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Self-supervised cost of transport estimation for multimodal path planning

IEEE Robotics and Automation Letters 2025年第7期10卷 6872-6879页

作者： Gherold, Vincent Mandralis, Ioannis Sihite, Eric Salagame, Adarsh Ramezani, Alireza Gharib, Morteza California Institute of Technology Aerospace Engineering Department PasadenaCA United States Northeastern University Electrical and Computer Engineering Department BostonMA United States

Autonomous robots operating in real environments are often faced with decisions on how best to navigate their surroundings. In this work, we address a particular instance of this problem: how can a robot autonomously decide on the energetically optimal path to follow given a high-level objective and information about the surroundings? To tackle this problem we developed a self-supervised learning method that allows the robot to estimate the cost of transport of its surroundings using only vision inputs. We apply our method to the multi-modal mobility morphobot (M4), a robot that can drive, fly, segway, and crawl through its environment. By deploying our system in the real world, we show that our method accurately assigns different cost of transports to various types of environments e.g. grass vs smooth road. We also highlight the low computational cost of our method, which is deployed on an Nvidia Jetson Orin Nano robotic compute unit. We believe that this work will allow multi-modal robotic platforms to unlock their full potential for navigation and exploration tasks. © 2016 IEEE.

关键词： Motion planning

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Command, Control and Communications for Unmanned Aereal Systems in C-Band

Command, Control and Communications for Unmanned Aereal Syst...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Alghamdi, Mubark Kostanic, Ivica Florida Institute of Technology Department of Electrical Engineering and Computer Science Melbourne United States

ISBN: (纸本)9798350364910

C band spectrum 5030-5091 MHz is allocated for command-and-control communication services with unmanned aircraft systems. This paper evaluates the possibility of using 3GPP 5G standards for provisioning of such services. Channelization of the spectrum and major system parameters are proposed. The performance of the proposed system in channel fading environment is evaluated using MATLAB based simulations. The evaluations examine SINR, and average throughput of the proposed system at different altitudes of the unmanned aircraft system. © 2024 IEEE.

关键词： MATLAB

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Improvement of reconstruction accuracy for hardware systems with Finite Rate of Innovation 2

Improvement of reconstruction accuracy for hardware systems ...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Wang, Jingyu Ding, Li Zhou, Tao University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai China

ISBN: (纸本)9798331515669

In classical Finite Rate of Innovation (FRI) theory, signal reconstruction is initially achieved with precision using the zeroing filter algorithm on noiseless pulse signals. However, with the introduction of noise, the zeroing filter algorithm exhibits reduced robustness when handling signals with low signal-to-noise ratios (SNR). This paper introduces the TLS-ESPRIT algorithm, which enhances robustness against noise to some extent. Additionally, building on the development of an FRI reconstruction system based on C-TEM sampling, this work innovatively proposes a cascaded filter phase compensation method. This method mitigates the nonlinear phase effects of analog filters, thereby improving reconstruction accuracy. Ultimately achieving a reduction in sampling rate while improving reconstruction accuracy. © 2024 IEEE.

关键词： Signal to noise ratio

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Comparative Analysis of Feature Selection Techniques and Machine Learning Classifiers for Accurate Classification of Pumpkin Seeds 2

Comparative Analysis of Feature Selection Techniques and Mac...

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2nd International Conference on Information and Communication technology for Sustainable Development, ICICT4SD 2023

作者： Siddique, Md Abu Ismail Haque, Fariha Shojol, Md. Shojeb Hossain Rajshahi University of Engineering and Technology Dept. of Electrical and Computer Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350358667

Pumpkin seeds are widely consumed due to their nutritional content and potential health advantages. Accurately categorizing pumpkin seeds based on their diversity and distinct physical properties, such as size, compactness, roundness, and others, is crucial in agriculture, food processing, and research. In this work, two approaches were used to categorize a dataset of pumpkin seeds and establish their relative performance. The first method used a typical machine learning methodology, whereas the second used a filter-based feature selection technique. The filter-based technique used principal component analysis (PCA) and recursive feature elimination (RFE) to extract the most significant features for identifying two varieties of pumpkin seeds. Machine learning classifiers were then used to assess the performance of each strategy. Machine learning classifiers were then applied to evaluate the performance of the approach where Random Forest performed best among all others and achieved 91.80% validation accuracy. On the other hand for the conventional machine learning classifier method, six classifiers were used to evaluate the performance of this approach where the XgBoost classifier performed the best and achieved 95% as training accuracy and 94.87% as validation accuracy. © 2023 IEEE.

