• 한국인터넷방송통신학회논문지
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• 제8권5호
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• pp.197-203
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• 2008

본 연구에서는 차세대 CDMA 셀룰러 네트워크의 성능향상을 위한 멀티 데이터 전송 레이트 조절과 전력제어 문제를 결합한 문제를 제시하고 유전 알고리즘 접근에 기반한 새로운 해법을 제안하였다. 본 연구에서 제안한 알고리즘으로 많은 사용자를 보다 빨리 서비스 할 수 있고 SIR 제한값을 고려하면서 최적의 해를 얻을 수 있었다. 이 연구에서는 CDMA 셀룰러 네트워크의 데이터 전송 레이트를 최대화하는 적합도 문제와 가능한 모바일의 수를 최대화하는 적합도 문제 두 개를 고려하였으나 이 들을 결합한 문제나 다른 것 들에 대한 적합도 함수도 충분히 장착이 가능하다. 시뮬레이션 결과는 접근 방식의 유효성과 타당성을 보여준다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권3호
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• pp.178-185
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• 2013

As computer technology continues to develop, computer networks are now widely used. As a result, there are many new intrusion types appearing and information security is becoming increasingly important. Although there are many kinds of intrusion detection systems deployed to protect our modern networks, we are constantly hearing reports of hackers causing major disruptions. Since existing technologies all have some disadvantages, we utilize algorithms, such as the fuzzy C-means (FCM) and the support vector machine (SVM) algorithms to improve these technologies. Using these two algorithms alone has some disadvantages leading to a low classification accuracy rate. In the case of FCM, self-adaptability is weak, and the algorithm is sensitive to the initial value, vulnerable to the impact of noise and isolated points, and can easily converge to local extrema among other defects. These weaknesses may yield an unsatisfactory detection result with a low detection rate. We use a genetic algorithm (GA) to help resolve these problems. Our experimental results show that the combined GA and FCM algorithm's accuracy rate is approximately 30% higher than that of the standard FCM thereby demonstrating that our approach is substantially more effective.

• Clinical and Experimental Pediatrics
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• 제58권11호
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• pp.407-414
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• 2015

Early-onset epileptic encephalopathies are one of the most severe early onset epilepsies that can lead to progressive psychomotor impairment. These syndromes result from identifiable primary causes, such as structural, neurodegenerative, metabolic, or genetic defects, and an increasing number of novel genetic causes continue to be uncovered. A typical diagnostic approach includes documentation of anamnesis, determination of seizure semiology, electroencephalography, and neuroimaging. If primary biochemical investigations exclude precipitating conditions, a trial with the administration of a vitaminic compound (pyridoxine, pyridoxal-5-phosphate, or folinic acid) can then be initiated regardless of presumptive seizure causes. Patients with unclear etiologies should be considered for a further workup, which should include an evaluation for inherited metabolic defects and genetic analyses. Targeted next-generation sequencing panels showed a high diagnostic yield in patients with epileptic encephalopathy. Mutations associated with the emergence of epileptic encephalopathies can be identified in a targeted fashion by sequencing the most likely candidate genes. Next-generation sequencing technologies offer hope to a large number of patients with cryptogenic encephalopathies and will eventually lead to new therapeutic strategies and more favorable long-term outcomes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권5호
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• pp.1920-1937
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• 2015

Network environment has been under constant threat from both malicious attackers and inherent vulnerabilities of network infrastructure. Existence of such threats calls for exhaustive vulnerability analyzing to guarantee a secure system. However, due to the diversity of security hazards, analysts have to select from massive alternative hardening strategies, which is laborious and time-consuming. In this paper, we develop an approach to seek for possible hardening strategies and prioritize them to help security analysts to handle the optimal ones. In particular, we apply a Risk Flow Attack Graph (RFAG) to represent network situation and attack scenarios, and analyze them to measure network risk. We also employ a multi-objective genetic algorithm to infer the priority of hardening strategies automatically. Finally, we present some numerical results to show the performance of prioritizing strategies by network risk and hardening cost and illustrate the application of optimal hardening strategy set in typical cases. Our novel approach provides a promising new direction for network and vulnerability analysis to take proper precautions to reduce network risk.

• 한국컴퓨터정보학회논문지
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• 제11권1호
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• pp.1-10
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• 2006

부하재분배 방법은 컴퓨터시스템에서 중요한 요소이다. 수신자 개시 부하재분배 알고리즘에서는 전체시스템이 저부하일 때 수신자(저부하 프로세서)가 부하를 이전받기 위해 송신자(과부하 프로세서)를 발견할 때까지 불필요한 이전 요청 메시지를 계속 보내게 된다. 따라서 이같은 상황에서는 과부하 상태인 송신자 프로세서로부터 승인 메시지를 받기까지 불필요한 프로세서간 통신으로 인하여 프로세서의 이용률이 저하되고, 타스크 처리율이 낮아지는 문제점이 발생한다. 본 논문에서는 이질형 분산 시스템에서의 동적 부하재분배를 위해 유전 알고리즘을 기반으로 하는 접근 방법을 제안한다. 이 기법에서는 불필요한 요청메시지를 줄이기 위해 요청 메시지가 전송될 프로세서들이 제안된 유전 알고리즘에 의해 결정된다.

