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Extreme value model is one of the most important models that are applicable in air pollution data. This paper aims at introducing a new model of extreme value that is more suitable in environmental studies.

The parameters of the new model have been estimated by method of maximum likelihood. In order to relate to air pollution impacts, the new extreme value model was used, applied to carbon monoxide (CO) in parts per million (ppm) at several places in Malaysia. The objective of this analysis is to fit the extreme values with a new model and to examine its performance. Comparison of the new model with others is shown to illustrate the applicability of this new model.

The results show that the new model is the best fit using the method of maximum likelihood. The new model gives a significant impact of CO data, which gives the smallest standard error and p‐values. The new extreme value model is able to identify significantly problems of air pollution. The results presented by the new extreme value model can be used as an air quality management tool by providing the decision makers means to determine the required reduction of source.

The new extreme value model has mostly been applied in environmental studies for the statistical treatment of air pollution. The results of the numerical and simulated CO data indicate that the new model both is easy to use and can achieve even higher accuracy compared with other models.

This paper aims to overcome the problem that the single structure of the driving term of the grey prediction model is not adapted to the complexity and diversity of the actual modeling objects, which leads to poor modeling results.

Firstly, the nonlinear law between the raw data and time point is fully mined by expanding the nonlinear term and the range of order. Secondly, through the synchronous optimization of model structure and parameter, the dynamic adjustment of the model with the change of the modeled object is realized. Finally, the objective optimization of nonlinear driving term and cumulative order of the model is realized by particle swarm optimization PSO algorithm.

The model can achieve strong compatibility with multiple existing models through parameter transformation. The synchronous optimization of model structure and parameter has a significant improvement over the single optimization method. The new model has a wide range of applications and strong modeling capabilities.

A novel grey prediction model with structure variability and optimizing parameter synchronization is proposed.

The highlights of the paper are as follows:

1. A new grey prediction model with a unified nonlinear structure is proposed.

2. The new model can be fully compatible with multiple traditional grey models.

3. The new model solves the defect of poor adaptability of the traditional grey models.

4. The parameters of the new model are optimized by PSO algorithm.

5. Cases verify that the new model outperforms other models significantly.

A new grey prediction model with a unified nonlinear structure is proposed.

The new model can be fully compatible with multiple traditional grey models.

The new model solves the defect of poor adaptability of the traditional grey models.

The parameters of the new model are optimized by PSO algorithm.

Cases verify that the new model outperforms other models significantly.

The purpose of this study is to develop and describe a process which can be applied to develop new methods in the context of preliminary aircraft sizing in a successful and efficient way.

The tasks to development new aircraft sizing methods are systematically analyzed. In particular, repeating and nonrepeating tasks and common or unique tasks. Then ordered in a sequence and described generically.

A development process for new aircraft design methods which are necessary for new technologies or configurations is introduced and explained step by step.

Introducing the capability to deal with new technologies or configurations, aircraft design tools or aircraft concepts requires new sizing methods.

The paper presents a systematic approach which can be used to develop a great amount of new sizing methods with a comparable usability and quality standard in an efficient and effective way.

This paper seeks to explore the sensitivity of these parameters and their impact on fiscal policy outcomes. We use the existing literature to establish possible ranges for each parameter, and we examine how changes within these ranges can alter the outcomes of fiscal policy. In this way, we aim to highlight the importance of these parameters in the formulation and evaluation of fiscal policy.

The role of fiscal policy, its effects and multipliers continues to be a subject of intense debate in macroeconomics. Despite adopting a New Keynesian approach within a macroeconomic model, the reactions of macroeconomic variables to fiscal shocks can vary across different contexts and theoretical frameworks. This paper aims to investigate these diverse reactions by conducting a sensitivity analysis of parameters. Specifically, the study examines how key variables respond to fiscal shocks under different parameter settings. By analyzing the behavioral dynamics of these variables, this research contributes to the ongoing discussion on fiscal policy. The findings offer valuable insights to enrich the understanding of the complex relationship between fiscal shocks and macroeconomic outcomes, thus facilitating informed policy debates.

This paper aims to investigate key elements of New Keynesian Dynamic Stochastic General Equilibrium (DSGE) models. The focus is on the calibration of parameters and their impact on macroeconomic variables, such as output and inflation. The study also examines how different parameter settings affect the response of monetary policy to fiscal measures. In conclusion, this study has relied on theoretical exploration and a comprehensive review of existing literature. The parameters and their relationships have been analyzed within a robust theoretical framework, offering valuable insights for further research on how these factors influence model forecasts and inform policy recommendations derived from New Keynesian DSGE models. Moving forward, it is recommended that future work includes empirical analyses to test the reliability and effectiveness of parameter calibrations in real-world conditions. This will contribute to enhancing the accuracy and relevance of DSGE models for economic policy decision-making.

This study is motivated by the aim to provide a deeper understanding of the roles macroeconomic model parameters play concerning responses to expansionary fiscal policies and the subsequent reactions of monetary authorities. Comprehensive reviews that encompass this breadth of relationships within a single text are rare in the literature, making this work a valuable contribution to stimulating discussions on macroeconomic policies.

