Special Issue on Transformations in Industry Using Artificial Intelligence, Machine Learning, Deep Learning and Transfer Learning

Submission Deadline: Jul. 15, 2020

Please click the link to know more about Manuscript Preparation: http://www.mlrjournal.org/submission

This special issue currently is open for paper submission and guest editor application.

Please download to know all details of the Special Issue

Special Issue Flyer (PDF)
  • Lead Guest Editor
    • Dr. Sandhya P
      School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India
  • Guest Editor
    Guest Editors play a significant role in a special issue. They maintain the quality of published research and enhance the special issue’s impact. If you would like to be a Guest Editor or recommend a colleague as a Guest Editor of this special issue, please Click here to complete the Guest Editor application.
    • Dr. Malathi G
      School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India
    • Dr. Neduncheliyan S
      School of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India
    • Dr. Balasubramanian M
      Department of Computer Science and Engineering, Annamalai University, Chidhambaram, India
    • Dr. Dinesh M
      Department of Information Technology, College of Computing and Informatics, Saudi Electronic University, Abha, Saudi Arabia
    • Dr. Asha P
      Department of Computer Science and Engineering, Sathyabama University, Chennai, Tamil Nadu, India
    • Dr. Andrews J
      Department of Computer Science and Engineering, Presidency University, Bengaluru, India
    • Dr. Kavitha Esther
      Department of Computer Science and Engineering, KCG College of Technology affiliated to Anna University, Chennai, India
    • Sadi Alawadi
      Malmo Univbersity, Mallmo, Sweden
    • Jeevanandam Jotheeswaran
      ACOE, Amity University, Noida, India
  • Introduction

    Artificial Intelligence (AI) has been in existence decades ago. Currently with the increase in computational power and storage capacities, AI is reborn. The Industry 4.0 disrupts every vertical through the emergence of AI. It mimics the cognitive skills of humans such as learning and problem solving. Machine Learning is a subset of AI that learns from historic data to predict outcomes and uncovers patterns. ML has practical implications across all the industrial sectors including healthcare, insurance, energy consumption, marketing, manufacturing, financial technology, etc. Data deluge from digital devices supports AI solutions to manage, analyze and gain insight. Data science extracts meaningful acumens from data by amalgamating domain expertise, programming skills, mathematical and statistical knowledge. A data scientist applies ML algorithms on multimedia and multi-dimensional data to construct AI systems. Deep Learning is a subset of ML that has the ability to process large number of features. Deep Learning is more powerful to explore unstructured data. It is estimated that in 2019, the AI empowerment entity economy industry scale is close to $570 billion. AI has been incorporated in topnotch applications from Siri the pseudo-intelligent personal digital assistant to Alexa; Tesla the car with self-driving features; Boxever that delivers micro-moments for travellers; Netflix using predictive technology to suggest films to customers; Nest the learning thermostat; Pandora that recommends songs, etc. This issue aims to bring out the transformations in various sectors through disruptions using AI.
    Artificial Intelligence (AI) is the brain behind Industry 4.0 which is driven by Cyber Physical Systems and Internet of Things. The connected machines collect tremendous volume of data that can be analyzed to identify patterns and insights. Currently there are several disruptions in different fields using Artificial Intelligence. It is used in analyzing agricultural farm data such as weather conditions, temperature, water usage, soil conditions etc. AI is used in health-care for clinical decision support, computer-aided diagnosis, computer-aided simple triage, medical image computing etc. In banking sector AI is used to enhance customer experience; predict fraud, detect anti-money laundering pattern and make customer recommendations; provide cognitive process automation; robotic automation of processes, etc. In education sector AI provides personalized learning, smart content, voice assistants, etc. This special issue invites unpublished prospective works on Artificial Intelligence, Machine Learning and Deep Learning that disrupts traditional business models.
    Scope:
    1. Disruptive Solutions using Artificial Intelligence
    2. AI in Agriculture
    3. Deep Learning in Imaging Science
    4. Big Data and Data Analytics
    5. AI in Health care
    6. AI in retail and marketing
    7. AI in Education
    8. Predictive Analytics
    9. AI for Natural Language Processing
    10. AI in scheduling and optimization
    11. AI in modeling and simulation
    12. Collective Intelligence
    13. Speech Understanding
    14. Web Intelligence
    15. Artificial Immune Systems
    16. Knowledge Engineering
    17. Machine Learning
    18. Human-Computer Interaction
    Aims and Scope:
    1. Artificial Intelligence
    2. Machine Learning
    3. Deep learning
    4. Big Data and Data Analytics
    5. Data Science
    6. Industry 4.0

  • Guidelines for Submission

    Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.

    Papers should be formatted according to the guidelines for authors (see: http://www.mlrjournal.org/submission). By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at http://www.sciencepublishinggroup.com/login. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.

  • Published Papers

    The special issue currently is open for paper submission. Potential authors are humbly requested to submit an electronic copy of their complete manuscript by clicking here.