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A Generalized Array Factor for Time-Modulated Hexagonal Based Antenna Array Geometry With Novel Trapezoidal Switching

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1967-1972页

作者： Gopi Ram Department of Electronics and communication eng.neering National Institute of TechnologyWarangal 506004India

The concept of the time-modulated array has been emerging as an alternative to the complex phase shifters,which lowers the cost of the array feeding network due to the utilization of radio frequency(RF)*** various forms of hexagonal antenna array geometries can be used for applications like surveillance tracking in phased array radar and wireless communication *** work proposes the generalized array factor(AF)for the hexagonal antenna array geometry based on time *** time modulation in generalized hexagonal geometry can maintain the fixed static amplitude excitation,giving more flexibility over ***,a novel trapezoidal switching function is also proposed and applied to the generalized array factor to enable future researchers to use this array factor in the field of advancement to observe how switching schemes like trapezoidal and rectangular affect the array pattern's side lobe level(SLL).The generalized equation can be utilized for the analysis and synthesis of radiation characteristics of the time-modulated hexagonal array(TMHA),time-modulated concentric hexagonal array(TMCHA),time-modulated hexagonal cylindrical array(TMHCA),and time-modulated hexagonal concentric cylindrical array(TMHCCA).The numerical result illustrates the generation of AF of time-modulated hexagonal structures and also shows that the trapezoidal switching sequence outperforms the rectangular switch using the cat swarm optimization(CSO)approach.

关键词： Hexagonal array geometry radiation pattern time-modulation trapezoidal pulse

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Cross-Modal Consistency with Aesthetic Similarity for Multimodal False Information Detection

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Computers, Materials & Continua 2024年第5期79卷 2723-2741页

作者： Weijian Fan Ziwei Shi State Key Laboratory of Media Convergence and communication Communication University of ChinaBeijing100024China Software Research institute China United Network Communication Group Co.Ltd.Beijing100024China

With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.

关键词： Social media false information detection image aesthetic assessment cross-modal consistency

Quantized autoencoder(QAE)intrusion detection system for anomaly detection in resource-constrained loT devices using RT-loT2022 dataset

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Cybersecurity 2024年第2期7卷 13-27页

作者： B S Sharmila Rohini Nagapadma Depatment of Electronics and communication eng.neering The National Institute of EngineeringMysoreKarnataka 570008India

In recent years,many researchers focused on unsupervised learning for network anomaly detection in edge devices to identify *** deployment of the unsupervised autoencoder model is computationally expensive in resource-constrained edge *** study proposes quantized autoencoder(QAE)model for intrusion detection systems to detect *** is an optimization model derived from autoencoders that incorporate pruning,clustering,and integer quantization *** autoencoder uint8(QAE-u8)and quantized autoencoder float16(QAE-f16)are two variants of QAE built to deploy computationally expensive Al models into Edge ***,we have generated a Real-Time Internet of Things 2022 dataset for normal and attack *** autoencoder model operates on normal traffic during the training *** same model is then used to reconstruct anomaly traffic under the assumption that the reconstruction error(RE)of the anomaly will be high,which helps to identify the ***,we study the performance of the autoencoders,QAE-u8,and QAE-f16 using accuracy,precision,recall,and F1 score through an extensive experimental *** showed that QAE-u8 outperforms all other models with a reduction of 70.01%in average memory utilization,92.23%in memory size compression,and 27.94%in peak CPU ***,the proposed QAE-u8 model is more suitable for deployment on resource-constrained IoT edge devices.

关键词： IoT constrained system

AI/ML Enabled Automation System for Software Defined Disaggregated Open Radio Access Networks:Transforming Telecommunication Business

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Big Data Mining and Analytics 2024年第2期7卷 271-293页

作者： Sunil Kumar institute for communication Systems University of SurreyGuildfordGU27XHUK

Open Air Interface(OAI)alliance recently introduced a new disaggregated Open Radio Access Networks(O-RAN)framework for next generation telecommunications and *** disaggregated architecture is open,automated,software defined,virtual,and supports the latest advanced technologies like Artificial Intelligence(AI)Machine Learning(AI/ML).This novel intelligent architecture enables programmers to design and customize automated applications according to the business needs and to improve quality of service in fifth generation(5G)and Beyond 5G(B5G).Its disaggregated and multivendor nature gives the opportunity to new startups and small vendors to participate and provide cheap hardware software solutions to keep the market *** paper presents the disaggregated and programmable O-RAN architecture focused on automation,AI/ML services,and applications with Flexible Radio access network Intelligent Controller(FRIC).We schematically demonstrate the reinforcement learning,external applications(xApps),and automation steps to implement this disaggregated O-RAN *** idea of this research paper is to implement an AI/ML enabled automation system for software defined disaggregated O-RAN,which monitors,manages,and performs AI/ML-related services,including the model deployment,optimization,inference,and training.

