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Sathishkumar, R.
- Micro Size Ultrasonic Transducer for Marine Applications
Authors
1 School of Electrical and Electronics, Faculty of Engineering and Technology, SRM University, IN
Source
Indian Journal of Science and Technology, Vol 4, No 1 (2011), Pagination: 8-11Abstract
We address the advancement and development of MEMS ultrasonic transducer for underwater applications. The development of MEMS transducer is investigated and proved that it is a viable concept. The flexibility in tailoring their frequency and acoustic impedance increases the potential of their application in various fields. Compared to conventional, MEMS offer the advantage of superior performance as far as bandwidth is concerned. In spite of their lower coupling coefficient, there is a potential for significant improvement. We present the latest design of the piezoelectric, pressure and capacitive transducers. The material employed, method utilized in development, performance and capacity of each transducer is presented. Finally, the importance and needs for modeling and simulation is discussed. Currently we design and modeling a micro size transducer in Intellisuite software.Keywords
MEMS, Acoustics Transducer, Underwater ApplicationsFull Text
References
- Akasheh F, Myers T and Fraser A (2004) Development of piezoelectric micro-machined ultrasonic transducers. Sensors Actuators A. 1, 275-287.
- Aravamudhan S and Bhansali S (2008) Reinforced piezoresistive pressure sensor for ocean depth measurements. Sensors Actuators A. 142, 111–117.
- Arshad MR (2009) Recent advancement in sensor technology for underwater applications. Indian J. Marine Sci. 38(3), 267-273.
- Bernstein JJ, Houston K, Niles LC, Finberg SL, Chen, HD, Cross LE, Li KK and Udayakumar K (1997) Micro-machined high frequency ferroelectric sonar transducers. IEEE Trans. on ultrasonics, ferroelectrics & frequency control. 44(5), 960- 969.
- Chowdhury S, Ahmadi M and William C. Miller (2002) Design of a MEMS acoustical beamforming sensor array. IEEE Sensors J. 2, 6-11
- Ito M, Okada N and Takabe M (2008) High sensitivity ultrasonic sensor for hydrophone applications using an epitaxial PZT fil grown on SrRuO3/Pt/_-Al2O3/Si. Sensors Actuators A. 1, 278-282.
- Jin X, Ladabaum I, Butrus T and Khuri-Yakub (1998) The micro-fabrication of capacitive ultrasonic transducers. J. Micro electromech. Sys. 7, 3-9.
- Mescher M, Houston K and Bernstein J (2002) Novel MEMS micro-shell transducer arrays for high-resolution underwater acoustic imaging applications. Proc. of the IEEE Sensors. 1, 541-546.
- Oralkan O, Sanli Ergun A and Khuri- Yakuh T (2002) Capacitive micromachined ultrasonic transducers: Next generation arrays for acoustic imaging? IEEE Trans. on Ultrasonics Ferroelectrics & Frequency Control. 49, 11-16.
- Zhu B and Varadan VK (2002) Integrated MOSFET based hydrophone device for underwater applications. Proc. of SPIE, 4700, 101-110.
- Analysis of Marine Sensor Signals in Fast Time Domain Processing
Authors
1 School of Electrical and Electronics, SRM University, IN
Source
Wireless Communication, Vol 1, No 5 (2009), Pagination: 210-215Abstract
Synthetic aperture sonar (SAS), a new emerging marine system and an enabling technology, is based on storing successive snapshots of the target's scene and processing the collected data. Advancing the speed and robustness of image reconstruction is greatly desired, this paper describes imaging algorithm, computation time and image signal to noise ratio. It gives an introduction to the time domain beamforming (TDB) and aperture processing. We initially look at the fundamental processing constraints that limit the frequency domain beamforming(FDB) technique. TDB technique has been successfully used instronomy, satellite, aircraft borne radar and used for AUV based mine hunting and numerous other applications. Its resolution is independent of range, which making available a wide signal processing trade-space. During the past few years, we have been applying synthetic aperture processing techniques to sonar. In this study, the use of TDB is investigated and concluded that it is very effective in removing the effects and restoring the focus of images. The algorithms can be outlined using the MATLAB.
Keywords
Real Aperture Sonar.
