Search Results (1,908)

In this paper, we study the weighted approximation properties of a family of Szász–Mirakyan-type operators preserving two exponential functions on the unbounded interval $[0,\infty )$. The operators act on exponential weighted spaces and are analyzed within the framework of positive linear operator theory. We first establish their well-definedness and boundedness between suitable weighted spaces. By applying a weighted Korovkin-type theorem, we prove convergence in the corresponding weighted norm. Furthermore, we obtain quantitative estimates in terms of a weighted modulus of continuity and derive an order of convergence result. A Voronovskaya-type asymptotic formula is also established, describing the precise asymptotic behavior of the operators. Numerical examples are included to support the theoretical results. Full article

The new-generation aeration blower, which uses a high-speed permanent-magnet synchronous motor supported by elastic-foil thrust bearings, represents the future development trend of high-end sewage treatment turbomachinery. An axial load tester was designed for the elastic-foil thrust bearings in this study. Firstly, the relationship between the axial load and the elastic-foil thrust bearing parameters was first established. An axial load tester was designed. Secondly, finite-element simulation and strain calibration of the axial load tester were performed to estimate the linear relationship between the strain and the axial load. Then, the time histories of axial load for the high-speed permanent-magnet synchronous motor were further obtained at a rotational speed of 15,000 rpm during the operation tests. Finally, the load spectrum was compiled by fitting the test data to a function. The results showed that the amplitude and frequency of the load spectrum obeyed an exponential decay function. It can be used for the life test of elastic-foil thrust bearings in the future. The method for obtaining the axial load in the direct-driven turbomachinery was proposed. The axial load tester proposed in the present study, based on operation tests, proves valuable for improving the performance of the high-speed permanent magnetic synchronous motor and the elastic-foil thrust bearing. Full article

This paper introduces a q-deformed extension of the Lindley distribution. This extension is obtained by replacing the classical exponential with the q-exponential function from Tsallis non-extensive statistical techniques. This transformation offers more control over the tail behavior of the distribution, providing a transition between exponential and power-law decay patterns. Such flexibility is particularly useful when modeling right-skewed data with excess kurtosis, where classical models may not adequately describe heavy-tailed and highly skewed data. We derive several key properties, including the quantile function, expressed by the Lambert–Tsallis function $W_q$, the raw and incomplete moments, the probability-weighted moments, and the Tsallis entropy. The distribution of order statistics is also investigated. For parameter estimation, we employ several frequentist methods and conduct extensive Monte Carlo simulation studies to assess and compare their performance. Finally, applications to real-world datasets show that the q-deformed Lindley model is practically superior and more flexible than the classical Lindley distribution and other well-known models. Full article

Time-reversible synchronization (TRS) of nonlinear oscillators is a recently proposed technique that ensures super-exponential convergence of dynamics between master and slave systems, which is beneficial in many real-time applications. Nevertheless, this approach has not been demonstrated in any real-time embedded system to practically verify it and quantitatively estimate its advantages. Furthermore, previous studies did not consider the application of time-reversible synchronization to a wide, practically relevant class of chaotic systems with piecewise-linear nonlinearity. To fill these gaps, in this work, we developed an FPGA-based time-reversible synchronization controller for the analog Chua circuit and its digital counterpart. To achieve complete synchronization, we first reconstructed dynamical equations of the circuit. Then, we performed a rigorous theoretical analysis of synchronization possibility between analog and digital systems by each single variable. Next, we implemented the digital model of the Chua circuit in the MyRIO-1900 FPGA using the reconstructed dynamical model and showed its capability of digital-to-analog and analog-to-digital conventional Pecora–Carroll (PC) synchronization. Then, an algorithm of time-reversible synchronization on MyRIO-1900 was tested, achieving complete synchronization at the predefined normalized RMSE level of 0.01, requiring an average of 8.0 fewer points and a median of 10.1 fewer points than the PC synchronization. Finally, we implemented a proof-of-concept version of a capacitive sensor based on the analog Chua circuit with an FPGA-based observer using PC synchronization or the TRS algorithm with a heuristic selection of a starting point. Our experiments reveal that when using the TRS algorithm, the time needed to detect a pre-selected 3% level of capacitance change is reduced by a mean factor of 4 and a median factor of 4.9 in comparison with the conventional PC synchronization. This allows for using the developed solution in applications where the synchronization rate is crucial, including chaos-based sensing, communication, and monitoring. Full article

