• Journal of the Korea Institute of Building Construction
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• v.22 no.1
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• pp.23-34
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• 2022

The purpose of this study is to evaluate the adhesion properties of polymer cement composites for crack repair of an RC structure. Polymer cement composites are manufactured from cement, three types of polymers and silica fume, and the mixture is designed by adjusting the water cement ratio and AE reducing agent so that the viscosity target of the polymer cement composites is 700mPa·s or less. According to the test results, the Type-A adhesion in tension of the polymer cement composite exceeded the adhesion standard of 1.0MPa of the polymer finishing material, and furthermore, depending on the type of polymer, the adhesion in tension was highest for SAE, followed in descending order by EVA, and SBR. In addition, the adhesion in tension of Type-B is up to 1/4.5 lower than that of Type-A, but the incorporation of silica fume shows a significant improvement in terms of adhesion in tension. Based on this study, the basic mixing design of the polymer cement composites required for viscosity and adhesive performance required for crack repair of the RC structure was completed. It could be proposed as an optimal mixing design under conditions for intermixing polymer type EVA, SAE, and P/C 80%-100%.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.219-229
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• 2022

This study is to evaluate the intervention effect using a flowmeter in bag-valve mask skill education. The purpose of this study was to compare the accuracy of bag-valve mask skill between intervention group with flowmeter and control group without flowmeter, understand the improvement effect of skill education of bag-valve mask, and provide basic data to suggest the method of skill education. The total number of subjects of this study was 60, with 30 intervention group and 30 control group. In comparison of the optimal number of normal tidal volume range at pre-test and post-test, the normal range percentages of the intervention group before and after education were 32.8% and 86.7%, respectively, and there was a significant difference(p<0.01). The normal range percentages of the control group before and after education were 20.0% and 34.7%, respectively, and there was a significant difference(p<0.05). To evaluate the factors associated with good performance of bag-valve mask skill of the subjects including the normal range of tidal volume, the logistic regression analysis has been performed, and the significant influential factors were gender(10.305, 1.20-87.98), educational experience of field practice(31.674, 1.25-805.16), and intervention(92.750, 4.58-1879.69). Through this study, it was confirmed that the intervention using flowmeter for the skill education of bag-valve mask was effective, and it is necessary to consider reflecting it in the education of students majoring in emergency medical technology in the future.

• Korean Journal of Optics and Photonics
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• v.33 no.1
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• pp.28-34
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• 2022

We study through computational simulation the focal performance of an infrared (IR) Fresnel lens, composed of a multilayer-graphene zone plate formed under a graphene electrode. Here the Fermi level E_F of the patterned multilayer graphene is adjusted by the overlying graphene electrode. The Fresnel lens effect, with respect to the reflectance contrast between the graphene electrode and the 8-layer graphene zone plate placed on a glass substrate, has been analyzed over a broad wavelength range from 4 to 30 ㎛. As the optimal wavelength of 8 ㎛ (considering the reflectance and the reflectance-contrast ratio) is incident upon the Fresnel lens with a focal length of 240 ㎛, the focal intensity is enhanced by a factor of 4.3 as the E_F of multilayer graphene increases from 0.4 eV to 1.6 eV, and is improved by a factor of 5.8 as the number of graphene layers increases from two to eight. As a result, an all-graphene-based IR Fresnel zone-plate lens, exhibiting multifocal function (240 ㎛ and 360 ㎛) according to the selected E_F, is proposed as an ultrathin lens platform.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• Journal of Adhesion and Interface
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• v.24 no.1
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• pp.17-25
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• 2023

In this study, waste polyethylene terephthalate (PET) was recycled to produce a support and then polyetherimide (PEI) was used for environmentally friendly organic solvent nanofiltration. The prepared composite membrane was first prepared by electrospinning a PET support, then casted on the support using PEI having excellent solvent resistance, and organic solvent nanoparticles using a Non-solvent Induced Phase Separation (NIPS) method. A filtration membrane was prepared. First, the fiber diameter and tensile strength of the PET scaffold prepared prior to membrane fabrication were identified through morphology analysis, and the optimal scaffold for the organic solvent nanofiltration membrane was identified. Afterward, the PET/PEI composite membrane prepared was checked for the DEA removal rate of Congo red having a molecular weight of 697 g/mol in ethanol to understand the performance as an organic solvent nanofiltration membrane according to the concentration of PEI. Finally, the removal rate of Congo red was 90% or more.

