Implementation Of Docker Container On Local Network By Applying Reverse Proxy

Virtualization is an implementation of a software. Virtualization technology has changed the direction of the computer industrial revolution by reducing capital costs and operating costs. The availability of a virtualization will also increase the availability of higher services and data protection mechanisms. Docker is configured to create multiple containers on a network, each container containing one image. The three containers will be created in one compose where each container is connected to each other for WordPress configuration and two composers will be created. Furthermore, from each compose a reverse proxy configuration is carried out which aims to set a different domain address. Lighten computer performance and can reduce the required storage so as to make hosting more effective and efficient. Containers also provide a security advantage over complete control over management running on separate, isolated containers.

A Data-Driven Platform to Computer Performance Analysis and Recommendation using AI and Big Data Analysis

When I was assembling the computer, I found a problem. This problem is that we need to spend a lot of time and energy when we choose a desktop with a configuration and price that we are satisfied with [5]. Some computer websites will only recommend some ordinary desktops to users. Does not allow users to get what they really want, and some other shops that assemble computer mainframes use the characteristics of customers that do not understand computers to increase prices. So I wanted to create a software to help these people who need to assemble a computer to find the most suitable computer efficiently and in accordance with their requirements [6]. This program, according to the needs of users, artificial intelligence application crawler technology can help users find the most suitable computer parts based on big data, and help users get the most cost-effective self-assembled computer host. We applied our application to match a person in need of a computer host with My Platform and conducted a qualitative evaluation of the method [7]. The results showed that My Platform can efficiently and quality match the user's needs and find the best solution for the user.

Partial Color Photo Processing Method for Components Based on Image Enhancement Technology

Computer vision is currently playing an increasingly important role in automatically identifying the character of the image processing technology as research hotbed in the field of smart computing, OCR, face recognition, fingerprinting, biometric recognition, and so forth. Content-based image recovery, video recovery, multimedia collection, watermarking, games, film stunts, virtual reality, e-commerce, and other apps are available all round. The color pictures of parts taken by industrial cameras depend on computer performance and the intricate environment, and in particular, on the whole resolution image display, a lot of CPU resources are needed. Some details cannot be shown completely at the same time. If the image is not sufficiently clearly visible, methods for image processing like improvement, noise reduction, and interpolation must be used to improve color photo clarity. This article, based on the OpenCV platform, uses frequency domain filters, median filters, Fourier transform, and other image improvement technologies to remove image noise in order to enhance the quality of local photos from industrial cameras’ components. Finally, clear and available image information is obtained in different experimental methods, which check the application of image enhancement technology to image rebuilding. Finally, the performance of the proposed method in terms of CPBD value, definition Q value, and operation time is compared, which shows that the proposed method has obvious advantages in the above performance.

MagmaFOAM-1.0: a modular framework for the simulation of magmatic systems

Numerical simulations of volcanic processes play a fundamental role in understanding the dynamics of magma storage, ascent and eruption. The recent extraordinary progress in computer performance and improvements in numerical modeling techniques allow simulating multiphase systems in mechanical and thermodynamical disequilibrium. Nonetheless, the growing complexity of these simulations requires the development of flexible computational tools that can easily switch between sub-models and solution techniques. In this work we present MagmaFOAM, a library based on the open source computational fluid dynamics software OpenFOAM, that incorporates models for solving the dynamics of multiphase, multicomponent magmatic systems. Retaining the modular structure of OpenFOAM, MagmaFOAM allows run-time selection of the solution technique depending on the physics of the specific process, and sets a solid framework for in-house and community model development, testing and comparison. MagmaFOAM models thermo-mechanical non-equilibrium phase coupling and phase change, and implements state-of-the-art multiple volatile saturation models and constitutive equations with composition-dependent and space-time local computation of thermodynamic and transport properties. Code testing is performed using different multiphase modeling approches for processes relevant to magmatic systems: Rayleigh-Taylor instability, for buyoancy-driven magmatic processes; multiphase shock tube simulations, propedeutical to conduit dynamics studies; bubble growth and breakage in basaltic melts. Benchmark simulations illustrate the capabilities and potential of MagmaFOAM to account for the variety of non-linear physical and thermodynamical processes characterizing the dynamics of volcanic systems.

A Parallel Processing Approach to Dynamic Simulation of Ethylbenzene Process

Parallel computing has been developed for many years in chemical process simulation. However, existing research on parallel computing in dynamic simulation cannot take full advantage of computer performance. More and more applications of data-driven methods and increasing complexity in chemical processes need faster dynamic simulators. In this research, we discuss the upper limit of speed-up for dynamic simulation of the chemical process. Then we design a parallel program considering the process model solving sequence and rewrite the General dynamic simulation & optimization system (DSO) with two levels of parallelism, multithreading parallelism and vectorized parallelism. The dependency between subtasks and the characteristic of the hottest subroutines are analyzed. Finally, the accelerating effect of the parallel simulator is tested based on a 500 kt·a−1 ethylbenzene process simulation. A 5-hour process simulation shows that the highest speed-up ratio to the original program is 261%, and the simulation finished in 70.98 s wall clock time.

Analysis of Optimal Control Strategies for Preventing Computer Virus Infection and Reduce Program Files Damage with Other Symptoms

Program files damage and other computer virus symptoms has become a very threatening issue to computer performance. This paper considered an model with incidence of infected and program files damaged computers and saturated incidence of vaccination and treatment function. Two control functions have been used; one for vaccinating the susceptible computer population and the other for the treatment of the program files damaged computer population. The Pontryagin’s Maximum Principle has been used to characterize the optimal control whose numerical results show the positive impact of the two controls used for controlling the infection dynamics of computer virus. Actually the intention of this study is to minimize the number of infected and program files damaged computer systems and at the same time minimize the cost associated to the controls. Efficiency analysis is also studied to determine the best control strategy among vaccination and treatment. Numerical simulations were carried out in this model to demonstrate the analytical results and it was revealed that combination of vaccination and treatment is the most successful way to minimize the incidence of program files damage.

A Parallel Attribute Reduction Method Based on Classification

Parallel processing as a method to improve computer performance has become a development trend. Based on rough set theory and divide-and-conquer idea of knowledge reduction, this paper proposes a classification method that supports parallel attribute reduction processing, the method makes the relative positive domain which needs to be calculated repeatedly independent, and the independent relative positive domain calculation could be processed in parallel; thus, attribute reduction could be handled in parallel based on this classification method. Finally, the proposed algorithm and the traditional algorithm are analyzed and compared by experiments, and the results show that the proposed method in this paper has more advantages in time efficiency, which proves that the method could improve the processing efficiency of attribute reduction and makes it more suitable for massive data sets.