• Title/Summary/Keyword: multi-level-optimization

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Optimal sustainable design of steel-concrete composite footbridges considering different pedestrian comfort levels

  • Fernando L. Tres Junior;Guilherme F. Medeiros;Moacir Kripka
    • Steel and Composite Structures
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    • v.51 no.6
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    • pp.647-659
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    • 2024
  • Given the increased interest in enhancing structural sustainability, the current study sought to apply multiobjective optimization to a footbridge with a steel-concrete composite I-girder structure. It was considered as objectives minimizing the cost for building the structure, the environmental impact assessed by CO2 emissions, and the vertical accelerations created by human-induced vibrations, with the goal of ensuring pedestrian comfort. Spans ranging from 15 to 25 meters were investigated. The resistance of the slab's concrete, the thickness of the slab, the dimensions of the welded steel I-profile, and the composite beam interaction degree were all evaluated as design variables. The optimization problem was handled using the Multiobjective Harmony Search (MOHS) metaheuristic algorithm. The optimization results were used to generate a Pareto front for each span, allowing us to assess the correlations between different objectives. By evaluating the values of design variables in relation to different levels of pedestrian comfort, it was identified optimal values that can be employed as a starting point in predimensioning of the type of structure analyzed. Based on the findings analysis, it is possible to highlight the relationship between the structure's cost and CO2 emission objectives, indicating that cost-effective solutions are also environmentally efficient. Pedestrian comfort improvement is especially feasible in smaller spans and from a medium to a maximum level of comfort, but it becomes expensive for larger spans or for increasing comfort from minimum to medium level.

Optimization of Double Polishing Pad for STI-CMP Applications (STI-CMP 적용을 위한 이중 연마 패드의 최적화)

  • Park, Seong-U;Seo, Yong-Jin;Kim, Sang-Yong
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.51 no.7
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    • pp.311-315
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    • 2002
  • Chemical mechanical polishing (CMP) process was required for the global planarization of inter-metal dielectric(IMD), inter-level dielectric (ILD) layers of multi-layer interconnections. In this paper, we studied the characteristics of polishing pad, which can apply shallow trench isolation (STI)-CMP process for global planarization of multi-level interconnection structure. Also, we investigated the effects of different sets of polishing pad, such as soft and hard pad. As an experimental result, hard pad showed center-fast type, and soft pad showed edge-fast type. Totally, the defect level has shown little difference, however, the counts of scratch was detected less than 2 on JR111 pad. Through the above results, we can select optimum polishing pad, so we can expect the improvements of throughput and device yield.

Compact implementations of Curve Ed448 on low-end IoT platforms

  • Seo, Hwajeong
    • ETRI Journal
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    • v.41 no.6
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    • pp.863-872
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    • 2019
  • Elliptic curve cryptography is a relatively lightweight public-key cryptography method for key generation and digital signature verification. Some lightweight curves (eg, Curve25519 and Curve Ed448) have been adopted by upcoming Transport Layer Security 1.3 (TLS 1.3) to replace the standardized NIST curves. However, the efficient implementation of Curve Ed448 on Internet of Things (IoT) devices remains underexplored. This study is focused on the optimization of the Curve Ed448 implementation on low-end IoT processors (ie, 8-bit AVR and 16-bit MSP processors). In particular, the three-level and two-level subtractive Karatsuba algorithms are adopted for multi-precision multiplication on AVR and MSP processors, respectively, and two-level Karatsuba routines are employed for multi-precision squaring. For modular reduction and finite field inversion, fast reduction and Fermat-based inversion operations are used to mitigate side-channel vulnerabilities. The scalar multiplication operation using the Montgomery ladder algorithm requires only 103 and 73 M clock cycles on AVR and MSP processors.

Potential Anomaly Separation and Archeological Site Localization Using Genetically Trained Multi-level Cellular Neural Networks

  • Bilgili, Erdem;Goknar, I. Cem;Albora, Ali Muhittin;Ucan, Osman Nuri
    • ETRI Journal
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    • v.27 no.3
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    • pp.294-303
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    • 2005
  • In this paper, a supervised algorithm for the evaluation of geophysical sites using a multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. ML-CNN is a stochastic image processing technique based on template optimization using neighborhood relationships of the pixels. The separation/enhancement and border detection performance of the proposed method is evaluated by various interesting real applications. A genetic algorithm is used in the optimization of CNN templates. The first application is concerned with the separation of potential field data of the Dumluca chromite region, which is one of the rich reserves of Turkey; in this context, the classical approach to the gravity anomaly separation method is one of the main problems in geophysics. The other application is the border detection of archeological ruins of the Hittite Empire in Turkey. The Hittite civilization sites located at the Sivas-Altinyayla region of Turkey are among the most important archeological sites in history, one reason among others being that written documentation was first produced by this civilization.

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Multi-Level Thresholding based on Non-Parametric Approaches for Fast Segmentation

  • Cho, Sung Ho;Duy, Hoang Thai;Han, Jae Woong;Hwang, Heon
    • 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.

Transfer Function Optimization Using Crowd Sourcing (크라우드 소싱을 이용한 변환함수 최적화)

  • Nam, Jinhyun;Nam, Doohee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.4
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    • pp.107-112
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    • 2014
  • This Study is Transfer function optimization plan of volume rendering of multi user environment. Each volume data, for appropriate transfer function, they should be adjusted parameter many times. To prevent this, we propose transfer function optimization plan using crowd sourcing. In multi user environment, we use weight value for reliability level for each user. Because transfer function parameter used previous users is provided next users, they can be used effectively optimized transfer function and can reduce attempts.

