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Recent Advances in science and engineering Technology (ICRASET), International Conference on

作者： A. Ponmalar Rajkumar Pandiarajan I. Sudha P.S. Ramesh J. Jagannathan R.M.K. Engineering College Chennai Tamilnadu India Department of Information and Technology School of Computing Kalasalingam Academy Of Research and Education Krishnankoil Virudhunagar India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences SIMATS University Chennai Tamil Nadu India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Katpadi Vellore India

ISBN: (数字)9798350388602

ISBN: (纸本)9798350388619

The aim of this work is to examine the application of FHE-SMPC as a viable security model for protecting the tenant isolation in multi-tenant cloud model. In multi-tenant environments, where various customers use the same cloud system, controlling the data leakage and protecting privacy is a major issue. Actual safeguards fail to meet the needs of data protection during processing, therefore, the introduction of highly elaborate encryption processes must happen. This research work focuses on the use of FHE technique and SMPC such that data can undergo processing while the plaintext remains unknown to any party. A kind of approach is based on the acquisition of synthetic and real data sets, system-level architecture, and cryptographic algorithms using open-source libraries with cloud service providers. The results of such implementation indicate that despite the fact that the FHE-SMPC system has a considerable computational overhead in comparison with classical schemes it is very secure and protected against different types of cryptographic attacks. The problem of scalability is still an open issue, but the complex is quite efficient with various data types that is why it can be used in various cloud applications. This paper offers a pertinent solution for security of data that is housed in multitenant environment and will go along way in creating fertile ground for research and innovation in secure clouding.

关键词： Resistance Technological innovation Scalability Data protection Libraries Service-oriented architecture Encryption Cryptography Time complexity Secure storage

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Mesh-based Object Tracking for Dynamic Semantic 3D Scene Graphs via Ray Tracing

arXiv

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arXiv 2024年

作者： Niecksch, Lennart Mock, Alexander Igelbrink, Felix Wiemann, Thomas Hertzberg, Joachim German Research Centre for Artificial Intelligence Plan-Based Robot Control Osnabrück Germany Osnabrück University Institute of Computer Science Knowledge-Based Systems Osnabrück Germany Fulda University of Applied Sciences Department of Applied Computer Science Robotics in Computer Science Fulda Germany

In this paper, we present a novel method for 3D geometric scene graph generation using range sensors and RGB cameras. We initially detect instance-wise keypoints with a YOLOv8s model to compute 6D pose estimates of known objects by solving PnP. We use a ray tracing approach to track a geometric scene graph consisting of mesh models of object instances. In contrast to classical point-to-point matching, this leads to more robust results, especially under occlusions between objects instances. We show that using this hybrid strategy leads to robust self-localization, pre-segmentation of the range sensor data and accurate pose tracking of objects using the same environmental representation. All detected objects are integrated into a semantic scene graph. This scene graph then serves as a front end to a semantic mapping framework to allow spatial reasoning. Copyright © 2024, The Authors. All rights reserved.

关键词： Mesh generation

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Multi-Task Collaborative Perception Algorithm Based on Consensus Perception

Multi-Task Collaborative Perception Algorithm Based on Conse...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Fuyu Luo Yunbo Yu Xiaoye Guo Systems Engineering Research Institute China State Shipbuilding Corporation Beijing China Department of Computer Science Harbin Institute of Technology Harbin China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

This Multi-agent collaborative perception is a hot topic in the current field of machine learning. Through communication and sharing of perceived scene information between agents, this approach can tackle issues such as occlusion and sparse observations present in single-agent observations. Existing studies have shown that localization errors are a significant factor affecting the accuracy of perception results. Furthermore, most prior work has focused solely on the performance of algorithms in individual tasks without considering multi-task scenarios. In this paper, a multitask collaborative perception method based on consensus perception is proposed. It integrates local perception information from each intelligent agent to form a global perception consensus, which is then used to correct the spatial feature maps of the agents, alleviating the impact of localization errors on perception results. Additionally, the use of a feature selection module based on spatial confidence maps and a multiscale attention feature fusion module optimizes the performance of the collaborative perception process. By setting up multiple decoders in parallel, a single model is able to handle diverse tasks. Experimental results demonstrate that the proposed consensus-based collaborative perception method effectively mitigates the negative impact of localization errors on perception performance, and the algorithm can achieve good perception results across multiple tasks.