• Clinical and Experimental Pediatrics
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• 제63권6호
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• pp.195-202
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• 2020

Developments in next-generation sequencing (NGS) techogies have assisted in clarifying the diagnosis and treatment of developmental delay/intellectual disability (DD/ID) via molecular genetic testing. Advances in DNA sequencing technology have not only allowed the evolution of targeted panels but also, and more currently enabled genome-wide analyses to progress from research era to clinical practice. Broad acceptance of accuracy-guided targeted gene panel, whole-exome sequencing (WES), and whole-genome sequencing (WGS) for DD/ID need prospective analyses of the increasing cost-effectiveness versus conventional genetic testing. Choosing the appropriate sequencing method requires individual planning. Data are required to guide best-practice recommendations for genomic testing, regarding various clinical phenotypes in an etiologic approach. Targeted panel testing may be recommended as a firsttier testing approach for children with DD/ID. Family-based trio testing by WES/WGS can be used as a second test for DD/ID in undiagnosed children who previously tested negative on a targeted panel. The role of NGS in molecular diagnostics, treatment, prediction of prognosis will continue to increase further in the coming years. Given the rapid pace of changes in the past 10 years, all medical providers should be aware of the changes in the transformative genetics field.

• 제어로봇시스템학회논문지
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• 제21권8호
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• pp.788-793
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• 2015

This paper proposes a path planning algorithm to reduce the inspection time of AOI (Automatic Optical Inspection) machines for SMT (Surface Mount Technology) in-line system. Since the field-of-view of the camera attached at the machine is much less than the entire inspection region of board, the inspection region should be clustered to many groups. The image acquisition time depends on the number of groups, and camera moving time depends on the sequence of visiting the groups. The acquired image is processed while the camera moves to the next position, but it may be delayed if the group includes many components to be inspected. The inspection delay has influence on the overall job time of the machine. In this paper, we newly considers the inspection delay time for path planning of the inspection machine. The unified approach using genetic algorithm is applied to generates the groups and visiting sequence simultaneously. The chromosome, crossover operator, and mutation operator is proposed to develop the genetic algorithm. The experimental results are presented to verify the usefulness of the proposed method.

• 한국정보통신학회논문지
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• 제8권6호
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• pp.1218-1227
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• 2004

멀티-도메인 공학시스템은 전기, 기계, 유압, 열등의 도메인을 포함하며, 시스템 구성이 복잡하여 설계에 많은 어려움을 가지고 있다. 최적의 설계를 위해서는 각 도메인에 대한 통합된 설계 방법과 자동적이고 효율적인 탐색방법이 요구된다. 본 논문은 도메인에 독립적인 본드 그래프(bond graph)와 대규모 공간 해의 탐색에 접합한 진화 알고리즘의 일종인 Genetic Programming(유전 프로그래밍, GP)를 결합하여 멀티 도메인 동적 시스템에 대한 디자인 해를 자동적으로 생성해주는 설계 방법을 제시하였다. 제안된 설계방법의 효용성을 입증하기 위해서 고유값(eigenvalue) 설계 문제가 실험되었고, 서로 다른 태아모델을 가진 고유값의 집합이 사용되었다.

• Journal of Electrical Engineering and Technology
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• 제4권1호
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• pp.1-12
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• 2009

In recent years, integration of new distributed generation (DG) technology in distribution networks has become one of the major management concerns for professional engineers. This paper presents a dynamic methodology of optimal allocation and sizing of DG units for a given practical distribution network, so that the cost of active power can be minimized. The approach proposed is based on a combined Genetic/Fuzzy Rules. The genetic algorithm generates and optimizes combinations of distributed power generation for integration into the network in order to minimize power losses, and in second step simple fuzzy rules designs based upon practical expertise rules to control the reactive power of a multi dynamic shunt FACTS Compensator (SVC, STATCOM) in order to improve the system loadability. This proposed approach is implemented with the Matlab program and is applied to small case studies, IEEE 25-Bus and IEEE 30-Bus. The results obtained confirm the effectiveness in sizing and integration of an assigned number of DG units.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.423-432
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• 2014

Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied for solving Combined Economic Emission Dispatch (CEED) problem with valve-point loading of thermal generators. This CEED problem with valve-point loading is a nonlinear, constrained multi-objective optimization problem, with power balance and generator capacity constraints. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a nonsmooth optimization problem. To validate its effectiveness of NSGA-II, two benchmark test systems, IEEE 30-bus and IEEE 118-bus systems are considered. To compare the Pareto-front obtained using NSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Comparison with other optimization techniques showed the superiority of the NSGA-II approach and confirmed its potential for solving the CEED problem. Numerical results show that NSGA-II algorithm can provide Pareto-front in a single run with good diversity and convergence. An approach based on Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) is applied on non-dominated solutions obtained to determine Best Compromise Solution (BCS).