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Sora for foundation robots with parallel intelligence:three world models,three robotic systems

Frontiers of Information Technology & Electronic engineering 2024年第7期25卷 917-923页

作者： Lili FAN Chao GUO Yonglin TIAN Hui ZHANG Jun ZHANG Fei-Yue WANG School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100044China School of Electrical Engineering Wuhan UniversityWuhan 430072China

This paper outlines the initial steps and basic framework for developing foundation/infrastructure robots/robotics based on foundation models and parallel intelligence,as well as the potential applications of new art... 详细信息

关键词： artificial foundation intelligence

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Design and Implementation of a Wide-Swing CMOS Multiplier for AC Source Signal Tracking and Modulation

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Circuits, Systems, and Signal Processing 2024年第9期43卷 5377-5400页

作者： Wang, Wei Xu, Sendren Sheng-Dong Chen, Chi-Lin Chiu, Huang-Jen Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei 106335 Taiwan Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taipei 106335 Taiwan Advanced Manufacturing Research Center National Taiwan University of Science and Technology Taipei 106335 Taiwan Himax Technologies Inc. Taipei 100507 Taiwan

The multiplier is a pervasive critical component today. However, most of them are difficult to be integrated into an integrated circuit. In this study, we proposed a novel analog multiplier for AC power application, using CMOS process to realize the analog voltage multiplication function of double-ended input and single-ended output. Under the working voltage of 3.3 V, the multiplier can operate with a wide input voltage range of 0–1.6 V (about 48.8% of the working voltage) and a wide output voltage range of 0–2.56 V (about 77.5% of the working voltage). The multiplier is implemented through the current difference between two NMOSs operating in the linear region and the saturation region, respectively. Compared with the existing technique, the proposed analog multiplier has a wider input and output range, and better linearity. It is suitable for AC power signal tracking and modulation. Finally, the United Microelectronics Corporation 0.18 μm 1P4M CMOS standard process was used for physical implementation. Moreover, there is not any BJT or special device used. It was measured that the analog multiplier circuit consumes about 0.56 mW at a working voltage of 3.3 V. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： AC power signal modulation AC source signal tracking Analog integrated circuit (IC) design Analog multipliers Circuits and systems

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High Efficiency Dual-Active-Bridge Converter with Triple-Phase-Shift control for Battery Charger of Electric Vehicles

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Energies 2024年第2期17卷 354页

作者： Kuo, Shih-Hao Chiu, Huang-Jen Chiang, Che-Wei Huang, Ta-Wei Chang, Yu-Chen Bachman, Serafin Piasecki, Szymon Jasinski, Marek Turzyński, Marek Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei106 Taiwan Institute of Control and Industrial Electronics Warsaw University of Technology Warsaw00-662 Poland Faculty of Electrical and Control Engineering Gdańsk University of Technology Gdansk80-233 Poland

An optimal modulation scheme with triple-phase-shift (TPS) control could increase the efficiency in the entire load range for a dual-active-bridge (DAB) converter under wide output voltage range conditions. Therefore, this study proposes a convergent approach to TPS mode selection, coupled with an optimal modulation scheme, ensuring the circuit’s efficiency over the entire range in the realm of a high-power and high-efficiency battery charger for electric vehicles. The convergent approach to TPS mode selection also reduces the numerous cases for small-signal analysis through general average modeling. After verifying the small-signal models under various voltage transfer ratios and load conditions to verify the stability, a converter prototype with a rated power of 15 kW is built and tested. Thus, a peak efficiency of 97.7% can be achieved. © 2024 by the authors.

关键词： Charging (batteries)

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Detection of DDoS Attacks with Gaussian Mixture Model 9

Detection of DDoS Attacks with Gaussian Mixture Model

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9th Scholar's Yearly Symposium of Technology, engineering and Mathematics, SYSTEM 2023

作者： Cecchetto, Alessandro Conte, Giuseppa Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Via dei Taurini 19 Roma00185 Italy Department of Computational Intelligence Czestochowa University of Technology Czestochowa42-201 Poland

A Distributed Denial of Service (DDoS) is an attack which aim is to stop or tamper with an online service incapacitating a server with a flood of packages or requests, using internet or intranet. The main aim of the DDoS attack is to collapse the network or server with abnormal traffic to make the service unavailable for the legitimate users. This problem is particularly profound, due to the development of emerging technologies, such as cloud computing, the Internet of Things or artificial intelligence techniques, from which attackers can take advantage by launching a huge volume of DDoS attacks at a lower cost, and it is much harder to detect and prevent DDoS attacks, because DDoS traffic is similar to normal traffic. In this paper we implement a novel technique implementing an unsupervised Gaussian Mixture Model (GMM) based algorithm. Using a real traffic dataset, the CIC-DDoS2019, for benchmark, the proposed GMM can achieve recall, precision, and accuracy up to 99%. Experiments reveal that this can be a promising solution for the detection of DDoS attacks. © 2023 Copyright for this paper by its authors.

