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Terahertz time-domain spectroscopy of boron nitride nanotube-reinforced PMMA composites

Polymer Testing 2025年 147卷

作者： Zhai, Min Gou, Feilin Ke, Changhong He, Wenlong Zhai, Cong Locquet, Alexandre Citrin, D.S. College of Electronics and Information Engineering Shenzhen University Guangdong Shenzhen518060 China Department of Mechanical Engineering State University of New York at Binghamton BinghamtonNY13902 United States School of Transportation and Civil Engineering and Architecture Foshan University Guangdong Foshan528000 China School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Georgia Tech-CNRS IRL2958 Georgia Tech-Europe 2 Rue Marconi Lorraine Metz57070 France

Polymethyl methacrylate (PMMA) reinforced with boron nitride nanotubes (BNNT) at weight fill factors fw of 0.2 and 0.5 wt % are characterized by terahertz time-domain spectroscopy (THz-TDS). It is known that the introduction of BNNTs in polymer composites can provide thermal conduction paths and significantly reduce interface thermal resistance. Despite the low values of fw, the presence of the BNNTs has a significant effect on the optical constants, either due to the intrinsic contribution of the BNNTs or due to extrinsic effects such as induced strain in the PMMA matrix. Negligible THz birefringence observed in the polarization-resolved THz transmission measurements indicates a high degree of isotropy of the BNNT dispersed in the PMMA. Assuming an intrinsic effect and the validity of modified Maxwell–Garnett theory regardless of the inclusion shape, the frequency-dependent optical constants of BNNTs are extracted. The refractive index of BNNTs varies roughly linearly from n(ν=500GHz)≈1.8 to n(ν=1.5THz)≈1.75, while the absorption coefficient increases from α(ν=500GHz)≈10 cm−1 to α(ν=1.5THz)≈45 cm−1. The extracted THz dielectric properties of the BNNTs trend toward reported values for bulk h-BNs. © 2025 The Authors

关键词： Terahertz spectroscopy

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Energy-aware load balancing of parallel evolutionary algorithms with heavy fitness functions in heterogeneous CPU-GPU architectures

Energy-aware load balancing of parallel evolutionary algorit...

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作者： Escobar, Juan José Ortega, Julio Díaz, Antonio Francisco González, Jesús Damas, Miguel Department of Computer Architecture and Technology CITIC University of Granada Spain

By means of the availability of mechanisms such as Dynamic Voltage and Frequency Scaling (DVFS) and heterogeneous architectures including processors with different power consumption profiles, it is possible to devise scheduling algorithms that are aware of both runtime and energy consumption in parallel programs. In this paper, we propose and evaluate a multi-objective (more specifically, a bi-objective) approach to distribute the workload among the processing cores in a given heterogeneous parallel CPU-GPU architecture. The aim of this distribution may be either to save energy without increasing the running time or to reach a trade-off among time and energy consumption. The parallel programs considered here are master-worker evolutionary algorithms where the evaluation of the fitness function for the individuals in the population demands the most part of the computing time. As many useful bioinformatics and data mining applications exhibit this kind of parallel profile, the proposed energy-aware approach for workload scheduling could be frequently applied. © 2018 John Wiley & Sons, Ltd.

关键词： Energy utilization

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Spike processing on an embedded multi-task computer: Image reconstruction

Spike processing on an embedded multi-task computer: Image r...

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5th International Workshop on Intelligent Solutions in Embedded Systems, WISES 07

作者： Luján-Martínez, Carlos Linares-Barranco, Alejandro Rivas-Pérez, Manuel Jiménez-Fernández, Ángel Jiménez-Moreno, Gabriel Civit-Balcells, Antón Computer Architecture and Technology Department University of Seville Seville Spain

ISBN: (纸本)9788489315471

There is an emerging philosophy, called Neuro-informatics, contained in the Artificial Intelligence field, that aims to emulate how living beings do tasks such as taking a decision based on the interpretation of an image by emulating spiking neurons into VLSI designs and, therefore, trying to re-create the human brain at its highest level. Address-Event-Representation (AER) is a communication protocol that has embedded part of the processing. It is intended to transfer spikes between bioinspired chips. An AER based system may consist of a hierarchical structure with several chips that transmit spikes among them in real-time, while performing some processing. There are several AER tools to help to develop and test AER based systems. These tools require the use of a computer to allow the higher level processing of the event information, reaching very high bandwidth at the AER communication level. We propose the use of an embedded platform based on a multi-task operating system to allow both, the AER communication and processing without the requirement of either a laptop or a computer. In this paper, we present and study the performance of a new philosophy of a frame-grabber AER tool based on a multi-task environment. This embedded platform is based on the Intel XScale processor which is governed by an embedded GNU/Linux system. We have connected and programmed it for processing Address-Event information from a spiking generator.

