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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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KIISE Transactions on Computing Practices
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Journal DOI :
Korean Institute of Information Scientists and Engineers
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Volume & Issues
Volume 22, Issue 9 - Sep 2016
Volume 22, Issue 8 - Aug 2016
Volume 22, Issue 7 - Jul 2016
Volume 22, Issue 6 - Jun 2016
Volume 22, Issue 5 - May 2016
Volume 22, Issue 4 - Apr 2016
Volume 22, Issue 3 - Mar 2016
Volume 22, Issue 2 - Feb 2016
Volume 22, Issue 1 - Jan 2016
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Co-scheduling Technique of Dataflow Applications with Shared Processor Allocation
Kang, Duseok ; Kang, Shinhaeng ; Yang, Hoeseok ; Ha, Soonhoi ;
KIISE Transactions on Computing Practices, volume 22, issue 1, 2016, Pages 1~7
DOI : 10.5626/KTCP.2016.22.1.1
When multiple applications are running concurrently on a multi-processor system, interferences between applications make it difficult to guarantee real-time constraints. We propose a novel interference analysis technique that allows sharing of share processors among dataflow applications, while satisfying real-time constraints. Based on the interference analysis, we develop a co-scheduling technique that aims to minimize the resource usage. Compared to an existent technique that involves converting application graphs to real-time tasks, the proposed technique shows better results in terms of resource usage, especially when it is applied to applications with tight time constraints.
Real Time Pothole Detection System based on Video Data for Automatic Maintenance of Road Surface Distress
Jo, Youngtae ; Ryu, Seungki ;
KIISE Transactions on Computing Practices, volume 22, issue 1, 2016, Pages 8~19
DOI : 10.5626/KTCP.2016.22.1.8
Potholes are caused by the presence of water in the underlying soil structure, which weakens the road pavement by expansion and contraction of water at freezing and thawing temperatures. Recently, automatic pothole detection systems have been studied, such as vibration-based methods and laser scanning methods. However, the vibration-based methods have low detection accuracy and limited detection area. Moreover, the costs for laser scanning-based methods are significantly high. Thus, in this paper, we propose a new pothole detection system using a commercial black-box camera. Normally, the computing power of a commercial black-box camera is limited. Thus, the pothole detection algorithm should be designed to work with the embedded computing environment of a black-box camera. The designed pothole detection algorithm has been tested by implementing in a black-box camera. The experimental results are analyzed with specific evaluation metrics, such as sensitivity and precision. Our studies confirm that the proposed pothole detection system can be utilized to gather pothole information in real-time.
A GPU-enabled Face Detection System in the Hadoop Platform Considering Big Data for Images
Bae, Yuseok ; Park, Jongyoul ;
KIISE Transactions on Computing Practices, volume 22, issue 1, 2016, Pages 20~25
DOI : 10.5626/KTCP.2016.22.1.20
With the advent of the era of digital big data, the Hadoop platform has become widely used in various fields. However, the Hadoop MapReduce framework suffers from problems related to the increase of the name node's main memory and map tasks for the processing of large number of small files. In addition, a method for running C++-based tasks in the MapReduce framework is required in order to conjugate GPUs supporting hardware-based data parallelism in the MapReduce framework. Therefore, in this paper, we present a face detection system that generates a sequence file for images to process big data for images in the Hadoop platform. The system also deals with tasks for GPU-based face detection in the MapReduce framework using Hadoop Pipes. We demonstrate a performance increase of around 6.8-fold as compared to a single CPU process.
Migration Mechanism of Communication Process for Load Balancing and Accuracy Improvement
Lee, Shineun ; Yoon, Gunjae ; Choi, Hoon ;
KIISE Transactions on Computing Practices, volume 22, issue 1, 2016, Pages 26~31
DOI : 10.5626/KTCP.2016.22.1.26
Migrim(Migration enhanced Grid Middleware) is a communication middleware between embedded devices and multiple servers. In traditional client-server communication, users' requests are sent to and processed by a designated server even though the server may suffer from a heavy load. In addition, the designated server may not have proper information to process the user's request correctly. Proposed connection migration mechanism and transaction migration mechanism are designed to improve the performance and accuracy of request processing. The connection migration is a procedure for delegating a connection to another server, which results in a well-distributed balancing of load among the servers. The transaction migration is a procedure for delegating a transaction to another server, and improves the accuracy of response.
M2M Transformation Rules for Automatic Test Case Generation from Sequence Diagram
Kim, Jin-a ; Kim, Su Ji ; Seo, Yongjin ; Cheon, Eunyoung ; Kim, Hyeon Soo ;
KIISE Transactions on Computing Practices, volume 22, issue 1, 2016, Pages 32~37
DOI : 10.5626/KTCP.2016.22.1.32
In model-based testing using sequence diagrams, test cases are automatically derived from the sequence diagrams. For the generation of test cases, scenarios need to be found for representing as a sequence diagram, and to extract test paths satisfying the test coverage. However, it is hard to automatically extract test paths from the sequence diagram because a sequence diagram represents loop, opt, and alt information using CombinedFragments. To resolve this problem, we propose a transformation process that transforms a sequence diagram into an activity diagram which represents scenarios as a type of control flows. In addition, we generate test cases from the activity diagram by applying a test coverage concept. Finally, we present a case study for test cases generation from a sequence diagram.
