Optimized Ensemble Deep Learning for Real-Time Intrusion Detection on Resource-Constrained Raspberry Pi Devices by Muhammad Bisri Musthafa, Samsul Huda, Tuy Tan Nguyen, Yuta Kodera, Yasuyuki Nogami

“…Building upon our previously developed stacked Long Short-Term Memory (LSTM) model integrated with ANOVA feature selection, we optimize it by integrating dual-stage model compression: pruning and quantization to create a lightweight model suitable for real-time inference on Raspberry Pi devices. …”
Get full text

Data driven decisions in education using a comprehensive machine learning framework for student performance prediction by Muhammad Nadeem Gul, Waseem Abbasi, Muhammad Zeeshan Babar, Abeer Aljohani, Muhammad Arif

“…This study applies eight advanced machine learning models-Decision Trees, Random Forest, Lasso, K-Nearest Neighbors, XGBoost, CatBoost, AdaBoost, and Gradient Boosting to analyze student performance based on demographic and academic features. …”
Get full text

A path aggregation network with deformable convolution for visual object detection by Chengming Rao, Zunhao Hu, QiMing Zhao, Min Shan, Li Mao

“…In this article, we propose a novel neck that can perform effective fusion of multi-scale features for a single-stage object detector. …”
Get full text

Manifold embeddings achieve comparable performance with multispectral imagery for time-series based land disturbance detection by Mengyao Li, Jianbo Qi, Su Ye, Qiao Wang

“…Two key findings emerge: (1) We developed a general UMAP-based dimensionality reduction model that works across global seasons, with manifold embeddings preserving time series coherence and exhibiting stable value ranges. (2) The embeddings achieved comparable performance to full-spectrum multispectral data in image prediction and disturbance detection with CCDC. …”
Get full text

Analysis of VAE-LSTM Performance in Detecting Anomalies in Average Daily Temperature Data in Jakarta 2000-2023 by INDRI RAMDANI, YENNI ANGRAINI, INDAHWATI INDAHWATI

“…The VAE-LSTM model identified all dates with significant temperature anomalies, including January 21, 2014, February 22, 2014, November 12, 2014, and February 9, 2015. …”
Get full text

Nighttime Vehicle Detection Algorithm Based on Improved YOLOv7 by Fan Zhang

“…Experiments on the BDD100K nighttime vehicle dataset show that E-YOLOv7 achieves an AP value of 94.9%, which is a 6.6% improvement over the original YOLOv7, with a significant increase in recall. The model also demonstrates strong real-time performance. …”
Get full text

Motives for choice of work in healthcare and individual performance of medical doctors working in public multispecialty hospitals in Warsaw by Malgorzata Chmielewska, Jakub Stokwiszewski, Justyna Markowska, Tomasz Hermanowski

“…ObjectiveThis study explores the relationship between the motives driving people to work in healthcare and the individual work performance of public hospital doctors. The results are analyzed in terms of changes necessary to improve work performance among medical practitioners.MethodsA cross-sectional study was conducted among 249 medical doctors from 22 randomly selected inpatient departments of multidisciplinary public hospitals in Warsaw. …”
Get full text

Multiresponse optimization applied to friction-stir processing to enhance wear and corrosion performance in Al–Si alloys by Denner Traiano, Silvia do Nascimento Rosa, Luciano Augusto Lourençato, Angel Sánchez Roca, Mario César Sánchez Orozco, Hipólito Domingo Carvajal Fals

“…The FSP tool, made of AISI H13 tool steel, features a concave shoulder and conical pin designed to induce severe plastic deformation. …”
Get full text

Winter Wheat Canopy Height Estimation Based on the Fusion of LiDAR and Multispectral Data by Hao Ma, Yarui Liu, Shijie Jiang, Yan Zhao, Ce Yang, Xiaofei An, Kai Zhang, Hongwei Cui

“…The model training results showed that the OP-RF model provided the best performance across all three growth stages of wheat. …”
Get full text

An Explainable Machine Learning Approach for IoT-Supported Shaft Power Estimation and Performance Analysis for Marine Vessels by Yiannis Kiouvrekis, Katerina Gkirtzou, Sotiris Zikas, Dimitris Kalatzis, Theodor Panagiotakopoulos, Zoran Lajic, Dimitris Papathanasiou, Ioannis Filippopoulos

