• Energy Research

The study aims to evaluate the way for creating agile institutions with organizational trust. Besides that, the understanding of the mediating role played by psychological empowerment during COVID-19 pandemic is one of the major objectives of this study. The way psychological empowerment affects the creation of agile organizations is another major aspect that the study investigated. The philosophical stance that the research has adopted is the positivism philosophy. The study was done by collecting and analyzing quantitative data. The approach for the study is deductive whereas the design of the research is descriptive. The study used a survey method for collecting information. Structural equation model was used for analyzing quantitative information. The study was done on 325 samples who are working at the finance sector of Turkey. All the samples have a residence in Turkey. It was identified that the leadership approach of a company has a huge impact on the psychological construction of the samples. Descriptive statistics and t-test for inferential statistics were done by the researchers. There is a strong positive relationship between the centricity of the organization towards the workforce or customer and employee performance. It was identified that the leadership approach helps employees to address and adopt the change in the marketplace. It was also found that an agile organizational structure has more possibilities to modify the processing based on the change in the marketplace. The structural equation model was used to represent the relationship between the variables.

The demographic low, and thus the inevitable aging of the populations of economically developed countries, makes it necessary to extend the working life of citizens. Therefore, an increasing percentage of workers are representatives of the so-called “silver” generation, i.e., people over 50 years of age. The main objective of the study is to characterize the system of values, attitudes to work, and related expectations of professionally active women and men over 50 years of age and to determine whether, and if so, how the hierarchy of values, attitudes to work, and job satisfaction affect the further development of their professional careers. In order to achieve such a goal, a CAVI survey was conducted on a sample of n = 600 respondents. The statistical significance of the differences between the groups was tested with the Mann–Whitney U test. To verify the main hypothesis, ordinal logistic regression models were built. The results of the study were supplemented with elements of descriptive statistics. In the course of the research work, it was confirmed that there are significant differences between the studied men and women in the assessment of traits concerning their value hierarchy, attitudes towards work, and career prospects. Traits such as value hierarchy and attitudes toward work have a significant impact on the career development of both women and men of the “silver” generation, while job satisfaction shows a significant impact on career development only for women.

Artificial neural network models for the task of detection are used in many fields and find various applications. Models of this kind require adequate computational resources and thus require adequate energy expenditure. The increase in the number of parameters, the complexity of architectures, and the need to process large data sets significantly increase energy consumption, which is becoming a key sustainability challenge. Optimization of computing and the development of energy-efficient hardware technologies are essential to reduce the energy footprint of these models. This article examines the effect of the type of model, as well as its parameters, on energy consumption during inference. For this purpose, sensors built into the graphics card were used, and software was developed to measure the energy demand of the graphics card for different architectures of YOLO models (v8, v9, v10), as well as for different batch and model sizes. This study showed that the increase in energy demand is not linearly dependent on batch size. After a certain level of batch size, the energy demand begins to decrease. This dependence does not occur only for n/t size models. Optimum utilization of computing power due to the number of processed images for the studied models occurs at the maximum studied batch size. In addition, tests were conducted on an embedded device.