International Journal of Computing Science and Mathematics (42 papers in press)

Regular Issues

• Stability and bifurcation study of interaction in the vermifiltration phase between predators and prey  
  by Madhan Kumar, Mullai Murugappan 
  Abstract: The issue of waste water disposal that poses a major challenge especially in the industrial sector is discussed in this article. Vermifiltration is used to transform toxic waste to non-hazardous waste. Our focus is on the survival of living organisms which is involved in the process of vermifiltration. We formulate and build a prey predator model with stage structure for the predator population. Model equilibria are observed and studied. The proposed model is expanded by incorporating time delays in the model. The global stability (with and without delay) of the model is discussed in detail. Our findings show that the increase in the density mortality rate of the predator maintains the equilibrium to a certain degree and Hopf bifurcation occurs in the model beyond this. The system exhibits oscillatory behavior when the gestation time delay reaches the threshold level. Further, computational simulations are demonstrated and biological explanations are provided.
  Keywords: vermifiltration; prey-predator; time delay; equilibria; stability; Hopf bifurcation.
  
  
• On the use of Container-based Virtualization for IoT Provisioning and Orchestration: A Survey  
  by Haleema Essa, Rawaa Qasha 
  Abstract: The Internet of Things has great potential to be adopted by applications covering several smart domains, as it consists of a set of physically linked objects that can be accessed through the Internet. Virtualization techniques play an important role in the field of IoT, especially for provisioning and orchestrating IoT applications to overcome the heterogeneity and diversity of the IoT components and environments that host the applications. Recently, container virtualization became the preferred technique for IoT applications due to providing execution isolation, portability, lightweight deployment, and reduced design time as compared with hypervisor-based virtualization. This survey presents a comprehensive study of provisioning and orchestrating the distributed IoT applications in different environments like Edge and Cloud Computing, and how containers can be used proficiently for provisioning and orchestrating IoT applications in these environments.
  Keywords: Internet of Things; IoT provisioning; IoT Orchestration; Container-basedrnvirtualization; Cloud Computing; Edge Computer.
  
  
• The time series modelling on exchange rate and inflation rate: finite normal mixture model  
  by Shi Ling Khek, Seuk Yen Phoong 
  Abstract: The economic growth of developing countries always a central issue concerned by all countries because any changes in global events might influence the performance of these countries. However, there are many debates on the relations between exchange rate and inflation rate in developing countries. In present study, finite mixture model is introduced to address the nexus between exchange rate and inflation rate among Malaysia, Thailand and the Philippines. With this, the monthly data with 182 observations are analysed using maximum likelihood estimation. The results reveal that negative relationship existed during growth situation while no interaction exhibited when a country is trapped into crisis period. Since this study presented the financial interaction among macroeconomic variables during different situations of country, hence, it is believed that statisticians and investors can get to know more details of these variables on these developing countries.
  Keywords: finite mixture model; maximum likelihood estimation; nonlinear time series analysis; Asian developing countries; exchange rate; inflation rate.
  
  
• Creep mechanical model of rock considering temperature effect  
  by Guilin Sun, Jiangchun Hu, Xiangyang Lu, Juncai Xu 
  Abstract: The temperature has an essential influence on the mechanical properties of rock. The present article proposes a novel creep model of rock, considering the temperature. The model explicated consists of three units: an improved Kelvin unit, an improved Maxwell unit, and an improved ideal viscoplastic unit. Based on the new model, the visco-elastic-plastic constitutive equation of rock with temperature effects is derived. When the temperature change is constant and the stress is stable, the creep equation of the system can be explicitly derived. By solving the equation with constant coefficients, the expression of rock strain is obtained. From the rock strain expression, it is demonstrated that the strain of rock is composed of a function of time and an exponential function..
  Keywords: rock; temperature; mechanical model; constitutive model.
  
  
• Numerical simulation and convergence analysis for Riemann-Liouville fractional initial value problem involving weak singularity  
  by Sudarshan Santra, Jugal Mohapatra 
  Abstract: The present work considers a Riemann-Liouville fractional initial value problem associated with homogeneous initial condition involving a weak singularity near the origin. Due to presence of initial singularity, an initial layer occurs at $t=0$. The L1 scheme is introduced on a uniform mesh to approximate the solution. The convergence analysis shows that the present method is more accurate and produces less error compared to some existing methods on any subdomain away from the origin while, the proposed method is comparable over the entire region. Numerical examples and comparison results are provided in order to show the effectiveness of the proposed method.
  Keywords: Riemann-Liouville fractional IVP; Caputo fractional derivative; L1 scheme; Error analysis.
  
  
• Performance Analysis of Internet Router Using Markovian Quasi Birth and Death Process  
  by Abhilash Vollala, Malla Reddy Perati 
  Abstract: In networking, network nodes play a crucial role, and their performance analysis has a greater significance for providing high quality service. Here, asynchronous network node with self-similar input traffic is modelled into single server queuing system with a finite buffer, where input process is Markov Modulated Poisson Process (MMPP), and service follows exponential distribution. It is intended to study the behaviour at arbitrary times, which carried out by using continuous time Markov chain and a finite quasi birth and death process (QBD). Transient state probability vector of transition rate matrix is obtained, which, in turn, gives performance metrics. Queuing behaviour is studied through performance metrics, namely blocking probability and mean waiting time (MWT) at arbitrary times, and comparison is made between steady and transient cases.
  Keywords: network node; queuing system; continuous time Markov chain, MMPP; self-similar traffic; exponential distribution; state probability vector, transition rate matrix.
  
