Search

Requirements Agile approaches have transformed engineering. This paper shows how RE in Agile software development has evolved from documentation-heavy to collaborative, adaptable, and customer-focused. Agile was born in the mid-1990s when the industry realized it needed to respond to changing client needs and market volatility. This evolution includes iterative development, client interaction, and emphasizing communication above documentation, as discussed in the paper. By comparing conventional and Agile RE approaches, we demonstrate the benefits of adapting to change, working with customers, and delivering functional software faster. This analysis provides a persuasive description of Agile RE implementation methodologies and resources through a detailed literature review and real-world experiences. User stories and backlog refinement are notable techniques. The research finishes by exploring how these techniques affect team dynamics, project success, and customer satisfaction. RE's Agile difficulties and opportunities are also examined. The findings illuminate RE methods' successful adaptation to Agile projects' dynamic character. Software development is more responsive and effective due to this adaptation. [ABSTRACT FROM AUTHOR]

Background: Agile methodology is known for delivering effective projects with added value within a shorter timeframe, especially in Business Intelligence (BI) system which is a valuable tool for informed decision-making. However, identifying impactful elements for successful BI implementation is complex due to the wide range of Agile attributes. Objective: This research aims to systematically review and analyze the integration of BI within Agile methodology, providing valuable guidance for future projects implementation, enhancing the understanding of effective application, and identifying influential factors. Methods: Based on the Kitchenham method, 19 papers were analyzed from 288 papers, sourced from databases like Scopus, ACM, IEEE, and others published in 2016-2022. Meanwhile the extracted key factors impacting agile BI implementation were validated by qualified expert. Results: Agile was discovered to provide numerous benefits to BI projects by promoting flexibility, collaboration, and rapid iteration for enhanced adaptability, while effectively addressing challenges including those related to technology, management, and skills gaps. In addition, Agile methods, including tasks such as calculating cycle time, measuring defect backlogs, mapping code ownership, and engaging end users, offered practical solutions. The advantages included adaptability, success, value enhancement, cost reduction, shortened timelines, and improved precision. The research additionally considered other critical Agile elements such as BI tools, Agile Practices, Manifesto, and Methods, thereby enhancing insights for successful implementation. Conclusion: In conclusion, the research outlined Agile BI implementation into seven key factor groups, validated by qualified expert, providing guidance for BI integration and practices, and establishing a fundamental baseline for future applications. [ABSTRACT FROM AUTHOR]

In this paper, we present a generalized adaptive Monte Carlo algorithm using the Diagonal and Off-Diagonal Splitting (DOS) iteration method to solve a system of linear algebraic equations (SLAE). The DOS method is a generalized iterative method with some known iterative methods such as Jacobi, Gauss-Seidel, and Successive Overrelaxation methods as its special cases. Monte Carlo algorithms usually use the Jacobi method to solve SLAE. In this paper, the DOS method is used instead of the Jacobi method which transforms the Monte Carlo algorithm into the generalized Monte Carlo algorithm. we establish theoretical results to justify the convergence of the algorithm. Finally, numerical experiments are discussed to illustrate the accuracy and efficiency of the theoretical results. Furthermore, the generalized algorithm is implemented to price options using the finite difference method. We compare the generalized algorithm with standard numerical and stochastic algorithms to show its efficiency. [ABSTRACT FROM AUTHOR]

To calculate the losses of distribution feeders, this paper uses an iterative method that is limited to restricted measurements. The approach presented in this paper uses bill data in addition to output information from a very small number of real-time measurements located on the secondary side of distribution transformers. This method attempts to estimate the load of distribution transformers injected into LV feeders. Energy losses for LV feeders are evaluated by first estimating the power and periodic energy injected to each of the LV feeders and then subtracting the total consumption bills from these estimated values. By using this method, the amount of energy loss is estimated. In this article, a new method called iterative power factor adjustment method is considered as a potential method for estimating losses. The power factor can be increased by repeatedly using evolutionary algorithms and including capacitors in the system. In order to reduce system losses and increase network effectiveness. In this paper, a new method for examining and evaluating Non-Technical Losses (NTL) is proposed. This method considers load estimation and limited measurement to place high priority feeders. [ABSTRACT FROM AUTHOR]

In this paper, we consider a new class of variational inequalities involving two operators, which is called the general variational inequality. We have shown that the general variational inequalities are equivalent to the fixed point problem using the projection technique. This equivalent fixed point formulation is used to discuss the existence of solution as well as to investigate several iterative methods for solving general variational inequalities. Some applications of the associated dynamical system coupled with finite difference are explored. Convergence analysis of the proposed methods is considered under suitable conditions. Since general variational inequalities include the variational inequalities, complementarity problems and nonlinear equations as special cases, our results continued to hold for these problems. The techniques and ideas of this paper be starting point for the future research. [ABSTRACT FROM AUTHOR]

