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检索条件"主题词=software algorithms"

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Towards a Distributed Quantum Computing Platform for Algorithm Experiments

Towards a Distributed Quantum Computing Platform for Algorit...

引用

Quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Sajjad Kashani Angadh Singh Ulrike Stege University of Victoria

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Distributed quantum computing (DQC) is a rapidly evolving field with its own unique challenges. Distributing a quantum algorithm involves several key steps and considerations. The steps involve decomposition at various levels of abstraction, given the underlying quantum stack and quantum network capabilities. In our DQC design explorations, we focus on the distribution at the algorithm and circuit levels. Algorithmic distribution involves distributing tasks before compilation, allowing different quantum processing units (QPUs) to receive distinct parts of an algorithm. Circuit distribution involves executing a quantum algorithm in a distributed manner at the circuit execution level using circuit and adaptive quantum technologies. If entanglement across QPUs is supported, then quantum states can be shared between qubits on remote quantum processors. This requires a specialized architecture with data and communication qubits with non-local gates such as telegates and teledata gates. This paper presents our progress towards a framework for exploring quantum distribution at the algorithm and circuit levels. Our implementation and case studies demonstrate the feasibility of our approach and show effective pathways for distributed quantum algorithm experiments.

关键词： Quantum computing Quantum algorithm Quantum entanglement Qubit software algorithms Prototypes Logic gates Quantum state software Quantum networks

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Real-Time, Multistatic RFID Localization with Commodity, Unsynchronized Radios

Real-Time, Multistatic RFID Localization with Commodity, Uns...

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IEEE International Conference on RFID

作者： Dimitrios Angelou Aggelos Bletsas School of Electrical and Computer Engineering Technical University of Crete Chania Greece Dept. of Electrical and Computer Engineering Rutgers WINLAB The State University of New Jersey

ISBN: (数字)9798331509057

ISBN: (纸本)9798331509064

Passive RFID tag localization has been mostly focused on monostatic and/or synchronized setups. This work moves a few steps further and performs real-time localization with distributed, i.e., multistatic radios, which are also unsynchronized at the carrier level. It succeeds by exploiting the elliptical direction of arrival (EllDoA) algorithm with a “playback” carrier frequency offset (CFO) mitigation method, showing localization feasibility at a small error cost, even with very cheap software defined radios. The inherent carrier phase offset (CPO) of such distributed setups is addressed, and it is shown that the calibration step needs to be performed only once, and not for further reruns of the experiment; thus, the proposed method is suitable for many real-world and real-time applications, which has not been shown before, to the best of our knowledge.

关键词： Location awareness Three-dimensional displays Prevention and mitigation Scalability software algorithms Real-time systems Calibration Synchronization Radiofrequency identification software radio

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Evaluating Code Emulating Upsets on Microcontroller Devices

Evaluating Code Emulating Upsets on Microcontroller Devices

引用

IEEE Southeastcon

作者： Cebron Williams Daniel B. Limbrick John Kelly Christopher Doss Department of Electrical and Computer Engineering North Carolina Agricultural and Technical State University Greensboro NC United States

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Fault attacks pose a significant threat to the functionality and reliability of embedded systems, particularly microcontrollers that are widely used in critical applications such as consumer electronics, medical devices, industrial systems, and recently machine learning models. Given the nature of fault injection attacks, the cost for setting up and running fault injection campaigns can be inaccurate, time consuming and expensive. Because of this, alternative methods such as software, GDB based and RTL model fault injection have been developed. This paper compares these fault injection methods and proposes a high-level, standalone method of injecting faults into the ARM Cortex M0+ microcontroller with high accuracy and customization, while exploring the vulnerability of various algorithms.

关键词： Embedded systems Medical devices Costs Microcontrollers software algorithms Machine learning Computer crashes software Reliability Consumer electronics

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Proactive Platform for Active Health Services (AHS) Considering Data Securities

Proactive Platform for Active Health Services (AHS) Consider...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： Peiping Wu Wangni Xu Xin Yu China Fine Art Academy Hangzhou China New York University New York USA

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

In order to meet the high requirements of active health service (AHS) platform for data security and privacy protection, this study innovates from many aspects and proposes a new design scheme of active health service platform. The innovations of this study mainly include three aspects: (1) This study designs and develops a new health monitoring device that integrates blood pressure, blood oxygen and pulse monitoring functions from the hardware and software levels. (2) This study implements a new cloud data encryption method based on a hybrid chaotic mapping algorithm. The algorithm integrates chaotic information to improve data transmission security. (3) This study proposes a system algorithm for the multi-factor authentication and access control to further enhance data privacy protection capabilities. In terms of data security, the proposed hybrid chaotic encryption algorithm combines Logistic and Rossler mapping to achieve a balance between complexity and encryption efficiency. Experimental results show that this platform can effectively support active health management and protect data security to the greatest extent.

