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Exploring the integration of multi criteria decision analysis in the clean energy biodiesels applications: A systematic review and gap analysis

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Engineering Applications of Artificial Intelligence 2024年 133卷

作者： Alamoodi, A.H. Garfan, Salem Al-Zuhairi, Omar Zaidan, B.B. Zaidan, A.A. Albahri, O.S. Y.Y. Ahmaro, Ibraheem Albahri, A.S. Yussof, Salman Magableh, Aws A. Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Malaysia Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan Perak Malaysia Applied Science Research Center Applied Science Private University Amman Jordan Low Dimensional Materials Research Centre Department of Physics Faculty of Science Universiti Malaya Kuala Lumpur50603 Malaysia SP Jain School of Global Management Lidcombe SydneyNSW2141 Australia International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Douliu Taiwan Victorian Institute of Technology Australia Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq Computer Science Department College of Information Technology Hebron University Hebron Palestine Technical College Imam Ja'afar Al-Sadiq University Baghdad Iraq Department of Information Systems Yarmouk University Irbid Jordan Baghdad Iraq Department of Computing College of Computing and Informatics Universiti Tenaga Nasional Malaysia Departments of Software Engineering Prince Sultan University Riyad Saudi Arabia

Biodiesel has gained tremendous attention from researchers due to its environmentally friendly and renewable fuel manufactured domestically from vegetable oils or animal fats. Multiple factors, including emission and fuel efficiency, measure the performance of biodiesel. These characteristics make the process of evaluation and benchmarking a multi-criteria decision-making (MCDM) problem. This research attempts to survey the literature for multi-criteria decision-making applications on biodiesel. This systematic review was carried out on four scientific databases: PubMed, scienceDirect, IEEE Xplore, and WoS. The collected articles were summarized and mapped into a coherent taxonomy, while the main challenges, motivations, and recommendations were collected and categorized for better understanding and finding out essential characteristics. The final set of included articles was 33, and they were categorized into six different categories. Most articles (n=15/33) investigated the evaluation and selection of biodiesel alternatives using MCDM. Furthermore, a state-of-art bibliometric analysis is provided. The analysis demonstrates several challenges in this area, such as source selection, optimum fuel blending, and uncertainty. This article is expected to assist future researchers in addressing the current gaps and contribute to advancing this area. © 2024 Elsevier Ltd

关键词： Biodiesel

DCPViz: A Visual Analytics Approach for Downscaled Climate Projections

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arXiv 2022年

作者： Nayeem, Abdullah-Al-Raihan Lee, Huikyo Han, Dongyun Elshambakey, Mohammad Tolone, William J. Dobbs, Todd Crichton, Daniel Cho, Isaac College of Computing and Informatics University of North Carolina at Charlotte Charlotte United States Jet Propulsion Laboratory California Institute of Technology Pasadena United States Computer Science Utah State University Logan United States City of Scientific Research and Technological Applications Alexandria Egypt

This paper introduces a novel visual analytics approach, DCPViz, to enable climate scientists to explore massive climate data interactively without requiring the upfront movement of massive data. Thus, climate scientists are afforded more effective approaches to support the identification of potential trends and patterns in climate projections and their subsequent impacts. We designed the DCPViz pipeline to fetch and extract NEX-DCP30 data with minimal data transfer from their public sources. We implemented DCPViz to demonstrate its scalability and scientific value and to evaluate its utility under three use cases based on different models and through domain expert feedback. © 2022, CC BY.

关键词： Data transfer

DCPViz: A Visual Analytics Approach for Downscaled Climate Projections

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DCPViz: A Visual Analytics Approach for Downscaled Climate P...

IEEE International Conference on Big Data

作者： Abdullah-Al-Raihan Nayeem Huikyo Lee Dongyun Han Mohammad Elshambakey William J. Tolone Todd Dobbs Daniel Crichton Isaac Cho College of Computing and Informatics University of North Carolina at Charlotte Charlotte United States Jet Propulsion Laboratory California Institute of Technology Pasadena United States Computer Science Utah State University Logan United States City of Scientific Research and Technological Applications Alexandria Egypt

ISBN: (纸本)9781665480468

关键词： Visual analytics Scalability Pipelines Data visualization Big Data Market research Data transfer

Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method

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arXiv 2021年

作者： Guo, Theron Rokoš, Ondřej Veroy, Karen Centre for Analysis Scientific Computing and Applications Department of Mathematics and Computer Science Netherlands Mechanics of Materials Department of Mechanical Engineering Eindhoven University of Technology Eindhoven5612 AZ Netherlands

