The Internet of Things (IoT) has transformed modern computing ecosystems by enabling large-scale data generation and real-time analytics. Traditional database optimizers and offline-trained predictive models often fail under sudden workload shifts and concept drift, resulting in degraded performance and high resource consumption. ALP-DB continuously learns from evolving IoT workloads, autonomously reconfigures database parameters, and ensures compliance with latency and energy constraints. Experimental evaluation using real-world and synthetic IoT workloads demonstrates that ALP-DB outperforms static, heuristic, and reinforcement learning-based baselines by reducing average query latency by up to 28%, tail latency by 35%, and energy consumption by 20%, while maintaining low reconfiguration overhead.

Indoor positioning systems (IPS) suffer from errors due to signal interference, sensor inaccuracies, and environmental changes. The challenges associated with the accuracy of the Indoor Positioning System (IPS) through the Received Signal Strength Indicato (RSSI) are plenty. The raw signals are prone to signal interference and multipath fading, and the quality of the received signal is severely impacted in indoor setups due to the internal structure of the walls and the presence of concrete walls, iron structures, metallic furniture, and different electrical wiring objects. All these factors lead to the deterioration of the quality of the signal received. In this paper, we illustrate a novel approach to position estimation based on a Feedback-Enhanced Federated Kalman Filter (FE-FKF) that enhances the accuracy of the Indoor Positioning System work on Federated Kalman Filter (FKF). The novel approach compares the estimated position with a predefined map and gives feedback to the Master filter to update the position. when an anomaly is identified by the error detection mechanism, feedback is relayed to the filter to tune its future estimations by incorporating the rectification request received. In this way, this approach rectifies the errors dynamically, thereby increasing the overall accuracy of the IPS. We evaluate the results of the proposed FE-FKF approach with other methods, such as the Federated Kalman Filter (FKF) on “Position-Annotated-BLE-RSSI-Dataset” from Kaggle. The comparative study of the results concludes that the Mean-Absolute Error (MAE) is significantly reduced with the FE-FKF approach by 18%. Additionally, the inclusion of floor map constraints during the Error Detection Mechanism shows that the position estimation resulting from the proposed study is closely associated with real-world layouts, with improved system robustness and reliability, thereby enhancing applicability in different indoor setups.

In this paper, the multi-objective (multiple criteria, vector) optimization is considered. Some examples of such optimization problems are presented, Pareto optimality is introduced, and arbitrage schemes are described. The special case of multi-objective linear optimization is studied, and methods for solving such problems are presented. Pareto optimality for the nonlinear optimization problem is also considered.

This work discusses inventory model based on EMQ, process variance setting, quality investment and parameters of sampling inspection. It also considers a long-term quality improvement tool for decreasing bias of product.

This study investigates the flow patterns around square as well as inclined cylinders, a critical area in civil engineering due to their complex flow interactions. The research objectives are to conduct numerical analyses in two dimensions to understand the flow behavior around inclined square cylinders and those enclosed by parallel surfaces, focusing on vortex shedding and flow dynamics at varying Reynolds numbers (Re) from 40 to 200. Key findings reveal that vortex shedding frequencies and Strouhal numbers (St) were calculated for different Re values, showing increased turbulence with higher Re. The inclination of the square cylinder caused significant changes in flow characteristics, including abrupt shifts in separation points and variations in drag and lift forces. Quantitative results included detailed streamlines, flow velocities, vortex shedding frequencies, and Strouhal numbers values across a range of inlet velocities and Reynolds numbers. The practical implications of these research findings are significant because velocity distributions show that asymmetric vortex flows occur around inclined cylinders at Reynolds numbers of 100 and 200. When building slanted structures to withstand approaching winds, civil engineers must consider these facts.

In this article, the paper addresses a modified EMQ model with inspection. For the process parameters problem, one considers that quadratic loss function with process adjustment cost. For the integrated model, one considers the specified process capability index with consumer’s risk.

We introduce a projectile model for pandemics which shows that a pandemic without control spreads in log-time scale within a population in the form of a mechanical projectile in a free atmosphere. Hence, a controlled pandemic behaves like a “decayed” projectile motion in a resistive atmosphere. If β is the “decay polynomial” associated with the decay in amplitude and range of a projectile in a resistive atmosphere, then U by analogy will be the “control polynomial” associated with the reduction in intensity and duration of a pandemic due to control measures. By comparing the r-square of the best-fit polynomial to β (i.e Rβ 2) to the r-square of the same-degree best-fit polynomial to U (i.e Rμ 2), the parameter; ϵ = Rβ 2/Rμ 2 serves the purpose of assessing pandemic control levels for different populations. The above framework was used to assess early transmission and control of COVID-19 in 20 high-burden countries from World Health Organization (WHO) COVID-19 case trends within the first half of year 2020. Four clusters were segregated using the ϵ parameter. China and countries from Europe and North America, appeared in Cluster 1- with the most effective early COVID-19 control, while countries with less effective control mainly from Africa (although with the least transmission), Asia and South America appeared in Clusters 2, 3 and 4. The framework achieves the purpose of obtaining an objective metric for pandemic control assessment; hence China with ϵ = 1.1 showed a near projectile-type controlled transmission so that the measures adopted by China may serve as model for future pandemic control especially in Africa where poor medical and social infrastructure was evident in the poor handling of the pandemic.

Regarding r-Pell numbers, we provide some identities. The r-Pell numbers with negative subscripts are shown below. The binomial summations for the r-Pell numbers are obtained. Several identities pertaining to r-Pell hybrid numbers are provided. We provide the negative subscripted r-Pell hybrid numbers. We develop various Cassini identities for the conjugate of the r-Pell hybrid numbers in accordance with two different determinant definitions of a hybrid square matrix (whose entries are hybrid numbers).

This work is about a suitable numerical method based on the Muntz-Legendre polynomials for solving a type of the generalized Abel integral equations. The propose method approximates the unknown function with the Muntz-Legendre polynomials. To do this, we apply these functions and using Muntz-Galerkin method for the numerical solutions of this problem. Also, the stability and uniqueness of the solution by this scheme will be shown. Moreover, the convergence of this algorithm will be proved by preparing some theorems. Several numerical examples are presented to show the superiority and efficiency of current method.

Challenges in composite number factorization are critical to the fields of information systems security and cryptography. This study meticulously examined the features of triangular numbers and systematically created a Factoring Table for both triangular and non-triangular numbers, enabling the factorization of any composite number. In turn, the study presents a novel number factorization algorithm, derived from this table and articulated through both a formula and instructions. Furthermore, the demonstration of primality testing was revealed to differentiate it from composite numbers. The specified algorithm can enhance the knowledge and security of key generation for the Rivest-Shamir-Adleman (RSA) system.