• Journal of Information Processing Systems
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• 제15권6호
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• pp.1326-1334
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• 2019

Knowledge base means a library stored in computer system providing useful information or appropriate solutions to specific area. Knowledge base associated with autism is the complex multidimensional information set related to the disease autism for its pathogenic factor and therapy. This paper focuses on the knowledge of biological molecular information extracted from massive biomedical texts with the aid of widespread used machine learning methods. Six classes of biological molecular information (such as protein, DNA, RNA, cell line, cell component, and cell type) are concerned and the probability statistics method, conditional random fields (CRFs), is utilized to discover these knowledges in this work. The knowledge base can help biologists to etiological analysis and pharmacists to drug development, which can at least answer four questions in question-answering (QA) system, i.e., which proteins are most related to the disease autism, which DNAs play important role to the development of autism, which cell types have the correlation to autism and which cell components participate the process to autism. The work can be visited by the address http://134.175.110.97/bioinfo/index.jsp.

• 한국안전학회지
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• 제11권1호
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• pp.133-141
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• 1996

In spite of a tendency automatizing manaufacturing processes, since power presses are highly repetitive at high speeds, they have still been using to a large extent in many industries. More often than not, press workers have to make decisions whether work materials are located well or not, they should rearrange them or not, and their bodies would be safe or not. If the decision would be wrong, of course, they cause severe damages to human workers so that many workers haven't been willing to work with them. However, with the help of computer technologies, it would be possible to aid the press workers' decisions, and to allow or prohibit them from inserting their hands between slide rams and dies. Thus, this research was aimed to evaluate and analyze possibilities of applying Image Processing Techniques for prevention of press accidents. Through a series of procedures including Capturing work sites and material, Image Enhancement, Contouring, and Edge Finding, work characteristics were obtained and analyzed. The results showed that there were somewhat differences in image characteristics between accident-induced work scenes and accident-free ones. Consequently, if the image analyses are well carried out in real time, they would give a successful help to human press workers.

• 한국빅데이터학회지
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• 제8권1호
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• pp.61-71
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• 2023

데이터 기반 의사결정 방법론, 고도화된 빅데이터 처리 기법의 발달로 데이터를 처리하는 방법에 대한 정보의 수요가 늘어나고 있다. 데이터를 활용하는 거의 모든 작업과 연구에서 데이터 전처리 과정이 포함되나, 이러한 과정은 주장하고자 하는 내용이나 결과물을 도출하기 위한 수단으로써 언급될 뿐 실질적인 과정에 대해서 자세하게 설명하고 있는 연구는 부족하였다. 실질적인 분석 기법을 활용하기 이전의 단계로 간단하게 언급되는 경우가 많아 데이터 처리에 대한 인사이트를 획득하기 어려운 경우가 많았다. 따라서 이 연구에서는, raw data에서부터 데이터를 처리하는 과정, 즉 데이터 처리 파이프라인에 대해서 자세하게 작성하고자 하였다. 특히 수입식품 수입 절차에 대한 설명을 구체화함으로써 해당 상황에서 데이터의 필드들이 어떻게 해석될 수 있고 어떠한 필드들을 왜 활용하게 되었는지에 대한 상황과 관련 도메인 지식을 공유하면서 흐름을 기술하고자 하였다.

• 소성∙가공
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• 제33권1호
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• pp.50-54
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• 2024

In this paper, the process of extruding Cu-10Fe alloy using a finite element analysis (FEA) was theoretically analyzed. To achieve this, the dependence of strain rate and temperature of the alloy required for the extrusion process was secured by utilizing databases for Cu and Fe and the KHL model. For microstructure analysis, FE-SEM with EDS was used to distinguish the phases present in Cu-10Fe alloy. The mechanical characteristics of Cu-10Fe alloy were secured using the results of fitting the mechanical properties of Copper and Steel from the Deform database to the KHL model. The deformation behavior within the alloy during hot extrusion was analyzed, providing insights into effective stress, effective strain, effective strain rate, and temperature. It was observed that the strain distribution was non-uniform. These research findings contribute to an improved understanding of the hot extrusion process of Cu-10Fe alloy and can aid in predicting the mechanical properties of the material.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.285-288
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• 2007

There is substantial evidence from earlier researches that older adults have difficult seeing under low illumination and at night, even in the absence of ocular diseases. During human aging, there is a rampant decrease in rod/cone-meditated adaptation which is caused by delayed rhodopsin regeneration and pigment depletion. This calls for a need to develop appropriate visual gadgets to effectively aid the aging generation. Our research culminates its approach from Pattanaik's model by making extensions to temporal visual filtering, thereby simulating a reduction of visual response which comes with age. Our filtering model paves way and lays a foundation for future research to develop a more effective adaptation model that may be further used in developing visual content adaptation aids and guidelines in MPEG 21 environment. We demonstrate our visual model using a High Dynamic Range image and the experiment results are in conversant with the psychophysical data from previous vision researches.

