• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.46-51
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• 1999

Objectives: Patients with premenstrual dysphoric disorder(or PMDD) have impairments of the social, occupational or academic function due to psychological or somatic symptoms, which have the characteristic pattern of symptom exacerbation in the week before menses begin and remission shortly after the onset of menses. In the chronobiological view, many researchers have assumed that the etiology of PMDD is the advanced circadian rhythm. It has been suggested that light has a therapeutic effect on PMDD, because evening light results in phase delay of circadian rhythm through the biochemical changes including melatonin. Methods: The authors investigated the therapeutic effect of light therapy on four patients with prospectively diagnosed PMDD by DSM-IV criteria using clinical psychiatric interview, Premenstrual Assessment Form(PAF) and Daily Rating Form(or DRF). In the evening(6:30pm-8:00pm), the 2,500 lux light administered for seven consecutive days during the symptomatic late luteal phase of menstrual cycle. Beck Depression Inventory(or BDI), Hamilton Rating Scale for Depression(or HAM-D), Spielberg State Anxiety Inventory(or SA), and DRF were evaluated before and after seven days of light therapy. Results: Premenstrual symptoms of PMDD could be effectively treated with the evening bright light therapy, especially in PMDD patients with atypical symptoms. In addition, the light therapy seemed to more effective on the psychologic symptoms than the somatic symptoms of PMDD. There was no significant side-effect of light therapy, except the transient and mild eye-strain in one case. Conclusions: In spite of the results of limited data from our clinical trial, the authors suggest that the potential use of light therapy as an alternative to the pharmacological management of patients with PMDD.

• The Journal of the Korean dental association
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• v.53 no.1
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• pp.36-46
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• 2015

Objectives: The objective of this work was to investigate the hospital nursing care of oral and maxillofacial health in jeju province. Methods: 438 Registered nurses(RN) who were working at each of secondary hospitals in Jeju province had responded to the questionnaire. The data were analyzed via frequency analyses and one-way ANOVA to assess the state of RN on hospital nursing care of oral and maxillofacial health. Results: The class of education on density in formal density that marked '0 hour' and '1-3 hours' were 73.5% and 19.9%, respectively. The class of refresher training on density that marked '0 hours' and '1-3 hours' were 92.9% and 6.6%, aggregately 99.5%. The nursing education on appearance after tumor of maxillofacial area that marked 'formal education' and 'none' were 45.2% and 52.1%, respectively. The score of question 'function, effect and side effect of hexamedin gaggle' was $2.68{\pm}0.95$ by Likert 5-point scale. Likewise, the scores were $2.82{\pm}0.88$ on question 'management of removal denture', $2.83{\pm}0.95$ on question 'preventive dental treatment before anticancer therapy', $2.88{\pm}0.86$ on question 'function of saliva', $2.96{\pm}0.99$ on question 'oral management of tube feeding patient', $3.13{\pm}1.00$ on question 'bacterial endocarditis from oral microflora', $3.36{\pm}0.89$ on question 'dysphagia' and $3.62{\pm}1.03$ on question 'aspiration pneumonia'. RN replied that 'lack of knowledge' and 'delay of cooperation' formed 53.7% and 33.3% respectively, on question 'problem in dental consultation other diseased patient'. Conclusions: From this study, it is necessary for RN and student of nursing science to be educated on the oral and maxillofacial nursing. Authors suggest further co-study and nation-wide research.

• Journal of Biomedical Engineering Research
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• v.21 no.3 s.61
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• pp.261-271
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• 2000

The present study investigated flow dynamics of a two-dimensional abdominal aortic bifurcation model under sinusoidal flow conditions considering wall motion. impedance phase angle(time delay between pressure and flow waveforms), and non-Newtonian fluid using computational fluid dynamics. The wall shear stress showed large variations in the bifurcated region and the wall motion reduced amplitude of wall shear stress significantly. As the impedance phase angle was changed to more negative values, the mean wall shear stress (time-averaged) decreased while the amplitude (oscillatory) of wall shear stress increased. At the curvature site on the outer wall where the mean wall shear stress approached zero. influence of the phase angle was relatively large. The mean wall shear stress decreased by $50\%$ in the $-90^{\circ}$ phase angle (flow wave advanced pressure wave by a quarter period) compared to the $0^{\circ}$ phase angle while the amplitude of wall shear stress increased by $15\%$. Therefore, hypertensive patients who tend to have large negative phase angles become more vulnerable to atherosclerosis according to the low and oscillatory shear stress theory because of the reduced mean and the increased oscillatory wall shear stresses. Non-Newtonian characteristics of fluid substantially increased the mean wall shear stress resulting in a less vulnerable state to atherosclerosis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.123-133
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• 2018

Cyber-Physical System (CPS) is a system in which a physical system and a cyber system are strongly integrated. In order to operate the target physical system stably, the CPS constantly monitors the physical system through the sensor and performs control using the actuator according to the current state. If a malicious attacker performs a forgery attack on the measured values of the sensors in order to conceal their attacks, the cyber system operated based on the collected data can not recognize the current operation status of the physical system. This causes the delay of the response of the automation system and the operator, and then more damage will occur. To protect the CPS from increasingly sophisticated and targeted attacks, countermeasures must be developed that can detect stealthy deception attacks. However, in the CPS environment composed of various heterogeneous devices, the process of analyzing and demonstrating the vulnerability to actual field devices requires a lot of time. Therefore, in this study, we propose a method of constructing the experiment environment of the PLCitM (PLC in the middle) which can verify the performance of the techniques to detect the CPS stealthy deception attack and present the experimental results.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.457-463
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• 2015

