Regular Issue Research Articles

Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)

Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)

Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)

Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)

Editorial

Dear Readers, It gives me great pleasure to announce the tenth regular issue of 2024. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research. Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to introduce six accepted papers involving 17 authors from six different countries (Argentina, Brazil, Ecuador, Hong Kong, India, Saudi Arabia). Álex dos Santos Moura, Fábio Gomes Rocha, and Michel S. Soares from Brazil propose in their research a recommendation tool based on information retrieval to assist developers in choosing the suitable microservices pattern to solve a given problem. In a collaborative research effort between Ecuador and Argentina, Gonzalo P. Espinel-Mena, José L. Carrillo-Medina, Eddie E. Galarza, and Mario Matias Urbieta discuss a systematic mapping of configuration management activities in software product line. Edward Kai Fung Dang, Robert Wing Pong Luk, and Qing Li from Hong Kong contribute to the forum for negative results with their study on word bigrams for pseudo-relevance feedback in information retrieval. Prateek Thakral and Yugal Kumar from India present in their work an improved water flow optimizer (IWFO) algorithm for cluster analysis that can address the issues of traditional and heuristic algorithms. Samit Bhanja, Banani Ghose, and Abhishek Das from India highlight their findings on multi-step-ahead time series forecasting using a deep learning and fuzzy time series-based error correction method. And last but not least, Abdullilah A. Alotaibi and Salman A. AlQahtani from Saudi Arabia present in their research an intelligent distributed channel selection framework with hybrid mode selection for interference mitigation in D2D based 5G networks.  Enjoy Reading! Best regards,  Christian Gütl, Managing Editor Graz University of Technology, Graz, Austria

Stabilisation of linear waves with inhomogeneous Neumann boundary conditions

ABSTRACT We study linear damped and viscoelastic wave equations evolving on a bounded domain. For both models, we assume that waves are subject to an inhomogeneous Neumann boundary condition on a portion of the domain's boundary. The analysis of these models presents additional interesting features and challenges compared to their homogeneous counterparts. In the present context, energy depends on the boundary trace of velocity. It is not clear in advance how this quantity should be controlled based on the given data, due to regularity issues. However, we establish global existence and also prove uniform stabilisation of solutions with decay rates characterised by the Neumann input. We supplement these results with numerical simulations in which the data do not necessarily satisfy the given assumptions for decay. These simulations provide, at a numerical level, insights into how energy could possibly change in the presence of, for example, improper data.

Navier-Stokes: Singularities and Bifurcations

This article presents substantial advances in the analysis of the Navier-Stokes equations for both compressible and incompressible fluids, focusing on the formation of singularities, hypercomplex bifurcations, and regularity in Sobolev and Besov spaces. Through new theorems, we extend the theory of singularities in fluid dynamics and introduce quaternionic bifurcations, representing an innovative extension of classical bifurcation theory. Moreover, we delve into the investigation of the regularity of compressible fluids, exploring the conditions under which solutions remain smooth or develop singularities. These contributions are fundamental to the understanding of global regularity issues, directly linked to the renowned Millennium Prize problem, which seeks definitive answers on the existence and smoothness of solutions to the Navier-Stokes equations. Additionally, we discuss how these theoretical advancements offer new approaches to unresolved problems related to the formation of singularities in turbulent flows and the multiscale behavior of solutions, which are crucial for a comprehensive understanding of fluid dynamics. This work not only broadens the scope of traditional mathematical analysis of the Navier-Stokes equations but also establishes a robust theoretical framework for the investigation of bifurcations and regularity in advanced functional spaces, fostering a deeper understanding of global regularity phenomena and the complex dynamics governing fluid systems.

Enhancing accuracy and robustness in FBS decoupling through Tikhonov regularization and unit balancing

Frequency-based Substructuring (FBS) enables the prediction of transfer functions for an assembled system based on those of a single-unit system. Conversely, FBS decoupling derives the frequency response function (FRF) of a single-unit system from the assembled system. This approach is valuable when obtaining the transfer functions of a system is challenging due to boundary conditions and deformation conditions. FBS decoupling can enhance accuracy by using additional indicator sensors. However, this often results in significant noise due to the ill-posed FRF matrix inversion. In this paper, Tikhonov regularization is employed to reduce noise-induced errors. Furthermore, this paper addresses the issue of inadequate Tikhonov regularization caused by the inherent scaling differences between the rotational and translational components within the FRF matrix. To rectify this challenge, a unit balancing method is proposed to mitigate the influence of scaling differences. This method enhances the accuracy and reliability of FRF matrix inversion processes, contributing to enhanced noise reduction and robustness in practical applications.

