• Title/Summary/Keyword: BIG4

Search Result 3,614, Processing Time 0.035 seconds

A Study on the Improvement of Technical Guidance Fee for Preventing Accidents at Small-Medium Construction Sites (중·소규모 건설현장 재해예방 기술지도 대가 개선에 관한 연구)

  • Lim, Se-Jong;Shin, Seung-Hyeon;Won, Jeong-Hun;Yoon, Young-Cheol
    • Journal of the Korea Institute of Building Construction
    • /
    • v.21 no.5
    • /
    • pp.469-481
    • /
    • 2021
  • Under Korean law, small-to-medium-sized construction projects with budgets of more than 100 million won and less than 12 billion won must receive technical guidance by a visiting technician belonging to a specialized institution. This study proposed a method for calculating the technical guidance fee to prevent the potential inadequacy of technical guidance when the responsibility providing the technical guidance fee is changed from a contractor to a client. The method simplified the construction works which should receive technical guidance into four sections according to the construction amount. For each section, the number of instances of technical guidance per day provided by the visiting technician and the minimum technical grade of the visiting technician were limited, and the guideline for estimating engineering services fees was applied to calculate the fee per instance of technical guidance. The results show that the proposed method can be applied to the establishment of a technical guidance fee guideline since it well reflects the current fee distribution and K2B analysis results.

A Study on the Conflict between the Use of Personally non-Identifiable Information and the Protection of Personal Information in Digital Behavioral Advertising: Focusing on the Domestic and Foreign Status and System (디지털 맞춤형 광고에서 비식별개인정보의 활용과 개인정보 보호와의 갈등에 관한 연구: 국내외 현황과 제도를 중심으로)

  • Choi, Min-Wook
    • Journal of Convergence for Information Technology
    • /
    • v.11 no.1
    • /
    • pp.71-79
    • /
    • 2021
  • This study looked at the conflict between the aspect of the use of personally non-identifiable information for the development of the big data industry and the digital advertising industry and the aspect of personal information protection. In order to achieve the research purpose, this study focused on literature research such as thesis, legal texts, administrative regulations, and recent media articles. As a result of this study, the main issues related to the protection of personally non-Identifiable Information in digital behavioral advertising were 'conflict between freedom of advertising expression and personal rights', 'personalization of unidentifiable information', 'information imbalance'. In this regard, as measures to protect personally non-identifiable information in digital behavioral advertising, it was proposed to 'harmonize with freedom of advertising expression and personal rights, 'improve notification and consent. process', and 'reinforce the right to control personal information'.

A Case Study on Smart Factory Extensibility for Small and Medium Enterprises (중소기업 스마트 공장 확장성 사례연구)

  • Kim, Sung-Min;Ahn, Jaekyoung
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.44 no.2
    • /
    • pp.43-57
    • /
    • 2021
  • Smart factories can be defined as intelligent factories that produce products through IoT-based data. In order to build and operate a smart factory, various new technologies such as CPS, IoT, Big Data, and AI are to be introduced and utilized, while the implementation of a MES system that accurately and quickly collects equipment data and production performance is as important as those new technologies. First of all, it is very essential to build a smart factory appropriate to the current status of the company. In this study, what are the essential prerequisite factors for successfully implementing a smart factory was investigated. A case study has been carried out to illustrate the effect of implementing ERP and MES, and to examine the extensibilities into a smart factory. ERP and MES as an integrated manufacturing information system do not imply a smart factory, however, it has been confirmed that ERP and MES are necessary conditions among many factors for developing into a smart factory. Therefore, the stepwise implementation of intelligent MES through the expansion of MES function was suggested. An intelligent MES that is capable of making various decisions has been investigated as a prototyping system by applying data mining techniques and big data analysis. In the end, in order for small and medium enterprises to implement a low-cost, high-efficiency smart factory, the level and goal of the smart factory must be clearly defined, and the transition to ERP and MES-based intelligent factories could be a potential alternative.

