2017 Eleventh International Conference on Sensing Technology (ICST)

Sydney, Australia | December 4 - 6, 2017

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Welcome Message ....................................................................................................... 1 Technical Programme Committee of ICST 2017 .......................................................... 3 Keynote Speakers ........................................................................................................ 7 Invited Speakers ........................................................................................................ 11 ICST 2017 Programme at a glance ........................................................................... 28 Venue ......................................................................................................................... 31 Banquet ...................................................................................................................... 32 Technical Programme ................................................................................................ 33 S0: Opening Session ................................................................................................. 33 Keynote Session I ...................................................................................................... 33 S2A: Biosensors ......................................................................................................... 33 S2B: WSN and IoT I ................................................................................................... 36 S2C: Sensors for Novel Applications I ....................................................................... 39 S3A: Wearable Sensors and Activity Monitoring ....................................................... 41 S3B: Image and Range Sensors ............................................................................... 46 S3C: Spectroscopy Techniques ................................................................................. 49 S4A: Sensors for Novel Applications II ...................................................................... 53 S4B: Mechanical Sensors .......................................................................................... 56 S4C: Gas Sensors ..................................................................................................... 60 S5: Keynote Session #2 ............................................................................................. 63 S6A: Special session on Smart Agriculture I ............................................................. 64 S6B: Optical and Fibre Optic Sensors ....................................................................... 69 S6C: WSN and IoT II .................................................................................................. 72 S7A: Magnetic Sensors .............................................................................................. 76 S7B: Special session on Smart Agriculture II ............................................................ 79 S7C: Ultrasound and Vibration Sensors .................................................................... 82 S8: Invited Session I .................................................................................................. 85 S9A: Healthcare Applications II.................................................................................. 86 S9B: Structural Health Monitoring .............................................................................. 89 S9C: Sensors for Novel Applications III ..................................................................... 92 S10A: Special Session: Micro and nano devices for biomedical applications. .......... 95 S10B: Sensors for Novel Applications IV ................................................................... 98 S10C: Special session: Sensors and instrumentation for the environment and climate change monitoring .................................................................................................... 101 S11: Invited Session II ............................................................................................. 105 S12: Closing Session ............................................................................................... 105

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Welcome Message

We would like to take this great opportunity to welcome you all to the 2017 Eleventh International Conference on Sensing Technology, ICST 2017, held from December 4 – 6, 2017 at the Macquarie University, NSW 2109, Australia. This is the Eleventh conference of the series and the First time will be held in Australia. In terms of the history of the ICST, the first two (2005, 2007) of which were held at Massey University, New Zealand, Palmerston North campus, the third (2008) one was held at National Cheng-Kung University, Tainan, Taiwan, the fourth (2010) one was held at the University of Salento, Lecce, Italy. Then the fifth (2011) one was held at Massey University, New Zealand, Palmerston North campus and the sixth (2012) was held at Kolkata, India. The seventh (2013) one was held at the Wellington campus of the Massey University, New Zealand and the eighth (2014) one was held at Liverpool John Moore University, Liverpool, United Kingdom. The Ninth one was held in Auckland (2015) and the Tenth one was held at Nanjing, China (2016). This conference has attracted 153 papers that were considered for a peer-review process. We would like to congratulate all the authors and share this happiness with you all. All total 107 accepted papers will be presented over three days in three parallel oral sessions. All total 10 eminent scientists from around the world will deliver two keynote and eight invited talks during the conference. The applications of Sensing Technology ranging from medical diagnostic to industrial manufacturing and to defense, agriculture and food safety, national security, prevention of natural disaster and terrorism. The proper detection of events by high performance sensors and appropriate analysis of sensor signals can lead to early warning of phenomena like the bridge collapse at Mississippi river and many other countries and help to prevent deaths from these types of catastrophic accidents. Nowadays, there is an increased need for interaction between researchers across technologically advanced and developing countries working on design, fabrication and development of different sensors. We sincerely hope ICST 2017 provides a forum for that. On behalf of the organizer we would like to extend our sincere thanks to many organizations and individuals. Firstly we would like to thank all the authors as they are the key people for any conference to succeed. The Technical programme committee has done a tremendous and wonderful job. We are very much indebted to everybody in the Technical Programme committee for accepting the invitation and for lending their help, support, time and effort to make this conference a great success. Our special thanks to our keynote speakers and invited speakers for their time and support.

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The conference is being organized by the School of Engineering, Macquarie University. We thank the Event management service for organizing all conference related services. We do sincerely belief that the conference will provide a platform for discussion on the advancement of technical and scientific issues of different sensing technological problems and interaction among the participants will be stimulating, productive and encouraging. We wish you all a pleasant stay during the conference at Sydney and enjoy your time while you are in Australia.

S. C. Mukhopadhyay, O. Postolache and K. P. Jayasundera Sydney, Australia December 2017

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Technical Programme Committee of ICST 2017 Honorary Chairs Iain Collings, Macquarie University, Australia Shoogo Ueno, Kyushu University, Japan K. T. V. Grattan, City University, UK Emil Petriu, University of Ottawa, Canada D.P. Tsai, AS, Taiwan P. Sallis, AUT, NZ

General Chair Subhas Mukhopadhyay, Macquarie University, Australia Technical Program Co-Chairs O. Postolache, ETA, Portugal S. Kharkivskiy, WSU, Aus A. Sanagavarapu, UTS, Aus K. P. Jayasundera, Massey University, New Zealand

Regional Programme Chairs America: G. Chattopadhyay, JPL, USA Eupore: I. Matias, PUN, Spain Middle-East: C. Gooneratne, KAUST Asia: R. Huang, NCKU, Taiwan UK: A. Mason, LJMU, UK Australia: D. Preethichandra, CQU, Australia

Publicity Chair K. Kuo, IIIR, Taiwan

Proceedings/Programme Booklet Lisa Lightband, Massey University, New Zealand

Finance Chair Kerry Morris, Macquarie University, Australia

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International Programme Committee Mohd Syaifudin Abdul Rahman, Malaysian Agricultural Research & Development Institute (MARDI), Malaysia Badr Abdullah, Liverpool John Moores University, United Kingdom Nasrin Afsarimanesh, Macquarie University, Australia Ibrahim Al-Bahadly, Massey University, New Zealand Md Eshrat Alahi, Macquarie University, Australia Mahmoud Alahmad, UAEU, United Arab Emirates (UAE) Khalid Arif, Massey University, New Zealand Francisco Arregui, Universidad Publica de Navarra, Spain Norhana Arsad, Universiti Kebangsaan Malaysia, Malaysia Ranjit Barai, Nanyang Technological University, Singapore S. Bhadra, McGill Uni, Canada Aniruddha Bhattacharjya, Guru Nanak Institute of Technology (GNIT), India Goutam Chakraborty, Iwate Prefectural University, Japan David Chavez, Pontificia Universidad Catolica del Peru, Peru Bryan Chin, Auburn University, USA Komkrit Chomsuwan, King Mongkut's University of Technology Thonburi, Thailand Cheng-Hsin Chuang, Southern Taiwan University of Science and Technology, Taiwan Eduardo Cordova-Lopez, Liverpool John Moores University, United Kingdom Jesus Corres, Public University of Navarra, Spain Tiziana D'Orazio, National Research Council, Italy Matthew D'Souza, The University of Queensland, Australia Saakshi Dhanekar, Indian Institute of Technology (IIT) Delhi, India Robin Dykstra, Victoria University of Wellington, New Zealand Bernd Eichberger, Graz University of Technology, Austria Mala Ekanayake, Central Queensland University, Australia Maria Fazio, University of Messina, Italy Cristian Fosalau, Technical University of Iasi, Romania Boby George, Indian Institute of Technology Madras, India Hemant Ghayvat, Massey University, New Zealand Avik Ghose, Tata Consultancy Services, India Boris Ginzburg, NRC Soreq, Israel Chinthaka Gooneratne, King Abdullah University of Science and Technology, Saudi Arabia Roman Gruden, DHBW Stuttgart, Germany Maki Habib, The American University in Cairo, Egypt Michael Haji-Sheikh, Northern Illinois University, USA Qingbo He, University of Science and Technology of China, P.R. China Yueh-Min Huang, National Cheng Kung University,Taiwan Chi-Hung Hwang, Instrument Technology Research Center, Taiwan

