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National Research Journal of Information Technology & Information Science

An International Reputed Peer Reviewed Refereed Research Journal I Open Access Journal I Impact Factor: 7.9
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NRJITIS - National Research Journal of Information Technology & Information Science


About The Journal


The National Research Journal of Information Technology and Information Science (NRJITIS) (ISSN: 2350-1278)  is a peer reviewed Journal academic publication dedicated to advancing research and knowledge in the fields of Information Technology (IT) and Information Science. The journal serves as a platform for scholars, practitioners, and industry professionals to share innovative research findings, emerging technologies, and practical applications. It covers a broad range of topics including data science, cybersecurity, artificial intelligence, software engineering, information systems, digital transformation, and human-computer interaction & Library Sciences and other multidisciplinary related topics. The journal aims to foster interdisciplinary collaboration and contribute to the evolving landscape of IT and information science through high-quality, original research.

The Journal is Published By "National Press Associates"

  • Publisher Website: www.npajournals.org
  • Journal Name: National Research Journal of Information Technology and Information Science
  • ISSN: 2350-1278
  • Impact Factor: 7.9
  • Peer Review Process: Double Blind Peer Review Process
  • Low Article Processing Fees
  • Frequency of Publication: Biannual (2 Issues Per Year)
  • Languages: English
  • Accessibility: Open Access
  • Plagiarism Checker: Turnitin

The journal invites submission of manuscripts that meet the general criteria of significance and scientific excellence, and will publish:

  1. Original articles (research paper, short communications, etc)
  2. Review articles
  3. Conference reports
  4. Book reviews, etc.

Interested in submitting to this journal? We recommend that you review the About the Journal page for the journal's section policies, as well as the Author Guidelines.

Journal Email ID: editornrjitis@gmail.com

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Current Issue

Year: 2025   Volume-12, Issue-2 (July-December)

Paper Title CHALLENGES IN MULTILINGUAL TYPESETTING AND TYPOGRAPHY FOR INDIAN VERNACULAR PRINTING
Author Name Amit Sharma
Country India
DOI https://doi.org/10.5281/zenodo.16014579
Page No. 1-11

Abstract View PDF Download Certificate
CHALLENGES IN MULTILINGUAL TYPESETTING AND TYPOGRAPHY FOR INDIAN VERNACULAR PRINTING
Author: Amit Sharma

India’s multilingual print ecosystem—encompassing education, governance, and media—relies heavily on accurate and culturally sensitive typesetting in over 20 major scripts. However, the structural complexity of Indic scripts such as Devanagari, Tamil, Bengali, and Urdu poses significant challenges in digital rendering, ligature formation, font compatibility, and layout automation. This paper investigates the evolution of typesetting technologies from metal casting and phototypesetting to Unicode-based digital publishing and highlights the persistent limitations in font engineering, rendering engines, and prepress workflows. Case studies from NCERT, regional boards, and vernacular newspapers illustrate how technical fragmentation and inadequate standardization hinder print accessibility and aesthetic integrity. The paper also reviews government-backed standardization efforts (TDIL, Bhashini), community-driven font development (e.g., Google Noto, Lohit), and advances in OpenType and OCR technologies. Finally, it recommends script-specific layout engines, policy-level standardization, and professional training initiatives as strategic pathways for building a robust, scalable, and inclusive multilingual print infrastructure in India.
Keywords: Multilingual typesetting, Indic scripts, Devanagari, Unicode rendering, OpenType features, Indian typography, vernacular printing, font standardization, digital publishing, ligature handling, government publishing, regional language fonts, desktop publishing, script complexity, print accessibility

Paper Title OPTIMIZING AWARENESS IN GREEN COMPUTING INITIATIVES
Author Name Kanwaldip Kaur
Country India
DOI https://doi.org/10.5281/zenodo.16521563
Page No. 12-16

Abstract View PDF Download Certificate
OPTIMIZING AWARENESS IN GREEN COMPUTING INITIATIVES
Author: Kanwaldip Kaur

Green computing (or green IT) refers to the design, use, and disposal of computers and IT infrastructure in a way that reduces environmental impact. This includes energy-efficient hardware, sustainable software, virtualization, cloud computing, and responsible e-waste management.

