Archive

Abstract:

Voltage instability is one of the major problems in the transmission line system it causes due to the dynamic load pattern and increasing load demand. Flexible AC transmission systems (FACTS) devices are used to maintain the voltage instability by controlling real and reactive power through the system. In transmission line system, the location and size of the FACTS devices are an important consideration to offer perfect real power flow in the bus system. In this paper, an optimal placement and sizing of the FACTS devices are carried out by combining the Kinetic Gas Molecular Optimization (KGMO) and Grey Wolf Optimization (GWO). There are three different FACTS devices are used in this research, such as Static VAR compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controllers (UPFC). The objective functions considered for the proposed hybrid KGMO-GWO method are installation cost, Total Voltage Deviation (TVD), Line Loading (LL) and real power loss. Moreover, the optimal placement using the hybrid KGMO-GWO method is validated using IEEE 30 bus system. The performance of the hybrid KGMO-GWO method is analyzed by means of TVD, power loss, installation cost and line loading. Additionally, the hybrid KGMO-GWO method is compared with two existing technique named as QOCRO and hybrid KGMO-PSO. The TVD of the hybrid KGMO-GWO is 0.1007 p.u., it is less when compared to the QOCRO and hybrid KGMO-PSO.

Keywords:

Flexible AC Transmission Systems,Grey Wolf Optimization,Kinetic Gas Molecular Optimization,Static VAR Compensator,Thyristor Controlled Series Compensator,Unified Power Flow Controllers,

Refference:

I. Agrawal, R., Bharadwaj, S.K. and Kothari, D.P., “Population based evolutionary optimization techniques for optimal allocation and sizing of Thyristor Controlled Series Capacitor”, Journal of Electrical Systems and Information Technology, vol. 5, pp: 484-501,2018.
II. Balamurugan, K., Muralisachithanandam, R. and Dharmalingam, V., “Performance comparison of evolutionary programming and differential evolution approaches for social welfare maximization by placement of multi type FACTS devices in pool electricity market”, International Journal of Electrical Power & Energy Systems, vol. 67, pp: 517-528, 2015.
III. Canbing, L.I., Liwu, X.I.A.O., Yijia, C.A.O., Qianlong, Z.H.U., Baling, F.A.N.G., Yi, T.A.N. and Long, Z.E.N.G., “Optimal allocation of multi-type FACTS devices in power systems based on power flow entropy,” Journal of Modern Power Systems and Clean Energy, vol. 2, pp: 173-180, 2014.
IV. Sen, D., Ghatak, S.R. and Acharjee, P., “Optimal allocation of static VAR compensator by a hybrid algorithm”, Energy Systems, vol. 10, pp: 677-719, 2019.
V. Dash, S.P., Subhashini, K.R. and Satapathy, J.K., “Optimal location and parametric settings of FACTS devices based on JAYA blended moth flame optimization for transmission loss minimization in power systems. Microsystem Technologies, pp: 1-10, 2019.
VI. Dutta, S., Paul, S. and Roy, P.K., “Optimal allocation of SVC and TCSC using quasi-oppositional chemical reaction optimization for solving multi-objective ORPD problem,” Journal of Electrical Systems and Information Technology, vol. 5, pp: 83-98, 2018.
VII. Ersavas, C. and Karatepe, E., “Optimum allocation of FACTS devices under load uncertainty based on penalty functions with genetic algorithm”, Electrical Engineering, VOL. 99, pp: 73-84, 2017.
VIII. Gitizadeh, M., Khalilnezhad, H. and Hedayatzadeh, R., “TCSC allocation in power systems considering switching loss using MOABC algorithm”, Electrical Engineering, vol. 95, pp: 73-85, 2013.
IX. Ghahremani, E. and Kamwa, I., “Optimal placement of multiple-type FACTS devices to maximize power system loadability using a generic graphical user interface,” IEEE Transactions on Power Systems, vol. 28, pp.764-778, 2012.
X. Hemachandra Reddy K, P. Ram Kishore Kumar Reddy and V. Ganesh, “Optimal Allocation of Multiple Facts Devices with Hybrid Techniques for Improving Voltage Stability”, International Journal on Emerging Technologies,vol. 10,pp. 76-84, 2019.
XI. Mondal, D., Chakrabarti, A. and Sengupta, A., “Optimal placement and parameter setting of SVC and TCSC using PSO to mitigate small signal stability proble,”. International Journal of Electrical Power & Energy Systems, vol. 42, pp: 334-340,2012.
XII. Kavitha, K. and Neela, R. “Optimal allocation of multi-type FACTS devices and its effect in enhancing system security using BBO, WIPSO & PSO,” Journal of Electrical Systems and Information Technology, vol. 5, , pp.777-793, 2018.
XIII. Panda, S., Patil R. N., “Location of Shunt FACTS Controllers for Transient Stability Improvement Employing Genetic Algorithm”, Electric Power Components and Systems, vol. 135, pp: 189-203, 2007.
XIV. Packiasudha, M., Suja, S. and Jerome, J., “A new Cumulative Gravitational Search algorithm for optimal placement of FACT device to minimize system loss in the deregulated electrical power environment”, International Journal of Electrical Power & Energy Systems, vol. 84, pp: 34-46,2017.
XV. Rahimzadeh, and Bina, M.T. “Looking for optimal number and placement of FACTS devices to manage the transmission congestion,” Energy conversion and management, vol. 52, pp.437-446,2011.
XVI. Safari, A., Bagheri, M. and Shayeghi, H., “Optimal setting and placement of FACTS devices using strength Pareto multi-objective evolutionary algorithm” Journal of Central South University, vol. 24, p: 829-839, 2017.