  
• Computational advantage in evaluating oscillatory integral using quadratic spline  
  by Ramachandran Mankali 
  Abstract: Quadratic spline is used in the Levins method in a conventional manner when evaluating the oscillatory integral. Generally, Levin method involves solving a linear system of equations and this requires O(n3) computations. The quadratic spline interpolation approach however has a computational advantage and needs solving recurrence relations that involves only O(n2) computations, where (n) is the number of selected nodes. The stability of these recurrence relations is analysed, and it is shown that the proposed method for large (n), is not ill-conditioned and solution is trustable. It is also shown that linear piecewise and cubic interpolation do not offer such advantages. The paper outlines how this reduction in computation can be extended to two-dimensional oscillatory integrals. A bound on the numerical solution is obtained in terms of the frequency. We consider numerical examples, including an application from scattering problem, to assess the performance of the proposed Levin method.
  Keywords: Oscillatory integral ; Levin method ; Quadratic Spline.
  
  
• Nonparametric Path Function Estimation of Fourier Series at Low Oscillations for Modeling Timely Paying Credit  
  by Adji Achmad Rinaldo Fernandes, Laili Nur Rasyidah, Atiek Iriany 
  Abstract: The development of the nonparametric path model is carried out with the assumption that each function formed has the same data pattern shape, so that some researchers only use one approach. However, in actual cases in the field, several cases are often encountered where the data patterns formed are different from each of the calculated functions. This research aims to estimate the nonparametric path function of the Fourier series and to describe the lemma and theorem for the analysis of the nonparametric path of the Fourier series at low oscillation levels (K=2,3,4,5). The analytical method used is a Fourier series nonparametric path analysis with a low level of oscillation. Primary data is obtained from customers at a Bank (Bank X) in Indonesia. The data is in the form of item scores that are used as the average variable so that the average data scale is obtained which is the data of the relevant latent variable. The function estimation in nonparametric path analysis using the Fourier series approach is ? ?(?)=(n^(-1) X^' X+?D)^(-1) n^(-1) X^' y.The best nonparametric path model that can describe the 5C variable on Time to Pay through Willingness to Pay is when the oscillation K=4 with R2 is 78%. This study applies the Fourier series approach to path analysis in modeling on time to pay credit in the banking sector.
  Keywords: Path analysis; Fourier series; on-time pay; willingness to pay.
  
  
• Non-destructive Diagnosis of Knee Osteoarthritis Based on Sparse Coding of MRI  
  by Huifeng Ren, Dong Zhang 
  Abstract: The disability rate of knee osteoarthritis (KOA) is high. A kind of non-destructive diagnosis of KOA based on sparse coding of magnetic resonance imaging (MRI) is presented. The two-dimensional Gabor filter bank is used to extract the high-dimensional features of KOA-MRI images. Secondly, a fitness feedback particle swarm optimization is proposed to choose three key parameters of Gabor filter, bandwidth parameters, maximum frequency of the centre and window size. Then the extracted Gabor visual features are described by sparse coding and sparse coefficient matrix of magnetic resonance images. An improved feature imbalance support vector machine is used to classify magnetic resonance images by considering the unbalanced influence of feature contributions. The overall performance of diagnosis is improved.
  Keywords: Non-destructive diagnosis; magnetic resonance imaging; Gabor; sparse coding; particle swarm optimization.
  DOI: 10.1504/IJCSM.2023.10055606
   
  
• Unsteady Flow of Hybrid-Nanofluid in a Non-Homogeneous Porous Medium  
  by Lalrinpuia Tlau 
  Abstract: This article presents an unsteady flow of a CuAg hybrid nanofluid flowing in a porous regime having variable permeability. The flow is pressure driven as well as time dependent. Two cases of variation in permeability is taken: exponential decay and quadratic growth. To solve the nonlinear partial differential equation, a transformation is utilised to get an ordinary differential equation. The homotopy analysis method is then used to solve the governing equation. A reduced form of the equation is solved analytically to verify the obtained solution. The effect of various flow parameter on the flow velocity is shown using a contour plot. Skin friction and volume flow rate are also shown graphically.
  Keywords: Unsteady; Hybrid Nanofluid; Variable Permeability; Porous Medium.
  
  
• A fractional-order love dynamical model with time delay for non synergic couple : Stability analysis and Hopf bifurcation  
  by SANTOSHI PANIGRAHI, SUNITA CHAND 
  Abstract: In this manuscript, we have investigated the fractional order love dynamic model with time delay for nonsynergic couples. The quantitative analysis of the model has been done in which the asymptotic stability of the equilibrium points of the model have been discussed. Furthermore, the Hopf bifurcation analysis of the model has been done under the impact of time delay. The analysis of the model has been done by using the Laplace transformation technique. Stability analysis is an established tool for the analysis of complex mathematical models. The model has been analyzed for integer order by various researchers, but none have considered the fractional order model under the impact of time delay and done the stability and Hopf bifurcation analysis for the aforesaid model. This motivates us to study the fractional order delay love dynamical model for non synergic couple. In ourwork, we have considered the fractional order time delay to represent the long term behaviour of the model. Finally, the numerical simulations have been carried out using MATLAB to illustrate our derived results.
  Keywords: Love dynamics; Stability; Hopf bifurcation; Time-delay; Fractional differential equation ;Caputo fractional derivative.
  
