Hybrid Quantum Cycle Generative Adversarial Network for Small Molecule Generation by Matvei Anoshin, Asel Sagingalieva, Christopher Mansell, Dmitry Zhiganov, Vishal Shete, Markus Pflitsch, Alexey Melnikov

“…This work develops an application of hybrid quantum generative models based on the integration of parameterized quantum circuits into known molecular generative adversarial networks and proposes quantum cycle architectures that improve model performance and stability during training. …”
Get full text

On the Extrapolation of Generative Adversarial Networks for Downscaling Precipitation Extremes in Warmer Climates by Neelesh Rampal, Peter B. Gibson, Steven Sherwood, Gab Abramowitz

“…We assess the extrapolation capabilities of a deterministic Convolutional Neural Network baseline and a Generative Adversarial Network (GAN) built with this baseline, trained to predict daily precipitation simulated by a Regional Climate Model (RCM) over New Zealand. Both approaches emulate future changes in annual mean precipitation well, when trained on historical data, though training on a future climate improves performance. …”
Get full text

Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies by Leonidas Theodorakopoulos, Aristeidis Karras, Alexandra Theodoropoulou, Georgios Kampiotis

“…Our findings ultimately inform practitioners about system efficiencies and limitations, but also the recent advances in hardware accelerators and algorithmic improvements aimed at shaping the new graph processing frontier in diverse technology domains.…”
Get full text

Advanced Brain Tumor Segmentation With a Multiscale CNN and Conditional Random Fields by Ala Guennich, Mohamed Othmani, Hela Ltifi

“…The use of high-precision automatic algorithms for segmenting brain tumors has the potential to improve disease diagnosis, treatment monitoring, and large-scale pathological studies. …”
Get full text

Enhancing Visual Perception in Immersive VR and AR Environments: AI-Driven Color and Clarity Adjustments Under Dynamic Lighting Conditions by Maryam Abbasi, Paulo Váz, José Silva, Pedro Martins

“…Future work will focus on extending the model’s capability to handle more complex lighting scenarios.…”
Get full text

Charting the path forward: CT image quality assessment - an in-depth review by Siyi Xun, Qiaoyu Li, Xiaohong Liu, Pu Huang, Guangtao Zhai, Yue Sun, Peter H. N. de With, Mingxiang Wu, Tao Tan

“…At present, Artificial intelligence (AI)-based CT-IQA is becoming a notable trend. It helps improve the accuracy of CT scanning equipment and the performance of CT system reconstruction algorithms, and provides a new idea for CT image processing algorithms. …”
Get full text

Hybrid ML/FWI method using GPR data to evaluate the tack coat characteristics in pavements: Experimental validation by Grégory Andreoli, Amine Ihamouten, Franziska Schmidt, Mai Lan Nguyen, David Souriou, Xavier Dérobert

“…These experiments serve to validate the performance improvements of various classification and regression SVM/SVR algorithms when adding the dielectric permittivity of the wearing course. …”
Get full text

Twitter Sentiment Classification towards Telecommunication Provider Users in Indonesia by Fernanda Mulya Syah Putra, Sindhu Rakasiwi, Noval Ariyanto

“…By applying machine learning algorithms such as Naïve Bayes and Support Vector Machine (SVM), this research analyzes customer perceptions of telecommunication service providers in Indonesia. …”
Get full text

Data-Driven Diagnostics for Pediatric Appendicitis: Machine Learning to Minimize Misdiagnoses and Unnecessary Surgeries by Deborah Maffezzoni, Enrico Barbierato, Alice Gatti

“…In this study, we explore the potential of machine learning (ML) algorithms to improve the diagnosis, management, and prediction of appendicitis severity in pediatric patients. …”
Get full text

A human pose estimation network based on YOLOv8 framework with efficient multi-scale receptive field and expanded feature pyramid network by Shaobin Cai, Han Xu, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…First, the EMRF module is employed to further enhance the model’s feature representation capability. Second, the EFPN optimizes cross-level information exchange and improves multi-scale data integration. …”
Get full text

Advancements in artificial intelligence for atopic dermatitis: diagnosis, treatment, and patient management by Fang Cao, Yujie Yang, Cui Guo, Hui Zhang, Qianying Yu, Jing Guo

“…Despite challenges in data privacy and model transparency, the potential of artificial intelligence in advancing AD care is enormous, bringing the future to precision medicine and improving patient outcomes. …”
Get full text

Integrating AIoT Technologies in Aquaculture: A Systematic Review by Fahmida Wazed Tina, Nasrin Afsarimanesh, Anindya Nag, Md Eshrat E. Alahi

“…In conclusion, while AIoT presents substantial opportunities for enhancing aquaculture practices, successful implementation will depend on overcoming challenges related to scalability, cost, and technical expertise, improving models’ adaptability, and ensuring environmental sustainability.…”
Get full text

Artificial Intelligence-Assisted Selection Strategies in Sheep: Linking Reproductive Traits with Behavioral Indicators by Ebru Emsen, Muzeyyen Kutluca Korkmaz, Bahadir Baran Odevci

“…The integration of accelerometers, GPS systems, and computer vision models enables continuous, non-invasive monitoring, leading to earlier detection of reproductive events and greater breeding precision. …”
Get full text

AEM-D3QN: A Graph-Based Deep Reinforcement Learning Framework for Dynamic Earth Observation Satellite Mission Planning by Shuo Li, Gang Wang, Jinyong Chen

“…These features are then encoded into a reinforcement learning model that dynamically optimizes scheduling policies under multiple resource constraints. …”
Get full text

Ant Colony Optimization Using Common Social Information and Self-Memory by Yoshiki Tamura, Tomoko Sakiyama, Ikuo Arizono

“…We apply the existing ACO algorithms and ASIM to some TSP benchmarks and compare the ability to solve TSP.…”
Get full text

Machine Learning Applications in Gray, Blue, and Green Hydrogen Production: A Comprehensive Review by Xuejia Du, Shihui Gao, Gang Yang

“…Among these, green hydrogen—particularly via water electrolysis and biomass gasification—received the most attention, reflecting its central role in decarbonization strategies. ML algorithms such as artificial neural networks (ANNs), random forest (RF), and gradient boosting regression (GBR) have been widely applied to predict hydrogen yield, optimize operational conditions, reduce emissions, and improve process efficiency. …”
Get full text

Security-centric node identification in complex networks by Lanying Liu, Ning Du, Duyong Sheng

“…To achieve this, we develop a mathematical model to compute SC, introduce efficient algorithms for identifying critical nodes, and implement an incremental update mechanism to enhance adaptability in real-time networks. …”
Get full text

Advancements in Parkinson’s Disease Diagnosis: A Comprehensive Survey on Biomarker Integration and Machine Learning by Ruchira Pratihar, Ravi Sankar

“…This comprehensive review explores the advancements in machine learning algorithms in the diagnosis of Parkinson’s disease (PD) utilizing different biomarkers. …”
Get full text

Fully automated multicolour structured illumination module for super-resolution microscopy with two excitation colours by Haoran Wang, Peter T. Brown, Jessica Ullom, Douglas P. Shepherd, Rainer Heintzmann, Benedict Diederich

“…This setup offers up to 1.55-fold improvement in lateral resolution over wide-field microscopy. …”
Get full text

Leveraging AI for Sustainable Energy Development in Solar Power Plants Operating Under Shading Conditions by Farhad Khosrojerdi, Stéphane Gagnon, Raul Valverde

“…This paper demonstrates how AI-based control systems can improve energy output in a solar power plant under shading conditions. …”
Get full text