Application of Machine Learning Techniques for Predicting Heating Coil Performance in Building Heating Ventilation and Air Conditioning Systems by Adam Nassif, Pasidu Dharmasena, Nabil Nassif

“…Bagging offered the best balance between outlier robustness and pattern recognition, while neural networks showed strong capability in capturing complex relationships. …”
Get full text

Research into the Application of ResNet in Soil: A Review by Wenjie Wu, Lijuan Huo, Gaiqiang Yang, Xin Liu, Hongxia Li

“…ResNet outperforms traditional methods by effectively mitigating the vanishing gradient problem, enabling deeper network training, enhancing feature extraction, and improving accuracy in complex pattern recognition tasks. …”
Get full text

Web-Biometrics for User Authenticity Verification in Zero Trust Access Control by Taisho Sasada, Yuzo Taenaka, Youki Kadobayashi, Doudou Fall

Get full text

Three-Dimensional Analysis of Seepage in Fractured Rock Masses and Evaluation of the Accuracy of Empirical Methods for Predicting Permeability in Cutoff Walls: A Case Study of Cham... by Alireza Baghbanan, Masoud Dararbi, Amirhosein Momeni, Ahmad Rahmani Shahraki, Amin Azhari

“…This study focuses on the investigation of the permeability of fractured rock masses and the design of a cutoff wall using numerical modeling techniques. The fracture network was modeled using the discrete element method (DEM) in the 3DEC software, considering the joint patterns specific to the region. …”
Get full text

Network and systems biology approaches help investigate gene regulatory interactions between Salmonella disease and host in chickens: Model‐based in silico evidence combined with g... by Reza Tohidi, Hoda Javaheri Bargourooshi, Arash Javanmard

“…The role of these promising biomarkers in our networks against SE susceptibility is essentially confirmed by these results. …”
Get full text

Probabilistic forecasting of renewable energy and electricity demand using Graph-based Denoising Diffusion Probabilistic Model by Amir Miraki, Pekka Parviainen, Reza Arghandeh

Get full text

A neuronal imaging dataset for deep learning in the reconstruction of single-neuron axons by Liya Li, Liya Li, Ying Hu, Ying Hu, Xiaojun Wang, Pei Sun, Tingwei Quan

“…To address these challenges, we propose a distance field-supervised segmentation network designed to enhance image signals effectively. …”
Get full text

LSTM model to predict missing data of dissolved oxygen in land-based aquaculture farm by Sang-Yeon Lee, Deuk-Young Jeong, Jinseo Choi, Seng-Kyoun Jo, Dae-Heon Park, Jun-Gyu Kim

Get full text

De Novo Design of Large Polypeptides Using a Lightweight Diffusion Model Integrating LSTM and Attention Mechanism Under Per-Residue Secondary Structure Constraints by Sisheng Liao, Gang Xu, Li Jin, Jianpeng Ma

“…By integrating a lightweight LSTM-attention neural network as the denoiser within a diffusion framework, PPD offers an innovative and efficient approach to polypeptide generation. …”
Get full text

Combination of artificial intelligence endoscopic diagnosis and Kimura‐Takemoto classification determined by endoscopic experts may effectively evaluate the stratification of gastr... by Kumiko Kirita, Seiji Futagami, Ken Nakamura, Shuhei Agawa, Nobue Ueki, Kazutoshi Higuchi, Mayu Habiro, Rie Kawawa, Yusuke Kato, Tomohiro Tada, Katsuhiko Iwakiri

“…The trained neural network generated a continuous number between 0 and 1 for gastric atrophy. …”
Get full text

Optimizing Remote Sensing Image Retrieval Through a Hybrid Methodology by Sujata Alegavi, Raghvendra Sedamkar

“…Low-level features are extracted using the modified Multiscale Multiangle Completed Local Binary Pattern (MSMA-CLBP) algorithm to capture local contexture features, while high-level features are obtained through a hybrid CNN structure combining pretrained networks (Alexnet, Caffenet, VGG-S, VGG-M, VGG-F, VGG-VDD-16, VGG-VDD-19) and a fully connected dense network. …”
Get full text

