Five-Axis Tool Path Generation of Injection Mold Represented by T-Spline Surface by Ce Shang, Hongyao Shen, Jianzhong Fu, Yangfan Sun, Shuhua Yue, Jianfeng Zhang

“…And, its patch layout information can be utilized for tool path planning. We propose an algorithm to determine the patch processing order and generate nonretraction tool path for T-spline surface models. …”
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Road Traffic Flow Speed on Rural Roads in Latvia by Juris Kreicbergs, Katerina Folla, Juris Smirnovs

“… The aim of this article is to perform a comprehensive analysis of the data obtained during flow speed measurements on Latvian national roads. An algorithm for data selection was developed and implemented allowing for an analysis of comparable and unbiased traffic flow measurement data. …”
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Theoretical Design and First Test in Laboratory of a Composite Visual Servo-Based Target Spray Robotic System by Dongjie Zhao, Ying Zhao, Xuelei Wang, Bin Zhang

“…In addition, locating algorithm for the MEC center in nozzle reference frame and the hand-eye calibration matrix were studied. …”
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Spatiotemporal Influence Analysis Through Traffic Speed Pattern Analysis Using Spatial Classification by Kyusoo Chong

“…This methodology uses high-resolution vehicle trajectory data to precisely identify unstable and low-speed traffic sections. Using the geohash algorithm, the area is hierarchically segmented based on the standard deviation of speed in general traffic flow, facilitating the identification of unstable traffic flow patterns. …”
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Optimization of Clinical Nursing Management System Based on Data Mining by Yongxia Chen

“…Therefore, this research is based on the framework of the hospital’s existing clinical care system, using data mining technology to improve the Bayesian algorithm and data preprocessing, optimizes the design of functional modules in the clinical nursing management system, and optimizes the patient information management, medical order management, medical order execution management, basic information and expense management, nursing execution process management, system and data management, barcode management, physical sign management, WAP information management, and other subsystems in the clinical nursing information management system. …”
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Bias Correction in Monthly Records of Satellite Soil Moisture Using Nonuniform CDFs by Shan Wang, Huiling Shan, Chi Zhang, Yuexing Wang, Chunxiang Shi

“…In this paper, we applied the Douglas–Peucker curve approximation algorithm to approximate the CDFs and found that three nonuniformly spaced samples can achieve the same reduction in standard deviation. …”
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Blind Channel Estimation Based on Multilevel Lloyd-Max Iteration for Nonconstant Modulus Constellations by Xiaotian Li, Jing Lei, Wei Liu, Erbao Li, Yanbin Li

“…Moreover, when the number of received symbols is small, we propose the lacking constellations equalization algorithm to reduce the influence of lacking constellations. …”
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Pseudo-siamese network image tampering localization model based on reinforced samples by Jinwei WANG, Zihe ZHANG, Xiangyang LUO, Bin MA

“…With the continuous development of the internet, an increasing number of images have been tampered with on the network, accompanied by a growing range of techniques to cover up tampering traces.However, most current detection models neglect the impact of image post-processing on tamper detection algorithms, limiting their real-life applications.To address these issues, a general image tampering location model based on enhanced samples and the pseudo-twin network was proposed.The pseudo-twin network enabled the model to learn tampering features in real images.On one hand, by applying convolution constraints, the image content was suppressed, allowing the model to focus more on residual trace information of tampering.The two-branch structure of the network facilitated the comprehensive utilization of image feature information.By utilizing enhanced samples, the model could dynamically generate the most crucial pictures for learning tamper types, enabling targeted training of the model.This approach ensured that the model converged in all directions, ultimately obtaining the global optimal model.The idea of data enhancement was employed to automatically generate abundant tampered images and corresponding masks, effectively resolving the limited tampering dataset issue.Extensive experiments were conducted on four datasets, demonstrating the feasibility and effectiveness of the proposed model in pixel-level tamper detection.Particularly on the Columbia dataset, the algorithm achieves a 33.5% increase in F1 score and a 23.3% increase in MCC score.These results indicate that the proposed model harnesses the advantages of deep learning models and significantly improves the effectiveness of tamper location detection.…”
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Methods for Improving Point Cloud Authenticity in LiDAR Simulation for Autonomous Driving: A Review by Yanzhao Yang, Jian Wang, Xinyu Guo, Xinyu Yang, Wei Qin

“…Experimental results demonstrate the effectiveness of these techniques in enhancing perception algorithm performance. The paper identifies challenges in simulating LiDAR data, such as accuracy discrepancies, brand adaptability, and the need for comprehensive evaluation metrics. …”
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Construction of a Visual Saliency Model for Neighborhood Building Landmarks Based on K-Means Clustering by Chen Li, Zheng Qiao