Laplacian operator and its square lattice discretization: Green function vs. Lattice Green function for the flat 2-torus and other related 2D manifolds

Abstract The paper investigates the truncation error between the Green function and the lattice Green function (LGF) for the Laplacian operator defined on the 2-torus and its discretization on a regular square lattice. Extensions to the cylinder and the rectangular domain with free (or Neumann) boundary conditions are also proposed. In each of these instances, the Green function and its discrete analog are given in exact analytical closed-form allowing to infer accurate estimates as the lattice spacing tends to zero. As expected, it is shown that the continuum limit of the LGF coincides well with the Green function in every case. In particular, the issue of logarithmic singularity regularization of the Green function by the lattice discretization is addressed through two related application examples regarding the rectangular domain, and devoted to the computation of corner-to-corner resistance of an electrical conducting square and the mean first-passage time between the diagonally opposite vertices of a square for a standard Brownian motion, both derived considering the continuum limit.

Do conference-journal articles receive more citations? A case study in physics

Conference-journal articles, which are expanded versions of conference proceedings papers, play an essential role in disseminating scientific knowledge but remain understudied. In the context of increasingly stringent research evaluation systems, this study focuses on conference-journal articles, examining the effectiveness of journals in selecting conference-derived publications. We also explore the factors influencing the citations of conference-journal articles. Here, we focused on Physics, analyzing 59,329 conference-journal articles published between 2012 and 2020, matched with general journal articles and conference proceedings papers based on the conference and journal. Results show that conference-journal articles receive significantly more citations than conference proceedings papers but fewer than general journal articles. Conference-journal articles in special issues receive fewer citations than those in regular issues. A U-shaped pattern emerges between the duration from the conference convening to the journal publication and the citation. We also found that conferences with sponsorship and those held in OECD member countries are more likely to produce highly cited conference-journal articles. Additionally, results indicate that conferences held in the USA, Japan, France, China, and Poland produce the most conference-journal articles, with articles from conferences in the USA, Japan, and France receiving relatively high citation counts. In contrast, articles from conferences held in China and Poland receive relatively low citation counts. This research provides valuable insights for academic conference committees, journal managers, and conference participants.

Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)

Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)

Another remark on the global regularity issue of the Hall-magnetohydrodynamics system

Another remark on the global regularity issue of the Hall-magnetohydrodynamics system

Lipschitz regularity of a weakly coupled vectorial almost-minimizers for the p-Laplacian

For a given constant λ>0 and a bounded Lipschitz domain D⊂Rn (n≥2), we establish that almost-minimizers of the functionalJ(v;D)=∫D∑i=1m|∇vi(x)|p+λχ{|v|>0}(x)dx,1<p<∞, where v=(v1,⋯,vm), and m∈N, exhibit optimal Lipschitz continuity in compact sets of D. Furthermore, assuming p≥2 and employing a distinctly different methodology, we tackle the issue of boundary Lipschitz regularity for v. This approach simultaneously yields an alternative proof for the optimal local Lipschitz regularity for the interior case.

MATLAB Implementation of Physics Informed Deep Neural Networks for Forward and Inverse Structural Vibration Problems

In this work, we illustrate the implementation of physics informed neural networks (PINNs) for solving forward and inverse problems in structural vibration. Physics informed deep learning has lately proven to be a powerful tool for the solution and data-driven discovery of physical systems governed by differential equations. In spite of the popularity of PINNs, their application in structural vibrations is limited. This motivates the extension of the application of PINNs in yet another new domain and leverages from the available knowledge in the form of governing physical laws. On investigating the performance of conventional PINNs in vibrations, it is mostly found that it suffers from a very recently pointed out similar scaling or regularization issue, leading to inaccurate predictions. It is thereby demonstrated that a simple strategy of modifying the loss function helps to combat the situation and enhance the approximation accuracy significantly without adding any extra computational cost. In addition to the above two contributing factors of this work, the implementation of the conventional and modified PINNs is performed in the MATLAB environment owing to its recently developed rich deep learning library. Since all the developments of PINNs till date is Python based, this is expected to diversify the field and reach out to greater scientific audience who are more proficient in MATLAB but are interested to explore the prospect of deep learning in computational science and engineering. As a bonus, complete executable codes of all four representative (both forward and inverse) problems in structural vibrations have been provided along with their line-by-line lucid explanation and well-interpreted results for better understanding.