关键词： Denial-of-service attack

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Meta-heuristics for Feature Selection and Classification in Diagnostic Breast Cancer

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computers, Materials & Continua 2022年第10期73卷 749-765页

作者： Doaa Sami Khafaga Amel Ali Alhussan El-Sayed M.El-kenawy Ali E.Takieldeen Tarek M.Hassan Ehab A.Hegazy Elsayed Abdel Fattah Eid Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Communications and Computers Engineering Department Faculty of EngineeringDelta University for Science and TechnologyInternational Coastal RoadGamasa CityDakhliyaEgypt Faculty of Applied Health Science Technology Delta University for Science and TechnologyMansoura35712Egypt Faculty of Medicine Head of Internal Medicine DepartmentDelta University for Science and TechnologyMansouraEgypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

One of the most common kinds of cancer is breast *** early detection of it may help lower its overall rates of *** this paper,we robustly propose a novel approach for detecting and classifying breast cancer regions in thermal *** proposed approach starts with data preprocessing the input images and segmenting the significant regions of *** addition,to properly train the machine learning models,data augmentation is applied to increase the number of segmented regions using various scaling *** the other hand,to extract the relevant features from the breast cancer cases,a set of deep neural networks(VGGNet,ResNet-50,AlexNet,and GoogLeNet)are *** resulting set of features is processed using the binary dipper throated algorithm to select the most effective features that can realize high classification *** selected features are used to train a neural network to finally classify the thermal images of breast *** achieve accurate classification,the parameters of the employed neural network are optimized using the continuous dipper throated optimization *** results show the effectiveness of the proposed approach in classifying the breast cancer cases when compared to other recent approaches in the ***,several experiments were conducted to compare the performance of the proposed approach with the other *** results of these experiments emphasized the superiority of the proposed approach.

关键词： Breast cancer image segmentation dipper throated optimization feature selection meta-heuristics

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A Machine Learning based Real-Time Application for Engagement Detection 9

A Machine Learning based Real-Time Application for Engagemen...

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9th Scholar's Yearly Symposium of Technology, engineering and Mathematics, SYSTEM 2023

作者： Iacobelli, Emanuele Russo, Samuele Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome Roma00185 Italy Department of Psychology Sapienza University of Rome Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Roma00185 Italy Department of Computational Intelligence Czestochowa University of Technology Czestochowa42-201 Poland

The study of human engagement has significantly grown in recent years, particularly accelerated by the interaction with a growing number of smart computing machines [1, 2, 3]. Engagement estimation has significant importance across various domains of study, including advertising, marketing, human-computer interaction, and healthcare [4, 5, 6]. In this paper, we propose a real-time application that leverages a single RGB camera to capture user behavior. Our approach implements a novel method for estimating human engagement in real-world scenarios by extracting valuable information from the combination of facial expressions and gaze direction analysis. To acquire this data, we employed fast and accurate machine learning algorithms from the external library dlib, along with custom versions of Residual Neural Networks implemented from scratch. For training our models, we used a modified version of the DAiSEE dataset, a multi-label user affective states classification dataset that collects frontal videos of 112 different people recorded in real-world scenarios. In the absence of a baseline for comparing the results obtained by our application, we conducted experiments to assess its robustness in estimating engagement levels, leading to very encouraging results. © 2023 Copyright for this paper by its authors.

关键词： Eye tracking

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Cloud-Edge Intelligent Collaborative Computing Model Based on Transfer Learning in IoT 9th

Cloud-Edge Intelligent Collaborative Computing Model Based o...