Personalized Itinerary Recommendation System based on Stay Time
Park, Sehwa ; Park, Seog ;
KIISE Transactions on Computing Practices, volume 22, issue 1, 2016, Pages 38~43
DOI : 10.5626/KTCP.2016.22.1.38
Recent developments regarding transportation technology have positioned travel as a major leisure activity; however, trip-itinerary planning remains a challenging task for tourists due to the need to select Points of Interest (POI) for visits to unfamiliar cities. Meanwhile, due to the GPS functions on mobile devices such as smartphones and tablet PCs, it is now possible to collect a user's position in real time. Based on these circumstances, our research on an automatic itinerary-planning system to simplify the trip-planning process was conducted briskly. The existing studies that include research on itinerary schedules focus on an identification of the shortest path in consideration of cost and time constraints, or a recommendation of the most-popular travel route in the destination area; therefore, we propose a personalized itinerary-recommendation system for which the stay-time preference of the individual user is considered as part of the personalized service.
Data Replication and Migration Scheme for Load Balancing in Distributed Memory Environments
Choi, Kitae ; Yoon, Sangwon ; Park, Jaeyeol ; Lim, Jongtae ; Bok, Kyoungsoo ; Yoo, Jaesoo ;
KIISE Transactions on Computing Practices, volume 22, issue 1, 2016, Pages 44~49
DOI : 10.5626/KTCP.2016.22.1.44
Recently, data has been growing dramatically along with the growth of social media and digital devices. A distributed memory processing system has been used to efficiently process large amounts of data. However, if a load is concentrated in a certain node in distributed environments, a node performance significantly degrades. In this paper, we propose a load balancing scheme to distribute load in a distributed memory environment. The proposed scheme replicates hot data to multiple nodes for managing a node's load and migrates the data by considering the load of the nodes when nodes are added or removed. The client reduces the number of accesses to the central server by directly accessing the data node through the metadata information of the hot data. In order to show the superiority of the proposed scheme, we compare it with the existing load balancing scheme through performance evaluation.
VOC Summarization and Classification based on Sentence Understanding
Kim, Moonjong ; Lee, Jaean ; Han, Kyouyeol ; Ahn, Youngmin ;
KIISE Transactions on Computing Practices, volume 22, issue 1, 2016, Pages 50~55
DOI : 10.5626/KTCP.2016.22.1.50
To attain an understanding of customers' opinions or demands regarding a companies' products or service, it is important to consider VOC (Voice of Customer) data; however, it is difficult to understand contexts from VOC because segmented and duplicate sentences and a variety of dialog contexts. In this article, POS (part of speech) and morphemes were selected as language resources due to their semantic importance regarding documents, and based on these, we defined an LSP (Lexico-Semantic-Pattern) to understand the structure and semantics of the sentences and extracted summary by key sentences; furthermore the LSP was introduced to connect the segmented sentences and remove any contextual repetition. We also defined the LSP by categories and classified the documents based on those categories that comprise the main sentences matched by LSP. In the experiment, we classified the VOC-data documents for the creation of a summarization before comparing the result with the previous methodologies.
Evaluation of the Redundancy in Decoy Database Generation for Tandem Mass Analysis
Li, Honglan ; Liu, Duanhui ; Lee, Kiwook ; Hwang, Kyu-Baek ;
KIISE Transactions on Computing Practices, volume 22, issue 1, 2016, Pages 56~60
DOI : 10.5626/KTCP.2016.22.1.56
Peptide identification in tandem mass spectrometry is usually done by searching the spectra against target databases consisting of reference protein sequences. To control false discovery rates for high-confidence peptide identification, spectra are also searched against decoy databases constructed by permuting reference protein sequences. In this case, a peptide of the same sequence could be included in both the target and the decoy databases or multiple entries of a same peptide could exist in the decoy database. These phenomena make the protein identification problem complicated. Thus, it is important to minimize the number of such redundant peptides for accurate protein identification. In this regard, we examined two popular methods for decoy database generation: 'pseudo-shuffling' and 'pseudo-reversing'. We experimented with target databases of varying sizes and investigated the effect of the maximum number of missed cleavage sites allowed in a peptide (MC), which is one of the parameters for target and decoy database generation. In our experiments, the level of redundancy in decoy databases was proportional to the target database size and the value of MC, due to the increase in the number of short peptides (7 to 10 AA). Moreover, 'pseudo-reversing' always generated decoy databases with lower levels of redundancy compared to 'pseudo-shuffling'.