• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.299-305
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• 2020

With the advancement of the 4th Industrial Revolution(4IR), microprocessor education is on the rise due to the explosive demand for IoT (Internet of Things) and M2M devices. However, it is difficult due to many constraints to efficiently transfer training on hardware assembly and implementation through online training. Thus, we developed a cost-effective online content based on Arduino simulations, Atmel Studio 7, and WinAvr simulator that are required for the utilization of AVR 128. These Camtasia videos overcame the limitation of theory focused on-line education by visually introducing the practical utilization of an actual AVR 128. In this paper, the proposed educational content was provided to university students, and the results of student feedback show that it has a strong effect.

• Journal of Korea Multimedia Society
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• v.23 no.4
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• pp.517-524
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• 2020

Recently, many researches have been conducted to automatically recognize license plates of vehicles and use the analyzed information to manage stolen vehicles and track the vehicle. However, such a system must eventually be investigated by people through direct monitoring. Therefore, in this paper, the system of tracking a vehicle is implemented by sharing the information analyzed by the vehicle image among cameras registered in the IoT environment to minimize the human intervention. The distance between cameras is indicated by the node and the weight value of the weighted-graph, and the eigenvector centrality is used to select the camera to search. It demonstrates efficiency by comparing the time between analyzing data using weighted graph searching algorithm and analyzing all data stored in databse. Finally, the path of the vehicle is indicated on the map using parsed json data.

• Annual Conference of KIPS
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• 2018.10a
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• pp.235-237
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• 2018

The Internet has allowed many things to move fast, including sharing of data, files and others within a second. Many domains use applications range from IoT, smart cities, healthcare, and organizations to share the data when necessary. However, there are some challenges faced by existing systems that works on centralized nature. Such challenges are data breach, trustiness issue, unauthorized access and data fraud. Therefore in this work, we focus on using a smart contract which is used by blockchain platform and works on decentralized form. Furthermore, in this work our contract provides an access to the file uploaded onto the decentralized storage such as IPFS. By leveraging smart contract-role based which consist of a contract owner who can manage the users when access the certain resources such as a file and as well as use of decentralized storage to avoid single point of failure and censorship over secure communication channel. We checked the gas cost of the smart contract since most of contracts tends to be a high cost.

• Journal of Institute of Convergence Technology
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• v.6 no.1
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• pp.27-30
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• 2016

In recent years, manufacturing industry takes a lot of significant change - such as Industry4.0, SMART factory, and IoT(Internet of things). To satisfy their requirements, many cutting-edge machineries are provided to enhance manufacturing industry's productivity. Also, IT technologies are applied to many machinery part and improve their functions. In Korea, Chung-buk plays an important role in machinery part industry. In this paper, we survey, analyze and summarize the current machinery part industry focused on Chunk-buk Area.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.120-121
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• 2019

The construction industry is known to be one of the representative industries that generate fine dust. Therefore, reducing the amount of fine dust generated in construction sites is very important for the overall fine dust management. Based on this, this study proposed the concept of fine dust measurement and removal technology combined with advanced technologies such as drones and IoT. The qualitative, quantitative and risk elimination effects that can be expected when applying the proposed technique are analyzed. We will verify the effectiveness of the proposed concept through system development and field application, and evaluate specific economic feasibility through cost analysis. The proposed concept will be validated through system development and field application and evaluated specific economics through cost analysis.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.4
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• pp.221-228
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• 2021

With the advent of the IoT (internet of things) era, there has been discussion on how to efficiently use various information from daily life. In academic and industrial society, various smart devices such as smart watches, smart phones, and smart glasses have been developed and commercialized for narrowing the physical/psychological distance with user information. According to recent developments of smart devices, the contemporary people have desired to check their body information and treat disease by themselves. According to the needs of the time, biological researches by phototherapy/monitoring have been actively conducted. Among various light sources, microLEDs have been spotlighted due to their superior optoelectric properties and stability. In this paper, we would like to review the state-of-the research results on the next-generation biological therapy devices via microLEDs.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.1
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• pp.1-7
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• 2023

In this paper, we implement a lossless compression technique for time-series data generated by IoT (Internet of Things) devices to reduce the disk spaces. The proposed compression technique reduces the size of the encoded data by selectively applying CNN (Convolutional Neural Networks) or Delta encoding depending on the situation in the Forecasting algorithm that performs prediction on time series data. In addition, the proposed technique sequentially performs zigzag encoding, splitting, and bit packing to increase the compression ratio. We showed that the proposed compression method has a compression ratio of up to 1.60 for the original data.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.216-224
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• 2023

Smart lighting systems have become increasingly popular in several public sectors because of trends toward urbanization and intelligent technologies. In this study, we designed and implemented a web application platform to explore and monitor data acquired from lighting devices at Thammasat University (Rangsit Campus, Thailand). The platform provides a convenient interface for administrative and operative staff to monitor, control, and collect data from sensors installed on campus in real time for creating geographically specific big data. Platform development focuses on both back- and front-end applications to allow a seamless process for recording and displaying data from interconnected devices. Responsible persons can interact with devices and acquire data effortlessly, minimizing workforce and human error. The collected data were analyzed using an exploratory data analysis process. Missing data behavior caused by system outages was also investigated.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.179-192
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• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.349-357
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• 2016

The era of the Internet of Things (IoT) is upon us. In this era, minimizing power consumption becomes a primary concern for system-on-chip designers. While traditional power minimization and dynamic power management (DPM) techniques have been heavily explored to improve the power efficiency of devices inside very large-scale integration (VLSI) platforms, there is one critical factor that is often overlooked, which is the power conversion efficiency of a power delivery network (PDN). This paper is a tutorial that focuses on the power conversion efficiency of the PDN, and introduces novel methods to improve it. Circuit-, architecture-, and system-level approaches are presented to optimize PDN designs, while case studies for three different VSLI platforms validate the efficacy of the introduced approaches.