关键词： Location awareness Accuracy Autonomous systems Collaboration Object detection Machine learning Multitasking Feature extraction Decoding Intelligent agents

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(Invited) Improved Thin Film Transistor Model Predicts TFT Operation in the THz Range 242

(Invited) Improved Thin Film Transistor Model Predicts TFT O...

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242nd ECS Meeting

作者： Shur, Michael Liu, Xueqing Ytterdal, Trond Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Electronics of the Future Inc ViennaVA22181 United States Department of Electronic Systems Norwegian University of Science and Technology Trondheim7491 Norway

ISBN: (纸本)9781607685395

Novel materials such as ZnO, InGaZnO, AMO-CNT, and organic materials and improved fabrication processes dramatically enhanced the achieved and projected thin film transistor (TFT) performance. The effective field-effect mobility of metal oxide TFT materials has reached values comparable to those for short-channel Si CMOS. We report on an improved compact model based on the RPI TFT model, the unified charge control model (UCCM), and the multi-segment TFT compact model. This improved model accounts for a non-exponential slope in the subthreshold regime by introducing a varying subthreshold slope and accounts for non-Trivial capacitance dependence on the gate bias. The application of this new TFT model to the analysis of the TFT response showed that a TFT complementary inverter using the phase-matched THz signal feeding should yield a very sensitive detection of THz radiation impinging on a short channel TFT. © 2022 ECS-The Electrochemical Society.

关键词： Thin film transistors

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Incentive Designs for Learning Agents to Stabilize Coupled Exogenous systems

arXiv

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arXiv 2024年

作者： Certório, Jair Martins, Nuno C. La, Richard J. Arcak, Murat The Department of Electrical and Computer Engineering Institute for Systems Research University of Maryland College Park College ParkMD20740 United States The Department of Electrical Engineering and Computer Science University of California BerkeleyCA94720 United States

We consider a large population of learning agents noncooperatively selecting strategies from a common set, influencing the dynamics of an exogenous system (ES) we seek to stabilize at a desired equilibrium. Our approach is to design a dynamic payoff mechanism capable of shaping the population's strategy profile, thus affecting the ES's state, by offering incentives for specific strategies within budget limits. Employing system-theoretic passivity concepts, we establish conditions under which a payoff mechanism can be systematically constructed to ensure the global asymptotic stability of the ES's equilibrium. In comparison to previous approaches originally studied in the context of the so-called epidemic population games, the method proposed here allows for more realistic epidemic models and other types of ESs, such as predator-prey dynamics. The stability of the equilibrium is established with the support of a Lyapunov function, which provides useful bounds on the transient *** Codes 92D10, 92D25 © 2024, CC BY-NC-ND.

关键词： Budget control

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Exploring the Role of Humanoid Robots in Adaptive Learning systems: A Case Study on Quizzing

Exploring the Role of Humanoid Robots in Adaptive Learning S...

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Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), International

作者： Eman A. Noh Haya k. Elsonbaty Noure A. Elnakeib Ghada K. El-Monayer Nada M. Enan Omar M Elzeki Aya M. Al-Zoghby Khaled M. Fouad Artificial Intelligence Science Faculty of Computer Science and Engineering New Mansoura University Dakhlia Egypt Faculty of Computer Science and Engineering New Mansoura University Faculty of Computer Science & Engineering Faculty of Computers and Information Mansoura University New Mansoura University Mansoura Egypt Computer Science Department Faculty of Computers and Artificial Intelligence Damietta University Damietta Egypt Faculty of Computer Science and Engineering New Mansoura University Dakhlia Egypt Information Systems Faculty of Computers and Artificial Intelligence Banha University Egypt

