Proceedings of the International Conference on Applied Statistics最新文献

{"title":"Sustainability literacy in the Romanian Universities","authors":"Elena-Maria Prada, Simona-Andreea Apostu, E. Gogu","doi":"10.2478/icas-2021-0020","DOIUrl":"https://doi.org/10.2478/icas-2021-0020","url":null,"abstract":"Abstract Sustainable university refers to the active involvement of higher education institutions in elaborating policies to protect the natural environment. The sustainable university is the one that, besides the governmental involvement, contributes to the safety of the environment by adapting the curriculum to the ecological needs and through the progress of the scientific knowledge, as a result of the didactic and research activities. As a vector of society’s development, the primary role of the university consists of educating future decision-makers. From the point of view of sustainable education, the concept of sustainable literacy has been shaped. Sustainable literacy involves educating future generations for sustainable development, considering the social, environmental, and cultural aspects specific to each country. In our opinion, “Sustainability literacy” in the academic environment is the formation and transmission of knowledge, skills, values, and attitudes that will allow students/graduates to engage deeply in building a sustainable future and improve their decision-making towards sustainability. The purpose of this research paper is to identify the context of ensuring and promoting sustainability in Romanian tertiary education. For this purpose, data obtained from the Romanian Agency for Quality Assurance in Higher Education were used regarding the number of students (as an element of the university demand) who follow a study program related to sustainable development, as well as data on the number of study programs in sustainability (as an element of the university offer). The results show that the number of students decreases, mainly due to demographic reasons, and the low graduation rates following the baccalaureate examination. Nevertheless, the number of programs in the sphere of sustainable development was higher in 2018 than the previous year. This fact demonstrates the importance given and the serious concerns regarding sustainability literacy in Romanian universities.","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115477464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of entrepreneurship on regional disparities in Romania: A spatial analysis at NUTS3 level","authors":"Mihai Antonia, Horia Tigau","doi":"10.2478/icas-2021-0003","DOIUrl":"https://doi.org/10.2478/icas-2021-0003","url":null,"abstract":"Abstract Our study contributes to bridging the empirical gap between regional disparities and entrepreneurship, using a spatial panel framework. Regional disparities in Romania increased after the communist period and even more after the EU accession. Using NUTS3 level data provided by The Romanian National Institute of Statistics, for the period 2008-2018, we investigate the impact of entrepreneurship on regional disparities. We have found new details regarding the link between entrepreneurial activity and inequality. Entrepreneurship matters but, most importantly, it matters differently in developed, emerging and low-income countries. The results suggest that entrepreneurship does not have a significant impact on regional disparities in Romania.","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123381143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Supporting secondary research in early drug discovery process through a Natural Language Processing based system","authors":"Alin-Bogdan Popa","doi":"10.2478/icas-2021-0019","DOIUrl":"https://doi.org/10.2478/icas-2021-0019","url":null,"abstract":"Abstract Last decades were characterised by a constant decline in the productivity of research and development activities of pharmaceutical companies. This is due to the fact that the drug discovery process contains an intrinsic risk that should be managed efficiently. Within this process, the early phase projects could be streamlined by doing more secondary research. These activities would involve the integration of chemical and biological knowledge from scientific literature in order to extract an overview and the evolution of a certain research area. This would then help refine the research and development operations. Considering the vast amount of pharmaceutical studies publications, it is not easy to identify the important information. For this task, a series of projects leveraged the advantages of the open pharmacological space through state-of-the-art technologies. The most popular are Knowledge Graphs methods. Although extremely useful, this technology requires increased investments of time and human resources. An alternative would be to develop a system that uses Natural Language Processing blocks. Still, there is no defined framework and reusable code template for the use-case of compounds development. In this study, it is presented the design and development of a system that uses Dynamic Topic Modelling and Named Entity Recognition modules in order to extract meaningful information from a large volume of unstructured texts. Moreover, the dynamic character of the topic modelling technique allows to analyse the evolution of different subject areas over time. In order to validate the system, a collection of articles from the Pharmaceutical Research Journal was used. Our results show that the system is able to identify the main research areas in the last 20 years, namely crystalline and amorphous systems, insulin resistance, paracellular permeability. Additionally, the evolution of the subjects is a highly valuable resource and should be used to get an in-depth understanding about the shifts that happened