Process standardization and characterization of Mies: Ethiopian honey wine by Weleba Muesho Gebremichael, Kiros Hagos Abay, Desta Berhe Sbhatu, Goitom Gebreyohannes Berhe, Gebreselema Gebreyohannes

“…Mies is a delicious honey wine traditionally processed in Ethiopia and Eritrea. This study aimed to investigate the standardization and characterization of high-quality Mies. …”
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Short-Form Psychoeducation Videos: Process Development Study by Louise Turtle, Helen Alexandra Wesson, Simon Williamson, Nathan Hodson

“…A major strength of this process was the large number of people from different professional backgrounds involved; this diversity boosted both the validity of the content and the creativeness of the videos. …”
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Signal Processing-Free Intelligent Model for Power Quality Disturbances Identification by Mohammed F. Al-Mashdali, Asif Islam, Abdulbasit Hassan, Md Shafiullah, Mujahed Al-Dhaifallah, Khalid Al Fuwail

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Novel Automatic Classification Method for Geological Structures in Carbonate Formations Based on Electrical Imaging Logging by FU Yafeng, HUANG Ke, ZHU Hanbin, WANG Hui, ZHANG Xu, ZHAO Jie, XIAO Ni

“…In the processing of electrical imaging logging data for carbonate formations, it is challenging to distinguish mudstone laminae, natural fractures, induced fractures, and vugs due to their similar resistivities and overlapping occurrences. …”
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A two-stage deep learning-based hybrid model for daily wind speed forecasting by Shahab S. Band, Rasoul Ameri, Sultan Noman Qasem, Saeid Mehdizadeh, Brij B. Gupta, Hao-Ting Pai, Danyal Shahmirzadi, Ely Salwana, Amir Mosavi

“…The latest models rely on artificial intelligence (AI) optimizations which constructs tests on a range of novel hybrid models to examine the reliability. Gradient Boosting (GB), Random Forest (RF), and Long Short-Term Memory (LSTM) are used in new combinations for data pre-processing. …”
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Fault Diagnosis of Wind Turbine Blades Based on One-Dimensional Convolutional Neural Network-Bidirectional Long Short-Term Memory-Adaptive Boosting and Multi-Source Data Fusion by Kangqiao Ma, Yongqian Wang, Yu Yang

“…The multi-source sensor features are then fed into the BiLSTM layer for further processing of the time-series characteristics. The processed data are classified through a fully connected layer. …”
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Early Breast Cancer Prediction Using Thermal Images and Hybrid Feature Extraction-Based System by Doaa Youssef, Hanan Atef, Shaimaa Gamal, Jala El-Azab, Tawfik Ismail

“…Then, an image fusion process is provided to construct one composite image retaining all the map’s information from which a highly valuable feature vector is extracted using the histogram of oriented gradients (HOG). …”
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Biomass Processing Network Optimisation Using P-graph with Pareto Screening by Wendy P. Q. Ng, Elida A. R. Ngu, Nur Faakhirah binti Haji Ahmadbi, Hon Loong Lam

“…Convincing economic and environmental performances of biomass waste-to-wealth processing networks are needed to motivate investors and boost the implementation of biomass projects. …”
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Recent progress in hybrid diamond photonics for quantum information processing and sensing by Ryota Katsumi, Kosuke Takada, Fedor Jelezko, Takashi Yatsui

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Dual Control Strategy for Non-Minimum Phase Behavior Mitigation in DC-DC Boost Converters Using Finite Control Set Model Predictive Control and Proportional–Integral Controllers by Alejandra Marmol, Elyas Zamiri, Marziye Purraji, Duberney Murillo, Jairo Tuñón Díaz, Aitor Vazquez, Angel de Castro

“…This paper introduces a system using a short-horizon Finite Control Set MPC (FCS-MPC) strategy to specifically address the challenge of non-minimum phase behavior in boost converters. The non-minimum phase issue, which complicates the control process by introducing an initial inverse response, is effectively mitigated by the proposed method. …”
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Synthesis and Evaluation of 3D Nitrogen Doped Reduced Graphene Oxide (3D N@rGO) Macrostructure for Boosted Solar Driven Interfacial Desalination of Saline Water by Fisseha A Bezza, Samuel A. Iwarere, Shepherd M. Tichapondwa, Hendrik G. Brink, Michael O. Daramola, Evans MN Chirwa

