Vol. 44, No. 3,
Mar. 2017
Digital Library
Sojourn Time Analysis Using SRPT Scheduling for Heterogeneous Multi-core Systems
Yang Bomi, Hyunjae Park, Young-June Choi
In this paper, we study the performance of recently popular multi-core systems in mobiles. Previous research on the multi-core performance usually focused on the desktop PC. However, there is enough scope to further analyze heterogeneous multi-core systems. Therefore, by extending homogeneous multi-core systems, we analyze the heterogeneous multi-core systems using Size Interval Task Allocation (SITA) for job allocation, and Shortest Remaining Processing Time (SRPT) scheduling, for each individual core. We propose a new computational method regarding the cutoff point, which is crucial in analyzing SITA, by calculating the sojourn time. This facilitate easy and accurate calculation of the sojourn time. We further confirm our analysis through the ESESC simulator that provides actual measurements.
AIOPro: A Fully-Integrated Storage I/O Profiler for Android Smartphones
Sangwook Shane Hahn, Inhyuk Yee, Donguk Ryu, Jihong Kim
Application response time is critical to end-user response time in Android smartphones. Due to the plentiful resources of recent smartphones, storage I/O response time becomes a major key factor in application response time. However, existing storage I/O trace tools for Android and Linux give limited information only for a specific I/O layer which makes it difficult to combine I/O information from different I/O layers, because not helpful for application developer and researchers. In this paper, we propose a novel storage I/O trace tool for Android, called AIOPro (Android I/O profiler). It traces storage I/O from application - Android platform - system call - virtual file system - native file system - page cache - block layer - SCSI layer and device driver. It then combines the storage I/O information from I/O layers by linking them with file information and physical address. Our evaluations of real smartphone usage scenarios and benchmarks show that AIOPro can track storage I/O information from all I/O layers without any data loss under 0.1% system overheads.
A Model of Probabilistic Parsing Automata
Probabilistic grammar is used in natural language processing, and the parse result of the grammar has to preserve the probability of the original grammar. As for the representative parsing method, LL parsing and LR parsing, the former preserves the probability information of the original grammar, but the latter does not. A characteristic of a probabilistic parsing automaton has been studied; but, currently, the generating model of probabilistic parsing automata has not been known. The paper provides a model of probabilistic parsing automata based on the single state parsing automata. The generated automaton preserves the probability of the original grammar, so it is not necessary to test whether or not the automaton is probabilistic parsing automaton; defining a probability function for the automaton is not required. Additionally, an efficient automaton can be constructed by choosing an appropriate parameter.
An Algorithm for Computing a Minimum-Width Color-Spanning Rectangular Annulus
In this paper, we present an algorithm that computes a minimum-width color spanning axis-parallel rectangular annulus. A rectangular annulus is a closed region between a rectangle and its offset, and it is thus bounded by two rectangles called its outer and inner rectangles. The width of a rectangular annulus is determined by the distance between its outer and inner rectangles. Given n points in the plane each of which has one of the prescribed k colors, we call a rectangular annulus color spanning if it contains at least one point for each of the k colors. Prior to this work, there was no known exact algorithm that computes a minimum-width color-spanning rectangular annulus. Our algorithm is the first to solve this problem and it runs efficiently in O(n-k)³nlogn) time.
Real-Time Nonlinear Lens-Flare Rendering Method Based on Look-Up Table
Sunghun Jo, Yuna Jeong, Sungkil Lee
In computer graphics, high-quality lens flares have been generated using costly offline rendering. A recent matrix-based approximation has enabled generation of high-quality lens flares suitable for real-time applications, but its quality degrades due to the lack of nonlinear patterns of lens flares. This paper introduces a method for high-quality lens-flare rendering, which includes blending of both nonlinear as well as linear patterns. The nonlinear patterns are pre-rendered or photographically captured offline and stored in a look-up table. The online stage reads only the pattern by looking up the table using a light angle, hence making its performance drop negligible while greatly improving the quality.
A Framework Integrating Problem Frames and Goal Modeling to Support Variability Analysis during Requirements Elicitation
Variability management is the foremost criterion that defines the extent to which complexities can be handled in a system. Predominantly, the requirements’ engineering (RE) study overlooks, or speculates a consistent behavior of, the environment in which a system functions. In real-time systems it is vital to observe and adjust to an intrinsically changing context. Therefore, in this work we identify the requirements of the system in various contexts by recommending a framework using i* goal model, problem frames, use case maps and live sequence charts. The framework is illustrated using a case study of the smart grid RTP system. In the case study, elaboration of scenarios using use case maps and live sequence charts proved beneficial as they assisted in early analysis and validation of contexts. In addition, the elaboration of requirements for obstacle and conflict analysis assists the requirements engineer to increase the robustness of the system. The proposed framework is evaluated theoretically and by empirical study.
Recovery of Software Module-View using Dependency and Author Entropy of Modules
Jung-Min Kim, Chan-Gun Lee, Ki-Seong Lee
In this study, we propose a novel technique of software clustering to recover the software module-view by using the dependency and author entropy of modules. The proposed method first performs clustering of modules based on structural and logical dependencies, then it migrates selected modules from the clustered result by utilizing the author entropy of each module. In order to evaluate the proposed method, we calculated the MoJoFM values of the recovery result by applying the method to open-source projects among which ground-truth decompositions are well-known. Compared to the MoJoFM values of previously studied techniques, we demonstrated the effectiveness of the proposed method.
