Data-driven modeling of open circuit voltage hysteresis for LiFePO4 batteries with conditional generative adversarial network by Lisen Yan, Jun Peng, Zeyu Zhu, Heng Li, Zhiwu Huang, Dirk Uwe Sauer, Weihan Li

“…The generator and discriminator are designed based on LSTM networks to capture the dependency of hysteresis on historical SOC and conditional information. …”
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Object-Level Contrastive-Learning-Based Multi-Branch Network for Building Change Detection from Bi-Temporal Remote Sensing Images by Shiming Li, Fengtao Yan, Cheng Liao, Qingfeng Hu, Kaifeng Ma, Wei Wang, Hui Zhang

“…Finally, an attention-based discriminative feature generation and fusion block is designed to enhance the representation of multi-scale change features. …”
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Scoring of swine lung images: a comparison between a computer vision system and human evaluators by Robert Valeris-Chacin, Beatriz Garcia-Morante, Marina Sibila, Albert Canturri, Isaac Ballarà Rodriguez, Ignacio Bernal Orozco, Ramon Jordà Casadevall, Pedro Muñoz, Maria Pieters

“…The CVS showed moderate accuracy (62–71%) in discriminating between non-lesioned and lesioned lung lobes in all but the diaphragmatic lobes. …”
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Olfaction-based learned preference assessment without the use of motivational fear or motivational weight loss by Sara E. Moss, Ekaterina S. McCurdy, Natalya N. Thomas, Danielle Gulick, Angela M. Poff, Dominic P. D'Agostino

“…We assessed whether this protocol discriminated learning deficit induced by lipopolysaccharide (LPS) administration.ConclusionWe conclude that this protocol is a viable tool for assessing learning abilities in preclinical models with auditory or visual deficits, motor impairments, or an inability to tolerate motivational weight loss.…”
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Classification of Strawberry Maturity Stages and Varieties Using Neural Networks Based on Volatile Organic Compounds by Jing Huang, Xuenan Zhang, Hang Yang, Zhenbiao Li, Zhengfang Xue, Qingqing Wang, Xinyuan Zhang, Shenghua Ding, Zisheng Luo, Yanqun Xu

“…Five ML models were developed, including partial least squares discriminant analysis (PLS-DA), decision trees, support vector machines (SVM), Xgboost and neural networks (NN). …”
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A Novel Semi-Supervised Learning Method Based on Fast Search and Density Peaks by Fei Gao, Teng Huang, Jinping Sun, Amir Hussain, Erfu Yang, Huiyu Zhou

“…When the labeled samples satisfy a certain requirement, S2DP uses fast search and a density peak clustering method to detect reliable unlabeled samples based on the weighted kernel Fisher discriminant analysis (WKFDA). Then, a labeling method based on clustering information (LCI) is designed to label the unlabeled samples. …”
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Serum levels of the Parkinson's disease-linked protein Parkin are specifically elevated in COVID-19 by Nadezhda G. Gumanova, Natalya L. Bogdanova, Alexander Yu. Gorshkov

“…This analysis identified Parkin as a top protein discriminating between the SARS-positive and negative status. …”
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Are lateralized and bold fish optimistic or pessimistic? by F. Berlinghieri, G. Rizzuto, L. Kruizinga, B. Riedstra, TGG. Groothuis, C. Brown

“…We used the judgement bias test with the go/no-go procedure where fish were first trained to discriminate between a black and white card and, after reaching a minimum learning criterion, tested their response to an ambiguous card (grey). …”
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Human Islet Amyloid Polypeptide Fibril Binding to Catalase: A Transmission Electron Microscopy and Microplate Study by Nathaniel G. N. Milton, J. Robin Harris

“…This suggests that catalase may be able to discriminate between different structural forms of IAPP fibrils. …”
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Development and validation of the gift reciprocation anxiety scale (GRAS) for youths and adults in intimate relationships by Mohd. Ashik Shahrier, Shakira Khatun

“…In addition, the item response theory (IRT) analyses confirmed that the items of the GRAS had high discriminative power, satisfactory threshold parameters, and covered a wide range of the latent trait. …”
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ZleepNet: A Deep Convolutional Neural Network Model for Predicting Sleep Apnea Using SpO2 Signal by Hnin Thiri Chaw, Thossaporn Kamolphiwong, Sinchai Kamolphiwong, Krongthong Tawaranurak, Rattachai Wongtanawijit

