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Abstract: The aim of this study was to conduct a systematic review of the school-based exercise programs for promoting cardiorespiratory fitness in overweight and obese children aged 6 to 10. Electronic databases (Web of Science and PubMed) were used as searching tools for collecting adequate studies published in the past 20 years. A total of 13 studies met the criteria for inclusion in this review, with a total of 2810 participants, both male and female. According to the results of this systematic review, overweight and obese children aged 6 to 10 who underwent certain interventions had their CRF improved. Furthermore, evidence suggested that interventions carried out during a longer period of time suggested led to greater improvement of cardiorespiratory fitness than a shorter one, but the level of cardiorespiratory fitness gradually decreases after the intervention.
Keywords: physical activity, physical fitness, motor competence, children, health, monitoring and promoting, sport, sedentary behavior, obesity, well-being
Published in DKUM: 07.04.2025; Views: 0; Downloads: 3
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Abstract: This article presents a cloud-based system for the on-line monitoring of tool conditions in end milling. The novelty of this research is the developed system that connects the IoT (Internet of Things) platform for the monitoring of tool conditions in the cloud to the machine tool and optical system for the detection of cutting chip size. The optical system takes care of the acquisition and transfer of signals regarding chip size to the IoT application, where they are used as an indicator for the determination of tool conditions. In addition, the novelty of the presented approach is in the artificial intelligence integrated into the platform, which monitors a tool’s condition through identification of the current cutting force trend and protects the tool against excessive loading by correcting process parameters. The practical significance of the research is that it is a new system for fast tool condition monitoring, which ensures savings, reduces investment costs due to the use of a more cost-effective sensor, improves machining efficiency and allows remote process monitoring on mobile devices. A machining test was performed to verify the feasibility of the monitoring system. The results show that the developed system with an ANN (artificial neural network) for the recognition of cutting force patterns successfully detects tool damage and stops the process within 35 ms. This article reports a classification accuracy of 85.3% using an ANN with no error in the identification of tool breakage, which verifies the effectiveness and practicality of the approach.
Keywords: machining, end milling, tool condition monitoring, chip size detection, cutting force trend identification, visual sensor monitoring, cloud manufacturing technologies
Published in DKUM: 26.03.2025; Views: 0; Downloads: 3
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Abstract: In the heavy industry, the value of cargo transported by rail is very high. Due to high value, poor security and volume of rail transport, the theft cases are often. The main problem of securing rail transport is predicting the location of a high probability of risk. Because of this,the aim of the presented research was to predict the highest probability of rail cargo theft for areas. It is important to prevent theft cases by better securing the railway lines. To solve that problem the authors' model was developed. The model uses information about past transport cases for the learning process of Artificial Neural Networks (ANN) and Machine Learning (ML).The ANN predicted the probability for 94.7% of the cases of theft and the Machine Learning identified 100% of the cases. This method can be used to develop a support system for securing the rail infrastructure.
Keywords: rail transport security, supply chain disruption, drones, security support systems, cargo theft, predicting, logistics, artificial neural network, drone monitoring, machine learning
Published in DKUM: 28.01.2025; Views: 0; Downloads: 4
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Abstract: Auditing, as a form of control (for example over financial management or compliance), has traditionally relied on manual processes that are time-consuming, labor-intensive and prone to human error. With the advent of robotic process automation (RPA), there has been a paradigm shift from manual to automated processes in audit processes as well. Automation dates back to the 1990s, which led to the creation of robotic process automation (RPA) tools. Today we are approaching or we are in the fourth industrial revolution, the era of universal automation. RPA refers to the use of software robots (or "bots") to automate repetitive rule-based activities previously performed by humans. As companies try to keep up with rapid technological improvements, incorporating RPA into audit processes provides a number of benefits that can radically change auditing. RPA has emerged as a transformative technology in auditing, changing established approaches with its ability to improve productivity, accuracy and compliance. One of the most significant benefits of RPA in auditing is its ability to increase efficiency. Traditional audit procedures can sometimes be time-consuming and labor-intensive, as auditors must manually collect and evaluate data from multiple sources. RPA accelerates these activities by automating common tasks such as data entry, coordination and report generation. For example, an RPA robot can be trained to collect financial data from multiple sources (eg from multiple companies) and verify its accuracy using established criteria. This not only reduces the time required to perform audits, but also eliminates the possibility of human error. In addition to efficiency, there is another key advantage: accuracy. RPA enables auditors to take proactive measures to reduce risk, thereby protecting the financial integrity and reputation of the organization. By automating mundane and repetitive activities, RPA allows auditors to focus on more strategic activities that deliver value to the business. Auditors (in the broadest sense) can spend more time evaluating data models, finding areas for improvement, and making strategic suggestions to management. The aim of this bachelor's degree thesis is to explore and demonstrate the application of RPA in audit procedures, highlighting its benefits such as increased productivity, improved quality of rapid processing of large databases, improved risk management, and cost savings. The thesis also discusses the challenges and considerations related to the implementation of RPA in audit practices. The history of RPA is detailed, revealing its use by different industries and their goals. The thesis defines all types of RPA tools and their advantages and weaknesses. It also distinguishes between artificial intelligence (AI) and RPA, as it can confuse the activities of RPA tools with AI.
Keywords: robotic process automation, RPA, monitoring, analytics, security, productivity, auditing, audit process.
Published in DKUM: 09.09.2024; Views: 25; Downloads: 33
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Abstract: Background Decarbonisation of the European economy is one of the main strategic goals of energy transition in the European Union (EU), which aims to become a leader in this process by 2050 and to include other European countries making thus the European continent the first carbon neutral region in the world. Although decarbonisation is an important goal of the EU, the models for monitoring the progress of this process have not yet been clearly defined, and views on the social, economic, and security implications in terms of prioritising decarbonisation are conflicting. The main objective of this paper is to determine the methodological correctness of the existing method of decarbonisation monitoring, to develop a new monitoring model indicating the differences in the EU and European countries that are non-EU and to point out the underlying social, economic and security implications that must certainly find their place in the decision-making process in this field. Results The main results showed that there is no clearly defined model for monitoring the success of decarbonisation, while the indicators that are commonly used for this purpose make a model that, as the analysis shows—is methodologically incorrect. In the case of EU countries, the following indicators proved to be the most reliable: consumption-based CO2 and share in global CO2. For non-EU countries, the best monitoring indicators are CO2 per unit of GDP, consumption-based CO2, and renewable energy consumption. These indicators can explain 99% of the variance in decarbonisation success. Conclusions The basic conclusion of the paper is that even before the implementation, the decarbonisation monitoring model should be defined and methodologically tested, and the use of a single model for all EU countries or for all countries is not recommended. It is proposed to simplify the monitoring model, with an emphasis on monitoring of consumption-based CO2, which proved to be the most efficient in all sampled countries. The current method of monitoring is based exclusively on environmentally related indicators while ignoring the fact that decarbonisation is associated with almost all aspects of development. The additional social, economic and security aspects need to be developed and included in the further monitoring process.
Keywords: decarbonisation, Eastern European economies, monitoring, social implications, security aspects
Published in DKUM: 02.07.2024; Views: 144; Downloads: 16
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