• 전자공학회논문지 IE
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• v.48 no.3
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• pp.26-32
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• 2011

This paper proposed that the method be searched for optimal route of evacuation by algorithm using potential field in specific situation, fire. When robot met an obstacle to be indicated it to ignition point, the installed sensor could be detected the point in restricted area. In according as the data of a fire detection sensor and a sensor complex in a building, the information was transmitted to server which computed optimal route of evacuation by algorithm using potential field. After that, it was able to blow a siren and mark the safe-path with using wireless device such as smart-phone. It was confirmed that the proposed method in functional test, fire emergency evacuation algorithm using potential field, was advanced in circumstance of simulation.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.120-124
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• 2017

This paper describes the product of search and rescue system with dynamic model. This spread spectrum system based new standard of COSPAS-SARSAT is results of RF signal generation and transmission. we will test performance evaluation which implement signal process adapting Dynamic model and we will adapt the CAF model using TDOA and FDOA relationship.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.82-96
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• 2020

The Demand Responsive Transit (DRT) system is the flexible public transport service that determines the route and schedule of the service vehicles according to users' requests. With increasing importance of public transport systems in urban areas, the development of stable and fast routing algorithms for DRT has become the goal of many researches over the past decades. In this study, a new heuristic method is proposed to generate fast and efficient routes for multiple vehicles using demand clustering and destination demand priority searching method considering the imbalance of users' origin and destination demands. The proposed algorithm is tested in various demand distribution scenarios including random, concentration and directed cases. The result shows that the proposed method reduce the drop of service ratio due to an increase in demand density and save computation time compared to other algorithms. In addition, compared to other clustering-based algorithms, the walking cost of the passengers is significantly reduced, but the detour time and in-vehicle travel time of the passenger is increased due to the detour burden.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.409-415
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• 2009

The head-related transfer function (HRTF), which has an important role in virtual sound localization has different characteristics across the subjects. Measuring HRTF is very time-consuming and requires a set of specific apparatus. Accordingly, HRTF customization is often employed. In this paper, we propose a method to search an adequate HRTF from a set of the HRTFs. To achieve rapid and reliable customization of HRTF, all HRTFs in the database are partitioned, where a binary search tree was employed. The distortion measurement adopted in HRTF partitioning was determined in a heuristic way, which predicts the differences in perceived sound location well. The DC-Davis CIPIC HRTF database set was used to evaluate the effectiveness of the proposed method. In the listening test, where 10 subjects were participated, the stimuli filtered by the HRTF obtained by the proposed method were closer to those by the personalized HRTF in terms of sound localization. Moreover, performance of the proposed method was shown to be superior to the previous customization method, where the HRFT is selected by using anthropometric data.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.669-680
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• 2001

Genetic Algorithms are optimization algorithm that mimics biological evolution to solve optimization problems. Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex fitness landscapes. Hybrid genetic algorithm that is combined with local search called learning can sustain the balance between exploration and exploitation. The genetic traits that each individual in the population learns through evolution are transferred back to the next generation, and when this learning is combined with genetic algorithm we can expect the improvement of the search speed. This paper proposes a genetic algorithm based Cellular Learning with accelerated learning capability for function optimization. Proposed Cellular Learning strategy is based on periodic and convergent behaviors in cellular automata, and on the theory of transmitting to offspring the knowledge and experience that organisms acquire in their lifetime. We compared the search efficiency of Cellular Learning strategy with those of Lamarckian and Baldwin Effect in hybrid genetic algorithm. We showed that the local improvement by cellular learning could enhance the global performance higher by evaluating their performance through the experiment of various test bed functions and also showed that proposed learning strategy could find out the better global optima than conventional method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.919-928
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• 2018

Out-Of-Bounds (OOB) is one of the most powerful vulnerabilities in heap memory. The OOB vulnerability allows an attacker to exploit unauthorized access to confidential information by tricking the length of the array and reading or writing memory of that length. In this paper, we propose a method to automatically detect OOB vulnerabilities in heap memory using dynamic symbol execution and shadow memory table. First, a shadow memory table is constructed by hooking heap memory allocation and release function. Then, when a memory access occurs, it is judged whether OOB can occur by referencing the shadow memory, and a test case for causing a crash is automatically generated if there is a possibility of occurrence. Using the proposed method, if a weak block search is successful, it is possible to generate a test case that induces an OOB. In addition, unlike traditional dynamic symbol execution, exploitation of vulnerabilities is possible without setting clear target points.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.195-202
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• 1999

