• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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• pp.636-643
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• 2005

Recently, performance based seismic design (PBSD) methods have been suggested in numerous forms and widely studied as a new concept of seismic design. The PBDSs are far from being practical method due to complexity of algorithms resided in the design philosophy. In this paper, optimal seismic design method based on displacement coefficient method (DCM) described in FEMA 273 is developed. As an optimizer simple genetic algorithms are used for implementations. In the optimization problem formulated in this Paper, strength design criteria stiffness design criteria, and nonlinear response criteria specified in DCM are included in design constraints. The optimal performance based design(OPBD) method is applied to seismic design of a 3-story two-dimensional steel frame structures.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.158-162
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• 2013

Building envelope systems with growing complexity in geometry and performance criteria demand adapted workflow processes toward the efficient integration of their design and fabrication. To facilitate integration of the workflow process, this study analyzes relationships among teams who share digital models and exchange information that help project participants identify areas of improvement in task allocation and exchanges among various actors, systems, and activities. In addition, major gaps identified in knowledge transfer, project tracking, and design integration during the performance evaluation stages, emphasize the need for a more comprehensive approach to integrating the design, the fabrication, and the construction parameters of building envelope systems. To evaluate the effectiveness of streamlining interactions of design parameters with fabrication constraints and constructability assessments, this paper examines a mechanical design approach as it applies to various project scenarios to develop a mechanical solution for streamlining building envelope design and construction workflow.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.321-327
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• 2023

The current rapid development of artificial intelligence technology has involved all aspects of the production field. The development of various algorithms and programs has pushed artificial intelligence to a new peak. Due to its complexity and diversity in the field of architectural design, the positive impact of artificial intelligence technology on architectural design is discussed from the perspective of conceptual design. For museums, which are one of the increasingly popular public facilities, the introduction of artificial intelligence technology has provided certain help in assisting the conceptual design of the museum. This article analyzes the theoretical and practical support of artificial intelligence technology in improving conceptual design, analyzing the architectural appearance, structural layout, materials, etc., to increase the feasibility and practicality of assisting conceptual design. It has certain reference significance for building a modern, advanced, international and interactive modern museum.

• 전자공학회논문지SC
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• 제40권3호
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• pp.145-151
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• 2003

본 논문에서는 고속의 연산동작과 낮은 회로 복잡도를 갖는 새로운 GF(2/sup m/)상의 승산기를 제안한다. 유한체 연산은 다항식 승산과 기약다항식을 적용한 모듈러 연산에 의해 전개되며, 본 논문에서는 이 두 과정을 분리하여 다루었다. 다항식 승산연산은 Permestzi의 기법을 토대로 전개하였고 기약다항식은 AOP로 하였다. 멀티플렉서를 사용하여 GF(2/sup m/)상의 승산회로를 구성하였고, 회로 복잡도와 지연시간을 타 논문과 비교하였다. 제안된 승산기는 낮은 회로 복잡도와 지연시간을 보이며, 회로의 구성이 정규성을 가지므로 VLSI 구현에 적합하다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.30-33
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• 2002

To obtain good performance of radial basis function (RBF) neural networks, it needs very careful consideration in design. The selection of several parameters such as the number of centers and widths of the radial basis functions must be considered carefully since they critically affect the network's performance. We propose a learning algorithm for growing of complexity of RBF neural networks which is adapted automatically according to the complexity of tasks. The algorithm generates a new basis function based on the errors of network, the percentage of decreasing rate of errors and the nearest distance from input data to the center of hidden unit. The RBF's center is located at the point where the maximum of absolute interference error occurs in the input space. The width is calculated based on the standard deviation of distance between the center and inputs data. The steepest descent method is also applied for adjusting the weights, centers, and widths. To demonstrate the performance of the proposed algorithm, general problem of function estimation is evaluated. The results obtained from the simulation show that the proposed algorithm for RBF neural networks yields good performance in terms of convergence and accuracy compared with those obtained by conventional multilayer feedforward networks.

