• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.625-635
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• 2008

Portable multimedia players have some different properties compared to general multimedia file server. Some of those properties are single user ownership, relatively low hardware performance, I/O burst by user special functions, and short software development cycles. Though suitable for processing multiple user requests at a time, the general multimedia file systems are not efficient for special user functions such as fast forwards/backwards. Soml' methods has been proposed to improve the performance and functionality, which the application programs give prediction hints to the file system. Unfortunately, they require the modification of all applications and recompilation. In this paper, we present a file system that efficiently supports user special functions in embedded multimedia systems using file block allocation, buffer-cache, and prefetch. A prefetch algorithm, SPRA (SPeed-based PRefetch Algorithm) predicts the next block using I/O patterns instead of hints from applications and it is resident in the file system, so doesn't affect application development process. From the experimental file system implementation and comparison with Linux readahead-based algorithms, the proposed system shows $4.29%{\sim}52.63%$ turnaround time and 1.01 to 3,09 times throughput in average.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.154-159
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• 2015

Over the past few years, user needs in the smartphone application market have been shifted from diversity toward intelligence. Here, we propose a novel cognitive agent that plans the daily routines of users using the lifelog data collected by the smart phones of individuals. The proposed method first employs DPGMM (Dirichlet Process Gaussian Mixture Model) to automatically extract the users' POI (Point of Interest) from the lifelog data. After extraction, the POI and other meaningful features such as GPS, the user's activity label extracted from the log data is then used to learn the patterns of the user's daily routine by POMDP (Partially Observable Markov Decision Process). To determine the significant patterns within the user's time dependent patterns, collaboration was made with the SNS application Foursquare to record the locations visited by the user and the activities that the user had performed. The method was evaluated by predicting the daily routine of seven users with 3300 feedback data. Experimental results showed that daily routine scheduling can be established after seven days of lifelogged data and feedback data have been collected, demonstrating the potential of the new method of place-time-activity coupled daily routine planning systems in the intelligence application market.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.2
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• pp.113-127
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• 2012

From the end of 1st quarter of 2012, Korean mandatory firms had started releasing financial reports conforming to the K-IFRS(Korean adopted International Financial Reporting Standards). Major characteristics of IFRS, such as 'principles based' features, consolidated reporting, 'fair value' measurement, increased pressure for non-financial disclosures have resulted in brief and various disclosure practices regarding the main body of each statements and vast amount of note description requirements. Meanwhile, a host of previous studies on IFRS disclosures have incorporated regulatory and/or 'compete information' perspectives, mainly focusing on suggesting further enforcement of strengthened requirements and providing guidelines for specific treatments. Thus, as an extension of prior findings and suggestions this study had explored to conduct an integrative approach embracing views of the reporting entities and the users of financial information. In spite of all the state-driven efforts for faithful representation and comparability of corporate financial reports, an overhaul of disclosure practices of fiscal year 2010 and 2011 had revealed numerous cases of insufficiency and discordance in terms of mandatory norms and market expectations. As to the causes of such shortcomings, this study identified several factors from the corporate side and the users of the information; some inherent aspects of IFRS, industry/corporate-specific context, expenditures related to internalizing IFRS system, reduced time frame for presentation. lack of clarity and details to meet the quality of information - understandability, comparability etc. - commonly requested by the user group. In order to improve current disclosure practices, dual approach had been suggested; Firstly, to encourage and facilitate implementation, (1) further segmentation and differentiation of mandates among companies, (2) redefining the scope and depth of note descriptions, (3) diversification and coordination of reporting periods, (4) providing support for equipping disclosure systems and granting incentives for best practices had been discussed. Secondly, as for the hard measures, (5) regularizing active involvement of corporate and user group delegations in the establishment and amendment process of K-IFRS (6) enforcing detailed and standardized disclosure on reporting entities had been recommended.

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.497-503
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• 2016

Emerging next-generation storage technologies such as non-volatile memory will help eliminate almost all of the storage latency that has plagued previous storage devices. In conventional storage systems, the latency of slow storage devices dominates access latency; hence, software efficiency is not critical. With low-latency storage, software costs can quickly dominate memory latency. Hence, researchers have proposed the memory mapped file I/O to avoid the software overhead. Mapping a file into the user memory space enables users to access the file directly. Therefore, it is possible to avoid the complicated I/O stack. This minimizes the number of user/kernel mode switchings. In addition, there is no data copy between kernel and user areas. Despite of the benefits in the memory mapped file I/O, its overhead still needs to be addressed, as the existing mechanism for the memory mapped file I/O is designed for slow block devices. In this paper, we identify the overheads of the memory mapped file I/O via experiments.

