In this paper, the computation of graph Fourier transform centrality (GFTC) of complex network using graph filter is presented. For conventional computation method, it needs to use the non-sparse transform matrix of g...
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Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband ***,they consume important and scarce net...
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Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband ***,they consume important and scarce network resources such as bandwidth and processing *** have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial *** paper draws its motivation from such real network disaster incidents attributed to signaling *** this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and *** provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding *** important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a *** paper presents an update and an extension of our earlier conference *** our knowledge,no similar survey study exists on the subject.
Timely estimation of earthquake magnitude plays a crucial role in the early warning systems for earthquakes. Despite the inherent danger associated with earthquake energy, earthquake research necessitates extensive pa...
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In batch production systems, detecting low-yield machines is essential for minimizing the production of defective pieces, which is a complex problem that currently requires multiple experts, considerable capital, or a...
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Healthcare systems nowadays depend on IoT sensors for sending data over the internet as a common *** ofmedical images is very important to secure patient *** these images consumes a lot of time onedge computing;theref...
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Healthcare systems nowadays depend on IoT sensors for sending data over the internet as a common *** ofmedical images is very important to secure patient *** these images consumes a lot of time onedge computing;therefore,theuse of anauto-encoder for compressionbefore encodingwill solve such a *** this paper,we use an auto-encoder to compress amedical image before encryption,and an encryption output(vector)is sent out over the *** the other hand,a decoder was used to reproduce the original image back after the vector was received and *** convolutional neural networks were conducted to evaluate our proposed approach:The first one is the auto-encoder,which is utilized to compress and encrypt the images,and the other assesses the classification accuracy of the image after decryption and *** hyperparameters of the encoder were tested,followed by the classification of the image to verify that no critical information was lost,to test the encryption and encoding *** this approach,sixteen hyperparameter permutations are utilized,but this research discusses three main cases in *** first case shows that the combination of Mean Square Logarithmic Error(MSLE),ADAgrad,two layers for the auto-encoder,and ReLU had the best auto-encoder results with a Mean Absolute Error(MAE)=0.221 after 50 epochs and 75%classification with the best result for the classification *** second case shows the reflection of auto-encoder results on the classification results which is a combination ofMean Square Error(MSE),RMSprop,three layers for the auto-encoder,and ReLU,which had the best classification accuracy of 65%,the auto-encoder gives MAE=0.31 after 50 *** third case is the worst,which is the combination of the hinge,RMSprop,three layers for the auto-encoder,and ReLU,providing accuracy of 20%and MAE=0.485.
The UAV-assisted wireless network is envisioned as a key player in the sixth generation (6G) wireless systems. One of the most challenging tasks to make it practically viable is to deploy UAVs considering user density...
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Autism spectrum disorder(ASD),classified as a developmental disability,is now more common in children than ever.A drastic increase in the rate of autism spectrum disorder in children worldwide demands early detection ...
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Autism spectrum disorder(ASD),classified as a developmental disability,is now more common in children than ever.A drastic increase in the rate of autism spectrum disorder in children worldwide demands early detection of autism in *** can seek professional help for a better prognosis of the child’s therapy when ASD is diagnosed under five *** research study aims to develop an automated tool for diagnosing autism in *** computer-aided diagnosis tool for ASD detection is designed and developed by a novel methodology that includes data acquisition,feature selection,and classification *** most deterministic features are selected from the self-acquired dataset by novel feature selection methods before *** Imperialistic competitive algorithm(ICA)based on empires conquering colonies performs feature selection in this *** performance of Logistic Regression(LR),Decision tree,K-Nearest Neighbor(KNN),and Random Forest(RF)classifiers are experimentally studied in this research *** experimental results prove that the Logistic regression classifier exhibits the highest accuracy for the self-acquired *** ASD detection is evaluated experimentally with the Least Absolute Shrinkage and Selection Operator(LASSO)feature selection method and different *** Exploratory Data Analysis(EDA)phase has uncovered crucial facts about the data,like the correlation of the features in the dataset with the class variable.
This research paper inscribes an alarming need for effective bridge health monitoring and controlling amid growing concerns over structural integrity and safety. India has been inherited by n number of rail bridges an...
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ISBN:
(纸本)9798350355611
This research paper inscribes an alarming need for effective bridge health monitoring and controlling amid growing concerns over structural integrity and safety. India has been inherited by n number of rail bridges and roadway bridges over valleys, rivers, hills etc. since british era. Many bridges in urban India near rivers face deterioration over time despite remaining operational. This poses risks to users due to factors like heavy vehicles, rising water levels, pressure variations, and heavy rainfall all potentially leading to collapses and disasters. Apart from these usual factors, earthquake is also one of the most disastrous factor which poses a great risk to the safety and structural integrity of bridges. Hence, it is of an utmost importance that periodic audits of structural integrity and safety of these bridges is critically evaluated. In this study we put forward development of a smart bridge system equipped with a network of sensors controlled using IoT system. We have developed a model prototype of a smart bridge wherein, sensors monitor and responds to variables such as water levels and structural deflections, vibrations, object detection etc. on a real time basis. The sensors we used included flex sensors which monitor deflections, IR sensors to detect objects, water sensors monitoring water level and vibration sensors. In addition to the conventional parameter evaluation, application of the modern sensor based techniques in combination with IoT controlling provide an enhanced system for monitoring of structural integrity and safety of the bridges. Should any monitored parameter exceed its safe threshold signifying a risk of collapse, the system triggers alerts via a monitoring system and activates automatic barriers. Additionally, the controlling system codes provide multidimensional approach of monitoring. This proactive approach aims to enhance safety and prevent potential disasters caused by bridge failures. Daily analysis carried out on the data
Purpose: The purpose of this paper is to present a family of robust metasurface-oriented wireless power transfer systems with improved efficiency and size compactness. The effect of geometric and structural features o...
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Purpose: The purpose of this paper is to present a family of robust metasurface-oriented wireless power transfer systems with improved efficiency and size compactness. The effect of geometric and structural features on the overall efficiency and miniaturisation is elaborately studied, while the presence of substrate losses is, also, considered. Moreover, to further enhance the performance, possible means for reducing the operating frequency, without comprising the unit-cell size, are proposed. Design/methodology/approach: The key element of the design technique is the edge-coupled split-ring resonators patterned in various metasurface configurations and optimally placed to increase the total efficiency. To this goal, a rigorous three-dimensional algorithm, launching a new high-order prism macroelement, is developed in this paper for the fast evaluation of the required quantities. The featured scheme can host diverse approximation orders, while it is drastically more economical than existing methods. Hence, the demanding wireless power transfer systems are precisely modelled via reduced degrees of freedom, without the need to conduct large-scale simulations. Findings: Numerical results, compared with measured data from fabricated prototypes, validate the design methodology and prove its competence to provide enhanced metasurface wireless power transfer systems. An assortment of optimized 3 x 3 and 5 x 5 metamaterial setups is investigated, and interesting deductions, regarding the impact of the inter-element gaps, the distance between the transmitting and receiving components and the substrate losses, are derived. Also, the proposed vector macroelement technique overwhelms typical implementations in terms of computational burden, particularly when combined with the relevant commercial software packages. Originality/value: Systematic design of advanced real-world wireless power transfer structures through optimally selected metasurfaces with fully controllable electro
Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws...
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Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.
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