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Abstract:

In this article we introduce A*-involution in additively inverse semirings. This involution have potential to extend the striking results of B*-algebras, C*- algebras and involutory rings in the domain of semirings. The remarkable result due to Herstein[XII] states that every Jordan derivation on a 2-torsion free prime ring is a derivation. In the present paper, we shall study the above mentioned result for Jordan left derivations in semirings with A* -Involution.

Keywords:

Jordan left derivation,Involution,Prime semirings,Additive Inverse semirings,

Refference:

I. Awtar, R, Lie ideals and Jordan derivations of prime rings, Proc. Amer. Math. Soc.90 (1984), 9-14.
II. Ashraf, M. and N. Ur. Rehmann, On Lie ideals and Jordan left derivations of prime rings. Arch. Math. (Brno) 36 (2000), 201-206
III. Bandlet H.J. and M. Petrich, Subdirect products of rings and distributive lattices Proc. Edin Math.Soc. 25 (1982) 135-171.
IV. Beidar K.I, WS Martindale On Functional Identities in Prime Rings with Involution,Journal of Algebra Volume 203. Issue 2, 15 May 1998, 491-532.
V. Bergen, J., Herstein, I.N. and Ker, J.W., Lie ideals and derivations of prime rings,J. Algebra 71 (1981), 259-267.
VI. Bresar. M. and Vukman, J., On left derivations and related mappings, Proc. Ameer. Math. Soc. 110 (1990), 7-16.
VII. C. Lanski, Commutation with skew elements in rings with involution, Pacific J. Math. Volume 83, Number 2(1979), 393-399.
VIII. Chadja. I , H. LANGER , Near Semirings and Semirings with Involution, Miskolc Mathematical Notes, Vol.17 (2017) No. 2, 801810
IX. Fadaee. B and H.Ghahramani, Continuous linear maps on reflexive algebras behaving like Jordan left derivations at idempotent- product elements,ar Xiv:1312.6953
X. Ghahramani. H., Characterizations of left derivable maps at non- trivial idempotents on nestalgebras, arXiv:1312.6959.
XI. Golan. J.S., The theory of semirings with applications in mathematics and theoretical computer science (John Wiley and Sons . Inc, New York, 1992). doi:10.1007/978- 94-015-9333-5-13.
XII. Herstein, I.N, Jordan derivations of prime rings, Proc. Amer. Math. Soc. 8(1957), 1104- 1110.
XIII. J. Li and J. Zhou, Jordan left derivations and some left derivable maps, Oper. Matrices 4(2010),127-138.
XIV. J.V. Markov, Pierce Sheaf for semirings with involution, Russian Mathmatics (Iz. VUZ), 2014, Vol.58, No. 4, 1419.
XV. Javed. M. A, Aslam M. Hussain M., On condition (A 2) of Bandlet and Petrich for inverse semirings, Int. Math. Forum, 2012,7, 2903-2914.
XVI. Javed. M. A., Aslam M., Some commutativity conditions in prime MA-semirings, Ars Combin., 2014,114,373-384.
XVII. Karvellas P.H, Inversive semirings, J. Austral. Math. Soc., 1974,18,277-288.
XVIII. Kill-Wong Jun and Byung-Do Kim, A note on Jordan left derivations, Bull. Korean Math. Soc.33 (1996) No.2,221-228.
XIX. M. Bresar, Characterizing homomorphisms, multopliers and derivations in rings with idempotents, Proc. Roy,Soc.Edinburgh Sect. A137(2007), 9-21.
XX. M. Burgos, J. Cabello-Sanchezanda. M . Peralta, Linear maps between C*-algebras that are*- homomorohism at a fixed point, arXiv: 1609.07776.
XXI. M.A. Chebotar, W.F. Ke and P.H .Lee , Maps characterized by action on zero products, Pacific J. Math.216 (2004), 217-2278.
XXII. Oukhtite.L., S. Salhi , On commutativity of – prime rings. Glas. Math. Ser. III Vol.41, no.1 (2006), 57-64.
XXIII. Yaqoub Ahmed, W.A. Dudek, Stronger Lie derivations on MA-semirings, Afrika Mat., doi.org/10.1007/s13370-020-00768-3.
XXIV. Yaqoub Ahmed, W.A. Dudek. Left Jordan derivation on certain semirings,. Hacepette J. Math. (accepted).
XXV. Vukman. J. On left Jordan derivations of rings and Banach algebras, Equations Math .75 (2008), no. 3, 260-266
XXVI. Y. Ahmed, M. Nadeem, M. Aslam, On Centralizers of MA semirings, JMCMS, Vol 15 (4), 47-57
XXVII. Y. Ahmed, Wieslaw Dudek, M. Aslam, Asian European journal of Mathematics (accepted), DOI: 10.1142/S1793557121500674

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Abstract:

In wide area monitoring system, phasor measurement units (PMUs) plays a vital role in providing synchronized measurements with the help of Global Positioning System (GPS). In conventional optimal PMU placement methodology these PMUs are placed optimally across the power system network ensuring completely observable.  It is found in literature, that most of them neglect the PMU channel limitations, variable PMU costs, and measurement redundancy improvement. To address this problem, in the present paper an optimal PMU problem is addressed by optimizing the two objective functions that are conflicting in nature, namely, minimization of PMU installation cost and maximization of measurement redundancy at the same time. In order to allocate PMUs, both channel limitation and variable cost of PMUs has been considered. A non-dominated sorting genetic algorithm-II (NSGA-II)based methodology is proposed to solve the combinatorial optimization problem. The Pareto optimal solution obtained using the concept of crowding distance and non-dominated sorting. A multi-criteria decision making technique based on VIKOR method is utilized for finding the best compromise solution from the set of Pareto-optimal solution obtained through NSGA-II. To verify the effectiveness and reliability, the proposed approach is tested on IEEE 14-bus, 30-bus, and 57-bus systems.

