• Journal of Platform Technology
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• v.9 no.1
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• pp.15-22
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• 2021

In a smart manufacturing environment, more and more devices are connected to the Internet so that a large volume of data can be obtained during all phases of the product life cycle. The large-scale industries, companies and organizations that have more operational units scattered among the various geographical locations face a huge resource consumption because of their unorganized structure of sharing resources among themselves that directly affects the supply chain of the corresponding concerns. Cloud-based smart manufacturing paradigm facilitates a new variety of applications and services to analyze a large volume of data and enable large-scale manufacturing collaboration. The manufacturing units include machinery that may be situated in different geological areas and process instances that are executed from different machinery data should be constantly managed by the super admin to coordinate the manufacturing process in the large-scale industries these environments make the manufacturing process a tedious work to maintain the efficiency of the production unit. The data from all these instances should be monitored to maintain the integrity of the manufacturing service system, all these data are computed in the cloud environment which leads to the latency in the performance of the smart manufacturing service system. Instead, validating data from the external device, we propose to validate the data at the front-end of each device. The validation process can be automated by script validation and then the processed data will be sent to the cloud processing and storing unit. Along with the end-device data validation we will implement the APM(Asset Performance Management) to enhance the productive functionality of the manufacturers. The manufacturing service system will be chunked into modules based on the functionalities of the machines and process instances corresponding to the time schedules of the respective machines. On breaking the whole system into chunks of modules and further divisions as required we can reduce the data loss or data mismatch due to the processing of data from the instances that may be down for maintenance or malfunction ties of the machinery. This will help the admin to trace the individual domains of the smart manufacturing service system that needs attention for error recovery among the various process instances from different machines that operate on the various conditions. This helps in reducing the latency, which in turn increases the efficiency of the whole system

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.2
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• pp.29-38
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• 2021

The Internet including mobile networks is developing to overcoming the limitation of physical distance and providing or acquiring information from remote locations. However, the systems that use video as primary information require higher bandwidth for recognizing the situation in remote places more accurately through high-quality video as well as lower latency for faster interaction between devices and users. The emergence of the 5th generation mobile network provides features such as high bandwidth and precise location recognition that were not experienced in previous-generation technologies. In addition, the Mobile Edge Computing that minimizes network latency in the mobile network requires a change in the traditional system architecture that was composed of the existing smart device and high availability server system. However, even with 5G and MEC, since there is a limit to overcome the mobile network state fluctuations only by enhancing the network infrastructure, this study proposes a high-definition video streaming system in ultra-low latency based on the SRT protocol that provides Forward Error Correction and Fast Retransmission. The proposed system shows how to deploy software components that are developed in consideration of the nature of 5G and MEC to achieve sub-1 second latency for 4K real-time video streaming. In the last of this paper, we analyze the most significant factor in the entire video transmission process to achieve the lowest possible latency.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.119-125
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• 2023

IT infrastructure operation has advanced, and the methods for managing systems have become widely adopted. Recently, research has focused on improving system management using Syslog. However, utilizing log data collected through these methods presents challenges, as logs are extracted in various formats that require expert analysis. This paper proposes a system that utilizes edge computing to distribute the collection of Syslog data and preprocesses duplicate data before storing it in a central database. Additionally, the system constructs a data dictionary to classify and count data in real-time, with restrictions on transmitting registered data to the central database. This approach ensures the maintenance of predefined patterns in the data dictionary, controls duplicate data and temporal duplicates, and enables the storage of refined data in the central database, thereby securing fundamental data for big data analysis. The proposed algorithms and procedures are demonstrated through simulations and examples. Real syslog data, including extracted examples, is used to accurately extract necessary information from log data and verify the successful execution of the classification and storage processes. This system can serve as an efficient solution for collecting and managing log data in edge environments, offering potential benefits in terms of technology diffusion.

