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RELATIONSHIP BETWEENCOLORING,EMBEDDINGAND DECYCLING NUMBER OF A GRAPH

Authors:

Sajid Hussain, Ren Han, Nisar Hussain Khoja

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00011

Abstract:

A set  of vertices of a graph  is said to be a decycling set if  is acyclic. The size of a minimum decycling set of  is called the decycling number of  and it is denoted by In this paper, our chief objectives areto obtain the upper bound of the decycling number of a graph by using graph chromatics number and its order. The relation of the genus of the surface  and the decycling number of a graph embedded in surface  is studied. The decycling number of a planar graph with  vertices is conjectured to be , which is shown in this paper if the girth of the graph is at least four. The decycling number of a graph with  vertices and maximum degree three is proved to be at most Also, we completely investigatethe decycling number of the hypercube .

Keywords:

Decycling number,Chromatic number,Maximum degree,Embedding,Girth,hypercube,

Refference:

I Albertson M and Berman D., The acyclic chromatic number, Congr. Number., 17(1976),51-69.
II BauS and Beineke L., The decycling number of graphs, Australas J. Combin., 25(2002),285-298.
III Beineke L and Vandell R., Decycling graphs, J.Graph Theory, 25(1997), No.1:59-77.
IV Beineke L and Harary F., The genus of the n-cube, Canad. J.Math.17(1965),494-496.
V Bondy J.A and Murty U.S.R., Graph Theory, Springer, 2008.
VI Brooks R.L, on coloring the nodes of a network, Proc. Cambridge Philos. Soc.37(1941),194-197.
VII Chartrand G, Kronk H.V and Wall C.E., The point-arboricity of a graph, Israel J. Math. (1968) 6:169C175.
VIII ErdÖs P, Saks M and Sós V, Maximum induced trees in graphs, J. Combin. Theory Ser.B,41(1986),61-79.
IX Festa P,Pardalos P.M and Reseude M.G.C., Feedback set problem, in Handbook ofCombinatorial Optimization, Supplement Vol. A Kluwer, Dordrecht, (1999),209-258.
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XII Kirchhoff K, Über die Auflösung der Gleichungen, auf welche man bei derUntersuchung der linearen VerteilunggalvanischerStrömeGfϋhrtwird, Ann.Phy. Chem, 72 (1847) 497-508.
XIII Liu J.P and Zhao C, A new bound on the feedback vertex sets in cubic graphs, Discrete Math., 184(1996), 119-131.
XIV Long S.D., Ren H, The decycling number and maximum genus of cubic graphs, Journal of GraphTheory, 88 (2018),375 C384.
XV Pike D.A, Decycling hypercubes, Graphs and Combin., 19(2003),547-550.

XVI Pike D.A and Zou Y., Decycling cartesian products of two cycles, SIAM J. Discrete Math. 19(2005),No. 3:651-663.
XVII Punnim N, Decycling connected regular graphs, Austral. J. Combin., 35(2006), 155 169.
XVIII Punnim N, The decycling number of regular graphs, Thai J. Math.,4(2006),145-161.
XIX Ren H, Yang C., and T.X Zhao, A new formula for the decycling number of regular graphs, DiscreteMath. 340(2017),3020-3031.
XX Thomassen C, Five-coloring maps on surfaces, J.Combin. Theory Ser.B,59(1993),89-105.
XXI White A.T, Graphs of groups on surfaces, Elsevier, Amsterdam, London, New York, Oxford, Paris, Shannon, Tokyo, 2001.
XXII Wilson R.J, Introduction to graph theory 4th Ed., Addison –Wesley Longman, Reading MA. (1996).
XXIII Zheng M and Lu X, On the maximum induced forests of a connected cubic graph without triangles, Discrete Math.,85(1990), 89-96.

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REAL TIME MONITORING OF WOMAN SAFETY WITH LOCATION TRACKING SYSTEM

Authors:

Sharvani Yedulapuram, Rajeshwarrao Arabelli, K. Ravi kiran, Kanegonda Ravi Chythanya

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00012

Abstract:

