• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.439-448
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• 1999

In this paper, two optimization algorithms based on artificial neural networks and genetic algorithms are proposed for cellular radio channel assignment problems. The channel assignment process is characterized as minimization of the energy function which represents constraints of the channel assignment problems. All three constraints such as the co-channel constraint, the adjacent channel constraint and the co-site channel constraint are considered. In the neural networks approach, certain techniques such as the forced assignment and the changing cell order are developed, and in the genetic algorithms approach, data structure and proper genetic operators are developed to find optimal solutions, As simulation results, the convergence rates of the two approaches are presented and compared.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.3
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• pp.135-144
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• 2003

An intrusion detection system shows different result over overall detection area according to its detection characteristics of inner detection algorithms or techniques. To expand detection areas, we requires an integrated detection which can be archived both by deploying a few detection systems which detect different detection areas and by combining their results. In addition to expand detection areas, we need to decrease the workload of security managers by false alarms and improve the correctness by minimizing false alerts which happen during the process of integration. In this paper, a method for aggregation detection use fuzzy inference to integrate a vague detection results which imply the characteristics of detection systems. Their analyzed detection characteristics are expressed as fuzzy membership functions and fuzzy rule bases which are applied through the process of fuzzy control. And, it integrate a vague decision results and minimize the number of false alerts by reflecting the characteristics of detection systems. Also it does minimize inference objects by applying thresholds decided through several experiments.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.117-129
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• 2008

The cost-based scheduling work has been done in both the Operations Research (OR) and Artificial Intelligence (AI) literature. To deal with more realistic problems, AI-based heuristic scheduling approach with non-regular performance measures has been studied. However, there has been little research effort to develop a full inter-job cost propagation algorithm (CPA) for different jobs having multiple downstream and upstream activities. Without such a CPA, decision-making in scheduling heuristics relies upon local, incomplete cost information, resulting in poor schedule performance from the overall cost minimizing objective. For such a purpose, we need two types of CPAs : intra-job CPA and inter-job CPA. Whenever there is a change in cost information of an activity in a job in the process of scheduling, the intra-job CPA updates cost curves of other activities connected through temporal constraints within the same job. The inter-job CPA extends cost propagation into other jobs connected through precedence relationships. By utilizing the cost information provided by CPAs, we propose cost-based scheduling heuristics that attempt to minimize the total schedule cost. This paper develops inter-job CPAs that create and update cost curves of each activity in each search state, and propagate cost information throughout a whole network of temporal constraints. Also we propose various cost-based scheduling heuristics that attempt to minimize the total schedule cost by utilizing the cost propagation algorithm.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.98-103
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• 2001

The binaural auditory system of human has the capability of differentiating the direction and distance of sound sources. This feature is well characterised in terms of the inter-aural intensity difference (IID), the inter-aural time difference (ITD) and/or the spectral shape difference (SSD) arising from the acoustic transfer of a sound source to the outer ears. This paper proposes an effective way of extracting the three sound perception factors (IID, ITD, SSD) from the head-related transfer functions (HRTF's) that depends on the direction and distance of the acoustic source from the listener. It includes the estimation method of the equivalent ITD and 1/3-octave band-based IID factors and their usage to locate a sound source in space. Subjective and objective tests were carried out to examine the effectiveness of the proposed methodology and its applicability to real sound systems. Those experimental results are illustrated in this paper.

• Proceedings of the KOR-KST Conference
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• 1998.10b
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• pp.261-261
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• 1998

교통계획의 목적은 교통체계를 분석하여 교통과 활동간의 상호작용을 효율화시켜 도시 및 지역사회의 목표를 달성하는데 있으며, 합리적인 교통계획을 수립하여 한정된 투자재원을 효율적으로 배분하기 위해서는 교통수요에 대한 합리적 접근이 필요하다. 교통수요예측의 접근방법은 미시적인 개별적 접근방법과 거시적인 집단적 접근방법으로 구분되며, 다시 모형화 기법이 결정적인가 확률적인가에 따라 개별결정적, 개별활률적, 그리고 집단결정적, 집단확률적 모형의 4가지로 구분될 수 있다. 이 중에서 일반적으로 관심의 대상이 되는 2가지 형태는 집단결정적, 개발확률적 모형이다. 집단결정적모형은 전통적 교통수요예측모형에 해당되며, 개별확률적모형은 1970년대 Mc Fadden을 시작으로 Ben-Akiva, Manheim을 중심으로 한 소비자 행동선택 이론에 근거한 개별행태모형이 이에 해당된다. 개별행태모형은 개개인의 통행행태를 다른 모든 조건이 동일할 때 개개인은 비용의 최소화를 추구하고, 비용과 관련한 통행행태는 거시적 수준에서의 주어진 제약 조건과 관계가 있으며, 의사결정은 확률분포에 의해서 결정되는 효용원칙(Efficiency Principle)에 입각하여 해석한다. 도시내와 도시간, 취업자와 비취업자, 출퇴근 시, 목적별 등의 여러 가지 통행에 있어서 다양한 변수들을 사용하여 교통수단 선택모형의 파라메카 값을 추정하고 통행패턴을 분석해 왔다. 본 논문에서는 개별행태모형인 로짓모형 중에서 집단다항로짓모형을 이용하여 여러 통행 중 공항시설의 접근에 필요한 교통수단 효용함수의 파라메타 값 추정 시, 일반적으로 사용되는 통행시간, 통행비용이라는 변수를 공통으로 두고, 대중교통의 경우에만 해당하는 환승이라는 특정대안변수(Specific alternative variable)를 첨가하여 그것이 수단선택에 미치는 영향을 분석한다. 또한, 대중교통의 속성을 가지고 있는 지하철과 버스를 하나의 대안으로 묶어서 효용함수를 구한 다음 다시 승용차, 택시, 대중교통을 독립된 대안으로 두고 모형을 정립하는 NESTED LOGIT모형으로 파라메타를 추정하여 대중교통의 효용에 관해 분석·비교하였다. 본 논문에 이용된 자료는 공항을 이용하는 이용객들을 대상으로 직접 설문·면접조사한 자료이며 대상 교통수단은 승용차, 택시, 지하철, 버스로 설정하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.3
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• pp.253-260
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• 2016

