• Wind and Structures
• /
• v.36 no.6
• /
• pp.379-392
• /
• 2023

Structural health monitoring is used to ensure the well-being of civil structures by detecting damage and estimating deterioration. Wind flow applies external loads to high-rise buildings, with the horizontal force component of the wind causing structural displacements in high-rise buildings. This study proposes a deep learning-based predictive model for measuring lateral displacement response in high-rise buildings. The proposed long short-term memory model functions as a sequence generator to generate displacements on building floors depending on the displacement statistics collected on the top floor. The model was trained with wind-induced displacement data for the top floor of a high-rise building as input. The outcomes demonstrate that the model can forecast wind-induced displacement on the remaining floors of a building. Further, displacement was predicted for each floor of the high-rise buildings at wind flow angles of 0° and 45°. The proposed model accurately predicted a high-rise building model's story drift and lateral displacement. The outcomes of this proposed work are anticipated to serve as a guide for assessing the overall lateral displacement of high-rise buildings.

• Wind and Structures
• /
• v.38 no.1
• /
• pp.75-91
• /
• 2024

Reliable wind signal reconstruction can be beneficial to the operational safety of long-span bridges. Non-Gaussian characteristics of wind signals make the reconstruction process challenging. In this paper, non-Gaussian wind signals are converted into a combined prediction of two kinds of features, actual wind speeds and wind angles of attack. First, two decomposition techniques, empirical mode decomposition (EMD) and variational mode decomposition (VMD), are introduced to decompose wind signals into intrinsic mode functions (IMFs) to reduce the randomness of wind signals. Their principles and applicability are also discussed. Then, four artificial intelligence (AI) algorithms are utilized for wind signal reconstruction by combining the particle swarm optimization (PSO) algorithm with back propagation neural network (BPNN), support vector regression (SVR), long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM), respectively. Measured wind signals from a bridge site in a deep-cutting gorge are taken as experimental subjects. The results showed that the reconstruction error of high-frequency components of EMD is too large. On the contrary, VMD fully extracts the multiscale rules of the signal, reduces the component complexity. The combination of VMD-PSO-Bi-LSTM is demonstrated to be the most effective among all hybrid models.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.8
• /
• pp.2082-2102
• /
• 2024

Accurate segmentation of magnetic resonance (MR) images is crucial for providing doctors with effective quantitative information for diagnosis. However, the presence of weak boundaries, intensity inhomogeneity, and noise in the images poses challenges for segmentation models to achieve optimal results. While deep learning models can offer relatively accurate results, the scarcity of labeled medical imaging data increases the risk of overfitting. To tackle this issue, this paper proposes a novel fuzzy c-means (FCM) model that integrates a deep learning approach. To address the limited accuracy of traditional FCM models, which employ Euclidean distance as a distance measure, we introduce a measurement function based on the skewed normal distribution. This function enables us to capture more precise information about the distribution of the image. Additionally, we construct a regularization term based on the Kullback-Leibler (KL) divergence of high-confidence deep learning results. This regularization term helps enhance the final segmentation accuracy of the model. Moreover, we incorporate orthogonal basis functions to estimate the bias field and integrate it into the improved FCM method. This integration allows our method to simultaneously segment the image and estimate the bias field. The experimental results on both simulated and real brain MR images demonstrate the robustness of our method, highlighting its superiority over other advanced segmentation algorithms.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.7
• /
• pp.1234-1242
• /
• 2003

In this paper we present a simple and efficient robust optimal design formulation for MEMS structures and its application to a resonant-type micro probe. The basic idea is to use the gradient index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-effective and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation. This method, although shown for MEMS structures, may as well be easily applied to conventional mechanical structures where information on uncertainties is lacking but robustness is highly important.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.4
• /
• pp.373-378
• /
• 2002

In fuzzy inferencing, most of conventional fuzzy controllers have problems of speed down in floating point operations of fuzzy membership functions in (0,1) as compared with integer operations. Therefore, in this paper, we propose a high-speed fuzzy controller with only integer operations. In this, for fast fuzzy computations, we use a scan line conversion algorithm to convert lines of each fuzzy linguistic term to the set of the closest integer pixels. We also implement a GUI (Graphic User Interface) application program for the convenient environments to modify and input fuzzy membership functions.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.16 no.2
• /
• pp.43-59
• /
• 2005

