• The KIPS Transactions:PartC
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• v.19C no.1
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• pp.1-8
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• 2012

Recently, due to the development of broadband, there is a significant increase in utilizing on-demand Saas (Software as a Service) which takes advantage of the technology. Nevertheless, the academic and practical levels of digital forensics have not yet been established in cloud computing environment. In addition, the data of user behavior is not likely to be stored on the local system. The relevant data may be stored across the various remote servers. Therefore, the investigators may encounter some problems in performing digital forensics in cloud computing environment. it is important to analysis History files, Cookie files, Temporary Internet Files, physical memory, etc. in a viewpoint of client, since the SaaS basically uses the web to connects the internet service. In this paper, we propose the method that analysis the usuage trace of the Saas which is the one of the most popular cloud computing services.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.171-181
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• 2010

The integrated transit fare system of Seoul metropolitan area has given positively evaluated with reduction of user cost and activating the transfer behavior from its opening year, July 2007. However, there were only few research about railway demand forecasting methodology, especially mode share, has conducted under the integrated fare system. This study focuses on the utility estimation by each mode under the integrated fare system, and on the coefficient actualization relates on travel time and travel cost estimation with Household Travel Survey Data 2006. Also the railway demand analysis methodology under various fare systems is presented. The methodology from this study is expected to improve accuracy and usefulness in railway demand analysis.

• Smart Media Journal
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• v.6 no.2
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• pp.50-56
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• 2017

Due to new social environment, expenditure on eating out has increased over the last few year, thereafter the food-tech industries have steadily grown as well. We have studied what variable would affect customer's choices when they plan to eat out or order in. There are two variables are taken into account to prove it. Firstly, it is climate changes, such as an amount of rainfall, snowfall and clouds. Secondly, it is days, such as seasons and holidays. Based on this, we looked up the SikSin user's behaviors patterns, then did analysis of the daily data provided by the Meteorological office. By the end of the study, it turned out that two variables, climate changes and days, both have a strong influence on customer's choices. It is considered that this research outcome will make contributions to small businesses founders who want to take the initiative, marketing managers and people who are engaged in the food-tech industry.

• Journal of the Korea Computer Industry Society
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• v.2 no.7
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• pp.945-952
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• 2001

In consequence of expansion of internet users, electronic commerce is becoming a new prototype for marketing and sales, arid most of electronic commerce sites or internet shopping malls provide a rich source of information and convenient user interfaces about the organizations customers to maintain their patrons. One of the convenient interfaces for users is service to recommend products. To do this, they must exploit methods to extract and analysis specific patterns from purchasing information, behavior and market basket about customers. The methods are association rules and sequential patterns, which are widely used to extract correlation among products, and in most of on-line electronic commerce sites are executed with users information and purchased history by category-oriented. But these can't represent the diverse correlation among products and also hardly reflect users' buying patterns precisely, since the results are simple set of relations for single purchased pattern. In this paper, we propose an efficient mining technique, which allows for multiple purchased patterns that are category-independent and have relationship among items in the linked structure of single pattern items.

• Geomechanics and Engineering
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• v.14 no.2
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• pp.141-149
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• 2018

In this paper, the creep behavior of bolted rock was analyzed by using the unconfined creep tests and the numerical results. Based on the test results, the Bolted Burgers creep model (B-B model) was proposed to clarify the creep mechanism of rock mass due to rock bolts. As to the simulation of the creep behaviour of bolted rock, a new user-defined incremental iterative format of the B-B model was established and the open-source $FLAC^{3D}$ code was written by using the object-oriented language (C++). To check the reliability of the present B-B creep constitutive model program, a numerical model of a tunnel with buried depth of 1000 m was established to analyze the creep response of the tunnel with the B-B model support, the non-support and the bolt element support. The simulation results show that the present B-B model is consistent with the calculated results of the inherent bolt element in $FLAC^{3D}$, and the convergence deformation can be more effectively controlled when the proposed B-B model is used in the $FLAC^{3D}$ software. The big advantage of the present B-B creep model secondarily developed in the $FLAC^{3D}$ software is the high computational efficiency.