in a specific domain. However, a limitation of this system is that it cannot detect association between two concepts or entities if they are not involved in the same document.","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121788412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling The Budget Revenues On The Basis Of Appropriate Macroeconomic Indicators. A Case Study For Romania","authors":"A. Bălţăţeanu","doi":"10.2478/icas-2021-0006","DOIUrl":"https://doi.org/10.2478/icas-2021-0006","url":null,"abstract":"\u0000 The article aims to identify if there is an interdependence between the main budgetary revenues and the macroeconomic indicators which can be found in the official forecasts. The proposed econometric method may constitute an alternative way of checking the consistency between the forecast of the budgetary indicators and the macroeconomic ones and can highlight in the same time the impact of some governmental policies on the public sector.","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122767510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Supporting secondary research in early drug discovery process through a Natural Language Processing based system","authors":"Alin-Bogdan Popa","doi":"10.2478/icas-2021-0023","DOIUrl":"https://doi.org/10.2478/icas-2021-0023","url":null,"abstract":"Abstract Last decades were characterised by a constant decline in the productivity of research and development activities of pharmaceutical companies. This is due to the fact that the drug discovery process contains an intrinsic risk that should be managed efficiently. Within this process, the early phase projects could be streamlined by doing more secondary research. These activities would involve the integration of chemical and biological knowledge from scientific literature in order to extract an overview and the evolution of a certain research area. This would then help refine the research and development operations. Considering the vast amount of pharmaceutical studies publications, it is not easy to identify the important information. For this task, a series of projects leveraged the advantages of the open pharmacological space through state-of-the-art technologies. The most popular are Knowledge Graphs methods. Although extremely useful, this technology requires increased investments of time and human resources. An alternative would be to develop a system that uses Natural Language Processing blocks. Still, there is no defined framework and reusable code template for the use-case of compounds development. In this study, it is presented the design and development of a system that uses Dynamic Topic Modelling and Named Entity Recognition modules in order to extract meaningful information from a large volume of unstructured texts. Moreover, the dynamic character of the topic modelling technique allows to analyse the evolution of different subject areas over time. In order to validate the system, a collection of articles from the Pharmaceutical Research Journal was used. Our results show that the system is able to identify the main research areas in the last 20 years, namely crystalline and amorphous systems, insulin resistance, paracellular permeability. Additionally, the evolution of the subjects is a highly valuable resource and should be used to get an in-depth understanding about the shifts that happened in a specific domain. However, a limitation of this system is that it cannot detect association between two concepts or entities if they are not involved in the same document.","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"334 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114234045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using discriminant analysis to study the discrinimation issue of refugees and migrants from MENA region in European countries","authors":"Amira Kobeissi, A. Bager, Hiba Mohammad","doi":"10.2478/icas-2021-0013","DOIUrl":"https://doi.org/10.2478/icas-2021-0013","url":null,"abstract":"Abstract In the last years and after the arrival of a significant number of migrants, asylum seekers, and refugees. Foreigners from MENA region started facing numerous issues in the host countries. One of the major issues that the refugees and migrants are facing now adays is discrimination. As most of the studies exposes that this topic is recently debatable among the European governments. Likewise, the literature review on this matter shows that most of the European countries who welcomed refugees in large numbers were more able to understand and keep away factors that drive to discrimination. It is well known that are many factors that lead to discrimination such as the difference in nationalities, religion, and gender. Although there are different places where the migrants and refugees can feel discriminated for instance: public authorities, workplace, schools, and universities. Moving on to the methodology used in this paper is the quantitative method, we conducted an online survey distributed on refugees and youth migrants in both languages (English and Arabic) that are living in European countries. We tried in our survey to ask questions related to discrimination, in order to understand how they are dealing with this issue and to what extent is discrimination affecting them. For that reason, we used the discriminant analysis. the discriminant analysis feature is split into a 2-step process firstly is testing significance of a series of functions that most affect the migrations as the results of the discriminant analysis had shown us that the number of years lived in Europe was directly affected by discrimination, in addition to the classification. As using the discriminant analysis was an efficient way to study the main factors affected by