• Toxicological Research
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• v.32 no.2
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• pp.123-132
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• 2016

The impact of mobile phone (MP) radiation on the brain is of specific interest to the scientific community and warrants investigations, as MP is held close to the head. Studies on humans and rodents revealed hazards MP radiation associated such as brain tumors, impairment in cognition, hearing etc. Melatonin (MT) is an important modulator of CNS functioning and is a neural antioxidant hormone. Zebrafish has emerged as a popular model organism for CNS studies. Herein, we evaluated the impact of GSM900MP (GSM900MP) radiation exposure daily for 1 hr for 14 days with the SAR of 1.34W/Kg on neurobehavioral and oxidative stress parameters in zebrafish. Our study revealed that, GSM900MP radiation exposure, significantly decreased time spent near social stimulus zone and increased total distance travelled, in social interaction test. In the novel tank dive test, the GSM900MP radiation exposure elicited anxiety as revealed by significantly increased time spent in bottom half; freezing bouts and duration and decreased distance travelled, average velocity, and number of entries to upper half of the tank. Exposed zebrafish spent less time in the novel arm of the Y-Maze, corroborating significant impairment in learning as compared to the control group. Exposure decreased superoxide dismutase (SOD), catalase (CAT) activities whereas, increased levels of reduced glutathione (GSH) and lipid peroxidation (LPO) was encountered showing compromised antioxidant defense. Treatment with MT significantly reversed the above neurobehavioral and oxidative derangements induced by GSM900MP radiation exposure. This study traced GSM900MP radiation exposure induced neurobehavioral aberrations and alterations in brain oxidative status. Furthermore, MT proved to be a promising therapeutic candidate in ameliorating such outcomes in zebrafish.

• Korean Journal of Social Welfare
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• v.65 no.2
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• pp.155-177
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• 2013

The aim of this study was to explore and understand the communication experiences of the deaf, from their perspective. This study obtained informations through in-depth interviews with five people with deafness using sign language. The collected data was analyzed according to Giorgi's phenomenological qualitative methods. The following main themes were extracted from the practical experiences of the participants interviewed: 'being confined in the world without sound by themselves', 'learning and comprehending how to communicate', and 'looking for identity as a membership of the deaf community'. Sign language was a tool and mediator so that they could come out of their comfort zone, communicate with people, and connect to others in the deaf community. However, on the other hand, sign language had a contradictory role that restricted their activities to the deaf societies that could understand each other using sign language. As a result of this study, we can be cognizant of how much not hearing and speaking(hearing disability) is a difficulty for human beings. The implication of this study's results on policy making and actual practices are discussed focusing on the rights and well-being of the deaf.

• Preventive Nutrition and Food Science
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• v.20 no.2
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• pp.126-132
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• 2015

This study investigated the anti-amnesic effect of fermented Ganoderma lucidum water extracts (GW) on scopolamine- induced memory impairment in rats. GW were fermented by the lactic acid bacterium Bifidobacterium bifidum (FGWB), followed by Lactobacillus sakei LI033 (FGWBL). To induce amnesia, scopolamine (1 mg/kg) was intraperitoneally injected into rats 30 min before the behavioral tests. Step-through latencies of rats treated with primary fermented extracts (300 mg/kg, FGWB) and secondary fermented extracts (300 mg/kg, FGWBL) were significantly longer than those of rats treated with GW (300 mg/kg) in the retention trial of the multiple trial passive avoidance test. In the Morris water maze task, FGWBL significantly shortened escape latencies in training trials. Furthermore, swimming times within the target zone during the probe trial with FGWBL were significantly higher than the GW and FGWB treatments. In addition, acetylcholinesterase activities were lower in the brains of scopolamine-treated rats treated with FGWBL. These results suggest that FGWBL could be useful to enhance learning memory and cognitive function via cholinergic dysfunction.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1047-1053
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• 2017