In 1989, Bakhtin proved a version of the Banach contraction principle in the context of b-metric spaces. More precisely, let (X, d; s) be a complete b-metric space with parameter s ⩾ 1 and let T a contractive map on X, that is a self-map T of X satisfying d(Tx, Ty) ⩽ λd(x, y), ∀x, y ∈ X, (Bλ) with some λ ∈ [0, 1). Bakhtin proved that if λ ∈ [0, 1 s), then T has a unique fixed point. In the two last decades many research papers were produced by many authors in the setting of b-metric spaces. In 2021, the author published a note on the Banach contraction principle in b-metric spaces in Divilgaciones Mat'ematicas dealing with some complements to Bakhtin results. The aim of this paper is to provide other complements. In particular, we discuss the remaining case where λ ∈ [1 s, 1). We give an evaluation of the order of convergence for the iterative Picard process and a posteriori error estimate for this process and we estimate the diameter of the T-orbits. We investigate well-posedness of the fixed problem of a map T satisfying Bλ when X is Torbitally complete and we establish two shadowing properties for these maps without requiring completeness of X. [ABSTRACT FROM AUTHOR]

For a ship, both synchronous and parametric roll motions can be modelled by nonlinear second-order differential equations with the roll angle as dependent variable and the nonlinearities coming from the damping and restoring moments. In the absence of exact solution techniques, approximate solutions for such equations can be obtained, in principle, analytically or numerically. In this paper, we focused on a fast and accurate recursive scheme based on the segmentation of the time domain into a fine grid of intervals of equal lengths. Due to the smallness of each time subinterval, a reset of the terms of the initial nonlinear equation of motion allows replacing it with a linear one in which the constant coefficients represent approximate values of the former variable coefficients in the middle of each subinterval. The linear equation is solved via the Laplace transform and the resulting solution together with its first derivatives is used to generate the iterative algorithm. This technique was applied to the case of two typical roll equations. The first describes the synchronous roll of a vehicle ferry model equipped or not with bilge keels while the second estimates the parametric roll of a container ship model. In both cases, the analyzed recursive algorithm not only generated results in full agreement with those provided by the ode45 solver in Matlab but also lead to a gain in computation time and offered more flexibility in imposing some restrictive conditions associated, for example, with exceeding some oscillation amplitudes or to the ship capsizing. [ABSTRACT FROM AUTHOR]

A photovoltaic emulator (PVE) is a specialized device designed to mimic the static and dynamic properties of a solar panel. It serves as a crucial tool for testing and validating PV systems. Despite the unpredictable variations in real environmental conditions, the PVE offers a controlled environment, facilitating the smooth implementation and testing of PV subsystems. The PVE consists of two essential components: the reference PV model and the PVE power electronics controller. For simplicity, both these elements must be inherently straightforward. Numerous advanced methods have been proposed in the literature to efficiently integrate the PV model into the PVE system. However, these approaches often involve complex iterative computations of intricate equations related to solar panels, making them less practical. To address these limitations, this paper introduces a novel PVE that aims to simplify the implementation and integration of the PV model. The proposed system employs a simple and non-iterative approach to provide the reference to the PVE, using a straightforward explicit model of the solar panel. In comparison to existing works, the proposed PVE stands out for its high flexibility and simplicity as it does not require the complex iterative computations of implicit equations related to the solar panel model. The overall PVE system is implemented with a basic proportional-integral (PI) controller and a DC-DC buck power electronic converter. It is then validated using a 200 W solar panel through a series of experiments, including the EN 50530 Test. The results of these experiments demonstrate that the proposed PVE efficiently reproduces the static and dynamic characteristics of a solar panel. [ABSTRACT FROM AUTHOR]

In this paper, we introduce two linearized proximal algorithms for solving DC composite optimization problems. The basic algorithms that we rely are the proximal-linear(ized) methods, which in each iteration solve regularized subproblems formed by linearizing the smooth maps and the concave component, respectively. It is proved that the two proposed algorithms provide descent methods and that if the sequences generated by the algorithms are bounded, every cluster points are critical points of the functions under consideration. Finally, a conclusion is stated and some directions for further research are suggested. [ABSTRACT FROM AUTHOR]