Paper Title SMART LIBRARIES: ENHANCING THE LIBRARY EXPERIENCE
Author Name Gurpreet Singh Sohal
Country India
DOI https://doi.org/10.5281/zenodo.16634127
Page No. 17-23

Abstract View PDF Download Certificate
SMART LIBRARIES: ENHANCING THE LIBRARY EXPERIENCE
Author: Gurpreet Singh Sohal

ABSTRACT
Modern libraries are being redefined more and more as locations to have unlimited access to
knowledge from a variety of sources and in a variety of formats. By offering literature that
can be accessed virtually and helping librarians navigate and analyze vast amounts of data
using a range of digital resources, they are expanding their services beyond the physical
boundaries of a building. Libraries are evolving into community centers where people can
participate in lifelong learning. Here, the concept of a smart library evolved, where resources
can be accessed easily and with less staff intervention. Smart Library provides state of the art
automated infrastructure and sophisticated technologies like automatic gates, lighting, selfservice kiosks, mobile library services on the smart phone or handheld devices, offer limitless
digital collection via the Internet, provides e-learning facilities & learning spaces; and uses
the social media platforms to share information about its collection and service. So the Smart
libraries will revolutionize library operations and services. In this paper, we will discuss
various concepts, needs, components and services provided by Smart Libraries.
Keywords: Smart Library, Technology, services, infrastructure, mobile library services

Paper Title CYBER SECURITY THREATS IN CLOUD COMPUTING
Author Name Sahil Luthra
Country India
DOI https://doi.org/10.5281/zenodo.16678363
Page No. 24-35

Abstract View PDF Download Certificate
CYBER SECURITY THREATS IN CLOUD COMPUTING
Author: Sahil Luthra

ABSTRACT:
Cloud computing has emerged as a revolutionary paradigm, offering scalable, flexible, and
cost-effective IT services to organizations. Despite its numerous benefits, including reduced
costs and increased efficiency, the adoption of cloud computing is hindered by security
concerns. The outsourcing of sensitive data to third-party providers raises significant risks,
including data breaches and unauthorized access. This paper presents a comprehensive
analysis of the security challenges and issues associated with cloud computing, highlighting
the need for organizations to be vigilant in understanding the risks and benefits of this
technology. By examining the security concerns and potential solutions, this study aims to
provide insights into the secure adoption of cloud computing.
Keywords: Cloud computing; Security in cloud; Security Threats.

Paper Title INFLUENCE OF CULTURAL AND SOCIO-ECONOMIC BACKGROUND ON PERSONALITY PATTERN OF MISHING ADOLESCENTS IN LAKHIMPUR DISTRICTS OF ASSAM
Author Name Ratul Borah
Country India
DOI https://doi.org/10.5281/zenodo.17043561
Page No. 36-47

Abstract View PDF Download Certificate
INFLUENCE OF CULTURAL AND SOCIO-ECONOMIC BACKGROUND ON PERSONALITY PATTERN OF MISHING ADOLESCENTS IN LAKHIMPUR DISTRICTS OF ASSAM
Author: Ratul Borah

1. INTRODUCTION:
North eastern region of India comprises the Seven Sisters States of Arunachal Pradesh,
Assam, Monipur, Meghalaya, Mizoram, Nagaland and Tripura. It covers 7.76% of the
country‟s total geographical area of 32.87,240 sq. km. The North East India lies between
latitudes 22 and 29.5 and longitudes 89.70‟ and 97.30‟E. According to 2001 census, the total
population in entire North-East India is 3, 85 core out of which the scheduled tribe population
is 1.06 core. In words, the scheduled tribes constituted 27.42% of the total population N.E.R.
There are many scheduled tribes, scheduled caste, OBC, MOBC, general etc. in the state of
Assam. Assam alone account for 3% of the total scheduled tribe population of the North-East.
According to the Scheduled Caste and Scheduled Tribes others (Amendment) Act, 2002 there
are, 25 scheduled tribes in Assam.
Keywords: Personality, Mishing, Adolescent, Assam, NER , Psychological

