基于小程序的零食铺商城的设计与实现外文翻译资料

1. System Analysis.
   1. Analysis and feasible
      1. Technical Feasibility

Depending on the spread of using Artificial intelligence applications in our daily life and the effect of Artificial Intelligence on human life, the need for a feasibility study appears, and such work needs a study that shows the pros and cons of using GAN, and the cost of that. Although the GAN is a very complicated field of study, it shows great usage, and it has been a very helpful technology that helped us to automate many tasks in our life. On one hand, this technology requires nothing except time of training to produce clear results and it does produce high quality and resolution photos with exact color brightness and shades. On the other hand, this technology may have a failure rate that would be shown as the result of the brownish hue of colors or some missing color areas in some of the photos but again it wont cost anything except time to train and understand the right results then work on producing perfect quality results after it takes the right amount of time needed to train, then it will start to give the right results automatically without any need of human supervision.

This implies that such kind of Artificial Intelligence application is very useful and have so many advantages in the automation of image colorization task which can make the human task easier and effective.

• • 1. Economic feasibility

This kind of Artificial intelligence application needs specific requirements such as high specification CPU and GPU that supports CUDA toolkit which can be provided by Nvidia GPUs which is more expensive than other companies.

That means not all computers can run the training algorithm which requires the user to buy high specification computer or laptop which can be expensive according this the cost of such application is very high, for this reason, economic feasibility should be done for such application to measure and study the cost that could be implied from implementing such project, based on this information the economic feasibility of such application implies that such project is costly and needs high budget for the research work and development and implementation of such application which means that companies want to invest in this kind of artificial engineering should make a very deep study on the cost and the budget needed to be spent on this type of artificial intelligence applications.

• • 1. Operational Feasibility

From a feasible business perspective, it is imperative to turn to market analysis and through a conscious and meticulous investigation of the user interest in this type of application, from an operational aspect, we find that such kind of application is operationally useful. I think its fair enough to say that using such Artificial intelligence applications can be helpful in the automation of image colorization depending on original-colored images without human supervision using a previously built knowledge model to color the grayscale images.

• 1. Functional requirements
• Import images: to import images from the dataset
• Analyze images: to analyze the original-colored images
• Build knowledge model: to store analysis result
• Color images: to color grayscale images
• Save images: to save colored images
  1. Non-functional requirements

Performance and scalability: in terms of performance the system will take a long time to give the results, however, it will give correct and accurate results if it takes the time needed.

Portability and compatibility: in terms of portability the system needs a core i7 and higher CPU, only and only Nvidia GPU with more than 4GB RAM, 8GB, and above dedicated RAM.

Reliability, availability, maintainability: In terms of reliability the system is reliable and wont be down easily, and the problems will take a short time to be solved.

Security: the system is very secured.

Usability: Very easy to be used by all kind of users.

• 1. Hardware requirements

CPU: Core i7 and above so it gives the needed computations

GPU: Nvidia GPU only because it supports the CUDA toolkit which is needed to be used with Pytorch

RAM: 8GB and above RAM: so, it can handle the work needed to be saved

Hard Drive: HDD hard drive will work, but SSD hard drive will be preferred as it is faster in reading and write data.

• 1. Analysis of System requirement

Table 1. analysis of system requirements

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