High-efficiency filtration: Smart designs for particle trapping by Bahador Abolpour, Ramtin Hekmatkhah, Rahim Shamsoddini

“…To achieve this, we use a genetic algorithm to determine the optimal arrangement of square obstacles within a turbulent flow field. The process starts with an image processing method (IPM) that identifies geometric objects in the filtered image. …”
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Chatbot Informasi Penerimaan Mahasiswa Baru Menggunakan Metode FastText dan LSTM by Fahmi Yusron Fiddin, Agus Komarudin, Melina Melina

“…In this study, the text classification model uses the FastText method as the stage for representing words in vector form, then combined with several pre-processing methods (Tokenization & Casefolding) and LSTM for the classification stage. …”
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Enhancing Neural Network Training Through Neuroevolutionary Models: A Hybrid Approach to Classification Optimization by Hyasseliny A. Hurtado-Mora, Luis A. Herrera-Barajas, Luis J. González-del-Ángel, Roberto Pichardo-Ramírez, Alejandro H. García-Ruiz, Katea E. Lira-García

“…Additionally, a Cellular Processing Algorithm (PCELL) is employed to expand the search space and improve solution quality. …”
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Prediabetes detection in unconstrained conditions using wearable sensors by Dimitra Tatli, Vasileios Papapanagiotou, Aris Liakos, Apostolos Tsapas, Anastasios Delopoulos

“…Features are aggregated per individual using bootstrap. Support Vector Machines are used to classify normoglycemic vs. prediabetic individuals. …”
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Integrating Remote Photoplethysmography and Machine Learning on Multimodal Dataset for Noninvasive Heart Rate Monitoring by Rinaldi Anwar Buyung, Alhadi Bustamam, Muhammad Remzy Syah Ramazhan

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Development of agricultural pests detection and identification system based on the technology of wireless transmission by Song Gelian, Han Ruizhen, Zhang Yonghua, He Yong

“…In structure, every single platform includes function modules like image acquisition, image processing, feature extraction and classification, GPS and transmission module. …”
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Research on the Defect Detection Method of Steel-Reinforced Concrete Based on Piezoelectric Technology and Weight Analysis by Yilong Yu, Yulin Dong, Yulong Jiang, Fan Wang, Qianfan Zhou, Panfeng Ba

“…Finally, the analytic hierarchy process (AHP) was introduced to study the weight vectors of different damage metrics on the detection signal, and a linear regression model based on different damage metrics was proposed as the comprehensive defect evaluation index. …”
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Application of computer vision and machine learning in morphological characterization of Adansonia digitata fruits by Franklin X. Dono, Bernard N. Baatuuwie, Felix K. Abagale, Peter Borgen Sørensen

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Dynamic neutrosophic cognitive map with improved cuckoo search algorithm (DNCM-ICSA) and ensemble classifier for rheumatoid arthritis (RA) disease by B. Chithra, R. Nedunchezhian

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COMPARISON OF SPACE IMAGES OF A SURFACE OF EARTH TO A STANDARD OF A DIGITAL DISTRICT MAP by A. A. Zalatoi, D. I. Novikau

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Analysis of the Impact of the Stylometric Characteristics of Different Levels for the Verification of Authors of the Prose by Alla Mikhajlovna Manakhova, Nadezhda Stanislavovna Lagutina

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Lexical associations can characterize clinical documentation trends related to palliative care and metastatic cancer by Hao Yuan Yang, Karthik Raghunathan, Eric Widera, Steven Z. Pantilat, Teva Brender, Timothy A. Heintz, Edie Espejo, John Boscardin, Hunter Mills, Albert Lee, Jacob Berchuck, Julien Cobert

“…We used word2vec to model language numerically as vectors. Relational data between vectors was captured using cosine similarity. …”
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Textual similarity for legal precedents discovery: Assessing the performance of machine learning techniques in an administrative court by Hugo Mentzingen, Nuno António, Fernando Bacao, Marcio Cunha

“…Leveraging the capabilities of natural language processing (NLP) and machine learning (ML), our study delves into the potential of automation in identifying similar cases indicative of precedents. …”
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AE-XGBoost: A Novel Approach for Machine Tool Machining Size Prediction Combining XGBoost, AE and SHAP by Mu Gu, Shuimiao Kang, Zishuo Xu, Lin Lin, Zhihui Zhang

“…The subsequent SHAP analysis reveals the importance and interrelationship of features and provides a reliable decision support system for machine tool processing personnel, helping to improve processing quality and achieve intelligent manufacturing.…”
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Prediction and optimization of hardness in AlSi10Mg alloy produced by laser powder bed fusion using statistical and machine learning approaches by İnayet Burcu Toprak

“…A multidisciplinary approach was adopted to optimize production processes, reduce manufacturing costs, and shorten processing times. …”
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A Temporal Network Based on Characterizing and Extracting Time Series in Copper Smelting for Predicting Matte Grade by Junjia Zhang, Zhuorui Li, Enzhi Wang, Bin Yu, Jiangping Li, Jun Ma

“…Addressing the issues of low prediction accuracy and poor interpretability in traditional matte grade prediction models, which rely on pre-smelting input and assay data for regression, we incorporate process sensors’ data and propose a temporal network based on Time to Vector (Time2Vec) and temporal convolutional network combined with temporal multi-head attention (TCN-TMHA) to tackle the weak temporal characteristics and uncertain periodic information in the copper smelting process. …”
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On the History of the Restoration of a Multi-Party Political System in Kenya by MATVEEVA Natalia Fedorovna

“…The outcome of this struggle brought victory to KANU and largely determined the vector of the future political history of this country. …”
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Advancing Kiwifruit Maturity Assessment: A Comparative Study of Non-Destructive Spectral Techniques and Predictive Models by Michela Palumbo, Bernardo Pace, Antonia Corvino, Francesco Serio, Federico Carotenuto, Alice Cavaliere, Andrea Genangeli, Maria Cefola, Beniamino Gioli

“…Three different regression methods—Partial Least Squares (PLS), Support Vector Regression (SVR), and Gaussian process regression (GPR)—were tested to assess their predictive accuracy. …”
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Dataset and machine learning-based computer-aided tools for modeling working sorption isotherms in dried parchment and green coffee beansMendeley Data by Gentil A. Collazos-Escobar, Andrés F. Bahamón-Monje, Nelson Gutiérrez-Guzmán

“…These models are particularly valuable as digital representations of the coffee storage process and can be used to optimize storage conditions, understand hygroscopic behavior, and ensure moisture-based quality monitoring in parchment and green coffee beans. …”
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Designing ISAR Lab Experiments for EO-SAR ATR by Michael Andrew Saville, Jacob D. Compaleo, Heather L. Judd, Jared Smith, Paul Sotirelis

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