• Title, Summary, Keyword: human error

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Optimal Sensor Placement of Boundaries and Robustness Analysis for Chemical Release Detection and Response of Near Plant (주변 사업장의 화학물질 확산 감지와 대응을 위한 경계면의 센서배치 최적화 및 강건성 분석)

  • Cho, Jaehoon;Kim, Hyunseung;Kim, Tae-Ok;Shin, Dongil
    • Journal of the Korean Institute of Gas
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    • v.20 no.5
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    • pp.104-111
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    • 2016
  • Recently, the quantities of chemical material are increasing in chemical industries. At that time, release accident is increasing due to aging of equipment, mechanical failure, human error, etc. and industrial complexes found community properties in a specific area. For that matter, chemical release accident can lead to hight probability of large disaster. There is a need to analyze the boundaries optimal sensor placement calculated by selecting release scenarios through release condition and wether condition in a chemical process for release detection and response. This paper is to investigate chlorine release accident scenarios using COMSOL. Through accident scenarios, a numerical calculation is studied to determine optimized sensor placement with weight of detection probability, detection time and concentration. In addition, validity of sensor placement is improved by robustness analysis about unpredicted accident scenarios. Therefore, this verifies our studies can be effectively applicable on any process. As mention above, the result of this study can help to place mobile sensor, to track gas release based concentration data.

Performance Evaluation of Hazardous Substances using Measurement Vehicle of Field Mode through Emergency Response of Chemical Incidents

  • Lee, Yeon-Hee;Hwang, Seung-Ryul;Kim, Jae-Young;Kim, Kyun;Kwak, Ji Hyun;Kim, Min Sun;Park, Joong Don;Jeon, Junho;Kim, Ki Joon;Lee, Jin Hwan
    • Korean Journal of Environmental Agriculture
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    • v.34 no.4
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    • pp.294-302
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    • 2015
  • BACKGROUND: Chemical accidents have increased owing to chemical usage, human error and technical failures during the last decades. Many countries have organized supervisory authorities in charge of enforcing related rules and regulations to prevent chemical accidents. A very important part in chemical accidents has been coping with comprehensive first aid tool. Therefore, the present research has provided information with the initial applications concern to the rapid analysis of hazardous material using instruments in vehicle of field mode after chemical accidents. METHODS AND RESULTS: Mobile measurement vehicle was manufactured to obtain information regarding field assessments of chemical accidents. This vehicle was equipped with four instruments including gas chromatography with mass spectrometry (GC/MS), Fourier Transform Infrared Spectroscopy (FT-IR), Ion Chromatography (IC), and UV/Vis spectrometer (UV) to analyses of accident preparedness substances, volatile compounds, and organic gases. Moreover, this work was the first examined the evaluation of applicability for analysis instruments using 20 chemicals in various accident preparedness substances (GC/MS; 6 chemicals, FT-IR; 2 chemicals, IC; 11 chemicals, and UV; 1 chemical) and their calibration curves were obtained with high linearity ( r 2 > 0.991). Our results were observed the advantage of the high chromatographic peak capacity, fast analysis, and good sensitivity as well as resolution. CONCLUSION: When chemical accidents are occurred, the posted measurement vehicle may be utilized as tool an effective for qualitative and quantitative information in the scene of an accident owing to the rapid analysis of hazardous material.

A 2MC-based Framework for Sensor Data Loss Decrease in Wireless Sensor Network Failures (무선센서네트워크 장애에서 센서 데이터 손실 감소를 위한 2MC기반 프레임워크)

  • Shin, DongHyun;Kim, Changhwa
    • Journal of the Korea Society for Simulation
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    • v.25 no.2
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    • pp.31-40
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    • 2016
  • Wireless sensor networks have been used in many applications such as marine environment, army installation, etc. The sensor data is very important, because all these applications depend on sensor data. The possibility of communication failures becomes high since the surrounding environment of a wireless sense network has an sensitive effect on its communications. In particular, communication failures in underwater communications occur more frequently because of a narrow bandwidth, slow transmission speed, noises from the surrounding environments and so on. In cases of communication failures, the sensor data can be lost in the sensor data delivery process and these kinds of sensor data losses can make critical huge physical damages on human or environments in applications such as fire surveillance systems. For this reason, although a few of studies for storing and compressing sensor data have been proposed, there are lots of difficulties in actual realization of the studies due to none-existence of the framework using network communications. In this paper, we propose a framework for reducing loss of the sensor data and analyze its performance. The our analyzed results in non-framework application show a decreasing data recovery rate, T/t, as t time passes after a network failure, where T is a time period to fill the storage with sensor data after the network failure. Moreover, all the sensor data generated after a network failure are the errors impossible to recover. But, on the other hand, the analyzed results in framework application show 100% data recovery rate with 2~6% data error rate after data recovery.

