• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.195-211
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• 2023

For the commercialization For the commercialization of autonomous vehicles (AV), the operational design domain (ODD) of automated driving systems (ADS) is to be clearly defined. A common language and consistent format must be prepared so that AV-related stakeholders can understand ODD at the same level. Therefore, overseas countries are presenting a standardized ODD framework and developing scenarios that can evaluate ADS-specific functions based on ODD. However, ODD includes conditions reflecting the characteristics of each country, such as road environment, weather environment, and traffic environment. Thus, it is necessary to clearly understand the meaning of the items defined overseas and to harmonize them to reflect the specific domestic conditions. Therefore, in this study, domestic optimization of the ODD classification system was performed by analyzing the domestic driving environment based on international standards. The driving environment of currently operating self-driving car test districts (Sangam, Seoul, and Gwangju) was investigated using the developed domestic ODD items. Then, based on the results obtained, the ranges of the ODDs in each test district were determined and compared.

• The Korea Journal of Herbology
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• v.37 no.2
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• pp.1-11
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• 2022

Objectives : Although the anti-obesity effect of Schizandrae Fructus water extract has been demonstrated, its underlying mechanism is still unclear. Therefore, we aimed to evaluate the anti-obesity effect of Schizandrae Fructus water extract through the p-AMP-activated protein kinase (p-AMPK), sirtuin1 (Sirt1), and peroxisome proliferator-activated receptor-gamma coactivator 1α (PGC-1α) signaling in 60% high-fat diet (HFD)-induced obese mouse model. Methods : Male C57BL/6 mice were divided into four groups. The Normal group was fed a normal diet and the obese groups were fed 60% HFD. Except for the Control group, the GG group was supplemented with 0.5% Garcinia gummigutta and the SCW group was supplemented with 0.5% Schizandrae Fructus water extract. After 6 weeks, obesity-related biomarkers in serum were measured and the expressions of protein for lipid-related factors in liver tissue were analyzed by western blot. Results : Treatment with SCW significantly down-regulated body weight compared to the Control group. SCW down-regulated levels of triglyceride and total cholesterol in serum and significantly increased p-AMPK, Sirt1, and PGC-1α in liver tissue. In addition, the expressions of fatty acid oxidation-related proteins such as peroxisome proliferator-activated receptor α (PPARα), carnitine palmitoyltransferase 1A (CPT-1A), uncoupling protein 1 (UCP1), and uncoupling protein 3 (UCP3) were significantly up-regulated. However, fatty acid synthesis-related proteins including sterol regulatory element-binding protein-1 (SREBP-1), phospho-Acetyl-CoA Carboxylase (p-ACC), and fatty acid synthase (FAS) were significantly down-regulated. Conclusions : Taken together, SCW treatment showed anti-obesity effect by regulating both fatty acid oxidation-related and fatty acid synthesis-related proteins through AMPK/Sirt1/PGC-1α signaling in 60% HFD-induced obese mice.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3C
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• pp.115-125
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by insitu test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network (NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. It was already found that NN model can come over the site dependency and prediction accuracy is greatly improved when compared with present theoretical and empirical models. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network (CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. Prediction results of CNN model are compared with those of conventional empirical and theoretical models and multi-layered neural network model, which has the optimized structure. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.145-151
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• 2009

Recently, the rapid development of GIS technology has made it possible to handle a various data associated with spatially hydrological parameters with their attribute information. Therefore, there has been a shift in focus from lumped runoff models to distributed runoff models, as the latter can consider temporal and spatial variations of discharge. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. K-DRUM (K-water hydrologic & hydaulic Distributed flood RUnoff Model) which was developed to calculate flood discharge connected to radar rainfall based on long-term runoff model developed by Kyoto- University DPRI (Disaster Prevention Research Institute), and Yondam-Dam watershed ($930km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model (K-DRUM). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2A
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• pp.163-169
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• 2009

The research performed a test concerning the fluidity and strength of concrete manufactured by combining lime stone power, fly ash, and blast furnace slag into two and three component systems, aiming at evaluating rheological and dynamic properties of concrete by manufacturing High Flowing Self-Compacting according to the strength changes of three levels. As a result of the research, for High Flowing Self-Compacting of 30 MPa, the combination of lime stone power 20% and fly ash 30% for securing quality and strength and adjusting viscosity satisfied the required performance. For High Flowing Self-Compacting of 50 MPa, the combination of blast furnace slag 10% and fly ash 20% satisfied the fluidity and strength of the requirement performance. Also, for 70 MPa that has many power contents, the combination of blast furnace slag 20% and fly ash 10% for the increase of fluidity and the reduction of viscosity satisfied the required performance. It is judged that fly ash in all combinations can be used to secure viscosity and reduce concrete amount. In addition, it is judged that for High Flowing Self-Compacting according to the levels of compressive strength the combination of three component system including fly ash is more appropriate than the combination of two component system.

