iosr-JEEE   Volume-9 ~ Issue-5 ~ Sep-Oct 2014

Abstract: Ultrasonic arrays are used in many applications including medical imaging. In this specific case is important to achieve precise information about the magnitude and position of the peak pressure and intensity produced by the probe. This paper presents the designof linear array transducers for ultrasonic measurements
Keywords: Ultrasonic, Linear array, Transducer,medical imaging.

[1] M. Redwood, "Transient performance of a piezoelectric transducer," J. Acoust. Soc. Am. 33, 527–536 ,1961.
[2] E. K. Sittig, "Transmission parameters of thickness-driven piezoelectric transducers arranged in multilayer configurations," IEEE Trans. Sonics Ultrason. SU-14, 167–174, 1967.
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[5] P. Marchal, F. Levarssort, L.-P. Tran-Huu-Hue, and M. Lethiecq, "Effects of acoustical properties of a lens on the pulse-echo response of a single element transducer," IEEE International Ultrasonics, Ferroelectrics, and Frequency Control Joint 50th Anniversary Conference, pp. 1651–1654,2004..

Abstract: Arrival of Micro-electromechanical system (MEMS) in the last decade has been immense and ever growing. MEMS is an expanding and fast growing technology with an extensive range of applications. Micro cantilevers belongs to MEMS set of devices and are often used for detection of forces in Micromechanical Sensors(e.g. pressure sensors & accelerometers) and probe for force sensor to atomic force microscope used as transducers, transport mechanisms, relays, switches, resonators etc. In this paper, the relative study and recent development of different micro cantilevers which differ in the material being used and in their construction are discussed and compared to each other based on various parameters.

Keywords: MEMS, Microcantilever, principles, shapes

[1] Saranya R, Saranya K, Ceemati D, Chandra Devi K, Meenakshi Sundaram N, "Design of MEMS-based Microcantilever for Tuberculosis Detection," in Proc. Conf COMSOL, Banglore., 2013.

[2] Naeli, Kianoush, "Optimization of piezoresistive cantilevers for static and dynamic sensing applications," Ph.D. dissertation, Institute of Technology Georgia, School of Electrical and Computer Engineering, Georgia, 2009.

[3] Yu Xiaomei, Zhang Dacheng, Wang Wei, Li Ting, "A sensor platform based on piezoresistive cantilever," in Proc. IEEE Int. Conf Electron Devices and Solid-State Circuits., pp. 121-124, 2003.

[4] Mathad, Aditya G., and Rajendra M. Patrikar, "The Origin of Surface Stress experienced by a Micro-cantilever beam," in Proc. IEEE Int. Conf Students' Technology Symposium (TechSym)., pp 12-16, April 2010

[5] Reddy, V. Mounika, and GV Sunil Kumar, "Design And Analysis of Microcantilevers With Various Shapes Using COMSOL Multiphysics Software," IJETAE Trans. vol. 3, issue 3, pp. 294-299, March 2013

Abstract: The principle issue with existing convention lies in the arbitrary choice of cluster heads. There exists a likelihood that the cluster heads structured are unequal and may stay in one part of the system making another part of the system inaccessible. In this work an attempt has been made to enhance the system existence with smart clustering component by dissecting the Connectivity, Distance and Residual proficiencies. The work will additionally decrease the rate of getting a particular node dead, rapidly. The proposed scheme will similarly control the amount of clusters in the system by indicating as far as possible for number of nodes in the cluster. This work will give an attractive balanced circulation of cluster and also sensor nodes over the system. \

Keywords: Sensor node, Cluster Head, Maximum Connectivity, Maximum Residual Energy and Maximum Response time

[1]. Macro conti, Giuseppe Anastasi, Mario Di Francesco, Andrea Passarella, "Energy conservation in wireless sensor networks: A Survey", Ad-hoc network 7 (2009), pp. 537-568.
[2]. S. Venkatesan, Shashidhar Rao ,Gandham. Milind Dawande, Ravi Prakash, "Energy Efficient Scheme for Wireless Sensor Networks with Multiple Mobile Base Stations". Vol-6, IEEE Aug 2003,pp.377-381.
[3]. Miodrag Potkonjak, Sasa Slijepcevic, "Power Efficient Organization of Wireless Sensor Networks". IEEE July 2001, pp.472-476.
[4]. Carlos Carreto, Tiago Camilo, Jorge SA Silva, Fernando Boavida, Energy Efficient Ant-Based Routing Algorithm for Wireless Sensor Network". IEEE 2006, pp 49-59.
[5]. Edward J. Coyle, Seema Bandyopadhyay, Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Network". IEEE Sept. 2003, pp. 1713-1723

Abstract: Edge detection technique is a vital part of image processing that can be applied to different types of images including medical images. Contrast adjustment is another important part of image processing which can have significant effect on the edge detection process. This paper discusses about edge detection technique along with the algorithm. Detailed analysis based on edge detection for images of different contrast has been performed. Results are analyzed corresponding to images of different contrast which can be achieved by histogram stretching.

