DATA ACQUISITION APPLICATIONS doc

DATA ACQUISITION APPLICATIONS Edited by Zdravko Karakehayov Data Acquisition Applications http://dx.doi.org/10.5772/2596 Edited by Zdravko Karakehayov Contributors Sohaib Majzoub, Hassan Diab, Wang Rui, Wang Tingfeng, Sun Tao, Chen Fei, Guo Jin, Troy C. Richards, Carlos Ricardo Soccol, Michele Rigon Spier, Luciana Porto de Souza Vandenberghe, Adriane Bianchi Pedroni Medeiros, Luiz Alberto Junior Letti, Wilerson Sturm, Paul Osaretin Otasowie, Chen Fan, José R. García Oya, Andrew Kwan, Fernando Muñoz Chavero, Fadhel M. Ghannouchi, Mohamed Helaoui, Fernando Márquez Lasso, Enrique López-Morillo, Antonio Torralba Silgado, Bogdan Marius Ciurea, Salah Sharieh, Franya Franek, Alexander Ferworn, Andrew Lang, Vijay Parthasarathy, Ameet Jain, V. González, D. Barrientos, J. M. Blasco, F. Carrió, X. Egea, E. Sanchis, Paulo R. Aguiar, Cesar H.R. Martins, Marcelo Marchi, Eduardo C. Bianchi, Feng Chen, Xiaofeng Zhao and Hong Ye Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2012 InTech All chapters are Open Access distributed under the Creative Commons Attribution 3.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. Notice Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Tanja Skorupan Typesetting InTech Prepress, Novi Sad Cover InTech Design Team First published August, 2012 Printed in Croatia A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechopen.com Data Acquisition Applications, Edited by Zdravko Karakehayov p. cm. ISBN 978-953-51-0713-2 Contents Preface IX Section 1 Industrial Applications 1 Chapter 1 Reconfigurable Systems for Cryptography and Multimedia Applications 3 Sohaib Majzoub and Hassan Diab Chapter 2 High Accuracy Calibration Technology of UV Standard Detector 29 Wang Rui, Wang Tingfeng, Sun Tao, Chen Fei and Guo Jin Chapter 3 Dynamic Testing of Data Acquisition Channels Using the Multiple Coherence Function 51 Troy C. Richards Chapter 4 Data Acquisition Systems in Bioprocesses 79 Carlos Ricardo Soccol, Michele Rigon Spier, Luciana Porto de Souza Vandenberghe, Adriane Bianchi Pedroni Medeiros, Luiz Alberto Junior Letti and Wilerson Sturm Chapter 5 Microwave Antenna Performance Metrics 107 Paul Osaretin Otasowie Chapter 6 The Data Acquisition in Smart Substation of China 123 Chen Fan Chapter 7 Subsampling Receivers with Applications to Software Defined Radio Systems 167 José R. García Oya, Andrew Kwan,Fernando Muñoz Chavero, Fadhel M. Ghannouchi, Mohamed Helaoui, Fernando Márquez Lasso, Enrique López-Morillo and Antonio Torralba Silgado Section 2 Medical Applications 195 Chapter 8 Data Acquisition in Pulmonary Ventilation 197 Bogdan Marius Ciurea VI Contents Chapter 9 Mobile Functional Optical Brain Spectroscopy over Wireless Mobile Networks Using Near-Infrared Light Sensors 233 Salah Sharieh, Franya Franek and Alexander Ferworn Chapter 10 Calibration of EM Sensors for Spatial Tracking of 3D Ultrasound Probes 253 Andrew Lang, Vijay Parthasarathy and Ameet Jain Section 3 Scientific Experiments 269 Chapter 11 Data Acquisition in Particle Physics Experiments 271 V. González, D. Barrientos, J. M. Blasco, F. Carrió, X. Egea and E. Sanchis Chapter 12 Digital Signal Processing for Acoustic Emission 297 Paulo R. Aguiar, Cesar H.R. Martins, Marcelo Marchi and Eduardo C. Bianchi Chapter 13 Making Use of the Landsat 7 SLC-off ETM+ Image Through Different Recovering Approaches 317 Feng Chen, Xiaofeng Zhao and Hong Ye Preface Today, the data acquisition technology has found its way into virtually every segment of electronics. A digital signal processing (DSP) system accepts analog signals as input, converts those analog signals to numbers, performs computations using the numbers and eventually converts the results of the computations back into analog signals. Once converted to numbers, signals are unconditionally stable. Error detection and correction methods can be applied to store, transmit and reproduce numbers with no corruption. Signals stored digitally are really just large arrays of numbers. As such, they are immune to the physical limitations of analog signals. Furthermore, DSP can allow large bandwidth signals to be sent over narrow bandwidth channels. Finally, communications security can be significantly improved through DSP. Since numbers are traveling instead of signals, encryption and decryption can be easily done. While traditionally the goal of data acquisition was to sense the environment, modern computing systems add another axis along which data acquisition is organized. Those systems are capable of measuring internal variables such as on-chip temperature or energy in the battery. Thus the environment to machine data flow frequently works in parallel with machine to machine data flow. Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world. The targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book. Many people have contributed to this book; first and foremost the authors who have contributed 13 chapters. These colleagues deserve our appreciation for taking the time out of their busy schedules to contribute to this book. I also owe a big word of thanks to the publishing process manager of this book, Tanja Skorupan. Tanja put in a great deal of effort organizing the interaction with the authors and the production team. Zdravko Karakehayov Department of Computer Systems, Technical University of Sofia, Bulgaria [...]... reproduction in any medium, provided the original work is properly cited 4 Data Acquisition Applications applications Application-Specific Integrated Circuits (ASIC), on the other hand, are used to implement a single fixed function Therefore, ASICs have no flexibility and they can only execute a very limited type of the targeted applications known beforehand (Singh et al., 1998), (Kozyrakis, 1998), (Möller... of loading data into the lookup table is then the same as the Frame Buffer This global lookup table could be placed between the Frame Buffer and the RC Array The data coming from the Frame Buffer to RC Array is multiplexed to the address bus of this lookup table and the needed data are passed to the RCs from this table The distribution of the data on the RCs follows the same Frame-BufferData-Distribution... (Singh et al., 1998) Figure 1 MorphoSys Block Diagram and RC Logic Digaram 6 Data Acquisition Applications Figure 2 RC Array Communication Buses 4 Cryptographic algorithms mapping onto MorphoSys Cryptography has grown to be a fundamental element to handle authenticity, integrity, confidentiality and non-reputability of private data flows through public networks With the increasing demand for high performance... platform is much more flexible than the ASIC or FPGA A wide range of applications can be implemented on MorphoSys, taking advantage of the fact that MorphoSys is a low power consumption platform (Majzoub & Diab, 2006) Saying all this, still the MorphoSys can and should be improved in order to compete with other platforms 14 Data Acquisition Applications 4.2 Twofish encryption algorithm In this section,... Frame-Buffer -Data- Distribution scheme, which means same Row/Column would have the same data or completely unshared data are sent to every one Whether the lookup table is place on or off the RC, the drawback of this method is that it increases the RC size greatly, and thus, the area of the whole chip, which make the system hard to scale Moreover, it puts a heavy load on the buses in loading the data to the... to map such applications on the hardware under examination Therefore, the mapping of the targeted applications for such hardware evaluation must be carried out manually This handmapping process can provide valuable information to prospective compilers that eventually Reconfigurable Systems for Cryptography and Multimedia Applications 5 will emerge out of the implementation of wide range of applications. .. instructions are very easy to implement and can greatly help the performance Since most of the cryptographic applications, as well as multimedia type of applications requires iterative and repetitive operations on different data 7 Conclusion In this chapter we implemented a number of multimedia applications, namely Rijndael, Twofish, image filtering and computer graphics algorithms This implementation... calculation of the vectors Mo and Me are straightforward We just have to separate the odd bytes from the even ones Afterwards the expanded key words should be derived from Me and Mo and stored in 16 Data Acquisition Applications the memory to be used later The key computations are performed offline and then stored in main memory to be used later in the encryption The key scheduling operation is shown in Fig... compared to other architectures (128 key) Overall Cycles 7098 13815 16315 25650 22790 100200 Overall Cycles 5681 11015 14415 22350 17690 67000 Overall Cycles 4361 8115 8515 17350 12790 56500 18 Data Acquisition Applications Architecture MorphoSys Pentium Pro Pentium II UltraSPARC PowerPC 750 68040 Encrypt 1 0.13 0.13 0.32 0.25 1.5 Key (128) 1 3.8 4 8.14 6 26 Overall 1 1.86 1.95 3.97 2.93 13 Table 5 Speedup... kernel a corresponding pixel in the image This operation is shown in Fig 13, which is the general case of the convolution operation The image size is MN pixels and the kernel is RS elements 20 Data Acquisition Applications Figure 13 An MN image processed using an RS convolution kernel This "shift, add, multiply" operation is termed the "convolution" of the kernel with the image If the kernel is an . DATA ACQUISITION APPLICATIONS Edited by Zdravko Karakehayov Data Acquisition Applications http://dx.doi.org/10.5772/2596 Edited. battery. Thus the environment to machine data flow frequently works in parallel with machine to machine data flow. Data acquisition systems have numerous applications. This book has a total of. Fei and Guo Jin Chapter 3 Dynamic Testing of Data Acquisition Channels Using the Multiple Coherence Function 51 Troy C. Richards Chapter 4 Data Acquisition Systems in Bioprocesses 79 Carlos