• Title/Summary/Keyword: inference Control

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Development of Moving Object Management System for Vehicle Monitoring/Control Management in e-Logistics Environment (e-Logistics 환경에서 차량관제를 위한 이동체 관리 시스템 개발)

  • Kim, Dong-Ho;Lee, Hye-Jin;Lee, Hyun-Ah;Kim, Jin-Suk
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1231-1238
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    • 2004
  • By virtue of the advanced Internet technology, there are lots of research works for e-Logistics which means virtual business activities or service architecture based on the Internet among the logistics companies. Because e-Logistics environment requires more dynamic and global service area, conventional vehicle monitoring and control technologies innate many problems in terms of Integrating, storing and sharing the location data. It needs the development of the moving object technology in order to resolve efficiently the limitations. In this paper, we propose the whole components of the moving object management system which supports the advanced sharing the location information as well as the integration of location data. We are sure the suggested system can be adopted to construct the next generation-logistics vehicle monitoring and control system by reducing the overall cost and time.

Intelligent Control System for Ship Steering Gear Using TCP/IP (TCP/IP 기반의 지능형 조타제어시스템에 관한 연구)

  • Seo Ki-Yeol;Oh Se-Woong;Cho Deuk-Jae;Park Sang-Hyun;Suh Sang-Hyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2006.05a
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    • pp.305-309
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    • 2006
  • The important field of research on ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships and the safety of navigation. For these purposes, many intelligent technologies for ship automation have been required and studied. As a way of practical application for a smart ship based on network system, this paper proposes the intelligent control system for ship steering gear based on TCP/IP and desires to testify the validity of the proposal by applying the fuzzy control model to the steering gear system. As study method, the fuzzy inference was adopted to build the maneuvering models of steersman and then the network system was implemented using the TCP/IP Socket programming. Lastly, the miniature steering control system was designed to testify for its effectiveness.

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Seismic Response Control of Cable-Stayed Bridge using Fuzzy Supervisory Control Technique (퍼지관리제어기법을 이용한 사장교의 지진응답제어)

  • Park, Kwan-Soon;Koh, Hyun-Moo;Ok, Seung-Yong;Seo, Chung-Won
    • Journal of the Earthquake Engineering Society of Korea
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    • v.8 no.4
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    • pp.51-62
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    • 2004
  • Fuzzy supervisory control technique for the seismic response control of cable-stayed bridges subject to earthquakes is studied. The proposed technique is a hybrid control method, which adopts a hierarchical structure consisting of several sub-controllers and a fuzzy supervisor. Sub-controllers are independently designed to reduced the responses to be controlled of a cable-stayed bridge, and a fuzzy supervisor achieves improved seismic control performance by tuning the pre-designed sub-controllers. It is realized by converting static gains of the sub-controllers into time-varying dynamic gains through the fuzzy inference mechanism. To evaluate the feasibility of the proposed technique, the benchmark control problem of cable-stayed bridge proposed by Dyke et al. is adopted. The control variables for the seismic response control of the cable-stayed bridge are determined to be t도 shear forces and bending moments at the base of the towers, the longitudinal displacements at the top of the towers, the relative displacements between the deck and the tower, and the tensions in the stay cables. Comparative results between the fuzzy supervisory controller and LQG controller demonstrate the effectiveness of the proposed control technique.

Development of System for Real-Time Object Recognition and Matching using Deep Learning at Simulated Lunar Surface Environment (딥러닝 기반 달 표면 모사 환경 실시간 객체 인식 및 매칭 시스템 개발)

  • Jong-Ho Na;Jun-Ho Gong;Su-Deuk Lee;Hyu-Soung Shin
    • Tunnel and Underground Space
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    • v.33 no.4
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    • pp.281-298
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    • 2023
  • Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

An RDF Ontology Access Control Model based on Relational Database (관계형 데이타베이스 기반의 RDF 온톨로지 접근 제어 모델)

  • Jeong, Dong-Won
    • Journal of KIISE:Databases
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    • v.35 no.2
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    • pp.155-168
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    • 2008
  • This paper proposes a relational security model-based RDF Web ontology access control model. The Semantic Web is recognized as a next generation Web and RDF is a Web ontology description language to realize the Semantic Web. Much effort has been on the RDF and most research has been focused on the editor, storage, and inference engine. However, little attention has been given to the security issue, which is one of the most important requirements for information systems. Even though several researches on the RDF ontology security have been proposed, they have overhead to load all relevant data to memory and neglect the situation that most ontology storages are being developed based on relational database. This paper proposes a novel RDF Web ontology security model based on relational database to resolve the issues. The proposed security model provides high practicality and usability, and also we can easily make it stable owing to the stability of the relational database security model.

