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Nguyen Duc Anh,Pham Van Thanh,Doan Tu Lap,Nguyen Tuan Khai,Tran Van An,Tran Duc Tan,Nguyen Huu An,Dang Nhu Dinh 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.2
Forest fires inflict great losses of human lives and serious damages to ecological systems. Hence, numerous fire detection methods have been proposed, one of which is fire detection based on sensors. However, these methods reveal several limitations when applied in large spaces like forests such as high cost, high level of false alarm, limited battery capacity, and other problems. In this research, we propose a novel forest fire detection method based on image processing and correlation coefficient. Firstly, two fire detection conditions are applied in RGB color space to distinguish between fire pixels and the background. Secondly, the image is converted from RGB to YCbCr color space with two fire detection conditions being applied in this color space. Finally, the correlation coefficient is used to distinguish between fires and objects with fire-like colors. Our proposed algorithm is tested and evaluated on eleven fire and non-fire videos collected from the internet and achieves up to 95.87% and 97.89% of F-score and accuracy respectively in performance evaluation.
An Overall Product Design Process Using Robust Design and Analytic Hierarchy Process (AHP)
Nguyen, Nhu-Van,Azamatov, Adulaziz,Tran, Si Bui Quang,Choi, Seok-Min,Lee, Jae-Woo,Byun, Yung-Hwan The Korean Society of Systems Engineering 2007 시스템엔지니어링학술지 Vol.3 No.2
In this study, an overall product design process will be presented by using the Analytic Hierarchy Process(AHP) and robust design. From the conceptual design stage, the logical methods are used to select the appropriate concepts satisfying the customer requirements and the other conditions. The next phase is the embodiment design phase in which the deterministic and robust design approach are used to obtain the improvement in product design. Typically, this approach is applied for developing the simple bookshelf design. The results show the efficient approach which can be supported to develop the new product.
Repetitively Enhanced Neural Networks Method for Complex Engineering Design Optimization Problems
Nhu Van Nguyen,Maxim Tyan,Jae-Woo Lee,Sangho Kim 한국전산유체공학회 2014 한국전산유체공학회 학술대회논문집 Vol.2014 No.5
Repetitively Enhanced Neural Networks (RENN) method is developed and presented for complex and implicit engineering design problems. Enhance neural networks module constructs an accurate surrogate models and ensures for avoiding over-fitting during neural networks training from supervised learning data. The optimizer is executed by the enhanced neural networks models to seek for a tentative optimum point. It is repetitively added into the supervised learning data set to refine surfaces till the RENN tolerance reaches. The RENN method demonstrates the effectiveness and feasibility for 2D highly non-linear numerical example and the structure design of two-member frame reaching convergent solution at 10 and 14 iterations respectively at the maximum error of 1% when compared with the exact solution. Then, the RENN method is applied for a long endurance unmanned aerial vehicle (UAV) airfoil design optimization. Class/Shape function transformation (CST) geometry parameterization method represents an accurate UAV airfoil with 10 geometry design variables. The high-fidelity analysis solvers with structured mesh for airfoil is used for UAV airfoil design problem. The total 88 experiment points are required to obtain an optimal UAV airfoil configuration after 13 RENN iterations and 75 initial experiments by Latin Hypercube method in reasonable turnaround time. The optimal UAV airfoil shows 10.8% in drag reduction in cruise condition and improvement in the maximum lift coefficient and stall angle of attack.
Adaptive Multifidelity Constraints Method for Efficient Multidisciplinary Missile Design Framework
Van Nguyen, Nhu,Tyan, Maxim,Jin, Sunghyun,Lee, Jae-Woo American Institute of Aeronautics and Astronautics 2016 Journal of spacecraft and rockets Vol.53 No.1
<P>The adaptive multifidelity constraints method is developed and proposed to ensure the convergence of significant constraints to high-fidelity results for increasing the reliability and robustness of an optimal configuration at the conceptual design stage without any noticeable turnaround time. The adaptive multifidelity constraints algorithm is demonstrated for two numerical examples, with savings of 58.6 and 64% in high-fidelity evaluations, to obtain the convergence of adaptive constraints to high-fidelity results. The implementation of the adaptive multifidelity constraints algorithm is integrated into the multidisciplinary air-to-ground missile design optimization framework. The lift, drag, and longitudinal control effectiveness coefficient constraints are considered as multifidelity constraints due to their importance in the sizing of air-to-ground missile control surfaces for diving and attacking missions. The optimal air-to-ground missile configuration using adaptive multifidelity constraints yields more reliable and robust results compared with the optimal air-to-ground missile configuration using the low-fidelity analysis only, whereas the adaptive constraints converge into the high-fidelity results.</P>
Nguyen Nhu-Van,Wan-Sub Kim,Jae-Woo Lee,Yung-Hwan Byun 한국항공우주학회 2008 한국항공우주학회 학술발표회 논문집 Vol.- No.-
The aerodynamic characteristics of various short and medium range air-to-air missiles are predicted by using the U.S. Air Force Missile DATCOM (97 version), which predicts the aerodynamic forces, moments, and stability derivatives of axi-symmetric and non-axisymmetric missile configurations for the wide range of angle of attacks and Mach numbers. To validate the accuracy of the code, the normal force, pitching moment and axial force of two missile configurations, Air Intercept Missile, AIM 7 and a generic missile shape with a high-aspect-ratio wing-body-tail configuration, are compared with the experimental data and the results using AeroPrediction 98 (AP98). The error for each aerodynamic component is calculated and evaluated. Next. the aerodynamic characteristics of AIM 9B and AMRAM 120B are evaluated and aero-data base are constructed for the fixed control surfaces. Finally, the aerodynamic optimization of the short range missile is performed using the Neural Networks. and shows the improvement in the range of missile by optimizing the wing configuration with four design variables and the finesses ratio.