- Design and Analysis of Furious Mechanism for Addition in Integers Using Quaternary Signed Digit Number System
Authors
1 Department of Electronics and Communication Engineering, SNS College of Technology, IN
2 SNS College of Technology, IN
Source
Software Engineering, Vol 7, No 4 (2015), Pagination: 110-112Abstract
With the binary system of numeration, the speed of arithmetic operations square measure restricted by formation and propagation of the carry. Mistreatment quaternary signed digit (QSD) system of numeration each carry free addition and borrow free subtraction are often achieved. The QSD system of numeration needs a special set of prime modulo based mostly logic for arithmetic operations. Employing a high base system of numeration like Quaternary Signed Digit, a carry free operation are often achieved. Arithmetic Operations like addition and subtraction for giant numbers like sixty four and 128 are often computed while not the propagation of carry mistreatment QSD system of numeration. Style is simulated and analyzed mistreatment 13.2 ISE machine.
Keywords
Quaternary Signed Digit (QSD).- A Study of Image Processing in Agriculture
Authors
1 Department of Mathematics, BIT, Sathyamangalam, IN
Source
International Journal of Advanced Networking and Applications, Vol 9, No 1 (2017), Pagination: 3311-3315Abstract
Agriculture is the backbone of human sustenance on this world. Now a days with growing population we need the productivity of the agriculture to be increased a lot to meet the demands. In olden days they used natural methods to increase the productivity, such as using the cow dung as a fertilizer in the fields. That resulted increase in the productivity enough to meet the requirements of the population. But later people started thinking of earning more profits by getting more outcome. So, there came a revolution called "Green Revolution". In this paper we implemented image processing using MATLAB to detect the weed areas in an image we took from the fields.Keywords
Image Processing, Agriculture, Image Segmentation, Classification, Plant Diseases.Full Text
References
- Hetzroni , Hossein Nejati, Zohreh Azimifar, Mohsen Zamani; “Using Fast Fourier Transform for weed detection in corn fields”; IEEE; 2008.
- Pydipati, Xavier P. Burgos-Artizzu, Angela Ribeiro, Maria Guijarro, Gonzalo Pajares; “Real- time image processing for crop/weed discrimination in maize fields”; Elsevier; 2010.[4]
- Huang, Grianggai Samseemoung, Peeyush Soni, Hemantha P. W. Jayasuriya, Vilas M. Salokhe; “Application of low altitude remote sensing (LARS) platform for monitoring crop growth and weed infestation in a soyabean plantation”; Springer; 2012.[4]
- Pugoy and Mariano,G. Jones, Æ Ch. Ge´e, Æ F. Truchetet; “Modeling agronomic images for weed detection and comparison of crop/weed discrimination algorithm performance”; Springer; 2008.[4]
- Anup Vibhute, S K Bodhe; “Applications of Image Processing in Agriculture: A survey; International Journal of Computer Applications”; 2012.[4]
- Alasdair McAndrew; “Introduction to digital image processing with MATLAB”; Course Technology; 2004.[1]
- S. Annadurai and Shanmugalakshmi, Fundamentals of Digital image processing India Pearson Education, 2007 , pp.310.
- Zhang, Pengyun and L.jigang, “Computer assistance image processing spores counting, “ in 2009 proc. Int.Asia Conf. on informatics in Control, Automation and robotics, pp.203-206.
- Xu, C.C Yang, S.O. Prasher, J.a.Landry, H.S. Ramaswamy, and A. Ditommaso, ”Application of artificial neurol networks in image precongation and classification of crop and weeds,”Canadian Agricultural Engineeering, vol. 42,no. 3, pp. 147-152, 2000
- Hairuddin ,S.Phadikar and J.Sil, “Rice disease indentification using pattern recongnition techniques,” in Proc. 11th Int. Conf. on computer and information technology, 2008, Khulna, Bangladesh, pp. 420-423
- R. Sathiskumar, Dr B Nagarajan, R.Karthigamani, Dr M.Gunasekaran “Region based object extraction using ANFIS combined with support vector machines” in 2017 Asia Life sciences.
- P. Saravanamoorthi “ Modified Bee Colony optimization for the selection of different combinations of food sources”, International Arab Journal of Information Technology, Vol. 13, No. 6, 2016.
- Prakash, K & Nagarajan, B 2014, ‘A Mathematical Based Approach For Vehicle Object Classification’, International Journal of Research in Computer Applications and Robotics, vol.2, no.7, pp.58-64.
- Sanyal, Abak, T, Barış, U & Sankur, B 1997, ‘The Performance of Thresholding Algorithms for Optical Character Recognition’, Int. Conf. on Document Analysis and Recognition: ICDAR’97, Ulm., Germany, pp.697-700.
- Kai , Kurniawati Ackley, D & Littman, M 1992, ‘Interactions between learning and evolution’, In C. G. Langton, C. Taylor, J. D. Farmer, and S.Rasmussen, eds., Artificial Life II. Addison−Wesly