Archive

Abstract:

Routing is the most widely seen in many wireless sensor network (WSN) applications. Some networks work routinely on single path and this is limited. Many issues are identified in routing in WSN such as traffic, malicious nodes, etc. In this paper, the new enhanced threshold-based policy (BP-T) and a heuristic policy, which seriously controls traffic bifurcations at overlay focused. This will reduce the traffic and find the optimal with multiple routing can be identified. Results show the performance of the proposed system.

Keywords:

Wireless sensor network,routing,BPT,OBP,

Refference:

I. D. Xu, et.al, “Link-state routing with hop-by-hop forwarding can achieve
optimal traffic engineering” IEEE/ACM Trans. Netw., vol. 19, no. 6, pp.
1717–1730, Dec. 2011.
II. J. Han, et.al, “Topology aware overlay networks,” in Proc. IEEE INFOCOM,
Mar. 2005, pp. 25542565.
III. K. Kondaveti, T. K. Latha and Md. Amanatulla, “Data Integrity and Delay
Differentiated Services with Dynamic Routing in Wireless Sensor Networks”,
IJDCST @ Jan,-2017,Issue-V-5,I-1,SW-12.
IV. L. Bui, et.al, “Novel architectures and algorithms for delay reduction in backpressure
scheduling and routing”, in Proc. IEEE INFOCOM, Apr. 2009, pp.
2936–2940.
V. L. L. Peterson et.al “Computer Networks: A Systems Approach”, 4th ed. San
Francisco, CA, USA: Morgan Kaufmann, 2007.
VI. M. J. Neely, et.al, “Dynamic power allocation and routing for time-varying
wireless networks” IEEE J. Sel. Areas Commun., vol. 23, no. 1, pp. 89–103,
Jan. 2005.
VII. Rai, C.-P, et.al “Loop-free backpressure routing using link-reversal
algorithms”, IEEE/ACM Trans. Net., vol. 25, no. 5, pp. 2988–3002, Oct.
2017.
VIII. S. A. Khan et.al, “Performance Analysis of a ZigBee Beacon Enable Cluster
Tree Network”, Proc. Int l Conf. Electrical Eng. (ICEE), Apr.
IX. W. Khan, L, et.al, “Autonomous routing algorithms for networks with widespread
failures” in Proc. IEEE MILCOM, Oct. 2009, pp. 1–6.
X. Yu-Kai Huang, et.al, “Distributed Throughput Optimization for ZigBee
Cluster-Tree Network”, IEEE Trans. Paral. Distr. Syst., vol. 23, no. 3, pp.
513-520, Mar. 2012.

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Abstract:

This article outlines the theoretical, methodological and practical problems of analysis and synthesis of complex systems. The static or dynamic property of a system can be evaluated when the system structure is known, and all its parameters are specified. The objective of system analysis is to find an exact analytical or approximate solution of equations based on a corresponding mathematical model, as well as its further research. Theoretical conclusions and results have allowed to build mathematical models applicable to the management of objects with different principles of operation, in particular, to the management of complex technical and technological objects that can be represented as nonlinear dynamic systems. Nonlinear dynamic integral models are deemed appropriate to study and design such systems in some critical application.

Keywords:

technical systems,engineering systems,mathematical models,management,system analysis,complex system,

Refference:

I. A.A. Denisov, Modern problems of system analysis: Information bases
(Publishing house of St. Petersburg State University, St. Petersburg, 2005).
II. A.A. Kolesnikov, Synergetic methods of control of complex systems: theory
of system synthesis (KomKniga, Moscow, 2006)
III. A.V. Panteleev, A.S. Bartacovsky, E.A. Rudenko, Nonlinear control
systems: description, analysis and synthesis (High school book, Moscow,
2008)
IV. I.Yu. Tyukin, V.A. Terekhov, Adaptation in nonlinear dynamical
systems(LKI, Moscow, 2008)
V. V.G. Fetisov, I.V. Fetisov, I.I. Paninа, Some open questions of synthesis of
systems containing Hλ-operators (Scientific and technical Bulletin of the
Volga region, Kazan, 2013. – № 6. – P. 469–473)
VI. V.G. Fetisov, V.I. Filippenko, O.I. Okhrimenko, Qualitative and
quantitative methods of system analysis (FGBOU HPE «JURUES»,
Shakhty, 2011).
VII. V.G. Fetisov, I.I. Paninа,Classification of the main types of systems based
on their degree of complexity (Actual problems of technique and
technology, Shakhty, 2013).
VIII. V.G. Fetisov, O.I. Okhrimenko, I.I. Paninа,Selected chapters of modern
control theory with applications (ISOiP (branch) of the DSTU, Shakhty,
2015).

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Abstract:

In present days, low power Very Large Scale Integration (VLSI) circuit assumes a significant job in structuring effective vitality sparing electronic frameworks for rapid execution. In this, low power utilization one of the most significant criteria in different gadgets like cell phones, workstations, High-speed work stations, and so on. FinFETs area unit multi-door transistors that supply higher entry direct management is very little component advancements. They show higher and lower spillage contrasted with the Complementary metal oxide semiconductor planar. As appeared in Figure one, the door is created of a slim balance that associates the availability of the channel on to form the avenue. The avenue is middle between 2 facet entryways on 2 inverse sides. the weather of the door area unit calculable through the entry length, chemical compound thickness, balance dimension, and balance tallness. The activity of the FinFET semiconductor unit is basically similar because of the CMOS planate. In this paper, an SR Latch utilizing eight transistors has been proposed. The proposed SR Latch is planned to utilize the CADENCE EDA apparatus and re-enacted utilizing the Specter Virtuoso at FinFET 18 nm innovation. The proposed outcomes as far as power, area, and delay from table3, table4, table5, and table6.