This paper presents a new distribution on the unit interval, named the Unit Arcsine–Rayleigh distribution (UASRD), which is the result of the exponential transformation of the Arcsine–Rayleigh distribution. The model suggested is versatile and can be used in modeling limited reliability and proportion data. Entropy-based measures are also studied to determine the uncertainty and information content of the proposed model and further explain the probabilistic nature of the proposed model and its potential applicability in information-theoretic and reliability tasks. These findings demonstrate the utility of the suggested model in the study of the limited data in the context of information theory. Basic statistical characteristics are derived, such as cumulative and density functions, quantile function, reliability and hazard functions, and ordinary moments. Estimation of parameters is obtained through approaches of maximum likelihood and maximum product spacing and Bayesian estimation of parameters. The performance of the estimators is also assessed by a Monte Carlo simulation study, and the application of real data shows the utility of the proposed model to the analysis of bounded data. Full article

This paper introduces a new family of distributions called exponentiated Harris-G. This new distribution is a weighted distribution of the well established exponentiated-G distributions. The model allows for easy derivation of statistical properties based on the exponentiated-G distribution. Several statistical properties for the new model were derived. The paper considered different parameter estimation techniques and the maximum likelihood estimation technique emerged as the best technique. This was evaluated via Monte Carlo simulation studies of the proposed family. Estimation techniques were ranked based on the lowest values of the root mean square error and average bias. The proposed model showed enhanced flexibility in data modeling when compared to some selected competing models. This was demonstrated through application of the special case to two real-world datasets. Full article

Urbanisation reshapes Land Cover and Land Use (LCLU) by driving deforestation, wetland loss, and the conversion of natural and agricultural areas into built environments. However, integrated analyses of LCLU change in response to climate variability in topographically complex, rapidly urbanising African cities remain limited. Therefore, this study examined 2000–2024 LCLU changes in hilly Gasabo District (Kigali, Rwanda) using 30 m Landsat imagery and a Random Trees classifier (92.7% accuracy, 70/30 train-test split), with 2032 projections via a population-driven hybrid trend model. Population estimates/projections 320,516 in 2002 to 967,512 in 2024, 1.41 million by 2032, were derived from Rwanda’s census data and exponential growth modelling (calibrated to 5.05% annual growth). Rapid population growth has driven a 539% expansion of Built-up Areas, accompanied by notable declines in cropland and Forest. Local climate trends (Meteo Rwanda stations) aligned with global datasets (ERA5-Land and CHIRPS): rainfall fluctuation and temperature rose, with strong correlations between population-driven Built-up Areas expansion. From 2024 to 2032, LCLU projections indicate that Built-up Areas will continue to expand by 29.5%. Cropland was forecast to decline to 15.9%, while Forest loss slowed to 5.7%. MLR analysis revealed strong correlations between population-driven expansion of Built-up Areas, cropland/forest loss, warming, and rainfall fluctuations in Gasabo. An ARDL model was applied to address multicollinearity among LCLU predictors, which limited the interpretation of individual coefficients, and confirmed the core MLR correlation trends, with statistically significant (p < 0.05) coefficients. The results highlight the need for data-driven spatial planning in Gasabo (stricter zoning, high-rise buildings, targeted reforestation, climate-resilient green infrastructure) to mitigate population and urbanisation-driven environmental degradation. Full article

In this article, we numerically investigate the effects of noise and heterogeneity on a model of immune–tumor cell interactions. We focus on stochastic dynamics and simulation-based analysis of the time required for tumor elimination. We identify the existence of a bistable response, which is disrupted by the introduction of intrinsic noise into the system. In particular, we characterize noise-induced transitions using first-passage time statistics and waiting-time distributions. We discuss various scenarios of tumor elimination, including the impact of vitamin intake and chemotherapy on tumor cell count, mean elimination time, and the duration of tumor dominance. Our results show that increasing chemotherapy reduces the maximum tumor count and decreases the average tumor elimination time, while intrinsic noise promotes memoryless switching toward the tumor-free state. This behavior is explained by the emergence of a quasi-stationary distribution governing the metastable tumor-present regime, leading to exponentially distributed extinction times. Furthermore, this framework enables the decay rate $\lambda$ to be estimated from simulation data and related to treatment parameters $({\beta }_1,\gamma )$. These findings provide a theoretical and statistical justification for memoryless tumor elimination dynamics and offer quantitative insights into stochastic treatment outcomes. Full article

The main focus of this paper is to introduce a new probability model. Specifically, this paper presents a modified form of the Weibull distribution and investigates its various statistical properties, such as moments, moment-generating functions, reliability functions, quantile functions, and inequality measures such as Bonferroni and Lorenz curves. It also investigates the mean absolute deviation and entropy. Distributions of order statistics, reversed order statistics, and upper record values are also obtained. Additionally, univariate and bivariate moment structures are considered. The model parameters are estimated via the maximum likelihood method under simple random sampling and ranked set sampling, allowing an empirical evaluation of efficiency and reliability. Graphical representations exhibit the flexibility of the model, capturing various shapes in the probability density and hazard rate functions. To measure the practical quality of the model, actuarial metrics are used. A comparative analysis based on insurance, biomedical, and reliability datasets demonstrates the empirically improved performance and stability of the proposed new model for these specific datasets. Full article

