A Robust Image Encryption Scheme Based on Quantum Walks and Dynamic DNA for Secure Cloud Applications by Ahmed A. Abd El-Latif, May Almousa, Bassem Abd-El-Atty

“…Furthermore, advances in quantum computing pose a significant threat to traditional cryptosystems, including those used in cloud systems, as they may become vulnerable to quantum-based attacks. …”
Get full text

Bayesian Quantile Regression for Partial Functional Linear Spatial Autoregressive Model by Dengke Xu, Shiqi Ke, Jun Dong, Ruiqin Tian

“…When performing Bayesian modeling on functional data, the assumption of normality is often made on the model error and thus the results may be sensitive to outliers and/or heavy tailed data. …”
Get full text

Problematic Issues in Conducting Expert Examinations for the Calculation of Key Financial Indicators of Business Entities by Ye. M. Andrushchenko

“…The primary focus is on problematic issues that may arise for expert economists when conducting research related to the calculation of key financial indicators, the most significant of which is the impact of current legislation on the calculation algorithm itself. …”
Get full text

Optimizing energy and CO2 efficiency in last-mile delivery using hybrid fleet models by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte, Seyed Mojtaba Sajadi

“…Given that existing solutions like e-bikes or electric vans may not be feasible everywhere, this research evaluates different vehicle types under various urban delivery scenarios. …”
Get full text

Characterizing HIV-1 Tropism and Key Positions within the V3 Loop Using Random Forest Analysis by Karenn Evangelista Miranda, Letícia Martins Raposo

“…Due to the genetic diversity of HIV-1 subtypes, V3 loop sequences may vary in amino acid composition depending on tropism and subtype. …”
Get full text

Advancing multi-categorization and segmentation in brain tumors using novel efficient deep learning approaches by Nadenlla RajamohanReddy, G. Muneeswari

“…Background A brain tumor is the development of abnormal brain cells, some of which may progress to cancer. Early identification of illnesses and development of treatment plans improve patients’ quality of life and life expectancy. …”
Get full text

Multiclass semantic segmentation for prime disease detection with severity level identification in Citrus plant leaves by P. Dinesh, Ramanathan Lakshmanan

“…Due to technological advancements, image processing and Deep learning algorithms can now detect and classify plant diseases early on, which assists in preserving crop health and productivity. …”
Get full text

ANALYSIS OF STOICHIOMETRIC REGULARITIES LIMITING STATIONARY STATES OF REACTION-RECTIFICATION PROCESSES by M. A. Yakhyaev, Yu. A. Pisarenko, S. Serna-Loaiza, C. A. Cardona

“…In reaction-rectification processes, the conversion of the process, the rate of reaction and selectivity may be increased due to continuous withdrawal of the formed products from the reaction zone. …”
Get full text

Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine by Xinxi Gong, Yaozhong Zhu, Yanhai Wang, Enyang Li, Yuhao Zhang, Zilong Zhang

“…Initially, we optimize the coati optimization algorithm (COA) through inverse refraction learning and Levy flight strategy. …”
Get full text

Automatic detection of trapping events of postnatal piglets in loose housing pen: comparison of YOLO versions 4, 5, and 8 by Taeyong Yun, Jinsul Kim, Jinhyeon Yun, Tai-Won Um

“…This study employed three deep learning object recognition algorithms–– You Only Look Once (YOLO)v4-Tiny, YOLOv5s and YOLOv8s––followed by a performance analysis. …”
Get full text

Enhancing radiomics robustness using bayesian penalized likelihood PET reconstruction: application to Phantom and non-small cell lung cancer patient studies by Zahra Valibeiglou, Jalil Pirayesh Islamian, Yunus Soleymani, Saeed Farzanehfar, Farahnaz Aghahosseini, Neda Gilani, Arman Rahmim, Peyman Sheikhzadeh

“…Conclusions The BPL reconstruction algorithm may enhance the robustness of PET radiomics features, supporting their use in clinical settings for non-invasive diagnosis and staging. …”
Get full text

Deep Learning-Based Recurrence Prediction in HER2-Low Breast Cancer: Comparison of MRI-Alone, Clinicopathologic-Alone, and Combined Models by Seoyun Choi, Youngmi Lee, Minwoo Lee, Jung Hee Byon, Eun Jung Choi

Get full text

Safe transductive support vector machine by Haiyan Chen, Ying Yu, Yizhen Jia, Linghui Zhang

“…Since semi-supervised learning can use fewer labelled samples to train a better model, semi-supervised methods are becoming popular in data mining. As an important algorithm of semi-supervised support vector machines (S $ ^{3} $ VM), transductive support vector machine (TSVM) sometimes  may get worse models trained on both labelled samples and unlabelled samples than those trained only on labelled samples. …”
Get full text

A New Management Paradigm in the Digital Economy by E. I. Styazhkina

Get full text

Analysis of thermoelastic stresses in filament wound composite pressure vessels using evolutionary deep learning and many-objective optimisation by Dominik Vondráček, Zdeněk Padovec, Tomáš Mareš, Nirupam Chakraborti

“…Knowing the critical places of the pressure vessel may improve the designer’s decision during the development and design process.…”
Get full text

Data stream mining techniques for real-time monitoring and control of smart power grids in Kenya: challenges and opportunities by Cornelius Mutuku Mulevu, George Onyango Okeyo, Joseph Muliaro Wafula

Get full text

A Learning Probabilistic Boolean Network Model of a Manufacturing Process with Applications in System Asset Maintenance by Pedro Juan Rivera Torres, Chen Chen, Sara Rodríguez González, Orestes Llanes Santiago

Get full text

Springback Angle Prediction for High-Strength Aluminum Alloy Bending via Multi-Stage Regression by Enzhi Gao, Di Xue, Yiming Li

Get full text

Fault Detection System of Photovoltaic Based on Artificial Neural Network by Ali Salman Zamzeer, Mansour S. Farhan, Haider TH. ALRikabi

Get full text

Evolving Hybrid Deep Neural Network Models for End-to-End Inventory Ordering Decisions by Thais de Castro Moraes, Jiancheng Qin, Xue-Ming Yuan, Ek Peng Chew

“…However, current approaches predominantly rely on feed-forward networks, which may have difficulty capturing temporal correlations in time series data and identifying relevant features, resulting in less accurate predictions. …”
Get full text