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Abstract:

This paper studies the effect of changing layers arrangement of composite materials (four samples consisting of 8 layers with a change in the arrangement of  layers and composite materials were used glass fibers, carbon fibers and perlon with lamina matrix) on the mechanical properties (yield stress, ultimate stress, Young's modulus, and Poisson's ratio) of the prosthetic below knee socket (BK) by using tensile test device. Also, calculate the (S-N) curves for these samples by using bending fatigue test device to calculate the fatigue life.       The pressure distribution between the (BK)socket and the residual lower limb using pressure sensor and the information on gait cycle was by using force plate on the case study patient with (BK) amputation.       The solid work program to drawn the socket and ANSYS workbench 14.5 was used to analyze and evaluate the fatigue characteristic by observing the maximum stress, total deformation and safety factor.       The results show that the yield stress in the samples 2, 3 and 4 is increased about 18 %, 95%, and 91% respectively more than the standard sample1. While the ultimate stress in the samples 2, 3 and 4 is increased 32%, 89%, and 68% respectively more than the standard sample1, the Young's modulus in the samples 2, 3 and 4 is increased about 5%, 18%, and 12% respectively more than the standard sample1, the Poisson's ratio is increased about 3%, 6%, and 7% respectively more than the standard sample1, and the fatigue life is increased about 23%, 73% and 29% in the samples 2, 3 and 4  respectively more than the standard sample 1.

Keywords:

Composite materials,mechanical properties,fatigue life,below knee socket,

Refference:

I. A. P. Irawan, I. Wayan S, “Tensile and Impact Strength of Bamboo Fiber Reinforced Epoxy Composite as Alternative Materials for above Prosthetic Socket”, International Conference on Sustainable Technology Development, Vol. 2, pp. 109-115, 2012.
II. A. Adawiya .Hamzah, “Vibrational Behavior of Three Floors Structure Equipped with Dampers”, International Journal of Mechanical and Mechatronics Engineering , Vol.17, No.04, 2017.
III. D .Popovic, T .Sinkjaer, “Control of Movement for the Physically Disabled”, Springer Verlag London, 2000.
IV. H. MajidFaidh-Allah, Mahmood W. Saeed and Adawiya A. Hamzah, “Experimental and Numerical Study the Effect of Materials Changing on Behavior of Dental Bur (Straight Fissure) under Static Stress Analysis” Innovative Systems Design and Engineering , Vol.6, No.2, 2015.
V. H .Majid. Faidh-Allah, Zainab A. Abdul Khalik, “Experimental and Numerical Stress Analysis of Involute Splined Shaft”, Journal of Engineering, College of Engineering, University of Baghdad, Vol.18 , No.4 , 2012.
VI. H. SaleelAbood, Majid H. Faidh-Allah, “Analysis of Prosthetic Running Plate of Limb Using Different Composite Materials”, Journal of Engineering, College of Engineering, University of Baghdad, Vol.25, No.12, pp.15-25, 2019.
VII. H. Majid .Faidh-Allah, Adawiya A. Hamzah, “Vibration Analysis of Aircraft Wing under Gust Load”, Journal of Engineering and Applied Sciences, Vol.14, No.11, pp.3571-3574, 2019.
VIII. H. Majid .Faidh-Allah, “Study the Steady-State and Dynamic Problems of the Rotating Blades”, International Journal of Mechanical Engineering and Technology, Vol.9, No.10, pp.548-558, 2018.
IX. H. Majid .Faidh-Allah, “The Temperature Distribution in Friction Clutch Disc under Successive Engagements”, Tribology in Industry, Vol.40, No.1, pp.92-99, 2018.
X. Hamill, J. and Knutzen, K., “Biomechanical Basis of Human Movement”, 2nd edition, Philadelphia: Lippincott Williams & Wilkins, 2003.
XI. K Sethi, P., “Technological Choices in Prosthetics and Orthotics for Developing Countries”, Prosthetic and Orthotics International ,Vol.13, pp.117-124,1989.
XII. Karen Junius, TomVerstraten, “Design of an Actuated Orthosis for Support of the Sound Leg of TransfemoralDysvascular Amputees”, Master Thesis in Department of Mechanical Engineering Vrije Universities Brussel Academic year: 2011 – 2012.
XIII. M. J. Jweeg , S. S. Hasan and J. S. Chiad , “Effects of Lamination Layers on the Mechanical Properties for above Knee Prosthetic Socket”, Eng. & Tech. Journal,Vol.27, No.4, 2009.
XIV. M .MuhammedA., “Experimental Investigation of Tensile and Fatigue Stresses for Orthotic / Prosthetic Composite Materials with Varying Fiber (Perlon, E-Glass and Carbon)”. Arpn Journal of Engineering and Applied Sciences, vol. 11, no. 21, November 2016.
XV. Standard, A. S. T. M. (2003), “Standard Test Method for Tensile Properties of Plastics”, ASTM International. Designation: D, 638, 1-13.
XVI. T. Mustafa Ismail ,Muhsin J. Jweeg and Kadhim K. Resan, “Study of Creep- Fatigue Interaction in the Prosthetic Socket below Knee”, Innovative Systems Design and Engineering , Vol.4, No.5, 2013.

