using machine learning techniques, the pattern of the complaint process can be found. It can be used for automation / intelligence of civil complaint processing by making this algorithm and applying it to the system. This study is expected to be used to suggest future public service quality improvement through process mining analysis on civil service.