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The electromagnetic field and cooling system of a high power switched reluctance motor (SRM) are studied numerically. The geometry of the motor and its main components are established using a computer-aided design software in the actual size. This study aims to evaluate the resulting thermal losses using the electromagnetic analysis of the motor.

In the electromagnetic analysis, the Joule’s loss in the copper wires of the coil windings and the iron losses (the eddy currents loss and the hysteresis loss) are considered. The flow and heat transfer model for the thermal analysis of the motor including the conduction in solid parts and convection in the fluid part is introduced. The magnetic losses are imported into the thermal analysis model in the form of internal heat generation in motor components. Several cooling system approaches were introduced, such as natural convection cooling, natural convection cooling with various types of fins over the motor casing, forced conviction air-cooled cooling system using a mounted fan, casing surface with and without heat sinks, liquid-cooled cooling system using the water in a channel shell and a hybrid air-cooled and liquid-cooled cooling system.

The results of the electromagnetics analysis show that the low rotational speed of the motor induces higher currents in coil windings, which in turn, it causes higher copper losses in SRM coil windings. For higher rotational speed of SRM, the core loss is higher than the copper loss is in SRM due to the higher frequency. An air-cooled cooling system is used for cooling of SRM. The results reveal when the rotational speed is at 4,000 rpm, the coil loss would be at the maximum value. Therefore, the coil temperature is about 197.9°C, which is higher than the tolerated standard temperature insulation material. Hence, the air-cooled system cannot reduce the temperature to the safe temperature limitation of the motor and guarantee the safe operation of SRM. Thus, a hybrid system of both air-cooled and liquid-cooled cooling system with mounting fins at the outer surface of the casing is proposed. The hybrid system with the liquid flow of Re = 1,500 provides a cooling power capable of safe operation of the motor at 117.2°C, which is adequate for standard insulation material grade E.

The electromagnetic field and cooling system of a high power SRM in the presence of a mounted fan at the rear of the motor are analyzed. The thermal analysis is performed for both of the air-cooled and liquid-cooled cooling systems to meet the cooling demands of the motor for the first time.

In recent years, the application of metaheuristics in training neural network models has gained significance due to the drawbacks of deterministic algorithms. This paper aims to propose the use of a recently developed “memory based hybrid dragonfly algorithm” (MHDA) for training multi-layer perceptron (MLP) model by finding the optimal set of weight and biases.

The efficiency of MHDA in training MLPs is evaluated by applying it to classification and approximation benchmark data sets. Performance comparison between MHDA and other training algorithms is carried out and the significance of results is proved by statistical methods. The computational complexity of MHDA trained MLP is estimated.

Simulation result shows that MHDA can effectively find the near optimum set of weight and biases at a higher convergence rate when compared to other training algorithms.

This paper presents MHDA as an alternative optimization algorithm for training MLP. MHDA can effectively optimize set of weight and biases and can be a potential trainer for MLPs.

Highly non-linear optimization problems exist in many practical engineering applications. To deal with these problems, this study aims to propose an improved optimization algorithm, named, adaptive resistance and stamina strategy-based dragonfly algorithm (ARSSDA).

To speed up the convergence, ARSSDA applies an adaptive resistance and stamina strategy (ARSS) to conventional dragonfly algorithm so that the search step can be adjusted appropriately in each iteration. In ARSS, it includes the air resistance and physical stamina of dragonfly during a flight. These parameters can be updated in real time as the flight status of the dragonflies.

The performance of ARSSDA is verified by 30 benchmark functions of Congress on Evolutionary Computation 2014’s special session and 3 well-known constrained engineering problems. Results reveal that ARSSDA is a competitive algorithm for solving the optimization problems. Further, ARSSDA is used to search the optimal parameters for a bucket wheel reclaimer (BWR). The aim of the numerical experiment is to achieve the global optimal structure of the BWR by minimizing the energy consumption. Results indicate that ARSSDA generates an optimal structure of BWR and decreases the energy consumption by 22.428% compared with the initial design.

A novel search strategy is proposed to enhance the global exploratory capability and convergence speed. This paper provides an effective optimization algorithm for solving constrained optimization problems.

The purpose of this paper is to determine the antioxidant activity of natural polyphenols from larch wood by the amperometric method.

Direct measurements of antioxidant activity were carried out by the amperometric method in an oxidizing mode with glassy carbon as a working electrode, set potential +1.3V and using a flow-injection system with 2.2 mM phosphoric acid as the mobile phase with a flow rate of 1.2 ml/min.

The reported results show the following values of antioxidant activity for the tested compounds: (−)-secoisolariciresinol – 0.199 ± 0.002 mg/L (p < 0.05); isolariciresinol – 0.196 ± 0.002 mg/L (p < 0.05); lariciresinol - 0.222 ± 0.001 mg/L (p < 0.05); O-isopropylidene derivative of (−)-secoisolariciresinol - 0.143 ± 0.002 mg/L (p < 0.05); (+)-dihydroquercetin – 0.153 ± 0.002 mg/L (p < 0.05); and quercetin – 0.521 ± 0.001 mg/L (p < 0.05). The last product was tested as the reference of a widely used current antioxidant. General tendencies of determined values of antioxidant activity for studied compounds are in good correlation with published data as determined by the t-BuOOH-initiated lipid peroxidation method.

