• International journal of advanced smart convergence
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• v.12 no.4
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.959-965
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• 2024

The High Temperature Test Unit (HTTU) was an experimental set-up to conduct separate and integral effects tests of the Pebble Bed Modular Reactor (PBMR) core. The annular core consisted of a randomly packed bed of uniform spheres. Natural convection tests using both nitrogen and helium, and forced convection tests using nitrogen, were conducted. The maximum material temperature achieved during forced convection testing was 1200 ℃. This paper presents the numerical analysis of the flow and temperature distribution for a forced convection test using 3D CFD as well as a 1D systems-CFD computer code. Several modelling approaches are possible, ranging from a fully explicit to a semi-implicit method that relies on correlations of their associated phenomena. For the comparison between codes, the analysis was performed using a porous media approach, where the conduction and radiative heat transfer were lumped together as an effective thermal conductivity and the convective heat transfer was correlated between the solid and gas phases. The results from both codes were validated against the experimental measurements. Favourable results were obtained, in particular by the systems-CFD code with minimal computational and time requirements.

• Journal of Web Engineering
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• v.19 no.2
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• pp.139-166
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• 2020

The functions, capabilities, and effects produced by the application services of cyber physical systems (CPS) are usually consumed by users performing their daily activities in a variety of environmental conditions. Thus, it is critical to ensure that those systems neither interfere with human activities nor harm the users involved. In this paper, we propose a framework for testing and verifying the safety and reliability of CPS services from the perspectives of CPS environments and users. The framework provides an environmentaware testing method by which the efficiency of testing CPS services can be improved by prioritizing CPS environments and by applying machinelearning techniques. The framework also includes a metric by which we can automate the test of the most effective services that deliver effects from physical devices to users. Additionally, the framework provides a computational model that assesses mental workloads to test whether a CPS service can cause cognitive depletion or contention problems for users. We conducted a series of experiments to show the effectiveness of the proposed approaches for ensuring the safety and reliability of CPS application services during the development and operation phases.

• Journal of applied mathematics & informatics
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• v.42 no.5
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• pp.1195-1210
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• 2024

This research aims to determine an optimal (best) solution for transporting the logistics at a minimum cost from various sources to various destinations. We proposed a new algorithm for the initial basic feasible solution (IBFS). Developing a new IBFS is the first step towards finding the optimal solution. A new approach for the initial basic feasible solution that reduces iterations and produces the best answer in the initial process of the transportation issue. Different IBFS approaches have been generated in the literature review. Some statistical fundamentals, such as normal distribution and the root mean square technique, are employed to find new IBFS. A TP is transformed into a normal distribution, and penalties are determined using the root mean square method. Excel Solver is used to calculate normal distribution values. The second step involves using a stepping-stone approach to compute the optimum solution. The results of our study were calculated using numerical examples and contrasted with a few other methodologies, such as Vogel's approximation, the Continuous Allocation Method (CAM), the Supply Demand Repair Method (SDRM), and the Karagul-Sahin Approximation Method (KSAM). The conclusion of our proposed method gives more accurate results than the existing approach.

• Earthquakes and Structures
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• v.27 no.4
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• pp.285-302
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• 2024

Conducting nonlinear pushover analysis typically demands intricate and resource-intensive computational efforts, involving a highly iterative process necessary for meeting both design-defined and requirements of codes in performance-based design. This study presents a computer-based technique for reinforced concrete (RC) buildings, incorporating optimization numerical approaches, optimality criteria and pushover analysis to automatically enhance seismic design performance. The optimal design of concrete beams, columns and shear walls in concrete frames is presented using the artificial bee colony optimization algorithm. The methodology is applied to three frames: a 4-story, an 8-story and a 12-story. These structures are designed to minimize overall weight while satisfying the levels of performance including Life Safety (LS), Collapse Prevention (CP), and Immediate Occupancy (IO). The process involves three main steps: first, optimization codes are implemented in MATLAB software, and the OpenSees software is used for nonlinear static analysis. By solving the optimization problem, several top designs are obtained for each frame and shear wall. Pushover analysis is conducted considering the constraints on relative displacement and plastic hinge rotation based on the nonlinear provisions of the FEMA356 nonlinear provisions to achieve each level of performance. Subsequently, convergence, pushover, and drift history curves are plotted for each frame, and leading to the selection of the best design. The results demonstrate that the algorithm effectively achieves optimal designs with reduced weight, meeting the desired performance criteria.

