• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.402-411
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• 2020

Power line noise in electrocardiogram signals makes it difficult to diagnose cardiovascular disease. ECG signals without power line noise are needed to increase the accuracy of diagnosis. In this paper, it is proposed DNN(Deep Neural Network) model to remove the power line noise in ECG. The proposed model is learned with noisy ECG, and clean ECG. Performance of the proposed model were performed in various environments(varying amplitude, frequency change, real-time amplitude change). The evaluation used signal-to-noise ratio and root mean square error (RMSE). The difference in evaluation metrics between the noisy ECG signals and the de-noising ECG signals can demonstrate effectiveness as the de-noising model. The proposed DNN model learning result was a decrease in RMSE 0.0224dB and a increase in signal-to-noise ratio 1.048dB. The results performed in various environments showed a decrease in RMSE 1.7672dB and a increase in signal-to-noise ratio 15.1879dB in amplitude changes, a decrease in RMSE 0.0823dB and a increase in signal-to-noise ratio 4.9287dB in frequency changes. Finally, in real-time amplitude changes, RMSE was decreased 0.3886dB and signal-to-noise ratio was increased 11.4536dB. Thus, it was shown that the proposed DNN model can de-noise power line noise in ECG.

• Journal of Korean Academy of Nursing
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• v.52 no.2
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• pp.202-213
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• 2022

Purpose: This study examined characteristics and patterns of interorganizational networks for smoking prevention and cessation in Korea. Methods: We surveyed two community health centers, ninety-five hospitals or clinics, ninety- two pharmacies, and sixty-five health welfare organizations in two districts of Seoul in 2020. Data on the organizations' characteristics of smoking cessation and interorganizational activities for information sharing, client referral, and program collaboration were collected and analyzed using network statistics and blockmodeling. Results: Network size was in the order of information sharing, client referral, and program collaboration networks. Network patterns for interorganizational activities on information sharing, client referral, and program collaboration among four organizations were similar between the two districts. Community health centers provided information and received clients from a majority of the organizations. Their interactions were not unidirectional but mutual with other organizations. Pharmacies were involved in information sharing with health welfare organizations and client referrals to hospitals or clinics. Health welfare organizations were primarily connected with the community health centers for client referrals and program collaboration. Conclusion: A community health center is the lead agency in interorganizational activities for smoking prevention and cessation. However, hospitals or clinics, pharmacies, and health welfare organizations also participate in interorganizational networks for smoking prevention and cessation with diverse roles. This study would be evidence for developing future interorganizational networks for smoking prevention and cessation.

• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.1923-1931
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• 2004

Manufacturing of complex surface plates in stern and stem is a major factor in cost of a preliminary ship design by computing process. If these hull plate parts are effectively classified, it helps to compute the processing cost and find the way to cut-down the processing cost. This paper presents a new method to classify surface plates effectively in the preliminary ship design using neural network. A neural-network-based ship hull plate classification program was developed and tested for the automatic classification of ship design. The input variables are regarded as Gaussian curvature distributions on the plate. Various applicable rules of network topology are applied in the ship design. In automation of hull plate classification, two different numbers of input variables are used. By observing the results of the proposed method, the effectiveness of the proposed method is discussed. As a result, high prediction rate was achieved in the ship design. Accordingly, to the initial design stage, the ship hull plate classification program can be used to predict the ship production cost. And the proposed method will contribute to reduce the production cost of ship.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.445-450
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• 2011

In this paper, we describe the implementation of an wireless sensor network testbed. We developed a web-based sensor network gateway and enhanced the Surge program which is used for sending and routing of packets in the sensor field. The developed program can transmit the source data of sensor nodes to the sink node via multi-hop routing, and deliver user commands to actuate sensor related equipments. Moreover, in this testbed, the data transport path from a node to the sink can be monitored. Thus we can approximate the network topology and the relative positions of sensor nodes. We also describe an application of the testbed that is used for controlling a remote robot.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.1-8
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• 2006

The home network system guarantees families a safe, economical, socially integrated and healthy life by using information appliances. And it provides a family with domestic safety, control of instruments, controllable energy and health monitoring by connecting to home appliances. This study designs the broadband PLC home controller using broadband PLC(Power Line Communication) technology which can save much cost at a network infrastructure by using the existing power line at home. The broadband PLC home controller consists of the broadband PLC module, the embedded main controller module and I/O module. The broadband PLC home controller can control various domestic appliances such as an auto door-lock, a boiler, an oven, etc., because it has various I/O specifications. In this study, selected home network middleware for the broadband PLC home controller is Jini surrogate using Jini technology designed by means of access to easily a home network system without a limitation of the devices. And a client application program is supported java servlet program to manage and monitor the broadband PLC home controller via web browser of a PC or a PDA, etc. Finally, for an application, we implemented and tested a home security system using one broadband PLC home controller.

