The Telecare Medicine Information System (TMIS) revolutionizes healthcare delivery by integrating medical equipment and sensors, facilitating proactive and cost-effective services. Accessible online, TMIS empowers pat...
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Traditional e-commerce recommendation systems often struggle with dynamic user preferences and a vast array of products,leading to suboptimal user *** address this,our study presents a Personalized Adaptive Multi-Prod...
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Traditional e-commerce recommendation systems often struggle with dynamic user preferences and a vast array of products,leading to suboptimal user *** address this,our study presents a Personalized Adaptive Multi-Product Recommendation System(PAMR)leveraging transfer learning and Bi-GRU(Bidirectional Gated Recurrent Units).Using a large dataset of user reviews from Amazon and Flipkart,we employ transfer learning with pre-trained models(AlexNet,GoogleNet,ResNet-50)to extract high-level attributes from product data,ensuring effective feature representation even with limited ***-GRU captures both spatial and sequential dependencies in user-item *** innovation of this study lies in the innovative feature fusion technique that combines the strengths of multiple transfer learning models,and the integration of an attention mechanism within the Bi-GRU framework to prioritize relevant *** approach addresses the classic recommendation systems that often face challenges such as cold start along with data sparsity difficulties,by utilizing robust user and item *** model demonstrated an accuracy of up to 96.9%,with precision and an F1-score of 96.2%and 96.97%,respectively,on the Amazon dataset,significantly outperforming the baselines and marking a considerable advancement over traditional *** study highlights the effectiveness of combining transfer learning with Bi-GRU for scalable and adaptive recommendation systems,providing a versatile solution for real-world applications.
The growing dependence on deep learning models for medical diagnosis underscores the critical need for robust interpretability and transparency to instill trust and ensure responsible usage. This study investigates th...
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To enhance the efficiency and accuracy of environmental perception for autonomous vehicles,we propose GDMNet,a unified multi-task perception network for autonomous driving,capable of performing drivable area segmentat...
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To enhance the efficiency and accuracy of environmental perception for autonomous vehicles,we propose GDMNet,a unified multi-task perception network for autonomous driving,capable of performing drivable area segmentation,lane detection,and traffic object ***,in the encoding stage,features are extracted,and Generalized Efficient Layer Aggregation Network(GELAN)is utilized to enhance feature extraction and gradient ***,in the decoding stage,specialized detection heads are designed;the drivable area segmentation head employs DySample to expand feature maps,the lane detection head merges early-stage features and processes the output through the Focal Modulation Network(FMN).Lastly,the Minimum Point Distance IoU(MPDIoU)loss function is employed to compute the matching degree between traffic object detection boxes and predicted boxes,facilitating model training *** results on the BDD100K dataset demonstrate that the proposed network achieves a drivable area segmentation mean intersection over union(mIoU)of 92.2%,lane detection accuracy and intersection over union(IoU)of 75.3%and 26.4%,respectively,and traffic object detection recall and mAP of 89.7%and 78.2%,*** detection performance surpasses that of other single-task or multi-task algorithm models.
The Internet of Things (IoT), which enables seamless connectivity and effective data exchange between physical items and digital systems, has completely changed the way we interact with our surroundings. This study ev...
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The increase in number of people using the Internet leads to increased cyberattack *** Persistent Threats,or APTs,are among the most dangerous targeted *** attacks utilize various advanced tools and techniques for att...
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The increase in number of people using the Internet leads to increased cyberattack *** Persistent Threats,or APTs,are among the most dangerous targeted *** attacks utilize various advanced tools and techniques for attacking targets with specific *** countries with advanced technologies,like the US,Russia,the UK,and India,are susceptible to this targeted *** is a sophisticated attack that involves multiple stages and specific ***,TTP(Tools,Techniques,and Procedures)involved in the APT attack are commonly new and developed by an attacker to evade the security ***,APTs are generally implemented in multiple *** one of the stages is detected,we may apply a defense mechanism for subsequent stages,leading to the entire APT attack *** detection at the early stage of APT and the prediction of the next step in the APT kill chain are ongoing *** survey paper will provide knowledge about APT attacks and their essential *** follows the case study of known APT attacks,which will give clear information about the APT attack process—in later sections,highlighting the various detection methods defined by different researchers along with the limitations of the *** used in this article comes from the various annual reports published by security experts and blogs and information released by the enterprise networks targeted by the attack.
