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相关概念视频

Data Collection I01:30

Data Collection I

6.0K
Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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Data Collection III01:05

Data Collection III

2.6K
The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the...
2.6K
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.6K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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Data Collection II01:29

Data Collection II

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The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and...
7.5K
Data Collection by Observations01:08

Data Collection by Observations

11.7K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
11.7K
Ethical Standards I01:25

Ethical Standards I

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The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
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Updated: May 28, 2025

Data Communication Based on MQTT in a Polymer Extrusion Process
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Data Communication Based on MQTT in a Polymer Extrusion Process

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基于分散的标识符的物联网数据可信收集.

Baitao Zhang1, Rui Shi2, Xiaolin Li3

  • 1School of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China.

Scientific reports
|February 8, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了TrID,这是一个新的物联网数据安全方案,使用去中心化标识符 (DID) 来增强数据收集. TrID为物联网 (IoT) 数据提供了一个分布式,高效和安全的解决方案,克服了集中和区块链模型的局限性.

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科学领域:

  • 计算机科学 计算机科学
  • 网络安全 网络安全
  • 物联网 (IoT) 的物联网 (IoT) 的物联网.

背景情况:

  • 物联网数据收集在访问,传输和存储方面面临着关键的安全挑战.
  • 像证书颁发机构 (CA) 这样的现有解决方案是集中式的,而区块链方法缺乏效率.
  • 由于用户对物联网设备的控制有限,智能医疗,家庭和城市等行业特别容易受到攻击.

研究的目的:

  • 提出一种新的物联网数据收集的信任模型,利用去中心化标识符 (DID).
  • 引入TrID,一个物联网数据安全收集方案,旨在提高安全性和效率.
  • 解决物联网环境中集中和基于区块链的安全解决方案的局限性.

主要方法:

  • 开发了一个基于分散识别器 (DID) 的信任模型.
  • 提出了使用分布式架构的TrID (可靠和集成数据) 计划.
  • 实施并评估TrID在相互认证协议和数据解密中的性能.

主要成果:

  • TrID解决了传统物联网安全模型中固有的集中问题.
  • 在链上解决方案中,TrID的身份验证时间成本约为10%.
  • 在1000KB的区块大小下解密10MB的数据需要不到100ms,这表明了高效率.

结论:

  • 与现有的方法相比,TrID为物联网数据收集提供了一种更安全,更有效的方法.
  • 分布性质和独立于区块链的特性提高了安全性和性能.
  • TrID提供了一种可行的解决方案,用于保护敏感物联网应用中的数据,例如智能医疗保健和城市.