• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2027-2034
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• 1997

Frame relay is a fast packet switching technology that performs relaying and multiplexing frames with variable lengths over a wide area link at the T1 or E1 speed, by elminating error and flow control in the network. In frame relay networks, congestion control is typically performed through the rate enforcement with a discard eligibility (DE) bit, and the explicit negative feedback meachanisms using explicit congetion notification bits. In this paper, we consider the congestiong control scheme using the rate enforcement mechanism with DE bit for frame relay network. Assuming that each frame with exponentially distributed length arrives according to the Poission fashion, we can treat the frame relay switch as an M/M/1/K priority queueing system with pushout basis. We analyze and present the blocking probabilities and waiting time distributions of frames.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.521-530
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• 2018

This paper proposes "The Agriculture Decision-making System(ADS) based on Deep Learning for improving crop productivity" that collects weather information based on location supporting precision agriculture, predicts current crop condition by using the collected information and real time crop data, and notifies a farmer of the result. The system works as follows. The ICM(Information Collection Module) collects weather information based on location supporting precision agriculture. The DRCM(Deep learning based Risk Calculation Module) predicts whether the C, H, N and moisture content of soil are appropriate to grow specific crops according to current weather. The RNM(Risk Notification Module) notifies a farmer of the prediction result based on the DRCM. The proposed system improves the stability because it reduces the accuracy reduction rate as the amount of data increases and is apply the unsupervised learning to the analysis stage compared to the existing system. As a result, the simulation result shows that the ADS improved the success rate of data analysis by about 6%. And the ADS predicts the current crop growth condition accurately, prevents in advance the crop diseases in various environments, and provides the optimized condition for growing crops.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.37-49
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• 2017

In order to maximize the efficiency and the quality of care in a hospital, hospitals in general operate by appointments. Patient no-shows or missed appointments waste the time of staffs who prepare for appointments, deprive patients of needed care, and increase burden on clinic capacity. The purpose of this study is to examine the importance and significance of factors that affect patient no-shows. The actual data of 50,000 outpatient appointments is compiled and analyzed from a VAMC in the United States with aims to identify the factors that contribute to outpatient no-shows and to draw meaningful implications. Random forest along with logistic regression analysis identify the factors affecting no-shows; appointment leadtime, show-up rate, travel distance, no-show rate in previous period, patient age, severity, complexity of disease, chronic pain, depression, drug dependence. The appointment leadtime, show-up rate, travel distance and previous no-show rate can be improved by enhancing SMS pre-notification and by improving afterwards telephone counseling. For other factors, it needs to study on the service differentiation with the characteristics of each patient group.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1B
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• pp.29-40
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• 2004

In this paper, we propose a new early congestion detection and notification technique called QR-AQM. Unlike RED and it's variation, QR-AQM measures the total traffic rate from TCP sessions, predicts future network congestion, and determine the packet marking probability based on the measured traffic rate. By incorporating the traffic rate in the decision process of the packet marking probability, QR-AQM is capable of foreseeing future network congestion as well as terminating congestion resolution procedure in much more timely fashion than RED. As a result, simulation results show that QR-AQM maintains the buffer level within a fairly narrow range around a target buffer level that may be selected arbitrarily as a control parameter. Consequently, compared to RED and its variations, QR-AQM is expected to significantly reduce the jitter and delay variance of packets traveling through the buffer while achieving nearly identical link utilization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1B
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• pp.39-46
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• 2005

As the multimedia application traffic takes more portion in the internet traffic, it is necessary to control the network congestion through the congestion control protocol. In addition, the QoS-enabled networks such as DiffServ become an indispensable technology when running the multimedia applications. However, the previously proposed end-to-end congestion control algorithms take the round trip time to react the network congestion. Thus, as the RTT becomes larger, the reaction against the congestion gets delayed further, while the network congestion gets worse. In addition the performance of end-to-end congestion control algorithm is degraded if the QoS-enabled network runs the congestion control mechanism in the network level without any coordination between them. In this paper, we propose the early rate adaptation protocol for the DiffServ network which effectively linke the congestion control algorithm at the host and the congestion mechanism in the network together. By taking advantage of early congestion notification from the network it is possible to react the network congestion more quickly and effectively.

