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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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Surveillance Video Summarization System based on Multi-person Tracking Status
Yoo, Ju Hee ; Lee, Kyoung Mi ;
KIISE Transactions on Computing Practices, volume 22, issue 2, 2016, Pages 61~68
DOI : 10.5626/KTCP.2016.22.2.61
Surveillance cameras have been installed in many places because security and safety has become an important issue in modern society. However, watching surveillance videos and judging accidental situations is very labor-intensive and time-consuming. So now, requests for research to automatically analyze the surveillance videos is growing. In this paper, we propose a surveillance system to track multiple persons in videos and to summarize the videos based on tracking information. The proposed surveillance summarization system applies an adaptive illumination correction, subtracts the background, detects multiple persons, tracks the persons, and saves their tracking information in a database. The tracking information includes tracking one's path, their movement status, length of staying time at the location, enterance/exit times, and so on. The movement status is classified into six statuses(Enter, Stay, Slow, Normal, Fast, and Exit). This proposed summarization system provides a person's status as a graph in time and space and helps to quickly determine the status of the tracked person.
Speech Recognition for the Korean Vowel 'ㅣ' based on Waveform-feature Extraction and Neural-network Learning
Rho, Wonbin ; Lee, Jongwoo ; Lee, Jaewon ;
KIISE Transactions on Computing Practices, volume 22, issue 2, 2016, Pages 69~76
DOI : 10.5626/KTCP.2016.22.2.69
With the recent increase of the interest in IoT in almost all areas of industry, computing technologies have been increasingly applied in human environments such as houses, buildings, cars, and streets; in these IoT environments, speech recognition is being widely accepted as a means of HCI. The existing server-based speech recognition techniques are typically fast and show quite high recognition rates; however, an internet connection is necessary, and complicated server computing is required because a voice is recognized by units of words that are stored in server databases. This paper, as a successive research results of speech recognition algorithms for the Korean phonemic vowel 'ㅏ', 'ㅓ', suggests an implementation of speech recognition algorithms for the Korean phonemic vowel 'ㅣ'. We observed that almost all of the vocal waveform patterns for 'ㅣ' are unique and different when compared with the patterns of the 'ㅏ' and 'ㅓ' waveforms. In this paper we propose specific waveform patterns for the Korean vowel 'ㅣ' and the corresponding recognition algorithms. We also presents experiment results showing that, by adding neural-network learning to our algorithm, the voice recognition success rate for the vowel 'ㅣ' can be increased. As a result we observed that 90% or more of the vocal expressions of the vowel 'ㅣ' can be successfully recognized when our algorithms are used.
The Development of the Korean Medicine Symptom Diagnosis System Using Morphological Analysis to Refine Difficult Medical Terminology
Lee, Sang-Baek ; Son, Yun-Hee ; Jang, Hyun-Chul ; Lee, Kyu-Chul ;
KIISE Transactions on Computing Practices, volume 22, issue 2, 2016, Pages 77~82
DOI : 10.5626/KTCP.2016.22.2.77
This paper presents the development of the Korean medicine symptom diagnosis system. In the Korean medicine symptom diagnosis system, the patient explains their symptoms and an oriental doctor makes a diagnosis based on the symptoms. Natural language processing is required to make a diagnosis automatically through the patients' reports of symptoms. We use morphological analysis to get understandable information from the natural language itself. We developed a diagnosis system that consists of NoSQL document-oriented databases-MongoDB. NoSQL has better performance at unstructured and semi-structured data, rather than using Relational Databases. We collect patient symptom reports in MongoDB to refine difficult medical terminology and provide understandable terminology to patients.
Subtopic Mining of Two-level Hierarchy Based on Hierarchical Search Intentions and Web Resources
Kim, Se-Jong ; Lee, Jong-Hyeok ;
KIISE Transactions on Computing Practices, volume 22, issue 2, 2016, Pages 83~88
DOI : 10.5626/KTCP.2016.22.2.83
Subtopic mining is the extraction and ranking of possible subtopics, which disambiguate and specify the search intentions of an input query in terms of relevance, popularity, and diversity. This paper describes the limitations of previous studies on the utilization of web resources, and proposes a subtopic mining method with a two-level hierarchy based on hierarchical search intentions and web resources, in order to overcome these limitations. Considering the characteristics of resources provided by the official subtopic mining task, we extract various second-level subtopics reflecting hierarchical search intentions from web documents, and expand and re-rank them using other provided resources. Terms in subtopics with wider search intentions are used to generate first-level subtopics. Our method performed better than state-of-the-art methods in almost every aspect.
