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3rd International Conference on Energy and Power Engineering, Control Engineering (EPECE)

作者： Zhou, Ning Jiang, Jianman Anhui Vocat & Tech Coll Sch Automot Engn Hefei 230011 Anhui Peoples R China

ISBN: (纸本)9798350366105;9798350366099

Against the backdrop of the gradual popularization of new energy vehicles, it is particularly important to improve the safety and comfort of driving new energy vehicles. As the market share of new energy vehicles gradually increases, improving the driving safety and comfort of new energy vehicles has become an urgent problem to be solved. This article helps improve the intelligent driving assistance system of new energy vehicles by combining intelligent algorithms and computer vision technology. This article realizes real-time detection and identification of vehicles, pedestrians and obstacles in road scenes by using target detection algorithms, then uses image segmentation technology to separate different areas in the road image, such as lane lines and pedestrian areas, and uses motion estimation algorithms to track and predict moving objects on the road to improve the performance of the new energy vehicles' driving assistance system. Experimental results show that the stability test results of this system are between 89% and 98%, and significant progress has been made in road environment perception and driving decision-making.

关键词： intelligent Driving Assistance New Energy Vehicles intelligent algorithms Computer Vision

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Novel mobility platforms utilizing intelligent algorithms

Novel mobility platforms utilizing intelligent algorithms

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Conference on Unmanned Ground Vehicle Technology VI

作者： Trentini, M Beckman, B Digney, B Collier, J Def R&D Canada Suffield Medicine Hat AB Canada

ISBN: (纸本)0819453455

The mobility requirement for Unmanned Ground Vehicles (UGVs) is expected to increase significantly as the number of conflicts shift from open terrain operations to the increased complexity of urban settings. In preparation for this role Defence R&D Canada - Suffield is exploring novel mobility platforms utilizing intelligent mobility algorithms that will each contribute to improved UGV mobility. The design of a mobility platform significantly influences its ability to maneuver in the world. Highly configurable and mobile platforms are typically best suited for unstructured terrain. intelligent mobility algorithms seek to exploit the inherent dexterity of the platform and available world representation of the environment to allow the vehicle to engage extremely irregular and cluttered environments. As a result, the capabilities of vehicles designed with novel platforms utilizing intelligent mobility algorithms will outperform larger vehicles without these capabilities. However, there exist many challenges in the development of UGV systems to satisfy the increased mobility requirement for future military operations. This paper discusses a research methodology proposed to overcome these challenges, which primarily involves the definition and development of novel mobility platforms for intelligent mobility research. It addresses intelligent mobility algorithms and the incorporation of world representation and perception research in the creation of necessary synergistic systems. In addition, it presents an overview of the novel mobility platforms and research activities at Defence R&D Canada - Suffield aimed at advancing UGV mobility capabilities in difficult and relevant military environments.

关键词： unmanned ground vehicles mobility control novel platforms intelligent algorithms

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Exploring the negative impacts of artificial intelligence in government: the dark side of intelligent algorithms and cognitive machines

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INTERNATIONAL REVIEW OF ADMINISTRATIVE SCIENCES 2024年第2期90卷 353-368页

作者： Valle-Cruz, David Garcia-Contreras, Rigoberto Gil-Garcia, J. Ramon Univ Autonoma Estado Mexico Unidad Acad Profes Tianguistenco Mexico City Mexico Univ Nacl Autonoma Mexico Escuela Nacl Estudios Super Unidad Leon Mexico City Mexico SUNY Albany Rockefeller Coll Publ Affairs & Policy Albany NY USA SUNY Albany Ctr Technol Govt Albany NY USA Univ las Amer Puebla Business Sch Cholula Mexico Univ Autonoma Estado Mexico Unidad Academ Profes Tianguistenco Paraje el Tejocote San Pedro Tlaltizapan Santiago Tianguistenco 52640 Mexico

This research proposes a framework for the negative impacts of artificial intelligence (AI) in government by classifying 14 topics of its dark side into five socio technical categories. The framework is based on a systematic literature review and highlights that the dark side is predominantly driven by political, legal, and institutional aspects, but it is also influenced by data and technology. Lack of understanding of AI outcomes, biases, and errors, as well as manipulation of intelligent algorithms and cognitive machines are contributing factors. The public sector should create knowledge about AI from an ethical, inclusive, and strategic perspective, involving experts from different areas. Points for practitioners Government officials and other decision-makers should be aware of the potential benefits of artificial intelligence, but also of the dark side, and try to avoid those potential negative consequences.