ISBN: (数字)9798350367775

ISBN: (纸本)9798350367782

This paper analyses how Quizmaster can be incorporated into the humanoid robot to improve learning processes in educational environments. The humanoid robot incorporates artificial intelligence in its function as an educator and adds a new dimension to the way an interactive learning environment can be achieved in the form of quiz-based learning modules. The current system of Quizmaster has been designed as a separate application but has been modified to work in harmony with the robot and all its hardware and software components. The idea of this integration is to develop an effective learning tool that will help teachers present personalized educational material and evaluate learners' performance immediately. The paper covers the technical changes needed for this integration and the obstacles met while implementing it, as well as possible educational benefits of using robots in classrooms. The effectiveness of the system is established according to the degrees of usability and learners' interest and knowledge gains data gathered from the pilot implementations in differentiated learning contexts. Thus, the results state the positive progress of student's engagement and their knowledge, and it proves how robotics is useful in current education. Thus, this paper provides practical recommendations for expanding research and mass application of robotics-based learning aids in educational organizations.

关键词： Humanoid robots Learning (artificial intelligence) Organizations Educational technology Ubiquitous computing Software Real-time systems Hardware Usability Testing

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Optimal control for Platooning in Vehicular Networks

Optimal Control for Platooning in Vehicular Networks

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IEEE International Conference on Communications (ICC)

作者： Thiago S. Gomides Evangelos Kranakis Ioannis Lambadaris Yannis Viniotis Carleton University School of Computer Science Ottawa ON Canada Department of Systems and Computer Engineering Carleton University Ottawa ON Canada Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA

As the automotive industry is developing autonomous driving systems and vehicular networks, attention to truck platooning has increased as a way to reduce costs (fuel consumption) and improve efficiency in the highway. Recent research in this area has focused mainly on the aerodynamics, network stability, and longitudinal control of platoons. However, the system aspects (e.g., platoon coordination) are still not well explored. In this paper, we formulate a platooning coordination problem and study whether trucks waiting at an initial location (station) should wait for a platoon to arrive in order to leave. Arrivals of trucks at the station and platoons by the station are modelled by independent Bernoulli distributions. Next we use the theory of Markov Decision Processes to formulate the dispatching control problem and derive the optimal policy governing the dispatching of trucks with platoons. We show that the policy that minimizes an average cost function at the station is of threshold type. Numerical results for the average cost case are presented. They are consistent with the optimal ones.

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Proposal of high attenuating external magnetic field chamber for biological experiments

Proposal of high attenuating external magnetic field chamber...

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International Conference on Computational Problems of Electrical engineering (CPEE)

作者： Marek Bajtoš Robert Cichorowski Roman Radil Ladislav Janoušek Department of Electromagnetic and Biomedical Engineering Faculty of Electrical Engineering and Informational Technology Žilina Slovakia Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

ISBN: (数字)9798331506643

ISBN: (纸本)9798331506650

This work presents the design, construction, and validation of a chamber for magnetic field attenuation. Needs of magnetic background controlling during experiments focused on behavior of biological samples exposed to various levels of the low frequency time-varying magnetic field set the motivation for this work. The solution is proposed with regard to the correct cultivation conditions of microbiological samples. The chosen methodology is established on the means of numerical modeling and simulations, as well as 3D printing techniques. The design process incorporates computer-aided design (CAD) software for the chamber proposal, subsequent printing via a 3D printer, followed by the construction of an attenuating chamber using mu-metal foil. The validation process involves measurements of magnetic flux density within the chamber, and comparison thereof with numerical simulations performed via CST Design Studio. All the solution steps resulted in a valid and effective magnetic field attenuation chamber, suitable for use in laboratory conditions.