Paper Title EVALUATING MRI PLANE AND MACHINE LEARNING ALGORITHM PERFORMANCE IN ALZHEIMER'S DISEASE CLASSIFICATION USING HARALICK TEXTURE FEATURES
Author Name Gayathri L , Muralidhara B. L
Country India
DOI https://doi.org/10.5281/zenodo.17097235
Page No. 48-57

Abstract View PDF Download Certificate
EVALUATING MRI PLANE AND MACHINE LEARNING ALGORITHM PERFORMANCE IN ALZHEIMER'S DISEASE CLASSIFICATION USING HARALICK TEXTURE FEATURES
Author: Gayathri L , Muralidhara B. L

ABSTRACT:
Classifying Alzheimer’s Disease (AD) using MRI scans is essential for timely detection and
effective treatment planning. This research aims to enhance AD diagnosis by employing
machine learning (ML) models, feature selection methods, and texture-based image analysis.
The study compares the effectiveness of various feature selection strategies and Principal
Component Analysis (PCA) combined with multiple ML algorithms to determine the most
suitable approach for differentiating between Cognitive Normal (CN), Mild Cognitive
Impairment (MCI), and AD cases.
The preprocessing workflow includes N4 bias correction, skull stripping, and linear coregistration, followed by the extraction of texture features that capture statistical
characteristics of image patterns. Different ML classifiers are then trained and tested on these
features to evaluate their ability to accurately categorize patients. Performance is measured
using multiple evaluation metrics to assess the discriminative power of the models across AD
stages.
The findings highlight that combining ML techniques with feature selection and texture
analysis provides a robust framework for early AD detection and personalized treatment
strategies, offering meaningful implications for clinical use.
Keywords— Alzheimer's disease, feature selection, machine learning, texture analysis.

Paper Title BEYOND WORDS: A COMPARATIVE STUDY OF SUMMARIZATION MODELS AND EMBEDDING TECHNIQUES
Author Name Maya A.K.R, Muralidhara B. L
Country India
DOI https://doi.org/10.5281/zenodo.17097274
Page No. 58-66

Abstract View PDF Download Certificate
BEYOND WORDS: A COMPARATIVE STUDY OF SUMMARIZATION MODELS AND EMBEDDING TECHNIQUES
Author: Maya A.K.R, Muralidhara B. L

ABSTRACT
Word embeddings are the basis of machine learning and deep learning models used in NLP
(Natural Language Processing), advancing the methods by which machines interpret and
handle textual data. High-quality embeddings can substantially boost performance in
downstream NLP tasks by better capturing linguistic nuances, including question-answering,
text summarization, text classification, and information retrieval. The present study offers an
in-depth examination of the development of word embeddings in NLP, comparing the
effectiveness of earlier methods to recent developments on both extractive and abstractive
summarization tasks. We explore the radical shift from classical static embeddings like
Word2Vec and GloVe to the dynamic, context-aware representations introduced by
transformer-based models like BERT, T5, and GPT. Additionally, we assess how these
embeddings are integrated with self-attention mechanisms, sequence-to-sequence (Seq2Seq)
architectures, and encoder-decoder models to generate summaries. The study evaluates the
models across standard benchmarks, measuring metrics like ROUGE, BLEU, and model
interpretability. Our analysis reveals a 20% ROUGE improvement with transformer-based
models over static ones on CNN/Daily Mail. Thus, we aim to provide valuable insights into
various word embeddings in text summarization that will be useful for training a new
embedding or using a pre-trained embedding for the NLP task.
Keywords: Contextualized Embeddings, Natural Language Processing, Summarization,
Transformers, Word Embeddings.

