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Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

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Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
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Elastic Collisions: Introduction01:00

Elastic Collisions: Introduction

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An elastic collision is one that conserves both internal kinetic energy and momentum. Internal kinetic energy is the sum of the kinetic energies of the objects in a system. Truly elastic collisions can only be achieved with subatomic particles, such as electrons striking nuclei. Macroscopic collisions can be very nearly, but not quite, elastic, as some kinetic energy is always converted into other forms of energy such as heat transfer due to friction and sound. An example of a nearly...
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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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Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

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In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
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Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Types of Collisions - II01:19

Types of Collisions - II

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When two or more objects collide with each other, they can stick together to form one single composite object (after collision). The total mass of the object after the collision is the sum of the masses of the original objects, and it moves with a velocity dictated by the conservation of momentum. Although the system's total momentum remains constant, the kinetic energy decreases, and thus such a collision is an inelastic collision. Most of the collisions between objects in daily life are...
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Related Experiment Video

Updated: Nov 17, 2025

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
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Collision Avoidance Resource Allocation for LoRaWAN.

Natalia Chinchilla-Romero1, Jorge Navarro-Ortiz1,2, Pablo Muñoz1,2

  • 1Department of Signal Theory, Telematics and Communications, University of Granada, 18071 Granada, Spain.

Sensors (Basel, Switzerland)
|February 12, 2021
PubMed
Summary
This summary is machine-generated.

A new algorithm, Collision Avoidance Resource Allocation (CARA), significantly boosts LoRaWAN network capacity by intelligently managing device transmissions. This enhances Internet of Things (IoT) connectivity without disrupting existing LoRaWAN devices.

Keywords:
LoRa MACLoRaWANPERcapacitypath lossthroughput

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Area of Science:

  • Wireless Communication Networks
  • Internet of Things (IoT)
  • Network Capacity Optimization

Background:

  • The proliferation of IoT devices necessitates scalable and efficient wireless communication solutions.
  • Low Power Wide Area Networks (LPWAN), particularly LoRaWAN, are crucial for IoT due to their range and low power, but face capacity limitations.
  • Existing LoRaWAN networks struggle to accommodate the rapidly growing number of connected devices.

Purpose of the Study:

  • To introduce a novel algorithm, Collision Avoidance Resource Allocation (CARA), designed to overcome LoRaWAN capacity constraints.
  • To significantly increase the data transmission capacity of LoRaWAN networks.
  • To ensure compatibility of the proposed solution with existing LoRaWAN infrastructure.

Main Methods:

  • Development of the Collision Avoidance Resource Allocation (CARA) algorithm.
  • Leveraging LoRaWAN's multichannel structure and spreading factor orthogonality for collision avoidance.
  • Simulation under ideal and realistic radio link conditions.
  • Implementation of a proof-of-concept using commercial LoRaWAN equipment.

Main Results:

  • CARA demonstrated a 95.2% capacity increase over standard LoRaWAN under ideal conditions.
  • A capacity increase of nearly 40% was achieved with a realistic propagation model.
  • CARA devices were shown to coexist effectively with traditional LoRaWAN devices, enabling simultaneous operation.
  • Proof-of-concept implementation validated the algorithm's feasibility and operational correctness.

Conclusions:

  • The CARA algorithm presents a viable and effective solution for enhancing LoRaWAN network capacity.
  • CARA offers substantial performance improvements, addressing a key limitation of current LPWAN technology.
  • The coexistence capability ensures a smooth transition and integration path for upgrading existing IoT networks.