• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.346-351
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• 2007

다중 전극으로 측정한 활동 전위의 분류(Multi-electrode spike sorting)는 단일 전극(single-electrode)보다 더 정확한 결과를 보여준다. 그러나 다중 전극에서 주어지는 활동 전위 크기들의 클러스터는 일반적으로 분류하기 쉴지 않은 문제이다. 이 논문에서는 고전적인 클러스터링 알고리듬 중의 하나인 Mountain method를 수정하여 다중 전극 활동전위의 분류에 적합한 알고리듬을 제안한다. 통상적인 데이터 클러스터링이 아닌 공간 분할을 통해 신경 데이터의 다양한 클러스터에 대해서 적응도가 높아지고 빠른 분류를 하게 된다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.759-762
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• 2002

A preliminary design process in the multi-stage gear drives design is important part. a preliminary design support system which run efficiently the design is developed with fuzzy expert system. the system automatically generate the mechanism of multi-stats gear drives and select a candidate mechanism by the general expert rule and sorting using fuzzy expert system. the preliminary mechanism design of multi-stage gear drives have a short execution time, add accuracy in a preliminary design considering volume, cost, power and efficiency in preliminary, a design efficiency is increased and a preliminary design have a elasticity using a weight on variable's sorting mechanism.

• The KSFM Journal of Fluid Machinery
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• v.17 no.4
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• pp.19-29
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• 2014

In addition to the development of micro hydro turbine, the challenge in micro hydro turbine design as sustainable hydro devices is focused on the optimization of turbine runner blade which have decisive effect on the turbine performance to reach higher efficiency. A multi-objective optimization method to optimize the performance of runner blade of propeller turbine for micro turbine has been studied. For the initial design of planar blade cascade, singularity distribution method and the combination of the Bezier curve parametric technology is used. A non-dominated sorting genetic algorithm II(NSGA II) is developed based on the multi-objective optimization design method. The comparision with model test show that the blade charachteristics is optimized by NSGA-II has a good efficiency and load distribution. From model test and scale up calculation, the maximum prototype efficiency of the runner blade reaches as high as 90.87%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1339-1343
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• 2004

This paper presents a development of the control algorithm and Pick & Placer. The Pick & Placer provides a powerful multi-task system that includes both graphical and remote interface. Users can easily set up sorting parameters and record important data including wafer number, data, and operator information. This System sets up a dustproof device and massively machined components to provide an extremely stable sorting environment. Precise resolution and accuracy result from using machine vision, a pneumatic slide drive and close -looped positioning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2177-2193
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• 2018

This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.99-102
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• 1997

A neural spike sorting technique has been developed that also has the capability of template learning. A system of software has been written that first obtains the templates by learning, and then performs the sorting of the spikes into single units. The spike sorting can be done in real time. The template learning consists of spike detection based on the discrete Haar transform (DHT), feature extraction by clustering of spike amplitude and duration, classification based on rms error, and fabrication of templates. The developed algorithms can be implemented into real time systems using digital signal processors.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.377-380
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• 2002

신경회로망은 문자인식, 자동제어 등의 여러 분야에 널리 쓰이는 방식이다. 그러나 신경회로망을 구현하는데는 연산량이 많아서 실시간으로 구현하기에 어려움이 많이 따른다. 본 논문은 신경회로망을 구현하는데 필요한 연산을 살펴보고 그 연산을 구현하는 방법을 비교 분석하였다. 신경회로망을 구현하기 위해 DSP(Digital Signal Processor), PC의 FPU(Floating Point Unit), Intel사의 Pentium 계열 프로세서에서 지원하는 SIMD(Single Instruction Multiple Data) 기술을 사용하여 결과를 비교 분석 하였다. 신경회로망의 핵심인 MLP(Multi Layer Perceptron) 연산에 대해 실험한 결과 SIMD 기술을 이용하는 방법이 다른 방법에 비해 2배이상 좋은 결과를 나타내었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.314-322
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• 2007

This paper proposes a new optimization algorithm named by GBNSGA(Goal-Pareto Based Non-dominated Sorting Genetic Algorithm) which determines the best configuration for CR(Cognitive Radio) communication systems. Conventionally, in order to select the proper radio configuration, genetic algorithm has been introduced so as to alleviate computational burden along the execution of the cognition cycle proposed by Mitola. This paper proposes a novel optimization algorithm designated as GBNSGA for cognitive engine which can be described as a hybrid algorithm combining well-known Pareto-based NSGA(Non-dominated Sorting Genetic Algorithm) as well as GP(Goal Programming). By conducting computer simulations, it will be verified that the proposed method not only satisfies the user's service requirements in the form of goals. It reveals the fast optimization capability and more various solutions rather than conventional NSGA or weighted-sum approach.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.4
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• pp.279-285
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• 2016

Reliable recording and analysis of peripheral nerve activity is important to recognize the user's intention for controlling a neuro-prosthetic hand. In this paper, we present a peripheral nerve recording system that consisted of an intrafascicular multi-electrode array, an electrode insertion device, and a multi-channel neural amplifier. The 16 channel multi-electrode array was stably implanted into the sciatic nerve of the rat under anesthesia using the electrode insertion device. During passive movements and mechanical stimuli, muscle and cutaneous afferent signals were recorded with the multi-channel neural amplifier. Furthermore, we propose a spike sorting method to isolate individual neuronal unit. The muscle proprioceptive units were classified as muscle spindle afferents or Golgi tendon organ afferents, and the skin exteroceptive units were categorized as slow adapting afferents or fast adapting afferents. Experimental results showed that the proposed method could be applicable to record and analyze peripheral nerve activity in neuro-prosthetic systems.

• Journal of Biosystems Engineering
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• v.26 no.2
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• pp.147-154
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• 2001

In Korea and Japan, dried oak mushrooms are classified into 12 to 16 different categories based on its external visual quality. And grading used to be done manually by the human expert and is limited to the randomly sampled oak mushrooms. Visual features of dried oak mushrooms dominate its quality and are distributed over both sides of the gill and the cap. The 2nd prototype computer vision based automatic grading and sorting system for dried oak mushrooms was developed based on the 1st prototype. Sorting function was improved and overall system for grading was simplified to one stage grading instead of two stage grading by inspecting both front and back sides of mushrooms. Neuro-net based side(gill or cap) recognition algorithm of the fed mushroom was adopted. Grading was performed with both images of gill and cap using neural network. A real time simultaneous discharge algorithm, which is good for objects randomly fed individually and for multi-objects located along a series of discharge buckets, was developed and implemented to the controller and the performance was verified. Two hundreds samples chosen from 10 samples per 20 grade categories were used to verify the performance of each unit such as feeding, reversing, grading, and discharging unites. Test results showed that success rates of one-line feeding, reversing, grading, and discharging functions were 93%, 95%, 94%, and 99% respectively. The developed prototype revealed successful performance such as the approximate sorting capability of 3,600 mushrooms/hr per each line i.e. average 1sec/mushroom. Considering processing time of approximate 0.2 sec for grading, it was desired to reduce time to reverse a mushroom to acquire the reversed surface image.