  
• A new form of LSMR for solving linear systems and least-squares problems  
  by Maryam Mojarrab, Afsaneh Hasanpour, Somayyeh Ghadamyari 
  Abstract: ?The LSMR (Least Squares Minimal Residual) method of Fong and Saunders (2011) is an algorithm for solving linear systems Ax=b and least-squares problems min''Ax-b''_2 that is analytically equivalent to the MINRES method applied to normal equation A^TAx=A^Tb? ?so that the quantities ''A^Tr_k''_2 are minimized (where r_k=b-Ax_k is the residual for current iterate x_k)?. ?This method is based on the Golub-Kahan bidiagonalization 1 process?, ?which generates orthonormal Krylov basis vectors?. ?Here?, ?the Golub-Kahan bidiagonalization 2 process is implemented in the LSMR algorithm?. ?This substitution makes the algorithm simpler than the standard algorithm?. ?Also?, ?numerical results show the new form to be competitive?.
  Keywords: Bidiagonalization process; Linear system; Least-squares problem; Krylov subspace method; LSMR.
  
  
• An Application of Rough Set Theory to Predict Telecom Customer Churn  
  by Binh Tu Van, Thy Ngo Giang 
  Abstract: The current paper applies algorithms of machine learning to predict customer churn. The study employs 211,777 instances in the telecommunication sector with six attributes employed, e.g. Data, Length of Stay, Top-up, External communication, Handset of phone, and churn. Although the rules generation of Na
  Keywords: Churn; telecom; rough set theory; decision table.
  
  
• Multi-objective firefly algorithm combining Logistic map-ping and cross-variation  
  by Ningkang Pan, Lu Li, Tanghuai Fan, Ping Kang 
  Abstract: In the process of evolution, the multi-objective firefly algorithm has low optimization accuracy and is prone to premature convergence, resulting in poor distribution and convergence of the population. To solve this problem, a multi-objective firefly algorithm (MOFA-LC) combining Logistic mapping and cross-mutation was proposed. To improve the distribution of the population, the initial population with good ergodicity and uniformity was generated by Logistic mapping. To improve population convergence, Levy flights and non-dominated sorting are used to improve the position updating formula. After the individual position updating, the cross-mutation method in the genetic algorithm can be used to improve the optimization accuracy of the algorithm and make it jump out of the local optimal, overcome the intelligent convergence of the algorithm, and maintain the convergence of the population. In the experimental part, two typical test functions are selected to plot IGD convergence curves of MOFA-LC and 11 recent multi-objective optimization algorithms. The results show that MOFA-LC has obvious advantages over other algorithms.
  Keywords: Multi-objective optimization; firefly algorithm; logistic mapping; lévy flights; non-dominated sorting; cross variation.
  DOI: 10.1504/IJCSM.2023.10056273
   
  
• Application of hybrid genetic algorithm based on travelling salesman problem in rural tourism route planning  
  by Zhijia Chen, Ping Zhang, Lei Peng 
  Abstract: It is very meaningful to integrate tourism resources, excavate valuable tourism information and develop a self-service tourism route planning system. In this study, a hybrid genetic algorithm (HGA) based on travelling salesman problem (TSP) is proposed, and the proposed algorithm is simulated and case analysed. The research shows that HGA algorithm has better optimisation efficiency when the number of iterations is less; When there are many urban attractions and large distances, the HGA algorithm will show more cross routes. After multiple iterations, the optimisation effect and results of the algorithm will be better. There is still much room for improvement in the method proposed in this study. In the next step, map technology can be used to design more detailed route display functions.
  Keywords: Traveling salesman problem; Genetic algorithm; Ant colony Rural tourism; Route planning.
  DOI: 10.1504/IJCSM.2023.10056280
   
  
• Improved composite methods by radial basis functions for solving nonlinear Volterra-Fredholm integral equations  
  by Dalila Takouk, Rebiha Zeghdane, Lakehali Belkacem 
  Abstract: In this paper, a hybrid radial basis function (HRBF) is developed for solving Volterra-Fredholm integral equations. It is based on combining between generalized multiquadric and gaussian RBFs. The generalized multiquadric is one of the powerful RBFs for approximating solutions of Volterra-Fredholm integral equations because, we benefit from the optimal choices of the exponent $\beta$ for improving the accuracy of the composite technique. The interpolation scheme using RBFs has the advantage of being meshless and dimensional independent because it takes Euclidean distance as input which can be trivially computed in any dimension. This type of radial basis functions depends on a shape parameter, which needs to be defined by the user and controls the stability and accuracy of the RBFs approximation. We discuss the new methods effectiveness compared to the widely used traditional RBFs and also investigate the effect of parameters on the methods performance. Also the adapted technique is compared with the use of Wendland's compactly supported radial basis functions (CSRBFs) in both condition number and accuracy by considering different numerical examples.
  Keywords: Generalized multiquadric radial basis functions ; Gaussian radial basis functions ; Compactly supported radial basis functions ; Nonlinear Volterra-Fredholm integral equations ; Legendre-Gauss-Lobatto nodes and weights.
  
