Advancements in medical technology have paved the way for non-invasive methods of assessing vital parameters, marking a significant innovation in healthcare. This research addresses the challenge of contactless health...
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Anticlustering involves partitioning objects into groups such that intergroup similarity is high and intragroup heterogeneity is high. In this paper, we propose five methods for anticlustering. The first proposed meth...
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Daily environment navigating and accessing visual information are critical problems for people with vision disabilities. To reduce this discrepancy VisionAid, an assistive application was introduced to make visually c...
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This research paper presents a comprehensive, intelligent system for detecting plant diseases using deep learning models. The system's novelty lies in its ability to automatically retrain itself when sufficient ne...
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Currently, free space optics (FSO) is the most promising technology for achieving high data transfer over short to medium or even long distances. Thus, FSO provides wireless line-of-sight (LOS) connectivity in the unl...
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The primary concern behind ownership in Web of Things (WoT) is to provide rights to own devices to operate and access. When the ownership of Internet of Things (IoT) devices changes, there is a likelihood of threats t...
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Sparse representation is an effective data classification algorithm that depends on the known training samples to categorise the test *** has been widely used in various image classification *** in sparse representati...
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Sparse representation is an effective data classification algorithm that depends on the known training samples to categorise the test *** has been widely used in various image classification *** in sparse representation means that only a few of instances selected from all training samples can effectively convey the essential class-specific information of the test sample,which is very important for *** deformable images such as human faces,pixels at the same location of different images of the same subject usually have different ***,extracting features and correctly classifying such deformable objects is very ***,the lighting,attitude and occlusion cause more *** the problems and challenges listed above,a novel image representation and classification algorithm is ***,the authors’algorithm generates virtual samples by a non-linear variation *** method can effectively extract the low-frequency information of space-domain features of the original image,which is very useful for representing deformable *** combination of the original and virtual samples is more beneficial to improve the clas-sification performance and robustness of the ***,the authors’algorithm calculates the expression coefficients of the original and virtual samples separately using the sparse representation principle and obtains the final score by a designed efficient score fusion *** weighting coefficients in the score fusion scheme are set entirely ***,the algorithm classifies the samples based on the final *** experimental results show that our method performs better classification than conventional sparse representation algorithms.
Currently,mobile communication is one of the widely used means of ***,it is quite challenging for a telecommunication company to attract new *** recent concept of mobile number portability has also aggravated the pro...
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Currently,mobile communication is one of the widely used means of ***,it is quite challenging for a telecommunication company to attract new *** recent concept of mobile number portability has also aggravated the problem of customer *** need to identify beforehand the customers,who could potentially churn out to the *** the telecommunication industry,such identification could be done based on call detail *** research presents an extensive experimental study based on various deep learning models,such as the 1D convolutional neural network(CNN)model along with the recurrent neural network(RNN)and deep neural network(DNN)for churn *** use the mobile telephony churn prediction dataset obtained from ***,containing the data for around 100,000 individuals,out of which 86,000 are non-churners,whereas 14,000 are churned *** imbalanced data are handled using undersampling and *** accuracy for CNN,RNN,and DNN is 91%,93%,and 96%,***,DNN got 99%for ROC.
The Internet of Things(IoT)has been growing over the past few years due to its flexibility and ease of use in real-time *** IoT's foremost task is ensuring that there is proper communication among different types ...
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The Internet of Things(IoT)has been growing over the past few years due to its flexibility and ease of use in real-time *** IoT's foremost task is ensuring that there is proper communication among different types of applications and devices,and that the application layer protocols fulfill this ***,as the number of applications grows,it is necessary to modify or enhance the application layer protocols according to specific IoT applications,allowing specific issues to be addressed,such as dynamic adaption to network conditions and ***,several IoT application layer protocols have been enhanced and modified according to application ***,no existing survey articles focus on these *** this article,we survey traditional and recent advances in IoT application layer protocols,as well as relevant real-time applications and their adapted application layer protocols for improving *** changing the nature of protocols for each application is unrealistic,machine learning offers means of making protocols intelligent and is able to adapt *** this context,we focus on providing open challenges to drive IoT application layer protocols in such a direction.
Previous research on radiology report generation has made significant progress in terms of increasing the clinical accuracy of generated *** this paper, we emphasize another crucial quality that it should possess, i.e...
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