This research project centres on creating an inclusive environment for the specially-abled. Created an app that integrates real-time object detection and speech-to-text capabilities which provides a multi-modal user e...
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Natural language processing (NLP) is an area of research and study that makes it possible for computers to comprehend human language by utilising software engineering concepts from computer science and artificial inte...
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Remote intelligence in the application of robotics and the autonomous system relies heavily on seamless wireless connections. The 5G mobile network technology meets traditional manufacturing enterprises' applicati...
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Remote intelligence in the application of robotics and the autonomous system relies heavily on seamless wireless connections. The 5G mobile network technology meets traditional manufacturing enterprises' application requirements for wireless networks based on robot transformation and upgrading, robot interconnection, and remote interactive applications in production. However, there exists many challenging 5G communication issues, such as different communication protocols in the system varies with different robots and no dis-ruptive changes to the physical layer.
Knowledge graphs represent a potent instrument for the classification and exhibition of data, as they encompass a systematic approach for the containment and retrieval of multifarious datasets. In finance, the utiliza...
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The detection of road anomalies in highway management is a crucial yet manpower-demanding task. Although there have been many previous types of research based on visual and acceleration data collected from vehicles. H...
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Wireless sensor networks (WSNs) are normally conveyed in arbitrary regions with no security. The source area uncovers significant data about targets. In this paper, a plan dependent on the cloud utilising data publish...
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Vehicular ad hoc networks (VANETs) have emerged as a key area of interest in the research community due to their wide range of applications. As the number of vehicles increases, VANETs encounter challenges with access...
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Capturing the distributed platform with remotely controlled compromised machines using botnet is extensively analyzed by various ***,certain limitations need to be addressed *** provisioning of detection mechanism wit...
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Capturing the distributed platform with remotely controlled compromised machines using botnet is extensively analyzed by various ***,certain limitations need to be addressed *** provisioning of detection mechanism with learning approaches provides a better solution more broadly by saluting multi-objective *** bots’patterns or features over the network have to be analyzed in both linear and non-linear *** linear and non-linear features are composed of high-level and low-level *** collected features are maintained over the Bag of Features(BoF)where the most influencing features are collected and provided into the classifier ***,the linearity and non-linearity of the threat are evaluated with Support Vector Machine(SVM).Next,with the collected BoF,the redundant features are eliminated as it triggers overhead towards the predictor ***,a novel Incoming data Redundancy Elimination-based learning model(RedE-L)is built to classify the network features to provide robustness towards BotNets *** simulation is carried out in MATLAB environment,and the evaluation of proposed RedE-L model is performed with various online accessible network traffic dataset(benchmark dataset).The proposed model intends to show better tradeoff compared to the existing approaches like conventional SVM,C4.5,RepTree and so ***,various metrics like Accuracy,detection rate,Mathews Correlation Coefficient(MCC),and some other statistical analysis are performed to show the proposed RedE-L model's *** F1-measure is 99.98%,precision is 99.93%,Accuracy is 99.84%,TPR is 99.92%,TNR is 99.94%,FNR is 0.06 and FPR is 0.06 respectively.
As a result of its aggressive nature and late identification at advanced stages, lung cancer is one of the leading causes of cancer-related deaths. Lung cancer early diagnosis is a serious and difficult challenge that...
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Imagine numerous clients,each with personal data;individual inputs are severely corrupt,and a server only concerns the collective,statistically essential facets of this *** several data mining methods,privacy has beco...
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Imagine numerous clients,each with personal data;individual inputs are severely corrupt,and a server only concerns the collective,statistically essential facets of this *** several data mining methods,privacy has become highly *** a result,various privacy-preserving data analysis technologies have ***,we use the randomization process to reconstruct composite data attributes ***,we use privacy measures to estimate how much deception is required to guarantee *** are several viable privacy protections;however,determining which one is the best is still a work in *** paper discusses the difficulty of measuring privacy while also offering numerous random sampling procedures and statistical and categorized data ***-more,this paper investigates the use of arbitrary nature with perturbations in privacy *** to the research,arbitrary objects(most notably random matrices)have"predicted"frequency *** shows how to recover crucial information from a sample damaged by a random number using an arbi-trary lattice spectral selection *** system's conceptual frame-work posits,and extensive practicalfindings indicate that sparse data distortions preserve relatively modest privacy protection in various *** a result,the research framework is efficient and effective in maintaining data privacy and security.
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