A scale adaptive visual object tracking algorithm based on weighted neutrosophic similarity coefficient by Keli HU, En FAN, Jun YE, Shigen SHEN, Yuzhang GU

“…The weight of the truth,indeterminacy,and falsity membership under the neutrosophic framework may be different when dealing with different problems.Due to this,a component weighted cosine similarity coefficient was proposed,and it was introduced into the mean shift tracking algorithm.Firstly,the corresponding methods for calculating the membership of the truth,indeterminacy,and falsity were proposed based on the theory of 3σ,as well as the similarity between the features of the corresponding area of the object and background.Then the weighted cosine similarity coefficient was used to construct the weight vector.In addition,a weighted cosine similarity coefficient based scale updating method was proposed.The experimental results demonstrate that the modified visual tracking algorithm performs well,even when there exists challenges like similar background,illumination or scale variation.…”
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Exploring the Capacity of Large Language Models to Assess the Chronic Pain Experience: Algorithm Development and Validation by Jacopo Amidei, Rubén Nieto, Andreas Kaltenbrunner, Jose Gregorio Ferreira De Sá, Mayte Serrat, Klara Albajes

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Creation of a Custom 3D Algorithm for Proper Alignment of Straight Nails in Tibiotalocalcaneal Arthrodesis by Omer Subasi PhD, Wei Shao Tung BS, Julian Hollander Bsc, Samir Ghandour MD, Atta Taseh MD, Nour Nassour MD, Adarsh Aratikatla, Alireza Ebrahimi MD, Bernard Burgesson MD, Soheil Ashkani-Esfahani MD, John Y. Kwon MD

“…The root mean (SD) square error of the affine transformation was 1.62 ± 1.02 mm, demonstrating the validity of mapping. …”
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A low complexity detection algorithm for large scale multiuser MIMO based on message passing by Qiong WANG, Wei YE, Mingming JI

“…According to the problem of high complexity of base station detection in large scale multiuser multiple input multiple output (MIMO) system,a low complexity multiuser variable node full information Gaussian message passing iterative detection algorithm based on forced convergence (VFI-GMPID-FC) was proposed.Firstly,the traditional Gaussian message passing iterative detection (GMPID) algorithm was improved to obtain VFI-GMPID algorithm,the detection performance of the VFI-GMPID algorithm approximates the minimum mean square error detection (MMSE) algorithm,but the complexity was considerably less than the MMSE algorithm.Then,the VFI-GMPID-FC algorithm was proposed to reduce the complexity of the algorithm and improve the detection efficiency.Finally,the simulation results show that the proposed algorithm can effectively reduce the algorithm complexity while ensuring the detection performance.…”
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Near-field localization algorithm of multiple sound sources based on approximated kernel density estimator by Yu-zhuo FANG, Zhi-yong XU, Zhao ZHAO

“…For near-field localization of multiple sound sources in reverberant environments,a algorithm model based on approximated kernel density estimator (KDE) was proposed.Multi-stage (MS) of sub-band processing was introduced to effectively solve the spatial aliasing by wide spacing.Spatial likelihood function (SLF) was built for multi-dimensional fusion by using two operators,sum (S) and prod (P).Then four algorithms,S-KDE,P-KDE,S-KDEMS,P-KDEMS,were derived.By the comprehensive comparison of the two statistical indicators root mean square error (RMSE) and percentage of SLF (PSLF) which denoted the recognition,P-KDEMS is confirmed as a near-field localization algorithm of multiple sound sources with high robustness and recognition.…”
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Research on DV-Hop location algorithm based on range correction and improved gray wolf optimizer by Xiaoqiang ZHAO, Shuai WU, Chuanyi GAO, Ning LI, Bodong LI, Xiaoyong YANG

“…Node location is an important problem in wireless sensor network.Although the location algorithm based on distance measurement has small positioning error, it has many limitations when applied to outdoor environments.Therefore, based on the original distance vector-hop (DV-Hop) algorithm, received signal strength indication (RSSI) technology and the minimum mean square error (MMSE) criterion to modify the algorithm’s ranging process were introduced, and the improved gray wolf optimizer was used to optimize the process of determining the coordinates of unknown nodes.Simulation results show that, compared with the original DV-Hop algorithm and IPDV-Hop algorithm, the average location error rate of the IGDV-Hop algorithm under the initial parameters was reduced by 28% and 17% respectively, and the location effect was significantly improved.…”
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Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm by K. Gopalakrishnan, R. Sivaraj, M. Vijayakumar

“…In the proposed AWRC-DLMLO technique, the main phase of Gaussian filtering (GF) utilizing image pre-processing is implemented to eliminate unwanted noise. …”
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Algorithm for Recognition of Movement of Objects in a Video Surveillance System Using a Neural Network by S. Harish, C. Anil Kumar, Lakshmi Shrinivasan, S. Rohith, Belete Tessema Asfaw

