• 제목/요약/키워드: artificial fit

검색결과 118건 처리시간 0.033초

Minimization of differential column shortening and sequential analysis of RC 3D-frames using ANN

  • Njomo, Wilfried W.;Ozay, Giray
    • Structural Engineering and Mechanics
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    • 제51권6호
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    • pp.989-1003
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    • 2014
  • In the preliminary design stage of an RC 3D-frame, repeated sequential analyses to determine optimal members' sizes and the investigation of the parameters required to minimize the differential column shortening are computational effort consuming, especially when considering various types of loads such as dead load, temperature action, time dependent effects, construction and live loads. Because the desired accuracy at this stage does not justify such luxury, two backpropagation feedforward artificial neural networks have been proposed in order to approximate this information. Instead of using a commercial software package, many references providing advanced principles have been considered to code a program and generate these neural networks. The first one predicts the typical amount of time between two phases, needed to achieve the minimum maximorum differential column shortening. The other network aims to prognosticate sequential analysis results from those of the simultaneous analysis. After the training stages, testing procedures have been carried out in order to ensure the generalization ability of these respective systems. Numerical cases are studied in order to find out how good these ANN match with the sequential finite element analysis. Comparison reveals an acceptable fit, enabling these systems to be safely used in the preliminary design stage.

은나노입자에 대한 방진마스크 포집효율 및 총누설율 (Filtration efficiency and Manikin-based Total Inward Leakage Study of Particle Filtering Mask Challenged with Silver Nanoparticles)

  • 김종규
    • 한국산업보건학회지
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    • 제26권3호
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    • pp.367-376
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    • 2016
  • Objectives: The production and use of nanoparticles have been increased. In 2014 Workplace Survey Results, 335 companies produce and treat nanoparticls. However, lack of data on nano-toxicity and a method for risk management and regulation on nanoparticles and the standard test method are not sufficient. Protective equipment selection guidelines for nanoparticles are not established. It is required to carry out respirator efficiency test against nanoparticles. This study was performed to evaluate filtration efficiency and manikin-based total inward leakage of particle filtering mask using in Korean country challenged with silver nanoparticles. Methods: We investigated filtration efficiency and total inward leakage of 7 respirator with silver nanoparticle. Results: The geometric mean diameters of Silver nanoparticles were 30 nm and number concentration were about $10^6{\sharp}/cm^3$. Filtration efficiency of six of the seven particle filtering masks was more than 98% and one particle filtering masks filtration efficiency was 94.9%. The filtration efficiency of particle filtering masks to 20 nm silver nanoparticels was highest. Artificial breathing machine with manikin based total inward leakage were 7.6% ~ 42.3%. Conclusions: The results of this study nano-silver filter efficiency was high but the total inward leakage was higher than filter penetration. Therefore, education on how to wear a respirator should be demanded. Especially for workers handling nanoparticles and toxic material, user seal checking and fit test must be performed.

ROS를 이용한 이동 로봇 제어 시스템 구현 (An Implementation of the Control System of the Mobile Robot using ROS)

  • 문용선;노상현;임승우;배영철
    • 한국전자통신학회논문지
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    • 제8권11호
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    • pp.1713-1718
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    • 2013
  • 본 논문은 로봇 미들웨어 기술 중 ROS(Robot Operating System)를 이용하여 이동 로봇의 원격 제어 및 인공전위계를 이용한 충돌회피를 구현하였으며, 충돌회피 노드에 동적 재구성(dynamic reconfigure)을 적용하였다. 또한 ROS의 주된 목적인 공유와 협업에 맞게 LRF와 조이스틱과 같은 로봇에 자주 사용되는 하드웨어를 ROS에서 제공하는 노드로서 재사용하였다.

