• Journal of Sensor Science and Technology
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• v.22 no.2
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• pp.162-173
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• 2013

The purpose of this paper is to classify VOC gases by emulating the characteristics found in biological olfaction. For this purpose, we propose new signal processing method based a polymeric chemical sensor array consisting of 4096 sensors which is created by NEUROCHEM project. To remove unstable sensors generated in the manufacturing process of very large scaled chemical sensor array, we used discrete wavelet transformation and cosine similarity. And, to remove the supernumerary redundancy, we proposed the method of selecting candidates of representative sensor representing sensors with similar features by Fuzzy c-means algorithm. In addition, we proposed an improved algorithm for selecting representative sensors among candidates of representative sensors to better enhance classification ability. However, Classification for very large scaled sensor array has a great deal of time in process of learning because many sensors are used for learning though a redundancy is removed. Throughout experimental trials for classification, we confirmed the proposed method have an outstanding classification ability, at transient state as well as steady state.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1472-1488
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• 2019

Critical elements in the China's Lunar Exploration reside in that the lunar rover travels over the surrounding undetermined environment and it conducts scientific exploration under the ground control via teleoperation system. Such an interplanetary transportation mission teleoperation system belongs to the ground application system in deep space mission, which performs terrain reconstruction, visual positioning, path planning, and rover motion control by receiving telemetry data. It plays a vital role in the whole lunar exploration operation and its so-called trustworthy evidence must be assessed before and during its implementation. Taking ISO standards and China's national military standards as trustworthy evidence source, the net assessment model and net assessment method of teleoperation system are established in this paper. The multi-dimensional net assessment model covering the life cycle of software is defined by extracting the trustworthy evidences from trustworthy evidence source. The qualitative decisions are converted to quantitative weights through the net assessment method (NAM) combined with fuzzy analytic hierarchy process (FAHP) and entropy weight method (EWM) to determine the weight of the evidence elements in the net assessment model. The paper employs the teleoperation system for interplanetary transportation as a case study. The experimental result drawn shows the validity and rationality of net assessment model and method. In the final part of this paper, the untrustworthy elements of the teleoperation system are discovered and an improvement scheme is established upon the "net result". The work completed in this paper has been applied in the development of the teleoperation system of China's Chang'e-3 (CE-3) "Jade Rabbit-1" and Chang'e-4 (CE-4) "Jade Rabbit-2" rover successfully. Besides, it will be implemented in China's Chang'e-5 (CE-5) mission in 2019. What's more, it will be promoted in the Mars exploration mission in 2020. Therefore it is valuable to the development process improvement of aerospace information system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.206-215
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• 2005

In this paper, we propose a new design method of Genetic Algorithm Processor(GAP) and Evolvable Hardware(EHW). All sorts of creature evolve its structure or shape in order to adapt itself to environments. Evolutionary Computation based on the process of natural selection not only searches the quasi-optimal solution through the evolution process, but also changes the structure to get best results. On the other hand, Genetic Algorithm(GA) is good fur finding solutions of complex optimization problems. However, it has a major drawback, which is its slow execution speed when is implemented in software of a conventional computer. Parallel processing has been one approach to overcome the speed problem of GA. In a point of view of GA, long bit string length caused the system of GA to spend much time that clear up the problem. Evolvable Hardware refers to the automation of electronic circuit design through artificial evolution, and is currently increased with the interested topic in a research domain and an engineering methodology. The studies of EHW generally use the XC6200 of Xilinx. The structure of XC6200 can configure with gate unit. Each unit has connected up, down, right and left cell. But the products can't use because had sterilized. So this paper uses Vertex-E (XCV2000E). The cell of FPGA is made up of Configuration Logic Block (CLB) and can't reconfigure with gate unit. This paper uses Vertex-E is composed of the component as cell of XC6200 cell in VertexE

• Geomechanics and Engineering
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• v.9 no.1
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• pp.57-81
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• 2015

