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检索条件"任意字段=Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition"

共 743 条记录，以下是121-130 订阅

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Cloud Energy-Efficient Load Balancing: A Green Cloud Survey 11

Cloud Energy-Efficient Load Balancing: A Green Cloud Survey

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11th international conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Kaushik, Anushree Khan, Gulista Singhal, Priyank CCSIT Tmu Moradabad India

ISBN: (纸本)9781665487320

Green Cloud computing is a scalable use of computing resources that uses a virtualized computing platform. Cloud services enable people and companies to use software and equipment that is remotely managed by other parties. Meanwhile Organizations are attempting to cut down on the electricity used by idle resources as cloud computing platforms are used more frequently. By properly dividing the load and decreasing resource consumption, load balancing can assist in lowering energy consumption. Utilizing an effective load balancing algorithm, the service provider's ultimate purpose is to utilize the computer resources as effectively as possible and to maximize revenues. Discussions on cloud computing don't necessarily center on resource consumption and energy efficiency. With effective load balancing, resource usage may be reduced, which not only lowers costs but also makes businesses more environmentally friendly. Load balancing also makes it possible for cloud computing to scale, which is one of its key characteristics. therefore, increasing resource efficiency and a distributed system's performance in this way will lower energy usage but also carbon emissions to obtain 'green computing.' Different energy-conscious load balancing methods are reviewed, and its relevant benefits, drawbacks, and performance parameters are shown. © 2022 IEEE.

关键词： Cloud computing

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Intermittent Intelligent Camera with LEO sensor-to-satellite Connectivity 11

Intermittent Intelligent Camera with LEO sensor-to-satellite...

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11th international Workshop on Energy Harvesting and Energy-Neutral Sensing Systems (ENSsys) Part of SenSys conference

作者： Nardello, Matteo Caronti, Luca Brunelli, Davide Univ Trento Dept Ind Engn Trento TN Italy

ISBN: (纸本)9798400704383

IoT systems can operate efficiently in scenarios with limited or sporadic power availability by utilizing intermittent power sources, such as energy harvesting. Typical implementations are based on fixed-size super-capacitors as energy storage. However, this limits the possible implementations. Large capacitors take more time to charge, resulting in extended off-time following a power failure. Small capacitors charge faster but provide a shorter active time, leading to more frequent power failures. this paper presents a fully intermittent, machine learning-based, low-power smart camera for monitoring applications integrating a two-stage energy harvester. A small first stage supports data acquisition and analysis. the second bigger energy storage is activated only for data streaming to support the integrated sub-GHz Low Earth Orbit transmission radio. this dual-stage energy storage strategy ensures both system reactivity and the capacity to sustain energy-intensive data transmission. the simulation highlights how the fully intermittent pipeline (i.e., for both the neural accelerator and the ARM core) makes the system resilient to power fluctuation and increases the throughput of processed images in ultra-low light conditions by up to 13%.

关键词： Intermittent computing LEO Satellite Communication Intelligent Camera Energy Harvesting Power Management

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Hybrid Soft computing based Approach for Ageing in Face recognition 5

Hybrid Soft Computing based Approach for Ageing in Face Reco...

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5th international conference on Contemporary computing and Informatics, IC3I 2022

作者： Chaudhary, Jitendra Kumar Nazeer, M. Sameena Singh, Rajesh Verma, Devvret Kasar, Amit B. Dhotay, Megha Graphic Era Hill University School of Computing Bhimtal Campus Uttrakhand Bhowali India Ashoka Women's Engineering College Affiliated to JNTUA Ananthapuramu Department of ECE Andhra Pradesh Kurnool India Uttaranchal Institute of Technology Uttaranchal University Arcadia Grant Chandanwari Uttarakhand Dehradun India Graphic Era Deemed to Be University Department of Biotechnology Uttarakhand Dehradun India Savitribai Phule Pune University Hinjawadi International Institute of Information Technology Department of Engineering Sciences Maharashtra Pune India Computer Engineering MIT School of Polytechnic Maharashtra Pune India

ISBN: (纸本)9798350398267

Proposed Approach is a collection of methods for handling a certain class of complicated issues that call for the usage of intelligent software computers. For computational complexity issues, the merger of pattern recognition with Soft Context of online like Rnns has demonstrated a bright future, giving birth to strategies and systems with great performance and speed. Utilization of this fusion approach greatly improved the quality of detecting faces in a face - recognition workflow. DCNs are used in our hybrid algorithm, which combines CNN and LSTM, and they focus on the idea of optimizing the face's deep features. Results from our suggested system's testing upon that CACD datasets are quite encouraging and supportive © 2022 IEEE.