This paper presents Calderón-Zygmund estimates for the weak solutions of a class of nonuniformly elliptic equations in R n , which are obtained through the use of the iteration-covering method. More precisely, a global Calderón-Zygmund type result | f | p 1 + a (x) | f | p 2 ∈ L s (R n) ⇒ | D u | p 1 + a (x) | D u | p 2 ∈ L s (R n) f o r a n y s > 1 is established for the weak solutions of − d i v A (x , D u) = − d i v F (x , f) i n R n , which are modeled on − d i v (| D u | p 1 − 2 D u + a (x) | D u | p 2 − 2 D u) = − d i v (| f | p 1 − 2 f + a (x) | f | p 2 − 2 f) , where 0 ≤ a (⋅) ∈ C 0 , α (R n) , α ∈ (0 , 1 ] and 1 < p 1 < p 2 < p 1 + α p 1 n . This paper presents Calderón-Zygmund estimates for the weak solutions of a class of nonuniformly elliptic equations in R n , which are obtained through the use of the iteration-covering method. More precisely, a global Calderón-Zygmund type result | f | p 1 + a (x) | f | p 2 ∈ L s (R n) ⇒ | D u | p 1 + a (x) | D u | p 2 ∈ L s (R n) f o r a n y s > 1 is established for the weak solutions of − d i v A (x , D u) = − d i v F (x , f) i n R n , which are modeled on − d i v (| D u | p 1 − 2 D u + a (x) | D u | p 2 − 2 D u) = − d i v (| f | p 1 − 2 f + a (x) | f | p 2 − 2 f) , where 0 ≤ a (⋅) ∈ C 0 , α (R n) , α ∈ (0 , 1 ] and 1 < p 1 < p 2 < p 1 + α p 1 n . [ABSTRACT FROM AUTHOR]

This paper presents the visualization process of finding the roots of a complex polynomial - which is called polynomiography - by the Caputo fractional derivative. In this work, we substitute the variable-order Caputo fractional derivative for classic derivative in Newton's iterative method. To investigate the proposed root-finding method, we apply it for two polynomials p(z) = z5 - 1 and p(z) = -2z4 + z3 + z2 - 2z - 1 on the complex plane and compute the MNI and CAI parameters. Presented examples show that through the expressed process, we can obtain very interesting fractal patterns. The obtained patterns show that the proposed method has potential artistic application. [ABSTRACT FROM AUTHOR]

Robust approach is a special scalarization method to deal with multiobjective optimization problems in the worst-case. In this paper, we propose a new non-monotone gradient type algorithm for solving unconstrained multiobjective optimization problems by the conjugate technique and the robust approach. The proposed method has a memory gradient property since the search direction is constructed by using the current descent direction and the past multi-step iterative descent directions. For this, the search direction is called a memory gradient search direction. The step-size is computed by the non-monotone linear search. A lower bound of the stepsize is presented under some mild conditions. Then the iterative sequence generated by the proposed method is proved to be convergent to a Pareto critical point of the multiobjective optimization problem under some mild conditions. Numerical experiments are reported to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Indoor location services often use Bluetooth low energy (BLE) devices for their low energy consumption and easy implementation. Applications like device monitoring, ranging, and asset tracking utilize the received signal strength (RSS) of the BLE signal to estimate the proximity of a device from the receiver. However, in multipath environments, RSS-based solutions may not provide an accurate estimation. In such environments, receivers with antenna arrays are used to calculate the difference in time of flight (ToF) and therefore calculate the direction of arrival (DoA) of the Bluetooth signal. Other techniques like triangulation have also been used, such as having multiple transmitters or receivers as a network of sensors. To find a lost item, devices like Tile© use an onboard beeper to notify users of their presence. In this paper, we present a system that uses a single-measurement device and describe the method of measurement to estimate the location of a BLE device using RSS. A BLE device is configured as an Eddystone beacon for periodic transmission of advertising packets with RSS information. We developed a smartphone application to read RSS information from the beacon, designed an algorithm to estimate the DoA, and used the phone's internal sensors to evaluate the DoA with respect to true north. The proposed measurement method allows for asset tracking by iterative measurements that provide the direction of the beacon and take the user closer at every step. The receiver application is easily deployable on a smartphone, and the algorithm provides direction of the beacon within a 30° range, as suggested by the provided results. [ABSTRACT FROM AUTHOR]

We study the existence and approximation of fixed points for the recently introduced class of mappings called enriched Suzuki nonexpansive mappings in the setting of Banach spaces. We use the modified K-iteration process to establish the main results of the paper. The class of enriched Suzuki nonexpansive operators is an important class of nonlinear operators that includes properly the class of Suzuki nonexpansive operators as well as enriched nonexpansive operators. Various assumptions are imposed on the domain or on the operator to establish the main convergence theorems. Eventually, a numerical example of enriched Suzuki nonexpansive operators is used to show the effectiveness of the studied iteration scheme. The main outcome of the paper is new and essentially suggests a new direction for researchers who are working on fixed point problems in a Banach space setting. Our results improve and extend some main results due to Hussain et al. [ABSTRACT FROM AUTHOR]

The aim of this note is to put straight the inaccuracy in Theorem 1 of the paper mentioned in the title (J. Math. Ineq. 13 (4), 1011-1022). The inaccuracy was due to an omission of a factor in the proof of the theorem. [ABSTRACT FROM AUTHOR]

