rss_2.0Computer Sciences FeedSciendo RSS Feed for Computer Sciences Sciences Feed Detection and Extraction of Research Topics from Academic Documents Using Deep Clustering<abstract><title style='display:none'>Abstract</title><sec><title style='display:none'>Purpose</title><p>Detection of research fields or topics and understanding the dynamics help the scientific community in their decisions regarding the establishment of scientific fields. This also helps in having a better collaboration with governments and businesses. This study aims to investigate the development of research fields over time, translating it into a topic detection problem.</p></sec><sec><title style='display:none'>Design/methodology/approach</title><p>To achieve the objectives, we propose a modified deep clustering method to detect research trends from the abstracts and titles of academic documents. Document embedding approaches are utilized to transform documents into vector-based representations. The proposed method is evaluated by comparing it with a combination of different embedding and clustering approaches and the classical topic modeling algorithms (i.e. LDA) against a benchmark dataset. A case study is also conducted exploring the evolution of Artificial Intelligence (AI) detecting the research topics or sub-fields in related AI publications.</p></sec><sec><title style='display:none'>Findings</title><p>Evaluating the performance of the proposed method using clustering performance indicators reflects that our proposed method outperforms similar approaches against the benchmark dataset. Using the proposed method, we also show how the topics have evolved in the period of the recent 30 years, taking advantage of a keyword extraction method for cluster tagging and labeling, demonstrating the context of the topics.</p></sec><sec><title style='display:none'>Research limitations</title><p>We noticed that it is not possible to generalize one solution for all downstream tasks. Hence, it is required to fine-tune or optimize the solutions for each task and even datasets. In addition, interpretation of cluster labels can be subjective and vary based on the readers’ opinions. It is also very difficult to evaluate the labeling techniques, rendering the explanation of the clusters further limited.</p></sec><sec><title style='display:none'>Practical implications</title><p>As demonstrated in the case study, we show that in a real-world example, how the proposed method would enable the researchers and reviewers of the academic research to detect, summarize, analyze, and visualize research topics from decades of academic documents. This helps the scientific community and all related organizations in fast and effective analysis of the fields, by establishing and explaining the topics.</p></sec><sec><title style='display:none'>Originality/value</title><p>In this study, we introduce a modified and tuned deep embedding clustering coupled with Doc2Vec representations for topic extraction. We also use a concept extraction method as a labeling approach in this study. The effectiveness of the method has been evaluated in a case study of AI publications, where we analyze the AI topics during the past three decades.</p></sec></abstract>ARTICLE2021-06-18T00:00:00.000+00:00Some fractional derivatives of -function of multivariable<abstract> <title style='display:none'>Abstract</title> <p>In the present paper, we study and develop Fractional derivatives of multivariable <italic>A</italic> – function. We derive two theorems which will act as the key formulas from which can obtain their special cases.</p> </abstract>ARTICLE2021-06-17T00:00:00.000+00:00Generalized Lindley-Quasi Xgamma distribution<abstract> <title style='display:none'>Abstract</title> <p>We obtained a new generalization of Lindley-Quasi Xgamma distribution by adding weight parameter to it through weighting technique and have shown the flexibility of proposed model. Expression for reliability measures, order statistics, Bonferroni curves &amp; indices, Renyi entropy along with some other important properties are derived. Maximum likelihood estimation method is put to use for estimation of unknown parameters of proposed model. Simulation study for checking the performance of maximum likelihood estimates and for model comparison is carried out. Proposed model and its related models are fitted to real life data sets and goodness of fit measure Kolmogorov statistic &amp; p-value, loss of information criteria’s AIC, BIC, AICC &amp; HQIC are computed through R software to check the applicability of proposed model in real life. The significance of weight parameter is also tested by using likelihood ratio test for both randomly generated data as well as real life data.</p> </abstract>ARTICLE2021-06-17T00:00:00.000+00:00Some new inequalities for generalized convex functions pertaining generalized fractional integral operators and their applications<abstract> <title style='display:none'>Abstract</title> <p>In this paper, authors establish a new identity for a differentiable function using generic integral operators. By applying it, some new integral inequalities of trapezium, Ostrowski and Simpson type are obtained. Moreover, several special cases have been studied in detail. Finally, many useful applications have been found.