Variability in Dust Observed over China Using A-Train CALIOP Instrument by Hui Xu, Fengjie Zheng, Wenhao Zhang

“…Patterns of dust aerosol variation over China are analyzed using A-Train CALIOP and precipitation, soil moisture, and vegetation coverage datasets during the period of 2007 and 2014. Spatially, dust is mostly prominent over northwestern China, with the highest and most widespread dust activities being in Taklimakan Desert. …”
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Efficiently Modeling Lateral Vehicle Movement Including its Temporal Interrelations Using a Two-Level Stochastic Model by N. Neis, J. Beyerer

“…The model’s capabilities are demonstrated based on five single driver datasets. It is shown that the model allows for efficient calibration, is able to replicate the behavior of these drivers, and is characterized by short runtimes. …”
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Unveiling the Complexity of Medical Imaging through Deep Learning Approaches by Javaid Iqbal Bhat, Novsheena Rasool

“…Encompassing a range of diseases, including Alzheimer’s, breast cancer, brain tumors, glaucoma, heart murmurs, retinal microaneurysms, colorectal liver metastases, and more, the analysis emphasizes contributions succinctly summarized in a tabular form.The table provides an overview of various deep learning approaches applied to different diseases, incorporating methodologies, datasets, and outcomes for each condition.Notably, performance metrics such as accuracy, specificity, sensitivity, and other crucial measures underscore the achieved results. …”
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Intelligent Fault Diagnosis of Aeroengine Sensors Using Improved Pattern Gradient Spectrum Entropy by Huihui Li, Linfeng Gou, Hua Zheng, Huacong Li

“…The method is validated with datasets containing different fault types. The experimental results show that this method can be easily applied to the online automatic fault diagnosis of aeroengine control system sensors.…”
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Leveraging machine learning to predict residential location choice: A comparative analysis by Vahid Noferesti, Hamid Mirzahossein

“…While discrete choice models have been used to predict residential locations, their limitations in handling complex datasets have hindered their accuracy. Machine learning has shown potential to outperform discrete choice methods in transportation-related decisions like travel mode. …”
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MCRCNet: A Bearing Fault Diagnosis Method for Unknown Faults Based on Transfer Learning by Guangyuan Xu, Ruifeng Guo, Zhenyu Yin, Feiqing Zhang

“…The proposed method is experimentally verified on Case Western Reserve University, Jiangnan University, and laboratory datasets. The experimental results show that the method has good performance in most tasks and has good generalization ability, which provides a feasible solution for the research of bearing fault diagnosis.…”
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EMM-CLODS: An Effective Microcluster and Minimal Pruning CLustering-Based Technique for Detecting Outliers in Data Streams by Mohamed Jaward Bah, Hongzhi Wang, Li-Hui Zhao, Ji Zhang, Jie Xiao

“…The analysis from our experimental studies on both synthetic and real-world datasets shows that the technique performs well with minimal memory and time consumption when compared to the other baseline algorithms, making it a very promising technique in dealing with outlier detection problems in data streams.…”
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Meta analysis of business valuation solutions – are AI based methods better? by Aljaž Herman, Damijan Mumel, Timotej Jagrič

“…These methodologies utilize vast datasets and sophisticated algorithms, enhancing predictive accuracy and understanding of market dynamics. …”
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Rethinking spatial-temporal contrastive learning for Urban traffic flow forecasting: multi-level augmentation framework by Lin Pan, Qianqian Ren, Zilong Li, Xingfeng Lv

“…Extensive experimental results on four real-world urban datasets demonstrate that UrbanGCL significantly outperforms other state-of-the-art methods, with the maximum improvement reaching nearly 8.80%.…”
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THE PREVALENCE AND THE MORPHOLOGICAL ASPECTS OF THE ONODI CELLS – COMPUTER TOMOGRAPHIC STUDY by Alin Horatiu Nedelcu, Cosmin Gabriel Popa, Simona Alice Partene Vicoleanu, Razvan Tudor Tepordei, Gabriel Statescu, Roxana-Andreea Popa, Marius Constantin Moraru, Manuela Ursaru