“…The aim of this article is to address the problem of protecting the private property of a protected object, namely: we propose an algorithm for detection of object movements by means of a neural network for the video surveillance system. …”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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DNN-based Sub-6 GHz assisted millimeter wave network power allocation algorithm by Changyin SUN, Liyan LIU, Fan JIANG, Jing JIANG

“…Aimed at the problems of the signaling cost and power consumption in the power control measurement of the millimeter wave system, as well as the complexity caused by iteration operations, a millimeter wave link power allocation prediction algorithm using the Sub-6 GHz frequency band was proposed.Firstly, the mapping between the Sub-6 GHz band channel information and the optimal power allocation of the millimeter wave band was analyzed.Then, a deep neural network (DNN) model was utilized to realize this mapping function.To predict the power allocation of millimeter wave channel with Sub-6 GHz channel as input, the neural network was trained with the weighted mean square error minimization method (WMMSE) as the supervisor in different scenarios.The simulation results show that compared with the WMMSE algorithm in millimeter wave band, the proposed algorithm can obtain more than 97% of its sum-rate performance while taking less than 0.1% of the time.…”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Sistem Monitoring Tekanan Darah Berbasis Maximum Amplitude Algorithm Menggunakan Android Secara Realtime by Barlian Henryranu Prasetio, Brylliano Maza Putra, Dahnial Syauqy

“…Dengan menggunakan pendekatan menggunakan sinyal osilometrik ini akan diproses pada mikrokontroler Arduino UNO R3 untuk mencari nilai Mean Arterial Pressure, systole dan diastole menggunakan metode Maximum Amplitude Algorithm (MAA).  …”
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A New Study on Halpern and Nonconvex Combination Algorithm for Nonlinear Mappings in Banach Spaces with Applications by Gaobo Li

“…In this paper, we introduce a Halpern algorithm and a nonconvex combination algorithm to approximate a solution of the split common fixed problem of quasi-ϕ-nonexpansive mappings in Banach space. …”
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Automatic Analysis Algorithm of Position and Orientation Characteristic Set of Parallel Mechanism based on Neural Network by Wang Gang, Mao Zhiwei, Luo Yufeng, Shi Zhixin

“…A detailed description of the algorithm in 6 rules parallel mechanism POC set model and the neural network model is introduced,the main steps and examples analysis of the method are given. …”
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The Nelder–Mead Simplex Algorithm Is Sixty Years Old: New Convergence Results and Open Questions by Aurél Galántai

“…For the first type of convergence, we generalize the main result of Lagarias, Reeds, Wright and Wright (1998). …”
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Distributed quantile regression over sensor networks via the primal–dual hybrid gradient algorithm by Zheng Qin, Zhaoting Liu

“…We reformulate this non-smooth optimization problem as the task of finding a saddle point of a convex–concave objective and develop a distributed primal–dual hybrid gradient (dPDHG) algorithm for this purpose. Theoretical analyses guarantee the convergence of the proposed algorithm under mild assumptions, while experimental results show that the dPDHG algorithm converges significantly faster than subgradient-based schemes.…”
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Lightweight multidimensional feature enhancement algorithm LPS-YOLO for UAV remote sensing target detection by Yong Lu, Minghao Sun

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Optimized Partial Band Preamble and Timing Synchronization Algorithm for Orthogonal Time Frequency Space System by Wenchao Zhang, Xiaochen Lu, Guangliang Ren, Lirui Shen

“…Simulation results show that, compared with the available best performance benchmark algorithm, the proposed method achieves a 2dB signal-to-noise ratio gain under the same capture probability, and its root mean square error of timing offset estimation is only 1/3 that of the available benchmark algorithm.…”
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Seismic Behavior of a Timber Structure Based on a Soft-Kill BESO Optimization Algorithm by Felipe Solis, Pablo F. Parra, Patricio Cendoya, Luis F. Gonzalez-Böhme, Francisco Quitral-Zapata, Ricardo Gallardo

“…Analysis results show that wood braced-frame structures with low structural redundancy (and fewer main joints to dissipate energy), such as those obtained from topology optimization algorithms, exhibit a markedly brittle behavior with almost no displacement ductility. …”
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Research on 3D stability algorithm of potential sliding body in surface mining in confined space by Dong WANG, Xiaoyu XING, Li YIN, Shougong WANG, Lingwei KONG, Xiangyu MENG

“…Using the equivalent idea, the mechanical effect of each row of micro-strips is superimposed, which is equivalent to the micro-strips on the main sliding line of the sliding body. The equivalent shear strength parameters on the bottom interface of the main sliding line column are obtained, so as to establish a three-dimensional stability equivalent algorithm for restricting Carry out engineering application and design to recover coal resources. …”
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