Keywords:

Low power,delay,area,FinFET SR Latch,FinFET NAND gate,DSP,VLSI,

Refference:

I. Alshraiedeh and A. Kodi An adaptive routing algorithm to improve
lifetime reliability in NoCs architecture, IEEE International Symposium
on Defect and Fault Tolerance in VLSI and Nanotechnology Systems
(DFT) (2016), pp. 127–130.
II. Amulya Boyina, K. Praveen Kumar “Active Coplanar Wave guide Fed
Switchable Multimode Antenna Design and Analysis” Journal Of
Mechanics Of Continua And Mathematical Sciences (JMCMS), Vol.-
14, No.-4, July-August (2019) pp 188-196.
III. Azizi, M. M. Khellah, V. K. De & F. N. Najm, Variations aware lowpower
design and block clustering with voltage scaling. IEEE Trans. Very
Large Scale Integr. Syst. 15, 746 (2007).
IV. Bahadori, M. Kamal, A. Afzali-Kusha & M. Pedram, A comparative study
on performance and reliability of 32-bit binary adders. Integr. VLSI J. 53,
54 (2016).
V. C. Catanzaro, K. Asanovic, D. A. Patterson, and K. A. Yelick, The
landscape of parallel computing research: A view from berkeley. EECS
Dep. Univ. Calif. Berkeley Tech. Rep. UCBEECS2006183 18, 19 (2006).

VI. Chen, A. Shafaei, Y. Wang, S. Chen, and M. Pedram, Maximizing the
performance of NoC-based MPSoCs under total power and power density
constraints, 17th International Symposium on Quality Electronic Design
(ISQED) (2016), pp. 49–56.
VII. Dousti, Q. Xie, X. Lin, Y. Wang, A. Shafaei, M. Ghasemi-Gol, and M.
Pedram, 5 nm FinFET standard cell library optimization and circuit
synthesis in near-and super-threshold voltage regimes, 2014 IEEE
Computer Society Annual Symposium on VLSI (2014), pp. 424–429.
VIII. G. Friedman, K. Xu, R. Patel and P. Raghavan, Exploratory design of onchip
power delivery for 14, 10, and 7 nm and beyond FinFET ICs.
Integration 61, 11 (2018).
IX. Hwang, Y. Li, S. Member, and T. Li, Process-variation effect, metal-gate
work-function fluctuation, and random-dopant fluctuation in emerging
CMOS technologies. IEEE Trans. Electron Devices 57, 437 (2010).
X. J. R. Ferreira, Analysis of many-core CPUs simulators. Tech. Rep.,
Instituto Superior Tecnico, Universidade de Lisboa, pp. 1–10.
XI. K Satish Reddy a, K Praveen Kumar, Habibulla Khan, Harswaroop Vaish
“Measuring the surface properties of a Novel 3-D Artificial Magnetic
Material” 2nd International Conference on Nanomaterials and
Technologies (CNT 2014), Elsevier Procedia material Science.
XII. K.Praveen Kumar, “Design of 3D EBG for L band Applications” IEEE
International conference on communication technology ICCT-April-2015.
Noor Ul Islam University Tamilnadu.
XIII. K.Praveen Kumar, “Effect of 2DEBG structure on Monopole Antenna
Radiation and Analysis of It’s characteristics” IEEE International
conference on communication technology ICCT-April-2015. Noor Ul
Islam University Tamilnadu.
XIV. K.Praveen Kumar, “Mutual Coupling Reduction between antenna
elements using 3DEBG” IEEE International conference on
communication technology ICCT-April-2015. Noor Ul Islam University
Tamilnadu.
XV. K.Praveen Kumar, “The surface properties of TMMD-HIS material; A
measurement” IEEE International conference on communication
technology ICCT-April-2015. Noor Ul Islam University Tamilnadu.
XVI. K.Praveen Kumar, “Active Switchable Band-Notched UWB Patch
Antenna”, International Journal of Innovative Technology and Exploring
Engineering (IJITEE), Volume-8 Issue-8 June, 2019.
XVII. K.Praveen Kumar, “Circularly Polarization of Edge-Fed Square Patch
Antenna using Truncated Technique for WLAN Applications”,
International Journal of Innovative Technology and Exploring
Engineering (IJITEE), Volume-8 Issue-8 June, 2019.

