Hybrid machine learning and regression framework for automated phase classification and quantification in SEM images of commercial steels by Pavan Hiremath, Krishnamurthy D. Ambiger, Shilpa Suresh, Ranjan Kumar Ghadai, Ramakrishna Vikas Sadanand, G. Divya Deepak

“…Images were segmented using the SLIC algorithm into 64 × 64 patches, from which six Gray Level Co-occurrence Matrix (GLCM) features were extracted: contrast, correlation, energy, homogeneity, dissimilarity, and angular second moment (ASM). …”
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Microplastic in the gastrointestinal tract of Bombay duck (Harpadon nehereus) in the Patenga Beach of the Bay of Bengal, Bangladesh: occurrence, abundance, and physicochemical feat... by Sabah tuz Zohora, Shahida Arfine Shimul, Saifuddin Rana, Antar Sarkar, Sui Naing Aye Marma Milky, Khing Khing U Marma, Kaji Mohammad Sirajum Monir, Farhan Azim, Tapos Kumar Chakraborty, Sk. Ahmad Al Nahid

“…The purpose of this study was to determine the presence, occurrence and physicochemical features of MPs in the gastrointestinal tract of Bombay duck (H. nehereus) from the Patenga Sea Beach of the Bay of Bengal, Bangladesh. …”
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Sweet pepper foliar diseases quantification and identification using an image analysis tool by Vijayanandh Rajamanickam, Adesh Ramsubhag, Jayaraj Jayaraman

“…The steps involved were color space conversions, detection of leaf area by Otsu’s method, and thresholding for foliar diseased area detection and quantification. Gray-Level Co-occurrence Matrix (GLCM) extracted the texture features from the diseased area of leaves. …”
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A Differential Biomarker Based on Recurrence Quantification Analysis of EEG Signal and Genetic Algorithm for Epilepsy Diagnosis by Vanithamani Palanisamy, A Ranichitra, Radhamani Ellapparaj

“…On the other hand, the features of divergence, trapping time and longest vertical line without occurrence of 100% accuracy yielded the poorest results. …”
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Quantifying Microplastic Leaching from Paper Cups: A Specklegram Image Analytical Approach by Mankuzhy Anilkumar Rithwiq, Puthuparambil Anju Abraham, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman

“…The study indicates contrast as the potential sensitive specklegram feature for microplastics detection and quantification.…”
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University genres and multisemiotic features: accessing specialized knowledge through disciplinarity by Giovanni Parodi

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Bag of Feature-Based Ensemble Subspace KNN Classifier in Muscle Ultrasound Diagnosis of Diabetic Peripheral Neuropathy by Kadhim K. Al-Barazanchi, Ali H. Al-Timemy, Zahid M. Kadhim

“…Muscle ultrasound quantification is a valuable complementary diagnostic tool for diabetic peripheral neuropathy (DPN), enhancing physicians’ diagnostic capabilities. …”
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Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018–2022) by Zhihan Liu, Hebin Li, Ziyan Zhang, Lu Ping, Wenxin Gu, Yuan Yao

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Feature Clustering Analysis Using Reference Model towards Rolling Bearing Performance Degradation Assessment by Xiaoxi Ding, Liming Wang, Wenbin Huang, Qingbo He, Yimin Shao

“…Finally, a clustering quantification factor, named as feature clustering indicator (FCI), is calculated to assess distribution evolution and migration of the monitor status as compared to the consistent healthy status. …”
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Decoding Pain Dynamics: EEG Insights into Neural Responses and Classification via RQA Analysis by Mahsa Tavasoli, Zahra Einalou, Reza Akhondzadeh

“…For this purpose, at the first step phasic pain is produced using coldness, then dynamical features via EEG are analyzed via Recurrence Quantification Analysis (RQA) method and finally Rough neural network classifier has been used for achieving accuracy to detect and categorize pain and non-pain states. …”
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Enhanced safety assessment on tunnel excavation via refined rock mass parameter identification by Hongwei Huang, Tongjun Yang, Jiayao Chen, Zhongkai Huang, Chen Wu, Jianhong Man

“…This study employs computer vision and deep learning techniques to execute the refined extraction and quantification of rock mass information in tunnel faces. …”
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A Hybrid Machine Learning Approach for Detecting and Assessing <i>Zyginidia pullula</i> Damage in Maize Leaves by Havva Esra Bakbak, Caner Balım, Aydogan Savran

“…Specifically, hand-crafted feature extraction methods, including Gabor filters, Gray Level Co-occurrence Matrix, and Hue-Saturation-Value color space, are combined with CNN-based models such as ResNet-50, DenseNet-201, and EfficientNet-B2. …”
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Expressiveness and frequency differences of hip joint tissues pathomorphological changes in diseases complicated by femoroacetabular impingement syndrome by V. V. Grigorovsky, V. V. Filipchuk, M. S. Kabatsiy