关键词： Image reconstruction

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Joint high-resolution feature learning and vessel-shape aware convolutions for efficient vessel segmentation

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computers in Biology and Medicine 2025年 191卷 109982-109982页

作者： Zhang, Xiang Zhu, Qiang Hu, Tao Guo, Song Bian, Genqing Dong, Wei Hong, Rao Lin, Xia Ling Wu, Peng Zhou, Meili Yan, Qingsen Mohi-ud-din, Ghulam Ai, Chen Li, Zhou College of Information and Control Engineering Xi'an University of Architecture and Technology Xi'an China Shaanxi Provincial Key Lab of Bigdata of Energy and Intelligence Processing School of Physics and Electronic Information Yanan University Yanan China School of Computer Science and Engineering Northwestern Polytechnical University Xi'an China School of Software Nanchang University Nanchang China School of Cyber Security Zhejiang University Hangzhou China Department of Basic Education and Research Jiangxi Police College Nanchang China Northwestern Polytechnical University China

Clear imagery of retinal vessels is one of the critical shreds of evidence in specific disease diagnosis and evaluation, including sophisticated hierarchical topology and plentiful-and-intensive capillaries. In this work, we propose a new topology- and shape-aware model named Multi-branch Vessel-shaped Convolution Network (MVCN) to adaptively learn high-resolution representations from retinal vessel imagery and thereby capture high-quality topology and shape information thereon. Two steps are involved in our pipeline. The former step is proposed as Multiple High-resolution Ensemble Module (MHEM) to enhance high-resolution characteristics of retinal vessel imagery via fusing scale-invariant hierarchical topology thereof. The latter is a novel vessel-shaped convolution that captures the retinal vessel topology to emerge from unrelated fundus structures. Moreover, our MVCN of separating such topology from the fundus is a dynamical multiple sub-label generation via using epistemic uncertainty, instead of manually separating raw labels to distinguish definitive and uncertain vessels. Compared to other existing methods, our method achieves the most advanced AUC values of 98.31%, 98.80%, 98.83%, and 98.65%, and the most advanced ACC of 95.83%, 96.82%, 97.09%,and 96.66% in DRIVE, CHASE_DB1, STARE, and HRF datasets. We also employ correctness, completeness, and quality metrics to evaluate skeletal similarity. Our method's evaluation metrics have doubled compared to previous methods, thereby demonstrating the effectiveness thereof. © 2025 Elsevier Ltd

关键词： Ophthalmology

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Early Prediction of the Winner in StarCraft Matches

Early Prediction of the Winner in StarCraft Matches

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9th International Joint Conference on Computational Intelligence, IJCCI 2017

作者： Alvarez-Caballero, Antonio Merelo, J.J. Sanchez, Pablo Garcıa Fernandez-Ares, A. Department of Computer Architecture and Computer Technology University of Granada Spain Department of Computer Science University of Cadiz Spain

ISBN: (纸本)9789897582745

A fast and precise prediction of the outcome of a game is essential for the design of bots that play the game;it can be used either offline as a fast way to design bot strategies or online for conserving resources and conceding defeat or speed up victory, as well as evaluating the consequences of actions. The objective of this paper is predicting the winner of a StarCraft match as soon as possible. This study is done with supervised learning, because a lot of suitable data is available. The main problem of this approach is the big amount of generated data, so it has to be selected and organised properly and be treated with proper tools. A set of six learning algorithms is used, from simpler ones to more complex algorithms. Spark and MLlib are used due to their capabilities to deal with big amounts of data. With the learned models, time of matches are restricted, trying to get a time bound for predicting results. With this approach we get that it is not necessary to play a whole match to predict its winner with high accuracy: with 10 minutes we can predict the outcome with 90% of accuracy. © 2017 by SCITEPRESS–Science and technology Publications, Lda. All rights reserved.

关键词： Forecasting

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The sandpile mutation operator for genetic algorithms

The sandpile mutation operator for genetic algorithms

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5th International Conference on Learning and Intelligent Optimization, LION 2011

作者： Fernandes, C.M. Laredo, J.L.J. Mora, A.M. Rosa, A.C. Merelo, J.J. Department of Architecture and Computer Technology University of Granada Spain Portugal

ISBN: (纸本)9783642255656

This paper describes an alternative mutation control scheme for Genetic Algorithms (GAs) inspired by the Self-Organized Criticality (SOC) theory. The strategy, which mimics a SOC system known as sandpile, is able to generate mutation rates that, unlike those given by other methods of adaptive parameter control, oscillate between very low values and cataclysmic mutations. In order to attain the desired behaviour, the sandpile is not just attached to a GA;it is also modified in an attempt to link its rates to the stage of the search, i.e., the fitness distribution of the population. Due to its characteristics, the sandpile mutation arises as a promising candidate for efficient and yet simple and context-independent approach to dynamic optimization. An experimental study confirms this assumption: a GA with sandpile mutation outperforms a recently proposed SOC-based GA for dynamic optimization. Furthermore, the proposed method does not increase traditional GAs' parameter set. © Springer-Verlag Berlin Heidelberg 2011.

关键词： Genetic algorithms

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New methodology for structure identification of fuzzy controllers in real time

New methodology for structure identification of fuzzy contro...

