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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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Zones of Protection01:16

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In power systems, the entire setup is divided into protective zones to isolate faults and protect the rest of the network. These zones include generators, transformers, buses, transmission lines, distribution lines, and motors. Each zone can be visualized as a separate room in a house, with each room protected by its own circuit breaker.
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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
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Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

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It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
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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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Updated: Oct 17, 2025

Peering into the Dynamics of Social Interactions: Measuring Play Fighting in Rats
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Multistage Attack-Defense Graph Game Analysis for Protection Resources Allocation Optimization Against Cyber Attacks

Chengwu Shao1, Yan-Fu Li1

  • 1Department of Industrial Engineering, Tsinghua University, Beijing, China.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|October 12, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a multistage attack-defense graph game model to optimize resource allocation for industrial systems facing sequential cyber threats. The model accounts for evolving attacker rationality and dynamic strategy spaces, improving defense against complex attacks.

Keywords:
Attack-defense graphgame theoryrationality evolution

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Area of Science:

  • Cybersecurity
  • Game Theory
  • Industrial Control Systems

Background:

  • Modern industrial systems are increasingly vulnerable to sophisticated cyber attacks, as demonstrated by the 2015 Ukrainian power grid incident.
  • Existing defense strategies often assume static attacker and defender capabilities, which is insufficient for dynamic, sequential attacks.
  • The Ukrainian power grid attack highlighted the need for dynamic defense models that account for evolving vulnerabilities and attacker behavior.

Purpose of the Study:

  • To propose a novel multistage attack-defense graph game model for optimizing resource allocation in industrial systems.
  • To address the limitations of static models by incorporating dynamic strategy spaces and evolving attacker rationality.
  • To provide practical guidance for defenders against sophisticated, sequential cyber attacks.

Main Methods:

  • Development of a multistage attack-defense graph game model.
  • Incorporation of dynamic strategy spaces that change during attack-defense confrontations.
  • Modeling of attacker rationality evolution due to factors like asymmetric information and learning.

Main Results:

  • The proposed model demonstrates superior effectiveness compared to static models in simulated Ukrainian-style cyber attacks.
  • Simulation results validate the model's ability to assist defenders in optimal resource allocation against sequential threats.
  • The approach effectively handles dynamic strategy spaces and evolving attacker behavior.

Conclusions:

  • The multistage attack-defense graph game model offers a more practical and effective solution for defending industrial systems against complex cyber threats.
  • The model's consideration of dynamic elements provides valuable insights for power grid operators and other industrial defenders.
  • Further research can build upon this model to enhance resilience against evolving cyber vulnerabilities.