XVIII. K.Praveen Kumar, “Triple Band Edge Feed Patch Antenna; Design and
Analysis”, International Journal of Innovative Technology and Exploring
Engineering (IJITEE), Volume-8 Issue-8 June, 2019.
XIX. K.Praveen Kumar, Dr Habibulla Khan ” Surface wave suppression band,
In phase reflection band and High Impedance region of 3DEBG
Characterization” International journal of applied engineering research
(IJAER), Vol 10, No 11, 2015.
XX. K.Praveen Kumar, Dr Habibulla Khan ” The surface properties of
TMMD-HIS material; a measurement” IEEE International conferance on
electrical, electronics, signals, communication & optimization EESCO –
January 2015.
XXI. K.Praveen Kumar, Dr. Habibulla Khan ” Active progressive stacked
electromagnetic band gap structure (APSEBG) structure design for low
profile steerable antenna applications” International Conference on
Contemporary engineering and technology 2018 (ICCET-2018) March 10
– 11, 2018. Prince Shri Venkateshwara Padmavathy Engineering College,
Chennai.
XXII. K.Praveen Kumar, Dr. Habibulla Khan “Active PSEBG structure design
for low profile steerable antenna applications” Journal of advanced
research in dynamical and control systems, Vol-10, Special issue-03,
2018.
XXIII. K.Praveen Kumar, Dr. Habibulla Khan “Optimization of EBG structure
for mutual coupling reduction in antenna arrays; a comparitive study”
International Journal of engineering and technology, Vol-7, No-3.6,
Special issue-06, 2018.
XXIV. K.Praveen Kumar, Dr. Habibulla Khan “Optimization of EBG structures
for Mutual coupling reduction in antenna arrays; A comparative study”
International Conference on Contemporary engineering and technology
2018 (ICCET-2018) March 10 – 11, 2018. Prince Shri Venkateshwara
Padmavathy Engineering College, Chennai.
XXV. K.Praveen Kumar, Dr. Habibulla Khan, “Design and characterization of
Optimized stacked electromagnetic band gap ground plane for low profile
patch antennas” International journal of pure and applied mathematics,
Vol 118, No. 20, 2018, 4765-4776.
XXVI. K.Praveen Kumar, Kumaraswamy Gajula “Fractal Array antenna Design
for C-Band Applications”, International Journal of Innovative Technology
and Exploring Engineering (IJITEE), Volume-8 Issue-8 June, 2019.
XXVII. Kumaraswami Gajula, Amulya Boyina, K. Praveen Kumar “Active Quad
band Antenna Design for Wireless Medical and Satellite Communication
Applications” Journal Of Mechanics Of Continua And Mathematical
Sciences (JMCMS), Vol.-14, No.-4, July-August (2019) pp 239-252.

XXVIII. Lim, H. Kim, H. Oh, and S. Kang, Dynamic voltage frequency scalingaware
refresh management for 3D DRAM over processor architecture.
Electron. Lett. 53, 910 (2017).
XXIX. Liu, R. Kim, P. Wettin, R. Marculescu, D. Marculescu, and P. P. Pande,
Energy-efficient VFI-partitioned multicore design using wireless NoC
architectures, Proceedings of the 2014 International Conference on
Compilers, Architecture and Synthesis for Embedded Systems-CASES
’14 (2014), pp. 1–9.
XXX. M. E. Salehi and H. Nejatollahi Voltage scaling & dark silicon in
symmetric multicore processors. J. Supercomput. 71, 3958 (2015).
XXXI. N. S. Kim, S. K. Khatamifard, M. Resch & U. R. Karpuzcu, VARIUS-TC:
A modular architecture-level model of parametric variation for thinchannel
switches. Proc. 34th IEEE Int. Conf. Comput. Des. ICCD 2016
(2016), pp.654–661.
XXXII. Navi, A. Arasteh, M. Hossein Moaiyeri, M. Taheri, and N. Bagherzadeh,
An energy and area efficient 4:2 compressor based on FinFETs. Integr.
VLSI J. 60, 224 (2018).
XXXIII. Nejatollahi, M. Ersali, and S. Nasab, Reliability-aware voltage scaling of
multicore processors in dark silicon era. Big Data and HPC: Advances in
Parallel Computing Ecosystem and Convergence (2018), Vol. 33, pp.242–
262.
XXXIV. S. S. Majzoub, R. A. Saleh, S. J. E. Wilton & R. K. Ward, Energy
optimization for many-core platforms: Communication and PVT aware
voltage-island formation and voltage selection algorithm. IEEE Trans.
Comput. Des. Integr. Circuits Syst. 29, 816 (2010).
XXXV. Singh, B. S. Reniwal, V. Vijayvargiya, V. Sharma & S. K. Vishvakarma,
Ultra low power-high stability, positive feedback controlled (PFC) 10T
SRAM cell for look up table (LUT) design. Integration 62, 1 (2018).
XXXVI. Stamelakos, S. Xydis, G. Palermo, and C. Silvano, Workload- and
process-variation aware voltage/frequency tuning for energy efficient
performance sustainability of NTC manycores. Integration (2018), In
Press.
XXXVII. Stillmaker and B. Baas, Scaling equations for the accurate prediction of
CMOS device performance from 180 nm to 7 nm. Integration 58, 74
(2017).
XXXVIII. T. Cui, J. Li, Y. Wang, S. Nazarian & M. Pedram, “An exploration of
applying gate-length-biasing techniques to deeply-scaled FinFETs
operating in multiple voltage regimes”, IEEE Transi. Emer. Top. Compu.
six, 172 (2018).
XXXIX. Uddin, R. Poss, and C. Jesshope, Cache-based high-level simulation of
microthreaded many-core architectures. J. Syst. Archit. 60, 529 (2014).

XL. Venkateswar Rao, Praveen Kumar Kancherla, Sunita Panda “Multiband
slotted Elliptical printed Antenna Design and Analysis” Journal Of
Mechanics Of Continua And Mathematical Sciences (JMCMS), Vol.-14,
No.-4, July-August (2019) pp 378-386.
XLI. W. Jose, A. R. Silva, H. Neto, & M. Vestias, Modeling and simulation of
a many-core architecture using systemC. Conf. Electron. Telecommun.
Comput. 17, 146 (2014).
XLII. X. Lin, Y. Wang, & M. Pedram, Joint sizing and adaptive independent
gate control for FinFET circuits operating in multiple voltage regimes
using the logical effort method, 2013 IEEE/ACM International
Conference on Computer-Aided Design (ICCAD), (2013), pp. 444–449.
XLIII. Z. Hao, S. X.-D. Tan, and G. Shi, Statistical full-chip total power
estimation considering spatially correlated process variations. Integr.
VLSI J. 46, 80 (2013).

