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检索条件"主题词=software algorithms"

共 12564 条记录，以下是1411-1420 订阅

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RVVe: A Minimal RISC-V Vector Processor for Embedded AI Acceleration

RVVe: A Minimal RISC-V Vector Processor for Embedded AI Acce...

引用

IEEE International SOC Conference

作者： Patrick Schmidt Johannes Pfau Tim Hotfilter Matthias Stammler Tanja Harbaum Jürgen Becker Karlsruhe Institute of Technology Germany

ISBN: (数字)9798350377569

ISBN: (纸本)9798350377576

In recent years, Deep Neural Networks (DNNs) have become common in the embedded domain for a wide variety of tasks. However, due to strict area and energy requirements, dedicated accelerators for these networks are necessary. Different architectures to fulfill this role are available, but an accelerator targeting the ultra-low area design point is still missing. In this work, we present an architecture focusing on minimizing resource utilization and energy requirements. We propose a small-scale vector processor that can be integrated into a RISC-V core. Unlike traditional, feature-rich vector instruction sets, we instead determine the most crucial instructions for DNN workloads through hardware-software co-design. To evaluate our implementation, we integrate our vector extension into an open-source RISC-V System-on-Chip, the NeoRV32, and measure the hardware overhead and achieved acceleration of operations commonly found in neural networks. Our results show an acceleration of up to 11.9x on convolutional workloads over the baseline architecture, while we demonstrate that our implementation introduces significantly less hardware overhead than previous works. We provide our work open-source to use for further exploration of low area design of VPUs 1 . 1 https://***/itiv-kit/rvve

关键词： software algorithms Computer architecture Artificial neural networks Vectors Hardware System-on-chip Vector processors Resource management Logic Artificial intelligence

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Development of Network Analyzer Sharing System with Multi-User Access

Development of Network Analyzer Sharing System with Multi-Us...

引用

International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： SungTae Hwang Janghoon Jeong Jongsik Lim Jae-Bok Lee Dal Ahn Seong-Ho Son Department of ICT Convergence Soonchunhyang University Asan Republic of Korea Erangtec Hwaseong Republic of Korea

ISBN: (数字)9798350375817

ISBN: (纸本)9798350375824

We presented a network analyzer sharing system that allows multiple user to access a single vector network analyzer. The system consists of hardware that is switching module to extend two-port VNA into multiple ports and software that distributes measurement signals eight port. The hardware uses SP4T switches to simplify the system. The software uses an automatic channel switching time setting algorithm to prevent signal distortion or abnormal signals. To validate this system, we conducted an experiment measuring a device under test. Experimental results validate the measurement performance of the sharing system.

关键词： software algorithms Network analyzers Switches Insertion loss Hardware software Vectors Time measurement Distortion measurement software measurement

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Subjective Answer Grader using Semantic Similarity and Keyword Matching

Subjective Answer Grader using Semantic Similarity and Keywo...

引用

International Conference for Convergence of Technology (I2CT)

作者： Sanchit Kripalani Tejas Lipare Dipali Kadam Department of Computer Engineering Pune Institute of Computer Technology Pune India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

Subjective exams and tests have been a staple metric of student evaluation. These tests require students to give brief theoretical responses to the questions. Evaluation of subjective responses is based on the presence of certain facts, keywords, phrases that need to be mentioned. Traditional assessment of these tests requires an examiner to affirm the understanding of concepts by students through their answers. The human-dependant evaluation, however, is tedious, time consuming and is rarely impartial. The time constraints often mean that the examiner is unable to provide a detailed feedback to each and every student. This calls for the need to develop an objective automated grader system, which can investigate and analyze the student performances by considering different facets of learning based on semantic similarity. The enhanced BERT model, which has been fine-tuned, is utilized to capture the semantic characteristics found in the student’s response. In order to achieve this, the model compares the student’s response with the model answer and generates a model score based on the comparison. This model score is boosted through a keyword matching algorithm, which emphasizes the factual information contained within the student’s response. These final similarity scores are employed to offer comprehensive feedback that illuminates the specific areas in which the student’s comprehension may be lacking. Finally, the proposed approach is compared to other renowned algorithms like Cosine Similarity, Word Mover’s Distance, Paraphrase-mpnet, and Multi-qa-mpnet. The proposed system yields an experimental Mean Absolute Error (MAE) of 2.11, which is significantly better as compared to other algorithms.

关键词： Measurement Flowcharts software algorithms Semantics Taxonomy Prediction algorithms software

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Examining the Potential of Machine Learning in Reducing Prescription Drug Costs

Examining the Potential of Machine Learning in Reducing Pres...

