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Parallel self-avoiding walks for a low-autocorrelation binary sequences problem Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-03-07 Borko Bošković, Jana Herzog, Janez Brest
A low-autocorrelation binary sequences problem with a high figure of merit factor represents a formidable computational challenge. An efficient parallel computing algorithm is required to reach the new best-known solutions for this problem. Therefore, we developed the solver for the skew-symmetric search space. The developed solver takes the advantage of parallel computing on graphics processing units
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Analyzing the impact of grid structures on traffic flow optimization in autonomous transport systems Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-03-05 Árpád Török, Gábor Pauer
A fundamental element of a centralized autonomous vehicle control process is the representation of the transport environment. The road surface has to be partitioned to be able to ensure the main safety requirements of the transport process: a vehicle can only be in one place at a time, and only one vehicle can be in one place at a time. The occupancy grid concept is widely used for this purpose; however
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MHD radiative natural convective heat transfer enhancement for Casson nanofluid flow on a horizontal circular cylinder Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-03-04 Muhammad Shoaib, Tariq Javed
The current numerical analysis investigates the sensitivity of heat transfer enhancement in the magnetohydrodynamic radiative natural convection flow of a Casson nanofluid over a cylinder, which has significant ramifications for different fields of science, e.g., biomedical devices, aerospace engineering, nanofluid-based cooling systems, energy harvesting devices, and drag reduction in marine engineering
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Numerical study of hydromagnetic bioconvection flow of micropolar nanofluid past an inclined stretching sheet in a porous medium with gyrotactic microorganism Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-03-01 Zeeshan Khan, Esraa N. Thabet, Shazia Habib, A.M. Abd-Alla, F.S. Bayones, F.M. Alharbi, Afaf S. Alwabli
The present article centers on the examination of novel bioconvection phenomena involving gyrotactic microorganisms and a micropolar nanofluid model with hydro-magnetic flow. The flow traversed a stretchable inclined plate within the permeable medium. Heat absorption and thermal radiation are considered. The objective of this study is to assess the rate of heat transfer exhibited by nanofluid when
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Shock waves generators: From prevention of hail storms to reduction of the smog in urban areas — experimental verification and numerical simulations Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-29 Marcin Łoś, Leszek Siwik, Maciej Woźniak, Dominik Gryboś, Paweł Maczuga, Albert Oliver-Serra, Jacek Leszczyński, Maciej Paszyński
Hail cannoning is a technique of preventing cloud formation before hailstorms by creating a sequence of shock waves. So far, despite numerous experiments, there is no clear evidence that this technique actually works. This paper provides a detailed analysis of the hail cannoning technique and its impact on local weather conditions. Through mathematical modeling, numerical simulations, and systematic
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The Galerkin Bell method to solve the fractional optimal control problems with inequality constraints Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-28 Lakhlifa Sadek, Said Ounamane, Bouchra Abouzaid, El Mostafa Sadek
In this manuscript, we adopt the Caputo fractional derivative approach and employ the Galerkin-Bell method to tackle fractional optimal control problems (FOCPs) with equality and inequality constraints in multi-dimensional settings. We derive the Riemann–Liouville (RL) operational matrix for Bell polynomials to facilitate our analysis. By leveraging these matrices and utilizing the Galerkin method
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The Allen–Cahn equation with a space-dependent mobility and a source term for general motion by mean curvature Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-28 Junxiang Yang, Seungyoon Kang, Soobin Kwak, Junseok Kim
We propose the Allen–Cahn (AC) equation with a space-dependent mobility and a source term for general motion by mean curvature. Using the space-dependent mobility, we can control the temporal evolution dynamics. Furthermore, by using the source term, we can control the growth and shrinkage of the interfaces. To efficiently solve the governing equation, we use an operator splitting method that splits
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A novel collocation approach using Chebyshev wavelets for solving fourth-order Emden-Fowler type equations Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-27 Julee Shahni, Randhir Singh
This research paper presents a new approach using to solve fourth-order Emden-Fowler type equations. To address the singularity issue at , we initially transform the problem into an equivalent Volterra integral equation. The paper establishes the existence and uniqueness of solutions for each integral equation. For numerical solutions, the proposed technique uses an approximation and collocation method
