rss_2.0Acta Universitatis Sapientiae, Informatica FeedSciendo RSS Feed for Acta Universitatis Sapientiae, Informatica Universitatis Sapientiae, Informatica 's Cover Laplacian spectrum of unitary Cayley graphs<abstract> <title style='display:none'>Abstract</title> <p>Let R be a commutative ring with unity 1 ≠ 0 and let R<sup>×</sup> be the set of all unit elements of R. The unitary Cayley graph of R, denoted by G<sub>R</sub> = Cay(R, R<sup>×</sup>), is a simple graph whose vertex set is R and there is an edge between two distinct vertices x and y of R if and only if x − y ∈ R<sup>×</sup>. In this paper, we determine the Laplacian and signless Laplacian eigenvalues for the unitary Cayley graph of a commutative ring. Also, we compute the Laplacian and signless Laplacian energy of the graph G<sub>R</sub> and its line graph.</p> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00Vertex stress related parameters for certain Kneser graphs<abstract> <title style='display:none'>Abstract</title> <p>This paper presents results for some vertex stress related parameters in respect of specific subfamilies of Kneser graphs. Kneser graphs for which diam(KG(n, k)) = 2 and k ≥ 2 are considered. The note establishes the foundation for researching similar results for Kneser graphs for which diam(KG(n, k)) ≥ 3. In addition some important vertex stress related properties are stated. Finally some results for specific bipartite Kneser graphs i.e. BK(n, 1), n ≥ 3 will be presented. In the conclusion some worthy research avenues are proposed.</p> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00Nonlinearity of the non-Abelian lattice gauge field theory according to the spectrum of Kolmogorov-Sinai entropy and complexity<abstract> <title style='display:none'>Abstract</title> <p>The quark-gluon plasma is written by the non-Abelian gauge theory. The dynamics of the gauge SU(2) are given by the Hamiltonian function, which contains the quadratic part of the field strength tensor <inline-formula> <alternatives> <inline-graphic xmlns:xlink="" xlink:href="graphic/j_ausi-2021-0018_ineq_001.png"/> <mml:math xmlns:mml="" display="inline"><mml:mrow><mml:msubsup><mml:mtext>F</mml:mtext><mml:mrow><mml:mi>μ</mml:mi><mml:mi>v</mml:mi></mml:mrow><mml:mtext>a</mml:mtext></mml:msubsup></mml:mrow></mml:math> <tex-math>{\rm{F}}_{\mu v}^{\rm{a}}</tex-math> </alternatives> </inline-formula> expressed in Minkowski space. The homogeneous Yang-Mills equations are solved on lattice N<sup>d</sup> considering classical approximation, which exhibits chaotic dynamics. We research the time-dependent entropy-energy relation, which can be shown by the energy spectrum of Kolmogorov-Sinai entropy and the spectra of the statistical complexity.</p> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00Dual quaternion-based osculating circle algorithm for finding intersection curves<abstract> <title style='display:none'>Abstract</title> <p>The intersection of surfaces is a fundamental process in computational geometry and computer-aided design applications to build and interrogate complex shapes in the computer. This paper presents a novel and simple dual quaternion-based osculating circle DQOC algorithm to find the intersection curve of two regular surfaces based on the osculating circle concept and dual quaternions. Additionally, we expressed the natural equations of the intersection curve. We have also demonstrated the superiority of our method through numerical examples.</p> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00On A-energy and S-energy of certain class of graphs<abstract> <title style='display:none'>Abstract</title> <p>Let A and S be the adjacency and the Seidel matrix of a graph G respectively. A-energy is the ordinary energy E(G) of a graph G defined as the sum of the absolute values of eigenvalues of A. Analogously, S-energy is the Seidel energy E<sub>S</sub>(G) of a graph G defined to be the sum of the absolute values of eigenvalues of the Seidel matrix S. In this article, certain class of A-equienergetic and S-equienergetic graphs are presented. Also some linear relations on A-energies and S-energies are given.</p> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00Reproducibility in the technical debt domain<abstract> <title style='display:none'>Abstract</title> <sec><title style='display:none'>Context</title><p>It is crucial to understand how reproducible the measurement results in the scientific publications are, as reproducibility is one of the cornerstones of engineering.</p></sec> <sec><title style='display:none'>Objective</title><p>The goal of this study is to investigate the scientific publications presented at the premier technical debt conferences by understanding how reproducible the reported findings are.</p></sec> <sec><title style='display:none'>Method</title><p>We conducted a systematic literature review of 135 unique papers published at the “International Workshop on Managing Technical Debt” and the “International Conference on Managing Technical Debt”, the premier scientific conference series on technical debt.