Keywords:

PMU placement, VIKOR method, NSGA-II,Power System,

Refference:

I. A. Enshaee, R. A. Hooshmand, and F. H. Fesharaki, “A new method for optimal placement of phasor measurement units to maintain full network observability under various contingencies,” Electr. Power Syst. Res., vol. 89, pp. 1–10, 2012.

II. A. Mahari and H. Seyedi, “Optimal PMU placement for power system observability using BICA, considering measurement redundancy,” Electr. Power Syst. Res., vol. 103, pp. 78–85, 2013.

III. B. Milošević and M. Begović, “Nondominated sorting genetic algorithm for optimal phasor measurement placement,” IEEE Trans. Power Syst., vol. 18, no. 1, pp. 69–75, 2003.

IV. C. Chang, “A modified VIKOR method for multiple criteria analysis,” Environ. Monit. Assess., vol. 168, pp. 339–344, Sep. 2010.

V. C. Peng, H. Sun, and J. Guo, “Multi-objective optimal PMU placement using a non-dominated sorting differential evolution algorithm,” Int. J. Electr. Power Energy Syst., vol. 32, no. 8, pp. 886–892, 2010.

VI. C. Ruben, S. C. Dhulipala, A. S. Bretas, Y. Guan, and N. G. Bretas, “Multi-objective MILP model for PMU allocation considering enhanced gross error detection: A weighted goal programming framework,” Electr. Power Syst. Res., vol. 182, p. 106235, 2020.

VII. H. Manoharan, S. Srikrishna, G. Sivarajan, and A. Manoharan, “Economical placement of PMUs considering observability and voltage stability using binary coded ant lion optimization,” Int. Trans. Electr. Energy Syst., vol. 28, no. 9, pp. 1–19, 2018.
VIII. J. Aghaei, A. Baharvandi, A. Rabiee, and M. A. Akbari, “Probabilistic PMU Placement in Electric Power Networks: An MILP-Based Multiobjective Model,” IEEE Trans. Ind. Informatics, vol. 11, no. 2, pp. 332–341, 2015.

IX. J. Aghaei, A. Baharvandi, M. A. Akbari, K. M. Muttaqi, M. R. Asban, and A. Heidari, “Multi-objective Phasor Measurement Unit Placement in Electric Power Networks: Integer Linear Programming Formulation,” Electr. Power Components Syst., vol. 43, no. 17, pp. 1902–1911, 2015.

X. K. Arul jeyaraj, V. Rajasekaran, S. K. Nandha Kumar, and K. Chandrasekaran, “A multi-objective placement of phasor measurement units using fuzzified artificial bee colony algorithm, considering system observability and voltage stability,” J. Exp. Theor. Artif. Intell., vol. 28, no. 1–2, pp. 113–136, Mar. 2016.

XI. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Trans. Evol. Comput., vol. 6, no. 2, pp. 182–197, Apr. 2002.

XII. K. Jamuna and K. S. Swarup, “Multi-objective biogeography based optimization for optimal PMU placement,” Appl. Soft Comput. J., vol. 12, no. 5, pp. 1503–1510, 2012.

XIII. M. Basu, “Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II,” Int. J. Electr. Power Energy Syst., vol. 30, no. 2, pp. 140–149, 2008.

XIV. N. P. Theodorakatos, N. M. Manousakis, and G. N. Korres, “A sequential quadratic programming method for contingency-constrained phasor measurement unit placement,” Int. Trans. Electr. Energy Syst., vol. 25, no. 12, pp. 3185–3211, Dec. 2015.

XV. R. Babu and B. Bhattacharyya, “Strategic placements of PMUs for power network observability considering redundancy measurement,” Meas. J. Int. Meas. Confed., vol. 134, pp. 606–623, 2019.

XVI. S. M. Mazhari, H. Monsef, H. Lesani, and A. Fereidunian, “A multi-objective PMU placement method considering measurement redundancy and observability value under contingencies,” IEEE Trans. Power Syst., vol. 28, no. 3, pp. 2136–2146, 2013.

XVII. S. Opricovic and G.-H. Tzeng, “Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS,” Eur. J. Oper. Res., vol. 156, no. 2, pp. 445–455, Jul. 2004.

XVIII. S. P. Singh and S. P. Singh, “A Multi-objective PMU Placement Method in Power System via Binary Gravitational Search Algorithm,” Electr. Power Components Syst., vol. 45, no. 16, pp. 1832–1845, 2017.

XIX. S. Prasad and D. M. V. Kumar, “Robust meter placement for active distribution state estimation using a new multi-objective optimization model,” IET Sci. Meas. Technol., vol. 12, no. 8, pp. 1047–1057, 2018.

XX. V. Basetti and C. Ashwani Kumar, “Optimal Multi-Objective Hybrid Measurement Placement Using NSGA-II,” i-manager’s J. Power Syst. Eng., vol. 2, no. 3, p. 28, 2014.

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Abstract:

The leaf spring is one of the vital components of an automobile which absorbs vibration from shocks generated due to uneven road surface. It is made up of conventional materials like plain carbon steel are heavy and add weight to vehicle which reduces mileage. This necessitates new material which is light in weight and could provide adequate strength to leaf spring along with higher strain energy absorption to absorb shocks.The current research investigates the application of Graphite Aluminum MMC on leaf spring for mass reduction using Finite Element Method.  The CAD model is developed in ANSYS design modeler and analyzed in workbench.  The design is then optimized using Taguchi Response Surface method using Central Composite Design scheme. The RSM optimization generated specific set values for optimization variables (inner radius and outer radius) along with sensitivity plot and goodness of fit curve. The application of Graphite Aluminum MMC resulted in 56.1% of mass reduction without increase in stress as compared to conventional steel material.