• 대한전자공학회논문지SD
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• 제40권2호
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• pp.117-125
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• 2003

본 논문에서는 저전력 및 고속의 특성을 갖는 MC-CDMA 시스템용의 동기획득 구조를 제안한다. 이를 위해 탐색핑거라는 새로운 구조를 설계하였다. 제안한 탐색핑거는 기존의 핑거를 수정한 구조로써, 원래의 핑거 기능 이외에 탐색기의 기능을 갖고 있다. 초기 동기획득시 탐색핑거는 탐색기와 함께 탐색기의 기능을 수행함으로써 초기 동기획득 시간을 단축시킨다. 그리고 초기 동기획득이 끝난 후에 본래의 핑거로 동작한다. 제안한 구조를 5㎒ MC-CAMA 시스템에 적용할 경우, 동기회득을 수행하는 블록에서 게이트카운트론 비교하였을 때, 약 63%의 하드웨어 복잡도 감소와 동시에 동기획득 시간을 5배 단축할 수 있었다.또한, 20㎒ MC-CDMA에서는, 약 75%의 하드웨어 복잡도를 감소시키면서 평균 동기 획득 시간을 최대 19배 단축할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1579-1602
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• 2020

In the design of production system, buffer capacity allocation is a major step. Through polymorphism analysis of production capacity and production capability, this paper investigates a buffer allocation optimization problem aiming at the multi-stage production line including unreliable machines, which is concerned with maximizing the system theoretical production rate and minimizing the system state entropy for a certain amount of buffers simultaneously. Stochastic process analysis is employed to establish Markov models for repairable modular machines. Considering the complex structure, an improved vector UGF (Universal Generating Function) technique and composition operators are introduced to construct the system model. Then the measures to assess the system's multi-state reliability and structural complexity are given. Based on system theoretical production rate and system state entropy, mathematical model for buffer capacity optimization is built and optimized by a specific genetic algorithm. The feasibility and effectiveness of the proposed method is verified by an application of an engine head production line.

• 한국자동차공학회논문집
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• 제24권2호
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• pp.127-136
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• 2016

The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.

• 전기학회논문지
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• 제66권9호
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• pp.1402-1408
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• 2017

Recently, services for personal biometric data analysis based on real-time monitoring systems has been increasing and many of them have focused on recognition of emotions. In this paper, we propose a classification model to classify anxiety emotion using biometric data actually collected from people. We propose to deploy the support vector machine to build a classification model. In order to improve the classification accuracy, we propose two data pre-processing procedures, which are normalization and data deletion. The proposed algorithms are actually implemented based on Real-time Traffic Flow Measurement structure, which consists of data collection module, data preprocessing module, and creating classification model module. Our experiment results show that the proposed classification model can infers anxiety emotions of people with the accuracy of 65.18%. Moreover, the proposed model with the proposed pre-processing techniques shows the improved accuracy, which is 78.77%. Therefore, we can conclude that the proposed classification model based on the pre-processing process can improve the classification accuracy with lower computation complexity.

• 한국컴퓨터산업학회논문지
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• 제2권3호
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• pp.377-388
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• 2001

소프트웨어 척도는 소프트웨어를 특징화하기 위한 효율적인 방법을 제공한다. 척도들은 전통적으로 식의 정의를 통해 구성되었지만 이러한 접근은 소프트웨어를 특징화해주는 모든 매개변수사이의 모든 관계를 완전하게 이해할 수 있을 때만 적용 가능하다는 한계가 있다. 이 논문은 비선형 함수를 매우 정교하게 근사화 시키고, 인지 심리 이론을 결합할 수 있는 퍼지 논리 시스템을 사용하였다. 우선, Java 프로그램으로부터 수집된 12개 척도들의 인자들로부터 다중 회귀식을 추출하였다. 또한 그 중에서 프로그램 볼륨 인자에 인지 심리 이론을 적용하고 퍼지 학습을 수행하여 프로그램 볼륨 복잡도를 측정하였다. 이 연구는 소프트웨어 척도의 분석과 설계의 더 나은 조사를 위한 토대가 될 수 있을 것이다.