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The purpose of this research paper is to recover the autonomous flight performance of a mini unmanned aerial vehicle (UAV) via stochastically optimizing the wing over certain parameters (i.e. wing taper ratio and wing aspect ratio) while there are lower and upper constraints on these redesign parameters.

A mini UAV is produced in the Iskenderun Technical University (ISTE) Unmanned Aerial Vehicle Laboratory. Its complete wing can vary passively before the flight with respect to the result of the stochastic redesign of the wing while maximizing autonomous flight performance. Flight control system (FCS) parameters (i.e. gains of longitudinal and lateral proportional-integral-derivative controllers) and wing redesign parameters mentioned before are simultaneously designed to maximize autonomous flight performance index using a certain stochastic optimization strategy named as simultaneous perturbation stochastic approximation (SPSA). Found results are used while composing UAV flight simulations.

Using stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV over previously mentioned wing parameters and FCS, it obtained a maximum UAV autonomous flight performance.

Permission of the directorate general of civil aviation in the Republic of Türkiye is essential for real-time UAV autonomous flights.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach is very useful for improving any mini UAV autonomous flight performance cost index.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach succeeds confidence, highly improved autonomous flight performance cost index and easy service demands of mini UAV operators.

Creating a new approach to recover autonomous flight performance cost index (e.g. satisfying less settling time and less rise time, less overshoot during flight trajectory tracking) of a mini UAV and composing a novel procedure performing simultaneous mini UAV having passively morphing wing over certain parameters while there are upper and lower constraints and FCS design idea.

The purpose of the present study was to investigate the interrelationships among the dimensions of sport event experience, event satisfaction and event behavioral intentions.

The sample was comprised of 186 individuals who actively participated in a mass participation sport event. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the relationships among the latent constructs.

The results indicated that the dimensions of sport event experience predicted 55% of the variance of event satisfaction and 63% of the variance of event behavioral intentions was predicted by sport event experience dimensions and event satisfaction. Specifically, the sensory, affective and relational dimensions of experience sought to have a statistically significant and positive association with event satisfaction, while event satisfaction and the relational dimension of experience were found to have a statistically significant and positive correlation with event behavioral intentions. In addition, event satisfaction was found to mediate the relationships between sensory, affective and relational experiences and event behavioral intentions.

The present study is one of the first that explores the relationships among sport event experience’s dimensions, event satisfaction and positive behavioral intentions in the context of sport event participation.

This paper aims to explore the impact of corruption (CP) on income inequality (IN) by considering the size of informal sector (IFS) at different levels of percentiles.

This paper uses a panel quantile regression approach for a sample of 50 developing countries. The study also applies panel co-integration (Kao residual co-integration test) in order to examine the long-run relationship between CP and IN.

This paper using a panel quantile regression approach shows that the high incidence of IFS in an economy marginalizes CP's positive effect because it works as a source of poor peoples' livelihood and skillful individuals. The spread of IFSs in the developing economies may raise earnings among groups and individuals who remain unemployed. Moreover, the results show that CP creates asymmetry in income distribution; fascinatingly, the asymmetric income distribution is high when CP is at higher percentiles.

Due to non-availability of IFS, we restrict our analysis up to 50 developing countries.

CP devastates the effectiveness of institutions over time. Therefore, the government should have to take bold steps to reduce CP in society. Another policy implication of this study is that the government should reduce CP to decrease IN in less developing countries. Moreover, to increase the net base, the authorities need to bring IFS under the umbrella of regulation to avoid inequality in society. In developing economies, a higher part of labor force is related to IFS; therefore, our findings suggest a dire need to reduce labor exploitation in IFS. The policymakers can reduce labor exploitation by reducing the size of IFS, which ultimately reduces IN.

On the basis of the authors’ findings, this paper further suggests that it is mandatory for government to reduce CP in order to reduce IN. Moreover, to reduce IN, one needs to reduce the size of IFS.

This study is unique as it is the first that examined the role of IFS in establishing the effect of CP on IN for developing countries at different percentiles.

The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.

The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.

Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.

The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.

The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.

Female adults diagnosed with myalgia encephalomyelitis (ME) and chronic fatigue syndrome (CFS) often are marginalised because their condition is not fully recognised by medical and health-care systems. The purpose of this small-scale study was to explore the lived experiences of adult females with ME/CFS in England in relation to contributing factors that impact their occupational participation.

