• Title/Summary/Keyword: process-monitoring

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A Study on Implications and Improvement Plans for the Developing Consultation Guidelines for Environmental Assessment of Offshore Wind Power Development Projects (해상풍력 개발사업의 환경성 평가 협의 지침 개발에 관한 시사점 및 개선안 연구)

  • Haemi, Lee;Junho, Maeng
    • Journal of Environmental Impact Assessment
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    • v.31 no.6
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    • pp.449-464
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    • 2022
  • This study reviewed the development process of the consultation guideline for the environmental assessment of offshore wind power. Based on this, implications and improvement plans for a future revision of the guidelines. Domestic and foreign case studies reviewed the consulting cases on domestic offshore wind power development projects, environmental location consulting cases, and guidelines related to overseas offshore wind power and analyzed location characteristics and significant environmental issues by project. Major environmental issues related to offshore wind power include birds, noise and vibration, marine animals and plants, marine physics, marine water quality and sediments, marine landscapes, and other auxiliary facilities installed on land. Implications and improvements for revising the consultation guidelines for evaluating offshore wind environments require data and clear guidelines at the central government level to determine areas where offshore wind projects can be located. In a situation where the importance of cumulative impact assessment is emphasized, guidelines for cumulative impact assessment methodologies for each item that reflect the domestic situation should be prepared for a cumulative impact assessment on offshore wind power environmental issues. In addition, when revising the consultation guidelines, empirical research cases should be reflected through the accumulation of environmental surveys and monitoring data of offshore wind farms by sea area.

Effects of Salix subfragilis communities on water quality in Namgang Dam reservoir (남강댐 선버들 군락이 수질에 미치는 영향)

  • Kim, Ki Heung
    • Journal of Korea Water Resources Association
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    • v.55 no.12
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    • pp.1065-1076
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    • 2022
  • The purpose of this study was to investigate the effect of the expansion and withering of Salix subfragilis communities on the water quality in Namgang Dam reservoir. The distribution area of the Salix subfragilis communities was 0.12 km2 in 2003 for the first time, but it was 3.58 km2 in 2019, which has increased rapidly by about 30 times in 16 years. However, in 2013, the distribution area has decreased by 0.17 km2 due to long-term immersion in high turbidity, and self-thinning in Salix subfragilis communities. The lake characteristics of reservoir showed a combination of lake type and river type in terms of average water depth, watershed area/lake surface area ratio, water residence time, flushing rate, and stratification. From the result of analyzing long-term changes in lake water quality, COD, TP, and chlorophyll-a in Salix subfragilis communities were significantly larger than those in the three points located in the central part of reservoir. In particular, the fact that the value of chlorophyll-a showed the maximum value in winter rather than summer, unlike the trend of the three points in the Namgang Dam water quality monitoring network, is thought to have occurred internally rather than externally. It can be estimated that one cause of this deterioration of the water quality in Namgang Dam reservoir is the huge amount of nutrients generated in the decomposition process of by-products such as fallen leaves, branches and withered trees in Salix subfragilis communities.

ECG Compression and Transmission based on Template Matching (템플릿 매칭 기반의 심전도 압축 전송)

  • Lee, Sang-jin;Kim, Sang-kon;Kim, Tae-kon
    • Journal of Internet Computing and Services
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    • v.23 no.1
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    • pp.31-38
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    • 2022
  • An electrocardiogram(ECG) is a recoding of electrical signals of the heart's cyclic activity and an important body information for diagnosing myocardial rhythm. Large amount of information are generated continuously and a significant period of cumulative signal is required for the purpose of diagnosing a specific disease. Therefore, research on compression including clinically acceptable lossy technique has been developed to reduce the amount of information significantly. Recently, wearable smart heart monitoring devices that can transmit electrocardiogram(ECG) are being developed. The use of electrocardiogram, an important personal information for healthcare service, is rapidly increasing. However, devices generally have limited capability and power consumption for user convenience, and it is often difficult to apply the existing compression method directly. It is essential to develop techniques that can process and transmit a large volume of signals in limited resources. A method for compressing and transmitting the ECG signals efficiently by using the cumulative average (template) of the unit waveform is proposed in the paper. The ECG is coded lovelessly using template matching. It is analyzed that the proposed method is superior to the existing compression methods at high compression ratio, and its complexity is not relatively high. And it is also possible to apply compression methods to template matching values.

