Journal Vol – 15 No -4, April 2020

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.
X. Cheng and Y. Hua, “Further study of the pencil-MUSIC algorithm,” IEEE Trans. Aerosp. Electron. Syst., vol. 32, no. 1, pp. 284–299, 1996.
XI. Y. Hua, T. K. Sarkar, and D. Weiner, “L-shaped array for estimating 2-D directions of wave arrival,” in Proceedings of the 32nd Midwest Symposium on Circuits and Systems, 1989, pp. 390–393.
XII. V. S. Kedia and B. Chandna, “A new algorithm for 2-D DOA estimation,” Signal Processing, vol. 60, no. 3, pp. 325–332, 1997.
XIII. Y. A. Sheikh, F. Zaman, I. M. Qureshi, and M. Atique-ur-Rehman, “Amplitude and direction of arrival estimation using differential evolution,” in 2012 International Conference on Emerging Technologies, 2012, pp. 1–4.
XIV. Y. Wu, G. Liao, and H.-C. So, “A fast algorithm for 2-D direction-of-arrival estimation,” Signal Processing, vol. 83, no. 8, pp. 1827–1831, 2003.
XV. Z. U. Khan, A. Naveed, I. M. Qureshi, and F. Zaman, “Independent null steering by decoupling complex weights,” IEICE Electron. Express, vol. 8, no. 13, pp. 1008–1013, 2011.

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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.
VI. Govindaraj T and B.Gokulakrishnan, “Simulation of PWM based AC/DC Converter control to improve Power Quality,” International Journal of Advanced and Innovative Research.ISSN: 2278-7844, Dec-2012, pp524-533.
VII. Govindaraj T, RasilaR,”Development of Fuzzy Logic Controller for DC – DC Buck Converters”, International Journal of Engineering TechsciVol 2(2), 192-198, 2010.
VIII. Gupta A. K, and A. M. Khambadkone, “A space vector PWM scheme for multilevel inverters based on two-level space vector PWM,” IEEE Trans. Ind. Electron., vol. 53, no. 5, pp. 1631–1639, Oct. 2006.
IX. Halasz S, B.T. Huu, A. Zakharov ;“Two-phase modulation technique for three-level inverter-fed AC drives,” IEEE Transactions on Industrial Electronics, Vol. 47, No.6, pp.1200 – 1211, 2000.
X. Hideaki Fujita, Ryo Suzuki : “A three-phase solar power conditioner using a single-phase PWM control method,” IEEJ Trans. IA, Vol. 130, No.2, pp.173-180, 2010.
XI. Haifeng Lu, WenlongQu, Xiaomeng Cheng, Yang Fan, Xing Zhang : “A Novel PWM Technique With Two-Phase Modulation,” IEEE Trans. On Power Electronics, Vol. 22, No.6, pp.2403-2409, 2007.
XII. Jin K., X. Ruan, and F. Liu, “An improved ZVS PWM three-level converter,” IEEE Trans. Ind. Electron., vol. 54, no. 1, pp. 319–329, Feb. 2007.
XIII. LingaSwamy. R and Satish Kumar. P (2008), ‘Speed control of space vectored modulated inverter driven induction motor’, proceedings of the International Multi conference of engineers and computer scientist, vol.2.
XIV. MousaviA and G. Moschopoulos, “A new ZCS-PWM fullbridge DC–DC converter with simple auxiliary circuits,” IEEE Trans. Power Electron., Vol. 29, No. 3, pp. 1321-1330, Mar. 2014.
XV. Ruan X. and Y. Yan, “A novel zero-voltage and zero current- switching PWM full-bridge converter using two diodes in series with the lagging leg,” IEEE Trans. Ind. Electron., Vol. 48, No. 4, pp. 777-785, Aug. 2001.
XVI. Szychta E., “ZVS operation region of multi resonant DC/DC boost converter”, Journal of Advances in Electrical and Electronic Engineering, Faculty of Electrical Engineering, Vol.6, No.2, 2007, Zilina University, pp. 60-62.
XVII. Sefa I., N. Altin, S. Ozdemi, and O. Kaplan, “Fuzzy PI controlled inverter for grid interactive renewable energy systems,” IET RenewablePower Generation, vol. 9, no. 7, pp. 729-738, 2015.
XVIII. Tabisz W.A., Lee F.C., ”DC analysis and design of zero-voltage switched multi-resonant converters”, IEEE 20th Annual Power Electronics Specialists Conference, PESC ’89, vol. 1, 1989, p. 243 – 251.
XIX. Tattiwong K. and C. Bunlaksananusorn, “Analysis design and experimental verification of a quadratic boost converter,” in TENCON 2014 – 2014 IEEE Region 10 Conference, Oct 2014, pp. 1–6.
XX. Taniguchi K., H. Irie ; “Trapezoidal modulating signal for three-phase pwm inverter,” IEEE Transactions on Industrial Electronics, Vol. 33 , No. 2, 193 – 200, 1986.
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XXII. Wai R.-J., M.-W. Chen, and Y.-K. Liu, “Design of adaptive control and fuzzy neural network control for single-stage boost inverter,” IEEE Trans. Ind. Electron., vol. 62, no. 9, pp. 5434-5445, 2015.
XXIII. Zhou K, D. Wang,(2002),‘Relationship between Space Vector Modulation and three phase carrier-based PWM: A comprehensive analysis’, IEEE Trans. Ind. Elec. Vol. 49,pp 186-196.