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Abstract:

The main intention of this paper was to deliver some of the distinctive features of the Vlasov equation and Landau damping from the perspective of mathematical physics. The main thrust can be reviewed as; Vlasov equation is understood from the origin point of view. The mean field is limit of the classical Nbody problem, is depicted in pure mathematical and also statistical guidelines. We also axiomatically concluded that the Vlasov equation is completely justified as one major source that led to numeral of open problems in mathematical physics: either from molecular chaos to the problems of kinetic theory. We have delivered the mathematics of the Vlasov equations: particularly the traditional partial differential equation analysis in the functional spaces. The problem is observed to be converted as a general transport equation and relaying on the well-posedness of the equation and preserving the transport structure the Vlasov equation is solved for pivotal analytic solutions and compared with the computational solution obtained using solver codes. The analysis of the Vlasov-Poisson equation and its qualitative properties and are focused on the mathematical aspects. In this paper Landau damping is identified numerically for 1D model of non relativistic Vlasov equation.

Keywords:

Vlasov equation,Landau dampin,functional spaces,Semi Lagrangian Schemes,

Refference:

I. Biskamp. D, “Magnetohydrodynamic Turbulence”,
doi:10.1017/cbo9780511535222, 2003.
II. Blaisdell, G. A,“Review of “Implicit Large Eddy Simulation: Computing
Turbulent Fluid Dynamics””, AIAA Journal, 46(12), 3168-3170.
doi:10.2514/1.40931, 2008.
III. Braun. W.&Hepp. K,“TheVlasov dynamics and its fluctuations in the 1/N
limit of interacting classical particles”, Communications in Mathematical
Physics, 56(2), 101-113. doi:10.1007/bf01611497, 1977.
IV. Dafermos. C. M & Feireisl. E, Handbook of differential equations:
evolutionary equations Boston: Elsevier, 2004.
V. Degond. P,“Spectral theory of the linearized Vlasov-Poisson
equation”, Transactions of the American Mathematical Society, 294(2), 435-
435. doi:10.1090/s0002-9947-1986-0825714-8, 1986.
VI. Derfler. H & Simonen, T. C,“Landau Waves: An Experimental
Fact”, Physical Review Letters, 17(4), 172-175.
doi:10.1103/physrevlett.17.172, 1966.
VII. Elskens. Y, “Irreversible behaviors in Vlasov equation and many-body
Hamiltonian dynamics: Landau damping, chaos and granularity”, Topics in
Kinetic Theory, 89-108. doi:10.1090/fic/046/03, 2005.

VIII. Glassey. R & Schaeffer. J,“On time decay rates in landau
damping”, Communications in Partial Differential Equations, 20(3-4), 647-
676. doi:10.1080/03605309508821107, 1995.
IX. Glassey. R & Schaeffer. J, “Time decay for solutions to the linearized Vlasov
equation”, TransportTheory and Statistical Physics, 23(4), 411-453.
doi:10.1080/00411459408203873, 1994.
X. Horst. E,“On the asymptotic growth of the solutions of the vlasov-poisson
system”, Mathematical Methods in the Applied Sciences, 16(2), 75-85.
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XI. Horst. E. & Neunzert. H, “On the classical solutions of the initial value
problem for the unmodified non-linear Vlasov equation I general theory”,
Mathematical Methods in the Applied Sciences, 3(1), 229-248.
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three dimensions for general initial data”, Journal of Differential
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Turbulence. Proceedings of the International Congress of
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Abstract:

Machines with intermittent movement of working body are widely used in industry. Currently, mechanisms with unilateral constraints or variable structures are used as actuators of such machines. Output link stops in most mechanisms are provided by periodic rupture of the kinematic connection between the links. This disadvantage limits the use of these mechanisms in high speed machines, since impacts occur at the end or beginning of the motion phase. So, there is a relevant task to create, analyze and effectively put into practice intermittent motion mechanisms (IMMs) in which during operation the kinematic constraint between the links is not broken. The author proposes and analyzes planetary trains, which include modified elliptical wheels. The variable transfer function of a non-circular wheel pair and certain dimensions of the mechanism links make it possible to obtain required motion function. The kinematics of the proposed IMMs is analyzed, as a result of which the functions of the angle of rotation and the analogue of the output shaft angular velocity are found and constructed. Created mechanisms due to the use of gears perform reliability and compactness with the possibility of transferring great forces, and they can find application in metalworking machinery, automatic lines, robotics, transporters.

Keywords:

Rotational motion,Intermittent motion,Elliptical gearwheels,Planetary mechanism,Kinematic analysis,Angular velocity,

Refference:

I. AnI. K., “Synthesis, geometric and strength calculations of rotor
hydromachines planetary mechanisms with non-circular gears”, Doctor
thesis, Tomsk Polytechnic University, Tomsk, 2001
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Press, Moscow, USSR, 1986.
III. BickfordJ. H., “Mechanisms for intermittent motion”, Industrial Press
Inc., New York, USA, 1972.
IV. ChangZ., XuC., PanT., WangL., ZhangX., “A general framework for
geometry design of indexing cam mechanism”, Mechanismand Machine
Theory, Volume: 44, Pages: 2079 – 2084, 2009.
https://doi.org/10.1016/j.mechmachtheory.2009.05.010
V. CoxeterH.S.M., “Introduction to Geometry”, Wiley Publishing House.
New York, USA, 1969.
VI. Dooner D. B., Palermo A., Mundo D., “An intermittent motion
mechanism incorporating a Geneva wheel and a gear train”, Transactions
of the Canadian Society for Mechanical Engineering, Volume: 38(3),
Pages: 359 – 372. 2014, https://doi.org/10.1139/tcsme-2014-0026

