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Distributed Loads01:19

Distributed Loads

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Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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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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Transformers in Distribution System01:27

Transformers in Distribution System

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Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
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Short-distance Transport of Resources02:12

Short-distance Transport of Resources

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Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
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Updated: Sep 3, 2025

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

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B/S-Based Construction of a Big Data Logistics Platform.

Li Zhang1

  • 1School of Management, Xi'an University of Finance and Economics, Xi'an, Shaanxi, China.

Computational Intelligence and Neuroscience
|July 25, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a big data-enabled logistics detection system to enhance efficiency and reduce costs in smart logistics. The developed model integrates supply, demand, and supervision subsystems for optimized operations.

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Area of Science:

  • Computer Science
  • Information Technology
  • Logistics Management

Background:

  • The Internet of Things (IoT) generates vast amounts of data, necessitating big data and cloud computing solutions.
  • Big data and cloud computing are increasingly applied in logistics, transforming traditional systems into smart logistics.
  • Existing smart logistics models face challenges in public information platforms, coordination, and government integration, leading to inefficiencies.

Purpose of the Study:

  • To design a novel big data-enabled logistics detection system.
  • To construct an integrated smart logistics model.
  • To realize an operational smart logistics model utilizing big data and cloud computing.

Main Methods:

  • Development of a big data-enabled logistics detection system with a B/S architecture.
  • Construction of a smart logistics model comprising supply, demand, and supervision subsystems.
  • Implementation and operation of the smart logistics model leveraging big data cloud computing.

Main Results:

  • A functional big data-enabled logistics detection system was successfully implemented.
  • The integrated smart logistics model demonstrated improved operational processes.
  • The system addresses key issues in traditional logistics such as low efficiency and high costs.

Conclusions:

  • The designed system and model offer a viable solution for enhancing smart logistics operations.
  • Big data and cloud computing are crucial for the advancement of modern logistics.
  • The research contributes to optimizing logistics through technological integration and system design.