2020 Studia Prawno-Ekonomiczne, T. 115, s. 203-226
Background: The process of appraising scientific institutions provides the possibility to review and rank their scientific publications, and makes it possible to assess the current publications in the aspect of the next appraisal. The article analyzes the scientific publications of scientific insti-tutions classified as economic.
Research purpose: The purpose of the research is to indicate the most popular journals, publish-ers, and scientific conferences in the economic disciplines, defining their significance in the next appraisal in 2021. It makes it possible to draw preliminary conclusions regarding the implemen-tation of scientific policy in the field of economic sciences.
Methods: The material was developed on the basis of data from scientific institutions that were assessed in the parametric appraisal in 2017. Using analytical methods, information on the literary output of researchers from the economic disciplines was extracted. Data on journals, publishers, and conferences were ranked. Various data records by the reporting agents were taken into ac-count, which were unified for this work.
Conclusions: The analysis shows that alarge part of the most valuable literary output in the studied disciplines will lose its relevance in the next evaluation. There is aneed to adapt to new appraisal principles in order to increase the importance of scientific achievements. It was pointed out that the publications under study in the field of economics are not fully representative.
2020 Przegląd Biblioteczny, T. 88, z. 1, s. 65-80
This article presents informations about scientific literature of researchers from the discipline of bibliology and information science from 2013-2016. The purpose/thesis – The purpose of the research is indicating the most popular journals, publishers and scientific conferences in the discipline defining their significance in the next evaluation process (2021). It allows drawing preliminary conclusions regarding the implementation of scientific policy in the field of bibliology and information science. The methods – The material was developed on the basis of data from scientific institutions that were assessed in the parameterization process in 2017. Using analytical methods, information on the literary output of researchers representing the discipline was extracted. Data on journals, publishers and conferences have been sorted by ranking. Various data records by the reporting agents were taken into account, which were unified for the purposes of this work. The results/conclusions – The analysis shows that a large part of the most valuable literary output in the studied discipline will lose its relevance in the next evaluation. Attention was drawn to the need to adapt to new evaluation principles in order to increase the importance of scientific achievements. It was pointed out that the representativeness of the researched publications in the scientific achievements of the studied discipline is not full.
Sławomir Dadas, Michał Perełkiewicz, Rafał Poświata
2020 W: TWELFTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, May 11-16 , 2020, PALAIS DU PHARO, Marseille, France : CONFERENCE PROCEEDINGS / Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis; Marseille: European Language Resources Association, s. 1674-1680
12th Language Resources and Evaluation Conference. Marsylia, 2020-05-11 - 2020-05-16
Methods for learning sentence representations have been actively developed in recent years. However, the lack of pre-trained models and datasets annotated at the sentence level has been a problem for low-resource languages such as Polish which led to less interest in applying these methods to language-specific tasks. In this study, we introduce two new Polish datasets for evaluating sentence embeddings and provide a comprehensive evaluation of eight sentence representation methods including Polish and multilingual models. We consider classic word embedding models, recently developed contextual embeddings and multilingual sentence encoders, showing strengths and weaknesses of specific approaches. We also examine different methods of aggregating word vectors into a single sentence vector.
Paweł Kobyliński, Mariusz Wierzbowski, Krzysztof Piotrowski
2020 International Journal of Electrical Power and Energy Systems, T. 117, May 2020, Article number 105635
Though extensive, the literature on electrical load forecasting lacks reports on studies focused on existing re- sidential micro-neighbourhoods comprising small numbers of single-family houses equipped with solar panels. This paper provides a full description of an ANN-based model designed to predict short-term high-resolution (15- min intervals) micro-scale residential net load profiles. Since it seems especially relevant due to the specificity of local autocorrelations in load signal, in this paper we put stress on the systematic approach to feature selection in the context of lagged signal. We performed a case study of a real micro-neighbourhood comprising only 75 single-family houses. The obtained average prediction error was equivalent to 5.4 per cent of the maximal measured net load. The issues, i.e.: (1) the feasibility of micro-scale residential load forecasting taking into account renewable energy penetration, (2) the feasibility to predict net load with dense temporal resolution of 15 min, (3) the feature selection problem, (4) the proposed prosumption- and comparison-oriented prediction model key performance measure, could be of interest to engineers designing energy balancing systems for local smart grids.
