• Wind and Structures
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• 제32권4호
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• pp.283-292
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• 2021

Performance-based seismic design (PBSD) is currently used for retrofitting of older buildings and the design of new buildings. Whereas, application of performance-based design for wind load is still under development. The tendency has been in the codes to increase wind hazard based on recent recorded events. Since tall buildings are highly susceptible to wind load, necessity for developing a framework for performance-based wind design (PBWD) has intensified. Only a few guidelines such as ASCE (2019) provide information on using PBWD as an alternative for code prescriptive wind design. Though wind hazards, performance objectives, analysis techniques, and acceptance criteria are explained, no recommendations are provided for several aspects like how to select a proper level of wind hazard for each target performance criterion. This paper is an attempt to explain current design philosophy for wind and seismic loads and inherent connection between the components of PBSD for development of a framework for PBWD of tall buildings. Recognizing this connection, a framework for PBWD based on limits set for serviceability and strength is also proposed. Also, the potential for carrying out PBWD in line with ASCE 7-16 is investigated and proposed in this paper.

• Smart Structures and Systems
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• 제30권3호
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• pp.287-301
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• 2022

The machine-vision based structural displacement measurement methods are widely used due to its flexible deployment and non-contact measurement characteristics. The accuracy of vision measurement is directly related to the image resolution. In the field of computer vision, super-resolution reconstruction is an emerging method to improve image resolution. Particularly, the deep-learning based image super-resolution methods have shown great potential for improving image resolution and thus the machine-vision based measurement. In this article, we firstly review the latest progress of several deep learning based super-resolution models, together with the public benchmark datasets and the performance evaluation index. Secondly, we construct a binocular visual measurement platform to measure the distances of the adjacent corners on a chessboard that is universally used as a target when measuring the structure displacement via machine-vision based approaches. And then, several typical deep learning based super resolution algorithms are employed to improve the visual measurement performance. Experimental results show that super-resolution reconstruction technology can improve the accuracy of distance measurement of adjacent corners. According to the experimental results, one can find that the measurement accuracy improvement of the super resolution algorithms is not consistent with the existing quantitative performance evaluation index. Lastly, the current challenges and future trends of super resolution algorithms for visual measurement applications are pointed out.

• Smart Structures and Systems
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• 제32권1호
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• pp.61-81
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• 2023

This study presents an ensemble learning based Bayesian model updating approach for structural damage diagnosis. In the developed framework, the structure is initially decomposed into a set of substructures. The autoregressive moving average (ARMAX) model is established first for structural damage localization based structural motion equation. The wavelet packet decomposition is utilized to extract the damage-sensitive node energy in different frequency bands for constructing structural surrogate models. Four methods, including Kriging predictor (KRG), radial basis function neural network (RBFNN), support vector regression (SVR), and multivariate adaptive regression splines (MARS), are selected as candidate structural surrogate models. These models are then resampled by bootstrapping and combined to obtain an ensemble model by probabilistic ensemble. Meanwhile, the maximum entropy principal is adopted to search for new design points for sample space updating, yielding a more robust ensemble model. Through the iterations, a framework of surrogate ensemble learning based model updating with high model construction efficiency and accuracy is proposed. The specificities of the method are discussed and investigated in a case study.

• 시스템엔지니어링학술지
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• 제12권2호
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• pp.101-114
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• 2016

A model-based systems engineering (MBSE) approach to implementing hardware-based network cybersecurity controls for APR1400 non-safety data network is presented in this work. The proposed design was developed by implementing packet filtering and deep packet inspection functions to control the unauthorized traffic and malicious contents. Denial-of-Service (DoS) attack was considered as a potential cybersecurity issue that may threaten the data availability and integrity of DCS gateway servers. Logical design architecture was developed to simulate the behavior of functions flow. HDL-based physical architecture was modelled and simulated using Xilinx ISE software to verify the design functionality. For effective modelling process, enhanced function flow block diagrams (EFFBDs) and schematic design based on FPGA technology were together developed and simulated to verify the performance and functional requirements of network security controls. Both logical and physical design architectures verified that hardware-based cybersecurity controls are capable to maintain the data availability and integrity. Further works focus on implementing the schematic design to an FPGA platform to accomplish the design verification and validation processes.

