• 한국산업융합학회 논문집
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• 제7권2호
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• pp.167-172
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• 2004

Neural networks are used in the framework of sensor based tracking control of robot manipulators. They learn by practice movements the relationship between PSD(an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple back propagation networks one of which is selected according to which division (Corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제4권3호
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• pp.85-90
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• 2015

본 논문에서는 새로운 병렬 이벤트구동 로직 시뮬레이션 기법을 제안한다. 제안한 예측에 기반한 병렬 이벤트구동 시뮬레이션 기법은 병렬 이벤트구동 시뮬레이션에서 다른 로컬시뮬레이션과의 연동 과정에서 사용되는 입력값과 출력값에 실제값과 예측값을 함께 사용함으로써 성능 향상의 제약 요소인 동기 오버헤드 및 통신 오버헤드를 크게 감소시킬 수 있다. 본 논문에서 제안한 예측기반 병렬 이벤트구동 로직 시뮬레이션의 유용함은 다수의 디자인들에 적용한 실험을 통하여 확인할 수 있었다.

• 전기전자학회논문지
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• 제19권2호
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• pp.176-185
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• 2015

The study aims to a design hybrid frequency synthesizer in spectrum analyzer and to propose new techniques designed for evasion of in-band spurious. The study focuses on calculating the exact location of multiple phase locked loop of hybrid frequency synthesizer and spurious of direct digital synthesizer to evade in-band spurious outside of frequency range that the user wants to see and thereby simulating technique to improve input related spurious of spectrum analyzer for algorithm. The proposed technique is designed to calculate spurious evasion algorithm in central processing system when in-band spurious arises, and to move output frequency of DDS(direct digital synthesizer) into the place where no in-band spurious exists thereby improving performance of frequency synthesizer. The study used simulation and result representation to prove the effectiveness of the proposed technique.

• Steel and Composite Structures
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• 제18권3호
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• pp.757-773
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• 2015

This work attempts to implement multiple regression analysis (MRA) for modeling and predicting the shear buckling strength of a steel beam with corrugated web. It was recognized from theoretical and experimental results that the shear buckling strength of a steel beam with corrugated web is complicated and affected by several parameters. A model that predicts the shear strength of a steel beam with corrugated web with reasonable accuracy was sought. To that end, a total of 93 experimental data points were collected from different sources. Then mathematical models for the key response parameter (shear buckling strength of a steel beam with corrugated web) were established via MRA in terms of different input geometric, loading and materials parameters. Results indicate that, with a minimal processing of data, MRA could accurately predict the shear buckling strength of a steel beam with corrugated web within a 95% confidence interval, having an $R^2$ value of 0.93 and passing the F- and t-tests.

• 산업경영시스템학회지
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• 제23권54호
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• pp.13-26
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• 2000

Machining route selection to produce parts should be based on shop flow information because of input data at scheduling tasks and is one of the main problem in process planning. This paper addresses the problem of machining route selection in multi-stage process with machine group included a similar function. The model proposed is formulated as 0-1 integer programing considering the relation of parts and machine table size, avaliable time of each machine for planning period, and delivery date. The objective of the model is to minimize the sum of processing, transportation, and setup time for all parts. Genetic algorithm approach is developed to solve this model. The efficiency of the approach is examined in comparison with the method of branch and bound technique for the same problem. Also, this paper is to solve large problem scale and provide it if the multiple machining routes are existed an optimal solution.

• 전기전자학회논문지
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• 제2권1호
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• pp.96-100
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• 1998

DCT 변환을 기반으로 하는 비디오 코딩은 많은 사용자와 더불어 급속한 기술 발전을 하게 되었다. 공간영역내에서 디코딩을 수행하는 것보다 DCT 영역에서 직접 데이터를 처리하는 것이 계산속도 면에서 빠르다. 그리고 블록처리 알고리듬은 병렬처리에 기초하므로 데이터 처리속도가 빠른 하드웨어로 구성되어질 수 있다. 본 논문에서는 서브밴드의 필터뱅크에서 블록변환영역 필터링을 이용한 JPEG브라우저를 제안한다. 디코딩시에 압축된 파일로부터 전체 영상을 디코딩하는대신 사용자가 원하는 크기의 영상을 브라우징 할 수 있다. 한편 DCT 영상 데이터가 입력으로 사용될 경우 제안된 블록변환 필터링은 일반적인 서브밴드 필터링보다 필터뱅크내에서의 곱셈 수를 줄임으로서 계산속도면에서 빠른 결과를 얻을 수 었다.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.313-326
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• 2020

