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38th ACM International conference on Supercomputing (ACM ICS)

作者： Neff, Reece Zarch, Mostafa Eghbali Minutoli, Marco Halappanavar, Mahantesh Tumeo, Antonino Kalyanaraman, Ananth Becchi, Michela North Carolina State Univ Raleigh NC 27695 USA Pacific Northwest Natl Lab Richland WA USA Washington State Univ Pullman WA USA

ISBN: (纸本)9798400706103

Probabilistic breadth-first traversals (BPTs) are used in many network science and graph machine learning applications. In this paper, we are motivated by the application of BPTs in stochastic diffusion-based graph problems such as influence maximization. These applications heavily rely on BPTs to implement a Monte-Carlo sampling step for their approximations. Given the large sampling complexity, stochasticity of the diffusion process, and the inherent irregularity in real-world graph topologies, efficiently parallelizing these BPTs remains significantly challenging. In this paper, we present a new algorithm to fuse a massive number of concurrently executing BPTs with random starts on the input graph. Our algorithm is designed to fuse BPTs by combining separate probabilistic traversals into a unified frontier. To show the general applicability of the fused BPT technique, we have incorporated it into two state-of-the-art influence maximization parallel implementations (gIM and Ripples). Our experiments on up to 4K nodes of the OLCF Frontier supercomputer (32, 768 GPUs and 196K CPU cores) show strong scaling behavior, and that fused BPTs can improve the performance of these implementations up to 182.13x (avg. 75.15x) and 359.86x (avg. 135.17x) for gIM and Ripples, respectively.

关键词： Parallel Graph Algorithms Influence Maximization

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Orianna: An Accelerator Generation Framework for Optimization-based Robotic applications 24

Orianna: An Accelerator Generation Framework for Optimizatio...

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29th ACM International conference on Architectural Support for Programming Languages and Operating systems (ASPLOS)

作者： Hao, Yuhui Gan, Yiming Yu, Bo Liu, Qiang Han, Yinhe Wan, Zishen Liu, Shaoshan Tianjin Univ Tianjin Peoples R China Chinese Acad Sci ICT Beijing Peoples R China BeyonCa Hong Kong Peoples R China Georgia Tech Atlanta GA USA PerceptIn Santa Clara CA USA

ISBN: (纸本)9798400703850

Despite extensive efforts, existing approaches to design accelerators for optimization-based robotic applications have limitations. Some approaches focus on accelerating general matrix operations, but they fail to fully exploit the specific sparse structure commonly found in many robotic algorithms. On the other hand, certain methods require manual design of dedicated accelerators, resulting in inefficiencies and significant non-recurring engineering (NRE) costs. The Orianna framework represents a significant advancement as it overcomes the limitations of existing approaches and provides a solution to generate accelerators for robotic applications that integrate multiple optimization-based algorithms. The framework leverages a common abstraction factor graph to overcome these challenges. Application designers can easily define their objectives and constraints using the Orianna software framework. The Orianna compiler then translates the high-level code into basic matrix operations and executes them in an out-of-order manner on the generated accelerator. We demonstrate its effectiveness by implementing a real FPGA-based prototype. Orianna accelerators achieve a 6.5x performance improvement and a 15.1x energy reduction compared to an advanced Intel CPU. Furthermore, Orianna achieves comparable performance to state-of-the-art dedicated accelerators while utilizing only 36.1% of hardware resources.

关键词： Application programs

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Polymer-Based Self-Calibrated Optical Fiber Tactile sensor

Polymer-Based Self-Calibrated Optical Fiber Tactile Sensor

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IEEE/RSJ International conference on Intelligent Robots and systems (IROS)

作者： Chen, Wentao Yan, Youcan Zhang, Zeqing Yang, Lei Pan, Jia Univ Hong Kong Dept Comp Sci Pokfulam Hong Kong Peoples R China Univ Montpellier Interact Digital Humans Grp LIRMM CNRS Montpellier France Ctr Transformat Garment Prod Hong Kong Peoples R China