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Ikuo Ihara, Nagaoka University of Technology, Japan Satoshi Ikezawa, Waseda University, Japan Tarikul Islam, Jamia Millia Islamia University, India Krishanthi Jayasundera, Massey University, New Zealand Joe-Air Jiang, National Taiwan University, Taiwan Keith Jones, Callaghan Innovation, New Zealand Olfa Kanoun, Chemnitz University of Technology, Germany Yau Hee Kho, Nazarbayev University, Kazakhstan Nemai Karmakar, Monash University, Australia Olga Korostynska, Liverpool John Moores University, United Kingdom Jagadeesh Kumar V, Indian Institute of Technology Madras, India Heri Kusuma, Institut Teknologi Sepuluh Nopember, Indonesia Aime' Lay-Ekuakille, University of Salento, Italy Hongkun Li, Dalian University of Technology, P.R. China Jinxing Liang, Southeast University, P.R. China Xixiang Liu, Southeast University, P.R. China Alayn Loayssa, Universidad Publica de Navarra, Spain Paulo Lopez-Meyer, Intel Corporation, Mexico Iliana Marinova, Technical University of Sofia, Bulgaria Alex Mason, Liverpool John Moores University, United Kingdom Ignacio Matias, Universidad Pública de Navarra, Spain Mohd Amri Md Yunus, Faculty of Electrical Engineering, Malaysia Mahmoud Meribout, Petroleum Institute, United Arab Emirates (UAE) Tanveer Mir, University of Toyama, Japan Lingfei Mo, Southeast University, P.R. China Tayeb Mohammed-Brahim, University Rennes 1, France Kazuo Mori, Mie University, Japan Subhas Mukhopadhyay, Massey University, New Zealand Mustapha Nadi, Université de Lorraine-CNRS, France Anindya Nag, Macquarie University, Australia Thomas Newe, University of Limerick, Ireland Hirofumi Ohtsuka, NIT, Kumamoto College, Japan Michael Ortner, Carinthian Tech Research AG, Austria Nitish Patel, University of Auckland, New Zealand Jose Pereira, ESTSetúbal, Portugal Ian Platt, Lincoln Agritech Ltd, New Zealand Octavian Postolache, Instituto de Telecomunicações, Lisboa/IT, Portugal D M Gamage Preethichandra, Central Queensland University, Australia Rajinikumar Ramalingam, Institute of Technical Physics, Germany Candid Reig, University of Valencia, Spain Daniel Riordan, Institute of Technology, Tralee, Ireland Joyanta Roy, MCKV Institute of Engineering, India

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Shubhajit Roy Chowdhury, School of Computing and Electrical Engineering, IIT Mandi, India Ricardo Sanchez, Universidad Nacional Autonoma de Mexico, Mexico E. Sazonov, UA, USA Veronica Sberveglieri, CNR-INO Sensor Lab, Italy Norbert Schwesinger, Technische Universität München, Germany Han-Cheng Seat, université de Toulouse, France Mohamed Serry, The American University in Cairo, Egypt Rajan Shankaran, MQ, Aus Pavel Shuk, Emerson, USA Mateusz Smietana, Warsaw University of Technology, Poland Janusz Smulko, Gdansk University of Technology, Poland Aiguo Song, Southeast University, P.R. China Rakesh Srivastava, Indian Institute of Technology Banaras Hindu University, India Dan Mihai Stefanescu, Romanian Measurement Society, Romania Qingquan Sun, The University of Alabama, USA Nagender Suryadevara, Geethanjali College of Engineering and Technology, India Akshya Swain, University of Auckland, New Zealand K. Tashiro, Shinshu University, Japan Om Thakur, NSIT, Delhi University, India Guiyun Tian, Newcastle University, United Kingdom Wei-Chen Tu, Chung Yuan Christian University, Taiwan Ioan Tuleasca, The Open Polytechnic in New Zealand, New Zealand Ramanarayanan Viswanathan, University of Mississippi, USA Huaqing Wang, Beijing University of Chemical Technology, P.R. China Peng Wang, Case Western Reserve University, USA Shibin Wang, The State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, P.R. China Daniel Watzenig, Graz University of Technology, Austria Wei Wei, Xi'an University of Technology, P.R. China Ruqiang Yan, Southeast University, P.R. China Bo-Ru Yang, Sun Yat-sen University, P.R. China Min Yao, Tsinghua University, P.R. China Mehmet Rasit Yuce, Monash University, Australia Hong Zeng, Southeast University, P.R. China Liye Zhao, Southeas t University, P.R. China Zhongkui Zhu, Soochow University, P.R. China Arcady Zhukov, Basque Country University, UPV/EHU, Spain

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Keynote Speaker

Bio-sensing in liquid medium with resonant mode

cantilevers

Professor Dr Enakshi Bhattacharya Abstract

The application of resonant cantilevers as biological sensors is well established and these resonators of micron/submicron dimensions have been demonstrated to deliver sub-femtogram mass sensitivity in the detection of cells, DNA, viruses, and other biomolecules in air or vacuum environment. However, many biological processes occur in liquid ambience and the operation of the same cantilevers in aqueous environment poses a problem due to viscous damping suppressing the cantilevers quality factor (Q) and reducing the sensitivity. Another problem with bio-sensing in aqueous environment relates to the repeatability and reliability in results obtained. The minimum limit of detection depends on Q and the mass of the cantilever sensor and, as the signal to noise ratio in liquid medium is low, the dependence of this limit on the external factors increases. In dynamic mode operation, phase locked loop (PLL) tracking is often employed to provide real-time measurements with the cantilever. Stability during signal tracking in liquid environment is important to obtain reliable information on the molecular interaction occurring on bio-functionalized cantilever surface.

We have followed a three pronged approach towards achieving better sensitivity and reliability for cantilever based sensors in liquid ambience. Firstly, we start with improving the measurement and the data analysis techniques on the silicon and polysilicon cantilevers. For measurements, we have used the frequency sweep (FS) method with a Laser Doppler Vibrometer, and FS and the PLL techniques with the Cantisens unit. Two data analysis protocols have been explored for improving the error margins. Secondly, we have investigated various functionalisation (immobilisation) techniques for maximum attachment of the bioanalyte to the cantilever beam surface. Thirdly, we have used smaller cantilevers and higher resonant modes to reduce the effect of damping and improve the mass sensitivity. Finally, we have used these techniques for investigating a few different systems like: antibody/antigen; live/dead e-coli; triglycerides; and standard biomarkers for TB

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and cholera toxin. Author’s Short Biography

Enakshi Bhattacharya completed her MSc (Physics) from the Indian Institute of Technology Bombay in 1980, PhD from Tata Institute of Fundamental Research Mumbai in 1985 and did post-doctoral work at the National Renewable Energy Laboratory (then SERI), USA from 1986-88 where she worked on the light induced effect in amorphous silicon solar cells. She was a faculty member in the Department of Physics, IIT Kanpur during 1988-91. Since 1991, she has been on the faculty of the Department of Electrical

Engineering at IIT Madras. She was on sabbatical from 1999 to 2000 at the Micromachined Products Division of Analog Devices, USA. She is interested in Microelectronics and MEMS technology and her current research areas are in MEMS/NEMS, BioMEMS and Biosensors, with over 150 papers in journals and conferences. She has successfully handled several sponsored projects and is the Principal Investigator for the Centre for NEMS and Nanophotonics, funded by the Ministry of Electronics and Information Technology (MeitY), Government of India. Some noteworthy works are measurement of stiction force, a Knudesn force based pressure sensor, a miniaturised silicon based biosensor with embedded electrodes. In collaboration with the department of biotechnology, the last device was used for triglyceride detection at clinical levels. The miniaturisation technology has been transferred to a start-up. Ongoing work includes detection of pathogens in liquids using cantilevers and using in-house fabricated silicon nanoporous membranes for biomolecular separation. www.ee.iitm.ac.in/~enakshi Contact Information Professor Enakshi Bhattacharya Department of Electrical Engineering and Centre for NEMS and Nanophotonics Indian Institute of Technology Madras Chennai 600036 Email: enakshi@ee.iitm.ac.in

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Keynote Speaker

Utilizing Surface Acoustic Waves and Nano-scale Phenomena for Sensing from Real Matrices

Professor Dr Venkat R. Bhethanabotla Abstract

Sensing from real fluids such as food matrices, body fluids like blood and urine, and real samples of water requires substantial sample preparation to avoid interference with sensor signals. For example, in biological sensors for clinical and food safety applications, non-specific binding is the major cause for these problems, which is difficult to manage with chemical methods. Sensing from real fluids adds to the complexity of point of use sensor systems by requiring many sample preparation steps. Suitably designed surface acoustic wave devices will be presented to eliminate the sample preparation step to achieve point of use sensor configurations in this talk. In addition, these designs allow faster response times by improving fluid mixing, and kinetics of interactions of the analytes with surface recognition elements. Fluid-solid interaction finite element models are constructed for these Rayleigh-SAW interactions with the fluid layers to study non-specific binding removal and mixing in these sensors to achieve suitable designs. One result of this effort is the realization of a compact SAW sensor, in which Rayleigh and Love waves are propagated in orthogonal directions to achieve mixing, non-specific binding removal and sensing in the same device. Such a device is realized in ST quartz and its applications will be presented. In application, these SAW sensors are combined with suitable nano-scale phenomena in sensing materials and their interaction with analytes to improve sensor performance. In one application, interaction of hydrogen with a palladium film is replaced with interaction with palladium nanoparticles loaded on flexible single-walled carbon nanotube surfaces. This allows for a robust hydrogen sensor using acoustic wave devices. In a second application, enhancement of luminescence by silver nanocubes is leveraged to construct an immunofluorosensor which is orders of magnitude more sensitive than without this plasmonic enhancement. Combined with a Rayleigh wave SAW device, a sensitive, selective and fast-responding point of use immunofluorosensor is realized. In a third application, gold nanoprobes are

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combined with a Love wave biosensor to achieve detection in the clinically-relevant pg/ml level. Additional electronic, microfluidic and other design elements necessary to achieve point of use sensor systems using these developments will also be presented. Modeling efforts at multiple scales are utilized throughout this sensor and sensing material development effort, which will be presented at relevant points of this talk.