Deep Learning is the most important key to the development of Artificial Intelligence (AI). There are several distinguishable architectures of neural networks such as MLP, CNN, and RNN. Among them, we try to understand one of the main architectures called Recurrent Neural Network (RNN) that differs from other networks in handling sequential data, including time series and texts. As one of the main tasks recently in Natural Language Processing (NLP), we consider Neural Machine Translation (NMT) using RNNs. We also summarize fundamental structures of the recurrent networks, and some topics of representing natural words to reasonable numeric vectors. We organize topics to understand estimation procedures from representing input source sequences to predict target translated sequences. In addition, we apply multiple translation models with Gated Recurrent Unites (GRUs) in Keras on English-Korean sentences that contain about 26,000 pairwise sequences in total from two different corpora, colloquialism and news. We verified some crucial factors that influence the quality of training. We found that loss decreases with more recurrent dimensions and using bidirectional RNN in the encoder when dealing with short sequences. We also computed BLEU scores which are the main measures of the translation performance, and compared them with the score from Google Translate using the same test sentences. We sum up some difficulties when training a proper translation model as well as dealing with Korean language. The use of Keras in Python for overall tasks from processing raw texts to evaluating the translation model also allows us to include some useful functions and vocabulary libraries as well.

• Journal of Information Processing Systems
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• 제14권4호
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• pp.892-903
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• 2018

The paper proposes a novel gait recognition algorithm based on feature fusion of gait energy image (GEI) dynamic region and Gabor, which consists of four steps. First, the gait contour images are extracted through the object detection, binarization and morphological process. Secondly, features of GEI at different angles and Gabor features with multiple orientations are extracted from the dynamic part of GEI, respectively. Then averaging method is adopted to fuse features of GEI dynamic region with features of Gabor wavelets on feature layer and the feature space dimension is reduced by an improved Kernel Principal Component Analysis (KPCA). Finally, the vectors of feature fusion are input into the support vector machine (SVM) based on multi classification to realize the classification and recognition of gait. The primary contributions of the paper are: a novel gait recognition algorithm based on based on feature fusion of GEI and Gabor is proposed; an improved KPCA method is used to reduce the feature matrix dimension; a SVM is employed to identify the gait sequences. The experimental results suggest that the proposed algorithm yields over 90% of correct classification rate, which testify that the method can identify better different human gait and get better recognized effect than other existing algorithms.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.775-779
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• 2002

Currently, high-resolution satellite imagery such as KOMPSAT and IKONOS has been tentatively utilized to various types of urban engineering problems such as transportation planning, site planning, and utility management. This approach aims at software development and followed applications of remotely sensed imagery to transportation geographic analysis. At first, GDPA (Gradient Direction Profile Algorithm) and main modules in it are overviewed, and newly implemented results under MS visual programming environment are presented with main user interface, input imagery processing, and internal processing steps. Using this software, road network are automatically generated. Furthermore, this road network is used to transportation geographic analysis such as gamma index and road pattern estimation. While, this result, being produced to do-facto format of ESRI-shapefile, is used to several types of road layers to urban/transportation planning problems. In this study, road network using KOMPSAT EOC imagery and IKONOS imagery are directly compared to multiple road layers with NGI digital map with geo-coordinates, as ground truth; furthermore, accuracy evaluation is also carried out through method of computation of commission and omission error at some target area. Conclusively, the results processed in this study is thought to be one of useful cases for further researches and local government application regarding transportation geographic analysis using remotely sensed data sets.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 춘계학술발표대회
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• pp.87-89
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• 2014

Aho-Corasick (AC) 알고리즘은 실시간 성능을 요하는 많은 응용 분야에 적용되는 스트링 매칭 알고리즘으로서, 한번에 여러 개의 패턴들을 동시에 매칭시키는 것이 가능하다. 본 논문에서는 Intel 의 Many Integrated Core (MICO 아키텍쳐인 Xeon Phi 칩 상에서 AC 알고리즘을 병렬화한다. 이를 위하여 AC 알고리즘에서 입력 데이터에 대하여 여러 개의 패턴들을 동시에 매칭시키는 데에 사용되는 Deterministic Finite Automaton 구조를 압축시키는 새로운 기법을 제안한다. 이 기법은 캐시 미스를 감소시켜서 XeonPhi 상에서 AC 알고리즘의 성능을 크게 향상시킨다.