Tensor decomposition based-joint active device detection and channel estimation under frequency offset by QU Ruiyun, LIU Zujun, HUANG Beilei

“…Compared with the existing algorithms under the frequency offsets, the proposed algorithm has a significant improvement in detection performance.…”
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Optimization of IoT-Based Motion Intelligence Monitoring System by Jian Qiao, Zhendong Zhang, Enqing Chen

“…For active pattern recognition, two types of classification algorithms with different complexity are proposed based on Support Vector Machine (SVM) and deep neural networks, respectively, to adapt to scenarios with different computational capabilities. …”
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FRANet: A Feature Refinement Attention Network for SAR Image Denoising by Shuaiqi Liu, Yu Lei, Qi Hu, Ming Liu, Bing Li, Weiming Hu, Yu-Dong Zhang

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QuantiFly: Robust Trainable Software for Automated Drosophila Egg Counting. by Dominic Waithe, Peter Rennert, Gabriel Brostow, Matthew D W Piper

“…The basis of the QuantiFly software is an algorithm which applies and improves upon an existing advanced pattern recognition and machine-learning routine. …”
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Massive unsourced multiple access scheme based on block sequence codebook and compressed sensing by Jing ZHANG, Lin MA, Chulong LIANG, Hongxu GAO

“…A massive unsourced multiple access scheme based on block sequence codebook and compressed sensing was proposed for sporadic burst scenario in massive machine type communication (mMTC).Firstly, a large-capacity spreading codebook generation scheme was designed according to a specific shift pattern, thus the codebook space was expanded.Secondly, the sparse structure of uplink signal was combined with multi-carrier technology to support overlapping transmission of multi-user data on some subcarriers, thus the spectral efficiency was improved.Finally, a multi-carrier CS-MUD model was established, and a group orthogonal matching pursuit algorithm based on codebook sequence blocks was designed to achieve the joint detection of active users and their uplink data.Simulation results show that the proposed scheme can effectively reduce the bit error rate of massive random access.…”
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Improving cancer detection through computer-aided diagnosis: A comprehensive analysis of nonlinear and texture features in breast thermograms. by Hamed Khodadadi, Shima Nazem

“…Besides, to optimize feature selection and reduce redundancy, a metaheuristic optimization technique called Non-Dominated Sorting Genetic Algorithm (NSGA III) is applied. The proposed method utilizes various machine learning algorithms, including Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Pattern recognition Network (Pat net), and Fitting neural Network (Fit net), for classification. ten-fold cross-validation ensures robust performance evaluation. …”
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Discriminatively Constrained Semi-Supervised Multi-View Nonnegative Matrix Factorization with Graph Regularization by Guosheng Cui, Ye Li, Jianzhong Li, Jianping Fan

“…Nonnegative Matrix Factorization (NMF) is one of the most popular feature learning technologies in the field of machine learning and pattern recognition. It has been widely used and studied in the multi-view clustering tasks because of its effectiveness. …”
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A Spiking Neural Network With Adaptive Graph Convolution and LSTM for EEG-Based Brain-Computer Interfaces by Peiliang Gong, Pengpai Wang, Yueying Zhou, Daoqiang Zhang

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A Multi-Epiphysiological Indicator Dog Emotion Classification System Integrating Skin and Muscle Potential Signals by Wenqi Jia, Yanzhi Hu, Zimeng Wang, Kai Song, Boyan Huang

“…Comprehensive feature extraction (time-domain, frequency-domain, nonlinearity) was conducted for each signal modality, and inter-emotional variance was analyzed to establish discriminative patterns. Four machine learning algorithms—Neural Networks (NN), Support Vector Machines (SVM), Gradient Boosting Decision Trees (GBDT), and XGBoost—were trained and evaluated, with XGBoost achieving the highest classification accuracy of 90.54%. …”
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Assessment of environmental impacts of armed conflict in Mozambique using remotely sensed data by Focas Francisco Bacar, Hilário Biché Faque

“…To evaluate these effects, we used Multi-temporal satellite images (Landsat 5 TM and Landsat 8 OLI-TIRS) in combination with fieldwork, geographic information systems, landscape ecology metrics, and the Random Forest machine learning algorithm. We also evaluated the spatiotemporal pattern of density of conflict events and landscape changes using the Kernel density estimator model. …”
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Development characteristics and intelligent identification method of natural fractures: A case study of the Upper Triassic Xujiahe Formation in the western Sichuan Depression, Sich... by LI Wei, WANG Min, XIAO Dianshi, JIN Hui, SHAO Haoming, CUI Junfeng, JIA Yidong, ZHANG Zeyuan, LI Ming

