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Modern unmanned air vehicles (UAVs) are usually equipped with rotors connected to electric motors that enable them to hover and fly in all directions. The purpose of the paper is to design optimal composite rotor blades for such small UAVs and investigate their aerodynamic performances both computationally and experimentally.

Artificial intelligence method (genetic algorithm) is used to optimize the blade airfoil described by six input parameters. Furthermore, different computational methods, e.g. vortex methods and computational fluid dynamics, blade element momentum theory and finite element method, are used to predict the aerodynamic performances of the optimized airfoil and complete rotor as well the structural behaviour of the blade, respectively. Finally, composite blade is manufactured and the rotor performance is also determined experimentally by thrust and torque measurements.

Complete process of blade design (including geometry definition and optimization, estimation of aerodynamic performances, structural analysis and blade manufacturing) is conducted and explained in detail. The correspondence between computed and measured thrust and torque curves of the optimal rotor is satisfactory (differences mostly remain below 15%), which validates and justifies the used design approach formulated specifically for low-cost, small-scale propeller blades. Furthermore, the proposed techniques can easily be applied to any kind of rotating lifting surfaces including helicopter or wind turbine blades.

Blade design methodology is simplified, shortened and made more flexible thus enabling the fast and economic production of propeller blades optimized for specific working conditions.

This chapter aims to improve the mechanisms of economic integration between Russia and Cuba. The methodology used by the author in this chapter is mainly composed of the method of historical-comparative, inductive, and analytical-synthetic analysis. The author used the existing information on the internet and other analyzed references. Additionally, the author qualitatively analyzed the opinions of various experts and drew conclusions. Regional integration is examined conceptually as a basis for a better understanding of integration processes. The research provides historical data after including Cuba in the Council for Mutual Economic Assistance (CMEA), considering this structure as the first one with characteristics of an economic integration structure. Next, the author considered the post-Soviet stage until the present. Statistical data according to the Observatory of Economic Complexity (OEC) summary are provided. These data correspond to the periods from 2018 to 2021 and show the statistics of exports, imports, and other important indicators between the two countries. Based on the analysis, it is necessary to update the integration mechanisms to reduce tariff rates, promote free trade between the two countries, and increase the participation of Russian companies in the Mariel Special Development Zone (ZED Mariel), Havana, Cuba.

The purpose of this paper is to develop a new perspective on urban tourist motivations by applying the analytic hierarchy process (AHP) model to help to understand how tourists make decisions about which destinations to visit.

This study was based on 30 one-hour-long structured interviews with visitors to Ljubljana, the capital city of Slovenia. Respondents were asked to express their preferences between different pull-factor motives for their visit, using Saaty’s scale, and further qualitative data were collected to examine these preferences in more depth.

The results of this study indicate that the most relevant criteria and thus predominant factors in motivation for visits to Ljubljana are the Cultural and Nightlife pull factors, while religious and business motives are the lowest ranked factors. The paper argues that the results show the value of applying the AHP model to understand the role of pull factors in urban tourism destination choice.

As a single-destination case study, it is important that the findings of this research are evaluated against similar studies in other cities. A limitation of this research is the fact that sub motives within major groups of pull-factor motives have not been explored in this study and this should be the subject of future, more detailed research.

This research shows the value of applying an under-used methodology to understand urban tourist motivations and knowledge gained through applying this method will be of value to destination marketing organisations as well as to researchers conducting future studies.

Understanding the multifaceted images of tourism destinations is critical for effective destination marketing and management strategies. Traditional approaches, including conceptualization of destination images or analysis of their antecedents and consequences, are commonly used. This study aims to advocate the inclusion of visitors’ latent profiles based on cognitive images to enrich the evaluation and formulation of destination marketing and management strategies.

The analysis focuses on Serbia, an emerging destination, that attracts an increasing number of first-time, repeat and prospective visitors. Exploratory factor analysis and confirmatory factor analysis were used to test the potential dimensions (tangible and intangible cultural destination; infrastructural and accessible destination; active, nature and family destination; sensory and hospitable destination; and welcoming, value for money (VFM) and safe destination) of the cognitive destination image factors scale while subtypes (profiles) were obtained using latent profile analysis (LPA).

The cognitive image component encompasses the perceived attributes of a destination, whether derived from direct experience or acquired through other means. The study identified the following profiles: conventional destination; sensory and hospitable destination; welcoming, VFM and safe destination; secure and active family destination and accessible cultural destination, which are presented individually with their sociodemographic assets.

The main contribution of the paper is the application of a novel method (LPA) for profiling visitor segments based on cognitive destination image. From a theoretical perspective, this research contributes to the extant body of literature pertaining to the destination image, thereby facilitating the identification of discrete latent visitor segments and elucidating noteworthy differences among them concerning a cognitive image.

The purpose of this paper is to identify the benefits of an approach in which document management systems (DMSs) are based on a formal and explicit document model, primarily in terms of facilitating domain-specific customization.

Within this paper, a generic document model is proposed. The model consists of two layers. A general purpose layer, which represents common features of the documents, and a domain-specific layer, modeling properties particular to application domain. The general purpose layer is based on ISO 82045, providing high degree of interoperability with other systems developed with respect to this set of standard.

Splitting document model into the layers enables DMSs to be tailored for each particular domain of application, depending on the general purpose layer. The existence of domain-specific layer allows documents to be interpreted differently in different domains of application.

In order to enable customization of DMS for a particular domain, the implementation of domain-specific document layer is required. Also, the proposed model does not explicitly deal with document dynamics.

The proposed document ontology is general enough to provide the representation of documents not depending on a specific scope of application, yet flexible enough to enable extensions through which domain-specific document features can be expressed. The separation of document model enables development of core DMS offering services relying explicitly on the general purpose layer on one hand, as well as domain-specific customization of DMS on the other.

Discusses the 6th ITCRR, its breadth of textile and clothing research activity, plus the encouragement given to workers in this field and its related areas. States that, within the newer research areas under the microscope of the community involved, technical textiles focuses on new, ‘smart’ garments and the initiatives in this field in both the UK and the international community at large. Covers this subject at length.

This study examines the returns from education for three distinct groups: always employees, dabblers in self-employment and sustained self-employed individuals. We aim to understand how educational attainment translates into earnings across these employment types in the UK.

Using data from the British Household Panel Survey (BHPS) and Understanding Society: The UK Household Longitudinal Study (UKHLS), we employ a random effects (RE) model to account for unobserved individual characteristics and the Heckman selection model to address self-selection bias, ensuring accurate estimates of educational returns.

Our findings indicate that sustained self-employed individuals benefit more from education compared to dabblers and, in certain cases, traditional employees. Dabblers with postgraduate education report higher returns than always employees, but those with lower educational levels experience disadvantages due to their intermittent labour market engagement.

This study introduces new evidence on the heterogeneity of educational returns for self-employed individuals in the UK, providing a novel comparative analysis of different employment types and highlighting the unique challenges and outcomes related to educational attainment and earnings.