Scalable network emulation on analog neuromorphic hardware by Elias Arnold, Philipp Spilger, Jan V. Straub, Eric Müller, Dominik Dold, Gabriele Meoni, Johannes Schemmel

“…We demonstrate the training of two deep spiking neural network models—using the MNIST and EuroSAT datasets—that exceed the physical size constraints of a single-chip BrainScaleS-2 system. …”
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A Novel Online Portfolio Selection Strategy with Multiperiodical Asymmetric Mean Reversion by Zijin Peng, Weijun Xu, Hongyi Li

“…Our empirical results testing six real market datasets show that this strategy can achieve better results in bearing higher transaction cost.…”
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A semi-supervised boundary segmentation network for remote sensing images by Yongdong Chen, Zaichun Yang, Liangji Zhang, Weiwei Cai

“…Experimental results on three benchmark datasets demonstrate that BS-GAN achieves superior accuracy and generalization capabilities compared to existing segmentation networks.…”
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Explicit Content Detection System: An Approach towards a Safe and Ethical Environment by Ali Qamar Bhatti, Muhammad Umer, Syed Hasan Adil, Mansoor Ebrahim, Daniyal Nawaz, Faizan Ahmed

“…The experimental result shows that the proposed model provides an accuracy of ~ 95% when tested on our image and video datasets.…”
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Evaluation of Novel AI Architectures for Uncertainty Estimation by Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja

“…Our research evaluates uncertainty in Convolutional Neural Networks (CNN) and Vision Transformers (ViT) using the MNIST and ImageNet-1K datasets. Using High-Performance (HPC) platforms, including the traditional Polaris supercomputer and AI accelerators like Cerebras CS-2 and SambaNova DataScale, we assessed the computational merits and bottlenecks of each platform. …”
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Model Architecture Analysis and Implementation of TENET for Cell–Cell Interaction Network Reconstruction Using Spatial Transcriptomics Data by Ziyang Wang, Yujian Lee, Yongqi Xu, Peng Gao, Chuckel Yu, Jiaxing Chen

“…The TENET framework has been implemented and evaluated on both real and synthetic ST datasets. This protocol primarily introduces our network architecture and its implementation.…”
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Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography by S. Jbabdi, P. Bellec, R. Toro, J. Daunizeau, M. Pélégrini-Issac, H. Benali

“…We evaluate the numerical performance of this approach on simulated datasets, as well as its robustness to local perturbation induced by fiber crossing. …”
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Modified Autoencoder Training and Scoring for Robust Unsupervised Anomaly Detection in Deep Learning by Nicholas Merrill, Azim Eskandarian

“…We demonstrate significant improvements over conventional AE training on image, remote-sensing, and cybersecurity datasets.…”
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A Deep Reinforcement Learning Approach to the Optimization of Data Center Task Scheduling by Haiying Che, Zixing Bai, Rong Zuo, Honglei Li

“…The proposed scheduling model was trained, tested, and compared with classical scheduling algorithms on real data center datasets in experiments to show the effectiveness and efficiency. …”
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Fault diagnosis and auto dispatchin of power communication network based on unsupervised clustering and frequent subgraph mining by Jihua WU, Pengyu ZHU, Zichen WU, Bin GU, Tao HONG, Bo GUO, Jing WANG, Jingyu WANG

“…Fault diagnosis is one of the most challenging tasks in power communication.The fault diagnosis based on rules can no longer meet the demand of massive alarms processing.The existing approaches based on the supervised learning need large sets of the labeled data and sufficient time to train models for processing continuous data instead of alarms, which are far behind the feasibility of deployment.As for alarm correlation and fault pattern discovery, a self-learning algorithm based on the density-based clustering and frequent subgraph mining was proposed.A novel approach for automatic fault diagnosis and dispatch were also introduced, which provided the scalable and self-renewing ability and had been deployed to the automatic fault dispatch system.Experiments in the real-world datasets authorized the effectiveness for timely fault discovery and targeted fault dispatch.…”
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Basic assumptions, core connotations, and path methods of model modification—using confirmatory factor analysis as an example by Zhangbo Xiong, Huixian Xia, Jianjun Ni, Hongzhen Hu

“…Finally, any modifications to the model should undergo cross-validation to ensure its applicability to other sample datasets.…”
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Microcluster-Based Incremental Ensemble Learning for Noisy, Nonstationary Data Streams by Sanmin Liu, Shan Xue, Fanzhen Liu, Jieren Cheng, Xiulai Li, Chao Kong, Jia Wu

“…Experiments with two synthetic datasets designed to test for both gradual and abrupt drift show that our method provides more accurate classification in nonstationary data streams with noise than the two popular baselines.…”
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A Novel Extended Susceptible, Exposed, Infected, and Recovered Model with Surveys for Analysis of COVID-19 Pandemic in Rajasthan by Meena Malik, Chander Prabha, Punit Soni, Khushboo Bhardwaj, Anshu Arora

“…Modeling frameworks, underlying assumptions, available datasets, and the region/time frame being modeled, predictions are possible, but the projections might vary widely, making it difficult to rely on one model universally way. …”
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Parametric and non-parametric data-driven analytics for socioeconomic challenges in a contemporary world by Thyago C. C. Nepomuceno

“…By harnessing diverse datasets and employing sophisticated analytical techniques, researchers, policymakers, and practitioners can gain profound insights into the root causes of socioeconomic challenges and devise innovative strategies to promote inclusive development and sustainable growth. …”
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Estimating the Proportion of True Null Hypotheses in Multiple Testing Problems by Oluyemi Oyeniran, Hanfeng Chen

“…Using experimental microarray datasets, we demonstrate that the new method provides satisfactory estimate in practice.…”
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Wading Birds of Northern Belize by Justin Dalaba, Venetia S. Briggs-Gonzalez, Jorge Eduardo Ruano, Frank J. Mazzotti

“… Belize is home to over 605 bird species, many of them wading birds popular with bird watchers who enjoy their bright colors and charismatic behavior. …”
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Enhanced capsule neural network with advanced triangulation topology aggregation optimizer for music genre classification by Linlin Jiang, Lei Yang, Shakiba azimi

“…The proposed method applied to two extensively utilized datasets, namely GTZAN and Ballroom, and compare its performance against several cutting-edge techniques. …”
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Rank-Based Ant System via the Relative Position in a Local Hierarchy by Tomoko Sakiyama, Kotaro Uneme, Ikuo Arizono

“…We show that, by using several TSP datasets, the proposed model can find a better solution than ASmulti.…”
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Differential Expression Profiles of mRNA and Noncoding RNA and Analysis of Competitive Endogenous RNA Regulatory Networks in Nonalcoholic Steatohepatitis by Mengjia Gao, Jingxin Xin, Xiaoling Li, Ling Gao, Shanshan Shao, Meng Zhao

“…In this study, differentially expressed circular RNAs (circRNAs) were obtained by analyzing NASH-related circRNA datasets, and then, corresponding target microRNAs (miRNAs) and messenger RNAs (mRNAs) were predicted to construct a circRNA–miRNA–mRNA regulatory network. …”
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LL’intelligenza artificiale generativa: rischi e opportunità in ambito educativo. Il progetto «CounselorBot» per il supporto tutoriale by Daniele Dragoni, Massimo Margottini

“…Its use raises issues of various kinds – educational, methodological-didactic, and ethical – highlighting risks such as discrimination, increasing technological dependency, and the uncontrolled generation of inaccurate and hardly recognizable content due to biases in datasets. The European Union, through the AI Act, has classified the use of AI in education as «high risk», emphasizing the importance of a cautious and responsible approach. …”
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