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检索条件"主题词=software algorithms"

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Design of English Speaking Exam System Based on Particle Swarm Optimization Algorithm

Design of English Speaking Exam System Based on Particle Swa...

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software Engineering, Social Network Analysis and Intelligent Computing (SSAIC), Asia-Pacific Conference on

作者： Yanyan Xu Chunfu Liu Heilongjiang University of Technology Jixi Heilongjiang China

ISBN: (数字)9798350393682

ISBN: (纸本)9798350393699

The English oral exam is an important component of language learning, but the traditional exam mode uses face-to-face exams between teachers and students. This oral exam mode has strong subjectivity for examiners, and their oral proficiency, pronunciation, and other factors directly affect the performance of candidates. Although there are videos of the entire exam sent to the exam center, the exam center can only conduct sampling inspections at most, resulting in unfair grading. In this regard, this article designs an English speaking exam system based on PSO (Particle Swarm Optimization), which can achieve online registration and login authentication for candidates. Online exams use computers to extract test questions from the established question bank according to the paper formation algorithm, and form test papers that meet the requirements. It is an effective means to achieve standardized and scientific examination. Implement online testing of different types of English knowledge, allowing users to analyze and count their test scores. And through experimental testing, the experimental results show that PSO has reached a convergence value of 682 when the number of iterations is 1150, while the GA (Genetic Algorithm) algorithm needs 2100 iterations to reach the optimal value. It can be seen that the algorithm proposed in this article is more suitable for English oral testing.

关键词： Heuristic algorithms Stability criteria software algorithms Cryptography Particle swarm optimization Standards Testing

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Research on Multivariable Coordinated Predictive Control Algorithm Based on Air Conditioning Controller

Research on Multivariable Coordinated Predictive Control Alg...

引用

Data Science and Computer Application (ICDSCA), IEEE International Conference on

作者： Yong Xu Manping Qin Choon Kit Chan School of Artificial Intelligence and Smart Manufacturing Hechi University Hechi China Faculty of Engineering and Quantity Surveying INTI International University Nilai Negeri Sembilan Malaysia

ISBN: (数字)9798350368239

ISBN: (纸本)9798350368246

In view of the significant hysteresis, nonlinearity, and time-varying characteristics of traditional air-conditioning systems, intelligent air-conditioning systems are evolving towards enhanced controllability, multifunctionality, and reduced power consumption. This paper proposes a multivariable coordinated predictive control algorithm applied to air-conditioning controller systems. The algorithm's principles are analyzed by examining input variables and set temperatures, such as temperature, humidity, electrical parameters of air conditioning operation, flammable gas concentration in the environment, ionic smoke detection status, and personnel mobility. Output variables such as humidity and its deviation are also analyzed, and the design steps of the multivariable coordinated predictive control algorithm applied to the PC server software of the air-conditioning system are presented. Finally, a comparative test of temperature and humidity control was conducted on a single Midea air conditioner. The results indicate that the multivariable coordinated predictive control algorithm is well-suited for air-conditioning control systems, particularly in the most economical temperature control mode. Compared to the system's performance before the algorithm's implementation, the control is optimized, resulting in a 19.4% energy saving.

关键词： Air conditioning Temperature System performance software algorithms Humidity Prediction algorithms software Temperature control Servers Predictive control

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Efficient Arm Motion Planning with Reduced Viapoints for Mars Rover Operations

Efficient Arm Motion Planning with Reduced Viapoints for Mar...

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Space Robotics (iSpaRo), International Conference on

作者： Justin Huang Valen Yamamoto Ana Warner Jet Propulsion Laboratory California Institute of Technology Pasadena CA Department of Electrical Engineering and Computer Science UC Irvine Irvine CA Department of Robotics University of Michigan Ann Arbor MI

ISBN: (数字)9798350367232

ISBN: (纸本)9798350367249

This paper describes additions and enhancements we made to the standard RRT-Connect motion planning algorithm to suit the unique needs of operating the robotic arm on the Perseverance Mars Rover. One constraint we have is to maintain a minimum distance between the terrain and any part of the arm hardware. Another goal specific to rover planning is to minimize the number of viapoints in our motion plans. These algorithms should also run efficiently so that rover planners can generate arm motion sequences in time for uplink windows. We applied the RRT-Connect algorithm to the rover’s robotic arm and tested its performance, and we found that it could be used successfully for rover planning with a few changes. First, we implemented the terrain clearance requirement using a software tool called Proximeter. Second, we simplify the paths computed by RRT-Connect to minimize the number of viapoints in a motion plan. Third, we leverage Proximeter to reduce the number of expensive terrain collision checks done by the algorithm, speeding up motion planning.