• Phonetics and Speech Sciences
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• v.14 no.4
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• pp.45-56
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• 2022

This paper proposes an optimal methodology for automatically diagnosing and predicting the severity of the chronic kidney disease (CKD) using patients' utterances. In patients with CKD, the voice changes due to the weakening of respiratory and laryngeal muscles and vocal fold edema. Previous studies have phonetically analyzed the voices of patients with CKD, but no studies have been conducted to classify the voices of patients. In this paper, the utterances of patients with CKD were classified using the variety of utterance types (sustained vowel, sentence, general sentence), the feature sets [handcrafted features, extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS), CNN extracted features], and the classifiers (SVM, XGBoost). Total of 1,523 utterances which are 3 hours, 26 minutes, and 25 seconds long, are used. F1-score of 0.93 for automatically diagnosing a disease, 0.89 for a 3-classes problem, and 0.84 for a 5-classes problem were achieved. The highest performance was obtained when the combination of general sentence utterances, handcrafted feature set, and XGBoost was used. The result suggests that a general sentence utterance that can reflect all speakers' speech characteristics and an appropriate feature set extracted from there are adequate for the automatic classification of CKD patients' utterances.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Korean Journal of Environmental Biology
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• v.40 no.4
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• pp.651-659
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• 2022

This study was conducted to investigate the effects of different water temperatures (8, 11, 14 and 17℃) on growth, survival and hematological parameters of juvenile chum salmon(Oncorhynchus keta) for eight weeks. At the end of the experiment, at 14℃, the final body weights of the O. keta group were the highest compared to the other groups. Also, the O. keta showed a higher tendency in the 14℃ group than the 8, 11, and 17℃ groups in terms of growth performances, including specific growth rate (SGR), feed conversion ratio (FCR), feed efficiency (FE), weight gain (WG), and condition factor (CF). The survival rate (SR) was 100% at 8 and 11℃ groups, 96% at 14℃ group and 98% at 17℃ group. In the plasma components, the alanine aminotransferase (ALT) was significantly decreased at 17℃ group, whereas there was no significant change in the albumin (ALB), total protein (TP), sodium (Na⁺), potassium (K⁺) and chloride (Cl^-) levels. Among the whole-body composition of salmon, moisture, crude protein, and ash were not significantly affected by water temperature. However, crude lipid in the 8℃ group was significantly higher than in other water temperature groups. The results of this study demonstrated that the optimal temperature to stable growth performance for juvenile O. keta was 14℃.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.486-494
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• 2021

Watermelon (Citrullus lanatus (Thunb.) Matsum. & Nakai) is sensitive to low temperature and shows retarded growth under 10℃. Although early transplanting guarantees higher returns, it requires cost and labor to maintain the appropriate temperature for plant growth. Therefore, cultivars tolerant to chilling stress is necessary to reduce the cost and labor requirements. The purpose of this study is to analyze data on plant growth and fruit enlargement under continuous chilling night temperature to develop new cultivars tolerant to chilling temperature. Two cultivars expected to have chilling tolerance and another cultivar sensitive to chilling temperature were grown in greenhouses with chilling and optimal night temperature conditions. In the early growth stage after transplanting, the cultivars expected to have chilling tolerance showed better vine length, fresh weight and dry weight. However, one of the tolerant cultivars showed significantly lower vine length, leaf length and width, and petiole length than the sensitive cultivar during pollination period and later growth stage, showing genotype specific responses. The fruit length, width, and weight were also significantly lower in the tolerant cultivar. The fruit set ratio was significantly higher in the chilling sensitive cultivar than the two tolerant cultivars. These results suggest that the present chilling tolerant cultivars in watermelon were selected based on their performance in the early growth stage, and further studies on chilling tolerance in different growth and development stages are required to develop cultivars adapted to various forcing cultivation systems.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.55-61
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• 2009

This paper describes a point of production(POP) system which collects and manages real-time shop floor machining information in a wafer dicing process. The system are composed of POP terminal, line controller and network. In the configuration of the system, LAN and RS485 network are used for connection with the upper management system and down stratum respectively. As a bridge between POP terminal and server, a line controller is used. The real-time information which is the base of production management are collected from information resources such as machine, product and worker. The collected information are used for the calculation of optimal cutting condition. The collection of the information includes cutting speed, spout of pure water, accumulated count of cut in process for blade and wafer defect. In order to manage machining information in wafer dicing process, production planning information is delivered to the shop floor, and production result information is collected from the shop floor, delivered to the server and used for managing production plan. From the result of the system application, production progress status, work and non-working hour analysis for each machine, and wafer defect analysis are available, and they are used for quality and productivity improvements in wafer dicing process. A case study is implemented to evaluate the performance of the system.