关键词： Feature Selection

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Statistical Eye Diagram for Nonideal Decision Feedback Equalizer (DFE)

Statistical Eye Diagram for Nonideal Decision Feedback Equal...

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2024 IEEE Joint International Symposium on Electromagnetic Compatibility, Signal and Power Integrity: EMC Japan/Asia Pacific International Symposium on Electromagnetic Compatibility, EMC Japan/APEMC Okinawa 2024

作者： Park, Junyong Kim, Dong Hyun Bill Missouri University Of Science And Technology Electrical And Computer Engineering RollaMO United States

ISBN: (纸本)9784885523472

This paper introduces the statistical eye diagram for the nonideal decision feedback equalizer (DFE). The DFE equalizes the inter-symbol-interference (ISI) based on the previous bits the DFE makes decisions. However, a DFE may make a wrong bit decision due to a substantial amount of noise, which is defined as a nonideal DFE in this paper. The statistical eye diagram was proposed for efficient signal integrity (SI) analysis, however, it is not applicable to the nonideal DFE. Because the statistical eye diagram has variables of the sampled voltage and sampling time. The DFE includes variables of a threshold voltage and sampling time for a slicer, which leads to a dependency between the variables and the corresponding statistical eye diagram. Thus, this paper proposes the statistical eye diagram for the nonideal DFE. The proposed method is verified by comparison to the transient simulation. Copyright © 2024 IEICE.

关键词： Sampling

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Leveraging UAV-assisted communications to improve secrecy for URLLC in 6G systems

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Digital Communications and Networks 2023年第6期9卷 1458-1464页

作者： Hemant Kumar Narsani Ali Ranjha Kapal Dev Fida Hussain Memon Nawab Muhammad Faseeh Qureshi Faculty of Engineering and Technology University of SindhPakistan Department of Electrical Engineering Ecole de Technologie Superieure Montreal QCCanada Department of Institute of Intelligent Systems University of JohannesburgSouth Africa Department of Electrical Engineering Sukkur IBA UniversityPakistan Department of Computer Education Sungkyunkwan UniversitySeoulRepublic of Korea

Unmanned Aerial Vehicles(UAVs)will be essential to support mission-critical applications of Ultra Reliable Low Latency Communication(URLLC)in futuristic Sixth-Generation(6G)***,several security vulnerabilities and attacks have plagued previous generations of communication systems;thus,physical layer security,especially against eavesdroppers,is vital,especially for upcoming 6G *** this regard,UAVs have appeared as a winning candidate to mitigate security *** this paper,we leverage UAVs to propose two *** first method utilizes a UAV as Decode-and-Forward(DF)relay,whereas the second method utilizes a UAV as a jammer to mitigate eavesdropping attacks for URLLC between transmitter and receiver ***,we present a low-complexity algorithm that outlines the two aforementioned methods of mitigating interception,*** secrecy rate,and we compare them with the benchmark null method in which there is a direct communication link between transmitter and receiver without the UAV DF ***,simulation results show the effectiveness of such methods by improving the secrecy rate and its dependency on UAV height,blocklength,decoding error probability and transmitter-receiver separation ***,we recommend the best method to enhance the secrecy rate in the presence of an eavesdropper based on our simulations.

关键词： URLLC UAV-Assisted communications 6G systems Secrecy rate

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High-Throughput Independent Component Analysis Processor for Full Duplex Systems

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IEEE Journal on Selected Areas in Communications 2023年第9期41卷 2821-2832页

作者： Cheng, Jen-Hao Chang, Tien-Min Shen, Chung-An Fouda, Mohammed E. Eltawil, Ahmed M. National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei10607 Taiwan University of California at Irvine Electrical Engineering and Computer Science Department IrvineCA92697 United States King Abdullah University of Science and Technology Electrical and Computer Engineering Program Thuwal23955 Saudi Arabia

This paper presents the algorithm and very-large-scale integration (VLSI) architecture of a high-throughput and highly efficient independent component analysis (ICA) processor for self-interference cancellation (SIC) in in-band full-duplex (IBFD) systems. This is the first VLSI architecture reported in the literature based on the state-of-the-art entropy bound minimization (EBM) approach. A novel ICA algorithm is presented in this paper with momentum gradient descent optimization. Simulation results show that the number of iterations for the proposed algorithm is significantly reduced compared to the conventional ICA algorithms. Furthermore, a novel early-distribution estimation scheme is proposed in the designed ICA processor to compute multiple distribution functions with low latency and low complexity. The processing flow and the efficiency for the hardware utilization are specifically designed so that the processing speed is maximized with minimum employment of hardware components. The proposed ICA processor is designed and implemented based on the application-specific-integrated circuit (ASIC) flow. The post-layout estimations show that compared with the conventional EBM-based scheme, the proposed design improves the throughput and efficiency by 30x. In addition, compared to prior designs shown in the literature, the proposed ICA processor also demonstrates a significant enhancement in terms of throughput and efficiency. © 1983-2012 IEEE.