关键词： Multi-factor authentication Chaotic mapping Data security software algorithms Blood pressure Encryption Protection Monitoring Blood Logistics

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Adversarial Evaluation Algorithm for Detecting Extreme Behaviors of LLMs in Psychological Counseling Scenarios

Adversarial Evaluation Algorithm for Detecting Extreme Behav...

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2025 2nd International Conference on algorithms, software Engineering and Network Security (ASENS)

作者： Qingxing Zeng Xiang Li Siyu Wang Kai Liu Legal Artificial Intelligence Laboratory South China University of Technology Guangzhou China School of Computer Science and Engineering South China University of Technology Guangzhou China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

This study aims to develop an adversarial evaluation algorithm to detect the ability of large language models (LLMs) to recognize extreme behaviors in psychological counseling scenarios. We constructed a CEA dataset containing background, emotion, and behavioral characteristics, and proposed a dynamic adversarial test method based on cross-variation to evaluate the sensitivity of LLMs to extreme behaviors and their ability to intervene ethically. The experimental results showed that different LLMs had different performances: DeepSeek, Wenxin Yiyan and Claude were usually able to actively intervene, showing a high sensitivity to extreme behaviors and effective intervention ability; GPT-4, on the other hand, was more indifferent and had a lower intervention rate. This study verifies the robustness and intervention ability of different LLMs in complex emotional scenarios, but also points out that their intervention strategies and response consistency still need to be further optimized in practical applications. Future research can focus on expanding the diversity of datasets, improving the ability of model behavior feature recognition, verifying in real-world scenarios, and strengthening ethics and privacy protection, so as to improve the application value of LLMs in the field of mental health.

关键词： Employee welfare Ethics Sensitivity Large language models software algorithms Mental health Network security Robustness Protection software engineering

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Identification Based on the Optimal Information Structure of Non-Stationary Objects

Identification Based on the Optimal Information Structure of...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Isroil I. Jumanov Sunatillo M. Xolmonov Olimjon I. Djumanov Department of Artificial Intelligence and Information Systems Samarkand state university named after Sh. Rashidov Samarkand Uzbekistan

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

Scientific and methodological foundations have been developed for optimizing the identification of non-stationary objects based on the optimal information structure with mechanisms for selecting an adequate model, reducing excess space, highlighting, dividing random time series, clustering, and forecasting, subject to a priori limitations and parametric uncertainty of processes. The effectiveness of using identifiers based on dynamic models combined with a neural network has been studied. algorithms for combined statistical and dynamic models and neural networks of various architectures have been implemented. Tools for modeling processes and presenting statistical, dynamic and specific characteristics were obtained. The computational schemes of network components with mechanisms for setting variables, optimization, and adaptive network training have been improved.v A cognitive analysis of variables has been implemented taking into account structural complexity, stochasticity of element connections based on a stochastic regression model, by tracking the ambiguity of dynamics. Optimization problems based on the probabilistic risk function and sliding control were solved. A generalized algorithm for identifying non-stationary objects is constructed based on tools for identifying boundaries, the general range of element values, selecting informative elements, and generating training sets. An identification software package was implemented in C++ in the parallel computing environment “CUDA”.

关键词： Training Adaptation models software packages Computational modeling Heuristic algorithms software algorithms Stochastic processes Data models Object recognition Optimization

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From Concepts to Applications: A Comprehensive Overview of ROS

From Concepts to Applications: A Comprehensive Overview of R...

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International Conference on Computational Cybernetics (ICCC)

作者： Esmeralda Kadena Marsidi Gupi Beatrix Fregan Aniko Horvath-Kiss Xhezmije Palushi Zoltan Rajnai Banki Donát Faculty of Mechanical and Safety Engineering Obuda University Budapest Hungary Faculty of Economics Governance and Law Barleti University Tirana Albania National University of Public Service Budapest Hungary Faculty of Information Technology Tirana Business University Tirana Albania

ISBN: (数字)9798331502461

ISBN: (纸本)9798331502478

This paper explores the Robot Operating System (ROS), a foundational open-source middleware designed to facilitate robotics development by integrating hardware and software. It provides essential tools and algorithms enabling efficient programming of complex robotic systems. This work delves into the core components of ROS, including its computational graph model, parameter servers, and messaging systems, while highlighting tools that enhance system capabilities. Additionally, the paper reviews navigation algorithms, from traditional ones to advanced path-planning techniques, emphasizing their applications in autonomous mobile robotics. Comparisons of robotics software platforms illustrate the diversity and adaptability required to meet the demands of modern robotics. In the end, this paper emphasizes its critical role in advancing academic research and industrial applications.