VII. DoonerD. B., “Use of noncircular gears to reduce torque and speed
fluctuations in rotating shafts”, Journal of Mechanical Design, Volume:
119(2), Pages: 299 – 306. 1997. https://doi.org/10.1115/1.2826251
VIII. FiglioliniG., AngelesJ., “Synthesis of conjugate Geneva mechanisms
with curved slots”, Mechanismand Machine Theory, Volume: 37, Pages:
1043 – 1061, 2002. https://doi.org/10.1016/S0094-114X(02)00062-9
IX. FiglioliniG., ReaP., AngelesJ., “The pure-rolling cam-equivalent of the
Geneva mechanism”, Mechanismand Machine Theory, Volume: 41,
Pages: 1320 – 1335, 2006.
https://doi.org/10.1016/j.mechmachtheory.2006.01.002
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sprockets and minimum slack-theory and application”, Journal of
Mechanical Design, Volume: 113(3), Pages: 253 – 262, 1991.
https://doi.org/10.1115/1.2912777
XI. HanJ. Y., “Complete balancing of the shaking moment in spatial linkages
by adding planar noncircular gears”,Archive of Applied Mechanics.
Volume: 67(1-2), Pages: 44 – 49. 1997.
https://doi.org/10.1007/BF00787138
XII. KozhevnikovS. N., EsipenkoY. I., RaskinY. M., “Mechanisms”,
Mechanical Engineering Press, Moscow, USSR, 1976.
XIII. LeeJ. J., JanB. H., “Design of Geneva mechanisms with curved slots for
non-undercutting manufacturing”, Mechanismand Machine Theory,
Volume: 44, Pages: 1192 – 1200, 2009.
https://doi.org/10.1016/j.mechmachtheory.2008.09.003
XIV. LevitskiyN.I., “Theory of mechanisms and machines”, Nauka Press.
Moscow, USSR, 1979
XV. LinC., XiaX., LiP., “Geometric design and kinematics analysis of
coplanar double internal meshing non-circular planetary gear train”,
Advances in Mechanical Engineering. Volume: 10(12), Pages 27 – 35.
2018, https://doi.org/10.1177/1687814018818910
XVI. LitvinF.L., FuentesA., “Gear geometry and applied theory”,Cambridge
University Press: Cambridge, UK, 2004.
XVII. LitvinF. L., Gonzalez-PerezI., FuentesA., HayasakaK., “Design and
investigation of gear drives with non-circular gears applied for speed
variation and generation of functions”, Computer Methods in Applied
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XVIII. LiuD., BaY., RenT., “Flow fluctuation abatement of high-order elliptical
gear pump by external noncircular gear drive”, Mechanismand Machine
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https://doi.org/10.1016/j.mechmachtheory.2019.01.011

XIX. MundoD., “Geometric design of a planetary gear train with non-circular
gears,” Mechanismand Machine Theory, Volume: 41, Pages: 456 – 472.
2006. https://doi.org/10.1016/j.mechmachtheory.2005.06.003
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reciprocating stirred tank with multiple impellers”, Proceedings of 2015
International Conference on Mechanical Engineering, Automation and
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stirred tank with planetary actuator”, Journal of Physics:Conference
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6596/858/1/012026
XXII. Prikhod’koA.A., SmelyaginA.I., “Investigation of power consumption in
a mixing device with swinging movement of the actuating
element”,Chemical and Petroleum Engineering. Volume: 54, Pages: 150
– 155. 2018.https://doi.org/10.1007/s10556-018-0454-7
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converting rotational motion into reciprocating rotational motion”,
Procedia Engineering.Volume: 129, Pages: 87–92. 2015.
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mechanisms with intermittent motion”, Procedia Engineering, Volume:
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State Technical University Press. Novosibirsk, Russia, 2001.
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“The structural and parametrical synthesis of machines and mechanisms”,
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XXVIII. SmelyaginA.I., Prikhod’koA.A., “Structure and kinematics of a planetary
converter of the rotational motion into the reciprocating rotary motion”,
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mechanisms”, Proceedings of the International Conference on Gearing,
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XXX. TeradaH., ZhuY., SuzukiM., ChengC., TakahashiR., “Developments of a
knee motion assist mechanism for wearable robot with a non-circular
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with free-form tooth profile and curvilinear tooth lengthwise”, Journal of
Mechanical Design. Volume: 138(6), 064501. 2016.
https://doi.org/10.1115/1.4033396
XXXIII. ZhengF., HuaL., HanX., LiB., ChenD., “Linkage model and
manufacturing process of shaping non-circular gears”, Mechanism
andMachine Theory. Volume: 96, Pages: 192 – 212. 2016.
https://doi.org/10.1016/j.mechmachtheory.2015.09.010
XXXIV. ZhengF., HuaL., HanX., LiB., ChenD., “Synthesis of indexing
mechanisms with non-circular gears”, Mechanismand Machine Theory,
Volume: 105, Pages: 108 – 128, 2016,
https://doi.org/10.1016/j.mechmachtheory.2016.06.019

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Abstract:

Glaucoma is a visual disorder, which is one of the significant driving reason for visual impairment. Glaucoma leads to frustrate the visual information transmission to the brain. Dissimilar to further eye diseases such as myopia and cataracts, the influence of glaucoma can’t be cured; however, the disease ranked as 2􀯡􀯗 driving reason for blindness according to the organization of the health world. Among eye sickness anticipated to influence around 80 million individuals by 2020. Raising the fluid pressure well-known by intraocular pressure (IOP) is the prime cause of Glaucoma disorder .Diagnoses of glaucoma could be achieved through observing the adjustment in the structure of Optic Nerve Head (ONH) to get its features. The proposed methodology suggests to extract region of Interest (ROI) and blurred its red band to enable the segmentation of Optic Disc(OD); followed by inpainting blood vessels stage to facilitate the work of the next stage, which was segmentation of the Optic Cup(OC), the accuracy rate, sensitivity and specificity for detection OD segmentation was 94.7549%, 95.058%, and 95.93%, respectively. The accuracy rate, sensitivity, and specificity for OC segmentation 94.3254%, 0.7877%, 0.9848% respectively.

Keywords:

Optic Disc,Optic Cup,Drishti_GS,Retinal fundus,Glaucoma Diagnosis,

Refference:

I. Bhat SH, Kumar P. Segmentation of Optic Disc by Localized Active
Contour Model in Retinal Fundus Image. Smart Innovations in
Communication and Computational Sciences: Springer; 2019. p. 35-44.
II. Eladawi N, ElTanboly A, Elmogy M, Ghazal M, Fraiwan L, Aboelfetouh
A, et al., editors. Diabetic Retinopathy Early Detection Based on OCT
and OCTA Feature Fusion. 2019 IEEE 16th International Symposium on
Biomedical Imaging (ISBI 2019); 2019: IEEE.
III. Guo Y, Zou B, Chen Z, He Q, Liu Q, Zhao R. Optic cup segmentation
using large pixel patch based CNNs. 2016. Available from:
https://ir.uiowa.edu/omia/2016_Proceedings/2016/17/ DOI:
10.17077/omia.1056
IV. Ho H, Tham Y-C, Chee ML, Shi Y, Tan NY, Wong K-H, et al. Retinal
nerve fiber layer thickness in a multiethnic normal Asian population: the
Singapore epidemiology of eye diseases study. 2019;126(5):702-711.
V. Jonas JB, Bergua A, Schmitz–Valckenberg P, Papastathopoulos KI,
Budde WMJIO, Science V. Ranking of optic disc variables for detection
of glaucomatous optic nerve damage. 2000;41(7):1764-1773.
VI. Lindeberg T, Li M-XJCV, Understanding I. Segmentation and
classification of edges using minimum description length approximation
and complementary junction cues. 1997;67(1):88-98.
VII. Stein SK, Barcellos A. Calculus and analytic geometry: McGraw-Hill
New York; 1992.
VIII. Sivaswamy J, Krishnadas S, Joshi GD, Jain M, Tabish AUS, editors.
Drishti-gs: Retinal image dataset for optic nerve head (onh)
segmentation. 2014 IEEE 11th international symposium on biomedical
imaging (ISBI); 2014: IEEE.
IX. Spaeth GL, Henderer J, Liu C, Kesen M, Altangerel U, Bayer A, et al.
The disc damage likelihood scale: reproducibility of a new method of
estimating the amount of optic nerve damage caused by glaucoma.
2002;100:181.
X. Suha Dh. Athab NHS. Localization of Optic Disc in Retinal Fundus
Image Using Appearance Based Method and Vasculature Convergence.
IJS. 2020;61(1).

XI. Thakur N, Juneja MJESwA. Optic disc and optic cup segmentation from
retinal images using hybrid approach. 2019;127:308-322.
XII. Weinreb RN, Bowd C, Moghimi S, Tafreshi A, Rausch S, Zangwill LM.
Ophthalmic Diagnostic Imaging: Glaucoma. High Resolution Imaging in
Microscopy and Ophthalmology: Springer; 2019. p. 107-134.
XIII. Xue L-Y, Lin J-W, Cao X-R, Zheng S-H, Yu LJJoC. Optic Disk
Detection and Segmentation for Retinal Images Using Saliency Model
Based on Clustering. 2018;29(5):66-79.
XIV. Yin F, Liu J, Wong DWK, Tan NM, Cheung C, Baskaran M, et al.,
editors. Automated segmentation of optic disc and optic cup in fundus
images for glaucoma diagnosis. 2012 25th IEEE international symposium
on computer-based medical systems (CBMS); 2012: IEEE.
XV. Yu D-Y, Cringle SJ, Morgan WH. Glaucoma Related Ocular Structure
and Function. Medical Treatment of Glaucoma: Springer; 2019. p. 1-31.

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Abstract:

Segmentation has vital employment in regression analysis where data have some change point. Traditional estimation methods such as Hudson, D.J.;(1966) and Muggeo, V. M., (2003)have been reviewed. But these methods do not take into account robustness in the presence of outliers values. However, third method was used as rank-based method, where the analysis will be devoted to the ranks of data instead of the data themselves. Our contribution in this paper is to use M-estimator methodology with three distinct weight functions (Huber, Tukey, and Hampel) which has been combined with Muggeo version approach to gain more robustness, Thus we get robust estimates from the change point and regression parameters simultaneously. We call our new estimator as robust Iterative Rewrighted Mestimator: IRWm-method with respect to its own weight function. Our primary interest is to estimate the change point that joins the segments of regression curve, and our secondary interest is to estimate the parameters of segmented regression model. The real data set were used which concerned to bed-loaded transport as dependent variable (y) and discharge explanatory variable (x). The comparison has been conducted by using several criteria to select the most appropriate method for estimating the change point and the regression parameters. The superior results were marked for IRWm-estimator with respect to Tukey weight function.

