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International Journal of Algorithms Design and Analysis Review Cover

International Journal of Algorithms Design and Analysis Review

E-ISSN: 2584-1866 | Peer-Reviewed Journal (Refereed Journal) | Hybrid Open Access

About the Journal

International Journal of Algorithms Design and Analysis Review International Journal of Algorithms Design and Analysis Review:is a peer-reviewed hybrid open-access journal launched in 2015 that focuses on original research and practice-driven application with relevance to algorithms designs and analysis. All articles included are peer-reviewed by scholars with colossal experience in the same fields. Dynamic programming, amortized analysis, and linear programming are major focus areas.

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Journal Information

Title: International Journal of Algorithms Design and Analysis Review
Abbreviation: ijadar
Issues Per Year: 2 Issues
E-ISSN: 2584-1866
Publisher: STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
DOI: 10.37591/IJADAR
Starting Year: 2023
Publication Format: Hybrid Open Access
Language: English
Copyright Policy: CC BY-NC-ND
Type: Peer-reviewed Journal (Refereed Journal)

Address:

STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd. A-118, 1st Floor, Sector-63, Noida, U.P. India, Pin - 201301

Editorial Board

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ijadar maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor in Chief

Editor

Dr. Sharada Patil, Associate Professor

Sinhagad Institute of business Administration and Research, Pune, India, 411048

Email :

Latest Articles

Ahead of Print

Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification

Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions.

Mental health, emotion detection, sentiment analysis, BERT, CNN, explainable AI

Enhancing Smart Grid Resilience Through AI-Based Fault Classification

Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation.

Artificial intelligence, distribution network, fault classification, random forest, smart grid

A Dynamic Text Compression Model for Big Data Applications Using Hadoop

In today’s data-driven era, efficiently handling vast amounts of information has become increasingly important.

Hadoop, MapReduce, YARN, Data compressions, Textual substitution

Parallel Greedy Approach for Phylogenetic Tree Construction in the Context of Marine Species

The rebuilding of phylogenetic trees for marine species shows major computing problems because of the massive genomic data and the huge biodiversity inherent in ocean ecosystems.

High-performance computing (HPC), marine genomics, metagenomic datasets, parallel greedy algorithms, phylogenetic tree reconstruction, Scalable phylogenetic pipelines

Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps

Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance.

Academic risk detection, at-risk student performance, classification models, learning analytics, machine learning, predictive modeling, random forest

Aspect-Based Sentiment Analysis Using a Hybrid Approach with Dependency Parsing

The rapid expansion of digital communication has resulted in an unprecedented volume of consumer-generated textual data across online reviews, social media platforms, forums, and e-commerce websites.

Bidirectional encoder representations from transformers (BERT), consumer behavior, dependency parsing, hybrid feature extraction, semantic role labeling, sentiment analysis, text classification