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arXiv 2024年

作者： Mei, Haoran Peng, Limei Ho, Pin-Han The School of Computer Science and Engineering Kyungpook National University Deagu Korea Republic of Shenzhen Institute for Advanced Study UESTC Department of Electrical and Computer Engineering University of Waterloo WaterlooON Canada

Grant-free access (GFA) has been envisioned to play an active role in massive Machine Type Communication (mMTC) under 5G and Beyond mobile systems, which targets at achieving significant reduction of signaling overhead and access latency in the presence of sporadic traffic and small-size data. The paper focuses on a novel K-repetition GFA (K-GFA) scheme by incorporating Reed-Solomon (RS) code with the contention resolution diversity slotted ALOHA (CRDSA), aiming to achieve high-reliability and low-latency access in the presence of massive uncoordinated MTC devices (MTCDs). We firstly defines a MAC layer transmission structure at each MTCD for supporting message-level RS coding on a data message of Q packets, where a RS code of KQ packets is generated and sent in a super time frame (STF) that is composed of Q time frames. The access point (AP) can recover the original Q packets of the data message if at least Q out of the KQ packets of the RS code are successfully received. The AP buffers the received MTCD signals of each resource block (RB) within an STF and exercises the CRDSA based multi-user detection (MUD) by exploring signal-level inter-RB correlation via iterative interference cancellation (IIC). With the proposed CRDSA based K-GFA scheme, we provide the complexity analysis, and derive a closed-form analytical model on the access probability for each MTCD as well as its simplified approximate form. Extensive numerical experiments are conducted to validate its effectiveness on the proposed CRDSA based K-GFA scheme and gain deep understanding on its performance regarding various key operational parameters. Copyright © 2024, The Authors. All rights reserved.

关键词： Multiuser detection

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Examining 6G Infrastructure Capabilities: Paving the Way for Future Connectivity

Examining 6G Infrastructure Capabilities: Paving the Way for...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Rawat, Devyani Chaubey, Anurag Kumar, Prashant Hemelatha, S. Gajendran, P. Wankhede, D.S. Graphic Era Deemed to Be University Department of Management Studies Uttarakhand Dehradun India School of Commerce and Management Iimt University Meerut India Tmu Department of Ece India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore641021 India Karpagam College of Engineering Department of Electrical and Electronics Engineering Coimbatore641032 India Vishwakarma Institute of Information Technology Computer Engineering Pune India

ISBN: (纸本)9798350357769

6G structures are anticipated to be a major driver for the smart data society, providing functionality that is better to 5G and satisfying innovative features and apps. In this piece, we outline utilization situations and specifications for non - linear and non per third and sophisticated 6G networks as well as our view of what 6G will be. That can provide all-encompassing and limitless wireless communication, we show a massive and independent structured cabling that combines land, air, sea, and space communications. For network interfaces and creative vapour style, we also address artificial intelligence and machine learning. The Internet of Graphene, microwave frequency connectivity, very highly directional arrays myriad, numerous different, large erudite textures and holograms directional antennas, orbital rotational frequency - division, laser and that can be seen comms, nanotech, genomic messaging, and Ethereum - based frequency hopping are a few of the systems we identify as enticing for the 6F I environment. © 2023 IEEE.

关键词： 6G infrastructure Artificial intelligence Autonomous networks Directional arrays Holograms directional antennas Machine learning Microwave frequency connectivity Nanotech Quantum communications and computing SDN Smart data society Wireless communication

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Detecting and Monitoring Bias for Subgroups in Breast Cancer Detection AI

arXiv

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arXiv 2025年

作者： Kundu, Amit Kumar Doo, Florence X. Patil, Vaishnavi Varshney, Amitabh Jaja, Joseph Department of Electrical and Computer Engineering University of Maryland United States Department of Diagnostic Radiology and Nuclear Medicine University of Maryland School of Medicine United States Department of Computer Science University of Maryland United States Institute for Health Computing University of Maryland United States University of Maryland Institute for Advanced Computer Studies United States

Automated mammography screening plays an important role in early breast cancer detection. However, current machine learning models, developed on some training datasets, may exhibit performance degradation and bias when deployed in real-world settings. In this paper, we analyze the performance of high-performing AI models on two mammography datasets—the Emory Breast Imaging Dataset (EMBED) and the RSNA 2022 challenge dataset. Specifically, we evaluate how these models perform across different subgroups, defined by six attributes, to detect potential biases using a range of classification metrics. Our analysis identifies certain subgroups that demonstrate notable underperformance, highlighting the need for ongoing monitoring of these subgroups’ performance. To address this, we adopt a monitoring method designed to detect performance drifts over time. Upon identifying a drift, this method issues an alert, which can enable timely interventions. This approach not only provides a tool for tracking the performance but also helps ensure that AI models continue to perform effectively across diverse populations. © 2025, CC BY.

