Method for Assessing the Development of Underground Hard Coal Mines on a Regional Basis: The Concept of Measurement and Research Results

Research on Early Warning for Gas Risks at a Working Face Based on Association Rule Mining

In the process of gas prediction and early warning, outliers in the data series are often discarded. There is also a likelihood of missing key information in the analysis process. To this end, this paper proposes an early warning model of coal face gas multifactor coupling relationship analysis. The model contains the k-means algorithm based on initial cluster center optimization and an Apriori algorithm based on weight optimization. Optimizing the initial cluster center of all data is achieved using the cluster center of the preorder data subset, so as to optimize the k-means algorithm. The optimized algorithm is used to filter out the outliers in the collected data set to obtain the data set of outliers. Then, the Apriori algorithm is optimized so that it can identify more important information that appears less frequently in the events. It is also used to mine and analyze the association rules of abnormal values and obtain interesting association rule events among the gas outliers in different dimensions. Finally, four warning levels of gas risk are set according to different confidence intervals, the truth and reliable warning results are obtained. By mining association rules between abnormal data in different dimensions, the validity and effectiveness of the gas early warning model proposed in this paper are verified. Realizing the classification of early warning of gas risks has important practical significance for improving the safety of coal mines.

Identification of Energy Efficiency Trends in the Context of the Development of Industry 4.0 Using the Polish Steel Sector as an Example

The steel sector is crucial for the national economy of Poland and the global economy. In response to the challenges of the global steel market and the need to increase the sector’s competitiveness, a number of actions have been taken to increase the energy efficiency of steel production. Based on the synthesis of the literature and our own research, we describe the issues related to energy efficiency and the Industry 4.0 concept. The main aim of this paper is to identify energy efficiency trends in enterprises, especially those that focus on increasing the energy efficiency of production processes, and to make recommendations for investment policy for the Polish steel sector in the era of Industry 4.0. To achieve our goals and answer the research question, we used data from 2000–2019 for the Polish steel industry. The calculations and models in this paper were made by using Gretl software. Using direct research, an econometric model was built that verified the hypothesis regarding the relationship between investment in new technologies and the energy efficiency of steel production. Future investment policies should take the implementation of Industry 4.0 tools in the steel sector into account, which, according to the authors, will measurably improve energy efficiency.

The Level of Maturity of Quality Management Systems in Poland—Results of Empirical Research

This paper examines the problem of measuring the maturity of quality management systems. The main scope of the study is to measure the level of maturity of quality management systems in organizations with an implemented quality management system compliant with the requirements of ISO 9001 in Poland; however, this paper also investigates which factors influence the level of maturity. An analysis of the maturity level of the quality management system in the surveyed organizations showed that the highest level of maturity occurs in those areas and activities that directly result from the requirements of the ISO 9001 standard and direct market pressure, and this level of maturity must be implemented. This can be included in case areas such as customer orientation, process approach, or evidence-based decision-making. However, a lower level of maturity is observed in the case of “soft” aspects of quality management related to leadership and human resource management. The problems are also related to the implementation of corporate social responsibility (CSR). In this respect, the surveyed organizations show numerous shortcomings which lead to low assessments of their level of maturity, for example, in ensuring openness and ethical behavior in contact with the public. The following hypothesis was formulated for the research objective: H1—control variables, such as the size of the organization (H1a), time of existence of the enterprise (H1b), business profile (H1c), market position (H1d), financial condition (H1e), and ratio of management to the normalization processes (H1f), affect the level of maturity of an enterprise’s quality management system.

Comparative Analysis of the Impact of the Business Incubator Center on the Economic Sustainable Development of Regions in USA and Poland

The innovativeness boosted by incubator centers has an important role in the sustainable development of the country and its regions. The paper describes a comparative analysis of the effectiveness of the business incubator center on the economic growth of a region. The goal of the paper is a comparison between two business incubators, CAN-BE in Hazleton, PA USA and Technopark in Gliwice, Poland. A number of indicators were used to measure economic growth. These selected indicators reflected social, organizational, technical, and financial aspects of economic growth.