• International Journal of Railway
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• v.9 no.2
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• pp.36-40
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• 2016

TETRA communication system is very versatile system which can transmit voice + data and packet data optimized. Direct mode operation permits to connect between mobiles when mobile stain is out of coverage of networks. It can be more secure communication channel for railway signaling systems. Railway signaling systems use many of wayside signal equipment, which require many maintenance efforts and budget. Many railway authorities want to reduce and replace the wayside equipment. Radio based signaling systems are one of candidate for replacing the conventional signaling systems. The radio based signaling systems can replace track circuit and wayside signal. The radio systems permit to connect between control centers and trains. The radio systems have to ensure high quality of the connectivity more or equal to the existed track circuits. We studied the application of TETRA systems for railway radio systems for bridging between train control centers and trains. We provide an operation scenario for radio based train control system to ensure the safety require to the existed trains control system and satisfied the existed operational availability. We showed the data transmission speed, maximum bit error rate, and data coding for the radio-based signal system using TETRA systems.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.110-116
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• 2024

Despite the continuous advancement of science and technology, fire accidents continue to occur without decreasing over time, so there is a constant need for a system that can accurately detect fires at an early stage. However, because most existing fire detection systems detect fire in the early stage of combustion when smoke is generated, rapid fire prevention actions may be delayed. Therefore we propose an early fire detection system that can perform early fire detection at a reasonable cost using LSTM, a deep learning model based on multi-gas sensors with high selectivity in the early stage of decomposition rather than the smoke generation stage. This system combines multiple gas sensors to achieve faster detection speeds than traditional sensors. In addition, through window sliding techniques and model light-weighting, the false alarm rate is low while maintaining the same high accuracy as existing deep learning. This shows that the proposed fire early detection system is a meaningful research in the disaster and engineering fields.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.176-180
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• 2004

The ST-segment that the beginning part of T wave is the important diagnostic parameter to finding myocardial ischemia. Abnormal ST appears in two types. One is the level change, and the other is the pattern change. In this paper, we describe the monitoring of abnormal ST using PC based system. Hardware of this system consists of transmitter, receiver and PC. The function of transmitter is measuring ECG in three channels which are selected manually and transmitting the data to receiver by digital radio way. Connection with receiver and PC is by RS232C, and the data received on the PC is analyzed automatically by ECG analysis algorithm and saved to file. In the algorithm part for detecting abnormal ST, ST-segments are approximated by a polynomial. This method can detect all of the deviation and pattern change of ST-segment regardless the change in the heart rate or sampling rate. To gain algorithm reliability, the method rejects distorted polynomial approximation by calculation the difference between the approximated ST-segment and original ST-segment. In pre-signal processing, the wavelet transformation separates high frequency bands including QRS complex from the original ECG. Consequently, the process improves the performance of detecting each feature points.

• Journal of Digital Contents Society
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• v.10 no.4
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• pp.649-657
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• 2009

Usually, The data transmission processing efficiency of the distributed system running on high speed networks depends on the system architecture and the data transmission processing system. In order to secure the real-time rate and the system reliability, the real-time distributed simulation system on the distributed environment has tried to satisfy the performance required by the data transmission processing system. However, the client/server-based data transmission processing system in the real-time simulation system has been difficult to satisfy the system stability, extensibility and maintenability, especially when system changes. So, it is natural to study another improved data transmission processing system to solve the problems at the existing real-time simulation system. After analyzing the existing real-time simulation system, this paper will propose the improved real-time data transmission system by using Software Design Pattern, which enhances extensibility, interoperability, reusability and maintenability of the system.

• Proceedings of the KIEE Conference
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• 2003.07e
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• pp.62-69
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• 2003

In recent years, data transmission using power lines has been much highlighted. Power line is known to be cost-effective communication medium because the entire cable infrastructure has been already established and it is entirely connected with any home. Recently, the target of researches is to communicate data reliably over power lines at the speed of at least 1Mbits/s over the frequency range from 1MHz to 10MHz. OFDM communication system has been used for the high speed data transmission. Next, the conventional and adaptive OFDM systems for high speed data transmission over power line channel are investigated. The performance of AOFDM(adaptive OFDM) over the frequency selective channel with impulsive and narrow-band noise are studied to be a nice solution for high speed data transmission over power lines. The simulation results show that data the rates of the AOFDM are improved about 47% more than the ones of the conventional OFDM over the frequency response of case 4. In the results, the data rate has been much improved by the proposed adaptive algorithm in the frequency selective channel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3093-3115
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• 2020

