Existing simulations of terrorist attacks do not consider individual *** overcome this lim-itation,we propose a framework to model heterogeneous behavior of individuals during terrorist *** constructed an emotional mo...
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Existing simulations of terrorist attacks do not consider individual *** overcome this lim-itation,we propose a framework to model heterogeneous behavior of individuals during terrorist *** constructed an emotional model that integrated personality and visual perception for *** emotional model was then integrated with pedestrian relationship networks to establish a decision-making model that sup-ported pedestrians’altruistic behaviors.A mapping model has been developed to correlate antisocial personality traits with attack strategies employed by *** demonstrate that the proposed algorithm can generate practical heterogeneous behaviors that align with existing psychological research findings.
Providing comfortable indoor air quality control in residential construction is an exceedingly important *** is due to the structure of the fast response controller of air *** presented work shows the breakdown and cr...
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Providing comfortable indoor air quality control in residential construction is an exceedingly important *** is due to the structure of the fast response controller of air *** presented work shows the breakdown and creation of a mathematical model for an interactive,nonlinear system for the required comfortable air ***,the paper refers to designing traditional proportional integral derivative regulators and proportional,integral,derivative regulators with independent parameters based on a backpropagation neural *** the end,we perform the experimental outputs of a suggested backpropagation neural network-based proportional,integral,derivative controller and analyze model results by applying the proposed *** obtained results demonstrated that the proposed controller can provide the required level of clean air in the *** proposed developed model takes into consideration international Heating,Refrigerating,and air conditioning standards as ASHRAE AND *** on the findings,we concluded that it is possible to implement a proposed system in homes and offer equivalent indoor air quality with continuous mechanical ventilation without a profuse amount of energy.
Because of the quantity, complexity and speed measurements of big data, access to the data needed for big data applications becomes ever more challenging for both end-users and IT-experts. access. This has however led...
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ISBN:
(数字)9781728173108
ISBN:
(纸本)9781728173115
Because of the quantity, complexity and speed measurements of big data, access to the data needed for big data applications becomes ever more challenging for both end-users and IT-experts. access. This has however led to problems of overloading information. While progress has been made in search engines, finding the right information still is a struggle due to the exponential increase in the everyday information provided. The need for Big Data Analytic now powers other aspects of modern society, because they can build new linkages and discoveries that help drive tomorrow's innovation. Data visualization of big data applications is an important tool to interpret and understand immense data, making the technology more enticing to use. Visualization of a search result with faceted search is increasingly popular in search engines. This seeks to allow users to easily and effectively find their way through large document collections. FS strategies presume that correct information is required so that the value, importance, and expense of achieving the requested information is optimized. In this work, we propose a new FS framework for visualizing browsing and refinements of search results to allow users to visually build complex search queries. The proposed FS can also solve the problem of lexical uncertainty in current search engines and give users more interest.
Vehicular ad-hoc networks(VANETs)are mobile networks that use and transfer data with vehicles as the network ***,VANETs are essentially mobile ad-hoc networks(MANETs).They allow all the nodes to communicate and connec...
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Vehicular ad-hoc networks(VANETs)are mobile networks that use and transfer data with vehicles as the network ***,VANETs are essentially mobile ad-hoc networks(MANETs).They allow all the nodes to communicate and connect with one *** of the main requirements in a VANET is to provide self-decision capability to the *** memory,which stores all the previous routes,is used by the vehicles to choose the optimal *** networks,communication is *** cellular-based vehicle-to-everything(CV2X)communication,vital information is shared using the cooperative awareness message(CAM)that is broadcast by each *** are allocated in a distributed manner,which is known as Mode 4 *** support vector machine(SVM)algorithm is used in the SVM-CV2X-M4 system proposed in this *** k-fold model with different values of k is used to evaluate the accuracy of the SVM-CV2XM4 *** results show that the proposed system achieves an accuracy of 99.6%.Thus,the proposed system allows vehicles to choose the optimal route and is highly convenient for users.
Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the *** this article,these issues are handled by prop...
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Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the *** this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things *** framework integrates Kalman filtering and *** smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction *** traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction *** evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art ***,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.
The exponential growth of Internet and network usage has neces-sitated heightened security measures to protect against data and network ***,executed through network packets,pose a significant challenge for firewalls t...
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The exponential growth of Internet and network usage has neces-sitated heightened security measures to protect against data and network ***,executed through network packets,pose a significant challenge for firewalls to detect and prevent due to the similarity between legit-imate and intrusion *** vast network traffic volume also complicates most network monitoring systems and *** intrusion detection methods have been proposed,with machine learning techniques regarded as promising for dealing with these *** study presents an Intrusion Detection System Based on Stacking Ensemble Learning base(Random For-est,Decision Tree,and k-Nearest-Neighbors).The proposed system employs pre-processing techniques to enhance classification efficiency and integrates seven machine learning *** stacking ensemble technique increases performance by incorporating three base models(Random Forest,Decision Tree,and k-Nearest-Neighbors)and a meta-model represented by the Logistic Regression *** using the UNSW-NB15 dataset,the pro-posed IDS gained an accuracy of 96.16%in the training phase and 97.95%in the testing phase,with precision of 97.78%,and 98.40%for taring and testing,*** obtained results demonstrate improvements in other measurement criteria.
The rapidly evolving darknet enables a wide range of cybercrimes through anonymous and untraceable communication *** detection of clandestine darknet traffic is therefore critical yet immensely *** research demonstrat...
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The rapidly evolving darknet enables a wide range of cybercrimes through anonymous and untraceable communication *** detection of clandestine darknet traffic is therefore critical yet immensely *** research demonstrates how advanced machine learning and specialized deep learning techniques can significantly enhance darknet traffic analysis to strengthen *** diverse classifiers such as random forest and naïve Bayes with a novel spiking neural network architecture provides a robust foundation for identifying concealed *** on the CIC-Darknet2020 dataset establishes state-of-the-art results with 98%accuracy from the random forest model and 84.31%accuracy from the spiking neural *** pioneering application of artificial intelligence advances the frontiers in analyzing the complex characteristics and behaviours of darknet *** proposed techniques lay the groundwork for improved threat intelligence,real-time monitoring,and resilient cyber defense systems against the evolving landscape of cyber threats.
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