The range data acquired by 2D/3D LIDAR, a core sensor for autonomous navigation of an unmanned ground vehicle, is effectively used for ground modeling and obstacle detection. Within the ambiguous boundary of a road environment, however, LIDAR does not provide enough information to analyze the traversable region. This paper presents a new method to analyze a candidate area using the characteristics of LIDAR reflectivity for better detection of a traversable region. We detected a candidate traversable area through the front zone of the vehicle using the learning process of LIDAR reflectivity, after calibration of the reflectivity of each channel. We validated the proposed method of a candidate traversable region detection by performing experiments in the real operating environment of the unmanned ground vehicle.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.2
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• pp.179-189
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• 2000

This study is tried to organic combination in implementing the suitability analysis of urban landuse between GSIS and ANN(Artificial Neural Network). ANN has merit that can decide rationally connectivity weights among neural network nodes through procedure of learning. It is estimated to be possible that replacing the weight among factors needed in spatial analysis of the connectivity weight on neural network. This study is composed of two kinds of neural networks to be executed. First neural network was used in the suitability analysis of landuse and second one was oriented to analyze of optimum landuse pattern. These neural networks were learned with back-propagation algorithm using the steepest gradient which is embodied by C++ program and used sigmoid function as a active function. Analysis results show landuse suitability map and optimum landuse pattern of study area consisted of residental, commercial. industrial and green zone in present zoning system. Each result map was written by the Grid format of Arc/Info. Also, suitability area presented in the suitability map and optimum landuse pattern show distribution pattern consistent with theroretical concept or urban landuse plan in aspect of location and space structure.

• Journal of Integrative Natural Science
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• v.9 no.1
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• pp.72-79
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• 2016

Hexane, ethyl acetate and methanol extracts of whole plant of Boerhavia diffusa were screened for phytochemical and biological activities. Qualitative phytochemical screening via colorimetric method and the quantitative estimation of phenolic and flavonoid content were performed. Antioxidant assay using DPPH scavenging method was studied. Antimicrobial screening of plant extracts was done by cup diffusion technique. Cytotoxic activity of B. diffusa was studied by brine shrimp bioassay and anthelminthic activity was evaluated in vitro in Pheretima posthuma. This study revealed B. diffusa as a source of various phyto-constituents such as alkaloids, glycosides, saponins, tannins, carbohydrates, cardiac glycosides, flavonoids and terpenoids. Quantitative estimation of total phenol was found to be maximum in BEE i.e. $29.73{\pm}0.88$, BME $19.8{\pm}2.02$ and in BHE $9.15{\pm}0.304mgGAE/g$. Similarly, the total flavonoid content was found to be $17.44{\pm}0.75$ in BEE, $14.43{\pm}0.23$ in BHE and 3.678 mg QE/g in BME. Ethyl acetate extract showed its antibacterial activity against all tested pathogens except Escherichia coli whereas Staphylococcus aureus and Salmonella Typhi were resistant to methanol and hexane extract. The zone of inhibition (ZOI) of ethyl acetate extract against S. Typhi and B. cereus was found to be 18 mm and 14 mm respectively. The MIC value of BEE in S. Typhi was $3.125{\mu}g/ml$ and in B. cereus was $12.5{\mu}g/ml$. The preliminary screening of anticancer property of B. diffusa i.e. BSLT in methanol was found to be $165.19{\mu}g/ml$. B. diffusa was also found to contain anthelmintic property. The study helped in further exploration of medicinal properties of B. diffusa by phytochemical screening and biological activities paving the path for study and investigation in this plant.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.45-53
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• 2020

The purpose of this paper is to reduce the ratio of the patient accidents that may occur in nursing hospitals. In other words, it determines whether the person approaching the dangerous area is a elderly (patient uniform) group or a practitioner(Casual Clothing) group, based on the clothing displayed by CCTV. We collected the basic learning data from web crawling techniques and nursing hospitals. Then model training data was created with Image Generator and Labeling program. Due to the limited performance of CCTV, it is difficult to create a good model with both high accuracy and speed. Therefore, we implemented the ResNet model with relatively excellent accuracy and the YOLO3 model with relatively excellent speed. Then we wanted to allow nursing hospitals to choose a model that they wanted. As a result of the study, we implemented a model that can distinguish patient and casual clothes with appropriate accuracy. Therefore, it is believed that it will contribute to the reduction of safety accidents in nursing hospitals by preventing the elderly from accessing the danger zone.

