A Deep Learning Method for Photovoltaic Power Generation Forecasting Based on a Time-Series Dense Encoder by Xingfa Zi, Feiyi Liu, Mingyang Liu, Yang Wang

“…Deep learning has become a widely used approach in photovoltaic (PV) power generation forecasting due to its strong self-learning and parameter optimization capabilities. In this study, we apply a deep learning algorithm, known as the time-series dense encoder (TiDE), which is an MLP-based encoder–decoder model, to forecast PV power generation. …”
Get full text

Transduction of γδ T cells with Baboon envelope pseudotyped lentiviral vector encoding chimeric antigen receptors for translational and clinical applications by Lorraine Pinot, Lorraine Pinot, Aylin Saßor, Aylin Saßor, Nina Möker, Congcong Zhang, Els Verhoeyen, Els Verhoeyen, José Villacorta Hidalgo, Rimas J. Orentas

Get full text

SVEA: an accurate model for structural variation detection using multi-channel image encoding and enhanced AlexNet architecture by Taixing Qiu, Jiawei Li, Yan Guo, Limin Jiang, Jijun Tang

“…The model demonstrates high accuracy, outperforming existing methods by approximately 4%, while also identifying areas for further optimization.…”
Get full text

Automatic Brain Tumor Segmentation: Advancing U-Net With ResNet50 Encoder for Precise Medical Image Analysis by Shoffan Saifullah, Rafal drezewski, Anton Yudhana, Andiko Putro Suryotomo

“…This study presents a novel ResUNet50-based approach, integrating ResNet50 as an encoder within the U-Net framework to achieve robust and precise segmentation. …”
Get full text

Analysis method combining improved AE algorithm and signal reconstruction in mechanical faults by Zhenhua Niu

Get full text

Power–Load Relationship of Bench Press, Ballistic Bench Press, and Prone Bench Pull in International Medal-Winning Canoeists and Kayakers by Oscar Crisafulli, Matteo Fortunati, Tiziano Gemelli, Massimiliano Febbi, Patrik Drid, Stefano Ramat, Giuseppe D’Antona

Get full text

Research on manufacturing quality improvement based on product gene evaluation method and a meta-heuristic algorithm with hybrid encoding scheme by Wenxiang Xu, Chao Wang, Shimin Xu, Junyong Liang, Dezheng Liu, Baigang Du

“…According to the data obtained by different components and algorithms, the search ability, speed of convergence of H-IGA-IABC are better than that of other components and algorithms, especially in solving large-scale problems. Compared with the solution before optimization, the quality evaluation results and other indicators of the solutions after optimization are significantly better. …”
Get full text

Pneumothorax detection and segmentation from chest X-ray radiographs using a patch-based fully convolutional encoder-decoder network by Jakov Ivan S. Dumbrique, Jakov Ivan S. Dumbrique, Reynan B. Hernandez, Reynan B. Hernandez, Juan Miguel L. Cruz, Ryan M. Pagdanganan, Prospero C. Naval

“…This architecture utilizes a patch-based encoder-decoder structure with skip connections to effectively combine high-level and low-level features. …”
Get full text

Application of the Bidirectional Encoder Representations from Transformers Model for Predicting the Abbreviated Injury Scale in Patients with Trauma: Algorithm Development and Vali... by Jun Tang, Yang Li, Keyu Luo, Jiangyuan Lai, Xiang Yin, Dongdong Wu

“…We mainly selected the patient’s diagnostic information, injury description, cause of injury, injury region, injury types, and present illness history as the key feature inputs. We used a robust optimization Bidirectional Encoder Representations from Transformers (BERT) pretraining method to embed these features and constructed a prediction model based on BERT. …”
Get full text

Lower Limb Torque Prediction for Sit-To-Walk Strategies Using Long Short-Term Memory Neural Networks by Chamalka Kenneth Perera, Alpha. A. Gopalai, Darwin Gouwanda, Siti. A. Ahmad, Pei-Lee Teh

