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10th International Symposium on Applied Computing for Software and Smart systems, ACSS 2023

作者： Chakraborty, Sumit Bhattacharyya, Riddhasree Chakraborty, Maumita Pal, Rajat Kumar Department of Computer Science Ramsaday College Howrah Amta711401 India Department of Computer Science and Engineering University of Calcutta JD-2 Sector III Salt Lake Kolkata700106 India Department of Computer Science and Technology University of Engineering and Management Kolkata New Town Kolkata700160 India

ISBN: (纸本)9789819977826

Enumeration of rooted trees is a major area of research in computer science and mathematics. Rooted ordered trees are used to solve combinatorial optimization problems, analyze the structure of chemical compounds, and many others. Several researchers from different continents have given different algorithms for generating rooted ordered trees. Different encodings have been used to represent the rooted ordered trees by these researchers. We have introduced the children sequence to represent each rooted ordered tree. In this paper, our proposed algorithm, All-Ordered-Trees, uses an efficient algebraic approach to generate all the children sequences (representing rooted ordered trees) in lexicographic order for a given number of vertices, n. With slight modification, this algorithm can also be used to generate degree-bound rooted ordered trees. We have also implemented three existing algorithms in this domain and included the experimental results of these algorithms with the experimental results of our proposed algorithm for comparative study. From the experimental results, we observe that each tree can be generated in approximately constant time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Trees (mathematics)

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Full-Duplex Millimeter Wave MIMO Channel Estimation: A Neural Network Approach

IEEE Transactions on Machine Learning in Communications and ...

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IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 1093-1108页

作者： Sattari, Mehdi Guo, Hao Gündüz, Deniz Panahi, Ashkan Svensson, Tommy Chalmers University of Technology Department of Electrical Engineering Gothenburg412 96 Sweden New York University Tandon School of Engineering Electrical and Computer Engineering Department BrooklynNY11201 United States Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2BX United Kingdom Chalmers University of Technology Department of Computer Science Gothenburg412 96 Sweden

Millimeter wave (mmWave) multiple-input-multi-output (MIMO) is now a reality with great potential for further improvement. We study full-duplex transmissions as an effective way to improve mmWave MIMO systems. Compared to half-duplex systems, full-duplex transmissions may offer higher data rates and lower latency. However, full-duplex transmission is hindered by self-interference (SI) at the receive antennas, and SI channel estimation becomes a crucial step to make the full-duplex systems feasible. In this paper, we address the problem of channel estimation in full-duplex mmWave MIMO systems using neural networks (NNs). Our approach involves sharing pilot resources between user equipments (UEs) and transmit antennas at the base station (BS), aiming to reduce the pilot overhead in full-duplex systems and to achieve a comparable level to that of a half-duplex system. Additionally, in the case of separate antenna configurations in a full-duplex BS, providing channel estimates of transmit antenna (TX) arrays to the downlink UEs poses another challenge, as the TX arrays are not capable of receiving pilot signals. To address this, we employ an NN to map the channel from the downlink UEs to the receive antenna (RX) arrays to the channel from the TX arrays to the downlink UEs. We further elaborate on how NNs perform the estimation with different architectures, (e.g., different numbers of hidden layers), the introduction of non-linear distortion (e.g., with a 1-bit analog-to-digital converter (ADC)), and different channel conditions (e.g., low-correlated and high-correlated channels). Our work provides novel insights into NN-based channel estimators. © 2023 CCBY.

关键词： Millimeter waves

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Guest Editorial: AutoML for Nonstationary Data

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2456-2457页

作者： Cheng, Ran Escalante, Hugo Jair Tu, Wei-Wei Rijn, Jan N. Van Wang, Shuo Yang, Yun Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China Instituto Nacional de Astrofísica Óptica y Electrónica Computer Science Department Puebla72840 Mexico 4Paradigm Inc. Beijing100089 China RA Leiden2300 Netherlands The University of Birmingham School of Computer Science BirminghamB15 2TT United Kingdom Yunnan University National Pilot School of Software Kunming650504 China

The five papers in this special section address different aspects of automated machine learning (AutoML) from fundamental algorithms to real-world applications. Developing high-performance machine learning models is a difficult task that usually requires expertise from data scientists and knowledge from domain experts. To make machine learning more accessible and ease the labor-intensive trial-and-error process of searching for the most appropriate machine learning algorithm and the optimal hyperparameter setting, AutoML was developed and has become a rapidly growing area in recent years. AutoML aims at automation and efficiency of the machine learning process across domains and applications. Nowadays, data is commonly collected over time and susceptible to changes, such as in Internet-of-Things (IoT) systems, mobile phone applications and healthcare data analysis. It poses new challenges to the traditional AutoML with the assumption of data stationarity. Interesting research questions arise around whether, when and how to effectively and efficiently deal with non-stationary data in AutoML. © 2020 IEEE.

