• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.326-329
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• 2008

현재 IEEE 802.11p 규격은 기존의 IEEE 802.11a 규격을 기반으로 하여 표준화가 진행되고 있다. 기존의 IEEE 802.11a 규격은 무선랜 (WLAN: Wireless Local Area Network) 규격으로서 고속으로 이동하는 차량 통신환경 즉 WAVE (Wireless Access for Vehicular Environment) 환경에 그대로 작용할 경우 수신 성능이 급격히 떨어지게 되 는 문제점이 있다. 본 논문에서는 긴 훈련 심볼 (LTS: Long Training Sequence)을 이용하는 기존의 채널 추정 기법을 기반으로 하되 WAVE 채널처럼 빠르게 변화하는 채널에 대응하기 위해 일정한 심볼 주기 마다 미드엠블 (Mid-Amble)을 삽입하는 전송구조를 제안한다. 또한, 미드엠블 사이의 심볼들의 위상과 크기를 3차원 스플라인 보간법을 적용하여 추정하는 알고리듬을 제안한다. 제안된 알고리듬의 성능실험을 위해 WAVE 채널을 모델링하였으며 이러한 채널에서 성능실험을 수행하였다. 실험결과에 의하면 제안된 알고리듬은 빠른 시변 채널에서도 매우 우수한 성능을 나타냄을 알 수 있다.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.311-315
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• 2006

"Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin

• Journal of the Korea Safety Management & Science
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• v.20 no.1
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• pp.23-31
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• 2018

Industrial disasters cause lots of damages from individuals to companies and country. Especially, damages caused by constructional disasters take very large portion in the whole industry and are accompanied by huge personal physical damages. For the prevention of disasters, roles of safety manager are very important and especially, effects of disaster prevention can be changed by occupational ability of construction safety manager. To improve job abilities of safety manager, job education is very important. This research suggested a model for job education management of construction safety manager and proposed improvements as a study on improvement of curriculum for vitalization of job education of construction safety manager so as to improve occupational ability of safety manager. To achieve them, this research examined standard and operation status of current job education of safety manager and the problems and suggested a model materializing job educational contents as a measure to vitalize job education system of safety manager.

• Journal of the Korea Safety Management & Science
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• v.19 no.1
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• pp.87-94
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• 2017

In construction work, safety accidents often occur in combination with unstable physical and human conditions during preparation and execution of work. In Korea, the accident rate is higher to that of any country in the world. Therefore, it is necessary to take measures by fundamental prescription. In this paper, in the case of construction safety management, we tried to find a reasonable alternative through a questionnaire survey to apply to subcontracting and small-scale construction. In conclusion, workers who are well aware of the task could be able to reduce the accident rate by deploying them as safety management officers after receiving the training.

• Proceedings of the KAIS Fall Conference
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• 2004.11a
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• pp.234-239
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• 2004

This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process fur each person, our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks (GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

• Proceedings of the KAIS Fall Conference
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• 2004.06a
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• pp.217-220
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• 2004

'Dynamic Neural Unit'(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised loaming algorithms, such as the backpropagation (BP) algorithm, that needs training information In each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

• Journal of Multimedia Information System
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• v.6 no.1
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• pp.1-6
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• 2019

In the field of industrial applications, the real-time performance of the target detection problem is very important. The most serious time consumption in the pedestrian detection process is the extraction phase of the candidate window. To accelerate the speed, in this paper, a fast extraction of pedestrian candidate window based on the BING (Binarized Normed Gradients) algorithm replaces the traditional sliding window scanning. The BING features are extracted with the positive and negative samples and input into the two-stage SVM (Support Vector Machine) classifier for training. The obtained BING template may include a pedestrian candidate window. The trained template is loaded during detection, and the extracted candidate windows are input into the classifier. The experimental results show that the proposed method can extract fewer candidate window and has a higher recall rate with more rapid speed than the traditional sliding window detection method, so the method improves the detection speed while maintaining the detection accuracy. In addition, the real-time requirement is satisfied.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2904-2926
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• 2022

Currently, diabetes is the most common chronic disease in the world, affecting 23.7% of the population in the Kingdom of Saudi Arabia. Diabetes may be the cause of lower-limb amputations, kidney failure and blindness among adults. Therefore, diagnosing the disease in its early stages is essential in order to save human lives. With the revolution in technology, Artificial Intelligence (AI) could play a central role in the early prediction of diabetes by employing Machine Learning (ML) technology. In this paper, we developed a diagnosis system using machine learning models for the detection of type 2 diabetes among adults, through the adoption of two different diabetes datasets: one for training and the other for the testing, to analyze and enhance the prediction accuracy. This work offers an enhanced classification accuracy as a result of employing several pre-processing methods before applying the ML models. According to the obtained results, the implemented Random Forest (RF) classifier offers the best classification accuracy with a classification score of 98.95%.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.198-207
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• 2023

Responding to changes in artificial intelligence models and the data environment is crucial for increasing data-learning accuracy and inference stability of industrial applications. A learning model that is overfitted to specific training data leads to poor learning performance and a deterioration in flexibility. Therefore, an early stopping technique is used to stop learning at an appropriate time. However, this technique does not consider the homogeneity and independence of the data collected by heterogeneous nodes in a differential network environment, thus resulting in low learning accuracy and degradation of system performance. In this study, the generalization performance of neural networks is maximized, whereas the effect of the homogeneity of datasets is minimized by achieving an accuracy of 99.7%. This corresponds to a decrease in delay time by a factor of 2.33 and improvement in performance by a factor of 2.5 compared with the conventional method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.804-810
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• 2013

The purpose of this study was to apply treadmill training through motor learning to cerebral palsy children and examine its effects on their motor Functions and balance. The subjects of this study were 16 spastic diplegia children who had difficulty in independent gait, and GMFCS level III, IV. The participant's were allocated randomy to 2 groups: a motor learning group(n=8) and the control group(n=8), Both groups received muscle strengthening exercise for 3 session, 30 minutes per week over 7 weeks period. Data collected from the 16 spastic diplegia children the results were as follows. The motor learning group showed significant increase in motor function(p<.05). The motor learning group showed significant increase in balance(p<.05). Between motor learning group and control group, motor functions and balance was a statistically significant difference(p<.05).