• Title/Summary/Keyword: Four operations

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A Study on the Environmental Effects of Improvement of Activated Carbon Adsorption Tower for the Application of Activated Carbon Co-Regenerated System in Sihwa/Banwal Industrial Complex (시화반월산업단지 활성탄 공동재생시스템 적용을 위한 활성탄 흡착탑 개선에 따른 환경적 효과분석)

  • Choi, Ye Jin;Rhee, Young Woo;Chung, Gu Hoi;Kim, Duk Hyun;Park, Seung Joon
    • Clean Technology
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    • v.27 no.2
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    • pp.160-167
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    • 2021
  • This study investigated the environmental effects of improving the general-type activated carbon adsorption tower used at the Sihwa/Banwol Industrial Complex with use of a cartridge-type activated carbon adsorption tower for the application of an activated carbon co-regenerated system. Four general-type activated carbon adsorption towers and two cartridge-type activated carbon adsorption towers were selected to analyze the properties of activated carbon and to compare the efficiency of reducing environmental pollutants. The results showed that the activated carbon used in the cartridge-type activated carbon adsorption towers was high quality activated carbon with an iodine adsorption force of more than 800 mg/g and that a good adsorption performance was maintained within the replacement cycle. From an analysis of the environmental pollutant reduction efficiency, it was confirmed that the cartridge-type activated carbon adsorption tower functioned properly as a prevention facility for handling emissions pollutants with a treatment efficiency of total hydrocarbons (THC), toluene, and methylethylketone (MEK) components of 71%, 77%, and 80%, respectively. The general activated carbon adsorption tower, which was confirmed to use low-performance activated carbon, had a very low treatment efficiency and did not function properly as a prevention facility for dealing with emission pollutants. It is believed that it is possible to reduce pollutants during operations by changing from the general-type activated carbon adsorption tower to a cartridge-type activated carbon adsorption tower.

Evaluation of Habitat Diversity Changes by Weir Operation of the Sejongbo Weir in Geum River using High-resolution Aerial Photographs (항공사진을 이용한 금강 세종보 수문개방에 따른 서식처 다양도 변화 분석)

  • Ock, Giyoung;Choi, Mikyoung;Kim, Jeong-cheol;Park, Hyung-Geun;Han, Ji Hyun
    • Ecology and Resilient Infrastructure
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    • v.7 no.4
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    • pp.366-373
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    • 2020
  • This study investigated habitat diversity changes by conducting weir operations at the Sejongbo site in the Geum River basin. High-resolution aerial photographs taken before and after the weir-opening operation were used for habitat analyses. We classified water and bar areas into 17 types, such as lotic habitats, including riffles, runs, and glides, and lentic habitats, including reservoirs, pools, bar-head backwaters, and bar ponds. Then, we estimated each habitat area quantitatively, calculated a habitat diversity index, and established a habitat diversity map. Our results indicated that after the weir-opening operation, lotic habitats and new types of shallow lentic habitats increased in the water area. In addition, for the bar area, bare lands without cultivation increased distinctively. Finally, we observed that the habitat diversity index drastically increased after the weir-opening operation, which could provide a relatively simple channel of diverse habitats.

A Study on the Effects of Domestic Medical Library Librarians' Awareness of the COVID-19 Situation on Information Services (국내 의학도서관 사서의 코로나19 상황 인식이 정보서비스에 미치는 영향에 관한 연구)

  • Kim, Tae Min;Kim, Hai Hin;Lee, Min Ji
    • Journal of the Korean Society for Library and Information Science
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    • v.55 no.3
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    • pp.303-319
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    • 2021
  • This study sought to find out the status of medical libraries in Korea that provide information services related to the Covid-19 situation, and how the librarian's perception of the Covid-19 situation, the main body of the library's information provision, affects the provision of related information services. For this purpose, we checked the website for Covid-19 information service. In order to understand the degree of awareness of Covid-19, Grunig's Situational Theory was applied to classify four types of librarians according to the degree of problem recognition, constraint recognition, and involvement recognition, and to analyze how the three perceptions affect Covid-19 related information services. As a result, only 25 out of 144 korean medical libraries provided information services related to Covid-19. The librarian, the main agent of the library's information provision, found that the problem recognition and involvement recognition in the Covid-19 situation were high, constraint recognition were low, and the level of information service was very active. And only constraint recognition has been shown to have a significant impact on providing Covid-19 related information services. Further research when future sources are available and follow-up research on how librarians' perceptions affect library operations are also proposed.