• Safety and Health at Work
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• v.3 no.1
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• pp.67-70
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• 2012

The surveillance programme of work-related diseases (WRD) is based on a network of occupational physicians who notify all WRD diagnosed during a two-week observation period. The aims are mainly to estimate the prevalence of non-compensated WRD in the working population according to socio economic factors; to determine new indicators of occupational health; to update the lists of compensable occupational diseases; to understand and assess under-compensation and under-notification. The participation rate for occupational physicians is around 33% in 2008. The main WRD are the musculoskeletal disorders, followed by the mental disorders. This 2-week protocol, repeated regularly, provides useful data on frequency of pathologies linked to employment as well as an estimate of unreported WRD subject to compensation or non-compensated WRDs, and the trends of WRDs over the time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2561-2576
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• 2013

The ship ad-hoc network (SANET) extends the coverage of the high data-rate terrestrial communications to the ships with the reduced cost in maritime communications. Cognitive radio (CR) has the ability of sensing the radio environment and dynamically reconfiguring the operating parameters, which can make SANET utilize the spectrum efficiently. However, due to the dynamic topology nature and no central entity for data fusion in SANET, the interference brought into the primary network caused by the hidden primary user requires to be carefully managed by a sort of decentralized cooperative spectrum sensing schemes. In this paper, we propose a self-weighted decentralized cooperative spectrum sensing (SWDCSS) scheme to solve such a problem. The analytical and simulation results show that the proposed SWDCSS scheme is reliable to detect the primary user in SANET. As a result, secondary network can efficiently utilize the spectrum band of primary network with little interference to primary network. Referring the complementary receiver operating characteristic (ROC) curves, we observe that with a given false alarm probability, our proposed algorithm reduces the missing probability by 27% than the traditional embedded spectrally agile radio protocol for evacuation (ESCAPE) algorithm in the best condition.

• Survey Research
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• v.3 no.1
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• pp.25-51
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• 2002

We examine the response patterns to web survey with a series of experiments embedded in a survey of students at the Sookmyung Women's University. A sample of 960 students was sent e-mail invitation to participate in a internet survey, The response rate was 53.9% except partial and overall non-response. Methodological experiments included the use of a pre-notification, reminder notices as well as the type of questionnaire. These factors that manipulate the perceived burden of the task had an effect on the likelihood of accepting the survey invitation. This paper discusses the overall implementation and outcome of the survey, and describes the results of the imbedded design experiments. Also we compared the representative of self-selected and probability sample.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.35-42
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• 2016

Electrocardiogram (ECG) signal gives a clear indication whether the heart is at a healthy status or not as the early notification of a cardiac problem in the heart could save the patient's life. Several methods were launched to clarify how to diagnose the abnormality over the ECG signal waves. However, some of them face the problem of lack of accuracy at diagnosis phase of their work. In this research, we present an accurate and successive method for the diagnosis of abnormality through Discrete Wavelet Transform (DWT), QRS complex detection and Support Vector Machines (SVM) classification with overall accuracy rate 95.26%. DWT Refers to sampling any kind of discrete wavelet transform, while SVM is known as a model with related learning algorithm, which is based on supervised learning that perform regression analysis and classification over the data sample. We have tested the ECG signals for 10 patients from different file formats collected from PhysioNet database to observe accuracy level for each patient who needs ECG data to be processed. The results will be presented, in terms of accuracy that ranged from 92.1% to 97.6% and diagnosis status that is classified as either normal or abnormal factors.

• International Commerce and Information Review
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• v.14 no.1
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• pp.87-114
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• 2012

The purpose of this paper is to analyze the economic effects of Foreign Direct Investment(FDI) and human capital using VECM in Korea from 1970 to 2009. Empirical results through VECM show that the coefficients of GDP, GFO(gross fixed capital), LAB(total labor), EXO(export), PCDB(public and commercial loan) and FDI have had a positive impact on Korean economic growth. In contrast, the effects of PCDB and FDI were not as significant as the other variables. In particular, the interaction effect, $FDI^*EDU$(the college graduation variable), was more important than that of the FDI alone. However, the coefficient of $FDI^*EDU$ was not so big. Korean government needs to attract more FDI to enhance Korean economic growth rate by the improvement of investment environment. There are a big amount gap between notification FDI and arrival FDI in Korea. So Korean government and companies should actively persuade foreign investors to invest after their investment notification. Also the Korean college authorities should emphasize more on curriculum which adapts to company skill in the field work.