Keyword: Contrast adjustment, Edge detection, Image processing, Medical image, Visual quality

[1] Mohamed A. El-Sayed, A New Algorithm Based Entropic Threshold for Edge Detection in Images, International Journal of Computer Science Issues, Vol. 8, Issue 5, No 1, September 2011
[2] Raman Maini and Dr. Himanshu Aggarwal, Study and Comparison of Various Image Edge Detection Techniques, International Journal of Image Processing, Vol. 3, Issue 1
[3] Anurag Sharma, Pankaj Sharma, Rashmi and Hardeep Kumar, Edge Detection of Medical Images Using Morphological Algorithms, International Journal for Science and Emerging Technologies with Latest Trends, Vol. 4, Issue 1
[4] Dr. Muna F. Al-Samaraie, A New Enhancement Approach for Enhancing Image of Digital Cameras by Changing the Contrast, International Journal of Advanced Science and Technology, Vol. 32, July 2011
[5] Sukhjinder Singh, R.K. Bansal and Savina Bansal, Comparative Study and Implementation of Image Processing Techniques Using Matlab, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, Issue 3, March 2012

Abstract: Now a days, frequency or spectral measure is one of the most important issues of the different regions of power system. The Power spectral density (PSD) estimation can give a direct indication of major areas of different power system contributing to the oscillations in a specific mode frequency, and therefore may be used in the future for determining control actions. PSD analysis also gives information on the characteristics of power signals used in control rooms for monitoring of power system dynamics thus can aid in improving the operational reliability of interconnected power system. Therefore, in this Paper, we concentrate on the study of spectral behavior of power signals of different regions such as US Eastern Interconnection, the Nordic Power system and Nigerian power system. Among different spectral estimation methods, parametric technique has been used in this Paper to estimate PSD of power signals of different regions. Parametric methods can yield higher resolutions than nonparametric methods in cases when the signals length is short as in case of blocks of power signals. These methods use a different approach to spectral estimation; instead of trying to estimate the PSD directly from the data, they model the data as the output of a linear system driven by white noise, and then attempt to estimate the parameters of that linear system. Another approach of presenting PSD, namely, spectrogram, a time-varying spectral representation that shows how the spectral density of a signal varies with time. Detail MATLAB simulations are carried out for synthetic power signals of different regions as mentioned above to investigate the performance of parametric methods in estimating PSD and to display spectrograms thus comparing spectral behavior of different regions.

Keywords: Spectral analysis of the power system, parametric spectral estimation methods, simulation results and comparisons of the parametric method and spectrogram in different regions using synthetic power signals.

[1] L. Dosiek, D. Trudnowski, and J. Pierre, "New algorithms for mode shape estimation using measured data," in IEEE Power and Energy Society General Meeting, July 2008, pp. 1-8.
[2] D. Trudnowski and J.W. Pierre, in Inter-area Oscillations in Power Systems: A Nonlinear and Nonstationary Perspective, ser. Power Electronics and Power Systems, A. R. Messina, Ed. Springer, 2009, ch. Signal Processing Methods for Estimating Small-Signal Dynamic Properties from Measured Responses, pp. 1-36.
[3] H. Ghasemi and C. Cañizares, "Confidence intervals estimation in the identification of electromechanical modes from ambient noise," IEEE Transactionson Power Systems, vol. 23, no. 2, pp. 641 –648, May 2008.
[4] H. Ghasemi, C. Cañizares, and A. Moshref, "Oscillatory stability limit prediction using stochastic subspace identification," IEEE Transactions on PowerSystems, vol. 21, no. 2, pp. 736 – 745, May 2006.
[5] D. Trudnowski, "Estimating Electromechanical Mode Shape From Synchrophasor Measurements," IEEE Transactions on Power Systems, vol. 23, no. 3, pp. 1188–1195, Aug. 2008

