Streszczenie: Współcześnie funkcjonujące przedsiębiorstwa zmuszone są do działania na rynku globalnym, wynikiem czego jest uczestniczenie w łańcuchach lub sieciach dostaw
The magazine's publications deal with issues related to work safety. Both in the area of occupational health and safety, organization of the workplace (technical aspects) and the environment (environmental factors in working conditions). The publications presented combine legal requirements in the field of work safety with the technical solutions that are designed to meet the minimum requirements. They present and analyze the requirements of technological processes carried out at workplaces. Sociological issues are also carried out in the analyzes, in the scope of training and creating a safety culture within production enterprises. Scope Subject areas, suitable for publication, include the following fields: Health and safety management systems Technological safety The role of the human factor in occupational health and safety management systems Safety of technical facilities operation (safety engineering) Environmental safety management Safety management of products and services Management of occupational risk Economical aspects of occupational health and safety Legal aspects of health and safety at work Safety in material engineering Safety in civil engineering
Abstract COVID-19, mobility, socio-social changes have transferred to the world of social media communication, purchasing activities, the use of services. Corporate social media has been created to support clients in using various services, give them the possibility of easy communication without time and local barriers. Unfortunately, they still very rarely take into account the security and privacy of customers. Considering that the purpose of this article is to investigate the impact of social media on the company’s image, it should be remembered that this image also works for the security and privacy of customer data. Data leaks or their sale are not welcomed by customers. The results of empirical research show that the safety, simplicity and variety of services offered on social media have a significant impact on the perceived quality, which in turn positively affects the reputation. The authors proposed a methodology based on the Kano model and customer satisfaction in order to examine the declared needs and undefined desires and divide them into different groups with different impacts on consumer satisfaction. The interview participants were employees of 10 randomly selected companies using social media to conduct sales or service activities. 5,000 people from Poland, Portugal and Germany participated in the study. 4,894 correctly completed questionnaires were received.
In this study, we derive a simple transportation scheme by post-optimizing the costs of a modified problem. The strategy attempts to make the original (mainly feasible) option more practicable by adjusting the building components’ costs. Next, we employ the previously mentioned cell or area cost operators to gradually restore the modified costs to their initial levels, while simultaneously implementing the necessary adjustments to the “optimal” solution. This work presents a multi-goal, multi-item substantial transportation problem with interval-valued fuzzy variables, such as transportation costs, supplies, and demands, as parameters to maintain the transportation cost. This research addresses two circumstances where task ambiguity may occur: the interval solids transportation problem and the fuzzy substantial transportation issue. In the first scenario, we express data problems as intervals instead of exact values using an interval-valued fermatean neutrosophic number; in the second case, the information is not entirely obvious. We address both models when uncertainty solely affects the constraint set. For the interval scenario, we define an additional problem to solve. Our existing efficient systems have dependable transportation, so they are also capable of handling this new problem. In the fuzzy case, a parametric technique generates a fuzzy solution to the preceding problem. Since transportation costs have a direct impact on market prices, lowering them is the primary goal. Using parametric analysis, we provide optimal parameterization solutions for complementary situations. We provide a recommended algorithm for determining the stability set. In conclusion, we offer a sensitivity analysis and a numerical example of the transportation problem involving both balanced and imbalanced loads.
The article concerns the monitoring of elements of the information security system in an enterprise. The purpose of the research was to determine the reasons for monitoring information flows in the surveyed enterprise. The identification of information flows facilitates information management, empowering individuals to process information and preventing information security incidents. The implementation of information management methods facilitates monitoring the information security status.
This study work is among the few attempts to understand the significance of AI and its implementation barriers in the healthcare systems in developing countries. Moreover, it examines the breadth of applications of AI in healthcare and medicine. AI is a promising solution for the healthcare industry, but due to a lack of research, the understanding and potential of this technology is unexplored. This study aims to determine the crucial AI implementation barriers in public healthcare from the viewpoint of the society, the economy, and the infrastructure. The study used MCDM techniques to structure the multiple-level analysis of the AI implementation. The research outcomes contribute to the understanding of the various implementation barriers and provide insights for the decision makers for their future actions. The results show that there are a few critical implementation barriers at the tactical, operational, and strategic levels. The findings contribute to the understanding of the various implementation issues related to the governance, scalability, and privacy of AI and provide insights for decision makers for their future actions. These AI implementation barriers are encountered due to the wider range of system-oriented, legal, technical, and operational implementations and the scale of the usage of AI for public healthcare.
In today’s world, a country’s economy is one of the most crucial foundations. However, industries’ financial operations depend on their ability to meet their electricity demands. Thus, forecasting electricity consumption is vital for properly planning and managing energy resources. In this context, a new approach based on ensemble learning has been developed to predict monthly electricity consumption. The method divides electricity consumption time series into deterministic and stochastic components. The deterministic component, which consists of a secular long-term trend and an annual seasonality, is estimated using a multiple regression model. In contrast, the stochastic part considers the short-run random fluctuations of the consumption time series. It is forecasted by four different time series, four machine learning models, and three novel proposed ensemble models: the time series homogeneous ensemble model, the machine learning ensemble model, and the heterogeneous ensemble model. The study analyzed data on Pakistan’s monthly electricity consumption from 1991-January to 2022-December. The evaluation of the forecasting models is based on three criteria: accuracy metrics (including the mean absolute percent error (MAPE), the mean absolute error (MAE), the root mean squared error (RMSE), and the root relative squared error (RRSE)); an equality forecast statistical test (the Diebold and Mariano’s test); and a graphical assessment. The heterogeneous ensemble model’s forecasting results show lower error values compared to the homogeneous ensemble models and the singles models, with accuracy metrics measured by MAPE, MAE, RMSE, and RRSE at 5.0027, 460.4800, 614.5276, and 0.2933, respectively. Additionally, the heterogeneous ensemble model is statistically significant (p < 0.05) and superior to the rest of the models. Also, the heterogeneous ensemble model demonstrates considerable performance with the least mean error, which is comparatively better than the individual and best models reported in the literature and are considered baseline models. Further, the forecast values’ monthly behavior depicts that electricity consumption is higher during the summer season, and this demand will be highest in June and July. The forecast model and graph reveal that electricity consumption rapidly increases with time. This indirectly indicates that the government of Pakistan must take adequate steps to improve electricity production through different energy sources to restore the country’s economic status by meeting the country’s electricity demand. Despite several studies conducted from various perspectives, no analysis has been undertaken using an ensemble learning approach to forecast monthly electricity consumption for Pakistan.
The social distancing, isolation and shortage of health workers, as well as the COVID-19 pandemic, as well as the ageing of the society requiring healthcare, influenced the fast pace of digital innovation and the implementation of new technologies and even digital services in healthcare health. Is this transformation a blessing or a curse for healthcare? To answer this question, we conducted a literature review on new technologies, innovations in medicine and e-health. A research survey was also carried out in three countries and the Servqual analysis made it possible to estimate the trust in modern technologies for e-health and the trust of surveyors in these methods.
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