Author’s Short Biography

Venkat Bhethanabotla obtained his Ph.D. in Chemical Engineering from Penn State in Pennsylvania, USA. He is a professor in the Department of Chemical & Biomolecular Engineering at University of South Florida and Director of the Materials Science and Engineering Program. He has served as Chair of the ChBME Department (2009-2015). Venkat is an

elected Fellow of the AIChE, AAAS, and AIMBE. He serves as an associate editor of the IEEE Sensors Journal, and has served as the General Chair for the IEEE SENSORS 2016 conference. His current research is in the areas of chemical and biological sensors, plasmonics and computational catalysis. He has published over 120 peer-reviewed articles, book chapters, and books on these topics, has 7 issued patents (one licensed) and has received over 60 grants in his career so far, mostly from federal agencies such as NSF, NASA, DTRA, DOE, and some industrial sources.

Contact Information Professor Venkat R. Bhethanabotla Professor, Department of Chemical & Biomolecular Engineering Director, Materials Science and Engineering Program College of Engineering University of South Florida Tampa, Florida, 33620-5350, USA Email: bhethana@usf.edu; Phone: 813.974.3041

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Invited Speaker

The Utility of bone biomarkers

Professor Dr Marlena Kruger

Abstract

Markers can predict imbalance between bone formation and resorption, and therefore should be able to predict the rate of bone loss. Markers reflect the whole body rates of bone resorption and formation and are likely to reflect changes in the number of bone remodelling sites. They may therefore provide a representative index of the overall skeletal bone loss than would be obtained by measuring the rates of change in bone mineral density at specific skeletal sites containing different ratios of cancellous to cortical component with different metabolic rates. Studies on the effect of ovariectomy have shown that artificial menopause results in an increase in bone remodelling. Markers of bone resorption increase by 50-150% and is followed by markers of formation that change up to 100% as well. During the first year of ovariectomy the markers indicate an imbalance in remodelling, and resorption is high. This imbalance remains in late menopausal women as well. With advancing age the negative correlation between bone mineral density and turnover becomes stronger. Several studies have investigated the relationships between markers of turnover and rate of bone loss, but these are limited by precision errors on repeated measurement of markers, repeated measurements of bone density in an individual and different rates of bone loss between sites in the skeleton. Current evidence indicates that in postmenopausal women biochemical markers of bone turnover are associated with bone loss measured at the forearm, calcaneus and hip, with a progressively greater risk of rapid bone loss with increasing levels of markers. Current data indicate that markers can predict the rate of bone loss at the spine and hip over a three year period in an individual with sufficient accuracy to be used in clinical practice, and levels of bone markers are related to risk of fracture. In this presentation the utility of currently available bone biomarkers will be discussed as well as progress in identifying new markers. Whereas in the application of laser heating, our experiments showed that the MNP DC magnetization temperature-measurement system can detect a 14.4 ns laser pulse at least.

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Author’s Short Biography

Prof. Kruger’s research portfolio shows long term commitment to, and excellence in research and development at Massey University, the acquisition of significant research funding, stable employment for support staff and acquiring of state of the art equipment. She is an internationally recognised researcher with strength in bone health research. This is supported by several

invitations to provide plenary lectures or be invited speaker at conferences, well established international collaborations. Her strong research portfolio has been recognised at a national level with assignment of PBRF A score in 2006 and 2012 PBRF rounds. Her international profile and achievements in research has also been acknowledged by Massey University by awarding me the 2016 Individual Research Medal for outstanding research achievements. She has been Director of Research for Institute of Food, Nutrition and Human Health (2008-2013), Director of Research for the College of Health (2013-2016) and Chair of the Doctoral Research Committee (2015). She is an extraordinary professor in Human Nutrition at the University of Pretoria, South Africa.

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Invited Speaker

Diagnostics Using Infrared Spectroscopy

Professor Dr A. G. Unil Perera Abstract

Fourier Transform Infrared spectroscopy is used as a diagnostic tool in biological sciences by characterizing the samples with infrared light-matter interaction. The so called fingerprint region for biological material is in the window 1800 – 1000 cm-1. Blood serum, for example, can be characterized to obtain the absorbance levels of IR light corresponding to the molecular bond vibrations of the serum components. This absorbance curve can then be mapped by using Gaussian oscillators which will correspond to the absorbance of the components of serum. The positions of the oscillators are obtained by performing a second derivative operation on the absorbance curve. This mapping technique can be performed on the absorbance curve of any biological material which will provide information on how the sample changes with respect to its own previous profile or another control. Similar technique will be discussed where spectral signatures so identified, can screen for Colitis which is an Inflammatory Bowel Disease (IBD). Two mice models of Colitis namely, chronic genetically induced (Interleukin 10 knockout) and acute chemically induced (Dextran Sodium Sulphate-induced) models are employed. Arthritis (Collagen Antibody Induced Arthritis) and metabolic syndrome (Toll like receptor 5 knockout) models are also tested as controls. The markers identified as mannose and alpha helix to beta sheet ratio, uniquely screens and distinguishes the colitic from the non-colitic samples and the controls. This potential technology can be further developed into a personalized diagnostic tool in which patient-to-patient differences in molecular signatures would allow the assessment of disease status and personalized drug management. We can anticipate that this technology could be integrated in a portable device, like the current glucometer, that each patient would wear as a platform to monitor multiple health parameters at the point-of-care, facilitating the creation of bedside technologies for diagnostics and treatment monitoring for various other medical conditions such as arthritis, viral or bacterial infections, allergies, cancer etc other than IBD.

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Author’s Short Biography Dr. A. G. Unil Perera is a Regents’ Professor at the Department of Physics and Astronomy, Georgia State University, Atlanta. Obtained his B.S. degree (Physics Special, 1st Class Honors) from the University of Colombo, Sri Lanka and M.S. and Ph.D. from the University of Pittsburgh. He has published 11 book chapters and more than 165 technical articles and 10 patents (or applications) to his credit. He has participated in more than 20 review panels and has presented more than 50 invited talks in

international conferences including several Key note addresses. He is a life Fellow of the American Physical Society and the Society of Photo-Instrumentation Engineers, and a Fellow of the Institute of Electrical and Electronics Engineers and also serves as a member of the editorial board for the IEEE journal of electron Device Society. Dr. Perera has established a research program that focuses on developing detectors responding from UV to FIR range of the electromagnetic spectrum. These include bias selectable, multiband polarization sensitive patented detectors operating up to room temperature. The group carries out basic material properties studies including device design, performance modeling, device characterizations and analysis utilizing III-V and II-VI materials. The detector configurations include quantum dot and quantum well infrared photodetectors (QDIPs and QWIPs), heterojunction internal photoemission infrared photodetectors (HEIWIP), type-II superlattice photodetectors (T2SLs) etc. Recently, he demonstrated a tunable hot carrier photodetector, overcoming the fundamental detection limit imposed by the band-gap of a material (Nature Photonics 8, 412–418, 2014). Dr. Perera has also used Infrared spectroscopy as a characterization tool in biology and neuroscience. Dr. Perera has initiated various outreach programs for K-12 participants, including “Advanced Physics Camps”, high school physics teacher enhancements through summer RET programs involving several elementary, middle and high schools in Georgia. Among the many awards he has received, some notable ones are the Alumni Distinguished Professor Award (2010), GSU, Outstanding Faculty Achievement Award (1999) and Lifetime Achievement Award (2012), Sri Lanka Foundation, CA, USA.

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Invited Speaker

Recent Trends in Nature Inspired Optimization Techniques

and their Applications in Sensor Technology

Professor Kusum Deep Abstract Optimization is the art of selecting "the best" alternative among a given set of options. Optimization problems arise in almost all fields of science, engineering, finance and Industry – in fact in all walks of human activity in which the problem may be mathematically modelled. The traditional optimization techniques are unable to tackle the complexities of real world optimization problems. As a substitute, recently nature inspired optimization techniques (NIOT) are being developed. NIOT are gaining popularity and are considered efficient due to their ability to find a reasonably acceptable solution within a fair amount of time. Some of the methods in this category are: Genetic Algorithms and Particle Swarm Optimization, etc. This talk will focus on the state-of-the-art NIOT and will provide an insight in many important non-linear optimization in sensor technology.

Author’s Short Biography

Prof. (Dr.) Kusum Deep, is a full Professor and Co-ordinator of Operations Research and Statistics Group, Department of Mathematics, Indian Institute of Technology Roorkee, India. Being a Gold Medalist in M.Phil, she earned her PhD in 1988 from IIT Roorkee and Post Doctorate from Loughborough

University, UK. With numerous awards, she has supervised 16 PhDs and has 95 research publications in refereed International Journals and 60 research papers in Conferences. Kusum is on the editorial board of many Journals and is the Executive Editor of International Journal of Swarm Intelligence, Inderscience. She is the Founder President of Soft Computing Research Society, India. She is a Senior Member of Operations Research Society of India, IEEE, Computer Society of India, Indian Mathematical Society and Indian Society of Industrial Mathematics. She is on the Expert Panel of the Department of Science and Technology, Govt. of India. She has co-authored a book entitled "Optimization Techniques". Her research areas is nature inspired optimization

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techniques and their applications to solve real life problems arising in engineering, science and finance.