关键词： artificial intelligence the dark side unintended consequences intelligent algorithms cognitive machines public sector multi-level government

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Synergy of intelligent algorithms for Efficient Child-Robot Interaction in Special Education: A Feasibility Study 1

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11th International Conference on Robotics in Education (RiE)

作者： Sidiropoulos, George K. Bazinas, Christos Lytridis, Chris Papakostas, George A. Kaburlasos, Vassilis G. Kechayas, Petros Kourampa, Efi Katsi, Sotirianna Rafaela Karatsioras, Charalambos Int Hellen Univ HUMAIN Lab Kavala 65404 Greece Aristotle Univ Thessaloniki Papageorgiou Gen Hosp Psychiat Clin 1 Thessaloniki 56403 Greece Family Ctr KPG Thessaloniki 54352 Greece Novel Therapeut & Consulting Unit Praxis El Venizelou 42 Kavala 65302 Greece

ISBN: (数字)9783030674113

ISBN: (纸本)9783030674106;9783030674113

In this paper the problem of algorithms' interoperability in the context of an intelligent child-robot interaction for special education is studied. Given a technically demanding intervention scenario designed by experts, the set of algorithms that needed to implement the scenario are defined explicitly. Following a test case implementation involving a NAO robot, a feasibility analysis of the algorithms' synergy, with respect to the adopted architecture consisting of the robot, its sensory modules and the timing performance of the incorporated algorithms is presented. The developed algorithms have been tested both in laboratory conditions as well as in a pilot study involving three children. The experiments reveal the hardware and software requirements for the implementation of such an intervention scenario with high intelligent child-robot interaction capabilities and highlight the need for an alternative system architecture.

关键词： Child-robot interaction intelligent algorithms Special education

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Exploration of the Teaching Reform Model for Computer Public Courses Based on intelligent algorithms 1

Exploration of the Teaching Reform Model for Computer Public...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Wei, Kai Jilin Animation Institute Changchun Jilin China

ISBN: (纸本)9798350316469

This article proposes a teaching reform model for computer public courses based on intelligent algorithms, aiming to improve the teaching quality of computer public courses and the learning effectiveness of students. This mode utilizes intelligent algorithms to optimize course content and teaching methods, achieving reasonable allocation of course resources and personalized teaching, and improving students' learning enthusiasm and grades. The experimental results indicate that this model has good feasibility and effectiveness, providing new ideas and methods for the teaching reform of computer public courses. And the learning efficiency of students has doubled compared to traditional methods, reaching 95%. © 2023 IEEE.

关键词： Computer public courses intelligent algorithms reform in education

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Optimization of Management Decision Based on Machine Learning: Application of intelligent algorithms in Enterprise Management Systems 5

Optimization of Management Decision Based on Machine Learnin...

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5th International Conference on Computers, Information Processing and Advanced Education, CIPAE 2024

作者： Cao, Jian Zhang, Yuxi Faculty of Business City University of Macau Macau999078 China School of Business Shanghai Normal University Tianhua College Shanghai201815 China

