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2nd International Conference on Self Sustainable Artificial Intelligence systems, ICSSAS 2024

作者： Bhargava, Neeraj Rathore, Pramod Singh Goswami, Ankur Bhowmick, Apoorva Singh, Jatin Mds University School of Engineering & System Sciences Ajmer India Manipal University Department of Computer and Communication Engineering Jaipur India Govt. Engineering College Department of Computer Applications Bikaner India United Nations Secretariate New YourkNY10017 United States Baghdad Iraq Mds University Ajmer India

ISBN: (纸本)9798350368413

Fingerprint identification systems play a vital role in biometric security but are often influenced by fluctuations in scanning settings and environmental variables. The conventional normalizing techniques such as Min-Max, Z-Score, and Tanh normalization provide fixed solutions that do not adjust to these variations, therefore degrading the accuracy and resilience of the results. This study presents a machine learning-based adaptive normalization system that seamlessly adapts to present circumstances by integrating contextual information, such as ambient variables and scanner-specific features, with raw fingerprint scores. The procedure includes the gathering of data, doing preprocessing, training models using decision trees, random forests, and neural networks, and implementing dynamic normalization. Comprehensive testing conducted on several scanners and settings has shown the efficacy of this method, demonstrating substantial improvements in both recognition accuracy and resilience. Assessment measures such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R2 Score validate the higher efficacy of this adaptive approach in comparison to static methods, thereby improving operational adaptability and establishing a basis for wider biometric identification applications. © 2024 IEEE.

关键词： Random forests

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Three-dimensional reconstruction based on three-dimensional phase mapping using single-pixel imaging

Three-dimensional reconstruction based on three-dimensional ...

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2024 International Conference on Optoelectronic Information and Optical engineering, OIOE 2024

作者： Liu, Yemei Li, Yanfei Yu, Jing Miao, Yupei Liu, Xiaoli Peng, Xiang Tang, Qijian Key Laboratory of Optoelectronic Devices and System of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW2522 Australia

ISBN: (数字)9781510680470

ISBN: (纸本)9781510680463

The single-pixel imaging technique has garnered widespread attention and research due to its low requirements on detector resolution and equipment cost. In this study, a laser point scanning single-pixel imaging system is constructed. It utilizes a grating installed in front of the detector to capture a single-frame deformed fringe pattern, combining Fourier transform profilometry with three-dimensional phase mapping to ultimately achieve three-dimensional data acquisition. Following the calibration of the system, the positions of each light ray are calibrated using the intrinsic and extrinsic parameters obtained through camera calibration. Consequently, this paper proposes a single-pixel three-dimensional reconstruction method based on three-dimensional phase mapping, establishing a correlation between three-dimensional points and phases to realize three-dimensional phase mapping. Experimental results demonstrate that the model can achieve high reconstruction accuracy, presenting a novel solution for the field of single-pixel three-dimensional reconstruction. © 2024 SPIE.

关键词： Calibration

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A cloud-edge-device collaborative offloading scheme with heterogeneous tasks and its performance evaluation

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Frontiers of Information Technology & Electronic engineering 2024年第5期25卷 664-684页

作者： Xiaojun BAI Yang ZHANG Haixing WU Yuting WANG Shunfu JIN School of Information Science and Engineering Yanshan UniversityQinhuangdao 066004China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan UniversityQinhuangdao 066004China

How to collaboratively offload tasks between user devices,edge networks(ENs),and cloud data centers is an interesting and challenging research *** this paper,we investigate the offoading decision,analytical modeling,and system parameter optimization problem in a collaborative cloud-edge device environment,aiming to trade off different performance *** to the differentiated delay requirements of tasks,we classify the tasks into delay-sensitive and delay-tolerant *** meet the delay requirements of delay-sensitive tasks and process as many delay-tolerant tasks as possible,we propose a cloud-edge device collaborative task offoading scheme,in which delay-sensitive and delay-tolerant tasks follow the access threshold policy and the loss policy,*** establish a four-dimensional continuous-time Markov chain as the system *** using the Gauss-Seidel method,we derive the stationary probability distribution of the system ***,we present the blocking rate of delay-sensitive tasks and the average delay of these two types of *** experiments are conducted and analyzed to evaluate the system performance,and numerical simulations are presented to evaluate and validate the effectiveness of the proposed task offloading ***,we optimize the access threshold in the EN buffer to obtain the minimum system cost with different proportions of delay-sensitive tasks.

关键词： Edge computing Ofloading scheme Cloud-edge device collaboration Markov chain Cost function

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IoT-Enabled Smart Manhole Management system for Real-time Status, Water Level, and Gas Detection

IoT-Enabled Smart Manhole Management System for Real-time St...

