• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.69-76
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• 2016

In this paper, we propose a real-time remote logging model for development of android applications using LBS(Location based Service). The model has two major parts: Mobile Log Management Service and Remote Log Server. Mobile Log Management Service consists of the log collector and the remote log manager. The log collector is an aspect of AOP which can collect logs from the target application without modifications of source codes. The remote log manager has a background service component so that it can receive logs whenever the log collector captures logs from the target application. Remote Log Server communicates with Mobile Log Management Service by socket interface. Therefore, Remote Log Server can show logs in real-time. To validate the efficiency of the proposed model, we show a case study, and compare the model with other models.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.589-594
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• 2013

As the concept of web characteristics represented by openness and mind sharing grows more and more popular, device log data generated by both users and developers have become increasingly complicated. For such reasons, a log data processing mechanism that automatically produces meaningful data set from large amount of log records have become necessary for mobile device UX(User eXperience) analysis. In this paper, we define the attributes of to-be-analyzed log data that reflect the characteristics of a mobile device and collect real log data from mobile device users. Along with the MapReduce programming paradigm in Hadoop platform, we have performed a mobile device User eXperience analysis in a distributed processing environment using the collected real log data. We have then demonstrated the effectiveness of the proposed analysis mechanism by applying the various combinations of Map and Reduce steps to produce a simple data schema from the large amount of complex log records.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.63-68
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• 2006

If web server occurs my fault, log file is important information to find out occurred error. The web server analyzer plays a vital role in improving the web service quality by analyzing log files stores in the web server. But, most conventional web server analysis programs are provided over wired networks, there are problems to be dealt with in terms of time-space restrictions and mobility. In order to solve above problem, this paper represent web server analyser based mobile. In case web server manager based mobile, it can immediately know recent log information accessing real-rime as also anytime, anywhere.

• Journal of Information Technology Services
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• v.7 no.2
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• pp.181-195
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• 2008

The rapid growth of mobile communication technology has provided the expansion of mobile internet services, particularly mobile realtime transaction takes much weight among mobile fields. There is an increasing demand for various mobile applications to process transactions in a mobile computing fields. Thus, During transmission in wireless networks a base station failure inevitably causes data loss of the base station buffer. It is required to compensate the loss for communication. The existing methods for a base station failure are not adequate because they all suffer from too much overhead and resolve only the link failure. In this paper, we study an efficient recovry systems for a mobile DBMS. We propose SLL (Segment Log List) that enables the mobile host to compensate data loss efficiently in the case of base station failure. In SLL, a base station deliveries an output information of data cells to a mobile host. when a base station fails, the mobile host can retransmit just next data cells. We also prove the efficiency of new method.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.727-731
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• 2010

Recently, mobile life-log data are collected by mobile devices and used to recode one's life. In order to help a user search data, a mobile life-log semantic network is introduced for storing logs and retrieving associative information. However, associative search systems on common semantic networks in previous studies provide for a user with only found data as text to users. This paper proposes an associative search system for mobile life-log semantic network that supports selection and keyword associative search of which a process and result are a visualized graph representing associative data and their relationships when a user inputs a keyword for search. In addition, by using semantic abstraction, the system improves user's understanding of search result and simplifies the resulting graph. The system's usability was tested by an experiment comparing the system and a text-based search system.

• 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%.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.23-33
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• 2014

The smart phone are changing the way people communicate. And, the mobile app marketplace is greatly fast-growing. The app store continues its rapid growth, there are already more than 900,000 mobile apps on AppStore. We anticipate to see gained momentum throughout the business. Mobile is also becoming popular for marketers. Therefore, specialized app analysis systems are becoming important to how marketers and app developers invest, analyze and market their apps. App analysis systems enable users to discover and analyze behavior through data observations and meaningful patterns. In this paper, we introduce app analysis system and CMS System Open API, NugaLog. The NugaLog acquires users data and engages with them in a variety of ways. It will be essential for us to understand how users interact with and move through the app. The NugaLog will be able to see the number of users, smart phone model, smart phone OS, resolution, page views, and app version.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.27-39
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• 2018

Since the global positioning system (GPS) has been included in mobile devices (e.g., for car navigation, in smartphones, and in smart watches), the impact of personal GPS log data on daily life has been unprecedented. For example, such log data have been used to solve public problems, such as mass transit traffic patterns, finding optimum travelers' routes, and determining prospective business zones. However, a real-time analysis technique for GPS log data has been unattainable due to theoretical limitations. We introduced a machine learning model in order to resolve the limitation. In this paper presents a new, three-stage real-time prediction model for a person's daily route activity. In the first stage, a machine learning-based clustering algorithm is adopted for place detection. The training data set was a personal GPS tracking history. In the second stage, prediction of a new person's transient mode is studied. In the third stage, to represent the person's activity on those daily routes, inference rules are applied.

• The Journal of Information Systems
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• v.23 no.1
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• pp.185-202
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• 2014

ERP, a typical enterprise application, helps companies to increase their productivity and to support their decision makings. ERP is composed of diverse functions that are optimized under PC environment, whereas the ERP applications on a mobile platform have many constraints such as a small screen, limited resolution, and computing power. Because all the functions of a ERP legacy system are not required for ERP on a mobile device, the core functions of the ERP system should be selected to increase system efficiency. In this study, two main methods were used; interviews and log analyses. The end users using a ERP system were interviewed for their perceptions, and log data analyses were made for the hitting number of specific ERP functions. The differences between the actual usage based on log data and users' cognitive preferences about ERP functions were analysed. Finally, the functional differences between users' perception and actual usage were suggested for some practical implications.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.1063-1068
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• 2004

A log file in web server stores various information of web server. The web server information is good reference information to improve web service quality. Also if web server occurs any fault, log file information is important information to find out occurred error. Currently, many of web server manager that they have wire have disadvantages in mobility. In order to solve above problem, this paper represent web server manager based mobile. Incase web server manager based mobile, it can immediately know recent log information accessing real-rime as also anytime, anywhere