关键词： Artificial Intelligence(AI) Reinforcement Learning(RL) Open Radio Access Networks(O-RAN) Flexible Radio access network Intelligent Controller(FRIC) external Applications(xApps) Machine Learning(ML),sixth generation(6G)

Research on Sarcasm Detection Technology Based on Image-Text Fusion

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Computers, Materials & Continua 2024年第6期79卷 5225-5242页

作者： Xiaofang Jin Yuying Yang YinanWu Ying Xu School of Information and communication eng.neering Communication University of ChinaBeijing100024China Cable Television Technology Research institute Academy of Broadcasting ScienceBeijing100053China

The emergence of new media in various fields has continuously streng.hened the social aspect of social *** tend to express emotions in social interactions,and many people even use satire,metaphors,and other techniques to express some negative emotions,it is necessary to detect sarcasm in social comment *** sarcasm,the more reference data modalities used,the better the experimental *** paper conducts research on sarcasm detection technology based on image-text fusion *** effectively utilize the features of each modality,a feature reconstruction output algorithm is *** algorithm is based on the attention mechanism,learns the low-rank features of another modality through cross-modality,the eigenvectors are reconstructed for the corresponding modality through weighted *** only the image modality in the dataset is used,the preprocessed data has outstanding performance in reconstructing the output model,with an accuracy rate of 87.6%.When using only the text modality data in the dataset,the reconstructed output model is optimal,with an accuracy rate of 85.2%.To improve feature fusion between modalities for effective classification,a weight adaptive learning algorithm is *** algorithm uses a neural network combined with an attention mechanism to calculate the attention weight of each modality to achieve weight adaptive learning purposes,with an accuracy rate of 87.9%.Extensive experiments on a benchmark dataset demonstrate the superiority of our proposed model.

关键词： Sentiment analysis sarcasm detection feature fusion feature reconstruction

Preparation of palladium-based catalyst by plasma-assisted atomic layer deposition and its applications in CO_(2) hydrogenation reduction

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Plasma Science and Technology 2024年第6期26卷 31-39页

作者：唐守贤田地李筝王正铎刘博文程久珊刘忠伟 Laboratory of Plasma Physics and Materials Beijing Institute of Graphic CommunicationBeijing 102600People’s Republic of China

Supported Pd catalyst is an important noble metal material in recent years due to its high catalytic performance in CO_(2)hydrogenation.A fluidized-bed plasma assisted atomic layer deposition(FP-ALD) process is reported to fabricate Pd nanoparticle catalyst over γ-Al_(2)O_(3)or Fe_(2)O_(3)/γ-Al_(2)O_(3)support,using palladium hexafluoroacetylacetonate as the Pd precursor and H_(2)plasma as *** transmission electron microscopy exhibits that highdensity Pd nanoparticles are uniformly dispersed over Fe_(2)O_(3)/γ-Al_(2)O_(3)support with an average diameter of 4.4 *** deposited Pd-Fe_(2)O_(3)/γ-Al_(2)O_(3)shows excellent catalytic performance for CO_(2)hydrogenation in a dielectric barrier discharge *** a typical condition of H_(2)to CO_(2)ratio of 4 in the feed gas,the discharge power of 19.6 W,and gas hourly space velocity of10000 h^(-1),the conversion of CO_(2)is as high as 16.3% with CH_(3)OH and CH4selectivities of 26.5%and 3.9%,respectively.