Water plays a critical role in residential consumption, accounting for a significant share of public water supply use. With increasing concerns over water scarcity and projections that a large portion of the global population will experience water stress by 2050, the need for effective water conservation strategies has become more urgent. This study evaluates the application and combined impact of water conservation measures in single-family homes. A deterministic modeling framework is developed to estimate household water consumption and conservation potential across four U.S. cities, namely, Houston, Phoenix, Las Vegas, and Des Moines, representing diverse climatic conditions. The analysis incorporates rainwater harvesting, HVAC condensate recovery, water-efficient fixtures, and greywater reuse systems. Scenario-based forecasting, including adoption rates of 1% and 5% of existing homes alongside new construction, is conducted over a six-year period using exponential smoothing techniques. Results indicate that the combined implementation of these measures can generate substantial aggregate water savings, with outcomes varying by climate and location. Greywater reuse and water-efficient fixtures consistently provide the largest contributions, while rainwater harvesting and condensate recovery depend more heavily on regional conditions. These findings highlight the importance of integrated and location-specific strategies and demonstrate the potential of decentralized, residential-level interventions to reduce demand on municipal water systems. Full article

Offshore wind turbine operation and maintenance in complex sea states is influenced by the coupled effects of low-frequency vessel drift and high-frequency wave-induced disturbances. In practical operations, the ship dynamic positioning system primarily regulates low-frequency motion through vessel position control, whereas a boarding compensation system is required to attenuate high-frequency six-degrees-of-freedom motions to ensure safe personnel transfer. This study establishes coupled kinematic mapping among the ship dynamic positioning system, the Stewart platform, and a three-degrees-of-freedom gangway and proposes a hierarchical cooperative control architecture. At the upper layer, an extended Kalman filter and an exponential moving average low-pass filter are employed for online state estimation and for separating low-frequency and high-frequency components. A Kalman filter lookahead predictor is then used to generate a short-horizon prediction of the high-frequency component and to construct a feedforward reference signal. At the middle layer, the feedforward reference and the gangway end error feedback are coordinated at the velocity level, and a quadratic programming-based allocation strategy distributes compensation tasks between the Stewart platform and the gangway under safety-related constraints, including actuator stroke limits and singularity avoidance. At the lower layer, a robust feedback controller is designed for the gangway to mitigate modeling uncertainties and environmental disturbances and to ensure stable tracking. MATLAB R2024a-based simulations under representative wave conditions demonstrate that the proposed architecture improves end effector tracking accuracy and closed-loop stability compared with baseline strategies, providing a feasible engineering solution for shipboard boarding operations in complex sea states. Full article

Wireless communication networks based on IEEE 802.15.4 and ZigBee PRO constitute a critical component of smart grid infrastructures, where reliability and availability requirements exceed those typically assumed in low-power wireless deployments. Despite extensive analytical modeling, most existing studies rely on independence assumptions for packet errors and simplified abstractions of reassociation dynamics. This work presents stochastic reliability characterization grounded on real MAC-layer traffic capture from an operational IEEE 802.15.4/ZigBee PRO network. The methodology combines statistical hypothesis testing, first-order Markov modeling, spectral-gap analysis, large-deviation theory, renewal processes, and survival analysis of realignment intervals. Empirical results reject the hypothesis of independent frame errors and demonstrate significant temporal dependence with geometric mixing behavior. The estimated transition structure reveals burst-error persistence, inflating long-run variance relative to memoryless models. Furthermore, coordinator realignment intervals deviate from exponential behavior, exhibiting non-constant event rates consistent with regenerative dynamics. These findings indicate that effective communication reliability is governed not only by average frame error probability but also by dependence structure and regeneration mechanisms. The proposed probabilistic framework provides a rigorous and reproducible methodology for dependence-aware reliability assessment in smart grid communication systems. Full article