Editorial

Dear Readers, It gives me great pleasure to announce the seventh regular issue of 2024. In this issue, 5 papers by 12 authors from 6 countries - Brazil, Ecuador, Germany, Iraq, Spain, Turkey - cover various topical aspects of computer science. In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. As always, I would like to thank all the authors for their sound research and the editorial board and guest reviewers for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest in our articles, which is reflected in the consistently high number of user accesses and PDF downloads. These contributions, together with the generous support of the consortium members, maintain the quality of our journal. In the seventh regular issue, I am very pleased to present the following 5 accepted articles: Vinicius Bischoff and Kleinner Farias from Brazil report their study on a controlled experiment with 22 participants (15 students, 7 professionals) in which the correctness and the effort required for the integration of feature models were investigated. Abdulkadir Buldu, Kaplan Kaplan and Melih Kuncan from Turkey present their research on an assistive system based on EEG data and Continuous Wavelet Transform (CWT), which aims to reduce the life-threatening risk for epilepsy patients. In a collaboration between researchers from Ecuador and Spain, Darwin Alulema, Maximiliano Paredes-Velasco and Ricardo de Arriba Lasso report in their manuscript on the LESCA system, which performs adaptive content feedback through scaffolding and supports the development of high-level competencies. In another joint research between colleagues from Iraq and Germany, Anwar Mira and Olaf Hellwich present their approach to improve recognition capabilities by optimizing deep learning features for hand gesture image recognition. Specifically, they propose to enhance features of well-trained DNNs using an improved radial basis function (RBF) neural network, targeting recognition within individual gesture categories. And last but not least, Rasim &amp;Ccedil;ekik and Mahmut Kaya from Turkey propose in their research a new performance metric to evaluate filter feature selection methods in text classification.&amp;nbsp; Enjoy Reading! Best regards,&amp;nbsp; Christian G&amp;uuml;tl, Managing Editor&amp;nbsp;

Editorial

Dear Readers, It gives me great pleasure to announce the sixth regular issue of 2024. In this issue, 6 papers cover various topical aspects of computer science by 19 authors from 7 countries: Brazil, Chile, France, India, Saudi Arabia, Tunisia, and Turkey. In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends. As always, I would like to thank all authors for their sound research and the editorial board and our guest reviewers for their extremely valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, help to maintain the quality of our journal.&amp;nbsp; In this regular issue, I am very pleased to introduce the following 6 accepted articles: George Marsicano, Edna Dias Canedo, Glauco V. Pedrosa, Cristiane S. Ramos, and Rejane M. da C. Figueiredo from Brazil look in their study into digital transformation of public services in a startup-based environment by 23 focus groups and 175 participants in total. Mauricio Solar and Pablo Aguirre from Chile discuss their research on 3D chest CT processes applying a ResNet-50 model to which a new dimension of information has been added, namely a simple autoencoder. In a collaborative work between researchers from Tunisia and France, Rakia Saidi, Fethi Jarray, and Didier Schwab propose in their article a cross-encoder neural network (Cross-BERT-GRU) to deal with the semantic similarity of Arabic sentences that benefits from both the strong contextual understanding of BERT and the sequential modeling capabilities of GRU. Also in a collaborative research between institutions from Tunisia and Saudi Arabia, Nozha Jlidi, Sameh Kouni, Olfa Jemai, and Tahani Bouchrika present their research on MediaPipe with GNN for human activity recognition. G.V.Vidya Lakshmi and S. Gopikrishnan from India look into missing values research for the IoT domain and in particular present IMD-MP technique that improves imputation accuracy for big data analysis in IoT applications based on spatial-temporal correlations. Last but not least, F. Didem Alay, Nagehan &amp;#304;lhan, and M. Tahir G&amp;uuml;ll&amp;uuml;o&amp;#287;lu address in their article a comparative study of data mining methods for solar radiation and temperature forecasting models. Enjoy Reading Cordially,&amp;nbsp; Christian G&amp;uuml;tl, Managing Editor Graz University of Technology, Graz, Austria