  
• A uniformly convergent numerical method for singularly perturbed delay parabolic partial differential equation through non-polynomial spline technique  
  by Awoke Tiruneh, Getachew Deresse, Mulunesh Ayele 
  Abstract: In this article, we proposed a uniformly convergent numerical method to solve singularly perturbed delay parabolic partial differential equation of convection-diffusion type. The scheme is developed using non-polynomial spline method by introducing a fitting factor in the spatial variable and Crank Nicholson finite difference method for time derivative. The proposed method is analyzed for stability and convergence, it is found that this method is unconditionally stable and is convergent. Numerical investigations are carried out to demonstrate the efficacy and uniform convergence of the proposed scheme, and the obtained numerical results show that the results of the present method are more accurate than the results of some methods discussed in the literature.
  Keywords: Singularly perturbation; delay; parabolic; non-polynomial spline; Boundary layer.
  DOI: 10.1504/IJCSM.2023.10056425
   
  
• Research on bonding damage of composite materials adhesive structures  
  by Jiaru Shao, Niu Liu, Zijun Zheng 
  Abstract: : In this paper, the continuum damage mechanics (CDM) and 3D Hashin criterion are implemented to simulate the formation and evolution of the intra-laminar damage. The cohesive layer was simulated by the cohesive zone model (CZM). The finite element method (FEM) results are consistent with the experimental results, which validate the effectiveness of the FEM. Then, different types of the adhesively bonded single-lap joints (SLJs) are analyzed. The results suggest that the 0o and 90o plies can improve the failure loads of SLJs. The
  Keywords: composites; adhesive damage; matrix damage; fiber damage.
  
  
• Research on the construction of personalized recommendation system based on LFM algorithm and tag data  
  by Guofang Liu, Lixiang Shi 
  Abstract: In view of the low efficiency of the current personalized recommendation system, this research proposes a personalized recommendation method combining LFM algorithm and label data. In this recommendation method, LFM algorithm decomposes the user click matrix by using the gradient descent method to complete the prediction of implicit feature feedback. The tag data can be predicted by explicit feature feedback through BM25 algorithm, item tag matrix and user scoring matrix. The results show that the performance of LFM algorithm is the best when the implicit feature dimension is 30. At this time, the accuracy, recall, coverage and F1 values were 27.82%, 8.82%, 53.32% and 19.86% respectively. The variation range of accuracy is 23.06%~26.67%, and the variation range of recall is 8.42%~10.03%. The application of the research results in the personalized recommendation system can obtain a more efficient and comprehensive recommendation technology.
  Keywords: Personalized algorithm; LEM; Interest characteristics; BM24.
  DOI: 10.1504/IJCSM.2023.10057828
   
  
• Tea disease recognition technology based on deep convolution neural network feature learning method  
  by Yuhan Feng  
  Abstract: China is a large tea country. Adopting more advanced science and technology to realize the intelligent identification of tea diseases will help to improve the planting, production and management of tea and carry out effective prevention and control of tea diseases. This research is based on the feature learning method of deep convolution neural network, introduces the optimal design of high-order residual module, proposes HRN algorithm, and combines self attention mechanism to improve the robustness of HRN algorithm model. Through the simulation and comparative analysis with the other three algorithms, it can be seen that the hrn algorithm proposed in this study has better recognition efficiency and recognition accuracy, can effectively realize the recognition of tea diseases, and can be applied to the production and planting management of tea.
  Keywords: Convolutional neural network Tea Diseases Feature extraction Image recognition.
  DOI: 10.1504/IJCSM.2023.10057854
   
  
• Learning Qualitative Probabilistic Networks with Reduced Ambiguous Signs from Complete Data.  
  by Qian Wang, Wei Xu, Yali Lv, Lifang Wang 
  Abstract: Qualitative Probabilistic Networks (QPNs) are the qualitative abstractions of probabilistic networks or Bayesian networks, summarizing probabilistic influences by qualitative signs. But the ambiguous sign is undesirable as it leads to uninformative results upon QPN inference. In this paper, we focus on learning QPN with reduced ambiguous signs from complete data. We first extend the definition of qualitative influences based on the situational signs, and prove the theorem on the range of qualitative signs. Second, we design an algorithm for learning QPN with reduced ambiguous (RAQPN Algorithm). The QPN structure can be optimized by the K2 search algorithm, and the corresponding qualitative signs can be acquired by ordering the conditional probabilities that are represented by the frequency formats. Furthermore, when the ambiguous signs appear, they can be reduced by being given the situational state of the network. Finally, experiment results verify the validity and feasibility of the proposed methods.
  Keywords: Qualitative probabilistic networks; Ambiguous signs; Bayesian networks; K2 algorithm.
  DOI: 10.1504/IJCSM.2023.10057879
   