According to the organizations like NCRB-social government and the reports of WHO, 35% women are subjected to physical harassment, abuse and violence that occur even in public places such as cabs, hospitals, public transport, public parks, in and around schools, railway-bus stands, foot paths, and worse in the very own neighbors. Changing dynamics of working environment also forces many to work in night shifts which make them to move out in vulnerable timings. In India, according to amendment to the Factories Act 1948, it was allowed under the law for women to work night shifts which enabled many women to work through shifts but also put them in risk. Most of the women are working in nightshiftsimply there is an increase in their productivity, quality and international competitiveness because of which many women tend to work nowadays and support their families. Companies always provide necessary security measures in place to ensure women safety, yet in several situations incidents happened to prove the vulnerability of them due to several attributes. Research works were being undertaken to device strategies, protocols, policies to protect women workforce from being vulnerable.   In this paper an attempt is made to make a device for the women security where the device provides the safety measure in public places, public transports such as cabs, schools, buses and company vehicle etc. We propose an advanced model, which aims to provide a safe environment for women in the society through live video streaming by embedding sensors with a processor chip. The core of the entire system is raspberry pi, Pi Camera which is used for video data which will be collected by the embedded system and sent to the cloud by wireless network. Through this device a live video camera is implemented in the device which feds the live video through a GPS module that can be used to trace the whereabouts and the issues a woman may face which can be used to rescue under distress situation.

Keywords:

Raspberry Pi,Embedded System,Pi camera, Image Capture,Video Streaming,

Refference:

I. A Research Study on “Night Shift for Women: Growth & Opportunities” Conducted by theAssociated Chambers of Commerce & Industry of India (ASSOCHAM), New Delhi; 2016;www.ncw.nic.in.

II. Arabelli, R.R. &Rajababu, D. 2019, “Transformer optimal protection using internet of things”, International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 11, pp. 2169-2172.

III. Arabelli, R.R.&Revuri, K. 2019, “Fingerprint and Raspberri Pi based vehicle authentication and secured tracking system”, International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 5, pp. 1051-1054.

IV. Ashlesha Wankhede, Ashwini velankar, Priyanka Shinde “PORTABLE DEVICE FOR WOMEN SECURITY”. IJRET, eISSN:2319-1163|p ISSN:2321-7308.

V. C. Garcia-Moreno, H. A. Jansen, M. Ellsberg, L. Heise, and C. H. Watts, “Prevalence of intimate partner violence: findings from the WHO multi-country study on women’s health and domestic violence,” The Lancet, vol. 368, no. 9543, pp. 1260–1269, 2006.View at: Publisher Site | Google Scholar

VI. C. Garcia-Moreno, L. Heise, H. A. F. M. Jansen, M. Ellsberg, and C. Watts, “Violence against women,” Science, vol. 310, no. 5752, pp. 1282–1283, 2005.View at: Publisher Site | Google Scholar

VII. Chheda, Dhaval, et al. “Smart Projectors Using Remote Controlled Raspberry Pi.” International Journal of Computer Applications, vol. 82, no. 16, Nov. 2013, pp. 6–11. DOI.org (Crossref), doi:10.5120/14245-2250.

VIII. “Dynamic Smart Alert Service for Women Safety System.” International Journal of Communication and Computer Technologies, vol. 5, no. 2, Jan. 2019. DOI.org (Crossref), doi:10.31838/ijccts/05.02.05.

IX. Guruge, Sepali,et al. “Violence against Women: An Exploration of the Physical and Mental Health Trends among Immigrant and Refugee Women in Canada.” Nursing Research and Practice, vol. 2012, 2012, pp.1-15.DOI.org (Crossref), doi:10.1155/2012/434592.

X. H. Crawley and T. Lester, Comparative Analysis of Gender-Related Persecution in National Asylum Legislation and Practice in Europe, United Nations High Commissioner for Refugees Evaluation and Policy Analysis Unit, Department of International Protection, and Regional Bureau for Europe, Geneva, Switzerland, 2004.

XI. Heise, Lori, et al. Violence against Women: The Hidden Health Burden. World Bank, 1994.

XII. Huu-Quoc Nguyen, et al. “Low Cost Real-Time System Monitoring Using Raspberry Pi.” 2015 Seventh International Conference on Ubiquitous and Future Networks, IEEE, 2015, pp. 857–59. DOI.org (Crossref), doi:10.1109/ICUFN.2015.7182665.

XIII. John Lekan, Akinode. (2011). IMPROVING NATIONAL SECURITY USING GPS TRACKING SYSTEM TECHNOLOGY.

XIV. R. Sundaramurthy and V. Nagarajan, “Design and implementation of reconfigurable virtual instruments using Raspberry Pi core,” 2016 International Conference on Communication and Signal Processing (ICCSP), India, 2016, pp. 2309-2313.

