Two kinds of solar thermal power generation systems (trough and tower) are selected as the research objects. The life cycle assessment (LCA) method is used to make a systematic and comprehensive environmental impact assessment on the trough and tower solar thermal power generation. This paper mainly analyzes the three stages of materials, production and transportation of two kinds of solar thermal power generation, calculates the unit energy consumption and environmental impact of the three stages respectively, and compares the analysis results of the two systems. At the same time, Rankine cycle is used to compare the thermal efficiency of the two systems.
In this study, the authors propose a method that combines CNN and LSTM networks to recognize facial expressions. To handle illumination changes and preserve edge information in the image, the method uses two different preprocessing techniques. The preprocessed image is then fed into two independent CNN layers for feature extraction. The extracted features are then fused with an LSTM layer to capture the temporal dynamics of facial expressions. To evaluate the method's performance, the authors use the FER2013 dataset, which contains over 35,000 facial images with seven different expressions. To ensure a balanced distribution of the expressions in the training and testing sets, a mixing matrix is generated. The models in FER on the FER2013 dataset with an accuracy of 73.72%. The use of Focal loss, a variant of cross-entropy loss, improves the model's performance, especially in handling class imbalance. Overall, the proposed method demonstrates strong generalization ability and robustness to variations in illumination and facial expressions. It has the potential to be applied in various real-world applications such as emotion recognition in virtual assistants, driver monitoring systems, and mental health diagnosis.
Nanotransformations of a blanket at the fair dimensional combined processing with imposing of electric field the tool in the form of untied metal granules are considered. An object of researches are the figurine details applied in aviation, the missile and space equipment and in the oil and gas industry: driving wheels and a flowing part of cases of turbo-pump units, screws, krylchatka where there are sites of variable curvature with limited access of the tool in a processing zone.It is shown that the combination in the combined process of two-component technological environments of current carrying granules and the electroconductive liquid environment given with a high speed to a processing zone allows to receive the required quality of a blanket; action of electric field from a source with the increased tension allows to create at fair dimensional processingthe required peening from blows of firm granules. It gives the chance to raise a resource and durability of responsible knots of the aerospace equipment and oil and gas equipment, to expand the field of use of the combined processing with untied granules on a detailwith the sitesnot available to processing by a profile electrode.
Blockchain technology is poised to significantly transform the corporate world, heralding a new era of innovation and efficiency. Over the past few years, its impact has been noted by leaders, academics, and government representatives around the globe this growing interest underscores businesses’ need to evolve and reconsider traditional operational models. To remain competitive, organizations must embrace this change. Before introducing such ground-breaking technology, it is crucial to assess the motivations of primary stakeholders concerning its implementation. This study looks into what influences the use of Blockchain technology in the oil and gas sector, primarily using a quantitative survey of Iraqi oil and gas companies. A questionnaire was distributed among 250 top-level managers, senior executives, project managers, and IT managers for analyzing the data, the study employs the Structural Equation Modelling-Partial Least Squares (SEM-PLS) technique, with Smart PLS for data processing. The findings suggest that the intention to utilise blockchain technology is influenced by one’s attitude towards it. Competitive pressure (environmental factors), functional benefit, and privacy/security (technological factors) significantly affect blockchain adoption intention. Nevertheless, there was no discernible correlation between regulatory backing and the desire to use Blockchain. Additionally, cost concern and perceived risk (organizational factors) two factors contribute negatively to the perception of blockchain technology. Besides the direct relationship, the findings revealed that attitude toward blockchain technology mediate the relationship between cost concern, perceived risk, and intention to adopt Blockchain. Built upon the Technology-Organization-Environment (TOE) model and the Theory of Reasoned Action, this research offers a comprehensive framework for investigating the intention to adopt blockchain technology. The results enhance both theoretical understanding and practical implementation by providing valuable insights into the emerging area of blockchain adoption intentions.
The research aims to map environmental protection strategies and the related control tools and to identify the links among companies with the largest number of employees and sites in Hungary. The research questions were answered using a questionnaire survey method. The authors used cluster analysis to classify the 205 company strategies into the identified strategy clusters: Leaders, Awakeners, and Laggards. Then, the examined 21 environmental management control tools in the sample were divided into four groups: strategic, administrative, methodological and economic. Economic and strategic methods were the most common in the sample. The authors used cross-tabulation analysis to examine whether there is a statistically proven relationship between belonging to environmental strategy clusters and specific control tools. The analysis showed significant but weak to moderate relationships. According to Cramer's V and the contingency coefficient, the closest relationship between the tested environmental management control tools and membership in environmental strategy clusters is shown by evaluating investments, assessing the economic viability of environmental strategies, and running an environmental training program for employees. In case of the robust lambda indicator, a significant relationship was found by examining the economics of environmental strategies and identifying environmental success factors and eco-balances. It can be concluded that the companies under examination follow a set of environmental goals, which they have incorporated into their strategic objectives. They use the available environmental management control toolbox to develop their strategies and to monitor their implementation to varying degrees.
In recent years, an ‘international’ unanimity has been reached as to the importance of collective collaboration to avoid the negative effects of climate change. This requires rethinking the old or traditional development model based on economic growth as the exclusive indicator of wealth. Thus, humanity has an urgent need to adopt a new, more humane and fairer economic model that constitutes an alternative to the models of exponential growth that have dominated in the last two centuries. To do so, humanity is looking to the Degrowth model as a potential concept that aims to reduce wealth from pollutants, seeks more justice (as equity), and the improvement of the capabilities of those who are poor and disadvantaged (in the sense of Amartya Sen and Martha Nussbaum). The purpose of this article is to question this model and whether it actually does improve environmental quality. Additionally, if the response is positive, another question arises: How to finance degrowth especially when we seek other less polluting energy sources whose costs seem to be very high?
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