International Journal of Modeling, Simulation, and Scientific Computing

Large-scale virtual scene exploration is still a challenging task. The novice users can easily get distracted and disorientated, which results in being lost in space. Assisted camera control technology is the most effective solution for virtual environment exploration problems which requires viewpoint computation and path planning. In this paper, a novel approach for large-scale virtual scene based on viewpoint scoring is proposed. First, the scene was adaptively divided into several meaningful and easily analyzed subregions according to the optimal view distance criterion. Second, a novel viewpoint scoring method based on visual perception and information entropy fusion was developed for optimal viewpoint determination and greedy N-Bestviewpoint selection algorithm was utilized for visual perceptibility calculation. Then evolutionary programming approach for the Traveling Salesman problem was applied for intra-subregion and inter-subregion exploring path optimization. Finally, the Cubic Hermite Curve was introduced to smoothen the inflection point on the exploration path. The experimental results demonstrate that the proposed method can effectively generate an automatic smooth, informative, aesthetic and non-intersecting path, with the characteristics of good exploring comfort, strong immersion and high scene information perception.

Tree skeleton could be useful to agronomy researchers because the skeleton describes the shape and topological structure of a tree. The phenomenon of organs’ mutual occlusion in fruit tree canopy is usually very serious, this should result in a large amount of data missing in directed laser scanning 3D point clouds from a fruit tree. However, traditional approaches can be ineffective and problematic in extracting the tree skeleton correctly when the tree point clouds contain occlusions and missing points. To overcome this limitation, we present a method for accurate and fast extracting the skeleton of fruit tree from laser scanner measured 3D point clouds. The proposed method selects the start point and endpoint of a branch from the point clouds by user’s manual interaction, then a backward searching is used to find a path from the 3D point cloud with a radius parameter as a restriction. The experimental results in several kinds of fruit trees demonstrate that our method can extract the skeleton of a leafy fruit tree with highly accuracy.

Mobile ad hoc network (MANET) consists of a group of self-operated mobile nodes that form a network without considering predefined infrastructure. In the network, each node poses less energy due to battery-operated sensor nodes. Numerous methods are devised for routing, but each method suffered from the energy constraint. This paper proposes an energy-efficient multipath routing protocol for exploiting different routes between source and destination to mitigate energy constraints. The key idea is to determine the optimal path from a set of paths available between the source and the target node. To improve the security in routing protocol, the factors, like energy, trust, and mobility are considered as major components. Here, the trust is modeled by considering trust factors, like average encounter rate (AER), successful cooperation frequency (SCF), direct trust, integrity factor, and forwarding rate factor. Moreover, secure routing is performed between the nodes using the proposed Adaptive-Atom Whale Optimization algorithm (Adaptive-AWOA). The proposed Adaptive-AWOA) is designed by incorporating the Adaptive concept in the Atom Whale Optimization algorithm (AWOA). The fitness function is newly modeled considering mobility, energy, and trust factors. The proposed Adaptive-AWOA outperformed the other methods with a minimal end-to-end delay of 0.009, maximal throughput of 85.802% and maximal packet delivery ratio (PDR) of 97.391%, respectively.

The development of the tourism industry has led to increased pressure of people flow in tourist blocks. Therefore, it is critical to ease the traffic pressure in these blocks. This paper aims to identify the bottleneck links of street networks in tourist blocks to achieve the effective prevention of congestion accidents. A logit stochastic user equilibrium model combined with spatial syntax is presented to study the travelers’ route choice behavior. The nonlinear Bureau of Public Roads function is applied to calculate the time impedance of each street. A case analysis of the Chongqing Ciqikou tourist block shows that the bottleneck link has the features of high integration and a large degree of negative time impedance evolution. The research’s results are more consistent with practical circumstances because the influence of the road network topological structure on pedestrian path selection has been considered.