Contact Information Prof. (Dr.) Kusum Deep Co-ordinator, Operations Research and Statistics Group Professor, Department of Mathematics Indian Institute of Technology Roorkee Roorkee – 247667 Uttarakhand, India Ph: +91 1332-285339, +91 9837164078 Emails: kusumfma@iitr.ac.in, kusumdeep@gmail.com https://www.iitr.ac.in/departments/MA/pages/People+Faculty+Deep_Kusum.html Google Scholar: http://scholar.google.com/citations?user=ByQN_c0AAAAJ General Chair: SocProS 2017 (www.socpros17.scrs.in) General Chair: RTORS-2017 (www.rtors.com)

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Invited Speaker

Electrical impedance sensing for measuring the evolution of

microstructure in sea ice.

Dr Gideon Gouws Abstract Sea ice forms in the high latitudes during the winter months when the sea temperature is cooled below its freezing point. The ice that forms is a complex material, consisting of an inhomogeneous mixture of pure ice, brine and air inclusions as well as solid salts. This microstructure is a strong function of temperature and a gradual seasonal evolution of structure thus takes place. Ultimately it is this microstructure that determines the macroscopic properties of the ice, so that a measurement of the microstructure will provide important information on the large scale properties. Electrical sensing methods provide an important technique for non-destructive, in-situ monitoring of the ice microstructure. Electrode strings can be allowed to freeze into the ice and electrode pairs can then be utilised for the measurement of magnitude and phase in an impedance analysis of the thermal and temporal evolution of the structure. From these measurements the complex permittivity of the ice can be extracted which, together with temperature and salinity data can provide microstructural information. This paper will present an overview of our results of impedance measurements obtained on sea ice both artificially grown in a laboratory environment as well as natural sea ice in the Arctic and Antarctica. Dedicated field instrumentation was developed to provide measurement over a frequency range of

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Author’s Short Biography

Gideon Gouws received a PhD degree in Physics from the University of Port Elizabeth in South Africa, after which he joined the CSIR and was involved in the development of thin film II-VI semiconductors by organometallic vapour phase epitaxy for optical detectors. He also spent several years in industry (Rakon

Ltd, New Zealand) where he developed commercial quartz crystal resonators. He is currently on the academic staff in Engineering and Computer Science at Victoria University of Wellington, New Zealand. His research interest is in materials and sensor instrumentation, with a focus on impedance based sensing for environmental and industrial applications and the fabrication of microstructured materials for sensing and energy transfer applications.

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Invited Speaker

Magnetic Composite Sensors

Dr. Jürgen Kosel

Abstract The current trend toward ubiquitous monitoring spurs the development of miniaturized, flexible, high-performance devices. Concepts like smart living, advanced robots, smart surgical instruments or wearable devices require small, unobtrusive, low-cost sensors that operate with low power consumption and can conform to curved or changing surfaces. As an example, tactile sensors play a central role in artificial skins, which can mimic the sense of touch in humans. This complex task requires sensors with specific properties including high sensitivity, durability, power consumption, scalability, biocompatibility, flexibility or stretchability. Material development plays a crucial role in the search for new sensor solutions. Magnetic composites that combine the flexibility, biocompatibility and chemical resistance of polymers with magnetic properties by incorporating nano or micro particles into them are specifically attractive because of their contact-free operation. In this talk, I will present magnetic composite devices that utilize polymeric substrates combined with either magnetic nanowires or micro beads. The properties of these sensors can easily be tuned by the magnetic filler concentration, the geometric parameters of the composite materials or by magnetic field induced anisotropy achieved during polymer curing. Bio-inspired artificial cilia built with magnetic nanocomposite on top of magnetic sensors provide a sensor signal upon cilia bending and can be realized on flexible or rigid substrates. These sensors feature a high performance in terms of sensitivity, power consumption and versatility, acting as force, flow, or tactile sensor in air or water. Forces of less than 100 μN can be detected with a power consumption below 100 nW. The magnetic composite cilia on top of micro coils can also be used for energy harvesting of low frequency vibrations, due to the voltage induced in the coils upon cilia vibration. Composite permanent magnets are suitable for marine animal monitoring, where small weights and surface conformity are relevant. The performance of these magnets in the harsh marine environment is shown and an efficient protective coating for the composite magnets is presented. By exploiting the remote heating capability of magnetic nanocomposites, drug delivery The devices covered in this talk will show the

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versatility of magnetic composite materials for sensor applications as well as the simple fabrication of the devices that provides flexibility with respect to optimizing geometrical parameters. Author’s Short Biography

Dr. Jürgen Kosel is Associate Professor of Electrical Engineering at KAUST since 2015, where he is with the Computer, Electrical and Mathematical Sciences and Engineering Division. He joined KAUST as Assistant Professor

in 2009, after he worked in the automotive industry as project manager. His research interests are in the field of micro- and nano devices with a focus on magnetic transducers. He is PI of the Sensing, Magnetism and Microsystems research group at KAUST. Dr. Kosel received his Dipl. Ing. (M.Sc.) and doctor of science (PhD) degrees in electrical engineering from the Vienna University of Technology, Austria, in 2002 and 2006, respectively.

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Invited Speaker

Every drop counts- Industry 4.0 (Smart Water Solution of Future)

Prof. Dr. Joyanta Kumar Roy Abstract A city cannot be called truly smart if it does not have smart water generation and distribution system. There are many essential layers to the smart water infrastructure, which include smart sensor and sensing system, remote automation and surveillance, data analytics, cloud computing, Internet of Things and cyber security. This smart water infrastructure is part of new generation Industry 4.0. The Industry 4.0 is the current trends in technology, which uses not only latest machineries but also cyber physical systems. It operates in building blocks of modular infrastructure with interconnected cyber-physical layers to communicate; interact within machineries and human over Internet of Things. This technology optimized production cost of potable drinking water, maintain water quality in treatment process, optimized energy consumption, minimize non-revenue water, detects and measures leakage in distribution, monitor and control water demand in real time, regulate distribution according to demand, increase life of distribution and pumping machineries as well communicate with all consumers to maintain the harmony of demand and supply through Internet of Things to maximize financial revenue. This technical discussion covers technology behind Smart water solution from treatment to the tap with some case studies. The readiness of the technology, benefits and challenges of implementation, the scope of future research and development are also to be discussed in the technical discussion. Keywords: Smart city; Smart water; Water quality surveillance; SCADA; Internet of Things, Cyber-Physical systems;

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Author’s Short Biography Prof. Dr. Joyanta Kumar Roy, PhD has been working in Electronics and Automation Engineer for last 33 years as Company Director, Consulting Engineering, Developer, Researcher and Educationist. Presently, he is associated with University of Calcutta as Visiting Professor, Company Director with System Advance Technologies and Freelance Consultant

with number of Industries to give design support towards Smart Technology in water sector. He is Senior Member of IEEE and IET, Fellow Member of IETE and IWWA, regular reviewer of IEEE and Springer Journals. He is associate editor of S2IS journal, published significant number of scientific and technical publication in the form of book, book chapter, design document, research paper etc. His research interest includes development of smart measurement and control system, multifunction sensors, IoT based m-health, and technology assisted living, Smart home and city.

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Invited Speaker

Extension of Thomson and Lampard Theorem for Sensing

Applications

Dr. Tarikul Islam Abstract Sensors are used to measure different physical, chemical and biological parameters. Today, sensors are playing very important role in the modernization of the systems used for different applications. Gradually, sensors are also playing important role for health monitoring of human, key electrical equipments, and different structures. However, this development is mostly due to the miniaturization of sensors and their important features. Nano-technology has played important role in it. Nano-technology based thin film sensors are in demand due to high order of static and dynamic characteristics. The characteristics of the sensors are tunable by modifying or functionalization of the nanostructures. However, conversion of non-physical quantities into measurable electrical form, for accurate and precise measurement, demands highly precise relationship between output and physical quantity. Many times, it is not possible to obtain highly precise relationship for the sensors for measuring parameters. Also for the nanostructure based sensors, the degradation of the nanostructure causes drift in sensor output and addressing drift due to aging is a challenge nowadays for their practical applications. Characterization techniques for sensing applications can be categorized as destructive and non destructive. Some minimally destructive techniques can also be utilized. Nondestructive techniques are preferable for durability, reliability and accuracy of the sensors. Because of contactless or minimal contact, they do not react with sensing parameters. Common nondestructive techniques are ultrasonic, optical, microwave etc. Different physical, chemical or biological parameters can be measured by these methods. Thompson and Lampard theorem, which gave birth to cylindrical cross capacitors, which are considered to be the primary standard of capacitance, was extended by some authors to measure the conductivities of materials, with high degree of accuracy and precision. This extension was found suitable for several very nice applications in the measurement of humidity, micro-droplet,

