• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1284-1294
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• 2007

In this paper, a blind nonlinear channel equalization is implemented by using a Modified Fuzzy C-Means (MFCM) algorithm. The proposed MFCM searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.12
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• pp.79-90
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• 2005

In this paper, we propose a new clustered reconfigurable interconnect network (CRIN) BIST to improve the embedding probabilities of random-pattern-resistant-patterns. The proposed method uses a scan-cell reordering technique based on the signal probabilities of given test cubes and specific hardware blocks that increases the embedding probabilities of care bit clustered scan chain test cubes. We have developed a simulated annealing based algorithm that maximizes the embedding probabilities of scan chain test cubes to reorder scan cells, and an iterative algorithm for synthesizing the CRIN hardware. Experimental results demonstrate that the proposed CRIN BIST technique achieves complete fault coverage with lower storage requirement and shorter testing time in comparison with the conventional methods.

• Journal of KIISE:Software and Applications
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• v.33 no.7
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• pp.624-635
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• 2006

This paper applies simulated annealing algorithm to the problem of generating a plan for intra-block remarshalling with multiple transfer cranes. Intra-block remarshalling refers to the task of rearranging containers scattered around within a block into certain designated target areas of the block so that they can be efficiently loaded onto a ship. In generating a remarshalling plan, the predetermined container loading sequence should be considered carefully to avoid re-handlings that may delay the loading operations. In addition, the required time for the remarshalling operation itself should be minimized. A candidate solution in our search space specifies target locations of the containers to be rearranged. A candidate solution is evaluated by deriving a container moving plan and estimating the time needed to execute the plan using two cranes with minimum interference. Simulation experiments have shown that our method can generate efficient remarshalling plans in various situations.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.1-8
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• 2024

The traveling salesman problem(TSP) is one of the well known combinatorial optimization problems. Local search has been used as a method to solve TSP. Greedy Random Insertion(GRI) is known as an effective neighbor generation method for local search. GRI selects some cities from the current solution randomly and inserts them one by one into the best position of the current partial solution considering only one city at a time. We first propose another greedy neighbor generation method which is named Full Greedy Insertion(FGI). FGI determines insertion location one by one like GRI, but considers all remaining cities at once. And then we propose a method to combine GRI with FGI, in which GRI or FGI is randomly selected and executed at each iteration in simulated annealing. According to the experimental results, FGI alone does not necessarily perform very well. However, we confirmed that the combined method outperforms the existing local search methods including GRI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2283-2288
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• 2006

As development in technology of bioinformatics recently makes it possible to operate micro-level experiments, we can observe the expression pattern of total genome through on chip and analyze the interactions of thousands of genes at the same time. Thus, DNA microarray technology presents the new directions of understandings for complex organisms. Therefore, it is required how to analyze the enormous gene information obtained through this technology effectively. In this thesis, We used sample data of bioinformatics core group in harvard university. It designed and implemented system that evaluate accuracy after dividing in class of two using Bayesian algorithm, ASA, of feature extraction method through normalization process, reducing or removing of noise that occupy by various factor in microarray experiment. It was represented accuracy of 98.23% after Lowess normalization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.540-543
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• 2013

선박은 판과 보강재를 효율적으로 조립한 매우 복잡한 구조물이고, 이동하는 구조물로써는 최대규모의 구조물이다. 특히, 선체 구조의 설계란 "예상되는 모든 하중에 충분히 견딜 수 있는 강도(strength)와 강성(stiffness)을 가진 부재의 크기를 결정하고 적절히 배치하는 과정이다." 라고 말할 수 있다. 선체 구조의 설계는 부재의 배치가 얼마나 적절하게 잘되어 있는가에 달려 있다고 하여도 과언이 아닐 정도로 매우 중요하다. 주요 구조 부재의 부재 배치에 대한 기본적인 개념은 판 부재의 용접선(seam line), 종, 횡늑골의 간격, 종거어더 등을 예로 들 수 있으며, 부재의 배치는 최적 설계 및 공작상의 관점으로부터 선정되어야 하며, 또한 선체 전체의 구조적인 연결이 불연속이 되지 않도록 하여야 한다. 특히, 판 부재의 용접선은 여러 가지 표준치수로 생산되는 판 들 중, 판의 기준 폭이 얼마인 것을 사용하는 것이 공작상 또는 배치상 가장 편리한 가를 생각하여야 한다. 이것은 선박의 크기에 따라 다르겠지만, 조선소 크레인의 용량 및 가공상, 강도상의 문제를 고려하여 가능한 한용접선의 수를 줄이는 것이 바람직하다. 용접선을 줄이기 위해서는 판 부재의 폭을 넓게 하면 되나, 철강회사에서 표준으로 생산 판매하는 주판의 폭보다 넓은 판을 주문 구입 한다는 것은 곧 생산비용의 증가로 이어지는 것으로 이는 주판 구입 경비 측면에서는 바람직하지 않다. 따라 서, 주판 구입경비의 최소화를 유도하면서도 주판 폭의 적정 및 용접선 개수 최소화를 유지할 수 있도록 설계하는 것은 중요하지만, 용접선 배치의 문제는 다양한 입력 변수를 고려해야 하는 복잡한 문제이기 때문에 그간 최적화 관점에서 접근하지 못하고 시니어급 엔지니어가 가진 경험과 조선소의 지침서에 기재된 절차에 따라 대략적인 해를 결정하여 왔다. 본 연구는 이러한 복잡한 문제를 최적화 방법인 당금질(Simulated Annealing) 방법을 이용하여 해결한 결과를 소개하며, 그 결과와 효용성에 대해 논하도록 하겠다.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.6
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• pp.37-45
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• 1998