XV. T. H. Mahony, Women in Canada: A Gender-Based Statistical Report, Statistics Canada, Ottawa, Canada, 2011.

XVI. Video surveillance using raspberry Pi architecture, R Shete, M Sabale – The International Daily journal ISSN, 2015 – researchgate.net

XVII. Vinay Sagar KN, Kusuma S M, “Home automation using Internet of things”, International research journal of Engineering and Technology (IRJET) Volume: 02 Issue: 03- June-2015.

XVIII. WHO, Violence against Women. Health Consequences, World Health Organization, Geneva, Switzerland, 1997.

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A SCIENTIFIC APPROACH TO CONTROL THE SPEED DEVIATION OF DUAL REGULATED LOW-HEAD HYDRO POWER PLANT CONNECTED TO SINGLE MACHINE INFINITE BUS

Authors:

Nagendrababu Mahapatruni, Velangini Sarat P., Suresh Mallapu, Durga Syamprasad K.

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00013

Abstract:

Analysis of single machine infinite bus system is made by considering single Kaplan turbine-generator with exciter and governor for the small-signal stability. In this research paper a scientific approach was adopted to minimize the settling time along with the stability of the given power system. Kaplan turbine generators were predominantly implemented in hydroelectric power plants with lower heads. However, dual regulation of such turbines in the plants are renowned in the current research trends. The dual regulation of hydro-turbine is incorporated through the operation of both wicket gate and runner blade position. In a worldwide scenario Kaplan turbine-generators play a vital role in power and energy generation. Whereas the life of these generator gates or runner blades depends on speed deviations. In this context, a PID controller has been designed for the extended single machine infinite bus system to improve the speed deviation. The results of the extended single machine infinite bus system are compared with and without PID controller for the enhancement of speed deviation.

Keywords:

Power System,Extended SMIB,Governor,Speed deviation,PID controller,

Refference:

I. Amar President, O., Hocine Supervisor, L., & Nadia Examiner MCB, B. (2019). People’s Democratic Republic of Algeria Ministry of Higher Education and Scientific Research THEME: Study of a Grid-Connected Photovoltaic System.
II. Bharatiraja, C., Kasilingam, G., Pasupuleti, J., Bharatiraja, C., & Adedayo, Y. (n.d.). Single Machine Connected Infinite Bus System Tuning Coordination Control using Biogeography-Based Optimization Algorithm. scindeks.ceon.rs.
III. Björk, J., & Johansson, K. (2019). Control Limitations due to Zero Dynamics in a Single-Machine Infinite Bus Network.
IV. Bux, R., Xiao, C., Hussain, A., & Wang, H. (2019, 11 16). Study of Single Machine Infinite Bus System with VSC Based Stabilizer. dl.acm.org, 159-163.
V. Chaib, H., Allaoui, T., Brahami, M., & Denai, M. (n.d.). Modelling, Simulation and Fuzzy Self-Tuning Control of D-STATCOM in a Single Machine Infinite Bus Power System.
VI. Chan, Z., & Aung, Z. (2020). Zar Ni Aung.
VII. Chen, J., & Engeda, A. (n.d.). IOP Conference Series: Earth and Environmental Science Design considerations for an ultra-low-head Kaplan turbine system Design considerations for an ultra-low-head Kaplan turbine system. iopscience.iop.org.
VIII. Czeslaw Banka, J. (2017). A RESEARCH PLAN FOR ASSESSING THE POWER AND ENERGY CAPABILITY OF A RIVER NETWORK UNDER AN INTEGRATED WIND/HYDRO-ELECTRIC DISPATCHABLE RÉGIME.
IX. Garbin, D. (2018). Analysis for the assessment of the wave energy and ISWEC productivity along the argentinian coast.
X. Ghosh, A., Das, A., & Sanyal, A. (2019, 10 1). Transient Stability Assessment of an Alternator Connected to Infinite Bus Through a Series Impedance Using State Space Model. Journal of The Institution of Engineers (India): Series B, 100(5), 509-513.
XI. GROULT, M. (2018). Optimization of Electromechanical Studies for the Connection of Hydro Generation MATHIEU GROULT KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ELECTRICAL ENGINEERING.
XII. Guo, B. (2019). Modelling and advanced controls of variable speed hydro-electric plants.
XIII. Haghighi, M., Mirghavami, S., Chini, S., energy, A.-R., & 2019, u. (n.d.). Developing a method to design and simulation of a very low head axial turbine with adjustable rotor blades. Elsevier.
XIV. Haghighi, M., Mirghavami, S., Ghorani, M., Energy, A.-R., & 2020, u. (n.d.). A numerical study on the performance of a superhydrophobic coated very low head (VLH) axial hydraulic turbine using entropy generation method. Elsevier.
XV. Houde, S., & Deschênes, C. (2019). Numerical investigation of flow in a runner of low-head bulb turbine and correlation with PIV and LDV measurements.
XVI. J French – US Patent 9, 8., & 2018, u. (2018). DIE K A N I K A N AT A UN.
XVII. Jacobsen, T. (2019). Distributed Renewable Generation and Power Flow Control to Improve Power Quality at Northern Senja, Norway.
XVIII. Kim, S. (2019, 9 17). Proportional-type non-linear excitation controller with power angle reference estimator for single-machine infinite-bus power system. IET Generation, Transmission and Distribution, 13(18), 4029-4036.
XIX. Komlanvi, A. (2018). Computer aided design of 3D of renewable energy platform for Togo’s smart grid power system infrastructure Item Type Thesis.
XX. Machowski, J., Bialek, J., & Bumby, J. (2020). POWER SYSTEM DYNAMICS Stability and Control Second Edition.
XXI. Mashlakov, A. (2017). SIMULATION ON DISPERSED VOLTAGE CONTROL IN DISTRIBUTION NETWORK.
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XXIV. Mukherjee, P., Das, A., & Bera, P. (2020). Design of P-I-D Power System Stabilizer Using Oppositional Krill Herd Algorithm for a Single Machine Infinite Bus System. In P. Mukherjee, A. Das, & P. Bera.
XXV. Naoe, N., on, A.-2., & 2019, u. (n.d.). A Three-Phase PM Generator with Double Rotors for Low-Head Hydropower–Trial Structure and Basic Characteristics. ieeexplore.ieee.org.
XXVI. Nichols, C. (2019). The Design of an In-Conduit Hydropower Plant with a Seal-Free Magnetic Transmission.
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XXVIII. Oo, M. (2019). Design of 50 kW Kaplan Turbine for Micro hydro Power Plant.
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XXX. Ramana Rao KV, Nagendrababu, M., Valanginisarat, P., & Kallempudi Vahini. (2020). Implementation strategy to minimize the speckle noise from polarimetric sar data. International Journal of Mechanical and Production Engineering Research and Development, 10(3), 5455–5466. https://doi.org/10.24247/ijmperdjun2020520
XXXI. Salehghaffari, H. (n.d.). Hardware-In-The-Loop Vulnerability Analysis of a Single-Machine Infinite-Bus Power System.
XXXII. Shah, N., & Joshi, S. (2019, 3 1). Utilization of DFIG-based wind model for robust damping of the low frequency oscillations in a single SG connected to an infinite bus. International Transactions on Electrical Energy Systems, 29(3).
XXXIII. Shah, N., Electrical, S.-I., & 2019, u. (n.d.). Utilization of DFIG‐based wind model for robust damping of the low frequency oscillations in a single SG connected to an infinite bus. Wiley Online Library.
XXXIV. Shahgholian, G., Hamidpour, H., & Movahedi, A. (2018). Transient Stability Promotion by FACTS Controller Based on Adaptive Inertia Weight Particle Swarm Optimization Method. advances.vsb.cz.
XXXV. Smil, V. (2019). Growth: from microorganisms to megacities.
XXXVI. Yang, W. (2017). Hydropower plants and power systems Dynamic processes and control for stable and efficient operation.
XXXVII. Ye, H., Pei, W., Kong, L., Power, T.-I., & 2018, u. (n.d.). Low-Order Response Modeling for Wind Farm-MTDC Participating in Primary Frequency Controls. ieeexplore.ieee.org.

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THE COMPARISON OF THE METHODS ESTIMATING THE FRACTIONAL DIFFERENCES OF PARAMETER AND ITS DEPENDENCE ON ESTIMATION THE BEST LINEAR MODEL OF TIME SERIES IN THE ENVIRONMENTAL FIELD

Authors:

Saad Kazem Hamza, Shareen Ali Hussein

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00014

Abstract:

This paper exploring the stability to be achieved in the stochastic processes and operations which are called the autoregressive moving average and symbolized by ARMA Model(the roots of the equation should be out of this model circle.  Although these models are not stable and become stable after so many conversions and differences. These new models called the autoregressive methods for integrated moving average which is symbolized ARFIMA (p, d, q) and these differences would be integers or fractional numbers. It is worth to be mentioned that the time series which depending on the long term (long memory) so this stability achieved by snapping the fractional differences which are located within the enclosed period (-0.5, 0.5) and are referred shortly ((ARFIMA (p,d,q))). Models which are located within the enclosed period (-0.5, 0.5). This search aims to estimate the parameter of fractional differences (d), three ways by using real data from the Ministry of Environment that include the rates of air pollution in Baghdad City with Nitrogen oxides(NO²), Ozone(Oᶟ) materials…these ways are: firstly, the way logarithm periodogram chart regression method which is called (Geweke and Porter- Hudak), symbolized (GPH) Secondly, smoothed periodogram regression. Thirdly, the way that called (KASHYAP AND EOM) and it has been used the standard error squares and standard error (SD) as two scale standards among these three ways to estimate the parameter. Akaike standard has been used for choosing the best model of linear models assumed.In this study, we will be dealt with the fractional differences

Keywords:

ARFIMA (p,d,q) models,long term memory,smoothed periodogram method,air pollution,spectrum function,

Refference:

I. Baillie, R. T. (1996). Long memory processes and fractional integration in econometrics. Journal of Econometrics,73(1), 5-59. doi:10.1016/0304-4076(95)01732-1

II. Franco, G. C., & Reisen, V. A. (2007). Bootstrap approaches and confidence intervals for stationary and non-stationary long-range dependence processes. Physica A: Statistical Mechanics and Its Applications,375(2), 546-562. doi:10.1016/j.physa.2006.08.027

III. Hassler, U. (1993). Regression of Spectral Estimators with Fractionally Integrated Time Series. Journal of Time Series Analysis,14(4), 369-380. doi:10.1111/j.1467-9892.1993.tb00151.

IV. Karemera, D., & Kim, B. J. (2006). Assessing the forecasting accuracy of alternative nominal exchange rate models: The case of long memory. Journal of Forecasting,25(5), 369-380. doi:10.1002/for.994

V. KASHYAP,R.L. and EOM,B.(1988) Estimation in long memory time series models J.time series Anal.9,35-41 long-memory parameter”.Department of Statistics, UFES, ES, UFMG, MGBrazil.

VI. Mandelbrot, B. B., & Wallis, J. R. (1968). Noah, Joseph, and Operational Hydrology. Water Resources Research, 4(5), 909-918. doi:10.1029/wr004i005p00909

VII. Ministry of Environment, records Waziriya station, daily readings of the station during the days of actual work for two years 2017.2018, Iraq – Baghdad 0.2019.

VIII. Porter, Hudak, S. (1982). Long – Term Memory: Modelling A simplified Spectral Approach. Unpublished Ph.D Dissertation, University of Wisconsin

IX. Reisen, V. A., Cribari-Neto, F., & Jensen, M. J. (2003). Long Memory Inflationary Dynamics: The Case of Brazil. Studies in Nonlinear Dynamics & Econometrics,7(3). doi:10.2202/1558-3708.1157

X. Reisen.V.A. (1993) “Estimation of the fractional difference parameter in the ARIMA(p,d,q) model using the smoothed periodogram”. Journal of time series analysis .Vol.15,No.3.

XI. Reisen.V.A.&Franco.G.C.(2006).”Log average sample spectral estimators oflong-memory parameter”.Department of Statistics, UFES, ES, UFMG, MGBrazil.

XII. RichardT.Baillie (1996) “long memory processes and fractional integration in econometric” department of Economics,Michigan state university,USA.

XIII. Wei, William W. S. – 1990 – (Time Series Analysis) – Addison – Wesley publishing Company p:278.

XIV. Wilkins, N. (2003). Fractional Integration at a Seasonal Frequency with an Application to Quarterly Unemployment Rates. School of Finance and Economics University of Technology, Sydney, 1-32.

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PERFORMANCE ANALYSIS OF FRUIT CROP FOR MULTICLASS SVM CLASSIFICATION

Authors:

Shameem Fatima, M. Seshashayee

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00015

Abstract:

The research study aim to improve the performance of fruit quality by two approaches, first by applying kernel technique combined with specific classification method support vector machine (SVM) with error-correcting output codes for fruit categorization and then by cross validation . It is measured by analyzing the different mention kernel selection on color and shape features. Two coding design method such as one-vs.-one and one- vs.- all are examined with three commonly used kernel function linear, polynomial (cubic) and Radial Basis Function (Gaussian). The Experiment was conducted on fruit dataset created from fruit 360 dataset with six categories such as Apples, Avacados, Bananas, Cherrys, Grapes and lemons. The accuracy obtained for the fruit category with 98% accuracy was enhanced by the proposed method by the use of kernel technique selection resulted to 99%. However kernel choice highly depends on the parameter used for fruit categorization is introduced and discussed. The Experiments was carried out to find the best SVM kernel among linear, cubic and Gaussian for fruit categorization. The Experiment also focuses on evaluation process using cross validation methods kfold and hold out which resulted in a better accuracy for the classification model.  The results show that the proposed method provides very stable and successful fruit classification performance over six categories of fruits. The coding design one- vs. - one performed better when compared to one- vs. - all with respect to accuracy and training speed.