ISBN: (纸本)9781665491907

Human skin can accurately sense the self-decoupled normal and shear forces when in contact with objects of different sizes. Although there exist many soft and conformable tactile sensors on robotic applications able to decouple the normal force and shear forces, the impact of the size of object in contact on the force calibration model has been commonly ignored. Here, using the principle that contact force can be derived from the light power loss in the soft optical fiber core, we present a soft tactile sensor that decouples normal and shear forces and calibrates the measurement results based on the object size, by designing a two-layered weaved polymer-based optical fiber anisotropic structure embedded in a soft elastomer. Based on the anisotropic response of optical fibers, we developed a linear calibration algorithm to simultaneously measure the size of the contact object and the decoupled normal and shear forces calibrated the object size. By calibrating the sensor at the robotic arm tip, we show that robots can reconstruct the force vector at an average accuracy of 0.15N for normal forces, 0.17N for shear forces in x-axis, and 0.18N for shear forces in Y-axis, within the sensing range of 0-2N in all directions, and the average accuracy of object size measurement of 0.4mm, within the test indenter diameter range of 5-12mm.

关键词： Anisotropy

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Design of real time monitoring and intelligent analysis system for fiber optic sensor networks driven by big data 3

Design of real time monitoring and intelligent analysis syst...

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3rd International conference on Electronic Information Engineering and Data Processing, EIEDP 2024

作者： Gang, Huang Like, Pan Chengzhang, He Chengfeng, Yang Zhong, Li xiuyi, Pan Yongjia County Electric Power Industry Co. Ltd. Zhejiang Wenzhou325100 China State Grid Yongjia County Power Supply Co. Ltd. Zhejiang Wenzhou325100 China

ISBN: (纸本)9781510680531

This article explores the application of big data technology in the design of real-time monitoring and intelligent analysis systems for fiber optic sensor networks (FOSN). An analysis was conducted on the limiting factors of current FOSN, such as cross sensitivity, data processing speed, signal-to-noise ratio, etc. This paper proposes an advanced data analysis engine based on CNN (Convolutional Neural Network) algorithm model and artificial intelligence to overcome these challenges. In the real-time data processing capability experiment, the average time for processing 10000 pieces of data based on CNN algorithm system was only 0.05 seconds, while the time for processing 100000 pieces of data was controlled within 0.5 seconds, demonstrating the efficiency of processing large-scale data. In the accuracy verification experiment of monitoring, the average error of the CNN algorithm system for 1000 data is only 0.03, indicating the high accuracy performance of the system in real-time monitoring. © 2024 SPIE.

关键词： sensor networks

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Statistical Stratification and Benchmarking of Robotic Grasping Performance

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IEEE TRANSACTIONS ON ROBOTICS 2023年第6期39卷 4539-4551页

作者： Denoun, Brice Hansard, Miles Leon, Beatriz Jamone, Lorenzo Queen Mary Univ London Sch Elect Engn & Comp Sci London E1 4NS England Shadow Robot Co London NW5 1LP England

Robotic grasping is fundamental to many real-world applications, and new approaches must be systematically evaluated. However, in most cases, the performance of a specific approach is assessed by simply counting the number of successful attempts in a given task, and this success rate is then compared to those of other solutions, without taking into account the random variability across different experiments (e.g. due to sensor noise or variations in object placement). In order to address this issue, we classify the observed performance into qualitatively ordered outcomes, thereby stratifying the results. We then show how to analyze these results in a statistical framework, which accounts for the variability between experiments. The advantages of our approach are demonstrated in the practical comparison of four grasp planning algorithms. In particular, we show that the proposed approach allows us to carry out several distinct evaluations from a single set of experiments, without having to repeat the data collection process. We demonstrate that differences between the algorithms, which would not be apparent from overall success rates, can be identified and evaluated.

关键词： Grasping Benchmark testing Task analysis Robot sensing systems Protocols performance evaluation and benchmarking probability and statistical methods

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International conference on Power Engineering and Intelligent systems, PEIS 2024

International Conference on Power Engineering and Intelligen...