• Smart Structures and Systems
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• v.16 no.1
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• pp.163-181
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• 2015

This research investigates the structural health monitoring of nonlinear structures after a major seismic event. It considers the identification of flag-shaped or pinched hysteresis behavior in response to structures as a more general case of a normal hysteresis curve without pinching. The method is based on the overall least squares methods and the log likelihood ratio test. In particular, the structural response is divided into different loading and unloading sub-half cycles. The overall least squares analysis is first implemented to obtain the minimum residual mean square estimates of structural parameters for each sub-half cycle with the number of segments assumed. The log likelihood ratio test is used to assess the likelihood of these nonlinear segments being true representations in the presence of noise and model error. The resulting regression coefficients for identified segmented regression models are finally used to obtain stiffness, yielding deformation and energy dissipation parameters. The performance of the method is illustrated using a single degree of freedom system and a suite of 20 earthquake records. RMS noise of 5%, 10%, 15% and 20% is added to the response data to assess the robustness of the identification routine. The proposed method is computationally efficient and accurate in identifying the damage parameters within 10% average of the known values even with 20% added noise. The method requires no user input and could thus be automated and performed in real-time for each sub-half cycle, with results available effectively immediately after an event as well as during an event, if required.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.133-153
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• 2021

Recently, organizations are making significant technology investments to build a centralized content management system. However, high-quality technology adoption can conversely create techno-stress in the user and cause negative behavior. The purpose of this study is to suggest the negative effects and mitigation directions of enterprise content management system(ECMS) related techno-stress. In order to verify the hypothesis, this study conducted a questionnaire survey on employees of organizations that adopted content management technology and conducted structural equation modeling. As a result of the analysis, ECMS related techno overload and complexity decreased the intention of continuous use of ECMS. But, internal communication activities reduced ECMS related techno stress and task-technology fit moderated the relationship between techno-stress and intention of continuous use of ECMS. The study has implications in terms of suggesting a strategic direction to minimize the negative causes of the use of content management systems.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.66-71
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• 2021

In this paper, we sought ways to accept and reject advertisements using the function of a smartphone gyro sensor to enable selective transmission and reception of YouTube advertisements by linking the gyro function of mobile phones. In the case of YouTube advertisements, the skip button is activated after the advertisement is played for a certain period of time (about 5 seconds) before and after the video is played. During the time the advertisement is maintained, it can be used to achieve various goals such as increased website traffic, brand awareness, and sales induction. Since this type of advertisement is not a setting in which the transition takes place immediately, it can be seen as the most suitable setting to strengthen brand awareness. However, due to the nature of the YouTube advertising system, it is often discarded through users' skipping behavior in the process of sharing and reproducing information. Therefore, in this paper, we implemented an optional advertisement transmission system that applies the principle of gyroscope to minimize wasted advertisements and selectively maintain desired advertisements in consideration of the transmission and reception aspects of advertisement broadcasts. It measures rotational repulsive force with directional stability and car wash characteristics, and uses algorithms to identify the slope and angular speed of mobile phones to ensure that advertisements are transmitted and received. Through this, it is expected that advertisement transmission can be performed on the side of an advertisement provider, and selective advertisement reception can be performed on the side of a user.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1439-1448
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• 2018

Many electronic document files, including Microsoft Office Word (MS Word), have become a major issue in various legal disputes such as privacy, contract forgery, and trade secret leakage. The internal metadata of OOXML (Office Open XML) format, which is used since MS Word 2007, stores the unique Revision Identifier (RSID). The RSID is a distinct value assigned to a corresponding word, sentence, or paragraph that has been created/modified/deleted after a document is saved. Also, document history, such as addition/correction/deletion of contents or the order of creation, can be tracked using the RSID. In this paper, we propose a methodology to investigate discrimination between the original document and copy as well as possible document file leakage by utilizing the changes of the RSID according to the user's behavior.

• KNOM Review
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• v.21 no.2
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• pp.18-25
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• 2018

Since the development of block-chain technology by Satoshi Nakamoto and Bitcoin pioneered a new cryptocurrency market, a number of scale of cryptocurrency have emerged. There are crimes taking place using the anonymity and vulnerabilities of block-chain technology, and many studies are underway to improve vulnerability and prevent crime. However, they are not enough to detect users who commit crimes. Therefore, it is very important to detect abnormal behavior such as money laundering and stealing cryptocurrency from the network. In this paper, the characteristics of the transactions and user graphs in the Bitcoin network are collected and statistical information is extracted from them and presented as plots on the log scale. Finally, we analyze visualized plots according to the Densification Power Law and Power Law Degree, as a result, present features appropriate for detection of anomalies involving abnormal transactions and abnormal users in the Bitcoin network.