Network anomaly detection system plays an essential role in detecting network anomaly and ensuring network security. Anomaly detection system based machine learning has become an increasingly popular solution. However, due to the unbalance and high-dimension characteristics of network traffic, the existing methods unable to achieve the excellent performance of high accuracy and low false alarm rate. To address this problem, a new network anomaly detection method based on data balancing and recursive feature addition is proposed. Firstly, data balancing algorithm based on improved KNN outlier detection is designed to select part respective data on each category. Combination optimization about parameters of improved KNN outlier detection is implemented by genetic algorithm. Next, recursive feature addition algorithm based on correlation analysis is proposed to select effective features, in which a cross contingency test is utilized to analyze correlation and obtain a features subset with a strong correlation. Then, random forests model is as the classification model to detection anomaly. Finally, the proposed algorithm is evaluated on benchmark datasets KDD Cup 1999 and UNSW_NB15. The result illustrates the proposed strategies enhance accuracy and recall, and decrease the false alarm rate. Compared with other algorithms, this algorithm still achieves significant effects, especially recall in the small category.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.369-384
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• 2021

In a personalized product recommendation system, when the amount of log data is large or sparse, the accuracy of model recommendation will be greatly affected. To solve this problem, a personalized product recommendation method using deep factorization machine (DeepFM) to analyze user behavior is proposed. Firstly, the K-means clustering algorithm is used to cluster the original log data from the perspective of similarity to reduce the data dimension. Then, through the DeepFM parameter sharing strategy, the relationship between low- and high-order feature combinations is learned from log data, and the click rate prediction model is constructed. Finally, based on the predicted click-through rate, products are recommended to users in sequence and fed back. The area under the curve (AUC) and Logloss of the proposed method are 0.8834 and 0.0253, respectively, on the Criteo dataset, and 0.7836 and 0.0348 on the KDD2012 Cup dataset, respectively. Compared with other newer recommendation methods, the proposed method can achieve better recommendation effect.

• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.4
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• pp.37-46
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• 1999

Field experimnet of constructed wetland for rural wastewater treatment was performed from July 1998 to April 1999 including winter to examine the seasonal effect on the wetland performance. The system worked without freezing even under $-10^{\circ}C$ of air temperature as long as watewater was flowing. BOD removal rates varied in similar pattern as the air temperature, and winter performance was relatively lower than that in the growing season. However, removing performance during winter was still significant, and BOD removal rates were almost the the same as in the growing season. SS removal rate was relativelyless affected by temmperature, but lower decay rate during the winter can result in accumulation of the SS in the system, which releases constituents in the next spring and can affect whole system performance. The winter removal rates of nutrients like T-N and T-P were decreased about half compared to the growing season and low temperature. To maintain stabilized wetland performanced including winter time, supplying minimum heating for plants could be an alternative in field application. Experimental data was compared with NADB(North Americal Wetlands for Water Quality treatment database), and general performance of the system was within the reasonable range. The pollutant loading and effluent concentration of the experimented system were in high margin. Base on the experiment and databases, the required effluent water quality could be achieved if loading rate adjusted as ilulstrated in the database.

• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.43-48
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• 2009

The purpose of the this paper is to make decision of the maintenance priority of power distribution system using Time-Varying Failure Rate(TVFR) with interruption cost. This paper emphasizes the practical use of the reliability indices and interruption cost. To make a decision of maintenance priority on power distribution system equipment, the quantification of the reliability level should be represented as a cost. In this paper, the TVFR of power distribution system equipment applied in this paper utilizes analytic method to use the historical data of KEPCO. From this result, the sensitivity analysis on TVFR of equipment was done for the priority, which represents that high priority of the equipment has more effect on system reliability, such as SAIDI or SAIFI, than other equipment. By this priority, the investment plan is established. In this result, customer interruption cost(CIC) could be extracted, and CIC is used as weighting factor to consider a importance of customer. After that, the result calculated the proposal method in this paper is compared with other priority method, such as lifetime, failure rate or only sensitivity.

• Journal of The Korean Society of Integrative Medicine
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• v.11 no.4
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• pp.291-298
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• 2023

Purpose : Although Korea's health insurance system and access to medical care are well established compared to other countries, the rate of non-fulfillment of dental treatment is high. Medical use rates can be affected by economic characteristics, individual heatlh condtions, health concerns, and health behaviors. This study was implemented to investigate the effect of the middle-aged elderly people's family living together on the dental examination rate and to use it as basic data for program development, research, and poicies to promote oral health. Methods : Raw data from the 7th national health and nutrition survey conducted by the Korea centers for disease control and prevention (2016~2018) were used and analyzed using SPSS 21.0 Version (IBM, United States). Results : As a result of the study family types accroding to general characteristics, the more women are (p<.001), the higther the age (p<.001), the lower the hosehold income level (p<.001), the lower the educational background (p<.001), the more people who live in Eup-Myeon (p<.001) It was fouend that the rate of living alone was high. The dental examination rate according to general characteristics was related to age (p<.001), income (p<.001), and educational background (p<.001), and the higher the examination rate was in the same (p<.001), and the higher the family living together (p<.001). Factors influencing whether or not dental treatment was not performed were in the following order: household income (p<.001), age (p=.001), and family type (p=.017). Conclusion : The above results confirmed the relationship between family membership and dental examination rates, and measures such as the development and operation of participatory programs to improve public oral health by resolving medical inequality and enhancing health equity, and it is believed that the development of professional manpower and the operation of education and programs for professionals are necessary.