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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:

I. ANSYS FLUENT, version 14.5, ANSYS Inc. 2013, “fluent 14.5 users guide”, 2013.

II. C.B.Baxi, and A.RamachAndran, “effect of vibration on heat transfer from spheres”, journal of heat transfer, 2016.

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

IV. EmreOzturk, ”CFD analysis of heat sinks for CPU cooling with fluent”, thesis submitted to the graduate school of natural and applied sciences, Middle East technical university, 2004.

V. Farouq Ali S. GDHAIDH, “heat transfer characteristics of natural convection within an enclosure using liquid cooling system”, submitted for the degree of doctor of philosophy, 2015.

VI. Fluent user services center, www.fluentusers.com accessed on septemper,2019.

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.

IX. Intel Celeron, D processor in the 775-Land LGA package for embedded applications data sheets.

X. J. M. Jalil, E.H.Ali and H.H.Kurdi, “numerical and experimental study of CPU cooling with finned heat sink and different P.C.Air passages configurations”, Al-Nahrain journal for engineering sciences, vol.21, No.1, pp.99-107, 2018.

XI. J.S Chiang, S.H.Chuang, Y.K.Wu, H.J Lee, “numerical simulation of heat transfer in desktop computer with heat generating components”, international communication in heat and mass transfer 32 (2005) 184-191.

XII. Jalal M. Jalil, Ekbal H. Ali and Hiba H. kurdi, “numerical and experimental study of cooling in desktop computer with block heat sink”, engineering and technology journal, vol.36, part A, No.4, PP.430-438, 2018.

XIII. K. Sreenivasan and A.Ramachandran, “effect of vibration on heat transfer from a horizontal cylinder to a normal air stream”, int.J.Heat mass transfer, Vol.3, pp.60-67, pergamon press, 1961.

XIV. MarcinSosnowski, JaroslawKrzywanski, Karolina G rabowska and RenataGnatowska, “polyhedral meshing in numerical analysis of conjugate heat transfer”, EPJ web of conferences 180, 02096 (2018).

XV. N.D etal,”heat induced vibration of a rectangular plate” journal of engineering for industry, 1974.

XVI. P.K.Nag and A.Bhattacharya, “effect of vibration on natural convection heat transfer from vertical fin arrays”, letters in heat and mass transfer, vol.9, pp.487-498, 1982.

XVII. Robert Lemlich, “effect of vibration on natural convective heat transfer”, industrial and engineering chemistry, 1955.

XVIII. S. Kong Wang, Juin Haw Hu and Chun-HsienKuo, “passive enhancement of heat dissipation of desktop computer chassis”, engineering applications of computational fluid mechanics, vol.4, No.1, pp.139-149, 2010.