In this paper, the optimal seismic design method for inducing the beam-hinge collapse mechanism of steel moment frames is presented. This uses the non-dominated sorting genetic algorithm II(NSGA-II) as an optimal algorithm. The constraint condition for preventing the occurrence of plastic hinges at columns is used to induce the beam-hinge collapse mechanism. This method uses two objective functions to minimize the structural weight and maximize the dissipated energy. The proposed method is verified by the application to nine story steel moment frame example. The minimum column-to-beam strength ratio to induce the beam-hinge collapse mechanism are investigated based on the simulation results. To identify the influence of panel zone on the minimum column-to-beam strength ratio, three analytic modeling methods(nonlinear centerline model without rigid end offsets, nonlinear centerline model with rigid end offsets, nonlinear model with panel zones) are used.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.2
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• pp.33-39
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• 2015

Recently, the event of slope failure has been occurring frequently due to rapid climate changes and broad development of infrastructures, and the research for establishment of monitoring and prevention system has been an attentive issue. The major influence factors of slope failure mechanism can be considered moisture and temperature in soil, and the slope failure can be monitored and predicted through the trend of moisture-temperature change. Therefore, the combined sensing technology for the continuous measurement of moisture-temperature with different soil depths is needed for the slope monitoring system. The various independent sensors for each item (i.e. temperature and moisture respectively) have been developed, however, the research for development of combined sensing system has been hardly carried out. In this study, the high-fidelity sensor combing temperature-moisture measurement by using the minimized current consuming temperature circuit and the microwave emission moisture sensor is developed and applied on the slope failure monitoring system. The feasibility of developed monitoring system is verified by various experimental approaches such as standard performance test, mockup test and long-term field test. As a result, the developed temperature-moisture combined measurement system is verified to be measuring and monitoring the temperature and moisture in soil accurately.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.337-343
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• 2014

This paper presents a continuum-based shape design sensitivity analysis(DSA) method for crack propagation problems using a reproducing kernel method(RKM), which facilitates the remeshing problem required for finite element analysis(FEA) and provides the higher order shape functions by increasing the continuity of the kernel functions. A linear elasticity is considered to obtain the required stress field around the crack tip for the evaluation of J-integral. The sensitivity of displacement field and stress intensity factor(SIF) with respect to shape design variables are derived using a material derivative approach. For efficient computation of design sensitivity, an adjoint variable method is employed tather than the direct differentiation method. Through numerical examples, The mesh-free and the DSA methods show excellent agreement with finite difference results. The DSA results are further extended to a shape optimization of crack propagation problems to control the propagation path.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.25-31
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• 2011

Principal component analysis (PCA) is a well-known method for dimensionality reduction and feature extraction. Although PCA has been applied in many areas successfully, it is sensitive to outliers due to the use of sum-square-error. Several variants of PCA have been proposed to resolve the noise sensitivity and, among the variants, improved robust fuzzy PCA (RF-PCA2) demonstrated promising results. RF-PCA2, however, still can fall into a local optimum due to equal initial membership values for all data points. Another reason comes from the fact that RF-PCA2 is based on sum-square-error although fuzzy memberships are incorporated. In this paper, a variant of RF-PCA2 called RF-PCA3 is proposed. The proposed algorithm is based on the objective function of RF-PCA2. RF-PCA3 augments RF-PCA2 with the objective function of PCA and initial membership calculation using data distribution, which make RF-PCA3 to have more chance to converge on a better solution than that of RF-PCA2. RF-PCA3 outperforms RF-PCA2, which is demonstrated by experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1852-1859
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• 2016

The effectiveness of a binarization algorithm in image processing depends on how to eliminate the uncertainty of determining threshold in a reasonable way and on minimizing information loss due to the binarization effect. Fuzzy binarization technique was proposed to handle that uncertainty with fuzzy logic. However, that method is known to be inefficient when the given image has low intensity contrast. In this paper, we propose an improved fuzzy binarization method to overcome such known drawbacks. Our method proposes a trapezoid type fuzzy membership function instead of most-frequently used triangle type one. We also propose an adaptive ${\alpha}$_cut determination policy. Our proposed method has less information loss than other algorithms since we do not use any stretching based preprocessing for enhancing the intensity contrast. In experiment, our proposed method is verified to be more effective in binarization with less information loss for many different types of images with low intensity contrast such as night scenery, lumber scoliosis, and lipoma images.