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...
详细信息
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.
In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of *** studies focus on optimizing base station deployment under t...
详细信息
In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of *** studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind ***,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic ***,research in this area still needs to be *** paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this *** algorithm considers the dynamic alterations in obstacle locations within the designated *** determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage *** experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle *** results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles *** 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.
High dynamic range (HDR) images are the one's which includes all the objects from the original scene with correct exposure. The HDR content can be very helpful in analysis purposes as it possess all features of th...
详细信息
Software is unavoidable in software development and *** literature,many methods are discussed which fails to achieve efficient software bug detection and *** this paper,efficient Adaptive Deep Learning Model(ADLM)is d...
详细信息
Software is unavoidable in software development and *** literature,many methods are discussed which fails to achieve efficient software bug detection and *** this paper,efficient Adaptive Deep Learning Model(ADLM)is developed for automatic duplicate bug report detection and classification *** proposed ADLM is a combination of Conditional Random Fields decoding with Long Short-Term Memory(CRF-LSTM)and Dingo Optimizer(DO).In the CRF,the DO can be consumed to choose the efficient weight value in *** proposed automatic bug report detection is proceeding with three stages like pre-processing,feature extraction in addition bug detection with ***,the bug report input dataset is gathered from the online source *** the pre-processing phase,the unwanted information from the input data are removed by using cleaning text,convert data types and null value *** pre-processed data is sent into the feature extraction *** the feature extraction phase,the four types of feature extraction method are utilized such as contextual,categorical,temporal and ***,the features are sent to the proposed ADLM for automatic duplication bug report detection and *** proposed methodology is proceeding with two phases such as training and testing *** on the working process,the bugs are detected and classified from the input *** projected technique is assessed by analyzing performance metrics such as accuracy,precision,Recall,F_Measure and kappa.
In this work, a virtual toll booth system utilizing cutting-edge technologies like EasyOCR with optical character recognition, or OCR, and YOLOv8 for object detection is introduced. By connecting the accounts stored i...
详细信息
Visual Question Answering for the visually impaired is an emerging and important research area. This field centers on creating technologies so visually impaired people can interact with their surroundings and learn by...
详细信息
Phishing attacks, a prevalent form of social engineering and cyber threats, exploit human vulnerabilities to deceive internet users into divulging sensitive data for deceptive intentions. Among these, URL-based phishi...
详细信息
Presently,precision agriculture processes like plant disease,crop yield prediction,species recognition,weed detection,and irrigation can be accom-plished by the use of computer vision(CV)*** plays a vital role in infl...
详细信息
Presently,precision agriculture processes like plant disease,crop yield prediction,species recognition,weed detection,and irrigation can be accom-plished by the use of computer vision(CV)*** plays a vital role in influencing crop *** wastage and pollution of farmland's natural atmosphere instigated by full coverage chemical herbicide spraying are *** the proper identification of weeds from crops helps to reduce the usage of herbicide and improve productivity,this study presents a novel computer vision and deep learning based weed detection and classification(CVDL-WDC)model for precision *** proposed CVDL-WDC technique intends to prop-erly discriminate the plants as well as *** proposed CVDL-WDC technique involves two processes namely multiscale Faster RCNN based object detection and optimal extreme learning machine(ELM)based weed *** parameters of the ELM model are optimally adjusted by the use of farmland fertility optimization(FFO)algorithm.A comprehensive simulation analysis of the CVDL-WDC technique against benchmark dataset reported the enhanced out-comes over its recent approaches interms of several measures.
Heart disease, a global health burden, demands early and accurate detection. While vast medical datasets exist, extracting crucial diagnostic patterns remains a challenge. This study investigates the potential of deep...
详细信息
With the increasing number of devices in the Internet of Things (IoT), security has become a necessary feature. Compared to traditional key encryption methods, IoT device authentication protocols based on strong Physi...
详细信息
暂无评论