关键词： Solid modeling Time-frequency analysis Design automation Three-dimensional displays Computational modeling Attenuation Three-dimensional printing Numerical models Magnetic fields Proposals

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Extracting Stress-Related EEG Patterns from Pre-Sleep EEG for Forecasting Slow-Wave Sleep Deficiency

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IEEE Transactions on Neural systems and Rehabilitation engineering 2024年 32卷 1817-1827页

作者： Su, Cheng-Hua Ko, Li-Wei Jung, Tzyy-Ping Onton, Julie Tzou, Shey-Cherng Juang, Jia-Chi Hsu, Chung-Yao Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Department of Biomedical Science and Environmental Biology Kaohsiung807 Taiwan University of California San Diego Swartz Center for Computational Neuroscience La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300 Taiwan University of California San Diego Institute for Neural Computation La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Biological Science and Technology Hsinchu300 Taiwan Kaohsiung Medical University Hospital Sleep Disorders Center Department of Neurology Kaohsiung807 Taiwan Kaohsiung Medical University College of Medicine Department of Neurology Kaohsiung807 Taiwan

Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall health. While stress is known for its detrimental impact on sleep quality, the precise effect of pre-sleep stress on subsequent sleep structure remains unknown. This study introduced a novel approach to study the pre-sleep stress effect on sleep structure, specifically slow-wave sleep (SWS) deficiency. To achieve this, we selected forehead resting EEG immediately before and upon sleep onset to extract stress-related neurological markers through power spectra and entropy analysis. These markers include beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn) and spectral entropy (SpEn). Fifteen subjects were included in this study. Our results showed that subjects lacking SWS often exhibited signs of stress in EEG, such as an increased beta/delta correlation, higher alpha asymmetry, and increased FuzzEn in frontal EEG. Conversely, individuals with ample SWS displayed a weak beta/delta correlation and reduced FuzzEn. Finally, we employed several supervised learning models and found that the selected neurological markers can predict subsequent SWS deficiency. Our investigation demonstrated that the classifiers could effectively predict varying levels of slow-wave sleep (SWS) from pre-sleep EEG segments, achieving a mean balanced accuracy surpassing 0.75. The SMOTE-Tomek resampling method could improve the performance to 0.77. This study suggests that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. Such information can be integrated with existing sleep-improving techniques to provide a personalized sleep forecasting and improvement solution. © 2001-2011 IEEE.

关键词： Entropy

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Logistic Regression Classification for Assessing the Risk of Kidney Tumor 2

Logistic Regression Classification for Assessing the Risk of...

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2nd International engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Alzubi, Dalia Al Mamlook, Rabia Emhamed Nasayreh, Ahmad Aljaidi, Mohammad Alazab, Rami Gharaibeh, Hasan Al-Naamneh, Qais Concordia University Dep. Information and Systems Engineering Montreal Canada Trine University Dep. of Business Administration IN United States University Zawia Department of Industrial Engineering Tripoli Libya Yarmouk University Dep. Computer Science Irbid Jordan Zarqa University Dep. of Computer Science Zarqa Jordan Jordan University of Science and Technology Dep. Surgery and Urology Irbid Jordan Applied Science Private University Dep. of Cyber Security Amman Jordan

ISBN: (纸本)9798350373363

The kidneys have the important function of filtering waste products and toxins from the blood in the human body. Any problems affecting the kidneys can potentially impact their efficiency and overall function. Kidney Tumor (KT) is a disease that specifically affects kidney cells and causes the abnormal growth of tissue in one or both kidneys. Assessing the risk of developing a kidney tumor and identifying the key factors that contribute to this risk are crucial for ensuring patient well-being. Additionally, this information assists doctors and specialists in making faster and more accurate diagnoses, determining appropriate treatment methods, and potentially influencing the course of the disease to minimize its severity and impact. Machine learning algorithms have recently been introduced to evaluate disease risks, and in this study, we specifically focus on examining the risk of kidney tumor development and investigating the influencing factors. We employed a logistic regression model to predict if a patient is at risk of developing a kidney tumor or not, and further categorized the samples into high-risk and low-risk groups. Our model was trained and tested using a unique dataset obtained from the (KAUH) hospital in Jordan, consisting of well-balanced metadata from 120 patients with kidney issues. Our work demonstrated accuracy results ranging from 90% to 98%. Ultimately, specialists can utilize our model as an additional tool to enhance the speed and accuracy of patient diagnoses © 2023 IEEE.

关键词： Tumors

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