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A robust weak Galerkin finite element method for two parameter singularly perturbed parabolic problems on nonuniform meshes Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-24 Jasbir Singh, Naresh Kumar, Ram Jiwari
In this study, we proposed a weak Galerkin finite element method (WG-FEM) for solving two-parameter singularly perturbed parabolic problems (TP-SPPPs) of convection–diffusion–reaction type on nonuniform mesh. The WG-FEM approach incorporates an interpolation operator and achieves optimal order convergence in an energy-like norm for continuous and fully discrete schemes. In the fully-discrete analysis
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Multilevel optimization for policy design with agent-based epidemic models Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-23 Jan-Hendrik Niemann, Samuel Uram, Sarah Wolf, Nataša Djurdjevac Conrad, Martin Weiser
Epidemiological modeling has a long history and is often used to forecast the course of infectious diseases or pandemics. These models come in different complexities, ranging from systems of simple ordinary differential equations (ODEs) to complex agent-based models (ABMs). The former allow a fast and straightforward optimization, but are limited in accuracy, detail, and parameterization, while the
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Assessment of morphological similarities for the conservative Allen–Cahn and Cahn–Hilliard equations Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-17 Dongsun Lee, Chaeyoung Lee
Phase separations occur in various natural environments, such as materials sciences and biochemistry, and have been scientifically modeled in various fields. We often need to distinguish between two different phase separation phenomena induced by the conservative Allen–Cahn (CAC) and Cahn–Hilliard (CH) equations, which are used to describe natural phenomena. Both phase-field equations share the same
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A Novel Dynamic Decision-Making Method: Addressing the Complexity of Attribute Weight and Time Weight Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-16 Bo Chen, Rui Tong, Xiue Gao, Yufeng Chen
Dynamic decision-making involves many factors, so it should consider both the Fuzzy uncertainty of the target and the time factor of the target information. The most important problem is the solution and combination decision related to attribute weight and time weight. For this purpose, this paper proposes a novel dynamic decision-making method based on attribute weight and time weight. Firstly, based
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FC-RRT⁎: A modified RRT⁎ with rapid convergence in complex environments Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-15 Jing Wang, Junyang Li, Yankui Song, Yaoyao Tuo, Chengguo Liu
The Rapidly-exploring Random Tree algorithm (RRT) is currently the preferred algorithm for solving motion planning problems. It enables fast path generation on a large scale with high-latitude spatial species. RRT⁎ as the optimal variant provides an asymptotically optimal solution and inspires the F-RRT⁎ algorithm, which significantly reduces the path cost but performs poorly in complex environments
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Analyzing categorical time series with the R package ctsfeatures Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-13 Ángel López-Oriona, José A. Vilar
Time series data are ubiquitous nowadays. Whereas most of the literature on the topic deals with real-valued time series, categorical time series have received much less attention. However, the development of data mining techniques for this kind of data has substantially increased in recent years. The package offers users a set of useful tools for analyzing categorical time series. In particular, several
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An exhaustive comparison of distance measures in the classification of time series with 1NN method Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-10 Tomasz Górecki, Maciej Łuczak, Paweł Piasecki
Time series classification is an important and challenging problem in data analysis. With the increase in time series data availability, hundreds of algorithms have been proposed. A huge effort over the past two decades caused a significant improvement in both the efficiency and effectiveness of time series classification. There is a belief in the community that the best method is a surprisingly simple
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The effects of cellular interactions on the sizes, composition, and dynamics of migrating cancer cell clusters Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-10 R, u, i, , Z, h, e, n, , T, a, n
Collective migration plays an important role in metastasis, promoting survival of migrating clusters and increasing malignancy. Hybrid cells in intermediate EMT states have been attributed to be responsible for collective migration. These are cells with both epithelial and mesenchymal characteristics allowing them to migrate while maintaining interactions with other cells. While the benefits of collective
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A physiological mathematical model of the human thyroid Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-10 Marcello Pompa, Andrea De Gaetano, Alessandro Borri, Antonella Farsetti, Simona Nanni, Alfredo Pontecorvi, Simona Panunzi
