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Digital Twin based Household Water Consumption Forecasting using Agent Based Modeling

  • Sultan Alamri;Muhammad Saad Qaisar Alvi;Imran Usman;Adnan Idris
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.147-154
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    • 2024
  • The continuous increase in urban population due to migration of mases from rural areas to big cities has set urban water supply under serious stress. Urban water resources face scarcity of available water quantity, which ultimately effects the water supply. It is high time to address this challenging problem by taking appropriate measures for the improvement of water utility services linked with better understanding of demand side management (DSM), which leads to an effective state of water supply governance. We propose a dynamic framework for preventive DSM that results in optimization of water resource management. This paper uses Agent Based Modeling (ABM) with Digital Twin (DT) to model water consumption behavior of a population and consequently forecast water demand. DT creates a digital clone of the system using physical model, sensors, and data analytics to integrate multi-physical quantities. By doing so, the proposed model replicates the physical settings to perform the remote monitoring and controlling jobs on the digital format, whilst offering support in decision making to the relevant authorities.

Data-driven Approach to Explore the Contribution of Process Parameters for Laser Powder Bed Fusion of a Ti-6Al-4V Alloy

  • Jeong Min Park;Jaimyun Jung;Seungyeon Lee;Haeum Park;Yeon Woo Kim;Ji-Hun Yu
    • Journal of Powder Materials
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    • v.31 no.2
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    • pp.137-145
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    • 2024
  • In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

A Study on the Strengthening of Smart Factory Security in OT (Operational Technology) Environment (OT(Operational Technology) 환경에서 스마트팩토리 보안 강화 방안에 관한 연구)

  • Young Ho Kim;Kwang-Kyu Seo
    • Journal of the Semiconductor & Display Technology
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    • v.23 no.2
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    • pp.123-128
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    • 2024
  • Major countries are trying to expand the construction of smart factories by introducing ICT such as the Internet of Things, cloud, and big data into the manufacturing sector to secure national-level manufacturing competitiveness in the era of the 4th industrial revolution. In addition, Germany is pushing for Industry 4.0 to build a fully automatic production system through the Internet of Things, and China is pushing for the expansion of smart factories to enhance the country's industrial competitiveness through Made in China 2025, Japan's intelligent manufacturing system, and the Korean government's manufacturing innovation 3.0. In this study, considering the increasing security connectivity of smart factories, we would like to identify security threats in the external connection part of smart factories and suggest security enhancement measures based on domestic and international standard security models to respond to the identified security threats. Eventually the proposed method can be applied by accurately identifying the smart factory security status, diagnosing vulnerabilities, establishing appropriate improvement plans, and expanding security strategies to respond to security threats.

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Investigating Factors Contributing to Inadequate Facility Safety Inspections and Diagnosis Services: A Machine Learning Approach (머신러닝 기반 시설물 안전 점검·진단용역 부실 판정 요인에 대한 연구)

  • Junyong Park;Chie Hoon Song
    • Journal of the Korean Society of Industry Convergence
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    • v.27 no.4_2
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    • pp.897-908
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    • 2024
  • Evaluating the adequacy of facility safety inspection and diagnosis services performed by private enterprises is a time-consuming and administratively complex process. This study aims to analyze the determinants that could influence the rating of these safety inspection and diagnosis services using data analytics approach. Through a comparative analysis of several machine learning algorithms suitable for multi-class classification, we selected the model with the best performance (Random Forest) and identified the main determinants using the permutation importance technique. Among the variables examined, "contract value," "days of service performed" and "adherence to fair market value" were found to be strongly correlated with the rating assessments. Furthermore, we discovered that the skills and expertise of service performing personnel significantly impacted the rating. The results of this study can contribute to the enhancement of the current post-evaluation administrative processes and offer valuable insights into rating assessments by incorporating previously unexplored variables pertaining to both service providers and the services itself.

Case Analysis on AI-Based Learning Assistance Systems (인공지능 기반 학습 지원 시스템에 관한 사례 분석)

  • Chee, Hyunkyung;Kim, Minji;Lee, Gayoung;Huh, Sunyoung;Kim, Myung sun
    • Journal of Engineering Education Research
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    • v.27 no.4
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    • pp.3-11
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    • 2024
  • This study classified domestic and international systems by type, presenting their key features and examples, with the aim of outlining future directions for system development and research. AI-based learning assistance systems can be categorized into instructional-learning evaluation types and academic recommendation types, depending on their purpose. Instructional-learning evaluation types measure learners' levels through initial diagnostic assessments, provide customized learning, and offer adaptive feedback visualized based on learners' misconceptions identified through learning data. Academic recommendation types provide personalized academic pathways and a variety of information and functions to assist with overall school life, based on the big data held by schools. Based on these characteristics, future system development should clearly define the development purpose from the planning stage, considering data ethics and stability, and should not only approach from a technological perspective but also sufficiently reflect educational contexts.

A study on Strengthening Cyber Capabilities According to the Digital Transformation in the Defense Sector (국방 디지털 전환에 따른 사이버역량 강화 방안 연구)

  • InJung Kim;Soojin Lee
    • Convergence Security Journal
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    • v.21 no.4
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    • pp.3-13
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    • 2021
  • As new technologies such as artificial intelligence (AI), cloud, Internet of Things (IoT), big data, and mobile become organically integrated, a new era of digital transformation is emerging. As a result of this digital transformation, cybersecurity issues have surfaced as a negative side effect. Cyberspace, unlike physical space, has no clear limits, which leads to additional side effects and hazards. While promoting digital transformation in defense, conventional customs and behavioral approaches make it difficult to alter the cybersecurity strategy, even if it is vital to comprehend and prepare the attributes associated with time and technology trends. As a result, in this study, we will look at the direction of technology application in the defense as a result of digital transformation and analyze how to correlate from the standpoint of cybersecurity.

