• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.117-127
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• 2010

In this study, the author examined medical information management research trends in abroad and Korea from the perspectives of library and information science. LISA was used to collect research data in abroad from 2007 to 2010 (a total of 225 research articles). Korean studies were investigated using DBPIA to compare research trends. Content analysis results based on subject category show that research in abroad increased consistently and electronic resources and collection-related subjects were frequently studied. In Korea, the electronic resources and collection-related research proportion was also high, and much research was done in the areas of bibliometrics. However, medical information management researches did not increase in Korea between 2000 and 2010.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.4
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• pp.326-330
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• 2020

Small-scale production control systems for smart manufacturing are becoming increasingly necessary as the manufacturing industry seeks to maximize manufacturing efficiency as the demand for customized product production increases. Correspondingly, the development of an embedded system to realize this capability is becoming important. In this study, we developed an embedded system based on an open source system that is cheaper than a widely applied programmable logic controller (PLC)-based production control system that is easier to install, configure, and process than a conventional relay control panel. This embedded system is system is based on a low-power, high-performance Cortex M4 processor and can be applied to smart manufacturing. It is designed to improve the development environment and compatibility of existing PLCs, control small-scale production systems, and enable data collection through heterogeneous communication. The real-time response characteristics were confirmed through an operation test for input/output control and data collection, and it was confirmed that they can be used in industrial sites.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.300-306
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• 2021

Due to the development of IT technology, hardware technologies applied to IoT equipment have recently been developed, so smart systems using low-cost, high-performance RF and computing devices are being developed. However, in the infrastructure environment where a large amount of IoT devices are installed, big data collection causes a load on the collection server due to a bottleneck between the transmitted data. As a result, data transmitted to the data collection server causes packet loss and reduced data throughput. Therefore, there is a need for an efficient big data collection technique in an infrastructure environment where a large amount of IoT devices are installed. Therefore, in this paper, we propose an efficient big data collection technique in an infrastructure environment where a vast amount of IoT devices are installed. As a result of the performance evaluation, the packet loss and data throughput of the proposed technique are completed without loss of the transmitted file. In the future, the system needs to be implemented based on this design.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.528-537
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• 2014

Wireless Sensor Network(WSN) is a network which consists of sensor nodes(SNs) in data collection area. It is hard for the SNs to replace battery. Thus energy and transfer efficiency is important because the energy is limited. In this paper, we propose energy-efficient data collection algorithm for wireless sensor networks by using mobile agent in distance-based cluster structure. For avoid collisions and guarantee low latency, make distance-based topology and build cluster by the topology. For performance comparison of the proposed algorithm, compare with existing mobile agent algorithm. When network constructed by 300 nodes, proposed algorithm has performance increase than existing algorithm(GCF, LCF, TBID) in network lifetime 194, 124.6, 1.46 times each and data merging energy efficiency 87.5%, 85%, 45% each.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.189-196
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• 2024

Frequent false positives alarm from the Intelligent Selective Control System have raised significant concerns. These persistent issues have led to declines in operational efficiency and market credibility among agents. Developing a new model or replacing the existing one to mitigate false positives alarm entails substantial opportunity costs; hence, improving the quality of the training dataset is pragmatic. However, smaller organizations face challenges with inadequate capabilities in dataset collection and refinement. This paper proposes an automatic human pose data collection system centered around a human pose estimation model, utilizing camera-based sensor fusion techniques and edge devices. The system facilitates the direct collection and real-time processing of field data at the network periphery, distributing the computational load that typically centralizes. Additionally, by directly labeling field data, it aids in constructing new training datasets.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.317-322
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• 2019

This study is based on big big data base for real-time collection/analysis/processing of data, creative analysis of data assets, and intelligent processing system based on IoT, which can measure distribution phase in real time. The mobile terminal uses the SDK of the provided device to measure the data information on the consumption of specific seafood production and distribution. We use the oneM2M protocol to store various kinds of information needed for seafood production, and implement a DB Server and a system that allows the administrator to manage the system using the UI.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.275-282
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• 2019

Clusters generated by features such as mountains or buildings are considered as the contaminated data that are independent of atmospheric phenomena. The basic way to reduce the clutter signal is to install a clutter fence around the wind profiler. In order to investigate the effect of clutter fence on the wind profiler data, the wind vector collection rate and wind vector accuracy of wind profiler was investigated before and after clutter fence installation. The clutter fence of wind profiler contributed to improve the data quality as well as the data collection rate.

• Journal of information and communication convergence engineering
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• v.22 no.3
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• pp.249-255
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• 2024

Advancements in deep learning have enhanced vision-based aggregate analysis. However, further development and studies have encountered challenges, particularly in acquiring large-scale datasets. Data collection is costly and time-consuming, posing a significant challenge in acquiring large datasets required for training neural networks. To address this issue, this study introduces a simulation that efficiently generates the necessary data and labels for training neural networks. We utilized a genetic algorithm (GA) to create optimized lists of aggregates based on the specified values of weight and particle size distribution for the aggregate sample. This enabled sample data collection without conducting sieving tests. Our evaluation of the proposed simulation and GA methodology revealed errors of 1.3% and 2.7 g for aggregate size distribution and weight, respectively. Furthermore, we assessed a segmentation model trained with data from the simulation, achieving a promising preliminary F1 score of 78.18 on the actual aggregate image.

• Journal of Korean Library and Information Science Society
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• v.52 no.3
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• pp.1-20
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• 2021

This study is the most important component in establishing the court library as the best legal library in Korea responsible for professional legal services. A perception survey was conducted on the target. As a result, first, looking at the collection direction based on the needs of general users, in the case of collection types, preference in the order of books, electronic materials, and non-books should be considered. It seems to be necessary to plan a collection development policy reflecting the high preference for books. In addition, in the non-books section, the preference for non-book materials in the form of video rather than audio is much higher, and in the case of language, domestic books should be collected mainly. Second, looking at the collection direction based on the needs of experts, the satisfaction of experts is generally low, so it seems that a collection development policy should be established to improve this. As for the type of information source, preference was shown in the order of electronic materials, books, and non-books. There is a need. The future collection direction should be based on the preference shown in the order of procedural law, specialized field, basic substantive law, and legal series. Also, when collecting the same book, electronic form of legal data should be considered rather than printed. In addition, it is necessary to collect collections mainly from domestic books, and then, it is expected that the scope of collection should be expanded to prioritize English and American books, Japanese books, and German books.

• Tunnel and Underground Space
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• v.28 no.6
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• pp.547-554
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• 2018

Using crowdsourced sensor data collection technique, it is possible to collect high-density ground vibration data which is difficult to obtain by conventional methods. In this study, we have developed a crowdsourced ground vibration data collection system using MEMS sensors mounted on small electronic devices including smartphones, and implemented client and server based on the proposed infrastructure system design. The system is designed to gather vibration data quickly through Android-based smartphones or fixed devices based on Android Things, minimizing the usage of resource like power usage and data transmission traffic of the hardware.