引用

International Conference on Computing and Networking Technology (ICCNT)

作者： Sachin C. Patil Sairam Madasu Krishna J Rolla Ketan Gupta N. Yuvaraj Senior Software Engineer USA Senior Cloud Software Engineer Microsoft Charlotte North Carolina USA Department of Information Technology University of The Cumberlands Williamsburg KY USA Computer Science and Engineering Sri Shakthi Institute of Engineering and Technology Coimbatore Tamil Nadu India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The ability of the system to gain knowledge for lowering prescription drug prices has been increasingly studied in recent years. Gadget-gaining knowledge is a branch of synthetic intelligence that enables machines and PC systems to enhance their overall performance on specific obligations by means of mastering beyond facts. Within the context of prescription drug costs, gadget learning may be used to find patterns and developments in drug pricing and usage, decide disparities in getting admission to and usage, and have a look at pricing strategies hired by pharmaceutical businesses. The use of gadgets to gain knowledge can help to discover elements using prescription drug costs, inclusive of the pricing and utilization of individual capsules or the relationships among drug costs and effects. Moreover, AI-primarily based algorithms may be used to use massive datasets in an effort to apprehend the role that healthcare vendors, insurers, and pharmaceutical organizations have on prescription drug ***, AI-based total fashions can also be used to become aware of and degree cost elements associated with specific drug combinations. Sooner or later, machine studying may be leveraged to examine the effects of policy changes and healthcare reforms on prescription drug costs and to become aware of goal populations with high prescription drug prices. By combining gadget studying with conventional healthcare price analysis gear, researchers can gain insights into the drivers of prescription drug charges and make public coverage decisions. In sum, a device gaining knowledge can be a powerful tool.

关键词： Drugs Costs Accuracy Machine learning algorithms software algorithms Pricing Medical services Organizations Machine learning software

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Research and Application of Tablet Backplane Detection Algorithm Based on Machine Vision

Research and Application of Tablet Backplane Detection Algor...

引用

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

作者： Xin Huang Yuqiang Wang Yuezhong Li Xianen Zhou School of Mechanical and Electronic Engineering East China University of Technology Nanchang China Jiangxi Communication Terminal Industry Technology Research Institute Co. Ltd. Nanchang China

ISBN: (数字)9798350344721

ISBN: (纸本)9798350344738

The detection of tablet backplane accessories is one of the important links in whether the tablet computer can be qualified to enter the market. The traditional inspection link usually uses artificial visual inspection, which has problems such as low efficiency and error rate increasing with workers' working time. Therefore, this paper proposes a system based on machine vision and industrial control computer, which studies and applies the vision algorithms. The system acquires pictures by a specific camera, perform two extraction of template area center points on the tablet backplane on the pipeline and the affine transformation to get the accurate location. The film detection algorithm is used for the film in the system. The nut adopts the nut detection algorithm. Foam uses statistical methods based on describing textures. After verification in 300 samples provided by the factory, the results show that the average detection time is 49.37 milliseconds, and the accuracy rate is 97%.

关键词： Visualization Accuracy Statistical analysis Backplanes Machine vision software algorithms Tablet computers

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CAD-Based Workspace Analysis of a 6-DOF Foldable Parallel Manipulator with a Circular Rail (FoldRail Manipulator)

CAD-Based Workspace Analysis of a 6-DOF Foldable Parallel Ma...

引用

ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Sergey V. Kiselev Alexey S. Fomin Anton V. Antonov Mechanical Engineering Research Institute of the Russian Academy of Sciences (IMASH RAN) Moscow Russia

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

Nowadays, computer-aided design (CAD) finds many applications in the development and analysis of manipulators and robots. It accurately reflects the design features of the considered mechanical system, including the geometry and material of its links. This article applies CAD tools to analyze a workspace of a 6-DOF foldable parallel manipulator with a circular rail (FoldRail manipulator). The article proposes an algorithm to determine a translation (constant orientation) workspace of the manipulator using a geometrical method implemented in the SolidWorks software. The combination of this method and a CAD model of the manipulator allows considering all of its design features. The results are presented for the horizontal and tilted orientations of the output link.

关键词： Rails Geometry Solid modeling Design automation software algorithms Kinematics Manipulators

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Air Data Sensor Fault Detection and Diagnosis Using Robust Unscented Kalman Filter

Air Data Sensor Fault Detection and Diagnosis Using Robust U...

引用

Artificial Intelligence and Signal Processing (AISP), INDIA, International Conference on

作者： Anitha G Jayaram Murugan Saravanan Elanchezhian Dept. of Aerospace engineering Anna university MIT Campus Chennai india

ISBN: (数字)9798350350654

ISBN: (纸本)9798350350661

The air data system measures and provides vital information like an aircraft's speed, altitude, and other safety parameters essential for flight. Errors in such critical system components result in loss of control of the aircraft, leading to aircraft crashes. Thus, redundancy for this critical component is highly important. The proposed work introduces a new method for identifying problems with the air data sensor in an airplane. Current techniques involve a complicated voting system that requires multiple sensors to function properly. However, this new approach uses analytic redundancy to monitor the sensor's performance continuously, which is more desirable than relying on air data probe measurements. The method involves using a mathematical model that considers only the inertial measurement unit and navigation system data to estimate air data and detect faults in the sensors. The robust three-stage unscented Kalman filter is used to provide an accurate estimation. By comparing the estimated data with the physical measurements, the algorithm can track the performance of each sensor and identify any faults. The algorithm is tested in X-Plane software and validated using real-time data from a Cessna Citation II transport aircraft. A sensor stuck fault was introduced twice in the 60-second run time. The UKF outperformed the novel EKF in most of the cases and showed its robustness during various fault conditions with a 1–2 % deviation in RMSE values. The results obtained showed that the estimated data can be used as a replacement for a redundant sensor, reducing the complexity and cost of these sensors.

