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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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KIPS Transactions on Software and Data Engineering
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Journal DOI :
Korea Information Processing Society
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Volume & Issues
Volume 3, Issue 12 - Dec 2014
Volume 3, Issue 11 - Nov 2014
Volume 3, Issue 10 - Oct 2014
Volume 3, Issue 9 - Sep 2014
Volume 3, Issue 8 - Aug 2014
Volume 3, Issue 7 - Jul 2014
Volume 3, Issue 6 - Jun 2014
Volume 3, Issue 5 - May 2014
Volume 3, Issue 4 - Apr 2014
Volume 3, Issue 3 - Mar 2014
Volume 3, Issue 2 - Feb 2014
Volume 3, Issue 1 - Jan 2014
Selecting the target year
Design of Checklist for Improvement of Reliability of Uncertainty and Variability Environment
Lee, Eun-Ser ;
KIPS Transactions on Software and Data Engineering, volume 3, issue 10, 2014, Pages 389~396
DOI : 10.3745/KTSDE.2014.3.10.389
There are many defects when we're working on a project. Especially, if we don't have experience in similar field, defects have a strong influence on the system entirely. Therefore, management of risk such like defects is important the factor for success of project. Finally, efficient management of risk can guarantee handling problems such like fault tolerancy, unexpected quality and delay of schedule. In this paper, we propose checkpoint for improvement of reliability and are willing to improve the reliability of an entire system using it.
Design and Implementation of a Large-Scale Spatial Reasoner Using MapReduce Framework
Nam, Sang Ha ; Kim, In Cheol ;
KIPS Transactions on Software and Data Engineering, volume 3, issue 10, 2014, Pages 397~406
DOI : 10.3745/KTSDE.2014.3.10.397
In order to answer the questions successfully on behalf of the human in DeepQA environments such as Jeopardy! of the American quiz show, the computer is required to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. In this paper, we present a scalable spatial reasoning algorithm for deriving efficiently new directional and topological relations using the MapReduce framework, one of well-known parallel distributed computing environments. The proposed reasoning algorithm assumes as input a large-scale spatial knowledge base including CSD-9 directional relations and RCC-8 topological relations. To infer new directional and topological relations from the given spatial knowledge base, it performs the cross-consistency checks as well as the path-consistency checks on the knowledge base. To maximize the parallelism of reasoning computations according to the principle of the MapReduce framework, we design the algorithm to partition effectively the large knowledge base into smaller ones and distribute them over multiple computing nodes at the map phase. And then, at the reduce phase, the algorithm infers the new knowledge from distributed spatial knowledge bases. Through experiments performed on the sample knowledge base with the MapReduce-based implementation of our algorithm, we proved the high performance of our large-scale spatial reasoner.
Korean Homograph Tagging Model based on Sub-Word Conditional Probability
Shin, Joon Choul ; Ock, Cheol Young ;
KIPS Transactions on Software and Data Engineering, volume 3, issue 10, 2014, Pages 407~420
DOI : 10.3745/KTSDE.2014.3.10.407
In general, the Korean morpheme analysis procedure is divided into two steps. In the first step as an ambiguity generation step, an Eojeol is analyzed into many morpheme sequences as candidates. In the second step, one appropriate candidate is chosen by using contextual information. Hidden Markov Model(HMM) is typically applied in the second step. This paper proposes Sub-word Conditional Probability(SCP) model as an alternate algorithm. SCP uses sub-word information of adjacent eojeol first. If it failed, then SCP use morpheme information restrictively. In the accuracy and speed comparative test, HMM's accuracy is 96.49% and SCP's accuracy is just 0.07% lower. But SCP reduced processing time 53%.
Diagnosis of Parkinson's Disease Using Two Types of Biomarkers and Characterization of Fiber Pathways
Kang, Shintae ; Lee, Wook ; Park, Byungkyu ; Han, Kyungsook ;
KIPS Transactions on Software and Data Engineering, volume 3, issue 10, 2014, Pages 421~428
DOI : 10.3745/KTSDE.2014.3.10.421
Like Alzheimer's disease, Parkinson's Disease(PD) is one of the most common neurodegenerative brain disorders. PD results from the deterioration of dopaminergic neurons in the brain region called the substantia nigra. Currently there is no cure for PD, but diagnosing in its early stage is important to provide treatments for relieving the symptoms and maintaining quality of life. Unlike many diagnosis methods of PD which use a single biomarker, we developed a diagnosis method that uses both biochemical biomarkers and imaging biomarkers. Our method uses
-synuclein protein levels in the cerebrospinal fluid and diffusion tensor images(DTI). It achieved an accuracy over 91.3% in the 10-fold cross validation, and the best accuracy of 72% in an independent testing, which suggests a possibility for early detection of PD. We also analyzed the characteristics of the brain fiber pathways of Parkinson's disease patients and normal elderly people.
