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Black-hole-inspired thermal trapping with graded heat-conduction metadevices

National science Review 2023年第2期10卷 131-138页

作者： Liujun Xu Jinrong Liu Peng Jin Guoqiang Xu Jiaxin Li Xiaoping Ouyang Ying Li Cheng-Wei Qiu Jiping Huang Department of Physics State Key Laboratory of Surface Physics and Key Laboratory of Micro and Nano Photonic Structures (MOE) Fudan University Department of Electrical and Computer Engineering National University of Singapore Graduate School of China Academy of Engineering Physics School of Materials Science and Engineering Xiangtan University Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical InstrumentationZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang University International Joint Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University

The curved space-time produced by black holes leads to the intriguing trapping *** far,metadevices have enabled analogous black holes to trap light or sound in laboratory ***,trapping heat in a conductive environment is still challenging because diffusive behaviors are *** by black holes,we construct graded heat-conduction metadevices to achieve thermal trapping,resorting to the imitated advection produced by graded thermal conductivities rather than the trivial solution of using insulation materials to confine thermal *** experimentally demonstrate thermal trapping for guiding hot spots to diffuse towards the *** heat-conduction metadevices have advantages in energy-efficient thermal regulation because the imitated advection has a similar temperature field effect to the realistic advection that is usually driven by external energy *** results also provide an insight into correlating transformation thermotics with other disciplines,such as cosmology,for emerging heat control schemes.

关键词： thermal trapping graded metadevices imitated advection

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A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System

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Journal of Bionic engineering 2023年第4期20卷 1828-1851页

作者： Serdar Ekinci Davut Izci Laith Abualigah Raed Abu Zitar Department of Computer Engineering Batman University72100BatmanTurkey Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi MinhVietnam Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains Malaysia11800PenangPulau PinangMalaysia Sorbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates

In this work,we propose a real proportional-integral-derivative plus second-order derivative(PIDD2)controller as an efficient controller for vehicle cruise control systems to address the challenging issues related to efficient *** this regard,this paper is the first report in the literature demonstrating the implementation of a real PIDD2 controller for controlling the respective *** construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning *** also propose a simple yet effective objective function to increase the performance of the proposed algorithm(CmOBL-AO)to adjust the real PIDD2 controller's parameters *** show the CmOBL-AO algorithm to perform better than the differential evolution algorithm,gravitational search algorithm,African vultures optimization,and the Aquila Optimizer using well-known unimodal,multimodal benchmark ***2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO *** the vehicle cruise control system,we confirm the more excellent performance of the proposed method against particle swarm,gray wolf,salp swarm,and original Aquila optimizers using statistical,Wilcoxon signed-rank,time response,robustness,and disturbance rejection *** also use fourteen reported methods in the literature for the vehicle cruise control system to further verify the more promising performance of the CmOBL-AO-based real PIDD2 controller from a wider *** excellent performance of the proposed method is also illustrated through different quality indicators and different operating ***,we also demonstrate the good performing capability of the CmOBL-AO algorithm for real traffic *** show

关键词： Aquila optimizer Chaotic local search Modified opposition-based learning Real PIDD^(2)controller Vehicle cruise control system Bionic engineering

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Hashgraph consensus-based simultaneous, asynchronous and big-data supported blockchain mechanism for IT-OT enabled critical infrastructure sectors

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Journal of Ambient Intelligence and Humanized Computing 2025年 1-13页

作者： Hasan, Mohammad Kamrul Ghazal, Taher M. Issa, Ghassan Islam, Shayla Ismail, Ahmad Fadzil Kabir, S. Rayhan Bangi43600 Malaysia Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman11937 Jordan School of Computing Skyline University College University City Sharjah Skyline University College Sharjah1797 United Arab Emirates Institue of Computer Science and Digitial Innovation UCSI University Malaysia Kuala Lumpur56000 Malaysia Department of Electrical and Computer Engineering International Islamic University of Malaysia Kuala Lumpur53000 Malaysia

Critical Infrastructure (CI) refers to the essential areas made up of public, private, and business sectors for the security of a country's development, such as electricity, water, health, education, etc. where information technologies (ITs) and operational technologies (OTs) enable automation services of CI. Currently, blockchain is being experimented in various CI sectors and any CI sector accumulates the data of millions of people in a country or nation from which big data is being generated. Big data connections are seen with large-scale blockchain networks because as the size of the blockchain network increases, so does the amount of connected data. Typically, the blockchain does not support asynchronous and simultaneous processes that indicate multiple block compilation does not allow at the same time for the blockchain systems. That is why high energy consumption, high bandwidth dependency, long-time computation, high mining process, and system slowness issues are seen on large-scale blockchain networks where big data is also connected. However, Hashgraph is an alternative distributed ledger technology (DLT) to blockchain and is also considered a consensus method that supports Asynchronous Byzantine Fault Tolerance (ABFT) as well as simultaneous process. Moreover, Hashgraph does not need mining and network node verification processes which saves bandwidth. In this research, we proposed a Hashgraph-enabled blockchain model for reducing the above issues and illustrated the adoption of IT-enabled OT to support CI. In addition, this manuscript discusses how the proposed model can create positive impacts in CI areas by replacing traditional blockchain systems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Critical infrastructures

