Journal Vol – 15 No -1, January 2020

Abstract:

The Multifocus image fusion objective in visual sensor networks is to combine the multi-focused images of the same scene into a focused fused image with improved reliability and interpretation. However, the existing fusion methods based on focus measures are not able to get entire focused fused image since they neglect the diagonal neighbor pixels during the selection of the focused objects. In order to get an image with all objects in focus a novel image fusion method using extended spatial frequency and wavelet based focus measures in the stationary wavelet transform domain is proposed. In our method, initially the two multi-focus source images are transformed and decomposed as low and high-frequency sub bands by using stationary wavelet transform. Then, each sub band is divided into equal subblocks. Focused sub-blocks of low and high-frequency sub bands are selected by using the extended spatial frequency and wavelet based focus measures. Lastly, the fused image is restored by performing the inverse stationary wavelet transform on selected sub-blocks. The performance of the proposed method is verified by carrying out the fusion on artificial, natural and misregistered multifocus images. The results of the proposed method are then compared with the results of existing image fusion methods. The experimental results indicate that proposed method not only removes artifacts in the fused image due to the shift-invariance of stationary wavelet transform and also preserves sharp details using extended spatial frequency and wavelet based focus measures.

Keywords:

Extended spatial frequency,focus measures,image fusion,waveletbased focus measure,

Refference:

I. Bhatnagar G, Raman B. A new image fusion technique based on directive contrast. ELCVIA: electronic letters on computer vision and image analysis 2009;8(2):18-38.
II. Borwonwatanadelok P, Rattanapitak W, Udomhunsakul S. Multi-focus image fusion based on stationary wavelet transform and extended spatial frequency measurement. In: IEEE 2009 International Conference on
Electronic Computer Technology, 2009 pp. 77-81.
III. Cao L, Jin L, Tao H, Li G, Zhuang Z, Zhang Y. Multi-focus image fusion based on spatial frequency in discrete cosine transform domain. IEEE signal processing letters 2014; 22(2):220-224.
IV. Chen Y, Blum RS. A new automated quality assessment algorithm for image fusion. Image and vision computing 2009; 27(10):1421-32.
V. Haghighat MB, Aghagolzadeh A, Seyedarabi H. Multi-focus image fusion for visual sensor networks in DCT domain. Computers & Electrical Engineering 2011; 37(5):789-97.
VI. Huang W, Jing Z. Evaluation of focus measures in multi-focus image fusion. Pattern recognition letters 2007; 28(4):493-500.
VII. Kumar BS. Multifocus and multispectral image fusion based on pixel significance using discrete cosine harmonic wavelet transform. Signal, Image and Video Processing 2013; 7(6):1125-1143.
VIII. Li H, Wei S, Chai Y. Multifocus image fusion scheme based on feature contrast in the lifting stationary wavelet domain. EURASIP Journal on Advances in Signal Processing 2012; 2012(1):39.
IX. Li S, Kwok JT, Wang Y. Combination of images with diverse focuses using the spatial frequency. Information fusion 2001; 2(3):169-176.
X. Li S, Yang B, Hu J. Performance comparison of different multi-resolution transforms for image fusion. Information Fusion 2011; 12(2):74-84.
XI. Naidu VP. Image fusion technique using multi-resolution singular value decomposition. Defence Science Journal 2011; 61(5):479-484.
XII. Nayar SK, Nakagawa Y. Shape from focus: An effective approach for rough surfaces. In: IEEE 1990 Robotics and Automation International Conference;Cincinnati,USA; 1990. pp. 218-225.
XIII. Paul S, Sevcenco IS, Agathoklis P. Multi-exposure and multi-focus image fusion in gradient domain. Journal of Circuits, Systems and Computers 2016; 25(10):1650123.
XIV. Pertuz S, Puig D, Garcia MA. Analysis of focus measure operators for shape-from-focus. Pattern Recognition 2013; 46(5):1415-1432.
XV. Petrovic VS, Xydeas CS. Gradient-based multiresolution image fusion. IEEE Transactions on Image processing 2004; 13(2):228-237.
XVI. Pu T, Ni G. Contrast-based image fusion using the discrete wavelet transform. Optical engineering 2000; 39(8):2075-2083.
XVII. Radha N, Babu TR. Performance evaluation of quarter shift dual tree complex wavelet transform based multifocus image fusion using fusion rules. International Journal of Electrical & Computer Engineering 2019; 9(2): 2377-2385.
XVIII. Sabre R, Wahyuni IS. Wavelet Decomposition in Laplacian Pyramid for Image Fusion. International Journal of Signal Processing Systems 2016; 4 (1): pp.37-44.
XIX. Sahoo T, Mohanty S, Sahu S. Multi-focus image fusion using variance based spatial domain and wavelet transform. In: IEEE 2011 International Conference on Multimedia, Signal Processing and Communication
Technologies, 2011. pp. 48-51.
XX. Sharma EA, Gulati T. Performance Analysis of Unsupervised Change Detection Methods for Remotely Sensed Images. International Journal of Computational Intelligence Research 2017; 13(4):503-508.
XXI. Subbarao M, Tyan JK. Selecting the optimal focus measure for autofocusing and depth-from-focus. IEEE transactions on pattern analysis and machine intelligence 1998; 20(8):864-870.
XXII. Thelen A, Frey S, Hirsch S, Hering P. Improvements in shape-from-focus for holographic reconstructions with regard to focus operators, neighborhood-size, and height value interpolation. IEEE Transactions on Image Processing 2008; 18(1):151-157.
XXIII. Vadhi R, Kilari V, Samayamantula S. Uniform based approach for image fusion. In: Springer 2012 International Conference on Eco-friendly Computing and Communication Systems; Berlin, Heidelberg; 2012. pp.186-194.
XXIV. Wang WW, Shui PL, Song GX. Multifocus image fusion in wavelet domain. In: IEEE 2003 Machine Learning and Cybernetics International Conference; Xi’an, China; 2003. pp. 2887-2890.
XXV. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing 2004; 13(4):600-12.
XXVI. Xie H, Rong W, Sun L. Wavelet-based focus measure and 3-d surface reconstruction method for microscopy images. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006. pp. 229-234.
XXVII. Xydeas CA, Petrovic V. Objective image fusion performance measure. Electronics letters 2000; 36(4): 308-309.
XXVIII. Yang C, Zhang JQ, Wang XR, Liu X. A novel similarity based quality metric for image fusion. Information Fusion 2008; 9(2):156-60.
XXIX. Yang J, Ma Y, Yao W, Lu WT. A Spatial domain and frequency domain integrated approach to fusion multifocus images. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2008; 37(PART B7).
XXX. Yang Y, Zheng W, Huang S. Effective multifocus image fusion based on HVS and BP neural network. The Scientific World Journal 2014.
XXXI. Zhang L, Zhang L, Mou X, Zhang D. FSIM: A feature similarity index for image quality assessment. IEEE transactions on Image Processing 2011; 20(8):2378-86.
XXXII. Zheng Y, Essock EA, Hansen BC, Haun AM. A new metric based on extended spatial frequency and its application to DWT based fusion algorithms. Information Fusion 2007; 8(2):177-192.