discrimination.","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130906896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kinetic energies in random vectors","authors":"Alexandru Daia, Stelian Stancu, Om Suchak","doi":"10.2478/icas-2021-0008","DOIUrl":"https://doi.org/10.2478/icas-2021-0008","url":null,"abstract":"Abstract This paper uses the Onicescu Coefficient concept, which is the sum of squared probabilities, through mathematical formulations to show the kinetic energy in random vectors. The paper has a brief introduction section that addresses the background of the study, the purpose of the study, and its objective. The literature review section provides an in-depth industrial application of mathematical formulations in solving real-life problems. The paper contains a methodology section highlighting the study design, data collection methods, and analysis section, highlighting some of the keywords used in locating resources and significant databases that provided the study with information. Later, the study takes the result and discussion sectional approach to present the experiments’ findings backed with facts from previous studies by other scholars in the same field. Lastly, the paper concludes with a section recapping the critical points of this study and study application in real-life, concluding with a list of references utilized by this study.","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127181283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is conventionally calculated anchor-based minimum clinically important difference value catches the real clinical increment? Determining the situations that make the answer “no” by a simulation study","authors":"S. Yüksel, P. Demır, A. Alkan","doi":"10.2478/icas-2019-0046","DOIUrl":"https://doi.org/10.2478/icas-2019-0046","url":null,"abstract":"Abstract The aim of this study was to examine the accuracy of conventionally used method-optimal cutoff of Receiver Operating Characteristic (ROC) curve- to determine the minimum clinically important difference (MCID), which is the estimator of responsiveness for scales, by a simulation study. The baseline person parameters were firstly generated and, by using these values, two gold standard groups were constructed as “improved” and “non-improved” after the treatment. Five point-likert response patterns were obtained for 20 items in each group, representing pre- and post-treatment responses of individuals. The mean change score between post treatment and baseline scores for the improved group was considered as real MCID (MCIDR), after baseline and post-treatment total scores were calculated from response patterns. The cut-off for change score specified by ROC analysis, which best discriminates between improved group and not improved group, MCIDROC, was compared to MCIDR. The scenarios of simulation were consisted of sample size and distribution of total scores for improved group. The data were generated for each of 40 scenarios with 1000 MCMC repeats. It was observed that the MCIDR and MCIDROC were not so affected by sample size. However, MCIDROC overestimated the MCIDR values in all scenarios. Briefly, the cut-off points obtained by ROC analysis found to be greater than the real MCID values. Therefore, alternative methods are required to calculate MCID.","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124950102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Post-Crisis Household Savings Behavior in Romania","authors":"D. Anghel, A. Străchinaru","doi":"10.2478/icas-2019-0003","DOIUrl":"https://doi.org/10.2478/icas-2019-0003","url":null,"abstract":"Abstract The recent linear growth trend recorded by net savings in Romania is very intriguing. We thus study household savings behavior using Vector Autoregression and Vector Error Correction models on a sample of post-2007 monthly data. Contrary to common economic theory, we find that real interest rates do not influence the loan and savings behavior of Romanian households in our sample, despite their significant volatility and, even, negative recorded values. The results indicate a change in attitude and in risk perception of Romanian households in the aftermath of the financial crisis in 2008, in the way that has significantly decreased their preference for present consumption in favor of savings. Despite the significant increase in net savings, we also find that they have not significantly contributed to economic growth.","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125919935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical applications of optimization methods and mathematical programming","authors":"D. Manea, E. Țițan, R. Serban, M. Mihai","doi":"10.2478/icas-2019-0028","DOIUrl":"https://doi.org/10.2478/icas-2019-0028","url":null,"abstract":"Abstract Optimization techniques perform an important role in different domains of statistic. Examples of parameter estimation of different distributions, correlation analysis (parametric and nonparametric), regression analysis, optimal allocation of resources in partial research, exploration of response surfaces, design of experiments, efficiency tests, reliability theory, survival analysis are the most known methods of statistical analysis in which we find optimization techniques. The paper contains a synthetic presentation of the main statistical methods using classical optimization techniques, numerical optimization methods, linear and nonlinear programming, variational calculus techniques. Also, an example of applying the “simplex” algorithm in making a decision to invest an amount on the stock exchange, using a prediction model..","PeriodicalId":393626,"journal":{"name":"Proceedings of the International Conference on Applied Statistics","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128144597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}