• Anxiety and mood
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• v.18 no.1
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• pp.17-25
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• 2022

Objective : The aim of this study was to investigate the prevalence of anxiety symptoms and its association with psychological factors in patients with hypertension. Methods : The Participants included 124 patients with hypertension. Anxiety symptoms were evaluated by the Hospital Anxiety and Depression Scale. Socio-demographics, perceived stress, state-trait anger, life satisfaction, and ego resiliency were assessed. Stepwise multiple regression analyses were carried out to examine the impact of perceived stress, state-trait anger, and life satisfaction on anxiety symptoms. In addition, moderated regression analysis was performed to explore the moderating effect of ego resiliency between perceived stress and anxiety symptoms. Results : A total of 17 subjects (13.7%) were identified as having anxiety symptoms. Higher perceived stress and state-trait anger, and lower life satisfaction were found to be significant correlates of anxiety symptoms. In the final model, higher levels of perceived stress (β=0.378, p<0.001) and trait anger (β=0.320, p<0.001) were related to higher levels of anxiety symptoms, while a higher level of life satisfaction (β=-0.166, p=0.025) was associated with a lower level of anxiety symptoms. Further, ego resiliency buffered the negative effect of perceived stress on anxiety symptoms. Conclusion : This study demonstrated the prevalence of anxiety symptoms and associated psychological factors among patients with hypertension. Our findings suggest that improving life satisfaction and ego-resiliency as well as controlling stress and anger may be important in the management of anxiety symptoms in patients with hypertension.

• Journal of Ocean Engineering and Technology
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• v.35 no.6
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• pp.446-456
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• 2021

To build an environment facility of a large-scale ocean basin, various detailed reviews are required, but it is difficult to find data that introduces the related research or construction processes on the environment facility. The current generator facility for offshore structure safety evaluation tests should be implemented by rotating the water of the basin. However, when the water in the large basin rotates, relatively large flow irregularities may occur and the uniformity may not be adequate. In this paper, design and review were conducted to satisfy the performance goals of the DOEB through computational numerical analysis on the shape of the waterway and the flow straightening devices to form the current in the large tank. Based on this, the head loss, which decreases the flow rate when the large tank water rotates through the water channel, was estimated and used as the pump capacity (impeller) design data. The impeller of the DOEB current generator was designed through computational numerical analysis (CFD) based on the lift surface theory from the axial-type impeller shape for satisfying the head loss of the waterway and maximum current velocity. In order to confirm the performance of the designed impeller system, the flow rate and flow velocity performance were checked through factory test operation. And, after installing DOEB, the current flow rate and velocity performance were reviewed compare with the original design target values. Finally, by measuring the current velocity of the test area in DOEB formed through the current generator, the spatial current distribution characteristics in the test area were analyzed. Through the analysis of the current distribution characteristics of the DOEB test area, it was confirmed that the realization of the maximum current velocity and the average flow velocity distribution, the main performance goals in the waterway design process, were satisfied.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.99-104
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• 2022

Artificial intelligence is getting a crucial part of our lives with its incredible benefits. Machines outperform humans in recognizing objects in images, particularly in classifying people into correct age and gender groups. In this respect, age and gender classification has been one of the hot topics among computer vision researchers in recent decades. Deployment of deep Convolutional Neural Network(: CNN) models achieved state-of-the-art performance. However, the most of CNN based architectures are very complex with several dozens of training parameters so they require much computation time and resources. For this reason, we propose a new CNN-based classification algorithm with significantly fewer training parameters and training time compared to the existing methods. Despite its less complexity, our model shows better accuracy of age and gender classification on the UTKFace dataset.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.84-96
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• 2022

In the worst case, a temporary ignition source (also known as transient combustibles) between two electrical panels can damage both panels. Mitigation strategies for electrical panel fires were previously developed using fire modeling and risk analysis. However, since they do not comply with deterministic fire protection requirements, it is necessary to analyze the boundary values at which combustibles may damage targets depending on various factors. In the present study, a sensitivity analysis of input variables related to the damage threshold of two electrical panels was performed for dimensionless geometry using a Fire Dynamics Simulator (FDS). A new methodology using a damage evaluation map was developed to assess the damage of the electrical panel. The input variables were the distance between the electrical panels, the vertical height of the fuel, the size of the fire, the wind speed and the wind direction. The heat flux was determined to increase as the vertical distance between the fuel and the panel decreased, and the largest heat flux was predicted when the vertical separation distance divided by one half flame length was 0.3-0.5. As the distance between the panels increases, the heat flux decreases according to the power law, and damage can be avoided when the distance between the fuel and the panel is twice the length of the panel. When the wind direction is east and south, to avoid damage to the electrical panel the distance must be increased by 1.5 times compared to no wind. The present scale model can be applied to any configuration where combustibles are located between two electrical panels, and can provide useful guidance for the design of redundant electrical panels.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2491-2509
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• 2022

As an important device in the nuclear island, the nuclear coolant pump can continuously provide power for medium circulation. The vane is one of the stationary parts in the nuclear coolant pump, which is installed between the impeller and the casing. The shape of the vane plays a significant role in the pump's overall performance and stability which are the important indicators during the safety serve process. Hence, the bionic concept is firstly applied into the design process of the vane to improve the performance of the nuclear coolant pump. Taking the scaled high-performance hydraulic model (on a scale of 1:2.5) of the coolant pump as the reference, a united bionic design approach is proposed for the unique structure of the guide vane of the nuclear coolant pump. Then, a new optimization design platform is established to output the optimal bionic vane. Finally, the comparative results and the corresponding mechanism are analyzed. The conclusions can be gotten as: (1) four parameters are introduced to configure the shape of the bionic blade, the significance of each parameter is herein demonstrated; (2) the optimal bionic vane is successfully obtained by the optimization design platform, the efficiency performance and the head performance of which can be improved by 1.6% and 1.27% respectively; (3) when compared to the original vane, the optimized bionic vane can improve the inner flow characteristics, namely, it can reduce the flow loss and decrease the pressure pulsation amplitude; (4) through the mechanism analysis, it can be found out that the bionic structure can induce the spanwise velocity and the vortices, which can reduce drag and suppress the boundary layer separation.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.3
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• pp.29-35
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• 2022

