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Subjects / keywords: blood glucose; lifestyle recommendation; patient; random forest; XGBoost

Digital technologies have revolutionized studying, analyzing, and interpreting human culture, history, and society. Digital humanities (DH) combine traditional disciplines such as literature, history, and philosophy with...

This thesis, entitled €High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study€ investigates the computational issues related to the resolution of linear systems o...

Abstract The catalytic decomposition of ammonia under mild conditions is a promising route for green hydrogen production. However, conventional dissociative ammonia decomposition pathways over metal sites are suffering f...

"A rapid and sensitive analytical method for the trace determination of aflatoxin M1 in domestic waters was developed using chitosan as a sorbent and HPLC with fluorescence detection (HPLC-FLD). Computational simulations...

ABSTRACT Background and Aims De novo drug design is the process of generating novel lead compounds that possess desirable pharmacological activities and optimal physicochemical properties for therapeutic development. In ...

This study employs computational intelligence techniques – gene expression programming (GEP), back-propagation neural network (BPNN), support vector regression (SVR) and linear regression (LR)–to model the quantitati...

Abstract Semiconductor lithography, a pivotal process in integrated circuit (IC) fabrication, accounts for approximately 30% of production costs and faces significant challenges as feature sizes shrink to sub-nanometer s...

In recent years, generative artificial intelligence represented by large language models (LLMs) and multimodal large language models (MLLMs) has achieved remarkable progress. These ultra-large-scale and complex models im...

Abstract In the power operation scenarios, there are problems such as large differences in target scales, small targets susceptible to occlusion, and limited computational resources for edge devices. This leads to insuff...

Abstract Globally, shrimp aquaculture is a vital source of food, but disease outbreaks present serious economic challenges. Traditional diagnostic techniques, such as visual inspection and polymerase chain reaction (PCR)...

Abstract The importance of fear level detection in affective computing using physiological signals has not been extensively explored. Accurately detecting fear responses facilitates real-time emotional monitoring and imp...

Abstract Advances in AI have transformed the traditional Internet of Things (IoT) into smarter, more versatile next-generation devices. Enhanced connectivity among sensors, actuators, and appliances boosts data availabil...

Traditional malware detection techniques frequently fail to detect and stop malicious activity in an era where cyber threats are becoming more complex. Any software that enters a computer system without the administrator...

Abstract Parkinson’s Disease (PD) is a progressive neurodegenerative disorder that causes motor and cognitive impairments, affecting approximately 1% of individuals over 60 years of age. Speech impairments are among th...

Global food security relies heavily on rice production, which is continuously threatened by crop diseases. Although deep learning (DL) models have demonstrated strong diagnostic performance, their high computational and ...

ABSTRACT Bio‐inspired optimisation methods have been widely applied to complex real‐world problems, particularly in low‐carbon power and energy systems, where optimisation tasks often involve high‐dimensional, co...

Paracetamol (PCM) is extensively used for the treatment of various diseases and is frequently released into aquatic environments, resulting in considerable environmental concerns. In the current study, UV, UV/H2O2, and p...

The performance of lithium-ion batteries is critical across a range of applications, including portable devices, electric vehicles, and energy storage systems. Effective diagnostics of these battery systems require evalu...

Abstract Medical images are inherently high-resolution and contain locally varying structures that are crucial for diagnosis. Efficient compression of such data must therefore preserve diagnostic fidelity while minimizin...

Anaerobic co-digestion of livestock waste presents a viable approach for addressing environmental challenges and reducing greenhouse gas emissions in semi-urban and rural contexts. This study focuses on the development o...

Drowsiness poses significant risks in safety-critical activities such as driving, industrial operations, and online learning. While advanced deep learning models (e.g., CNN-LSTM hybrids) achieve high accuracy in driver d...

Gradient-based optimization offers significant efficiency advantages for wind turbine blade design, but its application has often been limited by the cost and accuracy of finite-difference derivative calculations, especi...

In recent years, the frequency and complexity of financial fraud have been rising and have become an urgent challenge for the global financial system. Traditional rule-based detection methods struggle to cope with new ty...