Keywords:

Graphite Aluminum MMC,stress,Leaf Spring,Response Surface,FEA,

Refference:

I. Abbas MKG, Niakan A, Ming CC, Singh R, Teo P, “Design and numerical analysis of leaf spring using composite materials”, International Conference on Material Science and Engineering, pp: 305–310, (2017)
II. Agarwal A, Pitso I, “Modelling & Numerical Exploration of Pulsejet Engine Using Eddy Dissipation Combustion Model”, Material Today Proceedings, Volume:27, part:2, (2020)
III. Akshat Jain, Arun Jindal, Prateek Lakhiani, Sheelam Mishra, “Mathematical Approach to Helical and Wave Spring: A Review”, International Journal of Mechanical and Production Engineering, volume: 5, issue:6, (2017)
IV. Al-Qureshi HA, “Automobile leaf springs from composite materials”, Journal of Materials Processing Technology, volume:118, Issues:1–3, pp: 58-61, (2001)
V. Deshmukh BB, Jaju SB.,“Design and analysis of glass fiber reinforced polymer (GFRP) leaf spring”,IEEE 4th International Conference on Emerging Trends in Engineering and Technology, pp: 82-7(2011)
VI. Goette T, Jakobi R, Puck A,“Fundamentals of the dimensioning of fibre/plastics composite leaf springs for commercial vehicle application”, Kunststoffe – German Plastics,75,pp:17–19 (1985)
VII. Goette T, Jakobi R, Puck A, “On the development of fibre/plastics composite leaf springs for commercial vehicle application”,Kunststoffe – German Plastics,75, pp:20–24(1985)
VIII. Hameed MI, Alazawi DA, Hammoudi ZS,“Finite element analysis of steel and composite leaf springs under static loading”, International Scientific Conference of Engineering, Iraq, pp: 181-185 (2018)
IX. Jenarthanan MP, Ramesh Kumar S, Venkatesh G, Nishanthan S,“Analysis of leaf spring using carbon/glass epoxy and EN45 using ANSYS-A comparison”, Materials Today Proceedings, Volume:5, Issue:6, Part:2, pp: 14512-14519, (2018)
X. J-tJ Kueh, Faris T,“Finite element analysis on the static and fatigue characteristics of composite multi-leaf spring”, J Zhejiang Univ. Sci A,Volume:13,pp 159–164 (2012)
XI. M. Parwani, V. Jain, V. Sharma, “optimization of leaf spring using composite material,” Int. J. Recent Technol. Sci. Manag.,volume 2, pp: 17–26 (2017)
XII. N. Lavanya, P. S. Rao, M. P. Reddy, “Design and Analysis of A Suspension Coil Spring For Automotive Vehicle,” Int. J. Eng. Res. Appl., volume: 4, no. 9, pp. 151–157 (2014)
XIII. Rajendran I., S. Vijayarangan, “Design, analysis, fabrication and testing of a composite leaf spring,” volume: 82, pp: 180–187(2002)
XIV. Shamsaei N, D. Rezaei, “Comparing Fatigue Life Reliability of a Composite Leaf Spring With a Steel Leaf Spring”, Proceedings of the 7th Biennial Conference on Engineering Systems Design and Analysis, ESDA, pp: 371–374 (2004)
XV. Seretse O.M, Agarwal A., Letsatsi M.T., “Exploratory investigation of vibrational characteristics of the Un-damped and Damped Spring Mass Systems”, Journal of Mechanical Engineering Research & Developments, Volume: 4, issue: 3, pp: 96-103 (2018)
XVI. Singh H, Brar GS,“Characterization and investigation of mechanical properties of composite materials used for leaf spring”, Material Today Proceedings, Volume:5, Issue:2,pp: 5857–5863(2018)
XVII. Soner M. et al., “Design and Fatigue Life Comparison of Steel and Composite Leaf Spring”, in SAE 2012 World Congress & Exhibition(2012)
XVIII. Suraj Rawal, “Metal-Matrix Composites for Space Applications”, JOM, Volume:53,Issue:4, pp: 14-17 (2001)
XIX. Thippesh L, “Fabrication of Hybrid Composite Mono-Leaf Spring with Unidirectional Glass Fibers”, Materials Today Proc., volume 5, no. 1, pp: 2980–2984(2018)
XX. Yinhuan Z., X. Ka, H. Zhigao, “Finite element analysis of composite leaf spring,” in 2011 6th International Conference on Computer Science Education (ICCSE), pp: 316–319 (2011)
XXI. Yu W.J, H. C. Kim, “Double tapered FRP beam for automotive suspension leaf spring”, Composite Structure, volume 9, no. 4, pp: 279–300(1988)

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Abstract:

Bus travel is gaining importance during the last decade. Due to its rapidness, easiness in booking and sophisticated travel, ticket booking is slowly shifting from manual to cloud based due to increase in technology awareness. In this paper a ticketing system is designed by using image captured which will be used to predict and update available vacancy which can be further used for booking. This is a fully cloud based system linked to QR code-based wallet linked ticket booking mechanism which is connected to a secured payment gateway. Passenger availability inside the bus will be validated by using QR code which should be scanned near entrance; this validates the current availability and updates the system. The whole system is designed in a way such that it is fully automated and seat vacancy updates dynamically. The whole framework including software and tools will operate from cloud-based servers for increased stability and reliability.  

Keywords:

QR-code,Cloud-based servers,Cloud-based system,Ticketing system,

Refference:

I. Asha P, Albert Mayan J, Canessane A, “Efficient Mining of Positive and Negative Itemsets Using K-Means Clustering to Access the Risk of Cancer Patients”, Communications in Computer and Information Science, ICSCS 2018, Kollam, 2018, pp.373-382

II. C.Upendra Reddy , D.L.S.Vara Prasad Reddy “Bus Ticket System For Public Transport Using Qr Code”, Department Of Cse, Sathyabama Institute of Science and Technology, Chennai, India

III. Jafrul Islam Sojol, Nayma Ferdous Piya, ShalimSadman, “Tamanna Motahar An Automated Passenger Counting System”. Department of Electrical and Computer Engineering, North South University Dhaka, Bangladesh.

