• Structural Engineering and Mechanics
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• v.11 no.5
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• pp.485-502
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• 2001

Modem soft computing methods, such as neural networks, evolutionary models and fuzzy logic, are mainly inspired by the problem solving strategies the biological systems use in nature. As such, the soft computing methods are fundamentally different from the conventional engineering problem solving methods, which are based on mathematics. In the author's opinion, these fundamental differences are the key to the full understanding of the soft computing methods and in the realization of their full potential in engineering applications. The main theme of this paper is to discuss the fundamental differences between the soft computing methods and the mathematically based conventional methods in engineering problems, and to explore the potential of soft computing methods in new ways of formulating and solving the otherwise intractable engineering problems. Inverse problems are identified as a class of particularly difficult engineering problems, and the special capabilities of the soft computing methods in inverse problems are discussed. Soft computing methods are especially suited for engineering design, which can be considered as a special class of inverse problems. Several examples from the research work of the author and his co-workers are presented and discussed to illustrate the main points raised in this paper.

• Journal of Engineering Education Research
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• v.23 no.1
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• pp.59-64
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• 2020

The purpose of this study is to develop capstone design model of gender analysis methods suitable for engineering education field and examine improvements and effects by applying it to actual lessons for biomedical engineering students. Case study was performed to achieve the purpose of the study. Twelve gender analysis methods were applied to 'biomedical engineering capstone design' which was major course offered by department of biomedical engineering at J university. After the students understood how to analyze gender analysis methods and cases, they decided project topics and presented what gender analysis methods were applied for each project. Additionally, the results of analysis showed that the students were more able to understand the differences between men and women of all ages and try to narrow down the differences. They also found that they could contribute to development of new added value of knowledge and technology that reflected the needs of both men and women by applying gender analysis methods in system development.

• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.135-151
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• 2022

The generalized displacement method is a nonlinear solution scheme that follows the equilibrium path of the structure based on the development of the generalized displacement. This method traces the path uniformly with a constant amount of generalized displacement. In this article, we first develop higher-order generalized displacement methods based on multi-point techniques. According to the concept of generalized stiffness, a relation is proposed to adjust the generalized displacement during the path-following. This formulation provides the possibility to change the amount of generalized displacement along the path due to changes in generalized stiffness. We, then, introduce higher-order algorithms of variable generalized displacement method using multi-point methods. Finally, we demonstrate with numerical examples that the presented algorithms, including multi-point generalized displacement methods and multi-point variable generalized displacement methods, are capable of following the equilibrium path. A comparison with the arc length method, generalized displacement method, and multi-point arc-length methods illustrates that the adjustment of generalized displacement significantly reduces the number of steps during the path-following. We also demonstrate that the application of multi-point methods reduces the number of iterations.

• Journal of Engineering Education Research
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• v.21 no.6
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• pp.74-80
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• 2018

This paper proposes practical teaching methods for efficient progress of project-based learning in engineering design education. Engineering design courses consist of three categories; introductory, individual and capstone design courses. This study concentrates on the case of individual design courses. Individual design courses act as bridges between introductory and capstone design courses and deal with applicable projects based on theoretical frameworks. In this study, practical teaching methods are applied to Artificial Intelligence curriculum as an individual design course for Juniors in Computer Engineering Major. The results on application of practical teaching methods show relatively positive in all aspects.

• Journal of Engineering Education Research
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• v.20 no.2
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• pp.31-38
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• 2017

In this study, specific teaching methods of lecturing and improved discussion methods (combining discussion and problem-based learning) were selected and applied for each major subject and learning content area in the fields of engineering, language, and social sciences. Then, the selected teaching methods were examined to determine the most effective learning contents. Finally, in order to determine the most effective teaching methods, a survey on student satisfaction was analyzed statistically. The results showed that students preferred teaching methods that combine lectures and improved discussion methods to the traditional method of only lectures. Therefore, this research proposes the combined teaching method for each major subject and learning content area.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.587-591
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• 2013

Measuring the process of construction operations for productivity improvement remains a difficult task for most construction companies due to the manual effort required in most activity measurement methods. There are many ways to measuring the process. But past measurement methods was inefficient. Because they needed a lot of manpower and time. So, this article focus on the vision-based object recognition and tracking methods for automated construction. These methods have the advantage of efficient that human intervention was reduced. Therefore, this article is analyzed the performance of vision-based methods in the construction sites and is expected to contribute to selection of vision-based methods.