</p> </abstract>ARTICLE2021-06-17T00:00:00.000+00:00Applying fractional calculus to analyze final consumption and gross investment influence on GDP<abstract> <title style='display:none'>Abstract</title> <p>This paper points out the possibility of suitable use of Caputo fractional derivative in regression model. Fitting historical data using a regression model seems to be useful in many fields, among other things, for the short-term prediction of further developments in the state variable. Therefore, it is important to fit the historical data as accurately as possible using the given variables. Using Caputo fractional derivative, this accuracy can be increased in the model described in this paper.</p> </abstract>ARTICLE2021-06-17T00:00:00.000+00:00Doubly stochastic matrices and the quantum channels<abstract> <title style='display:none'>Abstract</title> <p>The main object of this paper is to study doubly stochastic matrices with majorization and the Birkhoff theorem. The Perron-Frobenius theorem on eigenvalues is generalized for doubly stochastic matrices. The region of all possible eigenvalues of n-by-n doubly stochastic matrix is the union of regular (n – 1) polygons into the complex plane. This statement is ensured by a famous conjecture known as the Perfect-Mirsky conjecture which is true for n = 1, 2, 3, 4 and untrue for n = 5. We show the extremal eigenvalues of the Perfect-Mirsky regions graphically for n = 1, 2, 3, 4 and identify corresponding doubly stochastic matrices. Bearing in mind the counterexample of Rivard-Mashreghi given in 2007, we introduce a more general counterexample to the conjecture for n = 5. Later, we discuss different types of positive maps relevant to Quantum Channels (QCs) and finally introduce a theorem to determine whether a QCs gives rise to a doubly stochastic matrix or not. This evidence is straightforward and uses the basic tools of matrix theory and functional analysis.</p> </abstract>ARTICLE2021-06-17T00:00:00.000+00:00Applying Data Envelopment Analysis Principle in Ordinal Multi Criteria Decision Analysis<abstract> <title style='display:none'>Abstract</title> <p>We consider a multicriteria decision analysis (MCDA) problem where importance of criteria, and evaluations of alternatives with respect to the criteria, are expressed on a qualitative ordinal scale. Using the extreme-point principle of Data Envelopment Analysis (DEA), we develop a two-parameter method for obtaining overall ratings of the alternatives when preferences and evaluations are made on an ordinal scale. We assume no parametric setup other than the two parameters that reflect minimum intensities of discriminating among rank positions: one parameter for the alternatives’ ranking and one for the criteria ranking. These parameters are bounded by the ordinal input data, and they imply a universal tie among the alternatives when both parameters are selected to be zero. We describe the model, discuss its theoretical underpinning, and demonstrate its application.</p> </abstract>ARTICLE2021-06-17T00:00:00.000+00:00Effect or Program Constructs on Code Readability and Predicting Code Readability Using Statistical Modeling<abstract> <title style='display:none'>Abstract</title> <p>In software, code is the only part that remains up to date, which shows how important code is. Code readability is the capability of the code that makes it readable and understandable for professionals. The readability of code has been a great concern for programmers and other technical people in development team because it can have a great influence on software maintenance. A lot of research has been done to measure the influence of program constructs on the code readability but none has placed the highly influential constructs together to predict the readability of a code snippet. In this article, we propose a novel framework using statistical modeling that extracts important features from the code that can help in estimating its readability. Besides that using multiple correlation analysis, our proposed approach can measure dependencies among di erent program constructs. In addition, a multiple regression equation is proposed to predict the code readability. We have automated the proposals in a tool that can do the aforementioned estimations on the input code. Using those tools we have conducted various experiments. The results show that the calculated estimations match with the original values that show the effectiveness of our proposed work. Finally, the results of the experiments are analyzed through statistical analysis in SPSS tool to show their significance.