Keywords:

Segmented regression,change point,rank-based estimator,iterative reweighted least squares,M-estimator,

Refference:

I. Almetwally, E.M., Almongy, H.M., (2018).”Comparison Between Mestimation,
S-estimation, And MM Estimation Methods of Robust Estimation
with Application and Simulation”. International Journal of Mathematical
Archive.Vol.9,No.11,pp 55-63.
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“Determination of the optimum working range in spectrophotometric
procedures”. Talanta;531–537.
III. Blicschke, W., (1961).”Least Squares Estimators of Two Intersecting Lines”.
Technical Report, No. 7, Department of Navy, Office of Naval Research,
Contract No. Nonr-401(39), Project No. NR 042-212, BU-135-M(1):1–10.
IV. Das, R.,Banerjee, M.,Nan, B. and Zheng, H., (2015).”Fast estimation of
regression parameters in a broken-stick model for longitudinal data”. Journal
of the American Statistical
Association,http://dx.doi.org/10.1080/01621459.2015.1073154.
V. Fasola, S. ,Muggeo,V.M.R. and Küchenhoff,H.,(2017).”A heuristic, iterative
algorithm for change-point detection in abrupt change models”.
Computational Statistics,Vol.33, Issue 2,pp 997-1015.

VI. Greene, M.E. ,Rolfson, O., Garellick, G., Gordon, M. and Nemes, S. , (2014).
“Improved statistical analysis of pre- and post-treatment patient-reported
outcome measures (PROMs) the applicability of piecewise linear regression
splines”. Quality of Life Research, Vol.24,Issue3,pp.567–573.
VII. Hettmansperger, T., McKean, J.W., (2011).”Robust Nonparametric Statistical
Methods”. 2nd Ed. New York, Chapman.
VIII. Hudson, D.J.,(1966).”Fitting Segmented Curves Whose Join Points Have to
be Estimated” . Journal of the American Statistical Association , Vol. 61, No.
316, pp.(1097-1129).
IX. Jaeckel, L. A., (1972).”Estimating regression coefficients by minimizing the
dispersion of the residuals”. The Annals of Mathematical
Statistics,Vol.43,No.5, pp1449–1458.
X. Jureckova, J., (1971).”Nonparametric estimate of regression coefficients”.
The Annals of Mathematical Statistics,Vol.42,No.4,pp1328–1338.
XI. Küchenhoff, H.,(1997).”An exact algorithm for estimating breakpoints in
segmented generalized linear models”. Computational Statistics; 12:235–247.
XII. Lain, M.,(2018).”JoinpointRegrese”.Univerzita Karlova, Matematickofyzikální
fakulta, BAKALÁŘSKÁ
PRÁCE.http://hdl.handle.net/20.500.11956/100141.
XIII. Maciak, M., Mizera, I.,(2016).”Regularization techniques in joinpoint
regression”. Statistical Papers,Vol. 57, Issue 4, pp 939–955.
XIV. Martin, J.,Martin, G.D., Asuero, A.G.,(2017).”Intersecting Straight Lines
Titrimetric Applications”.
Intechopen,http://dx.doi.org/10.5772/intechopen.68827.
XV. McKean, J. W. , Hettmansperger, T. P.,(2016).”Rank-Based Analysis of
Linear Models and Beyond: A Review”.In:Robust Rank-Based and
Nonparametric Methods; Liu, R.Y.; McKean, J.W., Eds.; Springer
International Publishing; pp. 1–24.
XVI. Muggeo, V. M. R.,(2003).”Estimating regression models with unknown
breakpoints”.Statistics in Medicine,Vol.22,Issue19,pp3055–3071.
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segmented regression: a smoothed score-based approach”. Aust. N. Z. J. Stat.
59(3), 311–322.
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214-224.

XXII. Roslyakova, I.,(2017).”Modeling thermodynamical properties by segmented
non-linear regression”.Ruhr-University Bochum, Doctoral Thesis.
XXIII. Ryan, S. E. and Porth, L. S.,(2007).”A Tutorial on the Piecewise Regression
Approach Applied to Bedload Transport Data”. Report No. RMRS-GTR-189,
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Regression Diagnostics”. International Statistical Review, 84(1):99–127.
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regression model with multiple change points”.The Journal of
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experiments”.arXiv:1807.00943v1 [stat.ME].

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Abstract:

In this work, γ-Al2O3powder as copper adsorbent material was synthesized from polyoxohydroxide aluminum (POHA) precursor using aluminum powder, potassium hydroxide and d- glucose dissolved in distilled water and ethanol, and calcined at 500 °C. Prepared γ-Al2O3powder was characterized using (XRD), (FTIR), (SEM), (LGI) and (BET) method. The copper ions concentration of oilfieldproducedwater was determined using (ICP-OES). The parameters considered asγ-Al2O3adsorbent dose, adsorption time and pH used in this work are (0.2 and 0.4 mg/l), (30-180 min) and (4-10 pH) respectively. The characterization results showed that γ-phase is the dominant phase of synthesized Al2O3 powder. The results also showed that high adsorption performance for copper ions with a high removal efficiency of 99.99% using synthesized γ-Al2O3was obtained with an absorbed dose of 0.4 mg /l, adsorption time of 90 min and a pH of 7.