Described results show practical applicability of the amperometric method as being faster and cheaper in comparison to other methods, including oxygen radical absorbance capacity (ORAC) assay or 2,2′diphenyl-1-picrylhydrazyl (DPPH) reagent based assay.

The described results show the first-time application of the amperometric method for the evaluation of the antioxidant activity of phenolic compounds from larch wood.

Additive manufacturing (AM) or solid freeform fabrication (SFF) technique is extensively used to produce intrinsic 3D structures with high accuracy. Its significant contributions in the field of tissue engineering (TE) have significantly increased in the recent years. TE is used to regenerate or repair impaired tissues which are caused by trauma, disease and injury in human body. There are a number of novel materials such as polymers, ceramics and composites, which possess immense potential for production of scaffolds. However, the major challenge is in developing those bioactive and patient-specific scaffolds, which have a required controlled design like pore architecture with good interconnectivity, optimized porosity and microstructure. Such design not only supports cell proliferation but also promotes good adhesion and differentiation. However, the traditional techniques fail to fulfill all the required specific properties in tissue scaffold. The purpose of this study is to report the review on AM techniques for the fabrication of TE scaffolds.

The present review paper provides a detailed analysis of the widely used AM techniques to construct tissue scaffolds using stereolithography (SLA), selective laser sintering (SLS), fused deposition modeling (FDM), binder jetting (BJ) and advanced or hybrid additive manufacturing methods.

Subsequently, this study also focuses on understanding the concepts of TE scaffolds and their characteristics, working principle of scaffolds fabrication process. Besides this, mechanical properties, characteristics of microstructure, in vitro and in vivo analysis of the fabricated scaffolds have also been discussed in detail.

The review paper highlights the way forward in the area of additive manufacturing applications in TE field by following a systematic review methodology.

City has a continuous need to diversify its products and services to ensure longer tourists’ stays and a profitable tourism industry. Kuala Lumpur is one of the most popular cities in the world, and within its vicinity, Batu Caves are not only an important Hindu religious site, but also a popular tourist attraction. Guided by the four realms of experience dimensions (Pine and Gilmore, 1998), the purpose of this paper is to analyze 54 essays written by university students, to examine the experience of their visit to Batu Caves. The findings confirmed the application of all the four realm dimensions – entertainment, educational, esthetic and escapist – revealing both positive and negative aspects of the experience. Batu Caves may capitalize on the positive experiences as pointers to create an effective marketing communication, while negative experiences are opportunities to devise appropriate corrective measures, and perhaps further develop tourism products and services that would appeal to the visitors’ experience.

This study employed a qualitative research strategy to examine visitors’ experiences at Batu Caves using the four realms of experience theory as coined by Pine and Gilmore (1998). A total of 54 undergrads were asked to describe their visit to Batu Caves (Lucia-Palacios et al., 2016) providing a complete insight of their opinions, feelings and perceptions (Jüttner et al., 2013) using the essay writing method.

The authors discovered firm evidence of the theory’s application, revealing the expected four experiential dimensions in explaining experience at a cultural religious site, extending the description to include its positive and negative aspects, all of which are useful for destination management. The study points out a lot of aspects that must be managed by the site, such as the poor esthetic experience (e.g. smell, rubbish, graffiti, etc.), controlling the animal aggression (i.e. monkeys) and perhaps develop new products and services which could enhance some experiences (e.g. cultural escapism through cultural performances in which visitors could participate).

The main weakness of the research is perhaps the qualitative research work in which data were collected from essays written by the university students. Data of this nature prevent us from being able to generalize the findings and reflect on the experience to the general public.

Tourist stays in Kuala Lumpur could be enhanced by providing meaningful, deep and memorable experiences. Tourist attractions such as Batu Caves should continuously examine the experience that they provide to the visitors. Batu Caves’ management could continuously measure its tourists’ experience provisions, as tourists’ needs evolve over time. From the results they could revamp their products and services offering to ensure the sustainability of Batu Caves’ natural and cultural appeal among visitors and tourists alike.

The outcome provides a better understanding of the current tourism product and services at the destination that have an impact on a visitor’s experience. The findings will assist the Batu Caves’ management to revise and develop the products and service offerings to the visitors.

This study constructs time series model, artificial neural networks (ANNs) and statistical topologies to examine the volatility and forecast foreign exchange rates. The Mauritian forex market has been utilized as a case study, and daily data for nominal spot rate (during a time period of five years spanning from 2014 to 2018) for EUR/MUR, GBP/MUR, CAD/MUR and AUD/MUR have been applied for the predictions.

Autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH) models are used as a basis for time series modelling for the analysis, along with the non-linear autoregressive network with exogenous inputs (NARX) neural network backpropagation algorithm utilizing different training functions, namely, Levenberg–Marquardt (LM), Bayesian regularization and scaled conjugate gradient (SCG) algorithms. The study also features a hybrid kernel principal component analysis (KPCA) using the support vector regression (SVR) algorithm as an additional statistical tool to conduct financial market forecasting modelling. Mean squared error (MSE) and root mean square error (RMSE) are employed as indicators for the performance of the models.