关键词： Face recognition

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Credit Card Fraud Detection using Machine Learning Techniques 11

Credit Card Fraud Detection using Machine Learning Technique...

引用

11th international conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Jain, Nishank Chaudhary, Alka Kumar, Anil Amity Institute of Information Technology Amity University Uttar Pradesh Noida India School of Computing DIT University Dehradun India

ISBN: (纸本)9781665487320

the COVID-19 pandemic has caused a huge decline in money usage, with everything turning online these days. It has contributed to an increase in contactless payments that was unimaginable before. A credit card is the most extensively used method of payment, and it is becoming increasingly digital as the number of daily electronic transactions increases, making it more vulnerable to fraud. Credit card firms have suffered losses because of widespread card fraud. the most common worry is the recognition of credit card fraud. As a result, organizations are looking toward advanced device understanding technologies since they can handle a lot of data and spot irregularities that humans would miss. the development of effective To stop these losses, fraud detection algorithms are essential. An increasing number of these algorithms rely on cutting-edge computer methods that can assist fraud investigators. However, the appearance of the full-proof Fraud Detection System demands the use of high performing algorithms that are both exact and sturdy enough to handle massive amounts of data. the algorithm is run using open-source software using R statistical programming. this project tries to provide options by studying several fraud detection systems and highlighting their strengths and limitations. © 2022 IEEE.

关键词： Machine learning

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Comparative Analysis of Scheduling Algorithms in Cloud computing using CloudSim 11

Comparative Analysis of Scheduling Algorithms in Cloud Compu...

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11th international conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Vidhya, M. Devi, R. VISTAS Department of Computer Science Chennai India

ISBN: (纸本)9781665487320

Cloud computing restructured the entire world of IT by providing shared scalable resources to the organization. Cloud establishes a huge path to find the solution for many major problems found in the industry. Cloud offers virtualized resources such as applications, software, networks, servers, and storage services. Cloud enables all the virtualized resources to clients on a pay-per-use basis. Because of handling the vast request sent by multiple clients and providing more versatile services to the organization, the cloud faces many critical problems such as security issues, dissatisfied Quality-Of-Services, and sometimes an unbalanced load arises. Among those, the most serious problem is balancing the load across the network. Load balancing issues can be handled by scheduling the work eventually to all nodes without overloading any single node. this paper gives an overview idea of different load balancing algorithms and provides comparative results on its quality metrics. © 2022 IEEE.

关键词： Cloud computing

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4th international conference on pattern Analysis and Intelligent Systems, PAIS 2022 - proceedings

4th International Conference on Pattern Analysis and Intelli...

引用

4th international conference on pattern Analysis and Intelligent Systems, PAIS 2022

ISBN: (纸本)9781665461610

the proceedings contain 57 papers. the topics discussed include: a deep learning-based system for detection at-risk students;an explainable self-labeling grey-box model;development of a biometric authentication platform using voice recognition;binary Archimedes optimization algorithm based feature selection for regression problem;semantic segmentation of breast cancer histopathology images using deep learning;a biased random-key genetic algorithm for extractive single-document summarization;a virtual clustering for data dissemination in vehicular fog computing;a novel method of requirements analysis for big data projects;combination of closed-set and open-set biometric identification;a formal integrated approach for cyber physical systems;and testing cyber-physical production system: test methods categorization and dataset.

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Combined Local pattern (CLP): A Novel Descriptor for Face recognition 4

Combined Local Pattern (CLP): A Novel Descriptor for Face Re...