Evaluation of Pressurized Water Mixing of Big Pipe with CFD at Water Treatment Process (CFD를 활용한 수처리공정 대형관에서 압력수 혼합공정 평가)

  • Cho, Young-Man;Yu, Hyun-chul;Jang, Gyeong-Hyuk;Jung, Yong-Jun
    • Journal of Korean Society on Water Environment
    • /
    • v.37 no.3
    • /
    • pp.168-174
    • /
    • 2021
  • Mixing is a very important unit in water treatment process. A mechanical stirring method is generally used for mixing, but recently, the use of pressurized water mixing method (pump diffusion flash mixer) has gained interest because it is more advantageous in terms of mixing time, noise, energy consumption, and maintenance. The following conclusions were obtained from the study of pressurized water mixing method by Computational Fluid Dynamics. Firstly, the mixing degree in the pipe increased as the density of water increased. Secondly, even if the relative velocity between flow rate in the pipe and the pressurized water was constant, the mixing degree decreased as the flow velocity in the pipe increased. Thirdly, the stronger the injection energy the higher the mixing degree. It was also found that the mixing degree was greatly affected by the injection velocity as compared to the injection flow amount. Finally, the required energy to achieve 95% mixing degree at the distance of 10 times diameter in big pipes of 500 mm to 3000 mm was 0.3 to 4.5 kJ. The result of this study could be used in the process design of injection with water purification chemicals, such as, ozone, chlorine, and coagulant.

Empirical Analysis of Medical Accessibility for People with Disabilities using Health Insurance Big Data (건강보험빅데이터의 고혈압 입원율 분석을 통한 장애인의 의료접근성 실증 분석)

  • Jeon, HuiWon;Hong, MinJung;Jeong, JaeYeon;Kim, YeSoon;Lee, ChangWoo;Lee, HaeJong;Shin, EulChul
    • Korea Journal of Hospital Management
    • /
    • v.27 no.1
    • /
    • pp.1-10
    • /
    • 2022
  • Background: This study aims to empirically compare and evaluate the current status of medical accessibility and health inequality between people with disabilities and without. We calculated the ACSC hospitalization rate, which is a medical accessibility index, for hypertension, a major risk factor for cardiovascular disease that accounts for more than 20% of deaths among people with disabilities using the 2016 National Health Insurance Big Data. Methods: The subjects of the study were a total of 601,520, including 64,018 people with disabilities and 537,501 people without. Logistic regression was performed to analyze the differences in hypertension hospitalization rates adjusted for demographic and sociological characteristics and disease characteristics using SAS 9.4 program. Results: Before adjusting for the characteristics, the hypertension hospitalization rate of people with disabilities was 1.55%, and the people without disabilities were 0.49%. After adjusting, it was found that people with disabilities were 2.11 times higher than people without disabilities, and it was statistically significant. Conclusion: The preventable hospitalization rate of people with disabilities is higher than that of people without, suggesting that the disabled have problems with access to medical care and health inequality. Therefore, the government's policy improvement is required to close the medical gap for the disabled.

Development of Rainfall Information Production Technology Using Optical Sensors (Estimation of Real-Time Rainfall Information Using Optima Rainfall Intensity Technique) (광학센서를 이용한 강우정보 생산기법 개발 (최적 강우강도 기법을 이용한 실시간 강우정보 산정))

  • Lee, Byung-Hyun;Kim, Byung-Sik;Lee, Young-Mi;Oh, Cheong-Hyeon;Choi, Jung-Ryel;Jun, Weon-Hyouk
    • Journal of Environmental Science International
    • /
    • v.30 no.12
    • /
    • pp.1101-1111
    • /
    • 2021
  • In this study, among the W-S-R(Wiper-Signal-Rainfall) relationship methods used to produce sensor-based rain information in real time, we sought to produce actual rainfall information by applying machine learning techniques to account for the effects of wiper operation. To this end, we used the gradient descent and threshold map methods for pre-processing the cumulative value of the difference before and after wiper operation by utilizing four sensitive channels for optical sensors which collected rain sensor data produced by five rain conditions in indoor artificial rainfall experiments. These methods produced rainfall information by calculating the average value of the threshold according to the rainfall conditions and channels, creating a threshold map corresponding to the 4 (channel) × 5 (considering rainfall information) grid and applying Optima Rainfall Intensity among the big data processing techniques. To verify these proposed results, the application was evaluated by comparing rainfall observations.