In this paper, preconditioned gridless methods are developed for solving the three-dimensional (3D) Euler equations at low Mach numbers. The preconditioned system is obtained by multiplying a preconditioning matrix of the type of Weiss and Smith to the time derivative of the 3D Euler equations, which are discretized under the clouds of points distributed in the computational domain by using a gridless technique. The implementations of the preconditioned gridless methods are mainly based on the frame of the traditional gridless method without preconditioning, which may fail to have convergence for flow simulations at low Mach numbers, therefore the modifications corresponding to the affected terms of preconditioning are mainly addressed in the paper. An explicit four-stage Runge–Kutta scheme is first applied for time integration, and the lower-upper symmetric Gauss-Seidel (LU-SGS) algorithm is then introduced to form the implicit counterpart to have the further speed up of the convergence. Both the resulting explicit and implicit preconditioned gridless methods are validated by simulating flows over two academic bodies like sphere or hemispherical headform, and transonic and nearly incompressible flows over one aerodynamic ONERA M6 wing. The gridless clouds of both regular and irregular points are used in the simulations, which demonstrates the ability of the method presented for coping with flows over complicated aerodynamic geometries. Numerical results of surface pressure distributions agree well with available experimental data or simulated solutions in the literature. The numerical results also show that the preconditioned gridless methods presented still functions for compressible transonic flow simulations and additionally, for nearly incompressible flow simulations at low Mach numbers as well. The convergence of the implicit preconditioned gridless method, as expected, is much faster than its explicit counterpart.

Nowadays, with the advent of the age of Web 2.0, several social recommendation methods that use social network information have been proposed and achieved distinct developments. However, the most critical challenges for the existing majority of these methods are: (1) They tend to utilize only the available social relation between users and deal just with the cold-start user issue. (2) Besides, these methods are suffering from the lack of exploitation of content information such as social tagging, which can provide various sources to extract the item information to overcome the cold-start item and improve the recommendation quality. In this paper, we investigated the efficiency of data fusion by integrating multi-source of information. First, two essential factors, user-side information, and item-side information, are identified. Second, we developed a novel social recommendation model called Two-Sided Regularization (TSR), which is based on the probabilistic matrix factorization method. Finally, the effective quantum-based similarity method is adapted to measure the similarity between users and between items into the proposed model. Experimental results on the real dataset show that our proposed model TSR addresses both of cold-start user and item issues and outperforms state-of-the-art recommendation methods. These results indicate the importance of incorporating various sources of information in the recommendation process.

Massive multiple-input multiple-output (massive MIMO) is a promising approach in wireless communication systems for providing improved link reliability and spectral efficiency and it helps several users. The main aim is to solve pilot contamination issue in massive MIMO systems; this research paper utilizes two approaches for reducing the contamination. This paper presents the user grouping approach based on sparse fuzzy C-means clustering (sparse FCM), which groups user parameters based on parameters such as large-scale fading factor, SINR, and user distance. Here, same pilot sequences are assigned to center users in which the impact of pilot contamination is limited, while the algorithm assigns orthogonal pilot sequences to the edge users that suffer severely from pilot contamination. Therefore, the proposed user grouping keeps away from the inappropriate grouping of users, enabling effective grouping even under the worst situations of the channel. Secondly, pilot scheduling is done based on elephant spider monkey optimization (ESMO), which is designed by integrating elephant herding optimization (EHO) into spider monkey optimization (SMO). The performance of pilot scheduling based on grouping-based ESMO is evaluated based on achievable rate and SINR. The proposed method achieves maximal achievable rate of 41.29bps/Hz and maximal SINR of 124.31dB.

The friction inevitably exists in the nonlinear suspension system for seats. It affects dynamic characteristics of the seat with the nonlinear suspension system. Analysis of the influences of the friction on the seat vibration responses is helpful to improve comfort. Moreover, it is also an important part of promoting the industrialization application of the nonlinear suspension system for seats. In order to verify the influences, a model of the seat with the nonlinear suspension system considering friction effects was established by combining experiments. Based on the model, by using the harmonic balance method, the analytical formulas of the seat frequency-domain vibration response considering friction effects were deduced, and the influences of the friction on the frequency response characteristics of the system were simulated and analyzed. Moreover, the influences of the friction on the time-domain response characteristics were investigated. The results show that the existence of the friction can help to reduce the vibration in the peak region and to increase the system stability, however, it is not conducive to the improvement of the seat comfort under random road conditions.