This paper aims to introduce a comprehensive framework for quality of context in pervasive context-aware systems. The framework includes the context quality characteristics, the quality policy, the quality calculation methods and the quality control algorithm.

This study used the constructive research method to introduce the framework. The data of a context-aware flooding prediction system to evaluate the approach were used.

The framework improves the quality of captured context by resolving the missing, error context and the context conflicts using the quality characteristics and quality control process that are introduced in the framework.

This work is original. It is based on the author’s PhD work in De Montfort University.

The purpose of this paper is to provide insights into the relationship between quality and accessibility, as selective influencing parameters of new product acceptance for Greek, fast moving, and consumer products.

The data for this study come from a mail questionnaire sent to 680 executives operating in Greek enterprises, by using a combination of sampling criteria (advertising budget, turnover). Non‐parametric tests (Wilcoxon, Spearman, Kruskal‐Wallis and Pearson χ²) were used, together with descriptive measures to test the hypotheses.

The results indicate that quality (usage/support) is a more important factor than Accessibility (economic/physical) in the formation of a “new product acceptance function”. Furthermore, usage quality is more important than support quality, while economic accessibility is more important than physical accessibility.

The research limitations refer to the fact that the justification of the hypotheses in connection with the executive‐based approach followed has not been found to have any precedents. In addition, a multi, rather than single, source identification process was used for the new product acceptance factors.

For marketers, research of the conceptualization of the “acceptance function” acts as a basis for building a new products' marketing plan focused on the consumer, in a way which reflects the company characteristics, as well as the particular market conditions.

This paper is exploring new ground in that it isolates and examines the substitution between quality and accessibility as selective influencing parameters of acceptance for new fast moving consumer goods in Greece.

The purpose of this paper is to develop new four-dimensional (4D) hyperchaotic system by adding another state variable and linear controller to three-dimensional T chaotic dynamical systems. Its dynamical analyses, circuit experiment, control and synchronization applications are presented.

A new 4D hyperchaotic attractor is achieved through a simulation, circuit experiment and mathematical analysis by obtaining the Lyapunov exponent spectrum, equilibrium, bifurcation, Poincaré maps and power spectrum. Moreover, hardware experimental measurements are performed and obtained results well validate the numerical simulations. Also, the passive control method is presented to make the new 4D hyperchaotic system stable at the zero equilibrium and synchronize the two identical new 4D hyperchaotic system with different initial conditions.

The passive controllers can stabilize the new 4D chaotic system around equilibrium point and provide the synchronization of new 4D chaotic systems with different initial conditions. The findings from Matlab simulations, circuit design simulations in computer and physical circuit experiment are consistent with each other in terms of comparison.

The 4D hyperchaotic system is presented, and dynamical analysis and numerical simulation of the new hyperchaotic system were firstly carried out. The circuit of new 4D hyperchaotic system is realized, and control and synchronization applications are performed.

A new simple parametric shear deformation theory applicable to isotropic and functionally graded plates is developed. This new theory has five degrees of freedom, provides parabolic transverse shear strains across the thickness direction and hence, it does not need shear correction factor. Moreover, zero-traction boundary conditions on the top and bottom surfaces of the plate are satisfied rigorously. The paper aims to discuss these issues.

Material properties are temperature-dependent and vary continuously through the thickness according to a power law distribution. The plate is assumed to be initially stressed by a temperature rise through the thickness. The energy functional of the system is obtained using Hamilton’s principle. Free vibration frequencies are then calculated using a set of characteristic orthogonal polynomials and by applying Ritz method for different boundary conditions.

In the light of good performance of the present theory for all boundary conditions considered, it can be considered as an excellent alternative to some two-dimensional (2D) theories for approximating the tedious and time consuming three-dimensional plate problems.

To the best of the authors’ knowledge and according to literature survey, almost all published higher order shear deformation theories have been limited to simply supported boundary conditions and without taking into account the thermal stresses effects. The existing 2D shear deformation theories of Reddy, Karama and Touratier can be easily recovered. Furthermore, this feature can be highly appreciated in an iterative design process where a large number of derived plate models can be tested by selecting only two parameters in a simple polynomial function which is computationally efficient. Finally, new results are presented to show the effect of material variation, and temperature rise on natural frequencies of the FG plate for different boundary conditions.

Forward rates in the money market are systematically higher than realised spot rates, reflecting an unobservable term premium. This paper uses a Kalman filter specification to produce time‐varying estimates of the term premia in New Zealand and Australia. Three time series specifications are used to examine the properties of the premia, such as the average size, volatility, and the degree of mean reversion. Compared to the constant term premia estimates, the time‐varying estimates explain significantly more of the difference between forward and spot rates. The results suggest that the premium in New Zealand is slowly mean‐reverting, while the Australian premium reverts quickly to the mean. It is not clear whether the method of monetary policy implementation affects the term premium, although in New Zealand the premium has been smaller and less variable since the introduction of the Official Cash Rate in March 1999. A related finding is that the size of the term premium is correlated with the volatility of short‐term rates.