<abstract xmlns="http://www.w3.org/1999/xhtml">One of the most studied aspect of complex graphs is identifying the most influential nodes. There are some local metrics like degree centrality, which is cost-effiective and easy to calculate, although using global metrics like betweenness centrality or closeness centrality can identify influential nodes more accurately, however calculating these values can be costly and each measure has it’s own limitations and disadvantages. There is an ever-growing interest in calculating such metrics in time-varying graphs (TVGs), since modern complex networks can be best modelled with such graphs. In this paper we are investigating the effectiveness of a new centrality measure called efficiency centrality in TVGs. To evaluate the performance of the algorithm Independent Cascade Model is used to simulate infection spreading in four real networks. To simulate the changes in the network we are deleting and adding nodes based on their degree centrality. We are investigating the Time-Constrained Coverage and the magnitude of propagation resulted by the use of the algorithm.</abstract>

Efficiency centrality in time-varying graphs

<abstract xmlns="http://www.w3.org/1999/xhtml">Formal concept analysis (FCA) is a method based on lattice theory, widely used for data visualization, data analysis and knowledge discovery. Amino acids (AAs) are chemical molecules that constitute the proteins. In this paper is presented a new and easy way of visualizing of the structure and properties of AAs. In addition, we performed a new Hydrophobic-Polar classification of AAs using FCA. For this, the 20 proteinogenic AAs were clustered, classified by hydrophobicity and visualized in Hasse-diagrams. Exploring and processing the dataset was done with Elba and ToscanaJ, some FCA tools and Conceptual Information System (CIS).</abstract>

Formal concept analysis for amino acids classification and visualization

<abstract xmlns="http://www.w3.org/1999/xhtml">Behavioural biometrics provides an extra layer of security for user authentication mechanisms. Among behavioural biometrics, mouse dynamics provides a non-intrusive layer of security. In this paper we propose a novel convolutional neural network for extracting the features from the time series of users’ mouse movements. The effect of two preprocessing methods on the performance of the proposed architecture were evaluated. Different training types of the model, namely transfer learning and training from scratch, were investigated. Results for both authentication and identification systems are reported. The Balabit public data set was used for performance evaluation, however for transfer learning we used the DFL data set. Comprehensive experimental evaluations suggest that our model performed better than other deep learning models. In addition, transfer learning contributed to the better performance of both identification and authentication systems.</abstract>

Sapientia Hungarian University of Transylvania

Mouse dynamics based user recognition using deep learning

<abstract xmlns="http://www.w3.org/1999/xhtml">Using software applications or services, which provide word or even word pattern recommendation service has become part of our lives. Those services appear in many form in our daily basis, just think of our smartphones keyboard, or Google search suggestions and this list can be continued. With the help of these tools, we can not only find the suitable word that fits into our sentence, but we can also express ourselves in a much more nuanced, diverse way. To achieve this kind of recommendation service, we use an algorithm which is capable to recommend word by word pattern queries. Word pattern queries, can be expressed as a combination of words, part-of-speech (POS) tags and wild card words. Since there are a lot of possible patterns and sentences, we use Big Data frameworks to handle this large amount of data. In this paper, we compared two popular framework Hadoop and Spark with the proposed algorithm and recommend some enhancement to gain faster word pattern generation.</abstract>

Word pattern prediction using Big Data frameworks

<abstract xmlns="http://www.w3.org/1999/xhtml">Closing a deal in a business to business environment implies a series of orchestrated actions that the sales representatives are taking to take a prospective buyer from first contact to a closed sale. The actions, such as meetings, emails, phone calls happen in succession and in different points in time relative to the first interaction.Time-series are ordered sequences of discrete-time data. In this work, we are examining the relationship between the actions as time series and the final win outcome for each deal. To assess whether the behavior of the salespeople have a direct influence on the final outcome of the current deal, we used histogram analysis, dynamic time warping and string edit distance on a real-world Customer Relationship Management System data set. The results are discussed and included in this paper.</abstract>

