• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.6 s.348
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• pp.30-37
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• 2006

This paper presents a modified scan cell architecture to reduce the power dissipation during testing. It not only eliminates switching activities in the combinational logic during scan shifting but also reduces switching activities in the scan chain during the time. Furthermore, it limits the transitions on capture cycles. It can be made for test-per-scan BIST and employed in both single scan style and multiple scan style. Experimental results demonstrate that the proposed structure achieves the same fault coverage with lower power consumption compared to other existing BIST schemes.

• Journal of Life Science
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• v.19 no.7
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• pp.968-975
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• 2009

The purpose of the present study was to examine effects of different exercise training modes (Aerobic Training, Resistance Training) on exercise specificity and transability. The tested subjects, composed of 10 healthy males without known family history or medical illnesses, were divided into two groups: Aerobic Training Group (ATG; n=5) and Resistance Training Group (RTG; n=5). An aerobic training program, based on maximum oxygen consumption rates taken during standard testing, was conducted in 60 minute sessions 3 times a week, and the Heart Rate Reserve (HRR) at 70% of maximum oxygen consumption rate was measured the using Polar. In the weight training program, based on repetition maximum rate (1-RM) taken during standard testing, the weight at 70% of such rates was measured during 60 minute sessions of 7 categories of exercise (Bench press, Leg press, Squat, Shoulder press, Arm curt Lat pull down, Triceps pull down), conducted 3 times a week. The data collected from this research were calculated to obtain average and differences compared to standards using an SPSS 11.0 statistics package. In conclusion, increase in V0$_{2max}$ and production of NO$_x$ (NO$_2$/NO$_3$), reduction of %fat, MAPwere shown effective in aerobic training and in different exercise tests, and aerobic testing within the aerobic training group (ATG) was shown to be more effective. In contrast, resistance training was shown to be more effective for the reduction of CK and LDH, and even in different tests, the resistance test within the resistance training group (RTG) showed to be more effective. Exercise specificity also significantly increased in both groups (ATG, RTG). but there was no significant difference in transability in both groups (ATG, RTG).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1676-1681
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• 2020

Collecting and managing information on all-round activities of students not only helps to improve school life adjustment and satisfaction, but also serves as the basis for preventive student support for academic warnings or dropouts. Therefore, in guiding students, it is necessary to integrate various information of students and provide them to the instructor quickly and accurately. In this study, in the special environment of an organization in which student information is scattered in several systems, a system model is proposed that not only integrates and provides student information to instructors quickly, but also saves cost and effort. And we tested the effectiveness of the proposed system model by developing a simple web page. As a result, it was confirmed that the proposed model provided information necessary for student guidance in an integrated, multifaceted, and instantaneous manner, and that user satisfaction was improved through an improved UI.

• Archives of design research
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• v.20 no.3 s.71
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• pp.215-224
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• 2007

A VR-Tangible Interaction therapy system for autistic children has been designed and implemented. The purpose of this system is to provide a virtual interactive experience for autistic children to check their performances in various tasks and to provide them with the effect of a medical treatment. An interdisciplinary study was deployed by a group of designers, doctors, psychologists and engineers. 14 interaction scenarios were designed and developed. Scenarios include such tasks as to guess a person's feeling by watching his facial expressions, to choose what a person is gazing at, and to pop virtual balloons with a stick. A prototype system was developed and a pilot study made with 11 autistic children. The test showed that autistic children easily understood and enjoyed the virtual environment, and promising theraphy results were also found.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.159-166
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• 2016

In this paper, an active object tracking system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and phase-type correlation scheme and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-embedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 480 frames of the test input stereo image, it is analyzed that a standard variation between the measured and computed the estimated target's height and an error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 1.03 and 1.18% on average, respectively. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.156-165
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• 2006

In this paper, a new intelligent moving target tracking and surveillance system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and phase-type correlation scheme and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-imbedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 480 frames of the test input stereo image, it is analyzed that a standard variation between the measured and computed the estimated target's height and an error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 1.03 and 1.18$\%$ on average, respectively. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.

• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.21-29
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• 1996

Industrial equipment, such as power plant, is required to operate reliably, continuously and economically under rather severe conditions of temperature, stress, and enbironment. To test structural integrity and fitness, ultrasonic nondestructive testing is used because of effectiveness and simplicity. In this paper, wavelet transform based least mean square(LMS) algorithm is applied to reduce the influence of the interference occurring between randomly positioned small scatters. The RUN test is performed to check the nonstationarity of the speckle noise signal. The performance of this new approach is compared with that of the time domain LMS algorithm by means of condition numbers, signal-to-noise ratio and 3-D image. As a result, the wavelet transform based LMS algorithm shows better performance than the time domain LMS algorithm in this experiment.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.55-61
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• 2020

In this paper, we present a novel approach to efficiently control the location of NPC(Non-playable characters) in the interactive virtual world such as game, virtual reality. To control the NPC's movement path, we first calculate the main trajectory based on the user's path, and then move the NPC based on the weight map. Our method constructs automatically a navigation mesh that provides new paths for NPC by referencing the user trajectories. Our method enables adaptive changes to the virtual world over time and provides user-preferred path weights for smartagent path planning. We have tested the usefulness of our algorithm with several example scenarios from interactive worlds such as video games, virtual reality. In practice, our framework can be applied easily to any type of navigation in an interactive world.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.433-441
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• 2021

Android applications are released across various categories, including productivity apps and games, and users are exposed to various applications and even malware depending on their usage patterns. On the other hand, most analysis engines train using existing datasets and do not reflect user patterns even if periodic updates are made. Thus, the detection rate for known malware is high, while types of malware such as adware are difficult to detect. In addition, existing engines incur increased service provider costs due to the cost of server farm, and the user layer suffers from problems where availability and real-timeness are not guaranteed. To address these problems, we propose an analysis system that performs on-device malware detection through transfer learning, which requires only one-time communication with the server. In addition, The system has a complete process on the device, including decompiler, which can distribute the load of the server system. As an evaluation result, it shows 90.3% accuracy without transfer learning, while the model transferred with adware catergories shows 95.1% of accuracy, which is 4.8% higher compare to original model.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.351-360
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• 2018

Human emotion recognition is a research topic that is receiving continuous attention in computer vision and artificial intelligence domains. This paper proposes a method for classifying human emotions through multiple neural networks based on multi-modal signals which consist of image, landmark, and audio in a wild environment. The proposed method has the following features. First, the learning performance of the image-based network is greatly improved by employing both multi-task learning and semi-supervised learning using the spatio-temporal characteristic of videos. Second, a model for converting 1-dimensional (1D) landmark information of face into two-dimensional (2D) images, is newly proposed, and a CNN-LSTM network based on the model is proposed for better emotion recognition. Third, based on an observation that audio signals are often very effective for specific emotions, we propose an audio deep learning mechanism robust to the specific emotions. Finally, so-called emotion adaptive fusion is applied to enable synergy of multiple networks. The proposed network improves emotion classification performance by appropriately integrating existing supervised learning and semi-supervised learning networks. In the fifth attempt on the given test set in the EmotiW2017 challenge, the proposed method achieved a classification accuracy of 57.12%.