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Research on Graphic 3D Modeling Technology Based on Neural Network in intelligent Construction System

Research on Graphic 3D Modeling Technology Based on Neural N...

引用

Electronics, Energy systems and Power Engineering (EESPE), ieee international conference on

作者： Jiwen Zhang Changchun University of Architecture and Civil Engineering Changchun China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

This paper mainly discusses the innovative application of neural network in 3D graphic modeling and designs an efficient 3D modeling algorithm. The algorithm takes deep learning as the core and realizes high-precision modeling of building structures by extracting multi-level features of graphic data. CNN is used to process multi-dimensional images to generate 3D models with rich details, which greatly improves the modeling efficiency and accuracy. In addition, this paper introduces the simulation technology of the model in the intelligent construction system, and verifies the stability and robustness of the algorithm through experiments under different parameters. The experimental results show that the proposed modeling algorithm achieves higher accuracy than traditional algorithms in complex structure recognition and saves nearly $\mathbf{3 0 \%}$ in computing time. data analysis further confirms the adaptability and effectiveness of the neural network model in complex building environments, and provides data support and algorithm basis for in-depth research on future intelligent construction systems.

关键词： Graphics Solid modeling Three-dimensional displays Accuracy Computational modeling Buildings Neural networks Feature extraction data models Stability analysis

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Design and Performance Research of Multi Channel acquisition Module

Design and Performance Research of Multi Channel Acquisition...

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Power Electronics, Computer Applications (ICPECA), ieee international conference on

作者： Xiqiang Jin Wei Wang Nantian Ruan Aijun Zhao Yalong He Hangzhou Applied Acoustics Research Institute Hangzhou China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

With the rapid development of signal acquisition technology, the requirements for signal acquisition resolution, sampling rate, and data processing speed are increasing in applications such as radar signals, communication, and intelligent transportation. Therefore, it is urgent to solve how to improve the sampling rate and resolution to meet the current demand for high precision and high sampling rate. This article uses multiple dual channel A/D sampling chips (with a sampling rate of 100MSPS and a resolution of 16 bits), implements synchronous sampling and data transmission based on FPGA, and completes functional and performance verification. The data collected by FPGA can be sent to the processor or upper computer for further data processing and storage through standard network protocols and SRIO protocols. Through practical application in signal processing systems, it has been verified that the multi-channel acquisition module has advantages such as universality and flexible scalability, and has certain application value in engineering applications.

关键词： Protocols Scalability Transportation Signal processing algorithms data processing Radar signal processing Reliability Signal resolution Field programmable gate arrays Standards

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Research on intelligent Recommendation Algorithm Model for Vocational Talent Training

Research on Intelligent Recommendation Algorithm Model for V...

引用

Electronics, Energy systems and Power Engineering (EESPE), ieee international conference on

作者： Yinghong Li Lanzhou University of Resources and Environment Lanzhou Gansu China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

This paper proposes a vocational talent training model based on intelligent recommendation algorithm. By integrating the personal characteristics, interests, hobbies, career potential and other data of students, intelligent recommendation technology is used to provide students with personalized course recommendations, career path planning and job matching. advanced algorithms such as collaborative filtering, deep learning and reinforcement learning are used in the study to construct a recommendation model that adapts to the needs of different students. The experimental results show that the vocational talent training system based on intelligent recommendation has significant improvements in recommendation accuracy, student satisfaction and course matching efficiency. The accuracy of course recommendations has increased by 18%, the student satisfaction with personalized recommendations has increased by 25%, and the accuracy of the system's career path planning has reached more than 90%. Through in-depth analysis of experimental data, this paper verifies the application value of intelligent recommendation technology in vocational talent training, and proves its advantages in improving educational effects, optimizing student training paths and enhancing career matching.

关键词： Training Deep learning Career development Adaptation models Accuracy Engineering profession Collaborative filtering Reinforcement learning Path planning Recommender systems

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intelligent data-driven methods for enhancing distributed excitation control in electrical grid

Intelligent data-driven methods for enhancing distributed ex...