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作者： Pomares, H. Rojas, I. González, J. Department of Computer Architecture and Computer Technology University of Granada Spain

ISBN: (纸本)354000131X

This paper presents an innovative approach to self-adaptation of the structure of a neuro-fuzzy controller in real time. Without any off-line pretraining, the algorithm achieves very high control performance through the iteration of a three-stage algorithm. In the first stage, coarse tuning of the neuro-fuzzy rules (both rule consequents and membership functions of the premises) is accomplished using the sign of the dependency of the plant output with respect to the control signal and an overall analysis of the main operating regions. In stage two, fine tuning of the rules is achieved based on the controller output error using a gradient-based method. Finally, the third stage is responsible of modifying the structure of the controller, proposing that input variable which should get a new membership function in order to improve the control policy in an optimum way. © Springer-Verlag 2002.

关键词： Membership functions

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Cacheap:Portable and Collaborative I/O Optimization for Graph Processing

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Journal of computer Science & technology 2019年第3期34卷 690-706页

作者： Peng Zhao Chen Ding Lei Liu Jiping Yu Wentao Han Xiao-Bing Feng State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190China University of Chinese Academy of Sciences Beijing 100049China Department of Computer Science University of RochesterRochester 14623U.S.A. Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

Increasingly there is a need to process graphs that are larger than the available memory on today's *** systems have been developed with grapli representations that are efficient and compact for out-of-core processing.A necessary task in these systems is memory *** paper presents a system called Cacheap which automatically and efficiently manages the available memory to maximize the speed of grapli processing,minimize the amount of disk access,and maximize the utilization of memory for graph *** has a simple interface that can be easily adopted by existing graph *** paper describes the new system,uses it in recent graph engines,and demonstrates its integer factor improvements in the speed of large-scale grapli processing.

关键词： out-of-core graph processing system I/O optimization memory cache graph analytics locality

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Modular, Adaptable and Reusable Approach to Thermal-Fluids: Outwitting the Norms (MARATHON)

Modular, Adaptable and Reusable Approach to Thermal-Fluids: ...

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2008 ASEE Annual Conference and Exposition

作者： Milanovic, Ivana Eppes, Tom Department of Mechanical Engineering College of Engineering Technology and Architecture University of Hartford Department of Electrical and Computer Engineering College of Engineering Technology and Architecture

This paper describes the results of a project that implemented modular, adaptable and reusable thermo-fluids laboratories in the undergraduate Mechanical Engineering technology (MET) Program. MARATHON (Modular, Adaptable and Reusable Approach to Thermal-Fluids Outwitting Norms) successfully engages students in inquiry and learning, gradually building toward intellectual and practical challenges without pre-determined outcomes. For the most part, research and discovery activities did not figure prominently in the MET curriculum. In the past, typical laboratories consisted of a set of exercises with pre-established experimental set up, and instructions. This concept did not foster critical thinking skills because it did not provide students with the opportunity to build experiments and models from scratch, experience difficulties, be resourceful, explore alternatives and make design decisions. Therefore, there was a strong pedagogical need for better practical problem solving skills in the area of thermo-fluids. MARATHON was created to facilitate development of student problem solving skills in which students become active participants in the process of discovery. To accomplish this, a cluster of interconnected laboratories in the area of thermo-fluids was reconfigured and organized in a pyramidal block-like system. These blocks were: (1) classical experiments, (2) jigsaw experiments, and (3) design of an experiment. This new laboratory structure provides an array of experiences, builds on already existing skills and knowledge, and connects them in a logical way. MARATHON was first implemented in Fall 2002 and has been used for four academic cycles. The primary benefits have been to expand the students' understanding of the complexity associated with designing and successfully performing an experiment from scratch. Each year at least one project has been featured at the University's undergraduate research colloquium. Laboratory platforms have been provided from other

关键词： Students

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CUDA 2D stencil computations for the Jacobi method

CUDA 2D stencil computations for the Jacobi method

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10th International Conference on Applied Parallel and Scientific Computing, PARA 2010

作者： Cecilia, José María García, José Manuel Ujaldón, Manuel Computer Engineering and Technology Department University of Murcia Spain Computer Architecture Department University of Malaga Spain

ISBN: (纸本)9783642281501

We are witnessing the consolidation of the GPUs streaming paradigm in parallel computing. This paper explores stencil operations in CUDA to optimize on GPUs the Jacobi method for solving Laplace's differential equation. The code keeps constant the access pattern through a large number of loop iterations, that way being representative of a wide set of iterative linear algebra algorithms. Optimizations are focused on data parallelism, threads deployment and the GPU memory hierarchy, whose management is explicit by the CUDA programmer. Experimental results are shown on Nvidia Teslas C870 and C1060 GPUs and compared to a counterpart version optimized on a quadcore Intel CPU. The speed-up factor for our set of GPU optimizations reaches 3-4x and the execution times defeat those of the CPU by a wide margin, also showing great scalability when moving towards a more sophisticated GPU architecture and/or more demanding problem sizes. © 2012 Springer-Verlag.

关键词： Iterative methods

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