• Structural Engineering and Mechanics
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• v.70 no.5
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• pp.639-647
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• 2019

The performance of precast concrete structures is greatly influenced by the behaviour of beam-to-column connections. A single connection may be required to transfer several loads simultaneously so each one of those loads must be considered in the design. A good connection combines practicality and economy, which requires an understanding of several factors; including strength, serviceability, erection and economics. This research work focuses on the performance aspect of a specific type of beam-to-column connection using partly hidden corbel in precast concrete structures. In this study, the results of experimental assessment of the proposed beam-to-column connection in precast concrete frames was used. The purpose of this research is to develop and apply the Extreme Learning Machine (ELM) for moment-rotation prediction of precast beam-to-column connections. The ELM results are compared with genetic programming (GP) and artificial neural network (ANN). The reliability of the computational models was accessed based on simulation results and using several statistical indicators.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.31-35
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• 1998

• Journal of Engineering Education Research
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• v.22 no.6
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• pp.21-27
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• 2019

In the last few years, interest in computer science education has increased significantly. The curriculum is being revised to introduce computer science. Although interest has focused on coding as the main subject, in fact the computer science includes much more than coding. It engages people in being creative with technology as well as understanding the fundamental principles of computer science. Therefore, it is important to consider the curriculum to provide a foundation by teaching and learning computer science. The curriculum is required the development of courses to teach computer science for non-majors in general education. To think like a computer scientist on the knowledge of computer science is computational thinking. In order to maximize the effectiveness of teaching and learning for computational thinking, various teaching methods and supplementary learning materials, and activities should be developed and provided.

• Steel and Composite Structures
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• v.31 no.5
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• pp.427-435
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• 2019

The estimation of moment and rotation in steel rack connections could be significantly helpful parameters for designers and constructors in the initial designing and construction phases. Accordingly, Extreme Learning Machine (ELM) has been optimized to estimate the moment and rotation in steel rack connection based on variable input characteristics as beam depth, column thickness, connector depth, moment and loading. The prediction and estimating of ELM has been juxtaposed with genetic programming (GP) and artificial neural networks (ANNs) methods. Test outcomes have indicated a surpass in accuracy predicting and the capability of generalization in ELM approach than GP or ANN. Therefore, the application of ELM has been basically promised as an alternative way to estimate the moment and rotation of steel rack connection. Further particulars are presented in details in results and discussion.

• Current Optics and Photonics
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• v.7 no.4
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• pp.362-377
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• 2023

Optical information processing technology is characterized by high speed and parallelism, and the light features short wavelength and large information capacity; At the same time, it has various attributes including amplitude, phase, wavelength and polarization, and is a carrier of multi-dimensional information. Therefore, optical encryption is of great significance in the field of information security transmission, and is widely used in the field of image encryption. For multi-image encryption, this paper proposes a multi-image encryption algorithm based on a modified Gerchberg-Saxton algorithm (MGSA) in the Fresnel-transform domain and computational ghost imaging. First, MGSA is used to realize "one code, one key"; Second, phase function superposition and normalization are used to reduce the amount of ciphertext transmission; Finally, computational ghost imaging is used to improve the security of the whole encryption system. This method can encrypt multiple images simultaneously with high efficiency, simple calculation, safety and reliability, and less data transmission. The encryption effect of the method is evaluated by using correlation coefficient and structural similarity, and the effectiveness and security of the method are verified by simulation experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.408-427
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• 2011

Intensive computational complexity is an obstacle of enabling multiview video coding for real-time applications. In this paper, we present a fast macroblock (MB) mode selection algorithm for B frames which are based on the computational complexity analyses between the MB mode selection and reference frame selection. Three strategies are proposed to reduce the coding complexity jointly. First, the temporal correlation of MB modes between current MB and its temporal corresponding MBs is utilized to reduce computational complexity in determining the optimal MB mode. Secondly, Lagrangian cost of SKIP mode is compared with that of Inter $16{\times}16$ modes to early terminate the mode selection process. Thirdly, reference frame correlation among different Inter modes is exploited to reduce the number of reference frames. Experimental results show that the proposed algorithm can promote the encoding speed by 3.71~7.22 times with 0.08dB PSNR degradation and 2.03% bitrate increase on average compared with the joint multiview video model.

• Prospectives of Industrial Chemistry
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• v.23 no.1
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• pp.42-54
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• 2020

계속적인 충·방전이 가능하여 반영구적으로 사용이 가능한 2차 전지는 친환경 소재로 주목받고 있으며, 노트북 컴퓨터와 휴대전화, 캠코더 등 소형 전자기기뿐만 아니라 전기자동차의 핵심소재이다. 전기자동차 시장의 성장과 더불어 중대형 에너지 저장용 2차 전지 시장의 규모는 더욱 확대되고 있어 관련된 소재의 개발 경쟁과 관심이 날이 갈수록 뜨거워지고 있다. 따라서 소재개발 측면에서 2차 전지 핵심 소재의 물성 발현의 원리 등을 이해하고 최적 소재 설계를 위해서는 원자 레벨에서의 소재 설계 접근법이 필요하다. 따라서 실험적인 연구가 어려운 부분과 원자단위에서의 물질 현상에 대한 이해 그리고 연구 개발의 효율성 증진을 위해서 전산재료과학(computational materials science) 기술이 광범위하게 활용될 수 있다. 본 기고문에서는 리튬이온전지에서의 전극 소재에 대한 전산재료모사의 활용과 연구동향에 대하여 소개하고자 한다.

• Advances in aircraft and spacecraft science
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• v.4 no.3
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• pp.297-316
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

• Advances in aircraft and spacecraft science
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• v.4 no.3
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• pp.317-334
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.261-267
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• 2023

Public research, which requires large computational resources, utilizes the supercomputers of the National Supercomputing Center in the Republic of Korea. The average utilization rate of resources over the past three years reached 80%. Therefore, to ensure the operational stability of this national infrastructure, specialized centers have been established to distribute the computational demand concentrated in the national centers. It is necessary to predict the computational demand accurately to build an appropriate resource scale. Therefore, it is important to estimate the inflow and outflow of computational demand between the national and specialized centers to size the resources required to construct specialized centers. We conducted a logit model analysis using the probabilistic utility theory to derive the preferences of individual users for future supercomputer resources. This analysis shows that the computational demand share of specialized centers is 59.5%, which exceeds the resource utilization plan of existing specialized centers.