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Hybrid Precoder Design for Angle-of-Departure Estimation with Limited-Resolution Phase Shifters

IEEE Transactions on Communications 2024年第6期73卷 4439-4453页

作者： Huang, Huiping Keskin, Musa Furkan Wymeersch, Henk Cai, Xuesong Wu, Linlong Thunberg, Johan Tufvesson, Fredrik Chalmers University of Technology Department of Electrical Engineering Gothenburg41296 Sweden Lund University Department of Electrical and Information Technology Lund22100 Sweden Luxembourg1855 Luxembourg

Hybrid analog-digital beamforming stands out as a key enabler for future communication systems with a massive number of antennas. In this paper, we investigate the hybrid precoder design problem for angle-of-departure (AoD) estimation, where we take into account the practical constraint on the limited resolution of phase shifters. Our goal is to design a radio-frequency (RF) precoder and a base-band (BB) precoder to estimate AoD of the user with high accuracy. To this end, we propose a two-step strategy where we first obtain the fully digital precoder that minimizes the angle error bound, and then the resulting digital precoder is decomposed into an RF precoder and a BB precoder, based on the alternating optimization and the alternating direction method of multipliers. Furthermore, we derive the quantization error upper bound and provide convergence conditions for the proposed algorithm. Numerical results demonstrate the superior performance of the proposed method over state-of-the-art baselines. © 1972-2012 IEEE.

关键词： Beamforming

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Detection of Conspiracy vs. Critical Narratives and Their Elements using NLP 25

Detection of Conspiracy vs. Critical Narratives and Their El...

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25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024

作者： Albladi, Aish Seals, Cheryl D. Department of Computer Science and Software Engineering Auburn University AuburnAL United States

The growing use of digital media or social media has given a platform to the people to deliver their ideas and viewpoints openly. It is facilitating the rapid spread of contrasting opinions openly. Ultimately, this has developed echo chambers or polarized platforms. These platforms either encourage conspiracy theories or critical narratives. So, nowadays, it has become crucial for people to be aware of being part of such narratives. Moreover, it is also necessary for the organisations to identify the conspiracy creators or the ones who do not possess a conspiracy mentality. This can be made possible by the use of natural language processing techniques to do this task automatically. This study presents the solutions to the two most pressing challenges in today's era. The subtask one of this study provides a solution for the identification of conspiracy narratives and critical narratives using the BERT model. Our model achieved an MCC score of 0.80. Secondly, the other subtask helps to recognize the span of the topic relevant to the important constituents of both categories of oppositional narratives, i.e., agent, facilitator, victim, campaigner, objective, negative effect. The overall accuracy of the model is 95%. These models can be used for the development of an algorithm that can automatically classify the conspiracy theories and critical narratives. © 2024 Copyright for this paper by its authors.

关键词： Social networking (online)

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Utilization of Cupola Slag as Fine Aggregates in Green Concrete 2nd

Utilization of Cupola Slag as Fine Aggregates in Green Concr...

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2nd International Conference on Mechanical engineering, INCOM 2024

作者： Sikder, Rakesh Chakravarty, Soumyabrata Sau, Debasis Haldar, Partha Mandal, Saroj Nandi, Titas Sutradhar, Goutam Department of Mechanical Engineering Jadavpur University Kolkata India Department of Civil Engineering Jadavpur University Kolkata India Department of Mechanical Engineering Government College of Engineering and Ceramic Technology Kolkata India National Institute of Technology Jamshedpur Jamshedpur India

