• Title/Summary/Keyword: Inference system

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The Study on Dynamic Images Processing for Finger Languages (지화 인식을 위한 동영상 처리에 관한 연구)

  • Kang, Min-Ji;Choi, Eun-Sook;Sohn, Young-Sun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.2
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    • pp.184-189
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    • 2004
  • In this paper, we realized a system that receives the dynamic images of finger languages, which is the method of intention transmission of the hearing disabled person, using the white and black CCD camera, and that recognizes the images and converts them to the editable text document. We use the afterimage to draw a sharp line between indistinct images and clear images from a series of inputted images, and get the character alphabet from the away of continuous images and output the accomplished character to the word editor by applying the automata theory. After the system removes the varied wrist part from the data of clean image, it gets the controid point of hand by the maximum circular movement method and recognizes the hand that is necessary to analyze the finger languages by applying the circular pattern vector algorithm. The system abstracts the characteristic vectors of the hand using the distance spectrum from the center of the hand and it compares the characteristic vector of inputted pattern from the standard pattern by applying the fuzzy inference and recognizes the movement of finger languages.

Smart Plants Management System based on Internet (인터넷 기반 스마트 화초 관리 시스템)

  • Park, Hyunsook;Park, Chun-Kwan;Hong, You-Sik
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.5
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    • pp.193-199
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    • 2015
  • Recently the artificial intelligence green house system, which collects automatically the informations of plants cultivation circumstances and controls the growing circumstances, is studied using temperature, humidity and illuminance sensors. In this paper, the inference for plants cultivation of optimum circumstance conditions is simulated on the internet bases by predicting the temperature, humidity and illuminance. On the IOT circumstances, the plant cultivation conditions of temperature, humidity and illuminance, using Arduino sensor, are transmitted to the manager on realtime and if the optimum condition of temperature and humidity for plant cultivation is not equal to the values, the system transmits automatically the SMS warning messages on realtime. Although the sudden climite conditions(snow, rain, hot weather) are occurred, the optimum condition of plant cultivation can be controlled. In this paper, using Fuzzy rules and WEKA TOOL, although the same flora temperature zone is used, the simulation is produced for the optimum value of temperature, humidity and illuminance for the zone.

Analysis of Artificial Intelligence Curriculum of SW Universities (SW중심대학의 인공지능 교육과정 현황분석)

  • Woo, HoSung;Lee, HyunJeong;Kim, JaMee;Lee, WonGyu
    • The Journal of Korean Association of Computer Education
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    • v.23 no.2
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    • pp.13-20
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    • 2020
  • The interest in artificial intelligence is due to an increase in influence on companies, organizations, daily lives and society. The purpose of this study is to analyze the key elements in the teaching subjects of artificial intelligence-related subjects of Korean universities based on the intelligent system area of Computer Science 2013 in terms of human resources development. According to the analysis, there are five out of nine universities that run the required courses. Based on the 12 detailed knowledge domains of intelligent systems, the compulsory subjects of universities are distributed in the field of basic search theory, basic knowledge expression and reasoning, and inference based on uncertainty. The elective courses of each university covered topics in five to eight areas of the total knowledge area of the intelligent system, with 69.9 percent of universities with the highest average ratio of areas involving the subject of teaching subjects and 46.3 percent of universities with the lowest. This study has implications for the fact that prior to entering an artificial intelligence graduate school, we were able to grasp the level of knowledge about artificial intelligence at the undergraduate level.

A Design of semantic web-based fish drug information system (시맨틱 웹기반 수산용 의약품 정보시스템 설계)

  • Ceong, Hee-Taek;Kim, Hae-Ran;Han, Soon-Hee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.1
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    • pp.145-155
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    • 2010
  • In this paper, we suggest a fish drug domain ontology to show an associated information and hierarchy together through concept-relation and inference mechanism instead of keyword matching. First, we investigate competency questions from workers of fishery industry and then we derive concepts and terminologies. Next, we present a process of fish drug ontology modelling using Protege-OWL editor, which is an extension of Protege that supports the Web Ontology Language(OWL). Last, we suggest the user interface of semantic web-based fish drug information system to search easily associated informations of fish drug using this ontology. It is to provide an effective search method that fish disease manager, fish farmer, and students majoring in fisheries can confirm details of diseases, fish, and drug evaluations associated with fish drug within one screen without moving to another position.

New Sequential Clustering Combination for Rule Generation System (규칙 생성 시스템을 위한 새로운 연속 클러스터링 조합)

  • Kim, Sung Suk;Choi, Ho Jin
    • Journal of Internet Computing and Services
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    • v.13 no.5
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    • pp.1-8
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    • 2012
  • In this paper, we propose a new clustering combination based on numerical data driven for rule generation mechanism. In large and complicated space, a clustering method can obtain limited performance results. To overcome the single clustering method problem, hybrid combined methods can solve problem to divided simple cluster estimation. Fundamental structure of the proposed method is combined by mountain clustering and modified Chen clustering to extract detail cluster information in complicated data distribution of non-parametric space. It has automatic rule generation ability with advanced density based operation when intelligent systems including neural networks and fuzzy inference systems can be generated by clustering results. Also, results of the mechanism will be served to information of decision support system to infer the useful knowledge. It can extend to healthcare and medical decision support system to help experts or specialists. We show and explain the usefulness of the proposed method using simulation and results.

