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The purpose of this paper is to develop and compare conventional and neural network-based controllers for gas turbines.

Design of two different controllers is considered. These controllers consist of a NARMA-L2 which is an artificial neural network-based nonlinear autoregressive moving average (NARMA) controller with feedback linearization, and a conventional proportional-integrator-derivative (PID) controller for a low-power aero gas turbine. They are briefly described and their parameters are adjusted and tuned in Simulink-MATLAB environment according to the requirement of the gas turbine system and the control objectives. For this purpose, Simulink and neural network-based modelling is used. Performances of the controllers are explored and compared on the base of design criteria and performance indices.

It is shown that NARMA-L2, as a neural network-based controller, has a superior performance to PID controller.

This study aims at using artificial intelligence in gas turbine control systems.

This paper provides a novel methodology for control of gas turbines.

Traditional administration of building services regards them as having confined scope, operating in isolation or tightly coupled and providing minimal support for overall coordination and holistic management hindering the provisioning of advanced services. This approach inherently bears weaknesses related to complex services management, results in increased costs, and formulates rigid architectural design that restricts flexibility and extensibility. Taking into consideration this set of drawbacks, the purpose of this paper is to propose exploiting a service‐oriented architecture that will allow for dynamic, coordinated and distributed building services management.

The paper presents the design of an enterprise‐based networking architecture for building services and systems and specifies its functional components.

The proposed architecture is compliant with established practices in the building automation field and focuses on catering for a wide spectrum of building and enterprise level services. A specific deployment use‐case scenario and its related implementation issues is considered, so as to promote interoperability and adoption of open standards and principles for the system level performance evaluation of the proposed architecture is also examined.

Literature review is not exhaustive and evaluation of the proposed architecture should be performed in a more systematic manner.

Adoption of a service‐oriented view as far as facilities management is concerned.

This paper identifies through a thorough literature review the research problems in the area of building services integration and proposes an approach to enable successful integration. The novelty of this work is based on the application of the state‐of‐the‐art in enterprise networking for integration of building management and IT‐based services.

This paper aims to provide a comprehensive understanding of the supply chain learning (SCL)–performance relationship based on the existing empirical evidence.

We sampled 54 empirical studies on the SCL–performance relationship. We proposed a conceptual research framework and adopted a meta-analytical approach to analyse the SCL–performance relationship.

The results of the meta-analysis confirm the positive effects of SCL on the performance of both firms and supply chains. In addition, building on the knowledge-based view, we found that learning from customers has a stronger positive effect on performance than does learning from suppliers, while joint learning has a stronger positive effect on performance than does absorptive learning. Business knowledge had a greater effect on performance than did general knowledge, process knowledge or technical knowledge, while explicit knowledge had a stronger effect than tacit knowledge. Moreover, the SCL–performance relationship is moderated by performance measure and industry type but not by regional economic development, highlighting the broad applicability of SCL.

This study is the first meta-analysis on the SCL–performance relationship. It differentiates between learning from customers and learning from suppliers, examines a more comprehensive list of performance measures and tests five moderators to the main effect, significantly contributing to the SCL literature.

The purpose of this paper is to explore the efficacy of 40 inventive principles of TRIZ for developing researchers' innovative capabilities and to evaluate the extent of application of “40 inventive principles” by inventors in the Research Center of Intelligent and Signal Processing (a successful research center that is producing new products in the field of signal processing and medical engineering).

A range of relevant literature is explored initially. A questionnaire about 40 inventive principles of TRIZ was developed based on literature review. Finally, a data analysis including descriptive statistics, correlation and regression analysis was designed by using SPSS software.

The results showed that about 71 percent of the researchers have employed TRIZ above the average in their innovative products. Also these studied researchers used TRIZ principles unintentionally. Therefore, if this research center and similar institutes want to make full use of their researchers' abilities, they can facilitate innovation through offering courses on TRIZ, the principles of TRIZ and its other tools to them.