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international conference on Energy, Power, Environment, Control and computing (ICEPECC 2025)

作者： Hafiz Ghulam Murtza Qamar Muhammad Imran Fareed Ahmad Ayesha Riaz Adil Ashraf Muhammad Zain Yousaf Imran Khan School of Electrical Engineering Yanshan University Qinhuangdao 066004 People's Republic of China Department of Electrical Electronics and Computer Systems University of Sargodha People's Republic of China Center for Renewable Energy and Microgrids Huanjiang Laboratory Zhejiang University Zhuji Zhejiang 311816 People's Republic of China

ISBN: (数字)9781837243150

This paper proposes a decentralized excitation control method based on synchronized estimation using asynchronous measurements from voltage/current transformers (VT/CT), addressing the challenges of decentralized excitation control caused by asynchronous updates. Due to the high cost and limited use of Phasor Measurement Units (PMUs), synchronized generator output measurements are often not feasible. The proposed method establishes a framework for decentralized excitation control that aligns with synchronized estimation in multi-machine power systems. It develops an estimation model for synchronized acquisition of excitation control feedback inputs, even under asynchronous sampling conditions. Simulation results using ieee standard test systems demonstrate that synchronized estimated values offer a more accurate representation of the system’s status compared to asynchronous measurements, with better compatibility with the network structure. The findings show that decentralized excitation control based on synchronized estimation significantly enhances power system stability compared to traditional control methods that rely on asynchronous feedback.

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CogniGuardianRoadscape: Advancing Safety through AI-Driven Roadway Audits

CogniGuardianRoadscape: Advancing Safety through AI-Driven R...

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2025 international conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility, ADMMS 2025

作者： Thangaraju, Shanmuganathan Nagarajan, Meenakshi Ganesan, Maragatham Raja, Selvakumar Sirotiya, Aviral Jasrotia, Bhargav Hindustan Institute of Technology & Science India SRM Institute of Science and Technology India

The escalation of road infrastructure anomalies, such as speed breakers and potholes, presents a formidable challenge to vehicular safety, efficient traffic management, and road maintenance strategies worldwide. In addressing these pervasive issues, this paper proposes an advanced, integrated approach for the detection and classification of speed breakers and potholes. Utilizing a sophisticated blend of deep learning methodologies and enhanced image processing techniques, our solution leverages Object Detection to analyze and interpret real-time visual data captured through advanced vehicle-mounted camera systems. This research meticulously details the comprehensive process involved in the development of this system, including the acquisition and preprocessing of a vast, varied dataset representative of numerous road types, conditions, and environmental factors. Through rigorous training, testing, and validation phases, the model demonstrates remarkable proficiency in recognizing and classifying road imperfections, outperforming existing models in accuracy, precision, recall, and F1 score metrics. The innovative approach underscores the potential of integrating cutting-edge machine learning algorithms with real-world applications to significantly enhance autonomous navigation systems and assist in the proactive maintenance of road infrastructure. Furthermore, the paper discusses the model's scalability and adaptability, emphasizing its potential application across a wide range of environments, weather conditions, and vehicular technologies. By providing a detailed analysis of the system's performance under varied operational scenarios, this research contributes valuable insights into the realm of intelligent transportation systems and smart city infrastructure development, the findings of this study not only pave the way for future advancements in autonomous vehicle technologies but also offer promising perspectives for the improvement of road maintenance and safety

关键词： advanced traffic management systems

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Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space

Safe Reinforcement Learning for Social Motor Coordination in...

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26th international conference on Industrial Technology, ICIT 2025

作者： Yang, Fan Huang, Yuening Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing HoustonTX United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (纸本)9798331521950

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints. © 2025 ieee.

关键词： Reinforcement learning

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Evaluating the Enhancement of Cognitive Skills and acquisition of New Skills in an Environment of Different Video Game Genres 5th

Evaluating the Enhancement of Cognitive Skills and Acquisiti...

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5th international conference on Advances in Information Communication Technology and computing, AICTC 2024

作者： Uzdenbayev, Zhanbay Kenzhe, Damir Mirambekov, Suienish Makatov, Arstan Omirgaliyev, Ruslan Department of Information and Communication Technologies Zhetysu University named after I. Zhansugurov Higher School of Technical Sciences Zhansugurov St. 187a Taldykorgan040000 Kazakhstan Department of Computer Engineering Astana IT University Mangilik El Avenue 55/11 Business Center EXPO Block C1 Astana010000 Kazakhstan Department of Intelligent Systems and Cybersecurity Astana IT University Mangilik El Avenue 55/11 Business Center EXPO Block C1 Astana010000 Kazakhstan

