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33rd ACM Web Conference, WWW 2024

作者： Hu, Haichuan Liu, Fangming Pei, Qiangyu Yuan, Yongjie Xu, Zichen Wang, Lin National Engineering Research Center for Big Data Technology and System The Services Computing Technology and System Lab Cluster and Grid Computing Lab in the School of Computer Science and Technology Huazhong University of Science and Technology 1037 Luoyu Road Wuhan China Peng Cheng Laboratory Huazhong University of Science and Technology China School of Mathematics and Computer Science Nanchang University China Paderborn University Paderborn Germany

ISBN: (纸本)9798400701719

Graph Neural Networks (GNNs) have been increasingly adopted for graph analysis in web applications such as social networks. Yet, efficient GNN serving remains a critical challenge due to high workload fluctuations and intricate GNN operations. Serverless computing, thanks to its flexibility and agility, offers on-demand serving of GNN inference requests. Alas, the request-centric serverless model is still too coarse-grained to avoid resource waste. Observing the significant data locality in computation graphs of requests, we propose λGrapher, a serverless system for GNN serving that achieves resource efficiency through graph sharing and fine-grained resource allocation. "Grapher features the following designs: (1) adaptive timeout for request buffering to balance resource efficiency and inference latency, (2) graph-centric scheduling to minimize computation and memory redundancy, and (3) resource-centric function management with fine-grained resource allocation catered to the resource sensitivities of GNN operations and function orchestration optimized to hide communication latency. We implement a prototype of λGrapher based on the representative open-source serverless platform Knative and evaluate it with real-world traces from various web applications. Our results show that λGrapher can achieve an average savings of 61.5% in memory resource and 47.2% in computing resource compared with the state of the arts while ensuring GNN inference latency. © 2024 ACM.

关键词： Efficiency

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Mechanism design optimization through CAD-based Bayesian optimization and quantified constraints

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Discover Mechanical engineering 2024年第1期3卷 1-18页

作者： Ben Yahya, Abdelmajid Ramos Garces, Santiago Van Oosterwyck, Nick De Boi, Ivan Cuyt, Annie Derammelaere, Stijn Department of Electromechanics CoSysLab University of Antwerp Antwerp Belgium AnSyMo/CoSys Flanders Make The Strategic Research Center For The Manufacturing Industry Antwerp Belgium Department of Electromechanics InViLab University of Antwerp Antwerp Belgium Department of Computer Science University of Antwerp Antwerp Belgium Division of Computing Science and Mathematics University of Stirling Stirling United Kingdom

This study addresses the challenge of mechanism design optimization, particularly focusing on the energy efficiency and design space of reciprocating mechanisms. The research question centers on how to effectively utilize computer-Aided Design (CAD) simulations alongside Bayesian optimization (BO) and a constrained design space to streamline the design optimization process, overcoming the limitations of traditional kinematic and dynamic analysis methods. The objective is to investigate and develop a novel optimization framework that integrates CAD-based simulations with a BO approach. To achieve this, the study employs a methodological approach. At first, the feasibility of a chosen mechanism design is evaluated through a sequence of CAD-motion simulations to quantify the (in)feasibility of this design. When this design appears to be feasible, a CAD-based design evaluation method is started, in which the objective value is extracted by a sequence of CAD-motion simulations. In this paper, we advocate the use of non-parametric Gaussian processes to build a surrogate model of the objective function and the feasible design space constrained by static and dynamic constraints. The main research results demonstrate that the proposed CAD-based Bayesian optimization framework can effectively identify optimal design parameters that minimize the root mean square (RMS) torque while adhering to specified static and dynamic constraints. This optimization approach significantly reduces the complexity associated with analytic methods, making it scalable to more complex mechanisms and implementable by machine builders. In conclusion, the study successfully develops a novel optimization framework that leverages CAD-based simulations and Bayesian optimization to streamline the design process of mechanisms. The results of an emergency ventilator case study with three design parameters show a reduction of the RMS torque with 71% after 255 CAD-based design evaluations. Moreover, the resu

关键词： Bayesian optimization Dimensional synthesis Mechanical systems Motion control

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advanced Spatio-Temporal Froth Analysis Using Smart Soft Sensors in Mineral Processing

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SN computer science 2024年第4期5卷 363页

作者： Bendaouia, Ahmed Abdelwahed, El Hassan Qassimi, Sara Boussetta, Abdelmalek Benzakour, Intissar Amar, Oumkeltoum Chekroun, Mohamed Hasidi, Oussama Lachihab, Oussama Computer Systems Engineering Laboratory (LISI) Cadi Ayyad University Marrakech Morocco SEIA Department Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Rabat Morocco R & amp D and Engineering Center Reminex Managem Group Marrakech Morocco Computer and Systems Engineering Laboratory (L2IS) Cadi Ayyad University Marrakech Morocco

