• JSTS:Journal of Semiconductor Technology and Science
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• v.5 no.3
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• pp.149-158
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• 2005

This paper describes design, fabrication, and application of the silicon based temperature controllable micro reactor. In order to achieve fast temperature variation and low energy consumption, reaction chamber of the micro reactor was thermally isolated by etching the highly conductive silicon around the reaction chamber. Compared with the model not having thermally isolated structure, the thermally isolated micro reactor showed enhanced thermal performances such as fast temperature variation and low energy consumption. The performance enhancements of the micro reactor due to etched holes were verified by thermal experiment and numerical analysis. Regarding to 42 percents reduction of the thermal mass achieved by the etched holes, approximately 4 times faster thermal variation and 5 times smaller energy consumption were acquired. The total size of the fabricated micro reactor was $37{\times}30{\times}1mm^{3}$. Microchannel and reaction chamber were formed on the silicon substrate. The openings of channel and chamber were covered by the glass substrate. The Pt electrodes for heater and sensor are fabricated on the backside of silicon substrate below the reaction chamber. The dimension of channel cross section was $200{\times}100{\mu}m^{2}$. The volume of reaction chamber was $4{\mu}l$. The temperature of the micro reactor was controlled and measured simultaneously with NI DAQ PCI-MIO-16E-l board and LabVIEW program. Finally, the fabricated micro reactor and the temperature control system were applied to the thermal denaturation and the trypsin digestion of protein. BSA(bovine serum albumin) was chosen for the test sample. It was successfully shown that BSA was successfully denatured at $75^{\circ}C$ for 1 min and digested by trypsin at $37^{\circ}C$ for 10 min.

• Journal of the Korean Geographical Society
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• v.46 no.6
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• pp.707-723
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• 2011

The purpose of this study was to quantitatively evaluate the effectiveness of learning management systems (LMS) in the physical geography class. The study adopted the experimental design and three classes participated in this study. The first class was controlled using only classroom lectures, the second class used PPT slides along with the classroom lectures, and the third class used online video clips along with the lectures. The experiments were conducted from the Spring Semester 2007 to the Spring Semester 2008 for the introductory physical geography course. The study results showed that online learning tools help students improve academic performance and their attitudes towards the class and the instructor. Compared to simple PowerPoint slides, voice recording attached to the visual lecture slide materials enhanced students' motivation. Class lectures with lecture slides did not improve students' scores. However, when the visual materials were combined with voice recording, the number of internet access to online class materials increased, and class attendance and students' final grades were improved. Based on the results, the instructional design model that combines classroom and online learning was suggested.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.1-10
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• 2013

Personalization aims to provide customized contents to each user by using the user's personal preferences. In this sense, the core parts of personalization are regarded as recommendation technologies, which can recommend the proper contents or products to each user according to his/her preference. Prior studies have proposed novel recommendation technologies because they recognized the importance of recommender systems. Among several recommendation technologies, collaborative filtering (CF) has been actively studied and applied in real-world applications. The CF, however, often suffers sparsity or scalability problems. Prior research also recognized the importance of these two problems and therefore proposed many solutions. Many prior studies, however, suffered from problems, such as requiring additional time and cost for solving the limitations by utilizing additional information from other sources besides the existing user-item matrix. This study proposes a novel implicit rating approach for collaborative filtering in order to mitigate the sparsity problem as well as to enhance the performance of recommender systems. In this study, we propose the methods of reducing the sparsity problem through supplementing the user-item matrix based on the implicit rating approach, which measures the trust level among users via the existing user-item matrix. This study provides the preliminary experimental results for testing the usefulness of the proposed model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2075-2082
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• 2006

This paper presents modeling and optimization techniques for hish efficiency solar cell process on single-crystalline float zone (FZ) wafers. Among a sequence of multiple steps of fabrication, the followings are the most sensitive steps for the contact formation: 1) Emitter formation by diffusion; 2) Anti-reflection-coating (ARC) with silicon nitride using plasma-enhanced chemical vapor deposition (PECVD); 3) Screen-printing for front and back metalization; and 4) Contact formation by firing. In order to increase the performance of solar cells in terms of efficiency, the contact formation process is modeled and optimized using neural networks and genetic algorithms, respectively. This paper utilizes the design of experiments (DOE) in contact formation to reduce process time and fabrication costs. The experiments were designed by using central composite design which consists of 24 factorial design augmented by 8 axial points with three center points. After contact formation process, the efficiency of the fabricated solar cell is modeled using neural networks. Established efficiency model is then used for the analysis of the process characteristics and process optimization for more efficient solar cell fabrication.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.465-472
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• 2015

