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A novel framework for expedited antenna optimization with an iterative prediction-correction scheme is proposed. The methodology is comprehensively validated using three real-world antenna structures: narrow-band, dual-band and wideband, optimized under various design scenarios.

The keystone of the proposed approach is to reuse designs pre-optimized for various sets of performance specifications and to encode them into metamodels that render good initial designs, as well as an initial estimate of the antenna response sensitivities. Subsequent design refinement is realized using an iterative prediction-correction loop accommodating the discrepancies between the actual and target design specifications.

The presented framework is capable of yielding optimized antenna designs at the cost of just a few full-wave electromagnetic simulations. The practical importance of the iterative correction procedure has been corroborated by benchmarking against gradient-only refinement. It has been found that the incorporation of problem-specific knowledge into the optimization framework greatly facilitates parameter adjustment and improves its reliability.

The proposed approach can be a viable tool for antenna optimization whenever a certain number of previously obtained designs are available or the designer finds the initial effort of their gathering justifiable by intended re-use of the procedure. The future work will incorporate response features technology for improving the accuracy of the initial approximation of antenna response sensitivities.

The proposed optimization framework has been proved to be a viable tool for cost-efficient and reliable antenna optimization. To the knowledge, this approach to antenna optimization goes beyond the capabilities of available methods, especially in terms of efficient utilization of the existing knowledge, thus enabling reliable parameter tuning over broad ranges of both operating conditions and material parameters of the structure of interest.

The purpose of this study is to find the optimum design of Reinforced Concrete (RC) pile foundation to enable efficient use of structural concrete with greater consequences for global environment and economy.

A non-linear optimisation technique based on the Generalised Reduced Gradient (GRG) algorithm was implemented to find the minimum cost of RC pile foundation in frictional soil. This was achieved by obtaining the optimum pile satisfying the serviceability and ultimate limit state requirements of BS 8004 and EC 7. The formulated structural optimisation procedure was applied to a case study project to assess the efficiency of the proposed design formulation.

The results prove that the GRG method in Excel solver is an active, fast, accurate and efficient computer programme to obtain optimum pile design. The application of the optimisation for the case study project shows up to 26% cost reduction compared to the conventional design.

The design and formulation of design constraints will be limited to provisions of BS 8004 and EC 7.

Since the minimum quantity of concrete was attained through optimisation, then minimum cement will be used and thus result in minimum CO₂ emission. Therefore, the optimum design of concrete structures is a vital solution to limit the damage to the Earth's climate and the physical environment resulting from high carbon emissions.

The current study considers the incorporation of different soil ground parameters in the optimisation process rather than assuming any pile capacity value for the optimisation process.

The purpose of this paper is to study the optimization of the geographical location of a network of points of sale, so that each retailer can have access to a potential geographic market. In addition, the authors study the importance of the distance variable in the commercial viability of a point of sale and a network of points of sale, analysing if the best location for each point (local optimum) is always the best location for the whole (global optimum).

Location-allocation models are applied using p-median algorithms and spatial competition maximization to analyse the actual journeys of 64,740 car buyers in 1240 postal codes using a geographic information system (GIS) and geomarketing techniques.

The models show that the pursuit of individual objectives by each concessionaire over the collective provides poorer results for the whole network of points of sale when compared to coordinated competition. The solutions provided by the models considering geographic and marketing criteria permit a reduction in the length of journeys made by the buyers. GIS allows the optimal control of market demand coverage through the collaborative strategies of the supplying retailers, in this case, car dealerships.

The paper contributes to the joint research of geography and marketing from a theoretical and practical point of view. The main contribution is the use of information on actual buyer journeys for the optimal location of a network of points of sale. This research also contributes to the analysis of the correlation between the optimum local and optimum global locations of a commercial network and is a pioneering work in the application of these models to the automotive sector in the territorial area of the study.

The purpose of this paper is to present the development of an optimal design framework for high altitude long endurance solar unmanned aerial vehicle. The proposed solar aircraft design framework provides a simple method to design solar aircraft for users of all levels of experience.

This design framework consists of algorithms and user interfaces for the design of experiments, optimization and mission analysis that includes aerodynamics, performance, solar energy, weight and flight distances.

The proposed sizing method produces the optimal solar aircraft that yields the minimum weight and satisfies the constraints such as the power balance, the night time energy balance and the lift coefficient limit.

The design conditions for the sizing process are given in terms of mission altitudes, flight dates, flight latitudes/longitudes and design factors for the aircraft configuration.