关键词： Accuracy software algorithms Redundancy Signal processing algorithms Signal processing Data systems Stability analysis software Kalman filters Aerospace control

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Research on Multimodal Optimization Mechanism based on Machine Learning

Research on Multimodal Optimization Mechanism based on Machi...

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Cloud Computing, Big Data Applications and software Engineering (CBASE), International Conference on

作者： Qianyu Chen Runxuan Tang School of Information Science and Technology ShanghaiTech University Shanghai China School of Information Science and Technology Shanghai Normal University Shanghai China

ISBN: (数字)9798331506582

ISBN: (纸本)9798331506599

As modern engineering optimisation problems become increasingly complex, a significant number of them exhibit multimodal characteristics. This implies that there are multiple local optimal solutions and a single global optimal solution. This not only increases the difficulty of problem-solving, but also necessitates the development of more sophisticated algorithms for optimisation. In this work, by constructing intelligent agents to continuously optimize their behavior strategies in the search process of multimodal optimization problems, they use environmental feedback to continuously optimize their behavior strategies, and at the same time simulate the process of natural selection and genetic variation to generate multiple candidate solutions, so as to conduct extensive searches on a global scale. Deep neural networks are used to build policy networks and value networks for reinforcement learning agents, enabling agents to accurately predict the potential benefits of different search strategies through a large amount of training data. Through real-time monitoring and analysis of feedback information, the model dynamically adjusts the search strategy to balance exploration and utilization, avoid falling into the local optimal solution, and finally find the global optimal solution. Experimental analysis shows that the model performs well in dealing with complex multimodal optimization problems, and significantly improves the efficiency and effect of solving.

关键词： Analytical models software algorithms Training data Reinforcement learning Search problems Robustness Real-time systems Problem-solving Optimization software engineering

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Pioneering Testing and Assessment Framework For AI-Powered SAR ATR Systems

Pioneering Testing and Assessment Framework For AI-Powered S...

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International Conference on Big Data and Artificial Intelligence (BDAI)

作者： Qiang Zhang Jiandong Bai Xin Chang Beijing Institute of Tracking and Communication Technology Beijing China

ISBN: (数字)9798350352009

ISBN: (纸本)9798350352016

Recent advancements in machine learning and deep learning techniques have significantly enhanced the performance of Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR). However, the inherent opacity and uncertainty of AI pose challenges, as there is a lack of systematic testing and standardized metrics for evaluating AI-based SAR ATR systems. It hinders the application of SAR ATR system in safety-critical domains. In this paper, we present testing and assessment framework for AI-based SAR ATR system inspired recent developed AI-system testing and standard. We further present the level-1 and level 2 metrics to assess the SAR-ATR systems. It does not involve that algorithm recognition performance but the whole software system quality in the perspective of software engineering. Throughout testing and assessment for the whole system, it fosters application of the AI-based SAR ATR system in practice.

关键词： Measurement Systematics Uncertainty Target recognition software algorithms software systems Synthetic aperture radar Standards Testing software engineering

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Driver fatigue detection based on multi-feature fusion facial features

Driver fatigue detection based on multi-feature fusion facia...

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Big Data & Artificial Intelligence & software Engineering (ICBASE), International Conference on

作者： Run Yuan Haonan Long Hunan Automotive Engineering Vocational University Zhuzhou Hunan China

ISBN: (数字)9798331506612

ISBN: (纸本)9798331506629

Fatigue driving is the main factor causing traffic accidents. To reduce the traffic risk, we explores a driver fatigue detection method based on OpenCV combined with PHOG algorithm. By extracting facial feature points from the eyes and mouth of drivers, this study employs an adaptive eyelid closure threshold for the eyes and a feature correction algorithm based on Euler angles. This approach enables real-time computation of fatigue indicators such as PERCLOS, blink frequency, and yawn frequency. By weighting and fusing these characteristic indicators, a fatigue score for the driver is derived. Based on predefined thresholds, the driver’s fatigue level is assessed, and corresponding warning messages are issued. Experimental results demonstrate the effectiveness of the proposed method in identifying driver fatigue, providing a reliable auxiliary tool for enhancing driving safety.

关键词： Face recognition software algorithms Mouth Fatigue Feature extraction Stability analysis Safety Reliability Facial features software engineering

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