Paper Title COUNTERFEIT DETECTION IN EDUCATIONAL CREDENTIALS USING MACHINE LEARNING TECHNIQUES
Author Name Sarala M, Muralidhara B L
Country India
DOI https://doi.org/10.5281/zenodo.17097310
Page No. 67-74

Abstract View PDF Download Certificate
COUNTERFEIT DETECTION IN EDUCATIONAL CREDENTIALS USING MACHINE LEARNING TECHNIQUES
Author: Sarala M, Muralidhara B L

ABSTRACT
Forgery detection in educational credentials is a challenging task. Machine learning(ML)
techniques are highly used in fraud detection and spam detection. Our primary objective is to
detect counterfeit educational credentials using ML algorithms. In this research work, we
conducted an empirical study as follows: (i) extracted the features of those credentials using
the Gray Level Histogram Analysis (GLHA) metrics such as standard deviation, mean,
skewness, kurtosis, and entropy, (ii) Trained the ML models with extracted features using
different classification algorithms including Support Vector Machine(SVM), Logistic
Regression, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbours(KNN).
(iii) Assessed the effectiveness of classification models using hyper-parameters. Random
Forest got 99.38% accuracy, and outperformed well than other algorithms. SVM, Decision
Tree, Logistic Regression, KNN, and Naïve Bayes got accuracies of 98.75%, 98.13%,
95.00%, 92.50%, and 90.00% respectively.
Keywords: machine learning, GLHA, counterfeit detection, supervised algorithms.

Paper Title AN EVOLUTIONARY APPROACH TO FRACTIONAL BILEVEL PROGRAMMING
Author Name Debjani Chakraborti
Country India
DOI https://doi.org/10.5281/zenodo.17097510
Page No. 75-87

Abstract View PDF Download Certificate
AN EVOLUTIONARY APPROACH TO FRACTIONAL BILEVEL PROGRAMMING
Author: Debjani Chakraborti

ABSTRACT
This study introduces an innovative method that employs evolutionary computation to
address interval-valued fractional bilevel programming (IVFBLP) problems. These involve
decision-making at two hierarchical levels, where some data is expressed as intervals rather
than fixed values, enhancing realism but increasing complexity. The proposed method
integrates mixed 0–1 programming, goal programming, and genetic algorithms to efficiently
address these challenges.
The genetic algorithm mimics natural evolutionary processes by generating multiple solution
candidates and iteratively selecting the best, allowing the model to explore a wide solution
space and converge towards optimal or near-optimal decisions. To ensure solutions closely
meet desired goals while minimizing adverse outcomes, termed regrets, the approach
employs two strategies—minsum and minmax—within a combined success-measuring
function.
The solution process follows two phases: first, it establishes optimal target intervals
representing achievable goal ranges; second, it identifies the best decisions for both leader
(upper) and follower (lower) roles. This structured approach delineates responsibilities
between decision-makers.
Utilizing evolutionary computing enables the model to handle uncertainties, nonlinearities,
and complex structures effectively. The paper demonstrates practical applicability through a
numerical example, showcasing its capability to solve real-world problems involving
interval-based objectives and constraints where decisions occur at multiple hierarchical
levels.
Keywords : Fractional bilevel programming, Goal programming, Evolutionary algorithm,
Interval programming, Interval-valued fractional bilevel programming, Multiobjective
decision-making.

Editorial Policy About Peer Reviewed Journal Publication Ethics & Practices Plagiarism Policy Open Access, Licencing & Copyright Disclaimer Policy Privacy Policy FAQ Special Issue About The Journal

Latest Announcements

  • CALL FOR PAPERS 2025 (January-June)

    01-01-2025
    SUBMIT PAPERS IN OUR RESEARCH JOURNAL! 2025
    National Research Journal of Information Technology and Information Science  contributes in the growth and application of Research & Technology, by delivering the latest information contained in research papers, which enables them to enhance understanding for advancements in research activities. We intends to Disseminate and promote the research works of research scholars, Academia.

  • Subscribe This Journal

    01-01-2025
    We Request to Subscribe our Journals for the Noble Cause to Spread Knowledge, Wisdom and also to Protect Intellectual Property Rights of Scholars Across the World.

    Subscription Price: 3500/- (Bi-Annual)

    CALL NOW!
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