Keywords:

Multiclass SVM,ECOC,kernel technique,KFold validation,

Refference:

I A.Bhargava, A.Bansal, Fruits and vegetables quality evaluation using computer vision: A review. Journal of King Saud University – Computer and Information Sciences (2018), https://doi.org/10.1016/j.jksuci.2018.06.002

II C.Maaoui, & A.Pruski, (2008, July). A comparative study of SVM kernel applied to emotion recognition from physiological signals. In 2008 5th International Multi-Conference on Systems, Signals and Devices (pp. 1-6). IEEE.

III C.Ouyang, D.Li, J.Wang, S.Wang, & Y.Han, (2012, October). The research of the strawberry disease identification based on image processing and pattern recognition. In International Conference on Computer and Computing Technologies in Agriculture (pp. 69-77). Springer, Berlin, Heidelberg.

IV C. Sammut and G. I. Webb, Eds., “Holdout Evaluation,” in Encyclopedia of Machine Learning and Data Mining, Boston, MA: Springer US, 2017, p. 624.

V Donahue, Jeff, et al. “Decaf: A deep convolutional activation feature for generic visual recognition.” arXiv preprint arXiv:1310.1531 (2013).

VI EzgiiErturk, Ebru AkapinarSezer “A comparision of some soft computing methods for software fault prediction” Expert system with applications,Elsevier, pp1872-1879,vol.42, 2015.

VII F.Al-Shargie, T.B.Tang, N.Badruddin, & M.Kiguchi, (2018). Towards multilevel mental stress assessment using SVM with ECOC: an EEG approach. Medical & biological engineering & computing, 56(1), 125-136.

VIII Fruits 360 Dataset on Kaggle. https://www.kaggle.com/moltean/fruits. last visited on 06.07.2019

IX G.Muhammad, (2015). Date fruits classification using texture descriptors and shape-size features. Engineering Applications of Artificial Intelligence, 37, 361-367.

X H. M.Zawbaa, M.Abbass, M.Hazman, & A. E.Hassenian, (2014, November). Automatic fruit image recognition system based on shape and color features. In International Conference on Advanced Machine Learning Technologies and Applications (pp. 278-290). Springer, Cham.

XI L.Qiang, C.Jianrong, L.Bin, D.Lie, & Z.Yajing, (2014). Identification of fruit and branch in natural scenes for citrus harvesting robot using machine vision and support vector machine. International Journal of Agricultural and Biological Engineering, 7(2), 115-121.

XII M.Achirul Nanda, K. Boro Seminar, D. Nandika, & A. Maddu, (2018). A comparison study of kernel functions in the support vector machine and its application for termite detection. Information, 9(1), 5.

XIII P. Refaeilzadeh, L. Tang, and H. Liu, “Cross-Validation,” in Encyclopedia of Database Systems, L. LIU and M. T. ÖZSU, Eds. Boston, MA: Springer US, 2009, pp. 532–538.

XIV R. S. Chora’s, “Image Feature Extraction Techniques and their Applications for CBIR and Biometrics Systems”.International Journal of Biology and Biomedical Engineering, 2007, 1(1), 6–16.

XV S.Fatima, and M. Sesehashayee, (2020). Healthy Fruits Image Label Categorization through Color Shape and Texture Features Based on Machine Learning Algorithm, International Journal of Innovative Technology and Exploring Engineering, ISSN: 2278-3075, Volume-9 Issue-3.

XVI S. R.Dubey, & A. S. (2012). Robust approach for fruit and vegetable classification. Procedia Engineering, 38, 3449-3453.

XVII S. M. Iqbal, A.Gopal, P. E., Sankaranarayanan, & A. B. Nair, (2016). Classification of selected citrus fruits based on color using machine vision system. International journal of food properties, 19(2), 272-288.

XVIII Shepperd, D. Bowes, and T. Hall, “Researcher bias: The use of machine learning in software defect prediction,” Software Engineering, IEEE Transactions on, vol. 40,no. 6, pp. 603-616, 2014.