</p> </abstract>ARTICLE2021-06-17T00:00:00.000+00:00A Statistical Evaluation of The Depth of Inheritance Tree Metric for Open-Source Applications Developed in Java<abstract> <title style='display:none'>Abstract</title> <p>The Depth of Inheritance Tree (DIT) metric, along with other ones, is used for estimating some quality indicators of software systems, including open-source applications (apps). In cases involving multiple inheritances, at a class level, the DIT metric is the maximum length from the node to the root of the tree. At an application (app) level, this metric defines the corresponding average length per class. It is known, at a class level, a DIT value between 2 and 5 is good. At an app level, similar recommended values for the DIT metric are not known. To find the recommended values for the DIT mean of an app we have proposed to use the confidence and prediction intervals. A DIT mean value of an app from the confidence interval is good since this interval indicates how reliable the estimate is for the DIT mean values of all apps used for estimating the interval. A DIT mean value higher than an upper bound of prediction interval may indicate that some classes have a large number of the inheritance levels from the object hierarchy top. What constitutes greater app design complexity as more classes are involved. We have estimated the confidence and prediction intervals of the DIT mean using normalizing transformations for the data sample from 101 open-source apps developed in Java hosted on GitHub for the 0.05 significance level.</p> </abstract>ARTICLE2021-06-17T00:00:00.000+00:00Acceptable-and-attractive Approximate Solution of a Continuous Non-Cooperative Game on a Product of Sinusoidal Strategy Functional Spaces<abstract> <title style='display:none'>Abstract</title> <p>A problem of solving a continuous noncooperative game is considered, where the player’s pure strategies are sinusoidal functions of time. In order to reduce issues of practical computability, certainty, and realizability, a method of solving the game approximately is presented. The method is based on mapping the product of the functional spaces into a hyperparallelepiped of the players’ phase lags. The hyperparallelepiped is then substituted with a hypercubic grid due to a uniform sampling. Thus, the initial game is mapped into a finite one, in which the players’ payoff matrices are hypercubic. The approximation is an iterative procedure. The number of intervals along the player’s phase lag is gradually increased, and the respective finite games are solved until an acceptable solution of the finite game becomes sufficiently close to the same-type solutions at the preceding iterations. The sufficient closeness implies that the player’s strategies at the succeeding iterations should be not farther from each other than at the preceding iterations. In a more feasible form, it implies that the respective distance polylines are required to be decreasing on average once they are smoothed with respective polynomials of degree 2, where the parabolas must be having positive coefficients at the squared variable.</p> </abstract>ARTICLE2021-06-17T00:00:00.000+00:00Testing the Feldstein Horioka puzzle in Algeria: Maki co-integratioan and hidden causality analysis<abstract><title style='display:none'>Abstract</title><p>The aim of this paper is to test the existence of Feldstein Horioka puzzle in the case of Algerian economy for the period 1970-2019 by examining the link between domestic savings and investments, we use in this paper both the co-integration tests under Gregory-Hansen (1996), Hatemi-J (2008) and Maki (2012) tests in the context of structural breaks, and the symmetric and asymmetric causality (hidden causality) proposed by Hacker-Hatemi (2010) and Hatemi (2012) respectively, the results suggest that there is a co-integration relationship between saving and investment with five endogenous structural breaks, and the saving retention coefficient is equal to 0.324 which means the existence of Feldstein-Horioka puzzle in a weaker form and high capital mobility, on the other hand, the results indicate asymmetric causal relationship between savings and investments.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00Sustainability literacy in the Romanian Universities<abstract><title style='display:none'>Abstract</title><p>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.</p><p>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.</p><p>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.</p><p>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.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00Budgetary efficiency expressed as the interdependence of public expenditures and the Gross Domestic Product in the Republic of Moldova<abstract><title style='display:none'>Abstract</title><p>We address budget performance in terms of savings, efficiency, and effectiveness. To facilitate a quantitative analysis of budgetary efficiency, we perform a detailed study based on an econometric model of the interdependence of public expenditure, both capital and private, and GDP. We show that an increase in public expenditure, especially current, can significantly accelerate the growth of the productive sectors of the economy. Further, the implementation of performance indicators for public expenditure can lead to accelerated economic growth, both quantitatively as well as qualitatively, in the Republic of Moldova.