A gas turbine engine plays an important role as a prime mover that is used in the marine transportation field as well as the space/aviation and power plant fields. However, it has a complicated structure and there is a time delay element in the combustion process. Therefore, an elaborate mathematical model needs to be developed to control a gas turbine engine. In this study, a modeling technique for a gas generator, a PLA actuator, and a metering valve, which are major components of a gas turbine engine, is explained. In addition, sub-models are obtained at several operating points in a steady state based on the trial running data of a gas turbine engine, and a method for controlling the engine speed is proposed by designing an NPID controller for each sub-model. The proposed NPID controller uses three kinds of gains that are implemented with a nonlinear function. The parameters of the NPID controller are tuned using real-coded genetic algorithms in terms of minimizing the objective function. The validity of the proposed method is examined by applying to a gas turbine engine and by conducting a simulation.

• Journal of Biomedical Engineering Research
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• v.21 no.4
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• pp.363-372
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• 2000

The present study investigated flow dynamics of a straight elastic blood vessel under sinusoidal flow conditions in order to understand influence of wall motion and impedance phase angle(time delay between pressure and flow waveforms) on wall shear stress distribution using computational fluid dynamics. For the straight elastic tube model considered in the our method of computation. The results showed that wall motion induced additional terms in the axial velocity profile and the pressure gradient. These additional terms due to wall motion reduced the amplitude of wall shear stress and also changed the mean wall shear stress. Te trend of the changes was very different depending on the impedance phase angle. As the wall shear stress increased. As the phase angle was reduced from 0$^{\circ}$to -90$^{\circ}$for ${\pm}$4% wall motion case, the mean wall shear stress decreased by 10.5% and the amplitude of wasll shear stress increased by 17.5%. Therefore, for hypertensive patients vulnerable state to atherosclerosis according to low and oscillatory shear stress theory.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.100-109
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• 2019

Maintainability indicates the extent to which maintenance can be done easily and quickly. The consideration of maintainability is crucial to reduce the operation and support costs of weapon systems, but if the maintainability is evaluated after the prototype production is done and necessitates design changes, it may increase the cost and delay the schedule. The evaluation should verify whether maintenance work can be performed, and support the designers in developing a design to improve maintainability. In previous studies, the maintainability index was calculated using the graph theory at the early design phase, but evaluation accuracy appeared to be limited. Analyzing the methods of evaluating the maintainability using fuzzy logic and 3D modeling indicate that the design of a system with good maintainability should be done in an integrated manner during the whole system life cycle. This paper proposes a method to evaluate maintainability using SysML-based modeling and simulation technique and fuzzy logic. The physical design structure with maintainability attributes was modeled using SysML 'bdd' diagram, and the maintainability was represented by an AHP matrix for maintainability attributes. We then calculated the maintainability using AHP-based weighting calculation and fuzzy logic through the use of SysML 'par' diagram that incorporated MATLAB. The proposed maintainability model can be managed efficiently and consistently, and the state of system design and maintainability can be analyzed quantitatively, thereby improving design by early identifying the items with low maintainability.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1229-1238
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• 2018

We examined if a state of sea-ice in Bering Sea acts as a prelude of variation in that of Chukchi Sea by using satellites-based Arctic sea-ice concentration time series. Datasets consist of monthly values of sea-ice concentration during 36 years (1982-2017). Time series analysis armed with Transfer entropy is performed to describe how sea-ice data in Chukchi Sea is affected by that in Bering Sea, and to explain the relationship. The transfer entropy is a measure which identifies a nonlinear coupling between two random variables or signals and estimates causality using modification of time delay. We verified this measure checked a nonlinear coupling for simulated signals. With sea-ice concentration datasets, we found that sea-ice in Bering Sea is influenced by that in Chukchi Sea 3, 5, 6 months ago through the transfer entropy measure suitable for nonlinear system. Particularly, when a sea-ice concentration of Bering Sea has a local minimum, sea ice concentration around Chukchi Sea tends to decline 5 months later with about 70% chance. This finding is considered to be a process that inflow of Pacific water through Bering strait reduces sea-ice in Chukchi Sea after lowering the concentration of sea-ice in Bering Sea. This approach based on information theory will continue to investigate a timing and time scale of interesting patterns, and thus, a coupling inherent in sea-ice concentration of two remote areas will be verified by studying ocean-atmosphere patterns or events in the period.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.6
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• pp.467-478
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• 2019

This paper describes the development and measurement results of a wide-band planar active phase array antenna system for an electronic warfare jamming transmitter. The system is designed as an $8{\times}8$ triangular lattice array using a $45^{\circ}$ slant wide-band antenna. The 64-element transmission channel is composed of a wide-band gallium nitride(GaN) solid state power amplifier and a gallium arsenide(GaAs) multi-function core chip(MFC). Each GaAs MFC includes a true-time delay circuit to avoid a wide-band beam squint, a digital attenuator, and a GaAs drive amplifier to electronically steer the transmitted beam over a ${\pm}45^{\circ}$ azimuth angle and ${\pm}25^{\circ}$ elevation angle scan. Measurement of the transmitted beam pattern is conducted using a near-field measurement facility. The EIRP of the designed system, which is 9.8 dB more than the target EIRP performance(P), and the ${\pm}45^{\circ}$ azimuth and ${\pm}25^{\circ}$ elevation beam steering fulfill the desired specifications.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.