Design of an integrated model with temporal graph attention and transformer-augmented RNNs for enhanced anomaly detection by Sai Babu Veesam, Aravapalli Rama Satish, Sreenivasulu Tupakula, Yuvaraju Chinnam, Krishna Prakash, Shonak Bansal, Mohammad Rashed Iqbal Faruque

“…Also, many traditional methods rely heavily on large labeled datasets, generalizing poorly when encountering unseen anomalies in the process. …”
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FusionScan: accurate prediction of fusion genes from RNA-Seq data by Pora Kim, Ye Eun Jang, Sanghyuk Lee

“…In the performance test using three cell line datasets with validated fusion cases (NCI-H660, K562, and MCF-7), FusionScan outperformed other existing programs by a considerable margin, achieving the precision and recall rates of 60% and 79%, respectively. …”
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Exploring integrated approaches for optimal well placement: a compelling case study of the Sarvak carbonate reservoir within an Iranian oilfield by Vali Mehdipour, Ahmad Reza Rabbani, Ali Kadkhodaie, David A. Wood

“…Abstract The primary purpose of this study is to identify the high reservoir quality area for drilling and perforation of new wells using interrelated geological, petrophysical, and seismic data. Various datasets such as, core analysis data (two wells), petrophysical logs (twenty wells) and 3D seismic cube were used to consider different scenarios for optimum well placement based on the availability and accuracy of the data. …”
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A novel hybrid CLARA and fuzzy time series Markov chain model for predicting air pollution in Jakarta by Nurtiti Sunusi, Ankaz As Sikib, Sumanta Pasari

“…. • The CLARA-FTSMC hybrid method demonstrates high effectiveness in analyzing large datasets, addressing the limitations of previous hybrid clustering fuzzy time series methods. • The number of fuzzy time series partitions is optimally determined based on clustering results obtained through the gap statistic approach, ensuring robust partitioning. • The forecasting accuracy of the CLARA-FTSMC hybrid method, evaluated using MAE and RMSE, showed excellent performance in predicting daily air pollution levels of SO₂ and CO in Jakarta.…”
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A risk signature constructed by Tregs-related genes predict the clinical outcomes and immune therapeutic response in kidney cancer by Gang Li, Jingmin Cui, Tao Li, Wenhan Li, Peilin Chen

“…Through analyzing two other external immune therapeutic datasets, we found that the risk score could predict the patient's immune therapeutic response. …”
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The evolution of gender studies in physical education: insights from a bibliometric analysis by Bustanol Arifin, Abdurrohman Muzakki, Ratko Pavlović, Edi Setiawan

“…Pre-process bibliographic datasets generated with the ScientoPy tools. Findings/Results: This research shows a growing interest in the topic of gender in physical education since 2005, with a peak in 2023. …”
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Metadag: a web tool to generate and analyse metabolic networks by Pere Palmer-Rodríguez, Ricardo Alberich, Mariana Reyes-Prieto, José A. Castro, Mercè Llabrés

“…MetaDAG was tested using two datasets. In an eukaryotic analysis, it successfully classified organisms from the KEGG database at the kingdom and phylum levels. …”
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AFN-Net: Adaptive Fusion Nucleus Segmentation Network Based on Multi-Level U-Net by Ming Zhao, Yimin Yang, Bingxue Zhou, Quan Wang, Fu Li

“…However, due to the challenge of detecting small targets and complex boundaries in datasets, traditional methods often fail to achieve satisfactory results. …”
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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. The results show that the proposed model outperformed the other methods with the accuracy of 91.30% with the split rate of 0.2% in which the training data are 20% and testing data are 80%. …”
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Influence of College Teacher’s Instructional Design on the Development of College Students’ Thinking of Innovation Multi-Algorithms Perspective Analysis by Leilei Wang, Jie Zhou, Xinying Li

“…Through the use of conventional datasets, this integrated multi-algorithmic system’s dependability is illustrated. …”
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In Silico Analysis of the Gene Expression Patterns between Aldosterone-Producing Adenoma and Nonfunctional Adrenocortical Adenoma by Yongfa Dai, Jing Li, Hong Wen, Jie Liu, Jianling Li