• 재활복지공학회논문지
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• 제11권1호
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• pp.63-71
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• 2017

본 논문에서는 달팽이관의 정원창 이식용으로 최근 새롭게 제안된 3코일 벨로우즈형 진동체(tri-coil bellows transducer, TCBT)를 이용하는 반이식형 인공중이(semi-implantable middle ear hearing device)를 위한 신호처리회로를 설계하였다. 설계된 반이식형 인공중이는 높은 효율을 가지는 유도결합 방법을 이용하여 귀 뒤편에 착용되는 체외기와 대응되는 피부 내측에 위치하는 체내기 간에 데이터를 전송한다. 귀 뒤 부위의 피부두께를 포함하는 반이식형 인공중이의 송수신 거리를 고려하여 송수신 코일과 신호처리 회로를 설계 및 구현하였다. 또한 데이터 전송 효율을 높이기 위하여, 전력을 충분히 증폭하기 위한 체외기의 출력부도 설계 하였다. 유도결합 방식을 이용한 반이식형 인공중이의 동작을 확인하기 위하여, PSpice를 이용하여 회로해석을 수행하였으며, 활용 가능한 크기의 신호처리 보드를 제작하여 그 성능을 검증하였다.

• 한국분말재료학회지
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• 제23권2호
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• pp.143-148
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• 2016

A microfluidic reactor with computer-controlled programmable isocratic pumps and online detectors is employed as a combinatorial synthesis system to synthesize and analyze materials for fabricating CdSe quantum dots for various applications. Four reaction condition parameters, namely, the reaction temperature, reaction time, Cd/Se compositional ratio, and precursor concentration, are combined in synthesis condition sets, and the size of the synthesized CdSe quantum dots is determined for each condition. The average time corresponding to each reaction condition for obtaining the ultraviolet-visible absorbance and photoluminescence spectra is approximately 10 min. Using the data from the combinatorial synthesis system, the effects of the reaction conditions on the synthesized CdSe quantum dots are determined. Further, the data is used to determine the relationships between the reaction conditions and the CdSe particle size. This method should aid in determining and selecting the optimal conditions for synthesizing nanoparticles for diverse applications.

• 전기학회논문지
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• 제60권4호
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• pp.862-870
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• 2011

In this paper, we introduce a new topology of Radial Basis Function-based Polynomial Neural Networks (RPNN) that is based on a genetically optimized multi-layer perceptron with Radial Polynomial Neurons (RPNs). This study offers a comprehensive design methodology involving mechanisms of optimization algorithms, especially Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization (PSO) algorithms. In contrast to the typical architectures encountered in Polynomial Neural Networks (PNNs), our main objective is to develop a design strategy of RPNNs as follows : (a) The architecture of the proposed network consists of Radial Polynomial Neurons (RPNs). In here, the RPN is fully reflective of the structure encountered in numeric data which are granulated with the aid of Fuzzy C-Means (FCM) clustering method. The RPN dwells on the concepts of a collection of radial basis function and the function-based nonlinear (polynomial) processing. (b) The PSO-based design procedure being applied at each layer of RPNN leads to the selection of preferred nodes of the network (RPNs) whose local characteristics (such as the number of input variables, a collection of the specific subset of input variables, the order of the polynomial, and the number of clusters as well as a fuzzification coefficient in the FCM clustering) can be easily adjusted. The performance of the RPNN is quantified through the experimentation where we use a number of modeling benchmarks - NOx emission process data of gas turbine power plant and learning machine data(Automobile Miles Per Gallon Data) already experimented with in fuzzy or neurofuzzy modeling. A comparative analysis reveals that the proposed RPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Journal of Communications and Networks
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• 제1권3호
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• pp.201-212
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• 1999

This paper studies the rapid design and implementation of the medium access control(MAC) and related interface circuits for 802.11 wireless LANs based on the field programmed gate ar-ray(FPGA) technology. Our design is thus aimed to support both the distributed coordination function (DCF) and the point coordination function(PCF) with the aid of FPGA technology. Further-more, in an infrastructure network, some stations may serve as the access points (APs) which may function like a learning bridge. This paper will also discuss how to design for such application. The hardware of the MAC and interface may at least consist of three major parts: wireless transmission and reception processes and in-terface, host(bus) interface, and the interface to the distributed system (optional). Through the increasing popularity of FPGA de-sign, this paper presents how Complex Programmable Logic De-vices(CPLD) can be utilized for speedy design of prototypes. It also demonstrates that there is much room for low-cost hardware prototype design to accelerate the processing speed of the MAC control function and for field testing.

• ETRI Journal
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• 제27권5호
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• pp.585-594
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• 2005

A small electronic nose (E-Nose) system has been developed using an 8-channel vapor detection array and personal digital assistant (PDA). The sensor array chip, integrated on a single microheater-embedded polyimide substrate, was made of carbon black-polymer composites with different kinds of polymers and plasticizers. We have successfully classified various volatile organic compounds such as methanol, ethanol, i-propanol, benzene, toluene, n-hexane, n-heptane, and c-hexane with the aid of the sensor array chip, and have evaluated the resolution factors among them, quantitatively. To achieve a PDA-based E-Nose system, we have also elaborated small sensor-interrogating circuits, simple vapor delivery components, and data acquisition and processing programs. As preliminary results show, the miniaturized E-Nose system has demonstrated the identification of essential oils extracted from mint, lavender, and eucalyptus plants.