关键词： Mammography

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Analysis of Research Trends in computer Science: A Network Approach

arXiv

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arXiv 2023年

作者： Kalhor, Ghazal Bahrak, Behnam School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Tehran Institute for Advanced Studies Tehran Iran

Nowadays, computer science (CS) has emerged as a dominant force in numerous research areas both within and beyond its own discipline. However, despite its significant impact on scholarly space, only a limited number of studies have been conducted to analyze the research trends and relationships within computer science. In this study, we collected information on fields and subfields from over 2,000 research articles published in the 2022 proceedings of the top Association for Computing Machinery (ACM) conferences spanning various research fields. Through a network approach, we investigated the interconnections between CS fields and subfields to evaluate their interdisciplinarity and multidisciplinarity. Our findings indicate that computing methodologies and privacy and security stand out as the most interdisciplinary fields, while human-centered computing exhibits the highest frequency among the papers. Furthermore, we discovered that machine learning emerges as the most interdisciplinary and multidisciplinary subfield within computer science. These results offer valuable insights for universities seeking to foster interdisciplinary research opportunities for their students. © 2023, CC BY.

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Deep Learning-Driven Culvert Monitoring: A Novel Approach for Flash Flood Mitigation through Visual Blockage Analysis 9

Deep Learning-Driven Culvert Monitoring: A Novel Approach fo...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Samuel, Betty Elezebeth Alghamdi, Sultan Priya, T. Deepalakshmi, R. Kannan, Sathish Selvaraju, Mayakannan Department of Computer Science And Information Technology Jazan Saudi Arabia King Abdulaziz University Faculty of Engineering Department of Electrical And Computer Engineering Jeddah Saudi Arabia Npr College of Engineering & Technology Department of Mathematics Dindigul Tamilnadu Natham India The Tamilnadu Dr. Ambedkar Law University Department of Inter-Disciplinary Studies Tamilnadu Chennai India Saveetha Institute of Medical And Technical Sciences Saveetha School of Engineering Department of Vlsi Microelectronics Tamilnadu Chennai602105 India Vidyaa Vikas College of Engineering And Technology Department of Mechanical Engineering Tamilnadu Namakkal India

ISBN: (纸本)9798350394474

The primary cause of urban flash floods is often cited as trash clogging culverts. Flash floods can be avoided with the help of intelligent video analytic (IVA) methods that can extract information about blockages in order to make maintenance-related decisions in a timely manner. Knowing the percentage of culverts that are visually blocked can help prioritise maintenance at heavily blocked locations. In this paper, we introduce a deep learning-powered segmentation-classification pipeline for automatically detecting and segmenting culvert openings and then classifying them into one of four categories based on the degree to which they are visually blocked. The deep learning models underwent training using datasets sourced from the Visual Hydraulics Blockage Dataset (VHD) and Images of Culverts Blockage (ICOB). The outcomes revealed that Mask R-CNN attains the highest performance in segmentation, achieving an mAP@75 score of 77.2%. In contrast, NASNet excelled in classification tasks, with a remarkable 81.2% accuracy on the test data. To underscore the practical importance of these findings, one potential application is demonstrated, which involves using the models for monitoring visual obstructions. © 2024 IEEE.

关键词： computer vision

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Named Entity Recognition for Protecting Sensitive Data using Hybrid CNN

Named Entity Recognition for Protecting Sensitive Data using...

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International Conference on Smart Systems and Inventive Technology (ICSSIT)

作者： Sheela Gowr. P Kumar. N Department of Computer science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India

Named entity recognition is a natural language processing technique that effectively recognizes and categorizes named entities in a document. The named entity recognition helps to bring out dynamic information about a document or gather critical data to store in a database. Deep learning helps to develop over time, while NLP examines the structure and standards of language and produces an automated system that can discern meaning from text. Mining the essential entities in a text helps identify related data, which is vital when functioning with enormous datasets. The proposed system has a feature that can retrieve and identify sensitive data such as PAN numbers, bank account numbers, and Aadhar numbers from unstructured text data.. The proposed model is designed using Hybrid CNN and it attains 95% F1-Score, 97.5% precision, and 98.3% recall.

关键词： Deep learning Training Radio frequency Databases Data security Forestry Predictive models

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A Social Network Approach to Analyzing Token Properties and Abnormal Events in Decentralized Exchanges

arXiv

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arXiv 2023年

作者： Mohammadi, Aryan Soltani Karami, Moein Motamed, Amir Pasha Bahrak, Behnam School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Tehran Institute for Advanced Studies Tehran Iran

The properties of tokens within the Ethereum blockchain, such as their current prices, trade volumes, and potential future values, have been the subjects of numerous studies. Employing social networks and graphs, as powerful tools for modeling connections within groups or communities would provide valuable guidance for analyzing these properties. This study mainly focuses on creating and examining networks related to two major decentralized exchanges including Uniswap Version 2 (UniswapV2) [1] and SushiSwap [2]. We have discovered that the distribution of nodes’ degrees follows a power law that makes them scale-free networks, in addition, the centrality of tokens in exchange graphs provides valuable insights into their price and significance in cryptocurrency markets. These measures of centrality can be used to detect anomalies in cryptocurrency markets and prices. Notably, these networks exhibit remarkably similar structures, hinting at exciting research opportunities for modeling such networks. Copyright © 2023, The Authors. All rights reserved.

