Autosoft Journal

Special Issues

Call For Papers

Special Issue on Recent Advances in Artificial Intelligence for Smart Manufacturing

Smart manufacturing, also known as Industry 4.0, refers to the next-generation manufacturing paradigm that aims to make use of smart sensors, cloud computing infrastructures, artificial intelligence or machine learning, advanced robotics to improve manufacturing productivity and cost efficiency. As one of the key enablers for smart manufacturing, the Internet of Things (IoT) enables integration of physical objects with digital systems by offering connectivity of manufacturing devices and systems through sensors or augmented reality. Due to the arrival of big data, Internet of Things, cyber-physical systems, cloud manufacturing, and so on, manufacturing is in the process of undergoing a significant transformation to become more intelligent and automated. More strikingly, various artificial intelligence techniques, machine learning algorithms, and big data analytics are being researched and deployed into remanufacturing context, e.g., design for remanufacturing, advanced remanufacturing process, robotics in manufacturing, critical failure prediction, inventory forecasting, resilient manufacturing networks, closed-loop supply chain management, etc. The purpose of this SI is to provide a forum for researchers and practitioners to exchange ideas and progress in related areas.

Topics of interest for articles include, but are not limited to:

Emerging sensing technologies for smart manufacturing
Sensor-enabled manufacturing process monitoring and control
Manufacturing intelligence and manufacturing informatics
Advanced diagnostics, prognostics and asset health management
Embedded systems for smart manufacturing
Augmented reality and wearable computing for greater equipment or process awareness
Machine-to-machine communication standards for smart manufacturing
Human machine interactions for smart manufacturing
Smart manufacturing test beds
Cybersecurity for smart manufacturing systems
Smart inspection systems
Cloud-based applications for smart manufacturing
IoT interoperability for smart manufacturing

Guest editors:

Zheng Xu, Shanghai University, Shanghai, China
Neil Yen, University of Aizu, Japan
Junchi Yan, IBM Research, China

Submission Instructions

Authors should follow the manuscript format and the submission procedure of Intelligent Automation & Soft Computing Journal manuscript format described below at the Journal site: The submission must include the title, abstract of your paper, and the corresponding author's name and affiliation. All papers will be rigorously reviewed based on the quality: originality, high scientific quality, well organized and clearly written, sufficient support for assertions and conclusions. Important Dates
Manuscript Due: October 1, 2018
First Round of Reviews: November 30, 2018
Final Decision: December 30, 2018

Special Issue on Soft Computing Techniques for Medical Healthcare Intelligent Systems

Today life is being continuously threatened by various harmful diseases, some of which are even incurable. Recently the rate of diseases is increasing rapidly with the increase in the change of symptoms of each disease. The medical industry requires new Intelligent technologies, to successful diagnoses and surgical outcomes depend on the experience and skill of examiners with it the risk of failure. Thus, the Medical industry requires new Intelligent technologies, such as soft computing techniques, to assess information objectively. Soft computing is based on natural as well as artificial ideas. It is referred as a computational intelligence. In fact the role model for soft computing is a human mind. Soft computing techniques have become one of promising tools that can provide practical and reasonable solution. It combines the design and problem solving skills of engineering with medical to advance health care treatment, including diagnosis, monitoring, treatment and therapy.Computers aid in developing a fully automated system which would help in accurate identification of abnormalities in the medical field. The accuracy of the computer aided systems is highly superior to the manual observations and hence automated systems are significantly preferred by the physicians. Most of the automated systems are based on soft computing techniques which includes Artificial neural networks, fuzzy theory, evolutionary algorithms, Artificial intelligence techniques, etc. The Medical Healthcare Systems are integrated with Soft Computing techniques and expert systems to assist the doctors in every possible ways. Modern intelligent Medical Healthcare systems and techniques give access to vast sources of knowledge base as well as virtual database most of which are self-updating. This special issue small effort to present a review of some of the Soft Computing techniques carried out by various researchers in the field of development of Expert systems, new algorithms and tools used for the diagnosis of different disease. Soft computing techniques came into existence to deal effectively with the emerging problems related to medical diagnosis. The purpose of this special session is to demonstrate the potential of several intelligent approaches exploited in medical planning, diagnosis and treatment. This also brings together researchers and practitioners from academia to industry working in multi-disciplinary area and technically converging areas.

