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The 2017 International Conference on Computer, Control, Informatics and its Applications (IC3INA 2017) is the 5th annual conference co-organized by Research Center for Informatics, Indonesian Institute of Sciences (LIPI). IC3INA is intended to gather researchers, academics, engineers, scholars and practitioners to present recent innovations and developments, and to exchange ideas and progresses in the advanced technologies of computer, control, informatics and its applications. The conference has been approved and co-sponsored by IEEE with the conference no. 41645.
This year event will be held in Jakarta, the capital city of Indonesia on 23-24 October 2017. Previous conferences have been successfully held and the proceedings have been indexed by IEEEXplore (2013, 2014, 2015, and 2016)
All papers accepted and presented in IC3INA 2017 will also be forwarded for consideration to be published in the IEEE Xplore Digital Library.
Dr. Yi Pan (Regents' Professor of Computer Science, Interim Associate Dean and Chair of Biology, Department of Computer Science, Georgia State University, USA)
Deep Learning for Big Data and Bioinformatics Applications
Abstract: Deep learning is a very hot area in machine learning research with many remarkable recent successes in computer vision, automatic speech recognition, natural language processing, audio recognition, and medical imaging processing. AlphaGo, the first Computer Go program to beat a professional human Go player, uses a deep learning method. Although various deep learning architectures such as deep neural networks, convolutional deep neural networks, deep belief networks and recurrent neural networks have been applied to many big data applications, using deep learning to solve bioinformatics problems is still in its infancy. In this talk, I will outline the challenges and problems in existing deep learning methods when applying it to big data in general and bioinformatics in particular. I will describe a few novel architectures and algorithms recently proposed by us to improve the accuracies and learning speeds of the existing deep learning technologies. These new deep learning architectures and algorithms will be applied to several big data applications including image processing, DNA sequence annotation, long intergenic non-coding RNA detection, and gene structure prediction. The data encoding schemes, the choice of architectures and methods used will be described in details. Performance comparisons with other machine learning and existing deep learning methods will be reported. The experimental results show that deep learning is very promising for many bioinformatics applications, but requires selection of suitable models and a lot of tuning to be effective. Future research directions in this exciting area will also be outlined.
Dr. Naoya Wada (Director General of Network System Research Institute, NICT, Japan)
Huge capacity and flexible optical network technologies - Common ground for IoT, big data, 5G, and beyond 5G
Abstract: We review the research and development of beyond Pb/s capacity space-division-multiplexed (SDM) transmission technology using multi-core optical fibers for satisfying the ever-increasing traffic demand due to IoT, big data, 5G, and beyond 5G. Moreover, we present an optical integrated network technology to improve switching capacity and flexibility in network nodes for the rapid traffic fluctuation and the data service diversification.
Dr. Rifki Sadikin (Head of High Performance Computing Lab, Research Center for Informatics, Indonesian Institute of Science, Indonesia)
High Performance Computing for Computational Sciences
Abstract: We present on how high performance computing service is delivered in Indonesian Institute of Sciences and some research activities conducted in the high performance computing laboratory.High performance computing service at Indonesian Institute of Sciences has enable scientists to conduct complex computation in various fields.It provides parallel computing environment in a computer clusters. The computations come from some problems that require numerical solutions, virtual experiments and complex simulations.We also present our involvement in ALICE (A Large Ion Collider Experiment) collaboration at CERN. We develop high perfomance computing solutions for data compression and data taking in TPC (Time Projection Chamber) one of detectors at ALICE.
GUIDELINES FOR AUTHORS
Prospective authors are invited to submit full-length papers, with up to six pages for technical content including figures and possible references. Topics of interest include, but are not limited to the following areas:
Computer Track - Computer Systems, Computer Communication and Networking, Distributed and Parallel Infrastructure, Computer Interfacing, Embedded System, Wireless Sensor Network, Network Security, Micro(processor/controller) System, Signal Processing
Control Track - Intelligence Control Systems, Neural Network, Fuzzy Control Systems, Control Theory,Real Time Control Systems.
Informatics Track - Artificial Intelligence and Machine Learning, Mobile and Cloud Computing, Software Engineering, Database Systems, Formal Method in Software Engineering, Data Mining, Image Processing, Computer Vision, High Performance Computing, Pattern Recognition, Object Recognition, Speech and Language Processing.
Applications Track - Bioinformatics, E-Business, Tele-medicine, Intelligence Building, Information Systems, Biomedical Engineering
Paper Format - Papers submitted for IC3INA 2017 should be up to 6 pages of text including figures and possible references. Any paper with more than 6 pages will not be considered for acceptance. The authors are responsible to ensure that the submitted papers are in the correct styles, fonts, etc. The submitted papers must be in the PDF format.
Template - The Style Manual and Conference Paper templates in various formats are available here.
Paper Submission Procedure - Submit your papers in pdf format through EDAS system (http://edas.info/N23551).
Non-presented Paper Policy IEEE reserves the right to exclude a paper from distribution after the conference, including IEEE Xplore Digital Library, if the paper is not presented by the author at the conference.
Please contact the IC3INA 2017 Technical Program Chairs at ic3ina[at]mail.lipi.go.id
Previous Conference (IC3INA 2015)
Previous Conference (IC3INA 2014)
Previous Conference (IC3INA 2013)
IC3INA 2017 is sponsored by Indonesian Institute of Sciences - LIPI.