A hybrid Framework for plant leaf disease detection and classification using convolutional neural networks and vision transformer by Sherihan Aboelenin, Foriaa Ahmed Elbasheer, Mohamed Meselhy Eltoukhy, Walaa M. El-Hady, Khalid M. Hosny

“…The performance proposed model is evaluated using two publicly available datasets (Apple and Corn). Each dataset consists of four classes. …”
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Transforming Alzheimer’s Disease Diagnosis: Implementing Vision Transformer (ViT) for MRI Images Classification by Dian Kurniasari, Muhammad Dwi Pratama, Akmal Junaidi, Ahmad Faisol

“…This study explores the application of the Vision Transformer (ViT) model for classifying MRI images of Alzheimer’s patients, focusing on enhancing accuracy and reliability through data augmentation during pre-processing. A dataset of 8,000 MRI images, categorised into four groups—non-demented, very mild demented, mild demented, and moderate demented—was used to evaluate the ViT model. …”
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BiAF: research on dynamic goat herd detection and tracking based on machine vision by Yun Hou, Mingjuan Han, Wei Fan, Xinyu Jia, Zhuo Gong, Ding Han

“…The BiAF-YOLOv7 algorithm achieves precision, recall, F1 score, and mAP values of 94.5, 96.7, 94.8, and 96.0%, respectively, on the goat herd dataset. Combined with DeepSORT, our system successfully tracks goat herds, demonstrating the effectiveness of the BiAF-YOLOv7 algorithm as a tool for livestock grazing monitoring. …”
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A neural network design for black-box identification of converter impedance models in arbitrary operating conditions by CHEN Bing, ZHAO Chongbin, JIANG Qirong, WANG Xu, WANG Fangming

“…In the model training stage, taking into account the latent features of the converter impedance model, a neural network with the same number as the disturbance frequency was designed, and the Levenberg-Marquardt algorithm with Bayesian regularization integrated is used to enhance the generalization ability of the network trained with a small dataset. In the model verification phase, the network is fed with set operating conditions, achieving highly accurate identification of stable operating conditions and offline prediction.…”
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A Study of Serum Adiponectin Levels in Patients with Polycystic Ovarian Syndrome and its Correlation with Various Cardiometabolic Risk Markers by G. Surendra Prasad, Uma Kaimal Saikia, Ashok Krishna Bhuyan, Abhamoni Baro

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A method for mining over-limit patterns of low voltage in users based on hierarchical affinity propagation clustering by SHEN Shuhao, ZHONG Qing, XU Zhong, WANG Gang, LI Haifeng, WANG Longjun

“…Finally, the proposed method is applied to a real dataset, effectively mining four over-limit patterns of low voltage. …”
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Annotation-free deep learning for predicting gene mutations from whole slide images of acute myeloid leukemia by Bo-Han Wei, Xavier Cheng-Hong Tsai, Kuo-Jui Sun, Min-Yen Lo, Sheng-Yu Hung, Wen-Chien Chou, Hwei-Fang Tien, Hsin-An Hou, Chien-Yu Chen

“…Our model predicts NPM1 mutations and FLT3-ITD without requiring patch-level or cell-level annotations. Using a dataset of 572 WSIs, the largest database with both WSI and genetic mutation information, our model achieved an AUC of 0.90 ± 0.08 for NPM1 and 0.80 ± 0.10 for FLT3-ITD in the testing cohort. …”
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Body image of men and women with congenital heart disease over a 15 years observational period by Siegfried Geyer, Claudia Dellas, Elmar Brähler, Johannes Beller

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Mathematical methodology for defining a frequent attender within emergency departments by Elizabeth Williams, Elizabeth Williams, Syaribah N. Brice, Syaribah N. Brice, Dave Price

“…Recursive clustering on the smallest time interval cluster created a new, smaller cluster and formal FA definition.ResultsApplied to a case study dataset of approximately 336,000 ED attendances, this framework can consistently and effectively identify FAs across EDs. …”
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Comparative Analysis of RESTful, GraphQL, and gRPC APIs: Perfomance Insight from Load and Stress Testing by Steven Chandra, Ahmad Farisi

