processable

简明释义

英[/ˈprɒsəˌseɪbəl/]美[/ˈprɒsəˌseɪbəl/]

adj. 可加工的；适合加工的

英英释义

单词用法

同义词

反义词

例句

1.The Zn-Al alloy has many advantages, such as good mechanical property, strong antifriction property, processable property, small density, low melting point, affluent raw material, low cost and so on.

高铝锌基合金具有优良的力学性能、耐摩性能、机加工性能、以及密度小、熔点低、原材料来源丰富和成本低等优点。

2.If you are primarily authoring topics, it makes sense to use a DTD that is designed for topics and can scale to large, processable collections of topics.

如果主要编辑主题，则最好使用为主题设计的DTD，也可放大到大型的、可处理的主题集合。

3.In addition, transreption allows the system to move information from inefficient forms into efficiently processable forms, for example, source code to byte code.

此外，transreption可以让系统将信息从低效形式转化为高效可处理的形式，例如，将源代码转化为字节码。

4.These chemicals are compatible and processable in urethane foam formulations and less flammable than foams derived from other conventional type glycols.

这些化学制品适合于尿烷泡沫加工，并较传统类型二元醇衍生的泡沫不易燃烧。

5.We have introduced a series of standard prefix mappings (XHTML, RDF and RDFS) as well as for vocabularies that will be of use to describe our event in machine processable ways.

我们已经介绍了一系列标准的前缀映射(XHTML、RDF和RDFS)，也介绍了用来描述机器可处理的方法中事件的词汇。

6.The Zn-Al alloy has many advantages, such as good mechanical property, strong antifriction property, processable property, small density, low melting point, affluent raw material, low cost and so on.

高铝锌基合金具有优良的力学性能、耐摩性能、机加工性能、以及密度小、熔点低、原材料来源丰富和成本低等优点。

7.The data we collected is not in a processable 可处理的 format.

我们收集的数据不是以< span>可处理的格式。

8.The software can only handle processable 可处理的 images.

该软件只能处理< span>可处理的图像。

9.The report was generated in a processable 可处理的 format for easy sharing.

报告以< span>可处理的格式生成，以便于共享。

10.Ensure all inputs are processable 可处理的 to avoid errors.

确保所有输入都是< span>可处理的以避免错误。

11.We need to convert these files into a processable 可处理的 type before analysis.

在分析之前，我们需要将这些文件转换为< span>可处理的类型。

作文

In today's digital age, the amount of data generated is staggering. Every click, every transaction, and every interaction contributes to a vast pool of information. However, not all of this data is equally useful. To make sense of the overwhelming volume of information, we must focus on what is processable. This term refers to data that can be analyzed, manipulated, or transformed into actionable insights. Without identifying processable data, organizations may struggle to derive meaningful conclusions from their datasets. To illustrate the importance of processable data, consider a retail company that collects customer purchase information. If the data is unstructured, such as comments from social media or open-ended survey responses, it may not be immediately useful. However, by employing natural language processing techniques, the company can convert this unstructured data into processable formats. This allows them to analyze customer sentiment and preferences, ultimately guiding their marketing strategies. Moreover, in the realm of scientific research, processable data plays a crucial role in advancing knowledge. Researchers often gather massive datasets from experiments or observational studies. For these datasets to be useful, they must be cleaned, organized, and formatted correctly. Only then can researchers perform statistical analyses and draw valid conclusions. For instance, genomic data must be processable to identify genetic markers associated with diseases, paving the way for personalized medicine. In contrast, when data is not processable, it can lead to wasted resources and misguided decisions. Companies that fail to invest in data management systems may find themselves overwhelmed by irrelevant information. This can result in poor customer service, ineffective marketing campaigns, and ultimately, loss of revenue. Therefore, recognizing which data is processable is essential for any organization aiming to thrive in a competitive landscape. Furthermore, technology continues to evolve, making it easier to transform raw data into processable formats. Machine learning algorithms can sift through vast amounts of information, identifying patterns and trends that would be impossible for humans to detect. This capability not only enhances decision-making but also fosters innovation. By leveraging processable data, companies can develop new products, improve existing services, and stay ahead of market trends. In conclusion, the concept of processable data is fundamental in our data-driven world. It empowers organizations to extract valuable insights from the noise of information overload. Whether in business, science, or technology, understanding and utilizing processable data can lead to significant advancements and success. As we continue to generate data at an unprecedented rate, the ability to identify and work with processable information will become increasingly vital for achieving our goals and driving progress.

在当今数字时代，产生的数据量惊人。每一次点击、每一笔交易和每一次互动都为一个巨大的信息池做出了贡献。然而，并非所有这些数据都是同样有用的。为了理解这庞大的信息量，我们必须关注什么是可处理的。这个术语指的是可以分析、操作或转化为可行见解的数据。如果不识别可处理的数据，组织可能会难以从其数据集中得出有意义的结论。为了说明可处理的数据的重要性，考虑一家收集客户购买信息的零售公司。如果数据是非结构化的，例如社交媒体上的评论或开放式调查响应，它可能不会立即有用。然而，通过采用自然语言处理技术，公司可以将这些非结构化数据转换为可处理的格式。这使他们能够分析客户情绪和偏好，最终指导他们的营销策略。此外，在科学研究领域，可处理的数据在推动知识进步方面发挥着至关重要的作用。研究人员通常从实验或观察研究中收集大量数据集。为了使这些数据集有用，它们必须被清理、组织并正确格式化。只有这样，研究人员才能进行统计分析并得出有效结论。例如，基因组数据必须是可处理的，以识别与疾病相关的遗传标记，从而为个性化医学铺平道路。相反，当数据不可处理时，可能导致资源浪费和错误决策。未能投资于数据管理系统的公司可能会发现自己被无关的信息淹没。这可能导致客户服务不佳、营销活动无效，最终导致收入损失。因此，识别哪些数据是可处理的对于任何旨在在竞争环境中蓬勃发展的组织来说都是至关重要的。此外，技术不断发展，使得将原始数据转化为可处理的格式变得更加容易。机器学习算法可以筛选大量信息，识别出人类难以检测的模式和趋势。这种能力不仅增强了决策能力，还促进了创新。通过利用可处理的数据，公司可以开发新产品、改进现有服务，并在市场趋势中保持领先。总之，可处理的数据概念在我们以数据驱动的世界中是基础。它使组织能够从信息过载的噪声中提取有价值的见解。无论是在商业、科学还是技术领域，理解和利用可处理的数据都能带来显著的进步和成功。随着我们继续以前所未有的速度生成数据，识别和处理可处理的信息的能力将变得越来越重要，以实现我们的目标并推动进步。