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Journal Photo for International Journal of Information Technology and Electrical Engineering
Peer reviewed only Open Access

International Journal of Information Technology and Electrical Engineering (IJITEE)

Publisher : ITEE Publishers
Information Technology Electrical Engineering
Claim Your Journal Get PRC Visit Website
e-ISSN 2306-708X
Issue Frequency Bi-Monthly
Est. Year 2012
Language English
APC YES
Impact Factor Assignee Google Scholar
Email editor@iteejournal.org

Journal Descriptions

The ITEE (ISSN:2306-708X) is an international scholarly peer reviewed bi-monthly open access journal. This Journal is launched to promote and publish original high quality research papers with theoretical and scientific aspects in all disciplines of Information Technology and Electrical Engineering.

International Journal of Information Technology and Electrical Engineering (IJITEE) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Information Technology, Electrical Engineering , Online , Bi-Monthly Journal

  • UGC Approved, ISSN Approved: P-ISSN E-ISSN: 2306-708X, Established: 2012,
  • Does Not Provide Crossref DOI

  • Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE

Indexing

Publications of IJITEE

ANALYSIS OF STEEL FRAME INCORPORATING EFFECT OF SEMI-RIGID STEEL CONNECTIONS
Ghanshyam M. July, 2024
IS 800:2007 for design of steel structures has provided an opportunity for modern design philosophy as per Limit State Method of design. Steel connections are key elements of steel frame, wh...
Internet of Things (IoT): Security and Data Management
Rina Aisyah July, 2024
The Internet of Things (IoT) has revolutionized the way devices interact and communicate, offering unprecedented convenience and efficiency across various domains. However, this interconnect...
Role of Computational Fluid Dynamics in Enhancing HVAC System Design and Thermal Performance Analysis
Krishna Srivastava October, 2010
Computational Fluid Dynamics (CFD) has revolutionized the design and analysis of Heating, Ventilation, and Air Conditioning (HVAC) systems, providing precise tools for evaluating thermal per...
OPTIMIZING AERODYNAMIC PERFORMANCE OF H-DARRIEUS VAWTS: A COMPUTATIONAL FLUID DYNAMICS APPROACH
Mirza Tauqeer September, 2024
This study investigates the aerodynamic performance optimization of a three-bladed H-Darrieus Vertical Axis Wind Turbine (VAWT) using Computational Fluid Dynamics (CFD) simulations, with a f...
Leveraging Machine Learning for Real-Time Big Data Analytics in Critical Care and Patient Monitoring Systems
Joseph Moore November, 2024
The advent of machine learning (ML) has revolutionized healthcare, particularly in critical care and patient monitoring systems. This study explores the integration of ML for real-time big d...
AI-Enhanced Configuration Management in CI/CD for Scalable and Automated Release Engineering Solutions
Mohamed Taufiq February, 2025
Configuration management (CM) plays a critical role in ensuring consistency, accuracy, and scalability within Continuous Integration and Continuous Deployment (CI/CD) pipelines, especially i...
COMPARATIVE ANALYSIS OF NEURAL-SYMBOLIC INTEGRATION TECHNIQUES IN ENHANCING THE INTERPRETABILITY OF ARTIFICIAL INTELLIGENCE DECISION SYSTEMS INHIGH-ST...
Sarah Sami May, 2024
In high-stakes domains such as healthcare, law, and finance, the need for interpretable artificial intelligence (AI) systems has become increasingly critical. Neural-symbolic integration, co...
Assessment of Machine Learning Assisted Debugging Approaches in Silicon Validation Workflows
BalaDharshithan September, 2023
The complexity of modern silicon designs necessitates advanced validation strategies to ensure timely product development. Machine Learning (ML) techniques have been increasingly integrated ...
LOW-CODE AI-DRIVEN AUTOMATION FOR ENHANCING OPERATIONAL EFFICIENCY IN SMES
mj iaeme November, 2022
This study explores the integration of low-code platforms with artificial intelligence (AI) to drive automation and enhance operational efficiency in Small and Medium Enterprises (SMEs). By ...
A BAYESIAN FRAMEWORK FOR UNCERTAINTY QUANTIFICATION IN AI-DRIVEN DIAGNOSTIC TOOLS FOR RARE AND UNDERREPRESENTED CLINICAL PHENOTYPES
Research Scholar December, 2023
Rare and underrepresented clinical phenotypes pose significant challenges for artificial intelligence (AI)-based diagnostic systems due to limited data and inherent variability. This paper p...