Given that various operational methods can be considered for a system, applying changes to study the results and determine the best operational technique is costly and disrupts the system. Thus, to analyze and evaluate the outcomes of employing different operational methods, simulation is utilized. In this study, to improve the performance of a medical imaging center (MIC), first, this center was simulated and then, different scenarios were defined and simulated. Subsequently, using the simulation results and for evaluating the scenarios through Data Envelopment Analysis (DEA), each scenario was considered as a decision making unit (DMU). Since simulation results of each scenario are uncertain and differ for different iterations, a method was utilized capable of using the results of all iterations. On the other hand, indexes such as satisfaction, patient’s appropriate waiting, helpful servicing with the least number nurses and the maximum number services that have fuzzy nature, are important factors for MIC. Therefore, using the simulation results and considering the system manager’s idea, a method was proposed for determining the fuzzy values of these indexes. Next, a ranking model and an algorithm were proposed for determining a unique ranking and introducing the best scenario to improve the performance of MIC.

This paper considers the task of evaluating micro-accelerations arising due to the temperature shock of large elastic elements when a small spacecraft leaves the Earth’s shadow. In this case, a one-dimensional model of thermal conductivity is used. Its solution was obtained by the method of direct approximation with the construction of difference schemes. It is shown that the accuracy of estimating micro-accelerations is commensurate with the accuracy of solving by a three-dimensional model of thermal conductivity. The proposed model allows reducing the time to obtain estimates and significantly simplifies the task at hand. The results of the work can be used in the formation of the dynamic characteristics of a small spacecraft for technological purposes.

Three-dimensional (3D) reconstruction of a human head with high precision has promising applications in scientific research, product design and other fields. However, it still faces resistance from two factors. One is inaccurate registration caused by symmetrical distribution of head feature points, and the other is economic burden due to high-accuracy sensors. Research on 3D reconstruction with portable consumer RGB-D sensors such as the Microsoft Kinect has been highlighted in recent years. Based on our multi-Kinect system, a precise and low-cost three-dimensional modeling method and its system implementation are introduced in this paper. A registration method for multi-source point clouds is provided, which can reduce the fusion differences and reconstruct the head model accurately. In addition, a template-based texture generation algorithm is presented to generate a fine texture. The comparison and analysis of our experiments show that our method can reconstruct a head model in an acceptable time with less memory and better effect.

The availability of network communication services is an important evaluation standard to measure the ability of the network to meet the user’s business needs. The current related research mostly focuses on the evaluation of network reliability, which cannot reflect the logical relationship between failure/maintenance and network performance parameters. Mobile Ad Hoc Network is a multi-hop, centerless and energy-constrained distributed system. Due to the dynamic change of communication environment and the instability of wireless link, Ad Hoc Network is facing great challenges in service availability. In this thesis, a fault-based quantitative evaluation model of traffic availability in Ad Hoc networks is proposed. By studying the multi-state Markov fault model of communication networks and the performance analysis of delay index based on CSMA∖CA protocol, the quantitative evaluation of traffic availability in Ad Hoc networks is realized. And the availability of tactical unit network under different typical network configuration conditions is analyzed through experiments.

The aim of this paper is testing a computer game as an alternative tool for the assessment of intelligence and creativity of school children. The relevance of the research task is determined by the growing interest in practical psychology in the use of computer games as a special diagnostic tool in educational process. There are two original factor models that have been developed and the structural equation modeling of measured parameters has been carried out. The relationships between game dynamic and final individual results in the computer game, on the one hand, and psychometric intelligence and divergent creativity, on the other, are presented. Weak correlation between the above-mentioned and individually measured intellectual and creativity characteristics of the participants with the computer game results was discovered. Consideration of these characteristics in the form of a common latent factor makes it possible to identify the corresponding dependencies only in some cases when there is a dividing the sample into groups according to their ability level. Particularly, the dynamics of game scoring allows to refer participants to the target group with a certain level of abilities (high intelligence and creativity versus low intelligence and creativity), and it is the high level of psychological traits that determines effectiveness in the game behavior, but not vice versa. The qualitative ratios of the two groups of subsets of participants were revealed: weak, medium and strong players and players with three different levels of psychological abilities. The prospects for the further use of computer games for assessment of cognitive abilities in the measurement of combination of psychological abilities are discussed.