Monitoring the Restoration of Evergreen Broad-Leaved Forests in the Warm-Temperate Region(III) (난온대 기후대의 상록활엽수림 복원 모니터링(III))

  • Kang, Hyun-Mi;Kang, Ji-Woo;Kim, Ji-Hae;Sung, Chan-Yong;Park, Seok-Gon
    • Korean Journal of Environment and Ecology
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    • v.36 no.1
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    • pp.87-101
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    • 2022
  • This study analyzed changes in the vegetation structure of 16 permanent plots (experimental and control) installed in Wando Arboretum in 1996 to monitor the long-term change process of evergreen broad-leaved forests in warm temperate. Especially, this study discusses the effects of trial treatment (selection cutting and plant introduction), introduced as a restoration technique in 1996, on vegetation development. In communities dominated by Quercus acuta in the canopy (permanent plots 1 through 3), this species's mean important percentage (MIP) decreased, and the evergreen broad-leaved species was introduced from outside increased, likely to change the vegetation structure in the future. The expansion of the evergreen broad-leaved species group was also confirmed in Q. acuta-deciduous broad-leaved forests (permanent plots 5 and 7) and Pinus densifloraforests (permanent plots 9 and 10). In the experimental plots where thinning was carried out, the zoochory (the dispersal of seeds by birds), Cinnamomum yabunikkei, Neolitsea sericea, Machilus thunbergii, etc., and the expansion of the influence of evergreen broad-leaved species were remarkable, so it is considered to have effectively promoted the vegetation development in warm temperate forests. Although evergreen broad-leaved species were planted in the experimental plot to change vegetation structure, it seems the effect on the change was weak due to the small amount of planting. Compared to other vegetation types, the change in the vegetative structure of the pine forest to an evergreen broad-leaved forest was clear due to the decline of P. densiflora and P. thunbergii.

Developing national level high alert medication lists for acute care setting in Korea (국내 급성기 의료기관 고위험 의약품 목록 도출)

  • Han, Ji Min;Heo, Kyu-Nam;Lee, Ah Young;Min, Sang il;Kim, Hyun Jee;Baek, Jin-Hee;Rho, Juhyun;Kim, Sue In;Kim, Ji yeon;Lee, Haewon;Cho, Eunju;Ah, Young-Mi;Lee, Ju-Yeun
    • Korean Journal of Clinical Pharmacy
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    • v.32 no.2
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    • pp.116-124
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    • 2022
  • Background: High-alert medications (HAMs) are medications that bear a heightened risk of causing significant patient harm if used in error. To facilitate safe use of HAMs, identifying specific HAM lists for clinical setting is necessary. We aimed to develop the national level HAM list for acute care setting. Methods: We used three-step process. First, we compiled the pre-existing lists referring HAMs. Second, we analyzed medication related incidents reported from national patient safety incident report data and adverse events indicating medication errors from the Korea Adverse Event Reporting System (KAERS). We also surveyed the assistant staffs to support patient safety tasks and pharmacist in charge of medication safety in acute care hospital. From findings from analysis and survey results we created additional candidate list of HAMs. Third, we derived the final list for HAMs in acute care settings through expert panel surveys. Results: From pre-existing HAM list, preliminary list consisting of 42 medication class/ingredients was derived. Eight assistant staff to support patient safety tasks and 39 pharmacists in charge of medication safety responded to the survey. Additional 44 medication were listed from national patient safety incident report data, KAERS data and common medications involved in prescribing errors and dispensing errors from survey data. A list of mandatory and optional HAMs consisting of 10 and 6 medication classes, respectively, was developed by consensus of the expert group. Conclusion: We developed national level HAM list for Korean acute care setting from pre-existing lists, analyzing medication error data, survey and expert panel consensus.

