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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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Analysis of Antenna Arrays in Command and Non-Payload Communication for Unmanned Aircraft Systems in the C-Band 14

Analysis of Antenna Arrays in Command and Non-Payload Commun...

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14th IEEE International Conference on RFID technology and Applications, RFID-TA 2024

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

ISBN: (纸本)9798331540227

This paper examines the use of the C band (5030-5091 MHz) for command-and-control (C2) communication with unmanned aircraft systems (UAS). A channel plan is suggested and key system settings for C2 communication are tested. MATLAB simulations are used to evaluate system performance in free-space environments. Signal-to-Interference-plus-Noise Ratio (SINR) and Reference Signal Received Power (RSRP) are measured at different UAS heights. Antenna arrays from single antenna up to 10×10 arrays are analyzed to measure the Front-to-Back Ratio (FBR) and simplify the system. The study uses a 20 MHz bandwidth and considers a system load of 50 percent. © 2024 IEEE.

关键词： Aircraft communication

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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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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 Hybrid Rectifier Mode Control for Communication-Free Wireless Power Transfer

A Hybrid Rectifier Mode Control for Communication-Free Wirel...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Zhu, Gangwei Dong, Jianning Bauer, Pavol Delft University of Technology Department of Electrical Engineering Mathematics and Computer Science Delft Netherlands

ISBN: (纸本)9798350376067

This paper presents a hybrid rectifier mode control for broad-range output power regulation in wireless power transfer (WPT) systems. The proposed control method employs a secondary-side active rectifier for output tuning, thereby eliminating the necessity for communication links. Furthermore, leveraging the pulse-skipping technique, two hybrid modes are introduced in the proposed approach. These hybrid modes reduce circulating reactive power within the resonant circuits, thereby optimizing the transmission efficiency of the WPT systems. To validate the effectiveness of the proposed method, experiments were conducted using a WPT prototype. Experimental results demonstrate that the proposed approach achieves higher efficiency than the conventional phase-shift control strategy, with a maximum efficiency improvement of up to 3.7%. © 2024 IEEE.

关键词： Inductive power transmission

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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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Absorptive Microwave Filters: From Narrowband to Wideband Operation

Absorptive Microwave Filters: From Narrowband to Wideband Op...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Cui, Jiaqian Zhu, Lei University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering Macau China

ISBN: (纸本)9798350355581

This paper presents a method to control the out-ofband performance of absorptive filters in both narrowband and wideband cases. To verify the method, a narrowband absorptive filter is designed with wideband matching, and a wideband one is proposed to achieve an infinite low-reflection range. Finally, the narrowband filter is implemented in microstrip-line platform, not only attaining symmetrical geometry but also improving impedance-matching performance. © 2024 IEEE.

关键词： Wiener filtering

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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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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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Multimodal survival prediction using TabTransformer and BioClinicalBERT on MIMIC-III

Multimodal survival prediction using TabTransformer and BioC...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Insalata, Beatrice Schmidt, Fabian Vlassov, Vladimir Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden

ISBN: (纸本)9798350362480

This paper explores the development and evaluation of a multimodal system for survival prediction in clinical settings, leveraging both structured electronic health records and unstructured clinical notes. The core objective is to enhance the accuracy and reliability of survival predictions in Intensive Care Units by integrating diverse data types through advanced machine learning models. The system combines the novel architecture of Tabular Transformers, adapted to process structured data such as patient demographics, medical history, and diagnoses, with Multi-Layer Perceptrons for text embeddings obtained from BioClinicalBERT, a specialized model for clinical narratives. These models' integration aims to capture the complex and multifaceted nature of patient profiles, thereby improving prediction performance. The finalized system, a Logistic Regression instance that aggregates the obtained predictions, demonstrates superior performance on evaluation metrics, highlighting the system's ability to identify high-risk patients. Comprehensive benchmarking against decision trees, standalone MLPs, and various configurations underscored the robustness of the proposed system. This research highlights the transformative potential of multimodal data integration in medical predictive modeling. Thus, medical professionals can guide their efforts and prioritization of patient care, enabling more efficient and targeted allocation of resources during triage. © 2024 IEEE.

关键词： Electronic health record

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