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Abstract:

In this present research work, durability studies like Sulphide attack, Acid Attack, and Chloride Attack are studied for the lightweight fiber reinforced concrete (LWFRC) by incorporating palm oil Shells (POS). Fiber-reinforced concrete is achieved by introducing 0.5% ECR – Glass fibers to the volume of the concrete and it will improve the ductility. Coarse aggregates are replacing with POS up to 50% (0, 10, 20, 30, 40 and 50) to achieve the Light Weight Concrete (LWC). To reduce the greenhouses from cement industries, the Cement is replaced with Palm oil Fuel Ash (POFA) and Ground Granulated Blast furnace Slag (GGBS) up to 50% (0, 10, 20, 30, 40 and 50) separately. By using all ingredients LWFRC is prepared and tested for the chemical attacks.

Keywords:

Light Weight Concrete,Fiber Reinforced Concrete,ECR – Glass Fibers,Sulphide Attack,Chloride Attack,Magnesium Attack,GGBS,POFA,POS,Durability,

Refference:

I. Antony Godwin I, Nancy Deborah S, Julius Ponraj I, Vinslin Blessho R, Stephen C, “Experimental Investigation on the Mechanical and Microstructural Properties of Concrete with Agro-Waste”, International
Journal of Engineering &Technology, 7 (3.12), PP 33-37, 2018.
II. Chia Chia Thong, Delsye Ching Lee Teo, and Chee Khoon Ng, “Durability Characteristics of Polyvinyl Alcohol–Treated Oil Palm Shell Concrete”, J.Mater. Civ. Eng., Vol 29, Issue 10, 2017.
III. DC L Teo, M A Mannan, V J Kurian, “Durability of Light Weight OPS Concrete under Different Curing Conditions”, Materials and Structures, 2009.
IV. Erevan Serri, Mohd. Zaillian Suleiman and Md Azree Othman Mydin, “Durability Performance of Oil Palm Shell Lightweight Concrete as Insulation Concrete”, Applied Mechanics and Materials, Vol. 747, 2015.
V. Faiz Shaikh “Mechanical and Durability Properties of Green Star Concretes”, Buildings, PP: 1-12, 2018.
VI. Kim Hung Mo, Fatin Amirah Mohd Anor, U. Johnson AlengaramMohd Zamin Jumaat and K. Jagannadha Rao “Properties of metakaolin-blended oil palm shell lightweight concrete”, European Journal of Environmental and Civil Engineering, PP 1-17,2016.
VII. K Muthusamy, M Y Fadzil, A Z Muhammad Nazrin Akmal, S Wan Ahmad, Z Nur Azzimah, H Mohd Hanafi and R Mohamad Hafizuddin “Effect of fly ash content towards Sulphate resistance of oil palm shell lightweight
aggregate concrete”, IOP Conference Series: Materials Science and Engineering, PP 1-5,2018.
VIII. M. Almograbi, “Durability study of lightweight concrete material made from date palm seeds (DPS)”, WIT Transactions on the Built Environment, Vol 112.
IX. Maria Mavroulidou “Mechanical Properties and Durability of Concrete with Water Cooled Copper Slag Aggregate”, Waste Biomass Valor, 8, PP: 1841–1854, 2017.
X. Matthew R Sherman, David B Mc Donald, Donald W Pfeifer, “Durability Aspects of Precast Prestressed Concrete Part 1: Historical Review”, 1996.
XI. Mehdi Maghfouri, Payam Shafigh and Muhammad Aslam “Optimum Oil Palm Shell Content as Coarse Aggregate in Concrete Based on Mechanical and Durability Properties”, Advances in Materials Science and Engineering,
PP 1-14, 2018.
XII. Ming Kun Yew, Hilmi Bin Mahmud, Bee Chin Ang, and Ming Chian Yew, “Effects of Oil Palm Shell Coarse Aggregate Species on High Strength Lightweight Concrete”, ScientificWorldJourna, 2014.
XIII. Ming Kun Yew, Ming Chian Yew, Lip Huat Sa1, Siong Kang Lim, Jing Hang Beh, Tan Ching Ng, “Enhancement of Durability Properties and Drying Shrinkage of Heat-treated Oil Palm Shell Species High-strength Lightweight Concrete”, Nanoscience and Nanotechnology, Volume 2, Issue 1, 2018.
XIV. Noh Irwan Ahmad, Khairulzan Yahya “The Effect of Oil Palm Shell as Coarse Aggregate Replacement on Densities and Compressive Strength of Concrete”.

