From AI-assisted art creation to large language model (LLM)-powered ChatGPT, AI-generated contents and services are becoming a transforming force. It calls for the telecom industry to embrace the prospects of AIGC ser...
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More than 115 million individuals were affected by the coronavirus (COVID-19), which the World Health Organization classified as a pandemic. The virus fatally affected more than 2 million people. This has underscored ...
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The banking sector is widely acknowledged for its intrinsic unpredictability and susceptibility to risk. Bank loans have emerged as one of the most recent services offered over the past several decades. Banks typicall...
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The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the ***,this development has ex...
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The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the ***,this development has expanded the potential targets that hackers might *** adequate safeguards,data transmitted on the internet is significantly more susceptible to unauthorized access,theft,or *** identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious *** research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks(RNN)integrated with Long Short-Term Memory(LSTM)*** proposed model can identify various types of cyberattacks,including conventional and distinctive *** networks,a specific kind of feedforward neural networks,possess an intrinsic memory *** Neural Networks(RNNs)incorporating Long Short-Term Memory(LSTM)mechanisms have demonstrated greater capabilities in retaining and utilizing data dependencies over extended *** such as data types,training duration,accuracy,number of false positives,and number of false negatives are among the parameters employed to assess the effectiveness of these models in identifying both common and unusual *** are utilised in conjunction with LSTM to support human analysts in identifying possible intrusion events,hence enhancing their decision-making capabilities.A potential solution to address the limitations of Shallow learning is the introduction of the Eccentric Intrusion Detection *** model utilises Recurrent Neural Networks,specifically exploiting LSTM *** proposed model achieves detection accuracy(99.5%),generalisation(99%),and false-positive rate(0.72%),the parameters findings reveal that it is superior to state-of-the-art techniques.
Breast Cancer Detection introduces a prominent confrontation for researchers and clinical experts as it is one of the major public health issues and is weighed as a leading root for cancer correlated deaths among wome...
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The deployment of distributed multi-controllers for Software-Defined Networking(SDN)architecture is an emerging solution to improve network scalability and ***,the network control failure affects the dynamic resource ...
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The deployment of distributed multi-controllers for Software-Defined Networking(SDN)architecture is an emerging solution to improve network scalability and ***,the network control failure affects the dynamic resource allocation in distributed networks resulting in network disruption and low ***,we consider the control plane fault tolerance for cost-effective and accurate controller location models during control plane *** fault-tolerance strategy has been applied to distributed SDN control architecture,which allows each switch to migrate to next controller to enhance network *** this paper,the Reliable and Dynamic Mapping-based Controller Placement(RDMCP)problem in distributed architecture is framed as an optimization problem to improve the system reliability,quality,and *** considering the bound constraints,a heuristic state-of-the-art Controller Placement Problem(CPP)algorithm is used to address the optimal assignment and reassignment of switches to nearby controllers other than their regular *** algorithm identifies the optimal controller location,minimum number of controllers,and the expected assignment costs after failure at the lowest effective cost.A metaheuristic Particle Swarm Optimization(PSO)algorithm was combined with RDMCP to form a hybrid approach that improves objective function optimization in terms of reliability and *** effectiveness of our hybrid RDMCP-PSO was then evaluated using extensive experiments and compared with other baseline *** findings demonstrate that the proposed hybrid technique significantly increases the network performance regarding the controller number and load balancing of the standalone heuristic CPP algorithm.
Nowadays,IT systems rely mainly on artificial intelligence(AI)algorithms to process *** is generally used to extract knowledge from stored information and,depending on the nature of data,it may be necessary to apply d...
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Nowadays,IT systems rely mainly on artificial intelligence(AI)algorithms to process *** is generally used to extract knowledge from stored information and,depending on the nature of data,it may be necessary to apply different AI *** this article,a novel perspective on the use of AI to ensure the cybersecurity through the study of network traffic is *** is done through the construction of a two-stage cyberattack classification ensemble model addressing class imbalance following a one-vs-rest(OvR)*** the growing trend of cyberattacks,it is essential to implement techniques that ensure legitimate access to *** address this issue,this work proposes a network traffic classification system for different categories based on several AI *** the first task,binary models are generated to clearly differentiate each type of traffic from the *** binary models generated,an ensemble model is developed in two phases,which allows the separation of legitimate and illegitimate traffic(phase 1)while also identifying the type of illegitimate traffic(phase 2).In this way,the proposed system allows a complete multiclass classification of network *** estimation of global performance is done using a modern dataset(UNSW-NB15),evaluated using two approaches and compared with other state-of-art *** proposal,based on the construction of a two-step model,reaches an F1 of 0.912 for the first level of binary classification and 0.7754 for the multiclass *** results show that the proposed system outperforms other state-of-the-art approaches(+0.75%and+3.54%for binary and multiclass classification,respectively)in terms of F1,as demon-strated through comparison together with other relevant classification metrics.
Graph structure expression plays a vital role in distinguishing various graphs. In this work, we propose a structure-sensitive graph dictionary embedding (SS-GDE) framework to transform input graphs into the embedding...
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The primary objective of this ground-breaking endeavor is to introduce and highlight the transformative potential of humanoid robotic technology, a domain poised to revolutionize various sectors including automation, ...
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The hybrid flow shop group scheduling problem(HFGSP)with the delivery time windows has been widely studied owing to its better flexibility and suitability for the current just-in-time production ***,there are several ...
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The hybrid flow shop group scheduling problem(HFGSP)with the delivery time windows has been widely studied owing to its better flexibility and suitability for the current just-in-time production ***,there are several unresolved challenges in problem modeling and algorithmic design tailored for *** our study,we place emphasis on the constraint of ***,this paper first constructs a mixed integer linear programming model of HFGSP with sequence-dependent setup time and delivery time windows to minimize the total weighted earliness and tardiness(TWET).Then a penalty groups-assisted iterated greedy integrating idle time insertion(PG IG ITI)is proposed to solve the above *** the PG IG ITI,a double decoding strategy is proposed based on the earliest available machine rule and the idle time insertion rule to calculate the TWET ***,to reduce the amount of computation,a skip-based destruction and reconstruction strategy is designed,and a penalty groups-assisted local search is proposed to further improve the quality of the solution by disturbing the penalized groups,i.e.,early and tardy ***,through comprehensive statistical experiments on 270 test instances,the results prove that the proposed algorithm is effective compared to four state-of-the-art algorithms.
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