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2024 International Conference on Intelligent systems for Cybersecurity, ISCS 2024

作者： Imran, Md Asif Masfequier Rahman Swapno, S.M. Chhabra, Gunjan Kaushik, Keshav Anzum Mahi, Md. Arif Islam, Md Babul Haque, Rezaul Bangladesh University of Business and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Graphic Era Hill University Department of Cse Uttarakhand Dehradun India Graphic Era Deemed to Be University Uttarakhand Dehradun India School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun India Modeling Electronic and System Engineering Unical Dept. of Computer Rende Italy Applied Bahari Big Data Research House Dhaka Bangladesh Modeling Electronic and System Engineering Unical Department of Computer Rende Italy

ISBN: (纸本)9798350375237

Regular monitoring of the maintenance manhole system is imperative to uphold the city's health and cleanliness standards. Our study offers an intelligent manhole that monitors the manhole's condition, water level, and gases. We tested the status, gas, and water levels of our revolutionary, innovative manhole in several places. Our system's Blink app position tracking of our smart manhole is critical. This capability improves monitoring efficiency and speeds up issue resolution. Our work revolutionizes municipal utility maintenance and safety by optimizing manhole performance. Integrating a Node MCU, GPS module, gas sensor, ultrasonic sensor, and Android Blynk software creates a complete real-time monitoring and data-collecting system. Combining these technologies, our Manhole Monitoring system improves safety and streamlines maintenance, making municipal infrastructure more robust and efficient. This paper highlights the promising features of IoT and shows how it may be used to improve the smart manhole. In the future, this creative method may result in a more durable and better intelligent city. © 2024 IEEE.

关键词： Maintenance

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Energy Efficient Hybrid Routing for Different Energy Levels Using Fuzzy Logic

Energy Efficient Hybrid Routing for Different Energy Levels ...

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2023 International Conference on IoT, Communication and Automation Technology, ICICAT 2023

作者： Singh, Kalpana Pandey, Prashant Ahamad, Firoj Rajkiya Engineering College Department of Computer Science Engineering Uttar Pradesh Sonbhadra231206 India Rajkiya Engineering College Department of Electronics Engineering Uttar Pradesh Sonbhadra231206 India School of Computer and System Sciences Jawaharlal Nehru University New Delhi Delhi 110067 India

ISBN: (纸本)9798350302820

Collection of sensor nodes and base station called as Wireless Sensor Networks. While, communicating with other nodes within network this type of network uses huge amount of energy. And, node has limited life time due to battery power. For efficiently utilizing these nodes energy and power, clustering was considered as a best approach. In proposed paper, we work on heterogeneous node, in such environment nodes are differ by their energy level, power, computation, communication etc. The protocol proposed for Energy Efficient Hybrid Routing in different energy levels using fuzzy logic provides three different network for three different initial energy level of nodes such that. 3J,. 4J and. 5J under same area (500∗500) m2 in which super node region uses multipath routing and clustering approach uses for transmitting packet/ data to base station and normal type nodes will uses single path routing transmitting packet/ data to Base station. The proposed protocol discussed different energy levels for finding best initial energy value of node in network and improved throughput, stability, lifetime of network on. 4J energy level as compare to. 3J and. 5J. To optimize the cluster formation we used predetermined technique i.e. inverted binary tree. This technique helps in balancing the load of super nodes region. The proposed model simulated in MATLAB, result shows better performance at 0.4J initial energy. © 2023 IEEE.

关键词： Fuzzy logic

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Multi-view 3D reconstruction based on speckle correlation 8

Multi-view 3D reconstruction based on speckle correlation

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8th International Conference on Speckle Metrology, Speckle 2023

作者： Zeng, Xiaoxian Jing, Yu Tang, Qijian Liu, Xiaoli Peng, Xiang Key Laboratory of Optoelectronic Devices System of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW2522 Australia

ISBN: (数字)9781510674592

ISBN: (纸本)9781510674585

Three-dimensional (3D) reconstruction based on digital speckle correlation has gained widespread usage in dynamic scenarios due to its ability to achieve single-frame reconstruction. Traditional binocular speckle structured light systems often face challenges such as insufficient surface texture richness and excessive curvature, leading to limitations in the accuracy of corresponding point localization during the matching process. Furthermore, partial point cloud loss caused by varying viewpoints can impact the precision and completeness of 3D reconstruction. This paper introduces a Multiview speckle correlation-based approach for 3D reconstruction. By establishing multi-view stereo camera epipolar rectification, complex speckle matching issues are transformed into one-dimensional searches along unified epipolar lines, simplifying the matching process and enhancing efficiency. Additionally, a digital speckle correlation computational model and subpixel interpolation algorithm based on Newton-Raphson iteration are employed to realize multi-view subpixel-level corresponding point localization. Ultimately, the reconstruction point cloud data is obtained through the intersection of three-ray least squares method. Experimental results demonstrate that this method achieves higher accuracy and better model completeness in 3D data reconstruction. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Speckle

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A Graph-based Multi-view Clustering Approach for Building Group Patterns Recognition 3

A Graph-based Multi-view Clustering Approach for Building Gr...