A COMPARATIVE STUDY ON THE DIMENSIONAL CHANGE OF THE DIFFERENT DENTURE BASES

  • Kim, Myung-Joo;Kim, Chang-Whe
    • 대한치과보철학회지
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    • 제44권6호
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    • pp.712-721
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    • 2006
  • Statement of problem. Acrylic resin is most commonly used for denture bases. However, acrylic resin has week points of volumetric shrinkage during polymerization that reduces denture fit. The expandability of POSS (Polyhedral Oligomeric Silsesquioxane) containing polymer could be expected to reduce the polymerization shrinkage of denture bases and would increase the adaptability of the denture to the tissue. Purpose. The purpose of this study was to compare the dimensional stability in the conventional acrylic resin base, POSS-containing acrylic resin base, and metal bases. Materials and methods. Thirty six maxillary edentulous casts and dentures of different base were fabricated. Tooth movement and tissue contour change of denture after processing (resin curing, deflasking, decasting and finishing without polishing) and immersion in artificial saliva at $37^{\circ}C$ for 1 week and 4 weeks were measured using digital measuring microscope and threedimensional laser scanner. Results. The results were as follows: 1. The conventional resin group showed significant (p<0.01) dimensional change throughout the procedure (processing and immersion in artificial saliva). 2. After processing, the metal group and POSS resin group showed lower linear and 3-dimensional change than conventional resin group (p<0.01). 3. There was no statistically significant linear and 3-dimensional change after immersion for 1 week and 4 weeks in metal and POSS resin group. 4. In all groups, the midline and alveolar ridge crest area presented smaller 3-dimensional change compared with vestibule and posterior palatal seal area after processing and soaking in artificial saliva for 1 week and 4 weeks (p<0.01). Conclusion. In this study, a reinforced acrylic-based resin with POSS showed good dimensional stability.

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

  • 김동화
    • 대한전기학회논문지:시스템및제어부문D
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    • 제51권1호
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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.

FUZZY LOGIC KNOWLEDGE SYSTEMS AND ARTIFICIAL NEURAL NETWORKS IN MEDICINE AND BIOLOGY

  • Sanchez, Elie
    • 한국지능시스템학회논문지
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    • 제1권1호
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    • pp.9-25
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    • 1991
  • This tutorial paper has been written for biologists, physicians or beginners in fuzzy sets theory and applications. This field is introduced in the framework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with linguistic entries or of fuzzy propositions. Relationships between symptoms and diagnoses are interpreted as labels of fuzzy sets. It is shown how possibility measures (soft matching) can be used and combined to derive diagnoses after measurements on collected data. The concepts and methods are illustrated in a biomedical application on inflammatory protein variations. In the case of poor diagnostic classifications, it is introduced appropriate ponderations, acting on the characterizations of proteins, in order to decrease their relative influence. As a consequence, when pattern matching is achieved, the final ranking of inflammatory syndromes assigned to a given patient might change to better fit the actual classification. Defuzzification of results (i.e. diagnostic groups assigned to patients) is performed as a non fuzzy sets partition issued from a "separating power", and not as the center of gravity method commonly employed in fuzzy control. It is then introduced a model of fuzzy connectionist expert system, in which an artificial neural network is designed to build the knowledge base of an expert system, from training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the connections: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through MIN-MAX fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feed forward network is described and illustrated in the same biomedical domain as in the first part.

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통합적 인지 모형의 가능성 (Toward a Possibility of the Unified Model of Cognition)

