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Research on Surface ablative defect detection of improved Unet

Research on Surface ablative defect detection of improved Un...

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international conference on Machine Learning, big data and Business Intelligence (MLBDBI)

作者： Xindan Hu Lichong Wu GuangPeng Liu Huan Chen Zhuzhou Tianqiao Crane Co. Ltd School of Mechanical and Electrical Engineering Lanzhou University of Technology

Design of improved U-net detection method for ablation and contamination defects generated during electrolysis of nickel plates. Improve channel attention and perceptual field during feature extraction by fusing ECANet and ASPP *** model ablation experiments and comparative analysis with classical semantic segmentation network were conducted. the results show that the algorithm in this paper outperforms other algorithms in detecting sheet ablation defects, and mIoU and mPA are improved by 5.07% and 3.54%, respectively, compared with those before improvement.

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Assessment of White Matter Fiber Integrity with High Angular Resolution Diffusion-Weighted Imaging 5th

Assessment of White Matter Fiber Integrity with High Angular...

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5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Sahoo, Girija Shankar Kumar, Ravindra Singh, Yaduvir Ganesh, D. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Mathematics Vivekananda Global University Jaipur India Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India

ISBN: (纸本)9789819780426

A sophisticated imaging method to unravel white count number (WM) pathways within the mind. It presents precise data about the mind's microstructural structure. this look aims to examine HARDI's ability to compare WM fiber integrity in preceding stroke sufferers. It investigated the utility of HARDI for the evaluation of WM fiber integrity by evaluating FA values from the affected and unaffected aspects in 15 stroke patients and ten wholesome controls. Consequences indicate that FA values were reduced in affected aspects of stroke patients in comparison to the unaffected facets and also as compared to the wholesome controls. those findings suggest that HARDI is a legitimate measure for assessing WM fiber integrity in stroke patients and may be used as a capacity imaging biomarker for detecting injury or degeneration of brain structures related to stroke. Excessive angular decision Diffusion-Weighted Imaging (HARDI) is an effective method that mind. HARDI allows for better angular decisions than maximum other methods, as much as a maximum resolution of ≤60 instructions, which permits extra unique measurements of the water diffusion in tissue, thereby generating a correct measure of the agency of white be-counted pathways inside the mind. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Compare Microstructural Microstructural Unravel Weighted

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CV-CXR: A Method for Classification and Visualisation of Covid-19 virus using CNN and Heatmap 5

CV-CXR: A Method for Classification and Visualisation of Cov...

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5th international conference on Recent Advances in Information technology, RAIT 2023

作者： Ajad, Ashok Saini, Taniya Niranjan, Kumar M L&t Technology Services Bangalore India

ISBN: (纸本)9798350335705

Nowadays Covid-19 is prevailing across the world, it has affected millions of populations across the world. the exponential increase in covid cases makes the health care system overwhelmed. Many testing methods are used for covid-19 detection like Rapid antigen test, RT-PCR test, etc. these tests have certain limitations, sometimes people got confused between respiratory infection and covid-19infection, as many symptoms are similar. So for confirming the disease, a chest x-ray is preferred. Covid-19 has similar symptoms of pneumonia, consolidation, and ground-glass opacities, in our approach we consider them as covid. In this paper, images are acquired from reputed hospitals and various online datasets used in Covidnet architecture. After accumulation, the dataset is verified by experienced radiologists. In our approach, we trained our models on various symptoms of covid19 like pneumonia, consolidation, ggopacities and finally on covid-19 dataset images. In our research, we have used single as well as ensemble models for classification. Models like densenet, efficient net, resnet, etc are used. Certain preprocessing techniques are used before passing the image dataset into training like adaptive histogram equalization, data augmentation methods, etc. Finally, a approach based on Deep Learning used for identification of covid 19. We are claiming 95% plus testing accuracy and 99% training accuracy. Beyond classification, we further generate the reports and localize the covid virus on Xray using various visualization methods. Further results are classified based on single and ensemble models on the in-house dataset. © 2023 IEEE.

关键词： Visualization

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Palmprint Encryption and Authentication Method Based on Masked Autoencoders 5th

Palmprint Encryption and Authentication Method Based on Mask...

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5th international conference on Artificial Intelligence in China, AIC 2023

作者： Feng, Yuanchao Chen, Bingcai School of Computer Science and Technology Xinjiang Normal University Urumqi830054 China School of Computer Science and Technology Dalian University of Technology Liaoning Dalian116024 China

ISBN: (纸本)9789819975440

With the rapid development of biometric recognition technology in the field of deep learning, such as face recognition, iris recognition and palmprint recognition, they are widely used in various fields, but with them comes the serious problem of information leakage and privacy protection. In this paper, we propose a palmprint encryption and authentication method based on the image recovery model MAE. Only 25% of the location information and features in the original image data are encrypted and saved separately, and then the encrypted data is used to generate an image and compare it with the original image for authentication purposes, and the encryption and authentication process is achieved with extremely low memory and resource consumption. the model has a very low image retention rate of 25% and uses de-imagination and fragmentation techniques to achieve privacy protection of palmprint data and ensure the security of biometrics through the irreversibility of data encryption. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image reconstruction

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An improved LEACH-FV protocol for communication networking during offshore operations of small fishing vessels 5

An improved LEACH-FV protocol for communication networking d...

