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Algorithms
Scopus
ISSN 1999-4893 · MDPI AG · 4.951 artikel di indeks
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Embedding-Based Detection of Indirect Prompt Injection Attacks in Large Language Models Using Semantic Context Analysis
Large Language Models (LLMs) are vulnerable to Indirect Prompt Injection Attacks (IPIAs), where malicious instructions are embedded within external content rather than direct user input. This study presents an embedding-based detection approach that analyses the semantic relationship between user…
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A Structured Review of EEG-Based Machine Learning Approaches for Brain Age Prediction
The determination of brain age based on electroencephalography (EEG) data has become widely developed with the spread of machine learning in recent years. In this research paper, we analyzed 21 articles published no earlier than 2015, focusing particularly on features, machine learning and deep…
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Collision of an Obstacle by an Elastic Bar in a Gravity Field: Solution with Discontinuous Velocity and Space-Time Primal-Dual Active Set Algorithm
A class of one-dimensional dynamic impact models is investigated with respect to non-smooth velocities using variational inequalities and space-time finite element approximation. For the problem of collision of a rigid obstacle by an elastic bar in the gravitational field, a benchmark based on…
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Non-Imaging Differential Diagnosis of Lower Limb Osteoarthritis: An Interpretable Machine Learning Framework
Background: Osteoarthritis (OA) is a prevalent chronic degenerative disorder, with coxarthrosis (hip OA) and gonarthrosis (knee OA) representing its most significant clinical manifestations. While diagnosis typically relies on imaging, such methods can be resource-intensive and insensitive to early…
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Mathematical Approach for Ameliorated Inventory Models
Hwang developed inventory models with amelioration items and applied the graphical method to locate the optimal solution. In this study, we derive an analytical method to find two local maximum points and one local minimum point. Our maximum profit is greatly superior to that of Hwang, because his…
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Path Planning in Sparse Reward Environments: A DQN Approach with Adaptive Reward Shaping and Curriculum Learning
Deep reinforcement learning (DRL) has shown great potential in path planning tasks. However, in sparse reward environments, DRL still faces significant challenges such as low training efficiency and a tendency to converge to suboptimal policies. Traditional reward shaping methods can partially…
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Improving Prostate Cancer Segmentation on T2-Weighted MRI Using Prostate Detection and Cascaded Networks
Prostate cancer is one of the most lethal cancers in the male population, and accurate localization of intraprostatic lesions on MRI remains challenging. In this study, we investigated methods for improving prostate cancer segmentation on T2-weighted pelvic MRI using cascaded neural networks. We…
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A Review of End-to-End Decision Optimization Research: An Architectural Perspective
Traditional decision optimization methods primarily focus on model construction and solution, leaving parameter estimation and inter-variable relationships to statistical research. The traditional approach divides problem-solving into two independent stages: predict first and then optimize. This…
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A Lightweight Embedded PPG-Based Authentication System for Wearable Devices via Hyperdimensional Computing
In the realm of wearable technology, achieving robust continuous authentication requires balancing high security with the strict resource constraints of embedded platforms. Conventional machine learning approaches and deep learning-based biometrics often incur high computational costs, making them…
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An Iterative Reinforcement Learning Algorithm for Speed Drop Compensation in Rolling Mills
In the process of steel rolling production, the speed reduction compensation of the rolling mill is a key link to ensure the stability of slab rolling and product quality. This paper proposes a hybrid compensation method that integrates motor dynamic modeling with reinforcement learning to minimize…
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Hybrid Optimization Technique for Finding Efficient Earth–Moon Transfer Trajectories
The Lunar Gateway is a planned small space station that will orbit the Moon and serve as a central hub for NASA’s Artemis program to return humans to the lunar surface and to prepare for Mars missions. This work presents a hybrid optimization strategy for designing minimum-fuel transfers from an…
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Physics-Aware Deep Learning Framework for Solar Irradiance Forecasting Using Fourier-Based Signal Decomposition
Photovoltaic Systems have been a long-standing challenge to integrate with electrical Power Grids due to the randomness of solar irradiance. Deep Learning (DL) has potential to forecast solar irradiance; however, black-box DL models typically do not offer interpretation, nor can they easily…
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Heuristic Conductance-Aware Local Clustering for Heterogeneous Hypergraphs
Graphs are widely used to model complex interactions among entities, yet they struggle to capture higher-order and multi-typed relationships. Hypergraphs overcome this limitation by allowing for edges to connect arbitrary sets of nodes, enabling richer modelling of higher-order semantics…
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Algorithms for Solving Ordinary Differential Equations Based on Orthogonal Polynomial Neural Networks
This article proposes single-layer neural network algorithms for solving second-order ordinary differential equations, based on the principles of functional connection. According to this principle, the hidden layer of the neural network is replaced by a functional expansion unit to improve input…
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Dynamic Resource Games in the Wood Flooring Industry: A Bayesian Learning and Lyapunov Control Framework
Wood flooring manufacturers face complex challenges in dynamically allocating resources across multi-channel markets, characterized by channel conflicts, demand uncertainty, and long-term cumulative effects of decisions. Traditional static optimization or myopic approaches struggle to address these…
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Key-Value Mapping-Based Text-to-Image Diffusion Model Backdoor Attacks
Text-to-image (T2I) generation, a core component of generative artificial intelligence(AI), is increasingly important for creative industries and human–computer interaction. Despite impressive progress in realism and diversity, diffusion models still exhibit critical security blind spots…
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Boundary-Aware Multi-Point Preview Control: An Algorithm for Autonomous Articulated Mining Vehicles Operating in Highly Constrained Underground Spaces
To achieve the automation and intelligence of mining equipment, it is essential to address the challenge of autonomous driving, with the core task being how to navigate safely from the starting point to the mining area endpoint. This paper proposes a boundary-aware multi-point preview control…
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An Intelligent Browser History Forensics Method for Automated Analysis of Web Activity Logs, Credentials, and User Behavioral Profiles
In digital forensics, one of the complicated tasks is analyzing web browser data due to different types of devices, browsers, and the absence of modern analytical approaches. Browsers store a large amount of information about user activity because users most often access the internet through them…
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Image-Based Segmentation of Hydrogen Bubbles in Alkaline Electrolysis: A Comparison Between Ilastik and U-Net
This study aims to enhance the efficiency of hydrogen production through alkaline water electrolysis by analyzing hydrogen bubble dynamics using high-speed image processing and machine learning algorithms. The experiments were conducted to evaluate the effects of electrical current and ultrasound…
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ICCA: Independent Multi-Agent Algorithm for Distributed Jamming Scheduling
In extreme scenarios, to prevent the leakage of jamming coordination information, the jammers must proactively terminate their communication functions and implement jamming resource scheduling via Non-Networked Cooperation. However, current research on this non-networked jamming approach is…
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