The aim of the proposed study is to present the partial results of a research study on the organizational climate in vocational schools as perceived by teachers. Special attention is paid to the applied leadership style by school leaders, and the existence of associations between school leaders’ and teachers’ behaviour in schools. Organizational climate was measured by the standardized OCDQ-RS adapted to the conditions of the Slovak educational environment on the sample of 474 vocational schoolteachers. The scale measures five dimensions: Supportive principal behaviour; Directive principal behaviour; Engaged teacher behaviour; Frustrated teacher behaviour; and Intimate teacher behaviour, allowing for calculation of the Index of school climate openness, which is an indicator of the quality of the organizational climate. The obtained results confirmed the existence of associations between teacher and principal behaviour and school climate openness. It can be assumed that the applied leadership style in an institution can affect the quality of interpersonal relationships and teacher behaviour both in positive and negative directions. Therefore, it is important to pay attention to building favourable organizational climate in schools, which represents a challenge for school leaders and educational systems that should provide school leaders with sufficient learning opportunities in the field of school leadership.

Fetal health holds paramount importance in prenatal care and obstetrics, as it directly impacts the wellbeing of mother and fetus. Monitoring fetal health through pregnancy is crucial for identifying and addressing potential risks and complications that may arise. Early detection of abnormalities and deviations in fetal health can facilitate timely interventions to mitigate risks and improve outcomes for the mother and fetus. Monitoring fetal health also provides valuable insights into the effectiveness of prenatal interventions and treatments. For fetal health classification, this research work makes use of cardiotocography (CTG) data containing 21 features including fetal growth, development, and physiological parameters such as heart rate and movement patterns with three target classes “normal,” “suspect,” and “pathological.” The proposed methodology makes use of data upsampled using the synthetic minority oversampling technique (SMOTE) to handle the class imbalance problem that is very crucial in medical diagnosing with a light gradient boosting machine. The results show that the proposed model gives 0.9989 accuracy, 0.9988 area under the curve, 0.9832 recall, 0.9834 precision, 0.9832 F1 score, 0.9748 Kappa score, and 0.9749 Matthews correlation coefficient value on the test dataset. The performance of the proposed model is compared with other machine learning models to show the dominance of the proposed model. The proposed model's significance is further evaluated using 10-fold cross-validation and comparing the proposed model with other state-of-the-art models.

Artificial intelligence (AI) transforms multiple businesses, including medical research, where AI-driven developments bring significant advantages. The application of machine learning algorithms enables medical researchers to examine large amounts of data accurately, which leads to the development of precise and effective treatment approaches. Lung cancer leads the list of critical healthcare issues because it remains the world’s most lethal form of cancer thus demanding innovative diagnostic tools for faster and accurate identification. The proposed study introduces an innovative method called CTGAN-RF which uses conditional tabular generative adversarial networks (CTGAN) and random forest (RF) classifier to detect lung cancer through synthetic data generation. The proposed model demonstrated superior performance by achieving a 0.9893 score of accuracy and 0.99 value for precision, F1 score, and recall. Extensive experimental evaluation for this method included testing nine classification algorithms. The implementation of different classifiers employed data balancing methods including SMOTE and borderline-SMOTE along with SMOTE ENN and unbalanced data configurations. Comparative analysis showed that CTGAN-RF consistently performed significantly better than traditional classifiers in dealing with class imbalance and improving prediction accuracy. After testing with fivefold cross-validation, the reliability of the model was further validated. In comparison to cutting-edge approaches for lung cancer diagnosis, the proposed methodology outperformed in terms of classification metrics. This in-depth evaluation of synthetic data augmentation with machine learning in lung cancer detection has helped in the development of personalized treatment strategies in the fight against such a life-threatening disease.

Instead of aiming to achieve as many members as possible, it is important to focus on retaining customers, which is achieved with the support of loyalty programmes. As the tourism and hospital industries have become the fastest growing sectors in the world, hotels have realised the potential to focus on their loyal customers. A qualitative approach was adopted to explore the attractiveness of loyalty programmes to Chinese consumers and the challenges of such programmes in the hospitality industry. The aim of this paper is to identify which aspects of a loyalty programme in the hospitality industry are perceived as attractive to Chinese customers. This qualitative research highlights the perspective of industry leaders such as general managers and executives working in the club lounges of five-star hotels in Suzhou as well as loyalty programme consultants with a focus on China. The qualitative research findings are aimed at supporting hotels in China and loyalty programmes with a focus on Chinese consumers in the hospitality industry in order to receive more knowledge and to explore new strategies on how to retain and satisfy Chinese programme members.

For the interpretation of digital entrepreneurship, the context in which the entrepreneurial process takes place plays an important role. The context emphasizes that to analyze the entrepreneurial process, it is no longer sufficient to analyze only the entrepreneurial actions, but also the environment in which the entrepreneurial process takes place. The aim of this paper is to analyze the part of the context in which the entrepreneurial process takes place in the Republic of Serbia, Montenegro, Bosnia and Herzegovina and Hungary. Following the methodology of The European Index of Digital Entrepreneurship Systems (EIDES), the paper analyzes the system framework conditions, in the scale-up phase of the enterprise life cycle, in the digital dimension. The aim of this paper is a comparative analysis of three countries in transition with one country belonging to the European Union. After identifying the most developed factors, as well as the most underdeveloped factors, the paper discusses the conditions that influenced the results achieved in the four previously listed countries and why their improvement is important.

The article aims to find a link between employee training and satisfaction with educational activities and marketing efforts of the organization. Qualification growth of employees is closely connected to the organization’s success. Since obstacles in education hinder achieving desirable results, they need to be identified and overcome. Theoretical background and knowledge was confronted with data collected in primary research. Interviewing was used as the method and questionnaire as the instrument. Data were statistically analysed and results of chi-square were calculated in software Statgraphics. Testing the relationship between barriers in training involvement of employees and their socio-economic characteristics proved that, gender, age, education level, sector of economy, length of current employment, and income satisfaction are independent. The only relevant dependence is apparent in case of fear of failure which is a barrier indicated for low income people. This article clarifies the state of satisfaction with education possibilities of employees through identifying of the main barriers and concludes consequences for sustainable growth of organization.