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Synthesis of Wideband Bandpass Filter With In-Band Complex Transmission Zeros for Frequency- and Attenuation-Reconfigurable In-Band Notch

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IEEE Transactions on Microwave Theory and Techniques 2024年第2期72卷 1162-1175页

作者： Liu, Bin Li, Kun Chi, Pei-Ling Yang, Tao University of Electronic Science and Technology of China School of Electronic Science and Engineering Chengdu610054 China National Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan

A novel synthesis method for wideband bandpass filter (BPF) with two in-band conjugate complex transmission zeros is proposed for realizing frequency- and attenuation-reconfigurable in-band notch. A new characteristic function with wideband bandpass response is constructed by merging two BPFs with relatively narrow bandwidths. With the newly constructed characteristic function, complex transmission zeros will be introduced in the filter passband, facilitating the generation and control of the in-band notch. Moreover, quasi-Chebyshev filtering response (with quasi-equal ripple level) is also guaranteed in the whole passband. Based on the new characteristic function, a series of filter topologies can be derived using matrix similarity transformations. By only tuning the resonant frequencies of particular resonators, these topologies can exhibit wideband bandpass responses with frequency- and attenuation-reconfigurable in-band notch. To demonstrate the proposed techniques, one prototype of the wideband BPF using waveguide resonators is designed, simulated, and fabricated. The fabricated wideband BPF exhibits a passband frequency from 8.12 to 11.76 GHz with one transmission zero at 13.36 GHz and a reconfigurable in-band notch with frequency tuning from 9.3 to 10.4 GHz and attenuation tuning from 2 to 60 dB. The simulated and measured results are in good agreement, validating the proposed technique. © 1963-2012 IEEE.

关键词： Topology

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Edge-Enabled Metaverse:The Convergence of Metaverseand Mobile Edge Computing

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Tsinghua science and Technology 2024年第3期29卷 795-805页

作者： Nyothiri Aung Sahraoui Dhelim Liming Chen Huansheng Ning Luigi Atzori Tahar Kechadi Information Engineering College Xinjiang Institute of EngineeringUrumqi 830023Chinaand also with School of Computer ScienceUniversity College DublinDublinD04 V1W8Ireland School of Computing Ulster UniversityBelfastBT151EDUK School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Department of Electrical and Electronic Engineering University of CagliariSardinia 09124Italy School of Computer Science University College DublinDublinD04 V1W8Ireland

Metaverse is a virtual environment where users are represented by their avatars to navigate a virtual world having strong links with its physical *** state-of-the-art Metaverse architectures rely on a cloud-based approach for avatar physics emulation and graphics rendering *** current centralized architecture of such systems is unfavorable as it suffers from several drawbacks caused by the long latency of cloud access,such as low-quality *** this end,we propose a Fog-Edge hybrid computing architecture for Metaverse applications that leverage an edge-enabled distributed computing *** applications leverage edge devices’computing power to perform the required computations for heavy tasks,such as collision detection in the virtual universe and high-computational 3D physics in virtual *** computational costs of a Metaverse entity,such as collision detection or physics emulation,are performed at the device of the associated physical *** validate the effectiveness of the proposed architecture,we simulate a distributed social Metaverse *** simulation results show that the proposed architecture can reduce the latency by 50%when compared with cloud-based Metaverse applications.

关键词： industrial Metaverse edge computing Blockchain virtual environment task offloading fog computing

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Fresh Food Product Insurance Model with Blockchain Technology 4

Fresh Food Product Insurance Model with Blockchain Technolog...

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4th International Conference on Electrical engineering and computer science, ICECOS 2024

作者： Inayatulloh Kusumadi Hartono, Indra Yasri School of Information System Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368253

One of the important components of the food industry is the availability of fresh food. The long supply chain for fresh food, from farmers to consumers or processed food companies, has an impact on the high risk of damage to fresh food products. Several parties involved in the fresh food supply chain transfer their risks to insurance companies to reduce the risk of loss. Meanwhile, there is currently no transparent insurance mechanism that provides transparent information for parties involved in fresh food insurance. Fresh fruit producers do not receive valid and accurate information about the reasons for the rejection of insurance claim submissions. Likewise, insurance companies do not receive valid and accurate information about the reasons why fresh fruit producers do not pay insurance premiums. Blockchain is a technology that has the advantage of creating transparent transactions with the concept of peer-To-peer validation. Premium payment transactions and claim submissions will be stored on the blockchain network if the transaction has passed the peer-To-peer validation process. Thus, this research aims to create a fresh food insurance model using blockchain technology. The research method uses a qualitative approach by studying the fresh food supply chain, insurance processes, and blockchain technology. The result of this research is a model and simulation with EVM for blockchain adoption in fresh food insurance. © 2024 IEEE.