• 한국미생물·생명공학회지
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• 제47권1호
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• pp.69-77
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• 2019

Screening microorganisms that can produce glucan hydrolases for industrial, environmental, and biomedical applications is important. Herein, we describe a novel approach to perform glucan hydrolase screening-based on analysis of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) spectra-which involves degradation of the oligo- and polysaccharides. As a proof-of-concept study, glucan hydrolases that could break down glucans made of several glucose units were used to demonstrate the MALDI-MS-based enzyme assay. First, the enzyme activities of ${\alpha}$-amylase and cellulase on a mixture of glucan oligosaccharides were successfully discriminated, where changes of the MALDI-MS profiles directly reflected the glucan hydrolase activities. Next, we validated that this MALDI-MS-based enzyme assay could be applied to glucan polysaccharides (i.e., pullulan, lichenan, and schizophyllan). Finally, the bacterial glucan hydrolase activities were screened on 96-well plate-based platforms, using cell lysates or samples of secreted enzyme. Our results demonstrated that the MALDI-MS-based enzyme assay system would be useful for investigating bacterial glucoside hydrolases in a high-throughput manner.

• 한국건설관리학회논문집
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• 제25권2호
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• pp.69-80
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• 2024

Currently rebar spacing inspection is carried out by human inspectors who heavily rely on their individual experience, lacking a guarantee of objectivity and accuracy in the inspection process. In addition, if incorrectly placed rebars are identified, the inspector need to correct them. Recently, laser scanning and AR technologies have been widely used because of their merits of measurement accuracy and visualization. This study proposes a technology for rebar spacing inspection and fixing by combining laser scanning and AR technology. First, scan data acquisition of rebar layers is performed and the raw scan data is processed. Second, AR-based visualization and fixing are performed by comparing the design model with the model generated from the scan data. To verify the developed technique, performance comparison test is conducted by comparing with existing drawing-based method in terms of inspection time, error detection rate, cognitive load, and situational awareness ability. It is found from the result of the experiment that the AR-based rebar inspection and fixing technology is faster than the drawing-based method, but there was no significant difference between the two groups in error identification rate, cognitive load, and situational awareness ability. Based on the experimental results, the proposed AR-based rebar spacing inspection and fixing technology is expected to be highly useful throughout the construction industry.

• Nuclear Engineering and Technology
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• 제48권4호
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• pp.1047-1057
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• 2016

Design engineering process for field programmable gate array (FPGA)-based reactor trip functions are developed in this work. The process discussed in this work is based on the systems engineering approach. The overall design process is effectively implemented by combining with design and implementation processes. It transforms its overall development process from traditional V-model to Y-model. This approach gives the benefit of concurrent engineering of design work with software implementation. As a result, it reduces development time and effort. The design engineering process consisted of five activities, which are performed and discussed: needs/systems analysis; requirement analysis; functional analysis; design synthesis; and design verification and validation. Those activities are used to develop FPGA-based reactor bistable trip functions that trigger reactor trip when the process input value exceeds the setpoint. To implement design synthesis effectively, a model-based design technique is implied. The finite-state machine with data path structural modeling technique together with very high speed integrated circuit hardware description language and the Aldec Active-HDL tool are used to design, model, and verify the reactor bistable trip functions for nuclear power plants.

• Journal of information and communication convergence engineering
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• 제10권2호
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• pp.141-148
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• 2012

This paper presents a simple but efficient scheme incorporating a reputation-based approach and a cross-layer approach, called the SIM scheme, for maintaining reliable connectivity and high performance in ad-hoc wireless networks. The SIM scheme incorporates the following two things: an ad-hoc routing scheme with a reputation-based approach exploiting the game theory concept based on an evolutionarily stable strategy, and a cross-layer approach between the network layer and the transport layer employing a reputation-based approach.

• ETRI Journal
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• 제31권4호
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• pp.457-459
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• 2009

The optimum maximum voiced frequency (MVF) estimation-based two-band excitation for hidden Markov model-based speech synthesis is presented. An analysis-by-synthesis scheme is adopted for the MVF estimation which leads to the minimum spectral distortion of synthesized speech. Experimental results show that the proposed method significantly improves synthetic speech quality.

• Current Optics and Photonics
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• 제5권6호
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• pp.672-679
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• 2021

We propose a high-speed layer-based algorithm for synthesizing computer-generated holograms (CGHs), featuring sparsity-based image segmentation and computational parallelism. The sparsity-based image segmentation of layer-based three-dimensional scenes leads to considerable improvement in the efficiency of CGH computation. The efficiency enhancement of the proposed algorithm is ascribed to the field localization of the fast Fourier transform (FFT), and the consequent reduction of FFT computational complexity.