This systematic literature review delves into the dynamic realm of graphical passwords, focusing on the myriad security attacks they face and the diverse countermeasures devised to mitigate these threats. The core obj...
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Protein-protein interactions (PPIs) are essential for various biological processes, and their binding sites provide important information for cell function and drug design. Traditional experimental methods for identif...
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In unsupervised video object segmentation(UVOS), the whole video might segment the wrong target due to the lack of initial prior information. Also, in semi-supervised video object segmentation(SVOS), the initial video...
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In unsupervised video object segmentation(UVOS), the whole video might segment the wrong target due to the lack of initial prior information. Also, in semi-supervised video object segmentation(SVOS), the initial video frame with a fine-grained pixel-level mask is essential to good segmentation accuracy. It is expensive and laborious to provide the accurate pixel-level masks for each training sequence. To address this issue, We present a weak user interactive UVOS approach guided by a simple human-made rectangle annotation in the initial frame. We first interactively draw the region of interest by a rectangle, and then we leverage the mask RCNN(region-based convolutional neural networks) method to generate a set of coarse reference labels for subsequent mask propagations. To establish the temporal correspondence between the coherent frames, we further design two novel temporal modulation modules to enhance the target representations. We compute the earth mover's distance(EMD)-based similarity between coherent frames to mine the co-occurrent objects in the two images, which is used to modulate the target representation to highlight the foreground target. We design a cross-squeeze temporal modulation module to emphasize the co-occurrent features across frames, which further helps to enhance the foreground target representation. We augment the temporally modulated representations with the original representation and obtain the compositive spatio-temporal information, producing a more accurate video object segmentation(VOS) model. The experimental results on both UVOS and SVOS datasets including Davis2016,FBMS, Youtube-VOS, and Davis2017, show that our method yields favorable accuracy and complexity. The related code is available.
Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which ent...
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Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high *** avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is *** combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection ***,the relationship between implicit and explicit techniques is ***,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink *** proposed improved Newton iteration significantly reduces the complexity of conventional Newton ***,its complexity is still high for higher ***,it is applied only for first two *** subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton *** guarantees of the proposed detector are also *** simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.
Autonomous aerial robots are increasingly being deployed in real-world scenarios, where transparent glass obstacles present significant challenges to reliable navigation. Researchers have investigated the use of non-c...
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Previous deep learning-based Network Intrusion Detection Systems (NIDS) require a sufficient number of labeled samples to train deep neural network models. However, in certain scenarios of the Internet of Things (IoT)...
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Rapid development in Information technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)*** networks give a safe and more effective driving experie...
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Rapid development in Information technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)*** networks give a safe and more effective driving experience by presenting time-sensitive and location-aware *** communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with ***,the scheme of an effectual routing protocol for reliable and stable communications is *** research demonstrates that clustering is an intelligent method for effectual routing in a mobile ***,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in *** FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the *** accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust *** the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR *** experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.
As an innovative propulsion technique, laser augmented chemical propulsion(LACP) seems superior to the traditional ones. However, the corresponding combustion theories have still to be ascertained for LACP. Burning ra...
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As an innovative propulsion technique, laser augmented chemical propulsion(LACP) seems superior to the traditional ones. However, the corresponding combustion theories have still to be ascertained for LACP. Burning rate of 5-aminotetrazole(5-ATZ) propellant has been studied by testing pressed samples under different combustor pressures and laser powers. Based on micro computed tomography(Micro CT),an advanced thickness-over-time(TOT) method to characterize the regression of the produced nonplanar burning surface is established. Because of a shell structure covering the combustion surface,the burning rate of the implemented 5-ATZ propellant is not constant during laser ablation. Resorting to functional fitting, a new law of non-constant burning including the effect of the observed unique burning surface structures is proposed. Accordingly, applicable combustion conditions of 5-ATZ based propellants have been preliminarily speculated for future research activities.
The challenge of bankruptcy prediction, critical for averting financial sector losses, is amplified by the prevalence of imbalanced datasets, which often skew prediction models. Addressing this, our study introduces t...
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The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,s...
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The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,such as Artificial Intelligence(AI)and machine learning,to make accurate *** science is the science of dealing with data and its relationships through intelligent *** state-of-the-art research focuses independently on either data science or IIoT,rather than exploring their ***,to address the gap,this article provides a comprehensive survey on the advances and integration of data science with the Intelligent IoT(IIoT)system by classifying the existing IoT-based data science techniques and presenting a summary of various *** paper analyzes the data science or big data security and privacy features,including network architecture,data protection,and continuous monitoring of data,which face challenges in various IoT-based *** insights into IoT data security,privacy,and challenges are visualized in the context of data science for *** addition,this study reveals the current opportunities to enhance data science and IoT market *** current gap and challenges faced in the integration of data science and IoT are comprehensively presented,followed by the future outlook and possible solutions.
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