In order to obtain information or discover knowledge from system logs, the first step is to performlog parsing, whereby unstructured raw logs can be transformed into a sequence of structured events. Although comprehensive studies on log parsing have been conducted in recent years, most assume that one event object corresponds to a single-line message. However, in a growing number of scenarios, one event object spans multiple lines in the log, for which parsing methods toward single-line events are not applicable. In order to address this problem, this paper proposes an automated log parsing method for multiline events (LPME). LPME finds multiline event objects via iterative scanning, driven by a set of heuristic rules derived from practice. The advantage of LPME is that it proposes a cohesion-based evaluation method for multiline events and a bottom-up search approach that eliminates the process of enumerating all combinations. We analyze the algorithmic complexity of LPME and validate it on four datasets from different backgrounds. Evaluations show that the actual time complexity of LPME parsing for multiline events is close to the constant time, which enables it to handle large-scale sample inputs. On the experimental datasets, the performance of LPME achieves 1.0 for recall, and the precision is generally higher than 0.9, which demonstrates the effectiveness of the proposed LPME. [ABSTRACT FROM AUTHOR]

Derivative-free iterative methods are useful to approximate the numerical solutions when the given function lacks explicit derivative information or when the derivatives are too expensive to compute. Exploring the convergence properties of such methods is crucial in their development. The convergence behavior of such approaches and determining their practical applicability require conducting local as well as semi-local convergence analysis. In this study, we explore the convergence properties of a sixth-order derivative-free method. Previous local convergence studies assumed the existence of derivatives of high order even when the method itself was not utilizing any derivatives. These assumptions imposed limitations on its applicability. In this paper, we extend the local analysis by providing estimates for the error bounds of the method. Consequently, its applicability expands across a broader range of problems. Moreover, the more important and challenging semi-local convergence not investigated in earlier studies is also developed. Additionally, we survey recent advancements in this field. The outcomes presented in this paper can be proved valuable to practitioners and researchers engaged in the development and analysis of derivative-free numerical algorithms. Numerical tests illuminate and validate further the theoretical results. [ABSTRACT FROM AUTHOR]

Initial conditions can have a substantial impact on the behavior of iterative root-finding techniques for nonlinear equations. By allowing complex starting points and complex roots, it is possible to examine the basins of attraction in the complex plane in order to compare the performance of various iterative techniques. In this paper, a one-parameter family of third-order root-finding methods is studied by varying its parameter A within −2.0 and 2.4 and applying it to a polynomial equation of high degree (degree 25). This family includes the Euler–Chebyshev's (A = 0), Halley's (A = 1) and BSC (A = 2) techniques. According to the results, the one-parameter family provides the best performance for values near A = 1, which equals to the Halley's method. [ABSTRACT FROM AUTHOR]

In one of our recent papers, we considered a complete metric space of nonexpansive mappings taking a bounded and closed subset of a complete hyperbolic space into the space so that the boundary of this subset is mapped back into the subset itself. Using the Baire category approach, we proved that most of these mappings possess a unique fixed point which attracts all their iterates. In the present paper, we improve upon this result by showing that the complement of the set of mappings which have a fixed point is not only of the first Baire category, but also is s-porous. [ABSTRACT FROM AUTHOR]

The steam generator is an important piece of energy exchange equipment for nuclear power plants, and the level control of the steam generator plays a key role in the stable operation of the plants. To improve the level control performance of the steam generator, it is necessary to adjust the parameters of the level control system during the commissioning process of nuclear power plants. However, the parameter setting process relies heavily on the experience of engineers, requires a lot of historical data, and is difficult to ensure the best. To address these issues, this paper proposes a hybrid iterative model reconstruction-based steam generator level control performance optimization method based on the idea of data-driven optimization. The method proposes a fusion idea and implementation mechanism in which process data and the hybrid model are jointly driven under the data-driven framework to maximize the advantages of different modeling mechanisms to achieve the performance optimization of a steam generator level control system. The method first constructs the initial dataset with a small-sample Latin-square experiment design and then builds two different fitting models, SVM and Kriging, based on the initial dataset respectively, under the hybrid model fusion idea. After that, the particle swarm optimization algorithm is used to calculate the optimal point of the current valid model, and the optimization process is controlled by establishing the iteration termination judgment based on the historical iteration data. Then, the current iteration point is used to dynamically reconstruct the two types of models. Finally, the two types of models are dynamically reconstructed using the current iteration points. The above process is iterated until the optimal iterative process of the system is satisfied. From the experimental results, it can be seen that compared with two types of single-model optimization methods, this method can reduce the iteration final value by 13.57% and 16.27%, respectively, with a slightly increased number of iterations. These results indicate that this method can significantly improve the efficiency of optimizing the control performance of the steam generator liquid level. [ABSTRACT FROM AUTHOR]