• Smart Structures and Systems
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• v.33 no.5
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• pp.333-347
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• 2024

There has been an increasing interest in the construction of smart buildings that can actively monitor and react to their surroundings. The capacity of these intelligent structures to precisely predict and respond to deflection is a crucial feature that guarantees both their structural soundness and efficiency. Conventional techniques for determining deflection often depend on intricate mathematical models and computational simulations, which may be time- and resource-consuming. Artificial intelligence (AI) algorithms have become a potent tool for anticipating and controlling deflection in intelligent structures in response to these difficulties. The term "deflection-aware smart structures" in this sense refers to constructions that have AI algorithms installed that continually monitor and analyses deflection data in order to proactively detect any problems and take appropriate action. These structures anticipate deflection across a range of operating circumstances and environmental factors by using cutting-edge AI approaches including deep learning, reinforcement learning, and neural networks. AI systems are able to predict real-time deflection with high accuracy by using data from embedded sensors and actuators. This capability enables the systems to identify intricate patterns and linkages. Intelligent buildings have the potential to self-correct in order to reduce deflection and maximize performance. In conclusion, the development of deflection-aware smart structures is a major stride forward for structural engineering and has enormous potential to enhance the performance, safety, and dependability of designed systems in a variety of industries.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.79-89
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• 2011

Recent development of embedded processors makes it possible to play back video contents in real-time on portable devices. Because of their limited battery capacity and low computational performance, however, portable devices still have significant problems in real-time decoding of high quality or high resolution compressed video. Although previous approaches are successful in achieving complexity-scalable decoder by controlling computational complexity of decoding elements, they cause significant objective quality loss coming from mismatch between encoder and decoder. In this paper, we propose a selective B slice skip-decoding method to implement a low complexity video decoder. The proposed method performs selective skip decoding process of B slice which satisfies the proposed conditions. The skipped slices are reconstructed by simple reconstruction method utilizing adjacent reconstructed pictures. Experimental result shows that proposed method not only reduces computational complexity but also maintains subjective visual quality.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.49-49
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• 2010

The most commonly used numerical modelling techniques for acoustics and vibration are based on element based techniques, such as the nite element and boundary element method. Due to the huge computational eorts involved, the use of these deterministic techniques is practically restricted to low-frequency applications. For high-frequency modelling, probabilistic techniques such as SEA are well established. However, there is still a wide mid-frequency range, for which no adequate and mature prediction techniques are available. In this frequency range, the computational eorts of conventional element based techniques become prohibitively large, while the basic assumptions of the probabilistic techniques are not yet valid. In recent years, a vast amount of research has been initiated in a quest for an adequate solution for the current midfrequency problem. One family of research methods focuses on novel deterministic approaches with an enhanced convergence rate and computational eciency compared to the conventional element based methods in order to shift the practical frequency limitation towards the mid-frequency range. Amongst those techniques, a wave based prediction technique using an indirect Tretz approach is being developed at the K.U.Leuven - Noise and Vibration Research group. This paper starts with an outline of the major features of the mid-frequency modelling challenge and provides a short overview of the current research activities in response to this challenge. Next, the basic concepts of the wave based technique and its hybrid coupling with nite element schemes are described. Various validations on two- and threedimensional acoustic, elastic, poro-elastic and vibro-acoustic examples are given to illustrate the potential of the method and its benecial performance as compared to conventional element based methods. A closing part shares some views on the open issues and future research directions.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1793-1802
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• 2013

Various approaches for sound source segregation have been proposed. Among these approaches, frequency domain binaural model(FDBM) has the advantages of low computational load and effective howling cancellation. A binaural hearing assistance system based on FDBM has been proposed. This system can enhance desired signal based on the directivity information. Although FDBM has been evaluated in terms of signal-to-noise ratio (SNR) and coherence function, the evaluation results do not always agree with the human impressions. These evaluation methods provide physical measures, and do not take account of perceptual aspect of human being. Considering a binaural hearing assistance system as a one of major applications, the quality of segregated sound should keep level enough. In the paper, signal segregation performance by means of FDBM is evaluated by three objective methods, i.e., SNR, coherence and Perceptual Evaluation of Speech Quality(PESQ), to discuss the characteristic of FDBM on the sound source segregation performance. The simulation's evaluation results show that FDBM improves the quality of the left and right channel signals to an equivalent level. And the results suggest the possibility that PESQ provides a more useful measure than SNR and coherence in terms of the segregation performance of FDBM. The evaluation results by PESQ show the effects from segregation parameters and indicate appropriate parameters under the conditions. In the paper, signal segregation performance by means of FDBM is evaluated by three objective methods, i.e., SNR, coherence and PESQ, to discuss the characteristic of FDBM on the sound source segregation performance. The simulation's evaluation results show that FDBM improves the quality of the left and right channel signals to an equivalent level. And the results suggest the possibility that PESQ provides a more useful measure than SNR and coherence in terms of the segregation performance of FDBM. The evaluation results by PESQ show the effects from segregation parameters and indicate appropriate parameters under the conditions.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.4
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• pp.82-92
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• 2006

In the field of image recognition, research on face recognition has recently attracted a lot of attention. The most important step in face recognition is automatic eye detection researched as a prerequisite stage. Existing eye detection methods for focusing on the frontal face can be mainly classified into two categories: active infrared(IR)-based approaches and image-based approaches. This paper proposes an eye region detection method in non-frontal faces. The proposed method is based on the edge--based method that shows the fastest computation time. To extract eye region in non-frontal faces, the method uses edge orientationhistogram of the global region of faces. The problem caused by some noise and unfavorable ambient light is solved by using proportion of width and height for local information and relationship between components for global information in approximately extracted region. In experimental results, the proposed method improved precision rates, as solving 3 problems caused by edge information and achieves a detection accuracy of 83.5% and a computational time of 0.5sec per face image using 300 face images provided by The Weizmann Institute of Science.