IV. Janewit“Vehicle Seat Vacancy Identification using ImageProcessing Technique” Wittayaprapakorn School of Information Technology Mae Fah Luang University Chiangrai, Thailand

V. M.K.Dharani M.Priadarsini K.Tamilselvi “Nifty system for tracking bus and seat availability” Department of CSE Kongu Engineering College,Erode-638 0522 dharani.cse@kongu.edu priadarsini.cse@kongu.edu tamilselvik.cse@kongu.edu

VI. Mohini,Pooja M. Chinchole,Vaishnavi R. Mahajan, S. Shirsath ,Varsha G. Moga “A Review on Smart Bus Ticketing System using QR-Code”. Department of Information Technology Engineering Matoshri College of Engineering and Research Centre

VII. Prof. Balram Timande, “Public Transport System Ticketing system using RFID and ARM processor Perspective Mumbai bus facility”, VLSI & Embedded System design Electronics and Telecommunication Engineering, DIMAT, Associate Professor Department of Electronics and Telecommunication Engineering

VIII. Xiao-Lei, M et al “Transit Smart Card Data Mining for Passenger Origin Information Extraction”, Journal of Zhenjiang University Science (2012),Vol. 13(10), pp.750-760

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Abstract:

Data mining is the process of discovering interesting patterns from the transactional database. In the past decade, numerous techniques have been proposed for mining frequent patterns using single minimum support threshold for all items from the transactional database which results in “rare item issue”. While fixing the minimum support to higher level, it results frequent patterns where rare item are missed. While fixing the minimum support to lower level, it results in too many frequent patterns which is known as combinatorial explosion. To confront the rare item problem, an effort has been made in the literature to find frequent patterns with “multiple minimum supports thresholds”. In this approach, minimum item support (MIS) is given to each item for mining frequent patterns. In this article, comparative analysis is done between MISFP-Growth and MISLP-Growth algorithm for mining frequent patterns using multiple minimum support threshold. In MISLP-Growth algorithm array based structure is adopted which is the major advantage and in MISFP-Growth algorithm pointer based structure is adopted which is the disadvantage. For this, the experiments are conducted using benchmark databases to find the efficient algorithm.From the results produced by these algorithms, it is found that the MISLP-Growth algorithm outperforms MISFP-Growth algorithm for all the databases in the criteria of consumption of runtime and memory.

Keywords:

Data Mining,Multiple Minimum Support, Minimum support, LP-Growth,Frequent Patterns,

Refference:

I. Agrawal, R., and Srikant, R, (1994) ‘Fast algorithms for mining association rules in large databases’, In Proceedings of the 20th International Conference on Very Large Data Bases, VLDB ’94, pp.487–499.
II. Borah, A., and Nath, B, (2019) ‘Rare Pattern Mining: Challenges and Future Perspectives.’ Complex Intell. Syst. 5,pp. 1-23.
III. Chee, C., Jaafar, J., Aziz, I.A. (2019)’ Algorithm for Frequent Itemset Mining: A Literature Review’ Arificial Intelligence,52,pp.2603-2621.
IV. Han, J., Pei, Y., Yin, (2000) ‘Mining frequent patterns without candidate generation’, Proceedings ACM-SIGMOD International Conference on Management of Data (SIGMOD’ 00), Dallas.
V. Han, J., Pei, J., Yin, and Mao, R, (2004) ‘Mining frequent patterns without candidate generation: A frequent- pattern tree Approach, Data Mining in Knowledge Discovery 8(1): pp.53–87.
VI. Hoque, F.A., Easmin, N., and Rashed, K. (2012) ‘Frequent pattern mining for multiple minimum supports with support tuning and tree maintenance on incremental database’, Research of Information Technology J., 3(2): pp.79-90.
VII. Hu, Y.H., and Chen, Y, (2006) ‘Mining association rules with multiple minimum supports: a new mining algorithm and a support tuning mechanism’, Decis. Support Syst., 42(1):pp.1–24.
VIII. Kiran, and Reddy, P.K. (2010) ‘Mining rare association rules in the datasets with widely varying items’ frequencies’, In DASFAA (1), pp. 49–62.
IX. Liu, B., Hsu, W., and Ma. Y. (1999) ‘Mining association rules with multiple minimum supports’. In KDD ’99: Proceedings of the Fifth ACM SIGKDD international conference on Knowledge discovery and data mining, ACM, pages 337–341.
X. Sinthuja, M, Puviarasan, N, and Aruna, P, (2018) ‘Proposed Improved FP-Growth Algorithm with Multiple Minimum Support Threshold Value (MISIFP-Growth) For Mining Frequent Itemset’, International Journal of Research in Advent Technology, Vol.6, May, pp.471-476.
XI. Sinthuja, M, Puviarasan, N, and Aruna, P, (2018) ‘Mining frequent Itemsets Using Top Down Approach Based on Linear Prefix tree’, Springer, Lecture Tabs on Data Engineering and Communications Technologies, Vol.(15), September, pp.23-32.

XII. Sinthuja, M, Puviarasan, N, and Aruna, P, (2018) ‘Geo Map Visualization for Frequent Purchaser in Online Shopping Database Using an Algorithm LP-Growth for Mining Closed Frequent Itemsets’, Elsevier, procedia computer science, Vol.132, pp.1512-1522.
XIII. Sinthuja, M. Puviarasan, N. and Aruna, P, (2019) Frequent Itemset Mining using LP-Growth algorithm based on Multiple Minimum Support Threshold Value (MIS-LP-Growth), Journal of Computational and Theoretical Nanoscience,Volume 16, No(4), pp. 1365-1372(8).

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Abstract:

This paper deals with accurate decoupling capacitance estimation which is commonly used for suppression of power supply noise in modern day system-on-chip. Supply noise is a major issue needs to be addressed for proper functioning which may lead to logic failure in digital integrated circuit. Capacitors directly effects the power consumption and delay parameters and hence the overall performance of integrated circuits.  In this work design verification has been done between the pre-layout stage and post-layout stage. Simulation results show that the difference in results between pre-layout and post-layout stages is marginal. This early detection of errors can be helpful for the designers in the latter stages of the system design. This CAD flow can also be used on any system-on-chip design.