• Journal of Engineering Education Research
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• v.16 no.4
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• pp.30-36
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• 2013

Applying intuitive learning method on engineering education, especially for the mechanical engineering, is hardly found from the previous case studies and is not easily proved its beneficial verification. Verbal repetition is also rarely used to investigate its positive effects on educational methodology for both science and engineering disciplines. To prove the education effects of these two methods; we used intuitive thinking time period at the beginning of each lecture and let students repeat the concepts and the equations verbally. These two methods were related to the subjects of each lecture, and were used for students to try to draw engineering thinking from natural phenomena that they could easily experience in daily life. The methods could help them to memorize theoretical ideas. We investigated the effects of intuition and verbal repetition methods by comparing the scores of final exam with those of midterm exam. The results revealed significant improvement; 77.6% of the students achieved higher score in their final exam compared to midterm exam. We plan to investigate qualitative contributions of intuition and verbal repetition methods to the students' achievement for the further research.

• Current Optics and Photonics
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• v.8 no.3
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• pp.282-299
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• 2024

Target detection (TD) is a research hotspot in the field of hyperspectral imaging (HSI). Traditional TD methods often mine targets from HSIs under a single imaging condition, without considering the influence of imaging conditions. In fact, the spectra of ground objects in HSIs are uncertain and affected by the imaging conditions (weather, atmospheric, light, time, and other angle conditions including zenith angle). Hyperspectral data changes under different imaging conditions. Therefore, the detection result for a single imaging condition cannot accurately reflect the effectiveness of the detection method used. It is necessary to analyze the performance of various detection methods under different imaging conditions, to find a more applicable detection method. In this paper, we study the performance of TD methods under various land-based imaging conditions. We first summarize classical TD methods and evaluation methods. Then, the detection effects under various imaging conditions are analyzed. Finally, the concepts of the stability coefficient (SC) and effective area under the curve (EAUC) are proposed to comprehensively evaluate the applicability of detection methods under land-based imaging conditions, in terms of both detection accuracy and stability. This is conducive to our selection of detection methods with better applicability in land-based contexts, to improve detection accuracy and stability.

• Journal of Biosystems Engineering
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• v.38 no.2
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• pp.149-162
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• 2013

Purpose: In image segmentation via thresholding, Otsu and Kapur methods have been widely used because of their effectiveness and robustness. However, computational complexity of these methods grows exponentially as the number of thresholds increases due to the exhaustive search characteristics. Methods: Particle swarm optimization (PSO) and genetic algorithms (GAs) can accelerate the computation. Both methods, however, also have some drawbacks including slow convergence and ease of being trapped in a local optimum instead of a global optimum. To overcome these difficulties, we proposed two new multi-level thresholding methods based on Bacteria Foraging PSO (BFPSO) and real-coded GA algorithms for fast segmentation. Results: The results from BFPSO and real-coded GA methods were compared with each other and also compared with the results obtained from the Otsu and Kapur methods. Conclusions: The proposed methods were computationally efficient and showed the excellent accuracy and stability. Results of the proposed methods were demonstrated using four real images.

• Structural Engineering and Mechanics
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• v.71 no.1
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• pp.57-63
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• 2019

During the last two decades, much joint research regarding vibration based methods has been done, leading to developing various algorithms and techniques. These algorithms and techniques can be divided into modal methods and signal methods. Although modal methods have been widely used for health monitoring and damage detection, signal methods due to higher efficiency have received considerable attention in various fields, including aerospace, mechanical and civil engineering. Signal-based methods are derived directly from the recorded responses through signal processing algorithms to detect damage. According to different signal processing techniques, signal-based methods can be divided into three categories including time domain methods, frequency domain methods, and time-frequency domain methods. The frequency domain methods are well-known and interest in using them has increased in recent years. To determine dynamic behaviours, to identify systems and to detect damages of bridges, different methods and algorithms have been proposed by researchers. In this study, a new algorithm to detect seismic damage in the bridge's piers is suggested. To evaluate the algorithm, an analytical model of a bridge with simple spans is used. Based on the algorithm, before and after damage, the bridge is excited by a sine force, and the piers' responses are measured. The dynamic specifications of the bridge are extracted by Power Spectral Density function. In addition, the Least Square Method is used to detect damage in the bridge's piers. The results indicate that the proposed algorithm can identify the seismic damage effectively. The algorithm is output-only method and measuring the excitation force is not needed. Moreover, the proposed approach does not need numerical models.