Search Results (77)

This work presents the development of a functional real-time SLAM system designed to enhance the perception capabilities of an Automated Guided Vehicle (AGV) using only a 2D LiDAR sensor. The proposal aims to address recurring gaps in the literature, such as the need for low-complexity solutions that are independent of auxiliary sensors and capable of operating on embedded platforms with limited computational resources. The system integrates scan alignment techniques based on the Iterative Closest Point (ICP) algorithm. Experimental validation in a controlled environment indicated better performance using Gauss–Newton optimization and the point-to-plane metric, achieving pose estimation accuracy of 99.42%, 99.6%, and 99.99% in the position ($x$, $y$) and orientation ($\theta$) components, respectively. Subsequently, the system was adapted for operation with data from the onboard sensor, integrating a lightweight graphical interface for real-time visualization of scans, estimated pose, and the evolving map. Despite the moderate update rate, the system proved effective for robotic applications, enabling coherent localization and progressive environment mapping. The modular architecture developed allows for future extensions such as trajectory planning and control. The proposed solution provides a robust and adaptable foundation for mobile platforms, with potential applications in industrial automation, academic research, and education in mobile robotics. Full article

Strawberry post-harvest losses are estimated at 50%, due to improper handling and harvest timing, necessitating the use of non-invasive methods. This study develops a non-invasive in situ bioelectrical spectroscopy for strawberry peduncles. Based on traditional assessments and invasive metrics, 100 physiologically ripe (PR) and 100 commercially mature (CM) strawberries were distinguished. Spectra from their peduncles were measured from 1 kHz to 1 MHz, collecting four parameters (magnitude (Z(f)), phase angle (θ(f)), resistance (R(f)), and reactance (X(f))), resulting in 80,000 raw data points. Through systematic spectral preprocessing, Bode and Cole–Cole plots revealed a distinction between PR and CM strawberries. Frequency selection identified seven key frequencies (1, 5, 50, 75, 100, 250, 500 kHz) for deriving 37 engineered features from spectral, extrema, and derivative parameters. Feature selection reduced these to 6 parameters: phase angle at 50 kHz (θ (50 kHz)); relaxation time (τ); impedance ratio (|Z_1k/Z_250k|); dispersion coefficient (α); membrane capacitance (Cm); and intracellular resistivity (ρi). Four algorithms (TabPFN, CatBoost, GPC, EBM) were evaluated with Monte Carlo cross-validation with five iterations, ensuring robust evaluation. CatBoost achieved the highest accuracy at 93.3% ± 2.4%. Invasive reference metrics showed strong correlations with bioelectrical parameters (r = 0.74 for firmness, r = −0.71 for soluble solids). These results demonstrate a solution for precise harvest classification, reducing post-harvest losses without compromising marketability. Full article

This study investigates the impact of response time on ability estimation within an Item Response Theory (IRT) framework, introducing time-sensitive formulations to enhance student assessment accuracy. Seven models were evaluated, including standard 1PL-IRT and six response-time-adjusted variants: TP-IRT, STP-IRT, TWD-IRT, NRT-IRT, DTA-IRT, and ART-IRT. Three optimization techniques—Maximum Likelihood Estimation (MLE), full parameter optimization, and K-fold Cross-Validation (CV)—were employed to assess model performance. Empirical validation was conducted using data from 150 students solving 30 mathematics items on the “TestYourself” platform, integrating response accuracy and timing metrics. Student abilities (θ), item difficulties (b), and time–effect parameters (λ) were estimated using the L-BFGS-B algorithm to ensure numerical stability. The results indicate that subtractive models, particularly DTA-IRT, achieved the lowest AIC/BIC values, highest AUC, and improved parameter stability, confirming their effectiveness in penalizing excessive response times without disproportionately affecting moderate-speed students. In contrast, multiplicative models (TWD-IRT, ART-IRT) exhibited higher variability, weaker generalizability, and increased instability, raising concerns about their applicability in adaptive testing. K-fold CV further validated the robustness of subtractive models, emphasizing their suitability for real-world assessments. These findings highlight the importance of incorporating response time as an additive factor to improve ability estimation while maintaining fairness and interpretability. Future research should explore multidimensional IRT extensions, behavioral response–time analysis, and adaptive testing environments that dynamically adjust item difficulty based on response behavior. Full article