Traditional paper records have to be preserved in the original form to ensure the authenticity. On the other hand. electronic records have to be continuously changed in content itself or metadata to be preserved in long-term period, so the proof of the legality of each change made so far and the proof of the protection against all the illegal changes are the essential. to ensure these requirements. We need some functions including the authentication of original captured records. the protection of records against the loss or forgery, the authentication of preserved records, and the treatment of authentication-failed records. This paper explains the fragility of authenticity for electronic records, identifies the functions needed, suggests the implementation idea, and describes the overall management polity for electronic records to ensure the authenticity.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.49 no.3
• /
• pp.11-20
• /
• 2007

Estimation of crop consumptive use is a key term of agricultural water resource systems design and operation. The 10-year return period drought has special aspects as a reference period in design process of irrigation systems in terms of agricultural water demand analysis so that crop evapotranspiration (ETc) about the return period also has to be analyzed to assist understanding of crop water requirement of paddy rice. In this study, The ETc of 10-year return period drought was computed using frequency analysis by 54 meteorological stations. To find an optimal probability distribution, 8 types of probability distribution function were tested by three the goodness of fit tests including ${\chi}^2$(Chi-Square), K-S (Kolmogorov-Smirnov) and PPCC (Probability Plot Correlation Coefficient). Optimal probability distribution function was selected the 2-parameter Log-Normal (LN2) distribution function among 8 distribution functions. Using the two selected distribution functions, the ETc of 10-year return period drought was estimated for 54 meteorological stations and compared with prior study results suggested by other researchers.

• The Korean Journal of Physiology
• /
• v.21 no.2
• /
• pp.305-311
• /
• 1987

To evaluate training effect, the step exercise was loaded to three mem for nine weeks. Step score, cardiopulmonary functions and blood constituents were measured before, during and after the test exercise (50 cm-step exercise and treadmill running), and were compared with the pre-tranining values. The results were as follows: 1) By the training, Harvard step score increased remarkably, expecially in the early stage of training. 2) The post-training values of maximal oxygen uptake increased very significantly and it seemed to be due to increases of stroke volume and tissue oxygen extraction. 3) After the training, the degree of increase in expired volume was small during the treadmill exercise. 4) By the training, increasing rate of respiratory quotient lessened during the exercise and it was considered to be caused by the decreases of carbohydrate consumption and anaerobic metabolism. 5) The blood cholesterol concentrations were harldy changed with this degree of training. 6) The blood lactate level decreased during the recovery periods and the values of the recovery 0 and 5 minutes decreased remarkably, in comparison with the pre-trained values. The above results suggest that the 9 week-training of the step exercise brings about the enhancement of circulatory functions and tissue oxygen utilization, and changes of food-stuffs used during the exercise.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.37 no.2
• /
• pp.28-37
• /
• 2000

An almost exact eigenvalue equation for optical fibers with graded-index profile Is derived mathematically based on a combination of the modified Airy functions and the WKB trial solution. By applying proper boundary conditions, a phase shift correction term $\delta$ is found out which improves the inherent error problems of the conventional WKB method. It is shown through computer simulations that results of the derived eigenvalue equation are in excellent agreement with those of the finite-element method.

• Aerospace Engineering and Technology
• /
• v.11 no.2
• /
• pp.129-139
• /
• 2012

This paper will describe the structure and characteristics of operator training system which was developed to maintain the quality of operational ability for COMS (Communication, Ocean and Meteorological Satellite) operators during a long-term nominal operations of missions and a contingency operations against an occurrence of anomaly. In particular it will present benefits and expected effects of the training system with a focus on three parts which are functions especially for trainer-friendly failure injection, an automatic sequencer of training scenario based on the predefined plan and additional functions of the existing COMS simulator. Furthermore, it will present a practical example of training on the training system to understand the overall mechanism of training process.