Conference Proceedings

This paper uses high frequency transformer less chopper with voltage boosting and low stress. The topology uses automatic current sharing capability and voltage summing at the output terminal by lower value of MOSFET, diodes. In addition to this proposed technology losses are reduced. Blocking capacitor introduces automatic current sharing in the circuit because of charge balance in the capacitor. The proposed topology provides voltage boosting with no extreme duty cycle. In relating to the existing proposed system voltage gain is proposed. Electrolytic capacitor used to reduce the current ripple .By having more current ripple will reduce the output port power in the circuit .Incase if output diode stress greater than the output voltage efficiency of circuit reduces for high output voltage application. The reduction of voltage stress and voltage gain can be achieved using ultra high step-up convertor with addition to power factor correction by voltage doubler circuit.

Keywords : non isolated, current ripple reduction, voltage boosting. low voltage stress, automatic current sharing system, power factor correction.

Recent

[1] Jianwu Zeng, Student Member, An Isolated Multiport DC–DC Converter for Simultaneous Power Management of Different Renewable Energy Sources IEEE, Wei Qiao, Senior Member, IEEE [2] “Novel high step-up DC–DC converter with coupled-inductor and voltage-doubling circuits,” L. S. Yang, T. J. Liang, H. C. Lee, and J. F. Chen, IEEE Trans. Ind. Electron. [3] “Wind/solar hybrid generation-based roadway microgrids,” W. Qiao, A. Sharma, J. Hudgins, E. Jones, and L. Rilett, in Proc. IEEE Power Energy Soc. [4] “Family of multiport bidirectional DC-DC converters,” H. Tao, A. Kotsopoulos, J. Duarte, and M. Hendrix, IEE Proc. Electr. Power Appl [5] “A novel multi-port DC-DC converter for hybrid energy distributed generation systems connected to power grid,” M. Qiang, Z. Xu, and W. Wu,in Proc. IEEE Int. Conf. Ind. Technol., [6] “Transformerless DC–DC converters with high step-up voltage gain,” L. S. Yang, T. J. Liang, and J. F. Chen, IEEE Trans. Ind. Electron [7] “High step-up soft-switched converters using voltage multiplier cells,” S. Lee,S. Choi, IEEE Trans. Power Electron., [8] “Interleaved high Step-Up ZVTconverter with built-in transformer voltage doubling cell for distributed PVgeneration system,” W. Li, X. Xiang, C. Li,W. Li, and X. He,IEEE Trans. Ind. Electron [9] “Switched-Capacitor-Cell-Based voltage multipliers and DC–AC inverters,” Z. Ke, M. J. Scott, and W. Jin, IEEE Trans. Ind. Appl. [10] “A review of the single phase photovoltaic module integrated converter topologies with different DC link configurations,” Q. Li and P. Wolfs,IEEE Trans. Power Electron., [11] “Integrated MPPT and battery charger for PV application using one multiphase interleaved three-port DC-DC converter,” Z. Wang and H. Li,, in Proc. IEEE Appl. Power Electron. Conf. Exposit [12] “An isolated three-port bidirectional chopper with decoupled power flow management,” C. Zhao, S. Round, and J. Kolar,IEEE Trans.Power Electron

Clock gating is one among the most widespread circuit technique to scale back power consumption. Clock gating is sometimes done at the register transfer level (RTL).Automatic synthesis of clock gating in gate level has been less explored, however it's certainly additional convenient to designers. Clock gating consists of 2 steps: extraction of gating conditions by merging gating conditions of individual flip-flops, implementation of the gating conditions with minimum quantity of further gates. In this paper, they show a way to do factored form matching, within which gating operates in factored kinds are matched, as way as possible, with factored kinds of the mathematician functions of existing combinable nodes within the circuit; further gates are then introduced, however just for the portion of gating functions that don't seem to be matched. Sturdy matching identifies matches that are explicitly gift within the factored forms, and their matching seeks matches that are inexplicit to the logic and so are tougher to get. Gate-level clock gating starts with a net list, with partial or no gating applied; some flip-flops are then selected for further gating to reduce the circuit’s power consumption, and a gating logic of the smallest possible size must then be synthesized.

Keywords : Flip-Flops, Gating logic, Strong Matching Forms etc

Recent

[1] I. Han And Y. Shin, “Synthesis Of Clock Gating Logic Through Factored Form Matching,” In Proc. Int. Conf. Ic Design Tech., Jun. 2012,Pp. 1–4. [2] D. Chinnery And K. Keutzer, Closing The Power Gap Between Asic &Custom, Norwell, Ma, Usa: Kluwer, 2007. [3] S. Unger, “Double-Edge-Triggered Flip-Flops,” Ieee Trans. Comput.,Vol. 30, No. 6, Pp. 447–451, Jun. 1981. [4] R. Pokala, R. Feretich, and R. Mcguffin, “Physical Synthesis For Performance Optimization,” In Proc. Int. Asic Conf. Exhibit., Sep. 1992, Pp. [5] Power Compiler User Guide, Synopsys, Inc., Mountain View, Ca, Usa,Dec. 2010. [6] F. Theeuwen and E. Seelen, “Power Reduction through Clock Gating By Symbolic Manipulation,” In Proc. Symp. Logic Archit. Design, Dec. 1996, Pp. 184–191. [7] S. Kim, I. Han, S. Paik, And Y. Shin, “Pulser Gating: A Clock Gating Ofpulsed-Latch Circuits,” In Proc. Asia South Pacific Design Autom. Conf., Jan. 2011, Pp. 190–195.

Corneal images can be acquired using confocal microscopes which provide detailed views of the different layers inside a human cornea. Some corneal problems and diseases can occur in one or more of the main corneal layers: the epithelium, stoma and endothelium. In this method, we have proposed a novel framework for automatic detection of true retinal area in SLO images. Artificial neural networks (ANNs) and, adaptive neuro fuzzy inference systems (ANFIS) have been investigated and tested to improve the recognition accuracy of the main corneal layers and identify abnormality in these layers. Feature selection is necessary so as to reduce computational time during training and classification. It shows that selection of features based on their mutual interaction can provide the classification power close to that of feature set with all features. As far as the classifier is concerned, the testing time of ANFIS was the lowest compared to other classifiers. The performance of the ANFIS achieves an accuracy of 100% for some classes in the processed data sets. This system is able to pre-process (quality enhancement, noise removal), classify corneal images, and identify abnormalities in the analyzed data sets.

Keywords : ANFIS, Retinal Disease

Recent

[1] M. S. Haleem, L. Han, J. van Hemert, and B. Li, “Automatic extraction of retinal features from colour retinal images for glaucoma diagnosis: A review,” Comput. Med. Image. Graph. vol. 37, pp. 581–596, 2013. [2] Optos. (2014). [Online]. Available: www.optos.com [3] R. C. Gonzalez and R. E. Woods, Eds., Digital Image Processing, 3rd ed.Englewood Cliffs, NJ, USA: Prentice-Hall, 2006. [4] M. J. Aligholizadeh, S. Javadi, R. S. Nadooshan, and K. Kangarloo, “Eyelid and eyelash segmentation based on wavelet transform for iris recognition,” in Proc. 4th Int. Congr. Image Signal Process., 2011, pp. 1231–1235. [5] D. Zhang, D. Monro, and S. Rakshit, “Eyelash removal method for human iris recognition,” in Proc. IEEE Int. Conf. Image Process., 2006, pp. 285– 288. [6] A. V.Mire and B. L. Dhote, “Iris recognition system with accurate eyelash segmentation and improved FAR, FRR using textural and topological features,” Int. J. Comput. Appl., vol. 7, pp. 0975–8887, 2010. [7] Y.-H. Li,M. Savvides, and T. Chen, “Investigating useful and distinguishing features around the eyelash region,” in Proc. 37th IEEE WorkshopAppl. Imag. Pattern Recog., 2008, pp. 16. [8] B. J. Kang and K. R. Park, “A robust eyelash detection based on iris focus assessment,” Pattern Recog. Lett., vol. 28, pp. 1630–1639, 2007. [9] T. H. Min and R. H. Park, “Eyelid and eyelash detection method in the normalized iris image using the parabolic Hough model and Otsus thresholding method,” Pattern Recog. Lett., vol. 30, pp. 1138–1143, 2009. [10] Iris database. (2005). [Online]. Available: http://www.cbsr.ia.ac.cn/ IrisDatabase.html. [11] H. Davis, S. Russell, E. Barriga,M.Abramoff, and P. Soliz, “Vision-based,real-time retinal image quality assessment,” in Proc. 22nd IEEE Int. Symp. Comput.-Based Med. Syst., 2009, pp. 1–6. [12] H. Yu, C. Agurto, S. Barriga, S. C. Nemeth, P. Soliz, and G. Zamora,“Automated image quality evaluation of retinal fundus photographs in diabetic retinopathy screening,” in Proc. IEEE Southwest Symp. Image Anal. Interpretation, 2012, pp. 125–128. [13] J. A. M. P. Dias, C. M. Oliveira, and L. A. d. S. Cruz, “Retinal image quality assessment using generic image quality indicators,” Inf. Fusion,vol. 13, pp. 1–18, 2012. [14] M. Barker and W. Rayens, “Partial least squares for discrimination,”J. Chemom., vol. 17, pp. 166–173, 2003. [15] J. Paulus, J.Meier, R. Bock, J. Hornegger, and G.Michelson, “Automated quality assessment of retinal fundus photos,” Int. J. Comput. Assisted Radiol. Surg., vol. 5, pp. 557–564, 2010. [16] R. Pires, H. Jelinek, J.Wainer, and A. Rocha, “Retinal image quality Analysis for automatic diabetic retinopathy detection,” in Proc. 25th SIBGRAPI Conf. Graph., Patterns Images, 2012, pp. 229–236. [17] R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. S¨usstrunk, “Slic superpixels compared to state-of-the-art superpixel methods,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 11, pp. 2274–2282, Nov. 2012. [18] A. Moore, S. Prince, J.Warrell, U. Mohammed, and G. Jones, “Superpixel lattices,” in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2008, pp. 1–8. an energy optimization framework,” in Proc. 11th Eur. Conf. Comput.Vis., 2010, pp. 211–224.

