2025 November - 53 articles
Monocular metric depth estimation (MMDE) aims to generate depth maps with an absolute metric scale from a single RGB image, which enables accurate spatial understanding, 3D reconstruction, and autonomous navigation. Unlike conventional monocular dept...
Modern web applications change frequently in response to user and market needs, making their testing challenging. Manual testing and automation methods often struggle to keep up with these changes. We propose an automated testing framework, AutoQALLM...
Early detection of plant diseases is key to ensuring food production, reducing economic losses, minimizing the use of agrochemicals, and maintaining the sustainability of the agricultural sector. Citrus plants, an important source of vitamin C, fiber...
Precise pore pressure prediction is highly essential for safe and effective drilling; however, the nonlinear and heterogeneous nature of the subsurface strata makes it extremely challenging. Conventional physics-based methods are not capable of handl...
Globally, potatoes are one of the major crops that significantly contribute to food security; hence, the field of machine learning has opened the gate for many advances in plant disease detection. For real-time agricultural applications, it has been...
Arabic natural language processing (NLP) has garnered significant attention in recent years due to the growing demand for automated text and Arabic-based intelligent systems, in addition to digital transformation in the Arab world. However, the uniqu...
The accurate recognition of cattle behaviours is crucial for improving animal welfare and production efficiency in precision livestock farming. However, existing methods pay limited attention to recognising behaviours under occlusion or those involvi...
Providing equitable, high-quality education to all children, including those with intellectual disabilities (ID), remains a critical global challenge. Traditional learning environments often fail to address the unique cognitive needs of children with...
This paper presents an Explainable Artificial Intelligence (XAI) framework for the automated generation of lesson plans aligned with Bloom’s Taxonomy. The proposed system addresses the dual challenges of accurate cognitive classification and pe...
Large language models (LLMs) such as GPT-4 are increasingly integrated into research, industry, and enterprise workflows, yet little is known about how input file formats shape their outputs. While prior work has shown that formats can influence resp...
Augmented reality (AR) offers a novel way to enrich museum visits by deepening engagement and enhancing learning. This study presents the development of a mobile application for the Abylkhan Kasteyev State Museum of Arts (Almaty, Kazakhstan), designe...
Risk assessment is critical for securing and sustaining operational resilience in cloud computing. Traditional approaches often rely on single-objective or subjective weighting methods, limiting their accuracy and adaptability to dynamic cloud condit...
Comprehensive highway scene understanding and robust traffic risk inference are vital for advancing Intelligent Transportation Systems (ITS) and autonomous driving. Traditional approaches often struggle with scalability and generalization, particular...
In the diagnosis of lung cancer, imaging findings of lung nodules are essential for benign and malignant classifications. Although numerous studies have investigated the classification of lung nodules, no method has been proposed for obtaining detail...
Deepfake technology, driven by advances in artificial intelligence (AI) and deep learning (DL), has become one of the foremost threats to digital trust and the authenticity of information. Despite the rapid development of deepfake detection methods,...
Investment in equity assets is characterized by high volatility, both in prices and returns, which poses a constant challenge for the efficient management of risk and profitability. In this context, investors continuously seek innovative strategies t...
This paper presents a novel Ripple Evolution Optimizer (REO) that incorporates adaptive and diversified movement—a population-based metaheuristic that turns a coastal-dynamics metaphor into principled search operators. REO augments a JADE-style...
This paper presents Multi_mil, a multilingual annotated corpus designed for the analysis of information operations in military discourse. The corpus consists of 1000 texts collected from social media and news platforms in Russian, Kazakh, and English...
In web-based services, users are often required to submit personal data, which may be shared with third parties. Although privacy regulations mandate the disclosure of intended recipients in privacy policies, this does not fully alleviate users&rsquo...
The integration of Artificial Intelligence (AI) systems into critical decision-making processes necessitates robust mechanisms to ensure trustworthiness, ethical compliance, and human oversight. This paper introduces trustSense, a novel assessment fr...
Sophisticated malware families exploit the openness of the Android platform to enable large-scale disruption, data exfiltration, and denial-of-service attacks, including the infiltration of IoT infrastructures. This systematic literature review exami...
With rapid advancements in large language models for natural language processing, their role in semantic-aware process mining is growing. We study semantics-aware process mining, where decisions must reflect both event logs and textual rules. We prop...
Currently, the increasing number of Internet of Things devices makes spectrum resource shortage prominent. Spectrum sensing technology can effectively solve this problem by conducting real-time monitoring of the spectrum. However, in practical applic...
The increasing demand for customized products has raised the significant challenges of increasing performance and reducing costs in the industry. Facing that demand requires operators to enhance their capabilities to cope with complexity, demanding s...
Achieving Artificial General Intelligence (AGI) requires a unified framework capable of modeling the full spectrum of intelligent behavior—from logical reasoning and sensory perception to emotional regulation and collective decision-making. Thi...