A study on an error recovery expert system in the advanced teleoperator system (지적 원격조작시스템의 일환으로서 에러회복 전문가 시스템에 관한 연구)

  • 이순요;염준규;오제상;이창민
    • Journal of the Ergonomics Society of Korea
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    • v.6 no.2
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    • pp.19-28
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    • 1987
  • If an error occurs in the automatic mode when the advanced teleoperator system performs a task in hostile environment, then the mode changes into the manual mode. The operation by program and the operation by hyman recover the error in the manual mode. The system resumew the automatic mode and continues the given task. In order to utilize the inverse kinematics as means of the operation by program in the manual mode, Lee and Nagamachi determined the end point of the robot trajectory planning which varied with the height of the task object recognized by a T.V monitor, solved the end point by the fuzzy set theory, and controlled the position of the robot hand by the inverse kinematics and the posture of the robot hand by the operation by human. But the operation by human did take a lot of task time because the position and the posture of the robot hand were separately controlled. To reduce the task time by human, this paper developes an error recovery expert system (ERES). The position of the robot hand is controlled by the inverse kinematics of the cartesian coordinate system to the end point which is deter- mined by the fuzzy set theory. The posture of the robot hand is controlled by the modulality of the robot hand's motion which is made by the posture of the task object. The knowledge base and the inference engine of the ERES is developed using the muLISP-86 language. The experimental results show that the average task time by human the ERES which was performed by the integration of the position and the posture control of the robot hand is shorter than that of the research, done by the preliminary experiment, which was performed by the separation of the position and the posture control of the robot hand. A further study is likely to research into an even more intelligent robot system control usint a superimposed display and digitizer which can present two-dimensional coordinate of the work space for the convenience of human interaction.

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Possibility of Selective Breeding of Red Sea Bream Pagrus major Under Non-fish Meal Diet (무어분 사료를 이용한 참돔(Pagrus major)의 선발육종 가능성에 대한 연구)

  • Dong In Kim;Fumiaki Takakuwa;Keitaro Kato;Youhei Washio
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.56 no.2
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    • pp.212-220
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    • 2023
  • Over the past 50 years, red sea bream Pagrus major has been selectively bred for more than 10 generations to improve its growth rate. However, the effect of genetic factors on growth under low- or non-fish meal diet is still unclear. Here, we analyzed 251 individuals randomly mating 21 females (dam) and 16 males (sire) to determine the difference in growth between non-fish meal (i.e., treatment group) and fish meal-based diet (i.e., control group), if any. The kinship coefficient between each group of individuals and their parents was estimated by the KING (Kinship-based Inference for GWASs) software package. The presumed parents of 74 individuals in the treatment group and 57 individuals in the control group could be effectively identified. Notably, one specific female was consistently related to high- rather than low-growth individuals in both groups. In addition, more than one parent in each group was related to either high- or low-growth individuals. Parents of both high-growth individuals in the treatment group and low-growth individuals in the control group were also identified. Although further study is required on various growth factors, this study suggests the possibility of selective breeding under non-fish meal diet.

On Developing The Intellingent contro System of a Robot Manupulator by Fussion of Fuzzy Logic and Neural Network (퍼지논리와 신경망 융합에 의한 로보트매니퓰레이터의 지능형제어 시스템 개발)

  • 김용호;전홍태
    • Journal of the Korean Institute of Intelligent Systems
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    • v.5 no.1
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    • pp.52-64
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    • 1995
  • Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

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A Study on the Lighting Control System using Fuzzy Control System and RGB Modules in the Ship's Indoor (퍼지 제어 시스템과 RGB LED 모듈을 이용한 선박 실내용 조명 제어 시스템에 관한 연구)

  • Nam, Young-Cheol;Lee, Sang-Bae
    • Journal of Navigation and Port Research
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    • v.42 no.6
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    • pp.421-426
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    • 2018
  • With regard to LED lighting devices which have currently been commercialized, LED operating sequences are being sold in a fixed state. In such a state, the external environmental factors are not taken into consideration as only the illumination environment application is considered. Currently, it is difficult to create an optimal lighting environment which can adapt to changes in external environmental factors in the ship. Therefore, it was concluded that there is a need to input the external environment value so that the optimal illumination value can be reflected in real time in order to adapt more organically and actively to the change of external environmental factors. In this paper, we used a microprocessor as an integrated management system for environmental data that changes in real time according to existing external environmental factors. In addition, a controller capable of lighting control of RGB LED module by combining fuzzy inference system. For this, a fuzzy control algorithm is designed and a fuzzy control system is constructed. The distance and the illuminance value from the external environment element are input to the sensor, and these values are converted to the optimum illumination value through the fuzzy control algorithm, and are expressed through the dimming control of the RGB LED module and the practical effectiveness of the fuzzy control system is confirmed.

A Study on Fuzzy Rule Functional Verification for Threshold Value Prediction of Buffer in ATM Networks (ATM 망에서 버퍼의 임계값 예측을 위한 퍼지 규칙 기능 검증에 관한 연구)

  • 정동성;이용학
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.8C
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    • pp.1149-1158
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    • 2004
  • In this thesis, we created a Fuzzy rule in a Fuzzy logic that are Fuzzy logic which is composed of linguistic rules and Fuzzy inference engine for effective traffic control in ATM networks. The parameters of the Fuzzy rules are adapted to minimize the given performance index in both cases. In other words, the difuzzification value controls the threshold in the buffer to arrival ratio to traffic priority (low or high) using fuzzy set theory for traffic connected after reasoning. Also, show experiment result about rule by MATLAB6.5 and on-line bulid-up to verify validity of created Fuzzy rule. As a result, we can verify that threshold value in buffer is efficiently controlled by the traffic arrival ratio.