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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Du, Zhen Liu, Fan Xiong, Yifeng Han, Tony Xiao Yuan, Weijie Cui, Yuanhao Yao, Changhua Eldar, Yonina C. School of Electronic and Information Engineering Nanjing University of Information Science & Technology Nanjing China Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen China School of Information and Electronic Engineering Beijing University of Posts and Telecommunications Beijing China Huawei Technologies Ltd. Shenzhen China Weizmann Institute of Science Faculty of Mathematics and Computer Science Rehovot Israel

ISBN: (纸本)9798350370218

Integrated Sensing and Communications (ISAC) has garnered significant attention as a promising technology for the upcoming sixth-generation wireless communication systems (6G). In pursuit of this goal, a common strategy is that a unified waveform, such as Orthogonal Frequency Division Multiplexing (OFDM), should serve dual-functional roles by enabling simultaneous sensing and communications (S&C) operations. However, the sensing performance of an OFDM communication signal is substantially affected by the randomness of the data symbols mapped from bit streams. Therefore, achieving a balance between preserving communication capability (i.e., the randomness) while improving sensing performance remains a challenging task. To cope with this issue, in this paper we analyze the ambiguity function of the OFDM communication signal modulated by random data. Subsequently, a probabilistic constellation shaping (PCS) method is proposed to devise the probability distributions of constellation points, which is able to strike a scalable S&C tradeoff of the random transmitted signal. Finally, the superiority of the proposed PCS method over conventional uniformly distributed constellations is validated through numerical simulations. © 2023 IEEE.

关键词： ambiguity function ISAC OFDM PCS

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Visual Analytics of Streaming Data in Concept Drift Detection

Visual Analytics of Streaming Data in Concept Drift Detectio...

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Electrical, electronic and Computing engineering (IcETRAN), International Conference on

作者： Aleksandra Stojnev Ilic Dragan Stojanovic dept. Computer Science Faculty of Electronic engineering University of Nis Nis Serbia

ISBN: (数字)9798350386998

ISBN: (纸本)9798350387001

Recent developments in sensor technology have enabled real-time data acquisition, high-frequency and multimodal data capturing thus underlying the need for monitoring physical or operational conditions in various aspects of the data. High dimensionality and volume of the data poses significant statistical challenges creating a need for accurate concept drift detection and prompt responses, a task that can be performed either by an algorithm or by human expert. Visual analytics plays a crucial role in concept drift detection by enabling analysts to visually explore, analyze, and interpret complex data streams, facilitating real-time monitoring, decision-making, and communication with stakeholders. This paper examines the usability of radar graphs for concept drift exploration, as well as their usage in other steps of analysis. For the purpose of demonstration, a pipeline for real-time health data analysis is presented and steps are visualized using radar graphs.

关键词： Data analysis Visual analytics Concept drift Pipelines Decision making Radar detection Data visualization

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Machine learning algorithms for surface plasmon resonance bio-detection applications, A short review 5

Machine learning algorithms for surface plasmon resonance bi...

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5th Photonics Meeting 2022, PM 2022

作者： Zain, H.A. Batumalay, M. Harith, Z. Rahim, H.R.A. Harun, S.W. Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Faculty of IT INTI International University Negeri Sembilan Nilai71800 Malaysia Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia

Surface plasmon resonance (SPR) sensors have many applications in detecting toxic gases, water pollutants, and biomarkers of many diseases. Surface plasmon resonance sensors are a good candidate for future sensing platforms due to their high sensitivity and fine resolution. However, the challenges of high cost, cross-sensitivity, and large amount of generated data need to be addressed to unlock surface plasmon resonance potential. Machine learning (ML) algorithms can address these challenges. In this short review, recent studies integrating the algorithms of Artificial Intelligence (AI) and Machine Learning (ML) with (SPR) sensing mechanisms for bio-detection applications are presented here. This short review shows how the integrated approach can help mitigate some of the challenges faced by traditional SPR sensing. © Published under licence by IOP Publishing Ltd.