Abstract: A new nonlinear observer-based controlscheme for a single-phase photovoltaic (PV) systemconnected to the grid is presented.The system consists of a PV array, DC-DC Boost converter and a DC-AC inverter coupled to grid network. The DC-DCconverter is used to extract maximum power from the PV array and the DC-AC inverter is used to synchronize a sinusoidal currentoutput with a voltage gridwith regulated DC bus voltage. A robust nonlinear controller isdeveloped using the sliding mode control design technique based on anaveraged nonlinear model of the whole controlled system. The control action is carried out assuming that all the states of the grid connected PV system are known by measurement. Then, a nonlinear stateobserver for Boost inductor current, DC bus voltage and grid injected current estimation is implemented from the measurementof PV array voltage state, PV array current signal and grid voltage signal. Theobserver-based control method provides robust maximum power point tracking (MPPT), grid current trackingand DC bus voltage regulation, achieves unity power factor and optimizes the PV energy extraction suitable for grid connected PV systems. Simulation results are provided to demonstrate the effectiveness of the proposed design and robustness under different operating conditions such as changes in atmospheric conditions and noise measurements.

Keywords: Grid connected photovoltaic system, Maximum power point tracking (MPPT), DC-DC converter, DC-AC inverter, Sliding mode control, asymptoticstability, State observer

[1] N. Femia, G. Petrone, G. Spagnuolo, and M. Vitelli, Optimization of Perturb and Observe maximum power point tracking method, Power Electronics, IEEE Transactions, Vol. 20, n.4, July 2005, pp. 963–973.
[2] Jae Ho Lee; HyunSuBae; Bo Hyung Cho, Advanced Incremental Conductance MPPT Algorithm with a Variable Step Size, Power Electronics and Motion Control Conference EPEPEMC 12th International, Sept 2006, pp. 603 – 607.
[3] NoppornPatcharaprakiti, SuttichaiPremrudeepreechacharn, YosanaiSriuthaisiriwong, Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system, Renewable Energy, Vol 30 n.11, Sept 2005, pp. 1771–1778.
[4] HazemFeshara, Mohamed Elharony, SolimanSharaf, Design, Digital Control, and Simulation of a GridConnected Photovoltaic Generation System. International Journal of Renewable Energy Research, Vol.4, No.2, 2014.
[5] Jui-Liang, Ding-Tsair Su, Ying-ShingShiao, Research on MPPT and Single-Stage Grid-Connected for Photovoltaic System, Wseas Transactions on Systems, Volume 7, October 2008.

Abstract: The human cells has different electrical conductivities. Due to difference in conductivities of cell constituents we can determine the electrical changes occurred in every constituent and characterized the human body to determine its composition such as fat free mass (FFM), fat mass (FM), total body water (TBW), Body mass index (BMI) and many other. Bioelectrical Impedance analysis (BIA) may be used for estimating body composition. It can be measured by applying a small 1mA, 50 KHz current which is injected into the body through a pair of electrodes and the induced voltage is picked up using another pair of electrodes. The impedance offered by the body to the applied current and the phase angle between the injected current and induced voltage is measured. The advantages of bioelectrical impedance method are non-invasive measurement, portability, safety, ease to use, low cost and acceptable levels of reliability and accuracy in estimation of body composition. A battery operated low cost and compact bio-impedance meter is developed which can be used for estimation of body composition parameters. It was proposed to measure body impedance and phase angle from healthy subjects using four electrode systems. The impedance values are recorded for different female and male individuals.

Keywords: Bio impedance, Body composition, Impedance, Phase angle.

[1] Edwin K. Bioelectrical Impedance Anal. and Body Composition [Online]. Available: http://www.thebody.com
[2] Paul B P and Maria A, "Use of Bioelectrical impedance anal. in clinical manage. of malnutrition", Amer. J. of Clinical Nutrition, pp. 485–488
[3] Paul D, "Changes in fat free mass during weight loss determined by bio impedance Anal. and by densitometry," The Amer. J. of Clinical Nutrition, vol. 49, pp. 33-36, 2014
[4] Baker L. E, "Principles of the impedance technique", IEEE Eng. in Medicine and Biology Mag. , vol. 8, no. 1, pp. 11–15
[5] Schwan H. P. and Kay C. F, "The conductivity of living tissues", Annals of the New York Academy of Sci. , vol. 65, no. 6, pp. 1007–1013
[6] Baumgartner R. N et. al., "Bioelectric impedance phase angle and body composition", The Amer. J. of Clinical Nutrition, vol. 48, pp. 16–23

Abstract: Facial expressions analysis most significant part for human computer interaction. Now days, face emotion recognition is most important application of computer vision that can be used for security, entertainment and human machine interface. Automatic face emotion recognition is still challenging & emerging problem with many applications such an automatic surveillance, robot motion, video indexing and retrieval and monitoring systems. Emotion recognition and classification depends upon gesture, pose, facial expression, speech and behavioral reactions, etc. In this paper, an automatic emotion recognition and classification method is based on Genetic Algorithm and on neural network. This system consists of 3 steps which automatically detect the face emotion image: First, pre-processing such as adjusting contrast, colour segmentation, filtering, and edge detection is applied on the input image. Secondly, features are extracted with projection profile method due to high speed which has taken as processed input image. Finally, in third stage to compute optimized parameters of eyes and lip through the GA, then emotions (neutral, happy, sad, dislike, angry, surprise and fear) is classified using artificial neural network. The proposed system is tested on a face emotion image. The obtained results show that better performance of genetic algorithm along with neural network.