In the transformative field of mineral processing, the need for innovative technologies to overcome inherent difficulties and a critical shortage of high-quality data is an acute challenge. This study addresses these pressing issues by leveraging advanced spatio-temporal deep learning techniques, specifically Convolutional Long Short-Term Memory (ConvLSTM). Focused on the Zinc flotation circuit at CMG Managem Group in Morocco, our comprehensive approach encompasses meticulous data collection from a real-world industrial setting, rigorous spatial and temporal analyses, practical and accurate data augmentation, and the development of a ConvLSTM model for precise prediction of mineral grades. By capturing the temporal intricacies of froth behavior through video data, we gain insights into mineral concentration fluctuations, a critical aspect of traditional analysis. By offering a comprehensive solution that combines cutting-edge technology, meticulous data analysis, and practical augmentation methods, we aim to elevate not only mineral processing efficiency but also a broader spectrum of resource utilization and sustainable practices. This study offers a promising solution to elevate mineral processing efficiency and accuracy in the face of data limitations. It underscores the potential for transformative impacts on mineral processing operations, paving the way for more effective resource utilization and sustainable practices. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Data augmentation Industrial data analysis Machine learning Mineral processing

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Incentive mechanism design via smart contract in blockchainbased edge-assisted crowdsensing

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Frontiers of computer science 2025年第3期19卷 65-85页

作者： Chenhao YING Haiming JIN Jie LI Xueming SI Yuan LUO Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Jiao Tong University(Wuxi)Blockchain Advanced Research Center Wuxi 214101China

Edge-assisted mobile crowdsensing(EMCS)has gained significant attention as a data collection ***,existing incentive mechanisms in EMCS systems rely on centralized platforms,making them impractical for the decentralized nature of EMCS *** address this limitation,we propose CHASER,an incentive mechanism designed for blockchain-based EMCS(BEMCS)*** fact,CHASER can attract more participants by satisfying the incentive requirements of budget balance,double-side truthfulness,double-side individual rationality and also high social ***,the proposed BEMCS system with CHASER in smart contracts guarantees the data confidentiality by utilizing an asymmetric encryption scheme,and the anonymity of participants by applying the zero-knowledge succinct non-interactive argument of knowledge(zk-SNARK).This also restrains the malicious behaviors of ***,most simulations show that the social welfare of CHASER is increased by approximately when compared with the state-of-the-art ***,CHASER achieves a competitive ratio of approximately 0.8 and high task completion rate of over 0.8 in large-scale *** findings highlight the robustness and desirable performance of CHASER as an incentive mechanism within the BEMCS system.

关键词： mobile crowdsensing edge computing blockchain smart contract incentive mechanism

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Deformable micro-supercapacitor fabricated via laser ablation patterning of Graphene/liquid metal

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npj Flexible Electronics 2024年第1期8卷 770-778页

作者： Keon-Woo Kim Seong Ju Park Su-Jeong Park Inae Kim Bomi Park Se Hyun Kim Unyong Jeong Jin Kon Kim Chanwoo Yang National Creative Research Initiative Center for Hybrid Nano Materials by High-level Architectural Design of Block Copolymer Department of Chemical EngineeringPohang University of Science and Technology(POSTECH)PohangGyeongbuk 37763Republic of Korea Advanced Nano-Surface&Wearable Electronics Research Laboratory Heat and Surface Technology R&D DepartmentKorea Institute of Industrial TechnologyIncheon 21999Republic of Korea Division of Chemical Engineering Konkuk UniversitySeoul 05029Republic of Korea Department of Materials Science and Engineering Pohang University of Science and Technology(POSTECH)PohangGyeongbuk 37763Republic of Korea

Deformable andminiaturized energy storage devices are essential for powering soft ***,we fabricate deformablemicro supercapacitors(MSCs)based on eutectic gallium-indium liquidmetal(EGaIn)current collectors with integrated *** well-define interdigitated electrode patterning with controlled gap is successfully realized by using the laser ablation because of a strong laser absorption of graphene and *** judicious control of gap size between neighboring interdigitated electrodes and mass loading of graphene,we achieve a high areal capacitance(1336μF cm^(−2))with reliable rate *** addition,owing to the intrinsic liquid characteristics of EGaIn current collector,the areal capacitance of fabricated MSC retains 90% of original value evenafter repetitive foldingand20%stretching up to 1000 ***,we successfully integrate deformable MSC with a commercial light-emitting diode to demonstrate the feasibility ofMSC as a deformable power *** fabricated MSCs operate stably under various mechanical deformations,including stretching,folding,twisting,and wrinkling.