Distributed generator (DG) is recognized as a viable solution for controlling line losses and represents a new era for distribution systems. This paper focuses on developing an approach for placement of DG in order to minimize the active power loss and reactive power loss of distribution line of a given power system. The optimization is carried out on the basis of optimal location and optimal size of DG. This paper developed a new, efficient and novel krill herd algorithm (KHA) method for solving the optimal DG allocation problem of distribution networks. To test the feasibility and effectiveness, the proposed KH algorithm is tested on standard 33-bus radial distribution networks. The simulation results indicate that installing DG in the optimal location can significantly reduce the power loss of distributed power system. A detailed performance analysis is carried out on IEEE 33 Radial bus distribution system to express the effectiveness of the proposed method. Computational outcomes obtained showed that the proposed method is capable of generating optimal solutions.

Keywords : Distributed generation (DG), Radial Distribution Network (RDN), Krill Herd Algorithm (KHA), Loss reduction

Recent

[1] Misthulananthan, O. Than, “ Distributed generator placement in power distribution system using genetic algorithm to reduce losses”, Thammasat Int.J. Sci. Techonol,Vol.9,2004,pp.55–62. [2] A.Keane, M.O’Malley,”Optimal distributed generation plant mix with novel loss adjustment factors”, in: IEEE Power Engineering Society General Meeting,2006. [3] A. Borghetti, “A mixed-integer linear programming approach for the computation of the minimum-losses radial configuration”,IEEE Trans. Power Syst,Vol.27, 2012,pp.1264–1273. [4] A.C. Rueda-Medina, J.F. Franco, “A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems”, Electr. Power Syst. Res,Vol.97,2013,pp.133–143. [5] T. Gozel, M.H. Hocaoglu, “An analytical method for the sizing and sitting of distributed generators in radial systems”, Electr. Power Syst. Res,Vol.79, 2009,pp.912–918. [6] H. Khan, A.C. Mohammad, “Implementation of distributed generation (IDG)algorithm for performance enhancement of distribution feeder under extreme load growth”, Int. J. Electr. Power Energy Syst,Vol.32, 2010,pp.985–997. [7] N. Rezaei, M.R. Haghifam, “DG allocation with application of dynamic programming for loss reduction and reliability improvement”, Int. J. Electr. Power EnergySyst,Vol.33,2011,pp.288–295. [8] M.M. Aman, G.B. Jasmon, “Optimal placement and sizing of a DG based on a new power stability index and line losses”, Int. J. Electr.Power Energy Syst,Vol.43, 2012,pp.1296–1304. [9] B. Vankatesh, R. Ranjan, H.B. Gooi, “Optimal reconfiguration of radial distribution systems to maximize loadability”, IEEE Trans. Power Syst,Vol.19, 2004,pp.260–266. [10] D.H. Popovic, J.A. Greatbanks, M. Begovic, A. Pregelj, “Placement of distributed generator and reclosers for distribution network security and reliability”, Int. J.Electr. Power Energy Syst,Vol.27, 2005,pp.398–408

Nowadays, it is not easy to keep vigil of the country from external threats. For guarding always we cannot rely on soldiers alone. In some cases, soldiers will leave their areas for a short duration just to escape from inclement weather. For continuous defence surveillance, automatic recharging has been done to the robot using wireless power transmission from docking section. For surveillance purpose, the path of the robot has to be fed initially. When the battery of the robot gets low it will automatically re-enter to the docking section for recharging purpose. This system also contains multiple sensor modules with an embedded system. This Robot will be ready to capture the image of any human who enters into robot surveillance region. In the existing system, many researchers worldwide are now engaged in designing various mobile surveillance robots for home security applications. The system integrates a variety of sensors to gather environmental information and detect abnormal events such as fire alarm, intruder alert and gas leakage. In this project the system proposed a development and characterization of a surveillance robot with automatic docking and recharging capabilities for home security. The proposed system is composed of a surveillance robot and a docking station. The robot can return to the docking station for recharging operations when the on-board battery is too low. A docking method based on the self-localization of the robot and the infrared detectors of the docking station is proposed.

Keywords : Surveillance Robot, Fire Alarm, Gas Leakage, Docking Station

Recent

[1] Basma M. Mohammad El-Basioni, Sherine Mohamed Abd El-Kader and Hussein S. Eissa (2014), ‘Independent Living for Persons with Disabilities and Elderly People Using Smart Home Technology’, IEEE Trans Industrial Electronics , Vol. 55, No. 1, pp. 270-279. [2] Chang C., Chen K., Lin H., Wang C. and Jean J. (2007), ‘Development of a patrol robot for home security with network assisted interactions’, in SICE Annual Conference 2007, Kagawa University, Japan, pp. 924-928. [3] Hada Y. and Yuta S. (1999), ‘Robust navigation and battery re-charging system for long term activity of autonomous mobile robot’, Proc. Int. Conf. Advance Robotics, pp. 297-302. [4] Hwang I. K. and Baek J. W. (2007), ‘Wireless access monitoring and control system based on digital door lock’, IEEE Trans Consum Electron, Vol. 53, No. 4, pp. 1724-1730. [5] MdAthiq UR Raza Ahamed M, and WajidAhamed (2013), ‘A Domestic Robot for Security Systems by Video Surveillance Using Zigbee Technology’, Int. Journal of Control, Automation, and Systems , vol. 6, no. 5, pp. 731-739. [6] Nugent C. D., Finlay D. D., Fiorini P., Tsumaki Y. and Prassler E. (Jan. 2008), ‘Home automation as a means of independent living’, IEEE Trans. Autom. Sci. Eng., Vol. 5, No. 1, pp. 1-8. [7] RaduDobrescu, Dan Popescu, Maximilian Nicolae and Stefan Mocanu (2009), ‘Hybrid wireless sensor network for homecaremonitoring of chronic patients’, IEEE Trans Consum Electron, Vol. 55, No. 4, pp. 2034-2039. [8] Silverman M. C., Nies D., Jung B. and Sukhatme G. S. (2002), ‘Staying alive: a docking station for autonomous robot recharging’, in IEEE Int. Conf. on Robotics and Automation, Washington D.C., pp. 1050-1055. [9] Song G., Wei Z., Zhang W. and Song A. (2007), ‘A hybrid sensor network system for home monitoring applications’, IEEE Trans Consum Electron, Vol. 53, No. 4, pp. 1434-1439.

This proposed work has two converters connected in cascade to have output voltage 4 times of input voltage. This converter is a non-isolated boost converter, which can level up Dc voltage from 24 Vdc input voltage to 120 Vdc output voltages. This is adequate suitable in order to develop and apply with any dc output renewable energy source, such as pv generation system etc. The proposed converter has totally four modules of Dc boost converter, which are connected in parallel. At the same time, the switching devices are controlled by 90 degree shifting, due to an interleaving technique. This will lead to a smoother output dc current. Two modes of operation are available for interleaved boost converter: Half mode and Full mode operation. Based on the power loss efficiency of the converter the reliability of the converter can be calculated. In an interleaved boost converter high reliability is present and increase in power will lead to a decrease in the reliability.

Keywords : Interleaved DC-DC converter, DC input source, Driver circuit, MOSFET. Model of reliability

Recent

[1] Behjati.H and A.Davoudi, “Reliability analysis framework for structural redundancy in power semiconductors,” IEEE Trans. Ind. Electron.,vol. 60, no. 10, pp. 4376–4386, Oct. 2013. [2] Busca.C, R. Teodorescu, F. Blaabjerg, S. Munk-Nielsen, L. Helle, T.Abeyasekera, and P. Rodriguez, “An overview of the reliability prediction related aspects of high power IGBTs in wind power applications,”Elsevier Microelectron. Rel., vol. 51, pp. 1903–1907, 2011. [3] Hegazy.O, J. V. Mierlo, and P. Lataire, “Analysis, modeling, and implementation of a multidevice Interleaved DC/DC converter for fuel cell hybrid electric vehicles,” IEEE Trans. Power Electron., vol. 27, no. 11,pp. 4445–4458, Nov. 2012. [4] Lai.C.M , C. T. Pan, and M. Cheng, “A two-phase interleaved power factor correction boost converter with a variation-tolerant phase shifting technique,” IEEE Trans. Power Electron., vol. 29, no. 2, pp. 1032–1040,Feb. 2014. [5] Wai R.J and B. H. Chen, “High-efficiency dual-input interleaved DC–DC converter for reversible power sources,” IEEE Trans. Power Electron.,vol. 29, no. 6, pp. 2903–2921, Jun. 2014. [6] Song.Y and B.Wang, “Survey on reliability of power electronic systems,IEEE Trans. Power Electron., vol. 28, no. 1, pp. 591–604, Jan. 2013 [7] Wang.H and F. Blaabjerg, “Reliability of capacitors for DC-link applications in power electronic converters – An overview,” IEEE Trans. Ind.Appl., vol. 50, no. 5, pp. 3569–3578, Oct. 2014. [8] Yang.Y, A. Bryant, P. Mawby, D. Xiang, L. Ran, and P. Tavner, “An industry-based survey of reliability in power electronic converters,” IEEE Trans. Ind. Appl., vol. 47, no. 3, pp. 1441–1451, May/Jun. 2011.