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00Combining Regression and Clustering for Financial Analysis<abstract><title style='display:none'>Abstract</title><p>Artificial Intelligence is used in business through machine learning algorithms. Machine learning is a part of computer science focused on computer systems learning to perform a specific task without using explicit instructions, relying on patterns and inference instead.</p><p>Though it might seem like we’ve come a long way in the last ten years, which is true from a research perspective, the adoption of AI among corporations is still relatively low. Over time it became possible to automate more tasks and business processes than ever before. The benefit of using artificial intelligence is that does not require to program every step of the process, predicting at each step what could happen and how to resolve it. The algorithms decide for themselves in each case how the problems should be solved, based on the data that is used.</p><p>I apply Python language to create a synthetic feature vector that allows visualizations in two dimensions for EDIBTA financial ratio. I use Mean-Square Error in order to evaluate the success, having the optimal parameters. In this section, I also mentioned about the purpose, goals, and applications of cluster analysis. I indicated about the basics of cluster analysis and how to do it and also did a demonstration on how to use K-Means.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00Romania’s tourism industry in free fall<abstract><title style='display:none'>Abstract</title><p>Tourism is one of the consistent branches of the national economy, which can ensure some concrete results and a tailor-made contribution to the formation of the Gross Domestic Product. The tourism industry is also called invisible trade in the sense that, although it does not export goods and services, by practicing it, by developing it, it ensures consistent revenues to the state budget, but also ensures the possibility of increasing Gross Domestic Product.</p><p>Analysing the current situation of the health and economic-financial crisis, it is found that in 2020 HoReCa, the tourism industry, complementary services have decreased alarmingly. Against this background, tourism has reduced its contribution to the formation of the Gross Domestic Product, which can lead to an even greater decrease.</p><p>Investments in tourism are eroding. There is no possibility of refinancing despite support measures provided by the authorities. We say in spite of some measures granted because the postponement of some payments, the postponement of some credits, the transition to technical unemployment and others will be coupled later with other measures with almost devastating effect for the Romanian economy. Thus, many jobs will be lost. On the other hand, tourism companies will not be able to move from technical unemployment to normal activity and give a minimum of six months to those in this situation.</p><p>The tourist market practically does not exist because there are only sequential possibilities in which it takes place, but especially under the rule of business activities, which are also considered tourist activities.</p><p>The tourist activity materialized through arrivals, overnight stays, arrivals and departures has decreased steadily and this result mainly from the data subject to the study we mentioned. It is necessary to interpret these data and possibly find ways to recover.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00Technical and scale efficiency in Romanian public hospitals: Estimating with Data Envelopment Analysis<abstract><title style='display:none'>Abstract</title><p>Hospitals are a major component of the health systems, due to the complexity of the medical services they deliver and the great resources consumption. They impact the performance of the health systems, the economic policies and the public health. Since performance is a multidimensional concept, the main technique used to get a proxy evaluation of performance in the healthcare sector is Data Envelopment Analysis. DEA measures the efficiency of the healthcare providers and allows comparative analysis to identify the best practice frontier. This study addresses the performance of Romanian public hospitals from the North-Eastern region of the country and measures technical and scale efficiency. DEA basic models were run under the assumptions of constant and variable returns to scale, in an input-oriented evaluation of a sample of 18 public hospitals. The results indicated that most of the hospitals are technically inefficient (89%) and these inefficiencies are in the form of scale inefficiency for 39% of the hospitals. The average efficiency scale value was of 82%, implying that the observed hospitals could have increased their outputs by 18% if they had reached the optimal scale. The conclusion of the paper is that the inefficiency of the compared hospitals is almost equally caused by the inefficient implementation of the production plan and by the divergence of the decision making units from the most productive scale size. This kind of efficiency analyses could support managers when planning hospitals activity and policy makers when planning resources allocation and implementation of new strategies for the health system governance.