• Smart Media Journal
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• v.5 no.3
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• pp.25-29
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• 2016

This paper presents research for non-contact gesture recognition system using EPS(Electronic Potential Sensor) for measuring the human body of electromagnetic fields. It implemented a signal acquisition and signal processing system for designing a system suitable for motion recognition using the data coming from the sensors. we transform AC-type data into DC-type data by applying a 10Hz LPF considering H/W sampling rate. in addition, we extract 2-dimensional movement information by taking difference value between two cross-diagonal deployed sensor.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1964-1965
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• 2011

본 연구에서는 패턴분류를 위해 기존의 방사형 기저 함수 신경회로망(Radial Basis Funtion Neural Network)과 다항식 신경회로망(Polynomial Neural Network)을 결합한 다중 출력 방사형 기저 함수다항식 신경회로망 (Multi Output Radial Basis Funtion Polynomial Neural Network)의 분류기를 제안한다. 제안된 모델은 PNN을 기본 구조로 하여 1층에 기존의 다항식 노드 대신 다중 출력 형태의 RBFNN을 적용 한다. RBFNN의 은닉층에는 기존의 활성함수가 아닌 fuzzy 클러스터링을 사용하여 입력 데이터의 특성을 고려한 적합도를 사용하였다. PNN은 입력변수의 수와 다항식 차수가 모델의 성능을 결정함으로 최적화가 필요하며 본 논문에서는 Differential Evolution(DE)을 사용하여 모델의 구조 및 파라미터를 최적화시켜 모델의 성능을 향상시켰다. 패턴분류기로써의 제안된 모델을 평가하기 위해 pima 데이터를 이용하였다.

• The Korean Journal of Rheology
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• v.9 no.1
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• pp.16-26
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• 1997

사출 성형된 제품에서 발생하는 잔류응력은 최종 제춤의 기하학적 정밀도와 기계적 성질 및 열적 성질에 영향을 미친다. 사출성형된 제품의 잔류응력을 예측하기 위해서는 먼 저 열 및 유동장의 해석을 수행하여야 하고이를 위해서는 사출 성형의 세단계. 즉 충전, 보 압, 냉각을 모두고려해야한다. 검사체적 방법에 기초한 혼합 유한요소/유한차분방법을 사용 하는 수치 해석적 기법에 의하여 충전과정가 후충전 과정의 유동장 해서을 수행하였다. 일 반화된 헬레쇼 유동을 가정하였고 보압과 냉각과정시의 고본자의 압축성을 고려하였다. 점 도의 전단 변형률의 크기와 온도에 대한 의존성은 개선된 크로스 모델을 사용하여 나타내었 다. Tait에 의해 제안된 상태방정식은 고분자의 온도, 압력, 부피의 상호관계를 묘사하는 좋 은 방법을 제공하였다. 유동해석을 통하여 전 공정에 걸쳐서 온도와 압\ulcorner장의 변화에 대한 데이터를 얻었고 제품의 고체 응력해석의 입력 데이터로 사용하였다. 유한요소응력해석에는 평면 응력요소를 사용하였다. 다양한 형태의 금형에 대해서 공정 변수들을 달리하여 유동장 의 해석과 잔류응력의 계산을 수행하였다. 이로부터 공정조건과 유동장의 관계를 밝히고 최 종 제춤의 잔류 응력에의 영향을 고찰하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.32-40
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• 2011

Reversible data hiding, which can recover the original image without any distortion after the extraction of the hidden data, has drawn considerable attention in recent years. However, underflow and overflow problems have occurred occasionally in the embedded image. To overcome these problems, we propose a new reversible data hiding algorithm which embeds a compressed location map used to identify these underflow and overflow points. In addition, the proposed algorithm allows for multilevel data hiding to increase the hiding capacity. The simulation results demonstrate that the proposed algorithm generates good performances in the PSNR, the embedding capacity, and the size of side information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.421-427
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• 2013

