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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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Korea Information Processing Society
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Volume & Issues
Volume 5, Issue 8 - Aug 2016
Volume 5, Issue 7 - Jul 2016
Volume 5, Issue 6 - Jun 2016
Volume 5, Issue 5 - May 2016
Volume 5, Issue 4 - Apr 2016
Volume 5, Issue 3 - Mar 2016
Volume 5, Issue 2 - Feb 2016
Volume 5, Issue 1 - Jan 2016
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A Study for Domain Categorization and Estimation of Complexity for Reliability Improvement of Domain Analysis
Lee, Eun-Ser ;
KIPS Transactions on Software and Data Engineering, volume 5, issue 1, 2016, Pages 1~6
DOI : 10.3745/KTSDE.2016.5.1.1
Domain analysis is an important component for reliability of development project. Domain analysis error have an effect in the whole system. As a result, the system reliability will be deteriorated. Therefore, we need a methodology to analyze domain characteristic for a reliable analysis in the domain analysis phase. In this paper, we propose a methodology for domain categorization and estimation of complexity for reliability improvement of domain analysis.
A Study for the Analysis of Domain for the Modeling of User Interface
Lee, Eun-Ser ;
KIPS Transactions on Software and Data Engineering, volume 5, issue 1, 2016, Pages 7~12
DOI : 10.3745/KTSDE.2016.5.1.7
User interface is important of programs collaboration. User interface error have a effect in the whole system. As a result, the system reliability will deteriorate. Therefore, we are need to methodology that user interface type is analyze for a reliable analysis in the domain analysis phase. In this paper, we are propose the methodology that extraction and standard of user interface for reliability improvement of domain analysis.
Design of the 3D Object Recognition System with Hierarchical Feature Learning
Kim, Joohee ; Kim, Dongha ; Kim, Incheol ;
KIPS Transactions on Software and Data Engineering, volume 5, issue 1, 2016, Pages 13~20
DOI : 10.3745/KTSDE.2016.5.1.13
In this paper, we propose an object recognition system that can effectively find out its category, its instance name, and several attributes from the color and depth images of an object with hierarchical feature learning. In the preprocessing stage, our system transforms the depth images of the object into the surface normal vectors, which can represent the shape information of the object more precisely. In the feature learning stage, it extracts a set of patch features and image features from a pair of the color image and the surface normal vector through two-layered learning. And then the system trains a set of independent classification models with a set of labeled feature vectors and the SVM learning algorithm. Through experiments with UW RGB-D Object Dataset, we verify the performance of the proposed object recognition system.
Three-Phase English Syntactic Analysis for Improving the Parsing Efficiency
Kim, Sung-Dong ;
KIPS Transactions on Software and Data Engineering, volume 5, issue 1, 2016, Pages 21~28
DOI : 10.3745/KTSDE.2016.5.1.21
The performance of an English-Korean machine translation system depends heavily on its English parser. The parser in this paper is a part of the rule-based English-Korean MT system, which includes many syntactic rules and performs the chart-based parsing. The parser generates too many structures due to many syntactic rules, so much time and memory are required. The rule-based parser has difficulty in analyzing and translating the long sentences including the commas because they cause high parsing complexity. In this paper, we propose the 3-phase parsing method with sentence segmentation to efficiently translate the long sentences appearing in usual. Each phase of the syntactic analysis applies its own independent syntactic rules in order to reduce parsing complexity. For the purpose, we classify the syntactic rules into 3 classes and design the 3-phase parsing algorithm. Especially, the syntactic rules in the 3rd class are for the sentence structures composed with commas. We present the automatic rule acquisition method for 3rd class rules from the syntactic analysis of the corpus, with which we aim to continuously improve the coverage of the parsing. The experimental results shows that the proposed 3-phase parsing method is superior to the prior parsing method using only intra-sentence segmentation in terms of the parsing speed/memory efficiency with keeping the translation quality.
Study on the Illocutionary Effect-Based FIPA-ACL Semantics
Koo, Ja Rok ;
KIPS Transactions on Software and Data Engineering, volume 5, issue 1, 2016, Pages 29~34
DOI : 10.3745/KTSDE.2016.5.1.29
One of the most important aspects of the research on multi-agent systems is the definition of agent communication languages(ACLs) and the specification of a proper formal semantics of ACLs. In this paper, we propose an illocutionary effect-based FIPA-ACL semantics which overcomes the two traditional semantic approaches. The key idea of this new semantics is based on the semantic concepts of success and satisfaction conditions of illocutionary acts in speech act theory, and the common ground theory-based framework. As case studies using this new semantics, we define the primitive speech acts of FIPA-ACL such as inform and request. For the strengths of the proposed approach we illustrate our new semantics on an e-commerce agent purchase negotiation. Also, we compare this approach with two traditional semantic approaches for ACLs.
A Fast Way for Alignment Marker Detection and Position Calibration
Moon, Chang Bae ; Kim, HyunSoo ; Kim, HyunYong ; Lee, Dongwon ; Kim, Tae-Hoon ; Chung, Hae ; Kim, Byeong Man ;
KIPS Transactions on Software and Data Engineering, volume 5, issue 1, 2016, Pages 35~42
DOI : 10.3745/KTSDE.2016.5.1.35
The core of the machine vision that is frequently used at the pre/post-production stages is a marker alignment technology. In this paper, a method to detect the angle and position of a product at high speed by use of a unique pattern present in the marker stamped on the product, and calibrate them is proposed. In the proposed method, to determine the angle and position of a marker, the candidates of the marker are extracted by using a variation of the integral histogram, and then clustering is applied to reduce the candidates. The experimental results revealed about 5s 719ms improvement in processing time and better precision in detecting the rotation angle of a product.
A Study on Appearance-Based Facial Expression Recognition Using Active Shape Model
Kim, Dong-Ju ; Shin, Jeong-Hoon ;
KIPS Transactions on Software and Data Engineering, volume 5, issue 1, 2016, Pages 43~50
DOI : 10.3745/KTSDE.2016.5.1.43
This paper introduces an appearance-based facial expression recognition method using ASM landmarks which is used to acquire a detailed face region. In particular, EHMM-based algorithm and SVM classifier with histogram feature are employed to appearance-based facial expression recognition, and performance evaluation of proposed method was performed with CK and JAFFE facial expression database. In addition, performance comparison was achieved through comparison with distance-based face normalization method and a geometric feature-based facial expression approach which employed geometrical features of ASM landmarks and SVM algorithm. As a result, the proposed method using ASM-based face normalization showed performance improvements of 6.39% and 7.98% compared to previous distance-based face normalization method for CK database and JAFFE database, respectively. Also, the proposed method showed higher performance compared to geometric feature-based facial expression approach, and we confirmed an effectiveness of proposed method.