Machine Learning and Applications: An International Journal (MLAIJ)

ISSN: 2394 – 0840

https://airccse.org/journal/mlaij/index.html

Call For Papers

Machine Learning and Applications: An International Journal (MLAIJ) is a quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the machine learning. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of machine learning and applications.The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on machine learning advancements, and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of machine learning.

Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of machine learning.

Topics of interest include but are not limited to the following: ·

  • Machine Learning Algorithms
  • Learning in knowledge-intensive systems
  • Learning Methods and analysis
  • Supervised Machine Learning
  • Unsupervised Machine Learning
  • Deep Learning
  • Neural Networks
  • Reinforcement Learning
  • Predictive Learning
  • Learning Problems
  • Computer Vision
  • Bayesian Network
  • Data Mining

Paper Submission

Authors are invited to submit papers for this journal through E-mail: mlaijjournal@yahoo.com  Or  mlaijjournal@airccse.org. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.

Important Dates             

  • Submission Deadline :  September 05, 2026
  • Notification : : September 25, 2026
  • Final Manuscript Due  :September 28, 2026

For other details please visit http://airccse.org/journal/mlaij/index.html

International Journal of Embedded Systems and Applications (IJESA)

ISSN : 1839 – 5171

https://wireilla.com/ijesa/index.html

Scope & Topics

International Journal of Embedded Systems and Applications (IJESA) is a quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Embedded Systems and applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Embedded Systems and establishing new collaborations in these areas.

Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Embedded Systems & applications.

Topics of interest include but are not limited to, the following

  • Application-specific processors and devices
  • Business Applications
  • Component and binding models
  • Embedded computing education
  • Embedded hardware support
  • Embedded software
  • Embedded system architecture
  • Hardware and software co-design
  • Industrial practices and benchmark suites
  • Integration with business logic
  • Integration with SOA
  • Middleware
  • Networked Embedded Systems
  • Policy-based management
  • Programming abstractions
  • Real-time systems
  • Recent Trends
  • Service-Oriented architectures
  • Testing techniques

Paper Submission

Authors are invited to submit papers for this journal through the Submission system. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.

Important Dates

  • Submission Deadline:   September 05, 2026
  • Notification                   : September 25, 2026
  • Final Manuscript Due : September 28, 2026

Contact Us

Here’s where you can reach us : ijesa@wireilla.com

Machine Learning and Applications: An International Journal (MLAIJ)

ISSN: 2394 – 0840

https://airccse.org/journal/mlaij/index.html

Call For Papers

Machine Learning and Applications: An International Journal (MLAIJ) is a quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the machine learning. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of machine learning and applications.The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on machine learning advancements, and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of machine learning.

Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of machine learning.

Topics of interest include but are not limited to the following: ·

  • Machine Learning Algorithms
  • Learning in knowledge-intensive systems
  • Learning Methods and analysis
  • Supervised Machine Learning
  • Unsupervised Machine Learning
  • Deep Learning
  • Neural Networks
  • Reinforcement Learning
  • Predictive Learning
  • Learning Problems
  • Computer Vision
  • Bayesian Network
  • Data Mining

Paper Submission

Authors are invited to submit papers for this journal through E-mail: mlaijjournal@yahoo.com  Or  mlaijjournal@airccse.org. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.

Important Dates             

  • Submission Deadline :  August 28, 2026
  • Notification : : September 21, 2026
  • Final Manuscript Due  :September 28, 2026

For other details please visit http://airccse.org/journal/mlaij/index.html

Current issue

December 2024, Volume 11, Number 4

Empirical Analysis of the Bias-Variance Tradeoff Across Machine Learning Models
Hardev Ranglani, EXL Service Inc, USA
Comparative Analysis of Clustering Algorithms on Synthetic Circular Patters Data
Hardev Ranglani, EXL Service Inc, USA