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Optimising fatigue, abdominal pain and faecal incontinence in people with inflammatory bowel disease (IBD-BOOST Optimise): feasibility study of a checklist and algorithm for initia... by Thomas Hamborg, John McLaughlin, Ailsa Hart, Christine Norton, Sonia Bouri, Laura Miller, Jean-Frédéric LeBlanc, Asma Fikree, Imogen Stagg, Fionn Cléirigh Büttner

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MODELING OF BUSINESS PROCESSES FOR MANAGING INTEGRATIVE DIGITAL DEVELOPMENT OF ENTERPRISES by Оlena V. Vynogradova, Svitlana V. Lehominova, Aliona Yu. Goloborodko, Tetiana I. Nosova

“…The fundamental methods for modeling business process flows using mathematical and analytical tools, specifically a system of differential equations with defined initial conditions, have been substantiated, enabling the integral assessment of enterprise business process modeling. …”
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An Improved DoH Traffic Classification Method for XGboost by LI Bo, WEN Xueyan, XU Kesheng, ZHAO Yonghui

“… Encrypted traffic has become the main traffic in the Internet, and its classification has always been one of the research hotspots.Aiming at the problems of accurate identification of DoH(DNS-over-HTTPS) traffic in the current network, slow processing speed and low detection efficiency, a dimension reduction method based on truncated singular value decomposition (TSVD) is proposed.Improved limit gradient boosting tree (IXGboost) with Bayesian optimization method for DoH Flow classification.This method classifies encrypted traffic into non-DOH traffic, benign DoH traffic and malicious DoH traffic by exposing data sets over the network.Experimental results show that the classification accuracy of the proposed method is more than 99%, and the processing time of each data is only 0.3ms, which proves that the proposed method has high accuracy and strong real-time performance, improves the performance of intrusion detection, and can effectively achieve accurate classification of DoH traffic.…”
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Image Processing Method Based on Chaotic Encryption and Wavelet Transform for Planar Design by Yiying Liu, Young Chun Ko

“…The plaintext image is decomposed in odd-even sequence using the boosting algorithm to get the sequence with an even index and the sequence with an odd index; then, the diffusion algorithm is applied to the two sequences by the prediction and update algorithm, and this process is repeated many times to get the two ciphertext sequences after scrambling, merging these two sequences, and matrixing them to get the ciphertext image. …”
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Process integration technique for targeting carbon credit price subsidy by Maria Victoria Migo-Sumagang, Kathleen B. Aviso, Raymond R. Tan, Xiaoping Jia, Zhiwei Li, Dominic C.Y. Foo

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Intelligent Data Processing Methods for Studying the Influence of the Environment on the Morbidity of the Population in Moscow by T. V. Zolotova, A. S. Marunko

“…Based on collected and processed open data on environmental indexes and population morbidity in various districts of Moscow, various types of analysis were carried out to identify the relationship between these data. …”
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Effect of Processing on Nutrient Composition and Antioxidant Capacity of Loquat Jam and Concentrated Syrup by Sahar, A.M. Sawy, Doaa, F. Hassan, Esraa, A.M. Mousa

“…Loquat fruit is nutritious food rich in vitamins, carotenoids, and polyphenolic compounds, offering a range of health benefits, such as antioxidant, anti-inflammatory, and immune-boosting properties. This study examined the effects of processing loquat fruit into syrup and jam on their functionality. …”
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ScTCN-LightGBM: a hybrid learning method via transposed dimensionality-reduction convolution for loading measurement of industrial material by Zihua Chen, Runmei Zhang, Zhong Chen, Yu Zheng, Shunxiang Zhang

“…Finally, we utilize the light-gradient boosting machine to measure loading capacity. Experimental results show that the ScTCN-LightGBM outperforms existing measurement models with high metrics, especially the stability coefficient R2 is 0.923. …”
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Correlation of rivaroxaban solubility in mixed solvents for optimization of solubility using machine learning analysis and validation by Muteb Alanazi, Jowaher Alanazi, Tareq Nafea Alharby, Bader Huwaimel

“…Three models—AdaBoost Gaussian process regression (ADAGPR), AdaBoost multilayer perceptron (ADAMLP), and AdaBoost LASSO regression (ADALASSO)—were evaluated using $$\:{R}^{2}$$ , RMSE, and MAPE metrics. …”
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