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water, milk quality analysis and other parameters. Thin film technology is providing a very sensitive relationship between the parameters and output impedance. Extension of Thompson and Lampard theorem has provided excellent shapes of electrodes and material for the sensors which may help in the precise and accurate measurement of parameters. In case of thin film humidity sensor, proper electrode system is required to have appropriate relationship between the changes in resistance, etc. with change in humidity. The sensor was designed and simulated using ANSYS Maxwel 3D software, and fabricated for the experimental verification of the proposed theorem. Different electrode arrangements were used for this purpose, which were needed for improvement. Experiments were conducted to measure humidity, micro droplet, water quality and milk quality. The sensor is easy to fabricate, highly reproducible, sensitive and selective. Noncontact/minimal contact operation of sensor gives almost drift free output. Author’s Short Biography

Dr. Tarikul Islam received the Ph.D degree from Jadavpur University, Kolkata, in 2007. He is a Professor in the Electrical Engineering Department, Jamia Millia Islamia (Central University, NAAC Grade A). He has published more than 130 papers in peer

reviewed journals and conferences. He filed three patents and published three book chapters published by Springer International Publishing, Switzerland and American Scientific Publishers. He is an associate editor of IEEE Sensors journal. He is program committee member of various conferences such as ICST, INDICON2015, SENSORNET2017, and IEEE Instruments and Measurement Society. He organized one MHRD GIAN course. He received research grant of more than 230,000 $USA from DST, DAE, MHRD and DRDO. His research interests include capacitive sensors, surface acoustic wave (SAW) and conductive sensors. He also works on electronic circuits for the interfacing and signal conditioning of the sensor signal.

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Invited Speaker

Smart Sensors and Tailored Environments for Neuro-Motor

Rehabilitation Monitoring

Prof. Dr. Octavian Adrian Postolache

Abstract The convergence of healthcare, instrumentation and measurement technologies will transform healthcare as we know it, improving quality of healthcare services, reducing inefficiencies, curbing costs and improving quality of life. Smart sensors, wearable devices, Internet of Things (IoT) platforms, and big data offer new and exciting possibilities for more robust, reliable, flexible and low-cost healthcare systems and patient care strategies. These may provide value-added information and functionalities for patients, particularly for those with neuro-motor impairments. It has great importance in developed countries in the context of population ageing. In this talk the focus will be on: hardware and software infrastructure for neuro-motor rehabilitation; signal processing, distributed instrumentation and communication standards; motor rehabilitation based on virtual reality and serious game; use of cloud computing for healthcare monitoring; use of mobile devices for the storage, update and communication of the information related to patients’ care and activities recognition; wearable sensor network integration with unobtrusive sensing technologies; Internet of Things technologies; standards in pervasive healthcare; data collection, data processing, data correlation, data presentation that may assist healthcare professionals in objective, accurate assessment of patients’ functioning, disability and health; in home patients health and activities monitoring; systems that support personalization of healthcare; systems that promote independent living and empower individuals and their families for self-care and healthcare management. Technologies for unobtrusive measurement of patient posture and balance, patient’s muscles activation, movements’ characterization during neuro-motor rehabilitation will be presented and discussed during the talk. As part of these interactive environments, 3D image sensors for natural user interaction with rehabilitation scenarios and remote sensing of user movement, represented by Leap Motion Controller and Kinect, as well as thermographic camera for muscle activity evaluation will be presented. Instrumented daily used equipment for rehabilitation, such as smart walkers and crutches, force platform and wearable motor activity monitors

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based on smart sensors embedded in clothes and accessories for muscular activity monitoring by electromyography (EMG), force and acceleration measurement capabilities will be presented and discussed. Smart sensing technologies that contribute to tailored environments, such as piezo-resistive force sensors, e-textile EMG, microwave Doppler Radar, MEMS inertial devices for motion measurement and optical fiber sensors will be presented in the context of IoT technologies, where RFID is used for smart object identification and localization in the augmented reality scenarios for therapy. Challenges related to simple and secure connectivity, signal processing, data storage, risk on data loss, power consumption, data representation, data analysis including the development of specific metrics that can be used to evaluate the progress of the patients during the rehabilitation process will be discussed. Author’s Short Biography

Prof. Dr. Octavian Adrian Postolache (M’99, SM’2006) graduated in Electrical Engineering at the Gh. Asachi Technical University of Iasi, Romania, in 1992 and he received the PhD degree in 1999 from the same university, and university habilitation in 2016 from Instituto Superior Tecnico, Universidade

de Lisboa, Portugal. In the period 1992-2000 he served as assistant professor at Technical University of Iasi. In 2000 he became principal researcher of Instituto de Telecomunicações where he is now Senior Researcher. He served as invited professor at EST/IPS Setubal, Portugal between 2001 and 2012 when he joined Instituto Universitario de Lisboa/ ISCTE-IUL Lisbon where he is currently Aux. Professor. His fields of interests are smart sensors for biomedical and environmental applications, pervasive sensing and computing, wireless sensor networks, signal processing with application in biomedical and telecommunications, non-destructive testing and diagnosis based on eddy currents smart sensors, computational intelligence with application in automated measurement systems. He was principal researcher of different projects including EHR-Physio regarding the implementation of Electronic Health Records for Physiotherapy and he is currently principal researcher of TailorPhy project Smart Sensors and Tailored Environments for Physiotheraphy.He served as technical principal researcher in projects such Crack Project related non-destructive testing of conductive materials. He is vice-director of Instituto de Telecomunicações/ISCTE-IUL delegation, director of PhD program Science and Communication Technologies at ISCTE-IUL, and he was leader of several collaboration projects between the Instituto de

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Telecomunicaçoes and the industry such as Home TeleCare project with Portuguese Telecommunication Agency for Innovation (PT Inovação), Integrated Spectrum Monitoring project with National Communication Agency (ANACOM). He is active member of national and international research teams involved in Portuguese and EU and International projects. Dr. Postolache is author and co-author of 9 patents, 10 books, 18 book chapters, 70 papers in international journals with peer review, more than 250 papers in proceedings of international conferences. He is IEEE Senior Member I&M Society, Distinguished Lecturer of IEEE IMS, chair of IEEE I&MSTC-13 Wireless and Telecommunications in Measurements, member of IEEE I&M TC-17, IEEE I&M TC-18, IEEE I&MS TC-25, IEEE EMBS Portugal Chapter and chair of IEEE IMS Portugal Chapter. He is Associate Editor of IEEE Sensors Journal, and IEEE Transaction on Instrumentation and Measurements, he was general chair of IEEE MeMeA 2014, and TPC chair of ICST 2014, Liverpool and ICST 2015 in Aukland. He received IEEE best reviewer and the best associate editor in 2011 and 2013 and other awards related to his research activity in the field of smart sensing.

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ICST 2017 Programme at a glance

Monday, December 4

09:00-09:30 Opening Session 10:00 - 10:45 Keynote Session I

Bio-sensing in liquid medium with resonant mode cantilevers (Prof. Enakshi Bhattacharya)

11:00-12:30 S2A: Biosensors S2B: WSN and IoT I S2C: Sensors for Novel Applications I

13:30-15:00

S3A: Wearable Sensors and Activity Monitoring S3B: Image and Range Sensors S3C: Spectroscopy Techniques

15:30-17:18 S4A: Sensors for Novel Applications II S4B: Mechanical Sensors S4C: Gas Sensors

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Tuesday, December 5

09:00-09:45 Keynote Session II Utilizing Surface Acoustic Waves and Nano-scale Phenomena for Sensing from Real Matrices (Prof. Venkat R. Bhethanabotla)

10:15-12:03 S6A: Special session on Smart Agriculture I S6B: Optical and Fibre Optic Sensors S6C: WSN and IoT II

13:15-14:45 S7A: Magnetic Sensors S7B: Special session on Smart Agriculture II S7C: Ultrasound and Vibration Sensors

15:15-17:15 S8: Invited Session I The Utility of bone biomarkers (Professor Marlena Kruger) Diagnostics Using Infrared Spectroscopy (Prof. Dr. A. G. Unil Perera) Recent Trends in Nature Inspired Optimization Techniques and their Applications in Sensor Technology (Prof. (Dr.) Kusum Deep) Electrical impedance sensing for measuring the evolution of microstructure in sea ice (Dr. Gideon Gouws, Victoria University of Wellington, New Zealand)

Banquet Dinner

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Wednesday, December 6

09:00 - 10:30

S9A: Healthcare Applications II S9B: Structural Health Monitoring S9C: Sensors for Novel Applications III

11:00-12:30 S10A: Special Session: Micro and nano devices for biomedical applications S10B: Sensors for Novel Applications IV S10C: Special session: Sensors and instrumentation for the environment and climate change monitoring

13:30-15:30 S11: Invited Session II Magnetic Composite Sensors (Prof. Jurgen Kosel) Every drop counts- Industry 4.0: Smart Water Solution of Future (Prof. Joyanta Kumar Roy) Extension of Thomson and Lampard Theorem for Sensing Applications (Prof. Tariqul Islam) Smart Sensors and Tailored Environments for Neuro-Motor Rehabilitation Monitoring (Prof. Octavian Postolache)