XIX. SelinArodag, UtkuOlgun, FatihAkturk and BurcuBasibuyuk,”CFD analysis of cooling of electronic equipment as an undergraduate design project”,2009

XX. Wu- Shung Fu, and Bao-Hong Tong, “numerical investigation of heat transfer from a heated oscillating cylinder in cross flow”, international journal of heat and mass transfer, 45(2002) 3033-3043.

XXI. Wu-Shung Fu, and Chien-Ping Huang, “effects of a vibrational heat surface on natural convection in a vertical channel flow”, international journal of heat and mass transfer 49(2006) 1340-1349.

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Abstract:

Artificial Intelligence (AI) technology has been adopted rapidly in the industry. Various research initiatives have been carried out to innate the AI system characteristics as humans. In our concept paper [VI] we disclosed the “Reflex layer” to mimic human systems. A reflex layer would have the ability to differentiate the repetitive stimuli, its related responses and ability to process this through a separate layer. We discussed the key characteristics of reflex features of the following AI capabilities:

• The vision interface
• The audio interface
• The kinematic interface
• The sheath interface
• The core layer

   In this paper we baseline the scope to core and kinematic interface; elaborate key characteristics, provide solutions and results.  

Keywords:

Artificial Intelligence,Distributed Artificial Intelligence,Reflex AI,

Refference:

I. Anna Melamed. “Distributed Systems Management on Wall Street- AI Technology needs”
II. B Thuraisingham, J Larson “ AI applications in Distributed System Design issues”
III. D Verma, G Bent “Policy Enabled Caching for Distributed AI”. 2017 IEEE International Conference on Big Data (BIGDATA)
IV. Du-Mim Yoon, Joo-Seon Lee, Hyun-SuSeon, Jeong-Hyeon Kim, Kyung-Joong Kim*. “Optimization of Angry Birds AI Controllers with Distributed Computing”. IEEE CIG 2015, Tainan, Taiwan August 31, 2015 – September 2, 2015
V. E Oyekanlu, K Scoles “Towards Low-Cost, Real-Time, Distributed Signal and Data Processing for Artificial Intelligence Applications at Edges of Large Industrial and Internet Networks”. 2018 IEEE First International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)
VI. Gandhi Sivakumar, G. Arumugam, “The Facets of Distributed And Artificial Intelligence”, Volume8, Issue 12, December 2019 Edition, International Journal of Scientific & Technology Research
VII. JSR Jang, “Self- learning fuzzy controllers based on temporal back propagation”
VIII. Sean Martin, Andrew slade “A methodology for distributed AI and its applicability for Data fusion applications”
IX. YAO Ping-xiang, FENG Wen-xian “DESIGN OF DISTRIBUTED MARINE AISCOMMUNICATION MECHANISM AND INTEGRATED MONITORING PLATFORM”
X. Z. A. Shah1, T. AbdulQayyum2, Dr. S. I. A. Shah “A Distributed Approach for Solving the Position Inverse Kinematics of Mobile Parallel Manipulators”, 2014 International Conference on Robotics and Emerging Allied Technologies in Engineering (iCREATE) Islamabad, Pakistan, April 22-24, 2014

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Abstract:

Human activity recognition through smartphones is now beneficial for humans to recognize their daily activities. Many of the researches are introduced for recognition of activities but somehow the performance of the classifiers is low because of different problems with the data or the classifiers. This research study offers a method to achieve the best performing classifiers. The comparative analysis held between the supervised and ensemble learning classifiers. Based on the best performing classifier, a system is also introduced in this study. We evaluate the method by using two publicly available datasets of human activities recognition acquired from UCI Machine Learning repository. One is UCI-Human Activity Recognition and the second is Smartphone-Based Recognition of Human Activities and Postural Transitions. The activities selected for this research study are Walking, Standing, Sitting, Laying, Downstairs and Upstairs. These input signals are a 3-dimensional raw form of data that was difficult to handle. The Principle Component Analysis (PCA) technique is used to reduce the dimensionalities of the data features and extract the most substantial data features for the classification of human activities. A comparison is performed between the different supervised and ensemble machine learning classifiers on the selected datasets. The supervised learning classifiers that we used are Gaussian Naïve Bayes, K-Nearest Neighbor, and Logistic Regression while the ensemble learning classifiers are Random Forest and Gradient Boosting. The achieved result shows that the Logistic Regression is more accurate as compared to other selected classifiers in this study for human activity recognition. The higher accuracy rate of Logistic Regression is 96.1% for UCI-HAR and 94.5% for HAPT dataset among all the compared classifiers.