关键词： Surface plasmon resonance

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Ontology-Based Crime News Semantic Retrieval System

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computers, Materials & Continua 2023年第10期77卷 601-614页

作者： Fiaz Majeed Afzaal Ahmad Muhammad Awais Hassan Muhammad Shafiq Jin-Ghoo Choi Habib Hamam Department of Information Technology University of GujratGujrat50700Pakistan Department of Computer Science University of Engineering&TechnologyLahore54890Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea Faculty of Engineering Uni de MonctonMonctonNB E1A3E9Canada International Institute of Technology and Management Commune d’AkandaBPLibreville1989Gabon School of Electrical Engineering Department of Electrical and Electronic Engineering ScienceUniversity of JohannesburgJohannesburg2006South Africa Spectrum of Knowledge Production&Skills Development Sfax3027Tunisia

Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular *** news exists on the Internet in unstructured formats such as books,websites,documents,and *** such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement ***-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant *** are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given ***,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the *** ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal *** semantic system retrieves information in view of the similarity of the semantics among indexed data and user *** this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two *** the first experiment,we implemented a keyword-based textual IR systemusing Apache *** the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL *** keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.

关键词： Web 3.0 crime ontology semantic web knowledge representation

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Population-Input Memristor Circuit Based on Matrix-Friendly Genetic Algorithm

IEEE Transactions on Circuits and Systems for Artificial Int...

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IEEE Transactions on Circuits and Systems for Artificial Intelligence 2025年第2期2卷 174-182页

作者： Hao Chen Quan Shi Ling Chen Tingwen Huang Chuandong Li College of Electronic and Information Engineering Southwest University Chongqing China Westa College Southwest University Chongqing China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen China

This paper presents the design and implementation of a novel matrix-friendly genetic algorithm (MGA) based population input memristor circuit. Selection, crossover and mutation operations can be efficiently implemented in MGA by utilizing the unique properties of memristors. The proposed circuit performs well in solving binary nonconvex function optimization problems. Through extensive simulations and comparisons with classical optimization algorithms, our method improves about 4.24% on average in exploring the optimal fitness value, which reflects the advantages of the method in finding the optimal solution. In addition, the existence of its function to visualize the image of a one-dimensional function is also found during the experimental process. The proposed circuit has good scalability and flexibility, demonstrating its potential for a wide range of applications in complex optimization tasks.

关键词： Memristors Circuits Genetic algorithms Biological cells Optimization Genetics Parallel processing Logic gates Education Artificial intelligence

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Surface plasmon resonance sensor for food safety 5

Surface plasmon resonance sensor for food safety

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5th Photonics Meeting 2022, PM 2022

Surface plasmon resonance sensors have numerous applications in the discovery of poisonous gasses, water toxins, and the biomarkers of numerous infections. Surface plasmon sensors are a great candidate for future detecting stages due to their high sensitivity and fine resolution. A surface plasmon resonance sensor is also built for food safety using a Kretschmann setup with a gold coated prism. The setup was used to detect the analyte solution with concentrations 0%-3%. The sensor showed a good response and stability. © Published under licence by IOP Publishing Ltd.

关键词： Food safety

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Terahertz Multiple Vortex Beams Generation Based On Graphene Metasurface

Terahertz Multiple Vortex Beams Generation Based On Graphene...

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National Conference on Radio Science (NSRC)

作者： Anas S. Zainud-Deen Hend A. Malhat Abdel-Razik Sebak Mona M. Badawy Faculty of Engineering Egyptian Russian University ERU Egypt Faculty of Electronic Engineering Menoufia University Egypt Electrical and Computer Engineering Concordia University Montreal Quebec Canada

This paper investigates the generation of vortex beams using a graphene metasurface at terahertz frequency band. A design of $20 \times 20$ unit-cell elements is described at 1.2THz. Each element is a graphene ring patch printed on silicon dioxide grounded substrate of $75 \times 75 \times 25 \mu \mathrm{m}^{3}$. The plane-wave excitation is investigated. The graphene reconfigurable surface conductivity is used to control the beam shape, direction, and directivity radiated from the metasurface, through the application of DC biasing voltages. A depiction of a single vortex beam in various orientations $\theta=0,30^{\circ}, 50^{\circ}$, and $70^{\circ}, \varphi=90^{\circ}$ for mode $l=1$ is presented. The graphene metasurface possesses the capability to convert linearly polarized input into multiple beams exhibiting orthogonal modes. The capacity of wireless communication in the terahertz band can be enhanced by utilizing the graphene metasurface.

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Braintransformer: Subject-Wise Patch Embed Transformer for Cross-Subject Brain Visual Information Decoding

Braintransformer: Subject-Wise Patch Embed Transformer for C...