Thematic Analysis of the Therapeutic Song Writing Experience of Music Therapy Interns: A Focus Group (음악치료 인턴들의 치료적 노래만들기 경험에 대한 주제분석: 포커스 그룹을 중심으로)

  • Park, Chanyang;Kim, Jinah
    • Journal of Music and Human Behavior
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    • v.17 no.1
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    • pp.1-24
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    • 2020
  • The internship is essential for the music therapy curriculum and affords interns the opportunity to apply their classroom-based knowledge and skills to real-world clinical settings. However, challenges associated with the internship can result in interns undergoing trial-and-error learning, interpersonal conflicts, and intrapersonal difficulties. An experiential music therapy group may be useful in helping interns process these incidents and develop their personal and professional skills. We explored the experiences of music therapy interns participating in therapeutic song writing. In this study, five music interns completed two 4-hour sessions of therapeutic song writing. Following the second session, a group interview was conducted with participants to gather data on their experiences. The interview was recorded, transcribed, and analyzed. Six themes and 18 sub-themes were derived from the data. The six themes were preconceptions of therapeutic song writing, meaningful lyric creation, challenges in song composition, structured experiences during song writing process, development of self-awareness through music, and relational experiences resulting from the group process. Participants were able to incorporate their individual internship experiences into a single song by communicating with group members during the step-by-step process. Participation in therapeutic song writing was found to help music therapy interns identify and process challenges encountered during their internship and further their personal and professional development.

DeNERT: Named Entity Recognition Model using DQN and BERT

  • Yang, Sung-Min;Jeong, Ok-Ran
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.4
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    • pp.29-35
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    • 2020
  • In this paper, we propose a new structured entity recognition DeNERT model. Recently, the field of natural language processing has been actively researched using pre-trained language representation models with a large amount of corpus. In particular, the named entity recognition, which is one of the fields of natural language processing, uses a supervised learning method, which requires a large amount of training dataset and computation. Reinforcement learning is a method that learns through trial and error experience without initial data and is closer to the process of human learning than other machine learning methodologies and is not much applied to the field of natural language processing yet. It is often used in simulation environments such as Atari games and AlphaGo. BERT is a general-purpose language model developed by Google that is pre-trained on large corpus and computational quantities. Recently, it is a language model that shows high performance in the field of natural language processing research and shows high accuracy in many downstream tasks of natural language processing. In this paper, we propose a new named entity recognition DeNERT model using two deep learning models, DQN and BERT. The proposed model is trained by creating a learning environment of reinforcement learning model based on language expression which is the advantage of the general language model. The DeNERT model trained in this way is a faster inference time and higher performance model with a small amount of training dataset. Also, we validate the performance of our model's named entity recognition performance through experiments.

Establishment and Application of an Integrated Platform for Navigation Safety Information (항행안전정보 통합 플랫폼 구축 및 활용방안에 관한 연구)

  • Kim, Do-Hoon
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.26 no.2
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    • pp.129-138
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    • 2020
  • This study recognizes problems in the current system of providing navigation safety information (NSI), which is centered on merchant ships, to prevent maritime accidents of fishing boats and small vessels in coastal areas. The system proposed in this study is an effective method of providing NSI to support the safe navigation of small vessels such as fishing boats. First, the status and characteristics of recent maritime accidents were examined, and NSI service targets were identified. Second, the limitations of the current NSI system were determined, and measures were proposed to establish an NSI Integrated Platform (NSIP) that ensures the integration, accessibility, and usability of NSI for a substantial portion of the public. Third, to utilize the NSIP, various NSIs are applied as additional information for the electronic chart system used in the e-navigation ship terminals being developed in connection with the Korean e-navigation project. Functions that set the audiovisual alarm function to automatically operate when a ship enters a navigation risk zone is proposed. These functions are technically achieved by reviewing expert opinions of related organizations and professional producers. The results of this study suggest that NSI can be applied to small vessels such as fishing boats, through the Korean e-Navigation project, to prevent maritime accidents caused by the human error of navigators.

Archival Program for Daily Life (일상생활과 기록)

  • Lee, Young-nam
    • The Korean Journal of Archival Studies
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    • no.63
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    • pp.167-225
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    • 2020
  • The author conducted a records research named 'daily life and records.' The purpose of the research was to find an archive, if possible, that would be effective in promoting exchange and cooperation among people in their daily lives, and to distinguish what type of archive it would be, as well as how to let it naturally take place in their ordinary lives. For 4 months (August-December 2019) with 100 college students in their 20s, trial and error were repeated. There was no separate laboratory for the research, and it used regular school hours at universities. Although it is true that there was a control through power by the college system, the plot was centered on the sunshine policy. To human being there is a voluntary and positive attitude. If anyone begins to take this attitude it is difficult to stop such action. Through emotional support, this voluntary action was encouraged to take root. The experiment was an attempt to doubt the obvious, and to search for something new. From afar, this may seem irrelevant to archives. However, for the author who is a professional archivist, it was a time of records through control by Records principles. By organizing into a form of story, its archival implications are observed.