ISBN: (纸本)9789819766666

Cupola slag, a by-product of manufacturing operations, is derived from the cupola furnace, a staple in the casting industry utilized for melting metals. This waste material comprises residues and impurities extracted during metal melting processes within the cupola furnace. Traditionally, cupola slag was viewed solely as a disposal burden, relegated to landfills without consideration for its potential value. However, a notable shift has occurred in recent years, marked by a burgeoning interest in researching and implementing innovative strategies for repurposing industrial waste materials like cupola slag. This renewed focus stems from a collective recognition of the environmental repercussions associated with conventional waste disposal methods, coupled with a growing imperative for sustainable practices and resource conservation. The partial replacement of fine aggregate with cupola slag (CS) is an effective approach for improving concrete properties. Within M20 grade concrete, the substitution is carried out in 10-weight-percent increments ranging from 0 to 60%. This substitution is carried out with a consistent water-cement ratio. The step-by-step replacement provides valuable insights into the impact of CS on concrete mix performance across a range of proportions, allowing for a comprehensive assessment of its effects on various properties. As the percentage of cupola slag-based aggregate increased, there was a corresponding decrease in the slump of the concrete. The mechanical characteristics exhibited by the concrete were thoroughly examined during 7 and 28 days of water curing. Notably, it was observed that achieving the target strength for M20 grade concrete was successful with a 50% replacement of CS for fine aggregates. Consequently, the application of CS as a fine aggregate in concrete appears promising, offering the potential to mitigate environmental impact and contribute to efforts in addressing global warming. © The Author(s), under exclusive license

关键词： Slags

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Recent Progress and New Horizons in Emerging Novel MXene-Based Materials for Energy Storage Applications for Current Environmental Remediation and Energy Crises

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Electrochemical Energy Reviews 2024年第1期7卷 700-786页

作者： Karim Khan Ayesha Khan Tareen Muhammad Iqbal Ye Zhang Asif Mahmood Nasir mahmood Zhe Shi Chunyang Ma J.R.Rosin Han Zhang Additive Manufacturing Institute Shenzhen UniversityShenzhen 518060GuangdongChina School of Mechanical Engineering Dongguan University of TechnologyDongguan 523808GuangdongChina Shenzhen Engineering Laboratory of Phosphorene and Optoelectronics International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology of Ministry of EducationInstitute of Microscale OptoelectronicsEngineeringShenzhen UniversityShenzhen 518060GuangdongChina Department of Bio‑Chemistry Quaid-I-Azam UniversityIslamabad 45320Pakistan School of Chemistry and Chemical Engineering University of South ChinaHengyang 421001HunanChina School of Chemical and Biomolecular Engineering The University of SydneySydneyNSW 2006Australia School of Science The Royal Melbourne Institute of Technology UniversityMelbourneVIC 3000Australia Department of Mechanical Engineering City University of Hong Kong83 Tat Chee AvenueKowloonHong KongChina

Unsustainable fossil fuel energy usage and its environmental impacts are the most significant scientific challenges in the scientific ***-dimensional(2D)materials have received a lot of attention recently because of their great potential for application in addressing some of society’s most enduring issues with renewable *** metal-based nitrides,carbides,or carbonitrides,known as“MXenes”,are a relatively new and large family of 2D *** the discovery of the first MXene,Ti_(3)C_(2) in 2011 has become one of the fastest-expanding families of 2D materials with unique physiochemical *** surface terminations with hydroxyl,oxygen,fluorine,etc.,are invariably present in the so far reported materials,imparting hydrophilicity to their *** current finding of multi-transition metal-layered MXenes with controlled surface termination capacity opens the door to fabricating unique structures for producing renewable *** NMs-based flexible chemistry allows them to be tuned for energy-producing/storage,electromagnetic interference shielding,gas/biosensors,water distillation,nanocomposite reinforcement,lubrication,and photo/electro/chemical *** review will first discuss the advancement of MXenes synthesis methods,their properties/stability,and renewable energy ***,we will highlight the constraints and challenges that impede the scientific community from synthesizing functional MXene with controlled composition and *** will further reveal the high-tech implementations for renewable energy storage applications along with future challenges and their solutions.

