processible

简明释义

英[ˈprəʊsesəb(ə)l]美[ˈprɑːsesəbəl]

adj. 适合加工的；可处理的（等于 processable）

英英释义

单词用法

同义词

反义词

例句

1.Then we designed and synthesized a series of solution processible donor-acceptor small molecules as donor materials.

同时设计合成了一系列可溶液加工的新型有机给受体小分子太阳能电池给体材料。

2.The foamable composition includes a partially-crystalline melt processible perfluoropolymer and a foam nucleating package.

所述可发泡组合物包含部分结晶的可熔 融加工的全氟聚合物和泡沫成核组合。

3.The foamable composition includes a partially-crystalline melt processible perfluoropolymer and a foam nucleating package.

所述可发泡组合物包含部分结晶的可熔 融加工的全氟聚合物和泡沫成核组合。

4.The new algorithm is designed to handle large datasets that are processible in real-time.

新算法旨在处理可实时处理的大型数据集。

5.The data collected from the survey is not easily processible due to its unstructured format.

由于数据格式不规范，从调查中收集的数据不易可处理的。

6.We need to convert these files into a processible format for our analysis software.

我们需要将这些文件转换为我们的分析软件可以处理的格式。

7.Only processible documents will be accepted for the project submission.

只有可处理的文件才会被接受用于项目提交。

8.To ensure efficiency, all inputs must be processible without manual intervention.

为了确保效率，所有输入必须是可处理的，无需人工干预。

作文

In today's fast-paced world, the ability to manage information effectively is more crucial than ever. One of the key concepts that has emerged in various fields, including data science and information technology, is the notion of something being processible. This term refers to the capacity of data or materials to be processed or transformed into a usable form. Understanding what makes information processible is essential for anyone involved in these industries, as it directly impacts efficiency and productivity.To begin with, let us explore the characteristics that make data processible. First and foremost, data needs to be structured. Structured data is organized in a defined manner, often in tables or databases, which allows for easy access and manipulation. For example, a well-organized spreadsheet containing sales figures can be analyzed quickly to identify trends. In contrast, unstructured data, such as emails or social media posts, may not be immediately processible without significant preprocessing to extract relevant information.Another important aspect of processible data is its quality. High-quality data is accurate, complete, and timely. If the data is riddled with errors or outdated information, it becomes less processible, leading to incorrect conclusions and decisions. For instance, if a company relies on faulty customer data, it may target the wrong audience in its marketing campaigns, wasting resources and missing potential sales opportunities.Moreover, the format of the data also plays a vital role in determining whether it is processible. Data that is stored in compatible formats can be easily integrated and analyzed. For example, CSV files are widely used because they can be imported into various software programs without compatibility issues. On the other hand, proprietary formats may require specific tools to access, making the data less processible for broader usage.In addition to these factors, the context in which data is generated can influence its processibility. Data collected from reliable sources, such as established surveys or official records, tends to be more processible than data gathered from informal channels. This is particularly important in research settings where the validity of the findings depends on the quality of the data used.Furthermore, technology plays a significant role in enhancing the processibility of data. Advanced algorithms and machine learning techniques can automate the processing of large datasets, making it possible to derive insights that would be impossible to obtain manually. For instance, companies can use predictive analytics to forecast future trends based on historical data, enabling them to make informed business decisions.In conclusion, the concept of processible data is fundamental in our data-driven society. To ensure that information is processible, it must be structured, of high quality, in compatible formats, and derived from reliable sources. As technology continues to evolve, the ability to process data efficiently will become even more critical. By understanding and applying the principles of processibility, individuals and organizations can unlock the full potential of their data, driving innovation and success in their respective fields.

在当今快节奏的世界中，有效管理信息的能力比以往任何时候都更加重要。一个在数据科学和信息技术等各个领域出现的关键概念是某物的可处理性。这个术语指的是数据或材料被处理或转化为可用形式的能力。理解什么使信息可处理对于任何参与这些行业的人来说都是至关重要的，因为这直接影响到效率和生产力。首先，让我们探讨一下使数据可处理的特征。首先，数据需要结构化。结构化数据以定义的方式组织，通常以表格或数据库的形式存在，这使得访问和操作变得容易。例如，一个组织良好的电子表格，其中包含销售数据，可以快速分析以识别趋势。相反，非结构化数据，如电子邮件或社交媒体帖子，可能在没有显著预处理以提取相关信息的情况下无法立即可处理。另一个重要方面是数据的质量。高质量的数据是准确、完整和及时的。如果数据存在错误或过时的信息，它就变得不那么可处理，导致不正确的结论和决策。例如，如果一家公司依赖于错误的客户数据，它可能会在营销活动中针对错误的受众，浪费资源并错失潜在的销售机会。此外，数据的格式也在决定其是否可处理方面发挥着重要作用。以兼容格式存储的数据可以轻松集成和分析。例如，CSV文件被广泛使用，因为它们可以在各种软件程序中导入，而不会出现兼容性问题。另一方面，专有格式可能需要特定工具才能访问，从而使数据对更广泛的使用变得不那么可处理。除了这些因素外，数据生成的上下文也会影响其可处理性。从可靠来源收集的数据，如建立的调查或官方记录，通常比从非正式渠道收集的数据更具可处理性。这在研究环境中特别重要，因为研究结果的有效性取决于所用数据的质量。此外，技术在增强数据的可处理性方面也发挥着重要作用。先进的算法和机器学习技术可以自动处理大型数据集，使得获得手动无法获得的洞察成为可能。例如，公司可以使用预测分析根据历史数据预测未来趋势，从而使他们能够做出明智的商业决策。总之，可处理性数据的概念在我们的数据驱动社会中是基础。为了确保信息是可处理的，它必须是结构化的、高质量的、以兼容格式存在的，并且来自可靠来源。随着技术的不断发展，高效处理数据的能力将变得更加关键。通过理解和应用可处理性的原则，个人和组织可以释放其数据的全部潜力，推动各自领域的创新和成功。