• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.21-22
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• 2007

Topology processing is indispensable basic function as it generate a real-time BUS-BRANCH model in Energy Management Systems because most application softwares such as state estimation, power flow, etc., require BUS-BRANCH circuit data. This paper propose an expert system to generate BUS-BRANCH circuit model using Artificial Intelligence technology and it is applied to 154kV distribution substations.

• Natural Product Sciences
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• v.25 no.2
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• pp.150-156
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• 2019

Conventional extraction of oil and azadirachtin, a botanical insecticide, from Azadirachta indica involves defatting the seeds and leaves using hexane followed by azadirachtin extraction with a polar solvent. In order to simplify the process while maintaining the yield we explored a binary extraction approach using Soxhlet extraction device and hexane and ethanol as non-polar and polar solvents at various ratios and extraction times. The highest oil and azadirachtin yields were obtained at 6 h extraction time using a 50:50 solvent mixture for both neem leaves (44.7 wt%, $720mg_{Aza}/kg_{leaves}$) and seeds (53.5 wt%, $1045mg_{Aza}/kg_{leaves}$), respectively.

• Structural Engineering and Mechanics
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• v.90 no.5
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• pp.481-492
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• 2024

This research examined the mechanical behavior of fiber-reinforced concrete at unstable environmental conditions. Concrete composites with varying percentages of steel and glass fibers were analyzed. Compressive, indirect tensile, and fracture toughness properties were evaluated using the Edge Notched Disc Bend (ENDB) test under freezing-thawing and acidic environments and the results were compared with normal conditions. Steel fibers decreased the strength in the specified cycles, while glass fibers showed a normal strength trend. The compressive, tensile and fracture toughness of the samples containing 1.5 vol.% fibers showed a 1.28-, 2.13- and 4.5-fold enhancement compared to samples without fibers, after 300 freezing-thawing cycles, respectively.

• Archives of Reconstructive Microsurgery
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• v.16 no.1
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• pp.1-5
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• 2007

The purpose of this article to evaluate the availability of the rectus femoris flap in Korean subjects. Material and Methods is that Cadaveric dissections were done on 51 femoral triangles of 26 cadevers. We measured the length of the direct head of rectus femoris from anterior superior iliac spine to patella upper pole, ASIS to lateral border of femoral nerve, and entry point of femoral nerve and vessel branches to rectus. Usually, there were three terminal branches to rectus femoris from the femoral nerve. The entry point of the first branch was at the proximal $17.5{\sim}31.4%$ portion of the rectus femoris. The second and the third branch entered at the proximal $22.5{\sim}40.7%$ and $26.3{\sim}42.3%$, respectively. The vessel entry was at $20.2{\sim}37.3%$. The length from ASIS to femoral nerve was $3.5{\sim}8.5\;cm$. Among the 51 rectus femoris muscles, 44 had one nutrient artery, and 7 had 2 nutrient arteries. The nutrient artery originated from the descending branch of the lateral femoral circumflex artery in 18(40.9%) cases, directly from the lateral femoral circumflex artery in 8(18.0%) cases, and from proximal(6 cases, 13.6%) and distal(12 cases, 27.3%) portion of the deep femoral artery. The average length of the nutrient artery was 29.8 mm and the width was 2.14 mm. The point where it meets the main feeding artery of the rectus femoris was $9.0{\sim}15.0\;cm$ from the ASIS. In all cases, the main artery's entrance was proximal to the first nerve branch. Conclusion is that rectus femoris has available data for functional flap.

• Journal of Multimedia Information System
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• v.3 no.3
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• pp.97-102
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• 2016

Deep learning enables machines to have perception and can potentially outperform humans in the medical field. It can save a lot of time and reduce human error by detecting certain patterns from medical images without being trained. The main goal of this paper is to build the optimal model for breast mass classification by applying various methods that influence the performance of Convolutional Neural Network (CNN). Google's newly developed software library Tensorflow was used to build CNN and the mammogram dataset used in this study was obtained from 340 breast cancer cases. The best classification performance we achieved was an accuracy of 0.887, sensitivity of 0.903, and specificity of 0.869 for normal tissue versus malignant mass classification with augmented data, more convolutional filters, and ADAM optimizer. A limitation of this method, however, was that it only considered malignant masses which are relatively easier to classify than benign masses. Therefore, further studies are required in order to properly classify any given data for medical uses.