본 논문은 배전 계통에서 부하 제약조건과 운전 제약조건을 고려한 손실 감소와 부하 평형에 대해 시뮬레이티드 어닐링 알고리즘을 적용한 재구성 방법을 서술하였다. 네트워크 재구성은 수많은 연계 개폐기와 구분 개폐기의 조합에 의해 이루어지기 때문에 조합적인 최적화 문제이다. 이러한 문제는 수많은 조합에 제약조건까지 있어 해를 구하기가 쉽지 않을 뿐 아니라 국소 해에 빠질 가능성이 많다. 따라서 신경망 중에서 제약조건에 따라 신경망 구조에 영향을 미치지 않으면서 전역 최소해에 수렴하는 특성을 가진 시뮬레이티드 어닐링 기법을 이용하여 배전 계통의 선로를 재구성하였다. 시뮬레이티드 어닐링은 이론적으로 최적해가 보장되지만 무한대의 시간이 걸리기 때문에 현실적으로 적용할 때 해 공간을 탐색하는 규칙과 온도를 적절히 내리는 냉각 스케줄(cooling schedule)이 중요하다. 본 논문에서는 알고리즘 상에서 제약조건 위반 여부를 점검할 수 있는 제약조건과 페널티 상수(penalty factor)를 통해 목적함수에 반영하는 제약조건으로 나누어 모든 후보해를 가능해가 되게 하였고 기존에 사용되던 Kirkpatrick의 냉각 스케줄 대신에 후보해의 통계적 처리에 의해 온도를 내리는 다항-시간 냉각 스케줄(polynomial-time cooling schedule)을 사용하여 수행시간을 단축하고 수렴성을 높였다. 제안한 알고리즘의 효용성을 입증하기 위해 32, 69모선 예제 계통으로 테스트하였다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.195-202
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• 1999

본 논문은 배전 계통에서 부하 제약조건과 운전 제약조건을 고려한 손실 감소와 부하 평형에 대해 시뮬레이티드 어닐링 알고리즘을 적용한 재구성 방법을 서술하였다. 네트워크 재구성은 수많은 연계 개폐기와 구분 계폐기의 조합에 의해 이루어지기 때문에 조합적인 최적화 문제이다. 이러한 문제는 수많은 조합에 제약조건까지 있어 해를 구하기가 쉽지 않을뿐 아니라 국소 해에 빠질 가능성이 많다. 따라서 신경망 중에서 제약조건에 따라 신경망 구조에 영향을 미치지 않으면서 전역 최소해에 수렴하는 특성을 가진 시뮬레이티드 어닐링 기법을 이용하여 배전 계통의 선로를 재구성하였다. 시뮬레이티드 어닐링은 이론적으로 최적해가 보장되지만 무한대의 시간이 걸리기 때문에 현실적으로 적용할 때 해 공간을 탐색하는 규칙과 온도를 적절히 내리는 냉각 스케줄(cooling schedule)이 중요하다. 본 논문에서는 알고리즘 상에서 제약조건 위한 여부를 점검할 수 있는 제약조건과 페널티 상수(penalty factor)를 통해 목적함수에 반영하는 제약조건으로 나누어 모든 후보해를 가능해가 되게 하였고 기존에 사용되는 Kirkpatrick의 냉각 스케줄 대신에 후보해의 통계적 처리에 의해 온도를 내리는 다항-시간 냉각 스케줄(polynomial-time schedule)을 사용하여 수행시간을 단축하고 수렴성을 높였다. 제안한 알고리즘의 효용성을 입증하기 위해 32,69모선 예제 계통으로 테스트하였다.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.58-71
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• 2002

Generally, multi-dimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amount of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel high-dimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-n$\times$mD(disk) architecture which is the hybrid type of nP-nD and lP-nD. Its node structure increases fan-out and reduces the height of a index tree. Also, A range search algorithm that maximizes I/O parallelism is devised, and it is applied to K-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• Journal of the Korean School Mathematics Society
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• v.20 no.4
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• pp.465-494
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• 2017

Teachers' conceptions about teaching are important driving and also interfering forces which might affect their actual practice and training. This research explores preservice mathematics teachers' conceptions of teacher discourse, through tasks analyzing and evaluating teachers' moment-to-moment discourse moves which occur in authoritative and dialogical classroom discourse. Some facets of the preservice teachers' conceptions were congruent with dialogical discourse: they criticized teacher's one-way communication and ignoring students' voices; they supported teacher's questions probing students' thinking and receptive attitude to ward students' wrong answers. However, some deep and subtle facets of their conceptions were more congruent with authoritative discourse rather than dialogical discourse: they positively perceived teacher's closed, information seeking questions that funnel students' thinking to the predetermined procedure; they emotionally resisted teacher's questions which might facilitate dialogical engagement by allowing students to judge mathematical correctness of ideas from their peers. Preservice teachers' conceptions of teacher discourse explored in this research provide useful foundations on which to build continuous and coherent teacher professional development programs about classroom discourse.