IoT-based approach to multimodal music emotion recognition by Hanbing Zhao, Ling Jin

“…Extensive experiments were conducted on two public datasets, DEAM and DEAP, and the results demonstrate that CGF-Net performs exceptionally well in various emotion recognition tasks, particularly achieving high accuracy and F1 scores in recognizing positive emotions such as ”Happy” and ”Relax.” …”
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Constructing Better Classifier Ensemble Based on Weighted Accuracy and Diversity Measure by Xiaodong Zeng, Derek F. Wong, Lidia S. Chao

“…The measure is compared to two representative measures, Kappa-Error and GenDiv, and two threshold measures that consider only accuracy or diversity, with two heuristic search algorithms, genetic algorithm, and forward hill-climbing algorithm, in ensemble selection tasks performed on 15 UCI benchmark datasets. The empirical results demonstrate that the WAD measure is superior to others in most cases.…”
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Compositional data analysis enables statistical rigor in comparative glycomics by Alexander R. Bennett, Jon Lundstrøm, Sayantani Chatterjee, Morten Thaysen-Andersen, Daniel Bojar

“…Applied to comparative glycomics datasets, including known glycan concentrations in defined mixtures, this approach controls false-positive rates and results in reproducible biological findings. …”
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Advancements in training and deployment strategies for AI-based intrusion detection systems in IoT: a systematic literature review by S. Kumar Reddy Mallidi, Rajeswara Rao Ramisetty

“…Moreover, the review assesses the datasets commonly used for training and validating IDS and discusses key performance metrics and validation measures critical for assessing IDS effectiveness. …”
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Ptr4BERT: Automatic Semisupervised Chinese Government Message Text Classification Method Based on Transformer-Based Pointer Generator Network by Mingxin Li, Kaiqian Yin, Minghao Wang

“…Besides, we designed a crawler program and obtained two datasets from different websites, which are named HNMes and QDMes. …”
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A dual-stream model based on PRNU and quaternion RGB for detecting fake faces. by Mohan Hua, Shuangliang Li, Jinwei Wang

“…Experimental results obtained from diverse datasets underscore the advantages of our method in terms of accuracy, achieving a detection accuracy of 96.81%.…”
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Graph-Attention Diffusion for Enhanced Multivariate Time-Series Anomaly Detection by Vadim Lanko, Ilya Makarov

“…The masked time-series data is then corrupted by noise and reconstructed back by the diffusion model that removes noise in a step-by-step manner. Evaluation on four datasets from various sources demonstrates the effectiveness of our approach, achieving an average <inline-formula><tex-math notation="LaTeX">$F1$</tex-math></inline-formula>-score of 96.51&#x0025;, outperforming many existing baselines. …”
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Compensating CBCT Motion Artifacts with Any 2D Generative Model by Yipeng Sun, Linda-Sophie Schneider, Mingxuan Gu, Siyuan Mei, Siming Bayer, Andreas K. Maier

“…Experimental results on simulated CBCT datasets demonstrate significant improvements in image quality metrics and artifact reduction, offering a promising solution for enhancing 3D CT reconstruction in industrial applications. …”
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A Database for the Future. Major Contributions from 47 Years of Database Development and Research at the Demographic Data Base by Sören Edvinsson

“…A countless number of customised datasets have been prepared and distributed to researchers in Sweden and abroad and to date, the research has resulted in more than a thousand published scientific reports, books, and articles within a broad range of academic fields. …”
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Political Bias in Large Language Models: A Comparative Analysis of ChatGPT-4, Perplexity, Google Gemini, and Claude by Tavishi Choudhary

“…The presence of such biases underscores the critical need for transparency in AI development and the incorporation of diverse training datasets, regular audits, and user education to mitigate any of these biases. …”
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A Novel Approach for Detecting DGA-Based Botnets in DNS Queries Using Machine Learning Techniques by Ali Soleymani, Fatemeh Arabgol

“…For this purpose, extracted and labeled domain name datasets containing healthy and infected DGA botnet data were used. …”
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Artificial Intelligence: An Untapped Opportunity for Equity and Access in STEM Education by Shalece Kohnke, Tiffanie Zaugg

“…., unequal representation in training datasets leading to unfair assessments) and data privacy risks (e.g., potential breaches of sensitive student data), require critical attention to ensure AI systems promote equity rather than exacerbate disparities. …”
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Forecasting Renewable energy and electricity consumption using evolutionary hyperheuristic algorithm by Yang Cao, Jun Yu, Rui Zhong, Masaharu Munetomo

“…As a result, AE-GAPB achieved excellent results on renewable energy generation and electricity consumption datasets from the Hokkaido, Kyushu, and Tohoku regions of Japan.…”
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The Expression of PPAR Pathway-Related Genes Can Better Predict the Prognosis of Patients with Colon Adenocarcinoma by Xiao-Yu Zhou, Jian-Qi Wang, Jin-Xu Chen, Jing-Song Chen

“…The reliability of the system was tested on six external validation datasets. Furthermore, PPAR-Riskscore was able to evaluate the immune cell infiltration and chemotherapy sensitivity of each tumor sample. …”
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Federated Learning for Brain Tumor Diagnosis: Methods, Challenges and Future Prospects by Ma Yuhan

“…Although these factors limit the widespread application of FL in medical settings, this paper also proposes potential solutions, such as improving algorithm interpretability through interpretable tools, and utilizing transfer learning and domain adaptation methods to enhance model effectiveness across different datasets. Techniques like knowledge distillation, model quantization, and pruning are proposed to enhance computational efficiency and minimize communication costs. …”
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Application of an Improved TF-IDF Method in Literary Text Classification by Lin Xiang

“…However, there are significant issues with utilizing this approach, including a lack of distribution information inside categories, a lack of distribution information between categories, and an inability to adjust to skewed datasets. It is possible to improve classification accuracy by using the TF-IDF algorithm in this paper’s application situation by exploiting the association between feature words and the quantity of texts in which they appear, while ignoring the variation in feature word distribution across categories. …”
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Examining inclusivity: the use of AI and diverse populations in health and social care: a systematic review by John Gabriel O. Marko, Ciprian Daniel Neagu, P. B. Anand

“…Results This research revealed disparities in AI outcomes, accessibility, and representation among diverse groups due to biased data sources and a lack of representation in training datasets, which can potentially exacerbate inequalities in care delivery for marginalized communities. …”
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Improving person re-identification based on two-stage training of convolutional neural networks and augmentation by S. A. Ihnatsyeva, R. P. Bohush

“…The use of two-stage learning technology and the proposed data augmentation method made it possible to increase the person re-identification accuracy for different CNNs and datasets: in the Rank1 metric  by 4–21 %; in the mAP by 10–31 %; in the mINP by 39–60 %.…”
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Classification in Networked Data with Heterophily by Zhenwen Wang, Fengjing Yin, Wentang Tan, Weidong Xiao

“…In empirical study, we apply the proposed algorithm to the real-world datasets, compared with some other algorithms. The experimental results show that the proposed algorithm performs better when the networks are of heterophily.…”
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Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions by Lu Zhuo, Dawei Han

“…The MODIS NDVI thresholds of 0.81 and 0.64 (for cropland and forest basins, resp.) are very effective in dividing soil moisture datasets into “denser” and “thinner” vegetation periods. …”
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