• Title/Summary/Keyword: Intelligent Techniques

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Intelligent Tuning Of a PID Controller Using Immune Algorithm (면역 알고리즘을 이용한 PID 제어기의 지능 튜닝)

  • Kim, Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.1
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    • pp.8-17
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    • 2002
  • This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

Multimodal biometrics system using PDA under ubiquitous environments (유비쿼터스 환경에서 PDA를 이용한 다중생체인식 시스템 구현)

  • Kwon Man-Jun;Yang Dong-Hwa;Kim Yong-Sam;Lee Dae-Jong;Chun Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.4
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    • pp.430-435
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    • 2006
  • In this paper, we propose a method based on multimodal biometrics system using the face and signature under ubiquitous computing environments. First, the face and signature images are obtained by PDA and then these images with user ID and name are transmitted via WLAN(Wireless LAN) to the server and finally the PDA receives verification result from the server. The multimodal biometrics recognition system consists of two parts. In client part located in PDA, user interface program executes the user registration and verification process. The server consisting of the PCA and LDA algorithm shows excellent face recognition performance and the signature recognition method based on the Kernel PCA and LDA algorithm for signature image projected to vertical and horizontal axes by grid partition method. The proposed algorithm is evaluated with several face and signature images and shows better recognition and verification results than previous unimodal biometrics recognition techniques.

3D Object Restoration and Data Compression Based on Adaptive Simplex-Mesh Technique (적응 Simplex-Mesh 기술에 기반한 3차원 물체 복원과 자료 압축)

  • 조용군
    • Journal of the Korean Institute of Intelligent Systems
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    • v.9 no.4
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    • pp.436-443
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    • 1999
  • Most of the 3D object reconstruction techniques divide the object into multiplane and approximate the surfaces of the object. The Marching Cubes Algorithm which initializes the mesh structure using a given isovalue. and Delaunay Tetrahedrisation are widely used. Deformable models are well-suited for general object reconstruction because they make little assumptions about the shape to recover and they can reconstruct objects *om various types of datasets. Now, many researchers are studying the reconstruction systems based on a deformable model. In this paper, we propose a novel method for reconstruction of 3D objects. This method, for a 3D object composed of curved planes, compresses the 3D object based on the adaptive simplexmesh technique. It changes the pre-defined mesh structure, so that it may approach to the original object. Also, we redefine the geometric characteristics such as curvatures. As results of simulations, we show reconstruction of the original object with high compression and concentration of vertices towards parts of high curvature in order to optimize the shape description.

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Intelligent System Design for Knowledge Representation and Interpretation of Human Cognition (인간 인지 지식의 표현과 해석을 위한 지능형 시스템 설계 방법)

  • Joo, Young-Do
    • Journal of Korea Society of Industrial Information Systems
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    • v.16 no.3
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    • pp.11-21
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    • 2011
  • The development of computer-based modeling system has allowed the operationalization of cognitive science issues. Human cognition has become one of most interesting research subjects in artificial intelligence to emulate human mentality and behavior. This paper introduces a methodology well-suited for designing the intelligent system of human cognition. The research investigates how to elicit and represent cognitive knowledge obtained from individual city-dwellers through the application of fuzzy relational theory to personal construct theory. Crucial to this research is to implement formally and process interpretatively the psychological cognition of urbanites who interact with their environment in order to offer useful advice on urban problem. What is needed is a techniques to analyze cognitive structures which are embodiments of this perceptive knowledge for human being.

Issue-Tree and QFD Analysis of Transportation Safety Policy with Autonomous Vehicle (Issue-Tree기법과 QFD를 이용한 자율주행자동차 교통안전정책과제 분석)

  • Nam, Doohee;Lee, Sangsoo;Kim, Namsun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.4
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    • pp.26-32
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    • 2016
  • An autonomous car(driverless car, self-driving car, robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Autonomous cars can detect surroundings using a variety of techniques such as radar, lidar, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Autonomous cars have control systems that are capable of analyzing sensory data to distinguish between different cars on the road, which is very useful in planning a path to the desired destination. An issue tree, also called a logic tree, is a graphical breakdown of a question that dissects it into its different components vertically and that progresses into details as it reads to the right.Issue trees are useful in problem solving to identify the root causes of a problem as well as to identify its potential solutions. They also provide a reference point to see how each piece fits into the whole picture of a problem. Using Issue-Tree menthods, transportation safety policies were developed with autonompus vehicle in mind.

A Study on Injury Severity Prediction for Car-to-Car Traffic Accidents (차대차 교통사고에 대한 상해 심각도 예측 연구)

  • Ko, Changwan;Kim, Hyeonmin;Jeong, Young-Seon;Kim, Jaehee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.4
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    • pp.13-29
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    • 2020
  • Automobiles have long been an essential part of daily life, but the social costs of car traffic accidents exceed 9% of the national budget of Korea. Hence, it is necessary to establish prevention and response system for car traffic accidents. In order to present a model that can classify and predict the degree of injury in car traffic accidents, we used big data analysis techniques of K-nearest neighbor, logistic regression analysis, naive bayes classifier, decision tree, and ensemble algorithm. The performances of the models were analyzed by using the data on the nationwide traffic accidents over the past three years. In particular, considering the difference in the number of data among the respective injury severity levels, we used down-sampling methods for the group with a large number of samples to enhance the accuracy of the classification of the models and then verified the statistical significance of the models using ANOVA.