关键词： Service robots Navigation Reviews Operating systems software algorithms Hardware Servers Middleware Robots Robot programming

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Modeling and Simulation of Directed Graph-Based DEVS System

Modeling and Simulation of Directed Graph-Based DEVS System

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Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-Electronics and Micro-Systems EuroSimE

作者： Shuai Ao Wei Hu Shengjie Wang Bo Li Chenglong Yin Xiaowei Liu Junfan Zhang Xiao Song Sandaogou Coal Mine Sandaogou Coal Mine Shaanxi Deyuan Fugu Energy Co. Ltd. Shaanxi Deyuan Fugu Energy Co. Ltd. Shannxi China Guoneng Digital Intelligence Technology Development Co. Ltd. Guoneng Digital Intelligence Technology Development Co. Ltd. Beijing China School of Cyber Science and Technology Beihang University Beijing China

ISBN: (数字)9798350393002

ISBN: (纸本)9798350393019

In the era of rapid advancements in energy, manufacturing, and aerospace, system modeling and simulation is essential across industries. Simulation technologies enable better control over experimental processes, cost reduction, and enhanced system safety. Traditional text-based methods, which utilize natural or programming languages, often lead to intricate coding and obscure system structures. Conversely, graphical methods employ visuals and symbols to depict system architectures and processes, offering superior interactivity and model clarity, thus garnering considerable research interest. Drawing from the System of Systems (SoS) theory, we introduce a simulation model definition tailored for complex systems, segmenting them into basic models, model connections, and subsystems, and employing hierarchical models to delineate system structure and functionality. We utilize directed graphs as graphical modeling elements, amalgamating them with the Discrete Event System Specification (DEVS) to craft a unified modeling and simulation algorithm apt for hierarchical models. This algorithm underpins a cloud-based platform for complex system modeling and simulation, replete with fundamental models and interfaces for cloud service model co-simulation. We exemplify this with an aircraft flight model, elucidating the graphical elements and their mathematical counterparts, thereby highlighting the lucidity and efficacy of graphical elements in complex system modeling. The results affirm that our directed graph-based algorithm adeptly integrates local and cloud service models, articulates system structure with clarity, and resolves complex system models with efficiency. A comparative analysis with mainstream software underscores the algorithm's expansibility. Our approach surpasses traditional text-based methods in accurately delineating complex system model structures, yielding more lucid and precise system models.

关键词： Visualization Atmospheric modeling software algorithms Directed graphs Systems architecture Symbols Systems modeling Mathematical models Complex systems System of systems

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Fault Model Establishment and Hybrid Neural Network Diagnosis for Manipulator

Fault Model Establishment and Hybrid Neural Network Diagnosi...

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Robotics, Control and Automation (ICRCA), International Conference on

作者： Yongbo Chen Zhang Ting Department of Mechanical and Electronic Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

Due to solve the problem of imbalanced and insufficient fault diagnosis data for manipulator, an effective joint fault model is established and the fault diagnosis analyses are proposed with an optimized hybrid neural network in the paper. the terminal acceleration data is gained by the Co-simulation analysis in Ansys and Adams software. The two-population algorithm is improved to optimize the hybrid network model with three shallow networks. In addition, after preprocessing the acceleration data, the hybrid network is used for training, learning and diagnosing fault. Finally, the network achieves a high fault-diagnosis accuracy with an average of 94.8%. The result indicates that not only the simulation model is established correctly, but also the fault features of acceleration data for the optimized network model are effective.

关键词： Fault diagnosis Solid modeling Accuracy Neural networks software algorithms Feature extraction Manipulators Data models Mathematical models software

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A Cross Strategy-Based Agent-Assisted Multi-Population Particle Swarm Optimization Algorithm

A Cross Strategy-Based Agent-Assisted Multi-Population Parti...

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2025 2nd International Conference on algorithms, software Engineering and Network Security (ASENS)

作者： Yuhan Wang Han Yu Jiahui Ma Nanping Li Lin Wang School of Cyber Science and Engineering Qufu Normal University Qufu China School of Computer Science Qufu Normal University Rizhao China School of Humanities and Law Tianjin University of Science and Technology China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

With the rapid increase in the complexity of modern engineering systems and scientific computing problems, Large-Scale Expensive Optimization Problems (LSEOPs) have become a core challenge in the field of optimization. Traditional Evolutionary algorithms (EAs) encounter the "curse of dimensionality" in high-dimensional scenarios, and most of the existing Surrogate-Assisted Evolutionary algorithms (SAEAs) are designed for low-dimensional problems and struggle to adapt to the characteristics of high-dimensional data. In this paper, a Cross Strategy-Based Agent-Assisted Multi-Population Particle Swarm Optimization algorithm (CS-AAMPSO) is proposed to improve the efficiency and robustness of methods for working out LSEOPs, and the experimental results show that the performance is improved to some extent.

关键词： Scientific computing High dimensional data software algorithms Network security Robustness Complexity theory Particle swarm optimization Optimization software engineering

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