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Abstract:

The incidences of diseases (morbidities) vary across geographic areas. Spatial statistical analysis concerning spread  and  direction  is useful to study  such diseases in the neighborhood. This helps the health provenance for reducing this disease and control spatially it. Many spatial interpolations have employed for predicting the risky diseases based on observed values. In this paper, two methods of the spatial interpolation have studied based on unmeasured values from the same characteristic of spatial data, area-to-point kriging and topological kriging. These methods exploit variogram structure to predict the unmeasured values, then they fit this variogram by one of the parametric variograms. The de-regularization or deconvolution method is iterative and search model of area that reduces the variation between the theoretical semivariogram model and the fitted model for irregular area data. However, it is an approximate method for different regions based on the concept of average distance between irregular areas. Then, area to point kriging method has used using back calculation for approximated irregular areas in topological kriging (top kriging) .The prediction results for top kriging is better than other method. Disease krige map explaining the embedding risk of effective disease from observed frequencies are summarizes and their performances have compared .The goal of this paper is  mapping and exploring the spatial variation and hot spots of district- level disease cases in Iraq country

Keywords:

Geostatistics ,Deconvolution,Change the support,Interpolatio,

Refference:

I. A. Soares et al. (eds.), geo ENV VI – Geostatistics for Environmental Applications, 3-22 , Springer Science& Business Media,vol .15 ,2008.
II. A .Minh, Muhajarine N, Janus M, Brownell M, Guhn M. A review of neighborhood effects and early child development: how, where, and for whom, do neighborhoods matter? Health & place;46:155 -74, 2017.
III. Atkinson, Peter, Jingxiong Zhang, and Michael F. Goodchild. Scale in spatial information and analysis. CRC Press, 2014.
IV. B .Ghosh, Random distances within a rectangle and between two rectangles.Bull. Calcutta Math. Soc. 43, 17- 24, 1951.
V. CA .Gotway, Young LJ , Combining incompatible spatial data. J Am Stat Assoc 97(459):632-648,2002.
VI. Duan, Qingyun, Soroosh Sorooshian, and Vijai Gupta. “Effective and efficient global optimization for conceptual rainfall-runoff models.” Water resources research 28.4: 1015-1031, 1992.
VII. Gotway Crawford C.A., Young L.J. , Change of support: an inter-disciplinary challenge. In: Geostatistics for Environmental Applications. Springer, Berlin, Heidelberg, 2005.
VIII. Gottschalk, Lars, Etienne Leblois, and Jon Olav Skøien. “Distance measures for hydrological data having a support.” Journal of hydrology 402.3-4 ,415-421,2011.
IX. G. Journel, A.., Huijbregts, C.J., Mining Geostatistics. Academic Press, London, UK, 1978.
X. H .Kupfersberger, Deutsch CV, Journel AG Deriving constraints on small-scale variograms due to variograms of large-scale data. Math Geol 30(7):837-852, 1998.
XI. Kyriakidis, P., A, geostatistical framework for area-to-point spatial interpolation. Geograph. Anal. 36 (3), 259 -289,2004 .
XII. N.Cressie, Statistics for Spatial Data. Wiley, a Wiley-Interscience-Publication, New York, NY, 1991.
XIII. O. Skøien, J., Merz, R., Blöschl, G., Top-kriging – geostatistics on stream network s. Hydrol. Earth Syst. Sci. 10, 277- 287, 2006 .
XIV. O .Skoien, J, Bloschl, G., Laaha, G., Pebesma, E., Parajka, J., Viglione, A., Rtop: An R package for interpolation of data with a variable spatial support, with an example from river networks. Computers & Geosciences, 67, 2014.
XV. P .Goovaerts,, “Kriging and semivariogram deconvolution in the presence of irregular geographical units”. Math. Geosci. 40 (1), 101 – 128 , 2008.
XVI. www.unicef.org