Performance Improvement of Human Detection in Thermal Images using Principal Component Analysis and Blob Clustering (주성분 분석과 Blob 군집화를 이용한 열화상 사람 검출 시스템의 성능 향상)

  • Jo, Ahra;Park, Jeong-Sik;Seo, Yong-Ho;Jang, Gil-Jin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.2
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    • pp.157-163
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    • 2013
  • In this paper, we propose a human detection technique using thermal imaging camera. The proposed method is useful at night or rainy weather where a visible light imaging cameras is not able to detect human activities. Under the observation that a human is usually brighter than the background in the thermal images, we estimate the preliminary human regions using the statistical confidence measures in the gray-level, brightness histogram. Afterwards, we applied Gaussian filtering and blob labeling techniques to remove the unwanted noise, and gather the scattered of the pixel distributions and the center of gravities of the blobs. In the final step, we exploit the aspect ratio and the area on the unified object region as well as a number of the principal components extracted from the object region images to determine if the detected object is a human. The experimental results show that the proposed method is effective in environments where visible light cameras are not applicable.

Digital Forensics Ontology for Intelligent Crime Investigation System (지능형 범죄수사 시스템을 위한 범용 디지털포렌식 온톨로지)

  • Yun, Han-Kuk;Lee, Sang-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.12
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    • pp.161-169
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    • 2014
  • Digital forensics is the process of proving criminal charges by collecting and analyzing digital evidence which is related to the crime in question. Most digital forensic research is focused on digital forensic techniques themselves or cyber crime. In this paper, we designed a digital forensics-criminal investigation linked model in order to effectively apply digital forensics to various types of criminal investigations. Digital forensic ontology was developed based on this model. For more effective application of digital forensics to criminal investigation we derived specific application fields. The ontology has legality rules and adequacy rules, so it can support investigative decision-making. The ontology can be developed into an intelligent criminal investigation system.

A Development of The Road Surface Decision Algorithm Using SVM(Support Vector Machine) Clustering Methods (SVM(Support Vector Machine) 기법을 활용한 노면상태 판별 알고리즘 개발)

  • Kim, Jong Hoon;Won, Jae Moo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.5
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    • pp.1-12
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    • 2013
  • Road's accidents caused by Ice, snow, Wet of roads surface conditions and weather conditions situations that are constantly occurring. That is, driver's negligence and safe driving ability of individuals due to lack of awareness, and Road management main agent(the government and the public, etc.) due to road conditions, if there is insufficient information. So Related research needs is a trend that is required. In this study, gather Camera(Stereo camera)'s image data, and analysis polarization coefficients and wavelet transform. And unlike traditional single-dimensional classification algorithms as multi-dimensional analysis by using SVM classification techniques, develop an algorithm to determine road conditions. Four on the road conditions (dry, wet, snow, ice) recognition success rate for the detection and analysis of experiments.

PubMine: An Ontology-Based Text Mining System for Deducing Relationships among Biological Entities

  • Kim, Tae-Kyung;Oh, Jeong-Su;Ko, Gun-Hwan;Cho, Wan-Sup;Hou, Bo-Kyeng;Lee, Sang-Hyuk
    • Interdisciplinary Bio Central
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    • v.3 no.2
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    • pp.7.1-7.6
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    • 2011
  • Background: Published manuscripts are the main source of biological knowledge. Since the manual examination is almost impossible due to the huge volume of literature data (approximately 19 million abstracts in PubMed), intelligent text mining systems are of great utility for knowledge discovery. However, most of current text mining tools have limited applicability because of i) providing abstract-based search rather than sentence-based search, ii) improper use or lack of ontology terms, iii) the design to be used for specific subjects, or iv) slow response time that hampers web services and real time applications. Results: We introduce an advanced text mining system called PubMine that supports intelligent knowledge discovery based on diverse bio-ontologies. PubMine improves query accuracy and flexibility with advanced search capabilities of fuzzy search, wildcard search, proximity search, range search, and the Boolean combinations. Furthermore, PubMine allows users to extract multi-dimensional relationships between genes, diseases, and chemical compounds by using OLAP (On-Line Analytical Processing) techniques. The HUGO gene symbols and the MeSH ontology for diseases, chemical compounds, and anatomy have been included in the current version of PubMine, which is freely available at http://pubmine.kobic.re.kr. Conclusions: PubMine is a unique bio-text mining system that provides flexible searches and analysis of biological entity relationships. We believe that PubMine would serve as a key bioinformatics utility due to its rapid response to enable web services for community and to the flexibility to accommodate general ontology.