The 2018 International Conference on Modern Computer Science and Applications (MCSA2018)

This editorial describes a special issue of papers from the 2018 International Conference on Modern Computer Science and Applications.1 There are 15 papers in this special issue. The debate on network neutrality regulation: a technological innovation perspective focuses on the impacts of network neutrality regulation on technological innovations in telecommunications. This study first briefly discusses the significant role of technological innovation in telecommunications. Then, we adopt a stylized two-sided model (Internet broadband provider connects the two sides of the Internet, ie, content providers and end customers) and use a two-stage game theory to examine the decision-making of network operators and content providers in two alternative situations, respectively, that is, the neutral regime and the non-neutral regime. By comparing players' decisions in the two regimes, the impacts of network neutrality regulation on innovations are revealed. Non-neutral regime increases both network infrastructure investments and congestion-sensitive content innovations. In other words, network neutrality regulation inhibits telecommunications technological innovation while hindering the emergence of high-level content innovation.2 An effective application of 3D cloud printing service quality evaluation in BM-MOPSO proposes a type of order task execution process evaluation indicator of an eight-dimensional target component, which includes T, Q, Mat, R, Flex, C, Ft, and Sa. Based on this research, combined with the Pareto optimal theory, this paper proposes a BM-MOPSO algorithm of order task execution evaluation model in which the evaluations are conducted on the basis of research and exploration work from the task before execution, task execution, and task after execution. Finally, the algorithm is used to solve 3D Cloud Printing Quality evaluation, and the above method is verified to show the effectiveness by MATLAB software.3 Design of damage identification algorithm for mechanical structures based on convolutional neural network proposes a numerical example of a three-layer steel frame used to construct the sample space of the convolution neural network by using the method proposed by the combined parameter method. The damage location and damage degree of the network with large damage and continuous unit damage and discontinuous unit damage are tested, respectively, and the training accuracy of the network meets the requirements completely at the same time. The location and degree of damage are measured in the case of small damage and continuous unit damage. Although the training of the degree of injury is not ideal in the case of small damage, it basically meets the requirements. It also shows that the combined parameter method can accurately identify the damage location and damage degree of the frame structure.4 Experimental investigation of effect of tooth geometrical parameters to flow characteristics in slant labyrinth seals makes an experimental investigation to study the influence of the geometry parameters of slant straight-through labyrinth seals on sealing characteristics. Moreover, 22 models with different geometry parameters were designed, and the geometry parameters studied include seal clearance, fin height, fin pitch, fin tip thickness, and fin number. The results showed that when p0/pn ranged from 1.2 to 1.8, the discharge coefficient increased with the drop pressure ratio, seal clearance, and fin tip thickness and decreased with fin height, fin pitch, and fin number. The rank of sensitivity of each parameter's variation in the unit size on sealing characteristics is seal clearance, fin tip thickness, fin pitch, back angle, fin height, and front angle. The correlation of different parameters was summarized for the designing of advanced labyrinth seals.5 A modified PSO algorithm for task scheduling optimization in cloud computing proposes a cloud computing energy consumption model, which takes into account the execution and transmission cost of the processor. Then, based on this model, we put forward a task scheduling optimization algorithm named Modified Particle Swarm Optimization (M-PSO) to handle the local optimum and slow convergence problem. Different from the PSO, M-PSO can dynamically adjust the inertia weight coefficient to improve the speed of convergence according to the number of iterations. Finally, the performance of the proposed algorithm is evaluated through the CloudSim toolkit, and the experimental results show that M-PSO can efficiently reduce the total cost compared with other algorithms.6 Application of VR computer image technology in 3D virtualization of sports human science focuses on the application of geometric reconstruction methods to study the application of VR computer images in the three-dimensional virtualization of sports human science. By combining the background difference method and the interframe difference method, the target region where the moving human body is located can be accurately extracted from the video, and then the idea of the human body can be divided along the virtual plane. Finally, the endpoint feature points of the human body are determined by the geodesic distance, and a three-dimensional model skeleton is buried using a discrete penalty function and an image-based three-dimensional reconstruction system is realized.7