• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.925-928
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• 2010

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor network. In this paper, we introduce a clustering protocol with mode selection (CPMS) for wireless sensor networks. Our scheme improves the performance of BCDCP (Base Station Controlled Dynamic Clustering Protocol) and BIDRP (Base Station Initiated Dynamic Routing Protocol) routing protocol. In CPMS, the base station constructs clusters and makes the head node with highest residual energy send data to base station. Furthermore, we can save the energy of head nodes using modes selection method. The simulation results show that CPMS achieves longer lifetime and more data messages transmissions than current important clustering protocol in wireless sensor networks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.111-120
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• 2009

Restructuring urban land use patterns from the motor-oriented to transit-oriented ones is a contemporary trend in urban planning and transportation. It is expected that transforming urban land use patterns to be transit and walking friendly would resolve various urban problems such as heavy energy consumptions, air pollutions, and traffic congestions. Korean cities have much potentials for developing transit-oriented urban environments in terms of its density and civil service levels, but the level of transit usage levels and the environmental quality of cities are not good enough for supporting such transition. The purpose of this study is to analyze the urban transit center areas and identify the problems to be solved to create transit-oriented urban environments. Case studies of four urban transit center areas in Seoul Metropolitan region were conducted to examine the spatial characteristics of urban transit center areas and identify their problems. Development density, land use diversity, walk-ability and transit connectivity were the primary feature of interests.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.246-248
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• 2021

Recently data has been transformed into a data economy and society that acts as a catalyst for the development of all industries and the creation of new value, and COVID-19 is accelerating digital transformation. In the upcoming intelligent Internet of Things era, the availability of decentralized systems such as blockchain and mixnet is emerging to solve the security problems of centralized systems that makes it difficult to utilize data safely and efficiently. Blockchain manages data in a transparent and decentralized manner and guarantees the reliability and integrity of the data through agreements between participants, but the transparency of the data threatens the privacy of users. On the other hand, mixed net technology for protecting privacy protects privacy in distributed networks, but due to inefficient power consumption efficiency and processing speed issues, low cost, light weight, low power consumption Internet Hard to use. In this paper, we analyze the limitations of conventional mixed-net technology and propose a mixed-net technology method for low power consumption, high speed, and the Internet of things.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.150-152
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• 2021

For the development of a resource recycling society, it is important to control the generation of waste in all processes such as production, distribution, consumption and disposal, and to recycle the recyclable resources of waste instead of simply landfilling and incineration. However, in order to develop a resource-recycling society, not only emitters, businesses, and the central government, but also local governments need to work together to find a solution. Therefore, in this study, we present a promotion strategy for the development of Sejong City's resource-recycling society, taking into consideration the current situation of Sejong City as well as changes in the government's institution system. We suggest that regionally preparing recycling priority management plan, maximizing waste resource utilization, establishing recycling industry activation plan, and building a systematic and efficient recycling platform, etc.

• International Area Studies Review
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• v.13 no.1
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• pp.491-512
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• 2009

The study on waiting time has been conducted from the psychological perspective since Maister (1985). In using medical institutions, especially general hospitals, it is not avoidable to wait for a long time. As a result, the waiting time gives clients psychological stress, which causes medical consumers to be more dissatisfied and decreases their rate of revisit. Accordingly, it is very urgent to study on the waiting time for hospitals' marketing and better image-making. This study is intended to find out how hospitals image and clients revisit is influenced by waiting environment and consumers' attitude, variables of waiting time perceived in medical services. Based on this study, those medical institutions are required to improve their medical service and waiting environment. Accordingly, they should convert waiting time into more efficient and comfortable recess and provide better environment for physical service and effective human services. As those medical institutions have relatively worse image than other businesses, they should actively study on ways of better image-making in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.41-54
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• 2023

Smart grid that supports efficient energy production and management is used in various fields and industries. However, because of the environment in which services are provided through open networks, it is essential to resolve trust issues regarding security vulnerabilities and privacy preservation. In particular, the identification information of smart meter is managed by a centralized server, which makes it vulnerable to security attacks such as device stolen, data forgery, alteration, and deletion. To solve these problems, this paper proposes a blockchain based authentication protocol for a smart meter. The proposed scheme issues an unique decentralized identifiers (DIDs) for individual smart meter through blockchain and utilizes a random values based on physical unclonable function (PUF) to strengthen the integrity and reliability of data. In addition, we analyze the security of the proposed scheme using informal security analysis and AVISPA simulation, and show the efficiency of the proposed scheme by comparing with related work.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.103-108
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• 2024

In this paper, a smart elevator system was studied using real-time object detection technology based on YOLO(You only look once)v5. When an external elevator button is pressed, the YOLOv5 model analyzes the camera video to determine whether there are people waiting, and if it determines that there are no people waiting, the button is automatically canceled. The study introduces an effective method of implementing object detection and communication technology through YOLOv5 and MQTT (Message Queuing Telemetry Transport) used in the Internet of Things. And using this, we implemented a smart elevator system that determines in real time whether there are people waiting. The proposed system can play the role of CCTV (closed-circuit television) while reducing unnecessary power consumption. Therefore, the proposed smart elevator system is expected to contribute to safety and security issues.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.93-104
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• 2024

Demand response is a strategy that encourages customers to adjust their consumption patterns at times of peak demand with the aim to improve the reliability of the power grid and minimize expenses. The integration of renewable energy sources into smart grids poses significant challenges due to their intermittent and unpredictable nature. Demand response strategies, coupled with reinforcement learning techniques, have emerged as promising approaches to address these challenges and optimize grid operations where traditional methods fail to meet such kind of complex requirements. This research focuses on investigating the application of reinforcement learning algorithms in demand response for renewable energy integration. The objectives include optimizing demand-side flexibility, improving renewable energy utilization, and enhancing grid stability. The results emphasize the effectiveness of demand response strategies based on reinforcement learning in enhancing grid flexibility and facilitating the integration of renewable energy.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.453-458
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• 2024

Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.

• Composites Research
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• v.37 no.2
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• pp.115-125
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• 2024

As global issues and interest in the environment increase, the transition to eco-friendly materials is accelerating in the automobile industry. In the automotive industry, eco-friendly composite materials are mainly used in various interior and exterior components, reducing the reliance on traditional petroleum-based materials. In particular, natural fiber composites help reduce fuel consumption and greenhouse gas emissions by making vehicles lighter. Additionally, they boast superior thermal properties and durability compared to non-recyclable composite materials, making them suitable for automotive interior parts. Furthermore, reduced production costs and sustainability are key advantages of natural fiber composites. The eco-friendly composites market is expected to grow to $86.43 billion at a CAGR of 15.3% from 2022 to 2030, and the natural fiber composites market is predicted to grow at a CAGR of 5.3% from 2023 to 2028 to $424 million. In this review paper, we explore research trends in nextgeneration natural fiber composite materials for automobiles and their application in the actual automobile industry.