Pretreatment of Livestock Wastewater containing PO4-3-P with Waste Oyster Shells (폐굴껍질을 이용한 축산폐수중 무기인의 1차 처리)

  • Kim, Eun-Ho;Kim, Seok-Tack;Jang, Sung-Ho
    • Korean Journal of Environmental Agriculture
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    • v.18 no.1
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    • pp.48-53
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    • 1999
  • In this study, various batch tests were performed to examine the utilization of waste oyster shells for removal of $PO_4^{3-}-P$ in livestock wastewater, because waste oyster shells have been known to be very porous and to have alkaline minerals such as calcium and mangnesium. $PO_4^{3-}-P$ removal rate were increased by waste oyster shells, as specific surface area and contact efficiency per unit area of their were increased. Generally, it could be showed that $PO_4^{3-}-P$ removal rate were very influenced by particle size, dosage and temperature. At low pH of initial reactions, it would be showed that $PO_4^{3-}-P$ removals were directly influenced by adsorption but crystallization process were dominated with passed time and pH increasing. The SEM observed that the variations were hardly seen, but particle sizes of waste oyster shell were relatively big after reactions and showed forms of smaller plate than before reactions.

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Economic evaluation on heating systems of apartment complex (공동주택단지 난방시스템들에 대한 경제성 평가)

  • 조금남;윤승호;김원배
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.10 no.6
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    • pp.773-783
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    • 1998
  • The heating system for apartment complex may be classified as old systems including central system with steam boiler(S1), gas engine driven heat pump system(S2), system using waste heat(S3) and new systems including mechanical vapor re-compression system with flashing heat exchangers(S4), system using methanol(S5), system using metal hydride (S6). The purpose of the present study is to suggest optimal heating system by technically, economically and environmentally evaluating old and new heating systems of apartment complex from 500 to 3,000 households. Economic evaluation based on the technical evaluation results which estimated heat transfer area of heat exchangers and capacity of equipments was estimated initial investment cost, annual operating cost and relative payback period by considering annual increasing rates of energy cost and interest. Environmental evaluation provided annual generation rate of carbon dioxide. Initial investment cost was cheap in the order of S6, S5, S3, S2, S4, S1, annual operating cost was cheap in the order of S1, S2, S4, S5 and relative payback period was short in the order of S6, S5, S2, S3 and S4. Relative payback period was within 8 years for all scenarios of 3,000 households, and was increased as annual increasing rates of energy cost and interest were increased. As transportation pipe length was increased twice, payback period was increased by 1.4~2.6 time. The effect of temperatures of waste gas and waste water on the relative payback period was small within 0.8 years. The annual generation rate of carbon dioxide was big in the order of S4, S2 and S1. S4 was the most economic system among whole scenarios when S1 was replaced with other scenarios.

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The 4th Industrial Revolution's Impact on Network Marketing - Focused on ABN Korea Case - (4차 산업혁명 시대 정보통신기술(ICT)이 가져온 네트워크 마케팅의 현재와 미래 - 한국암웨이 사례 연구 -)

  • Park, So-Jin;Oh, Chang-Gyu
    • The Journal of Information Systems
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    • v.26 no.4
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    • pp.379-400
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    • 2017
  • Purpose The purpose of this study is to investigate the effects of ICT on multilevel marketing organizations (MLMs) whose members are both salespeople and consumers. This study explores the effects of the latest ICT convergence on the direct selling, which is the oldest sales method, and suggests the direction for the development of network marketing. Therefore, we will propose the changes in direct sales brought by ICT and predict the future direction of network marketing in preparation for the 4th Industrial Revolution era. Design/methodology/approach Exploratory case study was the methodology selected for this paper. The case study enables the use of multiple methods for data collection and analysis. This study applies qualitative case-study methodology on Amway Korea, which is the top seller of MLM organizations, to better understand the impact of ICT. This study conducted an in-depth interview with four different levels of MLM members (e.g. membership, ruby, emerald, diamond) which are based on the qualification system of MLM organizations and observed their behaviors. Findings This study revealed that the ICT impact on network marketing organizations(MLMs) could be summarized as follows : new membership growth, easier communication with customers, increase in work efficiency, increase in organizational trust, change in educational environment, and increase in the use of social media. Based on the interview, we propose the changes of network marketing organizations in the fourth industrial revolution era and the future strategy of Amway Korea as follows: (1) retention of royal ABOs, (2) harmony with SMEs, (3) utilization of Big Data, (4) creation of IoT business model, and (5) construction of successful O2O business platform.

Development of Cloud based Data Collection and Analysis for Manufacturing (클라우드 기반의 생산설비 데이터 수집 및 분석 시스템 개발)

  • Young-Dong Lee
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.4
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    • pp.216-221
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    • 2022
  • The 4th industrial revolution is accelerating the transition to digital innovation in various aspects of our daily lives, and efforts for manufacturing innovation are continuing in the manufacturing industry, such as smart factories. The 4th industrial revolution technology in manufacturing can be used based on AI, big data, IoT, cloud, and robots. Through this, it is required to develop a technology to establish a production facility data collection and analysis system that has evolved from the existing automation and to find the cause of defects and minimize the defect rate. In this paper, we implemented a system that collects power, environment, and status data from production facility sites through IoT devices, quantifies them in real-time in a cloud computing environment, and displays them in the form of MQTT-based real-time infographics using widgets. The real-time sensor data transmitted from the IoT device is stored to the cloud server through a Rest API method. In addition, the administrator could remotely monitor the data on the dashboard and analyze it hourly and daily.