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00Labor force shortage analysis in Romania - size, impact and measures<abstract><title style='display:none'>Abstract</title><p>Under the impact of unfavourable demographic developments, some existing imbalances on the Romanian labor market have worsened. Thus, in 2019 the labor force shortage was estimated to 300000 persons, while in the last ten years the number of vacancies has exceeded 60,000 places, more than double the level at the beginning of the period (2010). This phenomenon may have negative social and economic effects. In this context, the present paper aims at analysing the labor shortages in Romania, at identifying its main determinants and the most important social and economic consequences and recommends a series of measures to mitigate the negative effects of this phenomenon.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00Spatial changes in entrepreneurship in relation to economic crisis and recovery. Insights from Romanian counties<abstract><title style='display:none'>Abstract</title><p>Trying to explain the sources of persisting high inequalities in the regional distribution of entrepreneurship in Romania, this paper puts a spotlight on the spatial interactions among neighbour regions in a spatial modelling framework. We explored the interplay of factors that inform the territorial distribution of SMEs by employing various spatial panel data models that not only provided better estimations of the parameters, but also removed the cross – sectional dependence detected in our previous research using classic panel models. We found that the existing regional inequalities in entrepreneurial activity are strongly associated with differences in economic development, gross investments, research and development, age of the population, and and differences in regional resilience to economic crises. Additional useful information was brought about by the computation of direct and indirect effects of these factors of influence.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00Use of Social Networks in Determining stockmarket Evolution<abstract><title style='display:none'>Abstract</title><p>This article aims to use text mining methods and sentiment analysis to determine the stock market evolution of companies as well as virtual currencies such as Bitcoin. The source of the text is the social media channel Twitter and the text is composed of individual messages sent by users. Although previous papers proved with a degree of certainty that this paper hypothesis is true, as we will see bellow, the area of research was focused only on the professional environment or known opinion makers and not taking into account a high population mass. To ensure that a high level of information is maintained after the sentiment analysis process, we will use multiple algorithms based on different calculation methods and different word dictionaries. In addition, indicators such as the number of assessments, the number of replays etc. will be added to the methodology. By the end of the paper we will be able to both identify a working methodology of analyzing text for the purposes of stock market prediction and also we will touch on the limitations faced when creating it and the ways through which we can expand and improve it’s reliability. The implementation of all these methods and of the multiple dictionaries helped us in simulating human behavior and the differences of opinion, when a group wants to analyze a text. The algorithm becoming a way to balance the different “opinions” that resulted out of the sentiment analysis.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00Digital innovation in education in Romania quantitative approach<abstract><title style='display:none'>Abstract</title><p>Economic growth, productivity and national well-being over time have been promoted through various innovation strategies. Education aims to shape the human personality according to its particularities but also according to the social dynamics, the mobility of teachers through the dynamic integration of man in society. Education differs from one historical stage to another. With the advancement of technology, students have the opportunity to take online courses, regardless of where they are, age, physical limitations or personal schedule. Technology can open up new opportunities for learning and assessment.</p><p>With the help of the regression analysis applied based on the indicators provided by the National Institute of Statistics: the number of students, computers, laboratories and workshops in each county in Romania (2010-2017) tested the influence of technology on the number of students enrolled in schools. The main conclusion of the study emphasizes that a higher number of children enrolled in school in a county is correlated with the degree of technology. Thus, the number of new devices will increase to ensure the possibility for both teachers and students to evolve. On the other hand, the fact that some areas of the country are less developed and lack funding, is also reflected in the number of children enrolled as well as in the number of computers available.</p></abstract>ARTICLE2021-05-31T00:00:00.000+00:00en-us-1