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5th international conference on Computer Communication and Network Security, CCNS 2024

作者： Nie, Wuzhou Ren, Yunfei Jiang, Baihui Li, Meng Ning, Lei College of Big Data and Internet Shenzhen Technology University Shenzhen518118 China

ISBN: (纸本)9781510681842

In current offshore fishing operations, there is a growing demand for long-distance operations by small and medium-sized fishing vessels. However, due to the remote distance from the land, terrestrial communication infrastructure such as land-based communication stations cannot communicate with these vessels in a timely manner. Installing satellite communication equipment on fishing vessels is a common method for communication, but the limited bandwidth capacity and expensive cost of satellite communication make it impossible to maintain continuous real-time communication with all fishing vessels. Utilizing the LEACH (Low Energy Adaptive Clustering Hierarchy) networking protocol for vessel networking communication can effectively address such issues. this involves integrating information from cluster head vessels within a cluster and then communicating with satellites, thus enabling satellite communication for vessels within the cluster and extending the lifespan of the communication network. However, the main challenges during offshore fishing operations are the long communication distances and significant delays, compounded by the limited energy carried by communication terminals. therefore, the traditional Leach protocol's frequent cluster iteration leading to communication energy consumption and substantial time overhead cannot be ignored. To address these challenges, this paper proposes an improved protocol named LEACH-FV. this protocol optimizes cluster head selection based on parameters such as remaining energy and location information of communication nodes, specifically tailored for scenarios with large delays and long communication distances. Furthermore, optimizations are made during subsequent cluster iteration rounds, effectively enhancing the survival period of communication networks for fishing vessels. Simulation conducted using Matlab, comparing the proposed LEACH-FV protocol with several clustering networking protocols including LEACH, LEACH-C, and

关键词： Satellite communication systems

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User-Centric Design: Flexible Strain Sensor Adhesive Tape 5

User-Centric Design: Flexible Strain Sensor Adhesive Tape

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5th IEEE international conference on Flexible and Printable Sensors and Systems, FLEPS 2023

作者： Sankar, Vetrivel Balasubramaniam, Krishnan Ramaprabhu, Sundara Indian Institute of Technology Madras Alternative Energy and Nanotechnology Laboratory Department of Physics Chennai India Center for Non-Destructive Evaluation Indian Institute of Technology Madras Department of Mechanical Engineering Chennai India

ISBN: (纸本)9781665457330

this research work focuses on developing a design framework for flexible strain sensors considering sensor performance, end-user difficulties and industrial packaging-cum-scalable feasibility. the sensor is prepared from PVDC-co-VC and PSS-CNT polymer nanocomposite with an underneath adhesive coating and a top copper contact pad. the ratio of PVDC-co-VC/PSS-CNT is optimized towards its percolation to achieve maximum sensing performance. the developed flexible strain sensor tape shows a gauge factor of 15± 1, and it is consistent throughout the length of the sensor tape. the PSS polymer functionalization plays a critical role in achieving the homogenized dispersion of CNT nanofillers which ensures the constant gauge factor along the length of the sensor. Finally, the flexible strain sensor is demonstrated for wearable electronics applications using an IOT-enabled portable interface device. © 2023 IEEE.

关键词： Nanocomposites

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Explore the Impact of Quantum Computing to Enhance Cryptographic Protocols and Network Security Measures 5

Explore the Impact of Quantum Computing to Enhance Cryptogra...

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5th IEEE international conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Ambika, S. Balaji, V. Rajasekaran, R.thalapathi Periyasamy, P.N. Kamal, N. E. G. S. Pillay Engineering College Department of Information Technology Tamil Nadu Nagapattinam India Chennai India Saveetha School of Engineering Simats Dept. of Computer Science and Engineering Chennai India Hindusthan Institute of Technology Department of Computer Science and Engineering India Grt Institute of Engineering and Technology Dept. of Computer Science and Engineering Tamil Nadu Tiruttani India

ISBN: (纸本)9798350383522

the revolutionary effects of quantum computing on security procedures for networks and cryptographic protocols are the focus of this study. Our research shows that conventional cryptographic algorithms are susceptible to quantum assaults;specifically, RSA and ECC encryption are very vulnerable. On the other hand, cryptographic algorithms that are immune to quantum attacks, such as multivariate polynomial cryptography and lattice-based algorithms, show promise in meeting these challenges. Key exchange rates between 200 kbps and 450 kbps and error rates as low as 0.5% are some of the significant achievements shown by Quantum Key Distribution (QKD) implementations. these applications show that QKD is a viable solution for protecting communication channels up to 200 km away. On top of that, there are remarkable outcomes when network security systems incorporate quantum advancements. the detection accuracy of Quantum-Enhanced Intrusion Detection Systems (QIDS) is 98.5% and the false positive rate is minimally 0.2%. the detection accuracy of quantum-secured communication systems is 99.2% and the false positive rate is an extremely low 0.1%. While quantum firewalls keep a detection accuracy of 97.8% and a false positive rate of 0.3%, quantum-safe cryptographic modules show a low latency of 3 ms. © 2024 IEEE.