The framework environment is light and easily accessible as it is implemented using open programs without the use of any expensive commercial tools or in-house programs. In addition, this study presents a sizing method for solar aircraft as traditional sizing methods fail to reflect their unique features.

Solar aircraft can be used in place of a satellite and introduce many advantages. The solar aircraft is much cheaper than the conventional satellite, which costs approximately $200-300m. It operates at a closer altitude to the ground and allows for a better visual inspection. It also provides greater flexibility of missions and covers a wider range of applications.

This study presents the implementation of a function that yields optimized flight performance under the given mission conditions, such as climb, cruise and descent for a solar aircraft.

A critical attribute of open educational practices (OEP) is the pursuit of open scholarship which comprises the release of educational resources under an open licence scheme that permits no-cost access, use, reuse, adaptation, retention and redistribution to others. The degree of openness in relation to this attribute will depend on the context and culture of the place and the people in it. When left to chance, the adoption and practice of open scholarship by educators is at best sketchy. For optimum impact, a design-based approach is essential. A central focus of such an approach will need to target educators’ belief systems and practices about their scholarship. Any such work will involve researchers collaborating with practitioners in real-life settings to improve educational practices through iterative analysis, design, development and implementation. The purpose of this paper is to report on how the development and use of such a design-based approach, implemented by the Open University of Sri Lanka, impacted the adoption and uptake of open scholarship among teachers in the Sri Lankan school system in terms of changes in their use of instructional resources, pedagogical thinking and pedagogical practices.

The study adopted a design-based research (DBR) approach (Reeves, 2006), which involved researchers collaboratively working with practitioners in real-life settings to improve their educational practices along three aspects – instructional resource use, pedagogical perspectives and pedagogical practices. Based on the four stages of the DBR approach – analysis, solution, testing and refinement, and reflection, a professional development intervention programme was designed and implemented to support teachers on the integration of open educational resources (OER) and adoption of OEP in their teaching-learning process. Data collected throughout the process using multiple strategies such as questionnaire surveys, concept mapping, lesson plans, focus group interviews, self-reflections and “stories”, were analyzed using both qualitative and quantitative methods.

By the end of the intervention, significant changes were observed in teachers’ use of instructional resources, their pedagogical thinking and pedagogical practices. While resource usage has shifted from no or low usage of OER to reuse, revise, remix and creation of OER, the pedagogical thinking and practices of teachers moved from a content-centric and individualized patterns to more constructivist, context centric and collaborative ways. The diffusion of OEP was prominent along two dimensions – enhancements in the individual practices in innovative OER use as well as collaborative practices of sharing of resources, knowledge and good practices.

The systematic and flexible methodology adopted based on the DBR approach via a framework designed as a contextualized, process oriented and a self-reflective enquiry has been very useful to support changes in OEP among practitioners over time.

This iterative process allowed the researchers to function as “designers”, while investigating real-life issues in collaboration with the practitioners through reflective enquiry to further refine innovative practices towards OEP. This provides valuable insights for improved design solutions for future interventions in similar contexts.

Nature-based tourism (NBT) blossoming requires sound monitoring models to maximize its potential in the tourism industry. Cooperation of different segments from nature to economy will lead to a sustainable NBT. Therefore, the qualitative and quantitative relation between these subdivisions has to be investigated.

This paper proposes an advanced NBT model for the design of an optimum tourism system. To this end, Bayesian network (BN) has been implemented to characterize the impact of each subsector on NBT.

The outcomes of this study can help the tourism managers, policymakers and related organizations to find the optimum approach to achieve a continuous improvement in the system. To demonstrate the applicability of the methodology, two cases of observations are considered.

The originality of the work is well demonstrated in the literature review of the paper.

This study aims to propose a computationally efficient framework for multi-objective optimization (MO) of antennas involving nested kriging modeling technology. The technique is demonstrated through a two-objective optimization of a planar Yagi antenna and three-objective design of a compact wideband antenna.

The keystone of the proposed approach is the usage of recently introduced nested kriging modeling for identifying the design space region containing the Pareto front and constructing fast surrogate model for the MO algorithm. Surrogate-assisted design refinement is applied to improve the accuracy of Pareto set determination. Consequently, the Pareto set is obtained cost-efficiently, even though the optimization process uses solely high-fidelity electromagnetic (EM) analysis.

The optimization cost is dramatically reduced for the proposed framework as compared to other state-of-the-art frameworks. The initial Pareto set is identified more precisely (its span is wider and of better quality), which is a result of a considerably smaller domain of the nested kriging model and better predictive power of the surrogate.

