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The COVID-19 pandemic continues to overwhelm global healthcare systems. While the disease primarily causes pulmonary complications, reports of central nervous system (CNS) involvement have recently emerged ranging from encephalopathy to stroke. This raises a practical dilemma for clinicians as to when to pursue neuroimaging and lumbar tap with cerebrospinal fluid (CSF) analysis in COVID-19 patients with neurological symptoms. We present a case of an encephalopathic patient infected with SARS-CoV-2 with no pulmonary symptoms. We propose a three-tier risk stratification for CNS COVID-19 aiming to help clinicians to decide which patients should undergo CSF analysis. The neurological examination remains an integral component of screening and evaluating patients for COVID-19 considering the range of emerging CNS complications.
Thanks to the rapid progress in the field of artificial intelligence algorithms are able to accomplish an increasingly comprehensive list of tasks, and often they achieve better results than human experts. Nevertheless, many consumers have ambivalent feelings towards algorithms and tend to trust humans more than they trust machines. Especially when tasks are perceived as subjective, consumers often assume that algorithms will be less effective, even if this belief is getting more and more inaccurate.
To encourage algorithm adoption, managers should provide empirical evidence of the algorithm’s superior performance relative to humans. Given that consumers trust in the cognitive capabilities of algorithms, another way to increase trust is to demonstrate that these capabilities are relevant for the task in question. Further, explaining that algorithms can detect and understand human emotions can enhance adoption of algorithms for subjective tasks.
Enterprises which want to ensure a secure and stable market position must constantly look for ways to convince customers (current and potential) that their goods and services are competitive and represent a sufficiently high level of quality, consistent with the their needs. Service enterprises use specific methods and tools to analyze the quality of their services and to be sure that these services are competitive on the market. One of the important elements of such an analysis is the assessment of customer satisfaction. This research should be treated as a key stage in the customer satisfaction management system. Without knowing the customers' expectations, the enterprise is unable to determine what to improve and correct. In this case, the Customer Satisfaction Index (CSI), which not only indicates what to improve, but also shows the level of customer satisfaction, should be used. The purpose of the paper is to assess customer satisfaction in a service point of a known producer of men's clothes. The CSI index and a specially developed survey were used for the research. The questionnaire was filled in by the customers of the research service point after the service delivery. According to the obtained results, individual determinants should be maintained and monitored by the enterprise. The research also identified areas for improvement, i.e. product quality, design and ways of payment. However, the overall CSI score is good, which means that despite few problems with customers' satisfaction, they are satisfied with the research service point.
Chronic rhinosinusitis represents an inflammatory condition of the nose and paranasal sinuses, characterized by two or more symptoms. The diagnosis of acute rhinosinusitis is made, most often, clinically; however, in the case of chronic rhinosinusitis, imaging, bacteriological, as well as the histological investigation are necessary in order to establish the diagnosis and to exclude other diseases that have caused and/or are associated with rhinosinusitis. Different scores (clinical, imagistic) have been described over time, being considered as important factors in the therapeutic decision (surgical or conservative) in patients with chronic rhinosinusitis. The authors present their experience in using and relying on endoscopic and histological scores.
Romance has the reputation of being an opiate for the masses. This paper intends to analyze if it is indeed a fantasy imposed from above or if there is room for negotiation. The chosen space is vampire romance writer J. R. Ward's forum. Power will be discussed through the lens of Foucault's Panopticon and de Certeau's productive consumption, among others.
Romance has the reputation of being an opiate for the masses. This paper intends to analyze if it is indeed a fantasy imposed from above or if there is room for negotiation. The chosen space is vampire romance writer J. R. Ward's forum. Power will be discussed through the lens of Foucault's Panopticon and de Certeau's productive consumption, among others
In this study of English Foreign Language Learners, the author explored the learning preferences of 14 students (ages 18-20) enrolled in English for Specific Purposes (ESP) course. All students were provided with the same content, course materials, assignments and time for completing the assignments. They were all given the same pre and post-learning questionnaire, writing tasks and final exam. However, they completed these tasks either in a digital environment or in-class.
The study was conducted at South East European University in Macedonia where digital instruction is not well known or practiced. The results indicate that the best way for students to learn is by combining the two learning environments. By completing an assignment both ways, students discovered not only that some tasks are best done in a digital environment and others in class, but also they discovered their preferred way of learning.
Whatever your perception of AI is, the machine age of marketing has arrived. To fully grasp how AI is changing every fabric of both our professional and private lives, we need to abstract beyond the presence of autonomous cars, digital voice assistants, or using machines to translate some text for us. AI is creating new forms of competition, value chains, and novel ways of orchestrating economies around the world. AI is more than just technology, it’s creating a new economy. The fuel that runs this economy is the combination of computational processing power, data, and the algorithms that process this data.
AI has the potential to make our life easier, but this convenience might come at a price which we have to pay such as biases directly built-in to the algorithms we use, data privacy issues or failed AI projects in business practice. But without testing, failing, and learning from our failures, there