Keywords:

Computer Aided Design (CAD),White Space (WS),System-on-chip (SoC),Power Distribution Network (PDN),Decoupling capacitor (decap),

Refference:

I C. Tirumurti, S. Kundu, S. Sur-Kolay, Y.Chang, “A modeling approach for addressing power supply switching noise related failures of integrated circuits”, Proceedings of Design, Automation and Test in Europe Conference and Exhibition (DATE) pp.: 1078- 1083, 2004.
II D. Kang, C. Yiran, K. Roy, “ Power_ supply Noise- aware Scheduling and Allocation for DSP Synthesis”, Proceedings of Sixth International Symposium on Quality Electronic Design (ISQED’05), 2005
III K. Shah, “Power Grid Analysis in VLSI Designs”, Dissertation in Master of Science (Engineering),Super Computer Education and Research Centre, Indian Institute of Science Bangalore, 2007.
IV K. Shimazaki, T. Okumura, “A Minimum Decap Allocation Technique Based on Simultaneous Switching for nano-scale SoC”. Proceedings of IEEE Custom Integrated Circuits Conference, 2009.
V M. Khellah, D. Khalil, D. Somasekhar, Y. Ismail, T. Karnik, V.De, “Effect of power supply noise on SRAM dynamic stability”, Proceedings of Symposium on VLSI Circuits 2007.
VI M. Saint-Laurent, M. Swaminathan,“Impact of power-supply noise on timing in high frequency microprocessors”, IEEE Transactions on Advanced Packaging, Vol.:27, pp.: 135-144, 2004.
VII P. Mitra, J. Bhaumik, “Pre-Layout Decap Allocation for Noise suppression and Performance Analysis for 512-Point FFT core”, Proceedings of 2017 Devices for Integrated Circuits (DevIC), pp.: 341-345, 2017.
VIII P. Mitra, J.Bhaumik, “A CAD Approach for Suppression of Power Supply Noise and Performance Analysis of Some Multi-core Processors in Pre-layout Stage”, Microsystem Technologies, Springer, Vol.: 25, Issue: 5, pp.: 1977-1986, 2019.
IX S. Pant, “Design and analysis of Power Distribution Networks in VLSI Circuits”, Ph.D. Dissertation, University of Michigan, 2008.
X S. Zhao, K. Roy, C.K. Koh, “Decoupling Capacitance Allocation and Its Application to Power-Supply Noise-Aware Flooring”, IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems, Vol.: 21, Issue: 1, pp.: 81-92, 2002.
XI T.C. Hsueh, F. O’Mahony, M. Mansuri, B. Casper, “An On-Die All-Digital Power Supply Noise Analyzer with Enhanced Spectrum Measurements”, IEEE Journal of Solid-State Circuits, Vol.: 50, Issue: 7, pp.:1711-1721, 2015.
XII T. Karim, “On-Chip Power Supply Noise: Scaling, Suppression and Detection”, Ph.D. Dissertation, University of Waterloo, 2012.
XIII Y.L. Chuang, P.W. Lee, Y.W. Chang, “Voltage-Drop Aware Analytical Placement by Global Power Spreading for Mixed-Sized Circuits Design”, IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems, Vol.: 30, Issue: 11, pp. 1649-1662, 2011.
XIV Y. Shi, J. Xiong, C. Liu, L. He,“Efficient Decoupling Capacitance Budgeting Considering Operation and Process Variations”, IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems, Vol.: 27, Issue: 7, pp.: 1253-1263, 2008.

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Abstract:

This paper details anM/M/1 system with breakdowns, two varieties of repair facilities, timeout and vacation. As soon as the system is vacant, the server pauses for a period 'c'. If no unit arrives at this time, the server get-away otherwise instigate the service to all the customers who gets in. There will be no delay in repair if the system breaks down as it is aided with two varieties of Repair facilities (TRF) based on the stage of service where it has failed. More clearly repair of Type-1 will be started with a chance of 1-q if the server fails atamidst of service and the other type is started with a likelihood q if failurehappens before the staring of service”. Various constants are derived and also done sensitivity analysis.

Keywords:

Vacation queuing system, two varieties of Repair facilities and timeout,breakdowns, length of the system,

Refference:

I Doshi, B.T (1986), Queuing system with vacations. A survey on queuing system: Theory and Applications. 1(1), 29-66.
II GeniGupur, (2010), Analysis of the M/G/1 retrial Queuing Model with server breakdowns. Oper. 1:313-340.
III H.White and L. Christie. (1958),Queuing with preemptive priorities or with breakdown. Operations System, vol. 6(1), 79-95.
IV K.C. Madan, (2003), An M/G/1 type queue with Time-Homogeneous Breakdowns and Deterministic Repair Times, Soochow Journal of Mathematics Volume 29, No. 1, pp. 103110..
V Levy.Y and Yechiali. U, (1975), Utilization of Idle Time in an M/G/1 Queuing System. Management Science, 22, 202-211. http://dx.doi.org/10.1287/mnsc.22.2.202.
VI Oliver C. Ibe (2007) Analysis and optimization of M/G/1 Vacation Queuing Systems with Server Timeout, Electronic Modeling, V.29, no. 4, ISSN 0204-3572.
VII S.Bama, M.I.Afthab Begum and P.Fijy Jose, (2015), Unreliable MX/G/1 queueing system with two types of Repair. International Journal of Innovative Research & Development, Vol. 4, No. 10, pp. 25-38.
VIII Y.Saritha, V.N. Rama Devi and K.Chandan (2020), M/G/1 Queue with Vacation, Two Cases of Repair Facilities and Server Timeout.TEST Engineering and Management,Vol.82,pp. 16358 – 16363.