• KIISE Transactions on Computing Practices
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• v.23 no.2
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• pp.110-115
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• 2017

We propose a new indoor positioning algorithm named Cut-off algorithm. This algorithm cuts off candidates of beacons and reference points in advance, before looking for K neighbor reference points which are guessed to be closest to the user's actual location. The algorithm consists of two phases: off-line phase, and on-line phase. In the off-line phase, RSSI and UUID data from beacons are gathered at reference points placed in the indoor environment, and construct a fingerprint map of the data. In the on-line phase, the map is reduced to a smaller one according to the RSSI data of beacons received from the user's device. The nearest K reference points are selected using the reduced map, which are used for estimating user's location. In both phases, relative ranks of the peak signals received from each beacon are used, which smoothen the fluctuations of the signals. The algorithm is shown to be more efficient in terms of accuracy and estimating time.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.328-333
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• 2017

Mobile game apps, which are popular in various mobile devices, tend to be power-hungry and rapidly drain the device's battery. Since a long battery lifetime is a key design requirement of mobile devices, reducing the power consumption of mobile game apps has become an important research topic. In this paper, we investigate the power consumption characteristics of popular mobile games with multiple threads, focusing on the inter-thread. From our power measurement study of popular mobile game apps, we observed that some of these apps have abnormally high-load threads that barely affect the user's gaming experience, despite the high energy consumption. In order to reduce the wasted power from these abnormal threads, we propose a novel technique that detects such abnormal threads during run time and reduces their power consumption without degrading user experience. Our experimental results on an Android smartphone show that the proposed technique can reduce the energy consumption of mobile game apps by up to 58% without any negative impact on the user's gaming experience.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.320-332
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• 2007

Recently, new interests on digital contents and UCC(User Created Content)s are growing fast through the development of internet. However, there have been many side-effects on those interests. The representative problems are perversing illegal copies and the distributions for personal valuable digital contents to unauthorized anonymous users. These decrease creation of good digital contents by interfering with the growth of information technology industry and the content provider#s creative will. To resolve these problems, in the paper, we propose a novel auction system for multimedia contents and bidding processes. The system applies the concept of used goods onto digital contents. Especially, the auction system is based on mobile environment. Finally, the performance evaluation shows that those main auction process algorithms indicate the time complexity of logarithm scale for insertions and searches. Therefore, the performance of the system is not significantly influenced by the amount of contents even though the volume of contents in the system is increasing.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.2
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• pp.86-99
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• 2007

Packet filtering is to filter out potentially malicious network packets. In order to test a packet filtering function we should verify whether security policies are performed correctly as intended. However there are few existing tools to test the function. Besides, they need user participation when generating test cases or deciding test results. Many security administrators have a burden to test systematically new security policies when they establish new policies or modify the existing ones. To mitigate the burdens we suggest a new test method with minimal user articipation. Our tool automates generation steps of the test cases and the test oracles, respectively. By using the test oracles generated automatically, deciding test results is possible without user intervention. Our method realizes an automatic testing in three phases; test preparation phase, test execution, and test evaluation. As a result it may enhance confidence of test activities more highly. This paper describes the design and implementation of our test method and tool.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.9
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• pp.906-910
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• 2008

As the mobile environment becomes widely used, there is a growth on the concern about recognizing and sharing user context. Sharing context makes the interaction between human more plentiful as well as helps to keep a good social relationship. Recently, it has been applied to some messengers or mobile applications with sharing simple contexts, but it is still required to recognize and share more complex and diverse contexts. In this paper, we propose a context-aware messenger that collects various sensory information, recognizes representative user contexts such as emotion, stress, and activity by using dynamic Bayesian networks, and visualizes them. It includes a modular model that is effective to recognize various contexts and displays them in the form of icons. We have verified the proposed method with the scenario evaluation and usability test.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.380-384
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• 2009

The log data collected on a mobile device contain diverse and continuous information about the user. From the log data, the location, pictures, running functions and services of the user can be obtained. It has interested in the research inferring the contexts and understanding the everyday-life of mobile users. In this paper, we have studied the methods for real-time collection of log data from mobile devices, analysis of the data, map based visualization and effective management of the personal everyday-life information. We have developed an application for sharing the contexts. The proposed application infers the personal contexts with Bayesian network probabilistic model. In the experiments, we confirm that the usability of visualization and information sharing functions based on the real world log data.