• Title/Summary/Keyword: Software classification

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Creative Resolution for Requirement Conflict Using Conflict Resolution Theory of TRIZ (TRIZ의 모순 해결 이론을 이용한 창의적 요구사항 충돌 해결)

  • Jung, Ji-Young;Kim, Jin-Tae;Park, Soo-Yong
    • Journal of KIISE:Software and Applications
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    • v.37 no.5
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    • pp.411-415
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    • 2010
  • The Conflicts between requirements may cause a failure of functions or even project. Currently, most of researches have focused on identifying requirements and some researchers have tried to resolve requirements conflicts but it was only based on requirement priority. This paper proposes the Creative Requirements Conflict Resolution (CRRC) to resolve requirement conflicts in a creative way using TRIZ methodology. TRIZ, which means the theory of solving inventor's problems, is made based on the analysis of over 2 million patent cases and helpful for developing a creative solution to resolve conflicts. CRRC classifies requirement conflicts into groups and then apply TRIZ theory related to each group. At the result of control experiment, CRRC provides the various kinds of creative solution for requirement conflicts.

Extensions of LDA by PCA Mixture Model and Class-wise Features (PCA 혼합 모형과 클래스 기반 특징에 의한 LDA의 확장)

  • Kim Hyun-Chul;Kim Daijin;Bang Sung-Yang
    • Journal of KIISE:Software and Applications
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    • v.32 no.8
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    • pp.781-788
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    • 2005
  • LDA (Linear Discriminant Analysis) is a data discrimination technique that seeks transformation to maximize the ratio of the between-class scatter and the within-class scatter While it has been successfully applied to several applications, it has two limitations, both concerning the underfitting problem. First, it fails to discriminate data with complex distributions since all data in each class are assumed to be distributed in the Gaussian manner; and second, it can lose class-wise information, since it produces only one transformation over the entire range of classes. We propose three extensions of LDA to overcome the above problems. The first extension overcomes the first problem by modeling the within-class scatter using a PCA mixture model that can represent more complex distribution. The second extension overcomes the second problem by taking different transformation for each class in order to provide class-wise features. The third extension combines these two modifications by representing each class in terms of the PCA mixture model and taking different transformation for each mixture component. It is shown that all our proposed extensions of LDA outperform LDA concerning classification errors for handwritten digit recognition and alphabet recognition.

Geometrical Feature-Based Detection of Pure Facial Regions (기하학적 특징에 기반한 순수 얼굴영역 검출기법)

  • 이대호;박영태
    • Journal of KIISE:Software and Applications
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    • v.30 no.7_8
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    • pp.773-779
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    • 2003
  • Locating exact position of facial components is a key preprocessing for realizing highly accurate and reliable face recognition schemes. In this paper, we propose a simple but powerful method for detecting isolated facial components such as eyebrows, eyes, and a mouth, which are horizontally oriented and have relatively dark gray levels. The method is based on the shape-resolving locally optimum thresholding that may guarantee isolated detection of each component. We show that pure facial regions can be determined by grouping facial features satisfying simple geometric constraints on unique facial structure. In the test for over 1000 images in the AR -face database, pure facial regions were detected correctly for each face image without wearing glasses. Very few errors occurred in the face images wearing glasses with a thick frame because of the occluded eyebrow -pairs. The proposed scheme may be best suited for the later stage of classification using either the mappings or a template matching, because of its capability of handling rotational and translational variations.

Gale Disaster Damage Investigation Process Provement Plan according to Correlation Analysis between Wind Speed and Damage Cost -Centering on Disaster Year Book- (풍속과 피해액 간 상관관계분석에 따른 강풍재해피해조사 프로세스 개선방안 -재해연보를 중심으로-)

  • Song, Chang Young;Yang, Byong Soo
    • Journal of the Korean Society of Safety
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    • v.31 no.2
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    • pp.119-126
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    • 2016
  • Across the world, the industrialization has increased the frequency of climate anomaly. The size of damage due to recent natural disasters is growing large and fast, and the human damage and economic loss due to disasters are consistently increasing. Urbanization has a structure vulnerable to natural disasters. Therefore, in order to reduce damage from natural disasters, both hardware and software approaches should be utilized. Currently, however, the development of a statistical access process for 'analysis of disaster occurrence factor' and 'prediction of damage costs' for disaster prevention and overall disaster management is inadequate. In case of local governments, overall disaster management system is not established, or even if it is established, unscientific classification system and management lead to low utility of natural statistics of disaster year book. Therefore, in order to minimize disaster damage and for rational disaster management, the disaster damage survey process should be improved. This study selected gale as the focused analysis target among natural disasters recorded in disaster year book such as storm, torrential rain, gale, high seas, and heavy snow, and analyzed disaster survey process. Based on disaster year book, the gale damage size was analyzed and the issues occurring from the correlation of gale and damage amount were examined, so as to suggest an improvement plan for reliable natural disaster information collection and systematic natural disaster damage survey.

Flight Range and Time Analysis for Classification of eVTOL PAV (eVTOL PAV 유형별 항속거리 및 항속시간 분석)

  • Lee, Bong-Sul;Yun, Ju-Yeol;Hwang, Ho-Yon
    • Journal of Advanced Navigation Technology
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    • v.24 no.2
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    • pp.73-84
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    • 2020
  • To overcome ground congestions due to growing number of cars, a lot of companies have proposed personal aerial vehicle (PAV). Among PAV, electric vertical take-off and landing (eVTOL) aircrafts capable of vertical take-off and landing with electric power are drawing attention, and their configurations vary from multicopters to tilt ducted fans. This study tries to analyze the characteristics of each eVTOL design configurations. Parasite drag was calculated using component build up method for Vahana, Aurora, Volocopter representing each eVTOL PAV type of tilt-wing, compound, and multicopter. Wetted area and induced drag was calculated using OpenVSP and XFLR5 that are aircraft design and aerodynamic analysis software. The batteries used in the eVTOL PAV was assumed as Tesla 2170 batteries and flight ranges were calculated. Also, energy consumption and maximum flight time for the given mission profile including take-off and landing, cruising segments were compared for each eVTOL.