• Journal of IKEEE
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• v.28 no.3
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• pp.458-464
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• 2024

This study proposes a fault-tolerant caching system to address the issue of caching content imbalance caused by the dynamic departure and participation of cache servers in a heterogeneous cache server network, and validates it in both real and virtual environments. With the increase of large-scale media content requiring various types and resolutions, the necessity of cache servers as key components to reduce response time to user requests and alleviate network load has been growing. In particular, research on heterogeneous cache server networks utilizing edge computing and low-power devices has been actively conducted recently. However, in such environments, the irregular departure and participation of cache servers can occur frequently, leading to content imbalance among the cache servers deployed in the network, which can degrade the performance of the cache server network. The fault-tolerant caching algorithm proposed in this study ensures stable service quality by maintaining balance among media contents even when cache servers depart. Experimental results confirmed that the proposed algorithm effectively maintains content distribution despite the departure of cache servers. Additionally, we built a network composed of seven heterogeneous cache servers to verify the practicality of the proposed caching system and demonstrated its performance and scalability through a large-scale cache server network in a virtual environment.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.4
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• pp.492-500
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• 2014

Objectives: The purpose of this study is to estimate the applicability of regional sample collection of environmental samples. The concentration of asbestos fibers were analyzed with two devices. One was an existing commercial air sampling pump that has been proved to be accurate and exact, and the other is a remodeled pump for sample collection which was made from an electric bubble generator originally designed for aquarium fish. Samples were collected with the two devices under the same environmental conditions and collection equipment. A comparative analysis of the concentration of ambient asbestos fiber was then performed. Methods: Based on previous research, six farmhouses with asbestos fiber slate roofs known to have high concentrations of asbestos fiber were selected. Using the existing commercial air sampling pump and the remodeled electric bubble generator, four to seven samples were collected each day one meter downwind from the edge of the slate roof at high volume (about 4 L/min) and low volume (about 1.4 L/min). The analyzer responsible for sample quality control of asbestos fibers counted the number of asbestos fibers with a phase microscope. Results: The rates of flow change of the existed sampler and the remodeled pump at high volume were 0.82% and 0.17%, respectively. The rates of flow change at low volume were 3.83% and 1.09%, but there was not significant difference. The rates of flow change are within the error range (${\pm}5%$) of OSHA analyzing methods. For the high volume sampler, the average asbestos fiber concentration in the air collected by the existed sampler is 6.270 fibers/L and for the remodeled one 5.527 fibers/L, not a significant difference. For the low volume sampler, the average asbestos fiber concentration in the air collected by the existed sampler is 7.755 fibers/L and for the remodeled one 7.706 fibers/L, not a significant difference. The total area of the slate roof of the targeted farmhouse has an effect on the concentration of asbestos fibers in the air from the existing pump and the remodeled one (p<0.01). Conclusions: The sampling function between the existing commercial pump and the remodeled one shows little difference. Therefore, the remodeled pump is considered a pump with a good availability for collecting ambient air asbestos samples.

• Journal of KIISE:Software and Applications
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• v.35 no.11
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• pp.671-680
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• 2008

Motion capture devices have been utilized in producing several contents, such as movies and video games. However, since motion capture devices are expensive and inconvenient to use, motions segmented from captured data was recycled and synthesized to utilize it in another contents, but the motions were generally segmented by contents producers in manual. Therefore, automatic motion segmentation is recently getting a lot of attentions. Previous approaches are divided into on-line and off-line, where ow line approaches segment motions based on similarities between neighboring frames and off-line approaches segment motions by capturing the global characteristics in feature space. In this paper, we propose a graph-based high-level motion segmentation method. Since high-level motions consist of repeated frames within temporal distances, we consider similarities between neighboring frames as well as all similarities among all frames within the temporal distance. This is achieved by constructing a graph, where each vertex represents a frame and the edges between the frames are weighted by their similarity. Then, normalized cuts algorithm is used to partition the constructed graph into several sub-graphs by globally finding minimum cuts. In the experiments, the results using the proposed method showed better performance than PCA-based method in on-line and GMM-based method in off-line, as the proposed method globally segment motions from the graph constructed based similarities between neighboring frames as well as similarities among all frames within temporal distances.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.32 no.3
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• pp.201-206
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• 2019