</p></sec> <sec><title style='display:none'>Results</title><p>Only 44 of the investigated 135 papers presented numerical evidence and only 5 papers listed the tools, the availability of the tools, and the version of the tools used. For the rest of the papers additional information would have been needed for the potential reproducibility. One of the published papers even referred to a pornographic site as a source of a toolset for empirical research.</p></sec> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00Bitcoin daily close price prediction using optimized grid search method<abstract> <title style='display:none'>Abstract</title> <p>Cryptocurrencies are digital assets that can be stored and transferred electronically. Bitcoin (BTC) is one of the most popular cryptocurrencies that has attracted many attentions. The BTC price is considered as a high volatility time series with non-stationary and non-linear behavior. Therefore, the BTC price forecasting is a new, challenging, and open problem. In this research, we aim the predicting price using machine learning and statistical techniques. We deploy several robust approaches such as the Box-Jenkins, Autoregression (AR), Moving Average (MA), ARIMA, Autocorrelation Function (ACF), Partial Autocorrelation Function (PACF), and Grid Search algorithms to predict BTC price. To evaluate the performance of the proposed model, Forecast Error (FE), Mean Forecast Error (MFE), Mean Absolute Error (MAE), Mean Squared Error (MSE), as well as Root Mean Squared Error (RMSE), are considered in our study.</p> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00Trading sparse, mean reverting portfolios using VAR(1) and LSTM prediction<abstract> <title style='display:none'>Abstract</title> <p>We investigated the predictability of mean reverting portfolios and the VAR(1) model in several aspects. First, we checked the dependency of the accuracy of VAR(1) model on different data types including the original data itself, the return of prices, the natural logarithm of stock and on the log return. Then we compared the accuracy of predictions of mean reverting portfolios coming from VAR(1) with different generative models such as VAR(1) and LSTM for both online and o ine data. It was eventually shown that the LSTM predicts much better than the VAR(1) model. The conclusion is that the VAR(1) assumption works well in selecting the mean reverting portfolio, however, LSTM is a better choice for prediction. With the combined model a strategy with positive trading mean profit was successfully developed. We found that online LSTM outperforms all VAR(1) predictions and results in a positive expected profit when used in a simple trading algorithm.</p> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00DP-solver: automating dynamic programming<abstract> <title style='display:none'>Abstract</title> <p>Dynamic programming (DP) is a widely used optimization method with several applications in various fields of science. The DP problem solving process can be divided in two phases: mathematical part and programming part. There are a number of researchers for whom the mathematical part is available, but they are not familiar with computer programming. In this paper we present a software tool that automates the programming part of DP and allows users to solve problems based only on their mathematical approach. The application builds up the “d-graph model” of the problem to be solved and applies the “d-variant” of the corresponding single source shortest path algorithm. In addition, we report experimental results regarding the e ciency of the tool relative to the Matlab implementation.</p> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00Incremental methods for community detection in both fully and growing dynamic networks<abstract> <title style='display:none'>Abstract</title> <p>In recent years, community detection in dynamic networks has received great interest. Due to its importance, many surveys have been suggested. In these surveys, the authors present and detail a number of methods that identify a community without taking into account the incremental methods which, in turn, also take an important place in dynamic community detection methods. In this survey, we provide a review of incremental approaches to community detection in both fully and growing dynamic networks. To do this, we have classified the methods according to the type of network. For each type of network, we describe three main approaches: the first one is based on modularity optimization; the second is based on density; finally, the third is based on label propagation. For each method, we list the studies available in the literature and state their drawbacks and advantages.