As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of *** connection between industrial control networks and the external internet is becoming increa...
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As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of *** connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security *** paper proposes a model for the industrial control *** includes a malware containment strategy that integrates intrusion detection,quarantine,and ***,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment *** addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction ***,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is *** otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control *** earlier the immunization of key nodes,the *** the time exceeds the threshold,immunizing key nodes is almost *** analysis provides a better way to contain the malware in the industrial control network.
As a deep learning network with an encoder-decoder architecture,UNet and its series of improved versions have been widely used in medical image segmentation with great ***,when used to segment targets in 3D medical im...
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As a deep learning network with an encoder-decoder architecture,UNet and its series of improved versions have been widely used in medical image segmentation with great ***,when used to segment targets in 3D medical images such as magnetic resonance imaging(MRI),computed tomography(CT),these models do not model the relevance of images in vertical space,resulting in poor accurate analysis of consecutive slices of the same *** the other hand,the large amount of detail lost during the encoding process makes these models incapable of segmenting small-scale tumor *** at the scene of small-scale target segmentation in 3D medical images,a fully new neural network model SUNet++is proposed on the basis of UNet and UNet++.SUNet++improves the existing models mainly in three aspects:1)the modeling strategy of slice superposition is used to thoroughly excavate the three dimensional information of the data;2)by adding an attention mechanism during the decoding process,small scale targets in the picture are retained and amplified;3)in the up-sampling process,the transposed convolution operation is used to further enhance the effect of the *** order to verify the effect of the model,we collected and produced a dataset of hyperintensity MRI liver-stage images containing over 400 cases of liver *** results on both public and proprietary datasets demonstrate the superiority of SUNet++in small-scale target segmentation of three-dimensional medical images.
Confidentiality of maintaining the Electronic Health Records of patients is a major concern to both the patient and Doctor. Sharing the data on cloud is one of the most efficient technology infrastructures with extens...
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Handling the massive amount of data generated by Smart Mobile Devices(SMDs)is a challenging computational *** Computing is an emerging computation paradigm that is employed to conquer this *** can bring computation po...
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Handling the massive amount of data generated by Smart Mobile Devices(SMDs)is a challenging computational *** Computing is an emerging computation paradigm that is employed to conquer this *** can bring computation power closer to the end devices to reduce their computation latency and energy ***,this paradigm increases the computational ability of SMDs by collaboration with edge *** is achieved by computation offloading from the mobile devices to the edge nodes or ***,not all applications benefit from computation offloading,which is only suitable for certain types of *** properties,SMD capability,wireless channel state,and other factors must be counted when making computation offloading ***,optimization methods are important tools in scheduling computation offloading tasks in Edge Computing *** this paper,we review six types of optimization methods-they are Lyapunov optimization,convex optimization,heuristic techniques,game theory,machine learning,and *** each type,we focus on the objective functions,application areas,types of offloading methods,evaluation methods,as well as the time complexity of the proposed *** discuss a few research problems that are still *** purpose for this review is to provide a concise summary that can help new researchers get started with their computation offloading researches for Edge Computing networks.
Contact angle is an essential parameter to characterize substrate *** measurement of contact angle in experiment and simulation is a complex and time-consuming *** this paper,an improved method of measuring contact an...
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Contact angle is an essential parameter to characterize substrate *** measurement of contact angle in experiment and simulation is a complex and time-consuming *** this paper,an improved method of measuring contact angle in multiphase lattice Boltzmann simulations is proposed,which can accurately obtain the real-time contact angle at a low temperature and larger density *** three-phase contact point is determined by an extrapolation,and its position is not affected by the local deformation of flow field in the three-phase contact region.A series of simulations confirms that the present method has high accuracy and *** contact angle keeps an excellent linear relationship with the chemical potential of the surface,so that it is very convenient to specify the wettability of a *** real-time contact angle measurement enables us to obtain the dynamic contact angle hysteresis on chemically heterogeneous surface,while the mechanical analyses can be effectively implemented at the moving contact line.
The recent development of the Internet of Things(IoTs)resulted in the growth of IoT-based DDoS *** detection of Botnet in IoT systems implements advanced cybersecurity measures to detect and reduce malevolent botnets ...