Cancer are considered to be the major health threat in several regions of the world. After HIV, it is the second foremost infectious disease in worldwide causing death. When it is left undiagnosed and untreated, humanity rates of patients are high. The diagnostic methods are slow and still unreliable to detect. In order to reduce the liability of the disease, this work presents our automatic methodology for identifying Cancer. Initially, the extraction of the lung region is done using a graph cut segmentation method. Using this lung region, we figure out a set of texture and shape features, which enable the X-rays to be classified as normal or abnormal using the SVM classifier. This paper presents a simplified methodology using fuzzy logic segmentation from the natural image processing to lung segmentation tasks over GC segmentation. The proposed indicative system for analyzing CANCER segmentation achieves a better performance than the approaches of graph cut segmentation

Keywords : Segmentation, Lung Structures, Fuzzy Clustering

Recent

[1] H. Demuth, M. Beale, “Neural Network Toolbox User’s Guide”, 2000 [2] Y. Kawata, et al., “Classification of pulmonary nodules in thin section CT images based on shape characterization”. IEEE IntConf Image Proc 3:528-531, 1997. [3] Croisille, et al., “Pulmonary nodules: Improved detection with vascular segmentation and extraction with spiral CT”, Radiology, 197:397-401. [4] S. Toshioka, et al., “Computer aided diagnosis system for lung cancer based on helical CT images”, Image Processing: KM Hanson, Proc SPIE 3034:pp. 975-984, 1997. [5] T. Logeswari, M. Karnan, “An improved implementation of brain tumor detection using segmentation based on soft computing”, Journal of Cancer Research and Experimental Oncology Vol. 2(1), 2010, pp 6-14. International Journal of Advanced Information Technology (IJAIT) Vol. 4, No. 1, February 2014 29. [6] R.C. Patil, A.S. Bhalchandra, “Brain Tumour Extraction from MRI Images Using MATLAB”, International Journal of Electronics, Communication & Soft Computing Science and Engineering, Volume 2, Issue 1. [7] Conrad, D.H.; Goyette, J.; Thomas, P.S. Proteomics as a Method for early detection of cancer: A review of proteomics, exhaled breath condensate, and lung cancer screening. J. Gen. Intern. Med.2008, 23, 78–84. [8] S.N.A. Hassan, et al., “Vision Based Entomology – How to Effectively Exploit Color and Shape Features”, Computer Science & Engineering: An International Journal (CSEIJ), 2014, Vol. 4, Issue 1, ISSN: 2231-3583. [9] V.J. Nagalkar, S.S Asole, “Brain Tumor Detection Using Digital Image Processing Based On Soft Computing”, Journal Of Signal And Image Processing, Volume 3, Issue 3, pp.-102-105. [10] D.A. Dahab, et al., “Automated Brain Tumor Detection and Identification Using Image Processing and Probabilistic Neural Network Techniques”, International Journal of Image Processing and Visual Communication ISSN2319-1724 Volume 1, Issue 2, October 2012. [11] Peng, G.; Hakim, M.; Broza, Y.Y.; Billan, S.; Abdah-Bortnyak, R.; Kuten, A.; Tisch, U.; Haick,H. Detection of lung, breast, colorectal, and prostate cancers from exhaled breath using a single array of nanosensors. Br. J. Cancer 2010, 103, 542–551. [12] T. Acharya, A.K. Ray, “Image Processing: Principles and Applications”, Wiley-Interscience, 2005. [13] Jemal, A.; Bray, F.; Center, M.M.; Ferlay, J.; Ward, E.; Forman, D. Global cancer statistics.CA: Cancer J. Clin. 2011, 61, 69–90. [14] Ferlay, J.; Shin, H.-R.; Bray, F.; Forman, D.; Mathers, C.; Parkin, D.M. Estimates of worldwide burden of cancer in 2008: Globocan 2008. Int. J.Cancer 2010, 127, 2893–2917. [15] Smith, R.A.; Brooks, D.; Cokkinides, V.; Saslow, D.; Brawley, O.W. Cancer screening in the united states, 2013: A review of current american cancer society guidelines, current issues in cancer screening, and new guidance on cervical cancer screening and lung cancer screening.CA: Cancer J. Clin. 2013, 63, 87–105. [16] Smith, R.A.; Brooks, D.; Cokkinides, V.; Saslow, D.; Brawley, O.W. Cancer screening in the united states, 2013: A review of current american cancer society guidelines, current issues in cancer screening, and new guidance on cervical cancer screening and lung cancer screening.CA: Cancer J. Clin. 2013, 63, 87–105

A Multi-band rectangular micro strip antenna (RMSA) is proposed by a dual slot in the rectangular patch and a dual slot in the ground plane. Each open-ended slot in the single-slotted antenna is responsible to generate a wide impedance band that is shifted to lower frequencies by the effect of the ground slot. The dimension of the resultant antenna (12 * 8*1.5875 mm) reduces an average compactness to 53.73% when compared with a conventional unslotted rectangular micro strip patch antenna. The proposed antenna makes to operate in four bands of frequencies with large immunity to interference. The dual slots in the patch are responsible for two bands of frequencies and the open ended slot in the ground is responsible for two more bands in lower frequencies and the closed slot in the ground is responsible for the reduction of antenna size. The size and position of open ended slot is adjusted for the antenna to operate in two higher bands (5.306-5.59GHz and 5.784-5.990GHz) and open ended slot in ground is adjusted for lower band frequencies (2.578-3.052GHz and 3.382-3.688GHz).The obtained resonant frequencies can be used for WLAN and WiMAX.

Keywords : Rectangular Micro Strip Antenna (RMSA), Wireless Application

Recent

[1] Compact Dual-Band Microstrip Antenna for IEEE 802.11a WLAN Application by U. Chakraborty, Member, IEEE, A. Kundu, S. K. Chowdhury, and A. K. Bhattacharjee,”Ieee Antennas And Wireless Prop Lettrs, Vol. 13, 2014” [2] T. Sittironnarit, “Wideband packaged antenna for 5–6 GHz WLAN application,” IEEE Trans. Antennas Propag., vol. 52, no. 2, pp. 610–615, Feb. 2004. [3] L. Li, S.W. Cheung, , “Dual band antenna with radiator for 2.4/5.2/5.8 GHz WLAN applications,” IEEE Trans. Antennas Propag., vol. 60, no. 12, Dec. 2012. [4] A. Khaleghi, “Dual band meander line antenna for wireless LAN communication,” IEEE Trans. Antennas Pro., vol. 55, no. 3, pp.1404–1409, Mar. 2007. [5] C.-Y. Huang and E.-Z. Yu, “A slot-monopole antenna for dual-band WLAN applications,” IEEE Antennas Wireless Pro.Let., vol. 10,pp. 500–502, 2011. [6] A. A. Deshmukh , “broadband slotted rectangular microstrip antenna,” IEEE Antennas Wireless Propag. Lett., vol. 8, pp. 1410–1413, 2009. [7] J. M. Patel, S. K. Patel, and F. N. Thakkar, “Comparative analysis of S-shaped multiband microstrip patch antenna,” Int. J. Adv. Elect.,Electron.Instru.Eng., vol. 2, no. 7, pp.3273–3280, 2013. [8] K.-L. Wong and W.-H. Hsu, “A broad-band rectangular patch antenna with a pair of wide slits,” IEEE Trans. Antennas Propg., vol. 49, no.9, pp. 1345–1347, Sep. 2001. [9] K. L. Wong, Compact and Broadband Microstrip Antennas. New York, NY, USA: Wiley, 2002.

There are several methods are available for Load Frequency Control in interconnected power system. This paper proposes an optimized PID controller by DE tuning for AGC of two area power system. The gain parameters of the PID controller are optimized by commissioning DE and PSO technique. In this paper ISE criterion is used as a performance index. The action of this proposed power system with optimal tuned PID controller provides a satisfactory balance between frequency overshoot and transient oscillations with minimum steady state error. A comparative study on tuned values has been presented to verify effectiveness between DE and PSO method. The simulation results reveals the effectiveness of the designed system in terms of reduced settling time and oscillations with tuning of DE. MATLAB/SIMULINK was used as simulation tool.

Keywords : AGC, Differential Evolutionary algorithm Hydrothermal Power system, ISE,PID controller, PSO algorithm.