2020 Fire Technology, T. 56, s. 545-581
In this paper, the author presents a novel information extraction systemthat analyses ﬁre service reports. Although the reports contain valuable informationconcerning ﬁre and rescue incidents, the narrative information in these reports hasreceived little attention as a source of data. This is because of the challenges associ-ated with processing these data and making sense of the contents through the use ofmachines. Therefore, a new issue has emerged: How can we bring to light valuableinformation from the narrative portions of reports that currently escape the attentionof analysts? The idea of information extraction and the relevant system for analysingdata that lies outside existing hierarchical coding schemes can be challenging forresearchers and practitioners. Furthermore, comprehensive discussion and proposi-tions of such systems in rescue service areas are insuﬃcient. Therefore, the authorcomprehensively and systematically describes the ways in which information extrac-tion systems transform unstructured text data from ﬁre reports into structured forms.Each step of the process has been veriﬁed and evaluated on real cases, including datacollected from the Polish Fire Service. The realisation of the system has illustratedthat we must analyse not only text data from the reports but also consider the dataacquisition process. Consequently, we can create suitable analytical requirements.Moreover, the quantitative analysis and experimental results verify that we can (1)obtain good results of the text segmentation (F-measure 95.5%) and classiﬁcationprocesses (F-measure 90%) and (2) implement the information extraction process andperform useful analysis
Zbigniew Bohdanowicz, Jarosław Kowalski, Katarzyna Abramczuk, Grzegorz Banerski, Daniel Cnotkowski, Agata Kopacz, Paweł Kobyliński, Aldona Zdrodowska, Cezary Biele
2020 W: Human Systems Engineering and Design II : Proceedings of the 2nd International Conference on Human Systems Engineering and Design (IHSED2019): Future Trends and Applications, September 16-18, 2019, Universität der Bundeswehr München, Munich, Germany / Tareq Ahram, Stefan Picki, Redha Taiar, Waldemar Karwowski; Cham: Springer, s. 397-403
The Virtual Reality (VR) world is very suggestive as it intensely affects the senses of vision, hearing and—to a limited extent—touch. It can be expected that in the near future VR will be widely disseminated and used by people of all ages, including children. We decided to conduct a qualitative research project to assess children’s (aged 7–12) first reactions to the use of VR. Children’s opinions and reactions gathered during the interviews indicate that children highly appreciated the attractiveness of the virtual experiences, which were often assessed at a similar or higher level than their real-world counterparts. Our findings clearly suggest that children very easily adopt VR without any prior experience with that technology. We recommend that studies on children’s behavior in VR are continued.
Marzena Feldy, Marta Bojko
2020 Marketing Instytucji Naukowych i Badawczych, T. 35, z. 1, s. 1-18
The decreasing supply of qualified people ready to take up employment, observed for several years on the labour market, results in the strengthening of the employee’s position. The consequences of this process affect not only the companies but also scientific institutions. The employee’s market, which is shaped as a result of the following changes, forces employers to focus increasingly on activities aimed at attracting and retaining individuals who constitute their human capital. The aim of our article is to diagnose satisfaction levels of various job facets and differences in attachment to the workplace in groups of scientists with varied job expectation profiles. On this basis, it will be possible to indicate the job facets that scientific institutions should take into consideration in order to provide researchers with a high level of job satisfaction. To broaden knowledge about the subject, we used data collected by the National Information Processing Institute in 2017 in a nationwide representative sample of 840 scientists who were at various stages of their academic career, represented all areas of science and worked in all types of scientific units in Poland. By performing factor analysis and a clustering procedure on variables describing researchers’ job expectations we were able to categorize the respondents into three groups: 1) demanding, 2) aspiring and 3) unengaged. The demanding employees have high expectations in all job facets that we examined, i.e.: economic and organizational matters, developmental and social opportunities as well as employment flexibility. The aspiring scientists above all appreciate developmental and social opportunities more than other groups. On the contrary, the unengaged employees value developmental and social opportunities the least while other job facets are moderately significant for them. The survey of satisfaction of particular groups of scientists with their current employer indicates the need to focus the scientific institutions employing them on different aspects of work. In the case of demanding employees, it is important to take care of their economic well-being. On the other hand, in order to increase satisfaction from work of scientists from the aspiring group, it will be important to provide them with a higher level of satisfaction from the development and social sphere. The greatest challenge may be the satisfaction of unengaged employees who declare a relatively low general level of satisfaction with the workplace, and at the same time do not have well-established expectations towards the institutions employing them.