A Novel Eyelashes Removal Method for Improving Iris Data Preservation Rate
Kim, Seong-Hoon ; Han, Gi-Tae ;
KIPS Transactions on Software and Data Engineering, volume 3, issue 10, 2014, Pages 429~440
DOI : 10.3745/KTSDE.2014.3.10.429
The iris recognition is a biometrics technology to extract and code an unique iris feature from human eye image. Also, it includes the technology to compare with other's various iris stored in the system. On the other hand, eyelashes in iris image are a external factor to affect to recognition rate of iris. If eyelashes are not removed exactly from iris area, there are two false recognitions that recognize eyelashes to iris features or iris features to eyelashes. Eventually, these false recognitions bring out a lot of loss in iris informations. In this paper, in order to solve that problems, we removed eyelashes by gabor filter that using for analysis of frequency feature and improve preservation rate of iris informations. By novel method to extract various features on iris area using angle, frequency, and gaussian parameter on gabor filter that is one of the filters for analysing frequency feature for an image, we could remove accurately eyelashes with various lengths and shapes. As the result, proposed method represents that improve about 4% than previous methods using GMM or histogram analysis in iris preservation rate.
The Stock Portfolio Recommendation System based on the Correlation between the Stock Message Boards and the Stock Market
Lee, Yun-Jung ; Kim, Gun-Woo ; Woo, Gyun ;
KIPS Transactions on Software and Data Engineering, volume 3, issue 10, 2014, Pages 441~450
DOI : 10.3745/KTSDE.2014.3.10.441
The stock market is constantly changing and sometimes the stock prices unaccountably plummet or surge. So, the stock market is recognized as a complex system and the change on the stock prices is unpredictable. Recently, many researchers try to understand the stock market as the network among individual stocks and to find a clue about the change of the stock prices from big data being created in real time from Internet. We focus on the correlation between the stock prices and the human interactions in Internet especially in the stock message boards. To uncover this correlation, we collected and investigated the articles concerning with 57 target companies, members of KOSPI200. From the analysis result, we found that there is no significant correlation between the stock prices and the article volume, but the strength of correlation between the article volume and the stock prices is relevant to the stock return. We propose a new method for recommending stock portfolio base on the result of our analysis. According to the simulated investment test using the article data from the stock message boards in 'Daum' portal site, the returns of our portfolio is about 1.55% per month, which is about 0.72% and 1.21% higher than that of the Markowitz's efficient portfolio and that of the KOSPI average respectively. Also, the case using the data from 'Naver' portal site, the stock returns of our proposed portfolio is about 0.90%, which is 0.35%, 0.40%, and 0.58% higher than those of our previous portfolio, Markowitz's efficient portfolio, and KOSPI average respectively. This study presents that collective human behavior on Internet stock message board can be much helpful to understand the stock market and the correlation between the stock price and the collective human behavior can be used to invest in stocks.
Spectral Perturbation of Theta and Alpha Wave for the Affective Auditory Stimuli
Du, Ruoyu ; Lee, Hyo Jong ;
KIPS Transactions on Software and Data Engineering, volume 3, issue 10, 2014, Pages 451~456
DOI : 10.3745/KTSDE.2014.3.10.451
The correlations between electroencephalographic (EEG) spectral power and emotional responses during affective sound clip listening are important parameters. Hemispheric asymmetry in prefrontal activation have been proposed in two decades ago, as measured by power value, is related to reactivity to affectively pleasure audio stimuli. In this study, we designed an emotional audio stimulus experiment in order to verify frontal EEG asymmetry by analyzing Event-related Spectral Perturbation (ERSP) results. Thirty healthy college male students volunteered the stimulus experiment with the standard IADS(International Affective Digital Sounds) clips. These affective sound clips are classified in three emotion states, high pleasure-high arousal (happy), middle pleasure-low arousal (neutral) and low pleasure-high arousal (fear). The analysis of the data was performed in both theta (4-8Hz) and alpha (8-13Hz) bands. ERSP maps in the alpha band revealed that there are the stronger power responses of high pleasure (happy) in the right frontal lobe, while the stronger power responses of middle-low pleasure (neutral and fear) in the left frontal lobe. Moreover, ERSP maps in the theta band revealed that there are the stronger power responses of high arousal (fear and happy) in the left pre-frontal lobe, while the stronger responses of low arousal (neutral) in the right pre-frontal lobe. However, the high pleasure emotions (happy) can elicit greater relative right EEG activity, while the low and middle pleasure emotions (fear and neutral) can elicit the greater relative left EEG activity. Additionally, the most differences of theta band have been found out in the medial frontal lobe, which is proved as the frontal midline theta. And there are the strongest responses of happy sounds in the alpha band around the whole frontal regions. These results are well suited for emotion recognition, and provide the evidences that theta and alpha powers may have the more important role in the emotion processing than previously believed.
Word Spell: Associative-Phonological Learning Method for Second Language Learners
Hong, Woneui ; Moon, Sungwon ; Gweon, Gahgene ;
KIPS Transactions on Software and Data Engineering, volume 3, issue 10, 2014, Pages 457~464
DOI : 10.3745/KTSDE.2014.3.10.457
Foreign language learners want to remember newly learned vocabularies for as long as possible. As demand for learning English as a second language grows, effective ways of memorizing English vocabularies also attract much interest so that various methods and apparatus are developed in order to support effective memorization. In this research, we introduce a new way of memorizing English vocabularies and evaluate the performance compared to an existing qualified method. Our study result shows that learners who memorize English words using our suggested method maintained a higher retention rate than those who studied using the existing method. From this research, we expect to gain new insights of effective way in learning English vocabularies.