Decision diagrams are an increasingly important tool in cutting-edge solvers for discrete optimization. However, the field of decision diagrams is relatively new, and is still incorporating the library of techniques that conventional solvers have had decades to build. We drew inspiration from the warm-start technique used in conventional solvers to address one of the major challenges faced by decision diagram based methods. Decision diagrams become more useful the wider they are allowed to be, but also become more costly to generate, especially with large numbers of variables. In the original version of this paper, we presented a method of peeling off a sub-graph of previously constructed diagrams and using it as the initial diagram for subsequent iterations that we call peel-and-bound. We tested the method on the sequence ordering problem, and our results indicate that our peel-andbound scheme generates stronger bounds than a branch-and-bound scheme using the same propagators, and at significantly less computational cost. In this extended version of the paper, we also propose new methods for using relaxed decision diagrams to improve the solutions found using restricted decision diagrams, discuss the heuristic decisions involved with the parallelization of peel-and-bound, and discuss how peel-and-bound can be hyperoptimized for sequencing problems. Furthermore, we test the new methods on the sequence ordering problem and the traveling salesman problem with time-windows (TSPTW), and include an updated and generalized implementation of the algorithm capable of handling any discrete optimization problem. The new results show that peel-and-bound outperforms ddo (a decision diagram based branch-and-bound solver) on the TSPTW. We also close 15 open benchmark instances of the TSPTW. [ABSTRACT FROM AUTHOR]

In this paper, we consider a multiple-sets split quasi-convex feasibility problem (MSSQFP), which is to find a point such that itself and its image under a linear transformation fall within two families of sublevel sets of quasi-convex functions in the space and the image space, respectively. A unified framework of the adaptive subgradient methods with general control schemes is proposed to solve the MSSQFP. This paper is contributed to establish the quantitative convergence theory of adaptive subgradient methods with several general control schemes. An interesting finding is disclosed by the iteration complexity results that the stochastic control enjoys both advantages of low computational cost requirement and low iteration complexity. In addition, a notion of the H¨older-type bounded error bound property for the MSSQFP is introduced, and the linear/sublinear convergence rates for the adaptive subgradient methods to a feasible solution of the MSSQFP is established. [ABSTRACT FROM AUTHOR]

As soil heavy metal pollution is increasing year by year, the risk assessment of soil heavy metal pollution is gradually gaining attention. Soil heavy metal datasets are usually imbalanced datasets in which most of the samples are safe samples that are not contaminated with heavy metals. Random Forest (RF) has strong generalization ability and is not easy to overfit. In this paper, we improve the Bagging algorithm and simple voting method of RF. AW-RF algorithm based on adaptive Bagging and weighted voting is proposed to improve the classification performance of RF on imbalanced datasets. Adaptive Bagging enables trees in RF to learn information from the positive samples, and weighted voting method enables trees with superior performance to have higher voting weights. Experiments were conducted using G-mean, recall and F1-score to set weights, and the results obtained were better than RF. Risk assessment experiments were conducted using W-RF on the heavy metal dataset from agricultural fields around Wuhan. The experimental results show that the RW-RF algorithm, which use recall to calculate the classifier weights, has the best classification performance. At the end of this paper, we optimized the hyperparameters of the RW-RF algorithm by a Bayesian optimization algorithm. We use G-mean as the objective function to obtain the optimal hyperparameter combination within the number of iterations. [ABSTRACT FROM AUTHOR]

This paper proposes a simple method to find an optimum and efficient basic solution to bi-objective transportation problem (BOTP) using weighted goal programming approach. Preferential weights for the goals (objectives) are derived from analytic hierarchy process (AHP). Solution obtained by the proposed approach has been found to be the nearest basic feasible solution to the ideal solution in terms of Euclidean distance measure. The method is illustrated with numerical examples taken from the literature and solutions compared in terms of the number of iterations, computational complexity and proximity to the ideal solution. The modified minimum supply and demand method is used to obtain initial basic feasible solutions that are found to be optimal, and hence this method is computationally simpler compared to other linear programming methods. It has been observed that weighted objective function optimization yields optimal efficient BOTP solutions using appropriate weights for the objective functions. [ABSTRACT FROM AUTHOR]

In this paper, by using symmetric first-order divided differences, we introduce a new family of Secant-like iterative methods with quadratic convergence. Afterthought, we analyze its semilocal and local behavior when the nonlinear operator F is not differentiable by imposing appropriate bounding conditions in each case. Theoretical results have also been tested by solving a problem which shows the applicability of our work. [ABSTRACT FROM AUTHOR]

In this paper, we consider the Krasnosel'skiĭ-Mann iteration for finding a fixed point of nonexpansive operators in real Hilbert spaces. By introducing new, concise, and self-contained techniques, we propose new inertial factors with desirable upper bounds better than or comparable to existing ones. [ABSTRACT FROM AUTHOR]

In this paper, we establish new iterative methods for the solution of scalar equations by using the decomposition technique given in [16]. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a forward-backward-forward splitting algorithm with double inertial effects to approximate a solution of a non-convex mixed variational inequality problem. Our algorithm does not involve an on-line rule and one of the inertial factors is chosen to be non-positive. We give global convergence results of the iterative sequence generated by our algorithm. Some known results are recovered as special cases of our results. Numerical test is given to support the theoretical findings. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a split common fixed point problem with multiple output sets within a more general framework and we present a novel iterative method that boasts the advantage of the step size calculation that is independent of the norm of linear mappings. We prove the weak convergence of the method and the strong convergence of its variants under certain conditions. Furthermore, we apply our main results to the split feasibility problem with multiple output sets. Our numerical results indicate that our method is an effective approach to this problem. [ABSTRACT FROM AUTHOR]