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Abstract:

This paper study the effect of Heat Recovery Steam Generator (HRSG) type on the thermal effeicncy  of Integrated Solar Combined Power Plant. The aim of this work is to improve thermal effeicncy of Integrated Solar Combined Cycle System (ISCCS). In this plant, recovery the largest possible amount of thermal energy in flue gases of gas power plants, to produce steam, and adopting solar energy to produce hot water. The efficiency of Solar Integrated Steam Power Plant can be increased from 40%  for case A to 50% for case B, due to increased  the aviable heat of HRSG from 168.27 MW to306 MW. Also, thermal environmental pollution can reduced  from 148.36 ℃ to 68.97 ℃.

Keywords:

Heat Recovery Steam Generator,Solar Energy,Integrated Solar Combined Power Plant,

Refference:

I. AL-Zafaraniyah Gas Power Plant / Baghdad, Iraq.
II. Cavalcanti E. J. C.,” Exergoeconomic and exergoenvironmental analyses of an integrated solar combined cycle system” renewable and sustainable energy reviews, V.67, PP.507-519, 2017.
III. E.Kabalci ,” Design and analysis of a hybrid renewable energy plant with solar and wind power”, energy conversion and management, V.xxx, PP.xxx-xxx, 2013.
IV. F. Calise , Accadia M. D., Libertini L. and Vicidomini M. ,” Thermoeconomic analysis of an integrated solar combined cycle power plant”, energy conversion and management, V.171, PP.1038-1051, 2018.
V. G .Khankari, and Karmakar S., ” power generation from flue gas waste heat in a 500 MW subcritical coal-fired thermal power plant using solar-assisted Kalina cycle system 11“, applied thermal engineering, V.xxx, PP.xxx-xxx, 2018.
VI. G. Bonforte, Buchgeister J., Manfrida G. and Petela K., ” Exergoeconomic and Exergoenvironmental analysis of an integrated solar gas turbine/combined cycle power plant “, energy, V.152, PP.xxx-xxx, 2018.
VII. G. Manente, Rech S., and Lazzaretto A.,” optimum choice and placement of concentrating solar power technologies in integrated solar combined cycle systems “renewable energy, V.96, PP.172-189, 2016.
VIII. H .Nezammahalleh, F. Farhadi, and Tanhaemami M., ” conceptual design and techno-economic assessment of integrated solar combined cycle system with DSG technology “, solar energy, V.84, PP.1696-1705, 2010.
IX. H.Nezammahalleh, Farhadi F., and Tanhaemami M.,” conceptual design and techno-economic assessment of integrated solar combined cycle system with DSG technology “, solar energy, V.84, PP.1696-1705, 2010.
X. J .Potter ,”Power plant , Theory and design “, John wiley pub,1956.
XI. N. Khan M,and Tlili I., “ Innovative thermodynamic parametric investigation of gas and steam bottoming cycles with heat exchanger and heat recovery steam generator: Energy and exergy analysis”, Energy Reports, V4, PP. 497-506, 2018.
XII. Q .Yan, Hu E., Yang Y. and Zhai R., ” Evaluation of solar aided thermal power generation with various power plants”, International journal of energy research, V.35, PP.909-922, 2011.
XIII. S .Jamel M., Shamsuddin A.H., and Abd- Rahman A.,” advances in the integration of solar thermal energy with conventional and non-conventional power plants”, renewable and sustainable energy reviews, V20, PP.71-81, 2013.
XIV. Y. Li and Xiong Y., ” Thermo-economic analysis of a novel cascade integrated solar combined cycle system”, energy, V145, PP.116-127,2018.
XV. Y.Li and Xiong Y.,” Thermo-economic analysis of a novel cascade integrated solar combined cycle system”, energy, V145, PP.116-127, 2018.

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Abstract:

In this paper we investigate some fundamental results on Jordan ideals, ∗-Jordan ideals, derivations and generalized derivations and hence establish some commutativity results for a certain class of semirings with involution

Keywords:

Inverse semirings,MA-semirings,Generalized derivations,*Jordanideals,

Refference:

