Search Results (962)

This study investigates the scheduling problem of return communication tasks for unmanned aerial vehicle (UAV) swarms, where disaster relief environmental global positioning is hampered. To characterize the utility of these tasks and optimize scheduling decisions, we developed a time window-constrained scheduling model that operates under constraints, including communication base station time windows, battery levels, and task uniqueness. To solve the above model, we propose an enhanced algorithm through integrating Dueling Deep Q-Network (Dueling DQN) into adaptive large neighborhood search (ALNS), referred to as Dueling DQN-ALNS. The Dueling DQN component develops a method to update strategy weights, while the action space defines the destruction and selection strategies for the ALNS scheduling solution across different time windows. Meanwhile, we design a two-stage algorithm framework consisting of centralized offline training and decentralized online scheduling. Compared to traditionally optimized search algorithms, the proposed algorithm could continuously and dynamically interact with the environment to acquire state information about the scheduling solution. The solution ability of Dueling DQN is 3.75% higher than that of the Ant Colony Optimization (ACO) algorithm, 5.9% higher than that of the basic ALNS algorithm, and 9.37% higher than that of the differential evolution algorithm (DE). This verified its efficiency and advantages in the scheduling problem of return communication tasks for UAVs. Full article

The neural architecture search technique is used to automate the engineering of neural network models. Several studies have applied this approach, mainly in the fields of image processing and natural language processing. Its application generally requires very long computing times before converging on the optimal architecture. This study proposes a hybrid approach that combines transfer learning and dynamic search space adaptation (TL-DSS) to reduce the architecture search time. To validate this approach, Long Short-Term Memory (LSTM) models were designed using different evolutionary algorithms, including artificial bee colony (ABC), genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO), which were developed to predict trends in global horizontal irradiation data. The performance measures of this approach include the performance of the proposed models, as evaluated via RMSE over a 24-h prediction window of the solar irradiance data trend on one hand, and CPU search time on the other. The results show that, in addition to reducing the search time by up to 89.09% depending on the search algorithm, the proposed approach enables the creation of models that are up to 99% more accurate than the non-enhanced approach. This study demonstrates that it is possible to reduce the search time of a neural architecture while ensuring that models achieve good performance. Full article

This study presents a comprehensive computational analysis of flow rate efficiency during uranium extraction via the In Situ Recovery method. Using field data from a deposit located in Southern Kazakhstan, a series of mathematical models were developed to evaluate the distribution and balance of leaching solution. A reactive transport model incorporating uranium dissolution kinetics and acid–rock interactions were utilized to assess the accuracy of both traditional and proposed methods. The results reveal a significant spatial imbalance in sulfuric acid distribution, with up to 239.1 tons of acid migrating beyond the block boundaries. To reduce computational demands while maintaining predictive accuracy, two alternative methods, a streamline-based and a trajectory-based approach were proposed and verified. The streamline method showed close agreement with reactive transport modeling and was able to effectively identify the presence of intra-block reagent imbalance. The trajectory-based method provided detailed insight into flow dynamics but tended to overestimate acid overflow outside the block. Both alternative methods outperformed the conventional approach in terms of accuracy by accounting for geological heterogeneity and well spacing. The proposed methods have significantly lower computational costs, as they do not require solving complex systems of partial differential equations involved in reactive transport simulations. The proposed approaches can be used to analyze the efficiency of mineral In Situ Recovery at both the design and operational stages, as well as to determine optimal production regimes for reducing economic expenditures in a timely manner. Full article

Understanding how prey and predator species partition activity patterns across time and space is essential for elucidating behavioral adaptation and ecological coexistence. In this study, we examined the diel and seasonal activity rhythms of two sympatric rodent species—Rhombomys opimus (Great gerbil) and Meriones meridianus (Midday gerbil)—and their primary predators, Otocolobus manul (Pallas’s cat) and Vulpes vulpes (Red fox), in a desert-steppe ecosystem on the northern slopes of the Qilian Mountains, China. Using over 8000 camera trap days and kernel density estimation, we quantified their activity intensity and spatiotemporal overlap. The two rodent species showed clear temporal niche differentiation but differed in their synchrony with predators. R. opimus exhibited a unimodal diurnal rhythm with spring activity peaks, while M. meridianus showed stable nocturnal activity with a distinct autumn peak. Notably, O. manul adjusted its activity pattern to partially align with that of R. opimus, whereas V. vulpes maintained a crepuscular–nocturnal rhythm overlapping more closely with that of M. meridianus. Despite distinct temporal rhythms, both rodent species shared high spatial overlap with their predators (overlap index OI = 0.64–0.83). These findings suggest that temporal partitioning may reduce predation risk for R. opimus, while M. meridianus co-occurs more extensively with its predators. Our results highlight the ecological role of native carnivores in rodent population dynamics and support their potential use in biodiversity-friendly rodent management strategies under arid grassland conditions. Full article