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Abstract:

In the underwater sensor network, the accurate position of every sensor node is of prime importance and the procedure of finding the node coordinates is known as localization. Localization plays a vital role in the designing and functioning of any Underwater Sensor Network(UWSN).Cheng et al(III) prove effective localization algorithm has a greater influence on the performance of the network.Recent research exists in the field of exploring meta-heuristic based localizationalgorithms for effective sensor node localization by Kulkarniet al. (XI), and Kumaret al.(XII). The research contributions of  Li& Wang (XIII), Goyal S Patterh& MS (VII) have proved that the cuckoo search(CS) algorithm is comparatively effectivebecause of its distinctiveness of few parameters thus dropping the computational complication and communication overhead.CS has also proved to have better proficient

Keywords:

Sensor,cuckoo,search, underwater,network, node,

Refference:

I. Adnan A and Razzaque MA, “A comparative study of Particle Swarm Optimization and Cuckoo Search techniques through problem-specific distance function”, Proceedings of Information and Communication Technology (ICoICT), vol. 160(1), pp. 83-92, 2013.
II. Arora S and Singh S,“A conceptual comparison of firefly algorithm, bat algorithm and cuckoo search”, Proceedings of International conference on Control Computing Communication and Materials (ICCCCM), pp. 1-4, 2013.
III. Cheng J and Xia L, “An Effective Cuckoo Search Algorithm for Node Localization in Wireless Sensor Network”,Sensors, Vol.16(9), pp.1390-1407, 2016.
IV. Cheng W, Teymorian AY, Ma L, Cheng X, Lu X, and Lu Z, “Underwater Localization in Sparse 3D Acoustic Sensor Networks”, Proceedings of 27th IEEE Conference on Computer Communications, pp. 236-240, 2008.
V. Doherty L,Pister K, and El Ghaoui L, “Convex Position Estimation in Wireless Sensor Networks”, Proceedings of the INFOCOM 2001- Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies, Helsinki, Finland, Volume 3, pp. 1655–1663, 2001.
VI. Gao J, Shen X, Zhao R ,Mei H, and Wang H, “A Double Rate Localization Algorithm with One Anchor for Multi-Hop Underwater Acoustic Networks” , Sensors, Vol.17(5), pp.984-1001, 2017.
VII. Goyal S and Patterh MS, “Wireless sensor network localization based on cuckoo search algorithm”, Journal of Wireless Personal Communication, vol. 79, pp. 223-234, 2014.
VIII. Han G, Jiang J, Shu L, Xu Y, and Wang F, “Localization Algorithms of Underwater Wireless Sensor Networks: A Survey”, Journal of Sensors, pp. 2026-2061, 2012.
IX. Han G, Zhang C, Shu L, and Rodrigues JJPC, “Impacts of Deployment Strategies on Localization Performance in Underwater Acoustic Sensor Networks”, IEEE Transactions on Industrial Electronics, vol. 62(3), pp. 1725-1733, 2015.
X. Harikrishnan R, Kumar VJS, and Ponmalar PS, “Firefly algorithm approach for localization in wireless sensor networks”, Proceedings of 3rd International Conference on Advanced Computing, pp. 209-214, 2016.
XI. Kulkarni RV, Venayagamoorthy GK, and Cheng MX, “Bioinspired node localization in wireless sensor networks”, Proceedings of International Conference on Systems, Man and Cybernetics, IEEE, pp. 205-210, 2009.
XII. Kumar A, Khosla A, Saini JS, and Singh S, “Meta-heuristic range based node localization algorithm for Wireless Sensor Networks”, In Proceedings of the IEEE International Conference on Localization and GNSS, pp. 1-7, 2012.
XIII. Li SP and Wang XH, “The research on Wireless Sensor Network node positioning based on DV-hop algorithm and cuckoo searching algorithm”, Proceedings of the IEEE International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC), pp. 620-623, 2013.
XIV. Priyadharsini Cand Kannimuthu S, “Polyhedron Model for Three Dimensional Node Deployment in Underwater Sensor Network”, Journal of Computational and Theoretical Nanoscience, vol. 14(12), pp. 5858-5862, 2017.
XV. Solihin MI and Zanil MF, “Performance comparison of cuckoo search and differential evolution algorithm for constrained optimization”, International Engineering Research and Innovation Symposium (IRIS), pp. 1-8, 2016.
XVI. Yang XS and Deb S, “Cuckoo Search via Levy Flights”, Proceedings of World Congress on Nature and Biologically Inspired Computing (NaBIC 2009), pp. 210-214, 2009.

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Abstract:

A series of glasses by melt quenching method fabricated for spectroscopic investigations of Dy³⁺ ions doped Antimony (Sb)-Magnesium (Mg)-Strontium (Sr) Oxyfluoroborate (BSbMgFS) glasses. The structural and optical characterizations such as XRD, Raman, UV-visible-NIR absorption spectroscopy, photoluminescence (PL) (excitation and emission), were skilled to study the various properties of the glasses. Amorphous nature of present glass confirm from the broad peaks of XRD.  The transitions from lowest energy state to excited state in RE³⁺ ions were identified using optical UV-visible-NIR absorption spectra. By using Judd-Ofelt theory the J-O intensity parameters Ω_λ (λ = 2, 4, 6) have been evaluated from experimental (f_exp) and calculated (f_cal) oscillator strengths. The value of Ω₂ is higher than Ω₄ and Ω₆ and follows the trend Ω₂˃ Ω₆˃ Ω₄. This confirms the high covalency of Dy³⁺ ion with ligands and more asymmetric environment around the rare earth ion in host. The emission of light from glass system was concluded through PL spectra (Excitation and emission) for Dy³⁺ion. In the present work branching ratio of ⁴F_9/2→⁶H_13/2transition is obtained higher than 50% (0.55). The highest readings of A_R, β_R and σ_se are obtained for the transition n ⁴F_9/2→⁶H_13/2 (yellow).Hence, this can be consider as an appropriate mechanism for lasing action. Gain band width (Δλ_eff x σ_se)and optical-gain (σ_se x τ_R) were found to be high for BSbMgFSDy01 and this suggest that BSbMgFSD01 glasses were appropriate for optical amplifier. In the present study of Dy³⁺ -doped glasses, BSbMgFSD05 has shown highest emission with a Y/B ratio of 2.73 which is useful for white-LED applications. BSbMgFSDy05 glass is suitable for white light emitting devices and lasers applications in the visible region at 575 nm upon excitation of 425 nm.

