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Volume-4 Issue-3: Published on March 15, 2016
Volume-4 Issue-3: Published on March 15, 2016


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S. No

Volume-4 Issue-3, March 2016, ISSN: 2319–6386 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Mohammad Quqazeh, Hasan .A.Aldabbas, Monzer.M. Krishan, Nabil Musa

Paper Title:

Characteristics and Analysis for Mechanical Instrumentation Used to Measure Fluid Viscosity

Abstract: The task of development of the measurement procedure and the general-purpose control equipment which can allow us to analyze fluid rheological properties and to ascertain the dependence of the stress tensor of the sample on the deformation tensor over a wide range of strain rates is urgent nowadays. At the same time the question of providing the continuous inspection of the product properties under the condition of high precision and measuring automation is a matter of principle.

 viscosimeter, measuring automation.


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3.   Anderson  D., Tannehill  G., Pletcher R.: Computational Fluid Mechanics and Heat Transfer.      V.1.-  Moscow:  The  World,  1990, 382.

4.   Alabugev P.M., Elnikov N.N., Kirnarsky M.Sh., Loktionov A.P., Polischu V.G.k, Sokolov V.S., Tatyanchenko V.A., Chigov A.E., Yushin V.V.: Similarities and Modelling in Sums and Exercises tutorial, Kursk: KSTU, 1997, 172 (in Russian).

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8.     C.T. Nguyen and F. Desgranges, Temperature and particle -Size  Dependent Viscosity Data for Water-Based Nan fluids- Heystersis Phenomenon”, International Journal of Heat and Fluid  Flow, Vol. 28, Issue 6, Dec. 2007, pp 1492-1506.

9.      Richard J. Goldestein, “Fluid Mechanics Measurements” 2nd  edition , Taylor & Francis,1996.

10.  Rehoo    Tec    Messtechnik    Gmb4,    operating manual, Falling Ball Viscometer KF Germany available at

11.    Bela G Liptak, “Instrument Engineer’s Handbook: Process-M measurement and Analysis” volume 1, 2013 

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Charlene A. Alcira, Mayraquel G. Balla, Nanette A. Burgos, John Paul O. Bilon, Mark Anthony M. Baris, Roselito E. Tolentino

Paper Title:

Scalar Product in Acquiring Angle for Mimicking Robotic Elbow using Two Tri-Axial Accelerometers

Abstract:  Most of the robotic arm is controlled using accelerometer by capturing different gestures and postures wherein the movement of the robotic arm is only limited on the given gestures, which doesn’t mimic the human arm correctly. This paper presents a method to acquire angle in mimicking robotic elbow using two low cost and small tri-axial accelerometers. These accelerometers are attached to the upper arm and forearm of the user. To find out the angular position of the elbow joint, scalar product is applied in the computation. The communication between human hand and robotic arm has been established using Arduino microcontroller. The result is that the robotic arm’s movement is synchronous with human arm’s movement. The system has been developed in Arduino IDE platform and Lab VIEW Robotics. In conclusion, the application of scalar product is effective in acquiring the value of user’s elbow angle.

Accelerometers, Elbow Angle, Robotic Elbow, Scalar Product


1.  Algan Uskarci. (2004). Human Arm Mimicking using Visual Data. Middle East Technical University Available from
2.     Aggarwal, Love, Varnika Gaur and Puneet Verma. (2013).Design and Implementation of a Wireless Gesture Controlled Robotic Arm with Vision. International Journal of Computer Applications, Vol.79. Available from /number 3/pxc3891906.pdf

3.    Khajone, Saurabh, Dr. S. W. Mohod and V.M. Harne. (2015). Implementation of a Wireless Gesture Controlled Robotic Arm. International Journal of Innovative Research in Computer and Communication Engineering, Vol.3 Issue 1. India: SantGadge Baba University. Available from

4.    Neto, Pedro, J. Norberto Pires and A. Paulo Moreira. (2009)Accelerometer-Based Control of an Industrial Robotic Arm. Japan: The 18th IEEE International Symposium on Robot and Human Interactive Communication. Retrieved from:

5. Pedley, Mark. (2013)Tilt Sensing Using a Three-Axis Accelerometer. Freescale Semiconductor Inc. Available fromhttps//

6.    Verma, Shamsheer. Hand Gestures Remote Controlled Robotic Arm. India: Research India Publications, Volume 3, 2013. [pdf file] Retrieved from:

7.     E-gizmo. Digital Accelerometer. Available from

8.     Analog. ADXL345 specification. Available from




Nagwa Albehery, Tonghui Wang

Paper Title:

Stochastic Dominance to Study Poverty Measures and its Applications

Abstract:   Poverty measures are used to measure poverty levels or degrees of poverty in a population. Stochastic dominance refers to a set of relations between distributions. Stochastic dominance orders of poverty measures have been discussed by many authors in the literature. In this paper, definition of stochastic dominance is introduced and used to order poverty measures. Hypotheses testing on stochastic dominance ordering of poverty measures are obtained. For illustration, our results are applied to the real data sets collected in Egypt between 1995/1996 to 2008/2009.