  • 이영의
    • 과학기술학연구
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    • 제1권2호
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    • pp.399-422
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    • 2001
  • 인지과학에서 최근 논의되고 있는 인지 이론들은 인지에 대한 적절한 모형을 제공하지 못하고 있다. 전통적인 인공지능 이론은 추리나 문제 해결과 같은 과제에는 적절한 것처럼 보이지만 문자와 음성 인식과 같은 패턴 인식 분야에서는 여전히 비효율적이다. 연결주의는 전통적인 인공지능 이론과는 정반대의 양상을 보이고 있다. 연결주의 체계는 패턴 인식에는 강하지만 추리에는 약하다. 한편 최근에 제시된 상황화 된 행동 이론은 전통적인 인공지능과 연결주의에서 기본적으로 전제되고 있는 표상의 개념을 부정하고 실제 세계에서 직접 유래되는 지각에 바탕을 둔 모형을 제시하지만 인간의 인지를 효과적으로 설명하고 있지 못하다. 인지 모형들이 갖고 있는 이러한 한계점들을 강조하여 나는 이 글에서 인공지능, 연결주의, 상황화된 행동 이론을 각각 좌뇌 모형, 우뇌 모형, 로봇 모형이라고 부르고 그러한 한계 상황을 벗어날 수 있는 방법으로서 모형들간의 양립가능성을 이용한 통합적 인지 모형의 구축을 모색한다.

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Research on Developing a Conversational AI Callbot Solution for Medical Counselling

  • Won Ro LEE;Jeong Hyon CHOI;Min Soo KANG
    • 한국인공지능학회지
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    • 제11권4호
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    • pp.9-13
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    • 2023
  • In this study, we explored the potential of integrating interactive AI callbot technology into the medical consultation domain as part of a broader service development initiative. Aimed at enhancing patient satisfaction, the AI callbot was designed to efficiently address queries from hospitals' primary users, especially the elderly and those using phone services. By incorporating an AI-driven callbot into the hospital's customer service center, routine tasks such as appointment modifications and cancellations were efficiently managed by the AI Callbot Agent. On the other hand, tasks requiring more detailed attention or specialization were addressed by Human Agents, ensuring a balanced and collaborative approach. The deep learning model for voice recognition for this study was based on the Transformer model and fine-tuned to fit the medical field using a pre-trained model. Existing recording files were converted into learning data to perform SSL(self-supervised learning) Model was implemented. The ANN (Artificial neural network) neural network model was used to analyze voice signals and interpret them as text, and after actual application, the intent was enriched through reinforcement learning to continuously improve accuracy. In the case of TTS(Text To Speech), the Transformer model was applied to Text Analysis, Acoustic model, and Vocoder, and Google's Natural Language API was applied to recognize intent. As the research progresses, there are challenges to solve, such as interconnection issues between various EMR providers, problems with doctor's time slots, problems with two or more hospital appointments, and problems with patient use. However, there are specialized problems that are easy to make reservations. Implementation of the callbot service in hospitals appears to be applicable immediately.

Space Syntax를 이용한 대중교통 접근성 분석에 관한 연구 (Connectivity analysis for the public transportation network using the Space Syntax)

  • 민보라;전철민
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2004년도 춘계학술발표회논문집
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    • pp.477-482
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    • 2004
  • Due to the traffic congestion of the city and public transportation-oriented policies, public transportation is receiving more attention and being used increasingly However, relatively less research on the design and distribution of public transportation network and limitations in quantitative approaches have made implementation and operation practically difficult. Over- or under-supply of transportation routes caused unbalanced connectivity among areas and differences in time, expenses and metal burden of users. On the other hand, the Space Syntax theory, designed to calculate the connectivity of urban or architectural space, helps generate quantitative connectivity of whole space simply based on the spacial structure. This study modified the original Space Syntax algorithm to fit the public transportation problem and showed how it is appied to a network by creating an artificial network using the GIS.

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Controcller design using parametric neural networks

  • HashemiNejad, M.;Murata, J.;Banihabib, M.E.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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    • pp.616-621
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    • 1994
  • Neural Networks (henceforth NNs, with adjective "artificial" implied) has been used in the field of control however, has a long way to fit to its abilities. One of the best ways to aid it is "supporting it with the knowledge about the linear classical control theory". In this regard we hive developed two kinds of parametric activation function and then used them in both identification and control strategy. Then using a nonlinear tank system we are to test its capabilities. The simulation results for the identification phase is promising. phase is promising.

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