September 2024, Volume 11, Number 3

Sensitivity Analysis of Word Importance using GPT Model: A Ranking XAI Approach with Attention Weights and KL Divergence
Arav Agarwal1 and Rhea Mahajan21India, 2University of Jammu, India

Artificial Intelligence: An Experiential Learning Tool to Acquire Knowledge and Enhance Creativity
Epilogue Jedishkem1 and Jesfaith Jedishkem21Ngwane College, Eswatini, 2Freelance Artist Researcher, Eswatini

June 2024, Volume 11, Number 2

Text-Based Detection of On-Hold Scripts in Contact Center Calls

Dmitrii Galimzianov and Viacheslav Vyshegorodtsev, DeepSound.AI, Kazakhstan
Developing an Android-based Adaptive Data Acquisition System Powered by Big Data Analysis

Priyank Singh Tanvi Hungund and Shobhit Kukreti
Leveraging Machine Learning to Enhance Information Exploration

Nikhil Ghadge, Software Architect, Workforce Identity Cloud, Okta.Inc

March 2024, Volume 11, Number 1

Thelxinoë: Recognizing Human Emotions Using Pupillometry and Machine Learning

Darlene Barker1 and Haim Levkowitz21Rivier University, USA, 2University of Massachusetts, USA

December 2023, Volume 10, Number 4

Evaluating the Accuracy of Classification Algorithms for Detecting Heart Disease Risk

Alhaam Alariyibi, Mohamed El-Jarai and Abdelsalam Maatuk, Benghazi University, Libya

September 2023, Volume 10, Number 2/3

Sentiment-Driven Cryptocurrency Price Prediction: A Machine Learning Approach Utilizing Historical Data and Social Media Sentiment Analysis


Saachin Bhatt, Mustansar Ghazanfar, and Mohammad Hossein Amirhosseini, University of East London, United Kingdom

Breast Tumor Detection Using Efficient Machine Learning and Deep Learning Techniques

Ankita Patra1, Santi Kumari Behera2, Prabira Kumar Sethy1, Nalini Kanta Barpanda1, Ipsa Mahapatra21Sambalpur University, India, 2VSSUT Burla, India

Face Mask Detection Model Using Convolutional Neural Network

Mamdouh M. Gomaa1, Alaa Elnashar1, Mahmoud M. Eelsherif2, and Alaa M. Zaki11Minia University, Egypt, 2Sinai university, Egypt

March 2023, Volume 10, Number 1

A Machine Learning Method for Prediction of Yogurt Quality and Consumers Preferencesusing Sensory Attributes and Image Processing Techniques

MahaHany1, Shaheera Rashwan1 and Neveen M. Abdelmotilib21Informatics Research Institute, Egypt, 2Arid Lands Cultivation Research Institute, Egypt

Face Mask Detection Model Using Convolutional Neural Network

Mamdouh M. Gomaa1, Alaa Elnashar1, Mahmoud M. Eelsherif2, and Alaa M. Zaki11Minia University, Egypt, 2Sinai university, Egypt

December 2022, Volume 9, Number 4

Automatic Spectral Classification of Stars using Machine Learning: An Approach based on the use of Unbalanced Data

Marco Oyarzo Huichaqueo1 and Renato Munoz Orrego21Rovira i Virgili University, Spain, 2Technical University of Madrid, Spain

Machine Learning Algorithms for Credit Card Fraud Detection

Amarachi Blessing Mbakwe and Sikiru Ademola Adewale, Virginia Tech, USA

September 2022, Volume 9, Number 3

Ai_Birder: Using Artificial Intelligence and Deep Learning to Create a Mobile Application that Automates Bird Classification
Charles Tian1 and Yu Sun21USA, 2California State Polytechnic University, USA

June 2022, Volume 9, Number 2

DSAGLSTM-DTA: Prediction of Drug-Target Affinity using Dual Self-Attention and LSTM
Lyu Zhijian, Jiang Shaohua and Tan Yonghao, Hunan Normal University, China