Recent

[1] H. i. abdul-ghaffar e. a. ebrahim m. azzam Design of PID Controller for Power System Stabilization Using Hybrid Particle Swarm-Bacteria Foraging Optimization-wseas transactions on power systems January 2013. [2] Pratap Chandra Pradhan a, Rabindra Kumar Sahu b, Sidhartha Panda b Firefly algorithm optimized fuzzy PID controller for AGC of multi-area multi-source power systems with UPFC and SMES- Engineering Science and Technology, an International Journal 2015. [3] Bervani Hassan, Hiyama Takashi. Intelligent automatic generation control. CRC Press; 2011 [4] Herreros A, Baeyens E,Perán JR .Design of PID-type controllers using multi objective genetic algorithms. ISATrans2002;41:457–72. [5] Reynoso-MezaG,GarciaNietoS,SanchisJ,BlascoFX.Controller tuning by means of multi-objective optimization algorithms:a global tuning framework.IEEE Trans Control System Technology l2013;21:445–58. [6] B.Nagaraj, S.Subha,B.Rampriya.Tuning Algorithms for PID Controller Using Soft Computing Techniques.IJCSNS International Journal of Computer Science and Network Security, VOL.8 No.4, April 2008. [7] Mohd s. saad, Hishamud Din Jamaluddin, Intan z. m. PID Controller Tuning Using Evolutionary Algorithm.WSEAS TRANSACTIONS on SYSTEMS and CONTROL. [8] Sukhwinder Singh Dhillona , Jagdeep Singh Latherb , Sanjay Marwaha Multi area load frequency control using particle swarm optimization and fuzzy rules Procedia Computer Science 57 ( 2015 ) 460 – 472. [9] Rout UK, Sahu RK, Panda S. Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. Ain Shams Eng J 2013;4(3):409–21.

The introduction of distributed generation unit in distributed system improves the voltage profile and reduces the system losses. Optimal placement and sizing of Distributed Generation units plays a major role in reducing system losses and improving voltage profile .The different technical issues are combined using weighting coefficients and solved under various operating constraints using Particle Swarm Optimization with Time – Varying Acceleration Coefficient (PSO-TAC). In general Distributed generation is defined as generation of electricity within distributed networks. The distributed capacities minimize the requirement for over dimensioning of transmission and distribution system. If the value of the voltage stability index is increased system is increased significantly, then it is possible to operate the system away from voltage instability condition .The Particle Swarm optimization can be used to find the best location of Distributed Generation units considering voltage stability and short circuit level in the distribution system.

Keywords : Distributed Generation, Distribution System, Voltage Stability, Particle Swarm Optimization.

Recent

[1] Ackermann T, Anderson G, Soder L. Distributed generation: a definition. Electric Power System Res 2001; 57:195–204. [2] Banerjee R. Comparison of options for distributed generation in India. Energy Policy 2006; 34:101–11. [3] Chiradeja P, Ramakumar R. An approach to quantify the technical benefits of distributed generation. IEEE Trans Energy Convers 2004; 19(4):764–73. [4] Ochoa LF, Padilha-Feltrin A, Harrison GP. Evaluating distributed generation impacts with a multi-objective index. IEEE Trans Power Del 2006; 21(3): 1452–8. [5] Ochoa LF, Padilha-Feltrin A, Harrison GP. Evaluating distributed time-varying generation through a multi-objective index. IEEE Trans Power Del 2008; 23(2): 1132–8. [6] Chakravorty M, Das D. Voltage stability analysis of radial distribution networks. Electric Power Energy Sys 2001; 23:129–35. [7] Ranjan R, Venkatesh B, Das D. Voltage stability analysis of radial distribution networks. Electric Power Compon Sys 2003; 31:501–11. [8] Sahoo NC, Prasad K. A fuzzy genetic approach for network reconfiguration to enhance voltage stability in radial distribution systems. Energy Conver Manage 2006; 47:3288–306. [9] Acharya N, Mahat P, Mithulananthan N. An analytical approach for DG allocation in primary distribution network. Electr Power Energy Sys 2006; 28: 669–78. [10] Hung DQ, Mithulananthan N, Bansal RC. Analytical expressions for DG allocation in primary distribution networks. IEEE Trans Energy Conver 2010; 25(3):814–20. [11] Singh D, Singh D, Verma KS. Multiobjective optimization for DG planning with load models. IEEE Trans Power Sys 2009; 24(1):427–36. [12] Singh D, Singh D, Verma KS. Multiobjective optimization for DG planning with load models. IEEE Trans Power Sys 2009; 24(1):427–36. [13] Nafar M. Optimal placement of DGs in distribution systems considering voltage stability and short circuit level improvement using GA. J Basic Appl Sci Res 2012;2(1):368–75. [14] Nafar M. PSO-based optimal placement of DGs in distribution systems considering voltage stability and short circuit level improvement. J Basic Appl Sci Res 2012; 2(1):703–9. [15] Moradi MH, Abedini M. A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. Electric Power Energy Sys 2012; 34:66–74. [16] Lee Soo-Hyoung, Park Jung-Wook. Selection of optimal location and size of multiple distributed generations by using Kalman filter algorithm. IEEE Trans Power System 2009; 24(3):1393–400. [17] Abu-Mouti FS, El-Hawary ME. Optimal distributed generation allocation and sizing in distribution systems via artificial bee colony algorithm. IEEE Trans Power Delivery 2011; 26(4):2090–101. [18] Imran AM Kowsalya M. Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization. Swarm Evolutionary Compt 2014; 15:58–65. [19] Esmaili M, Firozjaee EC, Shayanfar HA. Optimal placement of distributed generations considering voltage stability and power losses with observing voltage-related constraints. Appl Energy 2014; 113:1252–60. [20] Aman MM, Jasmon GB, Bakar AHA, Mokhlis H. A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses. Energy Converse Manage 2013; 70:202–10. [21] Das D. Optimal placement of capacitors in radial distribution system using a fuzzy-GA method. Electric Power Energy System 2008; 30:361–7. [22] IEEE task force on load representation for dynamic performance. Load representation for dynamic performance analysis. IEEE Trans Power System 1993; 8(2): 472–482 [23] Thukaram D, Banda HMW, Jerome J. A robust three-phase power flow algorithm for radial distribution systems. Electric Power Sys Res 1999; 50: 227–36. [24] Karaboga D. An idea based on honey bee swarm for numerical optimization. Technical Report – TR06, Dept. of Comp. Engg., Erciyes Univ.; October 2005. [25] Karaboga D, Basturk B. On the performance of artificial bee colony (ABC) algorithm. Appl Soft Comput 2008; 8:687–97. [26] Karaboga D, Akay B. A comparative study of artificial bee colony algorithm. Appl Math Comput 2009; 214:108–32. [27] Karaboga D, Basturk B. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Global Optim 2007; 39:459–71. [28] http://www.scholarpedia.org/article/Artificial_be e_ Colony algorithm. [29] Karaboga D, Akay B. A modified artificial bee colony (ABC) algorithm for constrained optimization problems. Apply Soft Comput 2011; 11:3021. [30] Akay B, Karaboga D. A modified artificial bee colony for real-parameter optimization. Info Sci 2012; 192:120–42.

The world’s fourth largest railway is Indian railway next to USA, Russia and China. Now a days there are many problem on trains collision. Therefore now our main aim is “Happy and Healthy Journey”. The work that we are proposing in this paper is preventing train collision prevention system using RFID technique. Here we use RFID tag and RFID reader which are attached to engine and track in order. Hence now by implementing these components we can get the information about track in which it is running and stores it in microcontroller. The same procedure is done in all the trains. And if any two trains RFID tags ID is same the LCD shows “it is wrong path”. Thus by doing so the collision of trains can be avoided, we just added another application also. It is that, if any obstacle is being detected then it is sensed by object sensor and the train will stops the loco pilot gives the current situation of the train to the station then they remove the obstacle.

Keywords : RFID, Railway track finder, Train collision avoidance

Recent

[1] Use of Rfid Based Real Time Location Tracking System to Curb Diversion of Transit Goods in East Africa.Siror, J.K.; Compute. Sci. & Eng. Dept., Shanghai JiaoTongUniv, Shanghai, China; ShengHuanye; Wang Dong. [2] An Anti-Collision Device Networks - A train collision prevention system using TCPS”; Bhatt, Ajay kumar A. [3] International journal research in engineering & avoidance technology volume 3,issue 2,April-May 2015 “Collision avoidance and data broadcasting for railways using RTSU and RFID” T.Kantharaju, B.L. Mamatha. [4] Design concept of train obstacle detection system Rossi Parassella, Bambang Tutuko, Aditya P.P.Prasetyo [5] International Journal of Computer application volume83-No 07,December 2013 “Railway track identifying system using RFID application” Anand Kr.Gupta, Sushant Katiyar , Nitin Kumar [6] RFID Technology and ApplicationsSridhar Iyer. [7] International Journal of Scientific and Engineering Research, August - 2013 “Improvement of Railway Safety with Tracking System using GSM-GPS Model and Obstacle Detection” Nisha S.Punekar, Archana A. Raut.

Knowledge and Data Engineering is the entire process of applying computer-based methodology, including new techniques for knowledge discovery, from data. It refers to the discovery of new information in terms of patterns or rules from vast amounts of data and also maintains privacy of data. Online social network have qualified immense growth in recent years and used by millions of people also.OSN is a platform which creates social relationship among users to share their interests, activities and real life connections but also raising a many privacy and security issues. While OSNs allow users to restrict access to shared data, they currently do not provide any mechanism to enforce privacy concerns over data associated with multiple users. This paper survives many techniques used in OSN privacy issues. Also discuss the pros and cons of these approaches.

