Trends in Artificial Intelligence

 ISSN: 2643-6000

Trends in Artificial Intelligence

About Journal


Trends in Artificial Intelligence is an open access, peer reviewed journal dedicated to publish novel research in the intelligence exhibited by software's or machines. It also includes but not limit to reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. Artificial Intelligence is interdisciplinary field in which a number of sciences and professions converge, including computer science, mathematics, psychology, linguistics, philosophy and neuroscience, as well as other specialized fields such as artificial psychology.

Trends in Artificial Intelligence covers various article types such as original, reviews, commentaries, rapid communication, other short articles in the academic field of study which studies how to create computers and computer software that are capable of intelligent behavior. All the published manuscripts undergo peer review processing under evaluation by International subject experts.

All the published content with us are made available freely with no restriction barriers under the terms of Creative Commons Attribution License.


Editorial Board



Prof. Xiaowei Xu

Professor
Department of Information Science
University of Arkansas, Little Rock
United States of America
Tel: 501-683-7266


Prof. Ernest Greene

Professor
Department of Psychology
University of Southern California
United States of America
Tel: 213-740-7967  


Prof. Fleur T Tehrani

Professor
Electrical Engineering (EE) Department
California State University
United States of America 
Tel: 714-281-5859


Dr. Anthony Christopher Chang

Chief Intelligence and Innovation Officer
The Sharon Disney Lund Medical Intelligence and Innovation Institute
Children Hospital of Orange County,
United States of America
Tel: 714-509-7576


Prof. Yiannis Papadopoulos

Leader of Dependable Systems Research Group
University of Hull
Cottingham Rd, HU67RX
HULL, United Kingdom
Tel: +44 (0) 1482 465981


Dr. Massimo Buscema

Director of Semeion
Research Centre of Sciences of Communication
Via Sersale 117
Rome, 00128, Italy
Phone: +39-06-50652350


Submit your manuscript to this journal through online or email us at editorialoffice@scholars.direct


Latest Articles

Commentary

A Commentary on the Application of Artificial Intelligence in the Insurance Industry

Millions of uninsured individuals in the US live in the areas, which are highly vulnerable to health and other risks. Artificial intelligence (AI) has... Read more

10.36959/643/305

Review Article

Artificial Intelligence (AI) Tools Constructed via the 5-Steps Rule for Predicting Post-Translational Modifications

Identification of the sites of post-translational modifications (PTMs) in protein, RNA, and DNA sequences is currently a very hot topic. This is beca... Read more

10.36959/643/304

Original Article

Solving Integer Programming Problems by Hybrid Bat Algorithm and Direct Search Method

The goal of this work is to suggest a new hybrid algorithm to solve integer programming by incorporating the bat algorithm with direct search methods.... Read more

10.36959/643/303

Research Article

Scan Transcription of Two-Dimensional Shapes as an Alternative Neuromorphic Concept

A similarity response is only one of many kinds of response we can elicit from a subject, by suitable manipulation of the number and variety of the st... Read more

10.36959/643/301

Communication

What Constitutes Elemental Shape Information for Biological Vision?

The part itself would be seen not as a "part" of some earlier figure but as a self-sufficient whole in its own right Friedrich Wulf. We do not yet und... Read more

10.36959/643/300

Research Article

A Hybrid Flower Pollination and Genetic Algorithm for Minimizing the Non-Convex Potential Energy of Molecular Structure

Minimizing the molecular potential energy function is a real-life problem which can help to predict the three-dimensional structure of the protein by ... Read more

10.36959/643/299

Research Article

Key Amino Acids in Understanding Evolutionary Characterization of Mn/Fe-Superoxide Dismutase: A Phylogenetic and Structural Analysis of Proteins from Corynebacterium and Hosts

Superoxide dismutases (SODs) are enzymes widely observed in nature and commonly studied to understand the protection of reactive oxygen species (ROS).... Read more

10.36959/643/298

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