关键词： Machine learning

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Advanced BERT and CNN-Based Computational Model for Phishing Detection in Enterprise Systems

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computer Modeling in engineering & sciences 2024年第12期141卷 2165-2183页

作者： Brij B.Gupta Akshat Gaurav Varsha Arya Razaz Waheeb Attar Shavi Bansal Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Business Administration Asia UniversityTaichung413Taiwan Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon College of Business Administration Management DepartmentPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Research and Innovation Insights2TechinfoJaipur302001India Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Electronic Engineering and Computer Science Hong Kong Metropolitan University(HKMU)Hong Kong518031China

Phishing attacks present a serious threat to enterprise systems,requiring advanced detection techniques to protect sensitive *** study introduces a phishing email detection framework that combines Bidirectional Encoder Representations from Transformers(BERT)for feature extraction and CNN for classification,specifically designed for enterprise information ***’s linguistic capabilities are used to extract key features from email content,which are then processed by a convolutional neural network(CNN)model optimized for phishing *** an accuracy of 97.5%,our proposed model demonstrates strong proficiency in identifying phishing *** approach represents a significant advancement in applying deep learning to cybersecurity,setting a new benchmark for email security by effectively addressing the increasing complexity of phishing attacks.

关键词： Phishing BERT convolutional neural networks email security deep learning

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CoViT-Net: A Pre-trained Hybrid Vision Transformer for COVID-19 Detection in CT-Scans 4th

CoViT-Net: A Pre-trained Hybrid Vision Transformer for COVID...

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4th International Conference on Frontiers in Computing and Systems, COMSYS 2023

作者： Das, Ankit Banik, Debapriya Roy, Kaushiki Chan, Gordon K. Bhattacharjee, Debotosh Department of Computer Science and Engineering Amity University Kolkata700135 India Department of Computer Science and Engineering ICFAI University Tripura799210 India Institute of Engineering and Management Kolkata700091 India University of Engineering and Management Kolkata700160 India Department of Oncology and the Department of Experimental Oncology Cross Cancer Institute University of Alberta EdmontonABT6G 1Z2 Canada Department of Computer Science and Engineering Jadavpur University Kolkata700032 India

ISBN: (纸本)9789819726103

The coronavirus disease, COVID-19, that grasped the earth since 2019, has taken a serious toll on humanity. COVID-19 cases were spiking exponentially in densely populated regions, and the health infrastructure was challenged daily. As such, Artificial Intelligence (AI) had to step in to improvise medical imaging applications. One such use case was the classification of computerized Tomography (CT) Scan images into COVID-infected and un-infected categories. Thus it would effectively classify a patient being either COVID Positive or Negative. computer Vision (CV) algorithms manifest the potential to solve such image classification problems. In retrospect, deep learning-based architectures have been very productive. However, Vision Transformers (ViT) have taken over CV since its inception. In this study, we propose CoViT-Net: A pre-trained hybrid Vision Transformer architecture for detecting COVID-19 in CT scan images. Our proposed CoViT-Net has a unique architecture incorporating a ViT-S/16 feature extractor, pre-trained on the ImageNet21k dataset, and a modified MLP block with dense layers on top. CoViT-Net has thereby achieved a state-of-the-art accuracy score of 0.9638. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： COVID-19

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Decentralized Federated Graph Learning with Lightweight Zero Trust Architecture for Next-Generation Networking Security

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IEEE Journal on Selected Areas in Communications 2025年第6期43卷 1908-1922页