Keywords : Online social networks, data privacy, social networking, privacy protection algorithms

Recent

[1] ”Fairness-Aware and Privacy-Preserving Friend Matching Protocol in Mobile Social Networks” Haojin Zhu ;Suguo Du ; Muyuan Li ; Zhaoyu Gao. Publication Year: 2013, Page(s): 192 – 200. [2] ”Multiparty Access Control for Online Social Networks: Model and Mechanisms” Hu, Hongxin ; Ahn, Gail-Joon ; Jorgensen, Jan. Publication Year: 2013 , Page(s): 1614 – 1627. [3] “A Trust-based Privacy-Preserving Friend Recommendation Scheme for Online Social Networks” Guo, L.;Zhang, C.; Fang, Y; Publication Year: 2014. [4] Amarja dgaonkar, Hasib M. Shaikh,”Privacy in Online Social Networks” IJARCSSE, Volume 5, Issue 3,2015 pp 28-32. [5] E. de Cristofaro et al., “Hummingbird: Privacy at the Time of Twitter,” IEEE Symp. Security and Privacy, IEEE CS, 2012, pp. 285–299. [6] J. Anderson and F. Stajano, “Must Social Networking Conflict with Privacy” IEEE Security & Privacy, vol.11, no. 3, 2013, pp. 51–60. [7] A. Cutillo, R. Molva, and T. Strufe, “Safebook: A PrivacyPreserving Online Social Network Leveraging on RealLife Trust,”Communications Magazine, vol. 47, no. 12, 2009, pp. 94–101. [8] F. Beato, M. Kohlweiss, and K. Wouters, “Scramble! Your Social Network Data” Privacy Enhancing Technologies, LNCS 6794, Springer, 2011, pp. 211–225. [9] J. Anderson et al., “Privacy-Enabling Social Networking over Untrusted Networks,” ACM Workshop Online Social Networks (WOSN 09), ACM, 2009, pp. 1–6. [10] B.Carminati and E.Ferrari,”Collaborative AccessControl in Online Social Network,”Proc.7th Internatioal conference collaborative computing:Networking,application and Work Sharing(collaborate-com),pp.231-240,2011.

Patient monitoring is essential to care in operating and emergency rooms, as well as intensive and critical care settings. Recently android has become one of the most popular technologies used in the medical sector. The aim of the paper addresses the survey on android based patient monitoring system to provide a better health care to people in more economic and pertinent friendly manner. Doctors can continuously monitor the patient’s health using the device attached to the patient and an android application. The applications in the healthcare monitoring system remotely monitor the vital signs of the patient and transmit the recorded signal to the doctor. The quality data obtained from the application helps in improving diagnostic and treatment related decision making. This paper also addresses the comparison of the state of the arts solutions available in the healthcare monitoring systems and the technologies used for generating emergency alarms.

Keywords : Android, Healthcare, Patient monitoring, Sensor, Bluetooth, Emergency alarm

Recent

[1] Roy Abi zeid daou,Elias AAD,Farid Nakhle and Ali Hayek,Josef Borcsok, “Patients vital signs monitoring via android application,” ,International Conference on Advances in Biomedical Engineering(ICABME) 2015. [2] Maradugu Anil Kumar ,Ravi kumar Y,”Android Based Health Care Monitoring System”,IEEE 2nd International Conference on Innovation in Information Embedded and Communication Systems ICIIECS’2015. [3] Yuanyuan Du, Yu Chen, Dan Wang, Jinzhao Liu, Yongqiang Lu,”An Android-Based Emergency Alarm and Healthcare Management system”, IEEE 2011. [4] Deepti Ameta, kalpana Mundalir and Palak patel, ”Medication Reminder And Healthcare-An Android Application”,International Journal of Managing Public Sector Information and Communication Technologies(IJMPICT) vol.6,No. 2,june 2015. [5] Sang-Joong Jung,Ristro Myllyla and Wan-Young Chung,”Wireless Machine-to-Machine healthcare solution using android mobile devices in global networks”,IEEE sensors,Vol. 13,no.5,pp.1419-1424,may 2013. [6] MathiasWager,Benjamin,CarlosCabera,Peter Enoksson and Arne Sieber,”Android based body area network for evaluation of medical parameters”,Intelligent solutions in embedded systems(WISES),pp.33-38,jul.2012. [7] Park, KeeHyun & Lim, SeungHyeon, “Construction of a Medication Reminder Synchronization System based on Data Synchronization”, International Journal of Bio-Science and Bio-Technology, Vol.4, No. 4, pp1-10. 2012. [8] Batz, D., Batz, M., Lobo, N.D.V. and Shah, M. “A computer vision system for monitoring medication intake”, Canadian Conf. on Computer and Robot Vision, May, pp. 362-369.2005. [9] Zao, J.K., Wang, M.Y., Peihsuan, T. and Liu, J.W.S., "Smart Phone Based Medicine In-take Scheduler, Reminder and Monitor", IEEE e-Health Networking Applications and Services (Healthcom), pp 162 – 168., 2010. [10] Bingchuan Yuan and John Herbert ,”Web based real time remote montoring for pervasive healthcare”,IEEE international conference on pervasive computing and communications workshops,pp.625-629,march 2011. [11] Aleksandra C. Zoric, SinisaS.llic, “PC Based Electrocardiography &Data Acquisition”, TELSIKS, IEEE, pp 619-622, September 28- 30 2005. [12] Tia Gao, Dan Greenspan, Matt Welsh, Radford R. Juang, and Alex Alm, “Real Time Patient MonitoringSystem Using Lab view”, International Journal of Scientific & Engineering Research,April-2012. [13] Sherin Sebastian, Neethu Rachel Jacob, ”Remote Patient Monitoring System Using Android Technology”, IJDPS, September 2012. [14] C. Wen, M. Yen, K. Chang and R. Lee , “Real-time ECG telemonitoring system design with mobile phone platform”, Measurement, Volume 41, Issue 4, May 2008, Pages 463-470. [15] Wilkoff BL, Auricchio A, Brugada J, Cowie M, Ellenbogen KA, Gillis AM et al. “HRS/EHRA Expert Consensus on the Monitoring of Cardiovascular Implantable Electronic Devices (CIEDs): Description of Techniques, Indications, Personnel, Frequency Ethical Considerations”, Euro pace 2008;10:707–25. [16] Varma N, Epstein A, Schweikert R, Love C, Shah JA, Irimpen “ Evaluation of efficacy and safety of remote monitoring for ICD follow-up” the TRUST trial, Circulation 2008, Vol. 118, No. 22, 2316, Abstract 4078. [17] Kiely DK, “Resident characteristics associated with wandering in nursing home”, Int J Geriatric Psychiatry. 2000; 15(11):1013-1020. [18] K. Lorincz et al., “Sensor Networks for Emergency Response: Challenges and Opportunities,” IEEE Pervasive Computing, IEEE,Press, pp. 16-23, October-December 2004. [19] J. Hill et al., “System Architecture Directions for Networked Sensors,” in Proc. 9th Int’l Conf. Architectural Support for Programming Languages and Operating Systems (ASPLOS 2000)”, ACM Press, pp.93-104, 2000. [20] K. Lorincz and M. Welsh, A Robust, “Decentralized Approach to RF Based Location Tracking, tech. report TR-19-04, Division of Eng. And Applied Sciences “ , Harvard Univ., Cambridge, MA, 2004. [21] Shyr-Kuen Chen, Tsair Kao, Chia-Tai Chan, Chih-NingnHuang, Chih-Yen Chiang, Chin-Yu Lai, Tse-Hua Tung, and Pi-Chung Wang, “A Reliable Transmission Protocol for ZigBee-Based Wireless Patient Monitoring” IEEE Transactions On Information Technology In Biomedicine, Vol. 16, No. 1, January 2012. [22] Suhas Kale, c. S. Khandelwal, “Design and Implementation of Real Time Embedded Tele-Health Monitoring System”, 2013 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2013]. [23] H. Wang, D. Peng, W. Wang, H. Sharif, H. H. Chen, and A. Khoynezhad, “Resource-aware secure ECG healthcare monitoring through body sensor networks”,IEEE Wireless Communication., vol. 17, no. 1, pp. 12–19, Feb. 2010

This paper presents that the concept of parking system in smart cities using Internet of Things (IoT). This system will reduce the time consuming problem during the parking. Sensors will be used to collect the information from the parking area that information will be used to park the vehicle in a particular place. Wireless Sensor Networks (WSN) has been employed to fulfil the necessity of reliable energy and efficient communication between these devices. That network will sense and control the parking area using the sensors and microcontroller. This system identify the vehicle at the entrance, monitors the availability of the free slots, allocate the slot and display the empty slot and path through the smart phones.