“…Considering that the visual saliency of the landmarks in the neighborhood is reflected by the variance of the influencing factors and that the scope of the landmarks is localized, the local outlier detection algorithm is used to solve the variance of the secondary indicators. …”
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New Features Using Robust MVDR Spectrum of Filtered Autocorrelation Sequence for Robust Speech Recognition by Sanaz Seyedin, Seyed Mohammad Ahadi, Saeed Gazor

“…This modification results in reduction of the noise residuals of the estimated spectrum from the filtered autocorrelation sequence, thereby leading to a more robust algorithm. Our proposed method, when evaluated on Aurora 2 task for recognition purposes, outperformed all Mel frequency cepstral coefficients (MFCC) as the baseline, relative autocorrelation sequence MFCC (RAS-MFCC), and the MVDR-based features in several different noisy conditions.…”
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Study on the Accuracy Improvement of the Second-Kind Fredholm Integral Equations by Using the Buffa-Christiansen Functions with MLFMA by Yue-Qian Wu, Xin-Qing Sheng, Xing-Yue Guo, Hai-Jing Zhou

“…In this paper, the multilevel fast multipole algorithm (MLFMA) is employed to accelerate iterative solution of the magnetic-field integral equation (MFIE). …”
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Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial Navigation by Zi-Ming Wang, Chun-Liang Lin, Chian-Yu Lu, Po-Chun Wu, Yang-Yi Chen

“…Our approach harnesses advanced image feature-recognition techniques, employing an enhanced scale-invariant feature transform algorithm and a neural network model. The recognition of prominent scene features is prioritized, thus improving recognition speed and precision. …”
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A Bicriteria Model to Determine Pareto Optimal Pulse Vaccination Strategies by Funda Samanlioglu, Nauman Tabassum, Tolga Kudret Karaca, Ayse Humeyra Bilge

“…To find approximate efficient solutions to this bicriteria problem, ODE and genetic algorithm toolboxes of MATLAB are integrated (GA-ODE). …”
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Management of Delayed Onset Postoperative Hemorrhage after Anastomotic Urethroplasty by L. A. Bertrand, S. P. Elliott, B. N. Breyer, B. A. Erickson

“…Through our experience with three separate cases of significant postoperative urethral hemorrhage after EPA, we developed an algorithm for treatment beginning with conservative management and progressing through endoscopic and open techniques, as well as consideration of embolization by interventional radiology. …”
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Development of a New Modified Sonar Inspired Optimization based on Machine Learning Methods for Evaluating Compressive of High-Performance Concrete by Ali Nikkhoo, Amin Moshtagh, Mehri Mehrnia

“…This study examines the effectiveness of expert frameworks in determining compressive strength, aiming to enhance accuracy through the development of a master artificial neural network (ANN) system utilizing the sonar inspired optimization (SIO) algorithm. The ANN model employs exploratory data to establish initial optimal weights and biases, thereby improving precision. …”
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Research on an Aerial Docking Strategy for Meta-UAVs Using Aerodynamic Data Surrogate Models by Kangwen Sun, Yixiang Gao, Zhiyao Wang, Haoquan Liang, Chenxuan Zhao, Xinzhe Ji

“…Optimization of the docking process, focusing on impulse and moment of impulse, is achieved using a greedy algorithm. The results show a reduction in drag impulse and rolling moment by 10.89% and 15.76%, respectively, thereby easing the burden on the control system of UAVs.…”
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Brain tumor segmentation by deep learning transfer methods using MRI images by E.Y. Shchetinin

“…However, due to its time-consuming nature, there is a need for a fast and reliable automatic segmentation algorithm. In recent years, deep learning methods applied to brain tumor segmentation have shown promising results. …”
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Theoretical and computational investigations on estimation of viscosity of ionic liquids for green adsorbent: Effect of temperature and composition by Zhaoxiong Han

“…The models are optimized using the Whale Optimization Algorithm (WOA) to fine-tune hyperparameters, enhancing their predictive performance. …”
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Charge Diagnostics and State Estimation of Battery Energy Storage Systems Through Transformer Models by Rolando Antonio Gilbert Zequera, Anton Rassolkin, Toomas Vaimann, Ants Kallaste

“…With the continuous development of Artificial Intelligence (AI), designing accurate algorithms that provide diagnostics and maintenance of energy technologies is a challenging task in the energy transition domain. …”
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