XIX S.Ibrahim, N. A.Zulkifli, N.Sabri, A. A.Shari, & M. R. M.Noordin, (2019). Rice grain classification using multi-class support vector machine (SVM). IAES International Journal of Artificial Intelligence, 8(3), 215.

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XXI Y.Zhang, & L. Wu, (2012). Classification of fruits using computer vision and a multiclass support vector machine. Sensors, 12(9), 12489-12505.

XXII Z.Wen, B.Li, R.Kotagiri, J.Chen, Y.Chen, & R.Zhang, (2017, February). Improving efficiency of SVM k-fold cross-validation by alpha seeding. In Thirty-First AAAI Conference on Artificial Intelligence.

XXIII Z.Yan, Y.Yang, (2014). Application of ecocsvms in remote sensing image classification. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(2), 191.

XXIV Z.Yan, & Y.Yang, (2014). Performance analysis and coding strategy of ECOC SVMs. International Journal of Grid and Distributed Computing, 7(1), 67-76

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CHARACTERISTIC BEHAVIOUR OF RARE EARTH DOPED OXYFLUOROBORATE GLASSES

Authors:

S. Farooq, V.B.Sreedhar, R. Padmasuvarna, Y.Munikrishna Reddy

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00016

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 Ωλ (λ = 2, 4, 6) have been evaluated from experimental (fexp) and calculated (fcal) 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 4F9/26H13/2transition is obtained higher than 50% (0.55). The highest readings of AR, βR and σse are obtained for the transition n 4F9/26H13/2 (yellow).Hence, this can be consider as an appropriate mechanism for lasing action. Gain band width (Δλeff x σse)and optical-gain (σse x τR) 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,Dy3+ -doped glasses,Judd-Ofelt theory,PL spectra,

Refference:

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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.

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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.

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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.

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SOFTg^* βCLOSED SETS IN SOFT TOPOLOGICAL SPACES

Authors:

Punitha Tharani. A., Sujitha. H.

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00017

Abstract:

We introduce a new class of soft generalized star -closed sets(brieflysoft-closed set), soft - open set in soft topological spaces(from now on STS). We have studied the relationship between this type of closed sets and other existing closed sets in STS and some of their basic properties.

Keywords:

Soft closed,Soft generalized closed,Soft g^* β-closed set,Soft g^* β-open set,Soft topological spaces,

Refference:

Arockiarani.I and ArockiaLancy.A,Generalized soft gβ closed sets and soft gsβ closed sets in soft topological spaces, International Journal of
Mathematical Archive-4(2),2013,17-23.

Hussain.S and Ahmad.B, Some Properties of Soft topological spaces,
Comput. Math. Appl., Vol. 62(2011), 4058-4067.

Kannan.K,Soft Generalized closed sets in soft topological spaces, Journal
of Theoretical and Applied information Technology,Vol.37, No.1(2012), 17-21.

Levine.N, Generalized closed sets in Topology, Rend. Circ. Mat. Palermo,
Vol. 19, No.2(1970), 89-96.

Molodstov.D,”soft set theory-first results”, Computers and Mathematics
with applications (1999), 19-31.

Muhammad Shabir and Munazza Naz,”on soft topological spaces”,
Computers and Mathematics with applications, (2011),Vol.61,issue 7,
1786-1799.

Punitha Tharani. A and Sujitha. H, The concept of g^* β-closed sets in topologicalspaces, International Journal of Mathematical Archive,(2020) Vol.11(4), 14-23.

Shabir.M and Naz.M, on soft topological spaces, Computers and Mathematics with Applications, 61(2011) 1786-1799.

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SELF-DIRECTED FIRE FIGHTING ROBOT USING INTERNET OF THINGS AND MACHINE LEARNING

Authors:

Rajeshwarrao Arabelli, T.Bernatin

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00018

Abstract:

Now a day, fire accidents in houses, apartments and communities, threatening to the victims and property. As it is a very dangerous job to involve any person like fire fighters during fire accidents, that potentially cause loss of property and human lives due to lack of technology innovation.Hence the firefighting robots are used to rescue the operation instead of humans. In our project, Firefighting robot is used to alert whenever fire accidents are detected and moves in the direction of flame or smoke to extinguish it. Hence the firefighting robot operation is to rescue victims and stop fire in a house within a little span of time.Thus, it reduces the risk of injury to the victims and also property damage.This device includes various sensors like Proximity Infrared Sensor (PIR), flame sensor, ultrasonic sensor, MQ2 (LPG) sensor, and actuators like Motorsand buzzer.

