• Title, Summary, Keyword: Timeline Analysis

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Analysis on Processing Timeline of COMS LHGS Design

  • Bae, Hee-Jin;Koo, In-Hoi;Seo, Seok-Bae;Ahn, Sang-Il;Kim, Eun-Kyou
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.216-219
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    • 2006
  • This paper analyzes on LHGS (LRIT/HRIT Generation Subsystem) processing timeline for COMS LHGS design. The LHGS shall transmit LRIT/HRIT (Low Rate Information Transmission/ High Rate Information Transmission) data to the users within 15 minutes after the end of the image acquisition. So, this paper performs experiment using MTSAT-1R LRIT/HRIT (11 days) and calculates minimum LHGS processing time. Only HRIT FD (Full Disk) image is considered in this paper because data size of HRIT FD image is the largest. As a result of experiment, COMS LHGS should be able to receive MI Level 1B product within 157 seconds at least.

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A Digital Forensic Analysis of Timestamp Change Tools for Windows NTFS

  • Cho, Gyu-Sang
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.9
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    • pp.51-58
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    • 2019
  • Temporal analysis is very useful and important for digital forensics for reconstructing the timeline of digital events. Forgery of a file's timestamp can lead to inconsistencies in the overall temporal relationship, making it difficult to analyze the timeline in reconstructing actions or events and the results of the analysis might not be reliable. The purpose of the timestamp change is to hide the data in a steganographic way, and the other purpose is for anti-forensics. In both cases, the time stamp change tools are requested to use. In this paper, we propose a classification method based on the behavior of the timestamp change tools. The timestamp change tools are categorized three types according to patterns of the changed timestamps after using the tools. By analyzing the changed timestamps, it can be decided what kind of tool is used. And we show that the three types of the patterns are closely related to API functions which are used to develop the tools.

Study on advanced analysis method based on timeline chart for Digital Forensic Investigation (타임라인 분석 기법을 이용한 디지털 증거 분석 방법론)

  • Lee, Keun-Gi;Hwang, Seong-Jin;Lee, Chang-Hoon;Lee, Sang-Jin
    • Journal of Advanced Navigation Technology
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    • v.18 no.1
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    • pp.50-55
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    • 2014
  • Recently, importance of digital forensics has increased and using analysis methods of digital evidence in the analysis of evidence of various types. However, analysis time and effort is steadily increasing because personal disk capacity is too big and it has many number of files. Most digital evidence has time property, such as access time, creation time, and modification time. These time information of digital evidence is one of most important factors in the digital forensic area. But if digital examiner simply analyze based on binary source only, it is possible to have wrong result because time has various types. In this paper, we classify various type of time in the digital evidence and describe advanced analysis method based on timeline chart for digital forensic investigation.

Extracting Core Events Based on Timeline and Retweet Analysis in Twitter Corpus (트위터 문서에서 시간 및 리트윗 분석을 통한 핵심 사건 추출)

  • Tsolmon, Bayar;Lee, Kyung-Soon
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.1
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    • pp.69-74
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    • 2012
  • Many internet users attempt to focus on the issues which have posted on social network services in a very short time. When some social big issue or event occurred, it will affect the number of comments and retweet on that day in twitter. In this paper, we propose the method of extracting core events based on timeline analysis, sentiment feature and retweet information in twitter data. To validate our method, we have compared the methods using only the frequency of words, word frequency with sentiment analysis, using only chi-square method and using sentiment analysis with chi-square method. For justification of the proposed approach, we have evaluated accuracy of correct answers in top 10 results. The proposed method achieved 94.9% performance. The experimental results show that the proposed method is effective for extracting core events in twitter corpus.

Development of a CAE Middleware and a Visualization System for Supporting Interoperability of Continuous CAE Analysis Data (연속해석 데이터의 상호운용성을 지원하는 CAE 미들웨어와 가시화 시스템의 개발)

  • Song, In-Ho;Yang, Jeong-Sam;Jo, Hyun-Jei;Choi, Sang-Su
    • Korean Journal of Computational Design and Engineering
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    • v.15 no.2
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    • pp.85-93
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    • 2010
  • This paper proposes a CAE data translation and visualization technique that can verify time-varying continuous analysis simulation in a virtual reality (VR) environment. In previous research, the use of CAE analysis data has been problematic because of the lack of any interactive simulation controls for visualizing continuous simulation data. Moreover, the research on post-processing methods for real-time verification of CAE analysis data has not been sufficient. We therefore propose a scene graph based visualization method and a post-processing method for supporting interoperability of continuous CAE analysis data. These methods can continuously visualize static analysis data independently of any timeline; it can also continuously visualize dynamic analysis data that varies in relation to the timeline. The visualization system for continuous simulation data, which includes a CAE middleware that interfaces with various formats of CAE analysis data as well as functions for visualizing continuous simulation data and operational functions, enables users to verify simulation results with more realistic scenes. We also use the system to do a performance evaluation with regard to the visualization of continuous simulation data.