The proposed technique can be generalized to accommodate low- and high-fidelity EM simulations in a straightforward manner. The future work will incorporate variable-fidelity simulations to further reduce the cost of the training data acquisition.

The fast MO optimization procedure with the use of the nested kriging modeling technology for approximation of the Pareto set has been proposed and its superiority over state-of-the-art surrogate-assisted procedures has been proved. To the best of the authors’ knowledge, this approach to multi-objective antenna optimization is novel and enables obtaining optimal designs cost-effectively even in relatively high-dimensional spaces (considering typical antenna design setups) within wide parameter ranges.

This paper aims to study the impacts of groundwater seepage on artificial freezing process of gravel strata, the temperature field characteristics of the strata, and the strata process, closure time and thickness evolution mechanism of the frozen wall.

In this paper several laboratory model tests were conducted, considering different groundwater seepage rate.

The results show that there is a significant coupling effect between the cold diffusion of artificial freezing pipes and groundwater seepage; when there is no seepage, temperature fields upstream and downstream of the gravel strata are symmetrically distributed, and the thickness of the frozen soil column/frozen wall is consistent during artificial freezing; groundwater seepage causes significant asymmetry in the temperature fields upstream and downstream of the gravel strata, and the greater the seepage rate, the more obvious the asymmetry; the frozen wall closure time increases linearly with the increase in the groundwater seepage rate, and specifically, the time length under seepage rate of 5.00 m d⁻¹ is 3.2 times longer than that under no seepage; due to the erosion from groundwater seepage, the thickness of the upstream frozen wall decreases linearly with the seepage velocity, while that of the downstream frozen wall increases linearly, resulting in a saddle-shaped frozen wall.

The research results are beneficial to the optimum design and risk control of artificial freezing process in gravel strata.

Destinations to be able to compete with each other need to equip themselves with as many competitive advantages as possible. Tourists' loyalty to a destination is considered as a prominent competitive tool for destinations. Tourists' loyalty manifests itself in recommendation of the destination to others, repeat visit of the destination and willingness to revisit the destination. Although a plethora of studies have tried to define models to show the relation between loyalty and the antecedent factors leading up to it, few of them have tried to integrate these models with mathematical approaches for better understanding of loyalty behavior. The purpose of this paper is to integrate a tourist destination model with Bayesian Network in order to predict the behaviour of destination loyalty and its antecedent factors.

This paper has developed a probability model by the integration of a destination loyalty model with a Bayesian network (BN) which enables to predict and analyze the behavior of loyalty and its influential factors. To demonstrate the application of this framework, Tehran, the capital of Iran, was chosen as a destination case study.

The outcome of this research will assist in identifying the weak key points in the tourist destination area for giving insights to the marketers, businesses and policy makers for making better decisions related to destination loyalty. In the analysis process, the most influential factors were recognized as the travel environment image, natural/historical attractions and, with a lower degree, infrastructure image which help the decision maker to detect and reinforce the weak factors and put more effort in focusing on improving the necessary parts rather than the irrelevant parts.

The research identified all critical factors that have the most influence on destination loyalty while driving the associate uncertainty which is significant for the tourism industry. This resulted in better decision-making which is used to identify the impact of tourism destination loyalty.

The goal of this paper is twofold: to assess the influence of specific corporate and market features on automobiles and parts sector's profitability in Euro area and to identify this particular sector's optimum debt level.

For the paper's purposes, the authors applied a panel data analysis on an annual basis for the period 2005–2017.

There is a strong statistical significance of debt ratio, growth domestic product per capita growth, E.C.'s economic sentiment index (ESI), the European Central Bank key interest rate and the Euro area crisis on sector's profitability, while weak statistical significance appears to emerge for the firm's size. Moreover, the authors find average 14.4% profitability for the entire sector of the Euro area, without significant fluctuations among firms and/or during the examined time period. Another interesting finding of this study is that results are consistent with the theory of Modigliani Miller that financial leverage at a “low” level is beneficial for the firm, but beyond a turning point, it becomes counterproductive. This turning point for the automobiles and parts sector in Euro area has been computed at 47.3%.

The paper focuses on issues of profitability, capital structure and optimal debt ratio of an important sector of the economy, the automotive sector. As regards the Euro area automotive sector, it is a dynamic sector with a significant multiplier effect for the European economy as it is strongly correlated with other industrial sectors as chemicals, steel, textiles, information technology and so forth, having an outstanding multiplier effect on the economy.