Advanced Intelligent Systems and Informatics (AISI) is an interdisciplinary research field which involves researchers from information technologies, bioinformatics, computer science, medical informatics, biology, social studies, national Language processing, IOT, as well as robotics research. AISI’2017 conference aims for encouraging the integration of these research fields by providing a chance for academics, researchers, analysts, industry consultants, and practitioners in the fields involved to discuss and exchange recent progress in the area of informatics and intelligent systems technologies and applications. The conference has three major tracks (Intelligent Systems, Intelligent Robotics Systems, and Informatics).

Topics of interest for each track include (but are not limited to):

Intelligent systems
• Machine Learning
•Genetic Algorithms
•Neural Nets, Fuzzy Systems
•Rough sets, near sets
•Fuzzy and Neuro-Fuzzy Control
•Knowledge Based Systems
•Expert Systems and Lazy learning
•Computing Machinery and Intelligence
•Computer Networks
•Mining of Massive Datasets
•Massive Data Analysis
•Massive Datasets Applications
•Algorithms for Modern Massive Data Sets
•Intelligent signal processing systems
•Bio-Inspired Systems
•Precision Farming
•Precision Agriculture

Intelligent Robotics Systems
• Human-Robotic Interaction
•Human-Robotic Interaction
•Control, Flexible Arm Control
•Pereception and Recognition
•Distributed robotics
•Evolutionary robotics
•Behavior-based robotics
•Biometrics and Bio-robotics
•Bio-morphics robotics
•Cognitive robotics
•Bio-Inspired Robotics Lab
•Sensory-Motor Systems
•Reasoning, and Learning
•Robotic Systems and Service
•Surgery Robotics
•Intelligent and autonomous systems
•Mathematical modeling and analysis of complex systems
•Knowledge based control systems
•Adaptive control systems
•Control applications in Intelligent robotics

• The Web and Business intelligence
•The Web and Business Intelligence
•Data mining and Big data analysis
•Healthcare Informatics
•Biomedical informatics
•Systems biology
•Medical imaging
•Medical informatics
•Informatics in education process
•Distributed multimedia
•Hypermedia information space
•Intelligent information retrieval
•Digital libraries
•Virtual and Augmented reality
•Signal and Speech processing
•Object recognition
•Image and video retrieval

Intelligent Natural Language Processing

New trends of intelligent language processing systems are emerging, such as big data analysis, social  network analysis, Internet of things, smart services, mobile computing, computer games, to name a few. Applications of these trends have been applied to various domains including education, travel and tourism, healthcare, among others. Many issues encountered during the development of these applications are resolved by incorporating language technology solutions, which involves speech processing, text extraction and retrieval, and deep learning, which are currently attractive topics within computational linguistics research areas.  The purpose of the “Intelligent Language Processing: Trends and application” track is to bring scientists, researcher scholars, practitioners, and students from academia and industry to present recent and ongoing research activities about the recent advances, techniques, and applications of intelligent language Processing systems and to allow the exchange of new ideas and application experiences face to face.

Internet of things and Big Data Analytics

The uses of Information Technology (IT) has increasedday which therefore ended to be every thing that we are doing, we can directly go through online on the spot. Information technology is any kinds of software or tools for keeping information, retrieve and sending the information using a certain type oftechnology such as computer, mobile phones, computer networks and more. With this IT, people are now able to upload, retrieve,store their information and collect information to Big Data. Since Big Data hold massive information with the use of IT such as the internet, students are now able to study online which is called as e-Learning. As the tools provided by Information Technology (IT) have increased continuously, these have affected all aspects of ourlives, specifically, in the area of academic. Big Data and e-Learning do bring people or the users specifically, both various benefits anddisadvantages because of its multi-function ability. Therefore, it affects our social skills, mental growth, physical and risks of invadingour personal information. Hence, the discussion from regular peopleperspectives to many other different perspectives such as, businesses perspectives, health care perspectives, government perspectivesand many more. The drive to incorporate more big data within organizations is a powerful one. The use of big data analytics has grown tremendously in just the past few years, and businesses are quickly catching on to what they stand to gain. At the same time, the Internet of Things (IoT) has entered the public consciousness, sparking people’s imaginations on what a fully connected world can offer. While separately the two trends give plenty of reason for excitement, combining the two only multiplies the anticipation.  The world is running on data now, and pretty soon, the world will become fully immersed in the Internet of Things.  This editing book is intended to present the state-of-the-art in research on Big data and IoT and related areas. 

All accepted papers will be published in the conference proceeding which will be published by Springer in the series of “Advances in Intelligent Systems and Computing” and abstracted/indexed in DBLP, Google Scholar, EI-Compendex, Mathematical Reviews, SCImago, Scopus. 

Student Best Paper Award
Papers accepted and presented in the conference and their first author is MSc or PhD students will be given the opportunity to compete for the Best Paper Award. The entries of the competition should be presented at the conference by the student.

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