• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.3
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• pp.642-648
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• 2008

The aim of this study is to investigate Chegameuiin-tang water extracts (CETE) have potent anti-obesity activities in a high fat diet-induced obesity mouse model. In this study, we designed three group (normal diet group, high fat diet group, high fat diet plus CETE group for 13-week oral administration). Increases in body weight and fat storage were inhibited by 13-week oral administration of CETE at a 500 mg/kg concentration in this animal model, while the amount of food intake was not affected. Results from blood lipid analysis showed that the levels of triglyceride, total cholesterol and LDL-cholesterol were significantly lowered by CETE administration, also HDL-cholesterol was increased more than high fat diet-induced obese mouse. To understand the underlying mechanism at the molecular level, the effects of CETE were examined on the expression of the genes involved in lipogenesis and lipolysis by real-time PCR. In epididymal fat of CETE-treated mice, the mRNA level of lipogenic genes such as sterol regulatory element binding protein 1 and fatty acid synthase were decreased, which was well correlated with the reduction of the epididymal fat weight. Also, CETE administration inhibited decreases of the hormone-sensitve lipase and lipoprotein lipase mRNA expressions, which are genes related with lipolysis. These results suggest that Chegameuiin-tang may have great potential as a novel anti-obesity agent.

• The Korean Journal of Food And Nutrition
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• v.2 no.1
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• pp.61-72
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• 1989

This study was conducted to gather the baseline data on realities of experimental-practice and opinions toward spot-practice, and to examine how to cope with the problems raised at the Department of Food and Nutrition of Junior Technical College in Korea. Questionnaires were gathered from 42 chairmans of the Department of Food and Nutrition and 140 Present dieticians worked in Seoul, Bucheon am Seongnam area. The results are as follows, First, as a whole, each college had 2~3 experimental laboratory (Lab), in which Cooking Science Lab. Chemistry Lab and Microbiology Lab were occurred at higher frequency as Lab's name. Second, the numbers per experimental-practice class were more than 40 at most colleges. 85% of Present dieticians have answered to feel too much numbers per the class during their college days, whereas professors' opinions toward the numbers per class were suitable at 20~30 persons per class. Third, professors' opinion toward the adquate ratio of the theory subject classes to experimental subject classes was suitable at 60 : 40. Dieticians answered to take the theory subject classes partly or mostly on behalf of the experimental-practice classes. Fourth, the main reasons which inhibited normal experimental-practice class were the class for emphasis on examination, the shortage of experiment budget, the excess of class members, the shortage of experimental Lab Also, this results showed same propensity to present dieticians' opinion toward the same question above. Fifth, among the experimenta1-practice subjects established at the Department of Food and Nutrition, Diet Therapy Lab was highest frequency class emphasized on theory followed by Nutrition Counselling Lab, Food Processing and Storage Lab, Food Hygiene Lab and Food Microbiology Lab in that order. Here, Basic Chemistry Lab, Biochemistry Lab, Food Microbiology Lab were pointed as subjects far from the present task of dieticians. Sixth, Department of Food and Nutrition, as a whole, has conferred with spot-practice arrangement About 50% (all who want to join spot-practice) of second year students took part in spot-practice. In the other way, all colleges except for 2 colleges didn't give the credit for the spot-practice system. Seventh, according to the on analysis on spot-practice places, manufacturing company was at highest frequcney followed by hospitals, elementary school having group feeding system in that order. Especially, 16.7% (5 colleges) of the total colleges sent the students to the research institute related to food industry for spot-practice experience. Eighth, Professors' opinions toward the spot-practice time and period were preferable on summer vacation of second year and for 1~2 weeks, respectively. On the contrary, 74 dieticians answered to the adquate period as for 4 weeks. Ninth, 86 dieticians of the total 140 answered to complete the spot-practice during their college days, which helps the present task of them. Lacks of spot-practice program, Lacks of comprehension of upper personals and lacks of group feeding equipments ranks higher as difficulties in spot-practice management.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.779-793
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• 1998