SEEMP (Ship Energy Efficiency Management Plan) guidelines for a ship's GHG reduction include a machinery modification of hull, an installation of energy efficiency enhanced attachment in hardware methods. It is also possible to bring a ship energy efficiency improvement by fuel-efficient operations or in other software methods. Hardware modification or installation on ship can bring financial burdens to a ship company compared to its improvement expectation. On the other hand, Software based energy-saving technology can be applicable on various ship types, and it is also expected high efficiency of ship energy use compared to hardware based technology in perspective of the investment costs and efficiency. In this paper, it is described that the ship handling simulator based evaluation was carried out using representative ship model of bulk, container and VLCC. Simulation environments were separated into 6 conditions according to the sea-state and weather condition, and the operation results were compared with those before and after energy saving system applied The container ship showed the largest FOC save rate after energy saving system applied although the others also showed energy save rate after using the system.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.164-175
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• 2019

The Tor Tong Daeng Irrigation Project with the irrigation area of 61,400 hectares is located in the Ping Basin of the Upper Central Plain of Thailand where farmers depended on both surface water and groundwater. In the drought year, water storage in the Bhumipol Dam is inadequate to allocate water for agriculture, and caused water deficit in many irrigation projects. Farmers need to find extra sources of water such as water from farm pond or groundwater as a supplement. The operation of Bhumipol Dam and irrigation demand estimation are vital for irrigation water allocation to help solve water shortage issue in the irrigation project. The study aims to determine the smart dam operation system to mitigate water shortage in this irrigation project via introduction of machine learning to improve dam operation and irrigation demand estimation via soil moisture estimation from satellite images. Via ANN technique application, the inflows to the dam are generated from the upstream rain gauge stations using past 10 years daily rainfall data. The input vectors for ANN model are identified base on regression and principal component analysis. The structure of ANN (length of training data, the type of activation functions, the number of hidden nodes and training methods) is determined from the statistics performance between measurements and ANN outputs. On the other hands, the irrigation demand will be estimated by using satellite images, LANDSAT. The Enhanced Vegetation Index (EVI) and Temperature Vegetation Dryness Index (TVDI) values are estimated from the plant growth stage and soil moisture. The values are calibrated and verified with the field plant growth stages and soil moisture data in the year 2017-2018. The irrigation demand in the irrigation project is then estimated from the plant growth stage and soil moisture in the area. With the estimated dam inflow and irrigation demand, the dam operation will manage the water release in the better manner compared with the past operational data. The results show how smart system concept was applied and improve dam operation by using inflow estimation from ANN technique combining with irrigation demand estimation from satellite images when compared with the past operation data which is an initial step to develop the smart dam operation system in Thailand.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.93-106
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• 2021

Many recent studies on deep learning-based road crack detection have shown significantly more improved performances than previous works using algorithm-based conventional approaches. However, many deep learning-based studies are still focused on classifying the types of cracks. The classification of crack types is highly anticipated in that it can improve the crack detection process, which is currently relying on manual intervention. However, it is essential to calculate the severity of the cracks as well as identifying the type of cracks in actual pavement maintenance planning, but studies related to road crack detection have not progressed enough to automated calculation of the severity of cracks. In order to calculate the severity of the crack, the type of crack and the area of the crack in the image must be identified together. This study deals with a method of using Mobilenet-SSD that is deep learning-based object detection techniques to effectively automate the simultaneous detection of crack types and crack areas. To improve the accuracy of object-detection for road cracks, several experiments were conducted to combine the U-Net for automatic segmentation of input image and object-detection model, and the results were summarized. As a result, image masking with U-Net is able to maximize object-detection performance with 0.9315 mAP value. While referring the results of this study, it is expected that the automation of the crack detection functionality on pave management system can be further enhanced.

• Journal of the Korean Institute of Gas
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• v.25 no.6
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• pp.22-28
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• 2021

Combustion characteristics were examined experimentally for a swirl-stabilized double cone premixed burner nozzle used for industrial gas turbines for power generation. An original model and a variant with a different fuel injection pattern are tested to compare their combustion characteristics such as NOx, CO and stability in pressurized conditions with single burner-flame and in an ambient multi-flame conditions with multi-burners. Test results show that NOx emissions are smaller for the variant, whose number of fuel holes is reduced with the same total area of fuel holes, in ambient and pressurized single-flame conditions with single burner, which results from enhanced fuel/air mixing due to a higher penetration of fuel into the air stream. The multi-burnerflame test results show that NOx emissions are smaller for the variant due to reduced flame interactions, which, on the contrary, slightly reduces the stability margin. On-site test results fromin an actual power plants also show that NOx emissions are reduced for the variant, compared with the original one, which is in agreement with the lab test results stated above.