Sławomir Dadas, Michał Perełkiewicz, Rafał Poświata
2020 W: Artificial Intelligence and Soft Computing : 19th International Conference, ICAISC 2020, Zakopane, Poland, October 12-14, 2020, Proceedings, Part II / Leszek Rutkowski, Rafał Scherer, Marcin Korytkowski, Witold Pedrycz, Ryszard Tadeusiewicz, Jacek M. Zurada; Cham: Springer, s. 301-314
19th International Conference, Artificial Intelligence and Soft Computing. Zakopane, 2020-10-12 - 2020-10-14
Transformer-based language models are now widely used in Natural Language Processing (NLP). This statement is especially true for English language, in which many pre-trained models utilizing transformer-based architecture have been published in recent years. This has driven forward the state of the art for a variety of standard NLP tasks such as classification, regression, and sequence labeling, as well as text-to-text tasks, such as machine translation, question answering, or summarization. The situation have been different for low-resource languages, such as Polish, however. Although some transformer-based language models for Polish are available, none of them have come close to the scale, in terms of corpus size and the number of parameters, of the largest English-language models. In this study, we present two language models for Polish based on the popular BERT architecture. The larger model was trained on a dataset consisting of over 1 billion polish sentences, or 135 GB of raw text. We describe our methodology for collecting the data, preparing the corpus, and pre-training the model. We then evaluate our models on thirteen Polish linguistic tasks, and demonstrate improvements over previous approaches in eleven of them.
Zbigniew Bohdanowicz, Jarosław Kowalski, Daniel Cnotkowski, Paweł Kobyliński, Cezary Biele
2020 ACHI 2020 : The Thirteenth International Conference on Advances in Computer-Human Interactions / Jaime Lloret Mauri, Diana Saplacan, Klaudia Çarçani, Prima Oky Dicky Ardiansyah, Simona Vasilache; Valencia : IARIA, s. 221-228
International Conference on Advances in Computer-Human Interactions ACHI 2020, Valencia, 2020-11-21 - 2020-11-25
Immersive Virtual Reality (IVR) may potentially effect considerable lifestyle changes in societies, comparable to those seen with the spread of smartphones. Questions arise as to the significance of IVR, and how people will respond to this type of innovation. The article presents the results of a qualitative study which assesses the reactions of adults from Generations X, Y and Z to IVR. 18 people aged 20-55 took part in the study; seven IVR applications were used. The study assessed participants' reactions, level of presence, affective response and susceptibility to cybersickness. The development potential of IVR was also considered. It was assumed that older generations would be less present in the IVR and their subjective assessment of satisfaction would be lower. The results of the study confirmed the hypothesis that, as people age, their level of presence in IVR decreases, but surprisingly, it emerged that satisfaction with being in IVR increases along with the age of the participants.
Hubert Suszek, Maciej Kopera, Robert A. Zucker, Marcin Wojnar, Elisa M. Trucco, Andrzej Jakubczyk, Paweł Kobyliński
2020 Journal of Addiction Medicine, T. 14, z. 5, s. e247-e256
Objectives: Although a theoretical link between childhood adversity and mental states recognition has been established, empirical findings are mixed. Some prior work indicates that childhood adversity might enhance, preserve, or reduce mentalization skills in selected at-risk populations. In the current study, we examine whether the presence of risky alcohol use during adolescence moderates the association between childhood alcohol-related family adversity and mental states recognition in young adulthood.
Methods: Secondary data analysis was conducted on 266 young adults who participated in the Michigan Longitudinal Study—a multiwave prospective study on at-risk youth. Children were assessed after initial recruitment (wave 1, target child age range 3–5 years), with assessments repeated every 3 years using parallel measures. The current study focuses on data spanning wave 2 (age range 7–9 years) through wave 6 (target child age range 18–21 years). A family adversity index was derived reflecting exposure to a maladaptive family environment during childhood as assessed at wave 1. An alcohol use risk factor was established reflecting early problem alcohol use during adolescence (target child age range 12–17 years). Mental states recognition was measured with a computerized version of the Reading the Mind in the Eyes Task (RMET) at wave 6. Information about demographics, psychopathological symptoms, and IQ was obtained. The alcohol use risk factor was tested as a potential moderator of the association between childhood family adversity on RMET performance during young adulthood.
Results: Alcohol use risk moderated the relationship between childhood alcohol-related family adversity, and negative and neutral mental states recognition. Specifically, childhood family adversity was positively associated with neutral mental states recognition among participants high in alcohol risk (P = 0.03) and positively associated with negative mental states recognition among participants at average (P = 0.02) and high (P = 0.002) levels of alcohol risk.
Conclusions: Findings indicate that history of childhood adversity may actually improve young adult negative and neutral mental states recognition among those demonstrating high levels of risky alcohol use, as substance use may serve as an external self-regulatory tool. Clinical interventions that target enhancing metacognitive competence and emotion regulation could ultimately help to break the cycle of alcohol-related family adversity.