  
• Analysis of influencing factors of College Students' Entrepreneurship Based on decision tree model  
  by Changliang Li, Qingqing Zhang 
  Abstract: In order to explore the influencing factors of College Students' entrepreneurship, the research combined geographic weighted regression model (GWR) and gradient boosting decision tree (GBDT) to analyze the influencing factors of College Students' entrepreneurship. The results show that the factors of geographical location have a significant impact on College Students' entrepreneurship, and the success rate and willingness intensity of College Students' entrepreneurship are significantly affected by geographical regions. Entrepreneurs' interpersonal communication, problem-solving and enterprise management ability have a great impact on entrepreneurship achievements, followed by learning ability, human resource management ability and entrepreneurship policy. At present, the quality of entrepreneurship education in Colleges and universities is not high, so entrepreneurship education has a relatively small impact on College Students' entrepreneurship. It provides an important reference point for the research on the relationship between the location of College Students' Entrepreneurship and the success rate of entrepreneurship.
  Keywords: Geographically weighted regression; Gradient lifting; Decision tree; College Students' entrepreneurship; Influence factor.
  DOI: 10.1504/IJCSM.2023.10057880
   
  
• Multi-population artificial bee colony algorithm based on nearest neighbor partition  
  by Mingze Ma, Wenjun Wang, Xin Li 
  Abstract: Artificial bee colony (ABC) has shown great potentiality among many swarm intelligence optimization algorithms. However, ABC still shows deficiencies in some aspects. The weak exploitation ability makes the original ABC hard to achieve promising results when dealing with complex optimization problems. The roulette selection method may not work at the late search stage. To make up these deficiencies, a modified multi-population ABC with nearest neighborhood partition (namely NNPMABC) is proposed in this paper. Firstly, a novel partition method is used to divide the swarm into several subgroups. Then, three improved search strategies and a new selection method based on nearest neighbor partition are designed. In addition, a new search strategy is constructed for the scout bee stage. To prove the effectiveness of NNPMABC, 22 benchmark problems are tested. Results show NNPMABC performs the best among six ABCs.
  Keywords: Artificial bee colony; nearest neighbor partition; multi-population; multiple search strategies.
  DOI: 10.1504/IJCSM.2023.10057935
   
  
• Signal recovery adapted to a dictionary from non-convex compressed sensing  
  by Jianwen Huang, Feng Zhang, Xinling Liu, Jinping Jia, Runke Wang 
  Abstract: This paper studies reconstruction of signals, which are sparse or nearly sparse with respect to a tight frame D from underdetermined linear systems. In the paper, we propose a non-convex relaxed q(0 Keywords: compressed sensing; ℓq robust D-Null Space Property; non-convex relaxed ℓq minimisation method; restricted isometry property adapted D; sparse recovery.
  DOI: 10.1504/IJCSM.2023.10057937
   
  
• Some computational aspects of terminal Wiener index  
  by Viswanathan Iyer, SULPHIKAR A 
  Abstract: The terminal Wiener index of a tree T is defined as the sum of the distance between all pairs of pendent vertices inT. The concept of terminalWiener index is used in mathematics as well as in chemistry. Several papers address the question: "What positive integers can be terminal Wiener indices of trees of a certain type?". The question is already answered for certain types of trees. In this paper we consider full binary trees and binomial trees. Since both these trees can be defined recursively, we introduce a common method to derive expressions for the terminal Wiener index. Algorithms are already available to compute Wiener index of a tree in linear time. We show that if Wiener index of a tree can be computed in linear time then its terminal Wiener index can also be computed in linear time. We also describe a linear time algorithm to compute terminal Wiener index of a tree.
  Keywords: terminal Wiener index; full binary tree; binomial tree; Wiener index; distance in graphs.
  DOI: 10.1504/IJCSM.2023.10057938
   
  
• Prediction model of hybrid recurrent neural network based on sequence decomposition  
  by Jia Zhao, Changxiang Li, Longzhe Han, Yannian Wu, Lieyang Wu 
  Abstract: A large number of random time series exhibit obvious nonlinear characteristics. In order to effectively learn the nonlinear characteristics in time series, this paper proposes a hybrid recurrent neural network prediction model based on sequence decomposition. Firstly, this model uses the seasonal trend decomposition method based on local weight regression to decompose the original time series into trend series, seasonal series and residual series, and fuses these three sub-sequences with the original feature series to form a new feature series. Secondly, the input sequence is decomposed into three levels through the progressive decomposition network, different neural networks are used to predict the decomposition sub-sequences of each level. Finally, the prediction results are spliced and put into the full connection layer for the final prediction. Simulation results show that, the proposed model has the lowest prediction error and higher prediction accuracy.
  Keywords: sequence decomposition; recurrent neural network; trend decomposition method; decomposition of network; generalization.
  DOI: 10.1504/IJCSM.2023.10058083
   