In this study, for the purpose of water supply planning, we propose a sophisticated multi-period mixed integer programming model that can coordinate the behavior of multi-reservoir operation, minimizing unnecessary spill. It can simulate the system with operating rules which are self- generated by the optimization engine in the algorithm. It is an optimization model in structure, but it indeed simulates the coordinating behavior of multi-reservoir operation. It minimizes the water shortfalls in demand requirements, maintaining flood reserve volume, minimizing unnecessary spill, maximizing hydropower generation release, keeping water storage levels high for efficient hydroelectric turbine operation. This optimization model is a large scale mixed integer programming problem that consists of 3.920 integer variables and 68.658 by 132.384 node-arc incidence matrix for 28 years of data. In order to handle the enormous amount of data generated by a big mathematical model, the utilization of DBMS (data base management system)seems to be inevitable. It has been tested with the Han River multi-reservoir system in Korea, which consists of 2 large multipurpose dams and 3 hydroelectric dams. We demonstrated successfully that there is a good chance of saving substantial amount of water should it be put to use in real time with a good inflow forecasting system.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.102-111
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• 2013

In this paper, we proposed a $4{\times}4$ block parallel architecture of interpolation for high-performance H.264/AVC Motion Compensation in 4K UHD($3840{\times}2160$) video real time processing. To improve throughput, we design $4{\times}4$ block parallel interpolation. For supplying the $9{\times}9$ reference data for interpolation, we design 2D cache buffer which consists of the $9{\times}9$ memory arrays. We minimize redundant storage of the reference pixel by applying the Search Area Stripe Reuse scheme(SASR), and implement high-speed plane interpolator with 3-stage pipeline(Horizontal Vertical 1/2 interpolation, Diagonal 1/2 interpolation, 1/4 interpolation). The proposed architecture was simulated in 0.13um standard cell library. The maximum operation frequency is 150MHz. The gate count is 161Kgates. The proposed H.264/AVC Motion Compensation can support 4K UHD at 72 frames per second by running at 150MHz.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.828-840
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• 2014

There is a new evolution in technological advancement taking place called the Internet of Things (IoT). The IoT enables physical world objects in our surroundings to be connected to the Internet. For this idea to come to life, two architectures are required: the Sensing Entity in the environment which collects data and connects to the cloud and the Cloud Service that hosts the data. In particular, the combination of wireless sensor network for sensing and cloud computing for managing sensor data is becoming a popular intervention for the IoT era. The pharmaceutical cold chain requires controlled environmental conditions for the sensitive products in order for them to maintain their potency and fit for consumption. The monitoring of distribution process is the only assurance that a process has been successfully validated. The distribution process is so critical that anomaly at any point will result in the process being no longer valid. Taking the cold chain monitoring to IoT and using its benefits and power will result in better management and product handling in the cold chain. In this paper, Arduino based wireless sensor network for storage and logistics (land and sea) is presented and integrated with Xively cloud service to offer a real-time and innovative solution for pharmaceutical cold chain monitoring.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.171-174
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• 2005

According as marine leisure industry has developed and the demand of leisure culture has increased rapidly, a desire about service which supply marine safety and connect marine information is enlarging. The performance of personal mobile device has improved and been evolved by composition terminal. So, it became possible that storage and expression of multimedia information as well as simple communication facility. Domestic wireless internet has given development strain to developer and contents Provider(CP) because of different platform. And this has become hindrance factor of wireless internet activation. But, recently, the use of WIPI(Wireless Internet Platform for Interoperability), the wireless internet standard platform, could use different wireless application programs and also guarantee the independency for hardware. We wish to develop contents of download form that supply geographic information of Electronic Navigational Chart(ENC) in the marine that is digitalized to carrying along terminal of WIPI base and various informations for marine leisure. For this, DB that offer ENC and additional information should be constructed. Also, we need server (CPS; Contents provider Server) that offer required contents. In this paper, we design web retrieval agent which store request information to database. When consumer required necessary information through personal mobile device, CPS can inform that by real time. So, we wish to develop agent component that parse informations in various World Wide Webs, and store to database.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.593-606
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• 2016

