• Title/Summary/Keyword: Operator Performance

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Development and Implementation of Statistical Edge Detectors on the Web (웹 상에서 통계적 에지검출기 개발 및 구현)

  • Lim, Dong-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.4 s.36
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    • pp.133-141
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    • 2005
  • An edge is where the intensity of an image moves from a low value to high value or vice versa. The edges tell where objects are. their shape and size. and something about their texture. Many traditional edge operators are derivative based and perform reasonably well for simple noise-free images. In recent, statistical edge detectors for complex images with noises have been described. This paper compares and analysis the performance of statistical edge detectors based on the T test and Wilcoxon test, and mathematical edge detectors based on Sobel operator, and the well-known Canny detector and Wavelet transformation detector, and provides the implementation of these edge detectors using Java on the web.

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A Study on Semantic Association between Transmitted Information and Design Parameters of Vibrotactile Signals

  • Kim, Sangho;Lee, Hyunsoo
    • Journal of the Ergonomics Society of Korea
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    • v.32 no.4
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    • pp.371-380
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    • 2013
  • Objective: The aim of this study is to investigate the effects of design parameters of vibrotactile signals on semantic association with transmitted information conveying different meanings. Background: As information communication relying on human visual channel becomes excessive, the utility of vibrotactile signals is being interested as a substitute measure of delivering information. Properly designed hapticons may relieve burden of visual communication by rendering distinct and meaningfully compatible haptic sensations. Method: A typical Kansei engineering approach was adopted in this study. Ten most distinctive hapticons were selected among those having different frequencies and amplitudes. Associations between the hapticons and twenty four pairs of adjectives used to describe the state of automobile in control were gathered from thirty subjects using semantic differential scales. Results: The selected pairs of adjectives were summarized by factor analysis into two semantic dimensions named 'Awareness' and 'Directionality'. The experimental hapticons matched with the semantic dimensions were presented as a haptic emotion map. Conclusion: The results from this study support that frequencies and amplitudes of haptic signals play important roles in arousing different human perceptions regarding the two haptic emotional dimensions. Application: Properly designed hapticons with respect to the contents of transmitted information will increase human operator's situation awareness as well as system performance. The result from this study can be used to develop standardized hapticons for active haptic communication.

An Onboard Image Processing System for Road Images (도로교통 영상처리를 위한 고속 영상처리시스템의 하드웨어 구현)

  • 이운근;이준웅;조석빈;고덕화;백광렬
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.7
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    • pp.498-506
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    • 2003
  • A computer vision system applied to an intelligent safety vehicle has been required to be worked on a small sized real time special purposed hardware not on a general purposed computer. In addition, the system should have a high reliability even under the adverse road traffic environment. This paper presents a design and an implementation of an onboard hardware system taking into account for high speed image processing to analyze a road traffic scene. The system is mainly composed of two parts: an early processing module of FPGA and a postprocessing module of DSP. The early processing module is designed to extract several image primitives such as the intensity of a gray level image and edge attributes in a real-time Especially, the module is optimized for the Sobel edge operation. The postprocessing module of DSP utilizes the image features from the early processing module for making image understanding or image analysis of a road traffic scene. The performance of the proposed system is evaluated by an experiment of a lane-related information extraction. The experiment shows the successful results of image processing speed of twenty-five frames of 320$\times$240 pixels per second.

A Study on the MDS performance improvement for Twofish cryptographic algorithm speed-up (Twofish 암호알고리즘의 처리속도 향상을 위한 MDS 성능개선에 관한 연구)

  • Lee, Seon Keun;Kim, Hwan Yong
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.42 no.10 s.340
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    • pp.35-38
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    • 2005
  • Treatise that see designed MDS block newly algorithm itself is concise and improve the speed of Twofish cryptographic algorithm that easy of implement is good but the processing speed has slow shortcoming than Rijndael cryptographic algorithm Problem of speed decline by a bottle-neck phenomenon of processing process existed as block that designed MDS block occupies critical path of Twofish cryptographic system Multiplication arithmetic that is used by operator in this MDS convex using LUT arithmetic and modulo-2 arithmetic speed decline and a bottle-neck phenomenon about MDS itself remove. Twofish cryptographic system including MDS block designed newly by these result confirmed that bing elevation of the processing speed about $10\%$ than existing Twofish cryptographic system.

Simulation and Experimental Study of A TLP Type Floating Wind Turbine with Spoke Platform

  • Kim, Hyuncheol;Kim, Imgyu;Kim, Yong Yook;Youn, DongHyup;Han, Soonhung
    • Journal of Advanced Research in Ocean Engineering
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    • v.2 no.4
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    • pp.179-191
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    • 2016
  • As the demand for renewable energy has increased following the worldwide agreement to act against global climate change and disaster, large-scale floating offshore wind systems have become a more viable solution. However, the cost of the whole system is still too high for practical realization. To make the cost of a floating wind system be more economical, a new concept of tension leg platform (TLP) type ocean floating wind system has been developed. To verify the performance of a 5-MW TLP type ocean floating wind power system designed by the Korea Advanced Institute of Science and Technology, the FAST simulation developed by the National Renewable Energy Laboratory is used. Further, 1/50 scale model tests have been carried out in the ocean engineering tank of the Research Institute of Medium and Small Shipbuilding, Korea. This paper compares the simulation and ocean engineering tank test results on motion prediction and tension assessment of the TLP anchor.