In order to optimally design materials, it is crucial to understand the structure-property relations in the material by analyzing the effect of microstructure parameters on the macroscopic properties. In computational homogenization, the microstructure is thus explicitly modeled inside the macrostructure, leading to a coupled two-scale formulation. Unfortunately, the high computational costs of such multiscale simulations often render the solution of design, optimization, or inverse problems infeasible. To address this issue, we propose in this work a non-intrusive reduced basis method to construct inexpensive surrogates for parametrized microscale problems;the method is specifically well-suited for multiscale simulations since the coupled simulation is decoupled into two independent problems: (1) solving the microscopic problem for different (loading or material) parameters and learning a surrogate model from the data;and (2) solving the macroscopic problem with the learned material model. The proposed method has three key features. First, the microscopic stress field can be fully recovered, which is useful for instance for revealing local stress concentrations inside the microstructure. Second, the method is able to accurately predict the stress field for a wide range of material parameters;furthermore, the derivatives of the effective stress with respect to the material parameters are available and can be readily utilized in solving optimization problems. Finally, it is more data efficient, i.e. requiring less training data, as compared to directly performing a regression on the effective stress. To construct the surrogate model, first, a proper orthogonal decomposition is performed on precomputed microscopic stress field snapshots to find a reduced basis for the stress. Second, a regression is employed to infer the coefficients of the reduced basis approximation for any arbitrary parameter value, thus enabling a rapid online evaluation of the microscopic stress.

关键词： Microstructure

COVID-19 vaccination strategies on dynamic networks

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arXiv 2021年

作者： Nguyen, Quoc Huy Liebig, Jess Shahzamal, Md Mans, Bernard Jurdak, Raja Trusted Networks Lab School of Computer Science Queensland University of Technology Australia Health and Biosecurity Commonwealth Scientific and Industrial Research Organisation Department of Computing Macquarie University Australia

Coronavirus disease (COVID-19), which was caused by SARS-CoV-2, has become a global public health concern. A great proportion of the world needs to be vaccinated in order to stop the rapid spread of the disease. In addition to prioritizing vulnerable sections of the population to receive the vaccine, an ideal degree-based vaccination strategy uses fined-grained contact networks to prioritize vaccine recipients. This strategy is costly and impractical due to the enormous amount of specific contact information needed. It also does not capture indirect fomite or aerosol-based transmission. We recently proposed a new vaccination strategy called Individual’s Movement-based Vaccination (IMV) [5], which takes both direct and indirect transmission into account and is based on the types of places people visit. IMV was shown to be cost-efficient in the case of the influenza-like diseases. This paper studies the application of IMV to COVID-19 using its documented transmission parameters. We conduct large scale computer simulations based on a city-wide empirical mobility dataset to evaluate the performance and practicability of the strategy. Results show that the proposed strategy achieves nearly five times the efficiency of random vaccination and performs comparably to the degree-based strategy, while significantly reducing the data collection requirements. Copyright © 2021, The Authors. All rights reserved.

关键词： Vaccines

High performance hyperspectral image classification using graphics processing units

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arXiv 2021年

作者： Mohammad, Mahmoud Ahmed Hossam Edeen Tolba, Mohammad Fahmy Ebied, Hala Muosher Aziz, Mohammad Hassan Abdel Basic Science Department Faculty of Computer and Information Sciences Ain Shams University Scientific Computing Department Faculty of Computer and Information Sciences Ain Shams University Basic Sciences Department Faculty of Computer and Information Sciences Ain Shams University

Real-time remote sensing applications like search and rescue missions, military target detection, environmental monitoring, hazard prevention and other time-critical applications require onboard real time processing capabilities or autonomous decision making. Some unmanned remote systems like satellites are physically remote from their operators, and all control of the spacecraft and data returned by the spacecraft must be transmitted over a wireless radio link. This link may not be available for extended periods when the satellite is out of line of sight of its ground station. In addition, providing adequate electrical power for these systems is a challenging task because of harsh conditions and high costs of production. Onboard processing addresses these challenges by processing data on-board prior to downlink, instead of storing and forwarding all captured images from onboard sensors to a control station, resulting in the reduction of communication bandwidth and simpler subsequent computations to be performed at ground stations. Therefore, lightweight, small size and low power consumption hardware is essential for onboard real time processing systems. With increasing dimensionality, size and resolution of recent hyperspectral imaging sensors, additional challenges are posed upon remote sensing processing systems and more capable computing architectures are needed. Graphical Processing Units (GPUs) emerged as promising architecture for light weight high performance computing that can address these computational requirements for onboard systems. The goal of this study is to build high performance hyperspectral analysis solutions based on selected high accuracy analysis methods. These solutions are intended to help in the production of complete smart remote sensing systems with low power consumption. We propose accelerated parallel solutions for the well-known recursive hierarchical segmentation (RHSEG) clustering method, using GPUs, hybrid multicore CPU with a GPU

关键词： Graphics processing unit

Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays

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Physical Review X 2025年第2期15卷 021034-021034页