A new optimized performance-based methodology for seismic collapse capacity assessment of moment resisting frames

  • Maddah, Mohammad M.;Eshghi, Sassan;Garakaninezhad, Alireza
    • Structural Engineering and Mechanics
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    • v.82 no.5
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    • pp.667-678
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    • 2022
  • Moment-resisting frames (MRFs) are among the most conventional steel structures for mid-rise buildings in many earthquake-prone cities. Here, a simplified performance-based methodology is proposed for the seismic collapse capacity assessment of these buildings. This method employs a novel multi-mode pushover analysis to determine the engineering demand parameters (EDPs) of the regular steel MRFs up to the collapse prevention (CP) performance level. The modal combination coefficients used in the proposed pushover analysis, are obtained from two metaheuristic optimization algorithms and a fitting procedure. The design variables for the optimization process are the inter-story drift ratio profiles resulting from the multi-mode pushover analyses, and the objective values are the outcomes of the incremental dynamic analysis (IDA). Here, the collapse capacity of the structures is assessed in three to five steps, using a modified IDA procedure. A series of regular mid-rise steel MRFs are selected and analyzed to calculate the modal combination coefficients and to validate the proposed approach. The new methodology is verified against the current existing approaches. This comparison shows that the suggested method more accurately evaluates the EDPs and the collapse capacity of the regular MRFs in a robust and easy to implement way.

Multi-Objective Optimization of Turbofan Engine Performance Using Particle Swarm Optimization (Particle Swarm Optimization을 이용한 터보팬 엔진 다목표 성능 최적화 연구)

  • Choi, Jaewon;Chung, Wonchul;Sung, Hong-Gye
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.43 no.4
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    • pp.326-333
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    • 2015
  • A turbo fan engine performance analysis program combined with a particle swarm optimization(PSO) has been developed to optimize the major design parameters of the combat aircraft gas turbine engine. The optimized parameters includes bypass ratio, fan pressure ratio, high pressure compression ratio and burner exit temperature. The objective parameters have been determined using a multi-objective function consisting of the net thrust and specific fuel consumption along a weight function. The basic model for the combat aircraft gas turbine engine has been selected as the F404 turbofan engine which is widely used in the combat aircraft, F-18 and Korean high level training aircraft, T-50. The optimal conditions of four parameters have been obtained for various design conditions.

Optimal sensor placement under uncertainties using a nondirective movement glowworm swarm optimization algorithm

  • Zhou, Guang-Dong;Yi, Ting-Hua;Zhang, Huan;Li, Hong-Nan
    • Smart Structures and Systems
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    • v.16 no.2
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    • pp.243-262
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    • 2015
  • Optimal sensor placement (OSP) is a critical issue in construction and implementation of a sophisticated structural health monitoring (SHM) system. The uncertainties in the identified structural parameters based on the measured data may dramatically reduce the reliability of the condition evaluation results. In this paper, the information entropy, which provides an uncertainty metric for the identified structural parameters, is adopted as the performance measure for a sensor configuration, and the OSP problem is formulated as the multi-objective optimization problem of extracting the Pareto optimal sensor configurations that simultaneously minimize the appropriately defined information entropy indices. The nondirective movement glowworm swarm optimization (NMGSO) algorithm (based on the basic glowworm swarm optimization (GSO) algorithm) is proposed for identifying the effective Pareto optimal sensor configurations. The one-dimensional binary coding system is introduced to code the glowworms instead of the real vector coding method. The Hamming distance is employed to describe the divergence of different glowworms. The luciferin level of the glowworm is defined as a function of the rank value (RV) and the crowding distance (CD), which are deduced by non-dominated sorting. In addition, nondirective movement is developed to relocate the glowworms. A numerical simulation of a long-span suspension bridge is performed to demonstrate the effectiveness of the NMGSO algorithm. The results indicate that the NMGSO algorithm is capable of capturing the Pareto optimal sensor configurations with high accuracy and efficiency.

Muti-Objective Design Optimization of Self-Compacting Concrete using CCD Experimental Design and Weighted Multiple Objectives Considering Cost-Effectiveness (비용효율을 고려한 자기 충전형 콘크리트의 CCD 실험설계법 및 가중 다목적성 기반 다목적설계최적화(MODO))

  • Do, Jeongyun
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.24 no.3
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    • pp.26-38
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    • 2020
  • Mixture design of self-compacting concrete is a typical multi-criteria decision making problem and conventional mixture designs are based on the low level engineering method like trials and errors through iteration method to satisfy the various requirements. This study concerns with performing the straightforward multiobjective design optimization of economic SCC mixture considering relative importances of the various requirements and cost-effectives of SCC. Total five requirements of 28day compressive strength, filling ability, segregation stability, material cost and mass were taken into consideration to prepare the objective function to be formulated in form of the weighted-multiobjective mixture design optimization problem. Economic SCC mixture computational design can be given in a rational way which considering material costs and the relative importances of the requiremets and from the result of this study it is expected that the development of SCC mixtue computational design and the consequent univeral concrete material design optimization methodology can be advanced.