The Intellectual Structure of Business Analytics by Author Co-citation Analysis : 2002 ~ 2020 (저자동시인용분석에 의한 Business Analytics 분야의 지적 구조 분석: 2002 ~ 2020)

  • Lim, Hyae Jung;Suh, Chang Kyo
    • The Journal of Information Systems
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    • v.30 no.1
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    • pp.21-44
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    • 2021
  • Purpose The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field. Design/methodology/approach This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data. Findings We identified seven sub- areas of business analytics field. The top four sub-areas are "Big Data Analytics Infrastructure", "Performance Management System", "Interactive Exploration", and "Supply Chain Management". We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

Location Inference of Twitter Users using Timeline Data (타임라인데이터를 이용한 트위터 사용자의 거주 지역 유추방법)

  • Kang, Ae Tti;Kang, Young Ok
    • Spatial Information Research
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    • v.23 no.2
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    • pp.69-81
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    • 2015
  • If one can infer the residential area of SNS users by analyzing the SNS big data, it can be an alternative by replacing the spatial big data researches which result from the location sparsity and ecological error. In this study, we developed the way of utilizing the daily life activity pattern, which can be found from timeline data of tweet users, to infer the residential areas of tweet users. We recognized the daily life activity pattern of tweet users from user's movement pattern and the regional cognition words that users text in tweet. The models based on user's movement and text are named as the daily movement pattern model and the daily activity field model, respectively. And then we selected the variables which are going to be utilized in each model. We defined the dependent variables as 0, if the residential areas that users tweet mainly are their home location(HL) and as 1, vice versa. According to our results, performed by the discriminant analysis, the hit ratio of the two models was 67.5%, 57.5% respectively. We tested both models by using the timeline data of the stress-related tweets. As a result, we inferred the residential areas of 5,301 users out of 48,235 users and could obtain 9,606 stress-related tweets with residential area. The results shows about 44 times increase by comparing to the geo-tagged tweets counts. We think that the methodology we have used in this study can be used not only to secure more location data in the study of SNS big data, but also to link the SNS big data with regional statistics in order to analyze the regional phenomenon.

An Analysis Method for Dynamical System

  • Niu, Yu;d'Auriol, Brian J.;Lee, Youngkoo;Lee, Sungyoung
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.583-584
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    • 2009
  • This paper provides a method to analyze the dynamical system. It considers the fact of realistic delay in dynamical system analysis for the first time. The method uses timeline and state space to emulate the inhibitive coupling nodes evolving procedure in transmission delayed environment. The resultant finite state machine shows the system predictability and hardware implementation feasibility.

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Propensity Analysis of Political Attitude of Twitter Users by Extracting Sentiment from Timeline (타임라인의 감정추출을 통한 트위터 사용자의 정치적 성향 분석)

  • Kim, Sukjoong;Hwang, Byung-Yeon
    • Journal of Korea Multimedia Society
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    • v.17 no.1
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    • pp.43-51
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    • 2014
  • Social Network Service has the sufficient potential can be widely and effectively used for various fields of society because of convenient accessibility and definite user opinion. Above all Twitter has characteristics of simple and open network formation between users and remarkable real-time diffusion. However, real analysis is accompanied by many difficulties because of semantic analysis in 140-characters, the limitation of Korea natural language processing and the technical problem of Twitter is own restriction. This thesis paid its attention to human's political attitudes showing permanence and assumed that if applying it to the analytic design, it would contribute to the increase of precision and showed it through the experiment. As a result of experiment with Tweet corpus gathered during the election of national assemblymen on 11st April 2012, it could be known to be considerably similar compared to actual election result. The precision of 75.4% and recall of 34.8% was shown in case of individual Tweet analysis. On the other hand, the performance improvement of approximately 8% and 5% was shown in by-timeline political attitude analysis of user.

A Study of Interpolation Methods for the Water Hammer Analysis using the Method of Characteristics (특성선 방법을 이용한 관망 수격현상 해석의 보간방법연구)

  • Jung, Bong Seog;Kim, Chu In;Kim, Sang Hyun;Park, Nam Sik
    • Journal of Korean Society of Environmental Engineers
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    • v.22 no.2
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    • pp.363-373
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    • 2000
  • It is necessary to employ the interpolation technique to resolve problems, which are associated with the characteristic locus in time-distance space, in the unsteady analysis of pipe flow. Various interpolation methods such as linear timeline interpolation, linear spaceline interpolation, wave speed adjustment, cubic spaceline interpolation and cubic timeline interpolation have been suggested and tested to investigate the interpolation error. Performance of various interpolation techniques was evaluated both a single pipeline and a complex one. The range of error was calculated as the courant number varied between 0 and 1 in a single pipeline. Reorganization of computational element and proper selection of interpolation method are found to be prerequisites for the effective computation of unsteady analysis.

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