The analysis of the efficiency of a master-slave parallel algorithm by Raimondas Čiegis, Ramūnas Šablinskas

“… A general master-slave parallel algorithm is described. Three applications are investigated and results of numerical experiments with various clusters of workstations are given. …”
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Survey of Robot 3D Path Planning Algorithms by Liang Yang, Juntong Qi, Dalei Song, Jizhong Xiao, Jianda Han, Yong Xia

“…We discuss the fundamentals of these most successful robot 3D path planning algorithms which have been developed in recent years and concentrate on universally applicable algorithms which can be implemented in aerial robots, ground robots, and underwater robots. …”
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Image denoising algorithm based on multi-channel GAN by Hongyan WANG, Xiao YANG, Yanchao JIANG, Zumin WANG

“…Aiming at the issue that the noise generated during image acquisition and transmission would degrade the ability of subsequent image processing, a generative adversarial network (GAN) based multi-channel image denoising algorithm was developed.The noisy color image could be separated into red-green-blue (RGB) three channels via the proposed approach, and then the denoising could be implemented in each channel on the basis of an end-to-end trainable GAN with the same architecture.The generator module of GAN was constructed based on the U-net derivative network and residual blocks such that the high-level feature information could be extracted effectively via referring to the low-level feature information to avoid the loss of the detail information.In the meantime, the discriminator module could be demonstrated on the basis of fully convolutional neural network such that the pixel-level classification could be achieved to improve the discrimination accuracy.Besides, in order to improve the denoising ability and retain the image detail as much as possible, the composite loss function could be depicted by the illustrated denoising network based on the following three loss measures, adversarial loss, visual perception loss, and mean square error (MSE).Finally, the resultant three-channel output information could be fused by exploiting the arithmetic mean method to obtain the final denoised image.Compared with the state-of-the-art algorithms, experimental results show that the proposed algorithm can remove the image noise effectively and restore the original image details considerably.…”
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Dynamic scheduling algorithm for streaming media based on CDN by YANG Ge1, FAN Xiu-mei3

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Improved Osprey Optimization Algorithm with Multi-Strategy Fusion by Wenli Lei, Jinping Han, Xinghao Wu

Subjects: “…osprey optimization algorithm…”
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Lidar Simultaneous Localization and Mapping Algorithm for Dynamic Scenes by Peng Ji, Qingsong Xu, Yifan Zhao

“…To address the issue of significant point cloud ghosting in the construction of high-precision point cloud maps by low-speed intelligent mobile vehicles due to the presence of numerous dynamic obstacles in the environment, which affects the accuracy of map construction, this paper proposes a LiDAR-based Simultaneous Localization and Mapping (SLAM) algorithm tailored for dynamic scenes. The algorithm employs a tightly coupled SLAM framework integrating LiDAR and inertial measurement unit (IMU). …”
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The finding and researching algorithm for potentially oscillating enzymatic systems by T. N. Lakhova, F. V. Kazantsev, S. A. Lashin, Yu. G. Matushkin

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Retracted: Iris Localization Algorithm based on Effective Area by International Journal of Antennas and Propagation

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Dissipative Variational Quantum Algorithms for Gibbs State Preparation by Yigal Ilin, Itai Arad

“…In recent years, variational quantum algorithms have gained significant attention due to their adaptability and efficiency on near-term quantum hardware. …”
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Diagnosis and Detection of Alzheimer’s Disease Using Learning Algorithm by Gargi Pant Shukla, Santosh Kumar, Saroj Kumar Pandey, Rohit Agarwal, Neeraj Varshney, Ankit Kumar

“…Apart from that, various classification algorithms, such as machine learning and deep learning, are useful for diagnosing MRI scans. …”
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Gamma norm minimization based image denoising algorithm by Hongyan WANG, Tuo WANG, Mian PAN, Zumin WANG

“…Focusing on the issue of rather poor denoising performance of the traditional kernel norm minimization based method caused by the biased approximation of kernel norm to rank function,based on the low-rank theory,a gamma norm minimization based image denoising algorithm was developed.The noisy image was firstly divided into some overlapping patches via the proposed algorithm,and then several non-local image patches most similar to the current image patch were sought adaptively based on the structural similarity index to form the similar image patch matrix.Subsequently,the non-convex gamma norm could be exploited to obtain unbiased approximation of the matrix rank function such that the low-rank denoising model could be constructed.Finally,the obtained low-rank denoising optimization issue could be tackled on the basis of singular value decomposition,and therefore the denoised image patches could be re-constructed as a denoised image.Simulation results demonstrate that,compared to the existing state-of-the-art PID,NLM,BM3D,NNM,WNNM,DnCNN and FFDNet algorithms,the developed method can eliminate Gaussian noise more considerably and retrieve the original image details rather precisely.…”
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Improved K-Means Algorithm for Nearby Target Localization by Zongwen Yuan, Xingdi Wang, Fuyang Chen, Xicheng Ma

“…In the K-means algorithm, we integrate a quartile range anomaly detection algorithm to address interference signal issues. …”
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Boosting any learning algorithm with Statistically Enhanced Learning by Florian Felice, Christophe Ley, Stéphane P. A. Bordas, Andreas Groll

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A Compression-based Algorithm for Chinese Word Segmentation by W. J. Teahan, Yingying Wen, Rodger McNab, Ian H. Witten

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Heterogeneous redundancies scheduling algorithm for mimic security defense by Qinrang LIU, Senjie LIN, Zeyu GU

“…The scheduling of heterogeneous redundancies is one of the key lines of mimic security defense,but the existing scheduling strategies are lack of consideration about the similarity among redundancies and the scheduling algorithms are incomprehensive.A new scheduling algorithm called random seed ＆amp; minimum similarity (RSMS) algorithm was proposed,which combined dynamics and reliability by determining a scheduling scheme with minimum global-similarity after choosing a seed-redundancy randomly.Theoretical analysis and simulation results show that RSMS algorithm possessed a far longer scheduling cycle than maximum dissimilarity algorithm,as well as a far lower failure rate than random scheduling algorithm,which represents an effective balance between dynamics and reliability.…”
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Early detection of sepsis using machine learning algorithms by Rasha M. Abd El-Aziz, Alanazi Rayan

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Using Genetic Algorithms for Navigation Planning in Dynamic Environments by Ferhat Uçan, D. Turgay Altılar

“…In this paper, the genetic algorithm solution of the dynamic flight planning problem is explained. …”
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Global Roots and Poles Finding Algorithm on Quantum Computer by Jakub Buczkowski, Tomasz Kozminski, Filip Szczepanski, Michal Wilinski, Tomasz P. Stefanski

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Android malware detection method based on combined algorithm by Hao CHEN, Sihan QING

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Energy constraint Bayesian compressive sensing detection algorithm by Chun-hui ZHAO, Yun-long XU

“…To solve the shortage of nodes handling ability and limited energy in wireless sensor network,an energy constraint Bayesian compressive sensing detection algorithm was proposed.To balance the energy of the whole network and prevent network paralyzed due to too fast consumption of some nodes energy,the new algorithm not only considers effect of reconstruction,but also regards energy of nodes,while choosing observation vector，and uses improved clustering algorithm to select an optimal transmission path.The simulation results show that the energy constraint Bayesian compressive sensing detection algorithm has longer the survival time of the network than traditional Bayesian compressive sensing.…”
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