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9th International Conference of Pioneering computer Scientists, Engineers and Educators, ICPCSEE 2023

作者： Long, Yang Li, Zhixin School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China School of Computer Technology and Engineering Changchun Institute of Technology Changchun130012 China

ISBN: (纸本)9789819959679

The deep neural network is a reliable technical support for cloud computing and edge computing. It has excellent nonlinear approximation and generalization capabilities, making it suitable for classifying and predicting Internet of Things data in cloud computing and edge computing fields. However, the increasing size of neural networks poses a challenge for their deployment on devices with limited computing and storage resources. Traditional cloud computing services also suffer from high latency, which hinders real-time tasks. To address these challenges, this paper proposes a cloud-side cooperation model for deep learning based on migration learning technology. This model used migration learning technology to reduce the size of deep neural networks. Specifically, it deployed the deep neural network model (CDLM) in the cloud and the shallow neural network model (EDLM) at the edge. CDLM is used to help train EDLM and improve its performance, enabling it to run independently on edge devices with high accuracy and respond to real-time tasks. This approach reduced the amount of user data transmitted to the cloud, alleviated bandwidth pressure, and protected user privacy. Experimental results show that the proposed model improved the accuracy of EDLM by 19.58% compared with traditional neural network models. These findings provide a theoretical and experimental foundation for the study of cloud-edge collaborative models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Edge computing

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Explaining complex systems: a tutorial on transparency and interpretability in machine learning models (part II)

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IFAC-PapersOnLine 2024年第15期58卷 497-501页

作者： Donatello Materassi Sean Warnick Cristian Rojas Maarten Schoukens Elizabeth Cross Department of Electrical and Computer Engineering University of Minnesota US Department of Homeland Security Science and Technology Directorate EECS/Division of Decision and Control Systems KTH Royal Institute of Technology Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands Department of Mechanical Engineering University of Sheffield

In the second segment of the tutorial, we transition from the granularity of local interpretability to a broader exploration of eXplainable AI (XAI) methods. Building on the specific focus of the first part, which delved into Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP), this section takes a more expansive approach. We will navigate through various XAI techniques of more global nature, covering counterfactual explanations, equation discovery, and the integration of physics-informed AI. Unlike the initial part, which concentrated on two specific methods, this section offers a general overview of these broader classes of techniques for explanation. The objective is to provide participants with a comprehensive understanding of the diverse strategies available for making complex machine learning models interpretable on a more global scale.

关键词： eXplainable AI

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Simulation Model of Data Consistency Protocol for Multicloud Systems 3

Simulation Model of Data Consistency Protocol for Multicloud...

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3rd IEEE KhPI Week on Advanced Technology, KhPI Week 2022

作者： Kozina, Olha Kozin, Mykyta National Technical University 'Kharkiv Polytechnic Institute' Department of Computer Engineering and Programming Kharkiv Ukraine Kharkiv Nation University of Radio Electronics Department of Information Control System Kharkiv Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

The development of multi-cloud systems with an acceptable level of service delays that significantly affect the quality of the end-users experience is an open research problem, for which simulation is successfully used. This paper proposes a simulation model in Matlab for estimating the time to write data updates initiated by the end-users to the databases of all cloud service providers for a multi-cloud system with a geo-distributed middleware that implements, as an example, the VIP-grab data consistency protocol. The simulation results indicate that our model can be useful in choosing a data consistency protocol that influences the architecture of a multicloud system. © 2022 IEEE.

关键词： MATLAB

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Sequential generation of self-starting diverse operations in all-fiber laser based on thulium-doped fiber saturable absorber

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Chinese Physics B 2022年第6期31卷 87-90页

作者： Pei Zhang Kaharudin Dimyati Bilal Nizamani Mustafa M.Najm S.W.Harun School of Electrical and Information Engineering Huaihua UniversityHuaihua 418008China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua UniversityHuaihua 418008China Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia Faculty of Advanced Technology and Multidiscipline Airlangga UniversitySurabaya 60115Indonesia Institute of Computer Science and Digital Innovation UCSI UniversityKuala LumpurMalaysia

Self-starting Q-switching,Q-switched mode-locking and mode-locking operation modes are achieved sequentially in an all-fiber erbium-doped fiber laser with thulium-doped fiber saturable absorber for the first *** central wavelengths of Q-switching,Q-switched mode-locking and mode-locking operation modes are 1569.7 nm,1570.9 nm,and 1572 nm,*** mode-locking operation of the proposed fiber laser generates stable dark soliton with a repetition rate of 0.99 MHz and signal-to-noise ratio of 65 *** results validate the capability of generating soliton pulse by doped fiber saturable ***,the proposed fiber laser is beneficial to the applications of optical communication and signal processing system.

关键词： all-fiber laser Q-switched mode-locking dark soliton fiber saturable absorber

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