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Abstract:

In this work plasma emission spectra and atomic structure of the holmium target by Q-switched Nd:YAG laser (1064 nm) has been studied. This work was done theoretically and experimentally. Cowan code was used to get the emission spectra for different transition of the holmium target. In the experimental work, the influences of the laser pulse energy and pulse repetition rate on the emission lines intensity of the laser induced plasma spectrum by spectroscopic technique in air has been investigated. Three laser pulse energies (600, 700 and 800) mJ with repetition rate (5Hz, and 20Hz) are used .The result indicate that, the emission line intensities increase with increasing of the laser pulse energy and repetition rate. The holmium target can give a good emission spectra in the UV region (200-400) nm.The best emission spectra appeared when the laser pulse energy is 800mJ and 20 Hz repetition rate at λ= 341.54nm, 342.76nm, and 345.53nm with the maximum intensity of 80000 counts .

Keywords:

Emission spectra,pulse energy,Nd-YAG laser,holmium,

Refference:

I. A. K. Aadim, (2015). Characterization of Laser induced cadmium plasma in air. Iraqi Journal of Science, 56(3B), 2292-2296.
II. B. Cagnac, & C. J. Pebay-Peyroula, (1975). Modern atomic physics: fundamental principles.
III. G. Başar, N. Al-Labady, B. Özdalgiç, F. Güzelçimen, A. Er, K. I. Öztürk, & S. Kröger, (2017). Line Identification of Atomic and Ionic Spectra of Holmium in the Near-UV. II. Spectra of Ho ii and Ho iii. The Astrophysical Journal Supplement Series, 228(2), 17.
IV. G. M.Kompitsas, F.Roubani-Kalantzopoulou, I. Bassiotis, A. Diamantopoulou, & A. Giannoudakos, (2000). Laser induced plasma spectroscopy (LIPS) as an efficient method for elemental analysis of environmental samples.
V. G. Nave, (2003). Atomic transition rates for neutral holmium (Ho I). JOSA B, 20(10), 2193-2202.
VI. H. G. Jihad, & A. K.Aadim, K (2018). Spectroscopic study the plasma parameters for Pb doped CuO prepared by pulse Nd: YAG laser deposition. Iraqi Journal of Physics, 16(38), 1-9.
VII. H. H. Murbat, & A. H. Hamza, (2017) The Influence of Nd: YAG Laser Energy on Plasma Characteristics Produced on Si: Al Alloy Target in Atmosph
VIII. J. Gurell, M. G. Wahlgren, G. Nave, & F. J. Wyart, (2009). Wavelengths, energy levels and hyperfine structure constants in Ho ii. Physica Scripta, 79(3), 035306.
IX. L.Fechner, (2016). High-Resolution Experiments on Strong-Field Ionization of Atoms and Molecules: Test of Tunneling Theory, the Role of Doubly Excited States, and Channel-Selective Electron Spectra. Springer.
X. M.Corsi, G.Cristoforetti, M.Hidalgo, S. Legnaioli, V.Palleschi, A.Salvetti, & C.Vallebona, (2006). Double pulse, calibration-free laser-induced breakdown spectroscopy: a new technique for in situ standard-less analysis of polluted soils. Applied Geochemistry, 21(5), 748-755.
XI. N.Al-Labady, B. Özdalgiç, A. Er, F. Güzelçimen, K. I. Öztürk, S. Kröger & G. Başar, (2017). Line identification of atomic and ionic spectra of holmium in the near-UV. Part I. spectrum of Ho I. The Astrophysical Journal Supplement Series, 228(2), 16.
XII. N. S. Mazhir, A. N. Abdullah, F. A. Rauuf, H. A. Ali, & I. H.al-Ahmed, (2018). Effects of Gas Flow on Spectral Properties of Plasma Jet Induced by Microwave. Baghdad Science Journal, 15(1), 81-86.
XIII. P. A. Rodgers, A. M. Rogoyski, S. J. Rose, Rutherford Appleton Laboratory Report, RAL-89-127, Dec.1989.
XIV. R. d’Agostino, P. Favia, C. Oeh, & R. M.Wertheimer, (2005). Low‐temperature plasma processing of materials: past, present, and future. Plasma Processes and Polymers, 2(1), 7-15.
XV. R. D. Cowan, J. of Optical Society of America, 58 (1968) 808-818.
XVI. S. M. Mahmoad, (2018). The emission spectra and hydrodynamic properties of Al plasma using Nd-YAG laser. Iraqi Journal of Physics (IJP), 16(38), 83-98.