关键词： Food industry

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Enhancing wireless sensing via a target-mounted intelligent reflecting surface

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National science Review 2023年第8期10卷 13-14页

作者： Xiaodan Shao Rui Zhang School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Department of Electrical and Computer Engineering National University of Singapore

An intelligent reflecting surface(IRS),or its various equivalents such as an reconfigurable intelligent surface(RIS), is an emerging technology to control radio signal propagation in wireless systems. An IRS is a digitally controlled metasurface consisting of a large number of passive reflecting elements, which are connected to a smart controller to enable dynamic adjustments of the amplitude and/or phase of the incident signal on each element independently [1].

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Detecting Inaudible Voice Commands via Acoustic Attenuation by Multi-channel Microphones

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IEEE Transactions on Dependable and Secure Computing 2024年 1-17页

作者： Ji, Xiaoyu Zhang, Guoming Li, Xinfeng Qu, Gang Cheng, Xiuzhen Xu, Wenyuan Electrical Engineering of Zhejiang University Hangzhou China School of Computer Science and Technology of Shandong University Qingdao China Department of Electrical and Computer Engineering at the University of Maryland College Park MD USA

DolphinAttacks (i.e., inaudible voice commands) modulate audible voices over ultrasounds to inject malicious commands silently into voice assistants and manipulate controlled systems (e.g., doors or smart speakers). Eliminating DolphinAttacks is challenging if ever possible since it requires to modify the microphone hardware. In this paper, we design EarArray, a lightweight method that can not only detect such attacks but also identify the direction of attackers without requiring any extra hardware or hardware modification. Essentially, inaudible voice commands are modulated on ultrasounds that inherently attenuate faster than the one of audible sounds. By inspecting the command sound signals via the built-in multiple microphones on smart devices, EarArray is able to estimate the attenuation rate and thus detect the attacks. We propose a model of the propagation of audible sounds and ultrasounds from the sound source to a voice assistant, e.g., a smart speaker, and illustrate the underlying principle and its feasibility. We implemented EarArray using two specially-designed microphone arrays and our experiments show that EarArray can detect inaudible voice commands with an accuracy of above 99% and recognize the direction of the attackers with an accuracy of 97.89% and can also detect the laser-based attack with an accuracy of 100%. IEEE

关键词： Microphones

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Energy and Bandwidth Based Link Stability Routing Algorithm for IoT

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computers, Materials & Continua 2022年第2期70卷 3875-3890页

作者： D.Kothandaraman A.Balasundaram R.Dhanalakshmi Arun Kumar Sivaraman S.Ashokkumar Rajiv Vincent M.Rajesh School of Computer Science and Artificial Intelligence SR UniversityWarangalTSIndia School of Computer Science and Engineering Center for Cyber Physical SystemsVellore Institute of Technology(VIT)ChennaiIndia Department of Computer Science and Engineering KCG College of TechnologyChennaiIndia School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiIndia Department of Computer Science and Engineering Saveetha School of EngineeringSIMATSChennaiIndia

