• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.34-41
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• 2009

This paper investigates the issue of efficient reading for sensor data of semi-passive sensor tag. The Cold Chain management system requires complete sensor data without data loss and the short processing time of reading sensor tag data. However, reading the sensed data could be interfered by RF environment such as a jamming, obstacle and so on. This study found that it could lead to loss of the sensed data and takes much time to read it when data loss is occurred. To solve this problem, we propose the transaction processing mechanism that guarantees efficient reading of the sensed data. To do this, we present the technique of dynamic packet size and technique of data recovery to execute read transaction. These techniques improve the reliability of reading operation as well as speed up of read process for the large capacity data. This paper contributes to the improvement of efficient reading of sensed data without any loss of data and large time required.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2218-2221
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• 1998

Data compression of 3 dimensional objects has limitations such as large data size, slow processing time, uncertainties of noise and measurement errors. Recently, along with activities of information transmission in internet, the researches in 3 dimensional information processing become a very important issue as the exchanges of large data are available. In this paper, we propose a data compression algorithm which first estimates the surfaces of 3 dimensional objects and then apply them to the FCV(Fuzzy c-Varieties) Clustering to obtain 3 dimensional edges and vertices, and represent the results.

• Journal of Internet of Things and Convergence
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• v.1 no.1
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• pp.11-19
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• 2015

The mobile and ubiquitous environment is experiencing a rapid development of information and communications technology as it provides an ever increasing flow of information. Particularly, GIS is now widely applied in daily life due to its high accuracy and functionality. GIS information is utilized through the tiling method, which divides and manages large-scale map information. The tiling method manages map information and additional information to allow overlay, so as to facilitate quick access to tiled data. Unlike past studies, this paper proposes a new architecture and algorithms for tile searching and indexing management to optimize map information and additional information for GIS mobile applications. Since this involves the processing of large-scale information and continuous information changes, information is clustered for rapid processing. In addition, data size is minimized to overcome the constrained performance associated with mobile devices. Our system has been implemented in actual services, leading to a twofold increase in performance in terms of processing speed and mobile bandwidth.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.119-124
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• 1998

Block Matching Motion Estimation(BMME) Algorithm is demands a very large amount of computing power and have been proposed many fast algorithms. These algorithms are many problem that larger size of VLSI scale due to non-localized search block data and problem of non-reuse of input data for each processing step. In this paper, we designed systolic arry of high processing capacity, constraints input output pin size and reuse of input data for small VLSI size. The proposed systolic array is optimized memory access time because of iterative reuse of input data on search block and become independent of problem size due to increase of algorithm's parallelism and total processing elements connection is localized spatial and temporal. The designed systolic array is reduced O(N6) time complexity to O(N3) on moving vector and has O(N) input/output pin size.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1375-1385
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• 1996

As there has been much demands for processing multimedia data, a storage manager for multimedia data makes much effects on system performance. Because the size of multimedia data is usually very large, disk I/O for the data consumes much time and causes the system performance to be decreased. Therefore, it makes a better effect on system performance that a multimedia data storage manager decreases its disk I/O by the buffer management of multimedia data. This paper proposes a buffer management technique which allocates the buffer to be equal to its corresponding segment which consists of physically continuous disk page set and is disk management unit for multimedia data in many multimedia data storage manager. As the size of buffer varies, it also proposes a buffer replacement policy which consider not only reference behavior of buffer but also buffer size The proposed multimedia data buffer management technique is implemented in KORED/STORM which is a storage manager for multimedia data.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.3 s.96
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• pp.329-333
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• 2005

This paper is concerned with the measurement of low-frequency vibrations of structures using the image processing method. To measure the vibrations visually, the measurement system consists of a camera, an image grabber board, and a computer. The specific target installed on the structure is used to calculate the vibration of structure. The captured image is then converted into a pixel-based data and then analyzed numerically. The limitation of the system depends on the image capturing speed and the size of image. In this paper, we propose the methodology for the vibration measurement using the image processing method. The method enables us to measure the displacement directly without any contact. The current resolution of the vibration measurement is limited to sub centimeter scale. However, the frequency bandwidth and resolution can be enhanced by a high-speed and high-resolution image processing system.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.143-146
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• 2015

Software Defined Network (SDN) separates control plane and data plane to achieve benefits such as centralized management, centralized provisioning, lower device cost and more flexibility. In SDN, scalability is an important issue. Centralized controller can be a bottle neck and many research tried to solve this issue on the control plan. However, scalability issue does not only happen in the control plane, but also happen in the data plane. In the data plane, flow table is an important component and its size is limited. In a large network operated by SDN technology, the performance of the network can be highly degraded because of the size limitation of a flow table. In this paper, we propose a ranking-based flow replacement method, Flow Table Management (FTM), to overcome this problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3182-3202
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• 2015

Flexibly expanding the storage capacity required to process a large amount of rapidly increasing unstructured log data is difficult in a conventional computing environment. In addition, implementing a log processing system providing features that categorize and analyze unstructured log data is extremely difficult. To overcome such limitations, we propose and design a MongoDB-based unstructured log processing system (MdbULPS) for collecting, categorizing, and analyzing log data generated from banks. The proposed system includes a Hadoop-based analysis module for reliable parallel-distributed processing of massive log data. Furthermore, because the Hadoop distributed file system (HDFS) stores data by generating replicas of collected log data in block units, the proposed system offers automatic system recovery against system failures and data loss. Finally, by establishing a distributed database using the NoSQL-based MongoDB, the proposed system provides methods of effectively processing unstructured log data. To evaluate the proposed system, we conducted three different performance tests on a local test bed including twelve nodes: comparing our system with a MySQL-based approach, comparing it with an Hbase-based approach, and changing the chunk size option. From the experiments, we found that our system showed better performance in processing unstructured log data.

• Electronics and Telecommunications Trends
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• v.39 no.1
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• pp.95-105
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• 2024

In natural language processing, large language models such as GPT-4 have recently been in the spotlight. The performance of natural language processing has advanced dramatically driven by an increase in the number of model parameters related to the number of acceptable input tokens and model size. Research on multimodal models that can simultaneously process natural language and image data is being actively conducted. Moreover, natural-language and image-based reasoning capabilities of large language models is being explored in robot artificial intelligence technology. We discuss research and related patent trends in robot task planning and code generation for robot control using large language models.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.211-216
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• 2009

As demands for high-definition television (HDTV) increase, the implementation of real-time decoding of high-definition (HD) video becomes an important issue. The data size for HD video is so large that real-time processing of the data is difficult to implement, especially with software. In order to implement a fast moving picture expert group-2 decoder for HDTV, we compose five scenarios that use parallel processing techniques such as data decomposition, task decomposition, and pipelining. Assuming the multi digital signal processor environments, we analyze each scenario in three aspects: decoding speed, L1 memory size, and bandwidth. By comparing the scenarios, we decide the most suitable cases for different situations. We simulate the scenarios in the dual-core and dual-central processing unit environment by using OpenMP and analyze the simulation results.