“…We conducted experiments to evaluate the performance of the proposed CNN using real patient data and compared them with traditional machine learning methods such as least discriminant analysis (LDA) and support vector machine (SVM), baggy representation tree, and artificial neural network (ANN) on publicly available sleep datasets using the same parameter setting. …”
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Attentive Self-supervised Contrastive Learning (ASCL) for plant disease classification by Getinet Yilma, Mesfin Dagne, Mohammed Kemal Ahmed, Ravindra Babu Bellam

“…However, traditional deep learning backbones often produce representations that are not sufficiently discriminative or interpretable for detailed plant disease analysis. …”
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Development and Validation of a Nomogram for Predicting Mortality in Patients with Atrial Fibrillation and Acute Coronary Syndrome Who Underwent Percutaneous Coronary Intervention... by Can Hua, Haitao Tian, Yubin Wang, Jianyong Zheng, Pengfei Liu, Boyang Zhang, Nannan Wang, Haihong Tang, Feng Wang, Xiufeng Xie, Haifeng Yuan, Tianchang Li

“…The predictive accuracy and discriminative ability of the nomogram were determined by a concordance index (C-index) and calibration curve and were compared using current risk scores such as GRACE, CRUSADE, CHA2DS2-VASc, and HAS-BLED. …”
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Salivary Lactate Dehydrogenase in Relationship to the Severity of Hypoxic-Ischemic Encephalopathy among Newborn Infants by Hend Elmoursi, Mohamed Abdalla, Bader Eldin Mesbah, Abdelmoneim Khashana

“…Moreover, salivary LDH showed a good discriminative ability where the AUC was 0.966 regarding salivary LDH (95% CI: 0.917–1.0) (p<0.001). …”
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Learning deep forest for face anti-spoofing: An alternative to the neural network against adversarial attacks by Rizhao Cai, Liepiao Zhang, Changsheng Chen, Yongjian Hu, Alex Kot

“…Unlike GSM, which scans raw pixels and lacks discriminative power, our LBP-based scheme is specifically designed to capture texture features relevant to spoofing detection. …”
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Typology of Tomato Cropping Systems and Determinants of Preharvest Losses in Western Cameroon by Roland Wilfried Titti, Anne Stéphanie Etoga, Pierre Germain Ntsoli, Georges Marius Kossi Etame, Asafor Henry Chotangui, Réné Mbonomo Bikomo, Aoudou Yaouba

“…Factor analysis for mixed data (FAMD) and canonical discriminant analysis, combined with multinomial logistic regression, were used to analyze the collected data. …”
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Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications by Francesco Benso, Carlo Chiorri, Eleonora Ardu, Paola Venuti, Angela Pasqualotto, Angela Pasqualotto

“…We address the blurred boundary between domain-specific and domain-general systems, proposing modular versus non-modular states—indexed by automaticity and mandatoriness—as key discriminators. This systematization, supported by empirical literature and our own research, provides a more stable framework for understanding modular systems, avoiding interpretive confusion across varying levels of complexity. …”
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Estimating the Risk of Maternal Death at Admission: A Predictive Model from a 5-Year Case Reference Study in Northern Uganda by Gasthony Alobo, Cristina Reverzani, Laura Sarno, Barbara Giordani, Luigi Greco

“…A cumulative risk score for each woman based on the unstandardised canonical coefficients was obtained by the discriminant equation. Results. The average maternal mortality ratio was 328 per 100,000 live births. …”
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Psychological Distress and Online Academic Difficulties: Development and Validation of Scale to Measure Students’ Mental Health Problems in Online Learning by Mihai Curelaru, Versavia Curelaru

“…., Average Variance Extracted) and discriminant validity (e.g., the heterotrait–monotrait ratio of correlations) of the scale. …”
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IncSAR: A Dual Fusion Incremental Learning Framework for SAR Target Recognition by George Karantaidis, Athanasios Pantsios, Ioannis Kompatsiaris, Symeon Papadopoulos

“…Moreover, a random projection layer improves the linear separability of features, and a variant of Linear Discriminant Analysis (LDA) decorrelates extracted class prototypes for better generalization. …”
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