16:00-16:30 S12: Closing Ceremony and Prize Distribution

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Venue

ICST 2017 will be held at: C5C Macquarie University Balaclava Road North Ryde Sydney, New South Wales 2109 Australia

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Banquet The ICST 2017 Conference Dinner will be held at: Crunch, MUSE Level 3

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Technical Programme

Monday, December 4 09:00 - 09:30 S0: Opening Session

10:00 - 10:45 Keynote Session #1 Chair: Subhas Mukhopadhyay (Macquarie University, Australia)

Bio-sensing in liquid medium with resonant mode cantilevers Prof. Enakshi Bhattacharya

11:00 - 12:30 S2A: Biosensors Chair: Mustapha Nadi (Université de Lorraine-CNRS & Institut Jean Lamour, France)

11:00 High reliability Microfluidic biosensor for single cell impedance cytometry

Julien Claudel (Université de Lorraine-CNRS, France); Mustapha Nadi (Université de Lorraine-CNRS & Institut Jean Lamour, France); Omar Elmazria and Djilali Kourtiche (Université de Lorraine-CNRS, France) This paper presents a microfluidic biosensor for micro particles and cells differentiation using cytometry. It is based on Electrical Bio-impedance Spectroscopy and able to perform cell by cell characterization at high flow rate. Sensing area is centered in platinum coplanar microelectrodes integrated in a 20x10 μm microchannel. Operating in laminar flow conditions, it permits to highly reduce risk of cell aggregation and focused cells and particles during measurement to improve reliability. Simulations by finite element method were performed to determinate fluid velocity profile along the channel and the effect of cell shifting during characterization. Comparison with measurement show that particles were correctly focused during

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measurement with a position shift less than 1μm. Measurement performed on 6μm calibrated beads, demonstrate the possibility to determine precisely the microparticles size with an error less than 2%. Measurements performed with yeast cells, red blood cells compared to calibrated beads validate the possibility to use our sensor to detect very small dimensional changes of cells and particles, the precision being function or their impedance response.

11:18 A Novel Electrochemical Biosensor for Bone Turnover Detection Based on Molecular Imprinting Technology

Nasrin Afsarimanesh, Md Eshrat E Alahi and Subhas Mukhopadhyay (Macquarie University, Australia) This research reports a novel label-free sensing method for the measurement of C-telopeptide of Type-I collagen (CTX-1) in order to monitor bone turnover at an early stage. An interdigital sensor jointly with Electrochemical Impedance Spectroscopy (EIS) was used to study the resistive and capacitive properties of samples. Molecular Imprinted Polymers (MIPs) containing recognition sites for CTX-1 molecules were synthesized. The sensor was coated with the prepared MIPs to increase the sensitivity of the sensor to CTX-1. Different known concentration samples were tested and the sensitivity curve was plotted. The Nyquist fitted Curve and its equivalent Randle's circuit was estimated using a complex non-linear least square method (CNLS). The initial results are promising for further development of an inexpensive and portable device for early detection of bone turnover, so therapy can be started earlier.

11:36 Novel Rapid Detection Method for Circulating Tumour Cells

Alex Mason (Animalia & Norwegian Meat and Poultry Research Institute, Norway) A major cause of cancer-associated mortality is metastasis. During metastasis cancer cells use the circulatory system to migrate and form secondary tumours in distant organs. Cancer cells which enter the peripheral circulation (circulating tumour cells) are of paramount

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research and clinical interest as they can be used as a biomarker of cancer progression and survival. Tumour cells produce more lactic acid than their normal counterparts. This paper reports on novel approach of using low power athermal electromagnetic waves as a sensing mechanism for early cancer detection.

11:54 Regeneratable Surface Acoustic Wave (SAW) Immunosensor for Monitoring of Physiological Information

Koji Toma and Koki Oishi (Tokyo Medical and Dental University, Japan); Naoyuki Yoshimura (Japan Radio Co. Ltd., Japan); Takahiro Arakawa (Tokyo Medical and Dental University, Japan); Hiromi Yatsuda (Japan Radio Co. Ltd., Japan); Kohji Mitsubayashi (Tokyo Medical and Dental University, Japan) A reusable immunosensor that employed surface acoustic wave (SAW) was developed for monitoring of physiological information. The SAW immunosensor was fabricated by modifying a propagation area of the SAW device with a self-assembled monolayer of pH tolerant protein, ORLA85, which allowed repeating of surface regeneration by changing pH, and thereby rapid and repetitive (semi-continuous) measurement of analyte concentration. In experiment, initially a SAW device used for the sensor was characterized using a series of solution with various viscosity, and results showed a good correlation between phase change and solution viscosity from 0.88 to 1.7 mPa∙s. In addition, performance of developed SAW immunosensor was evaluated using mouse IgG and anti-mouse IgG as model capturing molecule and analyte. It revealed that dynamic range of the immunosensor was 0.16-100 μg/ml with a measurement time of 20 minutes, and semi-continuous measurement was possible with a high reproducibility represented by a coefficient of variation of 3.4% for five repetitive measurement. These demonstrated that SAW immunosensor holds a huge potential for application to monitoring of time course of biomolecules which reflect physiological conditions.

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12:12 Performance Dependency of Enzyme Based NanoBiosensors on Fabrication and Enzyme Immobilization Techniques

D M Gamage Preethichandra and Mala Ekanayake (Central Queensland University, Australia) This paper presents a comparison of results from a range of experiments carried out to investigate the performance dependency of polypyrrole based nano-biosensors on fabrication and enzyme immobilization techniques. The methods compared are drop casting, co-entrapment, and electrophoretic enzyme deposition techniques. Templated polypyrrole nanotube array sensors provided high sensitivities and quick response time. The electrochemically developed nano-corrugated polypyrrole sensors with enzyme loaded under high electric field of 1kV/m have displayed extremely high sensitivity of 325mAM-1cm-2

11:00 - 12:30 S2B: WSN and IoT I Chair: Joyanta Kumar Roy (Calcutta University, India)

11:00 A Easy Installation Wireless Sensor System for Remote Mechanical Parts Monitoring

Huang-Chen Lee (National Chung-Cheng University, Taiwan); Cheng-Hsuan Tsai, Chi-Wei Liao, Kun-Chieh Lin and Chi-Feng Li (Precision Machinery Research Development Center, Taiwan); Yung-Lin Wu and Cheng-Yu Shi (National Chung-Cheng University, Taiwan); Yen-Sou Huang (National Kaohsiung Marine University, Taiwan) Newly developed techniques for intelligent sensor systems make it possible to register the mechanical wear-out of parts, such as band saws, ball screws and gearbox reducers, by collecting working signals from them, such as vibrations and preload pressure and temperature changes. To build an accurate wear model, we need to log as many real signals as possible from numerous parts in machine tools. This raises a substantial problem: How can we collect a large number of real signals from the parts installed in many machine tools—which could be located anywhere in the world—and aggregate data to use in

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constructing a wearing model, as well as enabling remote systems analysis and send warnings if the parts are worn? In this study, based on our previous work, we design a special embedded system to realize a cloud-based service that logs mechanical wear-out of parts. We design and implement this system and install it in a factory to evaluate it. The proposed system can be used to collect operating signals regarding mechanical wear-out of parts and can allow manufacturers to track state of wear and send warnings to tool owners before wear-out.

11:18 A modified energy efficient protocol for optimization of dead nodes and energy consumption in wireless sensor networks

Pallavi Yarde and Sumit Srivastava (Manipal University Jaipur, India); Kumkum Garg (Manipal University, India) The role of sensors (nodes) in Wireless Sensor Network (WSN) is to sense, collect the data and process that data, and forward the processed data to the other sensor node or base station. All these processes consumes energy. The level of energy consumption is higher in transmitting stage as compared to sensing, collecting and processing the data. The requirement of transmission power is directly depends on the distance between the sender and receiver nodes. In this paper, a comparative network life time analysis is done in the LEACH and its variant protocols on the basis of energy consumption, residual energy and dead nodes. In this paper TH-LEACH, an energy efficient routing protocol is also proposed. This protocol improves the number of dead nodes and total energy consumption in the network hence, optimizing network lifetime

11:36 A Survey on the Challenges and Opportunities of the Internet of Things (IoT)

Laith Farhan (Manchester Metropolitan University, United Kingdom (Great Britain)) Internet of Things (IoT) is a rapidly growing technology with a wide range of applications in various fields. It has unified a plethora of

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devices and infrastructure under the same umbrella and is considered by many technologies leaders as the Network of the Future (NoF). IoT connects heterogeneous devices that provide sensing, control, actuation, and monitoring activities for smarter environments. Smart IoT devices or objects are characterized with a unique identifier to transfer data over the network without human intervention. IoT is expected to further extend the boundaries of the autonomous world with advanced connectivity of physical entities, systems, services. However, there are some serious obstacles and challenges, which must be resolved before the full potential of IoT is realized. The focus of this study is to discuss the key drivers of change, challenges that may slow the adoption of IoT and the potential of the internet of things technology.