Bregman distance iterative methods for solving optimization problems are important and interesting because of the numerous applications of Bregman distance techniques. In this paper, for solving a split feasibility problem, we introduce a new Bregman projection algorithm and construct two selection strategies of stepsizes. Moreover, a relaxed Bregman projection algorithm is proposed with two selection strategies of stepsizes, where the two closed and convex sets are both level sets of convex functions. Weak convergence results of the proposed algorithms are obtained under suitable assumptions. In addition, using the proposed algorithms with different Bregman distances, a numerical experiment solving signal processing problem is also given to demonstrate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the iterative methods for the solution of different types of nonlinear matrix equations. More specifically, we consider iterative methods for the minimal nonnegative solution of a set of Riccati equations, a nonnegative solution of a quadratic matrix equation, and the maximal positive definite solution of the equation X + A ∗ X − 1 A = Q . We study the recent iterative methods for computing the solution to the above specific type of equations and propose more effective modifications of these iterative methods. In addition, we make comments and comparisons of the existing methods and show the effectiveness of our methods by illustration examples. [ABSTRACT FROM AUTHOR]

The Picard iterative approach used in the paper to derive conditions under which nonlinear ordinary differential equations based on the derivative with the Mittag-Leffler kernel admit a unique solution. Using a simple Euler approximation and Heun's approach, we solved this nonlinear equation numerically. Some examples of a nonlinear linear differential equation were considered to present the existence and uniqueness of their solutions as well as their numerical solutions. A chaotic model was also considered to show the extension of this in the case of nonlinear systems. [ABSTRACT FROM AUTHOR]

In this paper, we study a new iterative scheme to approximate fixed point of Suzuki nonexpansive type mappings in Banach space. We also prove some weak and strong theorems for Suzuki nonexpansive type mappings. Numerical example is given to show the efficiency of new iteration process. The results obtained in this paper improve the recent ones announced by Thakur et al. [17], Ullah and Arschad. [ABSTRACT FROM AUTHOR]

In this paper, we develop a new proposed iterative method (AWN) for root finding of nonlinear equations. The newly proposed method was subsequently proved and the fourth-order of convergence is obtained. Computationally, Based on MATLAB simulations, We demonstrated the efficiency of the AWN method compared to many recent methods. We conclude that the AWN method will help to get a good performance in applied science compared with other methods. [ABSTRACT FROM AUTHOR]

The iterative process of ethnography not only constructs theory, but its methodology should embody theory. Developing a theoretical framework often demands adjustments in methodology, to leverage previous work and to avoid assumptions compounding through the magnification of blind spots. New theory in policy-engaged ethnography has emphasised the importance of analysing interactions between teachers. However, such analyses have not yet emerged in research on education in Japan, partly because of enduring conceptualisations of teachers as homogeneous. Methodological tools that do exist are grounded in anglosphere data and remain unsuited to research in Japan's schools. As such, participants are positioned amongst, but not in relation to, other teachers and school administrators. Yet, taking teacher heterogeneity seriously enhances the salience of selection bias. The same teachers who are enthusiastic about participating in the research are often those who are enthusiastic about the topic of the research. What is difficult in school ethnography is procuring, and preferably ensuring, participation from teachers who are not enthusiasts toward the topic of the research. Designing research with both the heterogeneity of teachers and the specifics of the local context in mind can provide more diverse data with potential to inform analyses of micro-politics in Japan's schools. In reference to a five-year research project and grounded in data from Japan, the paper proposes some procedures to access a diverse range of teachers based on a theory developed to conceptualise teachers' orientations towards policy work. [ABSTRACT FROM AUTHOR]

In this paper, the Fuzzy Sumudu Transform Iterative method (FSTIM) was applied to find the exact fuzzy solution of the fuzzy space-time fractional telegraph equations using the Fuzzy Caputo Fractional Derivative operator. The Telegraph partial differential equation is a hyperbolic equation representing the reaction-diffusion process in various fields. It has applications in engineering, biology, and physics. The FSTIM provides a reliable and efficient approach for obtaining approximate solutions to these complex equations improving accuracy and allowing for fine-tuning and optimization for better approximation results. The work introduces a fuzzy logic-based approach to Sumudu transform iterative methods, offering flexibility and adaptability in handling complex equations. This innovative methodology considers uncertainty and imprecision, providing comprehensive and accurate solutions, and advancing numerical methods. Solving the fuzzy space-time fractional telegraph equation used a fusion of the Fuzzy Sumudu transform and iterative approach. Solution of fuzzy fractional telegraph equation finding analytically and interpreting its results graphically. Throughout the article, whenever we draw graphs, we use Mathematica Software. We successfully employed FSTIM, which is elegant and fast to convergence. [ABSTRACT FROM AUTHOR]

