• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1732-1739
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• 2004

In this paper, we proposed a visualization system with ANN algorithm that traits the motion of particles that move colliding in the water, where we got a great deal of variable information and predicts the distribution of particles according to the flowing of water and the pattern of their precipitation. We adopted ART2 to detect sensitively the collision between particles in this visualzation. Various particles and their mutual collision influencing the force such as buoyancy force, gravitational force, and the pattern of precipitation are considered in this system. Flowing particles whose motion is changed with the environment can be visualized in the system presented here as they are in real water.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.2
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• pp.208-218
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• 2014

Objectives: The major objective of this study was to develop and validate a tier 1 exposure model utilizing worker exposure monitoring data and characteristics of worker activities routinely performed at construction sites, in order to estimate worker exposures without sampling. Methods: The Registration, Evaluation, Authorization and Restriction of Chemicals(REACH) system of the European Union(EU) allows the usage of exposure models for anticipating chemical exposure of manufacturing workers and consumers. Several exposure models have been developed such as Advanced REACH Tools(ART). The ART model is based on structured subjective assessment model. Using the same framework, a tier 1 exposure model has been developed. Worker activities at construction sites have been analyzed and modifying factors have been assigned for each activity. Korean Occupational Safety and Health Agency(KOSHA) accrued work exposure monitoring data for the last 10 years, which were retrieved and converted into exposure scores. A separate set of sampling data were collected to validate the developed exposure model. These algorithm have been realized on Excel spreadsheet for convenience and easy access. Results: The correlation coefficient of the developed model between exposure scores and monitoring data was 0.36, which is smaller than those of EU models(0.6~0.7). One of the main reasons explaining the discrepancy is poor description on worker activities in KOSHA database. Conclusions: The developed tier 1 exposure model can help industrial hygienists judge whether or not air sampling is required or not.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.81-97
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• 2003

In this paper, we suggest a method of robust watermarking for protection of multimedia data using the wavelet transform and artificial neural network. for the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except fur the lowest subband LL$_3$, we apply a calculated threshold about chosen cluster as the biggest. We used binary logo watermarks to make sure that it is true or not on behalf of the Gaussian Random Vector. Besides, we tested a method of dual watermark insertion and extraction. For the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except for the lowest subband LL$_3$, we apply a above mentioned watermark insert method. In the experimental results, we found that it has a good quality and robust about many attacks.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.739-748
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• 2014

In this paper, we propose pyramid appearance and global structure action descriptors on both RGB and depth motion history images and a model-free method for human action recognition. In proposed algorithm, we firstly construct motion history image for both RGB and depth channels, at the same time, depth information is employed to filter RGB information, after that, different action descriptors are extracted from depth and RGB MHIs to represent these actions, and then multimodality information collaborative representation and recognition model, in which multi-modality information are put into object function naturally, and information fusion and action recognition also be done together, is proposed to classify human actions. To demonstrate the superiority of the proposed method, we evaluate it on MSR Action3D and DHA datasets, the well-known dataset for human action recognition. Large scale experiment shows our descriptors are robust, stable and efficient, when comparing with the-state-of-the-art algorithms, the performances of our descriptors are better than that of them, further, the performance of combined descriptors is much better than just using sole descriptor. What is more, our proposed model outperforms the state-of-the-art methods on both MSR Action3D and DHA datasets.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.418-434
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• 2018

With the increasing use of the Internet and electronic documents, automatic text categorization becomes imperative. Several machine learning algorithms have been proposed for text categorization. The k-nearest neighbor algorithm (kNN) is known to be one of the best state of the art classifiers when used for text categorization. However, kNN suffers from limitations such as high computation when classifying new instances. Instance selection techniques have emerged as highly competitive methods to improve kNN through data reduction. However previous works have evaluated those approaches only on structured datasets. In addition, their performance has not been examined over the text categorization domain where the dimensionality and size of the dataset is very high. Motivated by these observations, this paper investigates and analyzes the impact of instance selection on kNN-based text categorization in terms of various aspects such as classification accuracy, classification efficiency, and data reduction.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.269-272
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• 1987

