• Title/Summary/Keyword: Key-Value Database

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Boosting WiscKey Key-Value Store Using NVDIMM-N (NVDIMM-N을 활용한 WiscKey 키-밸류 스토어 성능 향상)

  • Il Han Song;Bo hyun Lee;Sang Won Lee
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.3
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    • pp.111-116
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    • 2023
  • The WiscKey database, which optimizes overhead by compaction of the LSM tree-based Key-Value database, stores the value in a separate file, and stores only the key and value addresses in the database. Each time an fsync system call function is used to ensure data integrity in the process of storing values. In previously conducted studies, workload performance was reduced by up to 5.8 times as a result of performing the workload without calling the fsync system call function. However, it is difficult to ensure the data integrity of the database without using the fsync system call function. In this paper, to reduce the overhead of the fsync system call function while performing workloads on the WiscKey database, we use NVDIMM caching techniques to ensure data integrity while improving the performance of the WiscKey database.

Content-Based Video Search Using Eigen Component Analysis and Intensity Component Flow (고유성분 분석과 휘도성분 흐름 특성을 이용한 내용기반 비디오 검색)

  • 전대홍;강대성
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.3
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    • pp.47-53
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    • 2002
  • In this paper, we proposed a content-based video search method using the eigen value of key frame and intensity component. We divided the video stream into shot units to extract key frame representing each shot, and get the intensity distribution of the shot from the database generated by using ECA(Eigen Component Analysis). The generated codebook, their index value for each key frame, and the intensity values were used for database. The query image is utilized to find video stream that has the most similar frame by using the euclidean distance measure among the codewords in the codebook. The experimental results showed that the proposed algorithm is superior to any other methols in the search outcome since it makes use of eigen value and intensity elements, and reduces the processing time etc.

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Digital Forensics Investigation of Redis Database (Redis 데이터베이스에 대한 디지털 포렌식 조사 기법 연구)

  • Choi, Jae Mun;Jeong, Doo Won;Yoon, Jong Seong;Lee, Sang Jin
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.5
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    • pp.117-126
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    • 2016
  • Recently, increasing utilization of Big Data or Social Network Service involves the increases in demand for NoSQL Database that overcomes the limitations of existing relational database. A forensic examination of Relational Database has steadily researched in terms of Digital Forensics. In contrast, the forensic examination of NoSQL Database is rarely studied. In this paper, We introduce Redis (which is) based on Key-Value Store NoSQL Database, and research the collection and analysis of forensic artifacts then propose recovery method of deleted data. Also we developed a recovery tool, it will be verified our recovery algorithm.

Parameter Identification of 3R-C Equivalent Circuit Model Based on Full Life Cycle Database

  • Che, Yanbo;Jia, Jingjing;Yang, Yuexin;Wang, Shaohui;He, Wei
    • Journal of Electrical Engineering and Technology
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    • v.13 no.4
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    • pp.1759-1768
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    • 2018
  • The energy density, power density and ohm resistance of battery change significantly as results of battery aging, which lead to decrease in the accuracy of the equivalent model. A parameter identification method of the equivale6nt circuit model with 3 R-C branches based on the test database of battery life cycle is proposed in this paper. This database is built on the basis of experiments such as updating of available capacity, charging and discharging tests at different rates and relaxation characteristics tests. It can realize regular update and calibration of key parameters like SOH, so as to ensure the reliability of parameters identified. Taking SOH, SOC and T as independent variables, lookup table method is adopted to set initial value for the parameter matrix. Meanwhile, in order to ensure the validity of the model, the least square method based on variable forgetting factor is adopted for optimizing to complete the identification of equivalent model parameters. By comparing the simulation data with measured data for charging and discharging experiments of Li-ion battery, the effectiveness of the full life cycle database and the model are verified.

Evaluation of Edge-Based Data Collection System for Key-Value Store Utilizing Time-Series Data Optimization Techniques (시계열 데이터 최적화 기법을 활용한 Key-value store의 엣지 기반 데이터 수집 시스템 평가)

  • Woojin Cho;Hyung-ah Lee;Jae-hoi Gu
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.911-917
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    • 2023
  • In today's world, we find ourselves facing energy crises due to factors such as war and climate crises. To prepare for these energy crises, many researchers continue to study systems related to energy monitoring and conservation, such as energy management systems, energy monitoring, and energy conservation. In line with these efforts, nations are making it mandatory for energy-consuming facilities to implement these systems. However, these facilities, limited by space and energy constraints, are exploring ways to improve. This research explores the operation of a data collection system using low-performance embedded devices. In this context, it proves that an optimized version of RocksDB, a Key-Value store, outperforms traditional databases when it comes to time-series data. Furthermore, a comprehensive database evaluation tool was employed to assess various databases, including optimized RocksDB and regular RocksDB. In addition, heterogeneous databases and evaluations are conducted using a UD Benchmark tool to evaluate them. As a result, we were able to see that on devices with low performance, the time required was up to 11 times shorter than that of other databases.

