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Study of millimetre-wave generation based on optical frequency multiplication

Study of millimetre-wave generation based on optical frequen...

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IET international Communication conference on Wireless Mobile and computing (CCWMC 2011)

作者： Yan Ding Jun Zhu Wei-Dong Fang Xiao-Guang Ge Xiang Chen Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei Anhui China Shanghai Research Centre for Wireless Communications China School of Communication and Information Engineering Key Laboratory of Specialty Fiber Optics and Optical Access Net works Shanghai University Shanghai China

ISBN: (纸本)9781618399571

To meet the increasing capacity and mobility as well as decrease the costs in next-generation optical access networks, RoF technology is a promising technique in the emerging optical and wireless convergence network, mm-wave generation is a key technique to realize the convergence network. In this paper, existing optical mm-wave generation technologies are introduced, including direct modulation, optical heterodyning and external modulation. Associated with Shanghai University, a scheme based on Optical Frequency Multiplication employing a dual drive Mach-Zehnder Modulator (DD-MZM) is presented. The novel efficient technique does not require expensive high-frequency electrical equipment. Moreover, no optical filtering is used, which significantly reduces the cost.

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convergence Analysis of Unscented Transform for Underwater Passive Target Tracking in Noisy Environment

Convergence Analysis of Unscented Transform for Underwater P...

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IEEE international conference on Signal Processing, Communications and computing (ICSPCC)

作者： Wasiq Ali Yaan Li Shujaat Ali Khan Tanoli Muhammad Asif Zahoor Raja Kashif Javaid Nauman Ahmed School of Marine Science and Technology Northwestern Ploytechnical University Xi'an China COMSATS University Islamabad Attock Pakistan

Optimal passive target tracking in noisy ocean environments is an important research problem. This issue is frequently dealt with nonlinear Bayesian filtering techniques, in which passive measurements are nonlinear while the dynamic system model is considered linear. The key objective of underwater passive object tracking is to accurately find the motion parameters of the object over uncertain measurements extracted from array elements. In this paper, the rule of unscented transform is used to examine the convergence of unscented Kalman filter (UKF) and unscented Rauch Tung Striebel (URTS) type Kalman post processing method. This study delicately finds the real-time state of a long distance dynamic target in a noisy complex underwater scenario, in which variance of background noise is high. Underwater Bearings-Only Tracking (BOT) technology is used for tracking purposes by deploying eight array elements which are localized on a horizontal Uniform Linear Array (ULA). Simulations are done for finding least Root Mean Square Error (RMSE) among real and approximated position of the target. Independent numerical results demonstrate that URTS smoother offers a higher convergence rate from UKF in a noisy ocean environment.

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Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text Retrieval 24

Focus, Distinguish, and Prompt: Unleashing CLIP for Efficien...

引用

32nd ACM international conference on Multimedia, MM 2024

作者： Zeng, Gangyan Zhang, Yuan Wei, Jin Yang, Dongbao Zhang, Peng Gao, Yiwen Qin, Xugong Zhou, Yu School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China Lenovo Research Beijing China Institute of Information Engineering Chinese Academy of Sciences Beijing China Laboratory for Advanced Computing and Intelligence Engineering Wuxi China TMCC College of Computer Science Nankai University Tianjin China

ISBN: (纸本)9798400706868

Scene text retrieval aims to find all images containing the query text from an image gallery. Current efforts tend to adopt an Optical Character Recognition (OCR) pipeline, which requires complicated text detection and/or recognition processes, resulting in inefficient and inflexible retrieval. Different from them, in this work we propose to explore the intrinsic potential of Contrastive Language-Image Pre-training (CLIP) for OCR-free scene text retrieval. Through empirical analysis, we observe that the main challenges of CLIP as a text retriever are: 1) limited text perceptual scale, and 2) entangled visual-semantic concepts. To this end, a novel model termed FDP (Focus, Distinguish, and Prompt) is developed. FDP first focuses on scene text via shifting the attention to the text area and probing the hidden text knowledge, and then divides the query text into content word and function word for processing, in which a semantic-aware prompting scheme and a distracted queries assistance module are utilized. Extensive experiments show that FDP significantly enhances the inference speed while achieving better or competitive retrieval accuracy compared to existing methods. Notably, on the IIIT-STR benchmark, FDP surpasses the state-of-the-art model by 4.37% with a 4 times faster speed. Furthermore, additional experiments under phrase-level and attribute-aware scene text retrieval settings validate FDP's particular advantages in handling diverse forms of query text. The source code will be available at https://***/Gyann-z/FDP. © 2024 ACM.

