A Maximum Power Point Tracking (MPPT) Strategy Based on Harris Hawk Optimization (HHO) Algorithm by Dabin Jia, Dazhi Wang

“…Although the Harris Hawk Optimization algorithm has advantages in optimizing multi-modal P-U curves, when the lighting conditions suddenly change, the output characteristic curve will undergo drastic changes, causing the algorithm to oscillate repeatedly at the maximum power point. …”
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Enhancing Scalability and Network Efficiency in IOTA Tangle Networks: A POMDP-Based Tip Selection Algorithm by Mays Alshaikhli, Somaya Al-Maadeed, Moutaz Saleh

“…Traditional tip selection algorithms (TSAs) struggle to ensure fair tip selection, leading to inefficient transaction confirmations and network congestion. …”
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Efficient Spectral Galerkin and Collocation Approaches Using Telephone Polynomials for Solving Some Models of Differential Equations with Convergence Analysis by Ramy Mahmoud Hafez, Hany Mostafa Ahmed, Omar Mazen Alqubori, Amr Kamel Amin, Waleed Mohamed Abd-Elhameed

“…The suggested approach also handles partial differential equations (PDEs), emphasizing hyperbolic PDEs. …”
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A hybrid genetic tabu search algorithm based on a multi-operation joint movement neighborhood structure for job shop scheduling problems by Lei Wang, Kongfu Hu, Jingcao Cai, Long Cheng, Yuan Xiong, Jiawei Ren, Qiangqiang Xia

“…A hybrid genetic tabu search algorithm (HGTSA) is introduced, which combines the global search ability of the genetic algorithm (GA) and the local search ability of the tabu search (TS), with the goal of minimizing makespan. …”
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Optimizing PAPR performance for 6G OTFS waveform using adaptive genetic PTS method for Rician fading channels by Arun Kumar, Aziz Nanthaamornphong, Nishant Gaur

“…Abstract This paper proposes a novel method for reducing the peak-to-average power ratio (PAPR) in orthogonal time–frequency space (OTFS) modulation over Rician fading channels using an adaptive genetic algorithm-based partial transmit sequence (AGA-PTS) technique. …”
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THz UM-MIMO system channel estimation algorithm based on deep residual block fixed-point network by YU Shujuan, WEI Yuyao, CAI Lianglong, LU Hongyu, ZHANG Yun, ZHAO Shengmei

“…To mitigate the channel estimation challenges induced by hybrid near-far field and beam squint effects in THz ultra-massive MIMO systems, a deep learning-based FPN-OAMP-SRLG algorithm was proposed. A feature extraction network SRLG was constructed by developing a deep residual block (BSRB) with coordinate attention and partial channel shift, along with a gated linear self-attention module (SARG). …”
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DOA Estimation for Non-Gaussian Signals: Three-Level Nested Array and a Successive SS-MUSIC Algorithm by Sha Shi, Haowei Zeng, Heng Yue, Changbo Ye, Jianfeng Li

“…Besides, a successive SS-MUSIC algorithm is proposed, which employs the spatial smoothing estimating signal parameter via rotational invariance techniques (SS-ESPRIT) algorithm and partial spectrum searching multiple signal classification (PSS-MUSIC) to obtain initial estimations and fine estimations, respectively, resulting in a better balance between computational complexity and estimation accuracy.…”
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De-noising algorithms for the raised cosine pulse signal using the minimum-energy frame in the discrete signal space by Ying-hai XIE, Wei YANG, Ting-ting FAN

“…The de-noising algorithms were proposed for the raised cosine pulse signal using minimum-energy(wavelet) frame in the discrete signal space.For the given two minimum-energy frames,the decomposition coefficients of sampled sequence appeared significant statistical characteristics difference between the raised cosine pulse signal and additive Gaussian noise under the frames’sub-sequences.Based on this,two threshold de-noising algorithms were provided to makes full use of the merit that the frame was fit for the de-noising work,they removed partial noise component while keeping the component of original signal and got effic nt de-noising result.The simulation results show that,when the modulating method is BPSK and its raised cosine pulse signal is polluted by the additive Gaussian noise,then if add a pre-processing link to denoise the receiving waveform using the algorithms,the receiver can greatly increase the signal-to-noise ratio of receiving signal and have about 3.1dB and 2.7dB performance gain of bit error ratio,respectively.…”
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De-noising algorithms for the raised cosine pulse signal using the minimum-energy frame in the discrete signal space by Ying-hai XIE, Wei YANG, Ting-ting FAN