作者： Zhou, Xiaokang Liang, Wei Wang, Kevin I-Kai Yada, Katsutoshi Yang, Laurence T. Ma, Jianhua Jin, Qun Kansai University Faculty of Business Data Science Osaka565-0823 Japan RIKEN Center for Advanced Intelligence Project RIKEN Tokyo103-0027 Japan Hunan University of Technology and Business School of Computer Science Changsha410205 China Xiangjiang Laboratory Changsha410205 China The University of Auckland Department of Electrical Computer and Software Engineering Auckland1010 New Zealand St. Francis Xavier University Department of Computer Science AntigonishNSB2G 2W5 Canada Hosei University Faculty of Computer and Information Sciences Chiyoda-ku102-8160 Japan Waseda University Faculty of Human Sciences Tokorozawa359-1192 Japan

The rapid development and usage of digital technologies in modern intelligent systems and applications bring critical challenges on data security and privacy. It is essential to allow cross-organizational data sharing to achieve smart service provisioning, while preventing unauthorized access and data leak to ensure end users' efficient and secure collaborations. Federated Learning (FL) offers a promising pathway to enable innovative collaboration across multiple organizations. However, more stringent security policies are needed to ensure authenticity of participating entities, safeguard data during communication, and prevent malicious activities. In this paper, we propose a Decentralized Federated Graph Learning (FGL) with Lightweight Zero Trust Architecture (ZTA) model, named DFGL-LZTA, to provide context-aware security with dynamic defense policy update, while maintaining computational and communication efficiency in resource-constrained environments, for highly distributed and heterogeneous systems in next-generation networking. Specifically, with a re-designed lightweight ZTA, which leverages adaptive privacy preservation and reputation-based aggregation together to tackle multi-level security threats (e.g., data-level, model-level, and identity-level attacks), a Proximal Policy Optimization (PPO) based Deep Reinforcement Learning (DRL) agent is introduced to enable the real-time and adaptive security policy update and optimization based on contextual features. A hierarchical Graph Attention Network (GAT) mechanism is then improved and applied to facilitate the dynamic subgraph learning in local training with a layer-wise architecture, while a so-called sparse global aggregation scheme is developed to balance the communication efficiency and model robustness in a P2P manner. Experiments and evaluations conducted based on two open-source datasets and one synthetic dataset demonstrate the usefulness of our proposed model in terms of training performance, computa

关键词： Federated learning

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VLSI-Implementation-Based Fast Symbol Detector for PQSM MIMO Systems

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Journal of Signal Processing Systems 2024年第8期96卷 415-429页

作者： Lu, Hoang-Yang Yen, Mao-Hsu Li, Yi-Jang Li, Guang-Yan Department of Electrical Engineering National Taiwan Ocean University Taiwan R.O.C. No.2 Beining Rd Keelung202301 Taiwan Department of Computer Science and Engineering National Taiwan Ocean University Taiwan R.O.C. No.2 Beining Rd Keelung202301 Taiwan

Parallel quadrature spatial modulation (PQSM) multiple-input multiple-output (MIMO) technology is a variant of spatial modulation (SM) technology and has shown significant performance gain. However, few low-complexity detection algorithms with optimal or near-optimal performance have been proposed. In this paper, a near-optimal fast detection scheme is presented along with a corresponding hardware architecture. The proposed algorithm first uses the features of PQSM MIMO systems to further merge the channel matrices of transmit antenna combinations (TACs) into corresponding smaller matrices. Then, the remaining steps of the proposed algorithm include conducting Givens rotations (GRs) to QR decompose the merged matrices, sorting and selecting TAC candidates with higher transmission possibilities for complexity reduction, performing symbol estimation for each TAC candidate, and computing Euclidean distances (EDs) to find the final solution. Based on the steps of the proposed algorithm, five corresponding pipeline architectures are designed for a PQSM MIMO system with four transmit antennas, four receive antennas, and 16-QAM symbol modulation. Finally, the results of simulations, complexity analysis, and hardware implementation show that the proposed detector can provide a near-optimal bit error rate performance as well as a high throughput rate, but with lower complexity. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Bit error rate

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The Low-Attenuation Endfire Leaky-Wave State on an Optically Transparent Lossy Film

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engineering 2024年第12期43卷 72-80页

作者： Ziheng Zhou Yongjian Zhang Yilin Zheng Ke Chen Yueming Gao Yuehe Ge Yue Li Yijun Feng Zhizhang(David)Chen College of Physics and Information Engineering Fuzhou UniversityFuzhou 350108China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China School of Electronic and Information Engineering Soochow UniversitySoochow 215006China School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China Department of Electrical and Computer Engineering Dalhousie UniversityHalifaxNS B3H 4R2Canada