关键词： Recent development in synthesis Structures Properties of MXenes nanomaterials Propose approaches of diverse MXene-based nanoplatforms MXenes for renewable energy applications Optimization strategies and mechanisms to enhance MXenes compatibility Current challenges and probable progress for MXenes in renewable energy applications

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NeurDB: an AI-powered autonomous data system

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Science China(Information Sciences) 2024年第10期67卷 129-150页

作者： Beng Chin OOI Shaofeng CAI Gang CHEN Yanyan SHEN Kian-Lee TAN Yuncheng WU Xiaokui XIAO Naili XING Cong YUE Lingze ZENG Meihui ZHANG Zhanhao ZHAO School of Computing National University of Singapore College of Computer Science and Technology Zhejiang University Department of Computer Science and Engineering Shanghai Jiao Tong University School of Information Renmin University of China School of Computer Science and Technology Beijing Institute of Technology

In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and selfdriving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.

关键词： AI$\times$DB in-database AI intelligent data system

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Earthquake response evaluation of cylindrical latticed roofs supported by BRBs: Comparison of responses based on Chinese codes and Japanese regulations

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International Journal of Space Structures 2024年第1期39卷 21-35页

作者： Takiuchi, Yuji Kato, Shiro Nakazawa, Shoji Niho, Yutaka Department of Architecture and Civil Engineering Toyohashi University of Technology Toyohashi Japan Kure College Kure Japan

The present study investigates the effectiveness of design strategies that induce yielding in the substructure of a single-layer latticed roof. The roof has a span of 28.9 m and a half-open angle of 30°. It is supported by a ductile substructure consisting of buckling-restrained braces (BRBs), and the substructure is designed to initiate yielding under a base shear coefficient of 0.40. The responses are analyzed using artificial earthquake motions corresponding to Chinese and Japanese design acceleration response spectra. The responses demonstrated that the dynamic amplification within the roof is considerably suppressed in comparison with a roof supported by elastic substructures. The negligible variance in the roof responses to the Japanese and Chinese spectra is also illustrated, suggesting the potential for reciprocal applicability of research results. © The Author(s) 2024.

关键词： Roofs

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Human Hand Gesture Classification Based on Surface Electromyography Signals by Using a Vector–Kernel Convolutional Takagi–Sugeno–Kang Neuro-fuzzy Classifier

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Sensors and Materials 2024年第2-3期36卷 623-637页

作者： Lin, Cheng-Jian Lin, Chun-Jung Lin, Xin-Wei Department of Computer Science & Information Engineering National Chin-Yi University of Technology Taichung411 Taiwan

Muscle–computer interfaces are devices that can identify the meaning of human bioelectrical signals, such as surface electromyography (sEMG) signals. sEMG signals can be obtained from arm-worn sensors and can be used to classify human gestures. In this paper, we propose a vector–kernel convolutional Takagi–Sugeno–Kang (TSK)-type neuro-fuzzy classifier (VK-CTNFC) to recognize human gestures represented by sEMG signals. First, vector–kernel convolution is used to extract the features of sEMG signals;this modification reduces the model parameters by half and increases the classification accuracy compared with those achieved with a conventional convolutional kernel. Second, the global average pooling method is used instead of the flattening method to improve feature fusion performance. Finally, a TSK-type neuro-fuzzy network is used for gesture classification. The publicly available dataset Ninapro DB1 was used in experiments for verifying the performance of the proposed VK-CTNFC. Data preprocessing was performed by wavelet denoising to smooth the sEMG waveform, and fast Fourier transform was used to convert time-domain sEMG signals into frequency-domain signals. Finally, the processed sEMG signals were input into the VK-CTNFC for training. The experimental results indicate that the proposed VK-CTNFC has an average accuracy of 87.18% and outperforms other reported methods. © MYU K.K.