关键词： laser stretching liquid

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Quantifying the Influences of Carbides and Porosities on the Fatigue Crack Evolution of a Ni-Based Single-Crystal Superalloy using X-ray Tomography

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Acta Metallurgica Sinica(English Letters) 2022年第1期35卷 133-145页

作者： Keli Liu Junsheng Wang Bing Wang Pengcheng Mao Yanhong Yang Yizhou Zhou School of Materials Science&Engineering Beijing Institute of TechnologyBeijing100081China Advanced Research Institute of Multidisciplinary Science Beijing Institute of TechnologyBeijing100081China Center for Micro and Nano Technologies Beijing Institute of TechnologyBeijing100081China Superalloys Division Institute of Metal ResearchChinese Academy of SciencesShenyang110016China

The detrimental effects of carbides and porosity on the fatigue crack initiation and propagation of nickel-based single-crystal superalloys have been reported by many previous ***,few studies have quantitatively compared the fatigue damaging effects of carbides and pores on the fatigue crack *** this study,a high-resolution X-ray computed tomography(XCT)characterization of a DD5 nickel-based single-crystal superalloy during fatigue test was *** evolution of carbides,pores and cracks at all stages was observed and *** order to quantify the 3D microstructures,a new damage factor that correlates the morphology of fracture surface with crack evolution behaviors was *** was found that porosity was more detrimental than carbides in crack initiation and propagation during fatigue ***,pore spacing has been found to be the most significant factor among all controlling pore characteristics in the crack initiation stage and sphericity is the most critical pore characteristic in the crack propagation ***,by statistically analyzing the evolution of carbides and pores during fatigue tests in this study,the underlying fatigue cracking mechanism of nickel-based superalloys is revealed.

关键词： X-ray tomography Ni-based superalloys Fatigue Porosity Carbide Crack initiation Crack propagation

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Observation of possible excitonic charge density waves and metal–insulator transitions in atomically thin semimetals

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Nature Physics 2024年第4期20卷 597-602页

作者： Gao, Qiang Chan, Yang-Hao Jiao, Pengfei Chen, Haiyang Yin, Shuaishuai Tangprapha, Kanjanaporn Yang, Yichen Li, Xiaolong Liu, Zhengtai Shen, Dawei Jiang, Shengwei Chen, Peng Shenyang National Laboratory for Materials Science Shanghai Center for Complex Physics School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China Institute of Atomic and Molecular Sciences Academia Sinica Taipei Taiwan Physics Division National Center for Theoretical Sciences Taipei Taiwan Shanghai Synchrotron Radiation Facility Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China College of Engineering International Advanced Technology Program National Taiwan University of Science and Technology Taipei Taiwan Chinese Academy of Sciences Shanghai China National Synchrotron Radiation Laboratory University of Science and Technology of China Hefei China

In solids, the condensation of electron and hole pairs with finite momentum leads to an ordered state known as a charge density wave, in which the charge has spatial modulation. However, lattice symmetry breaking and the accompanying relocation of the ions, which changes the charge distribution, can also occur simultaneously, making it difficult to disentangle the origin of the transition. Here we demonstrate a condensed phase in low-dimensional HfTe2. Angle-resolved photoemission spectroscopy measurements reveal a metal–insulator transition upon lowering the temperature. The observation of an opening gap, the renormalization of the bands and the emergence of replica bands in the low-temperature regime suggests that a charge density wave formed in the ground state. Raman spectroscopy shows no sign of lattice distortion within the detection limit. A small amount of electron doping substantially raises the transition temperature due to a reduced screening effect and a more balanced carrier density for electrons and holes. Our results indicate that the formation mechanism of the charge density wave is consistent with the excitonic insulator phase in low-dimensional HfTe2 without any structural modification. © The Author(s), under exclusive licence to Springer Nature Limited 2024.

关键词： Charge density waves

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Polyp image segmentation based on improved planet optimization algorithm using reptile search algorithm

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Neural Computing and Applications 2025年第8期37卷 6327-6349页

作者： Abd Elaziz, Mohamed Al-qaness, Mohammed A. A. Al-Betar, Mohammed Azmi Ewees, Ahmed A. Department of Mathematics Faculty of Science Zagazig University Zagazig Egypt College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua321004 China Zhejiang Institute of Optoelectronics Jinhua321004 China Faculty of Computer Science and Engineering Galala University Suze435611 Egypt Ajman University Ajman346 United Arab Emirates College of Computing and Information Technology University of Bisha Bisha Saudi Arabia Department of Computer Damietta University Damietta Egypt Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan