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International conference on Power Engineering and Intelligent systems, PEIS 2024

ISBN: (纸本)9789819767137

The proceedings contain 41 papers. The special focus in this conference is on Power Engineering and Intelligent systems. The topics include: Smart Seating: The Smart Seating Solution for Crowded Public Transit;comparative Study of Coil Shapes for Electric Vehicle Resonant Wireless Power Transfer System;A Case Study of Solar Photovoltaic and Biomass-Based Hybrid Power System in Educational Institutes in Delhi-NCR;comparative Analysis of Water Bodies Segmentation Techniques;load Frequency Control in Hybrid Integrated Power systems with Redox Flow Batteries Using Dual-Mode Gain Scheduling Method;enhanced Discrete Cosine Transform Image Compression for Ultra-High-Resolution Imagery;Simulation and Analysis of 6T SRAM Cell in NGSpice: Exploring Performance and Stability;design of Double Precision Floating Point Comparator for Multiple Numbers;secured Regulatory Data Compliance for the Pharmaceutical Sector Through Blockchain;Optimizing IoT-Based Quantum Wireless sensor Networks Using NM-TEEN Fusion of Energy Efficiency and Systematic Governance;optimal Sizing and Allocation of Multiple Distributed Generation;high-Gain x-Band Patch Antenna for Spaceborne Synthetic Aperture Radar applications;protection of Series Compensated Networks Using Different Techniques: An Overview;a Robotic Way to Investigate Unapproachable Places and Inaccessible Substances Using e-skin;a Review of Chatbot Technology: Its Design and Implementation;exploring the Microcosm: A Comprehensive Survey of Micro sensor applications Across Multidisciplinary Research;stress Classification Using Machine Learning Techniques: Comparative Study;normalized Mutual Information-Driven Feature Extraction Method for Big Data Analytics;modeling of a Novel Correlation-Weighted Elman Neural Network for Building Automation System;Application FOPID for PLL Design in Grid Integration;Impact of Inter-Next Generation Node B (gNB) Distance on End-User applications in 5G Networks.

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14th EAI International conference on Ad Hoc Networks, AdHocNets 2023

14th EAI International Conference on Ad Hoc Networks, AdHocN...

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14th EAI International conference on Ad Hoc Networks, AdHocNets 2023

ISBN: (纸本)9783031559921

The proceedings contain 15 papers. The special focus in this conference is on Ad Hoc Networks. The topics include: Two Embedding Algorithms in Schur-Based Image Watermarking Scheme;metaheuristics-Based Hyperparameter Tuning for Convolutional Neural Networks;antenna Array Pattern Nulling via Convex Optimization;interference Suppression Approaches Utilizing Phase-Only Control and Metaheuristic Algorithms: A Comparative Study;reconfigurable Intelligent Surface-Aided Wireless Communication Considering Interference Suppression;nature-Inspired Algorithms-Based Beamforming for advanced Antenna systems;Investigation of Transmit Antenna Selection for MU-VASM systems over Correlated Channels;Millimeter Wave Path Loss Modeling for UAV Communications Using Deep Learning;Enhance Secrecy Performance of the Cooperative NOMA/UAV Network Applying NSGA-II Algorithm;fake News Detection Based on Multi-view Fuzzy Clustering Algorithm;an Efficient Approach to the k-Strong Barrier Coverage Problem Under the Probabilistic Sensing Model in Wireless Multimedia sensor Networks;an Efficient Method for Solving the Best Coverage Path Problem in Homogeneous Wireless Ad-Hoc sensor Networks;performance of Uplink Ultra Dense Network with Antenna Selection.

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A Novel Compact Dual-Band Dipole Antenna for Vehicle applications 16

A Novel Compact Dual-Band Dipole Antenna for Vehicle Applica...

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16th International conference on Microwave and Millimeter Wave Technology (ICMMT)

作者： Liao, Yixuan Li, Shuangde Liu, Yuanjian Zheng, Chengcheng Nanjing Univ Posts & Telecommun Coll Elect & Opt Engn Nanjing Peoples R China Nanjing Univ Posts & Telecommun Coll Flexible Elect Future Technol Nanjing Peoples R China

ISBN: (纸本)9798350389968

A dual-band dipole vehicle antenna for 5G Sub-6G applications is demonstrated in this paper. The overall size of the proposed antenna is 0.287 lambda(0) x 0.165 lambda(0) x 0.008 lambda(0) (lambda(0) is the wavelength corresponding to the lowest frequency of 3.1 GHz), which is suitable for placing on top of the car inside a shark fin scenario. The antenna is accomplished in software. And all parameters are measured in a microwave darkroom. The -10 dB reflection coefficients have good impedance matching at 3.1-5.5 GHz (55.81% of the relative bandwidth) and 5.7-6.4 GHz (11.57% of the relative bandwidth). The antenna produces a stable omnidirectional pattern with maximum gain of 5.6 dBi at the interested band. Thus, these excellent characteristics can make the proposed antenna suitable for the in-vehicle wireless systems.

