• Journal of Information Science Theory and Practice
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• v.10 no.1
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• pp.73-88
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• 2022

This exploratory study aims to understand the potential of log data analysis and expand its utilization in user research methods. Transaction log data are records of electronic interactions that have occurred between users and web services, reflecting information-seeking behavior in the context of digital libraries where users interact with the service system during the search for information. Two ways were used to analyze South Korea's National Digital Science Library (NDSL) log data for three days, including 150,000 data: a log pattern analysis, and log context analysis using statistics. First, a pattern-based analysis examined the general paths of usage by logged and unlogged users. The correlation between paths was analyzed through a χ² analysis. The subsequent log context analysis assessed 30 identified users' data using basic statistics and visualized the individual user information-seeking behavior while accessing NDSL. The visualization shows included 30 diverse paths for 30 cases. Log analysis provided insight into general and individual user information-seeking behavior. The results of log analysis can enhance the understanding of user actions. Therefore, it can be utilized as the basic data to improve the design of services and systems in the digital library to meet users' needs.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.10
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• pp.781-785
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• 2009

We can constantly gather personal life log from developed mobile device. However, gathered personal life log in mobile environment have a large amount log and uncertainty such as uncertainty of mobile environment, limited capacity and battery of mobile device. Tagging task using a landmark such as a key word should be required to overcome the above problem and to manage personal life log. In this paper, we propose new tagging method and a life log tagging interface using high level context recognizer based on probability. The new tagging method extract high level context such as landmark of life log using recognizer which is modeled from bayesian network and recommend recognized high level context to user using tagging interface. Finally user can directly do tagging task to life log. This task is a special feature in our process. As the result of experiments in task support level which include usability, level of a goal, function and leading, we achieved a feeling of satisfaction of 81%.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.84-89
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• 2009

Personal mobile devices such as mobile phone, PMP and MP3 player have advanced incredibly. Such advance in mobile technology ignites the research related to the life-log to understand the daily life of an user. Since life-log collected by mobile sensors can aid memory of the user, many researches have been conducted. This paper suggests a methodology for user-context recognition and visualization based on the outdoor location by GPS as well as indoor location by wireless-lan. When the GPS sensor does not work well in an indoor location, wireless-lan plays a major role in recognizing the location of an user so that the recognition of user-context become more accurate. In this paper, we have also developed the method for visualization of the life-log based on map and blog interfaces. In the experiments, subjects have collected real data with mobile devices and we have evaluated the performance of the proposed visualization and context recognition method based on the data.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.333-336
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• 2005

The advance of wireless telecommunication and observation technologies leads developing sensor and sensor network for serving the context information continuously. Besides, in order to understand and cope with the context awareness based on the sensor network, it is becoming important issue to deal with plentiful data transmitted from various sensors. Therefore, we propose a context awareness system to deal with the plentiful sensor data in a vast area such as the prevention of a forest fire, the warning system for detecting environmental pollution, and the analysis of the traffic information, etc. The proposed system consists of the context acquisition to collect and store various sensor data, the knowledge base to keep context information and context log, the rule manager to process context information depending on user defined rules, and the situation information manager to analysis and recognize the context, etc. The proposed system is implemented for managing renewable energy data management transmitted from a large scale area.

• Korean Journal of Cognitive Science
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• v.20 no.4
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• pp.535-554
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• 2009

Information collected on mobile devices might be utilized to support user's memory, but it is difficult to effectively retrieve them because of the enormous amount of information. In order to organize information as an episodic approach that mimics human memory for the effective search, it is required to detect important event like landmarks. For providing new services with users, in this paper, we propose the prediction model to find landmarks automatically from various context log information based on attributed Bayesian networks. The data are divided into daily and weekly ones, and are categorized into attributes according to the source, to learn the Bayesian networks for the improvement of landmark prediction. The experiments on the Nokia log data showed that the Bayesian method outperforms SVMs, and the proposed attributed Bayesian networks are superior to the Bayesian networks modelled daily and weekly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.546-548
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• 2019

In recent days, vehicle safety technologies for supporting safe vehicle driving attract public attention. This paper proposes multi-log platform based vehicle safety system (MLPVSS) that analyzes multi-log data (i.e., log-data on human, object, and place) and supports vehicle safety. The MLPVSS gathers sensor data and image data on the human, object, and place, and then generates multi-log data that are context-aware data on the human, object, and place. The MLPVSS can detect, predict, and response vehicle dangers. The MLPVSS can contribute to reduce car accidents.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.144-152
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• 2009

To provide intelligent service in mobile environment, it needs to estimate user's intention or requirement, through analyzing context information of end-users such as preference or behavior patterns. In this paper, we infer context information from uncertain log stored in mobile device. And we propose the inference method of end-user's behavior to match context information with service, and the proposed method is based on context-tree. We adopt bayesian probabilistic method to infer uncertain context information effectively, and the context-tree is constructed to utilize non-numerical context which is hard to handled with mathematical method. And we verify utility of proposed method by appling the method to intelligent phone book service.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.525-530
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• 2010

Currently, most context-aware services are built by developers. Some researchers argued that services should be defined by end users, who understand their own needs best. We view that the significance of enabling the user to define his/her personalized services will multiply as our living spaces grow smarter. This paper introduces a novel method called CASPER, which is capable of deriving personalized services from the log of user's activities of daily living. CASPER can generate useful services that even the user may not perceive, mining causality of events in the log. We present the algorithm of CASPER in detail and discuss the result of an experiment which we conducted as a proof of concept.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.507-514
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• 2006

Various application systems are developed using RFID as a part of ubiquitous computing, and it is expected that RFID chip will become wide-spread for the distribution industry especially. Efficient and efact intelligent-type of warehouse management system is essential for small-to-medium-sized enterprises in the situation having a trouble in the viewpoint of expense and manpower. In this paper, we implement small-scale warehouse management system using log-based context awareness technology. This system is implemented to be controlled on web, configuring clients to control RFID readers and building up DBMS system in a server. Especially, it grasps user's intention of storing or delivering based on toE data for the history of user's access to the system and it reports user's irregular pattern of warehouse use and serves predictive information of the control of goods in stock. As a result, the proposed system can contribute to enhance efficiency and correctness of small-scale warehouse management.

• International Journal of Reliability and Applications
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• v.17 no.1
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• pp.85-105
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• 2016

In this paper accelerated life testing is incorporated in quality control technique of acceptance sampling plan to induce early failures in high reliability products.Stress under accelerated condition can be applied in constant-stress, step-stress and progressive-stress or combination of such loadings. A ramp-stress results when stress is increased linearly (from zero) with time. In this paper optimum failure-censored ramp-stress accelerated life test sampling plan for log-logistic distribution has been formulated with cost considerations. The log-logistic distribution has been found appropriate for insulating materials. The optimal plans consist in finding optimum sample size, sample proportion allocated to each stress, and stress rate factor such that producer's and consumer's interests are safeguarded. Variance optimality criterion is used when expected cost per lot is not taken into consideration, and bilevel programming approach is used in cost optimization problems. The methods developed have been illustrated using some numerical examples, and sensitivity analyses carried out in the context of ramp-stress ALTSP based on variable SSP for proportion nonconforming.