the paper proposes the use of 3D convolutional neural network for recognizing user emotions on videos in a recommender system. The data approach aims to use the recognized emotion as important implicit feedback and im...
the paper proposes the use of 3D convolutional neural network for recognizing user emotions on videos in a recommender system. The data approach aims to use the recognized emotion as important implicit feedback and improve the recommendation result. This is expected to significantly improve the performance of the recommender system.
Heterogeneous network (HetNet) is an attractive solution for future cellular networks with high data rate and coverage requirements. In HetNets, small cells such as micro cells, pico cells, femto cells and relay node ...
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With this work, a research contribution in the field of reliability theory has been made, with which a realistic prognosis of reliability parameters of technical systems can be carried out. The motivation to deal with...
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ISBN:
(纸本)9789811820168
With this work, a research contribution in the field of reliability theory has been made, with which a realistic prognosis of reliability parameters of technical systems can be carried out. The motivation to deal with this topic resulted from the realization that the prognosis quality of established prognosis models must be optimized. An early and realistic prognosis of reliability parameters contributes to the success of a concern, mainly through the early implementation of quality measures. The work focuses on the development of a new multivariate prognosis model, which uses multivariate stress parameters as reference variables. Its application enables the prediction of reliability parameters for electronic control units. The predicted reliability parameters can be specified as stress-dependent (bivariate/multivariate) or time-dependent variables. While univariate reference quantities usually use the time dwell time of a technical system, the prognosis model newly presented here can process multivariate reference quantities. During the time in the field, technical systems are not only exposed to different usage behavior, but also to other stresses and influences that make a not inconsiderable contribution to failure. The use of time in the field as a univariate reference variable does not allow for this differentiated consideration and does not take into account relevant information in the reliability analysis. All existing prediction models have in common that only univariate reference parameters can be processed. For a fully comprehensive reliability analysis, all stress variables that lead to a failure must be considered. This is not sufficiently possible with a simple univariate approach. With the new approaches, it is now possible for the first time to consider different stress variables, their changes and their effects on the technical system under investigation in a field data analysis. The presented approach for the multivariate prognosis model considers i
Road accidents have been known to be one of the leading death causes around the world for a long time. Thus, cars and all kinds of road vehicles form a huge source of danger, and they relate to multiple high risks. Th...
Road accidents have been known to be one of the leading death causes around the world for a long time. Thus, cars and all kinds of road vehicles form a huge source of danger, and they relate to multiple high risks. There are many factors that can contribute to road traffic accidents such as the health condition of the driver if a medical emergency event happened while driving, drowsiness, or mind-wandering. The proposed system can monitor the behavior of the driver while driving as well as his/her health status. Moreover, it analyzes the monitored data, alerts the driver in a timely manner, and assists him/her in adjusting the driving behavior. Different dangerous and risky situations which can be faced during driving can be captured and avoided by using such a system which leads at the end to increase road traffic safety and reduce vehicle collisions. Notifications are developed in cases of drowsiness, loss of focus, or other concerns that may emerge while driving. However, when the driver's ability to operate the vehicle safely is hampered by a health concern, the implemented system is only able at this stage to alarm the driver itself and the surrounding cars as a first level of alarms.
The report presents the results of a comparative analysis of methods for parameterization of cognitive models based on the use of fuzzy set theory and antonym logic. Reasoned expediency of using methods of the logic o...
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ISBN:
(数字)9798350384499
ISBN:
(纸本)9798350384505
The report presents the results of a comparative analysis of methods for parameterization of cognitive models based on the use of fuzzy set theory and antonym logic. Reasoned expediency of using methods of the logic of antonyms in the construction and research of cognitive models of weakly structured situations. An approach to calculating the magnitudes of the indirect and total influence of factors on each other in certain types of cognitive models built based on the logic of antonyms is proposed.
The paper evaluates the influence of wire thickness and insulation material on its heating temperature during operation. The temperature and time characteristics of wire exploitation under conditions of different load...
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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.
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.
Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems lik...
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Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems like traffic light signalling,map colouring,scheduling,***,social networks are prevalent systems in our ***,the users are considered as vertices,and their connections/interactions are taken as *** users follow other popular users’profiles in these networks,and some don’t,but those non-followers are connected directly to the popular *** means,along with traditional relationship(information flowing),there is another relation among *** depends on the domination of the relationship between the *** type of situation can be modelled as a directed fuzzy *** the colouring of fuzzy graph theory,edge membership plays a vital *** membership is a representation of flowing information between end nodes of the *** from the communication relationship,there may be some other factors like domination in *** influence of power is captured *** this article,the colouring of directed fuzzy graphs is defined based on the influence of *** with this,the chromatic number and strong chromatic number are provided,and related properties are *** application regarding COVID-19 infection is presented using the colouring of directed fuzzy graphs.
Joint safety and security analysis of cyber-physical systems is a necessary step to correctly capture inter-dependencies between these properties. Attack-Fault Trees represent a combination of dynamic Fault Trees and ...
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