I. B.E. Johnson, Continuity of derivations on commutative Banach algebras, Amer. J. Math.,vol. 91,pp: 1-10, 1969.
II. C. Lanski, Commutation with skew elements in rings with involution, Pacific J. Math., vol. 83, no. 2,pp: 393-399, 1979.
III. C.E. Rickart,Banach algebras with an adjoint operation, Ann. Math. (2), vol. 47, no. 3, pp:528-550, 1946.
IV. D.A. Jordan,On the ideals of a Lie algebra of derivations, J. London Math. Soc., vol. 33,no. 2,pp:33-39, 1986.
V. E.C. Posner, Derivations in prime rings, Proc. Amer. Math. Soc., vol. 8, pp:1093-1100, 1957.
VI. H.E. Bell, W. S. Martindale, Centralizing mappings of semiprime rings, Canad. Math. Bull., vol. 30, pp:92-101, 1987.
VII. H.J. Bandlet, M. Petrich, Subdirect products of rings and distributive attics, Proc. Edinburgh Math. Soc., vol. 25, pp:135-171, 1982.
VIII. I.E. Segal, Irreducible representations of operator algebras, Bull. Amer. Math. Soc., vol. 53, pp:73-88, 1947.
IX. I.N. Herstein, Topics in ring theory, Chicago lectures in mathematics, 1969.
X. I.N. Herstein,Rings with involution, University of Chicago, 1976.
XI. J. Berger, I.N. Herstein and J. W. Kerr, Lie ideals ana derivations of prime rings, J. Algebra, vol. 71, pp: 259-267, 1981.
XII. K.I. Beidar, W.S Martindale On functional identities in prime rings with involution, J. Algebra, vol. 203, no.2,pp:491-532, 1998.
XIII. L. Oukhtite, On Jordan ideals and derivations in rings with involution, Comment. Math. Univ. Carolin., 51(3) (2010), 389-395.
XIV. L. Oukhtite, A. Mamouni, Generalized derivations centralizing on Jordan ideals of rings with involution, Turk. J. Math., 38 (2014), 225-232.
XV. L. Oukhtite, A. Mamouni, Derivations satisfying certain algebraic identities on Jordan ideals, Arab. J. Math., vol. 1, no. 3, pp:341-346, 2012.
XVI. L. Oukhtite, Posner’s second theorem for Jordan ideals in rings with involution, Expos. Math., vol. 29, no. 4, pp:415-419, 2011.
XVII. Liaqat Ali, M. Aslam and Yaqoub Ahmed Khan, Commutativity of semirings with involution, Asian-European Journal of Mathematics, (2019) https://doi.org/10.1142/S1793557120501533
XVIII. Liaqat Ali, M. Aslam and Yaqoub Ahmed Khan, On Jordan ideals of inverse semirings with involution, Indian Journal of Science and Technology, vol. 13, no. 4, pp:430–438, 2020.
XIX. Liaqat Ali, M. Aslam and Yaqoub Ahmed Khan, On Posner’s second theorem for semirings with involution, Submitted.
XX. M. Bresar, On the distance of the composition of two derivations to the generalized derivations, Glasg. Math. J., vol. 33, no. 1, pp:89-93, 1991.
XXI. M.A. Javed, M. Aslam and M. Hussain, On condition (A2) of Bandlet and Petrich for inverse semirings, Int. Math. Forum, vol. 7, no. 59, pp:2903-2914, 2012.
XXII. M.N. Daif, Commutativity result for semiprime rings with derivations, Int. J. Math. Math. Sci., vol. 21, no. 3, pp:471-474, 1998.
XXIII. R. Awtar, Lie and Jordan structure in prime rings with derivations, Proc. Am.Math. Soc., vol. 41 ,pp:67-74, 1973.
XXIV. S.M.A. Zaidi, M. Ashraf, S. Ali, On Jordan ideals and left (θ,θ)-derivations in prime rings, Int. J. Math. Math. Sci. vol. 2004, no. 37, pp:1957-1964, 2004.
XXV. Sara Shafiq, M. Aslam, M.A Javed, On centralizer of semiprime inverse semiring, DiscussionesMathematicae, General Algebra andApplications, vol. 36, pp:71-84, 2016.
XXVI. T.K Lee, On derivations of prime rings with involution, Chin. J. Math., vol. 20, no. 2, pp:191-203, 1992.
XXVII. Yaqoub Ahmed Khan, M. Aslam and Liaqat Ali, Commutativity of additive inverse semirings through f(xy) = [x,f(y)], Thai J. of Math., Special Issue,pp:288-300, 2018.

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Abstract:

Drilling in bone is an inevitable operation performed to join damaged bone during accidents. Drilling facilitates use of screws and plates and in this immobilisation of bone is achieved which is a primary requirement for natural bone growth and re-joining. To study bone drilling, threshold temperature [VI] has to be the prime concern and accordingly drilling parameters and specifications are to be selected otherwise irreversible[III] bone damage can occur. In this study, drilling process is conducted on a sheep bone and optimization of drilling parameters is suggested using Taguchi and ANOVA method, so that the cell damage can be on lower side. To control thermal necrosis an intelligent drilling machine is also proposed.

Keywords:

Bone drilling,threshold temperature,optimization,

Refference:

I. Augustin G, Davila S, Udiljak T, Vedrinal DS, Bagatin D. (2009) .Determination of spatial distribution of increase in bone temperature during drilling by infrared thermography: preliminary report. Archives of Orthopaedic and Trauma. Surgery,129(5):703–9.