A surge in global connectivity has led to an increase in cyberattacks, creating a need for improved security. A promising area of research is using machine learning to detect these attacks. Traditional two-class machine learning models can be ineffec...
Efficient real-time computer vision-based passenger flow analysis is increasingly important for the management of intelligent transportation systems and smart cities. This paper presents the design and implementation of a system for real-time object...
Quantum machine learning (QML) integrates quantum computing with classical machine learning. Within this domain, QML-CQ classification tasks, where classical data is processed by quantum circuits, have attracted particular interest for their potentia...
Artificial Intelligence (AI) has revolutionized the way we think, perceive, and interact, delivering remarkable advances across domains ranging from computer vision and natural language processing to healthcare, power, finance, autonomy, and philosop...
This paper addresses the critical challenge of energy management for autonomous robots in the context of large-scale photovoltaic parks. The dynamic and vast nature of these environments, characterized by dense, structured rows of solar panels, intro...
Monitoring PM2.5 in mining areas is essential for air quality management; however, most studies focus on single-step forecasts, limiting timely decision making. This work addresses the need for accurate multi-step PM2.5 prediction to support proactiv...
Distributed denial of service (DDoS) attacks pose a serious risk to the operational stability of a network for companies, often leading to service disruptions and financial damage and a loss of trust and credibility. The increasing sophistication and...
The proliferation of sophisticated malware poses a persistent threat to cybersecurity. While visualizing malware as images enables the use of Convolutional Neural Networks, standard architectures are often inefficient and struggle with the high spati...
This paper presents the design and implementation of a vision-based score detection system tailored for smart IoT basketball applications. The proposed architecture leverages a compact, low-cost device comprising a high-resolution overhead camera and...
Irreducible polynomials are widely used in modern cryptography; however, algorithms for finding such polynomials remain quite complex and require significant computational resources. In this study, a new approach to finding irreducible equations over...
Memory forensics is an essential cybersecurity tool that comprehensively examines volatile memory to detect the malicious activity of fileless malware that can bypass disk analysis. Image-based detection techniques provide a promising solution by vis...
Maternal health care during labor requires the continuous and reliable monitoring of analgesic procedures, yet conventional systems are often subjective, indirect, and operator-dependent. Infrared thermography (IRT) offers a promising non-invasive ap...
Proficiency in machine learning (ML) and the associated computational math foundations have become critical skills for engineers. Required areas of proficiency include the ability to use available ML tools and the ability to develop new tools to solv...
Federated learning (FL), as a privacy-preserving distributed machine learning paradigm, demonstrates unique advantages in addressing data silo problems. However, the prevalent statistical heterogeneity (data distribution disparities) and system heter...
Building Information Modeling (BIM) is a transformative tool in Sustainable Design (SD), providing measurable benefits for efficiency, collaboration, and performance in architectural, engineering, and construction (AEC) practices. Despite its growing...
This article introduces an innovative hybrid methodology that integrates deterministic Mixed-Integer Linear Programming optimization with stochastic Agent-Based Simulation to address the PDP-TW. The approach is applied to real-world operational data...
Inconsistencies in Earth’s spinning, changes in calendar systems, etc., necessitate time being represented correspondingly. Date–time handling in programming involves specific challenges, including conflicts between calendars, time zone d...
Music plays an increasingly vital role in modern society, becoming a fundamental part of everyday life. Beyond entertainment, it contributes to emotional well-being by helping individuals express their feelings, process emotions, and find comfort dur...
Image restoration tasks such as deraining, deblurring, and dehazing are crucial for enhancing the environmental perception of autonomous vehicles and traffic systems, particularly for tasks like vehicle detection, pedestrian detection and lane line i...
The emergence of generative artificial intelligence (GAI) has significantly transformed higher education. As a linguistic assistant, GAI can promote equity and reduce barriers in academic writing. However, its widespread availability also raises ethi...
The classification performance of an inference model trained in a supervised manner depends substantially on the size and quality of the labeled training data. The characteristics of the underlying data distribution significantly impact the generaliz...
The growth of Agentic AI systems in Industrial Automation has brought forth new cybersecurity issues which in turn put at risk the reliability and integrity of these systems. In this study we look at the cybersecurity issues in industrial automation...
Traditional federated learning frameworks face significant challenges posed by non-independent and identically distributed (non-IID) data in the healthcare domain, particularly in multi-institutional collaborative gout staging prediction. Differences...
With the emergence of Industry 5.0 and explosive data growth, replica allocation has become a critical issue in edge computing systems. Current methods often focus on placing replicas on edge servers near terminals, yet this may lead to edge node ove...
Universities face continuous challenges in ensuring rapid and efficient communication during emergencies due to outdated, fragmented, and manual notification systems. This research presents the design, development, and implementation of a multiplatfo...
of 2