关键词： Fast Fourier transforms

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Hyperspectral Target Detection-Based 2-D-3-D Parallel Convolutional Neural Networks for Hyperspectral Image Classification

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2024年 17卷 9451-9469页

作者： Chen, Shih-Yu Hsu, Kai-Hsun Kuo, Tzu-Hsien National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Yunlin64002 Taiwan

This article presents a novel hyperspectral target detection (HTD) based two-dimensional (2-D)-three-dimensional (3-D) parallel convolutional neural network (HTD 2D-3D-PCNN) model, which integrates the HTD technique to achieve outstanding performance in hyperspectral image classification. The proposed model effectively leverages both spectral and spatial information through a dual-branch architecture in hyperspectral imaging. In the first branch, HTD is utilized to enhance the spectral features of targets of interest, while suppressing background. The resulting enhanced image is then inputted to a 2D-CNN, augmented with an additional deconvolution layer to highlight spatial characteristics. Concurrently, the second branch employs dimensionality reduction via principal component analysis, and a 3D-CNN is employed to capture both spectral and spatial attributes. Subsequently, the feature maps from both convolutional neural networks (CNNs) are combined and processed through fully connected layers for classification. To validate the effectiveness of the proposed HTD-2D-3D-PCNN, extensive experiments are conducted on five widely used hyperspectral public datasets (Indian Pines, Pavia university, Salinas Scene, Kennedy Space Center, and Botswana) with a consistent training sample ratio of either 10% or 5%. The results show that HTD-2D-3D-PCNN can achieve overall accuracy values of 98.41%, 99.85%, 99.92%, 99.82%, and 98.82% for the respective datasets, surpassing the performance of recent methodologies. © 2008-2012 IEEE.

关键词： Image classification

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Accelerated Peridynamic Computation on GPU for Quasi-static Fracture Simulations

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Journal of Peridynamics and Nonlocal Modeling 2024年第1期6卷 206-229页

作者： Zhong, Jiandong Han, Fei Zhang, Ling Department of Engineering Mechanics Dalian University of Technology Dalian 116023 China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Dalian University of Technology Dalian 116023 China

Due to the adoption of integral equations instead of partial differential equations to describe the deformations of materials, the peridynamics has advantages in dealing with fracture problems. However, the non-local effect of peridynamics brings too much computation cost to make large-scale engineering applications challenging. In this paper, a parallel algorithm in the Compute Unified Device Architecture (CUDA) framework is presented to speed up the computational process of a peridynamic model for quasistatic fracture simulations on GPU, in which the peridynamic model is numerically implemented by the peridynamics-based finite element method (PeriFEM) [1]. The parallel algorithm makes crack simulations by the pure peridynamics with millions of degrees of freedom possible with one GPU. To validate the accuracy and efficiency of the parallel algorithm based on PeriFEM, several numerical benchmarks are performed, and the results are compared with those obtained by the finite element method (FEM) and the serial algorithm. The results of the comparison show that the presented parallel algorithm is effective and efficient. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Crack simulation CUDA Finite element method Parallel computing Peridynamic

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Proposed AES-based Obfuscation and Encryption Model for Cloud Data Security 1

Proposed AES-based Obfuscation and Encryption Model for Clou...

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1st International Conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Singh, Prabhdeep Singh, Pawan Agarwal, Abhay Kumar Kumar, Anil Amity School of Engineering and Technology Department of Computer Science and Engineering Lucknow India Kamla Nehru Institute of Technology Department of Computer Science and Engineering Sultanpur India Amity University Amity School of Engineering and Technology Lucknow India

ISBN: (纸本)9798331529246

Cloud Computing (CC) offers a diverse range of services along with huge data storage across a network. CC has collaborated with varied emerging technologies like IoT because of its numerous advantages. Despite CC's benefits, cloud-based servers are not always trustworthy in real-world scenarios. Users' privacy will be compromised if they send their data straight to cloud platforms since crucial information will be exposed to cloud servers. Thereby, this work develops a data security model in the cloud with two stages, proposed secured data storage and proxy re-encryption. Initially, the data is stored securely in the cloud based on improved AES-based encryption as well as obfuscation-based encryption. Based on the request from the data user, proxy re-encryption is done using Kronecker product-based encryption. The enhanced AES achieved the lowest value of 0.025 for the CCA attack with a key size of 128 bits. Thus, the final encoded key is obtained. © 2025 IEEE.

关键词： Cloud platforms

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