A. Fanni, M. Marchesi, F. Pilo and A. Serri
This paper deals with the application of a Tabu Search (TS) metaheuristic to the design of digital filters, with coefficient values expressed as the sum of power of two. The…
Abstract
This paper deals with the application of a Tabu Search (TS) metaheuristic to the design of digital filters, with coefficient values expressed as the sum of power of two. The performances of the algorithm are heavily affected by the choice of its parameters, which in turn are related to different implemented strategies. The tuning of these parameters has been performed after many tests. The results of the proposed technique are compared to those obtained by simply rounding the optimal values of coefficients obtained by means of Remetz algorithm, and to those obtained using a simulated annealing algorithm.
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B. Cannas, S. Cincotti, A. Fanni, M. Marchesi, F. Pilo and M. Usai
Many practical applications of neural networks require the identification of non‐linear deterministic systems or chaotic systems. In these cases the use of a network architecture…
Abstract
Many practical applications of neural networks require the identification of non‐linear deterministic systems or chaotic systems. In these cases the use of a network architecture known as locally recurrent neural network (LRNN) is often preferable in place of standard feedforward multi‐layer perceptron (MLP) networks, or of globally recurrent neural network. In this paper locally recurrent networks are used to simulate the behaviour of the Chua’s circuit that can be considered a paradigm for studying chaos. It is shown that such networks are able to identify the underlying link among the state variables of the Chua’s circuit. Moreover, they are able to behave like an autonomous Chua’s double scroll, showing a chaotic behaviour of the state variables obtainable through a suitable circuit elements choice.
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Adem Kalinli and Nurhan Karaboga
The purpose of the paper is to present a novel design method for the optimal finite word length (FWL) finite impulse response (FIR) filters.
Abstract
Purpose
The purpose of the paper is to present a novel design method for the optimal finite word length (FWL) finite impulse response (FIR) filters.
Design/methodology/approach
The design method is based on a parallel tabu search (TS) algorithm which uses the crossover operator of the genetic algorithm.
Findings
Three design examples have been presented to show that the proposed method can provide a good solution to the design problem of a FWL FIR filter. In order to show the validity of the proposed method, the performance of the suggested method has been compared to those of widely‐used other methods. From the comparison results, it was concluded that the proposed method can be efficiently used for the optimal FWL FIR filter design.
Research limitations/implications
The number of examples can be increased and also the performance of the proposed method might be compared to other design methods, apart from those presented in this work, developed for the design of optimal FWL FIR filters.
Practical implications
The use of this method produces optimal digital FWL FIR filters with low complexity and therefore provides advantages in the terms of speed and cost.
Originality/value
The originality is the application of the parallel TS algorithm described by the authors to the FWL FIR filter design. The work presented in the paper is particularly important for the researchers studying on the design methods for FWL FIR filter design and the applications of these type filters.
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Leandro dos Santos Coelho and Piergiorgio Alotto
The purpose of this paper is to show, on a widely used benchmark problem, that normative knowledge concepts can be incorporated into particle swarm optimization (PSO) algorithms…
Abstract
Purpose
The purpose of this paper is to show, on a widely used benchmark problem, that normative knowledge concepts can be incorporated into particle swarm optimization (PSO) algorithms in order to improve their search ability.
Design/methodology/approach
Normative knowledge concepts are used within the framework of PSO algorithms in order to influence the cognitive and social components of the particle behaviour.
Findings
It is shown that the proposed algorithm can significantly improve the performance of PSO on the selected benchmark problem, in terms of both best and average solutions.
Research limitations/implications
Although the chosen benchmark is considered to be representative of typical electromagnetic problems, different test cases may give less satisfactory results.
Practical implications
The proposed approach appears to be an efficient general purpose stochastic optimizer for electromagnetic design problems.
Originality/value
This paper introduces the use of normative knowledge concepts to control the cognitive and social components of PSO algorithms.
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Davide Cherubini, Alessandra Fanni, Augusto Montisci and Pietro Testoni
To present a neural network‐based approach to the design of electromagnetic devices.
Abstract
Purpose
To present a neural network‐based approach to the design of electromagnetic devices.