11:54 A Secure Near Field Communication Sensors Interactive LEarning System (S-NILES)

Kam Chiang Wai (USM, Malaysia); Manmeet Mahinderjit Singh (University Sains Malaysia (USM), Malaysia); Huzaifa Marina (Universiti Sains Malaysia (USM), Malaysia) E-learning is known as a learning tool which based on technology to deliver learning material electronically through computer network. The involvement of the students and the lecturers in the existing learning system is not interactive as they use it as a medium to deliver notes and receive notes only. The traditional attendance system which passes the attendance sheet around the class or by calling names is also not productive and time consuming to process the data into attendance statistics. Therefore, an interactive learning system embedded with secure NFC attendance system using NFC enabled smartphone known as Secure NFC Interactive LEarning System (S-NILES) is proposed to record attendances and lecturers can conduct their classes in a more interactive way in school, college or university through the usage of social media and blended learning tools. The proposed solution include a NFC security attacks taxonomy and with some mitigation technique in securing the NFC attendances systems.

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12:12 Towards An Inexpensive Paper Based Flexible Chipless RFID Tag with Increased Data Capacity

Shuvashis Dey (Monash University, Australia); Nemai Karmakar (MONASH University, Australia) This paper exemplifies the design and analysis of an inexpensive, compact high data capacity chipless RFID tag on flexible paper substrate. The size of the overall tag with integrated antennas is similar to that of a credit card. The designed tag uses polarization diversity to provide a bit capacity of up to 30 bits in the short range UWB band of 22-26.5 GHz. A systematic progression on to the incorporation of increased number of bit capacity is depicted hereby. Along with frequency variation, this paper also proposes the scheme for bit detection using phase difference determination in order to increase robustness. An interrogation process of the proposed tag to extract the encoded information is demonstrated here and the resulting analysis establishes the reliability of the designed tag.

11:00-12:30 S2C: Sensors for Novel Applications I

Chair: Boby George (Indian Institute of Technology Madras, India)

11:00 Extra Wide Band 3D Patch Antennae System Design for Remote Vital Sign Doppler Radar Sensor Detection

Van Nguyen (Massey University, New Zealand) A very wide band (from 900 MHz to 12 GHz), enhancing beam capacity patch antennae system is developed in FR4 substrate with a dielectric constant 4.4 and 1.2 mm of height for vital detection purposes. This work focuses on development of 3D-orthogonal patch antennae to detect the respiratory beat at different frequencies. A transceiver antennae is proposed that allows to detect the thorax displacement at four band of frequencies, from L band to X band. The measurement shows that the proposed antennae can operate in extra wide band frequency to detect the vital signs.

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11:18 Operating point dependent lifetime estimation of small sized tungsten incandescent lamps

Henning Jürß, Martin Degner and Hartmut Ewald (University of Rostock, Germany) The lifetime of modulated incandescent lamps depends on modulation parameters like frequency, amplitude and the shape of modulation. On the contrary to well-known methods of DC lifetime estimation, this paper describes the lifetime-estimation of modulated small sized tungsten incandescent lamps. Therefor the approved procedure of material evaporation was compared with a proceeding based only on electrical lamp data. Both methods are specified for DC operation, so the most suitable proceeding was chosen and adapted for lifetime estimation at modulated operating points. To verify this procedure, lamps were tested at different modulated points of operation. A comparison of measured and estimated lifetime shows, that the new proceeding is able to estimate the lifetime sufficiently. This method does not require any knowledge of geometrical lamp parameters like filaments dimensions. It is based on easy to measure time dependent voltage and current data and is an adequate method for lifetime estimation of an incandescent lamp and applicable for different shapes of modulation.

11:36 Development and Application of an Orthodontic Near Infrared Photometer and Thermometer

Graham Michael Brooker, John Sambevski, M Darendeliler and Tony Zhi-wei Tang (University of Sydney, Australia) This paper describes the development and application of a small combined NIR photometer and thermometer that is placed in a newly vacated tooth socket to determine the amount of light that propagates from an intraoral therapeutic LED source, through the gum and jaw bone. Calibration of the device uses the Ames Photonics Oculus photometer. Measured results correlate quite well with the modelled attenuation through the jaw confirming that most attenuation occurs through oxygenated blood in the tooth socket.

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11:54 Successive Approximation Type Digital Converter for Floating-Wiper Inductive Displacement Sensor

Aparna Mohan (Indian Institute of Technology Madras, India); Mohanasankar Sivaprakasam (IIT Madras, India); Jagadeesh Kumar V (Indian Institute of Technology Madras, India) A successive approximation type direct displacement to digital converter suitable for a floating-wiper inductive displacement sensor is proposed here. The topology of a successive approximation type digital converter (SADC) is suitably altered so that a floating-wiper inductive displacement sensor becomes an integral part of the SADC. The successive approximation logic results in the final digital output directly proportional to the displacement of the floating wiper. The hardware and logic are so designed that the final digital output is independent of the interfering inputs. The results obtained from simulation studies establish the efficacy of the proposed technique.

12:12 Calibration of multi-focal planes for zoom-lens unit

Chien-Sheng Liu, Jyun-Cheng Huang and Yu-Cheng Huang (National Chung Cheng University, Taiwan) In this paper, the calibration method of multi-focal planes of a 3D scanning system with zoom-lens unit based on structured light has been discussed. Based on the development of calibration methods for zoom lens characteristics, we design a calibration target for zoom lens calibration. Also, we present a pragmatic calibration process that consists of five procedures.

13:30-15:00 S3A: Wearable Sensors and Activity Monitoring Chair: Enakshi Bhattacharya (IIT Madras, India)

13:30 Real Time Monitoring and Recognition of Eating and Physical Activity with a Wearable Device connected to the Eyeglass

Muhammad Farooq (University of Alabama, USA); Edward Sazonov (The University of Alabama, USA)

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Motion artifacts and speech have been found to degrade the accuracy of wearable device used for detection and recognition of food intake. Thus, there is a need to investigate and develop systems which are impervious to these artifacts. For these systems to be practical in daily living, it is necessary to evaluate their ability to monitor food intake in real-time. This study presents results of real-time testing of a wearable device for real-time classification of multiclass activities. The device consists of a sensor for chewing detection (piezoelectric film sensor) and an accelerometer for physical activity monitoring. The device is in the form of eyeglasses. The strain sensor is attached to the temporalis muscle for chewing detection. Ten participants tested the system while performing activities including eating at rest, talking, walking and eating while walking. For 5-second epochs, ten features were extracted from both sensor signals. A communication protocol was implemented where sensor data were uploaded to a remote server for real-time data processing. Data processing was performed in two steps. In the first step, a multiclass decision tree model was trained offline with data from seven participants to differentiate among eating/chewing and non-eating and two levels of physical activity (sedentary and physically active). In the second step, the trained model was used on remaining three participants to predict the activity label in real-time. Offline classification and real-time online classification achieved average F1-scores of 93.15% and 94.65% respectively. These results indicate that the device can accurately differentiate between epochs of eating and non-eating as well as epochs of two different physical activity levels; in real-time.

13:48 A Wearable Sensor Based Hand Movement Rehabilitation and Evaluation System

Qingquan Sun (California State University, USA) This paper presents a wearable hand rehabilitation system for stroke patients based on digital glove and keyboard games. It is achieved via hand gesture recognition. In this work, the digital glove with bending sensors is good for motion data collection during hand rehabilitation.

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The hand animation model, combined with keyboard games, enables the stroke patient under test to see its fingers movements and exercise process. In feedback stage, the rehabilitation evaluation and recommendation are provided based on the recognition of hand gestures. The experimental results have demonstrated a high accuracy on overt gesture recognition and a reasonable accuracy on complex key press gesture recognition.

