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Analysis of Microscopic Data on the Behavior of Metallic Nickel Ore During Magnetic Enrichment Using SAM2 and Tensor Decomposition-Based Zero-Shot Image Segmentation
No full texthttps://doi.org/10.1109/siu66497.2025.1111234
Comprehensive Evaluation of the Impacts of Mixed Traffic Conditions on Urban Networks
No full textThe emergence of connected and autonomous vehicles (CAVs) has become a focal point in the literature. This study proposes a comprehensive evaluation framework integrating multi-criteria analysis (MCA) methods with traffic microsimulation modeling to assess the impacts of mixed traffic conditions, comprising CAVs and human-driven vehicles (HDVs), on urban networks from various perspectives: traffic efficiency, environmental performance, and traffic safety. To this end, findings obtained from simulations of two real urban networks are employed to evaluate the impacts of penetration rates and different driving behaviors of CAVs. Six penetration rates (15%, 30%, 45%, 60%, 75%, and 90%), and three different driving behaviors of CAVs, namely defensive, normal, and aggressive, are considered in the scope of this study. While the Criteria Importance Through Intercriteria Correlation (CRITIC) method is utilized for determining objective criteria weights, the designed scenarios are scored by means of the Combined Compromise Solution (CoCoSo) method. The findings of the study indicate that defensive driving behavior enhances traffic safety, albeit with trade-offs in reduced traffic efficiency and increased traffic emissions. On the other hand, while aggressive driving behavior improves traffic efficiency and reduces traffic emissions, it also introduces safety risks, particularly at low penetration rates. According to the outcomes of the comprehensive evaluation, scenarios comprising only HDVs lose their dominance beyond 60% and 75% penetration rates, depending on the network. The proposed approach is expected to be effective in assessing the impacts of mixed traffic conditions on urban networks and can provide valuable insights to transportation policymakers and practitioners.https://doi.org/10.1109/access.2025.3563785https://doi.org/10.1109/ACCESS.2025.3563785https://doaj.org/article/513d1f17231e47adb9a284e1b615afd
Phase Portrait-Based Orientation-Aware Path Planning for Autonomous Mobile Robots
No full textPath planning algorithms for mobile robots and autonomous systems have advanced considerably, yet challenges remain in navigating complex environments while satisfying non-holonomic constraints and achieving precise target orientation. Phase portraits are traditionally used to analyse dynamical systems via equilibrium points and system trajectories, and can be a powerful framework for addressing these challenges. In this work, we propose a novel orientation-aware path planning algorithm that uses phase portrait dynamics by treating both obstacles and target poses as equilibrium points within the environment. Unlike conventional approaches, our method explicitly incorporates non-holonomic constraints and target orientation requirements, resulting in smooth, feasible trajectories with high final pose accuracy. Simulation results across 28 diverse scenarios show that our method achieves zero final orientation error with path lengths comparable to Hybrid A*, and planning times reduced by 52% on the indoor map and 84% on the playpen map relative to Hybrid A*. These results highlight the potential of phase portrait-based planning as an effective and efficient method for real-time autonomous navigation.https://doi.org/10.3390/inventions1004006
Toward Safer Digital Communication: A Deep Hybrid Model for Detecting Abusive Language on Social Networks
No full textThe prevalence of abusive language and cyberbullying on social media platforms presents a growing challenge to the user safety and digital well-being, necessitating the development of effective automated content moderation systems. This study proposes a hybrid deep learning model that combines Long Short-Term Memory (LSTM) networks with Convolutional Neural Networks (CNNs) to classify the abusive text with enhanced accuracy and contextual awareness. The LSTM component captures long-range dependencies and semantic context, while the CNN module extracts discriminative local n-gram features. The model was trained and evaluated on three benchmark datasets: HatebaseTwitter, HatEval, and TRAC. The experimental results demonstrated that the proposed architecture outperforms traditional classifiers, such as SVM, Random Forest, and Logistic Regression, as well as standalone CNN and LSTM models, achieving superior performance across all standard evaluation metrics. Notably, the model attained AUC scores of up to 0.97, indicating robust discriminatory power. These findings underscore the effectiveness of the hybrid LSTM–CNN model for abusive language detection and highlight its potential for deployment in real-time content moderation tools aimed at fostering safer online communication environments.https://doi.org/10.48084/etasr.1272
Biofouling Mitigation and Microbial Community Dynamics in the Quorum Quenching Membrane Bioreactors for Industrial Wastewater Treatment
No full texthttps://doi.org/10.2139/ssrn.5258764https://doi.org/10.1016/j.jwpe.2025.108379https://doi.org/10.2139/ssrn.512867
Codimensions-Two Submanifolds Contained in the Light-Like Hypercylinder \Mathcal{Lc}^N\Times\Mathbb R
No full textIn this paper, we investigate space-like codimension-two submanifolds of the Lorentz-Minkowski space constrained to lie on the light-like hypercylinder over the light cone . By constructing a geometrically defined global frame field on the submanifold, we analyze the geometric interpretations of the associated extrinsic invariants by providing characterizations of (pseudo-)isotropic and pseudo-umbilical submanifolds, as well as submanifolds with flat normal bundle. In particular, we obtain local classification theorems for these classes of submanifolds.https://doi.org/10.2139/ssrn.5381157https://dx.doi.org/10.48550/arxiv.2508.11653http://arxiv.org/abs/2508.1165
On the and superconformal holographic dictionary