Opportunity activity sequence investigations in B2B CRM systems

<abstract xmlns="http://www.w3.org/1999/xhtml">Let R be a commutative ring with Z*(R) as the set of non-zero zero divisors. The zero divisor graph of R, denoted by Γ(R), is the graph whose vertex set is Z*(R), where two distinct vertices x and y are adjacent if and only if xy = 0. In this paper, we investigate the metric dimension dim(Γ(R)) and upper dimension dim+(Γ(R)) of zero divisor graphs of commutative rings. For zero divisor graphs Γ(R) associated to finite commutative rings R with unity 1 ≠ 0, we conjecture that dim+(Γ(R)) = dim(Γ(R)), with one exception that <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ausi-2020-0006_eq_001.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mrow><mtext>R</mtext><mo>≅</mo><mi>Π</mi><msubsup><mrow><mtext>𝕑</mtext></mrow><mn>2</mn><mtext>n</mtext></msubsup></mrow></math><tex-math>{\rm{R}} \cong \Pi {\rm\mathbb{Z}}_2^{\rm{n}}</tex-math></alternatives></inline-formula>, n ≥ 4. We prove that this conjecture is true for several classes of rings. We also provide combinatorial formulae for computing the metric and upper dimension of zero divisor graphs of certain classes of commutative rings besides giving bounds for the upper dimension of zero divisor graphs of rings.</abstract>

Metric and upper dimension of zero divisor graphs associated to commutative rings

<abstract xmlns="http://www.w3.org/1999/xhtml">A common assumption about neural networks is that they can learn an appropriate internal representation on their own, see e.g. end-to-end learning. In this work we challenge this assumption. We consider two simple tasks and show that the state-of-the-art training algorithm fails, although the model itself is able to represent an appropriate solution. We will demonstrate that encouraging an appropriate internal representation allows the same model to solve these tasks. While we do not claim that it is impossible to solve these tasks by other means (such as neural networks with more layers), our results illustrate that integration of domain knowledge in form of a desired internal representation may improve the generalization ability of neural networks.</abstract>

Encouraging an appropriate representation simplifies training of neural networks

<abstract xmlns="http://www.w3.org/1999/xhtml">The paper focuses on providing an insight into the current state of computational modeling regarding reactive magnetron sputtering systems. A detailed compilation of developed models is gathered and grouped into categories based on the phenomena being modeled. The survey covers models developed for the analysis of magnetron discharges, particle-surface interactions at the target and the substrate, as well as macroscopic models. Corresponding software packages available online are also presented. After gaining the necessary insight into the current state of research, a list of the most challenging tasks is given, comparing diffierent approaches, that have been used to combat the encountered difficulties. The challenges associated with modeling tasks range from analytical complexity, mathematical know-how used for model approximation and reduction, as well as optimization between computational load and result accuracy. As a conclusion, the future challenges are compiled into a list and a probable direction in modeling is given, that is likely to be further pursued.</abstract>

Doctoral School of Applied Informatics and Applied Mathematics

Modeling reactive magnetron sputtering: a survey of different modeling approaches

<abstract xmlns="http://www.w3.org/1999/xhtml">Given a graph G = (V, E), with respect to a vertex partition 𝒫 we associate a matrix called 𝒫-matrix and define the 𝒫-energy, E𝒫 (G) as the sum of 𝒫-eigenvalues of 𝒫-matrix of G. Apart from studying some properties of 𝒫-matrix, its eigenvalues and obtaining bounds of 𝒫-energy, we explore the robust(shear) 𝒫-energy which is the maximum(minimum) value of 𝒫-energy for some families of graphs. Further, we derive explicit formulas for E𝒫 (G) of few classes of graphs with different vertex partitions.</abstract>

prajaktabharat.joshi@res.christuniversity.in

𝒫-energy of graphs

AHEAD OF PRINT

Volume 15 (2023): Issue 2 (December 2023)

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Acta Universitatis Sapientiae, Informatica

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