A novel discretized physics-informed neural network model applied to the Navier–Stokes equations

The advancement of scientific machine learning (ML) techniques has led to the development of methods for approximating solutions to nonlinear partial differential equations (PDE) with increased efficiency and accuracy. Automatic differentiation has played a pivotal role in this progress, enabling the creation of physics-informed neural networks (PINN) that integrate relevant physics into machine learning models. PINN have shown promise in approximating the solutions to the Navier–Stokes equations, overcoming the limitations of traditional numerical discretization methods. However, challenges such as local minima and long training times persist, motivating the exploration of domain decomposition techniques to improve it. Previous domain decomposition models have introduced spatial and temporal domain decompositions but have yet to fully address issues of smoothness and regularity of global solutions. In this study, we present a novel domain decomposition approach for PINN, termed domain-discretized PINN (DD-PINN), which incorporates complementary loss functions, subdomain-specific transformer networks (TRF), and independent optimization within each subdomain. By enforcing continuity and differentiability through interface constraints and leveraging the Sobolev (H 1) norm of the mean squared error (MSE), rather than the Euclidean norm (L 2), DD-PINN enhances solution regularity and accuracy. The inclusion of TRF in each subdomain facilitates feature extraction and improves convergence rates, as demonstrated through simulations of threetest problems: steady-state flow in a two-dimensional lid-driven cavity, the time-dependent cylinder wake, and the viscous Burgers equation. Numerical comparisons highlight the effectiveness of DD-PINN in preserving global solution regularity and accurately approximating complex phenomena, marking a significant advancement over previous domain decomposition methods within the PINN framework.

A Culture of Knowledge Sharing: Information Resources and Dissemination Practices for All

Volume 8, Issue 1 of The International Journal of Information, Diversity &amp; Inclusion (IJIDI). This introductory article presents the theme, “A Culture of Knowledge Sharing,” which we have identified as a common thread that weaves the papers featured in this regular issue. These papers cover knowledge sharing in research, literature reviews, and reports from the field discussing topics such as ways Hebrew children’s literature can bridge cultures in Israel, research from Nigeria examining prison libraries as information resources for rehabilitation, and community-based information projects empowering immigrant women in Canada. The papers in this issue highlight how knowledge sharing impacts citizens' information behaviors worldwide. Two book reviews are featured.

Editorial

Dear Readers,&amp;nbsp; It gives me great pleasure to announce the fourth regular issue of 2024. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research. I am also very proud to announce that our journal has been included in the Free Journal Network as one of the listed high-quality journals in this field. Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends. In this regular issue, I am very pleased to introduce six papers by 22 authors from nine countries: Brazil, Czech Republic, Germany, Iran, Jordan, Portugal, Thailand, Turkey, and the USA. In a collaboration between researchers from the Czech Republic and Germany, Sivaramasamy Elayaraja, Sunil Yeruva Vlastimil Stejskal, and Satish Nandipati look into multi-class microscopic image analysis of protozoan parasites using convolutional neural network and perform a study on 4740 microscopic images. Andr&amp;eacute; Diegues Fernandes, Jo&amp;atilde;o Cruz, Miguel Mira da Silva, and R&amp;uacute;ben Pereira from Portugal cover a systematic literature review for mapping and integrating security and risk standards. In a collaborative research between Jordan and the USA, Sahar Idwan, Junaid Zubairi, Syed Ali Haider, and Wael Etaiwi introduce their reactive traffic congestion control method based on a hierarchical graph approach. Shahrzad Riahi, Ramtin Khosravi, and Fatemeh Ghassemi from Iran conduct a study on knowledge-related policy analysis in an inference-enabled actor model. Josival Silva, Nelson Rosa, and Fernando Aires from Brazil research and present UP-Home, a self-adaptive solution that manages the security of smart homes by industry standards, and identifies and mitigates smart home security vulnerabilities. Last but not least, Sait Can Yucebas, Sukran Yalpir, Levent Genc, and Melike Dogan from Turkey discuss their research on price prediction and determination of the factors influencing real estate prices using X-Means clustering and CART decision trees. Enjoy Reading! Cordially, Christian G&amp;uuml;tl, Managing Editor Graz University of Technology, Graz, Austria

