Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

1.2K
Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
1.2K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

317
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
317
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

557
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
557
Reliability and Validity01:29

Reliability and Validity

14.3K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
14.3K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

383
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
383
Modeling in Therapy01:26

Modeling in Therapy

652
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
652

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Review of current status of targeted alpha therapy in cancer treatment.

Nuclear medicine review. Central & Eastern Europe·2024
Same author

Towards Secure Big Data Analysis via Fully Homomorphic Encryption Algorithms.

Entropy (Basel, Switzerland)·2022
Same author

Design-Time Reliability Prediction Model for Component-Based Software Systems.

Sensors (Basel, Switzerland)·2022
Same author

Greedy Firefly Algorithm for Optimizing Job Scheduling in IoT Grid Computing.

Sensors (Basel, Switzerland)·2022
Same author

The impact of intervention strategies and prevention measurements for controlling COVID-19 outbreak in Saudi Arabia.

Mathematical biosciences and engineering : MBE·2020
Same author

Model-based test case prioritization using selective and even-spread count-based methods with scrutinized ordering criterion.

PloS one·2020

Related Experiment Video

Updated: Mar 14, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.2K

Technique for Early Reliability Prediction of Software Components Using Behaviour Models.

Awad Ali1,2, Dayang N A Jawawi1, Mohd Adham Isa1

  • 1Department of Information Technology, Faculty of Computer Science, University of Kassala, Kassala, Sudan.

Plos One
|September 27, 2016
PubMed
Summary

This study introduces a new software reliability prediction technique using state machines to model component behavior. It offers more realistic and meaningful predictions early in the design phase.

More Related Videos

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
16:23

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

15.0K

Related Experiment Videos

Last Updated: Mar 14, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.2K
Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
16:23

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

15.0K

Area of Science:

  • Software Engineering
  • Reliability Engineering
  • System Design

Background:

  • Component behavior models are crucial for early software reliability prediction.
  • Existing techniques often lack fine-grained sequential models and overlook loop structures.
  • Operational data unavailability and limited early-stage analysis hinder current methods.

Purpose of the Study:

  • To propose a novel reliability prediction technique for software systems at the early design stage.
  • To address limitations of current methods regarding component behavior modeling and data availability.
  • To provide valuable analysis results for software architects.

Main Methods:

  • Synthesizing system behavior into a state machine from scenarios and constraints.
  • Utilizing the state machine to generate component operational data.
  • Constructing a component probabilistic dependency graph (CPDG) from the state machine.
  • Employing a stack-based algorithm on the CPDG for reliability computation.

Main Results:

  • The proposed technique generates fine-grained sequential behavior models.
  • It effectively handles loop entry and exit points in reliability computation.
  • The method addresses operational data unavailability by synthesizing data.
  • Evaluated through comparison and a robotic wheelchair case study, it shows improved relevance and prediction quality.

Conclusions:

  • The proposed technique offers a more pragmatic and effective approach to early-stage software reliability prediction.
  • It provides more realistic and meaningful predictions compared to existing methods.
  • The technique enhances the value of analysis for software architects during the design phase.