Understanding how Bitcoin mining is distributed across countries is important for evaluating both the sustainability and resilience of the network. In this study, we examine the evolution of total Bitcoin electricity consumption alongside the geographic distribution of Bitcoin mining. Data are provided by the Cambridge Centre for Alternative Finance (Licensed under CC BY–NC–SA 4.0): Annual data from the Cambridge Bitcoin Electricity Consumption Index (2010–2025) and a monthly panel of country-level Bitcoin hashrate shares for 105 countries (September 2019–January 2022). To assess the degree of decentralization in the global mining network, we employ entropy-based measures, inequality indices, and panel convergence tests. The results indicate that total electricity consumption grew exponentially during the early years of Bitcoin, but later transitioned to a more stable and approximately linear path. Country-level permutation entropy reveals highly volatile and dynamic mining trajectories. The Theil index shows that cross-sectional inequality declines over time, while increasing symbolic entropy reflects a progressively more even cross-country distribution of mining activity. Further evidence from $\sigma$-convergence supports a statistically significant reduction in cross-country dispersion of mining shares. Dynamic panel fixed-effects estimates reveal mean-reverting behavior in relative country shares, consistent with stochastic convergence. Finally, Phillips–Sul analysis points to heterogeneous early transition paths but ultimately supports convergence toward a single global club. The gradual geographical decentralization occurs alongside persistent core–periphery asymmetries in long-run mining shares. Overall, our findings suggest that Bitcoin mining behaves as a globally integrated industry in which computational capacity reallocates rapidly across countries in response to economic and regulatory conditions. Full article

This bibliometric study examines artificial intelligence’s impact on sustainable water management through systematic analysis of 424 publications from Scopus, Web of Science, and IEEE Xplore following the 2020 PRISMA guidelines. Four analytical approaches were implemented: descriptive bibliometric characterization, VOSviewer network visualization, principal component analysis with Ward’s hierarchical clustering (86.58% variance explained, cophenetic correlation = 0.951), and qualitative synthesis. The results reveal exponential growth from 4 publications (2018) to 167 (2025) with geographic concentration in China (30.2%), the USA (9.7%), and India (8.0%). Collaboration networks exhibit pronounced fragmentation (density = 0.04, modularity = 0.78) with minimal North–South partnerships (12%). Critically, keyword analysis identifies five thematic clusters dominated by machine learning methodologies, whereas governance and equity dimensions appear fewer than eight times, revealing a fundamental gap wherein technical optimization proceeds without the institutional frameworks necessary for equitable water access. Multivariate analysis suggests that technological infrastructure capacity is a stronger correlate of research output than geographic water stress, based on the observed geographic distribution of high-output nations rather than direct operationalization of scarcity indicators. The qualitative synthesis revealed that 68% of the studies remained pilot-scale studies, 82% were concentrated in developed nations, and 66% cited data quality as the primary constraint. The bibliometric patterns suggest a pronounced orientation toward computational approaches, alongside paradoxical AI infrastructure water consumption that may partially offset conservation benefits. (Note: 2025 figures reflect early-access articles retrieved before the November 2024 search date and should be interpreted as partial-year estimates.) Achieving sustainable water management requires a reorientation emphasizing measurement infrastructure in data-poor contexts, North–South partnerships, and the integration of socioinstitutional dimensions as constitutive elements within technical development frameworks. Full article

The literature indicates that the qubit requirements for factoring RSA-2048 remain on the order of 1 million, under commonly assumed architectures and error-correction models, leaving a substantial gap between current resource estimates and near-term practical feasibility. Reducing this requirement to the low-thousand-qubit regime therefore remains an important open research objective. This work proposes a hybrid classical–quantum algorithm that uses a classical modular exponentiation subroutine with a Quantum Number Theoretic Transform (QNTT) circuit to increase the speed and reduce the required quantum resources relative to Shor’s algorithm for integer factorization, which underpins cryptographic systems like RSA and ECC. We evaluate multiple coprime numbers, the result of multiplication of two primes, in both simulation and real quantum hardware, using IBM’s reference Shor implementation as the baseline. Because Shor and proposed Jesse–Victor–Gharabaghi (JVG) use different register sizes for the same coprime N, the reported gate/depth reductions should be interpreted as end-to-end quantum-resource budgets for factoring the same N, rather than a per-qubit or transform-only efficiency claim. In simulation, the JVG algorithm achieved substantial practical reductions in computational resources, decreasing runtime from 174.1 s to 5.4 s, memory usage from 12.5 GB to 0.27 GB, and quantum gate counts by approximately 99%. On quantum hardware, JVG reduced the required runtime from 67.8 s to 2 s, and the quantum gate counts by over 98%. We showed that the proposed algorithm can address the relevant RSA-1024 case scenario, establishing that this method can provide validation for large-scale situations. Furthermore, extrapolation to RSA-2048 indicates that the JVG algorithm significantly outperforms Shor’s approach, requiring a projected quantum runtime of 29 h for ten thousand runs for factorization under identical scaling assumptions. Overall, these results support JVG as a more hardware-compatible and robust noise-tolerant substitute for Shor’s framework, offering a viable research direction toward practical quantum integer factorization on near-term Noisy Intermediate-Scale Quantum (NISQ) devices. Full article