Keywords:

Firefighting robot, Proximity Infrared Sensor,flame sensor,ultrasonic sensor,MQ2 (LPG) sensor,Internet of Things,

Refference:

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VII. Revathi, R. & Renuka, G. 2019, “Child safety seat cooling system”, International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 6 Special Issue 4, pp. 810-814.

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X. William Dubel, Hector Gongora, Kevin Bechtold and Daisy Diaz, “An Autonomous Firefighting Robot”.

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SMART SECURITY SYSTEM FOR RURAL AREAS

Authors:

RamaswamyMalothu, Sandeep Kumar V.

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00019

Abstract:

The people leaves in rural areas will need security in many aspects. All security applications will be operated with the most advanced technology services in embedded and GSM.  This system will be useful to home and rural security for an area of village. In this paper we had smart security surveillance that can send information to authorized person about metal detected if any at entrance of the village. This smart security was done with ARM7 LPC2148 processor, PIR Sensor, metal detector for allowing them into the area by authorized and unauthorized with buzzer.In this paper the PIR sensor will detect the Person and it will check for any metal with the person who would like to enter into the secured zone. The system will send the information about the status of metal and allow them if there is no metal by unauthorized. If metal detected with the person then the system indicates with the buzzer primarily and then it will send the information to authorized person that the person will have some unsecured objects please check once and will not allow into the secured zone.

Keywords:

ARM7LPC2148,Security in rural areas,surveillance,metal detector,

Refference:

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VI. Face Detection and Face Recognition Using Raspberry Pi Shrutika V. Deshmukh1 , Prof Dr. U. A. Kshirsagar International Journal of Advanced Research in Computer and Communication Engineering

VII. Kumar, J. T., and Kumar, V. S. “Novel Distance-Based Subcarrier Number Estimation Method for OFDM System,” In International conference on Modelling, Simulation and Intelligent Computing, vol. 659, pp. 328-335, 2020.

VIII. Kumar, J. Tarun, and V. S. Kumar. “A Novel Optimization Algorithm for Spectrum Sensing Parameters in Cognitive Radio System,” International conference on Modelling, Simulation and Intelligent Computing. vol. 659, pp. 336-344, 2020.

IX. Kumar, V. Sandeep. “Joint Iterative Filtering and Companding Parameter Optimization for PAPR Reduction of OFDM/OQAM Signal,” AEU-International Journal of Electronics and Communications (2020): 153365.

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HYBRID ALGORITHM FOR INDOOR BASED LOCALIZATION

Authors:

Riam M. Zaal, Eyad I. Abbas, Mahmood F. Mosleh

DOI NO:

https://doi.org/10.26782/jmcms.2020.08.00020

Abstract:

Localization algorithm plays the major rule for different applications such as tracking, positioning, and monitoring. The general framework presented by localization approaches may not work well in practical environments, due to many reasons related with dealing with 2 Dimensional space only or having high computational costs. As a result, Hybrid Localization Algorithm (HLA) was proposed and presented in this paper based on the use of both Received Signal Strength (RSS) and Angle-of-Arrival (AoA). The algorithm has been tested in a 3 Dimensional indoor scenario, with considering the effects of different building materials. Obtained result indicate an effectiveness in localizing the received points by using 2 transmitters for more accuracy in positioning coordination with average ranging error of less than 0.23m for both Line of Sight (LoS) and Non Line of Sight (NLoS) cases.

Keywords:

RSS,Localization algorithm, indoor,,hybrid,

Refference:

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VIII. I. Guvenc, and C. Chia-Chin “A survey on TOA based wireless localization and NLOS mitigation techniques.” IEEE Communications Surveys & Tutorials, Vol.11, no.3 pp: 107-124, 2009.‏

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XII. M. M. Abdulwahid, O. A. S. Al-Ani, M. F. Mosleh and R. A. Abd-Alhmeed. “Optimal access point location algorithm based real measurement for indoor communication”. In Proceedings of the International Conference on Information and Communication Technology, pp: 49-55, 2019.‏

XIII. M. S. AL-Hakeem, I. M. Burhan, M. M. Abdulwahid, “Hybrid Localization Algorithm for Accurate Indoor Estimation Based IoT Services”, IJAST, vol. 29, no. 05, pp. 9921 – 9929, 2020.

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XVI. O. A Shareef, M. M. Abdulwahid, M. F. Mosleh, & R. A. Abd-Alhameed. “The optimum location for access point deployment based on RSS for indoor communication”, International Conference on Modelling and Simulation (UKsim2019), Vol.20, p 2.1, 2019.
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