14:06 Cluster Analysis-Based Classification of Healthy Female Netball Players Using Wearable Sensors

Arosha SM Namal Senanayake (University of Brunei & Visiting Research Fellow/Gifu University, Brunei Darussalam) Use of wearable wireless sensors (WWS) for classification of healthy female netball players is presented in this study. WWS comprised of wireless surface electromyography (EMG) sensors and 3Dimensional (3D) marker-based motion capture system for acquisition of lower extremity (LE) EMG data and 3DKinematics data respectively. Using WWS data obtained during ball interception (BI) task, subjects are classified based on their similarity-dissimilarity measure through hierarchical cluster analysis (HCA). By investigating existence of homogeneous subgroups (clusters) in LE features extracted, this work aimed to establish for the first time whether netball players exhibit identifiable and distinguishable EMG-3D Kinematic patterns during multiple trials of BI.BI is a key goal-oriented, often spontaneous, and multi-directional jump-landing task frequently performed by every player in a netball game. Thirteen professional subjects were recruited for this study with each asked to perform BI task in six trials in a semi-controlled game-play environment. EMG activity of eight LE muscles and 3D kinematics of the knee and ankle joints were recorded from each subject bilaterally during each BI trial. A total of sixty features (48 EMG and 12 3D-Kinematics) were extracted from the recorded raw data for analysis. Principal component analysis (PCA) was applied for dimensionality reduction of the total feature dataset, retaining only principal components that collectively explained more than 90% data

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variability. HCA was then used in clustering of the reduced datasets. Through inspection of the resulting dendrograms along with cophenetic correlation coefficients, 3 different clusters were confirmed. Based on HCA cluster-solutions, subjects were classified into three different classes (Class-1, Class-2, and Class-3) corresponding with respective clusters. Classification showed that majority (8 of the 13) subjects exhibited and maintained an identifiable LE biomechanical pattern 100% of the time (i.e for all six BI trials), while the remaining 5 subjects exhibited the same more than 66% of the time. Kruskal Walli's test showed that subgroups differed significantly (ρ

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14:42 Intelligent Integrated Wearable Sensing Mechanism for Vertical Jump Height Prediction in Female Netball players

Arosha SM Namal Senanayake (University of Brunei & Visiting Research Fellow/Gifu University, Brunei Darussalam) Vertical jump (VJ) height is a fundamental performance analysis parameter in several sports involving frequent jump-landing maneuvers such as netball. Recent studies have largely examined performance parameters associated with vertical jump height (VJH) in isolation from each other. This study presents an investigation into the relationship between integrated performance parameters (IPP) and VJH during single-leg (VJSL) and double-leg (VJDL) vertical jump tests. IPP considered include; electromyography (EMG) activity of eight lower extremity (LE) muscles, 3D Kinematics of the knee and ankle joints, body height (BH), reach height (RH), and Jump duration (JT). Thirteen healthy national female netball players participated in this study. Each subject performed VJSL and VJDL in three trials while simultaneously and synchronously recording their LE-EMG activity, 3D kinematics, and VJH in each jump trial. LE-EMG activity acquisition was through wirelessly transmitting BioRadio units (CleveMed Inc. USA), while 3D kinematics were obtained through a six-3D marker-based motion capture camera system (Qualisys Inc. Sweden). VJH reading was obtained from a vertec device (Power Systems Inc.USA). A total of 22 IPP were extracted from raw data of both VJSL tests (i.e VJSL Right-Leg (VJSLR), and VJSL Left-Leg (VJSLL)), while 44 IPP were extracted from raw data of VJDL. The relationship between the reduced datasets' parameters and response variable (VJH) was then modeled using Multilayer Perceptron Feed Forward Neural Networks (FFNNs). Significant features were further selected through stepwise regression analysis. Results showed that FFNNs trained with Scaled conjugate gradient back-propagation (SCG) algorithm achieved the best VJH prediction with accuracy of 97.39% for VJSLL, 94.52% for VJSLR, and of 96.74% for VJDL. These results demonstrate that the integration of 3D Kinematics and EMG using wearable sensors interfaced with motion capture system for IPP, has led to more accurate prediction of

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VJH. Thus, this serves as quantifiable feedback to coaches and players for performance enhancement as well as injury prevention in jump landing tasks investigated.

13:30-15:00 S3B: Image and Range Sensors Chair: Dariusz Kacprzak (University of Auckland, New Zealand)

13:30 Accuracy Evaluation of Hand Motion Measurement using 3D Range Image Sensor

Shuya Kawaguchi (Tokyo University of Science, Japan); Hiroshi Takemura (Noda Tus, Japan); Hiroshi Mizoguchi (Tokyo University of Science, Japan); Ryohei Egusa, Yoshiaki Takeda, Etsuji Yamaguchi and Shigenori Inagaki (Kobe University, Japan); Fusako Kusunoki (Tama Art University, Japan); Hideo Funaoi (Soka University, Japan); Masanori Sugimoto (Hokkaido University, Japan) Techniques capable of measuring hand motion are expected to be applied in various situations. Examples are the practice support systems used in activities such as sport and dance, for instance, the system employed in baseball pitching form analysis. This analysis evaluates the state of the throwing form numerically and visually by measuring the velocity and trajectory of the hand. This requires measurement of the hand by a sensor and is accomplished by using a motion capture system as the method for measuring hand motion with high accuracy. However, it is time consuming to prepare the system. Therefore, a 3D range image sensor, which is inexpensive and easy to prepare, is proposed. However, as the actual measurement accuracy of this sensor is unknown, it was evaluated by calculating the error with the measured value of motion capture as the true value. In this research, we calculated the error between the 3D coordinates and velocity to evaluate the error. As a result, the effectiveness of the measurement accuracy of the hand motion by the 3D range image sensor was confirmed. The results suggest that the 3D range image sensor can be used in various situations involving human activity.

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13:48 Novel Application of 3D Range Image Sensor for Estimation of Interests based on Fixation Time of Face Orientation

Mikihiro Tokuoka and Hiroshi Mizoguchi (Tokyo University of Science, Japan); Ryohei Egusa and Shigenori Inagaki (Kobe University, Japan); Fusako Kusunoki (Tama Art University, Japan); Masanori Sugimoto (Hokkaido University, Japan) In this paper, we describe the relationship between the presence or absence of interest and the fixation time of face orientation. There is a conventional method of measuring the fixation time of line-of-sight orientation to prevent accidents due to carelessness. In addition, studies are being performed on the estimation of the relationship between face orientation and line-of-sight orientation. However, even if face and line-of-sight remain, it has not been confirmed whether people are interested. Therefore, we conducted experiments to investigate the relationship between the presence or absence of interest and the fixation time of face orientation. We simultaneously measured the change in interest and face orientation with time as subjects watched two movies. As a result, it was suggested that face orientation remained longer for an object of interest.

14:06 Novel Application of 3D Range Image Sensor for Personal Identification based on Skeletal Information

Natsuki Sako (Tokyo University of Science, Japan); Hiroshi Takemura (Noda Tus, Japan); Hiroshi Mizoguchi (Tokyo University of Science, Japan) Robots that perform services for humans are expected to be effective and useful. Guide robots are examples of such service robots. For a guide robot to act according to the needs of the guidance target, the guide robot must have the ability to differentiate between the guidance target and other individuals. Therefore, the guide robot requires personal identification functionality. Here, a method to acquire an individual's upper-body skeletal information using a three-dimensional range image sensor, and to perform personal identification based on these data, is proposed. Personal identification using the proposed

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method is performed for 13 subjects, and identification is achieved with an accuracy of 98.4%. These results indicate the feasibility of personal identification using upper-body skeletal information.

14:24 Fundus Image Texture Features Analysis in Diabetic Retinopathy Diagnosis

Devvi Sarwinda (Universitas Indonesia & Faculty of Mathematics and Natural Sciences, Indonesia) This paper investigates texture feature capabilities from fundus images to differentiate between diabetic retinopathy (DR), age-related macular degeneration (AMD) screening and normal. Our proposed method using improvement of local binary pattern (LBP) with calculation of LBP original value and magnitude value of fundus images. This method is compared with Local Line Binary Pattern (LLBP). In this study, four experiments (DR-Normal, DR-AMD, AMD-Normal, Multiclass) were designed for two databases, DIARETDB0 database and STARE. Kernel PCA is choosed as feature selection method, and three classifiers are tested (Naive Bayes, SVM, and KNN). The experimental results show that our proposed method has higher accuracy than LLBP, with accuracy of binary classification 100% for DR-Normal and AMD-Normal. While, multiclass classification (DR-AMD-Normal) achieves an accuracy 80-84%. These results suggest that our proposed method in this paper can be useful in a diagnosis aid system for diabetic retinopathy.

14:42 Image Reconstruction Methodology Based on Block Stagewise Regularized Orthogonal Matching Pursuit Compressive Sensing

Xiongyong Zhu (Guangdong University of Education, P.R. China); Wenfang Wu (Sun Yat-Sen University, P.R. China); Guoming Chen (Guangdong University of Education, P.R. China); Deng Huang, Fukang Liu and Hongzhou Tan (Sun Yat-Sen University, P.R. China) The traditional approaches to signal acquisition need to collect large amounts of redundant data first, then compress them to extract useful information, which is inefficient and requires larger storage spaces.

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Compressed sensing (CS) can avoid sampling the redundant data; it obtains the discrete signals at the sampling rate that is lower than the Nyquist sampling rate, and reconstruct the original signal with high probability. Based on CS, we proposed a method called Block Stagewise Regularized Orthogonal Matching Pursuit (StROMP). Simulation results show that the proposed method can effectively reduce the storage spaces and computational complexity, which improves the quality of reconstructed images in the premise of ensuring a shorter reconstruction time.

13:30-15:00 S3C: Spectroscopy Techniques Chair: Rohini Mudhalwadkar (College of Engineering Pune, India)

13:30 Modelization of interdigitated electrode sensor for impedance spectroscopy measurement

Ayoub Bourjilat (Université de Lorraine, France); Frederic Sarry and Djilali Kourtiche (Université de Lorraine-CNRS, France); Mustapha Nadi (Université de Lorraine-CNRS & Institut Jean Lamour, France) In this paper, a new design of a sensor for conductivity measurements is presented. Impedance spectroscopy is often used as experimental techniques to detect and measure changes in electrical conductivity using an equivalent circuit model which is adapted to t