“…Materials and Methods: Our retrospective study analyses 121 cranio-cerebral computed tomography (CT) datasets. Two expert radiologists independently investigated the images using RadiAnt DICOM Viewer software. …”
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Fault Diagnosis Method of Check Valve Based on Multikernel Cost-Sensitive Extreme Learning Machine by Jun Ma, Jiande Wu, Xiaodong Wang

“…At the same time, the presented method can obtain very high accuracy under imbalance datasets condition and effectively overcome the weakness of diagnostic cost equalization and improve the interpretability and reliability of the decision function of classification model. …”
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Interpretable Detection of Malicious Behavior in Windows Portable Executables Using Multi-Head 2D Transformers by Sohail Khan, Mohammad Nauman

“…To address these limitations, this paper presents a novel model for malware detection, utilizing vision transformers to analyze the Operation Code (OpCode) sequences of more than 350000 Windows portable executable malware samples from real-world datasets. The model achieves a high accuracy of 0.9864, not only surpassing the previous results but also providing valuable insights into the reasoning behind the classification. …”
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A Small Target Detection Method Based on the Improved FCN Model by Guofeng Ma

“…The experimental results on public datasets show that the proposed method outperforms other deep learning algorithms (DLA) in the detection accuracy of small target objects. …”
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Feature Selection and Parameter Optimization of Support Vector Machines Based on Modified Cat Swarm Optimization by Kuan-Cheng Lin, Yi-Hung Huang, Jason C. Hung, Yung-Tso Lin

“…Experiment results demonstrate the superiority of MCSO in classification accuracy using subsets with fewer features for given UCI datasets, compared to the original CSO algorithm. Moreover, experiment results show the fittest CSO parameters and MCSO take less training time to obtain results of higher accuracy than original CSO. …”
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A Distribution Agnostic Rank-Based Measure for Proximity Search by Mayur Garg, Ashutosh Nayak, Rajasekhara Reddy Duvvuru Muni

“…We illustrate the effectiveness of the proposed methodology using five datasets in three application areas - Outlier Detection, Nearest Neighbor Search, and Text Similarity. …”
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JSTC: Travel Time Prediction with a Joint Spatial-Temporal Correlation Mechanism by Alfateh M. Tag Elsir, Alkilane Khaled, Pengfei Wang, Yanming Shen

“…Extensive experiments on three large-scale real-world traffic datasets (NYC, Chengdu, and Xi’an) show the efficiency of our model and its superiority compared to other methods.…”
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Detecting Communities in Complex Networks Using an Adaptive Genetic Algorithm and Node Similarity-Based Encoding by Sajjad Hesamipour, Mohammad Ali Balafar, Saeed Mousazadeh

“…Several experiments and comparisons were conducted to verify the effectiveness of the proposed method using modularity and NMI measures on both real-world and synthetic datasets. The results show that the proposed method can find the communities in a significantly shorter time than other GAs while reaching a better trade-off in the different measures.…”
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Explainable Security Requirements Classification Through Transformer Models by Luca Petrillo, Fabio Martinelli, Antonella Santone, Francesco Mercaldo

“…In this work, we fine-tuned four pre-trained transformers using four datasets (the original one and the three augmented versions). …”
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Multimodal Emotion Recognition: Emotion Classification Through the Integration of EEG and Facial Expressions by Songul Erdem Guler, Fatma Patlar Akbulut

“…The results validate the effectiveness of this approach, demonstrating the high accuracy of the Gated Recurrent Unit (GRU) model, which achieved an average of 91.8% classification accuracy on unimodal (EEG-only) data and an average of 97.8% classification accuracy on multimodal (EEG and facial expressions) datasets in the multi-class emotion categories. The findings emphasize that by applying a multi-class classification framework, multimodal approaches offer significant improvements over traditional unimodal techniques. …”
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Long-Term Trends in Marriage Timing and the Impact of Migration, the Netherlands (1650-1899) by Charlotte Störmer, Corry Gellatly, Anita Boele, Tine de Moor

“…We make use of two new large historical datasets, namely an aggregation of Dutch genealogies and the transcribed marriage banns of Amsterdam. …”
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