关键词： Semantics

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RIS-assisted MEC Computation Offloading for IoVT Networks

RIS-assisted MEC Computation Offloading for IoVT Networks

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international conference on Information and Communication technology convergence (ICTC)

作者： Daniar Estu Widiyanti Soo Young Shin Dept. of IT Convergence Engineering Kumoh National Institute of Technology Gumi South Korea

The Internet of Things (IoT) encompasses a wide range of applications; despite that, some challenges persist and require further research and development. One such challenge is encountered in sensing devices, particularly in Internet of Video Things (IoVT) applications that demand high-capacity wireless transmission. These applications face limitations in computational capability and energy consumption of users, posing significant obstacles to overcome. Mobile edge computing (MEC) has gained attention as it offers potential solutions by offloading complex tasks to assist users. However, the line-of-sight (LoS) issue between users and base stations (BS) caused by blocking objects remains a challenge in MEC. To address latency challenges in IoVT communication affected by obstacles, a collaborative framework between reconfigurable intelligence surfaces (RIS) and task offloading techniques in MEC, specifically in IoVT networks, is proposed. This collaboration aims to optimize the performance and efficiency of IoVT systems by harnessing the combined advantages of RIS and task offloading strategies.

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Strategic Security Audit Protocol: Safeguarding Smart Home IoT Devices against Vulnerabilities 18

Strategic Security Audit Protocol: Safeguarding Smart Home I...

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18th INDIAcom;11th international conference on computing for Sustainable Global Development, INDIACom 2024

作者： Dar, Arshad Ahmad Reegu, Faheem Ahmad Ahmed, Sarfaraz Hussain, Gousiya Jazan University College of Computer Science and Information Technology Jazan Saudi Arabia Mewar University Department of Computer Sciences Chittorgarh India

ISBN: (纸本)9789380544519

The world is experiencing a fast convergence of physical and cyber systems as objects used in day-to-day life are connected over the internet. These IoT devices are mass produced but ensure its usage in routine life. The impact of IoT in human life ranges from simple household equipment to life critical devices. Owing to the diversity both in application and nature, security had become a major concern on these devices and their applications. In spite of having many security frameworks and compliance regulations, attacks and on IoTs are exponentially growing. A handful of security frameworks are available for ensuring the security, there are very less frame works proposed for auditing the security. Confidentiality, Integrity and Availability which are the pillars of security in IoT are found missing or found to have been implemented with flaws. IoT security audit is one good solution which has proven success in the literature but challenging as the high level standards cannot be applied to low level device and applications. In addition, the challenges of audit include heterogeneity of IoT and lack of expert resources. IoT and related products reach market very quickly before it could be subjected to the complete audit procedures or in other words, the time taken for a new IoT device or application to be developed is very less than the time taken for developing an security audit mechanism. Hence, to enable an efficient security auditing of IoT devices, a definite and dynamic framework is needed that can propose feasible policies, automatic collection and analysis of audit data and tailor made procedures for risk assessment, risk control and risk mitigation. This Research focuses on the auditing of security vulnerability in IoT devices. A gradational methodology is proposed for extracting the feasible security checks from leading standards and guidelines in the IoT domain. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： IoT IT security audit Risk Assessment and Risk Mitigation Security Vulnerability

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Theoretical and empirical analyses of Evolutionary Negative Selection Algorithms for a combinational optimization problem

Theoretical and empirical analyses of Evolutionary Negative ...

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international conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Xingxin Pei Wenjian Luo Nature Inspired Computation and Application Laboratory School of Computer Science and Technology Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei Anhui China

Evolutionary Negative Selection Algorithms (ENSAs) could be regarded as hybrid algorithms of Evolutionary Algorithms (EAs) and Negative Selection Algorithms (NSAs). The average time complexity of ENSAs on combinational optimization problems has never been studied before. In this paper, the average time complexity of ENSAs on one combinational optimization problem is analyzed. The theoretical results demonstrate that, for the Two Max function, the ENSA with an appropriate matching threshold could perform better than the traditional (N+N) EA. Some simulation experiments on the combinational problem are also done, and the experimental results are consistent with theoretical results.

关键词： Algorithm design and analysis Software algorithms Immune system convergence Laboratories Computer applications Application software Computer science Evolutionary computation Biology computing

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Double Iterative Algorithm for Symmetric Solution of Multi-variable Quadratic Matrix Equation

Double Iterative Algorithm for Symmetric Solution of Multi-v...

引用

Cloud computing, Big Data and Internet of Things (3CBIT), international conference on

作者： Shijun Chen School of Fuzhou Institute of Technology Fuzhou China

ISBN: (纸本)9781665492263

In this article, a double iterative methods is suggested for solving symmetric matrix of multi-variable quadratic matrix equation. Firstly, the symmetric matrix of a quadratic matrix equation is transformed into the symmetric matrix of the corrected matrix equation by the Newton's algorithm. Then, we develop a modified conjugate gradient algorithm (MCG) for finding a symmetric solution of the modified equation. A numerical example is offered to show the inefficiency of the double iterative methods.

关键词： Cloud computing Symmetric matrices Big Data Iterative methods Internet of Things convergence

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Hardware realization of adaptive processing for noise elimination using TMS320C6713 DSP 11

Hardware realization of adaptive processing for noise elimin...