A Study on Asthmatic Occurrence Using Deep Learning Algorithm (딥러닝 알고리즘을 활용한 천식 환자 발생 예측에 대한 연구)

  • Sung, Tae-Eung
    • The Journal of the Korea Contents Association
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    • v.20 no.7
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    • pp.674-682
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    • 2020
  • Recently, the problem of air pollution has become a global concern due to industrialization and overcrowding. Air pollution can cause various adverse effects on human health, among which respiratory diseases such as asthma, which have been of interest in this study, can be directly affected. Previous studies have used clinical data to identify how air pollutant affect diseases such as asthma based on relatively small samples. This is high likely to result in inconsistent results for each collection samples, and has significant limitations in that research is difficult for anyone other than the medical profession. In this study, the main focus was on predicting the actual asthmatic occurrence, based on data on the atmospheric environment data released by the government and the frequency of asthma outbreaks. First of all, this study verified the significant effects of each air pollutant with a time lag on the outbreak of asthma through the time-lag Pearson Correlation Coefficient. Second, train data built on the basis of verification results are utilized in Deep Learning algorithms, and models optimized for predicting the asthmatic occurrence are designed. The average error rate of the model was about 11.86%, indicating superior performance compared to other machine learning-based algorithms. The proposed model can be used for efficiency in the national insurance system and health budget management, and can also provide efficiency in the deployment and supply of medical personnel in hospitals. And it can also contribute to the promotion of national health through early warning of the risk of outbreak by atmospheric environment for chronic asthma patients.

A Study on the Spatial Patterns and the Factors on Agglomeration of New Industries in Korea (신산업의 공간분포 패턴과 집적 요인에 관한 연구)

  • Sa, Hoseok
    • Journal of the Economic Geographical Society of Korea
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    • v.23 no.2
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    • pp.125-146
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    • 2020
  • There is an increasing need to foster new industries at the local level. This study aims to analyze the spatial patterns of new industries in Korea from 2007-2017 and to figure out its determinants of agglomeration in 2017. Through this study, it is found that new industries are unevenly distributed around Seoul Metropolitan Area(SMA). The regional disparity between SMA and non-SMA is prominent. Furthermore, new industries represent a strong spatial positive autocorrelation, showing a strong concentration on a few regions in Korea. This study explores the determinants on agglomeration of new industries with spatial statistical model. From the results of spatial error model, it is indicated that the number of graduate students, the ratio of technology based start-ups, and the number of elementary, middle, and high schools have a significant effect on new industries. In addition, the specialization and the diversity of industrial structure on knowledge-based manufacturing industries and knowledge-based service industries have been statistically significant. This study provides implications that non-SMA needs policies with respect to attracting talented people, developing human resources, and improving regional environment in order to improve regional competitiveness in promoting new industries.

Revisited meta-analysis of the effects of practical reasoning instruction on students' achievements in Home Economics classes (가정과수업에서 실천적추론수업의 학생성취에 대한 효과성 연구의 메타분석)

  • Yu, Nan Sook
    • Journal of Korean Home Economics Education Association
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    • v.30 no.3
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    • pp.151-173
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    • 2018
  • The purposes of this study was to identify the magnitude and direction of the effects of Practical Reasoning Instruction (PRI) on students' achievements in Home Economics classes using the meta-analysis method and to examine whether the effects of PRI vary across publication status, study design, year of the studies, school level, gender of students, type of students' achievements, content area, location where the interventions of PRI were conducted, and duration. Thirty-four primary studies with 44 effect sizes were analyzed with calculation method of Becker(1988). A funnel plot method result revealed no publication bias. The results of this meta-analysis are as follows. First, PRI was more effective than traditional instruction on students' achievements. A summary statistic was 0.60 with a standard error of .074, which means that an increase of about two-third of a standard deviation beyond what would be expected from traditional instruction was gained from PRI intervention. Second, categorical and regression analyses were employed to find the sources of variance and moderators that predict the effects of PRI. The moderator analyses revealed no statistically significant effects of publication status, study design, school level, gender of students, type of students' achievements, and duration. Content area, location where the interventions of PRI were revealed to be moderators. It was concluded that PRI was effective in improving students' achievements regardless of publication status, study design, year of the studies, school level, gender of students, type of student achievement, and duration.