Water inrush and mud outburst always restricts the tunnel constructions in mountain area, which becomes a major geological barrier against the development of underground engineering. In view of the complex disaster-causing mechanism and difficult quantitative predictions of water inrush and mud outburst, several theoretical methods are adopted to realize dynamic assessment of water inrush in the progressive process of tunnel construction. Concerning both the geological condition and construction situation, eleven risk factors are quantitatively described and an assessment system is developed to evaluate the water inrush risk. In the static assessment, the weights of eight risk factors about the geological condition are determined using Analytic Hierarchy Process (AHP). Each factor is scored by experts and the synthesis scores are weighted. The risk level is ultimately determined based on the scoring outcome which is derived from the sum of products of weights and comprehensive scores. In the secondary assessment, the eight risk factors in static assessment and three factors about construction situation are quantitatively analyzed using fuzzy evaluation method. Subordinate levels and weight of factors are prepared and then used to calculate the comprehensive subordinate degree and risk level. In the dynamic assessment, the classical field of the eleven risk factors is normalized by using the extension evaluation method. From the input of the matter-element, weights of risk factors are determined and correlation analysis is carried out to determine the risk level. This system has been applied to the dynamic assessment of water inrush during construction of the Yuanliangshan tunnel of Yuhuai Railway. The assessment results are consistent with the actual excavation, which verifies the rationality and feasibility of the software. The developed system is believed capable to be back-up and applied for risk assessment of water inrush in the underground engineering construction.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.1-10
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• 2006

It is widely accepted that the coverage with high user densities can only be achieved with small cell such as micro- and pico-cell. The smaller cell size causes frequent handovers between cells and a decrease in the permissible handover Processing delay. This may result in the handover failure. in addition to the loss of some Packets during the handover. In these cases. re-transmission is needed in order to compensate errors, which triggers a rapid degradation of throughput. In this paper, we propose a new handover scheme in the next generation mobile communication systems, in which the handover setup process is done in advance before a handover request by predicting the handover cell based on mobile terminal's current position and moving direction. Simulation is focused on the handover failure rate and Packet loss rate. The simulation results show that our proposed method provides a better performance than the conventional method.

• The Journal of Engineering Geology
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• v.20 no.3
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• pp.243-255
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• 2010

The slope design of an open-pit mine must consider economical efficiency and stability. Thus, the overall slope angle is the principal factor because of limited support or reinforcement options available in such a setting. In this study, slope displacement, as monitored by a GPS system, was analyzed for a coal mine at Pasir, Indonesia. Predictions of failure time by inverse velocity analysis showed good agreement with field observations. Therefore, the failure time of an unstable slope can be roughly estimated prior to failure. A GIS model that combines fuzzy theory and the analytical hierarchy process (AHP) was developed to assess slope instability in open-pit coal mines. This model simultaneously considers seven factors that influence the instability of open-pit slopes (i.e., overall slope gradient, slope height, surface flows, excavation plan, tension cracks, faults, and water body). Application of the proposed method to an open-pit coal mine revealed an enhanced prediction accuracy of failure time and failure site compared with existing methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.648-654
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• 2004

The Mass Flow Controller(MFC) has become crucial in semiconductor manufacturing equipments. It is an important element because the quality and the yield of a semiconductor process are decided by the accurate flow control of gas. Therefore, the demand for implementing the high speed and the highly accurate control of MFCs has been increasing. It is hard to find an article of the control algorithm applied to MFCs. But, it is known that commercially available MFCs adopt PID control algorithms. Particularly, when the system detects the flow by way of heat transfer, the MFC control problem includes the slow response and the nonlinearity. In this paper, MFC control algorithm with a superior performance to the conventional PID algorithm is discussed and the superiority is demonstrated through the experiment. A fuzzy controller was utilized in order to compensate the nonlinearity and the slow response, and the performance is compared with that of an MFC currently available in the market. The control system, in this paper, consists of a personal computer, the data acquisition board and the control algorithm carried out by LabWindows/CVI program on the PC. In addition, a method of estimating the actual flow from the sensor output with the slow response is presented. In conclusion, according to the result of the experiment, the proposed algorithm shows better accuracy and is faster than the conventional controller.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.472-477
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• 2003