II. Augustin G., S. Davila et al. (2008). Thermal osteonecrosis and bone drilling parameters revisited. Archives of Orthopaedic & Trauma Surgery.128(1): 71-77.

III. Bonfleld,W., Li,C.H.,. The temperature dependence of the deformation of bone J. Biomechanics.Vol I. pp. 323-329 PergamonPress..Printed in Great Britain.

IV. Brisman D.L., (1996).The effect of speed, pressure, and time on bone temperature during the drilling of implant sites. International Journal of Oral and Maxillofacial Implants, 11(1):35–7.

V. Davidson SRH, James D.F., (2000).Measurement of thermal conductivity of bovine cortical bone. Medical Engineering and Physics, 22(10):741–7.

VI. Eriksson, R. A. and Albrektsson,T . (1984).The effect of heat on bone regeneration: an experimental study in the rabbit using the bone growth chamber. Journal of Oral & Maxillofacial Surgery, 42(11): 705-711.

VI. Hillery M.T., Shuaib I. (1999). Temperature effects in the drilling of human and bovine bone. Journal of Materials Processing Technology. 92-93:302–8.

VIII. Jill E. Shea, (2002). Experimental Confirmation of the Sheep Model for Studying the Role of Calcified Fibrocartilage in Hip Fractures and Tendon Attachments,wiley-liss,inc.The anatomical record. 266:177–183,

IX. JoséCaeiroPotes, et.al, (2008).The Sheep as an Animal Model in Orthopaedic Research, Experimental pathology and health sciences;2(1):29-32,

X. Karaca, F., Aksakalb, B.,Komc,M.,. (2011). Influence of orthopaedic drilling parameters on temperature and histopathology of bovine tibia: An in vitro study, Medical Engineering & Physics, 33:1221– 1227.

XI. Lucia Martini, et.al, (2001). Sheep Model in Orthopaedic Research: A Literature Review,American Association for Laboratory Animal Science, August. vol.51.No. 4: Page 292-299.

XII. Lundskog,J., (1972).Heat and bone tissue, Scand. Journal of Plastic and Reconstructive Surgery, Sup.

XIII. Matthews LS, Green CA, Goldstein SA. (1984). The thermal effects of skeletal fixation pin insertion in bone. Journal of Bone and Joint Surgery. 66(7):1077–83.

XIV. Mortiz,A.R., Henerique,F.C., (1947).The relative importance of time and surface temperature in the causation of cutaneous burns, American Journal of Physiology. 23: 695-719.

XV. Nam O., Yu W., Choi M.Y., Kyung H.M. (2006), Monitoring of bone temperature during osseous preparation for orthodontic micro-screw implants: effect of motor speed and pressure. Key Engineering Materials, 321–323:1044–7.

XVI. Natali C., P. Ingle et al. (1996).Orthopaedic bone drills-can they be improved? Temperature changes near the drilling face. Journal of Bone and Joint Surgery.78-B (3): 357-362.

XVII. Ohashi H., Therin M., Meunier A., Christel P., (1994).The effect of drilling parameters on bone. Journal of Material Science: Materials in Medicine.5(4):225–31.
XVIII. Roy R., (2001).Design of experiments using the Taguchi approach: 16 steps to product and process improvement. John Wiley & Sons, New York, ISBN: 0471361011

XIX. Saha S, Pal S, Albright J. (1982), surgical drilling: design and performance of an improved drill. Transactions of ASME, Journal of Biomechanical Engineering.104(3):245–52.

XX. Sharawy M., Misch C.E., Weller N., Tehemar S., (2002). Heat generation during implant drilling: the significance of motor speed. Journal of Oral and Maxillofacial Surgery,; 60(10):1160–9.

XXI. Toews A. R., J. V. Bailey et al. (1999), Effect of feed rate and drill speed on temperatures in equine cortical bone. American Journal of Veterinary Research. 60(8): 942-944.

XXII. Tony M. Keaveny, Bone mechanics Source: standard handbook of biomedical engineering and design. Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright © 2004

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Abstract:

Nowadays water scarcity is a major threat to our society, in the name of development, depletion of water increases. The developing technologies had decreased the wealth of the soil. Advancement in agriculture brought artificial fertilizers to eradicate diseases, it turns the soil infertile. This could be overcome by an efficient method called “HYDROPONICS”. This plantation had brought smartness in agriculture. By this, we could achieve lesser space, less man power and 10% of water consumption compared to conventional method. The monitoring and control techniques could be  implemented using Internet of Things (IoT) for proper and advance maintenance.   The major parameters to be handled in Hydroponics are monitoring temperature, humidity, PH of water, water flow, nutrition level, pump motor speed and efficiency. The collected data are uploaded into cloud using IoT module. The data  can be processed in cloud or local server. Remote user can also control the system through Android/Web Application. The present work focused on the energy meter automation using Arduino. When the load is given to the energy meter the CAL led blinks and the blinking pulse is triggered using Opto coupler (4N35). The 5v impulse is given as digital HIGH input to any one of the Arduino digital pin. The pulse is counted in the Arduino and the power calculation  is processed in the program.