Keywords:

γ-alumina,chemical method,adsorption,copper adsorption,removal efficiency,

Refference:

I. Al-Haleem .A. A., Abdulah . H. H., Saeed .E. A., Components and
treatments of 36 oilfield produced water., Al Engineering Journal 2010; 6 (1) : 24
II. Al-Haleem .A. A., Razaq. A.H., Oilfield produced water management: treatment, 40, 1 – 9.
III. Arbabi.M., Golshani .,Removal of Copper Ions Cu (II) from
Industrial Wastewater:A Review of Removal Methods,International
Journal of Epidemiologic Research, 2016; 3(3): 283-293.
IV. Alvarez-Silva .M.,Uribe-Salas. A., Mirnezami.M. Mirnezami., Finch
.J., The point of zero charge of phyllosilicate minerals using the
Mular–Robertstitration technique, Minerals Engineering ,2010,23 (5) :383–389.
V. Hardi .M ., Siregar .Y. I., Anita .S., and Ilza .M., International
Conference of 38 Chemistry, in Journal of Physics: Conf. Series, 2019, pp. 1-6.
VI. Kanakaraju .D.,Ravichandar. S., Lim.Y.C ., Combined effects of
adsorption and 13 photocatalysis by hybrid TiO2/ZnO-calcium alginate
beads for the removal of 14 copper., Journal of Environmental Sciences
2017, 55 (1) : 214-223.
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S,Pescarmona.P, High surface area, nanostructured boehmite and alumina
catalysts: Synthesis andapplication in the sustainable epoxidation of
alkenes,Applied Catalysis A: General.2019;571(1):180-187.Volume
571, 5 February 2019, Pages 180-187.
VIII. Nassef E., El-Taweel. Y.A., Removal of copper from wastewater by
cementation 14 from simulated leach liquors J. Chem. Eng. Process
Technol 2015; 6(1) : 1-6.
IX. Segala .F, Correab .M,BacanieR,CastanheiracB, Politid M,Brochsztainc
S,Tribonia E,A Novel Synthesis Route of Mesoporous γ-Alumina from
Polyoxohydroxide Aluminum, Materials Research. 2018; 21(1):1-8
X. Visa. M., Synthesis and characterization of new zeolite materials
obtained from fly 15 ash for heavy metals removal in advanced
wastewater treatment. Powder Technol16 2016 ; 294(2) :338-374.
XI. Yang .J., HouBaohong., Wang J., Tian Beiqian., Bi.J., Wang.N., Li. X.,
and Huan.,Nanomaterials for the Removal of Heavy Metals from
Wastewater, Nanomaterials, 2019, 9(3):1-39.

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Abstract:

The optimal prediction or forecasting of time series values from the observations required many things such as checking the identification accuracy, model diagnosis, and data free from violations (outliers, for instance). Therefore, the researchers are always wondering if the used model or the supported method is sufficient to represent the data or there are more information that can be provided and probable increasing of precision as a consequence in the forecasting. This paper is an attempt to propose a new hybrid model building that can be denoted by AR-Holt (p+5). Also, suggest a new algorithm to estimate the parameters of this new hybrid model with its forecasting for inside and outside the series. Furthermore, the comparison has been done between this new hybrid model with AR(p) model which was identified as well as its parameters were estimated by many traditional methods which are Yule-Walker, Burg, robust RA, LS, Mcov and LMS methods for contaminated time series data. Simulation experiments have been conducted with different levels of contamination (p=0, 0.05, 0.15) to evaluate the superior of the performance of this new model according to different sample sizes (n=30, 70, 150). A real data application of the barley crops in Iraq is taken into consideration.

Keywords:

Yule-Walker method,Burg method,RA method,least squares,modified covariance,LMS method,autoregressive time series model,Holt,

Refference:

I. Abd El-Sallam, Moawad El-Fallah. “Methods of Estimation for
Autoregressive Models with Outliers”. Asian Journal of Mathematics and
Statistics, Vol. 6, No. 2, 2013.
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2018)”. Technical Report, Central Statistical Organization (CSO), Iraq, 2019.
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Application”. Englewood Cliffs, NJ: Prentice-Hall, 1988.
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Cliffs, NJ: Prentice-Hall, 1987.
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Covariance Method of linear Prediction”. Digital Signal Processing, Vol. 1,
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XI. Xiao, Han and Wu, Wei Biao. “Covariance Matrix Estimation for Stationary
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Walker Equations”. IEEE Transactions on Signal Processing, Vol. 40, No.
12, 1992.

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Abstract:

The prime aim of the current research is to investigate the thermal performance of the solar-assisted heat pump (SAHP) under the Iraqi climate experimentally and theoretically. In the winter season, the ambient air temperature reduces which causes a reduction in the coefficient of performance (COP) of heat pumps. By utilizing the thermal energy of solar to raise the heat transfer rate of the evaporator, compressor work diminishes and thus the COP of heat pump rises. The experimental setup of SAHP is perform by joining of a solar air heater and an air-toair heat pump. In this arrangement, the inlet of the air evaporator has been preheated by a solar air heater. The mathematical model based on energy balance was evolved and the performance of this system has been studied over a cold season of Baghdad city (placed in the middle of Iraq). The consequences revealed that the presence of porous media in the lower channel of the absorber plate providing a great surface area for convective heat transfer, therefore, the variation of air temperature and thermal efficiency of the solar air heater are raised. The average thermal efficiency for models (II, III, IV, and V) over the model I (Conventional) are (16.6%, 21.2%, 26.2%, and 30.3%) respectively at mass flow rate 0.02172 kg/s.

Keywords:

Air source Heat Pump,Solar Assisted Heat Pump,Power Consumption,

Refference:

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Solar Collectors with Application to Heat Pumps,” Journal of Solar
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