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Related Concept Videos

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...
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Data Collection I01:30

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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 by Experiments01:13

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Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
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Data Collection by Survey01:07

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The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
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Data Collection by Observations01:08

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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...
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Data Collection III01:05

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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...
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A Collaborative Data Collection Scheme Based on Optimal Clustering for Wireless Sensor Networks.

Guorui Li1, Haobo Chen2, Sancheng Peng3,4

  • 1School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China. lgr@neuq.edu.cn.

Sensors (Basel, Switzerland)
|August 4, 2018
PubMed
Summary
This summary is machine-generated.

We introduce an optimal clustering scheme for energy-efficient data collection in Wireless Sensor Networks (WSNs). This method significantly reduces energy consumption and extends network lifetime by 20x.

Keywords:
clusteringcompressed sensingdata collectionoptimizationwireless sensor networks

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Energy-efficient data collection is a critical challenge in resource-constrained Wireless Sensor Networks (WSNs).
  • Existing data collection models often struggle with balancing energy consumption and network longevity.

Purpose of the Study:

  • To propose a novel collaborative data collection scheme for WSNs.
  • To achieve energy efficiency and load balancing through optimal clustering.

Main Methods:

  • Developed an optimal clustering model as a separable convex optimization problem.
  • Derived analytical solutions for optimal cluster size and data transmission radius.
  • Designed a Cluster Heads (CHs)-linking algorithm using a pseudo Hilbert curve for data aggregation.
  • Implemented a distributed cluster-constructing algorithm for decentralized network organization.

Main Results:

  • The proposed scheme significantly reduces total energy consumption by 17.9% (vs. compression-based) and 67.9% (vs. non-compression-based).
  • Network lifetime is extended by at least 20 times compared to existing methods.
  • Energy consumption distribution among CHs is effectively balanced.

Conclusions:

  • The optimal clustering approach provides a superior solution for energy-efficient and load-balanced data collection in WSNs.
  • This method enhances overall network performance and extends operational lifespan.