Keywords:

Photoluminescence, Judd-Ofelt theory, PL spectra,Dy3+ -doped glasses,

Refference:

I. A. Lira, A. Speghini, E. Camarillo, M. Bettinelli, U. Caldino, Spectroscopic evaluation of Zn (Po3): Dy3+ glass as active medium of solid state laser, Opt. Mater. 38 (2014) 188.

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VII. C. Nageswara Raju, S.Sailaja, S. Hemasundara Raju, S.J.Dhoble, U.Rambabu, Young-Dahl Jho, B.Sudhakar Reddy, Emission analysis of CdO–Bi2O3–B2O3 glasses doped with Eu3+ and Tb3+,Ceramic.International 40(2014) 7701–7709.

VIII. D.K. Sardar, W.M. Bradly, R.M. Yow, J.B. Gruber, B. Zandi, J. of Luminescence 106 (2004) 195-203.

IX. D. Rajesh, Y.C. Ratnakaram, M. Seshadri, A. Balakrishna, T. Satya Krishna, Structural and luminescence properties of Dy3+ ion in strontium lithium bismuth borate glasses J. Lumin. 132 (2012) 841-849.

X. G. Chinna Ram, T. Narendrudu, S. Suresh, A. Suneel Kumar, M.V. Sambasiva Rao, V. Ravi Kumar, D. Krishna Rao, Investigation of luminescence and laser transition of Dy3+ion in P2O5-PbO-Bi2O3 -Dy2O3 glasses, Optical Materials 66 (2017) 189-196.

XI. G. S. Ofelt, Intensities of crystal spectra of rare earth ions, J. Chem. Phys. 37 (1962) 511.

XII. G. Venkata Rao, C.K. Jayasankar., “Dy3+-doped tellurite based tungsten zirconium glasses: Spectroscopy study”, J. Mol. Struct. 1084 (2015) 182-189.

XIII. H.A. Othman, G.M. Arzumanyan, D. Moncke, The effect of alkaline earth oxides and cerium concentration on the spectroscopic properties of Sm/Ce doped lithium alumino-phosphate glasses Opt. Mater. 62 (2016) 689–696.

XIV. J. Juarez-Batalla, A.N. Meza-Rocha, G.Munoz, H.I.Camarillo, U.Caldino, Luminescence properties of Tb3+-doped zinc phosphate glasses for green laser application, Opt Mater. 58(2016) 406–411.

XV. Kenyon A.J, “Recent developments in rare-earth doped materials for optoelectronics, Prog. J. Quantum Electron, 26(2002) 225–284.

XVI. K. Jaroszewski, P. Głuchowski, M. Chrunik, R. Jastrz, A. Majchrowski, D. Kasprowicz, Near-infrared luminescence of Bi2ZnOB2O6:Nd3+/PMMA composite, Optical Materials 75 (2018) 13-18.

XVII. K.S.V. Sudhakar, M. Srinivasa Reddy, L. Srinivasa Rao, N. Veeraiah, Influence of modifier oxide on spectroscopic and thermoluminescence characteristics of Sm3+ ion in antimony borate glass system, J. of Luminescence 128 (2008) 1791– 1798.

XVIII. K. Swapna, Sk. Mahamuda, A. Srinivasa Rao, M. Jayasimhadri, T. Sasikala, L. Rama Moorthy, Optical absorption and luminescence characteristics of Dy3+ doped Zinc Alumino Bismuth Borate glasses for lasing materials and white LEDs, Journal of Luminescence 139 (2013) 119 -124.

XIX. K. Vijaya Babu, Sandhya Cole, Luminescence properties of Dy3+-doped alkali lead alumino borosilicate glasses, Ceramics International(2018) 9080-9090.

XX. K.V. Krishnaiah, K. Upendra Kumar, C.K. Jayasankar, Mater. Exp. 3 (2013) 61-70.

XXI. L. Eyring (Ed.), Progress in the Science and Technology of the Rare Earths, Pergamon, London (1966).

XXII. M.J. Plodinec, Borosilicate glass for nuclear waste immobilisation, Glass Technol. 41(2000), 186-192.

XXIII. M. Kemere, J. Sperga, U. Rogulis, G. Krieke, J. Grube, Structural and optical studies on Sm3+ ions doped bismuth fluoroborate glasses for visible laser applications, J. Lumin. 181 (2017) 25–30.

XXIV. M. Sundara Rao, V. Sudarsan, M.G. Brik, Y. Gandhi, K. Bhargavi, M. Piasecki, I.V. Kityk, N. Veeraiah, De-quenching influence of aluminum ions on Y/B ratio of Dy3+ ions in lead silicate glass matrix, Journal of Alloys and Compounds 575 (2013) 375-381.

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XXVI. Nisha Deopa, A.S. Rao, Photoluminescence and energy transfer studies of Dy3+ ions doped lithium lead alumino borate glasses for w-LED and laser applications, J. of Luminescence 192 (2017) 832–841.

XXVII. N. Kiran, A. Suresh Kumar., “White light emission from Dy3+ doped sodium lead borophosphate glasses under UV light excitation”, J. Mol. Struct. 1054 (2013) 6-11.

XXVIII. P. Suthanthirakumar, K. Marimuthu, Investigations on spectroscopic properties of Dy3+ doped zinc telluro-fluoroborate glasses for laser and white LED application,J. Mol. Struct. 1125 (2011) 443-452.

XXIX. R.C. Lucacel, I. Ardelean, FT-IR and Raman study of silver lead borate-based glasses, J. Non-Cryst. Solids. 353 (2007) 2020-2024.
XXX. S. Abed, H. Boughrraf, K. Bouchouit, Z. Sofiani, B. Derkowska, M.S. Aida, B. Sahraoui, Influence of Bi doping on the electrical and optical properties of ZnO thin films, Superlattice Microstruct. 85 (2015) 370-378.