  
• Effect of thermal conductivity in a semiconducting medium under modified Green-Lindsay theory  
  by Praveen Ailawalia, Priyanka Gupta 
  Abstract: The objective of present investigation is to study the effect of varying thermal conductivity on photothermal interaction in a semiconducting medium under the modified Green-Lindsay theory. The normal mode analysis technique is used to find the analytic components of displacement, stress, carrier density and temperature distribution. The effect of thermal conductivity on these components is shown graphically for different theories of thermoelasticity namely the Modified Green-Lindsay theory (MGL theory), Green-Lindsay theory (GL theory), Lord-Shulman theory (LS theory) and Classical coupled theory of thermoelasticity (CTE theory). The graphical results show that all the physical quantities depend on thermal conductivity. Moreover, the variations of all the components are oscillatory and the magnitude of oscillations is more when thermal conductivity is constant.
  Keywords: Green-Lindsay theory; Semiconducting medium; Thermal conductivity; Temperature distribution; Normal mode analysis; Carrier density.
  DOI: 10.1504/IJCSM.2023.10058089
   
  
• Study on damage identification of aero-engine composite vane based on experimental modal parameters  
  by Jin GUO, Yunzhe HOU, Guanbing Cheng, Shuming LI 
  Abstract: The paper took both undamaged and damage composite plane plates as example to effectuate the modal experiments by laser vibrometer measurement systems. The plate vibration modal parameters were identified. One coefficient was further constructed to locate the damage position. The experimental results show that the presence of the damage reduces the plate vibration amplitude due to its material deformation. Several orders frequencies of the plate may not be identified only by the amplitude-frequency curves. For the plate, its first three orders natural frequencies are 67 Hz, 85 Hz and 105 Hz, respectively. The fourth and fifth orders ones correspond 140 Hz and 225 Hz. The plate natural frequencies decrease and its damping ratio increases in the presence of the damage on the plate. The plate damage does not change evidently its vibration shape features, but reduces its vibration amplitude. The constructed damage coefficient may identify the damage location in mostly cases.
  Keywords: Aero-engine; damaged composite plate; experiment modal; modal parameters; laser vibrometer; damage identification.
  DOI: 10.1504/IJCSM.2023.10058371
   
  
• Incorporation of Question Segregation Procedure in Visual Question Answering Models  
  by Souvik Chowdhury, Badal Soni, Doli Phukan 
  Abstract: There are various open issues in visual question answering (VQA). One of them is sometimes a model can predict Yes or No as an answer which is not relatable to the question and requires a descriptive answer and vice versa. To solve this issue in the VQA domain, in this paper, a question segregation (QS) technique is incorporated to classify the questions into three types (Yes/No, Other and Number). Then we successfully incorporated this technique with wo of the VQA models, stacked attention networks (SAN) and modular co-attention network (MCAN). We evaluate the performance of the QS and SAN models on two datasets VQA v.2 and CLEVR. We also studied and analysed the impact of Question Segregation on the performance of these two models on different datasets.
  Keywords: Visual Question Answering; Machine Learning; Deep Learning; CNN;LSTM.
  DOI: 10.1504/IJCSM.2023.10058564
   
  
• Numerical study on effects of branch numbers on vibration characteristics of engine fuel manifold system  
  by Yunzhe Hou, Haoyang Zhang, Guanbing Cheng, Hongbo Peng 
  Abstract: The modal analysis of fuel pipelines was done by experimental modal vibration measurement. The physical and calculated models of fuel manifold with various branches were established to examine effects of branch numbers on manifold system structural parameters. The results show that the natural frequency and frequency calculated by finite element method is in good agreement with experimental results. The fuel manifold systems' frequencies increase stepwise. The first third-order frequencies are highest for the fuel manifold with 12 branches, and the later fourth-order ones are highest for the 8 branches manifold system. Due to the symmetrical structure of the pipe, the fuel manifold system has repeated modes. The first and third modes are characterized as bending vibration. The second mode is a torsional vibration. The fuel manifold resonance frequency is in low-frequency region, radial frequency response value is lower than the axial one.
  Keywords: aero-engine; fuel manifold system; experimental modal analysis; finite element; resonance; modal analysis; harmonic response analysis.
  DOI: 10.1504/IJCSM.2023.10058878
   
  
• Two-machine reentrant circular robotic cells with swap ability  
  by Ali Khebouche, Mourad Boudhar 
  Abstract: We consider a robotic cell consisting of two machines placed circularly and a robot with swap ability, operating under the constraint of a reentrant chain where a processed part must return to the first machine. The objective is to determine the optimal cycle time for one unit to maximize throughput. We conducted an in-depth analysis of two-machine robot cells in unbalanced cases. We developed cycle time formulas for the six feasible one-unit cycles and found that three of these cycles outperformed the other three. We then determined the parameter regions in which each of the three cycles was optimal. Our study offers insights to improve reentrant robot cell efficiency and management recommendations for utilizing the robot with swap ability.
  Keywords: Scheduling robotic cells; throughput optimization; chain-reentrant; circular layout.
  DOI: 10.1504/IJCSM.2023.10058934
   