Automated Modelling of Ontology Schema for Media Classification
Nam-Gee Lee, Hyun-Kyu Park, Young-Tack Park
With the personal-media development that has emerged through various means such as UCC and SNS, many media studies have been completed for the purposes of analysis and recognition, thereby improving the object-recognition level. The focus of these studies is a classification of media that is based on a recognition of the corresponding objects, rather than the use of the title, tag, and scripter information. The media-classification task, however, is intensive in terms of the consumption of time and energy because human experts need to model the underlying media ontology. This paper therefore proposes an automated approach for the modeling of the media-classification ontology schema; here, the OWL-DL Axiom that is based on the frequency of the recognized media-based objects is considered, and the automation of the ontology modeling is described. The authors conducted media-classification experiments across 15 YouTube-video categories, and the media-classification accuracy was measured through the application of the automated ontology-modeling approach. The promising experiment results show that 1500 actions were successfully classified from 15 media events with an 86 % accuracy.
Face Representation Based on Non-Alpha Weberface and Histogram Equalization for Face Recognition Under Varying Illumination Conditions
Ha-Young Kim, Hee-Jae Lee, Sang-Goog Lee
Facial appearance is greatly influenced by illumination conditions, and therefore illumination variation is one of the factors that degrades performance of face recognition systems. In this paper, we propose a robust method for face representation under varying illumination conditions, combining non-alpha Weberface (non-alpha WF) and histogram equalization. We propose a two-step method: (1) for a given face image, non-alpha WF, which is not applied a parameter for adjusting the intensity difference between neighboring pixels in WF, is computed; (2) histogram equalization is performed to non-alpha WF, to make a uniform histogram distribution globally and to enhance the contrast. (2D)²PCA is applied to extract low-dimensional discriminating features from the preprocessed face image. Experimental results on the extended Yale B face database and the CMU PIE face database show that the proposed method yielded better recognition rates than several illumination processing methods as well as the conventional WF, achieving average recognition rates of 93.31% and 97.25%, respectively.
Expansion of Word Representation for Named Entity Recognition Based on Bidirectional LSTM CRFs
Named entity recognition (NER) seeks to locate and classify named entities in text into pre-defined categories such as names of persons, organizations, locations, expressions of times, etc. Recently, many state-of-the-art NER systems have been implemented with bidirectional LSTM CRFs. Deep learning models based on long short-term memory (LSTM) generally depend on word representations as input. In this paper, we propose an approach to expand word representation by using pre-trained word embedding, part of speech (POS) tag embedding, syllable embedding and named entity dictionary feature vectors. Our experiments show that the proposed approach creates useful word representations as an input of bidirectional LSTM CRFs. Our final presentation shows its efficacy to be 8.05%p higher than baseline NERs with only the pre-trained word embedding vector.
Churn Analysis of Maximum Level Users in Online Games
In MMORPG (Massively Multiplayer Online Role-Playing Game), users advance their own characters to get to the maximum (max) level by performing given tasks in the game scenario. Although it is crucial to retain users with high levels for running online games successfully, little efforts have been paid to investigate them. In this study, by analyzing approximately 60 million in-game logs of over 50,000 users, we aimed to investigate the process through which users achieve the max level and churn of such users since the moment of achieving the max level, and determine possible indicators related to churn after the max level. Based on the result, we can predict churn of the max level users by employing behavioral patterns before the max level. Moreover, we found users who are socially active and communicate with many people before the max level are less likely to leave the service (p<0.05). This study supports that communication patterns are important factors for persistent usage of the users who achieve the max level, which has practical implications to guide elite users on enjoying online games in the long run.
A Secure Key Exchange Protocol Using Smart Devices for U-healthcare Services
Sullha Park, Seung-Hyun Seo, Sang-Ho Lee
Due to the recent developments of various smart devices, U-healthcare services using these appliances has increased. However, the security of U-healthcare services is a very important issue since healthcare services contain highly sensitive and private personal health information. In order to handle the security issues, the functionality of encrypting medical information must be provided, and an encryption key exchange method is necessary. In this paper, we propose a key exchange protocol by utilizing smart devices for secure U-healthcare services. The proposed protocol has been designed based on the elliptic curve based public key cryptography, providing high level security for smart devices by using short keys. Moreover, in order to strengthen user authentication and security, a smart watch is used as a complementary device, whenever the key exchange protocol is performed.
IFC-based Data Structure Design for Web Visualization
When using IFC data consisting of STEP schema based on the EXPRESS language, it is not easy for collaborating project stakeholders to share BIM modeling shape information. The IFC viewer application must be installed on the desktop PC to review the BIM modeling shape information defined within the IFC, because the IFC viewer application not only parse STEP structure information model but also process the 3D feature construction for a 3D visualization. Therefore, we propose a lightweight data structure design for web visualization by parsing IFC data and constructing 3D modeling data. Our experimental results show the weight reduction of IFC data is about 40% of original file size and the web visualization is able to see the same quality with all web browsers which support WebGL on PCs and smartphones. If applied research is conducted about the web visualization based on IFC data of the last construction phase, it could be utilized in various fields ranging from the facility maintenance to indoor location-based services.
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