Topics of interest for articles include, but are not limited to:

Medical imaging, signal processing and text analysis
Data mining medical data and Clinical Expert Systems
Modelling and simulation of medical processes
Patient-centric care, medical imaging, medical ontology
Rational drug design and personalized medicine
Biomedical text/data mining and visualization
Computer-aided diagnosis, detection and surgery systems
Medical informatics and Healthcare
Medical image/signal analysis and theory/algorithm/systems
Multidimensional data Visualisation
Soft computing for medical Screening
Therapy, Prognosis and MonitoringBiomedical/Biological Analysis and Epidemiological Studies
Hospital Management,Medical Instruction and Training
Pathological signals (ECG, EEG, EMG)
Medical Images (mammograms, ultrasound, X-ray, CT, and MRI)
Neural networks ,fuzzy logic and Genetic algorithms
Intelligent medical imaging systems and Motion Analysis
Wireless Healthcare and Biological image analysis
Biomedical Data, Biomedical Ontology and Bioinformatics
Artificial Neural Networks for scan images such as brain, eye, lungs, blood, bone, etc.
Medical Image denoising, noise removal, etc.
Medical scan images and texture analysis

Guest editors:

Dr. A. Jayanthiladevi, Jain University, Bangalore, India-
Dr. Jenn-Wei Lin, Fu Jen Catholic University, Taiwan-
Manivel Kandasamy, OptumHealth|United Health Group, USA-

Submission Instructions

Authors should follow the manuscript format and the submission procedure of Intelligent Automation & Soft Computing Journal manuscript format described below at the Journal site: The submission must include the title, abstract of your paper, and the corresponding author's name and affiliation. All papers will be rigorously reviewed based on the quality: originality, high scientific quality, well organized and clearly written, sufficient support for assertions and conclusions.

Tentative submission deadline of the Special Section.
Manuscript due: September 25th, 2018
Acceptance/Rejection notification: November 20th, 2018
Final manuscript due: December 25th , 2018

Special Issue on Recent Advances in Data Driven Modeling & Soft Computing


Network information intelligent systems
Soft computing techniques
Driven modelling and control
Intelligent and knowledge based systems
Web interaction
Machine learning for big data and information processing
Statistical and deep learning methods
Distributed generation systems
Signal feature, fingerprint recognition
Computing on signal and/or image processing

Important Dates

Submission deadline: April 1, 2017
Notification of the first-round review: June 1, 2017
Revised submission due: October 1, 2017
Final notice of acceptance/reject: November 1, 2017
Camera Ready Due: December 1, 2017

Guest Editors

Prof. Wen-Hsiang Hsieh
Department of Automation Engineering, National Formosa University

Prof. Jerzy W Rozenblit
Department of Electrical and Computer Engineering, University of Arizona
Arizona, USA

Prof. Minvydas Ragulskis
Department of Mathematical Modeling, Kaunas University of Technology

Special Issue: Big Data & Analytics Architecture

Data is often considered the crown jewels of an organization. It can be used in myriad ways to run the business, market to customers, forecast sales, measure performance, gain competitive advantage, and discover new business opportunities. In addition, lately, a convergence of new technologies and market dynamics has opened a new frontier for information management and analysis. This new wave of computing involves data with far greater volume, velocity, and variety than ever before. Big Data is being used in ingenious ways to predict customer-buying habits, detect fraud and waste, analyze product sentiment, and react quickly to events and changes in business conditions. It is also a driving force behind new business opportunities. Traditional data analysis technologies are based on the well-structured data from operational systems that conform to pre-determined relationships. Big Data, however, does not follow this structured model. The streams are all different and it is difficult to establish common relationships. However, with its diversity and abundance come opportunities to learn and to develop new ideas which that can help researcher to learn some new knowledge. The architectural challenge is to bring the two paradigms together. So, rather than approach Big Data as a new technology silo, which enables to leverage all types of data, as situations demand, to promptly satisfy kinds of new needs.