Computer simulation is widely used in a variety of computational science and engineering fields, including computational fluid dynamics, nano physics, computational chemistry, structural dynamics, and computer-aided optimal design, to simulate the behavior of a system. As the demand for the accuracy and complexity of the simulation grows, however, the cost of executing the simulation is rapidly increasing. It, therefore, is very important to lower the total execution time of the simulation especially when that simulation makes a huge number of repetitions with varying values of input parameters. In this paper we develop a simulation service system that provides the ability to predict the result of the requested simulation without actual execution for that simulation: by recording and then returning previously obtained or predicted results of that simulation. To achieve the goal of avoiding repetitive simulation, the system provides two main functionalities: (1) storing simulation-result records into database and (2) predicting from the database the result of a requested simulation using statistical machine learning techniques. In our experiments we evaluate the prediction performance of the system using real airfoil simulation result data. Our system on average showed a very low error rate at a minimum of 0.9% for a certain output variable. Using the system any user can receive the predicted outcome of her simulation promptly without actually running it, which would otherwise impose a heavy burden on computing and storage resources.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.38-41
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• 2008

In this research, we propose a new method for tracking the release rate using the concentration data obtained from the sensor. We used a sensor network that has already been set surrounding the area where hazardous gas releases can occur. From the real-time sensor data, we detected and analyzed releases of harmful materials and their concentrations. Based on the results, the release rate is estimated using the neural network. This model consists of 14 input variables (sensor data, material properties, process information, meteorological conditions) and one output (release rate). The dispersion model then performs the simulation of the expected dispersion consequence by combining the sensor data, GIS data and the diagnostic result of the source term. The result of this study will improve the safety-concerns of residents living next to storage facilities containing hazardous materials by providing the enhanced emergency response plan and monitoring system for toxic gas releases.

• Journal of KIISE
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• v.42 no.8
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• pp.998-1009
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• 2015

In recent years, there has been a growing interest in RDFS Inference to build a rich knowledge base. However, it is difficult to improve the inference performance with large data by using a single machine. Therefore, researchers are investigating the development of a RDFS inference engine for a distributed computing environment. However, the existing inference engines cannot process data in real-time, are difficult to implement, and are vulnerable to repetitive tasks. In order to overcome these problems, we propose a method to construct an in-memory distributed inference engine that uses a parallel graph structure. In general, the ontology based on a triple structure possesses a graph structure. Thus, it is intuitive to design a graph structure-based inference engine. Moreover, the RDFS inference rule can be implemented by utilizing the operator of the graph structure, and we can thus design the inference engine according to the graph structure, and not the structure of the data table. In this study, we evaluate the proposed inference engine by using the LUBM1000 and LUBM3000 data to test the speed of the inference. The results of our experiment indicate that the proposed in-memory distributed inference engine achieved a performance of about 10 times faster than an in-storage inference engine.

• Journal of Apiculture
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• v.35 no.1
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• pp.49-54
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• 2020

Bee (Apis mellifera L.) venom is used for the treatment of various human diseases due to its known anti-inflammatory and antibacterial properties. This study investigated the effect of purified bee venom (PBV) on adipogenesis in 3T3-L1 preadipocytes. There was no cytotoxicity while cells were treated with PBV by various concentrations. In the PBV treated cells increases in fat storage were inhibited and also confirmed by oil red o staining. To understand the underlying mechanism at the molecular level were examined on the expression of the genes involved in adipogenesis by using real-time PCR. In this cell model, the mRNA level of adipogenic genes such as peroxisome-proliferator-activated receptors gamma (PPARγ) and CAAAT/enhancer binding protein alpha(C/EBPα) were decreased by PAE treatment, comparing with those of control group. Theses results suggest that PBV inhibits adipocyte differentiation in 3T3-L1 cells and can be used as an efficient natural substance to manage anti-obesity.