Keywords : Internet of Things (IoT), Smart Parking System

Recent

[1] Y. Geng and C. G. Cassandras, ``A new `smart parking' system based on optimal resource allocation and reservations,'' in Proc. 14th Int. IEEE Conf.Intell. Transp Syst. (ITSC), Oct. 2011, pp. 979_984. [2] D. J. Bonde, R. S. Shende, K. S. Gaikwad, A. S. Kedari, and A. U. Bhokre, ``Automated car parking system commanded by Android application,'' in Proc. Int. Conf. Comput. Commun. Inform. (ICCCI), 2014, pp. 1_4. [3] I. F. Akyildiz and I. H. Kasimoglu, ``Wireless sensor and actor networks: Research challenges,'' Ad Hoc Netw., vol. 2, no. 4, pp. 351_367, Oct. 2004. [4] K. Ashokkumar, R. B. Sam, and B. Arshadprabhu, ``Cloud based intelligent transport system,'' in Proc. 2nd Int. Symp. Big Data CloudComput.(ISBCC), vol. 50.2015, pp. 58_63. [5] Z. Suryady, G. R. Sinniah, S. Haseeb, M. T. Siddique, and M. F. M. Ezani, ``Rapid development of smart parking system with Cloud-based platforms,'' in Proc. 5th Int. Conf. Inf. Commun. Technol.Muslim World (ICT4M), 2014, pp. 1_6. [6] D. J. Bonde, R. S. Shende, K. S. Gaikwad, A. S. Kedari, and A. U. Bhokre, ``Automated car parking system commanded by Android application,'' in Proc. Int. Conf. Comput. Commun. Inform. (ICCCI), Coimbatore, India, Jan. 2014, pp. 1_4. [7] Hamada R.H. Al-Absi Patrick Sebastian Justin Dinesh Daniel Devaraj Yap VooiVoon. “Vision-based automated parking system.” 10th International Conference on Information Science,Signal Processing and their Applications (ISSPA 2010), pages 757-760, 2010.

The future generation of wireless communication technologies is expected to be energy-smart while providing rich multimedia contents with higher Quality of Service (QoS) to the end-users, which necessitates integration of various technologies. Green Cognitive and Cooperative HetNets involve optimal integration of cognitive and cooperative communication techniques in heterogeneous networks (HetNets) to increase the energy efficiency without sacrificing significantly the QoS. To reduce the energy consumption overhead introduced by cognitive and cooperative communications, there is a need to incorporate green concepts in communication technologies. Finally, design challenges in embracing green technologies to achieve Green Cognitive and Cooperative HetNets is addressed.

Keywords : HetNet, Cognitive and Cooperative communication, Green communication

Recent

[1] L. Chen, W. Wang, A. Anpalagan, A. V. Vasilakos, K. Illanko , H. Wang , M. Naeem, “ Green Cooperative Cognitive Communicationand Networking: A New Paradigm for Wireless Networks”, Springer , August 2013, Volume 18, Issue 4,pp 524-534 [2] Xing Zhang , YueGaoy, Zhi Yan, Xiao Jian_, FeiPengy, Laurie G. CuthbertyandWenbo Wang, “ Cognitive and Cooperative Communications in Wireless Heterogeneous Networks (HetNet): Current Status and Technical Perspectives” , 2012 IEEE International Conference on Wireless Information Technology and Systems (ICWITS), pages 1-4, ISBN 978-1-4673-0947-9 , DOI: 10.1109/ICWITS.2012.6417787 [3] ZiaulHasan, Student Member, IEEE, HamidrezaBoostanimehr, Student Member, IEEE,and Vijay K. Bhargava, Fellow, IEEE Green Cellular Networks: A Survey, Some Research Issues and Challenges Published in IEEE Communications Surveys & Tutorials (Volume: 13, Issue: 4) Page(s) 524-540ISSN1553-877X DOI:10.1109/SURV.2011.092311.00031 [4] Chethana R Murthy,Asst Prof, Dept of Information Science & Engineering R V College of Engineering,Bangalore, India Dr. C Kavitha, Professor, Dept of Computer Science & Engineering B.N.M. Institute of Technology,Bangalore, India “A Survey of Green Base Stations in CellularNetworks” IRACST – International Journal of Computer Networks and Wireless Communications (IJCNWC), ISSN: 2250-3501 Vol.2, No.2, April 2012 [5] R. Q. Hu ; Department of Electrical and Computer Engineering, Utah State University ; Y. Qian ; S. Kota ; G. Giambene HetNets - a new paradigm for increasing cellular capacity and coverage [Guest Editorial] Published in:IEEE Wireless Communications Page(s):8 – 9ISSN:1536-1284DOI:10.1109/MWC.2011.5876495 [6] Balakrishnan H, Heinzelman W, Chandrakasan A (2000) “Energyefficient communication protocol for wireless microsensor networks”. In: HICSS, pp 3005–3014Published in:System Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on Date of Conference:4-7 Jan. 2000 ISBN:0-7695-0493-0INSPEC Accession Number:6530466 DOI:10.1109/HICSS.2000.926982 [7] Jeffrey G. Andrews, University of Texas at Austin”Seven Ways that HetNets Are a Cellular Paradigm Shift” Published in:IEEE Communications Magazine Page(s): 136 – 144 ISSN:0163-6804 DOI:10.1109/MCOM.2013.6476878 [8] Heng Wang,1,2 Jiamo Jiang,2 Jian Li,2 Manzoor Ahmed,2 and Mugen Peng2.”High Energy Efficient Heterogeneous Networks: Cooperative and Cognitive Techniques” International Journal of Antennas and Propagation Volume 2013 (2013), Article ID 231794, 7 pages http://dx.doi.org/10.1155/2013/231794 [9] R. Xie, F. R. Yu, H. Ji, and Y. Li, “Energy-efficient resource allocation for heterogeneous cognitive radio networks with femtocells,” IEEE Transactions on Wireless Communications, vol. 11, no. 11, pp. 3910–3920, 2012. [10] S. Haykin, “Cognitive radio:brain- empowered wireless communications,” IEEE J. Sel. Areas Commun., vol. 23, no. 2, pp. 201-220, Feb. 2005. [11] ZellerD,BlumeO,BarthU(2010) Approaches to energy efficient wireless access networks. In: Special session on Green Communication at 4th Int. Symp. Commun. Control Signal Processing. Proceedings IEEE VTC Fall [12] Pei, Y.-C. Liang, K. C. Teh, and K. H. Li, “Energy-efficient design of sequential channel sensing in cognitive radio networks: optimal sensing strategy, power allocation, and sensing order,” IEEE Journal on Selected Areas in Communications, vol. 29, no. 8, pp. 1648–1659, 2011.

Small cell networks have emerged as a key technology in residential, office building or hotspot deployments that can significantly fulfil high data demands in order to offload indoor traffic from outdoor macro cells. However, as one of the major challenges, inter-small cell interference gets worse in some building scenarios because of the presence of numerous interfering sources and then needs to be considered in early network planning phase. Though, penetration loss and complex indoor environment make that it is difficult for existing cellular network to sufficiently follow the demand in indoor mobile traffic. The deployment of small cells is envisioned to be a key solution for providing high wireless data-rates, offloading the macro cell traffic and enhancing the coverage of existing networks. Based on the edge nodes all interfering nodes in the small cells are grouped into number of groups, and then the frequency reuse factor is applied according to the dominance interference strength. Hence the power gets transmitted for different groups according to the interference strength. Simulation results shows, the proposed scheme yields great performance gain in terms of the efficiency relative to the universal frequency reuse.

Keywords : In-building small cell networks; frequency reuse

Recent

[1] CERWALL P, BERGQVIST S. Ericsson Traffic and Market Data Report[R]. November, 2011. [2] 3GPP. Requirement for Further Advancements for E-UTRA (LTE-Advanced) [S]. 3GPP Technical Report (TR 36.913) v10.0.0, March, 2011. [3] LOPEZ-PEREZ D, VALCARCE A, ZHANG Jie, et al. OFDMA Femtocells: A Roadmap on InterferenceAvoidance[J]. IEEE Communications Magazine, 2009, 47(9): 41–48. [4] 3GPP, Coordinated Multi-Point Operation for LTE: Physical Layer Aspects[S], 3GPP Technical Report (TR 36.819) v1.1.0, August, 2011. [5] CHANG R Y, TAO Zhifeng, ZHANG Jinyun, et al. A Graph Approach to Dynamic Fractional Frequency Reuse (FFR) in Multi-Cell OFDMA Networks[C]// Proceedings of the IEEE International Conference on Communications: June 14-18, 2009, Dresden Germany, 2009: 1–6. [6] FEMTO FORUM WHITE PAPER. Interface Management in UMTS Femtocells[R]. www.femtoforum.org, Decamber,2008 [7] KOSTA C, IMRAN A, QUDDUS A U, et al. Flexible Soft Frequency Reuse Schemes for Heterogeneous Networks[C]// Proceedings of the IEEE 73rd Vehicular Technology Conference (VTC Spring): May 15-18, 2011, Budapest Marriott, [8] LEE H C, OH D C, LEE Y H. Mitigation of Inter- Femtocell Interference with AdaptiveFractional Frequency Reuse[C]// Proceedings of the IEEE International Conference onCommunications: May 23-27, 2010, Cape Town, South Africa, 2010: 1-5. [9] CHEN Jiming, WANG Peng, and ZHENG Jie. Adaptive Soft Frequency Reuse Scheme for In building Dense Femtocell Networks[C]// Proceedings of the IEEE International Conference on Communications: August 15-17, 2012, Beijing, China, 2012: 530-534.