  
• An Integration Model for Texas Hold'em  
  by Yajie Wang, Shengyu Han, Zhihao -wei, Zhonghui Shi 
  Abstract: Texas Holdem is a representative of incomplete information game. Existing research on computing Nash equilibrium as a Texas Holdem strategy has problems, including high resource consumption and conservative strategies. To solve the above problems, an integration model combining deep learning and reinforcement learning is proposed. Firstly, to reduce the storage resources consumed due to the large Texas Holdem state space, a long short-term memory (LSTM) is designed to predict the game results. Since the win rate and historical action information are used as input data by the LSTM, a convolutional neural network (CNN) is designed to predict the current win rate. Secondly, in order to enable the strategy to have dynamic adjustment ability, the deep Q-network (DQN) is used to generate the strategy by using the results predicted by LSTM. Finally, an agent is implemented to provide training data for LSTM. The experimental results show that the model wins more chips, which proves that it can be used as a solution for incomplete information games.
  Keywords: Reinforcement learning; Deep learning; Texas Hold'em; DQN algorithm; integration model.
  DOI: 10.1504/IJCSM.2023.10059015
   
  
• Redefine Trigonometric Cubic B Spline Collocation Scheme for Solving Convection-Diffusion Equation.  
  by Ashish Kumar Rawat, Neeraj Dhiman, Anand Chauhan, Saumya Gupta 
  Abstract: In present article, redefine formulation of trigonometrical Cubic b spline collocation technique being used to obtained numerical response of the convection-diffusion partial differential equation. This proposed work based on usual discretization of the linear and non-linear term of the partial differential equation. Robin graves technique used for the linearized the non-linear terms of the partial differential equation (pde), whether initial values are recall by the initial or boundary condition. Finite difference scheme applies on this work for discretized the time variable terms of the convection-diffusion equation. Von-Neumann stability state the method is unconditionally stable for considerable domain. To establishment of the scheme, two example are compared with existing results and comparison are finer than existing result.
  Keywords: Redefine Trigonometric cubic b-spline; collocation method; convection diffusion equation; finite difference scheme.
  DOI: 10.1504/IJCSM.2023.10059180
   
  
• Dynamics of a delayed stage structure predator-prey model with predator-dependent prey refuge  
  by Wensheng Yang, Qi Cao 
  Abstract: In this paper, a delayed stage structure predator-prey model with predator-dependent prey refuge is proposed. The prey population is divided into two parts: juvenile and adult prey, and the population of predator depends on adult prey only. The number of prey in refugia is nonlinear depends on the number of predator in this work. First, the existence and local stability of all possible equilibria are investigated. By constructing appropriate Lyapunov functions, we get the sufficient conditions for the global stability of the predator-free equilibrium and the positive equilibrium, respectively. Moreover, we introduce the gestation delay of predator to the system. The existence of periodic solutions at the positive equilibrium point via Hopf-bifurcation with respect to delay is established. The stability and direction of Hopf-bifurcation is also analyzed by using Normal form theory and Centre manifold theory.
  Keywords: Stage-structure model; Predator-dependent refuge; Time delay; Global stability; Hopf bifurcation.
  DOI: 10.1504/IJCSM.2023.10059181
   
  
• Particle resolved direct numerical simulation of heat transfer in gas-solid flows  
  by Ali Abbas Zaidi 
  Abstract: The purpose of this paper is to propose a new immersed boundary method for heat transfer calculations in gas-solid flows. In the proposed method, solid particles are fixed in the computational domain due to longer response times of particles (to mimic the gas-solid systems) and treated as sources of velocity and temperature. For calculations of fluid velocity and temperature, Navier-Stokes and energy equations are solved for fixed Cartesian grid. For the validation of the proposed method, number of benchmarking studies are done by comparing the simulation results with the studied problems in literature. Simulations showed good agreement with the literature results which verifies the accuracy and reliability of the immersed boundary method proposed in this paper.
  Keywords: immersed boundary method; particle resolved direct numerical simulation; porous medium; heat transfer; computational fluid dynamics.
  DOI: 10.1504/IJCSM.2023.10055914
   
  
• Application of particle swarm optimisation algorithm in manipulator compliance control  
  by Kai Guo, Zhi Bai, Zhilin Ma 
  Abstract: In this study, the motion model and impedance control model of the 9-DOF manipulator are established, and the impedance parameters in the model are optimised using particle swarm optimisation (PSO) algorithm. The experimental data shows that in the linear motion experiment, the maximum relative oscillation error of each scheme based on fuzzy adaptive proportional, integral and differential (PID) algorithm, offline parameter adjustment method and PSO algorithm on the vertical axis is 3.44%, 6.74% and 5.82% respectively, and the process control time from the contact between the robot and the environment to the contact force stability is 2.57 s, 3.82 s and 2.04 s respectively. The experimental results show that the PSO optimised impedance parameters can significantly improve the compliance control effect of the manipulator.
  Keywords: PSO; particle swarm optimisation; optimisation; mechanical arm; compliance control; environment impedance parameters.
  DOI: 10.1504/IJCSM.2023.10057853
   
  
• An integer programming model for controlling dengue transmission  
  by A.C. Mahasinghe, K.K.W.H. Erandi, S.S.N. Perera 
  Abstract: Prevailing dengue-control strategies in many developing countries yield only limited benefits due to non-optimality of those strategies. In this paper, we demonstrate howthe same strategies could be altered using the same amount of resources in order to yield more fruitful results. Accordingly, we develop a binary integer programming model, aimed at minimising the total number of susceptible individuals with high-risk of being infected with dengue, by identifying the most influential dengue-infected individuals who could undergo an epidemiological isolation, subject to the conditions imposed by the topological properties of the epidemiological network and budgetary constraints. Further, we analyse the proposed epidemiological isolation to examine its adequacy in a real-world implementation.
  Keywords: dengue control; integer programming; binary optimisation; epidemiological network; weighted graphs; control strategies; epidemiological isolation; time-dependent formulation; dominating set; computational challenges.
  DOI: 10.1504/IJCSM.2023.10059343
   