“…The conventional logging data with fracture and non-fracture labels were normalized, and machine learning algorithms were applied for fracture intelligent prediction. …”
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Early Warning for Stepwise Landslides Based on Traffic Light System: A Case Study in China by Shuangshuang Wu, Zhigang Tao, Li Zhang, Song Chen

“…Furthermore, leveraging the C5.0 machine learning algorithm, a comparison between the predictive capabilities of the TLS model and a pure rate threshold model reveals that the TLS model achieves a 93% accuracy rate, outperforming the latter by 7 percentage points. …”
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Temporal Backtracking and Multistep Delay of Traffic Speed Series Prediction by Licheng Qu, Minghao Zhang, Zhaolu Li, Wei Li

“…With a real traffic data set, the coordinate descent algorithm was employed to search and determine the optimal backtracking length of traffic sequence, and multistep delay predictions were performed to demonstrate the relationship between delay steps and prediction accuracies. …”
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A Fault Diagnosis Model for Rotating Machinery Using VWC and MSFLA-SVM Based on Vibration Signal Analysis by Lei You, Wenjie Fan, Zongwen Li, Ying Liang, Miao Fang, Jin Wang

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The Relationship Between Surface Meteorological Variables and Air Pollutants in Simulated Temperature Increase Scenarios in a Medium-Sized Industrial City by Ronan Adler Tavella, Daniele Feijó das Neves, Gustavo de Oliveira Silveira, Gabriella Mello Gomes Vieira de Azevedo, Rodrigo de Lima Brum, Alicia da Silva Bonifácio, Ricardo Arend Machado, Letícia Willrich Brum, Romina Buffarini, Diana Francisca Adamatti, Flavio Manoel Rodrigues da Silva Júnior

“…This study utilized five years of daily meteorological data (from 1 January 2019 to 31 December 2023) to model atmospheric conditions and two years of daily air pollutant data (from 21 December 2021 to 20 December 2023) to simulate how pollutant levels would respond to annual temperature increases of 1 °C and 2 °C, employing a Support Vector Machine, a supervised machine learning algorithm. …”
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A novel flexible near-infrared endoscopic device that enables real-time artificial intelligence fluorescence tissue characterization. by Gareth Gallagher, Ra'ed Malallah, Jonathan P Epperlein, Jeffrey Dalli, Niall Hardy, Abhinav Jindal, Pol G MacAonghusa, Ronan A Cahill

“…Here, to close this technical gap, we present our development of a colonoscope-compatible flexible imaging probe for NIR-ICG visualization combined with a full field of view machine learning (ML) algorithm for fluorescence quantification and perfusion pattern cross-correlation (including first in human testing). …”
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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…Artificial intelligence (AI) has emerged as a transformative technology in healthcare, offering outstanding capabilities in data analysis, pattern recognition, and helping in decision-making. …”
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A Novel Aerosol Optical Depth Retrieval Method Based on SDAE from Himawari-8/AHI Next-Generation Geostationary Satellite in Hubei Province by Shiquan Deng, Ting Bai, Zhe Chen, Yepei Chen

“…The study of the spatiotemporal change pattern of the hourly AOD in the Hubei province shows that the algorithm has good stability in the face of changes in the angle and intensity of sunlight.…”
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Probing real sensory worlds of receivers with unsupervised clustering. by Michael Pfeiffer, Manfred Hartbauer, Alexander B Lang, Wolfgang Maass, Heinrich Römer

“…We apply a recently developed unsupervised machine learning algorithm based on probabilistic inference to find frequently occurring firing patterns in the response of the acoustic interneuron. …”
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Neuropathological stages of neuronal, astrocytic and oligodendrocytic alpha-synuclein pathology in Parkinson’s disease by Maria Otero-Jimenez, Marcelina J. Wojewska, Lawrence P. Binding, Simona Jogaudaite, Sandra Gray-Rodriguez, Alexandra L. Young, Steve Gentleman, Javier Alegre-Abarrategui

“…Astrocytic α-syn pathology was mainly centered in the amygdala and exhibited a unique stereotypical progression whilst oligodendrocytes displayed a distribution akin to the established neuronal progression pattern. SuStaIn modeling was further used to test for heterogeneity in the spatiotemporal progression, revealing that a subset of cases might follow an alternative pattern. …”
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