Wireless sensor networks contain of many sensors that can serve as powerful tools for data collection in environments. A key challenge in these networks is the limited lifetime of sensor batteries. Ideally, all nodes would exhaust their energy simultaneously or through regular scheduling, maximizing the lifetime. Consequently, the primary concern is achieving optimal energy utilization to extend the network's lifetime over a logical duration. Depleting the batteries of the sensors means stopping the operation of the network, because it is practically impossible to replace the batteries of thousands of nodes. To address this issue, the low energy adaptive clustering hierarchical (LEACH) protocol has been widely recognized as one of the prominent solutions for clustering WSNs. However, the random selection of cluster heads in each round under the LEACH protocol fails to guarantee proper convergence. To overcome this limitation, this paper proposes a refined approach by utilizing a genetic algorithm and a novel objective function that incorporates various factors, including energy level and distance. The algorithm employs chromosomes to represent CHs and facilitates the selection of cluster nodes. Notably, the proposed algorithm dynamically performs clustering, meaning that clustering is conducted iteratively, considering identifying dead nodes. By leveraging this approach, the algorithm significantly enhances the clustering quality, ultimately leading to an increased network lifetime. To validate its effectiveness, it is compared with LEACH, LEACH_E and LEACH_EX algorithms, demonstrating its superior capabilities. On average, the proposed algorithm has more alive nodes in the network, and the remaining energy is at least 11% higher than the best other algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a new self-adaptive algorithm with the inertial technique is proposed for solving the split equality problem in p-uniformly convex and uniformly smooth Banach spaces. Under some mild control conditions, a strong convergence theorem for the proposed algorithm is established. Furthermore, the results are applied to split equality fixed point problem and split equality variational inclusion problem. Finally, numerical examples are provided to illustrate the convergence behaviour of the algorithm. The main results in this paper improve and generalize some existing results in the literature. [ABSTRACT FROM AUTHOR]

This paper generalizes the properties of the correlation matrix implied by a recursive path analysis model obtained using the Finite Iterative Method into the covariance case, where variables are no longer supposed to be standardized. We show that the implied covariance matrix computed using the Finite Iterative Method is affine with respect to each parameter of the considered model. Moreover, several other properties derive from this affinity and will be used to simplify the computation of the first as well as the second derivatives of the fit function used in the estimation of the model's parameters. Finally, we illustrate the advantages of the proposed properties compared to the classical approximation used to compute the aforementioned derivatives through numerical example. [ABSTRACT FROM AUTHOR]

In this paper, the resource allocation problem for user pairing (UP) in downlink non-orthogonal multiple access (NOMA) systems is investigated. NOMA allows the use of one subcarrier for more than one user at the same time, thus increases the total capacity of the wireless communication system. However, users pairing is a challenging task in the NOMA systems, because a good channel quality subcarrier should be selected and allocated for the user to enhance the performance of NOMA systems. The proposed UP algorithm aims to enhance the sum rate of the paired users per subcarrier and consequently enhance the total sum rate of downlink NOMA systems. Moreover, the proposed UP algorithm target to improve the fairness of the users. The proposed UP algorithm is based on a simple search for the subcarrier with the minimum average channel gains to be assigned its paired users and then excluding it from the next searching process. The proposed scheme ensures the higher channel gain for users by giving the priority to the subcarrier with the minimum average channel gains during the user pairing process. The simulation results demonstrate that the proposed UP algorithm can not only enhance the total sum rate compared with the random UP and conventional UP but also can enhance the fairness of the users. Moreover, it is clearly seen that the proposed UP algorithm provides the lowest outage probability. [ABSTRACT FROM AUTHOR]

Let A be a rational function of degree at least 2 on the Riemann sphere. We say that A is tame if the algebraic curve A(x) - A(y) = 0 has no factors of genus 0 or 1 distinct from the diagonal. In this paper, we show that if tame rational functions A and B have some orbits with infinite intersection, then A and B have a common iterate. We also show that for a tame rational function A decompositions of its iterates A0d, d ≤1, into compositions of rational functions can be obtained from decompositions of a single iterate A0N for N large enough. [ABSTRACT FROM AUTHOR]

In this paper, the multiple constraint least squares solution of the Sylvester equation AX + XB = C is discussed. The necessary and sufficient conditions for the existence of solutions to the considered matrix equation are given. Noting that the alternating direction method of multipliers (ADMM) is a one-step iterative method, a multi-step alternating direction method of multipliers (MSADMM) to solve the considered matrix equation is proposed and some convergence results of the proposed algorithm are proved. Problems that should be studied in the near future are listed. Numerical comparisons between MSADMM, ADMM and ADMM with Anderson acceleration (ACADMM) are included. [ABSTRACT FROM AUTHOR]