Topics of interest for articles include, but are not limited to:

Big data analysis algorithms
Scalable data storage and computation management for Big Data
Resource scheduling, SLA, Fault tolerance and reliability for Big Data
Multiple source streaming data processing and integration
Virtualization and visualization of Big Data
Novel programming models and platforms such as MapReduce or Spark for Big Data
Security and privacy in Big Data processing
Green, energy-efficient models and sustainability issues for Big Data
Innovative Cloud infrastructure for Big Data
Wireless and mobility support in for Big Data
Scalable software platforms for fast Big Data analytics on heterogeneous and hybrid architectures
Big Data applications on heterogeneous architectures such as healthcare, surveillance and sensing, e-commerce, etc.
Guest Editor Information
Arun Kumar Sangaiah, VIT University, India
Corresponding GE: Walter Miller, University of Alberta, Canada (
Ford Lumban Gaol, Bina Nusantara University, Republik Indonesia
KRISHN K. MISHRA, Department of Mathematics and Computer Science, University of Missouri, USA

Guest editors:

Arun Kumar Sangaiah
Dr. Walter Miller
Dr. Ford Lumban Gaol
Dr. K. K. Mishra

Submission Instructions

This special issue solicits original work not under consideration for publication in any other conference or journal. Authors need to prepare the manuscripts according to the rudiments of Intelligent Automation & Soft Computing journal (Autosoft Journal). Authors should submit their papers through the online manuscript portal system ( and select the right special issue. For more information, please contact the Corresponding Guest Editor Dr. Walter Miller at

Tentative submission deadline of the Special Section.
Manuscript due: December 31, 2017
First round of reviews: March 31, 2018
Revised paper due: May 15, 2018
Final author notification: June 30, 2018
Expected publication: the third quarter of 2018

Special Issue: Artificial Intelligence for Cloud-based Internet of Things (IoT)

The cloud-based Internet of Things (IoT) is used to connect a wide range of things such as vehicles, mobile devices, sensors, industrial equipments and manufacturing machines to develop a various smart systems it includes smart city and smart home, smart grid, smart industry, smart vehicle, smart health and smart environmental monitoring. A recent report from Juniper Research has discovered that “the number of IoT (Internet of Things) connected devices will number 38.5 billion in 2020, up from 13.4 billion in 2015: a rise of over 285%”. Similarly, “The Internet of Things: Consumer, Industrial & Public Services 2015-2020”, found that while the number of connected devices already exceeds the number of humans on the planet by over 2 times, for most enterprises, simply connecting their systems and devices remains the first priority. A recent report state that, “The overall Internet of Things market is projected to be worth more than one billion U.S. dollars annually from 2017 onwards”. As a result, data production at this stage will be 44 times greater than that in 2009, indicating a rapid increase in the volume, velocity and variety of data. Hence, IoT based smart systems generate a large volume of data often called big data that cannot be processed by traditional data processing algorithms and applications. Here will therefore, by difficulty in storing, processing and visualizing this huge data generated from IoT based system. However, there is highly useful information and so many potential values hidden in the huge volume of IoT based sensor data. IoT based sensor data has gained much attention from researchers in healthcare, bioinformatics, information sciences, policy and decision makers in governments and enterprises. Nowadays, Artificial intelligence methods play a significant role in various environments including business monitoring, healthcare applications, production development, research and development, share market prediction, business process, industrial applications, social network analysis, weather analysis and environmental monitoring. The Internet of Things (IoT) and Artificial intelligence will play a vital role in numerous ways in the future. There are multiple forces which are driving the growing need for both technologies and more and more industries, governments, engineers, scientists and technologists have started to implement it in manifold circumstances. The potential opportunities and benefits of both AI and IoT can be practiced when they are combined, both at the devices end as well as at server. For example, AI combined with Machine learning can study from the data to analyze and predict the future actions in advance, such as order replacements in marketing and failure of equipment in an industry just in time. Moreover, AI can be used with machine learning in smart-homes to make a truly grand smart home experience. Similarly, AI methods with IoT can be used to analyze the human behavior via Bluetooth signals, motion sensors, or facial-recognition technology and to make the corresponding changes in lighting and room temperatures. This special issue aims to gather recent research works in emerging artificial intelligence methods, intelligent algorithms, machine learning algorithms and multi-agent systems for cloud-based Internet of Things.