• Journal of Microbiology and Biotechnology
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• v.29 no.7
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• pp.1009-1013
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• 2019

Polymeric nanoparticles are widely used for drug delivery due to their biodegradability property. Among the wide array of polymers, chitosan has received growing interest among researchers. It was widely used as a vehicle in polymeric nanoparticles for drug targeting. This review explored the current research on the antimicrobial activity of chitosan nanoparticles (ChNP) and the impact on the clinical applications. The antimicrobial activities of ChNP were widely reported against bacteria, fungi, yeasts and algae, in both in vivo and in vitro studies. For pharmaceutical applications, ChNP were used as antimicrobial coating for promoting wound healing, preventing infections and combating the rise of infectious disease. Besides, ChNP also exhibited significant inhibitory activities on foodborne microorganisms, particularly on fruits and vegetables. It is noteworthy that ChNP can be also applied to deliver antimicrobial drugs, which further enhance the efficiency and stability of the antimicrobial agent. The present review addresses the potential antimicrobial applications of ChNP from these few aspects.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.48-56
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• 2024

We examine a single machine scheduling problem with step-improving jobs in which job processing times decrease step-wisely over time according to their starting times. The objective is to minimize total completion time which is defined as the sum of completion times of jobs. The total completion time is frequently considered as an objective because it is highly related to the total time spent by jobs in the system as well as work-in-progress. Many applications of this problem can be observed in the real world such as data gathering networks, system upgrades or technological shock, and production lines operated with part-time workers in each shift. Our goal is to develop a scheduling algorithm that can provide an optimal solution. For this, we present an efficient branch and bound algorithm with an assignment-based node design and tight lower bounds that can prune branch and bound nodes at early stages and accordingly reduce the computation time. In numerical experiments well designed to consider various scenarios, it is shown that the proposed algorithm outperforms the existing method and can solve practical problems within reasonable computation time.

• The Journal of Korean Society for School & Community Health Education
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• v.12 no.3
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• pp.1-15
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• 2011

Objectives: We describe the development of a smoking and drinking prevention program for adolescents, using intervention mapping. Methods: The study sample consisted of 1,000 high school second-grade students from 6 high schools in Seoul. The PRECEDE model was applied for the needs assessment. We carried out a social diagnosis by assessing the factors such as the quality of life, happiness level, and satisfaction with school life; an epidemiological diagnosis on the perceived health status, stress levels, and priority of health issues; a behavioral diagnosis on the smoking and drinking rate and the intention to smoke and drink; and an educational diagnosis on knowledge, beliefs, attitudes, self-efficacy, outcome expectations, social norms and life skills. Results: The development process included a needs assessment, identifying factors that influence smoking and drinking among adolescents. Intention, knowledge, perceived norms, perceived benefit, perceived cost, perceived susceptibility, self-efficacy, and life skills were identified as determinants. Three performance objectives were formulated to describe what an individual needs to do in order to avoid smoking and drinking. Subsequently, we constructed an intervention matrix by crossing the performance objectives with the selected determinants. Each cell describes the learning objectives of the smoking and drinking prevention program. The program used methods from the transtheoretical model, such as consciousness raising, outcome expectations, self-reevaluation, self-liberation, counterconditioning, environmental reevaluation, and stimulus control. The program deals with the effects of smoking and drinking, self-improvement, decision making, understanding advertisements, communication skills, social relationships, and assertiveness. Conclusions: By using the process of intervention mapping, the program developer was able to ensure a systematical incorporation of empirical and new data and theories to guide the intervention design. Programs targeting other health-related behavior and other methods or strategies can also be developed using this intervention mapping process.

• Design & Manufacturing
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• v.2 no.5
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• pp.16-20
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• 2008

Almost all injection molds have multi-cavity runner system for mass production, which are designed with geometrically balanced runner system in order to accomplish filling balance between cavity to cavity during processing; However, even though geometrically balanced runner is used, filling imbalances have been observed. In these day, the CAE has been used widely in injection molding. However, CAE with fusion mesh can't indicate such as jetting, flow mark and filling imbalance in multi cavity mold. In this study, we investigated the filling imbalance according to runner shapes by CAE analysis. As a result in CAE, in case of binary branch runner system, filling imbalance was indicated between cavity to cavity, but the flow pattern of each cavity uniformed in unary branch runner system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.325-339
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• 2018

In this paper, we propose a joint adaptive combining and variable tap-length multiuser detector (MUD) for amplify-and-forward (AF) underwater acoustic cooperative interleave-division multiple access (IDMA) communication system. The proposed MUD jointly realizes tap-length adjustment, adaptive combining, and multiuser detection. In contrast to the existing methods, the proposed detector can adaptively combine the received signals from different nodes at destination, and does not need the assumption that full and perfect channel state information (CSI) of all the links at the receiver is known. Moreover, the proposed detector can adaptively adjust the tap coefficient vector and tap-length of each branch according to the specific channel profile of each branch. Simulation results validate the feasibility and show the advantages of the proposed detector against existing counterparts.