“…Model inputs were hip and knee angles with horizontal center of mass velocity, while windowing allowed the LSTMs to dynamically adapt to real-time changes in STW transitions. The encoder-decoder LSTM showcased optimal performance with robust recognition of temporal features. …”
Get full text

Using BERT and ZFNet/ELM optimized by improved Orca optimization algorithm for sentiment analysis by Jun Yang, Jafar Safarzadeh

“…Then, the data were inserted into ZFNet/ELM, which was optimized by Improved Orca Optimization Algorithm (IOPA). …”
Get full text

Fed-DPSDG-WGAN: Differentially Private Synthetic Data Generation for Loan Default Prediction via Federated Wasserstein GAN by Padmaja Ramachandra, Santhi Vaithiyanathan

Get full text

Impact of B18R-Encoding Messenger Ribonucleic Acid Co-Delivery on Neutralizing Antibody Production in Self-Amplifying Messenger Ribonucleic Acid Vaccines by Yutao Wang, Lei Li, Min Liang, Gan Liu, Yinying Lu

“…Finally, we developed a saRNA-based COVID-19 vaccine and achieved superior immune protection in mice compared to mRNA vaccine by co-delivering the B18R-encoding mRNA. …”
Get full text

Enhancing image retrieval through optimal barcode representation by Rasa Khosrowshahli, Farnaz Kheiri, Azam Asilian Bidgoli, H. R. Tizhoosh, Masoud Makrehchi, Shahryar Rahnamayan

“…Abstract Data binary encoding has proven to be a versatile tool for optimizing data processing and memory efficiency in various machine learning applications. …”
Get full text

Optimal Res-UNET architecture with deep supervision for tumor segmentation by Rahman Maqsood, Fazeel Abid, Jawad Rasheed, Jawad Rasheed, Jawad Rasheed, Onur Osman, Shtwai Alsubai

“…Future studies should consider the broader application of optimized U-Net variants across other medical imaging segmentation tasks.…”
Get full text

Survey on video image reconstruction method based on generative model by Yanwen WANG, Weimin LEI, Wei ZHANG, Huan MENG, Xinyi CHEN, Wenhui YE, Qingyang JING

“…Traditional video compression technology based on pixel correlation has limited performance improvement space, semantic compression has become the new direction of video compression coding, and video image reconstruction is the key link of semantic compression coding.First, the video image reconstruction methods for traditional coding optimization were introduced, including how to use deep learning to improve prediction accuracy and enhance reconstruction quality with super-resolution techniques.Second, the video image reconstruction methods based on variational auto-encoders, generative adversarial networks, autoregressive models and transformer models were discussed emphatically.Then, the models were classified according to different semantic representations of images.The advantages, disadvantages, and applicable scenarios of various methods were compared.Finally, the existing problems of video image reconstruction were summarized, and the further research directions were prospected.…”
Get full text

Using artificial intelligence methods for the optimal synthesis of reversible networks by Taras Kyryliuk, Mykhailo Palahuta, Vitaly Deibuk

“…The research synthesized optimal reversible circuits based on reversible gates using evolutionary algorithms and compare them with existing analogues. …”
Get full text

Comparative analysis of chloroplast genomes and phylogenetic analysis of Vitex by XIU Zhiying1, ZHAO Yanling1, CHENG Yongqin2, JIA Yun3, YANG Yanci1*

Get full text

Convolutional Edge Constraint-Based U-Net for Salient Object Detection by Le Han, Xuelong Li, Yongsheng Dong

Get full text

Noise Robustness of Quantum Relaxation for Combinatorial Optimization by Kentaro Tamura, Yohichi Suzuki, Rudy Raymond, C. Hiroshi Watanabe, Yuki Sato, Ruho Kondo, Michihiko Sugawara, Naoki Yamamoto

“…In this article, we numerically demonstrate that the mean approximation ratio of the (3, 1)-QRAC Hamiltonian, i.e., the Hamiltonian utilizing the encoding of three bits into one qubit by QRAC, is less affected by noise compared with the conventional Ising Hamiltonian used in the quantum annealer and the quantum approximate optimization algorithm. …”
Get full text