A qualitative study design using semi-structured interviews was used with nine female adult participants who were selected using a purposive sampling method. A Thematic Networks tool was used to analyse data.

Four organising themes were identified: impairment-, person-, environment- and society-related factors. Two global themes, invisibility and diagnosis stigma, were identified as the overarching issues that female adults with ME/CFS face in occupational participation.

Many of the issues that contribute to lack of participation by this population are associated with environmental factors which are secondary to their illness.

The purpose of this paper is to analyze the social and functional features of micro-apartment and, based on the findings, to demonstrate the projects of modern micro-apartment designed for one or two people, which are implemented in the experimental design.

Based on the analysis of the study of theoretical scientific works on the research topic and from the standpoint of an interdisciplinary discourse the social and economic prerequisites for the demand for such a dwelling are determined and the categories of citizens for whom a micro-apartment is an advantage are identified. Particular attention is paid to the typological boundaries of the study, the generalization and synthesis of sources which is reflected in identifying the features of the functional zoning of a micro-apartment in connection with the needs of residents and determining modern ways to improve the comfort of living.

At the examples of experimental design of micro-apartment for the city of Almaty we substantiated the expanding the existing typology of residential buildings by adding a new type of urban dwelling – a micro-apartment which occupies a niche between apartment housing for permanent residence and traditional hotels.

The content of the study is devoted to the analysis of a micro-apartment as a new type of modern urban dwelling for a single and small-family population. Urban residents’ interest in economical, affordable small-area dwellings as well as the need to study and design micro format dwellings for the modern urban environment is a topical issue.

This study aims to propose novel edge device-tailored federated learning algorithms of local classifiers (stochastic gradient descent, support vector machines), namely, FL-lSGD and FL-lSVM. These algorithms are designed to address the challenge of large-scale ImageNet classification.

The authors’ FL-lSGD and FL-lSVM trains in a parallel and incremental manner to build an ensemble local classifier on Raspberry Pis without requiring data exchange. The algorithms load small data blocks of the local training subset stored on the Raspberry Pi sequentially to train the local classifiers. The data block is split into k partitions using the k-means algorithm, and models are trained in parallel on each data partition to enable local data classification.

Empirical test results on the ImageNet data set show that the authors’ FL-lSGD and FL-lSVM algorithms with 4 Raspberry Pis (Quad core Cortex-A72, ARM v8, 64-bit SoC @ 1.5GHz, 4GB RAM) are faster than the state-of-the-art LIBLINEAR algorithm run on a PC (Intel(R) Core i7-4790 CPU, 3.6 GHz, 4 cores, 32GB RAM).

Efficiently addressing the challenge of large-scale ImageNet classification, the authors’ novel federated learning algorithms of local classifiers have been tailored to work on the Raspberry Pi. These algorithms can handle 1,281,167 images and 1,000 classes effectively.

Sport events’ contribution to the destinations’ local economy implies in-depth knowledge of the economic benefits generated by non-resident spectators (NRS). Thus, this study aims to answer: What is the profile and shaping factors of the consumption patterns of the several types of NRS in international surf tourism events?

A total of 263 questionnaires applied to the NRS of an international surf event were collected and analysed. The identification of the NRS profile and the predictive factors of their total expenditure were performed through the correlation of factors and multiple linear regression, respectively.

Mostly, the event attracted generation Y NRS, with a high level of education and regular sport practice. The results showed differences among the NRS: the “casuals” included more women than men; the “extensioners” integrated the NRS whose surfing practice is higher; the “event visitors”/”time switchers” mostly integrated the domestic tourism flows; the “casuals” and “extensioners” spent the most at the destination, and those whose intention to recommend/revisit the destination, respectively, was higher; and the shaping factor that most influenced the increase in NRS expenditure was the overnight stay, added by older age, higher education level and foreign origin.

Regardless of the initial motivation that led to the trip to the destination, the results verified that the event’s attributes are capable of contributing to the recommendation/visitation of the destination. Consequently, the study of economic benefits (tangible and intangible) provided by sport events in destinations should be guided by an integrative analysis of NRS.