关键词： VLSI circuits

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Cooperative Gradient Coding for Semi-Decentralized Federated Learning

Cooperative Gradient Coding for Semi-Decentralized Federated...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Weng, Shudi Li, Chengxi Xiao, Ming Skoglund, Mikael Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden

ISBN: (纸本)9798350351255

Stragglers' effects are known to degrade FL performance. In this paper, we investigate federated learning (FL) over wireless networks in the presence of communication stragglers, where the power-constrained clients collaboratively train a global model by iteratively optimizing a local objective function with their local datasets and transmitting local model updates to the central parameter server (PS) through fading channels. To tackle communication stragglers without dataset sharing or prior information about the network at PS, we propose cooperative gradient coding (CoGC) for semi-decentralized FL to enable the exact global model recovery at PS. Furthermore, we conduct a thorough theoretical analysis of the proposed approach. Namely, an outage analysis of the proposed approach is provided, followed by a convergence analysis based on the failure probability of the global model recovery at PS. Nevertheless, simulation results reveal the superiority of the proposed approach in the presence of stragglers under imbalanced data distribution. © 2024 IEEE.

关键词： Fading channels

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A Comparative Study for Detecting Polycystic Ovary Syndrome Using A Machine Learning Framework 26

A Comparative Study for Detecting Polycystic Ovary Syndrome ...

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26th International Conference on computer and Information technology, ICCIT 2023

作者： Mou, Tamanna Hossain Jyoti, Oishi Ahmed, Tamal Imam, Md. Rafi Rajshahi University of Engineering & Technology Department of Electrical & Computer Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798350359015

Polycystic Ovary Syndrome (PCOS) is a widespread hormonal disorder affecting numerous women with ovaries, during their reproductive ages, often leading to various complications if undiagnosed or improperly managed. This research aims to improve PCOS detection by utilizing an interpretable machine-learning framework for diagnostic assistance. We utilized a publicly available dataset from Kaggle, featuring 541 samples and 44 attributes. Various preprocessing techniques and feature selection methods, such as Chi-Square, Mutual Information, and Correlation Coefficient, were employed here. Subsequently, we trained multiple machine learning algorithms and subjected them to K-fold cross-validation. Their performance is evaluated and compared by accuracy, precision, recall, and F1 score. Our findings reveal that the CatBoost algorithm, when paired with Chi-Square feature selection, achieved the highest accuracy rate of 93.9%. Our study focuses on investigating important features, comparing algorithm performance, and achieving high accuracy in PCOS detection. The research validates machine learning's effectiveness for non-invasive PCOS diagnosis, laying the groundwork for future medical diagnostics. © 2023 IEEE.

关键词： CatBoost Chi-Square Comparative Analysis Diagnosis Feature Selection Polycystic Ovary Syndrome

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A Comprehensive Exploration of Real-Time 3-D View Reconstruction Methods

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 5915-5927页

作者： Agrawal, Arya Sharma, Teena Verma, Nishchal K. Vellore Institute of Technology School of Computer Science and Engineering Vellore632014 India Indian Institute of Technology Mehta Family School of Data Science and Artificial Intelligence Guwahati781039 India Indian Institute of Technology Kanpur Department of Electrical Engineering 208016 India

Real-time 3-D view reconstruction in an unfamiliar environment poses complexity for various applications due to varying conditions such as occlusion, latency, precision, etc. This article thoroughly examines and tests contemporary methodologies addressing challenges in 3-D view reconstruction. The methods being explored in this article are categorized into volumetric and mesh, generative adversarial network based, and open source library based methods. The exploration of these methods undergoes detailed discussions, encompassing methods, advantages, limitations, and empirical results. The real-time testing of each method is done on benchmarked datasets, including ShapeNet, Pascal 3D+, Pix3D, etc. The narrative highlights the crucial role of 3-D view reconstruction in domains such as robotics, virtual and augmented reality, medical imaging, cultural heritage preservation, etc. The article also anticipates future scopes by exploring generative models, unsupervised learning, and advanced sensor fusion to increase the robustness of the algorithms. © 2020 IEEE.

关键词： Generative adversarial networks

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