Enhancing Classification Models With Sophisticated Counterfactual Images by Xiang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

“…Furthermore, 3) we combined counterfactual images into datasets to fine-tune the model, thus correcting the model's perception of feature relationships. …”
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Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers by R. Gallardo-Caballero, C. J. García-Orellana, A. García-Manso, H. M. González-Velasco, M. Macías-Macías

“…Although there exist many studies broaching this problem, most of them are nonreproducible due to the use of proprietary image datasets. We use a known subset of the currently largest publicly available mammography database, the Digital Database for Screening Mammography (DDSM), to develop a computer-aided detection system that outperforms the current reproducible studies on the same mammogram set. …”
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A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks by Shubin Zheng, Qianwen Zhong, Xiaodong Chai, Xingjie Chen, Lele Peng

“…Then, the model was successfully applied to predict the car body vibration acceleration of test datasets on different segments of the same railway. …”
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Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting by Jichang Zhang, Faisal Najeeb, Yulin Wang, Xinpei Wang, Pengfei Xu, Hammad Omer, Jianjun Zheng, Jingfeng Zhang, Sue Francis, Paul Glover, Richard Bowtell, Thomas Meersmann, Chengbo Wang

“…Both simulation and clinical datasets demonstrate that the proposed method provides superior motion correction, higher temporal resolution, and over 5 times faster reconstruction speed than existing motion-corrected GRASP frameworks.…”
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Impact of Sanction Shock on Iran's Stock Market Index by Reza Tehrani, Mahmood Mokhtarband, Menal Aboodeh

“…The research methodology employed an Auto-Regressive Distributed Lag (ARDL) model, considering datasets with both annual and seasonal frequencies over a 30-year period from 1991 to 2021. …”
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Thermodynamics of modified Chaplygin-Jacobi gas and modified Chaplygin-Abel gas: Stability analysis and observational constraints by Banadipa Chakraborty, Tamal Mukhopadhyay, Debojyoti Mondal, Ujjal Debnath

“…We then perform observational analysis using CC+BAO and Pantheon+SH0ES datasets to impose constraints on our model parameters using the Markov Chain Monte Carlo (MCMC) process.…”
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Impact of Environmental Conditions on Renewable Energy Prediction: An Investigation Through Tree-Based Community Learning by Ferdi Doğan, Saadin Oyucu, Derya Betul Unsal, Ahmet Aksöz, Majid Vafaeipour

“…The results indicate that less sophisticated models are inadequate for accurately representing complex datasets. The results evaluate the effectiveness of machine learning methods in delivering valuable insights for energy sectors managing environmental conditions and predicting renewable energy sources…”
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Semantic Schema Extraction in NoSQL Databases using BERT Embeddings by Saad Belefqih, Ahmed Zellou, Mouna Berquedich

“…The method analyzes semantic relationships within triplets from JSON documents through four stages: triplet extraction, preprocessing, BERT Embedding generation, and similarity analysis. Evaluation on real datasets demonstrates over 83% accuracy in extracting valid nested schema components. …”
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A New Transfer Learning Ensemble Model with New Training Methods for Gear Wear Particle Recognition by Chunhua Zhao, zhangwen Lin, Jinling Tan, Hengxing Hu, Qian Li

“…Aiming at solving the acquisition problems of wear particle data of large-modulus gear teeth and few training datasets, an integrated model of LCNNE based on transfer learning is proposed in this paper. …”
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A Novel Intelligent Recommendation Algorithm Based on Mass Diffusion by Guanglai Tian, Shuang Zhou, Gengxin Sun, Chih-Cheng Chen

“…Based on user-item bipartite graph, this paper establishes a multisubnet composited complex network (MSCCN) of multiple user relationships and then extends the mass diffusion (MD) algorithm into a novel intelligent recommendation algorithm. Two public online datasets, namely, Epinions and FilmTrust, were selected to verify the effect of the proposed algorithm. …”
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Semi-supervised Gaussian process classification algorithm addressing the class imbalance by Zhan-guo XIA, Shi-xiong XIA, Shi-yu CAI, Ling WAN

