The Impact of 3D Coordinate Technology Using Nanomaterials on Architecture Engineering Industry

Coordinate technologies play an important role in many industrial applications, especially for eco nanobuildings and spaces. Lately, the global new architecture seems to be more automated as appeared in the parametric architecture, topological, animate, metamorphic, and isomorphic and per formative architecture. They all depend on the visualization, the high precision techniques, and the 4th dimension all within sustainability. But till now, there is no main environmental space code, unit or standards to deal with to insure that the environmental design became in a form of an easier one to be the design of the era as all the global calls aware us to preserve the nature from pollution. Mainly within the call for the nanotechnology, if there is found a least architectural volumetric unit which can fulfill all the environmental sustainable systems within the visionary and the 4th dimensional acts, then we can act with the environment with easier spaces that can be duplicated in a uniform way, to work easily for measure and estimate the budget of his supposed built space. Therefore, the main liable issue concerns the research for the least architectural volumetric unit, and we can call it the nanoarchitectural unit. As nanoarchitecture is a virtual and proposed kind of architecture, which the architects aim to create it or follow it the nanotechnology to insure that the 3D technology is to submit as an application in all branches of science, to achieve a dream of the present-day from sustainability and environment for future generations. Accordingly, recent studies have confirmed that 3D coordinate technology using digital printing has an important subtle impact on industry, especially for green buildings and spaces.

Ten simple rules on writing clean and reliable open-source scientific software

Functional, usable, and maintainable open-source software is increasingly essential to scientific research, but there is a large variation in formal training for software development and maintainability. Here, we propose 10 “rules” centered on 2 best practice components: clean code and testing. These 2 areas are relatively straightforward and provide substantial utility relative to the learning investment. Adopting clean code practices helps to standardize and organize software code in order to enhance readability and reduce cognitive load for both the initial developer and subsequent contributors; this allows developers to concentrate on core functionality and reduce errors. Clean coding styles make software code more amenable to testing, including unit tests that work best with modular and consistent software code. Unit tests interrogate specific and isolated coding behavior to reduce coding errors and ensure intended functionality, especially as code increases in complexity; unit tests also implicitly provide example usages of code. Other forms of testing are geared to discover erroneous behavior arising from unexpected inputs or emerging from the interaction of complex codebases. Although conforming to coding styles and designing tests can add time to the software development project in the short term, these foundational tools can help to improve the correctness, quality, usability, and maintainability of open-source scientific software code. They also advance the principal point of scientific research: producing accurate results in a reproducible way. In addition to suggesting several tips for getting started with clean code and testing practices, we recommend numerous tools for the popular open-source scientific software languages Python, R, and Julia.

Decision Rule for Investment in Reusable Code

Reusable code helps to decrease code errors, code units and therefore development time. It serves to improve quality and productivity frameworks in software development. The question is not HOW to make the code reusable, but WHICH amount of software components would be most beneficial (i.e. costeffective in terms of reuse), and WHAT method should be used to decide whether to make a component reusable or not. If we had unlimited time and resources, we could write any code unit in a reusable way. In other words, its reusability would be 100%. However, in real life, resources and time are limited. Given these constraints, decisions regarding reusability are not always straightforward. The current chapter focuses on decision-making rules for investing in reusable code. It attempts to determine the parameters, which should be taken into account in decisions relating to degrees of reusability. Two new models are presented for decisions-making relating to reusability: (i) a restricted model, and (ii) a non-restricted model. Decisions made by using these models are then analyzed and discussed.

Decision Rule for Investment in Frameworks of Reuse

Reuse helps to decrease development time, code errors, and code units. Therefore, it serves to improve quality and productivity frameworks in software development. The question is not HOW to make the code reusable, but WHICH amount of software components would be most beneficial, that is, cost-effective in terms of reuse, and WHAT method should be used to decide whether to make a component reusable or not. If we had unlimited time and resources, we could write any code unit in a reusable way. In other words, its reusability would be 100%. However, in real life, resources are limited and there are clear deadlines to be met. Given these constraints, decisions regarding reusability are not always straightforward. The current research focuses on decision-making rules for investing in reuse frameworks. It attempts to determine the parameters, which should be taken into account in decisions relating to degrees of reusability. Two new models are presented for decision-making relating to reusability: (i) a restricted model and (ii) a non-restricted model. Decisions made by using these models are then analyzed and discussed.

Decision Rule for Investment in Frameworks of Reuse

Reuse helps to decrease development time, code errors, and code units. Therefore, it serves to improve quality and productivity frameworks in software development. The question is not HOW to make the code reusable, but WHICH amount of software components would be most beneficial, that is, cost-effective in terms of reuse, and WHAT method should be used to decide whether to make a component reusable or not. If we had unlimited time and resources, we could write any code unit in a reusable way. In other words, its reusability would be 100%. However, in real life, resources are limited and there are clear deadlines to be met. Given these constraints, decisions regarding reusability are not always straightforward. The current research focuses on decision-making rules for investing in reuse frameworks. It attempts to determine the parameters, which should be taken into account in decisions relating to degrees of reusability. Two new models are presented for decision-making relating to reusability: (i) a restricted model and (ii) a non-restricted model. Decisions made by using these models are then analyzed and discussed.