• (The) Korean Journal of Educational Psychology
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• v.31 no.2
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• pp.265-282
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• 2017

The purpose of this study was to applicate systematic RTI educational service by providing reading fluency program to identify high-risk students with dyslexia of a shadow zone based on their growth rate. Twenty-two students of 1st to 5th graders were selected as study subjects through "2016 Kyungi-Do Project of the Dyslexia Excellence Program". An individualized reading fluency program was provided through 8-10 sessions over a period of 3 months. The program was developed based on evidence-based reading strategies with the consideration of each student's educational needs. As results, three groups were identified with their learning growth rates: concerned, improving, and discrepancy groups. The study identified three students in a discrepancy group as students with dyslexia. Based on these results, implications and suggestions for further educational identification process along with effect programs were discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.321-327
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• 2023

With the development of artificial intelligence, the prediction system has become one of the essential technologies in our lives. Despite the growth of these technologies, traffic congestion at intersections in the 21st century has continued to be a problem. This paper proposes a system that predicts intersection traffic jams using a Convolutional LSTM (Conv-LSTM) algorithm. The proposed system models data obtained by learning traffic information by time zone at the intersection where traffic congestion occurs. Traffic congestion is predicted with traffic volume data recorded over time. Based on the predicted result, the intersection traffic signal is controlled and maintained at a constant traffic volume. Road congestion data was defined using VDS sensors, and each intersection was configured with a Conv-LSTM algorithm-based network system to facilitate traffic.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.112-112
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• 2020

하천에서 유해화학물질 유입 사고 발생 시 수환경 피해를 최소화하기 위해 신속한 초기 대응이 필요하다. 따라서, 본 연구에서는 수환경 화학사고 대응 시스템 구축을 위해 하천 실시간 모니터링 지점에서 관측된 유해화학물질의 농도 자료를 이용하여 발생원의 유입 지점과 유입량을 역추적하는 프레임워크를 개발하였다. 본 연구에서 제시하는 프레임워크는 첫 번째로 하천 저장대 모형(Transient Storage Zone Model; TSM)과 HEC-RAS 모형을 이용하여 다양한 유량의 수리 조건에서 화학사고 시나리오를 생성하는 단계, 두번째로 생성된 시나리오의 유입 지점과 유입량에 대한 시간-농도 곡선 (BreakThrough Curve; BTC)을 21개의 곡선특징 (BTC feature)으로 추출하는 단계, 최종적으로 재귀적 특징 선택법(Recursive Feature Elimination; RFE)을 이용하여 의사결정나무 모형, 랜덤포레스트 모형, Xgboost 모형, 선형 서포트 벡터 머신, 커널 서포트 벡터 머신 그리고 Ridge 모형에 대한 모형별 주요 특징을 학습하고 성능을 비교하여 각각 유입 위치와 유입 질량 예측에 대한 최적 모형 및 특징 조합을 제시하는 단계로 구축하였다. 또한, 현장 적용성 제고를 위해 시간-농도 곡선을 2가지 경우 (Whole BTC와 Fractured BTC)로 가정하여 기계학습 모형을 학습시켜 모의결과를 비교하였다. 제시된 프레임워크의 검증을 위해서 낙동강 지류인 감천에 적용하여 모형을 구축하고 시나리오 자료 기반 검증과 Rhodamine WT를 이용한 추적자 실험자료를 이용한 검증을 수행하였다. 기계학습 모형들의 비교 검증 결과, 각 모형은 가중항 기반과 불순도 감소량 기반 특징 중요도 산출 방식에 따라 주요 특징이 상이하게 산출되었으며, 전체 시간-농도 곡선 (WBTC)과 부분 시간-농도 곡선 (FBTC)별 최적 모형도 다르게 산출되었다. 유입 위치 정확도 및 유입 질량 예측에 대한 R²는 대부분의 모형이 90% 이상의 우수한 결과를 나타냈다.