Keywords: pre-processing, feature extraction, projection profile, recognition, Genetic Algorithm, Neural network

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[6]. Tian, Ying-li, Kanade, T.and Cohn, "Recognizing lower face action units for facial expression Analysis", IEEE Transaction on Automatic Face and Gesture Recognition, march,2000, pp.484-490.

Abstract: The Background Subtraction Algorithm is used to detect the object in the image. The subtraction of the image is pixel based subtraction. Before the subtraction of two images the pre-processing is done using the median filter. After the subtraction is done the segmentation is performed using threshold value. Once the segmentation is completed the morphological filtering is performed on that image to remove the unwanted blobs. System is designed using MATALAB/Simulink block sets. In MATLAB/Simulink the system generator token is used to convert Simulink model logic into the VHDL code which makes it compatible with FPGA. Using the system generator token VHDL code is generated. That VHDL code is synthesis in the Xilinx 14.1 and then .bit file is downloaded to the Virtex-5 board through JTAG cable and the output image is display on the VGA monitor which is interfaced with Virtex-5 board using DVI connector.

Keywords: Motion detection, Background subtraction algorithm, FPGA, VGA monitor

[1]. M. Kalpana Chowdary , S. Suparshya Babu , S. Susrutha Babu , Dr. Habibulla Khan"FPGA Implementation of Moving Object Detection in Frames by Using Background Subtraction Algorithm" International conference on Communication and Signal Processing, April 3-5, 2013.
[2]. Can Yang, Weichuan Yu "Moving Object Detection by Detection Contiguous Outliers in the Low Rank Representation" IEEE transaction on pattern analysis and intelligence, vol. 35, no.3, 2013.
[3]. C. S´anchez-Ferreira, J. Y. Mori, C. H. Llanos "Background Subtraction Algorithm for Moving Object Detection on FPGA " Department Mechanical Engineering University of Brasilia 2012.
[4]. "Motion and Feature Based Person Tracing In Surveillance Videos" transactions on computer vision 2011.
[5]. Jorge Hiraiwa, Enrique Vargas "An FPGA based Embedded Vision System for Real-Time Motion Segmentation" IWSSIP 2010 - 17th International Conference on Systems, Signals and Image Processing

Abstract: This paper presents a technique for classification of faults on single circuit transmission line using Wavelet Multiresolution Analysis.EMTP (Microtran) is used to perform simulations which generate time domain input signal on a 400KV, 300km transmission line fed from one end. Daubechies eight (D-8)wavelet transforms of the three phase currents on a transmission line fed from one end are used for fault analysis in this work. The summation of the 1st level output of MRA detail signals of current in each phase extracted from the original signals generated are employed in fault classification algorithm. Simulation results show that the proposed method is effective and simple and give accurate results irrespective of fault location, fault inception angle and fault impedance.

Keywords: Wavelet transforms, Multiresolution analysis, EMTP, fault classification

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Based on Discrete Wavelet Transform and Artificial Intelligence," IEEE/PES Transmission and Distribution Conf. and Exposition: Latin America 2006, Aug. 2006, pp. 1-6.

Abstract: This paper presents different series concept cascading four single units of dual buck inverter based on dual buck topology with phase-shift control using control systems. The dual buck type inverters are still VSI, but with the unique topology and operation, they do not have the shoot-through worries, which lead to greatly enhanced reliability. With phase-shifted PWM fed to different cascade units, zero crossing distortion is eliminated. The phase-shift control increases the equivalent switching frequency by N times that of single-unit inverter, which leads to lower current ripple. A 1 kW, 120 V ac output cascade dual buck inverter system has been built to validate the proposed topology and by comparing the results of single unit dual buck inverter, 2-unit , 3-unit and 4-unit cascade dual buck inverter at 1kW . The THD is reduced for 4-unit cascade inverter when compared with 3-unit cascade inverter. This is proved by using FFT analysis in MATLAB SIMULINK.

Keywords: Cascade unit, dual buck inverter, phase-shift control, shoot-through worries, zero crossing distortion

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