Effects of Hypervisor on Distributed Big Data Processing in Virtualizated Cluster Environment
Chung, Haejin ; Nah, Yunmook ;
KIISE Transactions on Computing Practices, volume 22, issue 2, 2016, Pages 89~94
DOI : 10.5626/KTCP.2016.22.2.89
Recently, cluster computing environments have been in a process of change toward virtualized cluster environments. The change of the cluster environment has great impact on the performance of large volume distributed processing. Therefore, many domestic and international IT companies have invested heavily in research on cluster environments. In this paper, we show how the hypervisor affects the performance of distributed processing of a large volume of data. We present a performance comparison of MapReduce processing in two virtualized cluster environments, one built using the Xen hypervisor and the other built using the container-based Docker. Our results show that Docker is faster than Xen.
Performance Optimization in GlusterFS on SSDs
Kim, Deoksang ; Eom, Hyeonsang ; Yeom, Heonyoung ;
KIISE Transactions on Computing Practices, volume 22, issue 2, 2016, Pages 95~100
DOI : 10.5626/KTCP.2016.22.2.95
In the current era of big data and cloud computing, the amount of data utilized is increasing, and various systems to process this big data rapidly are being developed. A distributed file system is often used to store the data, and glusterFS is one of popular distributed file systems. As computer technology has advanced, NAND flash SSDs (Solid State Drives), which are high performance storage devices, have become cheaper. For this reason, datacenter operators attempt to use SSDs in their systems. They also try to install glusterFS on SSDs. However, since the glusterFS is designed to use HDDs (Hard Disk Drives), when SSDs are used instead of HDDs, the performance is degraded due to structural problems. The problems include the use of I/O-cache, Read-ahead, and Write-behind Translators. By removing these features that do not fit SSDs which are advantageous for random I/O, we have achieved performance improvements, by up to 255% in the case of 4KB random reads, and by up to 50% in the case of 64KB random reads.
A Distributed Power Control Algorithm for Data Load Balancing with Coverage in Dynamic Femtocell Networks
Shin, Donghoon ; Choi, Sunghee ;
KIISE Transactions on Computing Practices, volume 22, issue 2, 2016, Pages 101~106
DOI : 10.5626/KTCP.2016.22.2.101
A femtocell network has been attracting attention as a promising solution for providing high data rate transmission over the conventional cellular network in an indoor environment. In this paper, we propose a distributed power control algorithm considering both indoor coverage and data load balancing in the femtocell network. As data traffic varies by time and location according to user distribution, each femto base station suffers from an unbalanced data load, which may degrade network performance. To distribute the data load, the base stations are required to adjust their transmission power dynamically. Since there are a number of base stations in practice, we propose a distributed power control algorithm. In addition, we propose the simple algorithm to detect the faulty base station and to recover coverage. We also explain how to insert a new base station into a deployed network. We present the simulation results to evaluate the proposed algorithms.
Word Sense Disambiguation of Predicate using Semi-supervised Learning and Sejong Electronic Dictionary
Kang, Sangwook ; Kim, Minho ; Kwon, Hyuk-chul ; Oh, Jyhyun ;
KIISE Transactions on Computing Practices, volume 22, issue 2, 2016, Pages 107~112
DOI : 10.5626/KTCP.2016.22.2.107
The Sejong Electronic(machine-readable) Dictionary, developed by the 21st century Sejong Plan, contains systematically organized information on Korean words. It helps to solve problems encountered in the electronic formatting of the still-commonly-used hard-copy dictionary. The Sejong Electronic Dictionary, however has a limitation relate to sentence structure and selection-restricted nouns. This paper discuses the limitations of word-sense disambiguation(WSD) that uses subcategorization information suggested by the Sejong Electronic Dictionary and generalized selection-restricted nouns from the Korean Lexico-semantic network. An alternative method that utilized semi-supervised learning, the chi-square test and some other means to make WSD decisions is presented herein.
Constructing Effective Smart Crosswalk Traffic Light Mechanism Through Simulation Technique
Lee, Hyeonjun ; Moon, Soyoung ; Kim, R.Youngchul ; Son, Hyeonseung ;
KIISE Transactions on Computing Practices, volume 22, issue 2, 2016, Pages 113~118
DOI : 10.5626/KTCP.2016.22.2.113
The walking speed of handicapped people generally is slower than that of normal people. So it is difficult for them to cross at crosswalks within the allotted time provided by the traffic light. This problem can be solved by expanding the time of the traffic light. However, if the latency of the traffic light is increased without distinguishing the handicapped among all other pedestrians, the efficiency of traffic signal lights will decrease. In this paper, we propose a smart traffic signal connecting mechanism between the previous pedestrian traffic signal and a pedestrian's device (smartphone). This Smart pedestrian traffic light, through this mechanism, minimizes traffic congestion by providing additional walking time only to the handicapped among pedestrians. This crosswalk traffic light recognizes the handicapped using a technique called Internet of things (IOT). In this paper, we extract the data necessary to build an effective smart crosswalk traffic light mechanism through simulation techniques. We have extracted different kinds of traffic signal times with our virtual simulation environment to verify the efficiency of the smart crosswalk pedestrian traffic light system. This approach can validate the effective delay time of the traffic signal time through a comparison based on number of pedestrians.