关键词： atomic layer deposition CO_(2)hydrogenation palladium based catalyst

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Dielectric barrier discharge plasma-assisted catalytic ammonia synthesis:synergistic effect of Ni-MOF-74 catalyst and nanosecond pulsed plasma

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Plasma Science and Technology 2024年第6期26卷 40-49页

作者：徐晓芳孙萌宋勤龙吴璇陈冲冲陈强张海宝 Laboratory of Plasma Physics and Materials Beijing Institute of Graphic CommunicationBeijing 102600People’s Republic of China

Ammonia is one of the most important chemical raw materials in both manufacture and life of *** Haber-Bosch method for ammonia synthesis involves high temperature and high pressure conditions,leading to significant energy consumption and environmental ***-thermal plasma(NTP) is a promising alternative approach to ammonia synthesis at low temperature and atmospheric *** this study,the synergistic effect of nanosecond pulsed dielectric barrier discharge(np-DBD) and Ni-MOF-74 catalyst was investigated in ammonia synthesis by utilizing nitrogen and hydrogen as *** results demonstrated that the plasma catalytic-synthesis process parameters play a crucial role in the synthesis process of *** highest ammonia synthesis rate of 5145.16 μmol·g^(-1)·h^(-1)with an energy efficiency of 1.27 g·kWh^(-1)was observed in the presence of the Ni-MOF-74 catalyst,which was3.7 times higher than that without Ni-MOF-74 *** synergistic effect of Ni-MOF-74catalyst and nanosecond pulsed plasma was explored by in-situ plasma discharge diagnostics.

关键词： ammonia synthesis low-temperature plasma nanosecond pulsed power source Ni-MOF-74

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Joint Rain Streaks & Haze Removal Network for Object Detection

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Computers, Materials & Continua 2024年第6期79卷 4683-4702页

作者： Ragini Thatikonda Prakash Kodali Ramalingaswamy Cheruku Eswaramoorthy K.V Department of Electronics and communication eng.neering National Institute of TechnologyWarangal506004India Department of Computer Science and eng.neering National Institute of TechnologyWarangal506004India Department of Electronics and communication eng.neering Indian Institute of Information TechnologyDesign and ManufacturingKurnool518008India

In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks(CNNs),supplanting traditional methods reliant on prior ***,the evolution of CNN architectures has tended towards increasing complexity,utilizing intricate structures to enhance performance,often at the expense of computational *** response,we propose the Selective Kernel Dense Residual M-shaped Network(SKDRMNet),a flexible solution adept at balancing computational efficiency with network accuracy.A key innovation is the incorporation of an M-shaped hierarchical structure,derived from the U-Net framework as M-Network(M-Net),within which the Selective Kernel Dense Residual Module(SDRM)is introduced to reinforce multi-scale semantic feature *** methodology employs two sampling techniques-bilinear and pixel unshuffled and utilizes a multi-scale feature fusion approach to distil more robust spatial feature map *** the reconstruction phase,feature maps of varying resolutions are seamlessly integrated,and the extracted features are effectively merged using the Selective Kernel Fusion Module(SKFM).Empirical results demonstrate the comprehensive superiority of SKDRMNet across both synthetic and real rain and haze datasets.

关键词： Image deraining Selective Dense Residual Module(SDRM) Selective Kernel Fusion Module(SKFM) Selective KernelDense Residual M-Shaped Network(SKDRMNet)

Exceptional point enhanced nanoparticle detection in deformed Reuleaux‑triangle microcavity

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Frontiers of Optoelectronics 2024年第3期17卷 83-91页

作者： Jinhao Fei Xiaobei Zhang Qi Zhang Yong Yang Zijie Wang Chuanlu Deng.Yi Huang Tingyun Wang Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced CommunicationShanghai Institute for Advanced Communication and Data ScienceSchool of Communication and Information EngineeringShanghai UniversityShanghai 200444China

In this paper,we propose a deformed Reuleaux-triangle resonator(RTR)to form exceptional point(EP)which results in the detection sensitivity enhancement of *** introducing single nanoparticle to the deformed RTR at EP,frequency splitting obtains an enhancement of more than 6 times compared with non-deformed *** addition,EP induced a result that the far feld pattern of chiral mode responses signifcantly to external perturbation,corresponding to the change in internal ***,single nanoparticle with far distance of more than 4000 nm can be detected by measuring the variation of far feld directional *** to traditional frequency splitting,the far feld pattern produced in deformed RTR provides a cost-efective and convenient path to detect single nanoparticle at a long distance,without using tunable laser and external *** structure indicates great potential in high sensitivity sensor and label-free detector.

关键词： Exceptional point Deformed microcavity Nanoparticle detection Far-feld pattern