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Abstract:

Accuracy in spectrum sensing is very much required in cognitive radio network, which is a revolutionary paradigm to drift the spectrum underutilization problem. To enhance the detection performance in presence of shadowing or fading multiple SUs cooperate among themselves. But the collaboration and so the detection process is severely affected by the presence of some harmful secondary users known as Malicious users. As a result of this false sensing, spectrum wastage or interference with primary users may happen which are not at all desired for the system. The proposed approach in this paper has intelligently excluded these malicious users from the decision making process and thus improves the efficiency of the system.

Keywords:

Cognitive radio,fusion rules,cooperative spectrum sensing,quantized fusion rule,

Refference:

I. A. Ghasemi and E. S. Sousa, “Collaborative spectrum sensing for opportunistic access in fading environments,” in Proceedings of the 1st IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN ’05), pp. 131– 136, November 2005

II. A. Ghasemi and E. S. Sousa, “Opportunistic spectrum access in fading channels through collaborative sensing,” Journal of Communications, vol. 2,no. 2, pp. 71–82, 2007
III. A. Ghasemi, & E. S. Sousa, “Spectrum sensing in cognitive radio networks: the cooperation-processing tradeoff”, Wireless Communications and Mobile Computing, 7(9), 1049-1060, 2007
IV. A. Chakraborty, and J.S. Banerjee, “An Advance Q Learning (AQL) Approach for Path Planning and Obstacle Avoidance of a Mobile Robot”. International Journal of Intelligent Mechatronics and Robotics, 3(1), pp 53-73
2013
V. A. Chakraborty, J. S. Banerjee, and A. Chattopadhyay, “Non-Uniform Quantized Data Fusion Rule Alleviating Control Channel Overhead for Cooperative Spectrum Sensing in Cognitive Radio Networks”. In: Proc. IACC, pp 210-215 2017
VI. A. Chakraborty, J. S. Banerjee, and A. Chattopadhyay, “Non-uniform quantized data fusion rule for data rate saving and reducing control channel overhead for cooperative spectrum sensing in cognitive radio networks”, Wireless Personal Communications, Springer, 104(2), 837-851, 2019
VII. D. Das, et. al., “Analysis of Implementation Factors of 3D Printer: The Key Enabling Technology for making Prototypes of the Engineering Design and Manufacturing”, International Journal of Computer Applications, pp.8-14, 2017
VIII. E. Hossain, D. Niyato, and Z. Han, “Dynamic Spectrum Access in Cognitive Radio Networks”, Cambridge University Press, Cambridge, UK, 2008 IX. E. Visotsky, S. Ku ffher, and R. Peterson, “On collaborative detection of TV transmissions in support of dynamic spectrum sharing”, in Proceedings of the 1st IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN ’05), pp. 338–345, Baltimore, USA, November 2005
X. F. Akyildiz, B. F. Lo, and R. Balakrishnan, “Cooperative spectrum sensing in cognitive radio networks: A survey”, Physical Communication (Elsevier) Journal, vol. 4, no. 1, pp. 40-62, March. 2011

XI. I. Pandey, et. al., “WBAN: A Smart Approach to Next Generation ehealthcare System”, In 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), pp. 344-349, IEEE, 2019

XII. J. Mitola III and G. Q. Maguire Jr., “Cognitive radio: making software radios more personal”, IEEE Personal Communications, vol. 6, no. 4, pp. 13–18, 1999
XIII. J. Mitola III, “Cognitive Radio— An Integrated Agent Architecture for Software Defined Radio”.Royal Institute of Technology, 2000
XIV. J. S. Banerjee, A. Chakraborty, and A. Chattopadhyay, “Relay node selection using analytical hierarchy process (AHP) for secondary transmission in multi-user cooperative cognitive radio systems”, in Proc. ETAEERE 2016,
LNEE-Springer, Dec. 2016
XV. J. S. Banerjee, A. Chakraborty, and A. Chattopadhyay, “Fuzzy based relay selection for secondary transmission in cooperative cognitive radio networks”, in Proc. OPTRONIX 2016, Springer, India, Aug. 2016
XVI. J. S. Banerjee, et. al., “A Comparative Study on Cognitive Radio Implementation Issues”, International Journal of Computer Applications, vol.45, no.15, pp. 44-51, May.2012
XVII. J. S. Banerjee, A. Chakraborty, and A. Chattopadhyay, “Reliable best-relay selection for secondary transmission in co-operation based cognitive radio systems: A multi-criteria approach”, Journal of Mechanics of Continua and
Mathematical Sciences, 13(2), 24-42, 2018
XVIII. J. S. Banerjee, and A. Chakraborty, “Fundamentals of Software Defined Radio and Cooperative Spectrum Sensing: A Step Ahead of Cognitive Radio Networks”. In Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management, IGI Global, pp 499-543 2015
XIX. J. S. Banerjee, A. Chakraborty, and K. Karmakar, “Architecture of Cognitive Radio Networks”. In N. Meghanathan & Y.B.Reddy (Ed.), Cognitive Radio Technology Applications for Wireless and Mobile Ad Hoc Networks, IGI
Global, pp 125-152 2013
XX. J. S. Banerjee, and A. Chakraborty, “Modeling of Software Defined Radio Architecture & Cognitive Radio, the Next Generation Dynamic and Smart Spectrum Access Technology”. In M.H. Rehmani & Y. Faheem (Ed.),
Cognitive Radio Sensor Networks: Applications, Architectures, and Challenges, IGI Global, pp. 127-158 2014
XXI. J. Banerjee, et. al., “Impact of machine learning in various network security applications”, In 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), pp. 276-281, IEEE, 2019
XXII. J. S. Banerjee, et. al., “A Survey on Agri-Crisis in India Based on Engineering Aspects”, Int. J. of Data Modeling and Knowledge Management, 3(1–2), pp.71-76, 2013
XXIII. J. S. Banerjee, A. Chakraborty, and A. Chattopadhyay, “A novel best relay selection protocol for cooperative cognitive radio systems using fuzzy AHP”, Journal of Mechanics of Continua and Mathematical Sciences, 13(2), 72-87,
2018
XXIV. K. B. Letaief and W. Zhang, “Cooperative spectrum sensing”, in Cognitive Wireless Communication Networks, Springer, New York, NY, USA, 2007

