With gigantic growth of data volume that is moved across the web links today, there has been a gigantic measure of perplexing information produced. Extremely huge sets of data including universities, organizations framework, institution gas, petroleum sector, photogrammetry, healthcare, and archaeology, that have so enormous thus complex information with more differed structure. The major challenge is how to handle this significant volume of data, also in archaeological photogrammetry which alluded to as Big Data. Although big data has to be securely flying and conveyed through the internet. It cannot be controlled with regular conventional methods that fail to handle it, so there is a need for more up-to-date developed tools. The big data have frequently divided into V’s characteristics beginning from three V’s: volume, velocity and variety. The initial three V’s have been stretched out during time through researches to arrive 56 V’s till now. Among them are three newfound by the author that implies it multiplied near twenty times. Researcher had to dive to search for all of these characteristics in many researches to detect and build comparisons to answer the old, current, and restored essential inquiry, “how many V’s aspects (characteristics) in big data with archaeological photogrammetry and blockchain.” This paper provides a comprehensive overview of all secured big data V’s (characteristics) as well as their strength and limitations with archaeological photogrammetry and blockchain.

中文翻译：

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基于近似导数算法的类脑尖峰神经网络高光谱图像分类


随着当今通过网络链接传输的数据量的巨大增长，产生了大量令人困惑的信息。极其庞大的数据集，包括大学、组织框架、机构天然气、石油部门、摄影测量、医疗保健和考古学，其信息如此庞大、复杂，结构也更加不同。主要挑战是如何处理如此大量的数据，在考古摄影测量中也被称为大数据。尽管大数据必须通过互联网安全地飞行和传输。它无法用无法处理的常规方法来控制，因此需要更先进的开发工具。大数据经常从三个V开始划分V特征：数量、速度和多样性。随着时间的推移，最初的三个V已经通过研究延长到了现在的56个V。其中三个是作者新发现的，意味着它增加了近二十倍。研究人员必须在许多研究中深入寻找所有这些特征，以检测和建立比较，以回答旧的、当前的和恢复的基本问题，“考古摄影测量和区块链的大数据中有多少 V 的方面（特征）”。本文全面概述了所有安全大数据 V（特征）及其在考古摄影测量和区块链方面的优势和局限性。