• International Journal of Contents
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• v.15 no.1
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• pp.10-24
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• 2019

This study applied network agenda-setting theory to analyze the impact of the agenda-setting function of the media on certain issues by focusing on the agenda at the center of controversy, 'Creative Economy'. To this end, the study extracted the data referred to creative economy in the media and SNS from 1 January 2008 to 31 December 2014, and analyzed the data using the network analysis program UCINET and the Korean language analysis program Textom. The results of the present study show that, during the period under former President Lee (2008-2011), the media's creative economy agenda-setting function did not exert a significant impact on the agenda-setting within SNS. However, from 2012 when the government of former President Park Geun-hye had started, the agenda-setting function of the media starts to show increasingly strong influence on the agenda cognition in SNS. The central words and sub-words configuration forming the center of the semantic network moved in the direction of a high correlation, in addition to the gradually increasing correlation based on QAP correlation analysis. In 2014, the semantic networks of the media and SNS bore a close resemblance to each other, while the shape of networks and sub-words structure also had a high level of similarity.

• 전기의세계
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• v.30 no.5
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• pp.297-305
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• 1981

The problem of finding shortest paths between every pair of points in a network is solved employing and optimal network decomposition in which the network is decomposed into a number of subnetworks minimizing the number of cut-set between them while each subnetwork is constrained by a size limit. Shortest path computations are performed on individual subnetworks, and the solutions are recomposed to obtain the solution of the original network. The method when applied to large scale networks significantly reduces core requirement and computation time. This is demonstrated by developing a computer program based on the method and applying it to 30-vertex, 160-vertex, and 273-vertex networks.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.549-551
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• 2002

A Wireless Local Area Network (WLAN) is a flexible data communication system implemented as an extension to, or as an alternative for, a wired LAN with in a building or campus. However, communications in an indoor environment present problems not encountered in outdoor wireless communication systems. Since cellular type systems are interference limited, the indoor environment is more hostile than the outdoor environment due to the lower propagation constant. In this paper, the equation for the signal to interference ratio in a multistory building will be derived. Knowing the S/I ratio, the floor frequency reuse can be determined. Finally, the simulation in this research is designed to study the performance (BER) of WLAN system in the multistory environment by applying the 8-PSK Trellis Coded modulation technique. The procedure allows a quick evaluation of BER in Wireless LAN system due to the co-channel interference.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.277-292
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• 2018

This paper presents the development and implementation of an artificial intelligence (AI)-based deep excavation induced wall and ground displacements and wall support member forces prediction program (ANN-EXCAV). The program has been developed in a C# environment by using the well-known AI technique artificial neural network (ANN). Program used ANN to predict the induced displacement, groundwater drawdown and wall and support member forces parameters for deep excavation project and run the stability check by comparing predict values to the calculated allowable values. Generalised ANNs were trained to predict the said parameters through databases generated by numerical analysis for cases that represented real field conditions. A practical example to run the ANN-EXCAV is illustrated in this paper. Results indicate that the program efficiently performed the calculations with a considerable accuracy, so it can be handy and robust tool for preliminary design of wall and support members for deep excavation project.

• Journal of the military operations research society of Korea
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• v.37 no.1
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• pp.1-9
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• 2011

The contractor management is one of the important factors for the modem defense acquisition program. The occurrence of unlawful company causes the reason in which defense acquisition program is unable to be reasonably fulfilled and setback to the deployment of defense weapon system. In this paper, we propose the Artificial Neural Network to develop a prediction model for the discrimination of unlawful company in defense procurement. The data which are used in analysis, are obtained targeting domestic small & medium manufacture enterprises. It is expected that our model can be used to improve the program management capability for defense acquisition and contribute to the establishment of efficient procurement procedure through entry of the reliable domestic manufacturer.