Topics include, but are not limited to, the following:

Automated reasoning and inference for cloud-based Internet of Things
Case-based reasoning in cloud-based Internet of Things
Cognitive aspects of AI in cloud-based Internet of Things
Intelligent interfaces for cloud-based Internet of Things
Knowledge representation in cloud-based Internet of Things
Machine learning for cloud-based Internet of Things
Multiagent systems for cloud-based Internet of Things
Natural language processing for cloud-based Internet of Things
Intelligent algorithms for cloud-based Internet of Things
Agent based algorithms for cloud-based Internet of Things
Swarm Intelligence, Nature Inspired algorithms for cloud-based Internet of Things
Artificial intelligence and Genetic algorithms for cloud-based Internet of Things
Machine learning and deep learning for cloud-based Internet of Things
Fuzzy systems for cloud-based Internet of Things
Neural networks for cloud-based Internet of Things

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. All papers are refereed through a peer review process.

All papers must be submitted online. To submit a paper, please read our information on submitting articles.

If you have any queries concerning this special issue, please email the Guest Editors.

• Submission deadline: July 30, 2018
• Author notification of first round review: Sep 25, 2018
• Revised submission due: Oct 25, 2018
• Final notification: Nov 15, 2018
• Camera-ready due: Dec 25, 2018

Guest Editors:

Dr.Gunasekaran Manogaran, University of California, Davis, USA,
Dr. Naveen Chilamkurti, Department of Computer Science and Computer Engineering, LaTrobe University, Melbourne, Australia,
Dr. Ching-Hsien Hsu, Department of Computer Science and Information Engineering, Chung Hua University, Taiwan

Special Issue: Advanced ICT and IoT technologies for the fourth Industrial Revolution

Based-on the rapid advancement of computers, internet, and ICT infrastructures, the fourth industrial revolution has recently begun. In this industrial era, diverse technological innovations that are focused on connectivity and convergence integrate the physical, biological, and digital boundaries and affects all areas of economy and industry. Accordingly, these technologies connect people and thing with things through internet, analyze vast amount of data produced by such connectivity to obtain a certain pattern, and predict human behaviors based on the results of the analysis to create new values. This Special Issue is about emerging ICT and IoT technology breakthroughs that are essential for moving towards fourth industrial revolution. These ICT and IoT innovations enables connectivity of smart things and seamless convergence of diverse technologies to provide productivity and efficiency improvements, better quality of life, and even solutions for environmental issues.

Topics of interests include, but are not limited to:
Artificial Intelligence and Autonomous Systems in Smart Factory
Big Data Integration, Algorithms, Methodology, Analytics and Challenges in IoT
Cognitive Computing, Affective Computing, Machine Learning for IoT
Edge Computing Technologies for IoT
Hybrid Intelligent Models and Applications for IoT and Industrial Applications
Information Coordination and Interaction in IoT
Intelligent and Interactive Interface for IoT
Intelligent Transportation Systems
Machine Learning and Decision Science Models for Data Analysis for Industrial IoT
Meta-Heuristic Algorithms for IoT
Software Engineering Approaches for IoT

Submission Details

Authors should follow the manuscript format and submission procedure of Intelligent Automation & Soft Computing Journal manuscript format described below at the Journal site: Further, the manuscript must be submitted in the form of WORD file to email ( The submission must include the title, abstract of your paper, and the corresponding author's name and affiliation. All papers will be rigorously reviewed based on the quality: originality, high scientific quality, well organized and clearly written, sufficient support for assertions and conclusion.


Manuscript due: July 5, 2018
Acceptance/rejection notification: November 5, 2018
2nd round check: January 15, 2019
Final manuscript due: January 31, 2019

Guest Editor(s)
Prof. Soo Kyun Kim(Corresponding GE), Paichai University, Korea, email:
Prof. Mario Köppen, Kyushu Institute Technology, Japan
Prof. Ali Kashif Bashir, University of Faroe Islands, Faroe Islands, Denmark
Prof. Yuho Jin, New Mexico State University, USA

For enquiries, please contact


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present

SCImago Journal & Country Rank


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