BIMLP Model Based on Deep Learning for Predicting Electrical Load Demand by Somayeh Talebzadeh, Reza Radfar, Abbas Toloei Ashlaghi

“…However, the complexities of demand patterns, weather variability, and socioeconomic factors make it challenging to forecast demand with high accuracy. …”
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ML-based Plant Stress Detection from IoT-sensed Reduced Electromes by Marcos De Oliveira Jr, Gregory Sedrez, Gerson Geraldo H. Cavalheiro

“…The recognition of patterns in the electrical activities of plants (electromes, in time series format) has gained prominence in recent years. …”
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Subgrouping autism and ADHD based on structural MRI population modelling centiles by Clara Pecci-Terroba, Meng-Chuan Lai, Michael V. Lombardo, Bhismadev Chakrabarti, Amber N. V. Ruigrok, John Suckling, Evdokia Anagnostou, Jason P. Lerch, Margot J. Taylor, Rob Nicolson, Stelios Georgiades, Jennifer Crosbie, Russell Schachar, Elizabeth Kelley, Jessica Jones, Paul D. Arnold, Jakob Seidlitz, Aaron F. Alexander-Bloch, Edward T. Bullmore, Simon Baron-Cohen, Saashi A. Bedford, Richard A. I. Bethlehem

“…We identified subgroups with distinct patterns of alterations relative to controls but note that these results rely heavily on the algorithm used and encourage detailed reporting of methods and features used in future studies.…”
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Rural Landscape Characters and Spatial Correlation Mechanism in the Tiaoxi River – Canal Basin in Zhejiang Province by Lin ZHANG, You ZUO, Binyi LIU

“…Future research will construct a spatio-temporal dynamic dataset of canal heritage landscapes, which aims to enhance the fine-grained character extraction and type classification accuracy of machine learning algorithm models for rural landscapes. …”
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Mapping Vegetation Dynamics in Wyoming: A Multi-Temporal Analysis using Landsat NDVI and Clustering by N. Kuppala, C. Navneet Krishna, V. V. Sajith Variyar, R. Sivanpillai

“…As part of this study, we compared the outputs generated by two unsupervised machine learning algorithms with a conventional image clustering technique. …”
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A comprehensive analysis of molecular characteristics of hot and cold tumor of gastric cancer by Chenxi Lv, Tianwei Chen, Jiangtao Li, Yuqiang Shan, Hong Zhou

“…Subsequently, 101 machine learning algorithm combinations were employed to construct a prognostic model based on the identified gene modules. …”
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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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Spatiotemporal assessment of ecological quality and driving mechanisms in the Beijing metropolitan area by Aibo Jin, Hui Li, Xiangrong Wang, Ziyao Wang

“…Ecological quality is quantitatively evaluated using the Remote Sensing Ecological Index (RSEI), leveraging MODIS imagery, climate data, land use patterns, and soil characteristics. Spatial clustering patterns of ecological quality are identified through RSEI calculations and spatial autocorrelation analyses, while future trends are projected utilizing the coefficient of variation, Sen and Mann–Kendall methods, and the Hurst index. …”
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Copy-Move Forgery Verification in Images Using Local Feature Extractors and Optimized Classifiers by S. B. G. Tilak Babu, Ch Srinivasa Rao

“…The paper aims to present copy-move forgery detection algorithms with the help of advanced feature descriptors, such as local ternary pattern, local phase quantization, local Gabor binary pattern histogram sequence, Weber local descriptor, and local monotonic pattern, and classifiers such as optimized support vector machine and optimized NBC. …”
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Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…Specifically, ANN models excel at detecting subtle, complex patterns that reflect battery health and performance, crucial for accurate SOC estimation. …”
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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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Research on load labeling method for big data in novel power system by ZHANG Ximing, XU Huan, YANG Qiuyong

“…The synthetic dataset is compared with the real dataset, and the smart grid machine learning algorithm is trained and tested on this basis. …”
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Regional trending topics mining from real time Twitter data for sentiment, context, network and temporal analysis by Mousumi Hasan, Mujiba Shaima, Quazi Saad ul Mosaher

“…Unlike other social media platforms, Twitter offers researchers an open data source for multifaceted studies, motivating us to delve into regional trending topics, analyzing associated sentiments, context, networks, and temporal patterns. Using machine learning techniques combined with the VADER algorithm, we conducted a comprehensive analysis involving text, metadata, contextual cues, media, links, and historical data. …”
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Classification of patients with lithium-treated bipolar disorder based on gene expression: Dirichlet Bayesian network model by Nader Salari, Sahar Souri Pilangorgi, Afshin Almasi, Soodeh Shahsavari, Andrew J. Fournier

“…Essential variables were selected using partial least squares regression to analyze and classify the data. The plaid algorithm was employed to identify identical patterns and biclusters within the gene expression data. …”
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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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Development of a Serum Metabolome‐Based Test for Early‐Stage Detection of Multiple Cancers by Rajnish Nagarkar, Mamillapalli Gopichand, Suparna Kanti Pal, Ankur Gupta, Najmuddin Md Saquib, Ahmad Ahmad, Ganga Sagar, Kanury V. S. Rao, Zaved Siddiqui, Imliwati Longkumer

“…After processing, the data were analyzed by our cancer detection machine‐learning algorithm to differentiate cancer from non‐cancer samples. …”
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Analysis and Recommendation of Outdoor Activities for Smart City Users Based on Real-Time Contextual Data by S. R. Mani Sekhar, D. M. Mushtaq Ahmed, G. M. Siddesh

“…This data are processed and interpreted using machine learning algorithms, which find correlations, trends, and patterns that affect outdoor activities. …”
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Enhancing multiclass brain tumor diagnosis using SVM and innovative feature extraction techniques by Mustafa Basthikodi, M. Chaithrashree, B. M. Ahamed Shafeeq, Ananth Prabhu Gurpur

“…This research addresses the challenge of multiclass categorization by employing Support Vector Machine (SVM) as the core classification algorithm and analyzing its performance in conjunction with feature extraction techniques such as Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP), as well as the dimensionality reduction technique, Principal Component Analysis (PCA). …”
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Development of an Automated Management System for Agricultural Technologies in Horticulture by D. O. Khort, A. I. Kutyrev, I. G. Smirnov, I. V. Voronkov

“…The web application used the Model View Controller design pattern, and Bootstrap as the css framework. Data visualization from the database was carried out using cloud technology, placing the site using a set of Internet Information Services. …”
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