In this article, we will introduce a new generalized proximal $\theta$-contraction for multivalued and single-valued mappings named ${(\mathcal{f}-{\theta }_{\kappa })}_{C_P}$-proximal contraction and ${(\mathcal{f}-{\theta }_{\kappa })}_{B_P}$-proximal contraction. Using these newly constructed proximal contractions, we will establish new results for the coincidence best proximity point, best proximity point, and fixed point for multivalued mappings in the context of rectangular metric space. Also, we will reduce these contractions for single-valued mappings, named ${\left({\theta }_{\kappa }\right)}_{C_P}$-proximal contraction and ${\left({\theta }_{\kappa }\right)}_{B_P}$-proximal contraction, to establish results for the coincidence proximity point, best proximity point, and fixed point results. We will give some illustrated examples for our newly generated results with graphical representations. In the last section, we will also find the solution to the equation of motion by using our defined results. Full article

In the framework of quasi-Hermitian quantum mechanics, the eligible operators of observables may be non-Hermitian, $A_j\ne A_j^{†}$, $j=1,2,\dots ,K$. In principle, the standard probabilistic interpretation of the theory can be re-established via a reconstruction of physical inner-product metric $\mathsf{\Theta }\ne I$, guaranteeing the quasi-Hermiticity $A_j^{†}\mathsf{\Theta }=\mathsf{\Theta }{A}_j$. The task is easy at $K=1$ because there are many eligible metrics $\mathsf{\Theta }=\mathsf{\Theta }\left(A_1\right)$. In our paper, the next case with $K=2$ is analyzed. The criteria of the existence of a shared metric, $\mathsf{\Theta }=\mathsf{\Theta }(A_1,A_2)$, are presented and discussed. Full article

Background: Evidence-based design aims to create healthy environments grounded in scientific data, yet the influence of spatial qualities on cognitive processes remains underexplored. Advances in neuroscience offer promising tools to address this gap while meeting both scientific and practical demands. Consumer-grade mobile EEG devices are increasingly used; however, their lack of transparency complicates output interpretation. Well-established EEG indicators from cognitive neuroscience may offer a more accessible and interpretable alternative. Methods: This feasibility study explored the sensitivity of five established EEG power band ratios to cognitive shifts in response to subtle environmental design experiences. Twenty participants completed two crossover sessions in an office-like setting with nature-inspired versus urban-inspired design elements. Each session included controlled phases of focused on-screen cognitive task and off-screen breaks. Results: Factorial analyses revealed no significant interaction effects of cognitive state and environmental exposure on EEG outcomes. Nonetheless, frontal (θ/β) and frontocentral (β/[α + θ]) ratios showed distinct patterns across cognitive states, with more pronounced contrasts in the nature-inspired compared to the urban-inspired design conditions. Conversely, occipital ([θ + α]/β), (θ/α), and (β/α) ratios remained consistent across exposures. Data triangulation with autonomic nervous system responses and performance metrics supported these observations. Conclusions: The findings suggest that EEG power band ratios can capture brain–environment interactions. However, limitations of consumer-grade EEG devices challenge both scientific rigour and practical application. Refining methodological reliability could improve interpretability, supporting more transparent and robust data-driven design decisions. Full article

This study investigates fuzzy fixed points and fuzzy best proximity points for fuzzy mappings within the newly introduced framework $\theta$-fuzzy metric spaces that extends various existing fuzzy metric spaces. We establish novel fixed-point and best proximity-point theorems for both single-valued and multivalued mappings, thereby broadening the scope of fuzzy analysis. Furthermerefore, we have for aore, we apply one of our key results to derive conditions, ensuring the existence and uniqueness of a solution to Hadamard $\Psi$-Caputo tempered fuzzy fractional differential equations, particularly in the context of the SIR dynamics model. These theoretical advancements are expected to open new avenues for research in fuzzy fixed-point theory and its applications to hybrid models within $\theta$-fuzzy metric spaces. Full article