XXV. Laneman, J. N., et al. “Cooperative diversity in wireless networks: Efficient protocols and outage behavior”, IEEE Trans. Inform. Theory, 50(12), pp.3062-3080, 2004
XXVI. M. K. Simon, & M. S. Alouini, [Digital communication over fading channels]. John Wiley & Sons, Hoboken, NJ, Vol. 95, 2005

XXVII. O. Saha; A. Chakraborty, and J. S. Banerjee, “A Decision Framework of ITBased Stream Selection Using Analytical Hierarchy Process (AHP) for Admission in Technical Institutions”, In: Proc. OPTRONIX 2017, IEEE, pp.
1-6, Nov. 2017
XXVIII. O. Saha; A. Chakraborty, and J. S. Banerjee, “A Fuzzy AHP Approach to ITBased Stream Selection for Admission in Technical Institutions in India”, In: Proc. IEMIS, AISC-Springer, pp. 847-858, 2019

XXIX. R. Chen, J.-M. Park, and J. H. Reed, “Defense against primary user emulation attacks in cognitive radio networks”, IEEE Journalon Selected Areas in Communications,vol.26,no.1,pp. 25–37, 2008
XXX. R. Chen, J.-M. Park, and K. Bian, “Robust distributed spectrum sensing in cognitive radio networks”, in Proceedings of IEEE International Conference on Computer Communications (INFOCOM ’08), pp. 31–35, Phoenix, Ariz,
USA, April 2008

XXXI. S. Haykin, “Cognitive radio: brain-empowered wireless communications”, IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, pp. 201–220, 2005
XXXII. S. M. Mishra, A. Sahai, and R. W. Brodersen, “Cooperative sensing among cognitive radios”, in Proceedings of the IEEE International Conference on Communications (ICC ’06), vol. 4, pp. 1658–1663, Istanbul, Turkey, June 2006
XXXIII. S. Paul, A. Chakraborty, and J. S. Banerjee, “A Fuzzy AHP-Based Relay Node Selection Protocol for Wireless Body Area Networks (WBAN)”, In: Proc. OPTRONIX 2017, IEEE, pp. 1-6, Nov. 2017
XXXIV. S. Paul, A. Chakraborty, and J. S. Banerjee, “The Extent Analysis Based Fuzzy AHP Approach for Relay Selection in WBAN”, In: Proc. CISC, (pp.331-341). Springer, Singapore, 2019
XXXV. T. Newman and T. Clancy, “Security threats to cognitive radio signal classifiers”, in Proceedings of the Virginia Tech Wireless Personal Communications Symposium, Blacksburg, USA, June 2009
XXXVI. T. Clancy and N. Goergen, “Security in cognitive radio networks: threats and mitigation”, in Proceedings of the 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (Crown Com ’08), Singapore, May 2008
XXXVII. Z. Han and K. J. R. Liu, “Resource Allocation for Wireless Networks: Basics, Techniques, and pplications”, Cambridge University Press, Cambridge, UK, 2008

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Abstract:

This paper proposes the design strategy of low power Dickson charge pump using associated block who is help in proper functionality at full chip level because of single charge circuit cannot be design for portable handheld based application. When a low power optimization based high speed charge pump circuit is designed at system level, then entire circuit block operates at different supply voltage so it requires. For this, the circuit designer needs a level shifter to manage the dual supply voltage and provide a non-overlapping ring oscillator to provide the clock to the circuit to operate at high speed. CMOS clocked circuit is required to work in sufficient voltage level pushup up to end level. Thus, In this paper, the actual simulation results using the CMOS 180nm technology along with each block are shown. Along with this, good brief discussion on each block has also been done.

Keywords:

Charge Pump,Ring Oscillator,NOC clock generator,clocked D-FF,CMLS level shifter,

Refference:

