In this work, we study the parameters impacting transmission energy consumption in Content-Centric Networking (CCN). This paper considers various cache placement strategies, and it presents experimental results for va...
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Medical research relies heavily on image processing tools, especially when it comes to early cancer diagnosis. The application of Gaussian rules and Gabor filters emphasizes image quality and improves photographs. The...
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Engaging in sports is essential for maintaining our mental and physical well being. Sports video libraries are expanding quickly, and as a result, automated classification is becoming necessary for many purposes such ...
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This paper proposes an extension of graph patterns, referred to as ontological graph patterns (OGPs), to accelerate ontology-mediated query answering. OGPs employ graph patterns to support topological queries, attach ...
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This study introduces a refined approach to Text-to-Speech (TTS) generation that significantly enhances sampling stability across languages, with a particular focus on Hebrew. By leveraging discrete semantic units wit...
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Nowadays,review systems have been developed with social media Recommendation systems(RS).Although research on RS social media is increas-ing year by year,the comprehensive literature review and classification of this R...
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Nowadays,review systems have been developed with social media Recommendation systems(RS).Although research on RS social media is increas-ing year by year,the comprehensive literature review and classification of this RS research is limited and needs to be *** previous method did notfind any user reviews within a time,so it gets poor accuracy and doesn’tfilter the irre-levant comments effi*** Recursive Neural Network-based Trust Recom-mender System(RNN-TRS)is proposed to overcome this method’s *** it is efficient to analyse the trust comment and remove the irrelevant sentence ***first step is to collect the data based on the transactional reviews of social *** second step is pre-processing using Imbalanced Col-laborative Filtering(ICF)to remove the null values from the *** the features from the pre-processing step using the Maximum Support Grade Scale(MSGS)to extract the maximum number of scaling features in the dataset and grade the weights(length,count,etc.).In the Extracting features for Training and testing method before that in the feature weights evaluating the softmax acti-vation function for calculating the average weights of the ***,In the classification method,the Recursive Neural Network-based Trust Recommender System(RNN-TRS)for User reviews based on the Positive and negative scores is analysed by the *** simulation results improve the predicting accuracy and reduce time complexity better than previous methods.
IEEE 802.11be Extremely High Throughput (EHT) improves the previous Wi-Fi generations with increased connectivity, throughput, and reliability. One of its key features, multi-link operation (MLO), enables using multip...
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Semantic understanding of point clouds is a major task in 3D scenes. Due to the enormous number of points within point clouds, it is strait to process point clouds directly. Generally, previous work follow a sampler-e...
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Wireless Sensor Networks (WSNs) have limited resources, it is critical to ensure data transmission that is both dependable and energy-efficient. This study provides a unique Transport Protocol designed specifically fo...
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Fifth-generation communication technology enables advanced indoor positioning with its high bandwidth and frequency capabilities. However, indoor environment variability causes signal propagation fluctuations, making ...
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