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Related Concept Videos

Associative Learning01:27

Associative Learning

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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
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Observational Learning01:12

Observational Learning

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Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
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Cognitive Learning01:21

Cognitive Learning

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
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Issues And Trends In Healthcare Delivery System01:29

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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
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Introduction to Learning01:18

Introduction to Learning

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Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
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Purposive Learning01:22

Purposive Learning

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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
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Updated: Oct 14, 2025

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
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Blockchain-based federated learning methodologies in smart environments.

Dong Li1,2, Zai Luo2, Bo Cao1

  • 1BULL, 32 Sanhai Road, Guanhaiwei Town, Cixi, Ningbo City, 315300 Zhejiang China.

Cluster Computing
|November 8, 2021
PubMed
Summary
This summary is machine-generated.

Blockchain technology enhances federated learning (FL) security for sensitive IoT data. This integration addresses privacy concerns in smart healthcare, industry, and finance, driving significant advancements in data science.

Keywords:
BlockchainFederated learningInternet of Things (IoT)PrivacySecurity

Related Experiment Videos

Last Updated: Oct 14, 2025

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
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Area of Science:

  • Data Science
  • Artificial Intelligence
  • Cybersecurity

Background:

  • Federated learning (FL) is crucial for data mining accuracy and privacy in smart environments.
  • Sensitive data in IoT domains (healthcare, industry, finance) requires secure collection and training.
  • Blockchain offers robust security and privacy solutions for transactional data.

Purpose of the Study:

  • To systematically review privacy and security in blockchain-based federated learning methodologies.
  • To provide an objective roadmap of the current status of blockchain-FL integration.
  • To highlight the growing importance of secure data handling in intelligent systems.

Main Methods:

  • Systematic study of scientific databases.
  • Analysis of research trends in blockchain-based federated learning.
  • Identification of key application domains and challenges.

Main Results:

  • Blockchain-based FL has experienced significant growth in the last five years.
  • Blockchain technology is increasingly applied to secure patient health records, industrial data, and financial information.
  • Key application areas include IoT, smart cities, smart healthcare, and smart industry.

Conclusions:

  • Blockchain-based FL is a rapidly advancing field with substantial potential for enhancing data security and privacy.
  • The integration of blockchain and FL is vital for addressing the challenges of sensitive data in IoT ecosystems.
  • Continued research in this area is essential for developing robust and secure intelligent systems.