“…The de-noising algorithms were proposed for the raised cosine pulse signal using minimum-energy(wavelet) frame in the discrete signal space.For the given two minimum-energy frames,the decomposition coefficients of sampled sequence appeared significant statistical characteristics difference between the raised cosine pulse signal and additive Gaussian noise under the frames’sub-sequences.Based on this,two threshold de-noising algorithms were provided to makes full use of the merit that the frame was fit for the de-noising work,they removed partial noise component while keeping the component of original signal and got effic nt de-noising result.The simulation results show that,when the modulating method is BPSK and its raised cosine pulse signal is polluted by the additive Gaussian noise,then if add a pre-processing link to denoise the receiving waveform using the algorithms,the receiver can greatly increase the signal-to-noise ratio of receiving signal and have about 3.1dB and 2.7dB performance gain of bit error ratio,respectively.…”
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A Robust Path Following Algorithm Based on the Orthogonal Bishop Parametrization for A non–Holonomic Mobile Manipulator by Mazur Alicja, Dyba Filip

“…The achieved results are verified with an exemplary simulation study. The proposed algorithm assures asymptotic convergence of errors to zero for less strict requirements imposed on the desired path and in the case of partial knowledge of the dynamics model.…”
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Optimizing Personalized Recommender Systems for Teachers’ Digital Learning Models Using Deep Learning Algorithms by Jun Zhong, Wenjuan Zhang

“…To address this issue, this paper proposes a personalized recommendation algorithm based on Graph Neural Networks (PRAGNN) for teachers’ digital learning models. …”
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Unsupervised Binary Classifier-Based Object Detection Algorithm with Integrated Background Subtraction Suitable for Use with Aerial Imagery by Gabija Veličkaitė, Ignas Daugėla, Ivan Suzdalev

“…This research presents the development of a novel object detection algorithm designed to identify humans in natural outdoor environments using minimal computational resources. …”
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Do FinTech algorithms reduce gender inequality in banks loans? A quantitative study from the USA by Ziheng Song, Shafiq Ur Rehman, Chun PingNg, Yuan Zhou, Patick Washington, Ricardo Verschueren

“…If the data is partial or biased, the algorithmic decision-making process may also be discriminatory, exacerbating existing inequalities. …”
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Effect of geographical parameters on PM10 pollution in European landscapes: a machine learning algorithm-based analysis by Seyedehmehrmanzar Sohrab, Nándor Csikós, Péter Szilassi

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Tsallis Entropy-Based Nonparametric Focusing Algorithm Under Dual-Stage Processing Framework for THz SAR Imaging by Siyu Chen, Yong Wang, Hongzhi Li

“…Here, THz SAR image focusing-oriented dual-stage processing framework and Tsallis entropy-based nonparametric image focusing algorithm are proposed. First, by distinguishing fundamental principles from specific application and implementation particulars, the proposed framework integrates the model constructed by multiple THz SAR image defocusing factors and the dual-strategy THz SAR image focusing algorithm driven by different defocusing factors. …”
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Near- and Mid-Infrared Spectroscopy Combined with Machine Learning Algorithms to Determine Minerals and Antioxidant Activity in Commercial Cheese by Ahmed Menevşeoglu, Nurhan Gunes, Huseyin Ayvaz, Sevim Beyza Öztürk Sarıkaya, Cuma Zehiroglu

“…Mineral content and antioxidant activity of ETC were aimed to be predicted using conventional FT-NIR and a portable FT-MIR spectrometer combined with partial least square regression (PLSR) and machine learning algorithms based on conditional entropy. …”
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Early Yield Prediction of Oilseed Rape Using UAV-Based Hyperspectral Imaging Combined with Machine Learning Algorithms by Hongyan Zhu, Chengzhi Lin, Zhihao Dong, Jun-Li Xu, Yong He

“…Meanwhile, optimized feature selection algorithms identified effective wavelengths (EWs) and vegetation indices (VIs) for yield estimation. …”
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Three-step surgical management algorithm for annular rupture in transcatheter aortic valve replacementCentral MessagePerspective by Kizuku Yamashita, MD, PhD, Kazuo Shimamura, MD, PhD, Koichi Maeda, MD, PhD, Ai Kawamura, MD, PhD, Masaki Taira, MD, PhD, Daisuke Yoshioka, MD, PhD, Shigeru Miyagawa, MD, PhD

“…Methods: From 2009 to 2022, 8 patients of 1083 transcatheter aortic valve implantation (0.8%) developed annulus rupture and were treated with the three-step algorithm. The algorithm was composed of a first step (pericardial drainage and protamine neutralization with blood pressure control), second step (manual hemostatic compression via full/partial sternotomy), and a third step (conservative treatment or radical surgical correction). …”
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Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm by Xuehui Fan, Ruixue Ye, Yan Gao, Kaiwen Xue, Zeyu Zhang, Jing Xu, Jingpu Zhao, Jun Feng, Yulong Wang

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Delineation of 3D crustal seismic structures beneath western Tibet and the Himalayan range using local earthquake tomography by Arghya Kusum Dey, Niptika Jana, Rahul Biswas

“…Preliminary events located using the VELEST algorithm resulted in the development of a 1-D velocity model through inversion, which was then used in the TomoDD algorithm to relocate earthquakes and generate a high-resolution 3-D velocity structure model. …”
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