IJAIA 2019 : International Journal of Artificial Intelligence & Applications

International Journal of Artificial Intelligence & Applications (IJAIA)

The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications.

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 Artificial Intelligence & applications. Topics of interest include, but are not limited to, the following:

Authors are invited to submit papers for this journal through Email: [email protected] or through 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.

• International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)

May 2019, Volume 10, Number 3

A Survey on Different Machine Learning Algorithms and Weak Classifiers Based on KDD and NSL-KDD Datasets  Full Text
Rama Devi Ravipati and Munther Abualkibash, Eastern Michigan University, USA

Multi-Level Feature Fusion Based Transfer Learning for Person Re-Identification  Full Text
Yingzhi Chen and Tianqi Yang, Jinan University, China

Improving the Communication for Children with Speech Disorders Using the Smart Toys Full Text
Amr Mohsen Jadi, University of Hail, Saudi Arabia

A Comparative Analysis of Different Feature Set on the Performance of Different Algorithms in Phishing Website Detection  Full Text
Hajara Musa¹, Bala Modi¹, Ismail Abdulkarim Adamu², Ali Ahmad Aminu¹, Hussaini Adamu¹ and Yahaya Ajiya¹, ¹Gombe State University, Nigeria and ²Gombe State Polytechnic, Nigeria

Mixtures of Trained Regression Curves Models for Handwritten Arabic Character Recognition  Full Text
Abdullah A. Al-Shaher, Public Authority for Applied Education and Training, Kuwait

• David B. Bracewell, Oculus360, USA

• Alessandro Massaro, Dyrecta Lab, IT Research Laboratory, Italy
  
• Dilana Hazer-Rau, University of Ulm, Germany

• Vijayaraghavan Varadharajan, Infosys Limited, India
  
• Bala Modi, Gombe State University, Nigeria
• Abdelkarim Mars, LIDILEM, French
• Abdelmonaime Lachkar, SMBA University Fez, Morocco
• Abhay Saxena, Dev Sanskriti University, India
• Abilash, Birla Technical Training Institute, India