关键词： Space vehicles Mars Costs software algorithms Manipulators Hardware Planning

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Analysis and Evaluation of an Off-Grid Mini-Grid PV System for Rural Electrification

Analysis and Evaluation of an Off-Grid Mini-Grid PV System f...

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Advanced Power Engineering and Energy (APEE), IEEE International Conference on

作者： Nnaemeka Genesis Ajah Chibuike Nicholas Ugwu Candidus Eya Ikenna Onyegbadue Emenike Chinedozi Ejiogu Chimaobi Ikenna Ndukwu Department of Electrical Engineering Africa Centre of Excellence in Sustainable Power and Energy Development (ACE-SPED) University of Nigeria Nsukka Enugu Nigeria Department of Electrical Engineering University of Nigeria Nsukka Enugu Nigeria Department of Electrical and Computer Engineering Igbinedion University Okada Edo Nigeria

ISBN: (数字)9798350360936

ISBN: (纸本)9798350360943

In recent years, there has been a growing interest in using renewable energy sources to electrify rural areas in Nigeria. The major motivation for this study is the recognition of the huge potential of renewable energy to improve rural electricity access in the country. One promising option is to use off-grid photovoltaic (PV) mini grid systems. These systems are small, modular, and can be easily installed in remote areas. However, some studies have shown that these systems are posed with certain problems such as its inability to carry loads for prolonged periods of time when the sun is out. This work investigates the feasibility of an optimized off-grid PV mini grid system for electrification of rural areas in Nigeria. The paper made use of the HOMER pro, SAM and MATLAB software. The HOMER pro software was to design a proposed mini grid for a case community in the northern part of Nigeria. The results of the HOMER pro simulations showed that the system generated high NPC and low LCOE. The proposed system for the northern generated an NPC of $\mathrm{N}\!\!\!\!\!\!{=}$ 380,498,512 and an LCOE of 37.01 $\mathrm{N}\!\!\!\!\!\!{=}$ /kWh. The results of the SAM software showed that the PV array of the proposed models was able to generate sufficient electricity for the community. The results of the MATLAB software showed that a short-term load forecasting carried out using the ANN Levenburg-Marquardt algorithm gave results more accurately for the short-term load demand of the community. This exchange rate at the time of this work was $\mathrm{N}\!\!\!\!\!\!{=}$ 769.5 to $1.

关键词： Renewable energy sources Costs Electricity software algorithms Electrification software MATLAB Sun Standards Power engineering and energy

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Inversion Design of Ultraviolet Achromatic Metalenses Based on Particle Swarm Optimization Algorithm

Inversion Design of Ultraviolet Achromatic Metalenses Based ...

引用

Electronics and Devices, Computational Science (ICEDCS), International Conference on

作者： Xiaojun Ding Xueyuan Zhong Jiluan Academy Nanchang University Nanchang China

ISBN: (数字)9798331527624

ISBN: (纸本)9798331527631

This paper employs a heuristic algorithm, specifically the Particle Swarm Optimization (PSO), to perform inverse design of metalenses in the ultraviolet spectrum, achieving chromatic aberration correction over a broad wavelength range of 300-400 nm. Initially, the study focuses on the construction of silicon nitride (Si 3 N 4 ) nano-pillars on a silicon nitride substrate. Numerical simulation software is utilized to scan the length and width of these nano-pillars, thereby establishing a phase database. Subsequently, the PSO is applied to identify the optimal meta-atoms within the phase database that meet the phase requirements for a wide wavelength range. Finally, the metalens is constructed, and numerical simulation is used to realize an achromatic metalens in the 300-400 nm wavelength band. This work provides a methodological approach for the inverse design of achromatic metalenses in the ultraviolet spectrum.