“…The experiment utilizes a dedicated server and client hardware to simulate real-world conditions, with parameters such as CPU usage, memory usage, response time, load time, latency, success rate, and failure rate evaluated using a dataset comprising 1,000 rows of student-related records. …”
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Experimental data suggest between population reversal in the condition dependence of two sexually selected traits by Gergely Hegyi, Miklós Laczi, Gyula Szabó, Dóra Kötél, Fanni Sarkadi, János Török

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A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning. by Fayaz Hassan, Zafi Sherhan Syed, Aftab Ahmed Memon, Saad Said Alqahtany, Nadeem Ahmed, Mana Saleh Al Reshan, Yousef Asiri, Asadullah Shaikh

“…The experimental results using CICIDS2017 dataset demonstrate that proposed hybrid model performs well not only in terms of classification performance but also yields trained models that have a low parameter count and model size. …”
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The corpus callosum in people with congenital adrenal hyperplasia (CAH) by Eileen Luders, Debra Spencer, Caitlin Dale, Ieuan A. Hughes, Ajay Thankamony, Umasuthan Srirangalingam, Helena Gleeson, Helen Simpson, Melissa Hines, Florian Kurth

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Discovering Object Stories: Linking Unstructured Museum Data Through Semantic Annotation by Sarah Middle, Maria Aristeidou, Elton Barker, Daniel Pett, Sarah Alcock

“…The study focuses on a sample dataset from National Museums Scotland, which includes metadata about navigational instruments from the 19th and early 20th centuries. …”
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Experiences of gender-based violence among women in sub-Saharan Africa: identifying evidence for intervention and public health priorities by Lucky Norah Katende-Kyenda, Judith I. Ani

“…This paper explored GBV among women in 25 sub-Saharan African (SSA) countries to identify and present key intervention priority areas for addressing GBV in these settings.MethodsThe study involved a cross-sectional analysis of a nationally representative dataset from the Demographic and Health Survey of 25 SSA African countries. …”
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Properties of the new N $$ \mathcal{N} $$ = 1 AdS4 vacuum of maximal supergravity by Nikolay Bobev, Thomas Fischbacher, Krzysztof Pilch

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Rethinking the Key Factors for the Generalization of Remote Sensing Stereo Matching Networks by Liting Jiang, Feng Wang, Wenyi Zhang, Peifeng Li, Hongjian You, Yuming Xiang

“…To improve the generalization ability of stereo matching networks on cross-domain data from different optical sensors and scenarios, in this article, we are dedicated to studying the key training factors from three perspectives. 1) When selecting a training dataset, prioritize data with similar regional target distribution as the test set, rather than relying on data from the same sensor. 2) Regarding the training modes, unsupervised methods generalize better than supervised methods. 3) We devised an unsupervised early stop strategy to help preserve the best model based on the pretrained weights. …”
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A study of lipid profile peculiarities and atherogenic index of plasma in patients younger than fifty years of age with newly diagnosed rheumatoid arthritis by Varsha R. Bhatt, Kavita K. Krishna, Vishal Asrani, Rajat Chauhan

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The Conscious Side of ‘Subliminal’ Linguistic Priming: A Systematic Review With Meta-Analysis and Reliability Analysis of Visibility Measures by David Hernández-Gutiérrez, Miguel A. Sorrel, David R. Shanks, Miguel A. Vadillo

“…Moreover, we conducted reliability analyses on a dataset from Berkovitch and Dehaene (2019), finding that low reliability in both syntactic priming and visibility tasks may better explain the absence of a significant correlation. …”
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Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation by Quentin Malé, Corentin J. Lapeyre, Nicolas Noiray

“…For these interpolation cases, the model approximates burning rates with low error even though the cases were not included in the training dataset. This a priori study shows that the proposed data-driven machine learning framework is able to address the challenge of modeling lean premixed $ {\mathrm{H}}_2 $ -air burning rates. …”
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