ISBN: (纸本)9789819761050

Video games, once perceived solely as a form of entertainment, have evolved into multifaceted tools that intersect with various aspects of daily life, including education. As digital technologies advance, the potential of video games in cognitive development and learning processes has become a focal point of research. This study investigates the influence of various video game genres on the enhancement of cognitive skills. Focusing on investigation of multiple genres, including action, puzzle, and strategy games, the research examines how exposure to these genres affects memory retention, problem-solving, strategic planning, and other cognitive abilities. Employing a mixed-methods approach, the study combines quantitative data from performance tests with qualitative insights from participant feedback. The findings reveal the possibility of different game genres uniquely contributing to cognitive skill development, with each genre enhancing specific abilities. These results suggest the potential of video games as educational tools and pave the way for future research in this domain. The study advocates for a tailored approach to using video games in education, where specific genres are utilized to target particular cognitive skills. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cognitive processes Games Genres Higher-order cognitive skills (HOCS) Lower-order cognitive skills (LOCS) Problem-solving skills

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Motion Planning in Automated Vehicles Based on Hierarchical MPC 1

Motion Planning in Automated Vehicles Based on Hierarchical ...

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1st international conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kapila, Pooja Kumar, Pankaj Negi, Rahul Bharti, Bhupender Kumar Punhani, Akash Bisht, Suraj Singh IIMT College of Engineering Department of Artifical Intelligence & Data Science India Amity University Department of Statistics Kolkata India Tula's Institute Department of ECE Dehradun248197 India Department of Mechanical Engineering VMSB UTU Campus Pithoragarh India KIET Group of Institutions Department of Computer Science Noida India Bipin Tripathi Kumaon Institute of Technology Department of ECE Dwarahat Almora India

ISBN: (纸本)9798331518578

In this study, a thorough hierarchical control structure that supports autonomous decision-making that arises in autonomous systems and robots is proposed. Distinct state and decision/control sets are frequently used to describe high-level decision making in a conventional hierarchical control architecture. To keep up with proficiency, wellbeing, and solace, robotized vehicles generally depend serious areas of strength for on powerful movement arranging calculations. The capacity of Model Prescient Control (MPC) to oversee imperatives and upgrade directions progressively has made it a strong system for movement arranging. To approve the proposed strategy, this exploration utilizes MATLAB recreations to look at various levelled MPC for movement arranging in robotized vehicles. With the low-level regulator guaranteeing exact direction observing and the undeniable level organizer computing a worldwide direction, a two-layer progressive MPC structure is fabricated. The discoveries show how well the progressive MPC handles street ebb and flow, dynamic hindrances, and continuous computational impediments. It is demonstrated that the suggested autonomous decision-making scheme's recursive practicality and stability are ensured by carefully crafting its essential components. An intelligent vehicle's autonomous lane-changing system is developed using the suggested framework. Simulation demonstrates that it has a potential capacity to manage a variety of behaviours in complex and dynamic contexts. It is anticipated that the suggested framework will be useful for autonomous decision-making in a variety of robotics along with autonomous technologies where safety as well as optimality are important factors. © 2025 ieee.

关键词： Motion planning

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Concept and Considerations for the Development of an Information database for Efficient international Freight Transport

Concept and Considerations for the Development of an Informa...

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international conference on Computational Cybernetics (ICCC)

作者： Petra Opitz Tamás Haidegger Enikö Nagy John von Neumann Faculty of Informatics Óbuda University Budapest Hungary University Research and Innovation Center (EKIK) Óbuda University Budapest Hungary School of Computing Queen's University Kingston ON John von Neumann Faculty of Informatics Óbuda University Antal Bejczy Center for Intelligent Robotics Budapest Hungary

ISBN: (数字)9798331502461

ISBN: (纸本)9798331502478

international freight transport is a growing market and a crucial component of the global economy, enabling the seamless flow of goods across regions and supporting global trade. However, the industry faces significant challenges, particularly in road transport orchestration, due to the increasing complexity of operations and the demand for real-time decision-making. This study sketched the algorithmic and programming framework to address these challenges by presenting an optimized database architecture designed to improve decision support systems for freight transport. The proposed system architecture may leverage the flexibility and scalability of NoSQL databases to manage large, semi-structured datasets in the future, while REST APIs enable seamless integration and real-time data manipulation. To enhance usability and transparency, the system incorporates advanced data visualization tools, allowing stakeholders to derive actionable insights and improve operational efficiency. By focusing on areas such as real-time tracking, sustainability, and process optimization, this work not only addresses current operational needs but also provides a robust foundation for future developments, including advanced analytics and mobile application integration. This contribution supports the logistics industry's shift toward more adaptive, efficient, and sustainable transport solutions.

关键词： Industries NoSQL databases data visualization systems architecture Real-time systems Visual databases Usability Sustainable development Optimization Logistics

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Dear participants of the 9th international conference “intelligent data acquisition and advanced computing systems”!

Dear participants of the 9th International conference “Inte...

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ieee international Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

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