关键词： 5G Sub-6 GHz shark fin scenario vehicular antenna dipole omnidirectional radiation

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The cultivation of autonomous strategic coordination systems 26

The cultivation of autonomous strategic coordination systems

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conference on Unmanned systems Technology xxVI

作者： Scully, Christopher Bahr, George Bajkowski, Trevor Keller, James Scott, Grant J. Carley, Samantha Price, Stanton Univ Missouri Columbia Elect Engn & Comp Sci Dept Columbia MO 65211 USA US Army Engineer Res & Dev Ctr Vicksburg MS USA

ISBN: (纸本)9781510674295;9781510674288

Recently, reinforcement learning has been exhibited as being capable of providing base-level reasoning towards agent-based intelligence. Agents have had applications of reinforcement learning applied from simpler problem spaces (such as learning how to play with virtual cards), to learning how to make a physical robot walk. With reinforcement learning exhibiting capabilities to provide intelligence towards an individual agent, a question becomes how well could a reinforcement learning agent be able to manage multiple individual agents that have their execution of tasks abstracted. This challenge is important to recognize when we consider more advanced applications of reinforcement learning, such as leveraging reinforcement learning to conduct strategic coordination. In our studies, we have developed a system that leveraged reinforcement learning in an abstracted competitive strategic environment (currently, a real-time strategy (RTS) engine) to evaluate the effectiveness of reinforcement learning in automating the strategic approach of individual agents. To do this, we've defined several objectives for our reinforcement learning agent to perform (eg. offense, defense, economy). Given each one of these tasks, we can incentivize and disincentivize based on both general and objective-specific metrics. Based on the cultivation of autonomous strategic coordination systems, we believe this process will enable more robust situational responses in the future for autonomous, cooperative systems, and enable automated strategic response systems in operational domains.

关键词： Education and training Performance modeling Reflection Control systems Video Organization management Roads Situational awareness sensors systems modeling Unmanned aerial vehicles

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THz Near-Field Imaging sensor Using Integrated Substrateless Silicon Interferometer 15

THz Near-Field Imaging Sensor Using Integrated Substrateless...

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15th German Microwave conference (GeMiC)

作者： Iwamatsu, Shuya Headland, Daniel Mohammad, Israa Fujita, Masayuki Stoehr, Andreas Univ Duisburg Essen Dept Optoelect Duisburg Germany Univ Carlos III Madrid Optoelect & Laser Technol Grp Madrid Spain Osaka Univ Grad Sch Engn Sci Toyonaka Osaka Japan

ISBN: (纸本)9783982039732

Terahertz (THz) time- domain spectroscopy (TDS) technology has greatly advanced various THz applications ranging from fundamental science to industrial non-destructive imaging. However, traditional THz-TDS systems rely on complex setups with femtosecond pulse lasers and bulky free-space optical components, hindering their miniaturization. A more practical approach introduces THz frequency domain imaging using semiconductor laser diodes, which replace femtosecond laser and facilitate integration into photonic integrated circuit (PIC) chips. Despite its promise, addressing real-world imaging applications remains challenging due to the need for free-space optics, which also negatively impact resolution due to the diffraction limit. To overcome this limitation, this study explores the use of silicon (Si) microphotonics, focusing on an integrated Y-junction that operates as an interferometer. The Y-junction essentially replaces all free-space components, paving the way towards compact, monolithically integrated all-silicon structures that span just similar to 1 cm. We demonstrate near-field imaging at 325 GHz employing the Y-junction. The experiments achieve a 500-mu m spatial resolution and a 100-mu m depth resolution, showcasing potential for handheld THz near-field imaging sensors.

关键词： chip-scale terahertz imaging integrated photonics interferometer silicon Y-junction

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