• Title/Summary/Keyword: response database

Search Result 549, Processing Time 0.029 seconds

A Study on the Correlation between Leak Hole Size, Leak Rate, and the Influence Range for Hydrochloric Acid Transport Vehicles (염산 운송차량의 누출공 크기와 누출률 및 영향범위간 상관관계 연구)

  • Jeon, Byeong-Han;Kim, Hyun-Sub
    • Journal of Environmental Health Sciences
    • /
    • v.47 no.2
    • /
    • pp.175-181
    • /
    • 2021
  • Objectives: The correlation between the size of a leak hole, the volume of the leakage, and the range of influence was investigated for a hydrochloric acid tank-lorry. Methods: For the case of a tank-lorry chemical accident, KORA (Korea Off-site Risk Assessment Supporting Tool) was used to predict the leak rate and the range of influence according to the size of the leak hole. The correlation was studied using R. Results: As a result of analyzing the leak rate change according to the leak hole size in a 35% hydrochloric acid tank-lorry, as the size of the leak hole increased from 1 to 100 mm, the leak rate increased from 0.008 to 83.94 kg/sec, following the power function. As a result of calculating the range of influence under conditions ranging from 1 to 100 mm in size and 10 to 60 minutes of leakage time, it was found that the range spanned from a minimum of 5.4 m to a maximum of 307.9 m. As a result of multiple regression analysis using R, the quadratic function model best explained the correlation between the size of the leak hole, the leak time, and the range of influence with an adjected coefficient of determination of 0.97 and a root mean square error of 22.33. Conclusion: If a correlation database for the size of a leak hole is accumulated for various substances and under various conditions, the amount of leakage and the range of influence can easily be calculated, facilitating field response activities.

Screening of Workers with Presumed Occupational Methanol Poisoning: The Applicablility of a National Active Occupational Disease Surveillance System

  • Eom, Huisu;Lee, Jihye;Kim, Eun-A
    • Safety and Health at Work
    • /
    • v.10 no.3
    • /
    • pp.265-274
    • /
    • 2019
  • Background: Methyl alcohol poisoning in mobile phone-manufacturing factories during 2015-2016 was caused by methyl alcohol use for cleaning in computerized numerical control (CNC) processes. To determine whether there were health complications in other workers involved in similar processes, the Occupational Safety and Health Research Institute conducted a survey. Methods: We established a national active surveillance system by collaborating with the Ministry of Employment and Labor and National Health Insurance Service. Employment and national health insurance data were used. Overall, 12,048 employees of major domestic mobile phone companies and CNC process dispatch workers were surveyed from 2016 to 2017. We investigated methyl alcohol poisoning by using the national health insurance data. Questionnaires were used to investigate diseases due to methyl alcohol poisoning. Results: Overall, 24.9% of dispatched workers were employed in at least five companies, and 23.9% of dispatched workers had missing employment insurance history data. The prevalence of blindness including visual impairment, optic neuritis, visual disturbances, and alcohol toxicity in the study participants was higher than that reported in the national health insurance database (0.02%, 0.07%, 0.23%, and 0.03% versus 0.01%, 0.07%, 0.13%, and 0.01%, respectively, in 2015). Moreover, 430 suspicious workers were identified; 415 of these provided an address and phone number, of whom 48 responded (response rate, 11.6%). Among the 48 workers, 10 had diseases at the time of the survey, of whom 3 workers were believed to have diseases related to methyl alcohol exposure. Conclusion: This study revealed that active surveillance data can be used to assess health problems related to methyl alcohol poisoning in CNC processes and dispatch workers.

Clinical Studies of Acupuncture Treatment for Alzheimer's Disease Using Neuroimaging Method: A Review of Literature (알츠하이머병의 신경영상 기법을 이용한 침치료 임상연구: 문헌고찰)

  • Lee, Dong Hyuk;Kim, Joo-Hee;Kwon, Bo-In
    • Journal of Physiology & Pathology in Korean Medicine
    • /
    • v.34 no.5
    • /
    • pp.222-228
    • /
    • 2020
  • The purpose of this article was to investigate the current state of studies on clinical trials of acupuncture treatment for Alzheimer's disease using neuroimaging method. We searched for clinical trials of acupuncture treatment for Alzheimer's disease(AD) and mild cognitive impairment(MCI) using neuroimaging method in the MEDLINE (Pubmed) database on March 18, 2020. Once the online search was finished, studies were selected manually by the inclusion criteria. Finally, we analyzed the characteristics of selected articles and reviewed the neural substrates of acupuncture treatment in AD. Total ten studies were included in this study. The most frequently applied modality for AD was functional MRI. The most frequently selected acupoints for AD were KI3, LR3 and LI4. One of studies showed that acupuncture treatment could improve the symptoms of MCI. Through the analysis, we demonstrated that neuroimaging method could capture the neural substrates associated with AD. Moreover, acupuncture may induce differential response according to the disease status. Finally, real acupuncture could produce more extensive activation/deactivation than sham acupuncture. We hope that neuroimaging method can contribute to the clinical research of acupuncture treatment for AD through large-scale RCT and diverse imaging modality.