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Du Zongxin Li Lin Faculty of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

Visual information decoding aims to infer the visual content perceived by a subject based on their brain responses, representing a cutting-edge area of neuroscience research. Functional magnetic resonance imaging (fMRI) provides millimeter-level spatial resolution and a relatively high signal-to-noise ratio, making it an ideal tool for neural information decoding. However, practical applications remain limited, primarily due to the reliance on subject-specific models. In this work, we propose BrainTransformer, a novel framework for cross-subject visual information decoding. To overcome the limitations, we develop a self-supervised patch embedding transformer trained using a masked signal modeling approach on large-scale fMRI data, enabling the learning of robust and generalizable neural representations across subjects. By aligning these learned fMRI representations with CLIP's image and text embeddings, BrainTransformer leverages rich semantic information from both visual and textual modalities. This alignment allows us to employ a multimodal latent diffusion model guided by CLIP's embeddings to generate images consistent with brain activity. Experimental results demonstrate BrainTransformer's effectiveness in decoding visual information across subjects, marking a significant step toward scalable and generalizable brain decoding.

关键词： Training Visualization Semantics Functional magnetic resonance imaging Brain modeling Transformers Diffusion models Data models Decoding Spatial resolution

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Surrogate-Assisted Particle Swarm Optimization with Dual-Subspace Search for Large-Scale Expensive Optimization 13

Surrogate-Assisted Particle Swarm Optimization with Dual-Sub...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Zhang, Jiajia Sun, Chaoli Zhang, Guochen Li, Jing Shi, Hui Xie, Zongchao School of Computer Science and Technology Taiyuan University of Science and Technology Taiyuan China School of Electronic Information Engineering Taiyuan University of Science and Technology Taiyuan China University of Melbourne Faculty of Science Melbourne Australia

ISBN: (纸本)9798350308365

Several meta-heuristic algorithms have gained attention for addressing large-scale optimization problems (LSOPs). However, their effectiveness is limited when dealing with LSOPs that involve expensive objective functions because the significant number of objective evaluations required before identifying the optimal solution. In this paper, two sets of subproblems are op-timized, assisted by surrogate models, to collaboratively explore the optimal solution space for large-scale expensive optimization problems (LSEOPs). A variant of particle swarm optimization (PSO), engineered to accelerate convergence, is proposed to search for the optimal solution for each subproblem. Moreover, a novel infill criterion is introduced, where the solution with the maximum expected improvement in the first set of subproblems and the solution with the minimum objective value discovered so far in the second set of subproblems are selected. Then, their mean position will be evaluated using the real objective function. Experimental findings on 15 CEC2013 benchmark problems show that our proposed approach outperforms four state-of-the-art algorithms in solving expensive large-scale optimization problems with up to 1000 decision variables. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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K/Ka-Band Wideband Dual-circularly Polarized Phased Array for Satellite Communication

K/Ka-Band Wideband Dual-circularly Polarized Phased Array fo...

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IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)

作者： Zezhong Yang Pengfei Yu Wenhao Feng Yang You Yunlong Lu JiFu Huang Faculty of Electrical Engineering and Computer Science Ningbo University East China Research Institute of Electronic Engineering Hefei China

ISBN: (数字)9798331520717

ISBN: (纸本)9798331520724

This paper presents a dual-circularly polarized antenna designed for low-orbit satellites, featuring wideband and wide-angle capabilities. A parallel-coupled three-line coupler, with a short-circuit coupling line in the center, is utilized as a feeding network to excite the upper dual-polarized dipole antenna. The design can realize the switching of receiving and transmitting of left and right circular polarization in the frequency band. The proposed dual-circularly polarized antenna operates from 20 GHz to 30 GHz with 40% less than -10 dB impedance bandwidth and greater than 12.5 dB port isolation. At the same time, a 1×8 one-dimensional array is used to verify the scanning performance phased array. For the designed 1 × 8 one-dimensional array, when the center frequency (24.5 GHz) beam is scanned to ± 60°, the axial ratio is better than 5.1 dB, and the gain drop is less than 4.6 dB.

关键词： Phased arrays Satellite antennas Satellites Dipole antennas Terahertz radiation Switches Antenna feeds Broadband antennas Wideband Terahertz communications

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