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International Journal of Data Structure Studies Cover

International Journal of Data Structure Studies

E-ISSN: 3049-2440 | Peer-Reviewed Journal (Refereed Journal) | Hybrid Open Access

About the Journal

International Journal of Data Structure Studies International Journal of Data Structure Studies is a peer-reviewed hybrid open-access journal launched in 2023 is an international peer-reviewed journal that is concerned to deliver good quality knowledge to readers. Journal accepts original research and review papers and welcomes experimental and theoretical papers of exceptional quality.

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Journal Information

Title: International Journal of Data Structure Studies
Abbreviation: ijdss
Issues Per Year: 2 Issues
E-ISSN: 3049-2440
Publisher: STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
DOI: 10.37591/IJDSS
Starting Year: 2023
Subject: Computer Science
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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ijdss 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. Dimple Thakar, Assistant Professor

Marwadi University, Gujarat, India, 360005

Email :

Latest Articles

Ahead of Print

Improving Dataset Integrity Through Automated Data Cleaning Techniques

High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models.

Data quality, data cleaning automation, machine learning workflows, outlier detection, imputation techniques, duplicate detection, data profiling

Learning Data Structures: Key to Good Programming

Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks.

Data structures, algorithms, time/space complexity, programming efficiency, problem resolution, computing performance

An Auxiliary Array Indexing Approach for Efficient Binary Search in Linked Lists

The paper covers an algorithm for searching a linked list structure using binary search. Binary search is a classic example of an algorithm that follows the divide-and-conquer approach.

Binary search, linked list, auxiliary array, indexing, array of pointers

Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education

Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment.

Algorithms, Feedback, machine learning, multinomial NaĂŻve Bayes, sentiment analysis, support vector machine (SVM)

Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems

Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem.

Resource allocation graph, wait-for graph, Bayesian inference, deadlock resolution, multiprocessor systems, priority queue, process scheduling

Application of B-trees for Design of Optimal Page Replacement Technique in Modern Operating Systems

Algorithms related to replacing the memory pages in operating systems are critical components of modern operating systems that manage virtual memory efficiently.

B-trees, page replacement, virtual memory, operating systems, memory management, cache optimization