Keywords:

UCI-HAR dataset,HAPT dataset,Smartphones,Accelerometer and gyroscope Sensors,Classifiers,HAR,

Refference:

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Abstract:

Face analysis is a requisite notion for dissimilar appeal allied to artificial intelligence has made possible for Classification of Gender. Facial Data images are still an arduous task for biometric systems due to diverse expressions, dimensions, pose, illustrations and age in facial and other affiliated images includes dissimilar object label classifications. In this paper, SIFT Probabilistic Fuzzy C-means Clustering Approach (SPFCA) proposed to intensify the stratification methodology in object classification for dissimilar images using GSVM. This approach extremely used for recognition and classification of an object due to its fundamental properties which make decorous contrasting object classification in divergent types of robust in facial and other related images. SPFCA is robust clustering approach to diminish uproar insensitivity and assists to group the vicinity ages, male, female and objects. It also assists to find a solution for coinciding cluster complications which may face preceding clustering approaches. Consequently the proficiency can also be used to increase the comprehensive robustness of face recognition and multi-label object classification system and the result increases its invariance and make it a reliably passable biometric.

Keywords:

Object classification,fuzzy c-means clustering,Eigenvalues,shape,corner,wavelet transform,face recognition ,principal component analysis,

Refference:

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Abstract:

Joining of heat-treated alloys(AA6061-T6) by Welding process often results a deterioration of mechanical properties because of the coarsening and dissolution of the strengthening precipitates(Mg₂Si,Al₃FeSi,Al₁₂FeSi) at the weld nugget. However, its scares the applications of AA6061-T6 alloy. In order to enhance mechanical properties of Friction stir welded(FSW) AA6061-T6 alloy and to minimize the loss of T6 condition , four butt joints (FSW-SiC, FSW- B₄C, FSW- Zn and FSW- Al₂O₃)were fabricate with the addition of harder reinforcement materials such as SiC, B₄C,Zn and Al₂O₃ particles. In this study, the microstructure, tensile strength and  hardness of reinforced friction stir welded AA6061-T6 alloy joints were investigated, while the base metal and the welded joint prepared without reinforcement material were utilized as reference to control the process. The grains refinement ,which had been the reason for improved mechanical properties was increased with the addition of reinforced particles in the weld region. Due to the high density of homogeneous dispersion of harder reinforcement particles and  considerably increased grain refinement in the entire welded joints, all the reinforced welded joints resulted improvements over the unreinforced joint in terms of strength and hardness. The addition of SiC, B₄C,Zn and Al₂O₃ reinforcements  particles increases the tensile strength by 24.2% ,1.79%,32.46 and 10.83% respectively, whereas the elongation decreased as compared to unreinforced welded. Due to extremely high hardness value and homogeneous dispersion of B₄C particles in the FSW- B₄C joint .It showed the highest percentage of hardness enhancement that was about 54.9% followed by Al₂O₃, SiC and Zn with improved hardness percentage as 50.37% 40.9%, and 23.2% respectively.

Keywords:

Friction Stir welding (FSW) AA 6061-T6 Hardness Reinforcement particles Microstructure,

Refference:

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XXXI. Zhang.C, Cui.L , Wang.D, Liu.Y, Liu.C, Li.H, The heterogeneous microstructure of heat affect zone and its effect on creep resistance for friction stir joints on 9Cr–1.5W heat resistant steel, Scr. Mater. Vol.158 ,pp.6–10, 2019.
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