关键词： Blockchain

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A Robotic Arm Vehicle using Voice Recognition for Physically Challenged People

A Robotic Arm Vehicle using Voice Recognition for Physically...

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Advances in Computation, Communication and Information Technology (ICAICCIT), International Conference on

作者： Jia Nannda Lokareddy Venkanna Dora Tanvi Gupta Aryan Chouhan Anmol Verma Department of Computer Science and Engineering Manav Rachna International Institute of Research and Studies Faridabad India Department of electrical and electronics engineering Manav Rachna International Institute of Research and Studies India

ISBN: (数字)9798331541217

ISBN: (纸本)9798331541224

In Today’s world, all the work is automated by robots. The Robots have become a significant part of today’s world, improving many people’s lives, especially those who are physically challenged. This research paper presents a unique method for helping people with physical disabilities: A robotic arm vehicle using voice recognition for physically challenged people. Two remarkable features of the robot are its design and its adaptability in handling objects accurately. The comparative research demonstrates improved performance, such as faster job completion and increased grasping efficiency, when compared to older methods. Additionally, by integrating AI, the robotic arm gains the flexibility needed to operate in real-world environments. This finding might lead to more autonomous and effective assistive technology for personal support and healthcare applications.

关键词： Microcontrollers Speech recognition Medical services Grasping Assistive technologies Manipulators Information and communication technology Artificial intelligence

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Measurement of Synthetic-Dimension Band Structures in Silicon Coupled Ring Resonators 16

Measurement of Synthetic-Dimension Band Structures in Silico...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Zhang, Ruming Li, Liucun Kamata, Mikiya Baba, Toshihiko Ozawa, Tomoki Ota, Yasutomo Iwamoto, Satoshi Research Center for Advanced Science and Technology The University of Tokyo Tokyo153-8904 Japan Yokohama National University Department of Electrical and Computer Engineering Yokohama240-8501 Japan Advanced Institute for Materials Research Tohoku University Sendai980-8577 Japan Keio University Department of Applied Physics and Physico-Informatics Yokohama223-8533 Japan

We fabricated integrated silicon coupled-ring resonators and measured photonic band structures for synthetic frequency lattices with different configurations. A phase difference between two modulation signals introduc... 详细信息

ISBN: (纸本)9798350372076

关键词： Silicon photonics

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Analysis of Short and Aging Faults in TSVs at the Physical Level with Parametric Variation

Analysis of Short and Aging Faults in TSVs at the Physical L...

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IEEE International Symposium on Quality Electronic Design

作者： Prosen Kirtonia Shelby Williams Prasanna Kawatkar Kasem Khalil Magdy Bayoumi Dept. of Electrical and Computer Engr. University of Louisiana at Lafayette Lafayette LA USA Center for Advanced Computer Studies Univ. of Louisiana at Lafayette Lafayette LA USA Department of Electrical and Computer Engineering Univ. of Mississippi Oxford MS USA

ISBN: (数字)9798331509422

ISBN: (纸本)9798331509439

The importance of using chiplets and 3D ICs is growing rapidly, driven by the slowing of Moore's Law and the benefits they offer. advanced packaging of chiplets, and interconnects in 3D ICs are crucial for enhancing computing performance and power efficiency. Hence, Through-Silicon Vias (TSVs) serve as prominent vertical conduits to ensure efficient chip-to-chip communication. The primary objective of this work is to model TSV faults at the material level to observe transmission performance deviations alongside other parametric analyses. We employ Ansys High-Frequency Structure Simulator (HFSS) to design the TSV at the physical level. The reflection coefficient is measured over a 0.1-30 GHz frequency band to observe −15 dB bandwidth for a wide range of lengths $(30-200 \mu m)$ , radius $(4-50 \mu m)$ , and insulator thickness $(0.2-1.5 \mu m)$ , considering distinct densities. Furthermore, a crack of $5-15 \mu m$ is introduced in the dielectric layer to implement a short fault, and copper conductance is reduced by 5-30% for different stages of aging faults to evaluate anomalies. Finally, multiple TSVs are incorporated into the design to assess near-end and far-end cross-talk at 15 and $30 \mu m$ pitch. Therefore, before developing an equivalent R-L-C circuit for fault detection, it is essential to investigate functionality and faults at the physical level for a more comprehensive understanding.

关键词： Semiconductor device modeling Semiconductor device measurement Three-dimensional displays Chiplets Aging Frequency measurement Reflection coefficient Circuit faults Through-silicon vias Thickness measurement

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