Modelling Gas Production Induced Seismicity Using 2D Hydro-Mechanical Coupled Particle Flow Code: Case Study of Seismicity in the Natural Gas Field in Groningen Netherlands (2차원 수리-역학적 연계 입자유동코드를 사용한 가스생산 유발지진 모델링: 네덜란드 그로닝엔 천연가스전에서의 지진 사례 연구)

  • Jeoung Seok Yoon;Anne Strader;Jian Zhou;Onno Dijkstra;Ramon Secanell;Ki-Bok Min
    • Tunnel and Underground Space
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    • v.33 no.1
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    • pp.57-69
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    • 2023
  • In this study, we simulated induced seismicity in the Groningen natural gas reservoir using 2D hydro-mechanical coupled discrete element modelling (DEM). The code used is PFC2D (Particle Flow Code 2D), a commercial software developed by Itasca, and in order to apply to this study we further developed 1)initialization of inhomogeneous reservoir pressure distribution, 2)a non-linear pressure-time history boundary condition, 3)local stress field monitoring logic. We generated a 2D reservoir model with a size of 40 × 50 km2 and a complex fault system, and simulated years of pressure depletion with a time range between 1960 and 2020. We simulated fault system failure induced by pressure depletion and reproduced the spatiotemporal distribution of induced seismicity and assessed its failure mechanism. Also, we estimated the ground subsidence distribution and confirmed its similarity to the field measurements in the Groningen region. Through this study, we confirm the feasibility of the presented 2D hydro-mechanical coupled DEM in simulating the deformation of a complex fault system by hydro-mechanical coupled processes.

Hazardous and Noxious Substances (HNSs) Styrene Detection Using Spectral Matching and Mixture Analysis Methods (분광정합 및 혼합 분석 방법을 활용한 위험·유해물질 스티렌 탐지)

  • Jae-Jin Park;Kyung-Ae Park;Tae-Sung Kim;Moonjin Lee
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.spc
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    • pp.1-10
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    • 2022
  • As the volume of marine hazardous and noxious substances (HNSs) transported in domestic and overseas seas increases, the risk of HNS spill accidents is gradually increasing. HNS leaked into the sea causes destruction of marine ecosystems, pollution of the marine environment, and human casualties. Secondary accidents accompanied by fire and explosion are possible. Therefore, various types of HNSs must be rapidly detected, and a control strategy suitable for the characteristics of each substance must be established. In this study, the ground HNS spill experiment process and application result of detection algorithms were presented based on hyperspectral remote sensing. For this, styrene was spilled in an outdoor pool in Brest, France, and simultaneous observation was performed through a hyperspectral sensor. Pure styrene and seawater spectra were extracted by applying principal component analysis (PCA) and the N-Findr method. In addition, pixels in hyperspectral image were classified with styrene and seawater by applying spectral matching techniques such as spectral distance similarity (SDS), spectral correlation similarity (SCS), spectral similarity value (SSV), and spectral angle mapper (SAM). As a result, the SDS and SSV techniques showed good styrene detection results, and the total extent of styrene was estimated to be approximately 1.03 m2. The study is expected to play a major role in marine HNS monitoring.