In general, it can be assumed that the tropospheric effect are removed through double-differencing technique in short-baseline GPS data processing. This means that the high-accuracy positioning can be obtained because various error sources can be eliminated and the number of unknown can be decreased in the adjustment computation procedure. As a consequence, short-baseline data processing is widely used in the fields such as deformation monitoring which require precise positioning. However, short-baseline data processing is limited to achieve high positioning accuracy when the height difference between the reference and the rover station is significant. In this study, the effects of tropospheric delays on the determination of short-baseline is analyzed, which depends on the orientation of baseline. The GPS measurements which include tropospheric effect and measurement noises are generated by simulation, and then rover coordinates are computed by short-baseline data processing technique. The residuals of rover coordinates are analyzed to interpret the tropospheric effect on the positioning. The results show that the magnitudes of the biases in the coordinate residuals increase as the baseline length gets longer. The increasing rate is computed as 0.07cm per meter in baseline length. Therefore, the tropospheric effects should be carefully considered in short-baseline data processing when the significant height difference between the reference and rover is observed.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.1
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• pp.55-63
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• 2000

This paper investigated the sub-region compression effect of the three dimensional DCT(3D-DCT) using the difference component(DC) of inter-frame in images. The proposed algorithm are the method that obtain compression effect to divide the information into subband after 3D-DCT, the data appear the type of cubic block(8${\times}$8${\times}$8) in eight difference components per unit. In the frequence domain that transform the eight differential component frames into eight DCT frames with components of both spatial and temporal frequencies of inter-frame, the image data are divided into frame component(8${\times}$8 block) of time-axis direction into 4${\times}$4 sub block in order to effectively obtain compression data because image components are concentrate in corner region with low-frequency of cubic block. Here, using the weight of sub block, we progressed compression ratio as consider to adaptive sub-region of low frequency part. In simulation, we estimated compression ratio, reconstructed image resolution(PSNR) with the simpler image and the complex image contained the higher frequency component. In the result, we could obtain the high compression effect of 30.36dB(average value in the complex-image) and 34.75dB(average value in the simple-image) in compression range of 0.04~0.05bpp.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.270-278
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• 2014

The stability and security management of IT data becomes more important because information security threats increases rapidly in Big Data era. The operational policy of the data backup considering information security threats is required because the backup policy is the fundamental method that prevents the damage of security threats. We present an economic approach for a data backup system with information security threats which damage the system. The backup operation consists of the differential backup and the batch backup. We present a stochastic model considering the occurrence of information security threats and their damage. We analyze the stochastic model to derive the performance measures for the cost analysis. Finally we analyze the average cost of the system and give numerical examples.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.93-100
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• 2024

With the advent of the Fourth Industrial Revolution, cutting-edge technologies such as artificial intelligence, big data, the Internet of Things, and cloud computing are driving innovation across industries. These technologies are generating massive amounts of data that many companies are leveraging. However, there is a notable reluctance among users to share sensitive information due to the privacy risks associated with collecting personal data. This is particularly evident in the healthcare sector, where the collection of sensitive information such as patients' medical conditions poses significant challenges, with privacy concerns hindering data collection and analysis. This research presents a novel technique for collecting and analyzing medical data that not only preserves privacy, but also effectively extracts statistical information. This method goes beyond basic data collection by incorporating a strategy to efficiently mine statistical data while maintaining privacy. Performance evaluations using real-world data have shown that the propose technique outperforms existing methods in extracting meaningful statistical insights.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.84-91
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• 2007

As GPS equipments improve, one can acquire GPS data easily in the field. To obtain precise and accurate coordinates, however, post processing is additionally required and the processing needs high degree of skills. Besides, it is very common that we cannot operate processing softwares in the field because the required system environment is usually not prepared. The aim of this study is the development of an internet-based GPS data processing service. For post processing, we used GIPSY developed by JPL. It has many advantages such as obtaining coordinates quickly by using precise or predicted ephemeris. This service proceeds as following orders by interlocking GIPSY software and internet service which is operated on a Linux platform: Users upload the raw data file on the internet, then GIPSY runs automatically and then the user gets the result in the field. We use an Apache web server as the hosting program and PHP scripts are used in coding web pages. The total processing time including data-uploading was around 30 seconds for a 24-hour data with a 30-second sampling rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.749-754
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• 2011

In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.