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Advances in Engineering and Intelligence Systems
Scopus
ISSN 2821-0263 · Bilijipub publisher · 154 articles in the index
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Hybrid Feature-Based Two-Stage Framework for Audio Deepfake Detection and Generative Model Attribution
Rapid advances in technology have made it difficult to distinguish fake voices from natural human voices, bringing serious security risks such as fraud and manipulation. While most studies in the current literature focus solely on binary classifications that question the authenticity of the voice…
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Obtaining Suitable Outcomes by Combining the Radial Basis Function with A Novel Optimizer for Predicting Unconfined Compressive Strength
This study introduces a novel approach for predicting the Unconfined Compressive Strength (UCS) of soil materials used in embankment fills for transportation construction by employing Radial Basis Function (RBF) modeling frameworks. Traditionally, UCS determination has relied on time-consuming…
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Multi-Criteria Deep Reinforcement Learning Energy-Aware and QoS-Driven Scheduling for Containerized Microservices in Docker Swarm Clusters
Efficient scheduling of containerized microservices is essential to ensure performance, scalability, and quality of service in cloud native environments. Docker Swarm comes with three container scheduling strategies by default: Spread, Binpack, and Random. These policies are based on static…
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Artificial İntelligence in Health Marketing Personalization: Integration with HR Systems to Predict Healthcare Staff Training Needs
The increasing demand for healthcare services, along with the rising complexity of the skill set of the workforce, has made it necessary to adopt data-based methods of human resource planning. This study develops an integrated predictive–prescriptive framework that systematically links healthcare…
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Automated Brain Tumor Classification using Deep Convolutional and Transfer Learning Networks
Brain cancers are some of the fastest-growing and most deadly types of neurological diseases in medicine. Early detection with accuracy is very important to improve the survival of patients. Manually reading MRI scan images is a slow process. It requires a special skills person and can differ from…
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Chaotic Status-Based Optimization: Deterministic Chaos Integration for Congress on Evolutionary Computation-2022 Benchmarks and Engineering Design Problems
Metaheuristic optimizers often suffer from premature convergence and instability in multimodal and constrained search landscapes. Although the recently proposed Status-Based Optimization demonstrates competitive performance, its reliance on stochastic randomization may limit the reliability of…
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An Integrated LCA-LCC-MCDA Decision-Support Framework for Sustainable Landing Gear Design
This study presents an integrated decision-support framework for sustainable technology adoption in aviation, demonstrated on lightweight landing-gear architectures. Because aviation decarbonization benefits from structural mass reduction but is constrained by certification readiness…
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A Fuzzy-IoT Irrigation Framework with LoRa-Based Connectivity for Climate-Resilient Agriculture in Semi-Arid Regions
In arid and semi-arid regions, water scarcity is one of the most significant challenges in agriculture. Efficient water management is important where precipitation is low, and groundwater resources are also depleting. Most existing systems rely on a single sensor input, require continuous internet…
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Prediction of Undrained Shear Strength of Soil Using Hybrid Automated Radial Basis Function
Accurate estimation of undrained shear strength (USS) is essential in geotechnical engineering applications, including foundation design, bearing capacity evaluation, and slope stability analysis, as it directly governs the short-term mechanical behavior of cohesive soils under undrained…
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Assessing and Improving Housing Flexibility in Duhok City Using Spatial Configuration, Space Syntax, and Machine Learning Surrogate Modeling: A Case Study
This study evaluates and enhances contemporary housing flexibility in Duhok City, Iraq, using an integrated architectural and space syntax workflow augmented with a lightweight machine learning surrogate. Ten residential units on plots of about 150 m² were assessed in original layouts Hi and…
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Attention Enhanced Hybrid CNN-LSTM Model for ECG-Based Arrhythmia Classification in the Federated Fog Computing Environment
Early detection of cardiac rhythm disorders (arrhythmias) poses a significant challenge, especially when using wearable IoT devices that continuously monitor ECG signals. Conventional cloud-based deep learning methods are largely infeasible due to considerable latency and raise serious data privacy…
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Design, Implementation, and Empirical Validation of an IEC 62305-Compliant Lightning Protection System for Enhancing Infrastructure Resilience and Energy System Reliability
This research presents a comprehensive and detailed study of the design, implementation, and experimental validation of a Lightning Protection System (LPS) for a multi-story commercial building in Isfahan, Iran, in full compliance with the international standard IEC 62305. The study bridges…
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MLF-Net: Hybrid CNN–Transformer with Lesion-Focused Fusion for Trustworthy Multi-Class Mpox Diagnosis on MSID
On the MSID dataset, which includes four classes—monkeypox, chickenpox, measles, and normal—to introduce MLF-Net, a small hybrid CNN-Transformer that fuses features focused on lesions to recognize monkeypox in multiple classes. From class-aware training (using effective-number weights, label…
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Skin Cancer Early Detection through Innovative Imaging Technology
Skin cancer constitutes a significant global health issue, and early detection is crucial for enhancing treatment efficacy and patient survival rates. This study presents a sophisticated system for the early identification of skin cancer utilizing computer vision and machine learning techniques…
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Employment of a Least Square Support Vector Regression Model for Predicting the Gasification Process
Biomass fuels, with minimal sulfur content, lower ash production, and reduced emissions, offer a reliable alternative to fossil fuels. The global requirements to decrease dependencies on imported energy and conserve fossil reserves highlight the significance of biomass for syngas production…
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Enhanced Fault Diagnosis Method for Tractors Using Random Forest Algorithm
In this study, we initially introduce a robust method to categorize large groups of educators into distinct communities, termed "genres," based on their shared instructional preferences. Building on this classification, we developed an educator experience recommendation pipeline designed to enhance…
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Predicting Compressive and Tensile Strength of High-Performance Concrete via Hybrid and Ensemble-Hybrid Machine Learning Approach
The emergence of new categories and technology has prompted investigators to deploy artificial intelligence (AI) to generate mechanical strength estimation models. Statistical and empirical models are widely utilized. The models need to provide inaccurate results and large amounts of inspection…
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Cooling Load Prediction in Residential Buildings: Machine Learning Approaches and Comparative Analysis
Accurate estimation of Cooling Loads (CLs) in Residential Buildings (RBs) is crucial for ensuring energy-efficient HVAC system design and maintaining indoor comfort. This research explores advanced Machine Learning (ML) approaches to forecast cooling demand by considering critical factors such as…
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Tunned Regression Analysis to Predict the Compressive Strength of Concrete Containing GGBFS
Accurate estimation of compressive strength (CS) is crucial in the design and construction of concrete structures, especially with the increasing use of ground granulated blast furnace slag (GGBFS) in concrete production to reduce carbon dioxide emissions associated with ordinary Portland cement…
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Predicting 28-Day Compressive Strength through a Hybrid Machine-Learning Approach with Meta-Heuristic Algorithm Integration
In recent years, the building sector's rapid production of construction supplies has been a major contributor to degradation of the environment on a global scale. Researchers have increasingly turned their attention towards exploring the surroundings advantages of reusing repurposed aggregates for…