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Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Reasoning is the action of thinking about something in a logical, sensible way. It is integral to problem-solving, decision-making, and critical thinking. Reasoning can be inductive or deductive. Reasoning involves transforming information into conclusions, which is essential for problem-solving, decision-making, and critical thinking.
Inductive reasoning involves deriving generalizations from specific observations. This type of reasoning helps form beliefs about the world. For example,...
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Deductive Reasoning01:16

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Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
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Inductive Reasoning00:59

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Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
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Cognitive Dissonance01:38

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Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
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Protein Networks02:26

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Related Experiment Video

Updated: Jan 31, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
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Applying Case-Based Reasoning to Tactical Cognitive Sensor Networks for Dynamic Frequency Allocation.

Jae Hoon Park1, Won Cheol Lee2, Joo Pyoung Choi3

  • 1Department of Information and Telecommunication Engineering, Soongsil University, Seoul 06978, Korea. pjh901118@soongsil.ac.kr.

Sensors (Basel, Switzerland)
|December 20, 2018
PubMed
Summary

This study introduces a cognitive radio engine for tactical networks, enabling dynamic spectrum access by identifying available frequencies while protecting primary users. The system reliably avoids interference, ensuring efficient communication for secondary users.

Keywords:
case-based reasoningchannel occupancy probabilitycognitive radio enginemilitary tactical communicationstactical cognitive radio sensor network

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Wireless Communication

Background:

  • Tactical wireless sensor networks require dynamic spectrum access to identify available frequencies.
  • Incumbent communication devices (primary users) must be protected from interference by secondary users.

Purpose of the Study:

  • To propose a cognitive radio engine platform for tactical wireless sensor networks.
  • To enable dynamic spectrum access (DSA) by identifying available frequency channels.
  • To ensure protection of primary users (PUs) from harmful interference.

Main Methods:

  • A case-based reasoning technique is employed within the cognitive engine.
  • A learning engine is developed to characterize channel usage patterns.
  • Simulation tests are used to verify the performance of the cognitive engine and its components.

Main Results:

  • The cognitive engine reliably identifies available channels for opportunistic access.
  • The learning and case-based reasoning engines demonstrate high fidelity.
  • The tactical cognitive radio node (TCRN) effectively avoids collisions with primary user operations.

Conclusions:

  • The proposed cognitive radio engine platform is effective for tactical wireless sensor networks.
  • The system successfully enables dynamic spectrum access while protecting primary users.
  • The TCRN functions as an etiquette secondary user (SU), ensuring reliable communication.