I. Louie Pylarinos. “Proceedings of the IEEE International Symposium on Circuits andSystems.1-7.citeseerx.ist.psu.edu/viewdoc/download http://citeseerx.ist.psu.edu/viewdoc/versions?doi=10.1.1.128.4085, 2003.
II. Feng pan and Tapan Samaddar, “Charge pump circuit designconc”,McGraw-Hill Electronic Engineering :ISBN-13: 978-007147045, 2006.
III. Moisiadisa Y, Bourasc I, and A. Arapoyanni, “Charge Pump Circuits for Low-voltage Applications”, Taylor and Francis VLSI Design. Vol 15, pp:477–483, 2002.
IV. Wu, J.T. and L.K. Chang, “MOS Charge pump for Low Voltage Operation”,.IEEE Journal of solid-state circuits.vol 33 pp: 592-597,1998.
V. Dickson, J.F. On-chip high voltage generation in NMOS integrated circuits using an improved voltage multiplier technique. IEEE journal of Solid-State circuits, vol 11, pp: 374-378, 1976.
VI. G. Palumbo, D. Pappalardo, M. Gaibotti, “Charge Pump Circuits- Power Consumption Optimization”, IEEE Trans. Circuits and Systems I: Fundamental Theory and Applications. Vol 49, pp: 1535–1542, 2002.
VII. R. L. Geiger, P. E. Allen, and N. R. Strader, “VLSI-Design Techniques for Analog and Digital Circuits”, McGraw-Hill Publishing Co. ISBN 0-07-023253-9, 1990.
VIII. Prabhakar Gyan., Singh R.K., Vikram A, “Boosted Clock Generator Using NAND Gate for Dickson Charge Pump Circuit”,Smart Innovation, Systems. and Technologies(Springer, Singapore.), vol 2(107), pp: 39-49,2019.
IX. Jacob Baker, Harry W. Li and David E. Boyce, CMOS Circuit Design, Layout, and Simulation Department of Electrical Engineering Microelectronics Research Center the University of Idaho.
X. Retdian, N., Takagi, S. and Fujii, N, “Voltage controlled ring oscillator with wide tuning range and fast voltage swing IEEE Asia- Pacific Conference”, ASIC on. Proceedings: pp: 201-204. 2002.
XI. Yongbo Liua, b, Zhengyong Zhua, Huilong Zhua, “Charge pumps, test technique using CMOS ring oscillator on the leakage issue”, Microelectronics Journal vol 68, pp: 40–45, 2017.
XII. Vladimir Stojanovic and Vojin G.(1999).„Comparative Analysis of Master–Slave Latches and Flip-Flops for High-Performance and Low-Power Systems. IEEE Journal of Solid-State Circuits. 34(4):536-548, 1999
XIII. http://ece-research.unm.edu/jimp/vlsi/slides/chap5_2.html
XIV. G. Prabhakar, A. Vikram , Rajendra Pratap, R.K. Singh, “Current contention Problem in Level shifter”,International Journal of Recent Technology and Engineering, Vol 8, pp: 11699-11703, 2019
XV. Mohammad Torikul Islam Badal, Mamun Bin Ibne Reaz, Araf Farayez, Siti A. B. Ramli, and Noorfazila Kamal., “Design of a Low-power CMOS Level Shifter for Low-delay SoCs in Silterra 0.13 μm CMOS Process”, Journal of Engineering Science and Technology Review , vol 4 pp: 10-15, 2017.
XVI. Prabhakar Gyan, Rabindra Kumar Singh and Abhishek Vikram, “Improved Efficiency and Voltage Gain Conversion Ratio using Inductor Model based modified Dickson Charge Pump”, Journal of Engineering Science and Technology review.vol 11,pp: 1-7.2018.
XVII. Prabhakar Gyan, Rabindra Kumar Singh and Abhishek Vikram, “Inductor-Based Modified Dickson Charge Pump Boost Voltage Converter with Higher Efficiency”,. Information and Communication Technology for
Intelligent Systems, Smart Innovation, Systems and Technologies Vol 2(107): pp: 39-49, 2019
XVIII. P. R. Gray and R. G. Meyer,“Analysis and Design of Analog Integrated Circuits”, 3rd ed., John Wiley and Sons.. ISBN 0-471-57495-3, 1993.

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Abstract:

This work studies the trajectory tracking of a non-holonomic WMR. A type of back stepping method in conjunction with Lyapunov method were used for deriving two controllers. But, in non-linear systems controllers may not be enough to reach a good performance. Different cases of trajectory where studied such as (straight line, circular, elliptical, sinusoidal, and infinity shape trajectory) to examine the WMR control system utilizing MATLAB (R2018a)/Simulink to simulate the results. In addition, particle swarm optimization technique was utilized to determine the controllers' parameters by implementing the summation absolute compound error for the position (x, y), the orientation 𝛽, the linear and angular velocity (𝑣􀯖,𝜔􀯖 ), and the energy. Results showed a very good matching between simulation and the desired trajectory where all errors converge to zero.

Keywords:

Mobile robot,Nonholonomic,DDWMR,Optimum,PSO,control,

Refference:

I. A. Sofi, B. R. Phanikumar, “An experimental investigation on flexural
behaviour of fibre-reinforced pond ash-modified concrete”, Ain Shams
Engineering Journal. vol. 6, pp: 1133-1142, 2015.
II. Fareh R, Saad M, Khadraoui S, and Rabie T 2016. Lyapunov-based
tracking control for nonholonomic wheeled mobile robot. J. International
Journal of Electrical and Computer Engineering. V10. PP1042-1047.
III. García-Sánchez J, et al 2017 Mexico. Tracking control for mobile robots
considering the dynamics of all their subsystems: experimental
implementation.P1-18.
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Abstract:

This paper proposes a novel precoding method using the pruned DFT (pDFT) spread FBMC along with the Poly-phase network (PPN). This method outperforms the pruned DFT spread FBMC in many aspects and also avoids Inter symbol Interference. This technique has advantages of both FBMC-Offset Quadrature amplitude modulation (OQAM) and Single carrier Frequency division multiple access (SC-FDMA).Proposed technique has same PAPR as SC-FDMA and has very low out-of-band emissions and does not need cyclic-prefix. This method reduces latency, computational complexity and complex orthogonality is restored. A comparative performance is also evaluated between pDFT-FBMC PPN and other multicarrier schemes and we observe that pDFT-FBMC PPN is better than other schemes. Simulation is performed by using Matlab.