No full textAbstract This study presents comprehensive examples of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>osp</mml:mi> <mml:mo>(</mml:mo> <mml:mi>N</mml:mi> <mml:mo>|</mml:mo> <mml:mn>2</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> Chern–Simons supergravity on <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>A</mml:mi> <mml:mi>d</mml:mi> <mml:msub> <mml:mi>S</mml:mi> <mml:mn>3</mml:mn> </mml:msub> </mml:mrow> </mml:math> for \mathcal {N}>2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>N</mml:mi> <mml:mo>&gt;</mml:mo> <mml:mn>2</mml:mn> </mml:mrow> </mml:math> . These formulations, which include the most general boundary conditions, represent extensions of previously discovered works (Ozer and Filiz in Eur Phys J C 82:472, 2022. https://doi.org/10.1140/epjc/s10052-022-10422-w) for \mathcal {N}<3 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>N</mml:mi> <mml:mo>&lt;</mml:mo> <mml:mn>3</mml:mn> </mml:mrow> </mml:math> . In our work, we show that under the loosest set of boundary conditions, the asymptotic symmetry algebras consist of two copies of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>osp</mml:mi> <mml:msub> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>3</mml:mn> <mml:mo>|</mml:mo> <mml:mn>2</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> <mml:mi>k</mml:mi> </mml:msub> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>osp</mml:mi> <mml:msub> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>4</mml:mn> <mml:mo>|</mml:mo> <mml:mn>2</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> <mml:mi>k</mml:mi> </mml:msub> </mml:mrow> </mml:math> algebras. We subsequently restrict the gauge fields upon the boundary conditions to achieve supersymmetric extensions of the Brown–Henneaux boundary conditions. Based on these results, we finally find that the asymptotic symmetry algebras are two copies of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>N</mml:mi> <mml:mo>=</mml:mo> <mml:mn>3</mml:mn> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>N</mml:mi> <mml:mo>=</mml:mo> <mml:mn>4</mml:mn> </mml:mrow> </mml:math> superconformal algebras for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>N</mml:mi> <mml:mo>=</mml:mo> <mml:mo>(</mml:mo> <mml:mn>3</mml:mn> <mml:mo>,</mml:mo> <mml:mn>3</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>N</mml:mi> <mml:mo>=</mml:mo> <mml:mo>(</mml:mo> <mml:mn>4</mml:mn> <mml:mo>,</mml:mo> <mml:mn>4</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> extended higher-spin supergravity theory in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>A</mml:mi> <mml:mi>d</mml:mi> <mml:msub> <mml:mi>S</mml:mi> <mml:mn>3</mml:mn> </mml:msub> </mml:mrow> </mml:math> .https://doi.org/10.1140/epjc/s10052-025-13786-xhttps://dx.doi.org/10.48550/arxiv.2407.17235http://arxiv.org/abs/2407.1723
Combined Dynamic and Thermodynamic Modeling of Beta-Type Stirling Engine with Hypocycloid Gear Mechanism
No full texthttps://doi.org/10.2139/ssrn.5213930https://doi.org/10.1016/j.rineng.2025.10710
Machine Learning Modeling for Building Energy Performance Prediction Based on Simulation Data: A Systematic Review of the Processes, Performances, and Correlation of Process-Related Variables
No full textMachine learning models have become a potential alternative for building energy performance studies since they provide fast and reliable prediction results. However, decisions in the modeling process are sometimes made without knowing their possible impact on the results, which may lead to unstable process management. Therefore, this study aims to obtain a machine learning modeling process framework focusing on critical-decision subjects through a systematic review of the recent literature. Preferences of the current supervised modeling practices on process-related variables to have prediction models with high accuracy were analyzed in the studies using simulation data. In this paper, a general framework of the processes is presented through their steps and decision subjects. Regarding these steps, the frequency of the methods used, strategies followed against the limitations, common sources of concerns, and intertwined workflows are analyzed with their effects on prediction performance in terms of accuracy. In addition, correlations between process-related variables, i.e., decision subjects and model performance, are investigated to quantify the impacts. As a result, the most effective decision subjects on accuracy were observed as the machine learning algorithm to be used, input variables to be included, and the range of the sample size, respectively.https://doi.org/10.3390/buildings15081301https://doaj.org/article/a51537b5eb474bccad94f61648b0f8d
Will Conventional Public Transport Users Adopt Autonomous Public Transport? A Model Integrating UTAUT Model and Satisfaction–Loyalty Model
No full textAs an emerging technology for sustainable, safe, energy-efficient, and smooth traffic flow, autonomous public transport (APT) has been widely studied in recent years. However, the influence of conventional public transport (CPT) on behavioural intentions toward APT is largely overlooked. While APT is in its nascent phase, users’ choices may be shaped by their perceptions and attitudes toward CPT. Therefore, identifying these perceptions and examining their effect on behavioural intention is crucial. In this study, the Unified Theory of Acceptance and Use of Technology (UTAUT) is integrated with the satisfaction-loyalty model to analyze the key factors influencing behavioural intentions toward APT. To obtain more precise findings, this study examined public transport by type, including rubber-tired systems, urban rail, and bus rapid transit, rather than as a single mode, unlike many previous studies. A survey (n = 1271) was employed to validate the theoretical model among CPT users in Istanbul. The results indicate that loyalty to CPT significantly influences behavioural intention toward APT. Moreover, users of different CPT types have distinct priorities influencing their intention to use APT. While users of rubber-tired systems prioritize effort expectancy, social influence and facilitating conditions, users of urban rail systems consider social influence, trust and loyalty to CPT to be decisive factors. Furthermore, users of bus rapid transit systems consider performance expectancy, effort expectancy, trust, and loyalty to CPT as key factors influencing their behavioural intention. The findings are expected to enrich theoretical research on behavioural intention toward APT and guide future integration and transition between CPT and APT.https://doi.org/10.3390/su1720908