Detecting Stress Based Social Network Interactions Using Machine Learning Techniques

  • S.Rajasekhar;K.Ishthaq Ahmed
    • International Journal of Computer Science & Network Security
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    • v.23 no.8
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    • pp.101-106
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    • 2023
  • In this busy world actually stress is continuously grow up in research and monitoring social websites. The social interaction is a process by which people act and react in relation with each other like play, fight, dance we can find social interactions. In this we find social structure means maintain the relationships among peoples and group of peoples. Its a limit and depends on its behavior. Because relationships established on expectations of every one involve depending on social network. There is lot of difference between emotional pain and physical pain. When you feel stress on physical body we all feel with tensions, stress on physical consequences, physical effects on our health. When we work on social network websites, developments or any research related information retrieving etc. our brain is going into stress. Actually by social network interactions like watching movies, online shopping, online marketing, online business here we observe sentiment analysis of movie reviews and feedback of customers either positive/negative. In movies there we can observe peoples reaction with each other it depends on actions in film like fights, dances, dialogues, content. Here we can analysis of stress on brain different actions of movie reviews. All these movie review analysis and stress on brain can calculated by machine learning techniques. Actually in target oriented business, the persons who are working in marketing always their brain in stress condition their emotional conditions are different at different times. In this paper how does brain deal with stress management. In software industries when developers are work at home, connected with clients in online work they gone under stress. And their emotional levels and stress levels always changes regarding work communication. In this paper we represent emotional intelligence with stress based analysis using machine learning techniques in social networks. It is ability of the person to be aware on your own emotions or feeling as well as feelings or emotions of the others use this awareness to manage self and your relationships. social interactions is not only about you its about every one can interacting and their expectations too. It about maintaining performance. Performance is sociological understanding how people can interact and a key to know analysis of social interactions. It is always to maintain successful interactions and inline expectations. That is to satisfy the audience. So people careful to control all of these and maintain impression management.

Study on the Prediction of Motion Response of Fishing Vessels using Recurrent Neural Networks (순환 신경망 모델을 이용한 소형어선의 운동응답 예측 연구)

  • Janghoon Seo;Dong-Woo Park;Dong Nam
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.5
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    • pp.505-511
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    • 2023
  • In the present study, a deep learning model was established to predict the motion response of small fishing vessels. Hydrodynamic performances were evaluated for two small fishing vessels for the dataset of deep learning model. The deep learning model of the Long Short-Term Memory (LSTM) which is one of the recurrent neural network was utilized. The input data of LSTM model consisted of time series of six(6) degrees of freedom motions and wave height and the output label was selected as the time series data of six(6) degrees of freedom motions. The hyperparameter and input window length studies were performed to optimize LSTM model. The time series motion response according to different wave direction was predicted by establised LSTM. The predicted time series motion response showed good overall agreement with the analysis results. As the length of the time series increased, differences between the predicted values and analysis results were increased, which is due to the reduced influence of long-term data in the training process. The overall error of the predicted data indicated that more than 85% of the data showed an error within 10%. The established LSTM model is expected to be utilized in monitoring and alarm systems for small fishing vessels.

Research on Advanced Measures for Emergency Response to Water Accidents based on Big-Data (빅데이터 기반 수도사고 위기대응 고도화 방안에 관한 연구)

  • Kim, Ho-sung;Kim, Jong-rip;Kim, Jae-jong;Yoon, Young-min;Kim, Dae-kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.317-321
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    • 2022
  • In response to Incheon tap water accident in 2019, the Ministry of Environment has created the "Comprehensive Measures for Water Safety Management" to improve water operation management, provide systematic technical support, and respond to accidents. Accordingly, K-water is making a smart water supply management system for the entire process of tap water. In order to advance the response to water accidents, it is essential to secure the reliability of real-time water operation data such as flow rate, pressure, and water level, and to develop and apply a warning algorithm in advance using big data analysis techniques. In this paper, various statistical techniques are applied using water supply operation data (flow, pressure, water level, etc) to prepare the foundation for the selection of the optimal operating range and advancement of the monitoring and alarm system. In addition, the arrival time is analyzed through cross-correlation analysis of changes in raw water turbidity between the water intake and water treatment plants. The purpose of this paper is to study the model that predicts the raw water turbidity of a water treatment plant by applying raw water turbidity data considering the time delay according to the flow rate change.

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