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Efficient Tree-based Parallel Algorithms for N-Body Simulations Using C++ Standard Parallelism

Efficient Tree-based Parallel Algorithms for N-Body Simulati...

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2024 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Cassell, Thomas Lane Deakin, Tom Alpay, Aksel Heuveline, Vincent Gadeschi, Gonzalo Brito University of Bristol School of Computer Science BristolBS8 1UB United Kingdom Heidelberg University Engineering Mathematics and Computing Lab Interdisciplinary Center for Scientific Computing Heidelberg Germany NVIDIA GPU Architecture Munich Germany

ISBN: (纸本)9798350355543

The Barnes-Hut approximation for N-body simulations reduces the time complexity of the naive all-pairs approach from O(N2) to O(N log N) by hierarchically aggregating nearby particles into single entities using a tree data structure. This inherently irregular algorithm poses substantial challenges for performance portable implementations on multi-core CPUs and GPUs. We introduce two portable fully-parallel Barnes-Hut implementation strategies that trade-off different levels of GPU support for performance: an unbalanced concurrent octree, and a balanced bounding volume hierarchy sorted by a Hilbert spacefilling curve. We implement these algorithms in portable ISO C++ using parallel algorithms and concurrency primitives like atomics. The results demonstrate competitive performance on a range of CPUs and GPUs. Additionally, they highlight the effectiveness of the par execution policy for highly concurrent irregular algorithms, outperforming par_unseq on CPUs and GPUs with Independent Thread Scheduling. © 2024 IEEE.

关键词： n/a

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Efficiency and Precision: Control Systems Empowered by Smart Image Processing 3

Efficiency and Precision: Control Systems Empowered by Smart...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Sreenivasulu, Gunji Padmavathi, T. Nirisha, Anagandula Prakash, Dudi Bhanu Oudah, Mohammed Yousif Saikumar, K. Madanapalle Institute of Technology & Science Department of Computer Science & Engineering Madanapalle India Cvr College of Engineering Department of Ece India Mlr Institute of Technology Department of Computer Science and Information Technology Telangana Hyderabad India Cvr College of Engineering Department of Ece Hyderabad India Al-Ayen University Scientific Research Center Thi-Qar64001 Iraq School of Engineering Malla Reddy University Computer Science Telangana Hyderabad500100 India

ISBN: (纸本)9798350319125

The rapid increase in the population has resulted in traffic jams on the roads. There was a corresponding increase in the number of calls for emergency services, such as ambulances, police cars, and fire trucks. Maintaining rapid response times for emergency vehicles is critical right now. In this study, we present a smart traffic control system that integrates Internet of Things (IoT) chips into traffic signals and modifies their timing parameters. These chips will function in response to a road's estimated automobile count and the subsequent need for emergency vehicles along that route. The number of people in each automobile is going to be calculated using digital image analysis of the live camera feed. To make sure emergency vehicles get the help they require, GPS systems are going to be utilized to track the vehicles and update the chips with their current locations. It is envisioned that traffic lights on a road network will function by dynamically assigning weights for a particular node or the time among two consecutive lights. In order to maintain track of each node in the network, the weights assigned to each one must be updated in real-time. © 2023 IEEE.

关键词： Digital Image Processing Dijkstra's Algorithm Internet of things Smart Cities Transportation

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Human Blood Cell (Haematologicalimages) Recognition by Applying Deep Convolution Methods 9

Human Blood Cell (Haematologicalimages) Recognition by Apply...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Krishna Kumar, N. Sarada, Ch. Mallika, S. Suguna Subhashini, P. Sai Kumar, K. Zearah, Sajad Ali Gnitc Department of Cse Hyderabad India Cvr College of Engineering Department of Cse Telangana Hyderabad India Mlr Institute of Technology Department of Computer Science And Information Technology Telangana Hyderabad India Malla Reddy University School of Engineering Computer Science Dulapally Maisammaguda Telangana Hyderabad500100 India Al-Ayen University Scientific Research Center Thi-Qar Iraq