In this paper, a new type of contraction mapping is introduced, called generalized quasi like contractive mapping, and three types of new iterative schemes are presented as multi_L_explicit four step iteration, multi_ L_ explicit Noor iteration and multi_ L_Picard s-iteration. We study the rate of convergence and stability with generalized quasi like contractive mapping [ABSTRACT FROM AUTHOR]

In this paper, we further investigate the proper nonnegative splittings of rectangular matrices. The concept of proper nonnegative splittings over proper cones of rectangular matrices is proposed. Convergence results for the proper double nonnegative splitting over proper cones of a rectangular matrix are established, and comparison theorems for the spectral radii of matrices arising from proper nonnegative splittings over proper cones of the same rectangular matrix or different rectangular matrices are presented. The results obtained in this paper extend the results of proper nonnegative splittings over field to ones over proper cones of rectangular matrices. For ill-posed linear systems, the regularized iterative method based on splittings over proper cones is introduced, and the application of research results of proper nonnegative splittings over proper cones in the ill-posed linear system is given. [ABSTRACT FROM AUTHOR]

In this paper, triangular and symmetric splitting method is applied for determining the steady state probability vector π of regularized linear system. Ax b = The homogeneous system 0, πR= where 0, is block stochastic rate matrix, is transformed into regularized non-homogeneous linear system Ax b = by using preconditioned matrix with the small perturbation. ε>0. It is proved that the regularized matrix T A=RT +εI is positive definite. In this convergence analysis of the (triangular and symmetric) TS iteration method, both relative error and absolute error are considered. From the numerical results, it is concluded that TS iteration method converge rapidly when compared with other existing methods. [ABSTRACT FROM AUTHOR]

Copyright of Buletinul AGIR is the property of Asociatia Generala a Inginerilor din Romania and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Advanced Encryption Standard cryptographic algorithm, named AES, is implemented in cryptographic circuits to ensure high security level to any system which required confidentiality and secure information exchange. One of the most effective physical attacks against the hardware implementation of AES is fault attacks which can extract secret data. Until now, a several AES fault detection schemes against fault injection attacks have been proposed. In this paper, so as to ensure a high level of security against fault injection attacks, a new efficient fault detection scheme based on the AES architecture modification has been proposed. For this reason, the AES 32-bit round is divided into two half rounds and input and pipeline registers are implemented between them. The proposed scheme is independent of the procedure the AES is implemented. Thus, it can be implemented to secure the pipeline and iterative architectures. To evaluate the robustness of the proposed fault detection scheme against fault injection attacks, we conduct a transient and permanent fault attacks and then we determine the fault detection capability; it is about 99.88585% and 99.9069% for transient and permanent faults respectively. We have modeled the AES fault detection scheme using VHDL hardware language and through hardware FPGA implementation. The FPGA results demonstrate that our scheme can efficiently protect the AES hardware implementation against fault attacks. It can be simply implemented with low complexity. In addition, the FPGA implementation performances prove the low area overhead and the high efficiency and working frequency for the proposed AES detection scheme. [ABSTRACT FROM AUTHOR]

Solving various real-life problems ultimately requires solving systems of linear equations. However, the parameters involved in such real-life problems may be pervaded with uncertainty, which results in fuzzy parameters rather than crisp parameters. Intuitionistic fuzzy parameters are more suitable for some cases, since they allow us to tackle the feeling of fear or hesitation when making a decision. These are characteristics of human beings that occur when applying knowledge and skills. The intuitionistic fuzzy linear system (IFLS) resulting from real-life problem involves large number of equations and equally large number of unknowns. When IFLS is in matrix-vector form, the resulting coefficient matrix will have a sparse structure, which makes iterative methods necessary for their solution. In this paper, the known Gauss-Seidel and SOR iterative methods for solving linear system of equations are discussed, to the best of our knowledge for the first time, to solve (IFLS). The single parametric form representation of intuitionistic fuzzy numbers (IFN) makes it possible to apply these iterative techniques to IFLS. Finally, a problem of voltage input output in an electric circuit has been considered to show the applicability and the efficiency of these methods. [ABSTRACT FROM AUTHOR]

In this paper, we consider two-step fourth-order and three-step sixth-order derivative free iterative methods and study their convergence in Banach spaces to approximate a locally-unique solution of nonlinear equations. Study of convergence analysis provides radius of convergence, error bounds and estimates on the uniqueness of the solution. Such estimates are not provided in the approaches that use Taylor expansions using higher order derivatives. Furthermore, in quest of fast algorithms, a generalized q-step scheme with increasing convergence order 2q + 2 is proposed and analyzed. Novelty of the q-step algorithm is that, in each step, order of convergence is increased by an amount of two at the cost of only one additional function evaluation. To maximize the computational efficiency, the optimal number of steps is calculated. Theoretical results regarding convergence and computational efficiency are verified through numerical experimentation. [ABSTRACT FROM AUTHOR]