“…To establish hip joint tissues pathomorphological changes, to which FAI syndrome leads, and on the basis of graded expressiveness quantification of pathological changes to define differences of their occurrence frequency in groups of patients in some diseases with affected hip joint. …”
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Reliability of radiomic analysis on multiparametric MRI for patients affected by autosomal dominant polycystic kidney disease by Francesca Lussana, Ettore Lanzarone, Giulia Villa, Alfonso Mastropietro, Anna Caroli, Elisa Scalco

“…Additionally, lower-order features, including those computed from histograms and co-occurrence matrices, demonstrate higher reproducibility than other texture features.…”
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Alpine Catchments’ Hazard Related to Subaerial Sediment Gravity Flows Estimated on Dominant Lithology and Outcropping Bedrock Percentage by Davide Tiranti

“…The study used 78 well-documented catchments of Susa Valley (Western Italian Alps), having 614 historical flow events reported, that present a great variability in geomorphological and geological features. As the main result, three catchment groups were recognized based on the dominant catchment bedrock’s lithology characteristics that influence the SGFs’ rheology, sedimentological and depositional features, triggering rainfall values, seasonality, occurrence frequency and alluvial fan architecture. …”
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Predictive Models Using Machine Learning to Identify Fetal Growth Restriction in Patients With Preeclampsia: Development and Evaluation Study by Qing Hua, Fengchun Yang, Yadan Zhou, Fenglian Shi, Xiaoyan You, Jing Guo, Li Li

“…ResultsThe RF model performed best in discriminative ability among the 7 ML models. After reducing features according to importance rank, an explainable final RF model was established with 9 features, including urinary protein quantification, gestational week of delivery, umbilical artery systolic-to-diastolic ratio, amniotic fluid index, triglyceride, D-dimer, weight, height, and maximum systolic pressure. …”
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Geological Evaluation of In-Situ Pyrolysis Development of Oil-Rich Coal in Tiaohu Mining Area, Santanghu Basin, Xinjiang, China by Guangxiu Jing, Xiangquan Gao, Shuo Feng, Xin Li, Wenfeng Wang, Tianyin Zhang, Chenchen Li

“…An analytic hierarchy process incorporating index classification and quantification was employed in combination with the geological features of the Tiaohu mining area to establish a feasibility evaluation index system suitable for in-situ development in the study region. …”
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Correlation Analysis of External Environment Risk Factors for High-Speed Railway Derailment Based on Unstructured Data by Haixing Wang, Yuanlanduo Tian, Hong Yin

“…This paper establishes the matching model of high-speed railway derailment-based external environment risk factors and applies it to the occurrence of unsafe events. This model could be utilized to analyze and excavate the link between external environment risk factors and the occurrence of unsafe events and carry out the automatic extraction of characteristic information such as risk possibility and consequence severity; hence, it has potential for identifying, with enhanced accuracy, high-risk factors that may lead to high-speed railway derailment. …”
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Predicting stroke with machine learning techniques in a sub-Saharan African population by Benjamin Segun Aribisala, Deirdre Edward, Godwin Ogbole, Onoja M. Akpa, Segun Ayilara, Fred Sarfo, Olusola Olabanjo, Adekunle Fakunle, Babafemi Oluropo Macaulay, Joseph Yaria, Joshua Akinyemi, Albert Akpalu, Kolawole Wahab, Reginald Obiako, Morenikeji Komolafe, Lukman Owolabi, Godwin Osaigbovo, Akinkunmi Paul Okekunle, Arti Singh, Philip Ibinaye, Osahon Osawata, Adeniyi Sunday, Ijezie Chukwuonye, Carolyn Jenkins, Hemant K. Tiwari, Okechukwu Ogah, Ruth Y. Laryea, Daniel T. Lackland, Oyedunni Arulogun, Omotolani Ajala, Rufus Akinyemi, Bruce Ovbiagele, Steffen Sammet, Mayowa Owolabi

“…Results: Our results showed that the 16 features-based classification (maximum AUC of 82.32%) had a slightly better performance than the 11 feature-based (maximum AUC 81.17%) algorithm. …”
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Quantifying the energy imbalance in hydrogen energy storage-assisted power systems under heat waves by Wenqian Yin, Kun Zhuang, Pei Kong, Pengcheng Fan, Jilei Ye, Yuping Wu, Xun Dou

“…The increasing occurrence frequency of extreme temperature events, e.g., heat and cold waves, causes prolonged periods of low renewable production and increased load demand, threatening the power system energy balance. …”
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