</p> </abstract>ARTICLE2022-02-02T00:00:00.000+00:00Towards autoscaling of Apache Flink jobs<abstract> <title style='display:none'>Abstract</title> <p>Data stream processing has been gaining attention in the past decade. Apache Flink is an open-source distributed stream processing engine that is able to process a large amount of data in real time with low latency. Computations are distributed among a cluster of nodes. Currently, provisioning the appropriate amount of cloud resources must be done manually ahead of time. A dynamically varying workload may exceed the capacity of the cluster, or leave resources underutilized. In our paper, we describe an architecture that enables the automatic scaling of Flink jobs on Kubernetes based on custom metrics, and describe a simple scaling policy. We also measure the e ects of state size and target parallelism on the duration of the scaling operation, which must be considered when designing an autoscaling policy, so that the Flink job respects a Service Level Agreement.</p> </abstract>ARTICLE2021-07-08T00:00:00.000+00:00Animal Farm—a complex artificial life 3D framework<abstract> <title style='display:none'>Abstract</title> <p>The development of computer-generated ecosystem simulations are becoming more common due to the greater computational capabilities of machines. Because natural ecosystems are very complex, simplifications are required for implementation. This simulation environment o er a global view of the system and generate a lot of data to process and analyse, which are difficult or impossible to do in nature. 3D simulations, besides of the scientific advantages in experiments, can be used for presentation, educational and entertainment purposes too. In our simulated framework (Animal Farm) we have implemented a few basic animal behaviors and mechanics to observe in 3D. All animals are controlled by an individual logic model, which determines the next action of the animal, based on their needs and surrounding environment.</p> </abstract>ARTICLE2021-07-08T00:00:00.000+00:00Confluence number of certain derivative graphs<abstract> <title style='display:none'>Abstract</title> <p>This paper furthers the study on the confluence number of a graph. In particular results for certain derivative graphs such as the line graph of trees, cactus graphs, linear Jaco graphs and novel graph operations are reported.</p> </abstract>ARTICLE2021-07-08T00:00:00.000+00:00Differential privacy based classification model for mining medical data stream using adaptive random forest<abstract> <title style='display:none'>Abstract</title> <p>Most typical data mining techniques are developed based on training the batch data which makes the task of mining the data stream represent a significant challenge. On the other hand, providing a mechanism to perform data mining operations without revealing the patient’s identity has increasing importance in the data mining field. In this work, a classification model with differential privacy is proposed for mining the medical data stream using Adaptive Random Forest (ARF). The experimental results of applying the proposed model on four medical datasets show that ARF mostly has a more stable performance over the other six techniques.</p> </abstract>ARTICLE2021-07-08T00:00:00.000+00:00Estimating the fractional chromatic number of a graph<abstract> <title style='display:none'>Abstract</title> <p>The fractional chromatic number of a graph is defined as the optimum of a rather unwieldy linear program. (Setting up the program requires generating all independent sets of the given graph.) Using combinatorial arguments we construct a more manageable linear program whose optimum value provides an upper estimate for the fractional chromatic number. In order to assess the feasibility of the proposal and in order to check the accuracy of the estimates we carry out numerical experiments.</p> </abstract>ARTICLE2021-07-08T00:00:00.000+00:00Improving productivity in large scale testing at the compiler level by changing the intermediate language from C++ to Java<abstract> <title style='display:none'>Abstract</title> <p>This paper is based on research results achieved by a collaboration between Ericsson Hungary Ltd. and the Large Scale Testing Research Lab of Eötvös Loránd University, Budapest. We present design issues and empirical observations on extending an existing industrial toolset with a new intermediate language<sup>1</sup>.</p> <p>Context: The industry partner’s toolset is using C/C++ as an intermediate language, providing good execution performance, but “somewhat long” build times, o ering a sub-optimal experience for users.</p> <p>Objective: In cooperation with our industry partner our task was to perform an experiment with Java as a different intermediate language and evaluate results, to see if this could improve build times.</p> <p>Method: We extended the mentioned toolset to use Java as an intermediate language.