Objectives The purpose of this systematic review is to analyse randomized controlled trials about acupuncture for patellofemoral pain syndrome (PFPS) and evaluate it's pain improvement effect. Methods Studies will be searched from ten databases (Medline/PubMed, Cochrane Library, EMBASE, China National Knowledge Infrastructure [CNKI], WanFang Data, Citation Information by NII [CiNII], ScienceON, Koreanstudies Information Service System [KISS], KMBASE, and KoreaMed). Participants will be patients diagnosed with PFPS, regardless of cause, gender, age or race, and interventions will be acupuncture, electroacupuncture, dry needling, fire needle, and acupotomy. Other treatments than interventions will be the control group and the main outcome will be reviewed by visual analogue scale (VAS). Results Data will be extracted and assessed according to the Preferred Reporting Items for Systematic Review and Meta-Analysis flow chart and Cochrane risk of bias tools. Meta-analysis will be conducted using random effect model within 95% confidence interval. Conclusions We expect this systematic review to provide useful data about the pain improvements of patellofemoral pain using acupuncture and expect to stimulate and systematize acupuncture treatment on PFPS in the future.

• Health Policy and Management
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• v.32 no.2
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• pp.164-172
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• 2022

Background: The purpose of this study was to the impact of the coronavirus disease 2019 (COVID-19) outbreak on emergency departments (EDs) in patients under the age of 18 years with respiratory disease. Also, we analyzed similarities and differences in patients including revisit before and after the COVID-19 outbreak. Methods: This study population was respiratory patients under the age of 18 years who visited all 403 EDs in Korea between January 1st, 2019 and December 31st, 2020, using the National Emergency Department Information System Database. The primary outcome was the number of respiratory patients according to age, sex, the type of EDs, season, Korean Triage and Acuity Scale (KTAS) levels, the result of ED, and length of stay. The secondary outcome was the number of revisit respiratory patients within 72 hours. We calculated the risk-adjusted revisit rates according to the KTAS level using a multiple logistic regression model. Results: The number of ED visits decreased from 274,526 in 2019 to 79,007 in 2020; this number was 71.2% lower than that before COVID-19. In spring 2020, this number was 90.1% lower than during the same period in 2019. For the revisit rate in the study population, the adjusted odds ratio (95% confidence interval) was 1.22 (1.05-1.41) in 2019 and 1.39 (1.07-1.81) in 2020. Conclusion: Implementing appropriate emergency care policies in severe respiratory patients would have contributed to improving the safety of reducing in revisit rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1205-1212
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• 2022

Cyber threat targeting ICS (Industrial Control System) has indicated drastic increases over the past decade and Cyber Incident in Critical Infrastructure such as Energy, Gas Terminal and Petrochemical industries can lead to disaster-level accidents including casualties and large-scale fires. In order to effectively respond to cyber attacks targeting ICS, a multi-layered defense-in-depth strategy considering Control System Architecture is necessary. In particular, the centralized security log system integrating OT (Operational Technology) and IT (Information Technology) plays an important role in the ICS incident response plan. The paper suggests the way of implementing centralized security log system that collects security events and logs using OPC Protocol from Level 0 to Level 5 based on IEC62443 Purdue Model to integrate ICS security logs with SIEM (Security Information Event Management) operated in IT environment.

• Animal Bioscience
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• v.35 no.2_spc
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• pp.317-331
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• 2022

The aim of the present investigation is to determine the nutritional composition of various insects and their potential uses as alternative protein sources in animal diets. The feeding industry requires production systems that use accessible resources, such as feed resources, and concentrates on the potential impacts on production yield and nutritional quality. Invertebrate insects, such as black soldier flies, grasshoppers, mealworms, housefly larvae, and crickets, have been used as human food and as feed for nonruminants and aqua culture while for ruminants their use has been limited. Insects can be mass-produced, participating in a circular economy that minimizes or eliminates food- and feed-waste through bioconversion. Although the model for formula-scale production of insects as feed for domestic animals has been explored for a number of years, significant production and transformation to being a conventional protein resource remains to be deeply investigated. This review will focus on the nutritional composition of various insects and their potential use as alternative protein sources, as well as their potential use to promote and support sustainable animal production. Furthermore, nutritional compositions, such as high protein, lauric acid omega 6, and omega 3, and bioactive compounds, such as chitin, are of great potential use for animal feeding.

• Journal of IKEEE
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• v.26 no.3
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• pp.341-348
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• 2022

Wi-Fi Sensing, which uses Wi-Fi technology to sense the surrounding environments, has strong potentials in a variety of sensing applications. Recently several advanced deep learning-based solutions using CSI (Channel State Information) data have achieved high performance, but it is still difficult to use in practice without explicit data collection, which requires expensive adaptation efforts for model retraining. In this study, we propose a Channel State Information Automatic Labeling System (CALS) that automatically collects and labels training CSI data for deep learning-based Wi-Fi sensing systems. The proposed system allows the CSI data collection process to efficiently collect labeled CSI for labeling for supervised learning using computer vision technologies such as object detection algorithms. We built a prototype of CALS to demonstrate its efficiency and collected data to train deep learning models for detecting the presence of a person in an indoor environment, showing to achieve an accuracy of over 90% with the auto-labeled data sets generated by CALS.