Keywords:

Cloud,Hydroponics,Internet of Things,PH,Web Application ,

Refference:

I. Abdur Rahim Biswas and RaffaeleGiaffreda, “IoT and Cloud Convergence: Opportunities and Challenges”, 2014 IEEE World Forum on Internet of Things (WF-IoT).
II. Asumadu, J.A., Smith, B., Dogan, N.S., Loretan, P.A., Aglan, H.,
Microprocessor-based instrument for hydroponic growth chambers used in ecological life support systems Instrumentation and Measurement Technology, IEEE Instrumentation and Measurement Technology Conference, June 4-6, 1996.
III. K. Kalovrektis, Ch. Lykas, I. Fountas, A. Gkotsinas, I.Lekakis,
Development and application embedded systems and wireless network of sensors to control of hydroponic greenhouses, International Journal of Agriculture and Forestry 2013, 3(5): pp. 198-202.
IV. Mamta D. Sardare, Shraddha V. Admane, A review on plant without soil hydroponics‘, IJRET: International Journal of Research in Engineering and Technology ISSN: 2319-1163, Volume: 02 Issue: 03, Mar-2013
V. NiveditaWagh, VijendraPokharkar, AvinashBastade, Priyanka
Surwase, UmeshBorole,PLC based automated hydroponic system‘, IJSTE International Journal of Science Technology & Engineering, Volume 2, Issue 10, April 2016.
VI. Rahul Nalwade, Mr.Tushar Mote, “Hydroponics Farming”, pg: 647, International Conference on Trends in Electronics and Informatics ICEI 2017
VII. Rajeev lochan Mishra1 and Preet Jain, ―Design and implementation of automatic hydroponics system using ARM processor, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 4,Issue 8, August 2015.
VIII. S.S.Kalamkar, “Urbanisation and Agricultural Growth in India”, Indian Journal Of Agri. Econ. Vol. 64, No.3, July-Sept. 2009.

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Abstract:

This paper proposes an approach to study the effect of faulty array element on the accuracy of the parameter estimation of direction of arrival of the plain waves and their amplitudes from sources that are considered to be far field sources. In this approach we require only one snapshot. The cost function is developed for heuristic computation using genetic algorithm (GA). Cost function is based on  norm of the difference between actual observation vector and the constructed vector plus the correlation between the two normalized vectors. The results have been given for different length of array i.e. 10, 15 and 20.Longer array is able to minimize the effect of faulty array element.

Keywords:

Direction of Arrival,Uniform Linear Array,Parameter Estimation,Faulty Array,

Refference:

I. B. Ottersten and T. Kailath, “Direction-of-arrival estimation for wide-band signals using the ESPRIT algorithm,” IEEE Trans. Acoust., vol. 38, no. 2, pp. 317–327, 1990.
II. F. Zaman, I. M. Qureshi, A. Naveed, and Z. U. Khan, “Real time direction of arrival estimation in noisy environment using particle swarm optimization with single snapshot,” Res. J. Appl. Sci. Eng. Technol., vol. 4, no. 13, pp. 1949–1952, 2012.
III. F. Zaman, I. M. Qureshi, A. Naveed, and Z. U. Khan, “Joint estimation of amplitude, direction of arrival and range of near field sources using memetic computing,” Prog. Electromagn. Res. C, vol. 31, pp. 199–213, 2012.
IV. F. Zaman, I. M. Qureshi, A. Naveed, J. A. Khan, and R. M. A. Zahoor, “Amplitude and directional of arrival estimation: comparison between different techniques,” Prog. Electromagn. Res. B, vol. 39, pp. 319–335, 2012.
V. F. Zaman, J. A. Khan, Z. U. Khan, and I. M. Qureshi, “An application of hybrid computing to estimate jointly the amplitude and direction of arrival with single snapshot,” in Proceedings of 2013 10th International Bhurban Conference on Applied Sciences & Technology (IBCAST), 2013, pp. 364–368.
VI. J. A. Khan, M. A. Z. Raja, and I. M. Qureshi, “Numerical treatment of nonlinear Emden–Fowler equation using stochastic technique,” Ann. Math. Artif. Intell., vol. 63, no. 2, pp. 185–207, 2011.
VII. M. Mouhamadou, P. Vaudon, and M. Rammal, “Smart antenna array patterns synthesis: Null steering and multi-user beamforming by phase control,” Prog. Electromagn. Res., vol. 60, pp. 95–106, 2006.
VIII. M. Mukhopadhyay, B. K. Sarkar, and A. Chakraborty, “Augmentation of anti-jam gps system using smart antenna with a simple doa estimation algorithm,” Prog. Electromagn. Res., vol. 67, pp. 231–249, 2007.
IX. M. A. Ur Rehman, F. Zaman, I. M. Qureshi, and Y. A. Sheikh, “Null and sidelobes adjustment of damaged array using hybrid computing,” Proc. – 2012 Int. Conf. Emerg. Technol. ICET 2012, pp. 386–389, 2012.
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Abstract:

This work aims on improving the dynamic time response of closed-loop Bootstrap controlled SVM inverter (BSVMI) with PI, FOPID and FLC. In this work the simulink model of FLC based ZVS bootstrap SVM inverter system is discussed. Bootstrap converter is a popular device within the family of power Electronics device. The SVM inverter is used with voltage source inverter (VSI) and the switching pulses are given using FLC controller. The ZVS bootstrap converter is used for reduction of switching losses. The simulation results are presented to find the effect of BSVMI using FLC. The simulation results with PI, FOPID and FLC Controller based BSVMI are compared and the consequent time-domain parameters are presented. The results specify that FLC Controller system has enhanced response than PI and FOPID controlled system

Keywords:

FLC,Bootstrap,SVM,Cloased Loop,Dynamic reponse,

Refference:

I. Ayyanar R and Mohan N “Novel soft-switching DC-DC converter with full ZVS-range and reduced filter requirement. I: Regulated-output applications,” IEEE Trans. Power Electron., Vol. 16, No. 2, pp. 184-192, Mar. 2001.
II. Cavalcanti M.C, E.R.C. da Silva, A.M.N Lima, C.B. Jacobina, R.N.C.Alves ; “Reducing losses in three-phase PWM pulsed DC-link voltagetype inverter systems,” IEEE Transactions on Industry Applications, Vol. 38 , No.4 , pp. 1114 – 1122, 2002.
III. CelanovicN. and D. Boroyevich, “A fast space vector modulation algorithm for multilevel three phase converters,” IEEE Trans. Ind. Appl., Vol. 37, No. 2, pp. 637 – 641, Feb. 2001.
IV. Chu E. H, X. T. Hou, H. G Zhang, M. Y. Wu, and X. C. Liu, “Novel zero-voltage and zero-current switching (ZVZCS) PWM three-level DC/DC converter using output coupled inductor,” IEEE Trans. Power Electron., Vol. 29, No. 3, pp. 1082-1093, Mar. 2014.
V. Chen T. F and S. Cheng, “A novel zero-voltage zero-current switching full-bridge PWM converter using improved secondary active clamp,” IEEE International Symposium on Industrial Electronics, Montreal, pp. 1683-1687, 2006.
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Abstract:

The present investigation adoptsComputationalFluid Dynamics CFD to analyze the problem of forced convection cooling of electronic equipment equipped with a heat sink, including inclination and vibration effects. Two fans were usedto circulate the air inside the computer chassis. Three main components on the motherboard were used;CentralProcessorUnit (CPU), North Bridge, and South Bridge.These components generate heat at the rate of 3750, 2500, and 2222.22kW/ respectively. Three different types of heat sink were used for CPU, these are: plate heat sink, radial heat sink without core,and radial heat sink with core.Theother two main components on the motherboardused the same standard heat sink. The two fans are operated with different cases to specify the suitable operation. Inclination for the computer chassis and motherboard with vibration influence was also investigated. The power dissipation, fan flow rate, and ambient temperature are fixed. The results show that the radial heat sink with core enhances the heat transfer by reducing the temperature of the CPU. Also the influence of vibration has more effect in case of without heat sink, for other cases the influence of vibration is not affected in the investigated range. The effect of inclination angle for computer chassis also is not affected, just when the mother board inclination by  from top edge with vertical plane, the temperature reduction approximately 18  in case without heat sink,  4.8 with plate heat sink on CPU, 1  in case with radial heat sink. The CFD analysis was validated with a thermal profile for real operation CPU, the results show good agreement with a mean deviation of (0.023). A radial heat sink with core reduce the temperature more than 114.5 compared without heat sink on CPU case.

Keywords:

CFD,Forced Convection,Inclination and Vibration,Electronic Equipment Cooling,Heat Sink,

Refference:

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III. Cengel Y.A. Heat transfer a practical approach (MGH, 2002)

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VII. GeorgiosBalafas, “polyhedral mesh generation for CFD-analysis of complex structures”, master thesis for the master of science program computational mechanics,2014.

VIII. HibaMudhafarHashim , Ihsan Y. Hussain, ” Natural Convection Cooling of PCB Equipped with Perforated Fins Heat Sink including Inclination and Vibration Effects”,JMCMS,2019.

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