</p> <p>Results: Our measurements show that using Java as an intermediate language improves build times significantly. We also found that, while the runtime performance of C/C++ is better in some situations, Java, at least in our testing scenarios, can be a viable alternative to improve developer productivity.</p> <p>Our contribution is unique in the sense that both ways of building and execution can use the same source code as input, written in the same language, generate intermediate codes with the same high-level structure, compile into executables that are configured using the same files, run on the same machine, show the same behaviour and generate the same logs.</p> <p>Conclusions: We created an alternative build pipeline that might enhance the productivity of our industry partner’s test developers by reducing the length of builds during their daily work.</p> </abstract>ARTICLE2021-07-08T00:00:00.000+00:00Fog-LAEEBA: Fog-assisted Link aware and energy efficient protocol for wireless body area network<abstract> <title style='display:none'>Abstract</title> <p>The integration of Wireless Sensor Networks (WSN) and cloud computing brings several advantages. However, one of the main problems with the existing cloud solutions is the latency involved in accessing, storing, and processing data. This limits the use of cloud computing for various types of applications (for instance, patient health monitoring) that require real-time access and processing of data. To address the latency problem, we proposed a fog-assisted Link Aware and Energy E cient Protocol for Wireless Body Area Networks (Fog-LAEEBA). The proposed solution is based on the already developed state-of-the-art protocol called LAEEBA. We implement, test, evaluate and compare the results of Fog-LAEEBA in terms of stability period, end-to-end delay, throughput, residual energy, and path-loss. For the stability period all nodes in the LAEEBA protocol die after 7445 rounds, while in our case the last node dies after 9000 rounds. For the same number of rounds, the end-to-end delay is 2 seconds for LAEEBA and 1.25 seconds for Fog-LAEEBA. In terms of throughput, our proposed solution increases the number of packets received by the sink node from 1.5 packets to 1.8 packets. The residual energy of the nodes in Fog-LAEEBA is also less than the LAEEBA protocol. Finally, our proposed solution improves the path loss by 24 percent.</p> </abstract>ARTICLE2021-07-08T00:00:00.000+00:00On ordering of minimal energies in bicyclic signed graphs<abstract> <title style='display:none'>Abstract</title> <p>Let S = (G, σ) be a signed graph of order n and size m and let x<sub>1</sub>, x<sub>2</sub>, ..., x<sub>n</sub> be the eigenvalues of S. The energy of S is defined as <inline-formula> <alternatives> <inline-graphic xmlns:xlink="" xlink:href="graphic/j_ausi-2021-0005_eq_001.png"/> <mml:math xmlns:mml="" display="inline"><mml:mrow><mml:mi>ɛ</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>S</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo>=</mml:mo><mml:munderover><mml:mo>∑</mml:mo><mml:mrow><mml:mi>j</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>n</mml:mi></mml:munderover><mml:mrow><mml:mrow><mml:mo>|</mml:mo> <mml:mrow><mml:msub><mml:mrow><mml:mi>x</mml:mi></mml:mrow><mml:mi>j</mml:mi></mml:msub></mml:mrow> <mml:mo>|</mml:mo></mml:mrow></mml:mrow></mml:mrow></mml:math> <tex-math>\varepsilon \left( S \right) = \sum\limits_{j = 1}^n {\left| {{x_j}} \right|}</tex-math> </alternatives> </inline-formula>. A connected signed graph is said to be bicyclic if m=n + 1. In this paper, we determine the bicyclic signed graphs with first 20 minimal energies for all n ≥ 30 and with first 16 minimal energies for all 17 ≤ n ≤ 29.</p> </abstract>ARTICLE2021-07-08T00:00:00.000+00:00Statistical complexity of the kicked top model considering chaos<abstract><title style='display:none'>Abstract</title><p>The concept of the statistical complexity is studied to characterize the classical kicked top model which plays important role in the qbit systems and the chaotic properties of the entanglement. This allow us to understand this driven dynamical system by the probability distribution in phase space to make distinguish among the regular, random and structural complexity on finite simulation. We present the dependence of the kicked top and kicked rotor model through the strength excitation in the framework of statistical complexity.</p></abstract>ARTICLE2021-01-29T00:00:00.000+00:00Enhanced type inference for binding-time analysis<abstract><title style='display:none'>Abstract</title><p>In this paper we will be taking a look at type inference and its uses for binding-time analysis, dynamic typing and better error messages. We will propose a new binding-time analysis algorithm ℬ, which is a modification of an already existing algorithm by Gomard [4], and discuss the speed difference.</p></abstract>ARTICLE2021-01-29T00:00:00.000+00:00en-us-1