Keywords:

FBMC,Poly-phase network,FBMC-OQAM,

Refference:

I. K.Mahender,T.Anilkumar, K.S.Ramesh, “AN EFFICIENT FBMC BASED
MODULATION FOR FUTUREWIRELESS COMMUNICATIONS”,ARPN
Journal of engineering and applied science, ISSN 1819-6608,vol
13,no.24,DEC-2018
II. K.Mahender, T. Anilkumar, 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
III. K.Mahender, T. Anilkumar, K.S. Ramesh, “An Efficient OFDM system with
reduced PAPR for combating multipath fading”, Journal of advanced
research in dynamical and control systems.9: 1939-1948.
IV. K.Mahender, T. Anilkumar, 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
V. K.Mahender, T. Anilkumar, K.S. Ramesh, “Analysis of Multipath Channel
Fading Techniques in Wireless Communication systems”, American Institute
of Physics,AIP Conference Proceedings1952, 020050; doi:
10.1063/1.5032012.
VI. K.Mahender, T.Anilkumar, K.S. Ramesh. “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
VII. K.Mahender, T. Anilkumar, 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.
VIII. R.Nisseland,M.Rupp,“PrunedDFTspreadFBMC-OQAM:Low-
PAPR,lowlatency, highspectralefficiency,”Submitted to IEEE
TransactionsonCommunications,2018.
IX. R. Nissel, J. Blumenstein, and M. Rupp, “Block frequency spreading: A
method for low-complexityMIMOinFBMC-OQAM,”in IEEE Workshop on
Signal Processing Advances in Wireless Communications (SPAWC),
Hokkaido, Japan, July2017.
X. R. Nissel, M. Rupp, and R. Marsalek, “FBMC-OQAM in doubly-selective
channels: A new perspective on MMSE equalization,” in IEEE Workshop on
Signal Processing Advances in Wireless Communications (SPAWC),
Hokkaido, Japan, July2017.
XI. R. Nissel, E. Zöchmann, and M. Rupp, “On the influence of doublyselectivity
in pilot-aided channel estimation for FBMC-OQAM,” in IEEE
Vehicular Technology Conference (VTC Spring), Sydney, Australia,
June2017.

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Abstract:

India is a country of having versatile language and culture. Here, people speak in 22 different languages. With the help of Google Indic keyboard people can express their sentiments about any product, news, incidents, laws, games etc. over the social media in their native languages from individual smart phones, tablets or laptops. Sentiment analysis (SA) itself is a tough job, while multilingual SA is even harder as the style of expression varies in different languages. Among the existing approaches of SA till now the machine learning approach through neural network has overcome the limitations of others. The main aim of this paper is to represent a detailed study of the outputs generated from three different models implemented using Convolution Neural Network(CNN), Simple Recurrent Neural Network(RNN) and an amalgamated model of CNN and Long Short Term Memory (LSTM) without worrying about versatility of multilingualism using 2600 sample reviews in Hindi and Bengali. It is anticipated that the experimental results on these realistic reviews will prove to be effective for further research work.

Keywords:

Machine learning,Neural Network,Sentiment Analysis,Multilingual Tweets,

Refference:

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A. Trivedi, A. Srivastava, I. Singh, K. Singh, and S. K. Gupta, “Literature Survey on
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Textual Data of English.” IJCSI,2011.
B. G. Patra, D. Das,, A. Das, and R. Prasath, “Shared task on sentiment analysis in
indian languages (sail) tweets-an overview”, In International Conference on Mining
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Publishing, December, 2015.
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summarization based on minimum cuts” In Proceedings of the 42nd annual meeting
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Koyel Chakraborty et al
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Abstract:

It has been observed that the extreme rainfall is anunusual and very essential hydrological parameter therefore probabilistic modeling is important for the analysis of such extreme weather events. Extreme rainfall analysis has much importance for a civil engineer and planning division of a country to take into account the capability of building structures for extreme weather conditions. To understand the extreme behavior of Khyber Pakhtunkhwa we use yearly maximum rainfall of four major cities of this province from 1960 to 2010. In this study, we have estimated the parameters of Generalized Extreme Value (GEV) distribution by using Bayesian approach. The Akaike Information Criteria and Acceptance Rate are used to check the reliability of the model. After getting ensured the reliability we find return levels against different return periods (10, 25, 50, 75 and 100 years) of Meteorological stations Peshawar, Dir, Parachinar and D I Khan of KPK province of Pakistan. Our result will be useful for policy makers, civil engineers, planning division, agricultural departments and research scholars, formers for irrigation system and civil society of KPK, Pakistan for precautionary measures.

Keywords:

Extreme Rainfall,Bayesian approach,Return period,Return levels,

Refference:

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Abstract:

Multi-View Human Action Recognition, as a hot research area in computer vision, has many more applications in various fields. Despite its popularity, more precise recognition still remains a major challenge due to various constraints. Extracting the robust and discriminative feature from video sequence is a crucial step in the Human Action Recognition system. In this paper, a new feature extraction technique is proposed based on the integration of three different features such as intensity, Orientation and Contour features. Unlike the earlier approaches which applied feature extraction directly over actions videos, this approach applies the feature extraction only over key frames which are extracted from a large set of frames. The key frames selection is accomplished based on a new mechanism, called Gradient Self-Similarity Matrix (GSSM). GSSM is proposed as an extension to the most popular Self-Similarity Matrix (SSM) by evaluating the gradients of actions frames before SSM accomplishment. Once the key frames are extracted, the hybrid feature extraction mechanism is applied and the obtained features are processed for classification through Support Vector Machine Classifier. The proposed framework is systematically evaluated on IXMAS dataset and NIXMAS dataset. Experimental results enumerate that our method outperforms the conventional techniques in terms of recognition accuracy.