Raising the bar in spatial economic analysis: two laws of spatial economic modelling

ABSTRACT Based on a prospective and retrospective analysis of the ‘Raising the bar’ editorials preceding regular issues of this journal from 2016–2023, this paper identifies two laws of spatial economic modelling: (i) Units of observation cannot be treated as independent entities because they interact and (ii) interaction causes spillovers from one unit to another. Common themes and trends uncovered in these editorials, the progress that has been made and the direction in which the research fields can continue to develop are discussed, using both laws as references. Currently, there is no single approach that adequately addresses both laws.

Наукова, міжнародна і громадська діяльність товариства у 2023 році

Information on the main results of the activities of the Public Union “Ukrainian Society of Geodesy and Cartography (GS “USGC”)” and the Western Geodetic Society of USGC (WGS USGC) in the difficult conditions of the military state. The main focus is on the professional protection of the country’s geodetic industry, the holding of the Geoforum-2023 MNTC and the support of other MNTCs, the participation of the Society’s delegation in the INTERGEO world congress in Berlin, in the work of the CLGE Assembly in Romania, cooperation with FIG CLGE and professional public societies of various countries, publication of regular issues of the professional journal of HRT, marking of important events in the country, industry, society, collectives, in the life of specialists in Ukraine and abroad, etc.

Editorial

Dear Readers, It gives me great pleasure to announce the third regular issue of 2024. In this issue, 6 papers by 20 authors from 6 countries - China, Ecuador, Spain, The Netherlands, Turkey, United Kingdom - cover various topical aspects of computer science. In a continuous effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in high-quality proposals for special issues on new topics and trends.&amp;nbsp; As always, I would like to thank all the authors for their sound research and the editorial board for their extremely valuable review effort and suggestions for improvement. I also want to thank the readers for their interest on our articles indicated by an increasing access number and PDF downloads. These contributions, together with the generous support of the consortium members, sustain the quality of our journal.&amp;nbsp; In the third regular issue, I am very pleased to introduce the following 6 accepted articles: In a collaboration between researchers from The Netherlands and the United Kingdom, Jan Bergstra and John V. Tucker discuss their research on synthetic fracterm calculus, more specifically they introduce a new intermediate and informal axiomatisation of elementary arithmetic. Yasir Yakup Demircan and Serhat Ozekes from Turkey highlight their research on least significant bit steganography technique based on image segmentation. In a collaborative research effort between Spain and Ecuador, Alberto Jimenez-Macias, Pedro Mu&amp;ntilde;oz-Merino, Margarita Ortiz-Rojas, Mario Mu&amp;ntilde;oz-Organero, and Carlos Delgado-Kloos present their study on a systematic literature review on content modeling using machine learning algorithms in smart learning environments considering content indicators based on student interaction. Melih Kuncan, Kaplan Kaplan, Y&amp;#305;lmaz Kaya, Mehmet Recep Minaz, and H. Metin Ertun&amp;ccedil; from Turkey focus on computer numerical control (CNC) systems, more specifically on classification of CNC vibration speeds by Heralick features. Lifang Ren, Jing Li, and Wenjian Wang from China address in their research support vector regression (SVR) and the location-aware method for mobile QoS prediction to overcome the difficulty caused by the sparsity of data and to predict the unknown QoS more accurately. Last but not least, Emre Sad&amp;#305;ko&amp;#287;lu, &amp;#304;rfan K&amp;ouml;sesoy, and Murat G&amp;ouml;k from Turkey look into the vulnerability of artificial systems to cyber-attacks by applying a gradient descent-based method to generate fake data. Enjoy Reading! Cordially,&amp;nbsp; Christian G&amp;uuml;tl, Managing Editor-in-Chief Graz University of Technology, Graz, Austria