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1 – 10 of 902Slawomir Koziel and Anna Pietrenko-Dabrowska
A novel framework for expedited antenna optimization with an iterative prediction-correction scheme is proposed. The methodology is comprehensively validated using three…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Originality/value
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.
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Competition among higher education institutions has pushed universities to expand their competitive advantages. Based on the assumption that the core functions of universities are…
Abstract
Purpose
Competition among higher education institutions has pushed universities to expand their competitive advantages. Based on the assumption that the core functions of universities are academic, understanding the teaching–learning process with the help of student evaluation of teaching (SET) would seem to be a logical solution in increasing competitiveness. The paper aims to discuss these issues.
Design/methodology/approach
The current paper presents a narrative literature review examining how SETs work within the concept of service marketing, focusing specifically on the search, experience, and credence qualities of the provider. A review of the various factors that affect the collection of SETs is also included.
Findings
Relevant findings show the influence of students’ prior expectations on SET ratings. Therefore, teachers are advised to establish a psychological contract with the students at the start of the semester. Such an agreement should be negotiated, setting out the potential benefits of undertaking the course and a clear definition of acceptable performance within the class. Moreover, connections should be made between courses and subjects in order to provide an overall view of the entire program together with future career pathways.
Originality/value
Given the complex factors affecting SETs and the antecedents involved, there appears to be no single perfect tool to adequately reflect what is happening in the classroom. As different SETs may be needed for different courses and subjects, options such as faculty self-evaluation and peer-evaluation might be considered to augment current SETs.
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Abstract
Purpose
Increasing carbon productivity is an effective way to reduce carbon emissions, while boosting economic prosperity. For appropriate formulating and enforcement of energy saving and carbon emissions reduction policies in various sectors, it is of great significance to investigate the evolution characteristics and convergence modes of carbon productivity across the manufacturing sectors.
Design/methodology/approach
Using slack-based measure directional distance function (SBM-DDF) and global Malmquist–Luenberger (GML) productivity index, this paper measures the carbon productivities of 29 manufacturing subsectors in Shanghai, China, from 2001 to 2016 under the total factor framework. Furthermore, based on the convergence theories, it empirically examines the convergence of carbon productivity across these manufacturing sectors.
Findings
The measurement results suggest that the carbon productivities of the manufacturing sectors in Shanghai show an increasing tendency on the whole, and technical efficiency instead of technological change makes a main contribution to the increase. It is found that there is no obvious σ convergence across the manufacturing sectors in Shanghai, but there exist both absolute ß convergence and conditional ß convergence. Moreover, there is heterogeneity in convergence characteristics between the clean sectors and polluting sectors. The findings also show that firm size and industry structure have significant positive impacts on the growth of carbon productivities of the manufacturing sectors, whereas the impacts of capital deepening and energy consumption structure are significantly negative.
Originality/value
This paper measures the carbon productivities of the manufacturing subsectors by applying SBM-DDF and GML index, so as to improve the accuracy. It provides an insight into the convergence of carbon productivity across the manufacturing sectors.
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Ming-Miin Yu, Bo Hsiao, Shih-Hsun Hsu and Shaw Yu Li
This paper presents an alternative approach to evaluating the overall efficiency and performance of Taiwanese container ports. Specifically, a parallel activity with series…
Abstract
This paper presents an alternative approach to evaluating the overall efficiency and performance of Taiwanese container ports. Specifically, a parallel activity with series structure concept in the form of data envelopment analysis (MNDEA) is used to construct a model that applies to three different activities: harbor management, stevedoring and warehousing operations. We will further divide each activity into two process types, production processes and services processes. We will also adopt a Delphi survey approach and use the Analytic Network Process (ANP) to identify these processes’influence dependence and their degree of importance for the MNDEA model setting. An empirical application demonstrates the performance of Taiwanese container ports by using MNDEA with window analysis techniques via the directional distance functionThe results demonstrate that the application is effective in indicating and/or suggesting resource-adjustments, while considering which undesirable output levels and shared inputs were involved. The results also present directions for possible improvements in workplace efficiency.
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