Understanding soil properties’ spatial and temporal variability is essential for optimizing road construction and maintenance practices. This study investigates the seasonal variability of soil properties along a 4.8 km roadway in Maiduguri, Nigeria. Using a novel integration of network analysis and geotechnical testing, we analyzed nine soil parameters (e.g., particle size distribution (PSD), Atterberg limits, California bearing ratio) across wet (September 2024) and dry (January 2021) seasons from 25 test stations. Average Atterberg limits (LL: 22.8% wet vs. 17.5% dry; PL: 18.7% wet vs. 14.7% dry; PI: 4.2% wet vs. 2.8% dry; LS: 1.8% wet vs. 2.3% dry), average compaction characteristics (MDD: 1.8 Mg/m³ wet vs. 2.1 Mg/m³ dry; OMC: 12.3% wet vs. 10% dry), and average CBR (18.9% wet vs. 27.5% dry) were obtained. Network construction employed z-score standardization and similarity metrics, with multi-threshold analysis (θ = 0.05, 0.10, 0.15) revealing critical structural differences. During the wet season, soil networks exhibited a 5.0% reduction in edges (321 to 305) and density decline (1.07 to 1.02) as thresholds tightened, contrasting with dry-season networks retaining 99.38% connectivity (324 to 322 edges) and stable density (0.99). Seasonal shifts in soil classification (A-4(1)/ML wet vs. A-2(1)/SM dry) underscored moisture-driven plasticity changes. The findings highlight critical implications for adaptive road design, emphasizing moisture-resistant materials in wet seasons and optimized compaction in dry periods. Full article

This paper investigates the existence of common attractors for generalized $\theta$-Hutchinson operators within the framework of partial metric spaces. Utilizing a finite iterated function system composed of $\theta$-contractive mappings, we establish theoretical results on common attractors, generalizing numerous existing results in the literature. Additionally, to enhance understanding, we present intuitive and easily comprehensible examples in one-, two-, and three-dimensional Euclidean spaces. These examples are accompanied by graphical representations of attractor images for various iterated function systems. As a practical application, we demonstrate how our findings contribute to solving a functional equation arising in a dynamical system, emphasizing the broader implications of the proposed approach. Full article

Background: Cancer remains one of the leading causes of mortality worldwide, with radiotherapy playing a crucial role in its treatment. Intensity-modulated radiotherapy (IMRT) enables precise dose delivery to tumors while sparing healthy tissues. However, geometric uncertainties such as patient positioning errors and anatomical deformations can compromise treatment accuracy. Traditional methods use safety margins, which may lead to excessive irradiation of healthy organs or insufficient tumor coverage. Robust optimization techniques, such as minimax approaches, attempt to address these uncertainties but can result in overly conservative treatment plans. This study introduces an interval analysis-based optimization model for IMRT, offering a more flexible approach to uncertainty management. Methods: The proposed model represents geometric uncertainties using interval dose influence matrices and incorporates Bertoluzza’s metric to balance tumor coverage and organ-at-risk (OAR) protection. The $\theta$ parameter allows controlled robustness modulation. The model was implemented in matRad, an open-source treatment planning system, and evaluated on five prostate cancer cases. Results were compared against traditional Planning Target Volume (PTV) and minimax robust optimization approaches. Results: The interval-based model improved tumor coverage by 5.8% while reducing bladder dose by 4.2% compared to PTV. In contrast, minimax robust optimization improved tumor coverage by 25.8% but increased bladder dose by 23.2%. The interval-based approach provided a better balance between tumor coverage and OAR protection, demonstrating its potential to enhance treatment effectiveness without excessive conservatism. Conclusions: This study presents a novel framework for IMRT planning that improves uncertainty management through interval analysis. By allowing adjustable robustness modulation, the proposed model enables more personalized and clinically adaptable treatment plans. These findings highlight the potential of interval analysis as a powerful tool for optimizing radiotherapy outcomes, balancing treatment efficacy and patient safety. Full article