The thyroid is one of the largest endocrine glands in humans. The thyroid produces two major hormones: thyroxine (T4) and triiodothyronine (T3). The secretion and production of thyroid hormones are controlled via two feedbacks: one positive, where the thyrotropin-releasing hormone (TRH) stimulates the thyroid-stimulating hormone (TSH) that stimulates the production of T3 and T4 hormones; one negative
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Empirical validation of machine learning techniques for heterogeneous cross-project change prediction and within-project change prediction Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-09 Ruchika Malhotra, Shweta Meena
Software change prediction plays key role for maintaining software quality. Identification of change prone parts of a software in early stages helps in optimization of resources and amount of effort required for the maintenance of software. The change prediction model can be built by using the same project for training and testing, which is termed as within-project change prediction. Sometimes, the
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A product integration method for numerical solutions of [formula omitted]fractional differential equations Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-08 Maria Amjad, Mujeeb ur Rehman
We introduce a numerical method for approximating the solutions of fractional differential equations. The method employs a generalization of the Lagrange polynomial to approximate the unknown function in the differential equations and a product integration strategy to approximate fractional integrals. The product integration formula developed for fractional integrals yields two numerical schemes for
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On the dynamics of a nutrient–plankton system with Caputo and Caputo–Fabrizio fractional operators Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-06 Kaushik Dehingia, Salah Boulaaras, Suman Gogoi
This study aims to investigate the dynamics of a nutrient–plankton system by incorporating Caputo and Caputo–Fabrizio fractional operators. We examine the impact of fractional order on the stability of the nutrient–plankton interaction. The properties of the system’s solutions, such as the existence, uniqueness, and non-negativity under both operators, have been discussed. The system’s equilibria has
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Dynamic load/propagate/store for data assimilation with particle filters on supercomputers Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-02-02 Sebastian Friedemann, Kai Keller, Yen-Sen Lu, Bruno Raffin, Leonardo Bautista-Gomez
Several ensemble-based Data Assimilation (DA) methods rely on a propagate/update cycle, where a potentially compute intensive simulation code propagates multiple states for several consecutive time steps, that are then analyzed to update the states to be propagated for the next cycle. In this paper we focus on DA methods where the update can be computed by gathering only lightweight data obtained independently
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Data-driven robust optimization based on position-regulated support vector clustering Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-29 Somayeh Danesh Asgari, Emran Mohammadi, Ahmad Makui, Mostafa Jafari
The changes experienced in integrating machine learning and data science into mathematical programming over the past decade remain unprecedented. They have created a novel optimization component under deep uncertainty known as “Data-Driven Robust Optimization” (DDRO). It considers a dataset's complexity, hidden information, and inherent form when creating data-driven uncertainty sets. One of the more
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A framework for damage detection in AIS data based on clustering and multi-label classification Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-27 Marta Szarmach, Ireneusz Czarnowski
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Structure-exploiting interior-point solver for high-dimensional entropy-sparsified regression learning Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-22 Edoardo Vecchi, Juraj Kardoš, Malik Lechekhab, Andreas Wächter, Illia Horenko, Olaf Schenk
The solution of high-dimensional nonlinear regression problems through standard machine learning approaches often relies on first-order information, due to the numerical and memory challenges arising from the computation of the Hessian matrix and of the higher-order derivatives. While this scenario seems not favorable to second-order methods, here we show that an efficient and modular structure-exploiting
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A methodology combining reinforcement learning and simulation to optimize the in silico culture of epithelial sheets Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-20 Alberto Castrignanò, Roberta Bardini, Alessandro Savino, Stefano Di Carlo
Tissue Engineering (TE) and Regenerative Medicine (RM) aim to replicate and replace tissues for curing disease. However, full tissue integration and homeostasis are still far from reach. Biofabrication is an emerging field that identifies the processes required for generating biologically functional products with the desired structural organization and functionality and can potentially revolutionize