Capacitive pressure sensors have attracted considerable interest due to their high sensitivity, low energy consumption, and potential for miniaturization, making them suitable for applications in automotive systems, c...
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In modern society,an increasing number of occasions need to effectively verify people's *** is the most ef-fective technology for personal *** research on automated biometrics recognition mainly started in the 196...
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In modern society,an increasing number of occasions need to effectively verify people's *** is the most ef-fective technology for personal *** research on automated biometrics recognition mainly started in the 1960s and *** the following 50 years,the research and application of biometrics have achieved fruitful *** 2014-2015,with the successful applications of some emerging information technologies and tools,such as deep learning,cloud computing,big data,mobile communication,smartphones,location-based services,blockchain,new sensing technology,the Internet of Things and federated learning,biometric technology entered a new development ***,taking 2014-2015 as the time boundary,the development of biometric technology can be divided into two *** addition,according to our knowledge and understanding of biometrics,we fur-ther divide the development of biometric technology into three phases,i.e.,biometrics 1.0,2.0 and *** 1.0 is the primary de-velopment phase,or the traditional development *** 2.0 is an explosive development phase due to the breakthroughs caused by some emerging information *** present,we are in the development phase of biometrics *** 3.0 is the future development phase of *** the biometrics 3.0 phase,biometric technology will be fully mature and can meet the needs of various *** 1.0 is the initial phase of the development of biometric technology,while biometrics 2.0 is the advanced *** this paper,we provide a brief review of biometrics ***,the concept of biometrics 2.0 is defined,and the architecture of biometrics 2.0 is *** particular,the application architecture of biometrics 2.0 in smart cities is *** challenges and perspectives of biometrics 2.0 are also discussed.
Removing noise in the real-world scenario has been a daunting task in the field of natural language processing. Research has shown that Deep Neural Networks (DNN) have proven to be very useful in terms of noise genera...
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With its untameable and traceable properties,blockchain technology has been widely used in the field of data *** to preserve individual privacy while enabling efficient data queries is one of the primary issues with s...
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With its untameable and traceable properties,blockchain technology has been widely used in the field of data *** to preserve individual privacy while enabling efficient data queries is one of the primary issues with secure data *** this paper,we study verifiable keyword frequency(KF)queries with local differential privacy in *** the numerical and the keyword attributes are present in data objects;the latter are sensitive and require privacy ***,prior studies in blockchain have the problem of trilemma in privacy protection and are unable to handle KF *** propose an efficient framework that protects data owners’privacy on keyword attributes while enabling quick and verifiable query processing for KF *** framework computes an estimate of a keyword’s frequency and is efficient in query time and verification object(VO)size.A utility-optimized local differential privacy technique is used for privacy *** data owner adds noise locally into data based on local differential privacy so that the attacker cannot infer the owner of the keywords while keeping the difference in the probability distribution of the KF within the privacy *** propose the VB-cm tree as the authenticated data structure(ADS).The VB-cm tree combines the Verkle tree and the Count-Min sketch(CM-sketch)to lower the VO size and query *** VB-cm tree uses the vector commitment to verify the query *** fixed-size CM-sketch,which summarizes the frequency of multiple keywords,is used to estimate the KF via hashing *** conduct an extensive evaluation of the proposed *** experimental results show that compared to theMerkle B+tree,the query time is reduced by 52.38%,and the VO size is reduced by more than one order of magnitude.
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