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Related Concept Videos

Machines01:19

Machines

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
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Machines: Problem Solving II01:30

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Machines: Problem Solving I01:22

Machines: Problem Solving I

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A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
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Mechanical Efficiency of Real Machines01:14

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The mechanical efficiency of a machine is a fundamental concept that describes how effectively a machine can convert input work into output work. According to this concept, the efficiency of a machine is equal to the ratio of the output work to the input work. An ideal machine, meaning a machine that has no energy losses, has an efficiency of one. This implies that the input work and the output work are equal.
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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
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Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

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The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
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Human-like machines: Transparency and comprehensibility.

Piotr M Patrzyk1, Daniela Link1, Julian N Marewski1

  • 1Faculty of Business and Economics,University of Lausanne,Quartier UNIL-Dorigny,Internef,CH-1015 Lausanne,Switzerland.piotr.patrzyk@unil.chdaniela.link@unil.chjulian.marewski@unil.ch.

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Artificial intelligence (AI) can improve by mimicking human cognition. Designing AI to transparently mirror human thought processes leads to more understandable and reliable machine decisions.

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Area of Science:

  • Cognitive Science
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Human cognitive systems excel in complex decision-making where current artificial intelligence (AI) algorithms fall short.
  • The optimal level for AI to approximate human cognition remains an open question in AI research.

Purpose of the Study:

  • To propose that AI should emulate human cognitive processes for transparent and comprehensible decision-making.
  • To argue for mirroring human cognition as a design principle for human-like AI.

Main Methods:

  • Conceptual analysis of AI design principles.
  • Argumentation based on the benefits of transparency in AI systems.

Main Results:

  • Human-like AI should prioritize transparent decision-making processes.
  • Accurate mirroring of human cognitive processes is key to achieving AI transparency.

Conclusions:

  • Designing AI to emulate human cognition enhances understandability and trustworthiness.
  • Transparency in AI decision-making, achieved through cognitive process mirroring, is crucial for human-like machine intelligence.