Internet of Things(IoT)is becoming popular nowadays for collecting and sharing the data from the nodes and among the nodes using internet ***,some of the nodes in IoT are mobile and dynamic in *** maintaining the link among the nodes,efficient bandwidth of the links among the mobile nodes with increased life time is a big challenge in IoT as it integrates mobile nodes with static nodes for data *** such networks,many routing-problems arise due to difficulties in energy and bandwidth based quality of *** to the mobility and finite nature of the nodes,transmission links between intermediary nodes may fail frequently,thus affecting the routing-performance of the network and the accessibility of the *** existing protocols do not focus on the transmission links and energy,bandwidth and link stability of the nodes,but node links are significant factors for enhancing the quality of the *** stability helps us to define whether the node is within or out of a coverage *** paper proposed an Optimal Energy and bandwidth based Link Stability Routing(OEBLS)algorithm,to improve the link stable route with minimized error rate and *** this paper,the optimal route from the source to the sink is determined based on the energy and bandwidth,link stability *** the existing routes,the sink node will choose the optimal route which is having less link stability *** stable link is determined by evaluating link stability value using distance and ***-energy of the node is estimated using the current energy and the consumed *** energy is estimated using transmitted power and the received *** bandwidth in the link is estimated using the idle time and channel capacity with the consideration of probability of collision.

关键词： Link stability internet of things optimal energy optimal bandwidth residual energy

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Machine learning integrated graphene oxide‐based diagnostics, drug delivery, analytical approaches to empower cancer diagnosis

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BMEMat(BioMedical engineering Materials) 2025年第1期3卷 158-181页

作者： Suparna Das Hirak Mazumdar Kamil Reza Khondakar Ajeet Kaushik Department of Computer Science and Engineering BVRIT HYDERABAD College of Engineering for WomenHyderabadIndia School of Engineering and Technology Department of Computer Science and EngineeringAdamas UniversityKolkataIndia School of Technology Woxsen UniversityHyderabadIndia NanoBiotech Laboratory Department of Environmental EngineeringFlorida Polytechnic UniversityLakelandUSA

Machine learning(ML)and nanotechnology interfacing are exploring opportunities for cancer treatment *** improve cancer therapy,this article investigates the synergistic combination of Graphene Oxide(GO)‐based devices with ML *** production techniques and functionalization tactics used to modify the physicochemical characteristics of GO for specific drug delivery are explained at the outset of the *** is a great option for treating cancer because of its natural biocompatibility and capacity to absorb medicinal ***,complicated biological data are analyzed using ML algorithms,which make it possible to identify the best medicine formulations and individualized treatment plans depending on each patient's particular *** study also looks at optimizing and predicting the interactions between GO carriers and cancer cells using *** modeling helps ensure effective payload release and therapeutic efficacy in the design of customized drug delivery ***,tracking treatment outcomes in real time is made possible by ML algorithms,which permit adaptive modifications to therapy *** optimizing medication doses and delivery settings,the combination of ML and GO in cancer therapy not only decreases adverse effects but also enhances treatment accuracy.

关键词： artificial intelligence cancer diagnosis graphene oxide machine learning real‐time monitoring sensing

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A Multi-Bit ECRAM-Based Analog Neuromorphic system With High-Precision Current Readout Achieving 97.3% Inference Accuracy

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IEEE Transactions on Biomedical Circuits and systems 2025年第3期19卷 590-604页

作者： Um, Minseong Kang, Minil Eom, Kyeongho Kwak, Hyunjeong Noh, Kyungmi Lee, Jimin Son, Jeonghoon Kwon, Jiseok Kim, Seyoung Lee, Hyung-Min Korea University School of Electrical Engineering Seoul02841 Korea Republic of Korea University Department of Semiconductor System Engineering Seoul02841 Korea Republic of Pohang University of Science and Technology Department of Materials Science and Engineering Pohang37673 Korea Republic of The Catholic University of Korea School of Information Communications and Electronic Engineering Bucheon14662 Korea Republic of

This article proposes an analog neuromorphic system that enhances symmetry, linearity, and endurance by using a high-precision current readout circuit for multi-bit nonvolatile electro-chemical random-access memory (ECRAM). For on-chip training and inference, the system uses activation modules and matrix processing units to manage analog update/read paths and perform precise output sensing with feedback-based current scaling on the ECRAM array. The 250nm CMOS neuromorphic chip was tested with a 32 × 32 ECRAM synaptic array, achieving linear and symmetric updates and accurate read operations. The proposed circuit system updates the 32 × 32 ECRAM across 100 levels, maintaining consistent synaptic weights, and operates with an output error rate of up to 2.59% per column. It consumes 5.9 mW of power excluding the ECRAM array and achieves 97.3% inference accuracy on the MNIST dataset, close to the software-confirmed 97.78%, with only the final layer (64 × 10) mapped to the ECRAM. © 2007-2012 IEEE.