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Complexity of direct and iterative solvers on space–time formulations and time-marching schemes for h-refined grids towards singularities Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-17 Marcin Skotniczny, Anna Paszyńska, Sergio Rojas, Maciej Paszyński
We study computational complexity aspects for Finite Element formulations considering hypercubic space–time full and time-marching discretization schemes for -refined grids towards singularities. We perform a relatively comprehensive study comparing the computational time via time complexities of direct and iterative solvers. We focus on the space–time formulation with refined computational grids and
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D-FFP: A directional force field protocol for the efficient management of aerial conflicts between UAVs Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-15 Julián Arenillas, Jamie Wubben, Enrique Hernández-Orallo, Carlos T. Calafate
Airspace management is currently experiencing significant legislative changes in many countries due to the high complexity of the procedures involved, and the need to guarantee high levels of flight safety, particularly in urban air spaces. In this regard, both strategic and tactical conflict management solutions are being devised to handle conflicts between different UAVs. In this paper, we propose
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A stabilized finite element formulation with shock-capturing for solving advection-dominated convection–diffusion equations having time-fractional derivatives Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-14 Süleyman Cengizci, Ömür Uğur, Srinivasan Natesan
Numerical instabilities arising when simulating transport phenomena dominated by convection processes are among the most challenging situations in computational science, demanding the use of non-classical formulations and techniques to achieve accurate approximations. Although the stabilized formulations usually help suppress node-to-node nonphysical oscillations, numerical approximations typically
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A dual number formulation to efficiently compute higher order directional derivatives Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-13 R. Peón-Escalante, K.B. Cantún-Avila, O. Carvente, A. Espinosa-Romero, F. Peñuñuri
This contribution proposes a new formulation to efficiently compute directional derivatives of order one to fourth. The formulation is based on automatic differentiation implemented with dual numbers. Directional derivatives are particular cases of symmetric multilinear forms; therefore, using their symmetric properties and their coordinate representation, we implement functions to calculate mixed
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Elzaki projected differential transform method for multi-dimensional aggregation and combined aggregation-breakage equations Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-08 Saddam Hussain, Rajesh Kumar
Numerous real-world fields, including planetary science, bio-pharmaceutical, chemical study, food processing industry, and many more are profoundly impacted by population balance equations. Model complexity limits the analytical investigations to a few aggregation-breakage parameters, although various numerical and semi-analytical schemes are available. This article proposes a new semi-analytical approach
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A multi-indicator prediction method for NOx emission concentration and ammonia escape value for cement calciner system Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-09 Xiaochen Hao, Xinqiang Wang, Jinbo Liu, Xing Wang, Zhipeng Zhang, Yukun Ji
It is particularly important to accurately predict NOx emission concentration in cement production. As the cement industry is a process industry, there are many chemical reactions, coupling of front and back processes, and large fluctuations in production, resulting in time-delayed denitration data, strong coupling, and uncertainty, which makes it difficult to adequately extract the characteristics
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Multifidelity aerodynamic shape optimization for airfoil dynamic stall mitigation using manifold mapping Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-08 Vishal Raul, Leifur Leifsson
Aerodynamic shape optimization for dynamic stall mitigation is computationally challenging, requiring multiple costly CFD evaluations. This work proposes a multifidelity modeling technique to efficiently mitigate dynamic stall over an airfoil, particularly manifold mapping (MM) within a trust-region-based optimization framework to find an optimal shape defined by six PARSEC parameters. The high-fidelity
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Characteristics of sodium alginate-based hybrid nanofluid and darcy-forchheimer flow induced by stretching surface with thermal radiation and cattaneo–christov heat flux model Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2024-01-06 Umar Farooq, Chemseddine Maatki, Karim Kriaa, Bilel Hadrich, Muhammad Imran, Sobia Noreen, Hassan Waqas, Ali Akgül
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A reliable scheme for nonlinear delay differential equations of pantograph-type Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-28 Soniya Dhama