“…The traditional supervised learning is difficult to deal with real-world datasets with less labeled information when the training sets class is imbalanced.Therefore,a new semi-supervised Gaussian process classification of address-ing was proposed.The semi-supervised Gaussian process was realized by calculating the posterior probability to obtain more accurate and credible labeled data,and embarking from self-training semi-supervised methods to add class label into the unlabeled data.The algorithm makes the distribution of training samples relatively balance,so the classifier can adaptively optimized to obtain better effect of classification.According to the experimental results,when the circum-stances of training set are class imbalance and much lack of label information,The algorithm improves the accuracy by obtaining effective labeled in comparison with other related works and provides a new idea for addressing the class im-balance is demonstrated.…”
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Historical Population Database of Transylvania. Sources, Particularities, Challenges, and Early Findings by Luminița Dumănescu, Mihaela Hărăguș, Angela Lumezeanu, Elena Crinela Holom, Nicoleta Hegedűs, Daniela Mârza, Diana Covaci, Ioan Bolovan

“…The database has already been employed in a wide-ranging series of analyses conducted on datasets extracted from HPDT, which include infant and adult mortality, nuptiality and age at first marriage, social mobility, and the medicalization of childbirth. …”
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Hybrid Quantum Cycle Generative Adversarial Network for Small Molecule Generation by Matvei Anoshin, Asel Sagingalieva, Christopher Mansell, Dmitry Zhiganov, Vishal Shete, Markus Pflitsch, Alexey Melnikov

“…Through extensive experimentation on benchmark drug design datasets, quantum machine 9 (QM9) and PubChemQC 9 (PC9), the introduced models are shown to outperform the previously achieved scores. …”
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Deep Grassmannian multiview subspace clustering with contrastive learning by Rui Wang, Haiqiang Li, Chen Hu, Xiao-Jun Wu, Yingfang Bao

“…Extensive experiments conducted on five benchmarking datasets demonstrate the effectiveness of the proposed method. …”
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LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers by Durmus Ozkan Sahin, Sedat Akleylek, Erdal Kilic

“…These classifiers are compared on four different datasets with basic machine learning techniques such as support vector machine, k-nearest neighbor, Naive Bayes, and decision trees. …”
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Inosine monophosphate dehydrogenase 2 (IMPDH2) modulates response to therapy and chemo-resistance in triple negative breast cancer by Tatiane da Silva Fernandes, Bryan M. Gillard, Tao Dai, Jeffrey C. Martin, Kanita A. Chaudhry, Scott M. Dugas, Alyssa A. Fisher, Pia Sharma, RongRong Wu, Kristopher M. Attwood, Subhamoy Dasgupta, Kazuaki Takabe, Spencer R. Rosario, Anna Bianchi-Smiraglia

“…Analysis of publicly available datasets reveals elevated IMPDH2 expression to associate with worse overall TNBC prognosis in the clinic, including lower recurrence-free survival post adjuvant/neoadjuvant therapy. …”
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A Short Report on the Markov Property of DNA Sequences on 200-bp Genomic Units of ENCODE/Broad ChromHMM Annotations: A Computational Perspective by Hyun-Seok Park

“…Our aim was to identify the possible relationship between DNA sequences and the newly built chromatin states based on the integrated ChromHMM datasets of different cells and tissue types.…”
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AquaYOLO: Enhancing YOLOv8 for Accurate Underwater Object Detection for Sonar Images by Yanyang Lu, Jingjing Zhang, Qinglang Chen, Chengjun Xu, Muhammad Irfan, Zhe Chen

“…The model is evaluated on two standard underwater sonar datasets, UATD and Marine Debris, demonstrating superior accuracy and robustness compared to baseline models.…”
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Customer Behavior Analysis and Predictive Modeling in Supermarket Retail: A Comprehensive Data Mining Approach by Kavitha Dhanushkodi, Akila Bala, Nithin Kodipyaka, V. Shreyas

“…We delve into the intricacies of data mining methodologies, exploring how retailers can leverage diverse datasets to uncover valuable insights and build predictive models that drive business growth and customer satisfaction. …”
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siMacro: A Fast and Easy Data Processing Tool for Cell-Based Genomewide siRNA Screens by Nitin Kumar Singh, Bo Yeun Seo, Mathukumalli Vidyasagar, Michael A. White, Hyun Seok Kim

“…Here, we present siMacro, a fast and easy-to-use Microsoft Office Excel-based tool with a graphic user interface, designed to process single-condition or two-condition synthetic screen datasets. siMacro normalizes position and batch effects, censors outlier samples, and calculates Z-scores and robust Z-scores, with a spreadsheet output of >120,000 samples in under 1 minute.…”
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