Abstract Most natural images can be approximated using their low-rank components. This fact has been successfully exploited in recent advancements of matrix completion algorithms for image recovery. However, a major limitation of low-rank matrix completion algorithms is that they cannot recover the case where a whole row or column is missing. The missing row or column will be simply filled as an arbitrary combination of other rows or columns with known values. While increasing the size of the image the original image quality will be affected. In order to avoid the loss of quality while enhancing the image, Low rank optimization based on TV and Non Local Means (NLM) Optimized Sparse Method is used. The resulting is then further enhanced with the help of DTCWT. The noises and the pixel differences occurring in the up sampling and down sampling of the images were identified and they were removed based on the proposed method. The resulting images were then further enhanced with the help of DTCWT. In DTCWT DWT, SWT, SVD decomposition was used. Using DTCWT the image size is further increased and also the image is enhanced. This process is more applicable for medical images since the loss in the original pixel information’s were well preserved. The performance of the proposed method is proved using the performance parameters

Keywords : DTCWT, NLM, SVD

Recent

[1] R.C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd Edition, Prentice Hall, NJ, 2008. [2] Muhammad Zafar Iqbal, Abdul Ghafoor, Adil Masood Siddiqui, Muhammad Mohsin Riaz and Umar Khalid, “Dual-tree complex wavelet transform and SVD based medical image resolution enhancement,” Elsevier, Signal processing, 2014, vol. 10, pp 430-437. [3] K. V. Kale, R. R. Manza, S. S. Gornale, P. D. Deshmukh and Vikas Humbe, “ SWT based Composite Method for fingerprint image enhancement,” IEEE International symposium in signal processing and information technology, 2006, pp 162-167. [4] Hasan Demriel and Gholamreza Anbarjafari, “Satellite image Resolution enhancement using complex wavelet transform,” IEEE Geoscience and remote sensing letters, 2010, vol. 7, no. 1, pp 123-126. [5] A. Marquina and S. J. Osher, "Image super-resolution by TVregularization and Bregman iteration," Journal of Scientific Computing, vol. 37, pp. 367-382, 2008. [6] Janaki Sivakumar, Dr. K. Thangavel and P. Saravanan, “ Computed radiography skull image enhancement using weiner filter,” IEEE International Conference on Pattern recognition, informatics and medical engineering(PRIME), 2012, pp 307-311. [7] Sudipto Dolui, Alan Kuurstra, Ivan C. Salgado Patarroyo and Oleg V. Michailovich, “ A new similarity measure for non-local means filtering of MRI images,” Elsevier, J. Vis. Commun. Image. [8] R., 2013, vol. 24, no.7, pp 1040-1054.Li Yang, Yanmei Liang and Hailun Fan, “Study on the methods of image enhancement for liver CT images,” Elsevier, Optik, 2010, vol. 121, pp 1752-1755. [9] P.-T. Yap, H. An, Y. Chen, and D. Shen, "Fiber-driven resolution enhancement of diffusion-weighted images," NeuroImage, vol. 84, pp. 939-950, 2014. [10] B. Scherrer, A. Gholipour, and S. K. Warfield, "Super-resolution reconstruction to increase the spatial resolution of diffusion weighted images from orthogonal anisotropic acquisitions," Medical image analysis, vol. 16, pp. 1465-1476, 2012. [11] S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, "Advances and challenges in superresolution," International Journal of ImagingSystems and Technology, vol. 14, pp. 47-57, 2004. [12] S. Borman and R. L. Stevenson, "Super-resolution from image sequences-a review," in Circuits and Systems, 1998. Proceedings. 1998 Midwest Symposium on, 1998, pp. 374-378. [13] M. Priyadarshini, Ms. R. Sasikala and Dr. R. Meenakumari, “Novel approach for satellite resolution and contrast enhancement using wavelet transform and brightness preserving dynamic histogram equalization,” IEEE International Conference on green computing communication and electrical engineering, 2014, pp 1-4. [14] M. Irani and S. Peleg, "Improving resolution by image registration," CVGIP: Graphical models and image processing,vol. 53, pp. 231-239, 1991. [15] J. V. Manjón, P. Coupé, A. Buades, V. Fonov, D. Louis Collins, and M. Robles, "Non-local MRI upsampling," Med Image Anal,vol. 14, pp. 784-792, 2010. [16] I. Begin and F. P. Ferrie, "Comparison of super-resolution algorithms using image quality measures," in Computer and RobotVision, 2006. The 3rd Canadian Conference on, 2006, pp. 72-72. [17] J. Yang, J. Wright, T. S. Huang, and Y. Ma, "Image superresolution via sparse representation," Image Processing, IEEETransactions on, vol. 19, pp. 2861-2873, 2010. [18] Vinay Sahu, Gagan Sharma “A Hybrid Approach Of Image Fusion Using Modified DTCWT With High Boost Filter Technique” International Journal of Computer Applications (0975 – 8887) Volume 117 – No. 5, May 2015. [19] Tarun Gulati, Kapil Gupta, Dushyant Gupta” Better Perception of Low Resolution Images Using Wavelet Interpolation Techniques” World Academy of Science, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Vol:9, No:4, 2015. [20] Mayuri D Patil,Shivkumar S Tomar, Setu K Chaturvedi,” Dual Tree Complex Wavelet Transform (DTCWT) based Adaptive Interpolation Technique for Enhancement of Image Resolution” International Journal of Computer Applications (0975 – 8887) Volume 80 – No 14, October 2013.

E-commerce websites are very widely used and the data is constantly growing. Recommendation is a technique used to suggest items based on customer’s likes. The problem is that there is a vast amount of data. This remedy is to use a hybrid approach by combining the Matrix Factorization and Genetic algorithm to conclude the best results. This technique is now applied in the field of medicines.

Keywords : Keyword- Hybrid recommendation, MF, GA, Cold Start

Recent

[1] BamshadMobasher, Honghua Dai, Tao Luo, Yuqing Sun and Jiang Zhu, "Integrating Web Usage and Content Mining for More Effective Personalization, ",2008 [2] A. Naak, H. Hage, and E.A (meur, "A Multi-criteria Collaborative Filtering Approach for Research Paper Recommendation in Papyres," MCETECH 2009, LNBIP 26, pp. 25-39, 2009. [3] Felice Ferrara, NirmalaPudota, and Carlo Tasso, "A Keyphrase -Based Paper Recommender System" IRCDL 2011, CCIS 249, pp. 14-25, 2011. [4] A. Nisgav and B. Patt-Shamir, “Finding similar users in social networks,” Theory Comput.Syst., vol. 49, pp. 720–737, 2011. [5] Bo X., Peng, H., Fan, Y., Ruimin, S., Pipe, CF.: A scalable DHT-based collaborative filtering recommendation system, WWW 2004, May, 17–22, 2004. [6] D. E. Goldberg and J. H. Holland, "Genetic Algorithms and Machine Learning," Machine Learning, vol. 3, no. 2-3, pp. 95-99, 1988. Robin Burke,” Hybrid Web Recommender Systems”.

Dimensionality Reduction is the process of extracting the more relevant information. Conventional dimensionality reduction is categorized into two methods like Stand alone and Hybrid method. Standalone dimensionality reduction reduces the dimensions based on a single criterion whereas Hybrid method combines two or more criterion. In this paper, we proposed new hybrid method for dimensionality reduction Using Kaiser Component Analysis (KCA) and Independent Component Analysis (ICA). Kaiser component Analysis extracts the uncorrelated information and Independent Component Analysis maximizing the Independency among the data. The hybrid method using these Kaiser Component Analysis and Independent Component Analysis achieves both correlations and Independency among the Information and it is applied on SVM classification. The result improves the accuracy of the classification.

Keywords : Dimensionality reduction, Kaiser Component Analysis, Independent Component Analysis, Stand alone and Hybrid methods, SVM classification.