关键词： Databases Scientific computing Heuristic algorithms software algorithms Silicon nitride Numerical simulation software Particle swarm optimization Substrates

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Comparative performance indexs for fractional-order PID controller use of whale optimization algorithm applied to speed DC motor

Comparative performance indexs for fractional-order PID cont...

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Electrical Engineering and Automatic Control (ICEEAC), International Conference on

作者： Sofia Mansouri Bachir Bourouba Department of Electrical Engineering Automatic Laboratory of Setif Setif-1 University Algéria

ISBN: (数字)9798350349740

ISBN: (纸本)9798350349757

This paper a compare studying some of renowned performance indices improvement. The objective of this comparison is to identify the best objective function for optimizing the controller parameters using a new métha_heureustic method. Optimization was conducted to enhance the performance of fractional PID controllers. In this paper, the (WOA) technique is employed to adjust the parameters of fractional PID controllers. Numerical simulations results with Matlab software are given to selected the good objective function for this class of controller.

关键词： Electrical engineering software algorithms Linear programming Numerical simulation Whale optimization algorithms software Performance analysis

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Privacy Preserving Federated Learning for Advanced Scientific Ecosystems

Privacy Preserving Federated Learning for Advanced Scientifi...

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IEEE International Conference on Big Data

作者： Rick Archibald Addi Malviya Thakur Marshall McDonnell Gregory Cage Cody Stiner Lance Drane Paul Laiu Michael J. Brim Mathieu Doucet William T. Heller Ryan Coffee Computing and Computational Sciences Directorate Neutron Sciences Directorate Oak Ridge National Laboratory Oak Ridge TN SLAC National Accelerator Laboratory Menlo Park CA

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

We present a framework to provide privacy preserving (PP) federating learning (FL) across multiple computational and experimental facilities. This work joins the compute capabilities of National Energy Research Scientific Computing Center (NERSC) and Oak Ridge National Laboratory Research Cloud (ORC) with simulated experimental data, such as those produced at the SLAC National Accelerator Laboratory and Spallation Neutron Source (SNS). We describe the software infrastructure developed to provide privacy for computational and experimental networks. We developed algorithmic privacy across the federated system by embedding database security, computation, and communication into the federation architecture, utilizing scientific tools developed by the experimental community.

关键词： Privacy Federated learning Scientific computing Ecosystems software algorithms Distributed databases software Security Synthetic aperture sonar Sustainable development

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SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems

SwiftRL: Towards Efficient Reinforcement Learning on Real Pr...

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IEEE International Symposium on Performance Analysis of Systems and software

作者： Kailash Gogineni Sai Santosh Dayapule Juan Gómez-Luna Karthikeya Gogineni Peng Wei Tian Lan Mohammad Sadrosadati Onur Mutlu Guru Venkataramani George Washington University USA ETH Zürich Switzerland Independent

ISBN: (数字)9798350376388

ISBN: (纸本)9798350376395

Reinforcement Learning (RL) is the process by which an agent learns optimal behavior through interactions with experience datasets, all of which aim to maximize the reward signal. RL algorithms often face performance challenges in real-world applications, especially when training with extensive and diverse datasets. For instance, applications like autonomous vehicles include sensory data, dy-namic traffic information (including movements of other vehicles and pedestrians), critical risk assessments, and varied agent actions. Consequently, RL training is significantly memory-bound due to sampling large experience datasets that may not fit entirely into the hardware caches and frequent data transfers needed between memory and the computation units (e.g., CPU, GPU), especially during batch updates. This bottleneck results in significant execution latencies and impacts the overall training time. To alleviate such is-sues, recently proposed memory-centric computing paradigms, like Processing-In-Memory (PIM), can address memory latency-related bottlenecks by performing the computations inside the memory devices. In this paper, we present SwiftRL, which explores the potential of real-world PIM architectures to accelerate popular RL workloads and their training phases. We adapt RL algorithms, namely Tab-ular Q-learning and SARSA, on UPMEM PIM systems and first observe their performance using two different environments and three sampling strategies. We then implement performance opti-mization strategies during RL adaptation to PIM by approximating the Q-value update function (which avoids high performance costs due to runtime instruction emulation used by runtime libraries) and incorporating certain PIM-specific routines specifically needed by the underlying algorithms. Moreover, we develop and assess a multi-agent version of Q-learning optimized for hardware and illustrate how PIM can be leveraged for algorithmic scaling with multiple agents. We experimentally evaluate RL w