XXXI. S.D. Jackson, Continuous wave 2.9µm dysprosium-doped fluoride fiber laser, Appl. Phys. Lett. 83 (2003) 1316-1318.

XXXII. S. Gai, C. Li, P. Yang, J. Lin, Recent progress in rare earth micro/nanocrystals: soft chemical synthesis, luminescent properties, and biomedical applications, Chem. Rev. 114 (2014) 2343-2389.

XXXIII. Sk. Mahamuda, K. Swapna, P. Packiyaraj, A. Srinivasa Rao, G. Vijaya Prakash, Lasing potentialities and white light generation capabilities of Dy3+ doped oxyfluoro borate glasses, J.Lumin. 153 (2014) 382−392.

XXXIV. Sudhakar Reddy: Judd–Ofelt theory: optical absorption and NIR emission spectral studies of Nd3+: CdO–Bi2O3– B2O glasses for laser applications, J Mater Sci. 47 (2012) 772–778.

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XXXIX. W.T. Carnall, P.R. Fields, K.Rajnak, Electronic Energy Levels in the Trivalent Lanthanide AquoIons. I. Pr3+, Nd3+, Pm3+, Sm3+, Dy3+, Ho3+, Er3+, and Tm3+, J. Chem. Phys. 49 (1968) 4424–4442.

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Abstract:

Orthogonal Frequency Division Multiplexing (OFDM) is one of the best techniquesfor improving bandwidthefficiently and combating multipath fading by choosing proper modulation scheme in wireless communications. However, this technique has a major drawback of   high Peak-to-Average Power Ratio (PAPR) which makes transmitter section inefficient by leading to power inefficiency in the Radio Frequency section Therefore OFDM with high PAPR makes the high power amplifier nonlinear and decreases efficiency of power and generates a nonlinear distorted output, and thereby reducing performance of both spectral efficiency and energy efficiency. These drawbacks of OFDM can be mostly reduced by using proposed 5G transmission schemes.

Keywords:

PAPR,5G,Spectral efficiency,OFDM,Radiofrequency,

Refference:

I. A Lomayev, A Maltsev, A Khoryaev, A Sevastyanov, R Maslennikov, in 7th IEEE Consumer Communications and Networking Conference. Comparisonof Power Amplifier Non-Linearity Impact on 60 GHz Single Carrier andOFDM Systems, (2010), pp. 1–5. doi:10.1109/CCNC.2010.5421601

II. G Fettweis, S Bittner, M Krondorf, in 69th IEEE Vehicular Technology Conference. GFDM – Generalized Frequency Division Multiplexing, (2009),pp. 1–4. doi:10.1109/VETECS.2009.5073571

III. H Bouhadda, H Shaiek, D Roviras, Y Medjahdi, R Bouallegue, Theoretical analysis of BER performance of nonlinearly amplified FBMC/OQAM and OFDM signals. EURASIP J. Adv. Signal Process. 2014(1), 1–16 (2014). doi:10.1186/1687-6180-2014-60

IV. JG Andrews, W Choi, S Buzzi, SV Hanly, A Lozano, ACK Soong, JC Zhang, What will 5G be? IEEE J. Sel. Areas Commun. 32(6), 1065–1082 (2014). doi:10.1109/JSAC.2014.2328098

V. K.Mahender, K.S. Ramesh T.Anilkumar. “Simple Transmit Diversity Techniques for Wireless Communications”, Smart Innovations in Communication and Computational Sciences, Advances in Intelligent Systemsand Computing 669, https://doi.org/10.1007/978-981-10-8968-8_28, pp. 329-342,2019

VI. K.Mahender, K.S. Ramesh T. Anilkumar, “An Efficient OFDM system with reduced PAPR for combating multipath fading”,Journal of advanced research in dynamical and control systems.9: 1939-1948.

VII. K.Mahender, K.S. Ramesh, “PAPR analysis of fifth generation multiple access waveforms for advanced wireless communication”,International journal of engineering and technology,Vol 7,No.(3.34) (2018) 487-490

VIII. K.Mahender, T.Anilkumar, “AN EFFICIENT FBMC BASED MODULATION FOR FUTUREWIRELESS COMMUNICATIONS”,ARPN Journal of engineering and applied science,ISSN 1819-6608,vol 13,no.24,DEC-2018

IX. K.S. Ramesh, K.Mahender, T.Anilkumar, “Analysis of Multipath Channel Fading Techniques in Wireless Communication systems”, American Institute of Physics,AIP Conference Proceedings1952, 020050; doi: 10.1063/1.5032012.

X. MG Bellanger, FBMC physical layer: a primer. Technical report, PHYDYAS (2010). http://www.ict-phydyas.org/teamspace/internal-folder/FBMCPrimer_ 06-2010.pdf. Accessed 4 Oct 2016

XI. M Matthe, I Gaspar, D Zhang, G Fettweis, in 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall). Near-ml detection for mimo-gfdm,(2015), pp. 1–2. doi:10.1109/VTCFall.2015.7391033

XII. T. Anilkumar, K.Mahender, K.S. Ramesh, “Performance study of OFDM over Multipath Fading channels for next Wireless communications”,International journal of applied engineering research , ISSN 0973-4562, 12(20): 10205-10210.

XIII. T. Anilkumar, K.Mahender, K.S. Ramesh, “SER and BER Performance analysis of digital modulation scheme over multipath fading channel”,Journal of Advanced Research in Dynamical and Control Systems,vol 9,issue 2,pp 287-291

XIV. T Wild, F Schaich, Y Chen, in 79th IEEE Vehicular Technology Conference. Waveform Contenders for 5G—Suitability for Short Packet and Low Latency Transmissions, (2014), pp. 1–5. doi:10.1109/VTCSpring.2014.7023145

XV. T Wild, D Zhang, F Schaich, Y Chen, in 19th International Conference on Digital Signal Processing. 5G Air Interface Design Based on Universal Filtered(UF-)OFDM, (2014), pp. 699–704. doi:10.1109/ICDSP.2014.6900754

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