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4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Karanwal, Shekhar Cse Department UK Dehradun India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

LBP is renowned as most powerful texture descriptor. But major issue which LBP possesses is the noisy thresholding function. this sacrifices the discriminativity of the descriptor. To complement that three LBP variants are introduced and these are Mean LBP (MLBP), Median LBP (MnLBP) and Combined Local pattern (CLP). In MLBP, the mean of the whole patch (3×3) is used for neighborhoods comparison. In MnLBP, the median of whole patch (3×3) is used for neighborhood comparison. the Mean and Median value proves out very effective in contrast to LBP, in which center pixel is used for the neighborhoods comparison. Both MLBP and MnLBP comprehensively conquer the performance of the LBP. To build more productive descriptor features of LBP, MLBP and MnLBP are integrated into one framework. this joined descriptor is called as CLP. the CLP conquer the results of all alone descriptors. Additionally it outrun the performance of the various literature methods. the compression in feature size is accomplished by PCA and classification is assisted from SVMs. Experiments are conducted on ORL and GT face datasets. © 2022 IEEE.

关键词： Local binary pattern

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Signal Transformation Analysis for Damage Detection Using pattern recognition 11

Signal Transformation Analysis for Damage Detection Using Pa...

引用

11th international conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2022

作者： Qiao, Long Missouri Western State University Saint JosephMO64507 United States

Civil structures are susceptible to damages over their service lives due to aging, environmental loading, fatigue and excessive response. Such deterioration significantly affects the performance and safety of structure. In this study, the measured structure vibration signals were decomposed by Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT) and Wavelet Packet Transform (WPT) to extract the sensitive features of the structural response, and to form one-dimensional or two-dimensional feature patterns. Correlation pattern recognition was used to perform pattern-matching for damage detection. To demonstrate the validity and accuracy of the method, experimental study was conducted on a small-scale three-story building. the results showed that the features of the signal for different damage scenarios can be uniquely identified by these transformations, and correlation algorithm can then be used to identify the most probable damage scenario. © 2022 international conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII. All rights reserved.

关键词： Fast Fourier transforms

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Research on the application of "quantum computing + dynamic face recognition" in bank personal business

Research on the application of "quantum computing + dynamic ...

引用

2022 international conference on Network Communication and Information Security, ICNCIS 2022

作者： Liu, Bin Huang, Shasha Zhou, Manzhen Yang, Shihao School ofEconomics and Management Jiangxi Science and Technology Normal University Nanchang China Graduate School Jiangxi Science and Technology Normal University Nanchang330000 China

ISBN: (纸本)9781510661134

With the improvement of informatization and the wide application of artificial intelligence technology, the rapid development of Internet Finance and the development of technology have promoted the improvement of security and management of commercial banks. Based on the basic concepts of dynamic face recognition technology and quantum computing, combined with the technological development process and the application status of security prevention and control scenario, business handling scenario and personalized service scenario in bank personal business, this paper explores the feasibility of integrating quantum computing into the innovative practice of dynamic face recognition in view of the problems of dynamic face recognition. the paper mainly summarize the effectiveness of pattern innovation design and the problems that should be paid attention to the process setting. In conclusion, integrating quantum computing into dynamic facial recognition more effectively will be the direction for banks to explore personal business in the future. © 2022 SPIE.

关键词： Face recognition

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Using Heterogeneous Cloud computing to Manage Resources in Sustainable Cyber-Physical Systems 11

Using Heterogeneous Cloud Computing to Manage Resources in S...

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11th international conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Shrimal, Gajendra Sandeep Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9781665487320

A significant increase in heterogeneous distributed computing has allowed for significant advancements in cyber physical systems (CPS). An additional strategy for enhancing system sustainability is to combine CPS with heterogeneous cloud computing. However, there are still certain difficulties with resource management in cloud systems, such as work allocation in heterogeneous clouds and Web server capacity limitations. Service delays are frequently caused by the erratic demand for services, which is embarrassing for the businesses' ability to compete. this article tackles the NP-hard problem of job assignment in heterogeneous clouds, which has been shown. the suggested method is known as the Smart Cloud-based Optimizing Workload (SCOW) Model, which assigns jobs to heterogeneous clouds using forecast cloud capacity and sustainable parameters. We provide a few strategies, such as the Workload Resource Minimization (WRM), Smart Task Assignment (STA), and Task Mapping Algorithm, to achieve the optimization target (TMA). Our experimental analyses have looked at how well the suggested strategy performs. © 2022 IEEE.

关键词： Cloud computing

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