This study is probably the first to provide an exploring of TRIZ inventive principles applications through a research center.

Ukraine hosts thousands of international students for educational tourism, of which more than 18,000 Indian medical students were compelled to escape Ukraine under emergency conditions of war. This paper aims to examine their intention to return to Ukraine to complete their education based on an integrated theory of planned behaviour (TPB) framework with added constructs, i.e. risk perception, career anxiety, rescue and relief memory.

The data were collected from 26 February 2022 to 30 June 2022 in two phases and two modes. It was ensured that the respondents were strictly confined to Indian medical students who had travelled to Ukraine for educational tourism. SPSS 25 and AMOS 23.0 were used to analyse the data. The hypotheses proposed were statistically tested.

The analysis reveals that the extended TPB model resulted in a strong model and the empirical findings corroborate that the students’ attitude, subjective norms, perceived behavioural control and career anxiety significantly and positively influence the students’ revisit intention (RI) while risk perception and rescue and relief memory have a negative influence on the RI.

The study provides timely insights and implications to the Ukrainian tourism industry, particularly educational tourism business and medical institutions under the present turmoil, which can also act as blueprint research for destinations with a similar unstable political background.

The primary value of this research work is that it provides an understanding of the intention of medical students (educational tourists) towards revisiting the war-hit destination of Ukraine.

One of the concepts most commonly evoked in order to characterize and explain the zig-zag trajectory of political dynamics in the Islamic Republic of Iran has been the “middle class.” Yet there is no scholarly consensus on a fundamental approach to identification and measurement of the middle class. Rather, the category of the middle class is both a category of analysis – long debated within social theory – as well as a category of practice – routinely deployed in political behavior and social distinction. In order to better conceptualize and understand the formation and role of Iran's middle classes in the country's sociopolitical dynamics, theories of class formation in the global South should be rearticulated away from a reified notion of the middle class as a transhistorical subject. To do so, this chapter is divided into four sections. First, internal debates over the role of Iran's middle classes in the country's recent political history are assessed and data from the 2016 Iran Social Survey is used to test a long-standing demographic assumption on the class dynamics of electoral behavior. Second, the tradition of theorizing the social power of middle classes is reassessed, drawing on the growing scholarly attention to the heterogenous origins and differentiated internal composition of middle classes across the global South. Third, a typology is proposed of four middle classes across the twentieth century shaped by varying state attempts at “catch-up” development. These types are then applied in a revisionist telling of the making and unmaking of middle classes in postrevolutionary Iran. Finally, implications of this framework beyond Iran are sketched out for global waves of protest in the twenty-first century.

This paper aims to identify external factors that are critical to the success of estate surveying business in Lagos State, Nigeria.

Primary data were collected with the aid of questionnaires from estate surveying firms in the study area. Using a sampling interval computed as 1.93-2, 186 firms were selected from the 359 estate surveying firms based in the study area. The sampling interval required that, after the first selection, every subsequent second estate firm in the group (List) was selected for the survey. Data collected were analysed with the aid of criticality assessment index method such as the Relative Criticality Index and Criterion Criticality Score.

The result showed that it was critical for an estate surveying to interdepend with surrounding businesses and maintain good corporate social responsibility for it to succeed. Also, good social relations of the practitioners with the society was found to be an external factor critical to success. In addition, the study found the need to use the advantage of ICT for real estate marketing as an external technological factor for success. It was also found that the economic situation of the immediate locality of the firm and the economic buoyancy of the nation at large influenced both the planning for and the execution of real estate activities of the firm.

Limiting the findings of the study to external factors alone could subject the findings of the study to bias. Further research targeted at identifying internal factors will provide a balanced view.

The study will serve as useful tools for existing and upcoming real estate practitioners to chart a performance course for their businesses. It will help estate surveyors to understand what to place more emphasis on if they will succeed in business.

The findings from this study will provide the estate surveyors and valuers and the professional body with data on things that are critical to their success in business and enhance the practice of real estate management.