This study sheds light on the performance of the common high-precision electromagnetic sensor TEROS 10 to estimate volumetric soil water content (θ) from dry to saturation across three different substrates, six different soil types having three different levels of electrical conductivity of soil solutions (EC_w), and in liquids with increasing salinity level under laboratory conditions, by using low-cost but accurate experimental IoT hardware arrangements. This performance was evaluated using statistical analysis metrics such as Root Mean Square Error (RMSE). It was found that TEROS 10 performance did not conform to the manufacturer’s specifications throughout the full scale range, although in some cases good water content estimation was provided. Some inconsistencies were identified by applying the manufacturer’s calibration equations, and thus recommendations for improvements are provided, aiming to enhance the sensor’s overall performance. TEROS 10 performance across all six soils and three substrates was improved on average from an RMSE of 0.052 and 0.078 cm³ cm⁻³, respectively, by using factory-derived calibration, to 0.031 and 0.031 cm³ cm⁻³ by using the multipoint calibration method (CAL). Furthermore, a linear calibration formula, using Raw output as the predictor variable, was tested and resulted in an RMSE of 0.026 and 0.046 cm³ cm⁻³ for soils and substrates, respectively. Full article

This paper is inspired by cutting-edge advancements in chaos theory, fractional calculus, and fixed point theory, which together provide a powerful framework for examining the dynamics of complex systems. At the heart of our research is the fractional-order Dadras–Momeni chaotic system, a pivotal model in chaos theory celebrated for its intricate, multi-scroll dynamics. Leveraging the Atangana–Baleanu fractional derivative, we extend fractional computation to chaotic systems, offering deeper insights into their behavior. To fortify the mathematical foundation of our analysis, we employ the relaxed $\theta$ rational contractions in the realm of metric spaces, enabling a more precise exploration of the system’s dynamics. A key goal of this work is to simplify the definition of the function class $\mathsf{\Theta }$ while maintaining the existence and uniqueness of fixed points under $\theta$-relaxed contractions, integrating this framework with the established literature on complete metric spaces. We explore the system’s behavior across six distinct cases by varying $\delta$ with a fixed fractional order of $\hslash =0.98$. In the first case, a single scroll forms, while successive cases lead to increased scrolls—reaching up to four by the sixth case. Phase portraits and time series analyses reveal a progression in complexity and chaos, with denser, intertwined scrolls as $\delta$ increases. This behavior highlights the system’s heightened sensitivity to parameter variations, demonstrating how fractional parameters influence the chaotic dynamics. Our results offer meaningful contributions to both the theoretical foundations and practical applications of chaos theory and fractional calculus, advancing the understanding of chaotic systems in new and impacted ways. Full article

This paper presents the experimental and numerical results of a study on producing axisymmetric parts made of the C60-grade steel by skew rolling. The experimental part of this study involved conducting the skew rolling process with varying parameters, including the forming angle α, tool angle θ, chuck velocity V_u, and reduction ratio δ. Their effect on the quality of produced parts was examined and described by the roughness parameter Ra. Numerical calculations involved the use of machine learning models to predict the quality class of produced parts. The highest prediction accuracy of the results was obtained with the random forest and logistic regression models. Metrics such as precision, recall and accuracy were used to evaluate the performance of individual models. Confusion matrices and ROC curves were also employed to illustrate the performance of the classification models. The results of this study will make it possible to prevent the formation of spiral grooves on the circumference of steel parts during the rolling process. Full article

In this manuscript, we present a novel concept termed graphical ${\Theta }_c$-Kannan contraction within the context of graphically controlled metric-type spaces. Unlike traditional Kannan contraction, this novel concept presents a modified method of contraction mapping. We discuss the significance and the existence of fixed point results within the framework of this novel contraction. To strengthen the credibility of our theoretical remarks, we provide a comparison example demonstrating the efficiency of our suggested framework. Our study not only broadens the theoretical foundations inside graphically controlled metric-type spaces by introducing and examining visual ${\Theta }_c$-Kannan contraction, but it also demonstrates the practical significance of our innovations through significant examples. Furthermore, applying our findings to second-order differential equations by constructing integral equations into the domain of Fredholm sheds light on the broader implications of our research in the field of mathematical analysis and contributes to the advancement of this field. Full article

This paper combines the concept of an arbitrary binary connection with the widely recognized principle of $\theta$-contraction to investigate the innovative features of vector-valued metric spaces. This methodology demonstrates the existence of fixed points for both single- and multi-valued mappings within complete vector-valued metric spaces. Through the utilization of binary relations and $\theta$-contraction, this study advances and refines the Perov-type fixed-point results in the literature. Furthermore, this article furnishes examples to substantiate the validity of the presented results. Additionally, we establish an application for finding the existence of solutions to a system of matrix equations. Full article