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3rd International Conference on Internet of Things and Smart City, IoTSC 2023

作者： Yang, Ruolin Yang, Lin Zuo, Zejun Wei, Jing National Engineering Research Center of Geographic Information System China University of Geosciences Wuhan China School of Computer Science China University of Geosciences Wuhan China

ISBN: (纸本)9781510666375

Building pattern informs urban spatial structure understanding and modeling. However, previous studies showed limitations on the identification of building groups which has complex spatial distribution. Specifically, they usually use original spatial or non-spatial characteristics but omit certain complementary among multi-faceted features of buildings. In this paper, we give a novel method based on a multi-view clustering framework, which establishes a centroid distance view and a building attribute view to recognize building patterns accurately. The two views are based on both the spatial structure and non-spatial attributes. The similarity graphs on these views, which are obtained by the Gaussian kernel function, are executed graph diffusion and fusion process to obtain a unified graph. Then, the clustering results are obtained via the Normalized cut algorithm. We conduct experiments to recognize building patterns by four real-world community building footprint datasets of two cities in China: Wuhan and Chengdu. The experimental results show that our proposed method identifies building groups with grid, grid-like and unstructured patterns more effectively. Our method performs better in seven evaluation indexes compared with the baseline model. © 2023 SPIE.

关键词： Pattern recognition

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Classification And Prediction of Brain Tumors and its Types using Deep Learning 1

Classification And Prediction of Brain Tumors and its Types ...

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Bajaj, Madhvan Rawat, Priyanshu Bhatt, Aastha Sharma, Vikrant Jain, Ayushi Kumar, Navneet Graphic Era Hill University Computer Science and Engineering Dehradun India BSc Nursing Uttar Pradesh Lucknow India Jawaharlal Nehru University School of Computer & System Sciences New Delhi India

ISBN: (纸本)9798350338027

Brain tumors are a major source of illness and mortality globally, with about 11,700 persons diagnosed with one each year. Brain tumor diagnosis and categorization are critical for proper treatment planning, which can increase patients' life expectancy. Due to the intricacy of brain tumors and their attributes, the traditional approach of manual assessment of brain MRI images might be error-prone. Automated classification approaches based on Machine Learning (ML) and Artificial Intelligence (AI) have been shown to be more accurate than manual categorization. Deep Learning techniques including Convolutional Neural Networks (CNNs), Artificial Neural Networks (ANNs), and Transfer Learning (TL) have shown promising results for the automatic categorization of brain MRI images in this context. These automated procedures can save time and lessen the possibility of misdiagnosis, but they should always be used in tandem with clinical experience. The suggested method has the potential to significantly improve the accuracy and efficiency of brain tumor identification and categorization for doctors and radiologists globally. © 2023 IEEE.

关键词： Tumors

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BuildingMap-GAN: A Map Translator From Road to Building Footprint 3

BuildingMap-GAN: A Map Translator From Road to Building Foot...

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3rd International Conference on Internet of Things and Smart City, IoTSC 2023

作者： Wei, Jing Zuo, Zejun Yang, Lin Yang, Ruolin School of Computer Science China University of Geosciences Wuhan China National Engineering Research Center of Geographic Information System China University of Geosciences Wuhan China

ISBN: (纸本)9781510666375

Building footprint information is crucial for urban-related applications. Due to the rapid growth of the number and types of community-level buildings, the completeness and coverage of building footprint data at the community level are lagging. Efficiently and accurately generating community-level building footprint maps for the update of community electronic maps, post-disaster assessment, navigation services, etc. is an urgent and challenging task. To fill the data gaps of community-level building footprint with high accuracy, we design a building map translator named BuildingMap-GAN that is configured with a novel generator: MACU-Net. It has multi-scale connections with channel attention and asymmetric convolution blocks (ACB), which are used for fully capturing the spatial structure information of buildings and roads. An experiment is conducted on real-world community dataset in Wuhan, China, in which the street network data of 700 communities were used for training and the street network data of 42 communities were used for verification. Compared with the two baseline models, F1 scores are improved by 6.7% and 4.5%, respectively, and IoU values increase by 5.0% and 3.2%, respectively. Our model can generate refined building footprint data with higher precision and is closer to the real building distribution. © 2023 SPIE.

关键词： Generative adversarial networks

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Output Linearization of Single-Input Single-Output Fuzzy system to Improve Accuracy and Performance

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computers, Materials & Continua 2023年第5期75卷 2413-2427页

作者： Salah-ud-din Khokhar QinKe Peng Muhammad Yasir Noor Department of Automation Science and Technology(System Engineering Institute) School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’anShaanxi710049China Department of Computer Science G.C.UniversityLahore54000PunjabPakistan Department of Physics(Electronics) G.C.UniversityLahore54000PunjabPakistan

For fuzzy systems to be implemented effectively,the fuzzy membership function(MF)is essential.A fuzzy system(FS)that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output(SISO)FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s *** a variety of non-linear techniques,a SISO FS is *** results of FS experiments conducted in comparable conditions are then *** simulated results and the results of the experimental setup agree fairly *** findings of the suggested model demonstrate that the relative error is abated to a sufficient range(≤±10%)and that the mean absolute percentage error(MPAE)is reduced by around 66.2%.The proposed strategy to reduceMAPE using an FS improves the system’s performance and control *** using the best input and output MFs protocol,the energy and financial efficiency of every SISO FS can be improved with very little tuning of *** proposed fuzzy system performed far better than other modern days approaches available in the literature.

关键词： Mean absolute percentage error membership functions relative error fuzzy system

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