Implementation of Management performance Analysis System with KDD (KDD에 기반한 경영성과 분석 시스템 구현)

  • An, Dong-Gyu;Jo, Seong-Hun
    • 한국디지털정책학회:학술대회논문집
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    • 2004.05a
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    • pp.575-592
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    • 2004
  • In modern dynamic management environment, there is growing recognition that? information & knowledge management systems are essential for CEO's efficient/effective decision making. As a key component to cope with this current, we suggest the management performance analysis syystem based on Knowledge Discovery in Database (KDD). The system measures management performance that is considered with both VA(Value- Added), which represents stakeholder's point of view and EVA(Economic Value-Added), which represents shareholder's point of view. The relation ship between management performance and some 80 financial ratios is analyzed, and then important financial ratios are drawn out. In analyzing the relationship, we applied KDD process which includes such as multidimensional cube, OLAP(On-Line Analytic Process), data mining and AHP(Analytic Hierarchy Process). To demonstrate the performance of the system, we conducted a case study using financial data over the 16-years from 1981 to 1996 of Korean automobile industry which is taken from database of KISF AS(Korea Investors Services Financial Analysis System).

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Implementation of Management performance Analysis System with Genetic Algorithms (Genetic Algorithm에 기반한 경영성과분석 시스템 구현)

  • An, Dong-Gyu;Jo, Seong-Hun
    • 한국디지털정책학회:학술대회논문집
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    • 2003.12a
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    • pp.191-210
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    • 2003
  • In modern dynamic management environment, there is growing recognition that information & knowledge management systems are essential for CEO's Efficient/effective decision making, As a key component to cope with this current, we suggest the management performance analysis system based on Knowledge Discovery in Database (KDD). The system measures management performance that is considered with both VA(Value-Added), which represents stakeholder's point of view and EVA(Economic Value-Added), which represents shareholder's point of view, The relationship between management performance and some 80 financial ratios is analyzed, and then important financial ratios are drawn out. In analyzing the relationship, we applied KDD process which includes such as multidimensional cube, OLAP(On -Line Analytic Process), data mining and AHP(Analytic Hierarchy Process). To demonstrate the performance of the system, we conducted a case study using financial data over the 16-years from 1981 to 1996 of Korean automobile industry which is taken from database of KISFAS(Korea Investors Services Financial Analysis System).

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A study of the value of Korean medical text "Uibang Yuchi(醫方類聚)" as a representative Database for developing new diseases treatment skills (『의방유취』를 이용한 한의학 치료기술 개발의 가능성에 대한 모델링 연구)

  • CHA Wung-seok;JANG Young-jae;NA Ji-won;AHN Sangwoo
    • The Journal of Korean Medical History
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    • v.36 no.1
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    • pp.143-154
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    • 2023
  • This paper is a study that considers how current scientific medicine could be supported by traditional medicine, and if the scope of this support is expected to gradually widen. This study begins by understanding the process by which Traditional Chinese Medicine (TCM) has developed interventions for COVID-19. We then examine what support is offered by the ancient Korean medical text "Uibang Yuchi". This paper insists that a key database is absolutely necessary to develop treatment techniques for new diseases. The key database should be considered not only from the point of view of knowledge but also from the point of view of intellectual property rights, and for this reason, the text of "Uibang Yuchi" is important. This paper shows the process of how a new treatment technique can be derived from the ancient book "Uibang Yuchi". We expect that the suggested model would play a role as a reference model in the process of pursuing similar strategies in the future.

Stock Excess Return, R&D intensity and Market Concentration: A Study of IT Firms in India

  • Sahu, Santosh K.;Narayanan, K.
    • Asian Journal of Innovation and Policy
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    • v.4 no.2
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    • pp.200-216
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    • 2015
  • This paper empirically investigates the role of R&D intensity on market concentration of firms using four key market valuation variables, namely (1) market share, (2) labor intensity, (3) firm age and, (4) firm's market value. The empirical tests use database at firm level for the Indian IT sector from 1999 to 2013 from the CMIE Prowess database. The results of the regression analyses partially support our hypothesis that R&D intensity positively influences firm's market value measure by the H-index. The test results are consistent with the hypotheses that R&D spending is more valuable for firms with larger market shares, higher labor intensity, and firms that are diversified.

Business Performance Analysis System based on Knowledge Discovery in Databases (Knowledge Discovery in Databases에 기반한 경영성과분석 시스템)

  • 조성훈;정민용
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.57
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    • pp.11-20
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    • 2000
  • In dynamic management environment, CEO must make an efficient decision with information & knowledge management systems based on IT(Information Technology). As a key component to cope with this current, we suggest the business performance analysis system based on KDD(Knowledge Discovery in Databases). We consider the theoretical model that is composited both Value-Added in respect of stakeholder and Economic Value-Added in respect of shareholder. Additionally we use DBMS and data mining method using Genetic Algorithms as physical model. To demonstrate the performance of the business performance analysis system, we analyse a domestic motors industry. The empirical case is based on the financial data of KISFAS(Korea Investors Services Financial Analysis System) database. The samples included in the study consist of H motors/S motors industry over the 16-year from 1981 to 1996.

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