A multi-step method introduced by Raziyeh and Masoud for solving nonlinear systems with convergence order five has been considered in this paper. The convergence of the method was studied using Taylor series expansion, which requires the function to be six times differentiable. However, our convergence study does not depend on the Taylor series. We use the derivative of F up to two only in our convergence analysis, which is presented in a more general Banach space setting. Semi-local analysis is also discussed, which was not given in earlier studies. Unlike in earlier studies (where two sets of assumptions were used), we used the same set of assumptions for semi-local analysis and local convergence analysis. We discussed the dynamics of the method and also gave some numerical examples to illustrate theoretical findings. Full article

The proliferation of biometric technology across various domains including user identification, financial services, healthcare, security, law enforcement, and border control introduces convenience in user identity verification while necessitating robust protection mechanisms for sensitive biometric data. While chaos-based encryption systems offer promising solutions, many existing chaos-based encryption schemes exhibit inherent shortcomings including deterministic randomness and constrained key spaces, often failing to balance security robustness with computational efficiency. To address this, we propose a novel dual-layer cryptographic framework leveraging a four-dimensional (4D) Qi hyperchaotic system for protecting biometric templates and facilitating secure feature matching operations. The framework implements a two-tier encryption mechanism where each layer independently utilizes a Qi hyperchaotic system to generate unique encryption parameters, ensuring template-specific encryption patterns that enhance resistance against chosen-plaintext attacks. The framework performs dimensional normalization of input biometric templates, followed by image pixel shuffling to permutate pixel positions before applying dual-key encryption using the Qi hyperchaotic system and XOR diffusion operations. Templates remain encrypted in storage, with decryption occurring only during authentication processes, ensuring continuous security while enabling biometric verification. The proposed system’s framework demonstrates exceptional randomness properties, validated through comprehensive NIST Statistical Test Suite analysis, achieving statistical significance across all 15 tests with p-values consistently above 0.01 threshold. Comprehensive security analysis reveals outstanding metrics: entropy values exceeding 7.99 bits, a key space of ${10}^{320}$, negligible correlation coefficients (<${10}^{-2}$), and robust differential attack resistance with an NPCR of 99.60% and a UACI of 33.45%. Empirical evaluation, on standard CASIA Face and Iris databases, demonstrates practical computational efficiency, achieving average encryption times of 0.50913s per user template for 256 × 256 images. Comparative analysis against other state-of-the-art encryption schemes verifies the effectiveness and reliability of the proposed scheme and demonstrates our framework’s superior performance in both security metrics and computational efficiency. Our findings contribute to the advancement of biometric template protection methodologies, offering a balanced performance between security robustness and operational efficiency required in real-world deployment scenarios. Full article

In this study, theorems and proofs related to spherical and focal curves are presented in the BCV-Sasakian space. An approximate solution to the differential equation characterizing spherical curves in the BCV-Sasakian manifold ${\mathfrak{M}}^3$ is obtained using the Taylor matrix collocation method. The general equations of canal and tubular surfaces are provided within this geometric framework. Additionally, the curvature properties of the tubular surface constructed around a non-vertex focal curve are computed and analyzed. All of these results are presented for the first time in the literature within the context of the BCV-Sasakian geometry. Thus, this study makes a substantial contribution to the differential geometry of contact metric manifolds by extending classical concepts into a more generalized and complex geometric structure. Full article

In this work, we consider a generalized form of the classical $(2+1)$-dimensional sine-Gordon system. The mathematical model considers a generalized reaction term, and the two-dimensional Laplacian includes the presence of space-fractional derivatives of the Riesz type with two different differentiation orders in general. The system is equipped with a conserved quantity that resembles the energy functional in the integer-order scenario. We propose a numerical model to approximate the solutions of the fractional sine-Gordon equation. A discretized form of the energy-like quantity is proposed, and we prove that it is conserved throughout the discrete time. Moreover, the analysis of consistency, stability, and convergence is rigorously carried out. The numerical model is implemented computationally, and some computer simulations are presented in this work. As a consequence of our simulations, we show that the discrete energy is approximately conserved throughout time, which coincides with the theoretical results. Full article