  
• Algebraic modelling of concurrent systems and its practical application  
  by Weidong Tang, Shengnan Li, Huaxu Li 
  Abstract: For decades, formal methods have greatly contributed to the modelling and validation of concurrent systems. Event structure is a powerful and efficient formal method. However, the traditional event structure has some limitations, so it cannot describe the exchange process of data flow, but the exchange process of data flow is exactly one of the most important behaviour characteristics of concurrent systems. This paper formally defines a new event structure model based on data flow by means of symbolic computation and uses it for modelling the handling of objects by robots independently and cooperatively.
  Keywords: data flow; event structure; concurrent system; modelling and verification; symbolic computation.
  DOI: 10.1504/IJCSM.2022.10057619
   
  
• Applicability of double power law model for the statistical analysis of meteorological wind velocity time series data  
  by Shashank Bhardwaj, Sammedkumar Patil, Vijesh V. Joshi 
  Abstract: This paper is devoted to the statistical analysis of wind velocity variance time-series data obtained over the Bay of Bengal to investigate the turbulent energy cascade. The spectral distribution of wind velocity variance followed two different power laws. It was proposed that these power laws express the inertial subrange and the dissipation range. So, to cover these spectral ranges of frequencies, a double power-law(DPL) model was employed. The statistical analysis conducted on the power spectrum provided equations of both the power laws with high confidence levels. The Heaviside functions helped to formulate a single equation describing the entire spectral density. It was observed that the DPL model was very compliant with the -5/3 power law, and the statistical tests concluded that this model was a better fit with a close to 96% R² score when compared to a 90% R² score of -5/3 power law.
  Keywords: Kolmogorov Energy Spectra; DPL; double power law; -5/3 power law; turbulence; inertial subrange; time series analysis.
  DOI: 10.1504/IJCSM.2023.10059344
   
  
• Hierarchical neural network detection model based on deep context and attention mechanism  
  by Yuxi Zhang, Yu Zhao 
  Abstract: In order to improve the ability of sentence event detection in natural language processing and solve the problem of event processing caused by polysemy, an event detection model based on neural network is proposed. The model adjusts the structure to a hierarchical neural network model based on neural network, and introduces attention calculation into the internal structure to realise the correlation analysis of sentence context. The value of the model is judged through performance analysis and application test. The results show that the average harmonic value of the model in polysemy detection is 74.1%, which is higher than the existing model. The application test shows that the model can detect events for sentences in different environments. The results show that the hierarchical neural network event detection model with deep contextual representation and attention mechanism has good performance, which provides theoretical support for the development of multi event detection technology.
  Keywords: natural language processing; event detection; deep context; attention mechanism; hierarchical neural network.
  DOI: 10.1504/IJCSM.2023.10056282
   
  
• Research on VLSI layout method based on spatial evolutionary algorithm  
  by Hongmin Wang 
  Abstract: Aiming at the multi-objective method of weighted circular layout (WCP) problem, a multi-objective configuration space evolutionary algorithm (MOCSEA) is proposed, at the same time, the nearest and farthest candidate solutions are proposed to select the best individual. The results show that the sum of the weight distances between the objects to be distributed should be as small as possible. The area of the outsourcing container that can accommodate all the objects to be distributed is as small as possible. The sum of area s and weight distance Q of MOCSEA algorithm is significantly lower than the optimal solution of other algorithms. MOCSEA of multi-objective optimisation algorithm can better solve WCP problem, which belongs to an effective multi-objective optimisation algorithm. It is hoped that this study can provide a certain reference value for the layout problem in actual industrial production.
  Keywords: spatial evolutionary algorithm; multi-objective optimisation; very large scale integration; WCP; weighted circular layout.
  DOI: 10.1504/IJCSM.2023.10056284
   
  
• Research on bilingual text similarity detection and analysis based on improved fragment merging algorithm  
  by Miao Zhang 
  Abstract: To achieve cross language text similarity analysis, an improved fragment merging algorithm based on dynamic programming is proposed. Dynamic programming is introduced into the fragment merging algorithm to improve the merging algorithm, so as to improve the cross language detection, gradually merge fragments from keyword detection, and verify the performance of the algorithm, such as recall, accuracy and detection time, through comparative analysis experiments. The results show that the recall and accuracy of the merging algorithm based on dynamic programming are more than 80% in the performance test. In addition, it can be found that the fragment merging algorithm has faster fragment merging speed and plagiarism detection speed in the comparison of algorithms. The performance of the improved fragment merging algorithm in plagiarism detection has great advantages, but also has great application value, which provides a new solution for the field of text similarity calculation.
  Keywords: cross language; similarity analysis; dynamic programming; plagiarism detection; fragment merging.
  DOI: 10.1504/IJCSM.2023.10056283