“…Model performance was assessed using the coefficient of determination (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>) and RMSE, with XGBoost achieving the highest accuracy (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup><mspace width="3.33333pt"></mspace><mo>=</mo><mspace width="3.33333pt"></mspace><mn>0.9490</mn></mrow></semantics></math></inline-formula>, RMSE 888) and LightGBM being close behind (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup><mspace width="3.33333pt"></mspace><mo>=</mo><mspace width="3.33333pt"></mspace><mn>0.9474</mn></mrow></semantics></math></inline-formula>, RMSE 902), with both substantially exceeding the industry baseline model (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup><mspace width="3.33333pt"></mspace><mo>=</mo><mspace width="3.33333pt"></mspace><mn>0.9028</mn></mrow></semantics></math></inline-formula>, RMSE 1500). …”
Get full text

Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning by Shaojie Li, Zaixing Dong, Jianfeng Jin, Hucheng Pan, Zongqing Hu, Rui Hou, Gaowu Qin

“…The SVR model combined with multi‐objective genetic algorithm are successfully used to optimize mechanical properties of four extruded alloys from Mg‐Ca, Mg‐Ca‐Zn, Mg‐Ca‐Mn‐Sn, and Mg‐Ca‐Al‐Zn‐Mn series alloys, respectively, and the corresponding experimental results are in good agreement with the designed ones. …”
Get full text

Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection by Onur Polat, Ali Ayid Ahmad, Saadin Oyucu, Enes Algul, Ferdi Dogan, Ahmet Aksoz

“…The developed model identifies complex attacks in the network by taking advantage of the strengths of CNNs that reveal spatial features and LSTMs that detect temporal dependency. …”
Get full text

Performance of Textured Metallized Teflon Coverings with High Diffuse Reflectance Coefficient in Low Earth Orbit on ISS by Jacob Kleiman

Get full text

Small Object Detection in UAV Remote Sensing Images Based on Intra-Group Multi-Scale Fusion Attention and Adaptive Weighted Feature Fusion Mechanism by Zhe Yuan, Jianglei Gong, Baolong Guo, Chao Wang, Nannan Liao, Jiawei Song, Qiming Wu

“…Such modifications enhance the model’s ability to capture the minute features of small objects. …”
Get full text

A lightweight Xray-YOLO-Mamba model for prohibited item detection in X-ray images using selective state space models by Kai Zhao, Shufan Peng, Yujin Li, Tianliang Lu

“…Despite significant advancements in deep learning, challenges such as feature extraction, object occlusion, and model complexity remain. …”
Get full text

CO₂ Emission Prediction for Coal-Fired Power Plants by Random Forest-Recursive Feature Elimination-Deep Forest-Optuna Framework by Kezhi Tu, Yanfeng Wang, Xian Li, Xiangxi Wang, Zhenzhong Hu, Bo Luo, Liu Shi, Minghan Li, Guangqian Luo, Hong Yao

“…The results illustrated the enhancements in model performance and showed a significant improvement with a 0.12706 increase in R² and reductions in MSE and MAE by 81.70% and 36.88%, respectively, compared to the best performance of the traditional model. …”
Get full text

Underwater Side-Scan Sonar Target Detection: An Enhanced YOLOv11 Framework Integrating Attention Mechanisms and a Bi-Directional Feature Pyramid Network by Junhui Zhu, Houpu Li, Min Liu, Guojun Zhai, Shaofeng Bian, Ye Peng, Lei Liu

“…Additionally, an attention module is incorporated to enhance feature extraction from blurred images, thereby boosting the detection accuracy of the model. …”
Get full text

Enhancing Areca Nut Detection and Classification Using Faster R-CNN: Addressing Dataset Limitations with Haar-like Features, Integral Image, and Anchor Box Optimization by Yovi Pratama, Errissya Rasywir, Suyanti, Agus Siswanto, Fachruddin

“…While the integration of Haar-like features and integral images into faster R-CNN contributes to detection accuracy, the study also reveals that high-resolution images, precise annotations, and dataset scale significantly amplify model performance.…”
Get full text

Identifying microbial functional guilds performing cryptic organotrophic and lithotrophic redox cycles in anaerobic granular biofilms. by Zachary Flinkstrom, Samuel J Bryson, Bojan Pelivano, Pieter Candry, Kristopher A Hunt, Mari-Karoliina H Winkler

Get full text

Performance of predictive algorithms in estimating the risk of being a zero-dose child in India, Mali and Nigeria by Sebastian Bauhoff, John Tucker, Arpita Biswas

“…Region and measures of contact with the health system (antenatal care and birth in a facility) had the highest feature importance. Model performance decreased in the time between the data on which the model was trained and the data to which it was applied (test data). …”
Get full text