The Navier equations are reformulated to be third-order partial differential equations. New anti-Cauchy-Riemann equations can express a general solution in 2D space for incompressible materials. Based on the third-order solutions in 3D space and the Boussinesq–Galerkin method, a third-order method of fundamental solutions (MFS) is developed. For the 3D Navier equation in linear elasticity, we present three new general solutions, which have appeared in the literature for the first time, to signify the theoretical contributions of the present paper. The first one is in terms of a biharmonic function and a harmonic function. The completeness of the proposed general solution is proven by using the solvability conditions of the equations obtained by equating the proposed general solution to the Boussinesq–Galerkin solution. The second general solution is expressed in terms of a harmonic vector, which is simpler than the Slobodianskii general solution, and the traditional MFS. The main achievement is that the general solution is complete, and the number of harmonic functions, three, is minimal. The third general solution is presented by a harmonic vector and a biharmonic vector, which are subjected to a constraint equation. We derive a specific solution by setting the two vectors in the third general solution as the vectorizations of a single harmonic potential. Hence, we have a simple approach to the Slobodianskii general solution. The applications of the new solutions are demonstrated. Owing to the minimality of the harmonic functions, the resulting bases generated from the new general solution are complete and linearly independent. Numerical instability can be avoided by using the new bases. To explore the efficiency and accuracy of the proposed MFS variant methods, some examples are tested. Full article

Peak detection is a fundamental task in spectral and time-series data analysis across diverse scientific and engineering disciplines, yet traditional approaches are highly sensitive to the choice of algorithm parameters, complicating reliable and consistent interpretation. Triggered by the requirement for the energy calibration for the 128 detectors of the PI3SO gamma ray scanner, we introduce a versatile methodology inspired by concepts from persistent homology, extending the traditional notion of persistence to a multi-parameter setting. Our approach systematically explores the space defined by multiple detection parameters and quantifies peak robustness through the hyper-volume in the parameter space where each peak is consistently identified. This volumetric multi-parameter persistence (VM-PP) measure enables robust peak ranking and significantly reduces the sensitivity of detection outcomes to individual parameter selection, demonstrating utility across simulated and experimental spectral datasets. Extensive validation reveals that this method reliably differentiates genuine peaks from noise-induced fluctuations under diverse noise conditions, proving effective in practical spectroscopic calibration scenarios. This framework, general by design, can be readily adapted to diverse signal-processing applications, enhancing interpretability and reliability in complex feature-detection tasks. Full article

This study estimates a willingness-to-pay (WTP) space mixed logit model to evaluate user valuations of travel time, safety, and comfort attributes associated with common access modes in Bangkok, including walking, motorcycle taxis, and localized minibuses. The model accounts for preference heterogeneity by specifying random parameters for travel time. Results indicate that users—exhibiting substantial variation in preferences—place higher value on reducing motorcycle taxi travel time, particularly in time-constrained contexts such as peak-hour commuting, whereas walking is more acceptable in less pressured settings. Safety and comfort attributes—such as helmet availability, smooth pavement, and seating—significantly influence access mode choice. Notably, the WTP for helmet availability is estimated at THB 8.04 per trip, equivalent to approximately 40% of the typical fare for station access, underscoring the importance of safety provision. Women exhibit stronger preferences for motorized access modes, reflecting heightened sensitivity to environmental and social conditions. This study represents one of the first applications of WTP-space modeling for valuing informal station access transport in Southeast Asia, offering context-specific and segment-level estimates. These findings support targeted interventions—including differentiated pricing, safety regulations, and service quality enhancements—to strengthen first-/last-mile connectivity. The results provide policy-relevant evidence to advance equitable and sustainable transport, particularly in rapidly urbanizing contexts aligned with SDG 11.2. Full article

The present paper examines a novel exact solution to nonlinear fractional partial differential equations (FDEs) through the Sardar sub-equation method (SSEM) coupled with Jumarie’s Modified Riemann–Liouville derivative (JMRLD). We take the (3+1)-dimensional space–time fractional modified Korteweg-de Vries (KdV) -Zakharov-Kuznetsov (ZK) equation as a case study, which describes some intricate phenomena of wave behavior in plasma physics and fluid dynamics. With the implementation of SSEM, we yield new solitary wave solutions and explicitly examine the role of the fractional-order parameter in the dynamics of the solutions. In addition, the sensitivity analysis of the results is conducted in the Galilean transformation in order to ensure that the obtained results are valid and have physical significance. Besides expanding the toolbox of analytical methods to address high-dimensional nonlinear FDEs, the proposed method helps to better understand how fractional-order dynamics affect the nonlinear wave phenomenon. The results are compared to known methods and a discussion about their possible applications and limitations is given. The results show the effectiveness and flexibility of SSEM along with JMRLD in forming new categories of exact solutions to nonlinear fractional models. Full article

