• Membrane Journal
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• v.5 no.1
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• pp.35-43
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• 1995

For several years lots of attempts have been made to establish the liquid membrane-based techniques for separations of gas mixtures especially containing carbon dioxide. A more effective system to separate $CO_{2}$ from flue gases, a circulatory hollow-fiber membrane absorber(HFMA) consisting of absorption and desorption modules with vacuum mode, has been considered in this study. Gas-liquid mass transfer has been modeled on a membrane module with non-wetted hollow-fibers in the laminar flow regime. The influence of an absorbent flow rate on the separation performance of the circulatory HFMA can be predicted quantitatively by obtaining the $CO_{2}$ concentration profile in a tube side. The system of $CO_{2}/N_{2}$ binary gas mixture has been studied using pure water as an(inert) absorbent. As the absorbent flow rate is increased, the permeation flux(i.e., defined as permeation rate/membrane contact area) also increases. The enhanced selectivity compared to the previous results, on the other hand, shows the decreasing behavior. It has been found obviously that the permeation flux depends on the variations of pressure in gas phase of desorption module. From an accurate comparison with the results of conventional flat sheet membrane module, the advantageous permeability of this circulatory HFMA can be clearly ascertained as expected. Our efforts to the theoretical model will provide the basic analysis on the circulatory HFMA technique for a better design and process.

• Food Science of Animal Resources
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• v.40 no.6
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• pp.1014-1032
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• 2020

This work aimed to investigate the psychobiotic effects of six bacterial strains on the mind and behavior of male Wistar rats. The probiotic (PRO) group (n=7) were rats pre-treated with antibiotics for 7 days followed by 14-day probiotic administration, antibiotics (ANT) group (n=7) were rats treated with antibiotics for 21 days without probiotics. The control (CON) group (n=7) were rats that received sham treatment for 21 days. The six bacterial strains with probiotic properties were mostly isolated from Thai fermented foods; Pedicoccus pentosaceus WS11, Lactobacillus plantarum SK321, L. fermentum SK324, L. brevis TRBC 3003, Bifidobacterium adolescentis TBRC 7154 and Lactococcus lactis subsp. lactis TBRC 375. The probiotics were freeze-dried into powder (6×10⁹ CFU/5 g) and administered to the PRO group via oral gavage. Behavioral tests were performed. The PRO group displayed significantly reduced anxiety level and increased locomotor function using a marble burying test and open field test, respectively and significantly improved short-term memory performance using a novel object recognition test. Antibiotics significantly reduced microbial counts in rat feces in the ANT group by 100 fold compared to the PRO group. Probiotics significantly enhanced antioxidant enzymatic and non-enzymatic defenses in rat brains as assessed using catalase activity and ferric reducing antioxidant power assay, respectively. Probiotics also showed neuroprotective effects with less pyknotic cells and lower frequency of vacuolization in cerebral cortex. This multi-strain probiotic formulation from Thai fermented foods may offer a potential to develop psychobiotic-rich functional foods to modulate human mind and behaviors.

• 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.