Quantitative Analysis for Win/Loss Prediction of 'League of Legends' Utilizing the Deep Neural Network System through Big Data

  • No, Si-Jae;Moon, Yoo-Jin;Hwang, Young-Ho
    • Journal of the Korea Society of Computer and Information
    • /
    • v.26 no.4
    • /
    • pp.213-221
    • /
    • 2021
  • In this paper, we suggest the Deep Neural Network Model System for predicting results of the match of 'League of Legends (LOL).' The model utilized approximately 26,000 matches of the LOL game and Keras of Tensorflow. It performed an accuracy of 93.75% without overfitting disadvantage in predicting the '2020 League of Legends Worlds Championship' utilizing the real data in the middle of the game. It employed functions of Sigmoid, Relu and Logcosh, for better performance. The experiments found that the four variables largely affected the accuracy of predicting the match --- 'Dragon Gap', 'Level Gap', 'Blue Rift Heralds', and 'Tower Kills Gap,' and ordinary users can also use the model to help develop game strategies by focusing on four elements. Furthermore, the model can be applied to predicting the match of E-sports professional leagues around the world and to the useful training indicators for professional teams, contributing to vitalization of E-sports.

Heart Disease Prediction Using Decision Tree With Kaggle Dataset

  • Noh, Young-Dan;Cho, Kyu-Cheol
    • Journal of the Korea Society of Computer and Information
    • /
    • v.27 no.5
    • /
    • pp.21-28
    • /
    • 2022
  • All health problems that occur in the circulatory system are refer to cardiovascular illness, such as heart and vascular diseases. Deaths from cardiovascular disorders are recorded one third of in total deaths in 2019 worldwide, and the number of deaths continues to rise. Therefore, if it is possible to predict diseases that has high mortality rate with patient's data and AI system, they would enable them to be detected and be treated in advance. In this study, models are produced to predict heart disease, which is one of the cardiovascular diseases, and compare the performance of models with Accuracy, Precision, and Recall, with description of the way of improving the performance of the Decision Tree(Decision Tree, KNN (K-Nearest Neighbor), SVM (Support Vector Machine), and DNN (Deep Neural Network) are used in this study.). Experiments were conducted using scikit-learn, Keras, and TensorFlow libraries using Python as Jupyter Notebook in macOS Big Sur. As a result of comparing the performance of the models, the Decision Tree demonstrates the highest performance, thus, it is recommended to use the Decision Tree in this study.

Sustainable Smart City Building-energy Management Based on Reinforcement Learning and Sales of ESS Power

  • Dae-Kug Lee;Seok-Ho Yoon;Jae-Hyeok Kwak;Choong-Ho Cho;Dong-Hoon Lee
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.17 no.4
    • /
    • pp.1123-1146
    • /
    • 2023
  • In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.

IT Fusion Global Education Methods for Fostering Global Teachers (글로벌 교원 양성을 위한 IT 융합 글로벌 교육 방법)

  • Kang, Ju-Young;Kim, Seong-Baeg;Kwon, Sang-Chul
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
    • /
    • v.6 no.4
    • /
    • pp.341-349
    • /
    • 2016
  • To meet the requirements in the global age, the necessity and importance of global education in the field of education is rapidly increasing. However, according to the viewpoint on global education, a general consensus of its definition and model is not clear yet and the substantial outcome falls short of our expectation due to high cost, low effectiveness, and lack of persistency in the process of global education. Furthermore, there has been little research on global education for fostering global capabilities of pre-teachers. In this research, we compared and analyzed the ongoing global education programs for training global teachers in domestic universities. Also, through a study on IT fusion education system for tackling the difficulties in global education, we examined appropriate IT fusion education methods. In particular, beased on big data analysis techniques, we presented a recommendation system to complete a global curriculum, which can help a dual-degree or exchange student program.