This paper is concerned on kinematic analysis and simulation of an automatic feeding mechanism subjected by the motion of a curvilinear inverse cam. The main objection is the development of computer-aided design (CAD) program for simulating the motion of the cam-feeding mechanism using computer-graphics. A computer program CACAFS (Computer-Aided Cam and Automatic Feeding System) is independent of computer hardware used. The program is also interactive using a menu-selection technique. As the second part of the paper for the motion simulation of the cam-feeding system, this paper discusses the state-of-art for CAD. The first part of the paper presents the algorithm to simulate the notion of the cam-feeding mechanism.

• Journal of Welding and Joining
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• v.14 no.3
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• pp.2-11
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• 1996

용접 능률과 품질에 영향을 미치는 여러가지 요인들 중에서 용접기의 성능은 가장 중요한 요소의 하나이다. 이러한 점에서 숙련도에 주로 의존하던 종래의 용접성 에 대한 관념이 바뀌어야 하며, 품질 표준화 작업의 일환으로 용접기 제어 성능의 향상도 절실하다고 하겠다. 용접품질의 제어성능에 직접 영향을 주는 요소가 무엇인지 를 생각해 볼때, 그것은 바로 용접부에 공급되는 에너지의 제어, 용접 물리현상의 이해와 관찰을 기초로 적절한 함수의 설정과 함께 이들의 관리가 필요함을 알게된다. system화된 용접기는 이들 용접의 물리적 현상과 그 해석 결과를 어떤 방식으로든 이용하고 제어하여야 할 것이므로, 용접기 전력제어의 중요성과 함께 제어 소자의 성능은 물론 제어 algorithm의 최적화가 필수 요소임을 실감하게 된다. 따라서, 여기 에서는 제조 공정에서 가장 중요한 용접 공정의 하나인 아크 용접(GMAW, GTAW) system 의 개요와 특성 및 향후 기술개발의 과제에 대하여 기술하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.945-958
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• 2017

This paper proposes a novel method of reversible data hiding in JPEG images. After analyzing the JPEG features, we provide a new algorithm of selecting appropriate blocks and coefficients to carry secret messages. Instead of embedding data into the histogram of all coefficients, we propose a strategy of ordered embedding to hide data by histogram shifts in several rounds. On the recipient end, secret messages can be exactly extracted, and the original JPEG image can be losslessly recovered. Experimental results show that high embedding rate can be achieved with limited distortions. Most importantly, the marked JPEG file generated by the proposed method requires less storage size than state-of-the-art works.

• Journal of Power Electronics
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• v.2 no.1
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• pp.25-31
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• 2002

Servo drives with microcomputer control provide the possibility of using modern and sophisticated control algorithms. As an additional feature it is possible to implement parallel and/or redundant software and hardware structures to realise safe motion or similar security functions. Unfortunately microcomputer control also has some impact on the behaviour of servo drives. Control algorithm, cycle time, sensors and interface have to be perfectly synchronised. Special control schemes are necessary on the line side (power supply) to meet the actual requirements concerning EMC. This contribution presents experiences and results obtained from a modern digital drive system pointing out the influences of low and high accuracy position sensors and the interdependencies mentioned above.

• Journal of Communications and Networks
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• v.17 no.2
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• pp.145-156
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• 2015

In recent years, electronic commerce and online social networks (OSNs) have experienced fast growth, and as a result, recommendation systems (RSs) have become extremely common. Accuracy and robustness are important performance indexes that characterize customized information or suggestions provided by RSs. However, nefarious users may be present, and they can distort information within the RSs by creating fake identities (Sybils). Although prior research has attempted to mitigate the negative impact of Sybils, the presence of these fake identities remains an unsolved problem. In this paper, we introduce a new weighted link analysis and influence level for RSs resistant to Sybil attacks. Our approach is validated through simulations of a broad range of attacks, and it is found to outperform other state-of-the-art recommendation methods in terms of both accuracy and robustness.