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11th international conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2020

作者： Godbole, Swati S. Surywanshi, Jaya R. Department of Electronics Engineering Shri Ramdevbaba College of Engineering and Management Nagpur-13 India Department of Information Technology MVPS's KBT College of Engineering Nashik India

ISBN: (纸本)9781713818519

Every day, we knowledge the property of acoustic noise whereas communicating on portable phones be it a moving vehicles. In reality, it is there even having conversation on a noisy telephone control. This noise pollutes the unique information carrying signal with noise starting its nearby atmosphere. Allowing for, a classification has been developed to discriminate a original signal from other noise sources or intrusive signals in an audio noisy surroundings. The hardware design to implement such a system is a tough task in real-time realistic noise deletion applications. Thus, this Article describe the real-time Architecture design to implement Adaptive Noise deletion method which considers the Least Mean Square (LMS) algorithm as a bench mark on TMS320C6713 DSP, to eliminate unwanted noise from the receiver for different audio associated applications. For the research affirmation, we used Texas Instruments' integrated development environment (IDE), and Code Composer Studio (CCS) for TMS320C6713 Digital Signal Processing Starter Kit (DSK) as the objective board. Three different cases are conceded by considering different audio inputs to test the effectiveness of the considered ANC arrangement. The Code Composer Studio is used to implement Least Means Square Algorithm, and realize with the DSP C6713. A 300, 500, 800Hz,1, 3KHz sound signals and male- vocalization signals are taken as the bench mark inputs, to map out the noise of the signal till it is disappeared. Hence, the preferred signal can be prevail. outcome of this research specify that the adaptive noise eliminator can eliminate the noise from signal expediently and in point of fact. The concert of ANC system is calculated in terms of different parameters like 1) convergence speed, and the2) order of the filter and 3) S/N ratio. The intended system expresses a note worthy level of enhancement in S/N Ratio (SNR). Hence, the S/N ratio of the processed signal using LMS adaptive filter progressed by 3 to 9 dB. T

关键词： Signal to noise ratio

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Development of image error correction system for 3D optical microscope

Development of image error correction system for 3D optical ...

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international conference on computing technology and Information Management (ICCTIM)

作者： Jiyoung Yoon HyunDeok Kim Cheolhwan Kim 3D Convergence Technology Center Kyungpook National University Daegu Republic of Korea

ISBN: (纸本)9781479962129

Recently 3D optical microscope is developing to see micro details in three-dimensions. To see images of an optical microscope in three-dimensions, we mount two cameras on the optical microscope. Three-dimension images are created using by two images that are incoming image through the refractive mirror with eye piece lens and those are made by two cameras. In this time, because of optical design errors and deformation mechanism of an optical microscope, it makes the problem which is disconformity of images. This case cannot be made a three-dimensional image correctly. We have corrected the error-output image of 3D optical microscope and developed the system showing the correct three-dimensional image.

关键词： Microscopy Optical microscopy Adaptive optics Optical imaging Optical sensors Optical refraction Cameras

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AI-Driven Energy Optimization: Household Power Consumption Prediction With LSTM Networks and PyTorch-Ray Tune in Smart IoT Systems

AI-Driven Energy Optimization: Household Power Consumption P...

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2024 international conference on Microelectronics, ICM 2024

作者： Kolluru, Vinoth Kumar Challagundla, Yagnesh Chintakunta, Advaitha Naidu Roy, Bappadittya Bermak, Amine Renuka Devi, S.M. Stevens Institute of Technology Department of Data Science HobokenNJ United States University of Florida Engineering Education Dept. United States University of North Carolina Department of Computer Science and Engineering Charlotte United States School of Electronics Engineering VIT-AP University Andhra Pradesh Amaravati India College of Science and Engineering Hamad Bin Khalifa Universityy Ar-Rayyan Qatar Dept. of Ece Hyderabad500104 India

ISBN: (纸本)9798350379396

Energy optimization is critical in smart home systems and IoT networks, necessitating innovative models that reduce energy use. This research presents two Long Short-Term Memory (LSTM) network models for estimating home power consumption using time-series data. The first model employs a standard LSTM technique with multivariate characteristics including global active power, voltage, and sub-metering variables. This technique strikes a balance between prediction accuracy and computing economy, making it ideal for resource-constrained applications. The second model provides an optimized version of the LSTM, which uses PyTorch and Ray Tune for hyperparameter optimization. The optimization focuses on tweaking learning rates, batch sizes, and LSTM layers to improve model accuracy and convergence speed. Using hyperparameter tuning, the Mean Squared Error (MSE) for global active power forecasts is decreased to 0.0018, proving its appropriateness for low-resource IoT systems. Both models are tested on a resampled real-world household electric power consumption dataset for effective training. The study emphasizes the advantages of multivariate time-series analysis and hyperparameter optimization, demonstrating that the optimized LSTM model can accurately predict energy consumption, enhance energy management in smart homes, and lower computing costs. Future work will look into combining more IoT data streams and real-world deployment for further improvement. The findings add to the expanding body of knowledge about energy optimization in IoT environments, addressing the crucial demand for effective, real-time energy management systems. © 2024 IEEE.

关键词： Mean square error

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