멸종위기종의 서식지를 효율적으로 관리하기 위해서는 해당 종의 서식 가능한 지역의 분포를 알아야 한다. 본 연구의 목적은 GIS와 퍼지집합을 이용하여 산양(Nemorhaedus caudatus)의 서식지적합성모형을 개발하여 멸종 위기종의 서식지를 관리하기 위한 정보를 제공하는 것이다. 산양의 서식지적합성모형 개발을 위한 본 연구의 주요내용은 다음과 같다. 첫째, 산양 서식지 이용에 관한 기존 연구를 바탕으로 산양의 잠재적 서식지 환경변수를 분류하였으며, 분석 대상지의 산양 흔적 조사를 통해 서식지 환경변수의 재분류 및 x²검정(Chi-square test)을 통한 변수들의 유용성을 파악하고, 쌍체비교를 통한 환경변수별 가중치를 계산하였다. 둘째, 기존 부울논리(boolean logic)의 단점을 보완하기 위해 현장 조사의 결과를 바탕으로 퍼지논리(fuzzy logic)에 의한 산양 서식지의 각 환경변수별 주제도를 작성하고, 주제도들의 상관관계를 분석하여 상호 관련성이 높은 변수들의 중복을 피하였다. 셋째, 환경변수별 주제도와 변수별 가중치를 바탕으로 다기준평가기법(MCE, Multi-Criteria Evaluation)을 이용하여 분석대상지의 산양 서식지적합성모형을 개발하였다. 마지막으로, 개발된 서식지적합성모형의 타당성을 검증하기 위해 분석대상지 외부 지역을 대상으로 검증을 실시하였다. 분석 결과 분석대상지의 분류정확도는 서식가능성 0.5를 기준으로 93.94%의 매우 높은 분류정확도를 나타내었으며, 검증대상지에서는 95.74%의 분류정확도를 나타내어 본 모형의 분류정확도는 일관성이 높은 것으로 판단되었다. 또한 전체 공원구역에서 서식가능성 0.5이상의 면적은 59%를 차지하였다.퇴적이 우세한 것으로 관측되었다.보체계의 구축사업의 시각이 행정정보화, 생활정보화, 산업정보화 등 다양한 분야와 결합하여 보다 큰 시너지 효과와 사용자 중심의 서비스 개선을 창출할 수 있는 기반을 제공할 것을 기대해 본다.. 이상의 결과를 종합해볼 때, ${\beta}$-glucan은 고용량일 때 직접적으로 또는 $IFN-{\gamma}$ 존재시에는 저용량에서도 복강 큰 포식세로를 활성화시킬 뿐 아니라, 탐식효율도 높임으로써 면역기능을 증진 시키는 것으로 나타났고, 그 효과는 crude ${\beta}$-glucan의 추출조건에 따라 달라지는 것을 알 수 있었다.eveloped. Design concepts and control methods of a new crane will be introduced in this paper.and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be simplified considering a steady state of the process. O

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.465-472
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• 2006

Recently, many suggestions have been made in image segmentation methods for extracting human organs or disease affected area from huge amounts of medical image datasets. However, images from some areas, such as brain, which have multiple structures with ambiruous structural borders, have limitations in their structural segmentation. To address this problem, clustering technique which classifies voxels into finite number of clusters is often employed. This, however, has its drawback, the influence from noise, which is caused from voxel by voxel operations. Therefore, applying image enhancing method to minimize the influence from noise and to make clearer image borders would allow more robust structural segmentation. This research proposes an efficient structural segmentation method by filtering based clustering to extract detail structures such as white matter, gray matter and cerebrospinal fluid from brain MR. First, coherence enhancing diffusion filtering is adopted to make clearer borders between structures and to reduce the noises in them. To the enhanced images from this process, fuzzy c-means clustering method was applied, conducting structural segmentation by assigning corresponding cluster index to the structure containing each voxel. The suggested structural segmentation method, in comparison with existing ones with clustering using Gaussian or general anisotropic diffusion filtering, showed enhanced accuracy which was determined by how much it agreed with the manual segmentation results. Moreover, by suggesting fine segmentation method on the border area with reproducible results and minimized manual task, it provides efficient diagnostic support for morphological abnormalities in brain.