Optimized Ballast Water Exchange Management for Bulk Carriers (벌크 화물선용 자동 밸러스트수 교환계획 시스템 개발)

  • HONG CHUNG-YOU;PARK JE-WOONG
    • Journal of Ocean Engineering and Technology
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    • v.18 no.4 s.59
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    • pp.65-70
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    • 2004
  • Many port states, such as New Zealand, U.S.A., Australia, and Canada, have strict regulations to prevent arriving ships from discharging polluted ballast water that contains harmful aquatic organisms and pathogens. They are notified that transfer of polluted ballast water can cause serious injury to public health and damage to property and environment. For this reason, ballast exchange in deep sea is perceived as the most effective method of emptying ballast water. The ballast management plan contains the effective exchange method, ballast system, and safety considerations. In this study, we pursued both nautical engineering analysis and optimization of the algorithm, in order to generate the sequence of stability and rapidity. A heuristic algorithm was chosen on the basis of optimality and applicability to a sequential exchange problem. We have built an optimized algorithm for the automatic exchange of ballast water, by redefining core elements of the A$\ast$ algorithm, such as node, operator, and evaluation function. The final version of the optimized algorithm has been applied to existing bulk carrier, and the performance of the algorithm has been successfully verified.

Vulnerability Assessment of a Large Sized Power System Using Neural Network Considering Various Feature Extraction Methods

  • Haidar, Ahmed M. A;Mohamed, Azah;Hussian, Aini
    • Journal of Electrical Engineering and Technology
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    • v.3 no.2
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    • pp.167-176
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    • 2008
  • Vulnerability assessment of power systems is important so as to determine their ability to continue to provide service in case of any unforeseen catastrophic contingency such as power system component failures, communication system failures, human operator error, and natural calamity. An approach towards the development of on-line power system vulnerability assessment is by means of using an artificial neural network(ANN), which is being used successfully in many areas of power systems because of its ability to handle the fusion of multiple sources of data and information. An important consideration when applying ANN in power system vulnerability assessment is the proper selection and dimension reduction of training features. This paper aims to investigate the effect of using various feature extraction methods on the performance of ANN as well as to evaluate and compare the efficiency of the proposed feature extraction method named as neural network weight extraction. For assessing vulnerability of power systems, a vulnerability index based on power system loss is used and considered as the ANN output. To illustrate the effectiveness of ANN considering various feature extraction methods for vulnerability assessment on a large sized power system, it is verified on the IEEE 300-bus test system.

A Study on the Recognition of an English Calling Card by using Contour Tracking Algorithm and Enhanced ART1 (윤곽선 추적 알고리즘과 개선된 ART1을 이용한 영문 명함 인식에 관한 연구)

  • 김광백;김철기;김정원
    • Journal of Intelligence and Information Systems
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    • v.8 no.2
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    • pp.105-115
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    • 2002
  • This paper proposed a recognition method of english calling card using both 4-directed contour tracking algorithm and enhanced ART1 algorithm. After we extract candidate character string region using horizontal smearing and 4-directed contour tracking method, we extract character string region through comparison of character region and non-character region using horizontal and vertical ratio and area in english calling card. In extracted character string region, we extract each character using horizontal smearing and contour tracking algorithm, and recognize each character by enhanced ART1 algorithm. The proposed ART1 algorithm is enhanced by dynamic control of similarity using fuzzy sum connective operator. The result indicate that the proposed method is superior in performance.

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A Study on the Prediction of Ship's Roll Motion using Machine Learning-Based Surrogate Model (기계학습기반의 근사모델을 이용한 선박 횡동요 운동특성 예측에 관한 연구)

  • Kim, Young-Rong;Park, Jun-Bum;Moon, Serng-Bae
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2018.05a
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    • pp.41-42
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    • 2018
  • This study is about the prediction of ship's roll motion characteristic which has been used for evaluating ship's seakeeping performance. In order to obtain the ship's roll RAO during voyage, this paper utilized machine learning-based surrogate model. By comparing the prediction result data of surrogate model with test data, we suggest the best approximation technique and data sampling interval of the surrogate model appropriate for predicting the ships' roll motion characteristic.

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A Study on Face Recognition using a Hybrid GA-BP Algorithm (혼합된 GA-BP 알고리즘을 이용한 얼굴 인식 연구)

  • Jeon, Ho-Sang;Namgung, Jae-Chan
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.2
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    • pp.552-557
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    • 2000
  • In the paper, we proposed a face recognition method that uses GA-BP(Genetic Algorithm-Back propagation Network) that optimizes initial parameters such as bias values or weights. Each pixel in the picture is used for input of the neuralnetwork. The initial weights of neural network is consist of fixed-point real values and converted to bit string on purpose of using the individuals that arte expressed in the Genetic Algorithm. For the fitness value, we defined the value that shows the lowest error of neural network, which is evaluated using newly defined adaptive re-learning operator and built the optimized and most advanced neural network. Then we made experiments on the face recognition. In comparison with learning convergence speed, the proposed algorithm shows faster convergence speed than solo executed back propagation algorithm and provides better performance, about 2.9% in proposed method than solo executed back propagation algorithm.

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