Comparison of External Information Performance Predicting Subcellular Localization of Proteins (단백질의 세포내 위치를 예측하기 위한 외부정보의 성능 비교)

  • Chi, Sang-Mun
    • Journal of KIISE:Software and Applications
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    • v.37 no.11
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    • pp.803-811
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    • 2010
  • Since protein subcellular location and biological function are highly correlated, the prediction of protein subcellular localization can provide information about the function of a protein. In order to enhance the prediction performance, external information other than amino acids sequence information is actively exploited in many researches. This paper compares the prediction capabilities resided in amino acid sequence similarity, protein profile, gene ontology, motif, and textual information. In the experiments using PLOC dataset which has proteins less than 80% sequence similarity, sequence similarity information and gene ontology are effective information, achieving a classification accuracy of 94.8%. In the experiments using BaCelLo IDS dataset with low sequence similarity less than 30%, using gene ontology gives the best prediction accuracies, 93.2% for animals and 86.6% for fungi.

The Object-Oriented Class Hierarchy Structure Design Method using the Rapid Prototyping Techniques (래피드 프로토토입핑 기법을 사용한 객체 지향 클래스 계층 구조 설계 방법)

  • Heo, Kwae-Bum;Choi, Young-Eun
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.1
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    • pp.86-96
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    • 1998
  • The class hierarchy structure in an object-oriented design model is effective to the software reusabilily and lhe design of complex syslem. This paper suggests lhe objecl-orienled class hierarchy structure design melhod using lhe rapid prololyping lechniques. In this method, relationship recognition and similarity are estimated by the new class classification in object modeling level. Then lhe estimation of aUribute and method in class is needed. Each design module such as class hierarchy struclure which is generaled wilh inleractive and repealed work consisls of reference relationship, inheritance relationship and composite relationship. These information are slored in lhe table to maintenance lhe program and implementation, the class relationship is represented with graph and the node class is iconized. This method is effective in reslructuring of class hierarchy are reusing of design information, because of addition of new class and deletion with ease. The efficiency of syslem analysis, design and implementation is enhanced by converting into prololype system and real system.

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Detection of Direction Indicators on Road Surfaces Using Inverse Perspective Mapping and NN (원근투영법과 신경망을 이용한 도로노면 방향지시기호 검출 연구)

  • Kim, Jong Bae
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.4
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    • pp.201-208
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    • 2015
  • This paper proposes a method for detecting the direction indicator shown in the road surface efficiently from the black box system installed on the vehicle. In the proposed method, the direction indicators are detected by inverse perspective mapping(IPM) and bag of visual features(BOF)-based NN classifier. In order to apply the proposed method to real-time environments, the candidated regions of direction indicator in an image only performs IPM, and BOF-based NN is used for the classification of feature information from direction indicators. The results of applying the proposed method to the road surface direction indicators detection and recognition, the detection accuracy was presented at least about 89%, and the method presents a relatively high detection rate in the various road conditions. Thus it can be seen that the proposed method is applied to safe driving support systems available.

Development of Feature Extraction Algorithm for Finger Vein Recognition (지정맥 인식을 위한 특징 검출 알고리즘 개발)

  • Kim, Taehoon;Lee, Sangjoon
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.9
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    • pp.345-350
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    • 2018
  • This study is an algorithm for detecting vein pattern features important for finger vein recognition. The feature detection algorithm is important because it greatly affects recognition results in pattern recognition. The recognition rate is degraded because the reference is changed according to the finger position change. In addition, the image obtained by irradiating the finger with infrared light is difficult to separate the image background and the blood vessel pattern, and the detection time is increased because the image preprocessing process is performed. For this purpose, the presented algorithm can be performed without image preprocessing, and the detection time can be reduced. SWDA (Down Slope Trace Waveform) algorithm is applied to the finger vein images to detect the fingertip position and vein pattern. Because of the low infrared transmittance, relatively dark vein images can be detected with minimal detection error. In addition, the fingertip position can be used as a reference in the classification stage to compensate the decrease in the recognition rate. If we apply algorithms proposed to various recognition fields such as palm and wrist, it is expected that it will contribute to improvement of biometric feature detection accuracy and reduction of recognition performance time.

Implementation for Texture Imaging Algorithm based on GLCM/GLDV and Use Case Experiments with High Resolution Imagery

  • Jeon So Hee;Lee Kiwon;Kwon Byung-Doo
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.626-629
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    • 2004
  • Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program for GLCM algorithm is newly implemented in the MS Visual IDE environment. While, additional texture imaging modules based on GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV texture variables, it composed of six types of second order texture function in the several quantization levels of 2(binary image), 8, and 16: Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality, four directions are provided as $E-W(0^{\circ}),\;N-E(45^{\circ}),\;S-W(135^{\circ}),\;and\;N-S(90^{\circ}),$ and W-E direction is also considered in the negative direction of E- W direction. While, two direction modes are provided in this program: Omni-mode and Circular mode. Omni-mode is to compute all direction to avoid directionality problem, and circular direction is to compute texture variables by circular direction surrounding target pixel. At the second phase of this study, some examples with artificial image and actual satellite imagery are carried out to demonstrate effectiveness of texture imaging or to help texture image interpretation. As the reference, most previous studies related to texture image analysis have been used for the classification purpose, but this study aims at the creation and general uses of texture image for urban remote sensing.

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