关键词： CMOS integrated circuits

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Provable Data Possession with Outsourced Tag Generation for AI-Driven E-Commerce

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computers, Materials & Continua 2025年第5期83卷 2719-2734页

作者： Yi Li Wenying Zheng Yu-Sheng Su Meiqin Tang School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China School of Computer Science and Technology(School of Artificial Intelligence) Zhejiang Sci-Tech UniversityHangzhou310018China Department of Computer Science and Information Engineering National Chung Cheng UniversityChiayi621301TaiwanChina Advanced Institute of Manufacturing with High-tech Innovations National Chung Cheng UniversityChiayi621301TaiwanChina Department of Computer Science and Engineering National Taiwan Ocean UniversityKeelung202301TaiwanChina School of Integrated Circuits Wuxi Vocational College of Science and TechnologyWuxi214028China

AI applications have become ubiquitous,bringing significant convenience to various *** e-commerce,AI can enhance product recommendations for individuals and provide businesses with more accurate predictions for market strategy ***,if the data used for AI applications is damaged or lost,it will inevitably affect the effectiveness of these AI ***,it is essential to verify the integrity of e-commerce *** existing Provable Data Possession(PDP)protocols can verify the integrity of cloud data,they are not suitable for e-commerce scenarios due to the limited computational capabilities of edge servers,which cannot handle the high computational overhead of generating homomorphic verification tags in *** address this issue,we propose PDP with Outsourced Tag Generation for AI-driven e-commerce,which outsources the computation of homomorphic verification tags to cloud servers while introducing a lightweight verification method to ensure that the tags match the uploaded ***,the proposed scheme supports dynamic operations such as adding,deleting,and modifying data,enhancing its ***,experiments show that the additional computational overhead introduced by outsourcing homomorphic verification tags is acceptable compared to the original PDP.

关键词： Provable data possession data auditing cloud computing e-commerce bloom filter

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A three-stage novel framework for efficient and automatic glaucoma classification from retinal fundus images

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Multimedia Tools and Applications 2024年第37期83卷 85421-85481页

作者： Singh, Law Kumar Khanna, Munish Garg, Hitendra Singh, Rekha Iqbal, Md. Department of Computer Engineering and Applications GLA University Mathura India School of Computing Science and Engineering Galgotias University Greater Noida203201 India Department of Physics Uttar Pradesh Rajarshi Tandon Open University Uttar Pradesh Prayagraj India Department of Computer Science and Engineering Meerut Institute of Engineering and Technology Meerut India

Glaucoma is one of the leading causes of visual impairment worldwide. If diagnosed too late, the disease can irreversibly cause severe damage to the optic nerve, resulting in permanent loss of central vision and blindness. Therefore, early diagnosis of the disease is critical. Recent advancements in machine learning techniques have greatly aided ophthalmologists in timely and efficient diagnosis through the use of automated systems. Training the machine learning models with the most informative features can significantly enhance their performance. However, selecting the most informative feature subset is a real challenge because there are 2n potential feature subsets for a dataset with n features, and the conventional feature selection techniques are also not very efficient. Thus, extracting relevant features from medical images and selecting the most informative is a challenging task. Additionally, a considerable field of study has evolved around the discovery and selection of highly influential features (characteristics) from a large number of features. Through the inclusion of the most informative features, this method has the potential to improve machine learning classifiers by enhancing their classification performance, reducing training and testing time, and lowering system diagnostic costs by incorporating the most informative features. This work aims in the same direction to propose a unique, novel, and highly efficient feature selection (FS) approach using the Whale Optimization Algorithm (WOA), the Grey Wolf Optimization Algorithm (GWO), and a hybridized version of these two metaheuristics. To the best of our knowledge, the use of these two algorithms and their amalgamated version for FS in human disease prediction, particularly glaucoma prediction, has been rare in the past. The objective is to create a highly influential subset of characteristics using this approach. The suggested FS strategy seeks to maximize classification accuracy while reducing the t

关键词： Image classification

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