In this study, a new generalized model of thermo-viscoelasticity with three phase-lag (TPL) theory concerning memory-dependent derivative (MDD) theory is emphasized. The governing combined equations of the novel model...
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This work is devoted to the determination of influence of the internal forces on the propagation of the waves in electromechanical systems. The task is simplified to an inverse problem for the third order hyperbolic e...
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ISBN:
(数字)9798350378627
ISBN:
(纸本)9798350378634
This work is devoted to the determination of influence of the internal forces on the propagation of the waves in electromechanical systems. The task is simplified to an inverse problem for the third order hyperbolic equation with the integral overdetermination condition and with the unknown function in the right-hand side of the equation. Some numerical results are presented for viscoelastic medium and for liquid like water with solid parameters. The presented method gives us opportunity to find the precise analytical solutions to the mathematical problems that simulate the wave propagation.
The quality of medical images is paramount. Being of high grade, it guarantees the quality of medical diagnosis, treatment and quality of patient’s life through the means of health care or using automate intelligent ...
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ISBN:
(纸本)9781665458429
The quality of medical images is paramount. Being of high grade, it guarantees the quality of medical diagnosis, treatment and quality of patient’s life through the means of health care or using automate intelligent systems for medical diagnosing, treatment and monitoring. The paper presents the computational challenges in medical images processing. The great challenges are to propose parallel computational models and parallel program implementations based on the algorithms for medical images filtering. Parallel computational model based on two-dimensional filters is designed. The proposed parallel model is verified by multithreaded parallel program implementation. An investigation of the efficiency of medical images filters based on parallel multithreaded program implementation, applying two-dimensional filters on a given list of compressed jpeg medical images and generating output jpeg images for each type of applied filter. The applied filters are Brightness Control, horizontal and vertical filter of Sobel, Laplace and Blur. A number of experiments have been carried out for the case of dataset consisted of 162 whole mount slide images of Breast Cancer (BCa) specimens scanned at 40x and various number of threads. Parallel performance parameters execution time and speedup are estimated experimentally. The performance estimation and scalability analyses show that the suggested model has good scalability.
The subject of the study is methods of balancing raw data. The purpose of the article is to improve the quality of intrusion detection in computer networks by using class balancing methods. Task: to investigate method...
The subject of the study is methods of balancing raw data. The purpose of the article is to improve the quality of intrusion detection in computer networks by using class balancing methods. Task: to investigate methods of balancing classes and to develop a classification method on imbalanced data to increase the level of network security. The methods used are: methods of artificial intelligence, machine learning. The following results were obtained: Class balancing methods based on Undersampling, Oversampling and their combinations were studied. The following methods were chosen for further research: SMOTEENN, SVMSMOTE, BorderlineSMOTE, ADASYN, SMOTE, KMeansSMOTE. The UNSW-NB 15 set was used as the source data, which contains information about the normal functioning of the network and during intrusions. A decision tree based on the CART (Classification And Regression Tree) algorithm was used as the basic classifier. According to the research results, it was found that the use of the SMOTEENN method provides an opportunity to improve the quality of detection of intrusions in the functioning of the network. Conclusions. The scientific novelty of the obtained results lies in the complex use of data balancing methods and the method of data classification based on decision trees to detect intrusions into computer networks, which made it possible to reduce the number of Type II errors.
A method for determining the probability of occurrence of a critical combination of events for the three-element minimum cross-sections of attributes of the characteristics of the software quality model of intelligent...
A method for determining the probability of occurrence of a critical combination of events for the three-element minimum cross-sections of attributes of the characteristics of the software quality model of intelligent decision support systems is proposed.
Heterogeneous IoT architectures are evolving rapidly and different challenged are faced with the traditional IoT architectures including the performance time of real-time IoT application. Parallel computing programmin...
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ISBN:
(数字)9798350349740
ISBN:
(纸本)9798350349757
Heterogeneous IoT architectures are evolving rapidly and different challenged are faced with the traditional IoT architectures including the performance time of real-time IoT application. Parallel computing programming technique could enhance the performance and efficiency for distributed systems and multicore processors as well as the IoT systems. However, parallel computing, presents certain difficulties and constraints, including synchronization, communication, security concerns, and load balancing. In this regard, a novel IoT workload balancing model for heterogeneous IoT architectures is presented in this paper. This model is intended to reduce the execution time of large systems by redistributing part of their functions to other involved IoT nodes. An experiment has been conducted to evaluate the actual real load for each IoT node and tried to rebalance the load using the proposed model. The results were encouraging as the performance time was reduced by about one third on two cores.
A developed adaptive forecasting model for cloud resource allocation is presented. It employs principal component analysis on a sequence of virtual machine (VM) requests. Requests are processed to detect anomalies, an...
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This paper introduces AbotalebNet, a novel deep learning architecture optimized for time series forecasting, with a particular focus on the complexities of COVID-19 data. AbotalebNet’s architecture is mathematically ...
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ISBN:
(数字)9798350384277
ISBN:
(纸本)9798350384284
This paper introduces AbotalebNet, a novel deep learning architecture optimized for time series forecasting, with a particular focus on the complexities of COVID-19 data. AbotalebNet’s architecture is mathematically represented as:\begin{equation*}\hat Y = {\text{Attention}}(\operatorname{LSTM} ({\text{CNN}}(X)))\tag{1}\end{equation*}Here, X represents the input time series data, and Ŷ is the forecasted output. AbotalebNet integrates the feature extraction capabilities of Convolutional Neural Networks (CNNs) with the sequential data processing power of Long Short-Term Memory (LSTM) networks, further enhanced by a Multi-Head Attention *** address overfitting, a key challenge in deep learning, the model incorporates regularization strategies, dropout mechanisms, and batch normalization:\begin{equation*}\mathop {\min }\limits_\Theta ( Loss (X,\hat Y;\Theta ) + \lambda R(\Theta ))\tag{2}\end{equation*}In this equation, Θ denotes the model parameters, R(Θ) represents regularization terms, and λ is the regularization coefficient. These additions aid in preventing the model from overfitting to the training data, ensuring robust performance on unseen *** evaluation on COVID-19 time series data demonstrates AbotalebNet’s enhanced predictive accuracy over traditional models, solidifying its potential for advanced non-linear time series analysis.
In this present work, a new similarity measure of Gaussian fuzzy numbers has been proposed. The proposed method is based on the exponent distance about mean, standard deviation and height of the Gaussian fuzzy numbers...
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