Multilingual Speech to Text using Deep Learning based on MFCC Features

P Deepak Reddy, Chirag Rudresh and Adithya A S, PES University, India

March 2022, Volume 9, Number 1

Exoplanets Identification and Clustering with Machine Learning Methods
Yucheng Jin, Lanyi Yang, Chia-En Chiang, University of California-Berkeley, USA

December 2021, Volume 8, Number 4

A Comprehensive Study on Occlusion Invariant Face Recognition under Face Mask Occlusions
Susith Hemathilaka1 and Achala Aponso2, 1University of Westminster, United Kingdom, 2Informatics Institute of Technology, Sri Lanka

A Survey of Neural Network Hardware Accelerators in Machine Learning
Fatimah Jasem and Manar AlSaraf, Kuwait University, Kuwait

September 2021, Volume 8, Number 2/3

A Development Framework for a Conversational Agent to Explore Machine Learning Concepts
Ayse Kok Arslan, Oxford Alumni of Northern California, USA

An Enhancement for the Consistent Depth Estimation of Monocular Videos using Lightweight Network
Mohamed N. Sweilam1, 2, and Nikolay Tolstokulakov2, 1Suez University, Egypt, 2Novosibirsk State University, Russia

Catwalkgrader: A Catwalk Analysis and Correction System using Machine Learning and Computer Vision
Tianjiao Dong1 and Yu Sun2, 1USA, 2California State Polytechnic University, USA

Hybridization of DBN with SVM and its Impact on Performance in Multi-Document Summarization
Karari Kinyanjui, Malanga Ndenga and H.O Nyongesa, Dedan Kimathi University of Technology, Kenya

March 2021, Volume 8, Number 1

Artificial Intelligence Models for Crime Prediction in Urban Spaces

Ana Laura Lira Cortes1 and Carlos Fuentes Silva21Universidad Autónoma de Querétaro, México, 2Universidad Politécnica de Querétaro, México

Analysis of Covid-19 in the United States using Machine Learning

James G. Koomson, Marymount University, USA

June 2020, Volume 7, Number 1/2

Quantum Criticism: an Analysis of Political News Reporting

Ashwini Badgujar, Sheng Chen, Pezanne Khambatta, Tuethu Tran, Andrew Wang, Kai Yu, Paul Intrevado and David Guy Brizan, University of San Francisco, USA

September 2019, Volume 6, Number 2/3

Human Activity Recognition Using Recurrent Neural Network

Yoshihiro Ando

March 2019, Volume 6, Number 1

Predicting Forced Population Displacement Using News Articles 
Sadra Abrishamkar and Forouq Khonsari, York University, Canada

Fault Diagnosis Using Clustering. What Statistical Test to use for Hypothesis Testing? 
Nagdev Amruthnath and Tarun Gupta, Western Michigan University, USA

Analysis of WTTE-RNN Variants that Improve Performance 
Rory Cawley and John Burns, Institute of Technology Tallaght, Ireland

December 2018, Volume 5, Number 4

Study on Cerebral Aneurysms: Rupture Risk Prediction Using Geometrical Parameters and Wall Shear Stress With CFD and Machine Learning Tools

Alfredo Aranda and Alvaro Valencia, Universidad de Chile, Chile

June 2018, Volume 5, Number 1/2

A Comparative Study on Human Action Recognition Using Multiple Skeletal Features and Multiclass Support Vector Machine 

Saiful Islam1, Mohammad Farhad Bulbul2*, Md. Sirajul Islam21Jessore University of Science and Technology,
Bangladesh and 2Bangabandhu Sheikh Mujibur Rahman Science and Technology University, India

December 2017, Volume 4, Number 4

Reinforcement Learning : MDP Applied to Autonomous Navigation  
Mark A. Mueller, Georgia Institute of Technology, USA

September 2017, Volume 4, Number 1/2/3

Enhancing Customer Retention Through Data Mining Techniques  
Alexiei Dingli, Vincent Marmara and Nicole Sant Fournier, University of Malta, Malta