In this article, an iterative method to obtain approximate analytical solutions to delay differential equations of the pantograph type is presented. The primary goal of this approach to solving such problems is to transform them into integral problems. The proposed method involves two stages. First, create an integral operator for the problem. Applying the Normal-S iterative scheme to this integral
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Automated parameter tuning with accuracy control for efficient reservoir simulations Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-27 Erik Hide Sæternes, Andreas Thune, Alf Birger Rustad, Tor Skeie, Xing Cai
Computer simulations of complex physical processes typically require sophisticated numerical schemes that internally involve many parameters. Different choices of such internal numerical parameters may lead to considerably different levels of computational efficiency, some may even result in wrong simulation results. The task of finding an optimal set of the numerical parameters (e.g. for the purpose
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Stability analysis of MHD stagnation point flow of Casson fluid past a shrinking sheet in porous medium considering heat sink or source, thermal radiation and suction effects Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-23 Sradharam Swain, Golam Mortuja Sarkar, Bikash Sahoo
This study investigates the magnetohydrodynamic stagnation point flow of Casson fluid and heat transfer phenomena past a shrinking sheet in porous medium with thermal radiation, heat sink/source and suction effects. The Lie group analysis approach transforms the governing equations into self-similar equations, which are then solved through the shooting methodology. Asymptotic solutions for large stretching
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Computational analysis of financial system through non-integer derivative Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-23 Ziad Ur Rehman, Salah Boulaaras, Rashid Jan, Imtiaz Ahmad, Salma Bahramand
The context-specific meaning of finance includes, among other things, increasing support for social goals, developing skills, increased education, economic health, and fairness. To put it another way, it is an effective tool for ensuring a more prosperous and unrestricted society and it helps you decide what is the best course of action for your money both now and in the near future. In this study
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Impact of neck angle variation on particle and virus-laden droplet transport from lung to lung using eighth-generation airway model Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-22 Shohei Kishi, Masashi Yamakawa, Ayato Takii, Shinichi Asao, Seiichi Takeuchi, Minsuok Kim
In this study, the motion of particles from the respiratory tract of an infected person to that of an exposed person was simulated using computational fluid dynamics. The angle of the exposed person’s neck was varied from 0 ° to 20 ° to assess its impact on particle motion. The airway models for the infected and exposed individuals were based on software and CT data, respectively. Particles, generated
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Project indicators and flexible project structure generators Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-18 Zsolt T. Kosztyán, Gergely L. Novák
Project indicators are essential in characterizing project structures, structural complexity, duration, slacks, and resource demands. This information can fundamentally influence how the scheduling or resource allocation algorithm performs. In addition, most of these indicators assume a fixed project structure, while recent project management approaches, such as agile, hybrid, and extreme approaches
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On the convergence of overlapping and non-overlapping Schwarz methods for the Cahn–Hilliard equation Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-12 Gobinda Garai, Bankim C. Mandal
In this study, we develop and investigate the Schwarz method with or without overlap for the Cahn–Hilliard (CH) problem. The CH equation has a wide range of applications, hence it is crucial to develop effective numerical techniques. In this article, we provide the formulation of the classical Schwarz methods (CSM) and optimized Schwarz methods (OSM) for the CH equation and present the convergence
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IBJA: An improved binary DJaya algorithm for feature selection Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-14 Bilal H. Abed-alguni, Saqer Hamzeh AL-Jarah
Feature Selection (FS) is a special preprocessing step in Machine Learning (ML) that reduces the number of unwanted features in datasets to increase the accuracy of ML classifiers. A popular binary variant of the continuous Jaya algorithm is the Discrete Jaya (DJaya) algorithm. It is commonly used for addressing optimization problems with binary design variables (also known as binary decision variables)
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Mining actionable concepts in concept lattice using Interestingness Propagation Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-11 Mohamed Hamza Ibrahim, Rokia Missaoui
