• Journal of Industrial Technology
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• v.27 no.B
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• pp.97-101
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• 2007

We have developed a Edge Position Controller (EPC) using a ultrasonic sensor and applied to a fabric machine as a web guide system. Hardware devices composed of a ultrasonic transmitter-receiver sensor module and microprocessor-based sensor signal processing system are developed to realize the proposed system. We evaluated the control characteristics of the EPC and the performance of the system was good enough to apply the actual system.

• Current Optics and Photonics
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• v.2 no.1
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• pp.69-78
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• 2018

This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.12
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• pp.48-52
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• 1998

We fabricated the newly proposed nano structure memory with SOI edge channel and a nano dot. The width of the edge channel of this device, which uses the side wall as a channel and has a nano dot on this channel region, was determined by the thickness of the recessed top-silicon layer of SOI wafer. The size of side-wall nano dot was determined by the RIE etch and E-Beam lithography. The I$_{d}$-V$_{d}$, I$_{d}$-V$_{g}$ characteristics of the devices without nano dots and memory characteristics of the devices with nano dots were obtained, where the voltage scan was done between -20 V and 14 V and the threshold voltage shift was about 1 V.t 1 V.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2658-2681
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• 2023

In edge computing scenarios, IoT end devices play a crucial role in relaying and forwarding data to significantly improve IoT network performance. However, traditional routing mechanisms are not applicable to this scenario due to differences in network size and environment. Therefore, it becomes crucial to establish an effective and reliable data transmission path to ensure secure communication between devices. In this paper, we propose a trusted path selection strategy that comprehensively considers multiple attributes, such as link stability and edge cooperation, and selects a stable and secure data transmission path based on the link life cycle, energy level, trust level, and authentication status. In addition, we propose the Stability-based On-demand Multipath Distance Vector (STAOMDV) protocol based on the Ad hoc AOMDV protocol. The STAOMDV protocol implements the collection and updating of link stability attributes during the route discovery and maintenance process. By integrating the STAOMDV protocol with the proposed path selection strategy, a dependable and efficient routing mechanism is established for IoT networks in edge computing scenarios. Simulation results validate that the proposed STAOMDV model achieves a balance in network energy consumption and extends the overall network lifespan.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.251-258
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• 2012

The conventional network security solutions for manufacturing or factory automation devices are concentrated on protecting the internal networks from the attacks of external networks. Recently, however, so called Day-zero attacks are increased; the threat from internal devices such as notebooks, USB devices are as critical as attacks from external networks. Thus a new security solution is needed to protect manufacturing devices from both external and internal threat. To this purpose, we propose an edge-security system to provide cost effective, integrated, and simple end-point security solution specialized for automated manufacturing devices, which may avoid the shortcomings of NAC.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.1
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• pp.34-42
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• 2019

Receiving great attention of IoT and 4th industrial revolution, the necessity comes to the fore of the plant system which aims making it smart and effective. Smart Factory is the key realm of IoT to apply with the concept to optimize the entire process and it presents a new and flexible production paradigm based on the collected data from numerous sensors installed in a plant. Especially, the wireless sensor network technology is receiving attention as the key technology of Smart Factory, researches to interface those technology is actively in progress. In addition, IoT devices for plant industry security and high reliable network protocols are under development to cope with high-risk plant facilities. In the meanwhile, Blockchain can support high security and reliability because of the hash and hash algorithm in its core structure and transaction as well as the shared ledger among all nodes and immutability of data. With the reason, this research presents Blockchain as a method to preserve security and reliability of the wireless communication technology. In regard to that, it establishes some of key concepts of the possibility on the blockchain based IoT Edge devices for Plant O&M (Operations and Maintenance), and fulfills performance verification with test devices to present key indicator data such as transaction elapsed time and CPU consumption rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.1-8
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• 2024

On-device AI technology, which can operate AI models at the edge devices to support real-time processing and privacy enhancement, is attracting attention. As intelligent IoT is applied to various industries, services utilizing the on-device AI technology are increasing significantly. However, general deep learning models require a lot of computational resources for inference and learning. Therefore, various lightweighting methods such as quantization and pruning have been suggested to operate deep learning models in embedded edge devices. Among the lightweighting methods, we analyze how to lightweight and apply deep learning models to edge computing devices, focusing on pruning technology in this paper. In particular, we utilize dynamic and static pruning techniques to evaluate the inference speed, accuracy, and memory usage of a lightweight AI vision model. The content analyzed in this paper can be used for intelligent video control systems or video security systems in autonomous vehicles, where real-time processing are highly required. In addition, it is expected that the content can be used more effectively in various IoT services and industries.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.803-809
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• 2023

This paper analyzes and evaluates to optimally build a data collection system essential for factory energy management systems on an edge-based lightweight platform. A "Sensor/OPC-UA simulator" was developed based on sensors in an actual food factory and used to evaluate the storage engine of edge devices. The performance of storage engines in edge devices was evaluated to suggest the optimal storage engine. The experimental results show that when using the RocksDB storage engine, it has less than half the memory and database size compared to using InnoDB, and has a 3.01 times faster processing time. This study enables the selection of advantageous storage engines for managing time-series data on devices with limited resources and contributes to further research in this field through the sensor/OPC simulator.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.21-29
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• 2020

This paper presents an effective single image haze removal using edge-preserving and adaptive transmission estimation to enhance the visibility of outdoor images vulnerable to weather and environmental conditions with computational complexity reduction. The conventional methods involve the time-consuming refinement process. The proposed transmission estimation however does not require the refinement, since it preserves the edges effectively, which selects one between the pixel-based dark channel and the patch-based dark channel in the vicinity of edges. Moreover, we propose an adaptive transmission estimation to improve the visual quality particularly in bright areas like sky. Experimental results with various hazy images represent that the proposed method is superior to the conventional methods in both subjective visual quality and computational complexity. The proposed method can be adopted to compose a haze removal module for realtime devices such as mobile devices, digital cameras, autonomous vehicles, and so on as well as PCs that have enough processing resources.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.109-112
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• 2020

Many devices are connected on the internet to give functionalities for interconnected services. In 2020', The number of devices connected to the internet will be reached 5.8 billion. Moreover, many connected service provider such as Google and Amazon, suggests edge computing and mesh networks to cope with this situation which the many devices completely connected on their networks. This paper introduces the current state of the introduction of the wireless mesh network and edge cloud in order to efficiently manage a large number of nodes in the exploding Internet of Things (IoT) network and introduces the existing Network Time Protocol (NTP). On the basis of this, we propose a relatively accurate time synchronization method, especially in heterogeneous mesh networks. Using this NTP, multiple time coordinators can be placed in a mesh network to find the delay error using the average delay time and the delay time of the time coordinator. Therefore, accurate time can be synchronized when implementing IoT, remote metering, and real-time media streaming using IoT mesh network.