Multinational enterprises (MNEs) are increasingly seeking to demonstrate their commitment to sustainability and inclusiveness within the societies they operate in, often by highlighting the amount of tax they pay. The author proposes to summarize channels through which tax impacts the achievement of sustainable development goals (SDGs) and analyze them in relation to a single goal, SDG 10 (reduced inequalities) in a single region (the Central and Eastern Europe, CEE). The impact of tax is often ambivalent, but above all it is hard to quantify as there are many stakeholders involved and corporations still tend to disguise their internal information. The author analyzes MNEs’ operations in the CEE region to better understand how reporting standards influence the achievement of SDG 10, focusing on country-by-country reporting (CbCR) and non-financial reporting of European banks and other corporations who publish CbCR on a voluntary basis. The authors perform a quantitative analysis of CbCR data and a qualitative investigation of 201 non-financial reports by 30 MNEs. From the theoretical viewpoint, this research may help to construct a framework to evaluate the tax impact of a given company. Given that, this chapter also outlines why and how it can be beneficial for MNEs to publish voluntary reports it can also serve to motivate increased voluntary participation of MNEs in the transition to sustainability.

The use of volunteers is one of the approaches to capacity building, preparedness and the response of the health system in disasters. Appropriate management of volunteers during disasters and emergencies is essential. This study aimed to explain the challenges of volunteer management in the Pandemic COVID-19 in Iran.

Qualitative research was conducted using the content analysis based on the Graneheim method. The participants' selection was done based on purposeful sampling and theoretical sampling until data saturation. Direct field observation and 26 interviews were applied to collect data.

Four categories and 15 sub-categories emerged to describe the challenges of volunteer management during the COVID-19 crisis including policymaking barriers (including legal barriers, insurance and support coverage and risk governance), managerial barriers (including planning, coordinating and organizing, training and awareness, command and leadership and information management and documentation), socio-cultural barriers (personal safety attitude and culture, attitudes and expectations of the community and perspectives on volunteers) and executive-operational barriers (monitoring and evaluation, cost and needs assessment).

It is essential to increase managers', officials' and volunteers' perceptions of COVID19 risk through education and information. Preparing a database for volunteers' information, including non-governmental organization and governmental organization volunteers, planning for needs assessment, establishing a mechanism for recruiting volunteers and using their capacities and appropriate organizing, tracking and monitoring of volunteers can be among effective strategies.

In emergency services, maximizing population coverage with the lowest cost at the peak of the demand is important. In addition, due to the nature of services in emergency centers, including hospitals, the number of servers and beds is actually considered as the capacity of the system. Hence, the purpose of this paper is to propose a multi-objective maximal covering facility location model for emergency service centers within an M _(t)/M/m/m queuing system considering different levels of service and periodic demand rate.

The process of serving patients is modeled according to queuing theory and mathematical programming. To cope with multi-objectiveness of the proposed model, an augmented ε-constraint method has been used within GAMS software. Since the computational time ascends exponentially as the problem size increases, the GAMS software is not able to solve large-scale problems. Thus, a NSGA-II algorithm has been proposed to solve this category of problems and results have been compared with GAMS through random generated sample problems. In addition, the applicability of the proposed model in real situations has been examined within a case study in Iran.

Results obtained from the random generated sample problems illustrated while both the GAMS software and NSGA-II almost share the same quality of solution, the CPU execution time of the proposed NSGA-II algorithm is lower than GAMS significantly. Furthermore, the results of solving the model for case study approve that the model is able to determine the location of the required facilities and allocate demand areas to them appropriately.

In the most of previous works on emergency services, maximal coverage with the minimum cost were the main objectives. Hereby, it seems that minimizing the number of waiting patients for receiving services have been neglected. To the best of the authors’ knowledge, it is the first time that a maximal covering problem is formulated within an M _(t)/M/m/m queuing system. This novel formulation will lead to more satisfaction for injured people by minimizing the average number of injured people who are waiting in the queue for receiving services.