The United States Army Aeromedical Research Laboratory Multi-Attribute Task Battery by Jonathan Vogl, Charles D. McCurry, Charles D. McCurry, Sharon Bommer, Sharon Bommer, J. Andrew Atchley

“…However, the USAARL MATB takes this foundation and enhances it to meet the demands of contemporary research, particularly in the areas of performance modeling, cognitive workload assessment, adaptive automation, and trust in automation. …”
Get full text

Specific features of current intraperitoneal therapy in patients with ovarian cancer by A. G. Kedrova, S. A. Levakov, S. E. Krasil’nikov, T. A. Maksimenko, V. I. Voznesenskiy, A. V. Gerasimov, D. A. Astakhov, V. V. Kosyy, O. E. Nechaeva

Get full text

Distribution and morphological features of astrocytes and Purkinje cells in the human cerebellum by Christa Hercher, Christa Hercher, Kristin Ellerbeck, Louise Toutée, Xinyu Ye, Refilwe Mpai, Refilwe Mpai, Claudia Belliveau, Maria Antonietta Davoli, W. Todd Farmer, Alanna J. Watt, Keith K. Murai, Gustavo Turecki, Gustavo Turecki, Naguib Mechawar, Naguib Mechawar, Naguib Mechawar

“…Lastly, to determine if these features differ from those of cerebellar astrocytes and PCs in species used to model human illnesses, we performed comparative analyses in mice and macaques showing both divergence and commonalities across species.DiscussionThe present study highlights the heterogeneity of astrocytes in the human cerebellum and serves as a valuable resource on cerebellar astrocyte and PC properties in the healthy human brain.…”
Get full text

Integrating near-infrared hyperspectral imaging with machine learning and feature selection: Detecting adulteration of extra-virgin olive oil with lower-grade olive oils and hazeln... by Derick Malavi, Katleen Raes, Sam Van Haute

Get full text

Features of Conceptualization of Wine Drinking Situation in the Works of N. S. Leskov by O. A. Dimitrieva

“…Firstly, it participates in the spatial organization of the work, “sets” the background for the development of events. Secondly, it performs a plot-modeling function, that is, forms a narrative canvas, is a key turning point of events. …”
Get full text

Insights into Galaxy Evolution from Interpretable Sparse Feature Networks by John F. Wu

“…We find that SFNets do not sacrifice accuracy in order to gain interpretability, and that they perform comparably well to cutting-edge models on astronomical ML tasks. …”
Get full text

EMG features dataset for arm activity recognitionGoogle Drive by Koundinya Challa, Issa W. AlHmoud, Chandra Jaiswal, Anish C. Turlapaty, Balakrishna Gokaraju

“…The raw EMG data were filtered and processed to extract seven time-domain features across each channel, resulting in 28 total features. …”
Get full text

Spatio-Temporal Feature Extraction for Pipeline Leak Detection in Smart Cities Using Acoustic Emission Signals: A One-Dimensional Hybrid Convolutional Neural Network–Long Short-Ter... by Saif Ullah, Niamat Ullah, Muhammad Farooq Siddique, Zahoor Ahmad, Jong-Myon Kim

“…The performance of the proposed model was compared with two alternative approaches: a method that employs combined features from the time domain and LSTM and a bidirectional gated recurrent unit model. …”
Get full text

Home is where my villa is: a machine learning-based predictive suitability map for Roman features in Northern Noricum (ca. 50–500 CE/Lower Austria/AUT) by Dominik Hagmann

“…The 1161 km² area of interest includes the municipium Aelium Cetium (Sankt Pölten) and the forts Arelape (Pöchlarn), Favianis (Mautern an der Donau), and Augustianis (Traismauer), now part of the UNESCO World Heritage site „Danube Limes.“ Based on 1184 features from 551 findspots grouped into 129 sites, a machine learning-based Archaeological Predictive Model was developed using Maximum Entropy (Maxent), integrating environmental and agency-related factors. …”
Get full text

MP-NER: Morpho-Phonological Integration Embedding for Chinese Named Entity Recognition by Pu Li, Guopeng Cheng, Guojun Deng, Shuanghong Qu, Min Huang, Guoxiang Li

“…Ablation experiments further validate the effectiveness of the introduced radicals and phonetic features. The experimental results demonstrate that this model effectively captures the semantic information of Chinese characters, addresses the problem of Chinese character heterophony, and improves entity recognition performance. …”
Get full text