Financial Time Series Forecasting – A Machine Learning Approach  
Alexiei Dingli and Karl Sant Fournier, University of Malta, Malta

December 2016, Volume 3, Number4

Model Based Technique for Vehicle Tracking in Traffic Video Using Spatial Local Features  
Arun Kumar H. D and Prabhakar C. J, Kuvempu University, India

September 2016, Volume 3, Number3

Image Based Recognition – Recent Challenges and Solutions Illustrated on Applications 
Daniel Garten1, Katharina Anding2 and Steffen Lerm2, 1Society for Production Engineering and Development, Germany
and 2Ilmenau University of Technology, Germany

Evaluation of a New Incremental Classification Tree Algorithm for Mining High Speed Data Streams  
N. Sivakumar1 and S. Anbu2, 1St. Peter’s University, India and 2St. Peter’s College of Engineering and Technology, India
Machine Learning Toolbox 
Pankaj Agarwal, Akshay Bhasin, Rohit Keshwani, Aman Verma and Suryansh Kaushik, IMS Engineering College, India

 

June 2016, Volume 3, Number 2

An Ensemble of Filters and Wrappers for Microarray Data Classification 
Mohamad Morovvat and Alireza Osareh, Shahid Chamran University of Ahvaz, Iran
A Multi-Level Security for Preventing DDOS Attacks in Cloud Environments 
Subramaniam.T. K and Deepa B, Nandha Engineering College, India
Machine Learning Based Approaches for Prediction of Parkinson’s Disease  
Arvind Kumar Tiwari, GGS College of Modern Technology, India
An New Attractive Mage Technique Using L-Diversity 
Anandhi G1 and K.Saravanan2, 1GSSS Institute of Engineering & Technology for Women, India and 2Erode Sengunthar Engineering College, India
Opposition Based Firefly Algorithm Optimized Feature Subset Selection Approach for Fetal Risk Anticipation
V. Subha and D. Murugan, Manonmaniam Sundaranar University, India
Analysis of Opinionated Text for Opinion Mining  
K Paramesha1 and K C Ravishankar2, 1Vidyavardhaka College of Engineering, India and 2Government Engineering College – Hassan, India

March  2016, Volume 3, Number 1

Developing Prediction Model of Loan Risk in Banks Using Data Mining  
Aboobyda Jafar Hamid and Tarig Mohammed Ahmed, University Khartoum, Sudan
A Conceptual Framework on Futuristic Studies  
Sushma Rani Senior Research Fellow, Banasthali University, India
A Survey on Similarity Measures in Text Mining  
M.K.Vijaymeena and K.Kavitha, Nandha Engineering College, India

December 2015, Volume 2, Number 3/4

Machine Learning Based Approaches for Cancer Classification Using Gene Expression Data
Amit Bhola1 and Arvind Kumar Tiwari2, 1Kashi Institute of Technology, India and 2IIT (B.H.U.), IndiaCartoon Based Image Retrieval : An Indexing Approach  
Suman Muralidhar and Sharath Kumar Y H, Maharaja Institute of Technology, IndiaClassification of Machine Translation Outputs Using NB Classifier and SVM for Post-Editing
Kuldeep Kumar Yogi, Chandra Kumar Jha and Shivangi Dixit, Banasthali University, IndiaClassification of Enzymes Using Machine Learning Based Approaches: A Review
Sanjeev Kumar Yadav1 and Arvind Kumar Tiwari2, 1KIT, India and 2IIT (BHU), India

June 2015, Volume 2, Number 2

Feature Selection and Classification Approach for Sentiment Analysis
Gautami Tripathi and Naganna S, Galgotias University, India

March 2015, Volume 2, Number 1

Using Machine Learning Algorithms to Analyze Crime Data
Lawrence McClendon and Natarajan Meghanathan, Jackson State University, USA