ISBN: (纸本)9798331527662

The optimization of an organization’s management decisions through the inclusion of machine learning remains a factor that represents significant advancements in the element of enterprise management. These algorithms are designed to focus on the leveraging of intelligent algorithms intended at enhancing the decision-making process. An initial data collection process that involves the collection and the pre-processing of real-time and historical data from different enterprise systems plays a critical role in ensuring the system operates on quality data. Further, a feature selection model is used in the system in identifying varied variables that influence managerial decisions, a process that relies on techniques that include principal component and correlation analysis. A training and validation process equally help in the design of the system as it splits data into validation and training sets through a cross-validation approach that prevents the overfitting while ensuring robust system performance. Lastly, the deployment and optimization of the system helps in refining the model and systems parameters through the use of Bayesian optimization, grid search, and the integration of optimized models into real-time support in the enterprise management system. According to the findings of the study, a continuous improvement of the system is achieved through the monitoring of the model’s performance and its periodical retention of new data in a bid to maintain the systems accuracy. The algorithms model facilitates the making of informed and data-driven managerial decisions, thus enhancing the effectiveness and efficiency of enterprise operations. © 2024 IEEE.

关键词： Enterprise Management Systems Feature Selection intelligent algorithms Machine Learning Optimization of Management Decision

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Big Data Analysis and Applications in International Trade: Decision Optimization Based on intelligent algorithms 3

Big Data Analysis and Applications in International Trade: D...

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3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024

作者： Yang, Wenwen Jiangxi College of Foreign Studies Nanchang330096 China

ISBN: (纸本)9798350384598

In the field of international trade, due to its wide range and complex interest relations, it is necessary to synthesize various information for analysis and decision-making. However, traditional data processing methods have been unable to meet the needs of enterprise development. As a new, efficient, safe and reliable solution, large database technology has been widely used in various fields and achieved good results. The purpose of this paper is to discuss and study the cross-department collaboration problem driven by intelligent algorithm through application examples. This paper first introduces the basic concepts, characteristics and relevant theoretical basis of inter-departmental collaboration. By studying the application of intelligent algorithms in interdepartmental collaboration, effective decision support tools are provided to deal with the complex situations in international trade. After that, this paper conducts a simulation test on the intelligent algorithm-driven decision optimization model, and the test results show that the test range of this model for the risk-return rate in trade is 0.04-0.09. © 2024 IEEE.

关键词： big data analysis decision optimization intelligent algorithms international trade

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Editorial: Safety and security of robotic systems: intelligent algorithms

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FRONTIERS IN NEUROROBOTICS 2024年 17卷 1342742页

作者： Wu, Chengwei Harbin Inst Technol Dept Control Sci & Engn Harbin Peoples R China

The paper titled "Face morphing attack detection based on high-frequency features and progressive enhancement learning" by Jia et al. reported a detection method that leverages high-frequency features and progressive enhancement learning. This technique extracts high-frequency information from the three-color channels of an image to precisely capture details and texture changes. Simultaneously, a progressive enhancement learning framework is devised, integrating self-enhancement and interactive enhancement modules. These modules systematically amplify features to capture subtle deformation traces, seamlessly merging high-frequency information with RGB details. Experimental results on standard databases, in comparison with nine classical techniques, showcase the exceptional performance of the proposed *** paper titled "Research on control strategy of vehicle stability based on dynamic stable region regression analysis" by Liu et al. reported a support vector regression (SVR) model for the automated regression of the dynamic stable region and devised a direct yaw-moment control (DYC) stability controller based on linear time-varying model predictive control (LTV-MPC). The impact of critical factors, such as the center of mass position and road adhesion coefficient, on the stable region is scrutinized through phase diagrams. Simulation experiments substantiate the effectiveness of the stability judgment and control *** paper titled "Research on Reinforcement Learning-Based Safe Decision-Making Methodology for Multiple Unmanned Aerial Vehicles" by Yue et al. reported a Transfer Safety Soft Actor-Critic (TSSAC) for decision-making in multiple UAVs. The decisionmaking process for each drone is modelled using a constrained markov decision process (CMDP), where safety constraints are imposed to maximize returns. Within the CMDP model, the soft actor-critic-Lagrangian (SAC-Lagrangian) algorithm is integrated with an enhanced Lag