Big Data Model for Analyzing Plant Growth Environment Informations and Biometric Informations (농작물 생육환경정보와 생체정보 분석을 위한 빅데이터 모델)

  • Lee, JongYeol;Moon, ChangBae;Kim, ByeongMan
    • Journal of Korea Society of Industrial Information Systems
    • /
    • v.25 no.6
    • /
    • pp.15-23
    • /
    • 2020
  • While research activities in the agricultural field for climate change are being actively carried out, smart agriculture using information and communication technology has become a new trend in line with the Fourth Industrial Revolution. Accordingly, research is being conducted to identify and respond to signs of abnormal growth in advance by monitoring the stress of crops in various outdoor environments and soil conditions. There are also attempts to analyze data collected in real time through various sensors using artificial intelligence techniques or big data technologies. In this paper, we propose a big data model that is effective in analyzing the growth environment informations and biometric information of crops by using the existing relational database for big data analysis. The performance of the model was measured by the response time to a query according to the amount of data. As a result, it was confirmed that there is a maximum time reduction effect of 23.8%.

Analysis of Pharmacogenetic Information in Korea Drug Labels (국내 허가사항에 반영된 약물 유전정보 분석)

  • Lee, Mijin;Kim, Sukyung;Yee, Jeong;Gwak, Hye Sun;Choi, Kyung Hee
    • Korean Journal of Clinical Pharmacy
    • /
    • v.31 no.1
    • /
    • pp.21-26
    • /
    • 2021
  • Background: Pharmacogenomics is the study of how genetic mutations in patients affect their response to drugs. Pharmacogenomic studies aim to maximize drug effects and minimize adverse drug events. The Food and Drug Administration and the European Medicine Agency published guidelines for pharmacogenetics in 2005 and 2006, respectively; the Korean Ministry of Food and Drug Safety followed suit in 2015. Methods: This study analyzed pharmacogenomic information in the Korean Ministry of Food and Drug Safety's integrated drug information system to evaluate whether domestic pharmaceutical products reflect the current research on pharmacogenomic differences. Results: In June 2020, the Korean pharmacogenomic database contained genomic data on 90 compounds. Of these, 45 compounds were classified as "Antineoplastic and immunomodulating agents." The other 45 non-antineoplastic agents were in the following categories: Anti-infectives, Mental & behavior disorder, Hormone & metabolism related diseases, Cardiovascular system, Skin & subcutaneous tissue disease, Genito-urinary system and sex hormones, Blood and blood forming organs, Nervous system, Alimentary tract and metabolism, Musculo-skeletal system, and Other conditions including the respiratory system. In addition, 30 additives unrelated to the main ingredient were associated with genetic precautions. Conclusion: This study showed that antineoplastic and immunomodulating agents accounted for half the drugs associated with pharmacogenetic information. For antitumor and immunomodulatory drugs, genomic tests were recommended depending on the indication; this was in contrast to genomic testing recommendations for non-antineoplastic medications. Genomic tests were rarely requested or recommended for non-antineoplastic medications because the relationships between genotype and efficacy among those drugs were relatively weak.

Implementation and Performance Evaluation of Pavilion Management Service including Availability Prediction based on SVM Model (SVM 모델 기반 가용성 예측 기능을 가진 야외마루 관리 서비스 구현 및 성능 평가)

  • Rijayanti, Rita;Hwang, Mintae
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.25 no.6
    • /
    • pp.766-773
    • /
    • 2021
  • This paper presents an implementation result and performance evaluation of pavilion management services that does not only provide real-time status of the pavilion in the forest but also prediction services through machine learning. The developed hardware prototype detects whether the pavilion is occupied using a motion detection sensor and then sends it to a cloud database along with location information, date and time, temperature, and humidity data. The real-time usage status of the collected data is provided to the user's mobile application. The performance evaluation confirms that the average response time from the hardware module to the applications was 1.9 seconds. The accuracy was 99%. In addition, we implemented a pavilion availability prediction service that applied a machine learning-based SVM (Support Vector Model) model to collected data and provided it through mobile and web applications.