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The recent development of the Internet of Things(IoTs)resulted in the growth of IoT-based DDoS *** detection of Botnet in IoT systems implements advanced cybersecurity measures to detect and reduce malevolent botnets in interconnected *** detection models evaluate transmission patterns,network traffic,and device behaviour to detect deviations from usual *** learning(ML)techniques detect patterns signalling botnet activity,namely sudden traffic increase,unusual command and control patterns,or irregular device *** addition,intrusion detection systems(IDSs)and signature-based techniques are applied to recognize known malware signatures related to *** ML and deep learning(DL)techniques have been developed to detect botnet attacks in IoT *** overcome security issues in an IoT environment,this article designs a gorilla troops optimizer with DL-enabled botnet attack detection and classification(GTODL-BADC)*** GTODL-BADC technique follows feature selection(FS)with optimal DL-based classification for accomplishing security in an IoT *** data preprocessing,the min-max data normalization approach is primarily *** GTODL-BADC technique uses the GTO algorithm to select features and elect optimal feature ***,the multi-head attention-based long short-term memory(MHA-LSTM)technique was applied for botnet ***,the tree seed algorithm(TSA)was used to select the optimum hyperparameter for the MHA-LSTM *** experimental validation of the GTODL-BADC technique can be tested on a benchmark *** simulation results highlighted that the GTODL-BADC technique demonstrates promising performance in the botnet detection process.
Advancements in cloud computing and virtualization technologies have revolutionized Enterprise Application Development with innovative ways to design and develop complex *** Architecture is one of the recent technique...
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Advancements in cloud computing and virtualization technologies have revolutionized Enterprise Application Development with innovative ways to design and develop complex *** Architecture is one of the recent techniques in which Enterprise Systems can be developed as fine-grained smaller components and deployed *** methodology brings numerous benefits like scalability,resilience,flexibility in development,faster time to market,*** the advantages;Microservices bring some challenges *** microservices need to be invoked one by one as a *** most applications,more than one chain of microservices runs in parallel to complete a particular requirement To complete a user’s *** results in competition for resources and the need for more inter-service communication among the services,which increases the overall latency of the application.A new approach has been proposed in this paper to handle a complex chain of microservices and reduce the latency of user requests.A machine learning technique is followed to predict the weighting time of different types of *** communication time among services distributed among different physical machines are estimated based on that and obtained insights are applied to an algorithm to calculate their priorities dynamically and select suitable service instances to minimize the latency based on the shortest queue waiting *** were done for both interactive as well as non interactive workloads to test the effectiveness of the *** approach has been proved to be very effective in reducing latency in the case of long service chains.
Objective: The purpose of this paper was to use Machine Learning (ML) techniques to extract facial features from images. Accurate face detection and recognition has long been a problem in computer vision. According to...
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A common cardiovascular illness with high fatality rates is coronary artery disease (CAD). Researchers have been exploring alternative methods to diagnose and assess the severity of CAD that are less invasive, cost-ef...
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Over the past era,subgraph mining from a large collection of graph database is a crucial *** addition,scalability is another big problem due to insufficient *** are several security challenges associated with subgraph...
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Over the past era,subgraph mining from a large collection of graph database is a crucial *** addition,scalability is another big problem due to insufficient *** are several security challenges associated with subgraph mining in today’s on-demand *** address this downside,our proposed work introduces a Blockchain-based Consensus algorithm for Authenticated query search in the Large-Scale Dynamic Graphs(BCCA-LSDG).The two-fold process is handled in the proposed BCCA-LSDG:graph indexing and authenticated query search(query processing).A blockchain-based reputation system is meant to maintain the trust blockchain and cloud server of the proposed *** resolve the issues and provide safe big data transmission,the proposed technique also combines blockchain with a consensus algorithm *** of the big data is ensured by dividing the BC network into distinct networks,each with a restricted number of allowed entities,data kept in the cloud gate server,and data analysis in the *** consensus algorithm is crucial for maintaining the speed,performance and security of the *** Dual Similarity based MapReduce helps in mapping and reducing the relevant subgraphs with the use of optimal feature ***,the graph index refinement process is undertaken to improve the query *** query error,fuzzy logic is used to refine the index of the graph *** proposed technique outperforms advanced methodologies in both blockchain and non-blockchain systems,and the combination of blockchain and subgraph provides a secure communication platform,according to the findings.
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