In this paper, we report the first three-dimensional simulation result of the transient enhanced diffusion(TED) of dopants in the ion-implanted silicon by employing our 3D semiconductor process simulator, INPROS system. In order to simulate three-dimensional TED redistribution of dopants in silicon, the dopant distributions after the ion implantation was calculated by Monte Carlo(MC) method, followed by finite element(FE) numerical solver for thermal annealing. Excellent agreement between the simulated 3D profile and the SIMS data has been obtained for ion-implanted arsenic and phosphorus after annealing the boron marker layer at 75$0^{\circ}C$ for 2 hours. Our three-dimensional TED simulation could successfully explain the reverse short channel effect(RSCE) by taking the 3D point defect distribution into account. A coupled TED simulation and device simulation allows reverse short channel effect on threshold to be accurately predicted.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.396-396
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• 2012

$TiO_2$ anatase nanotube arrays (NTAs) were grown by electrochemical anodization and followed annealing of Ti foil. Ethylene glycol/$NH_4F$-based organic electrolyte was used for electrolyte solution and using second anodization process to obtain free-standing NTAs. After obtaining NTAs, ITO film was deposited by sputtering process on bottom of NTAs. UV-curable NOA was used for attach free-standing NTAs on flexible plastic substrate (PEN). Solid state electrolyte (spiro-OMeTAD) was coated via spin-coating method on top of attached NTAs. Ag was deposited as a counter electrode. Under AM 1.5 simulated sunlight, optical characteristics of devices were investigated. In order to use flexible polymer substrate, processes have to be conducted at low temperature. In case of $TiO_2$ nano particles (NPs), however, crystallization of NPs at high temperature above $450^{\circ}C$ is required. Because NTAs were conducted high temperature annealing process before NTAs transfer to PEN, it is favorable for using PEN as flexible substrate. Fabricated flexible solid-state DSSCs make possible the preventing of liquid electrolyte corrosion and leakage, various application.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.286-289
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• 1991

We simulated ion implantation and annealing condition of 1 ${\mu}m$ CMOS device using process simulator, SUPREM-II. In this simulation, optimal condition of ion implantation for symmetric threshold voltage determination of PMOS and NMOS region, junction depth and sheet resistance of source/drain region, impurity profile of each region are investigated. Ion implantation dose for 3 ${\mu}m$ N-well junction depth and symmetric threshold voltage of $|0.6|{\pm}0.1$ V were $1.9E12Cm^{-2}$(for phosphorus), $1.7E122Cm^{-2}$(for boron) respectively. Also annealing condition for dopant activation are examined about $900^{\circ}C$, 30 minutes. After final process step, N-well junction, P+ S/D junction and N+ S/D junction depth are calculated 3.16 ${\mu}m$, 0.45 ${\mu}m$ and 0.25 ${\mu}m$ respectively.

• Investigative Magnetic Resonance Imaging
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• v.6 no.2
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• pp.137-146
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• 2002

Purpose : This paper introduces an improved classification approach which adopts a deterministic relaxation method and an agglomerative clustering technique for the classification of MRI using neural network. The proposed approach can solve the problems of convergency to local optima and computational burden caused by a large number of input patterns when a neural network is used for image classification. Materials and methods : Application of Hopfield neural network has been solving various optimization problems. However, major problem of mapping an image classification problem into a neural network is that network is opt to converge to local optima and its convergency toward the global solution with a standard stochastic relaxation spends much time. Therefore, to avoid local solutions and to achieve fast convergency toward a global optimization, we adopt MFA to a Hopfield network during the classification. MFA replaces the stochastic nature of simulated annealing method with a set of deterministic update rules that act on the average value of the variable. By minimizing averages, it is possible to converge to an equilibrium state considerably faster than standard simulated annealing method. Moreover, the proposed agglomerative clustering algorithm which determines the underlying clusters of the image provides initial input values of Hopfield neural network. Results : The proposed approach which uses agglomerative clustering and deterministic relaxation approach resolves the problem of local optimization and achieves fast convergency toward a global optimization when a neural network is used for MRI classification. Conclusion : In this paper, we introduce a new paradigm to classify MRI using clustering analysis and deterministic relaxation for neural network to improve the classification results.