Design/methodology/approach
A neural model is created which reproduces the relationship between the design parameters of the device and the performance parameters, typically field values.
Findings
The neural model is a single hidden layer MLP network, trained by using a set of cases calculated, for example, by means of a finite element analysis. The design problem can be solved by fixing the performance values at the output of the network and by calculating the corresponding input values. The relationship between the input and the output of the neural network is represented by three equations systems. By means of these three systems, we can forward the domain of the input, and we can back propagate the desired output throughout the network layers. In such a way, both the domain of the design parameters and the domain of the desired performances values can be projected in the same space. Whatever point inside the intersection between the two projected domains corresponds to a solution of the design problem.
Originality/value
Presents a procedure which is able to find a point belonging to such an intersection.
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Hesham El Marsafawy, Rumpa Roy and Fahema Ali
This study aims to identify the gap between the requirements of the accreditation bodies and the widely used learning management systems (LMSs) in assessing the intended learning…
Abstract
Purpose
This study aims to identify the gap between the requirements of the accreditation bodies and the widely used learning management systems (LMSs) in assessing the intended learning outcomes (ILOs). In addition, this study aims to introduce a framework, along with the evaluation of the functionality of the LMS, for measuring the ILO.
Design/methodology/approach
A qualitative method was deployed to examine the gap between the requirements of the accreditation standards and the LMS functionalities. The researchers collaborated to design a mechanism, develop a system architecture to measure the ILO in alignment with the accreditation standards and guide the development of the Moodle plugin. The appropriateness and effectiveness of the plugin were evaluated within the scope of assessment mapping and design. Focus group interviews were conducted to collect feedback from the instructors and program leaders regarding its implementation.
Findings
The results of this study indicate that there is no standardized mechanism to measure course and program ILO objectively, using the existing LMS. The implementation of the plugin shows the appropriateness and effectiveness of the system in generating ILO achievement reports, which was confirmed by the users.
Originality/value
This study proposed a framework and developed a system architecture for the objective measurement of the ILO through direct assessment. The plugin was tested to generate consistent reports during the measurement of course and program ILO. The plugin has been implemented across Gulf University’s program courses, ensuring appropriate reporting and continuous improvement.
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Stefan Höhne and Victor Tiberius
The purpose of this study is to formulate the most probable future scenario for the use of blockchain technology within the next 5–10 years in the electricity sector based on…
Abstract
Purpose
The purpose of this study is to formulate the most probable future scenario for the use of blockchain technology within the next 5–10 years in the electricity sector based on today’s experts’ views.
Design/methodology/approach
An international, two-stage Delphi study with 20 projections is used.
Findings
According to the experts, blockchain applications will be primarily based on permissioned or consortium blockchains. Blockchain-based applications will integrate Internet of Things devices in the power grid, manage the e-mobility infrastructure, automate billing and direct payment and issue certificates regarding the origin of electricity. Blockchain solutions are expected to play an important big role in fostering peer-to-peer trading in microgrids, further democratizing and decentralizing the energy sector. New regulatory frameworks become necessary.
Research limitations/implications
The Delphi study’s scope is rather broad than narrow and detailed. Further studies should focus on partial scenarios.
Practical implications
Electricity market participants should build blockchain-based competences and collaborate in current pilot projects.
Social implications
Blockchain technology will further decentralize the energy sector and probably reduce transaction costs.
Originality/value
Despite the assumed importance of blockchain technology, no coherent foresight study on its use and implications exists yet. This study closes this research gap.
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Zahra Khalilnezhad and Karim Eslamloueyan
This study aims to investigate the impact of the oil crash during the COVID-19 pandemic on the economy, energy and the environment in MENA countries, with and without fiscal…
Abstract
Purpose
This study aims to investigate the impact of the oil crash during the COVID-19 pandemic on the economy, energy and the environment in MENA countries, with and without fiscal policy, in a global context.
Design/methodology/approach
This study applies a Global Vector Autoregressive (GVAR) model for 47 countries from 2006Q1 to 2021Q3. The sign restriction method is used to identify the oil shocks originating from the COVID-19 crisis.
