• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2213-2231
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• 2013

Compressed sensing is a novel technology used in the field of wireless communication and sensor networks for channel estimation, signal detection, data gathering, network monitoring, and other applications. It plays a significant role in highly secure, real-time, well organized, and cost-effective data communication in smart-grid (SG) systems, which consist of multi-tier network standards that make it challenging to synchronize in power management communication. In this paper, we present a multi-layer communication model for SG systems and propose compressed-sensing based data transmission at every layer of the SG system to improve data transmission performance. Our approach is to utilize the compressed-sensing procedure at every layer in a controlled manner. Simulation results demonstrate that the proposed monitoring devices need less transmission power than conventional systems. Additionally, secure, reliable, and real-time data transmission is possible with the compressed-sensing technique.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1431-1440
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• 1998

Video data are retrieved and stored in various compressed forms according to their characteristics, In this paper, we present a generic data model that captures the structure of a video document and that provides a means for indexing a video stream, Using this model, we design and implement CVIMS (the MPEG-2 Compressed Video Information Management System) to store and retrieve video documents, CVIMS extracts I-frames from MPEG-2 files, selects key-frames from the I -frames, and stores in database the index information such as thumbnails, captions, and picture descriptors of the key-frames, And also, CVIMS retrieves MPEG- 2 video data using the thumbnails of key-frames and v31ious labels of queries.

• Journal of Navigation and Port Research
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• v.46 no.2
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• pp.92-98
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• 2022

Maritime accidents result in enormous economic loss and loss of life; thus, such accidents must be prevented, and risks must be managed to prevent these occurrences Risk management must be based on statistical evidence such as variables. Because calculating when variables increase statistically can be difficult, compressing the designated variables is necessary to use the maritime accident data in Korea. Thus, in this study, variables of marine accident data are compressed using statistical methods. The date, ship type, and marine accident type included in all maritime accident data were extracted, the number of optimal variables was confirmed using the hierarchical clustering analysis method, and the data were compressed. For the compressed variables, the validity of the data use was statistically confirmed using analysis of variance, and the data of the variables identified using the variable compression method were designated. Consequently, among the monthly and yearly data, statistical significance was confirmed in yearly data, and compression was possible. The significance of the data was confirmed in six and eight types of ships and accidents, respectively, and these were compressed. These results can be directly used for prevention or prediction based on past maritime accident data. Additionally, the data range extracted from past maritime accidents and the number of applicable data will be studied in the future.

• Korean Journal of Artificial Intelligence
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• v.6 no.1
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• pp.1-10
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• 2018

Compressed Air is an important energy source used in most factories nowadays. The automation trend using air compressor has been gradually increasing with the interest of the 4th industry in recent years. With the air compressor system, it is possible to construct the device at low cost and easily achieve automation and energy saving. In addition, With trend of FA, miniaturation and light weight manufacturing trend expand their use in the electronics, medical, and food sectors. Research method is to design the technology for the remote control of the following information as USN base. Development of flexible sensing module from real time observation module for fusion of IT technology in compressed air systems, design and manufacture of flexible sensing module, and realiability assessment. Design of real-time integrated management system for observation data of compressed air system - Ability to process observation data measured in real time into pre-processing and analysis data. This study expects unconventionally decreasing effect of energy cost that takes up 60~70% of air compressor layout and operation and maintenance management cost through USN(Ubiquitous Sensor Network) technology by using optimum operational condition from real time observation module. In addition, by preventing maintenance cost from malfunction of air compressor beforehand, maintenance cost is anticipated to cut back.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.733-740
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• 2008

Recently, mobile computing devices are used popularly. And quantity of information on mobile computing devices is being increased due to digitalization of information. So it needs an embedded DBMS for effective information management. Furthermore, since flash memory having a restriction on the number of partial write cycles is rapidly deployed on mobile computing devices as data storage and is more expensive than the conventional magnetic hard disk, the compressed data management system(CDMS) has been considered as an effective storage management technique for mobile computing devices in previous research. However, the research of CDMS is at the initial stage and has several problems. Hence, in this paper, we present additional storage management methods to solve the problems and improve the effectiveness of the CDMS for embedded DBMS.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.545-550
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• 2004

