An Intelligent Medical Imaging Approach for Various Blood Structure Classifications by Madallah Alruwaili

“…The performance of the proposed approach is assessed by employing 8 different datasets of blood structures. It is assured that the proposed method has achieved significant results under different blood structure images including COVID-19.…”
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Using the Nonuniform Dynamic Mode Decomposition to Reduce the Storage Required for PDE Simulations by Brenton T. Hall, Ching-Shan Chou, Jen-Ping Chen

“…Partial Differential Equation simulations can produce large amounts of data. These datasets are very slow to transfer, for example, from an off-site supercomputer to a local research facility. …”
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Improving Text Recognition Accuracy for Serbian Legal Documents Using BERT by Miloš Bogdanović, Milena Frtunić Gligorijević, Jelena Kocić, Leonid Stoimenov

“…Producing a new high-quality text corpus is a big challenge due to the required complexity and labor expenses. High-quality datasets, considered a prerequisite for many supervised machine learning algorithms, are often only available in very limited quantities. …”
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Social media network public opinion emotion classification method based on multi-feature fusion and multi-scale hybrid neural network by Yuan Yao, Xi Chen, Peng Zhang

“…Experimental comparisons on two multi-class microblog comment datasets demonstrate that the multi-feature fusion (WOOSD-CNN) word vector model achieves notable improvements in sentiment polarity accuracy and categorization effectiveness. …”
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Meta-Analysis of Pulmonary Transcriptomes from Differently Primed Mice Identifies Molecular Signatures to Differentiate Immune Responses following Bordetella pertussis Challenge by René H. M. Raeven, Jeroen L. A. Pennings, Elly van Riet, Gideon F. A. Kersten, Bernard Metz

“…To that end, three postchallenge transcriptome datasets of previously primed mice were combined and compared to the responses in unprimed control mice. …”
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Open-world barely-supervised learning via augmented pseudo labels by Zhongnian Li, Yanyan Ding, Meng Wei, Xinzheng Xu

“…Our experimental results on multiple benchmark datasets demonstrated the effectiveness of our method.…”
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The Construction of Regulatory Network for Insulin-Mediated Genes by Integrating Methods Based on Transcription Factor Binding Motifs and Gene Expression Variations by Hyeim Jung, Seonggyun Han, Sangsoo Kim

“…In the present study, we used previously published gene expression microarray datasets of human skeletal muscle samples collected from 20 insulin sensitive individuals before and after insulin treatment in order to construct insulin-mediated regulatory network. …”
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Grasping Variance in Word Norms: Individual Differences in Motor Imagery and Semantic Ratings by Emiko J. Muraki, Sydney Born, Penny M. Pexman

“…Word norming datasets have become an important resource for psycholinguistic research, and they are based on the underlying assumption that individual differences are inconsequential to the measurement of semantic dimensions. …”
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RTAPM: A Robust Top-View Absolute Positioning Method with Visual–Inertial Assisted Joint Optimization by Pengfei Tong, Xuerong Yang, Xuanzhi Peng, Longfei Wang

“…Based on two open-source datasets and real-time flight experimental tests, the method proposed in this study has significant advantages in positioning accuracy and system robustness over existing typical UAV absolute positioning methods, and it can temporarily replace GNSS for application in challenging environments such as disaster aid or forest rescue.…”
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Multi-view Clustering: A Survey by Yan Yang, Hao Wang

“…In addition, it lists some publically available multi-view datasets. Overall, this paper serves as an introductory text and survey for multi-view clustering.…”
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Sentiment Analysis from Face Expressions Based on Image Processing Using Deep Learning Methods by Orhan Emre Aksoy, Selda Güney

“…With the application written in Python programming language, classical machine learning methods such as k-Nearest Neighborhood and Support Vector Machines and deep learning methods such as AlexNet, ResNet, DenseNet, Inception architectures were applied to FER2013, JAFFE and CK+ datasets. In this study, while comparing classical machine learning methods and deep learning architectures, real-time and non-real-time applications were also compared with two different applications. …”
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An intrusion detection model based on Convolutional Kolmogorov-Arnold Networks by Zhen Wang, Anazida Zainal, Maheyzah Md Siraj, Fuad A. Ghaleb, Xue Hao, Shaoyong Han