Findings
Empirical evidence shows that without fiscal interventions, MENA countries experienced a decline in output growth, energy consumption and CO2 emissions due to lower oil prices caused by the COVID-19 pandemic. The impact of the oil price shock on inflation varied across the region. Economic growth and inflation rates in MENA countries turn positive when the member states implement expansionary fiscal measures to stimulate economic activities during the pandemic. Hence, fiscal policy played a crucial role in supporting the economy and preventing a severe recession during COVID-19 in the MENA region. However, expansionary fiscal measures increased energy consumption and air pollution.
Practical implications
The findings help policymakers better cope with the outbreak of deadly pandemics in the coming years. It improves our understanding of the role of fiscal policy in boosting economic efforts and reducing the adverse environmental impact of increased government spending.
Originality/value
This paper enhances the current body of literature by investigating how fiscal policies implemented by the MENA countries help mitigate the adverse economic effects of the COVID-19 crisis. Moreover, it enables us to analyze the impact of fiscal support on energy consumption and the environment during an oil shock influenced by global uncertainty, lockdowns, and supply chain disruptions.
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Marina Mattera, Carmen Alba Ruiz-Morales, Luana Gava and Federico Soto
The purpose of this study is to evaluate whether the implementation of sustainable business models contributes to improving a firm’s performance during a global crisis, such as…
Abstract
Purpose
The purpose of this study is to evaluate whether the implementation of sustainable business models contributes to improving a firm’s performance during a global crisis, such as the one caused by COVID-19. Based on the triple bottom line theory, the paper explores the relation between the creation of value through solid corporate social responsibility (CSR) strategies, United Nations (UN) Global Compact’s (GC) business model proposals and Global Reporting Initiative’s (GRI) reporting scheme.
Design/methodology/approach
The present paper studies companies within the European Union, focusing specifically on the long-term impact of using the world’s most widely used standards for sustainability reporting – the GRI’s standards and/or the UNGC management models, as well as on the firm’s performance based on the financial results during COVID-19 crisis. To achieve this goal, the study analyses the share price of firms publicly listed in the FTSEMIB (benchmark index of Italy’s largest trading platform) out of those companies that are implementing the UN and GRI’s tools.
Findings
Findings show how a commitment to sustainable business models and long-term CSR strategies can contribute to firm’s ability to overcome periods of economic crisis. Furthermore, implementing GRI standards and UNGC guidelines within the business model seems to have a positive impact in overcoming a hard context such as COVID-19. In addition, it contributes to a better understanding of stakeholders’ needs, consumer profiling and value creation.
Originality/value
This study evaluates firms’ business models, considering the effects of decisions made in the context of COVID-19. The role of UNGC and GRI is evaluated in terms of their contribution to firms’ financial performance and corporate reputation during a context of hardship. Consequently, this study contributes to academia and practice, adding value in areas related to strategic planning and business model design.
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Ali Amin, Muhammad Arshad, Naheed Sultana and Rabeeya Raoof
The rapid spread of COVID-19 has dramatic effects on financial market across the globe. This study analyzes the relationship between the COVID-19 cases, age and stock market…
Abstract
Purpose
The rapid spread of COVID-19 has dramatic effects on financial market across the globe. This study analyzes the relationship between the COVID-19 cases, age and stock market indexes in Central America, North America, and South America.
Design/methodology/approach
The panel regression analysis on three regions from March 10, 2020 to April 9, 2020 was conducted to test the hypothesized model. The authors used Levin et al.’s (2002) panel data unit root test to check the stationarity, and Hausman (1978) test was applied to determine the random and fixed effects.
Findings
The authors’ panel regression results indicate that the COVID-19 cases have a negative impact on stock indexes, whereas the age has a positive impact on the stock indexes. The region-wise analysis supports the panel finding except for South America, which shows an insignificant association between stock indexes and COVID-19 cases.
Originality/value
The study supplements the literature by examining the impact of pandemics on stock indexes and focus on three multicultural regions, comprising developed, developing and emerging countries, which are hitherto unaddressed.