Forecasting arctic sea ice extent trend using time series models: NNAR, SARIMA and SARIMAX using the data prior to the COVID-19 pandemic by Benoit Ahanda, Türkay Yolcu, Rachel Watson

“…Abstract This research paper aims to examine the patterns of Arctic sea ice extent (ASIE) between 1979 and 2020 by using monthly data acquired from NSIDC. …”
Get full text

International Natural Uranium Price Prediction Based on TF-CNN-BiLSTM Model by YANG Jingzhe, XUE Xiaogang

“…The dataset was split into training (80%) and testing (20%) sets to evaluate the model’s performance. The proposed TF-CNN-BiLSTM model was designed with three core modules: 1) a Transformer encoder to capture long-term global dependencies via self-attention mechanisms; 2) a 1D CNN layer to extract localized price fluctuations; 3) a BiLSTM network to model bidirectional temporal relationships. …”

Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A Survey by Ghalib Ahmed Salman, Inas Jawad Kadhim, Ahmed Husham Al-Badri

“…FR applications relying on Artificial Neural Network (ANN) techniques have recorded higher accuracy rates in diagnosing facial diseases. …”
Get full text

A Unified Approach to Voice Classification: Leveraging Spectrograms, Mel Spectrograms, and Statistical Features by Muhammad Talha, Huma Ghafoor, Seung Yeob Nam

“…This study presents a multi-input neural network architecture for voice classification that integrates two parallel convolutional neural networks (CNNs) for spectrogram and Mel spectrogram images, along with a fully connected dense network for six handpicked numerical statistical features from time domain signal. …”
Get full text

Geographical feature and method factors significantly influence the reliability of ecological source information transmission at multi-scale by Kai Li, Wei Wu, Shiqi Tian, Linjuan Li, Zhe Li, Yue Cao

“…We employed Morphological Spatial Pattern Analysis (MSPA) and Comprehensive Evaluation (CE) methods to identify ecological sources across different extents and grain sizes, while analyzing the influence of various factors on information transmission. …”
Get full text

Improving the Performance of Charge Trapping Memtransistor as Synaptic Device by Ti-Doped HfO₂ by Yu-Che Chou, Wan-Hsuan Chung, Chien-Wei Tsai, Chin-Ya Yi, Chao-Hsin Chien

“…We used NeuroSim simulator with multilayer perceptron and convolutional neural network models to evaluate the pattern recognition accuracy of neural network hardware accelerator using CTMTs as synaptic devices and benchmarked the performance of our CTMT with those of other types of synaptic devices.…”
Get full text

State of health prediction of lithium-ion batteries in charging chambers based on multi-modal deep learning by ZHAO Yinghua, CHEN Anbi, ZHANG Zengyu, LI Wenzhong, HAN Yu

“…A multi-modal deep learning network model, TCN-BiLSTM-Transformer, was constructed, leveraging a multi-level feature extraction mechanism for efficient processing of temporal signals. …”
Get full text

A map of human protein interactions derived from co‐expression of human mRNAs and their orthologs by Arun K Ramani, Zhihua Li, G Traver Hart, Mark W Carlson, Daniel R Boutz, Edward M Marcotte

“…Abstract The human protein interaction network will offer global insights into the molecular organization of cells and provide a framework for modeling human disease, but the network's large scale demands new approaches. …”
Get full text

Predictive modeling and optimization of noise emissions in a palm oil methyl ester-fueled diesel engine using response surface methodology and artificial neural network integrated... by J.M. Zikri, M.S.M. Sani, M.F.F.A. Rashid, J. Muriban, G.S. Prayogo

“…This research examines the predictive performance of two modeling techniques—Response Surface Methodology (RSM) and an Artificial Neural Network enhanced by a Genetic Algorithm (ANN-GA)—in relation to noise emission levels from a single-cylinder diesel engine running on palm oil methyl ester (POME). …”
Get full text