Trustworthy AI Framework for Malware Response (악성코드 대응을 위한 신뢰할 수 있는 AI 프레임워크)

  • Shin, Kyounga;Lee, Yunho;Bae, ByeongJu;Lee, Soohang;Hong, Heeju;Choi, Youngjin;Lee, Sangjin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.5
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    • pp.1019-1034
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    • 2022
  • Malware attacks become more prevalent in the hyper-connected society of the 4th industrial revolution. To respond to such malware, automation of malware detection using artificial intelligence technology is attracting attention as a new alternative. However, using artificial intelligence without collateral for its reliability poses greater risks and side effects. The EU and the United States are seeking ways to secure the reliability of artificial intelligence, and the government announced a reliable strategy for realizing artificial intelligence in 2021. The government's AI reliability has five attributes: Safety, Explainability, Transparency, Robustness and Fairness. We develop four elements of safety, explainable, transparent, and fairness, excluding robustness in the malware detection model. In particular, we demonstrated stable generalization performance, which is model accuracy, through the verification of external agencies, and developed focusing on explainability including transparency. The artificial intelligence model, of which learning is determined by changing data, requires life cycle management. As a result, demand for the MLops framework is increasing, which integrates data, model development, and service operations. EXE-executable malware and documented malware response services become data collector as well as service operation at the same time, and connect with data pipelines which obtain information for labeling and purification through external APIs. We have facilitated other security service associations or infrastructure scaling using cloud SaaS and standard APIs.

Development of a Korean-version Integrated Message Set to Provide Information on Traffic Safety Facilities for Autonomous Vehicles (자율주행 자동차 대응 교통안전시설의 정보 제공을 위한 한국형 통합 메시지 셋 설계 방안 연구)

  • Eunjeong Ko;Hyeokjun Jang;Eum Han;Kitae Jang
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.6
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    • pp.284-298
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    • 2022
  • It is necessary to acquire information on traffic safety facilities installed on the roadways specifically for the operation of autonomous vehicles. The purpose of this study is to prepare a Korean version of an integrated message-set design as a way to provide to autonomous vehicles standardized information on traffic safety facilities. In this study, necessary facilities are classified according to four criteria (no legal basis; not providing information to autonomous vehicles; providing duplicate information; not standardized, and too difficult to generalize) based on information that must be provided to operate autonomous vehicles. The priority of information delivery (gross negligence followed by behavior change) was classified according to the importance of the information to be provided during autonomous driving, and the form was defined for the classification code in the information delivered. Finally, the information location and delivery method of traffic facilities for compliance with SAE J2735 were identified. This study is meaningful in that it provides a plan for roadway operations by suggesting a method for providing information to autonomously driven vehicles.

Optimized Hardware Design using Sobel and Median Filters for Lane Detection

  • Lee, Chang-Yong;Kim, Young-Hyung;Lee, Yong-Hwan
    • Journal of Advanced Information Technology and Convergence
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    • v.9 no.1
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    • pp.115-125
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    • 2019
  • In this paper, the image is received from the camera and the lane is sensed. There are various ways to detect lanes. Generally, the method of detecting edges uses a lot of the Sobel edge detection and the Canny edge detection. The minimum use of multiplication and division is used when designing for the hardware configuration. The images are tested using a black box image mounted on the vehicle. Because the top of the image of the used the black box is mostly background, the calculation process is excluded. Also, to speed up, YCbCr is calculated from the image and only the data for the desired color, white and yellow lane, is obtained to detect the lane. The median filter is used to remove noise from images. Intermediate filters excel at noise rejection, but they generally take a long time to compare all values. In this paper, by using addition, the time can be shortened by obtaining and using the result value of the median filter. In case of the Sobel edge detection, the speed is faster and noise sensitive compared to the Canny edge detection. These shortcomings are constructed using complementary algorithms. It also organizes and processes data into parallel processing pipelines. To reduce the size of memory, the system does not use memory to store all data at each step, but stores it using four line buffers. Three line buffers perform mask operations, and one line buffer stores new data at the same time as the operation. Through this work, memory can use six times faster the processing speed and about 33% greater quantity than other methods presented in this paper. The target operating frequency is designed so that the system operates at 50MHz. It is possible to use 2157fps for the images of 640by360 size based on the target operating frequency, 540fps for the HD images and 240fps for the Full HD images, which can be used for most images with 30fps as well as 60fps for the images with 60fps. The maximum operating frequency can be used for larger amounts of the frame processing.

Development and Validation of Virtual Training Content Satisfaction Measurement Tool (가상훈련 콘텐츠 만족도 측정도구 개발 및 타당화)

  • Miseok Yang;Woocheol Kim;Ohyoung Kwon
    • Journal of Practical Engineering Education
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    • v.15 no.1
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    • pp.1-11
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    • 2023
  • The purpose of this study is to develop and validate a tool that measures the satisfaction of virtual training learners' use of virtual training content. To this end, 491 copies of the basic questions derived from the satisfaction questions used by the K University Online Lifelong Education Center were used for the final analysis by conducting an online survey of learners who accessed STEP, the K University Online Lifelong Education Center portal. The 491 copies of data finally used were analyzed by methods such as basic question analysis, exploratory factor analysis, reliability analysis, and confirmatory factor analysis. First, in the basic question analysis, there were no questions that exceeded the acceptance criteria of an average of 4 points or more, skewness ±2, and kurtosis ±4. Second, the correlation coefficient for each sub-factor of virtual training content satisfaction derived after exploratory factor analysis was good as r=.682 to .822 (p<.01). The reliability coefficient for each sub-factor is content .849, content utilization .922, System and Operations Support .841, Intention to Continue Utilization .920, the overall reliability is. It was very high at .956 Fifth, as a result of confirmatory factor analysis, the compositional conceptual diagram is. It was .842 to .926, higher than the recommended standard of .7, and the average variance extraction degree. It appears to be .640 to .796, higher than the recommended standard of .5, which can be seen as representative of each constituent concept. As a result of verifying the validity of virtual training learners' content satisfaction recruitment, four factor models were derived: content substance, content utilization, system and operation support, and intention to continue use. This study is meaningful in that it empirically developed a tool to measure content satisfaction of virtual training learners and provided a reference frame and criteria.