Keywords:

Computer Vision,Human Action Recognition,Multiple Views,Self- Similarity Matrix,Gaussian,Gabor,Wavelet,Accuracy,

Refference:

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Abstract:

Designing an electronic circuit with low power and small area are two important concerns for signal processing designers. Though fast emergence of the new technologies and several reviews over signal and speech processing, the difficulty cannot be fulfilled for the hearing impaired people. Many filter bank algorithms have been discussed on the hearing aid design to extend the efficiency. The conventional design of cascaded Direct Truncation (DT) data path is mainly based on the design of Full Precision Static Floating Point. In this paper, we introduce Static Floating Point Sample Rate Converter (SFP-SRC) with Linear Phase Finite Impulse Response (LPFIR) for hearing aid applications. The Sampling Rate Conversion is done before or after the LPFIR filter with upsampling and downsampling factors. In order to increase efficiency of DSP systems, filter bank algorithms need more than one sampling rate. The proposed method provides minimum delay and excellent Signal to Noise Ratio (SNR) performance when compared to Post Truncation (PT) data path. In order to obtain better performance, many experiments have been conducted. The proposed SFP-SRC is suitable for hearing assistance applications. Hence, it is implemented on 1/3 octave analysis filter bank with umc-90nm CMOS technology at 24 KHz.

Keywords:

Finite Impulse Response,Filter bank algorithms,Digital hearing aid,DSP algorithms,

Refference:

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Abstract:

Getting the culture right, is challenging – but is well worth for the rewards of success. Every Institution is characterized byits ownculture, which is different from others. Identification of organizational culture in an institution may help in determining if mission, goals, and strategic objectives were being met. This study investigated academic staff members’ perceptions of organizational culture inselected institutions of higher learning. Faculty’s views about different dimensions of organizational culture were examined. A total of 100 academic staff members from privateinstitutions of higher learning have completed the Organizational Culture Assessment Instrument. Analysis of data was done by using descriptive statistics explicitly to determine the kind of existing organizational culture in private institutions. Results of this study revealed that private institutions mainly have market culture.

Keywords:

Organizational culture,Private institution,Academic staff members,

Refference:

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Navneesh Tyagi et al
167
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Abstract:

In this paper, the effect of dynamic coefficients of different bearings types on the dynamic response and the frequency of maximum response of rotor bearing system have been studied. The ANSYS Mechanical APDL 18.0 was used to model rotor with different bearings types. MATLAB software has been used to achieve the analytical solution. The results showed that the using of ball bearing, roller bearing or self aligning bearing with fluid film journal bearing strongly increasing the dynamic response amplitude and slightly increasing frequency of maximum response compared with the using of journal bearing to support rotor while using ball bearing with roller bearing have insignificant effect on the dynamic response and frequency of maximum response also using of self aligning bearing with ball bearing or roller bearing strongly decreasing the dynamic response and slightly decreasing the frequency of maximum response and using the self aligning bearing with others bearings types give the misalignment self-overcoming feature.

Keywords:

Rotor,Dynamic Response,Journal Bearing,Roller Bearing,Ball Bearing,

Refference:

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Abstract:

Segmentation of MR brain image is quite useful in detection of tumors and further diagnosis. However, precise segmentation of tumors plays a significant role in diagnosing the patient more effectively. Previously, there are plenty of approaches was implemented and however they were failed to detect the exact tumor which led to the failure diagnosis. Therefore, an accurate detection of tumor is required for effective diagnosis. Here, this article presented an efficient segmentation of MR brain image tumors. Our approach includes a hybrid clustering mechanism with pre-processed by savitzky-golay filter (SGF). In addition, tumor area also estimated for better diagnosis of patient. Simulation results disclosed the superiority of proposed hybrid approach over conventional segmentation algorithms in terms of computational complexity and segmentation accuracy.

Keywords:

Magnetic resonance imaging,Brain tumor,Thresholding,Fuzzy C-means,K-means,Hybrid clustering,

Refference:

I. A.M. Usó, F. Pla and P.G. Sevila, “Unsupervised Image Segmentation
Using a Hierarchical Clustering Selection Process”, Structural,
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191
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Abstract:

Multilevel inverters are superior to the two-level inverters to meet medium and high - power applications. A seven-level diode-clamped multilevel topology (7LDCMT) proposed, and compare the advantages and disadvantages of various control strategies such as multilevel space vector pulse width modulation (MSVPWM) with multicarrier sinusoidal pulse width modulations (MCSPWM) named as level shift and phase shift PWM based on the position of carriers at certain frequency. In level shift is further divided and compare the Inphase disposition sinusoidal pulse width modulation (IPD-SPWM), phase opposition and disposition-sinusoidal pulse width modulation (POD-SPWM), alternate phase opposition and disposition-sinusoidal pulse width modulation (APOD-SPWM) and carrier phase displacement sinusoidal pulse width modulation (CPD-SPWM). The 7L-DCMT designed with MATLAB/SIMULINK and the performance can analyses based on the observing total harmonic distortion (THD) at different control strategies.

Keywords:

Seven level diode-clamped multilevel inverter,Multicarrier sinusoidal pulse width modulation,level shift,phase shift,Multilevel Space vector pulse width modulation,

Refference:

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