关键词： cryptographic protocol data security quantum key distribution quantum-enhanced intrusion detection

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Segmenting Stenotic Regions from Coronary Angiograms using Mask Region-based Convolutional Neural Network 5

Segmenting Stenotic Regions from Coronary Angiograms using M...

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5th international conference on data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Velvizhi, R. Ankayarkanni, B. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350389609

Coronary artery disease (CAD) is the primary cause of mortality and a key driver of healthcare expenses globally. Accurately segmenting stenotic regions from coronary angiograms is decisive in identifying and treating cardiovascular diseases. However, it is a challenging task for medical professionals to use X-ray Coronary Angiogram (XCA) due to the reduced signal quality, the existence of obstructive contextual elements, and various types of noise. Furthermore, handcrafted segmentation is arduous, laborious, and prone to inconsistencies and human errors. In this context, this research aim to develop an automatic stenosis segmentation system using a deep network. Initially, the input image is processed by Gaussian filters and the improved angiogram is filtered by Hessian-based Vessel Filtering (HVF) technique to increase the clarity of vascular components in the angiogram images. this study identifies the branch points (BP) in the angiograms based on the eigenvalues of the Hessian matrix. the proposed model employ a Mask Region-based Convolutional Neural Network (Mask R-CNN) to provide precise pixel-wise masks for every detected stenosis. the proposed Mask R-CNN includes (i) ResNet50 as the backbone network to extract significant attributes;(ii) Region Proposal Network (RPN) to identify possible Regions of Interest (RoIs) that may have stenosis;(iii) RoI Align to ensure precise alignment of the RoIs for improved mask prediction;and (iv) a mask branch to create a pixel-level segmentation mask for each RoI. the effectiveness of the model is assessed by applying an open-access ARCADE Phase 1 (Automatic Region-based CAD diagnostics using XCA images) dataset. the Mask R-CNN model achieves better results with 97.8% dice score, 92.9% sensitivity, and 96.6% specificity. Besides, it provides reduced standard deviation (SD) in the segmentation task with a 0.8% dice score, 1.0% sensitivity, and 1.0% specificity. these results shows that the Mask R-CNN model provides more relia

关键词： Eigenvalues and eigenfunctions

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Exploring Novel Machine Learning Approaches for Cheat Detection in Competitive Gaming 5

Exploring Novel Machine Learning Approaches for Cheat Detect...

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5th international conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Singh, Uday Pratap Kumari, Bersha Goyal, Dinesh Afrid, Mohd Department of Artificial Intelligence & Data Science Poornima Institute of Engineering & Technology Jaipur India

ISBN: (纸本)9798400709418

the issue of cheating in competitive gaming is a major concern that undermines fair play and the overall gaming experience. Although machine learning has proven to be an effective tool for detecting cheats, there is still untapped potential for innovative approaches that can further improve anti-cheat systems. this research paper delves into unexplored machine learning methods that hold promise for future cheat detection strategies. these include Graph Neural Networks (GNNs) for multifaceted analysis, reinforcement learning-based cheat adaptation, federated learning for privacy-preserving cheat detection, Explainable AI (XAI) for transparent cheat detection, Generative Adversarial Networks (GANs) for anomaly detection, unsupervised learning for unlabeled data analysis, active learning for efficient data collection, continuous learning for evolving cheat landscapes, multi-agent reinforcement learning for collaborative cheat detection, and transfer learning for cross-game cheat detection. By leveraging these novel techniques, the gaming industry can develop more robust and comprehensive cheat detection solutions that uphold the integrity of competitive gaming environments. © 2023 ACM.

关键词： Unsupervised learning

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Assessment of rural built environment based on regional adaptability: An empirical study of the Huinong Center in Guangzhou Jingxia Village 5

Assessment of rural built environment based on regional adap...

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5th international conference on Green Energy, Environment, and Sustainable Development, GEESD 2024

作者： Chen, Jue Dai, Xuejuan Zhao, Fei Wang, Chen School of Arts and Design Guangdong University of Finance & Economics Guangdong Guangzhou510320 China School of Design South China University of Technology Guangzhou Higher Education Mega Centre Guangdong Guangzhou510006 China

ISBN: (纸本)9781510683006

this study attempts to introduce "regional adaptability" as an indicator for evaluating the Environmental sustainability in the context of New Rural Construction. the newly constructed Huinong Center in Jingxia Village, located on the outskirts of the Pearl River Delta region, was chosen as the research subject. through surveys of different groups of people regarding their evaluations of the built environment in the new rural areas and by using factor-regression analysis, nine independent variables were condensed from various influencing factors to generate a regional adaptability evaluation index model. the regression analysis further clarified these nine independent variables and identified four variables, namely, satisfaction with agricultural support, sensory satisfaction, usage satisfaction, and hygiene satisfaction, that had a positive impact on the new rural construction environment. these variables were determined to be the dominant factors influencing the changes in the rural built environment. © 2024 SPIE.

关键词： Natural environment

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