Performance Characteristics of an Ensemble Machine Learning Model for Turbidity Prediction With Improved Data Imbalance (데이터 불균형 개선에 따른 탁도 예측 앙상블 머신러닝 모형의 성능 특성)

  • HyunSeok Yang;Jungsu Park
    • Ecology and Resilient Infrastructure
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    • v.10 no.4
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    • pp.107-115
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    • 2023
  • High turbidity in source water can have adverse effects on water treatment plant operations and aquatic ecosystems, necessitating turbidity management. Consequently, research aimed at predicting river turbidity continues. This study developed a multi-class classification model for prediction of turbidity using LightGBM (Light Gradient Boosting Machine), a representative ensemble machine learning algorithm. The model utilized data that was classified into four classes ranging from 1 to 4 based on turbidity, from low to high. The number of input data points used for analysis varied among classes, with 945, 763, 95, and 25 data points for classes 1 to 4, respectively. The developed model exhibited precisions of 0.85, 0.71, 0.26, and 0.30, as well as recalls of 0.82, 0.76, 0.19, and 0.60 for classes 1 to 4, respectively. The model tended to perform less effectively in the minority classes due to the limited data available for these classes. To address data imbalance, the SMOTE (Synthetic Minority Over-sampling Technique) algorithm was applied, resulting in improved model performance. For classes 1 to 4, the Precision and Recall of the improved model were 0.88, 0.71, 0.26, 0.25 and 0.79, 0.76, 0.38, 0.60, respectively. This demonstrated that alleviating data imbalance led to a significant enhancement in Recall of the model. Furthermore, to analyze the impact of differences in input data composition addressing the input data imbalance, input data was constructed with various ratios for each class, and the model performances were compared. The results indicate that an appropriate composition ratio for model input data improves the performance of the machine learning model.

Optimized Implementation of PIPO Lightweight Block Cipher on 32-bit RISC-V Processor (32-bit RISC-V상에서의 PIPO 경량 블록암호 최적화 구현)

  • Eum, Si Woo;Jang, Kyung Bae;Song, Gyeong Ju;Lee, Min Woo;Seo, Hwa Jeong
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.6
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    • pp.167-174
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    • 2022
  • PIPO lightweight block ciphers were announced in ICISC'20. In this paper, a single-block optimization implementation and parallel optimization implementation of PIPO lightweight block cipher ECB, CBC, and CTR operation modes are performed on a 32-bit RISC-V processor. A single block implementation proposes an efficient 8-bit unit of Rlayer function implementation on a 32-bit register. In a parallel implementation, internal alignment of registers for parallel implementation is performed, and a method for four different blocks to perform Rlayer function operations on one register is described. In addition, since it is difficult to apply the parallel implementation technique to the encryption process in the parallel implementation of the CBC operation mode, it is proposed to apply the parallel implementation technique in the decryption process. In parallel implementation of the CTR operation mode, an extended initialization vector is used to propose a register internal alignment omission technique. This paper shows that the parallel implementation technique is applicable to several block cipher operation modes. As a result, it is confirmed that the performance improvement is 1.7 times in a single-block implementation and 1.89 times in a parallel implementation compared to the performance of the existing research implementation that includes the key schedule process in the ECB operation mode.

A Study on the Perception and Experience of Daejeon Public Library Users Using Text Mining: Focusing on SNS and Online News Articles (텍스트마이닝을 활용한 대전시 공공도서관 이용자의 인식과 경험 연구 - SNS와 온라인 뉴스 기사를 중심으로 -)

  • Jiwon Choi;Seung-Jin Kwak
    • Journal of the Korean Society for Library and Information Science
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    • v.58 no.2
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    • pp.363-384
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    • 2024
  • This study was conducted to examine the user's experiences with the public library in Daejeon using big data analysis, focusing on the text mining technique. To know this, first, the overall evaluation and perception of users about the public library in Daejeon were explored by collecting data on social media. Second, through analysis using online news articles, the pending issues that are being discussed socially were identified. As a result of the analysis, the proportion of users with children was first high. Next, it was found that topics through LDA analysis appeared in four categories: 'cultural event/program', 'data use', 'physical environment and facilities', and 'library service'. Finally, it was confirmed that keywords for the additional construction of libraries and complex cultural spaces and the establishment of a library cooperation system appeared at the core in the news article data. Based on this, it was proposed to build a library in consideration of regional balance and to create a social parenting community network through business agreements with childcare and childcare institutions. This will contribute to identifying the policy and social trends of public libraries in Daejeon and implementing data-based public library operations that reflect local community demands.