To recognize the potential for colon polyps to develop into cancer over time, early diagnosis is crucial for preventative healthcare. Timely identification significantly improves the prognosis and treatment outcomes for colorectal cancer patients. Image segmentation is crucial in medical image analysis for accurate diagnosis and treatment planning. Therefore, in this study, we present an alternative multilevel thresholding polyp segmentation method (MPOA) to enhance the segmentation of polyp images. The proposed method is based on enhancing the planet optimization algorithm (POA) by integrating operators from the reptile search algorithm (RSA). The evaluation of the developed MPOA is tested with different polyp images and compared with other image segmentation approaches. The results highlight the superior capability of MPOA, as evidenced by various performance measures in effectively segmenting polyp images. Furthermore, metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and fitness values demonstrate that MPOA outperforms the basic version of POA and other methods. The evaluation outcomes underscore the significant impact of RSA in enhancing the performance of POA for the segmentation of polyp images. © The Author(s) 2025.

关键词： Diseases

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A Comprehensive Evaluation of State-of-the-Art Deep Learning Models for Road Surface Type Classification

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Intelligent Automation & Soft Computing 2023年第8期37卷 1275-1291页

作者： Narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Image Information and Intelligence Laboratory Department of Computer EngineeringFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication TechnologyUniversity of PhayaoPhayao56000Thailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research InstituteKing Mongkut’s University of Technology North BangkokBangkok10800Thailand

In recent years,as intelligent transportation systems(ITS)such as autonomous driving and advanced driver-assistance systems have become more popular,there has been a rise in the need for different sources of traffic situation *** classification of the road surface type,also known as the RST,is among the most essential of these situational data and can be utilized across the entirety of the ITS ***,the benefits of deep learning(DL)approaches for sensor-based RST classification have been demonstrated by automatic feature extraction without manual *** ability to extract important features is vital in making RST classification more *** work investigates the most recent advances in DL algorithms for sensor-based RST classification and explores appropriate feature extraction *** used different convolutional neural networks to understand the functional architecture better;we constructed an enhanced DL model called SE-ResNet,which uses residual connections and squeeze-and-excitation mod-ules to improve the classification *** experiments with a publicly available benchmark dataset,the passive vehicular sensors dataset,have shown that SE-ResNet outperforms other state-of-the-art *** proposed model achieved the highest accuracy of 98.41%and the highest F1-score of 98.19%when classifying surfaces into segments of dirt,cobblestone,or asphalt ***,the proposed model significantly outperforms DL networks(CNN,LSTM,and CNN-LSTM).The proposed RE-ResNet achieved the classification accuracies of asphalt roads at 98.98,cobblestone roads at 97.02,and dirt roads at 99.56%,respectively.

关键词： Road surface type classification deep learning inertial sensor deep pyramidal residual network squeeze-and-excitation module

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Pre-Impact and Impact Fall Detection Based on a Multimodal Sensor Using a Deep Residual Network

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Intelligent Automation & Soft Computing 2023年第6期36卷 3371-3385页

作者： Narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Image Information and Intelligence Laboratory Department of Computer EngineeringFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication TechnologyUniversity of PhayaoPhayaoThailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok 10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research Institute King Mongkut’s University of Technology North BangkokBangkok 10800Thailand

Falls are the contributing factor to both fatal and nonfatal injuries in the ***,pre-impact fall detection,which identifies a fall before the body collides with the floor,would be ***,researchers have turned their attention from post-impact fall detection to pre-impact fall ***-impact fall detection solutions typically use either a threshold-based or machine learning-based approach,although the threshold value would be difficult to accu-rately determine in threshold-based ***,while additional features could sometimes assist in categorizing falls and non-falls more precisely,the esti-mated determination of the significant features would be too time-intensive,thus using a significant portion of the algorithm’s operating *** this work,we developed a deep residual network with aggregation transformation called FDSNeXt for a pre-impact fall detection approach employing wearable inertial *** proposed network was introduced to address the limitations of fea-ture extraction,threshold definition,and algorithm *** training on a large-scale motion dataset,the KFall dataset,and straightforward evaluation with standard metrics,the proposed approach identified pre-impact and impact falls with high accuracy of 91.87 and 92.52%,*** addition,we have inves-tigated fall detection’s performances of three state-of-the-art deep learning models such as a convolutional neural network(CNN),a long short-term memory neural network(LSTM),and a hybrid model(CNN-LSTM).The experimental results showed that the proposed FDSNeXt model outperformed these deep learning models(CNN,LSTM,and CNN-LSTM)with significant improvements.

关键词： Pre-impact fall detection deep learning wearable sensor deep residual network

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