作者： Anantha S. Rao Donovan Buterakos Barnaby van Straaten Valentin John Cécile X. Yu Stefan D. Oosterhout Lucas Stehouwer Giordano Scappucci Menno Veldhorst Francesco Borsoi Justyna P. Zwolak Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA Department of Physics University of Maryland College Park Maryland 20742 USA National Institute of Standards and Technology Gaithersburg Maryland 20899 USA QuTech and Kavli Institute of Nanoscience Delft University of Technology P.O. Box 5046 2600 GA Delft The Netherlands QuTech and Netherlands Organisation for Applied Scientific Research (TNO) Delft The Netherlands Present address: NNF Quantum Computing Programme Niels Bohr Institute University of Copenhagen Blegdamsvej 17 2100 Copenhagen Denmark.

Arrays of gate-defined semiconductor quantum dots are among the leading candidates for building scalable quantum processors. High-fidelity initialization, control, and readout of spin qubit registers require exquisite and targeted control over key Hamiltonian parameters that define the electrostatic environment. However, due to the tight gate pitch, capacitive crosstalk between gates hinders independent tuning of chemical potentials and interdot couplings. While virtual gates offer a practical solution, determining all the required cross-capacitance matrices accurately and efficiently in large quantum dot registers is an open challenge. Here, we establish a modular automated virtualization system (MAViS)—a general and modular framework for autonomously constructing a complete stack of multilayer virtual gates in real time. Our method employs machine learning techniques to rapidly extract features from two-dimensional charge stability diagrams. We then utilize computer vision and regression models to self-consistently determine all relative capacitive couplings necessary for virtualizing plunger and barrier gates in both low- and high-tunnel-coupling regimes. Using MAViS, we successfully demonstrate accurate virtualization of a dense two-dimensional array comprising ten quantum dots defined in a high-quality Ge/SiGe heterostructure. Our work offers an elegant and practical solution for the efficient control of large-scale semiconductor quantum dot systems.

关键词： Semiconductor quantum dots

On pressure robustness and independent determination of displacement and pressure in incompressible linear elasticity

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arXiv 2022年

作者： Zdunek, Adam Neunteufel, Michael Rachowicz, Waldemar HB Berrit Solhemsbackarna 73 Spånga SE-163 56 Sweden Institute for Analysis and Scientific Computing Tu Wien Wiedner Hauptstr. 8-10 WienA-1040 Austria Institute of Computer Science Cracow University of Technology CracowPL 31-155 Poland

We investigate the possibility to determine the divergence-free displacement u independently from the pressure reaction p for a class of boundary value problems in incompressible linear elasticity. If not possible, we investigate if it is possible to determine it pressure robustly, i.e. pollution free from the pressure reaction. For convex domains there is but one variational boundary value problem among the investigated that allows the independent determination. It is the one with essential no-penetration conditions combined with homogeneous tangential traction conditions. Further, in most but not all investigated cases, the weakly divergence-free displacement can be computed pressure robustly provided the total body force is decomposed into its direct sum of divergence- and rotation-free components using a Helmholtz decomposition. The elasticity problem is solved using these components as separate right-hand sides. The total solution is obtained using the superposition principle. We employ a (u, p) higher-order finite element formulation with discontinuous pressure elements. It is inf-sup stable for polynomial degree p ≥ 2 but not pressure robust by itself. We propose a three step procedure to solve the elasticity problem preceded by the Helmholtz decomposition of the total body force. The extra cost for the three-step procedure is essentially the cost for the Helmholtz decomposition of the assembled total body force, and the small cost of solving the elasticity problem with one extra right-hand side. The results are corroborated by theoretical derivations as well as numerical *** Codes 65N30, 74B05 Copyright © 2022, The Authors. All rights reserved.

关键词： Boundary value problems

Position-Dependent Snap Feedforward: A Gaussian Process Framework

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arXiv 2022年

作者： van Haren, Max Poot, Maurice Portegies, Jim Oomen, Tom The Control Systems Technology Section Department of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands The Centre for Analysis Scientific Computing and Applications Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands The Delft Center for Systems and Control Delft University of Technology Delft Netherlands

Mechatronic systems have increasingly high performance requirements for motion control. The low-frequency contribution of the flexible dynamics, i.e. the compliance, should be compensated for by means of snap feedforward to achieve high accuracy. Position-dependent compliance, which often occurs in motion systems, requires the snap feedforward parameter to be modeled as a function of position. Position-dependent compliance is compensated for by using a Gaussian process to model the snap feedforward parameter as a continuous function of position. A simulation of a flexible beam shows that a significant performance increase is achieved when using the Gaussian process snap feedforward parameter to compensate for position-dependent compliance. © 2022, CC BY.

关键词： Flexible structures