The results demonstrated that the GARCH model performed better in terms of volatility clustering and prediction compared to the ARIMA model. On the other hand, the NARX model indicated that LM and Bayesian regularization training algorithms are the most appropriate method of forecasting the different currency exchange rates as the MSE and RMSE seemed to be the lowest error compared to the other training functions. Meanwhile, the results reported that NARX and KPCA–SVR topologies outperformed the linear time series models due to the theory based on the structural risk minimization principle. Finally, the comparison between the NARX model and KPCA–SVR illustrated that the NARX model outperformed the statistical prediction model. Overall, the study deduced that the NARX topology achieves better prediction performance results compared to time series and statistical parameters.

The foreign exchange market is considered to be instable owing to uncertainties in the economic environment of any country and thus, accurate forecasting of foreign exchange rates is crucial for any foreign exchange activity. The study has an important economic implication as it will help researchers, investors, traders, speculators and financial analysts, users of financial news in banking and financial institutions, money changers, non-banking financial companies and stock exchange institutions in Mauritius to take investment decisions in terms of international portfolios. Moreover, currency rates instability might raise transaction costs and diminish the returns in terms of international trade. Exchange rate volatility raises the need to implement a highly organized risk management measures so as to disclose future trend and movement of the foreign currencies which could act as an essential guidance for foreign exchange participants. By this way, they will be more alert before conducting any forex transactions including hedging, asset pricing or any speculation activity, take corrective actions, thus preventing them from making any potential losses in the future and gain more profit.

This is one of the first studies applying artificial intelligence (AI) while making use of time series modelling, the NARX neural network backpropagation algorithm and hybrid KPCA–SVR to predict forex using multiple currencies in the foreign exchange market in Mauritius.

The purpose of this paper is to discuss published research in rotorcraft which has taken place in India during the last ten years. The helicopter research is divided into the following parts: health monitoring, smart rotor, design optimization, control, helicopter rotor dynamics, active control of structural response (ACSR) and helicopter design and development. Aspects of health monitoring and smart rotor are discussed in detail. Further work needed and areas for international collaboration are pointed out.

The archival journal papers on helicopter engineering published from India are obtained from databases and are studied and discussed. The contribution of the basic research to the state‐of‐the‐art in helicopter engineering science is brought out.

It is found that strong research capabilities have developed in rotor system health and usage monitoring, rotor blade design optimization, ACSR, composite rotor blades and smart rotor development. Furthermore, rotorcraft modeling and analysis aspects are highly developed with considerable manpower available and being generated in these areas.

Two helicopter projects leading to the “advanced light helicopter” and “light combat helicopter” have been completed by Hindustan Aeronautics Ltd These helicopter programs have benefited from the basic research and also provide platforms for further basic research and deeper industry academic collaborations. The development of well‐trained helicopter engineers is also attractive for international helicopter design and manufacturing companies. The basic research done needs to be further developed for practical and commercial applications.

This is the first comprehensive research on rotorcraft research in India, an important emerging market, manufacturing and sourcing destination for the industry.

Technology has penetrated in every aspect of society, and information and communication technologies (ICTs) have become a part of every aspect of life. Over 20 years of ICT use, nearly every government and the big business area has been radically transformed. Education is a profoundly social profession, and historically, effective education has been associated with good instructors who have a high level of personal connection with students. The use of ICT in higher education allows for more student-cantered learning settings. Nevertheless, as digital media and information continue to take over our lives, the importance of ICT inside higher education continues to rise. The higher education system plays a crucial part in every country’s growth in improving human resources (HR); higher education should create an educated population that will bring peace and socioeconomic and societal growth. Education reform agendas benefit from the use of ICT in most developing nations. ICT in education is one of the most practical approaches to improve India’s higher education system. The purpose of this review chapter was to examine the role of ICT in higher education. This chapter addressed how ICT may promote and revolutionize higher education in India through new government initiatives. Furthermore, the chapter addressed the issues and challenges associated with the use of ICT for educational purposes.

Today, amid a global pandemic, the world is changing rapidly. This bought a sense of urgency to adopt this change for the sustainability of both individual and corporate existence. The name given to the future world on the brink of this change and transformation is VUCA (Volatility, Uncertainty, Complexity and Ambiguity). COVID-19 pandemic exposed leadership teams to novel challenges that required many changes to their practices. This has been the most volatile, uncertain, complex, and ambiguous (VUCA) times in healthcare. VUCA software technologies that connect different geographies of the world over the Internet have provided institutions with standardization, harmonization, and acceleration. Understanding the VUCA world, adapting to it, focusing on the opportunities rather than the challenges it brings are the basis of sustainability. In order to increase or maintain the level of development of the countries, it is possible with the health institutions to provide a quality service and the development of standardization based on the VUCA approach. This global pandemic has clearly affected healthcare systems and workers throughout the world, with many worse affected than others. This chapter aimed to give information about the importance of why health managers should provide services based on the VUCA approach.