• Korean Journal of Culture and Social Issue
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• v.19 no.2
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• pp.109-131
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• 2013

It is expected that expanded use of smartphone and enhanced information technology will enable smartwork to change individuals and organizations. Smartwork is expected to allow people to perform their roles without barriers of time and space. However, people tend not to accept and actively utilize smartwork. The present study is to examine how important flexibility-willingness is for performance outcome in the context of smartwork. It was hypothesized that flexibility-willingness mediates between perceived smartwork usefulness and work-family conflict. It was also hypothesized based on technology acceptance model that task interdependence and process control moderates the relationship between flexibility-willingness and work-family conflict because the relationship is not consistent. The results show that the mediation effect of the flexibility-willingness is statistically significant. The moderator effects of task interdependence was marginal proved but process control wasn't. From these results, we discussed the theoretical implications of findings, limitations, suggestions for future research in discussion.

• Journal of Distribution Science
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• v.9 no.2
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• pp.111-122
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• 2011

The purpose of this study is to survey the successful cases of small and medium Business Systematization Cognition by examining their entrepreneurial characteristics and analysing the factors affecting their success. To that end, previous studies on the association types of small businesses were studied. A research model was developed, and research hypotheses for an empirical analysis were established upon it. Suh et al. (2010) insist on the importance of Small Business Systematization in Korea but also show that small business performance is suffering: they are too small to stand alone. That is why association is so crucial for them: they must stand together. Unfortunately, association is difficult, as they have few specific links and little motivation. Even in franchising networks, association tends to be initiated by big franchisers, not small ones. In that sense, association among small businesses is crucial for their long-term survival. With this in mind, this study examines how they think and feel about the issue of 'Industrial Classification', how important Industrial Classification is to their business success, and what kinds of problems it raises in the markets. This study seeks the different cognitions among the association types of small businesses from the perspectives of participation motivation, systematization expectation, policy demand level, and management performance. We assume that different industrial classification types of small businesses will have different cognitions concerning these factors. There are four basic industrial classification types of small businesses: retail sales, restaurant, service, and manufacturing. To date, most of the studies in this area have focused on collecting data on the external environments of small businesses or performing statistical analyses on their status. In this study, we surveyed 4 market areas in Busan, Masan, and Changwon in Korea, where business associations consist of merchants, shop owners, and traders. We surveyed 330 shops and merchants by sending a questionnaire or visiting. Finally, 268 questionnaires were collected and used for the analysis. An ANOVA, T-test, and regression analyses were conducted to test the research hypotheses. The results demonstrate that there are differences in cognition depending upon the industrial classification type. Restaurants generally have a higher cognition concerning job offer problems and a lower cognition concerning their competitiveness. Restaurants also depend more on systematization expectation than do the other industrial classification types. On the policy demand level, restaurants have a higher cognition. This study identifies several factors that are contributing to management performance through differences in cognition that depend upon association type: systematization expectation and policy demand level have positive effects on management performance; participation motivation has a negative effect on management performance. We confirm also that the image factors of different cognitions are linked to an awareness of the value of systematization and that these factors show sequential and continual patterns in the course of generating performances. In conclusion, this study carries significant implications in its classifying of small businesses into the four different associational types (retail sales, restaurant, services, and manufacturing). We believe our study to be the first one to conduct an empirical survey in this subject area. More studies in this area will likely use our research frameworks. The data show that regionally based industrial classification associations such as those in rural cities or less developed areas tend to suffer more problems than those in urban areas. Moreover, restaurants suffer more problems than the norm. Most of the problems raised in this study concern the act of 'associating itself'. Most associations have serious difficulties in associating. On the other hand, the area where they have the least policy demand is that of service types. This study contributes to the argument that associating, rather than financial assistance or management consulting, promotes the start-up and managerial performance of small businesses. This study also has some limitations. The main limitation is the number of questionnaires. We could not survey all the industrial classification types across the country because of budget and time limitations. If we had, we could have produced many more useful results and enhanced the precision of our analysis. The history of systemization is very short and the number of industrial classification associations is relatively low in Korea. We should keep in mind, though, that this is very crucial to systemization entrepreneurs starting their businesses, as it can heavily affect their chances of success. Being strongly associated with each other might be critical to the business success of industrial classification members. Thus, the government needs to put more effort and resources into supporting the drive of industrial classification members to become more strongly associated.