Exploring Welfare Discourse in Korea Based on M. Foucault's Power And Knowledge Relations (M. Foucault의 권력지식관계론에 기초한 한국의 복지담론 해석)

  • Seo, Jeonghoon
    • Korean Journal of Social Welfare
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    • v.67 no.4
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    • pp.79-101
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    • 2015
  • What is the role of welfare discourse? Michel Foucault suggests the power and knowledge relation that power in a particular society and period controls the society and members by creating knowledge affecting the formation of cognitive and normative systems. Having the formation of exclusions(constraint of cognition), and materiality and reality(normative system) as an analytical framework, this article attempts the exploration of welfare discourse analyses with public statements relating to welfare subjects of the four former Korean presidents. As a result, It is found that dominant epistemic system is formed by balancing welfare and growth and regarding jobs as the best welfare(the linkage of welfare-growth-employment), emphasizing individual economic responsibility and self-reliance, pursuing welfare selectivism, and excluding comprehensive welfare provisions. At the same time, it is observed that power is not always formulating systematic knowledge and that there is a gap between cognition and norm. While the Foucauldian discourse analysis provides a causal inference about low social welfare expenditure, excessive focus on the role of power as knowledge generator and infuser causes a question of how to accommodate contemporary changes into knowledge system.

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Motion Control of a Mobile Robot Using Natural Hand Gesture (자연스런 손동작을 이용한 모바일 로봇의 동작제어)

  • Kim, A-Ram;Rhee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.1
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    • pp.64-70
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    • 2014
  • In this paper, we propose a method that gives motion command to a mobile robot to recognize human being's hand gesture. Former way of the robot-controlling system with the movement of hand used several kinds of pre-arranged gesture, therefore the ordering motion was unnatural. Also it forced people to study the pre-arranged gesture, making it more inconvenient. To solve this problem, there are many researches going on trying to figure out another way to make the machine to recognize the movement of the hand. In this paper, we used third-dimensional camera to obtain the color and depth data, which can be used to search the human hand and recognize its movement based on it. We used HMM method to make the proposed system to perceive the movement, then the observed data transfers to the robot making it to move at the direction where we want it to be.

Prediction of Transfer Lengths in Pretensioned Concrete Members Using Neuro-Fuzzy System (뉴로-퍼지 시스템을 이용한 프리텐션 콘크리트 부재의 전달길이 예측)

  • Kim, Minsu;Han, Sun-Jin;Cho, Hae-Chang;Oh, Jae-Yuel;Kim, Kang Su
    • Journal of the Korea Concrete Institute
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    • v.28 no.6
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    • pp.723-731
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    • 2016
  • In pretensioned concrete members, a certain bond length from the end of the member is required to secure the effective prestress in the strands, which is defined as the transfer length. However, due to the complex bond mechanism between strands and concrete, most transfer length models based on the deterministic approach have uncertainties and do not provide accurate estimations. Therefore, in this study, Adaptive Neuro-Fuzzy Inference System (ANFIS), a Neuro-Fuzzy System, is introduced to reduce the uncertainties and to estimate the transfer length more accurately in pretensioned concrete member. A total of 253 transfer length test results have been collected from literatures to train ANFIS, and the trained ANFIS algorithm estimated the transfer length very accurately. In addition, a design equation was proposed to calculate the transfer length based on parametric studies and dimensional analyses. Consequently, the proposed equation provided accurate results on the transfer length which are comparable to the ANFIS analysis results.

Robustness Estimation for Power and Water Supply Network : in the Context of Failure Propagation (피해파급에 대한 고찰을 통한 전력 및 상수도 네트워크의 강건성 예측)

  • Lee, Seulbi;Park, Moonseo;Lee, Hyun-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.3
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    • pp.33-42
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    • 2018
  • In the aftermath of an earthquake, seismic-damaged infrastructure systems loss estimation is the first step for the disaster response. However, lifeline systems' ability to supply service can be volatile by external factors such as disturbances of nearby facilities, and not by own physical issue. Thus, this research develops the bayesian model for probabilistic inference on common-cause and cascading failure of seismic-damaged lifeline systems. In addition, the authors present network robustness estimation metrics in the context of failure propagation. In order to quantify the functional loss and observe the effect of the mitigation plan, power and water supply system in Daegu-Gyeongbuk in South Korea is selected as case network. The simulation results show that reduction of cascading failure probability allows withstanding the external disruptions from a perspective of the robustness improvement. This research enhances the comprehensive understanding of how a single failure propagates to whole lifeline system performance and affected region after an earthquake.

Design of the Call Admission Control System of the ATM Networks Using the Fuzzy Neural Networks (퍼지 신경망을 이용한 ATM망의 호 수락 제어 시스템의 설계)

  • Yoo, Jae-Taek;Kim, Choon-Seop;Kim, Yong-Woo;Kim, Young-Han;Lee, Kwang-Hyung
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.8
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    • pp.2070-2079
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    • 1997
  • In this paper, we proposed the FNCAC (fuzzy neural call admission control) scheme of the ATM networks which used the benefits of fuzzy logic controller and the learning abilities of the neural network to solve the call admission control problems. The new call in ATM networks is connected if QoS(quality of service) of the current calls is not affected due to the connection of a new call. The neural network CAC(call admission control) system is predictable system because the neural network is able to learn by the input/output pattern. We applied the fuzzy inference on the learning rate and momentum constant for improving the learning speed of the fuzzy neural network. The excellence of the proposed algorithm was verified using measurement of learning numbers in the traditional neural network method and fuzzy neural network method by simulation. We found that the learning speed of the FNCAC based on the fuzzy learning rules is 5 times faster than that of the CAC method based on the traditional neural network theory.

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