Enhancing Surveillance Video Abnormal Behavior Detection Using Deep Convolutional Generative Adversarial Network With GRU Model by Setegn Asnakew Kasegn, Ronald Waweru Mwangi, Michael Kimwele, Surafel Lemma Abebe

“…This includes recent generative methods that use deep convolutional generative adversarial networks (DCGAN). The DCGAN model has gained high research attention recently due to its performs well in extracting spatial features and solve class imbalance issue to detect abnormalities. …”
Get full text

A Two-Tiered Bidirectional Atrous Spatial Pyramid Pooling-Based Semantic Segmentation Model for Landslide Classification Using Remote Sensing Images by G. NaliniPriya, E. Laxmi Lydia, Reem Alshenaifi, Radhika Kavuri, Mohamad Khairi Ishak

“…Next, for the semantic segmentation method, the BASPP-SSCM technique utilizes the DeepLabV3 method with the backbone of the ConvNeXtLarge model for determining the landslide region. Furthermore, the CapsNet model is utilized for the feature extraction process. …”
Get full text

Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction by Hangyu Zhou, Yongquan Yan

“…The experimental results show that the proposed model achieves superior performance in one-step-ahead AQI prediction, with a Root Mean Squared Error (RMSE) of 3.445, a Mean Absolute Percentage Error (MAPE) of 4.737%, a Coefficient of Determination (R2) of 0.993, a Mean Absolute Error (MAE) of 2.263, a Percentage Bias (PBIAS) of −0.511%, and a Willmott Index of Agreement (WI) of 0.998, outperforming other baseline models.…”
Get full text

Comparison of Linear and Nonlinear Features of Electroencephalogram to Classify Alcoholic and Non-Alcoholic People by Elizabeth Stewart, Owen Kelly

Get full text

Adsorptive performance of cottonseed cakes biosorbent and derived activated carbon towards Cu2+ ions removal from aqueous solution: Kinetics modelling, isotherms analysis and therm... by Yowe Kidwe, Djakba Raphaël, Wangmene Bagamla, Mouhamadou Sali, Abia Daouda, Tcheka Constant, Harouna Massai

“…FTIR shows good surface chemistry with various functional groups while Raman spectroscopy and SEM analyses revealed myriad morphological features and carbon phases (graphite and diamond). …”
Get full text

Can eXplainable AI Offer a New Perspective for Groundwater Recharge Estimation?—Global‐Scale Modeling Using Neural Network by Hyekyeng Jung, Jan Saynisch‐Wagner, Stephan Schulz

Get full text

An active learning driven deep spatio-textural acoustic feature ensemble assisted learning environment for violence detection in surveillance videos by Duba Sriveni, Dr.Loganathan R

“…As the name indicates, the proposed DestaVNet model exploits visual and acoustic features to perform violence detection. …”
Get full text

SV-SAE: Layer-Wise Pruning for Autoencoder Based on Link Contributions by Joohong Rheey, Hyunggon Park

“…Using cooperative game theory, the proposed algorithm models the autoencoder as a coalition of interconnected units and links, where the Shapley value quantifies their individual contributions to overall performance. …”
Get full text

GlassBoost: A Lightweight and Explainable Classification Framework for Tabular Datasets by Ehsan Namjoo, Alison N. O’Connor, Jim Buckley, Conor Ryan

“…This paper introduces a novel XAI system designed for classification tasks on tabular data, which offers a balance between performance and interpretability. The proposed method, <i>GlassBoost</i>, first trains an XGBoost model on a given dataset and then computes gain scores, quantifying the average improvement in the model’s loss function contributed by each feature during tree splits. …”
Get full text

App-DDoS detection method using partial binary tree based SVM algorithm by Bin ZHANG, Zihao LIU, Shuqin DONG, Lixun LI

“…As it ignored the detection of ramp-up and pulsing type of application layer DDoS (App-DDoS) attacks in existing flow-based App-DDoS detection methods,an effective detection method for multi-type App-DDoS was proposed.Firstly,in order to fast count the number of HTTP GET for users and further support the calculation of feature parameters applied in detection method,the indexes of source IP address in multiple time windows were constructed by the approach of Hash function.Then the feature parameters by combining SVM classifiers with the structure of partial binary tree were trained hierarchically,and the App-DDoS detection method was proposed with the idea of traversing binary tree and feedback learning to distinguish non-burst normal flow,burst normal flow and multi-type App-DDoS flows.The experimental results show that compared with the conventional SVM-based and naïve-Bayes-based detection methods,the proposed method has more excellent detection performance and can distinguish specific App-DDoS types through subdividing attack types and training detection model layer by layer.…”
Get full text