ISBN: (纸本)9798350394474

Utilizing Deep Convolution Strategies to Perceive Human Platelets (Hematological Pictures): Deep Learning is rapidly becoming seen as a preferable method for learning over conventional ML models. This is on the grounds that it has previously been demonstrated to have the option to manage continuous issues in numerous application regions. Convolutional neural networks (CNNs), a sort of deep learning calculation, have a few advantages in the field of well-being, where a ton of pictures should be handled and inspected. The objective of the review is to make a deep learning model to take care of the issue of placing platelets into gatherings. It is one of the hardest things to sort out while checking blood out. A CNN-based framework has been made that consequently sorts pictures of platelets into various kinds of cells, like MONOCYTE, LYMPHOCYTE, NEUTROPHIL, and EOSINOPHIL. To further develop CNN innovation, specialists have investigated thoughts like the utilization of numerous initiation and misfortune capabilities, regularization, boundary advancement, and plan development. Be that as it may, changes to CNN's design have made it feasible for it to show much more. A block of layers can likewise be utilized as a structure block. This concentrates first glances at the inward scientific classifications of recently declared deep CNN frameworks. This is done so that new CNN configuration patterns can be placed into classes. The seven regions are channel gain, utilization of room, utilization of element maps, multipath, profundity, width, and consideration. Overall information on CNN's parts, its ongoing issues, and how it tends to be utilized is likewise given. © 2024 IEEE.

关键词： Platelets

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Efficient learning of continuous-variable quantum states

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Physical Review Research 2024年第3期6卷 033280页

作者： Ya-Dong Wu Yan Zhu Giulio Chiribella Nana Liu John Hopcroft Center for Computer Science QICI Quantum Information and Computation Initiative Department of Computer Science The Department of Computer Science for Theoretical Physics Waterloo Ontario N2L 2Y5 Canada Institute of Natural Sciences Ministry of Education Key Laboratory in Scientific and Engineering Computing School of Mathematical Sciences University of Michigan-

The characterization of continuous-variable quantum states is crucial for applications in quantum communication, sensing, simulation, and computing. However, a full characterization of multimode quantum states requires a number of experiments that grows exponentially with the number of modes. Here we propose an alternative approach where the goal is not to reconstruct the full quantum state, but rather to estimate its characteristic function at a given set of points. For multimode states with reflection symmetry, we show that the characteristic function at M points can be estimated using only O(logM) copies of the state, independently of the number of modes. When the characteristic function is known to be positive, as in the case of squeezed vacuum states, the estimation is achieved by an experimentally friendly setup using only beamsplitters and homodyne measurements.

关键词： Machine learning Quantum information processing with continuous variables Quantum tomography

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A Data-Driven Rutting Depth Short-Time Prediction Model With Metaheuristic Optimization for Asphalt Pavements Based on RIOHTrack

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IEEE/CAA Journal of Automatica Sinica 2023年第10期10卷 1918-1932页

作者： Zhuoxuan Li Iakov Korovin Xinli Shi Sergey Gorbachev Nadezhda Gorbacheva Wei Huang Jinde Cao School of Mathematics Southeast UniversityNanjing 210096China Scientific Research Institute of Multiprocessor Computer Systems Southern Federal UniversityTaganrog 347928Russia School of Cyber Science and Engineering Southeast UniversityNanjing 210096China Russian Academy of Engineering Moscow 125009Russia Intelligent Transportation System Research Center Southeast UniversityNanjing 210096China Nanjing Modern Multimodal Transportation Laboratory Nanjing 211100China Yonsei Frontier Laboratory Yonsei UniversitySeoulKorea(South)

Rutting of asphalt pavements is a crucial design criterion in various pavement design guides. A good road transportation base can provide security for the transportation of oil and gas in road transportation. This study attempts to develop a robust artificial intelligence model to estimate different asphalt pavements’ rutting depth clips, temperature, and load axes as primary characteristics. The experiment data were obtained from19 asphalt pavements with different crude oil sources on a 2.038km long full-scale field accelerated pavement test track(Road Track Institute, RIOHTrack) in Tongzhou, Beijing. In addition,this paper also proposes to build complex networks with different pavement rutting depths through complex network methods and the Louvain algorithm for community detection. The most critical structural elements can be selected from different asphalt pavement rutting data, and similar structural elements can be found. An extreme learning machine algorithm with residual correction(RELM) is designed and optimized using an independent adaptive particle swarm algorithm. The experimental results of the proposed method are compared with several classical machine learning algorithms, with predictions of average root mean squared error(MSE), average mean absolute error(MAE), and a verage mean absolute percentage error(MAPE) for 19 asphalt pavements reaching 1.742, 1.363, and 1.94% respectively. The experiments demonstrate that the RELM algorithm has an advantage over classical machine learning methods in dealing with non-linear problems in road engineering. Notably, the method ensures the adaptation of the simulated environment to different levels of abstraction through the cognitive analysis of the production environment parameters. It is a promising alternative method that facilitates the rapid assessment of pavement conditions and could be applied in the future to production processes in the oil and gas industry.