A Design of File Leakage Response System through Event Detection (이벤트 감지를 통한 파일 유출 대응 시스템 설계)

  • Shin, Seung-Soo
    • Journal of Industrial Convergence
    • /
    • v.20 no.7
    • /
    • pp.65-71
    • /
    • 2022
  • With the development of ICT, as the era of the 4th industrial revolution arrives, the amount of data is enormous, and as big data technologies emerge, technologies for processing, storing, and processing data are becoming important. In this paper, we propose a system that detects events through monitoring and judges them using hash values because the damage to important files in case of leakage in industries and public places is serious nationally and property. As a research method, an optional event method is used to compare the hash value registered in advance after performing the encryption operation in the event of a file leakage, and then determine whether it is an important file. Monitoring of specific events minimizes system load, analyzes the signature, and determines it to improve accuracy. Confidentiality is improved by comparing and determining hash values pre-registered in the database. For future research, research on security solutions to prevent file leakage through networks and various paths is needed.

Implementation and Performance Evaluation of Environmental Data Monitoring System for the Fish Farm (양식장 환경 데이터 모니터링 시스템의 구현 및 성능 평가)

  • Wahyutama, Aria Bisma;Hwang, Mintae
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.26 no.5
    • /
    • pp.743-754
    • /
    • 2022
  • This paper contains the results of the development and performance evaluation of the environmental data monitoring system for the fish farm. For the hardware development, the analogue sensor is used to collect dissolved oxygen, pH, salinity, and temperature of the fish farm water, and the digital sensor is used for collecting ambient temperature, humidity, and location information via a GPS module to be sent to cloud-based Firebase DB. A set of LoRa transmitters and receivers is used as a communication module to upload the collected data. The data stored in Firebase is retrieved as a graph on a web and mobile application to monitor the environmental data changes in real-time. A notification will be delivered if the collected data is outside the determined optimal value. To evaluate the performance of the developed system, a response time from hardware modules to web and mobile applications is ranging from 6.2 to 6.85 seconds, which indicates satisfactory results.

Research Trends and Tasks in the field of Public Library Programs in Korea (국내 공공도서관 프로그램 분야의 연구 동향과 과제)

  • Pan Jun, Kim
    • Journal of the Korean Society for Library and Information Science
    • /
    • v.56 no.4
    • /
    • pp.51-71
    • /
    • 2022
  • Since the 1990s, the growth of the public library program field progressed rapidly at home and aborad as the proportion of programs increased as a major job for public libraries in response to social changes and user demands. However, it is difficult to find a study to grasp the overall research trend in the field of public library programs in Korea. Accordingly, intellectual structure analysis was performed based on keyword profiling to examine research trends in the domestic public library program field. In particular, keyword analysis, network analysis and cluster analysis, and period/year analysis were performed step by step based on the author keywords (uncontrolled keywords) of degree papers and academic journals retrieved from the RISS database. In addition, based on the results of this intellectual structure analysis, the research trends of public library programs were comprehensively reviewed and future research tasks were presented.

High-throughput sequencing-based metagenomic and transcriptomic analysis of intestine in piglets infected with salmonella

  • KyeongHye, Won;Dohyun, Kim;Donghyun, Shin;Jin, Hur;Hak-Kyo, Lee;Jaeyoung, Heo;Jae-Don, Oh
    • Journal of Animal Science and Technology
    • /
    • v.64 no.6
    • /
    • pp.1144-1172
    • /
    • 2022
  • Salmonella enterica serovar Typhimurium isolate HJL777 is a virulent bacterial strain in pigs. The high rate of salmonella infection are at high risk of non-typhoidal salmonella gastroenteritis development. Salmonellosis is most common in young pigs. We investigated changes in gut microbiota and biological function in piglets infected with salmonella via analysis of rectal fecal metagenome and intestinal transcriptome using 16S rRNA and RNA sequencing. We identified a decrease in Bacteroides and increase in harmful bacteria such as Spirochaetes and Proteobacteria by microbial community analysis. We predicted that reduction of Bacteroides by salmonella infection causes proliferation of salmonella and harmful bacteria that can cause an intestinal inflammatory response. Functional profiling of microbial communities in piglets with salmonella infection showed increasing lipid metabolism associated with proliferation of harmful bacteria and inflammatory responses. Transcriptome analysis identified 31 differentially expressed genes. Using gene ontology and Innate Immune Database analysis, we identified that BGN, DCN, ZFPM2 and BPI genes were involved in extracellular and immune mechanisms, specifically salmonella adhesion to host cells and inflammatory responses during infection. We confirmed alterations in gut microbiota and biological function during salmonella infection in piglets. Our findings will help prevent disease and improve productivity in the swine industry.