Ensuring food security necessitates a high level of coordinated development between agricultural trade and production. Based on China’s provincial panel data from 2010 to 2023, this study constructs an evaluation index system for agricultural trade and production, employing an entropy-weighted TOPSIS model to measure their development levels. On this basis, a coupling coordination degree model and Moran’s I indices are used to analyze the coordinated development level’s temporal changes and spatial effects. The research finds that the development levels of China’s agricultural trade and production show an upward trend but currently still exhibit the pattern of higher levels in Eastern China and lower levels in Western China. The coupling coordination level between them demonstrates an increasing trend, yet the overall level remains relatively low, with an average value of only 0.445, consistently staying in a marginal disorder “running-in stage” and spatially presenting a distinct “east-high–west-low” stepped distribution pattern. Furthermore, from a spatial perspective, the Global Moran’s index decreased from 0.293 to 0.280. The coupling coordination degree of agricultural trade and production in China generally exhibits a positive spatial autocorrelation, but this effect has been weakening over time. Most provinces show spatial clustering characteristics of high–high and low–low agglomeration in local space, and this feature is relatively stable. Building on these insights, this study proposes a refinement of the coordination mechanisms between agricultural trade and production, alongside the implementation of differentiated regional coordinated development strategies, to promote the coupled and coordinated advancement of agricultural trade and production. Full article

Background/Objectives: The accurate localization of interfascial planes is critical for effective regional anesthesia, yet current techniques relying on ultrasound guidance can be challenging, especially in obese or pediatric patients. Previous cadaveric and clinical studies have suggested that injection pressure varies depending on needle placement relative to fascial and neural structures. This pilot study aimed to evaluate whether the continuous monitoring of injection pressure can reliably differentiate interfascial spaces from surrounding anatomical structures in a porcine tissue model. Methods: A custom-built pressure monitoring system was used to continuously measure saline injection pressure during regional block procedures performed on porcine thighs. Injections were guided by ultrasound and conducted using an infusion pump. Needle positions were classified as intramuscular, resting on fascia, or interfascial. Statistical comparisons of pressure levels, variability, and temporal trends were conducted using Wilcoxon signed-rank tests and regression analysis. Results: Mean intramuscular pressure was significantly higher than the mean interfascial pressure (p < 1 × 10⁻¹³). Interfascial injections demonstrated lower pressure variability (p = 2.1 × 10⁻⁴) and an increasing trend in pressure over time (p = 2.1 × 10⁻⁴), whereas intramuscular injections exhibited a decreasing pressure trend (p = 3.15 × 10⁻³). Conclusions: Continuous pressure monitoring effectively distinguishes interfascial from intramuscular and fascial penetration phases during regional anesthesia. The method demonstrates potential as a real-time, objective tool for enhancing needle guidance and improving the safety and accuracy of interfascial plane blocks. Further cadaveric and clinical studies are warranted to validate these findings. Full article

Material stocks (MS) serve as essential physical foundations for socio–economic systems, reflecting the accumulation, transformation, and consumption of resources over time and space. Positioned at the intersection of environmental and socio–economic systems, MS are increasingly recognized as leverage points for advancing sustainability. However, there is currently a lack of comprehensive overview, making it difficult to fully capture the latest developments and cutting–edge research. We adopt a systems perspective to conduct a comprehensive bibliometric and thematic review of 602 scholarly publications on MS research. The results showed that MS research encompasses has three development periods: preliminary exploration (before 2007), rapid development (2007–2016), and expansion and deepening (after 2016). MS research continues to deepen, gathering multiple teams and differentiating into diverse topics. MS research has evolved from simple accounting to intersection with socio–economic, resources, and environmental systems, and shifted from relying on statistical data to integrating high–spatio–temporal–resolution geographic big data. MS research is shifting from problem revelation to problem solving, constantly achieving new developments and improvements. In the future, it is still necessary to refine MS spatio–temporal distribution, reveal MS’s evolution mechanism, establish standardized databases, strengthen interaction with other systems, enhance problem–solving abilities, and provide powerful guidance for the formulation of dematerialization and decarbonization policies to achieve sustainable development. Full article