“…The model proposed in this paper is constructed by incorporating attention mechanisms into CKAN’s computational logic. The datasets CICIoT2023 and CICIoMT2024 were used for model training and validation. …”
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Spatial conservation planning: Proposing clustering methods to improve connectivity protection by Nikolaos Nagkoulis, Maria Papazekou, Stelios Katsanevakis, Antonios Mazaris

“…Overall, by illustrating the clustering properties of the connectivity datasets, the proposed metrics can introduce new approaches to improve the integration of ecological connectivity in conservation prioritization.…”
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Rain removal method for single image of dual-branch joint network based on sparse transformer by Fangfang Qin, Zongpu Jia, Xiaoyan Pang, Shan Zhao

“…Experimental validation on synthetic and real datasets demonstrates that rain removal images exhibit richer detail information, significantly improving the overall visual effect.…”
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CLIMATIC PATTERN ANALYSIS OF RAINFALL AND DRY SPELLS DURING THE AGRICULTURAL SEASON IN MALAWI by Medrina Linda Mloza Banda, Wim Cornelis, Henry R. Mloza Banda

“…Utilizing observed daily station rainfall datasets from the rainy season (November to April) spanning the years 1961 to 2007, a set of indices including percentile, absolute, threshold, and duration measures, was derived for locations at low (Balaka), medium (Bunda, Chitedze, KIA), and high (Dedza) altitudes in Malawi. …”
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Enhancing Stock Portfolio Selection with Trapezoidal Bipolar Fuzzy VIKOR Technique with Boruta-GA Hybrid Optimization Model: A Multicriteria Decision-Making Approach by Sunil Kumar Sharma

“…The Boruta-GA approach combines the advantages of the Genetic Algorithm (GA) and Boruta Optimization Algorithm (BOA) methods, implementing the comprehensive feature selection capability of Boruta to detect all relevant features and harnessing the strength of GA to bring about improvement within a wide range of datasets. The result shows that this novel approach is effective and can help to investors to take decisions in the unpredictable financial market. …”
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Bearing Fault Diagnosis Based on Domain Adaptation Using Transferable Features under Different Working Conditions by Zhe Tong, Wei Li, Bo Zhang, Meng Zhang

“…In this paper, a novel bearing fault diagnosis under different working conditions method is proposed based on domain adaptation using transferable features(DATF). The datasets of normal bearing and faulty bearings are obtained through the fast Fourier transformation (FFT) of raw vibration signals under different motor speeds and load conditions. …”
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A paradoxical population structure of var DBLα types in Africa. by Mun Hua Tan, Kathryn E Tiedje, Qian Feng, Qi Zhan, Mercedes Pascual, Heejung Shim, Yao-Ban Chan, Karen P Day

“…By applying a novel ups classification algorithm (cUps) to publicly-available DBLα sequence datasets, we categorised DBLα according to association with the three ups groups, thereby avoiding the need to sequence complete genes. …”
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Hybrid deep learning approach for brain tumor classification using EfficientNetB0 and novel quantum genetic algorithm by Kerem Gencer, Gülcan Gencer

“…Deep learning models can achieve high accuracy when trained on datasets in diagnosis and classification. This study examined deep learning-based approaches for automatic multi-class classification of brain tumors, and a new approach combining deep learning and quantum genetic algorithms (QGA) was proposed. …”
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Label iteration-based clustering ensemble algorithm by HE Yulin, YANG Jin, HUANG Zhexue, YIN Jianfei

“…The experimental results showed that the normalized mutual information, adjusted Rand index, Fowlkes-Mallows index and purity of LICE algorithm increased by 17.23%, 16.75%, 31.29%, and 12.37% on average at the 5th iteration compared to the initial iteration and these four indexes increased by 11.76%, 16.50%, 9.36%, and 14.20% on average for the representative datasets in comparison with seven state-of-the-art clustering ensemble algorithms and thus demonstrate that LICE algorithm is an efficient and reasonable clustering ensemble algorithm with the potential to handle large-scale data clustering problems.…”
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