 Poverty measures, poverty lines, stochastic dominance, Hypotheses testing.


1.             N. Albehery and T. Wang, “Statistical inference of poverty measures using U-Statistics approach”, International Journal of Intelligent Technology and Applied Statistics, 2011, vol. 4, pp. 245--263.
2.             N. Albehery and T. Wang, “ Estimating poverty measures using truncated distributions and its applications”,  International Journal of Inventive Engineering and Sciences (IJIES), 2014, vol. 3, pp. 28--32.

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5.             M.L. Blackburn, “International comparisons of poverty”, The A merican Economic Review , 1994, vol. 84, pp. 371--374.

6.             K.V. Bosch, J. Callan, J. Estivill, P. Hausman, B. Jeandidier, R. Muffels  and J.Yfantopoulos, “ A comparison of poverty in seven European countries and regions using subjective and relative Measures”, Journal of Populaion Economics, 1993, vol. 6, pp. 235--259.

7.             R. Davidson and J. Duclos, “Statistical inference for stochastic dominance and for the measurement of poverty and inequality”, Econometrica, 2000, vol. 68, pp. 1435--1464.

8.             R. Davidson, “Stochastic dominance”, Discussion paper, 2006, Palgrave Macmillan, Canada.

9.             J. Duclos, and A. Arrar, “Poverty and Equity: Measurement, Policy and Estimation with DAD”, Springer Science+Business Media, New york, 2006.

10.           Egyptian Central Agency of Statistics. (1996), “Income, Consumption and Expenditure Research (1995/1996)”, Egyptian Central Agency of Statistics, Cairo, Egypt.

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13.           Egyptian Central Agency of Statistics. (2009), “Income, Consumption and Expenditure Research (2008/2009)”, Egyptian Central Agency of Statistics, Cairo, Egypt.

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19.           H. Levy, Stochastic dominance: Investment decision making underuncertainty, Springer, New York, 2006.

20.           O. Linton, E.  Maasoumi and Y. Whang, “Consistent testing for stochastic dominance under general sampling schemes”, Review of Economic Studies, 2005, vol.72, pp. 735--765.

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27.           S. Sriboonchitta,W. Wong, S. Dhompongsa,  and H. Nguyen,  “Stochastic dominance and applications to finance, risk and Economics”, Taylor and Francis group, LLC, USA, 2010.

28.           K. Villaverde, N.  Albehery, T. Wang, Tonghui and V. Kreinovich,, “Semi - Heuristic poverty measures used by Economists: Justification motivated by Fuzzy techniques”,  IEEE World Congress on Computational Intelligence Conference, 2012.

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Rasi Shamalbhai Bhatol

Paper Title:

Design and Simulation of Microstrip Patch Antenna for RFID Application

Abstract:    This paper presents a new design of a microstrip patch antenna. The slotted antenna is presented for RFID applications. The antenna is simulated using Ansoft HFSS and area of the antenna is 7.92mm x10.92mm. The FR4 substrate is used in this antenna. This is a very compact, high efficiency and simple microstrip patch antenna. This Antenna increases the gain and reduces the complication of design greatly while compared to other slot geometries. This slot can also reduce the size of the patch. The proposed antenna is designed for the 5.8 GHz ISM band.

  Rectangular Microstrip Slotted Antenna (RMSA), High Frequency Simulation Software (HFSS).


1.  Vidya J.S, “Ultra Wide Band Twin Eleven Slot Patch Antenna for Bandwidth Enhancement,” International conference on Communication and Signal Processing, April 3-5, 2013.
2. M. H. Mokhtar.” A Compact Slotted Microstrip Patch Antenna for RFID applications,” Proceeding of the 2013 IEEE International Conference on RFID Technologies and Applications, 4 - 5 September.
3.  M. Jagdish, Rathod, “Comparative Study of Microstrip Patch Antenna for Wireless Communication Application,” International Journal of Innovation, Management and Technology, vol. 1, pp. 194–197, June. 2010.

4.   K.T. Ahamed, B. Hossian, and J. Hossian, “Designing a high bandwidth Patch Antenna and comparison with the former Patch Antennas,” Canadian Journal on Multimedia and Wireless Network.,vol. 2, pp. 29-39, April. 2011.

5.  Constantine A. Balanis, ”Antenna Theory”, John Wiley and Sons Inc., 2005