• The Journal of Bigdata
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• v.6 no.2
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• pp.125-137
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• 2021

The number of CCTV installed in Korea is over 1.3 million, increasing by more than 15% annually. However, due to the limited budget compared to the installation demand, the infrastructure is composed of 500,000 pixel low-quality CCTV, and there is a limits on identification of objects in the video. Public CCTV has high utility in various fields such as crime prevention, traffic information collection (control), facility management, and fire prevention. Especially, since installed in high height, it works as its role in solving diverse crime and is in increasing trend. However, the current public CCTV field is operated with potential problems such as inability to identify due to environmental factors such as fog, snow, and rain, and the low-quality of collected images due to the installation of low-quality CCTV. Therefore, in this study, in order to remove the typical low-quality elements of public CCTV, the method of attenuating scattered light in the image caused by dust, water droplets, fog, etc and algorithm application method which uses deep-learning algorithm to improve input video into videos over quality over 4K are suggested.

• The Journal of Bigdata
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• v.7 no.1
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• pp.15-27
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• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.176-183
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• 2023

The extraction and filtration of red ginseng with a mixed solvent of water and alcohol-a common processing method-and the production of a concentrate through heat treatment, such as steaming, leads to its hydrolysis or polymerization. Approximately 200 ginsenosides have consequently been detected in small amounts, in addition to the identification of the functions of approximately 30 major ginsenosides. This complicates the identification of the functionality of red ginseng and its efficacy, and has negative effects as a functional food, as the astringent taste becomes stronger with an increase in the number of extractions. The red ginseng concentrate was, therefore, extracted at a low temperature (less than 40 ℃) and processed to eliminate these negative aspects, with a specific focus on the characteristics of the functional components of ginsenosides.

• Journal of Practical Agriculture & Fisheries Research
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• v.18 no.1
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• pp.101-112
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• 2016

Monitoring and control of the greenhouse environment play a decisive role in greenhouse crop production processes. The network system for greenhouse control was developed by using recent technologies of networking and wireless communications. In this paper, a remote monitoring and control system for greenhouse using a smartphone and a computer with internet has been developed. The system provides real-time remote greenhouse integrated management service which collects greenhouse environment information and controls greenhouse facilities based on sensors and equipments network. Graphical user interface for an integrated management system was designed with bases on the HMI and the experimental results showed that a sensor data and device status were collected by integrated management in real-time. Because the sensor data and device status can be displayed on a web page, transmitted using the server program to remote computer and mobile smartphone at the same time. The monitored-data can be downloaded, analyzed and saved from server program in real-time via mobile phone or internet at a remote place. Performance test results of the greenhouse control system has confirmed that all work successfully in accordance with the operating conditions. And data collections and display conditions, event actions, crops and equipments monitoring showed reliable results.

• Journal of Practical Agriculture & Fisheries Research
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• v.19 no.1
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• pp.119-128
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• 2017

The field trial was performed to evaluate the rice growth and yield in different direct seeding methods. The required time for seed emergence was for 8~ 9days in the tested direct seeding methods and there was high in seedling establishment according to wet hill-seeding with iron-coated seeds> wet hill-seeding with soil coverage>water seeding with iron-coated seeds and water seeding with pregerminated seeds as the conventional treatment. The rice plant height was taller in wet hill-seeding methods than that of water seeding with broadcasting method but there was not significant difference in terms of statistical analysis at 75day after seeding except the water seeding with pregerminated seeds. The growth of tiller number in the rice plant was highest in water seeding with iron-coated seeds. The milled rice yield was highest in water seeding with iron-coated seed being with 6.4t/ha and percentage of head rice was the highest in wet hill-seeding and water seeding with iron-coated seeds.