Investigating Spatial Effects through Machine Learning and Leveraging Explainable AI for Child Malnutrition in Pakistan by Xiaoyi Zhang, Muhammad Usman, Ateeq ur Rehman Irshad, Mudassar Rashid, Amira Khattak

“…A multi-model approach was employed to address the research questions, which included Ordinary Least Squares Regression (OLS), various Spatial Models, Machine Learning Algorithms and Explainable Artificial Intelligence methods. …”
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Quantum-classical deep learning hybrid architecture with graphene-printed low-cost capacitive sensor for essential tremor detection by Javier Villalba-Díez, Ana González-Marcos

“…This integration offers improved processing capabilities, facilitating a more nuanced analysis of tremor patterns. Initial findings indicate greater stability in loss variability; however, further research is necessary to confirm these effects across broader datasets and clinical environments. …”
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AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction by Vij Priya, Tiwari Ankita

“…The proposed system offers real-time alerts and forecasts, facilitating proactive water resource management, agricultural planning, and disaster preparedness. Moreover, the research conducts a comparative evaluation of various machine learning models to identify the most effective algorithms for different climatic zones and crop types. …”
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Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

“…These findings enrich existing research and offer policy insights to enhance coordinated development in the Chengdu–Chongqing Economic Circle.…”
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Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques by Arifa Zahir, Zulfiqar Ali, Ahmad Sami Al-Shamayleh, Syed Raza Ab bas, Basharat Mahmood, Abdullah Hussein Al-Ghushami, Rubina Adnan, Adnan Akhunzada

“…Various Deep Learning algorithms, including Convolution Neural Network (CNN), LeNet, and Inception-V3 are implemented to classify the records and extract various patterns. …”
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Deciphering the complex links between inflammatory bowel diseases and NAFLD through advanced statistical and machine learning analysis by Deepak Kumar, Brijesh Bakariya, Chaman Verma, Zoltán Illés

“…There is an urgent need for non-invasive methods to diagnose various stages of liver dysfunction and uncover hidden pattern based on individual disease characteristics. …”
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Efficient Real-Time Pathfinding for Visually Impaired Individuals by Tadeh Ghahremanians, Hossein Mahvash Mohammadi

“…Traditional methods usually focus on the detection of specific patterns or objects, requiring custom algorithms for each object of interest. …”
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Decoding Subjective Understanding: Using Biometric Signals to Classify Phases of Understanding by Milan Lazic, Earl Woodruff, Jenny Jun

“…Action units (AUs) for each phase instance were measured using AFFDEX software. AU patterns associated with each phase were then identified through the application of six supervised machine learning algorithms. …”
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Cooling Load Forecasting Method for Central Air Conditioning Systems in Manufacturing Plants Based on iTransformer-BiLSTM by Xiaofeng Huang, Xuan Zhou, Junwei Yan, Xiaofei Huang

“…Due to the influence of multiple factors, the cooling load in manufacturing plants exhibits complex characteristics, including multi-peak patterns, periodic fluctuations, and short-term disturbances during meal periods. …”
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Efficient IDS for IoT Networks Using Host-Based Data Aggregation and Multi-Entropy Analysis by Yusei Katsura, Arata Endo, Ismail Arai, Kazutoshi Fujikawa

“…Against this backdrop, research on Intrusion Detection Systems (IDSs) leveraging machine learning in IoT environments has been actively conducted. …”
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PCA-Kriging-Based Oscillating Jet Actuator Optimization and Wing Separation Flow Control by Qixiang Sun, Wanbo Wang, Jiaxin Pan

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Evaluating GDPR right to information implementation in automated insurance decisions by Jakobi Timo, Arslan Salih, Harms Patrick

“…By identifying these concerns and correlating them to existing deceptive patterns, our research contributes to usable security by alerting process designers, data protection authorities, and enterprises to the significance of user-centric implementations. …”
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Concept Drift Detection in Data Stream Mining : A literature review by Supriya Agrahari, Anil Kumar Singh

“…The traditional classifiers are not expected to learn the patterns in a non-stationary distribution of data. …”
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Early Warning Systems for Plant Diseases in delta regions: Machine Learning Approaches by Biswas Debarghya, Sharma Priti

“…Integrated into the study is a variety of machine learning techniques such as supervised and unsupervised learning, as well as deep learning, and the study makes use of satellite imagery, weather data, soil sensors, and historical disease records from various sources. Some patterns and anomalies can indicate the onset of plant diseases, and the algorithms are trained to recognize them. …”
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Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory by Kgothatso Makubyane, Daniel Maposa

“…Future research could focus on enhancing prediction accuracy through hybrid algorithms and incorporating additional meteorological variables. …”
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Optimization of sports injury treatment through artificial intelligence: Methods for effective prevention, diagnosis and rehabilitation by Kimi Milić Marko, Sinanović Šćepan, Jestrović Vladimir

“…Through a systematic review of existing studies and technological advancements, key strategies introduced by AI in this field have been identified. The research methodology includes big data analysis, image processing, machine learning, and customized algorithms for prediction and rehabilitation monitoring. …”
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An Exploration of the Use of Educational Robotics in Preschool Education by Veronica Mihaela Rus, Beatrice Almășan

“…Decomposition, abstraction, pattern recognition and algorithms were the four components of computational thinking analyzed and all obtained a score above the mean of the Likert scale used. …”
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AI Methods for New Psychoactive Substance (NPS) Design and Analysis by Enrico Greco

“…Special emphasis is placed on mass spectrometry (MS)-based techniques, where AI algorithms (e.g., for spectral prediction and pattern recognition) are revolutionizing the detection and characterization of unknown NPSs. …”
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Autoinflammatory diseases: An immunologist’s view by A. Yu. Shcherbina

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A cosine similarity-based method for improving the accuracy of GIS discharge spectrum recognition by CHEN Xiaoxin, ZHOU Tonghao, LIU Jiangming, DAI Pengfei, LIU Yanqi, LI Wendong, ZHANG Guanjun

“…To enhance the precision and reliability of GIS partial discharge detection by utilizing the phase information in discharge spectra， this paper proposes a neural network-based PD pattern recognition method that incorporates cosine similarity. …”
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