The performance of convolutional neural networks (CNN) for computer vision problems depends heavily on their architectures. Transfer learning performance of a CNN strongly relies on selection of its trainable layers. ...
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In blockchain-based unmanned aerial vehicle(UAV)communication systems,the length of a block affects the performance of the *** transmission performance of blocks in the form of finite character segments is also affect...
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In blockchain-based unmanned aerial vehicle(UAV)communication systems,the length of a block affects the performance of the *** transmission performance of blocks in the form of finite character segments is also affected by the block ***,it is crucial to balance the transmission performance and blockchain performance of blockchain communication systems,especially in wireless environments involving *** paper investigates a secure transmission scheme for blocks in blockchain-based UAV communication systems to prevent the information contained in blocks from being completely eavesdropped during *** our scheme,using a friendly jamming UAV to emit jamming signals diminishes the quality of the eavesdropping channel,thus enhancing the communication security performance of the source *** the constraints of maneuverability and transmission power of the UAV,the joint design of UAV trajectories,transmission power,and block length are proposed to maximize the average minimum secrecy rate(AMSR).Since the optimization problem is non-convex and difficult to solve directly,we first decompose the optimization problem into subproblems of trajectory optimization,transmission power optimization,and block length ***,based on firstorder approximation techniques,these subproblems are reformulated as convex optimization ***,we utilize an alternating iteration algorithm based on the successive convex approximation(SCA)technique to solve these subproblems *** simulation results demonstrate that our proposed scheme can achieve secure transmission for blocks while maintaining the performance of the blockchain.
Analyzing incomplete data is one of the prime concerns in data analysis. Discarding the missing records or values might result in inaccurate analysis outcomes or loss of helpful information, especially when the size o...
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Analyzing incomplete data is one of the prime concerns in data analysis. Discarding the missing records or values might result in inaccurate analysis outcomes or loss of helpful information, especially when the size of the data is small. A preferable alternative is to substitute the missing values using imputation such that the substituted values are very close to the actual missing values and this is a challenging task. In spite of the existence of many imputation algorithms, there is no universal imputation algorithm that can yield the best values for imputing all types of datasets. This is mainly because of the dependence of the imputation algorithm on the inherent properties of the data. These properties include type of data distribution, data size, dimensionality, presence of outliers, data dependency among the attributes, and so on. In the literature, there exists no straightforward method for determining a suitable imputation algorithm based on the data characteristics. The existing practice is to conduct exhaustive experimentation using the available imputation techniques with every dataset and this requires a lot of time and effort. Moreover, the current approaches for checking the suitability of imputations cannot be done when the ground truth data is not available. In this paper, we propose a new method for the systematic selection of a suitable imputation algorithm based on the inherent properties of the dataset which eliminates the need for exhaustive experimentation. Our method determines the imputation technique which consistently gives lower errors while imputing datasets with specific properties. Also, our method is particularly useful when the real-world data do not have the ground truth for missing data to check the imputation performance and suitability. Once the suitability of a DI technique is established based on the data properties, this selection will remain valid for another dataset with similar properties. Thus, our method can save time an
Cloud computing and edge computing brought more software,which also brought a new danger of malicious software *** synchronization mechanisms of software can further help reverse data *** on the mechanisms,attackers c...
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Cloud computing and edge computing brought more software,which also brought a new danger of malicious software *** synchronization mechanisms of software can further help reverse data *** on the mechanisms,attackers can cover themselves behind the network and modify data *** knowledge of software reverse engineering can be organized as rules to accelerate the attacks,when attackers intrude cloud server to access the source or binary ***,we proposed a novel method to resist this kind of reverse engineering by breaking these *** method is based on software obfuscations and encryptions to enhance the security of distributed software and cloud services in the 5G *** method is capable of(1)replacing theoriginal assembly codes of theprotectedprogramwithequivalent assembly instructions inan iteration way,(2)obfuscating the control flow of the protected program to confuse attackers meanwhile keeps the program producing the same outputs,(3)encrypting data to confuse *** addition,the approach can periodically and automatically modify the protected software binary codes,and the binary codes of the protected software are encrypted to resist static analysis and dynamic ***,a simplified virtual machine is implemented to make the protected codes unreadable to *** game is one of the specific scenarios which needs low latency and strong data *** engine,Ollydbg,and Interactive Disassembler Professional(IDA)are used prevalently for *** improved methods can protect the software from the most vulnerable *** improved dynamic code swapping and the simplified virtual machine technologies for cloud games are the main *** inductively learned that our methods have been working well according to the security mechanisms and time complexity *** show that hidden dangers can be eliminated with efficient methods:Execution time and file sizes of
Purpose-Path planning is an important part of UAV mission *** main purpose of this paper is to overcome the shortcomings of the standard particle swarm optimization(PSO)such as easy to fall into the local optimum,so t...
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Purpose-Path planning is an important part of UAV mission *** main purpose of this paper is to overcome the shortcomings of the standard particle swarm optimization(PSO)such as easy to fall into the local optimum,so that the improved PSO applied to the UAV path planning can enable the UAV to plan a better quality ***/methodology/approach-Firstly,the adaptation function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV ***,the standard PSO is improved,and the improved particle swarm optimization with multi-strategy fusion(MFIPSO)is *** method introduces class sigmoid inertia weight,adaptively adjusts the learning factors and at the same time incorporates K-means clustering ideas and introduces the Cauchy perturbation ***,MFIPSO is applied to UAV path ***-Simulation experiments are conducted in simple and complex scenarios,respectively,and the quality of the path is measured by the fitness value and straight line rate,and the experimental results show that MFIPSO enables the UAV to plan a path with better ***/value-Aiming at the standard PSO is prone to problems such as premature convergence,MFIPSO is proposed,which introduces class sigmoid inertia weight and adaptively adjusts the learning factor,balancing the global search ability and local convergence ability of the *** idea of K-means clustering algorithm is also incorporated to reduce the complexity of the algorithm while maintaining the diversity of particle *** addition,the Cauchy perturbation is used to avoid the algorithm from falling into local ***,the adaptability function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself,which improves the accuracy of the evaluation model.
Power load forecasting is essential for optimizing power generation and distribution efficiency. This paper proposes a novel method for daily average load forecasting, referred to as LARSI-TPE-XGB, which integrates th...
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Globally, skin diseases are emerging as the most common health problem. It initiates depressive disorder, and it also causes physical health distress. It rarely led to skin cancer in extreme cases. Diagnosing skin dis...
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Image captioning is a technique that generates concise and meaningful descriptions of the visual contents present in an image. Image captioning frameworks generally employ an encoder-decoder-based pipeline to generate...
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In this paper, an evaluation strategy is proposed for evaluation of optimization algorithms, called the Complex Preference Analysis, that assesses the efficiency of different evolutionary algorithms by considering mul...
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In the area of data hiding and information security, the greater need is to ensure high embedding capacity of the stego media without hampering the visual quality while ensuring the tightest possible security. Now, it...
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