Mining important conceptual patterns is an essential task for understanding the context and content of complex data in many scientific and engineering applications. While exact relevance indices in Formal Concept Analysis provide accurate importance evaluation that can be used for extracting interesting concepts, they often have expensive algorithmic complexity (e.g., at least quadratic in the lattice
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Mesoscale material modeling with memoryless isotropic point particles Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-13 Erik Strand, Filippos Tourlomousis, Neil Gershenfeld
There has been a proliferation of particle systems developed to model complex systems. These are attractive because they are mesh-free, avoiding issues associated with solver remeshing and convergence. They have however fragmented into niches, using increasingly complex particles that introduce internal degrees of freedom and external solver coupling. We show that, contrary to prior assumptions in
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Efficient computation of the photovoltaic single-diode model curve by means of a piecewise linear self-adaptive representation Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-07 F. Javier Toledo, Vicente Galiano, Victoria Herranz, Jose M. Blanes
The current–voltage curve (I–V curve) associated to the photovoltaic (PV) single-diode model (SDM) is an important tool to analyze the behavior of a PV panel, nevertheless, obtaining it is not easy due to the implicit nature of the SDM equation that requires a lot of computation to solve it accurately. In this paper we provide a simple, accurate and almost instantaneous method to obtain the I–V curve
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A study of concurrent multi-frontal solvers for modern massively parallel architectures Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-03 Jan Trynda, Maciej Woźniak, Sergio Rojas
Leveraging Trace Theory, we investigate the efficient parallelization of direct solvers for large linear equation systems. Our focus lies on a multi-frontal algorithm, and we present a methodology for achieving near-optimal scheduling on modern massively parallel machines. By employing trace theory with Diekert Graphs and Foata Normal Form, we rigorously validate the correctness of our proposed solution
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Dimension reduction for uncertainty propagation and global sensitivity analyses of a cesium adsorption model Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-06 Pierre Sochala, Christophe Chiaberge, Francis Claret, Christophe Tournassat
This paper presents an efficient method to perform uncertainty and sensitivity analyses in a cesium adsorption model upstream chained with a pore water composition model. As the number of uncertain input parameters is about twenty for each of the two models, a dimension reduction technique is implemented to build a polynomial approximation of the cesium distribution coefficient in a reduced subspace
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An improved Coupled Level Set and Volume of Fluid (i-CLSVoF) framework for sessile droplet evaporation Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-12-06 Huihuang Xia, Marc Kamlah
Surface-tension-dominant droplet evaporation is ubiquitous and of importance to many applications. We present an improved Coupled Level Set and Volume of Fluid (i-CLSVoF) framework without explicit interface reconstruction for modelling micro-sized droplets with and without evaporation. In the i-CLSVoF framework, an improved surface tension force model with additional filtering steps to filter un-physical
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Analysis of the influence of a pseudo-random number generator type on the kinetics of the cellular automata recrystallization model Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-30 Klaudia Baran, Mateusz Sitko, Lukasz Madej
Models based on discrete simulation methods, i.e., cellular automata (CA) or Monte Carlo (MC), often contain probabilistic elements in the code to capture the stochastic character of material behaviour. They can be related to various physical aspects reflected in the model, e.g., heterogeneous energy distribution or random crystallographic orientation assignment to subsequent grains. Therefore, the
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Numerical algorithm for solving real-life application problems of Lane–Emden type equation Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-27 Vikash Kumar Sinha, Prashanth Maroju
This paper presents an advanced variational iteration method for finding the approximate-exact solution for initial value problems of the Lane–Emden type equation that arise in several applications by employing the quasilinearization approach to the variational iteration method. Also, the convergence analysis of the method is studied under the Lipschitz condition. To demonstrate the applicability of
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HCGCCDA: Prediction of circRNA-disease associations based on the combination of hypergraph convolution and graph convolution Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-20 Pengli Lu, Jinkai Wu, Wenqi Zhang