This report constitutes the first demonstration in Korea of single-crystal lateral gallium oxide ($Ga_2O_3$) as a metal-oxide-semiconductor field-effect-transistor (MOSFET), with a breakdown voltage in excess of 480 V. A Si-doped channel layer was grown on a Fe-doped semi-insulating ${\beta}-Ga_2O_3$ (010) substrate by molecular beam epitaxy. The single-crystal substrate was grown by the edge-defined film-fed growth method and wafered to a size of $10{\times}15mm^2$. Although we fabricated several types of power devices using the same process, we only report the characterization of a finger-type MOSFET with a gate length ($L_g$) of $2{\mu}m$ and a gate-drain spacing ($L_{gd}$) of $5{\mu}m$. The MOSFET showed a favorable drain current modulation according to the gate voltage swing. A complete drain current pinch-off feature was also obtained for $V_{gs}<-6V$, and the three-terminal off-state breakdown voltage was over 482 V in a $L_{gd}=5{\mu}m$ device measured in Fluorinert ambient at $V_{gs}=-10V$. A low drain leakage current of 4.7 nA at the off-state led to a high on/off drain current ratio of approximately $5.3{\times}10^5$. These device characteristics indicate the promising potential of $Ga_2O_3$-based electrical devices for next-generation high-power device applications, such as electrical autonomous vehicles, railroads, photovoltaics, renewable energy, and industry.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.33-45
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• 2020

This paper aims to look at the perspective that the latest cutting-edge technologies are predicting individual diseases in the actual medical environment in a situation where various types of wearable devices are rapidly increasing and used in the healthcare domain. Through the process of collecting, processing, and transmitting data by merging clinical data, genetic data, and life log data through a user-participating wearable device, it presents the process of connecting the learning model and the feedback model in the environment of the Deep Neural Network. In the case of the actual field that has undergone clinical trial procedures of medical IT occurring in such a high-tech medical field, the effect of a specific gene caused by metabolic syndrome on the disease is measured, and clinical information and life log data are merged to process different heterogeneous data. That is, it proves the objective suitability and certainty of the deep neural network of heterogeneous data, and through this, the performance evaluation according to the noise in the actual deep learning environment is performed. In the case of the automatic encoder, we proved that the accuracy and predicted value varying per 1,000 EPOCH are linearly changed several times with the increasing value of the variable.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.126-136
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• 2014

In the Advanced Driver Assistance Systems (ADAS) of smart vehicle and Intelligent Transportation System (ITS) for to detect the boundary of lane is being studied a lot of Hough Transform. This method detects correctly recognition the lane. But recognition rate can fall due to detecting straight lines outside of the lane. In order to solve this problems, this paper proposed an algorithm to recognize the lane boundaries and the accumulator cells in Hough space. Based on proposed algorithm, we develop application for Android was developed by H/W verification. Users of smart phone devices could use lane detection and lane departure warning systems for driver's safety whenever and wherever. Software verification using the OpenCV showed efficiency recognition correct rate of 93.8% and hardware real-time verification for an application development in the Android phone showed recognition correct rate of 70%.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.433-438
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• 2017

Containing an Angle-of-Arrival(: AOA) estimation and interference suppression techniques, an adaptive beamformer is one of core techniques for the Signal Intelligence(: SIGINT) which collect various intelligence utilizing cutting edge devices including the radar and satellite. It generates a beam with the directivity in a corresponding direction, to efficiently receive a signal from the specific direction, using antenna array. In this paper, we present the received signal model including interference signals and noise, which can be applied to an input of the signal intelligence satellite system equipped with the AOA estimation and the interference cancellation techniques, and analysis the characteristics of various signals, which can be included in the proposed received signal model. This proposed signal model can be directly applied to the performance evaluation for a variety of beamforming techniques. Also, we verify the spectrum characteristic of the presented received signal model in the frequency domain through computer simulation examples.