KronNet a lightweight Kronecker enhanced feed forward neural network for efficient IoT intrusion detection by Saeed Ullah, Junsheng Wu, Mian Muhammad Kamal, Abdul Khader Jilani Saudagar

“…The model operates with minimal computational overhead, utilizing 5,074 parameters (19.82 KB) for CICIoT2023 and 4,703 parameters (18.37 KB) for BoT-IoT, with inference times of 0.209 ms and 0.208 ms. …”
Get full text

A method for IoT devices test case generation using language models by Sumit Kumar, Kiran Napte, Ruchi Rani, Sanjeev Kumar Pippal

Get full text

A Deep Learning-Based Diagnostic Framework for Shaft Earthing Brush Faults in Large Turbine Generators by Katudi Oupa Mailula, Akshay Kumar Saha

Get full text

Reliability of using CBCT scans to derive the parameters of the facial canal by Shavana Govender, Tania Hanekom, René Human-Baron

“…The purpose of this study was to evaluate the reliability and accuracy of deriving the parameters from the FC on cone-beam computed tomography (CBCT) scans by comparing it to FC morphometric analyses of dissected heads. …”
Get full text

An advanced deep learning method for pepper diseases and pests detection by Xuewei Wang, Jun Liu, Qian Chen

“…Comparative experiments highlight YOLO-Pepper’s superiority over nine benchmark models, particularly in detecting small and occluded targets. By addressing computational inefficiencies and refining small object detection capabilities, YOLO-Pepper provides robust technical support for intelligent agricultural monitoring systems, making it a highly effective tool for early disease detection and integrated pest management in commercial greenhouse operations.…”
Get full text

An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

Get full text

Improving air quality prediction using hybrid BPSO with BWAO for feature selection and hyperparameters optimization by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

“…The study concludes that feature selection and hyperparameter optimization significantly improve model accuracy and computational efficiency, offering a robust framework for air quality forecasting.…”
Get full text

Design of Interface ASIC with Power-Saving Switches for Capacitive Accelerometers by Juncheng Cai, Yongbin Cai, Xiangyu Li, Shanshan Wang, Xiaowei Zhang, Xinpeng Di, Pengjun Wang

Get full text

Federated Learning Framework Based on Distributed Storage and Diffusion Model for Intrusion Detection on IoT Networks by Ricardo Manzano, Marzia Zaman, Darshana Upadhyay, Nishith Goel, Srinivas Sampalli

Get full text

Classification of tomato leaf disease using Transductive Long Short-Term Memory with an attention mechanism by Aarthi Chelladurai, D.P. Manoj Kumar, S. S. Askar, Mohamed Abouhawwash, Mohamed Abouhawwash

“…However, the usage of a single architecture does not provide the best results due to the limited computational ability and classification complexity. …”
Get full text

An Integrative Framework for Healthcare Recommendation Systems: Leveraging the Linear Discriminant Wolf–Convolutional Neural Network (LDW-CNN) Model by Vedna Sharma, Surender Singh Samant, Tej Singh, Gusztáv Fekete

Get full text

Deep hybrid architecture with stacked ensemble learning for binary classification of retinal disease by Priyadharsini C, Asnath Victy Phamila Y

Get full text

Laser sintering of metal powders: failure analysis and implementation of solutions for aluminium and stainless steel parts by Valentin Endre Szabó, Krisztián Kun

Get full text

Forecasting dengue across Brazil with LSTM neural networks and SHAP-driven lagged climate and spatial effects by Xiang Chen, Paula Moraga

Get full text

Brazilin from Caesalpinia sappan L. as a Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Inhibitor: Pharmacophore-Based Virtual Screening, In Silico Molecular Docking, and In... by Muhammad Iqbal, Nur Hasanah, Aimee Detria Arianto, Widya Dwi Aryati, Meidi Utami Puteri, Fadlina Chany Saputri

Get full text

Semi-supervised Federated Learning for Digital Twin 6G-enabled IIoT: A Bayesian estimated approach by Yuanhang Qi, M. Shamim Hossain

Get full text

An optimized generative adversarial network for state estimator in electric power systems by Ying-Yi Hong, Yen-Cheng Wang, Weina Zhang

“…Traditional state estimation methods typically rely on criteria like the maximum likelihood criterion, weighted least-squares criterion, or Kalman filter to compute these states. However, these conventional methods may be susceptible to issues such as noise, false readings, or missing measurements. …”
Get full text

Efficient Generative-Adversarial U-Net for Multi-Organ Medical Image Segmentation by Haoran Wang, Gengshen Wu, Yi Liu

“…Manual labeling of lesions in medical image analysis presents a significant challenge due to its labor-intensive and inefficient nature, which ultimately strains essential medical resources and impedes the advancement of computer-aided diagnosis. This paper introduces a novel medical image-segmentation framework named Efficient Generative-Adversarial U-Net (EGAUNet), designed to facilitate rapid and accurate multi-organ labeling. …”
Get full text

Diagnosing epileptic seizures using combined features from independent components and prediction probability from EEG data by Madiha Khalid, Ali Raza, Adnan Akhtar, Furqan Rustam, Julien Brito Ballester, Carmen Lili Rodriguez, Isabel de la Torre Díez, Imran Ashraf

Get full text

Application of Machine Learning for Predictive Analysis and Management of Mediterranean-Farmed Fish Mortalities: A Risk Management Case Study Using Apache Spark by Marios C. Gkikas, Dimitris C. Gkikas, Gerasimos Vonitsanos, John A. Theodorou, Spyros Sioutas

Get full text