关键词： Extreme learning machine algorithm with residual correction(RELM) metaheuristic optimization oil-gas transportation RIOHTrack,rutting depth

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A Global Best-guided Firefly Algorithm for engineering Problems

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Journal of Bionic engineering 2023年第5期20卷 2359-2388页

作者： Mohsen Zare Mojtaba Ghasemi Amir Zahedi Keyvan Golalipour Soleiman Kadkhoda Mohammadi Seyedali Mirjalili Laith Abualigah Department of Electrical Engineering Faculty of EngineeringJahrom UniversityJahrom***FrasIran Department of Electronics and Electrical Engineering Shiraz University of TechnologyShiraz***Iran Department of Electrical and Computer Engineering Tarbiat Modares UniversityTehran***Iran Department of Computer Engineering Sari BranchIslamic Azad UniversitySari***Iran Department of Electrical Engineering Urmia BranchIslamic Azad UniversityUrmia571696896Iran Centre for Artificial Intelligence Research and Optimisation Torrens University AustraliaBrisbaneQLD4006Australia Yonsei Frontier Lab Yonsei UniversitySeoul03722South Korea Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan School of Computer Sciences Universiti Sains Malaysia11800George TownPulau PinangMalaysia University Research and Innovation Center Obuda University1034BudapestHungary School of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Applied science research center Applied science private universityAmman11931Jordan

The Firefly Algorithm(FA)is a highly efficient population-based optimization technique developed by mimicking the flashing behavior of fireflies when *** article proposes a method based on Differential Evolution(DE)/current-to-best/1 for enhancing the FA's movement *** proposed modification increases the global search ability and the convergence rates while maintaining a balance between exploration and exploitation by deploying the global best ***,employing the best solution can lead to premature algorithm convergence,but this study handles this issue using a loop adjacent to the algorithm's main ***,the suggested algorithm’s sensitivity to the alpha parameter is reduced compared to the original *** GbFA surpasses both the original and five-version of enhanced FAs in finding the optimal solution to 30 CEC2014 real parameter benchmark problems with all selected alpha ***,the CEC 2017 benchmark functions and the eight engineering optimization challenges are also utilized to evaluate GbFA’s efficacy and robustness on real-world problems against several enhanced *** all cases,GbFA provides the optimal result compared to other *** that the source code of the GbFA algorithm is publicly available at https://***/projects/gbfa.

关键词： Firefly algorithm New movement vector Global best-guided firefly algorithm Global optimization engineering design

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Application of functional near-infrared spectroscopy(fNIRS) for studying the influence of capsaicin stimulation on brain perception

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Food science and Human Wellness 2025年

作者： Ran Tao Hang Liang Huiting Qiao Xin Liu Na Xu Ling Wang Xinglian Xu Lingqi Li Yujia Yang Peng Wang State Key Laboratory of Meat Quality Control and Cultured Meat Development， Ministry of Education China， Jiangsu Collaborative Innovation Center of Meat Production and Processing， Quality and Safety Control， College of Food Science and Technology， Nanjing Agricultural University Danyang SuHuichuang Brain Scientific Research Center School of Biological Science and Medical Engineering， Beihang University College of Computer Science， Sichuan Normal University

Spicy taste have been utilized in the food industry as appetizers， stomachics， and beverages and in the health sector to alleviate high cholesterol and hypertension. However， an understanding of neural mechanisms and cognitive processes associated with spicy diets remains limited due to the lack of instruments that directly monitoring the brain’s reaction to spicy sensations. This study aimed to examine the neural responses of participants to oral capsaicin solutions through functional near-infrared spectroscopy and reveal distinct neural activation patterns associated with spiciness induction and relief phases. Results showed that the perception of spiciness is a dynamic process， and significant differences in sensory intensity and emotion were observed between the phases. The prefrontal regions of the brain were activated during spicy flavor perception and presented clear lateralization effects. Further spatial localization results indicated that the orbitofrontal， dorsolateral prefrontal， and ventral lateral prefrontal cortices were the main causes of difference in activation among the phases. In addition， correlational analyses indicated that spicy flavor perception activated cortical areas related to emotion and reward processing. Overall， this research enhances our understanding of the neural mechanisms underlying addiction to spicy food and may be useful in the development of food on the basis of consumers’ preferences and behavioral responses.

关键词： Taste Capsaicin fNIRS Prefrontal cortex Oral irritation

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