In the enormous field of Natural Language Processing (NLP), deciphering the intended significance of a word among a multitude of possibilities is referred to as word sense disambiguation. This process is essential for...
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Cancer remains a leading cause of mortality worldwide, with early detection and accurate diagnosis critical to improving patient outcomes. While computer-aided diagnosis systems powered by deep learning have shown con...
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Security is a major challenge in storage and transmission of digital data. Secret sharing scheme is a fundamental primitive used in multiparty computations, access control and key management, which is based here on tw...
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Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system ***,the Internet of Things(IoT)has revolutionized the Fourth...
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Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system ***,the Internet of Things(IoT)has revolutionized the Fourth Industrial Revolution by enabling interconnected devices to offer innovative services,ultimately enhancing human *** paper presents a new approach utilizing lightweight blockchain technology,effectively reducing the computational burden typically associated with conventional blockchain *** integrating this lightweight blockchain with IoT systems,substantial reductions in implementation time and computational complexity can be ***,the paper proposes the utilization of the Okamoto Uchiyama encryption algorithm,renowned for its homomorphic characteristics,to reinforce the privacy and security of IoT-generated *** integration of homomorphic encryption and blockchain technology establishes a secure and decentralized platformfor storing and analyzing sensitive data of the supply chain *** platformfacilitates the development of some business models and empowers decentralized applications to perform computations on encrypted data while maintaining data *** results validate the robust security of the proposed system,comparable to standard blockchain implementations,leveraging the distinctive homomorphic attributes of the Okamoto Uchiyama algorithm and the lightweight blockchain paradigm.
Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the *** Convolution Network(GCN)algorithms have been employed to...
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Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the *** Convolution Network(GCN)algorithms have been employed to implement the RIS ***,the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning *** address this issue,we propose a Weighted Forwarding method using the GCN(WF-GCN)*** proposed method involves multiplying the embedding results with different weights for each hop layer during graph *** applying the WF-GCN algorithm,which adjusts weights for each hop layer before forwarding to the next,nodes with many neighbors achieve higher embedding *** approach facilitates the learning of more hop layers within the GCN *** efficacy of the WF-GCN was demonstrated through its application to various *** the MovieLens dataset,the implementation of WF-GCN in LightGCN resulted in significant performance improvements,with recall and NDCG increasing by up to+163.64%and+132.04%,***,in the *** dataset,LightGCN using WF-GCN enhanced with WF-GCN showed substantial improvements,with the recall and NDCG metrics rising by up to+174.40%and+169.95%,***,the application of WF-GCN to Self-supervised Graph Learning(SGL)and Simple Graph Contrastive Learning(SimGCL)also demonstrated notable enhancements in both recall and NDCG across these datasets.
Air is very beneficial and crucial for every living creature on earth, hence it is very important to protect the air quality in order to avoid diseases. However, due to the increase in population, some human activitie...
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Emotion Recognition is one field that is taking the world by storm in this current age. Multimodal emotion recognition has shown promising results however, previous studies shows that recognition using speech is a fie...
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The primary goals of research in the fields of Artificial Intelligence (AI) and Machine Learning (ML) are to develop an autonomous agent that can perform tasks or make decisions without human intervention. Deep Reinfo...
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Nuclei segmentation is a challenging task in histopathology *** is challenging due to the small size of objects,low contrast,touching boundaries,and complex structure of *** segmentation and counting play an important...
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Nuclei segmentation is a challenging task in histopathology *** is challenging due to the small size of objects,low contrast,touching boundaries,and complex structure of *** segmentation and counting play an important role in cancer identification and its *** this study,WaveSeg-UNet,a lightweight model,is introduced to segment cancerous nuclei having touching *** blocks are used for feature *** one feature extractor block is used in each level of the encoder and ***,images degrade quality and lose important information during *** overcome this loss,discrete wavelet transform(DWT)alongside maxpooling is used in the down-sampling *** DWT is used to regenerate original images during *** the bottleneck of the proposed model,atrous spatial channel pyramid pooling(ASCPP)is used to extract effective high-level *** ASCPP is the modified pyramid pooling having atrous layers to increase the area of the receptive *** and channel-based attention are used to focus on the location and class of the identified ***,watershed transform is used as a post processing technique to identify and refine touching boundaries of *** are identified and counted to facilitate *** same domain of transfer learning is used to retrain the model for domain *** of the proposed model are compared with state-of-the-art models,and it outperformed the existing studies.
The oropharyngeal swabbing is a pre-diagnostic procedure used to test various respiratory diseases, including COVID and Influenza A (H1N1). To improve the testing efficiency of testing, a real-time, accurate, and robu...
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The oropharyngeal swabbing is a pre-diagnostic procedure used to test various respiratory diseases, including COVID and Influenza A (H1N1). To improve the testing efficiency of testing, a real-time, accurate, and robust sampling point localization algorithm is needed for robots. However, current solutions rely heavily on visual input, which is not reliable enough for large-scale deployment. The transformer has significantly improved the performance of image-related tasks and challenged the dominance of traditional convolutional neural networks (CNNs) in the image field. Inspired by its success, we propose a novel self-aligning multi-modal transformer (SAMMT) to dynamically attend to different parts of unaligned feature maps, preventing information loss caused by perspective disparity and simplifying overall implementation. Unlike preexisting multi-modal transformers, our attention mechanism works in image space instead of embedding space, rendering the need for the sensor registration process obsolete. To facilitate the multi-modal task, we collected and annotate an oropharynx localization/segmentation dataset by trained medical personnel. This dataset is open-sourced and can be used for future multi-modal research. Our experiments show that our model improves the performance of the localization task by 4.2% compared to the pure visual model, and reduces the pixel-wise error rate of the segmentation task by 16.7% compared to the CNN baseline.
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