关键词： Training Performance evaluation Silver Q-learning software algorithms Graphics processing units Computer architecture

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Sub-THz Communications Beyond 6G: Experimental Platform for Testing Beam Realignment algorithms

Sub-THz Communications Beyond 6G: Experimental Platform for ...

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IEEE Conference on Vehicular Technology (VTC)

作者： Sergey Petrushkevich Vitaly Petrov Josep M. Jornet Institute for the Wireless Internet of Things Northeastern University Boston MA USA Division of Communication Systems KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

The increasing demand for ultra-high data rates in wireless communications has attracted interest in upper-frequency bands, namely sub-terahertz and terahertz frequencies. However, severe path loss and narrow beamwidth antennas used at these frequencies necessitate precise antenna alignment and realignment algorithms. Existing solutions often rely on constrained simulations or out-of-band techniques that may not capture the unique propagation characteristics of terahertz frequencies. To address this challenge, we introduce THzAlign, an integrated sub-terahertz and terahertz platform that enables rapid prototyping and real-world testing of antenna alignment algorithms. THzAlign combines rotary tables for precise beam steering with a modular software architecture supporting algorithm simulation and over-the-air experiments. To illustrate this platform, we evaluate three reference realignment algorithms in terms of their performance using THzAlign under varying distances, frequencies, and antenna beamwidth conditions. The developed platform with its documented API facilitates real-world hardware validation of forthcoming advanced solutions for beam (re-)alignment as an integral part of intelligent ultra-high-rate communication systems in the (sub-)THz bands toward 6G and beyond.

关键词： 6G mobile communication Vehicular and wireless technologies Beam steering Wireless networks software algorithms Hardware software measurement Antennas Testing Terahertz communications

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A Diffusion Model Augmented Indoor Robot Local Navigation Planner Based On Decision Transformer

A Diffusion Model Augmented Indoor Robot Local Navigation Pl...

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software Engineering and Artificial Intelligence (SEAI), IEEE International Conference on

作者： Yangfan Wu Junzhi Li Jianmin Ji School of Computer Science and Technology University of Science and Technology of China Anhui China

ISBN: (数字)9798350374346

ISBN: (纸本)9798350374353

As the demand for indoor service robots grows, reliable local navigation techniques are crucial for their applications. Due to the speed limitations of interacting with the physical world, training robot navigation policies from pre-gathered of-fline datasets is becoming increasingly popular. However, training local navigation policies on offline datasets is not easy and faces two main challenges: (1) Myopia: Common assumptions based on Markov Decision Processes and limited local observations impose higher demands on navigation policies, making decision-making difficult for planners in complex scenarios. (2) Distribution Shift: Limited offline datasets only cover a portion of the state-action space, resulting in learned policies differing from behavioral policies and performing poorly in real world scenarios, while common non-generative data augmentation methods are not suitable for navigation scenarios. Therefore, we introduce a global information guided- diffusion model augmented local planner based on decision transformer. Our approach combines offline reinforcement learning and sequence modeling to train a local navigation algorithm, while a diffusion model guided by global information generates trajectories similar to the distribution of offline datasets but with different global paths, further improving navigation policies with synthetic data. Results in simulator demonstrate that this approach effectively improves the performance of various imitation learning algorithms on offline datasets and has good modeling capabilities for trajectories in multiple scenarios. Real-world tests also show that the algorithm can plan smooth, safe paths in complex scenarios, demonstrating excellent obstacle avoidance capabilities.

关键词： Training Navigation Service robots software algorithms Transformers Diffusion models Trajectory

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