With the advancement of modern biological experiments, an increasing body of evidence indicates a complex relationship between circRNA and diseases, which holds significant implications for disease research and treatment. However, traditional biological experiments have shown low efficiency and high costs when studying the association between circRNA and diseases. To address this issue, researchers
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Corrigendum to “An intelligence-based hybrid PSO-SA for mobile robot path planning in warehouse” J. Comput. Sci. 67 (2023) 101938 Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-24 S. Lin, A. Liu, J. Wang, X. Kong
Abstract not available
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Mathematical modelling of cancer invasion: Phenotypic transitioning provides insight into multifocal foci formation Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-20 Zuzanna Szymańska, Mirosław Lachowicz, Nikolaos Sfakianakis, Mark A.J. Chaplain
The transition from the epithelial to mesenchymal phenotype and its reverse (from mesenchymal to epithelial) are crucial processes necessary for the progression and spread of cancer. In this paper, we investigate how phenotypic switching at the cancer cell level impacts the behaviour at the tissue level, specifically on the emergence of isolated foci of the invading solid tumour mass leading to a multifocal
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Ranking influential nodes in complex network using edge weight degree based shell decomposition Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-10 Giridhar Maji, Soumya Sen
Identifying critical nodes in a complex network or ranking the nodes based on their influence over the network has many utilities. As an example, these come in handy while choosing customers for viral marketing of a new product or identifying users whom to block for preventing the spreading of misinformation/rumor among others. With proper network modeling, a large number of real-world problems could
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Enhancing the SVD compression losslessly Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-10 Huiwen Wang, Yanwen Zhang, Jichang Zhao
Orthonormality is the foundation of a number of matrix decomposition methods. For example, Singular Value Decomposition (SVD) implements the compression by factoring a matrix with orthonormal parts and is pervasively utilized in various fields. Orthonormality, however, inherently includes constraints that would induce redundant information, preventing SVD from deeper compression and even making it
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Bidirectional EMD-RLS: Performance analysis for denoising in speech signal Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-10 Uender Barbosa de Souza, João Paulo Lemos Escola, Thiago Vedovatto, Leonardo da Cunha Brito, Rodrigo Pinto Lemos
Empirical Mode Decomposition (EMD) is an alternative decomposition method that allows the analysis of non-stationary and non-linear signals, decomposing them into components called Intrinsic Mode Functions (IMFs). In this paper, we introduce the bidirectional combination between EMD and the Recursive Least Squares (RLS) adaptive filter and compare it to Least Mean Square (LMS), EMD-LMS and RLS methods
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Legendre-finite difference method for solving fractional nonlinear Sobolev equation with Caputo derivative Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-10 H. Azin, A. Habibirad, O. Baghani
The Sobolev equation is known as a partial differential equation with second-order partial derivatives. Initially, the Sobolev equation was used to solve the problem of turbulence in physics. However, due to its extensive use in mathematics and geometry, it soon became one of the most important mathematical equations. Despite the significance of this equation, its solution in fractional and nonlinear
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Efficient GPU implementation of the multivariate empirical mode decomposition algorithm Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-10 Zeyu Wang, Zoltan Juhasz
An efficient GPU implementation of the Multivariate Empirical Mode Decomposition (MEMD) method is presented for speeding up the process of decomposing non-stationary multi-channel bioelectric signals into different oscillation modes. Each step of the MEMD algorithm is designed with performance in mind and implemented to remove all unnecessary overheads caused by CPU-GPU communication, data transfer
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GCN-RA: A graph convolutional network-based resource allocator for reconfigurable systems Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-10 Seyed Mehdi Mohtavipour, Hadi Shahriar Shahhoseini
Nowadays, hardware architectures with various reconfiguration capabilities provide significant computational speedup using parallelism and concurrency features. However, data transmission after allocating resources to the application is one of the critical challenges that produces communicational delays and time overheads, specifically in the execution of large-scale applications. This paper proposes
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Machine learning approach for predicting the yield of pyrroles and dipyrromethanes condensation reactions with aldehydes Int. J. Comput. Sci. Eng. (IF 3.3) Pub Date : 2023-11-09 Dmitry M. Makarov, Michail M. Lukanov, Aleksey I. Rusanov, Nugzar Zh. Mamardashvili, Alexander A. Ksenofontov