АNALYSIS OF CLINICAL AND EXPERIMENTAL FORECASTING OF INFLUENCE OF ERGONOMICS OF DENTISTS WORK ON THE RESULT OF ENDONTIC TREATMENT by R.I. Ratushniy, N. Goderdzi, M.Yu. Goncharuk-Khomyn, S.B. Kostenko, I.V. Penzelyk, A.S. Chobeі

“…In-depth study and development of ways to optimize the basic ergonomic principles of work, monitoring the dynamics of implementation and, if necessary, the possibility of their correction is an important scientific and practical issue that can increase the level of dental care. …”
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Intelligent Algorithm Deep Learning Reinforcement Learning Module Integrated into the Navigation System to Enhance the Ability of Navigation to Accurately Serve Users by Li Jinhao

“…Subsequently, machine - learning algorithms are utilized to analyze user behavior data, identifying personalized demand patterns. Based on these analysis results, an intelligent navigation system prototype is designed and developed, featuring real - time road condition optimization, personalized route recommendation, and voice interaction functions. …”
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Ascetical and mystical experience in Chinese Buddhism by Dabetić Ilija

“…The permeation of indigenous Chinese and newly arrived religious patterns will lead to the emergence of an unusual authentic form of ascetism and mysticism in religious life of the Far East. …”
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A comprehensive survey of the machine learning pipeline for wildfire risk prediction and assessment by Naveed Ejaz, Salimur Choudhury

“…It highlights the integration of diverse data sources, including remote sensing, in-situ measurements, geospatial layers, and historical fire records and outlines pre-processing and feature engineering techniques to represent climatic, topographic, vegetation, anthropogenic, and temporal fire patterns. …”
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A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems by Asli Kaya Karakutuk, Ozer Ozdemir

“…The method is enhanced with various feature extraction methods. On the JAFFE dataset, the algorithm achieved an average classification accuracy of 94.55% when supported with local binary patterns and 94.27% with a histogram of oriented gradients. …”
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A performance-driven hybrid text-image classification model for multimodal data by Swati Gupta, Bal Kishan

“…Roberta is very good at extracting valuable information from both textual embeddings and at capturing complex patterns across many modalities. By using multi-modal feature extraction layers, which guarantee that different kinds of data are compatible, image representations attain this. …”
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Decoding a Huge Success: the Two Faces of C’è ancora domani (There’s Still Tomorrow) by Marco Cucco, Raoul Spiccia

“…From this perspective, C’è ancora domani demonstrates how, in order to valorized films, it is always important to develop ad hoc strategies, and that the prototypal nature of films also concerns the promotional patterns.…”
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Discriminative graph regularized representation learning for recognition. by Jinshan Qi, Rui Xu

“…Specifically, DGRL first integrates dimension reduction into ridge regression rather than treated them as two irrelevant steps, which enables us to capture the underlying subspace structure and correlation patterns among classes. Additionally, a graph regularizer that fully utilizes the local class information is developed and introduced to the new framework so as to enhance the classification accuracy and prevent overfitting. …”
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Assistive Devices Analysis for Visually Impaired Persons: A Review on Taxonomy by Sadia Zafar, Muhammad Asif, Maaz Bin Ahmad, Taher M. Ghazal, Tauqeer Faiz, Munir Ahmad, Muhammad Adnan Khan

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Optimized Ensemble Deep Learning for Real-Time Intrusion Detection on Resource-Constrained Raspberry Pi Devices by Muhammad Bisri Musthafa, Samsul Huda, Tuy Tan Nguyen, Yuta Kodera, Yasuyuki Nogami

“…Building upon our previously developed stacked Long Short-Term Memory (LSTM) model integrated with ANOVA feature selection, we optimize it by integrating dual-stage model compression: pruning and quantization to create a lightweight model suitable for real-time inference on Raspberry Pi devices. …”
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LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure by Zhi Liu, Xiaoli Zhang, Yong Wu, Yuansu Xu, Zhengying Cao, Zhibo Yu, Zihang Feng, Hongbin Luo, Chi Lu, Weibin Wang, Guanglong Ou

“…Spatial structure parameters facilitated a more precise and realistic depiction of competitive interactions and spatial distribution patterns among trees, thereby enhancing model performance. …”
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Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research by Muskan Kapoor, Enrique Sapena Ventura, Amy Walsh, Alexey Sokolov, Nancy George, Sunita Kumari, Nicholas J. Provart, Benjamin Cole, Marc Libault, Timothy Tickle, Wesley C. Warren, James E. Koltes, Irene Papatheodorou, Irene Papatheodorou, Doreen Ware, Doreen Ware, Peter W. Harrison, Christine Elsik, Galabina Yordanova, Tony Burdett, Christopher K. Tuggle

“…Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. …”
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Improved method for a pedestrian detection model based on YOLO by Yanfei LI, Chengyi DONG

“…The proposed method had superior performance in dense agricultural contexts while improving detection capabilities for pedestrian distribution patterns under complex farmland conditions, including variable lighting and mechanical occlusions. …”
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Assessing distortion in carbon fiber woven fabrics based on machine vision by Shiyue Li, Quanzhou Yao, Lin Ye

“…This work proposes a machine vision method to locate defective areas, identify defects, and describe fiber tow distribution patterns. A back-lighting imaging system was designed to minimize surface reflection interference, enabling high-quality fabric image acquisition. …”
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Intermittent Demand Forecasting for Spare Parts Using Artificial Neural Networks and Deep Learning: Literature Review by Omnia Nabil, Nahid Afia, T Ismail

“…Despite the advances, the availability and quality of datasets remain a significant limitation in developing robust models. Future research directions are identified, including the need for improved feature engineering, architecture optimization, and model interpretability. …”
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Efficient Classification of Pomegranate Diseases Using Deep Learning Models and Interactive Visualization by Mishra Gaurav, Nagaonkar Jagruti, Parmar Harsh, Joshi Gaurav

“…These models accurately detect complicated disease patterns, allowing for timely intervention to reduce crop losses and increase agricultural production. …”
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Predicting Accident Severity on Taiwan Highways Using Machine Learning and Electronic Toll Collection (ETC) Data by Pei-Chun Lin, Kuan-Yen Chen, Jenhung Wang

“…Unlike traditional accident-reporting systems, the ETC infrastructure provides a uniquely comprehensive and precise dataset that captures spatiotemporal traffic patterns and environmental conditions across the national highway network. …”
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"Svag elev" som social representation i Statens offentliga utredningar by Therese Friberg

“… Classifications of pupils as ‘weak’ have featured during the last century in Sweden and are still present in contemporary descriptions of pupils. …”
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Leveraging multi-source data and teleconnection indices for enhanced runoff prediction using coupled deep learning models by Jintao Li, Ping Ai, Chuansheng Xiong, Yanhong Song

“…Support Vector Regression (SVR) and Multi-Layer Perceptron Regression (MLPR) were chosen due to their strong adaptability in capturing nonlinear relationships and extracting latent hydrological patterns. The integration of these methods significantly improves prediction accuracy and model stability. …”
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Seasonal Coloration and Ecological Adaptations of Adventitious Roots of Four Salicaceous Species in Jiuzhaigou World Natural Heritage Site, Southwestern China by Ting Liu, Junhuai Xu, Weiyang Xiao, Lv Zhou, Yingzhou Chen, Xue Qiao, Sha Deng, Zongliang Du, Ya Tang

“…Seasonal color variations followed a distinct temporal pattern, transitioning from red or pink hues in summer to reddish‐brown in spring and autumn, and maroon or gray in winter. …”
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