关键词： safety security robotic systems intelligent algorithms cyber attacks

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Recognition of the rhizome of red ginseng based on spectral-image dual-scale digital information combined with intelligent algorithms

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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023年第1期297卷 122742页

作者： Zhang, Hongxu Pan, Yixia Liu, Xiaoyi Chen, Yuan Gong, Xingchu Zhu, Jieqiang Yan, Jizhong Zhang, Hui Zhejiang Univ Technol Coll Pharmaceut Sci 18 Chaowang Rd Hangzhou 310014 Peoples R China Zhejiang Univ Pharmaceut Informat Inst Coll Pharmaceut Sci Hangzhou 310058 Peoples R China

Red ginseng is a widely used and extensively researched food and medicinal product with high nutritional value, derived from steamed fresh ginseng. The components in various parts of red ginseng differ significantly, resulting in distinct pharmacological activities and efficacies. This study proposed to establish a hyperspectral imaging technology combined with intelligent algorithms for the recognition of different parts of red ginseng based on the dual-scale of spectrum and image information. Firstly, the spectral information was processed by the best combination of first derivative as pre-processing method and partial least squares discriminant analysis (PLS-DA) as classification model. The recognition accuracy of the rhizome and the main root of red ginseng is 96.79% and 95.94% respectively. Then, the image information was processed by the You Only Look Once version 5 small (YOLO v5s) model. The best parameter combination is epoch = 30, learning rate = 0.01, and activation function is leaky ReLU. In the red ginseng dataset, the highest accuracy, recall and mean Average Precision at IoU (Intersection over Union) threshold 0.5 (mAP@0.5) were 99.01%, 98.51% and 99.07% respectively. The application of spectrum-image dual-scale digital information combined with intelligent algorithms in the recognition of red ginseng is successful, which provides a positive significance for the online and on-site quality control and authenticity identification of crude drugs or fruits.

关键词： Red Ginseng Hyperspectral imaging intelligent algorithms Pre-processing method YOLO v5s

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DISPLAY SPACE AND DISTRIBUTION VISUALIZATION OF intelligent algorithms AND 3D INTERACTIVE IMAGING TECHNOLOGY

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COMPUTING AND INFORMATICS 2024年第4期43卷 993-1011页

作者： Li, Qing Ni, Longjiao Bai, Liu Huainan Normal Univ Coll Art & Design Huainan 232000 Anhui Peoples R China Suzhou Univ Coll Fine Arts & Design Suzhou 234000 Anhui Peoples R China

The traditional two-dimensional data visualization method is difficult to accurately express and display the three-dimensional information of the data, while the 3D interactive image technology can visually display the data in the threedimensional space. At the same time, it can also operate and edit the data through interactive methods to help people better understand and use the data. intelligent algorithms are an important supplement to 3D interactive imaging technology, which can improve visualization and analysis accuracy through calculations, model building, and other methods, achieving more accurate data display and analysis. This article aimed to explore the application of intelligent algorithms and 3D interactive imaging technology in the field of spatial visualization. intelligent algorithms can help analyze data features and relationships, extract data attributes, and optidata in a virtual three-dimensional space, enhancing the interaction and visualization effect between users and data. The combination of the two can achieve better data analysis and presentation results. This article conducted simulation experiimaging technology, and scored some experimental indicators using a scoring system. The experimental results of this article indicate that the intelligent algorithm had a time efficiency of 46.5 seconds and an accuracy of 95 % in displaying spatial and distribution visualization. The usability score was 75. The interactivity score of 3D interactive imaging technology in displaying spatial and distribution visualization was 96. The visual effect score was 96, and the usability score was 65. The combination of the two in terms of displaying spatial and distribution visualization had a time efficiency of 50.8 seconds, interactivity of 86 minutes, and accuracy of 98%. It shows that different data visualization technologies have their own characteristics in display space and distribution visualization, and suitable technologies can be selected according

关键词： Space and distribution visualization 3D interaction intelligent algorithms imaging technology

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