Recent natural disasters like flooding and slope collapse have shown the need for natural risk management system, as they endanger directly public health and cause severe damages on the national economy. In order to improve the efficiency of risk management systems, this management system based on AANN(Auto-Associative Neural Network)is proposed in this paper. AANN can be effectively used for identification of abnormal data and data compression. The proposed AANN-based risk management system collects and stores measurement data from sensors and transmits them to remote server for web-monitoring. Generally, it is desirable to transmit the compressed data instead of raw data in normal state. However, if dangerous situation happens, rapid tramission of measurement data should be required. These requirements are easily satisfied by using AANN. In order to verify the feasibilities of the proposed system, The AANN-based risk management system is applied to slope collapse monitoring system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.293-300
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• 2016

Traditional databases exploit a record-based model, where the attributes of a record are placed contiguously in a slow hard disk to achieve high performance. On the other hand, for read-intensive data analysis systems, the column-based compressed database has become a proper model because of its superior read performance. Currently, flash memory SSD is largely recognized as the preferred storage media for high-speed analysis systems. This paper introduces a compressed column-storage model and proposes a new index and its data management scheme for a high-capacity data warehouse system. The proposed index management scheme is based on the asymmetric index duplication and achieves superior search performance using the master index and compact index, particularly for large read-mostly databases. In addition, the data management scheme contributes to the read performance and high reliability by compressing the related columns and replicating them in two mirrored SSD. Based on the results of the performance evaluation under the high workload conditions, the data management scheme outperforms the traditional scheme in terms of the search throughput and response time.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.113-118
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• 2007

기존의 연구 과제에서 모바일 기기에 쓰이는 데이터 압축 관리 시스템인 CDMS(Compressed Data Management System)을 제안하였다. 그러나 CDMS의 DB파일에서 Free Page의 발생, 또는 데이터가 늘어났다가 줄어들었음에도 불구하고 실질적인 파일크기가 줄어들지 않는 문제점이 발견되었다. 따라서 데이터들을 Compact하게 배치하여 데이터베이스를 재구성한 후 사용되어지지 않는 공간을 반환하여 다른 모듈에서 활용할 수 있도록 하기 위하여 Compaction Mechanism을 제안하였다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.43-52
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• 2021

IoT applications are quickly spread in many fields. Blockchain methods(BC), defined as a distributed sharing mechanism, offer excellent support for IoT evolution. The BC provides a secure way for communication between IoT devices. However, the IoT environments are threatened by hacker attacks and malicious intrusions. The IoT applications security are faced with three challenges: intrusions and attacks detection, secure communication, and compressed storage information. This paper proposed a system based on double-blockchain to improve the communication transactions' safety and enhance the information compression method for the stored data. Information security is enhanced by using an Ellipse Curve Cryptography(ECC) considered in a double-blockchain case. The data compression is ensured by the Compressed Sensing(CS) method. The conducted experimentation reveals that the proposed method is more accurate in security and storage performance than previous related works.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5855-5877
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• 2017

In view of personal health and disease management based on cost effective healthcare services, there is a growing need for real-time monitoring services. The electrocardiogram (ECG) signal is one of the most important of health information and real-time monitoring of the ECG can provide an efficient way to cope with emergency situations, as well as assist in everyday health care. In this system, it is essential to continuously collect and transmit large amount of ECG data within a given time and provide maximum user convenience at the same time. When considering limited wireless capacity and unstable channel conditions, appropriate signal processing and transmission techniques such as compression are required. However, ISO/IEEE 11073 standards for interoperability between personal health devices cannot properly support compressed data transmission. Therefore, in the present study, the problems for handling compressed data are specified and new extended agent and manager are proposed to address the problems while maintaining compatibility with existing devices. Extended devices have two PM-stores enabling compression and a novel transmission scheme. A variety of compression techniques can be applied; in this paper, discrete cosine transformation (DCT) is used. And the priority of information after DCT compression enables new transmission techniques for performance improvement. The performance of the compressed signal and the original uncompressed signal transmitted over the noisy channel are compared in terms of percent root mean square difference (PRD) using our simulation results. Our transmission scheme shows a better performance and complies with 11073 standards.