“…WISP2, S100A10, SSTR5-AS1, SLC29A1, APOC1, and SLITRK4 are six real hub genes with the same gene expression pattern between the combined and validation datasets, three of which indirectly or directly participate in lipid metabolism including WISP2, S100A10, and APOC1. …”
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Hypergraph User Embeddings and Session Contrastive Learning for POI Recommendation by Yan Zhang, Bin Wang, Qian Zhang, Sulei Zhu, Yan Ma

“…Extensive experiments on two real-world datasets show that HUE-SCL outperforms existing state-of-the-art baseline methods.…”
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Evaluation of CMIP5 Global Climate Models for Simulating Climatological Temperature and Precipitation for Southeast Asia by Suchada Kamworapan, Chinnawat Surussavadee

“…Historical simulations of climatological temperature and precipitation of the 40 GCMs for the 40-year period of 1960–1999 for both land and sea and those for the century of 1901–1999 for land are evaluated using observation and reanalysis datasets. Nineteen different performance metrics are employed. …”
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Temporal Study of Environmental DNA and Acoustic Data Reveals Coexistence of Sympatric Bat Species in a North American Ecosystem by Vrinda M. Suresh, Trevor Hébert, Kirsten Isabel Verster, Elizabeth A. Hadly

“…We demonstrate differences between the acoustic data and eDNA data, which has implications for how such datasets may be interpreted in future research. The study finds evidence of some types of niche partitioning in this community and characterizes baseline interactions between species, providing a foundation for future efforts to non‐invasively monitor for unexpected biological change in local ecosystems.…”
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Comprehensive Bioinformatics Method to Explore Immune-Related Genes in the Pathogenesis of Myocardial Infarction by Xin Zhang, Yiren Yao, Ying Ding, Wenting Yan, Yang Gu, Xiwen Zhang, Xiaojin Xu

“…Methods: Gene expression data were analyzed from three datasets: GSE29111 and GSE66360, which were combined as a training set, and GSE48060, which served as the validation set. …”
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A temporal knowledge graph reasoning model based on recurrent encoding and contrastive learning by Weitong Liu, Khairunnisa Hasikin, Anis Salwa Mohd Khairuddin, Meizhen Liu, Xuechen Zhao

“…A quantity of experiments conducted on four benchmark datasets demonstrate the exceptional performance of the proposed TRCL model across a range of metrics, surpassing state-of-the-art TKG reasoning models. …”
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Fortifying IoT Infrastructure Using Machine Learning for DDoS Attack within Distributed Computing-based Routing in Networks by Sharaf Aldeen Abdulkadhum Abbas, Abdullahi Abdu Ibrahim

“…We evaluate these algorithms using metrics such as the confusion matrix, F1 score, and AUC-ROC to determine their performance in managing imbalanced datasets and generating meaningful insights. Our results indicate that Random Forest outperforms the other models, achieving an accuracy of 99.2%, a false positive rate of 0.8%, and an AUC-ROC of 0.997. …”
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Overview of Solar Photovoltaic MPPT Methods: A State of the Art on Conventional and Artificial Intelligence Control Techniques by Debabrata Mazumdar, Chiranjit Sain, Pabitra Kumar Biswas, P. Sanjeevikumar, Baseem Khan

“…A collection of several datasets pertaining to various control processes that were gleaned from various research articles has also been presented. …”
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Cardiovascular Disease Detection through Innovative Imbalanced Learning and AUC Optimization by Karthikeyan Palanisamy, Krishnaveni Krishnasamy, Praba Venkadasamy

“…This integration simplifies the model by reducing the number of parameters needing adjustment, making it particularly effective for handling imbalanced datasets through an efficient training process; 2) Theoretical analysis demonstrates that ImAUC-PSVM retains the same structural solution as standard PSVM. …”
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Correlation between the Dissemination of Classic English Literary Works and Cultural Cognition in the New Media Era by Weiwei Guo

“…Most of the existing classic English literary works are appreciated based on modern literature datasets. Nowadays, with the continuous development of new media technology, there are fewer studies on the dissemination and cultural cognition of classic English literary works. …”
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