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Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

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Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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Language and Cognition

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Language Development01:22

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
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Components of Language01:24

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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Statically Indeterminate Problem Solving01:16

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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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Related Experiment Video

Updated: Nov 23, 2025

Automated Robotic Liquid Handling Assembly of Modular DNA Devices
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Knowledge-Based Verification of Concatenative Programming Patterns Inspired by Natural Language for

Salvatore Gaglio1,2, Giuseppe Lo Re1, Gloria Martorella1

  • 1Department of Engineering, University of Palermo, Viale delle Scienze, Ed.6, 90128 Palermo, Italy.

Sensors (Basel, Switzerland)
|December 30, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for verifying natural language-inspired applications on resource-constrained devices. It enables runtime verification and testing of software interacting with physical environments.

Keywords:
concatenative languagesdistributed programmingembedded systemsforthinternet of thingssymbolic programmingwireless sensor networks

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Area of Science:

  • Computer Science
  • Software Engineering
  • Embedded Systems

Background:

  • Resource-constrained devices require efficient programming paradigms.
  • Interacting with physical environments necessitates robust verification methods.
  • Traditional verification approaches often struggle with distributed, resource-limited systems.

Purpose of the Study:

  • To propose a methodology for verifying applications using natural language-inspired programming patterns.
  • To enable runtime verification on resource-constrained interconnected devices.
  • To reduce reliance on complex, synchronized ontologies for mapping physical concepts to code.

Main Methods:

  • Utilizing natural language programming patterns to map physical concepts directly to executable code.
  • Employing a rule-based system for automated oracle and test case generation.
  • Performing runtime verification on-board target devices, including syntactic, semantic, and physical effect checks.
  • Leveraging sensor and actuator rules to verify code execution impact on the physical environment.

Main Results:

  • Successful runtime verification of software under test (SUT) on target hardware.
  • Automated generation of test cases and oracles for comprehensive testing.
  • Verification of code execution effects on both hardware and the physical environment.
  • Identification of potential software issues through repeated execution testing.

Conclusions:

  • The proposed methodology effectively verifies applications on resource-constrained devices using natural language-inspired patterns.
  • This approach simplifies development by avoiding complex ontology management.
  • It enhances the reliability of software interacting with physical systems.