The development of high-performance optically transparent radio frequency(RF)radiators is limited by the intrinsic loss issue of transparent conductive films(TCFs).Instead of pursuing expensive endeavors to improve the TCFs'electrical properties,this study introduces an innovative approach that leverages leaky-wave mode manipulation to mitigate the TCFs'attenuating effect and maximize the RF *** finding reveals that the precise control of the mode confinement on glass-coated TCFs can create a low-attenuation window for leaky-wave propagation,where the total attenuation caused by TCF dissipation and wave leakage is effectively *** observed low-attenuation leaky-wave state on lossy TCFs originates from the delicate balance between wave leakage and TCF dissipation,attained at a particular glass cladding *** leveraging the substantially extended radiation aperture achieved under suppressed wave attenuation,this study develops an optically transparent antenna with an enhanced endfire realized gain exceeding 15 dBi and a radiation efficiency of 66%,which is validated to offer competitive transmission performance for advancing ubiquitous wireless communication and sensing applications.

关键词： Antennas Endfire radiation Low attenuation Material losses Transparent conductive films

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Online Simulator-Based Experimental Design for Cognitive Model Selection

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Computational Brain and Behavior 2023年第4期6卷 719-737页

作者： Aushev, Alexander Putkonen, Aini Clarté, Grégoire Chandramouli, Suyog Acerbi, Luigi Kaski, Samuel Howes, Andrew Department of Computer Science Aalto University Espoo 02150 Finland Department of Information and Communications Engineering Aalto University Espoo 02150 Finland Department of Computer Science University of Helsinki Helsinki 00560 Finland Department of Computer Science University of Manchester Manchester M13 9PR United Kingdom School of Computer Science University of Birmingham Birmingham B15 2TT United Kingdom

The problem of model selection with a limited number of experimental trials has received considerable attention in cognitive science, where the role of experiments is to discriminate between theories expressed as computational models. Research on this subject has mostly been restricted to optimal experiment design with analytically tractable models. However, cognitive models of increasing complexity with intractable likelihoods are becoming more commonplace. In this paper, we propose BOSMOS, an approach to experimental design that can select between computational models without tractable likelihoods. It does so in a data-efficient manner by sequentially and adaptively generating informative experiments. In contrast to previous approaches, we introduce a novel simulator-based utility objective for design selection and a new approximation of the model likelihood for model selection. In simulated experiments, we demonstrate that the proposed BOSMOS technique can accurately select models in up to two orders of magnitude less time than existing LFI alternatives for three cognitive science tasks: memory retention, sequential signal detection, and risky choice. © 2023, The Author(s).

关键词： Cognitive models Experimental design Likelihood-free inference Model selection

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A Truly Decentralized Blockchain Consensus Protocol that Avoids Concentration of Power 17

A Truly Decentralized Blockchain Consensus Protocol that Avo...

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17th IEEE International Conference on Industrial and Information Systems, ICIIS 2023

作者： Wimal, Kesara Liyanage, Geethapriya School of Computer Science and Engineering University of Westminster LondonW1B 2HW United Kingdom Department of Computer Science and Engineering University of Moratuwa Moratuwa10400 Sri Lanka

ISBN: (纸本)9798350323634

A consensus protocol plays a vital role in any blockchain platform by ensuring all components agree on common data values and follow the same course of action, even in the presence of defective components. This research project has discovered a problem associated with contemporary blockchain consensus protocols, which has an impact on both users of blockchain technology and investors in cryptocurrencies. The question of whether current blockchain platforms are truly decentralized has been raised by the blockchain community over a period of time. The most popular blockchains use Proof of Work (PoW), Proof of Stake (PoS), or a combination of both, but both systems have limitations in terms of decentralization. Several alternative consensus protocols have emerged recently, but none have achieved total decentralization or welcomed any level user to be the next miner or forger. Therefore, true decentralization of a blockchain system is more challenging as most of the popular consensus protocols were invented to accommodate decentralization but eventually, driven by the centralization of power. This paper proposes a truly decentralized consensus protocol that is capable of avoiding the centralization of power even in the future regardless of the number of peers. The protocol also makes sure it avoids the use of specialized hardware resources, decreases the level of energy consumption, and encourages network activities. Additionally, the novel consensus protocol offers a more democratic and fair approach to blockchain consensus. © 2023 IEEE.

关键词： Blockchain

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