Recent

[1] Jun Li ; Dacheng Tao ,”Simple Exponential Family PCA”, IEEE Transactions on Neural Networks and Learning Systems, Volume: 24 , Issue:3 Publication Year: 2013 , Page(s): 485 - 497 [2] S. Moon and H. Qi ,“ Hybrid dimensionality reduction method based on Support vector machine and independent component analysis", IEEE Transaction on Neural Networks, volume. 23, pages.749 -761 year 2012 [3] Qi Ding ; Kolaczyk, E.D. , “ A Compressed PCA Subspace Method for Anomaly Detection in High-Dimensional Data “,IEEE Transactions on InformationTheory,Volume:59, Publication Year: 2013 ,Page(s):7419 – 7433 [4] Chuxiong Miao ; Yu Wang ; Yonghong Zhang ,” A SVM classifier combined with PCA for ultrasonic crack size classification“ , International conference on Computer Engineering, 2010, Page(s): 001627 – 001630 [5] N. Kwak , “Principal component analysis based on L1-norm maximization", IEEE Transaction on Pattern Analysis and Machine Intelligence, volume. 30, no. 9, pages.1672 -1680 Year : 2008 [6] Xu Chunming ; Jiang Haibo ; Yu Jianjiang ,” Robust two-dimensional principle component analysis “, IEEE transaction on signals and control Publication Year: 2010 , Page(s): 452 - 455 [7] Amiri-Simkooei, A.R.; Snellen,M. ; Simons, D.G., “ Principal Component Analysis of Single-Beam Echo-Sounder Signal Features for Seafloor Classification” ,IEEE Transaction on Oceanic Engineering, Volume: 36, Issue: 2 Publication Year: 2011 , Page(s): 259 – 272 [8] Ran He; Bao-Gang Hu; Xiang-Wei Kong ,"Robust Principal Component Analysis Based on Maximum Correntropy Criterion", IEEE Transactions on Image page(s): 1485 - 1494 , Issue: 6, June 2011 [9] J. Zhao , P. Yu and J.Kwok “ Bilinear probabilistic principal component analysis", IEEE Transaction on Neural Networks and Learning system., volume. 23, no. 3, pages.492 -503, publication year: 2012 [10] Dobry, G. ; Hecht, R.M. ; Avigal, M. ; Zigel, Y., “ Supervector Dimension Reduction for Efficient Speaker Age Estimation Based on the Acoustic Speech Signal”, IEEE Transactions on Audio, Speech, and Language Processing, Issue: 7 Publication Year: 2011 , Page(s): 1975 - 1985 [11] Senthilnath, J. ;Omkar, S.N. ; Mani,”Crop Stage Classification of Hyperspectral Data Using Unsupervised Techniques”, IEEE Transcation on Applied Earth Observations and Remote Sensing, Volume: 6, Issue: 2 , Part:3 Publication Year: 2013 , Page(s): 861 - 866 [12] Van De Ville, D. ; Kocher, M. , “Nonlocal Means With Dimensionality Reduction and SURE-Based Parameter Selection“, IEEE Transactions on Image Processing, Volume: 20 , Year: 2011 , Page(s): 2683 - 2690 [13] Kamath, Sunil ; Ravindran, S. ; Anderson, D.V., ”Independent Component Analysis for audio classification“ IEEE Transactions on Digital Signal Processing Year: 2009, Page(s): 352 355 [14] S. Dhir and S.-Y. Lee, “ Discriminant independent component analysis “, IEEE Transaction on Neural Networks, volume. 22, pages : 845 -857 2011

In this paper, we have proposed a DWT-based image compression algorithm via a popular Distributed Arithmetic (DA) technique for image and video compression. It is applied to determine the wavelet coefficients and so that the number of arithmetic operations can be reduced. The compression rate is enhanced by introducing RW block. It blocks some of the coefficients obtained from the high pass filter to zero. Then Differential Pulse-Code Modulation (DPCM) and Huffman-encoding are applied to acquire the binary sequence of the image. The functional simulation and performance of each module is analyzed with gate requirement, area, power, compression rate, and computation time. The proposed compression approach offers good performance in power efficiency than the prior methods. Furthermore, Altera FPGA based hardware realization shows 32% reduction in dynamic power consumption when compared to the literature.

Keywords : Image compression, DWT, DA, DPCM, Huffman-coding.

Recent

[1] Dhulap S. and Nalbalwar S., “Image Compression Based on IWT, IWPT & DPCMIWPT,” International Journal of Engineering Science and Technology, vol. 2, no. 12, pp. 7413- 7422, 2010. [2] Bhuyan M., Amin N., Madesa M., and Islam M., “FPGA Realization of Lifting Based Forward Discrete Wavelet Transform for JPEG 2000,” International Journal of Circuits, Systems andSignal Processing, vol. 1, no. 2, pp. 124-129, 2007. [3] Chen S., Bermak A., Yan W., and Martinez D., “Adaptive-Quantization Digital Image Sensor for Low-Power Image Compression,” IEEETransaction Circuits System I: Regular Papers, vol. 54, no. 1, pp. 13-25, 2007. [4] Song M., “Entropy Encoding in Wavelet Image Compression,” in Proceedings of Representations, Wavelets and Frames, Applied and Numerical Harmonic Analysis , BirkhauserBoston, pp. 2932311, 2007. [5] Cao X., Xie Q., Peng C., Wang Q., and Yu D.,“An Efficient VLSI Implementation of Distributed Architecture for DWT,” in Proceedings of the IEEE 8th Workshop on Multimedia Signal Processing, Victoria, pp. 364- 367, 2006. [6] Huang C., Seng P., and Chen L., “Analysis and VLSI Architecture for 1-D and 2-D Discrete Wavelet Transform,” IEEE Transactions onSignal Processing, vol. 53, no. 4, pp. 1575-1586, 2005. [7] Huang C., Tseng P., and Chen L., “Flipping Structure: an Efficient VLSI Architecture for Lifting-Based Discrete Wavelet Transform,” IEEE Transaction Signal Processing, vol. 52, no. 4, pp. 1080-1089, 2004. [8] Pillai L., “Huffman Coding,” available at:http://www.xilinx.com/support/documentation/application_notes/xapp616.pdf, last visited 2003. [9] Andra K., Chakrabarti C., and Acharya T., “A VLSI Architecture for Lifting-Based Forward and Inverse Wavelet Transform,” IEEETransaction Signal Process, vol. 50, no. 4, pp. 966-977, 2002. [10] Davis G. and Nosratinia A., “Wavelet-Based Image Coding: an Overview,” in Proceedings ofApplied and Computational Control, Signals, and Circuits, New York, vol. 1, pp. 205-269, 1998. [11] Chakrabarti C., Vishwanath M., and Owens R., “Architectures for Wavelet Transforms: A Survey,”Journal VLSI Signal Process, vol. 14, no. 2, pp. 171-192, 1996.

In this paper, we demonstrate the performance characteristics of the gain, surface waves, return loss of microstrip patch antenna with and without Electromagnetic Band Gap structure (EBG) for WLAN application. Electromagnetic Bandgap Structure (EBG) is mainly focused on overcoming the limitation of Microstrip Patch antenna such as low gain, excitation of surface waves etc., The Microstrip Patch Antenna consists of dielectric substrate with ground plane at one end and patch at other end whereas in EBG concept, additional EBG substrate with EBG cells are inserted in between ground and dielectric substrate. The simulation is done by using High Frequency Structure Simulator (HFSS).We have obtained gain of 14.2 dB for circular EBG and gain of 8.64 dB for rectangular EBG model respectively. Hence, we improved the efficiency of the antenna the EBG model.

Keywords : Micro strip Patch Antenna, Electromagnetic Band Gap Structure (EBG), Band Gap Gain, Surface waves, Return Loss

Recent

[1] C.A.Balanis, “Antenna theory, Analysis and Design”, 2nd Edition. [2] Dan Sievenpiper, Lijun zhang, Romulo F. Jimenez Broas, Nicholas G. Alexopolous and Eli Yablonovitch, “High- Impedence Electromagnetic Surfaces with the forbidden frequency band”, IEEE transactions on Microwave theory and techniques, 1999 [3] Ananias Parameswaran, Bandwidth Enhancement of Microstrip Patch Antenna using Metamaterials , IOSR Journal of Electronics and Communication Engineering (IOSR-JECE ), Dec 2013. [4] M.N. Tan, T.A. Rahman, S.K.A. Rahim, M.T. Ali and M.F. Jamlos, “Antenna Array Enhancement Using Mushroom-like Electromagnetic Band Gap (EBG)”, Antennas and Propagation, April 2010. [5] Sandhya Bhavsar, Prof. Bharati Singh “Electromagnetic Band Gap Structures Incorporated In Antenna Array: A Review”, International Journal of Computer Technology and Electronics Engineering (IJCTEE), March-April 2013. [6] M.S. Alam, M.T. Islam and N. Misran, “Design Analysis of an Electromagnetic Band Gap Microstrip Antenna”, American Journal of Applied Sciences 8 (12): pp 1374-1377, 2011. [7] Zaid A.Hamid, “Design and Implementation of a Microstrip Patch Antenna for WLAN 802.11b communication standard”, International Journal of Multidisciplinary and Current Research, 2015.

Skin cancer is one of the major causes of deaths in recent days. Early detection of skin cancer reduces death at higher rate. Ceroscopy is one of the major modalities used in diagnosis of skin lesions. Skin lesions are of different types. Among them the most common types of skin lesion found in human are melanoma, basal cell carcinoma (BCC) and squamous cell carcinoma (SCC).The accurate diagnosis information cannot be obtained by human interpretation. In order to overcome the error due to human interpretation an efficient computerized image analysis system has been developed. The proposed image analysis system consists of preprocessing, lesion segmentation, feature extraction and classification. In classification, different types of classifiers such as support vector machine (SVM), probabilistic neural network (PNN) and adaptive neurofuzzy inference system (ANFIS) are applied to classify the skin cancer types and their performance is compared using the evaluated parameters.

Keywords : Skin cancer, Feature extraction, Adaptive Neurofuzzy inference system, Thresholding

Recent

[1] S.G.Mallat,“A Theory for Multiresolution, (1989) Signal Decomposition: The Wavelet Representation”, IEEE Transactions on Pattern Analysis and Machine Intelligence vol. 7, no. 11, pp. 674–93. [2] P.Bilek,A. B. Cognetta,M. Landthaler, T. Merckle,F. Nachbar,G. Plewig, W. Stolz and T. Vogt(1994)“The ABCD ruleof dermatoscopy:High prospective value in the diagnosis of doubtful melanocytic skin lesions,” J. Amer. Acad. Dermatol., vol. 30, pp.551–559. [3] R. Mahmud,A. Ramli, M.Al-Qdaha, (2005) “A system of Micro-Calcifications Detection and Evaluation of the Radiologist: Comparative Study of the three main races in Malaysia”, Elsevier Journal of Computers in Biology and Medicine vol. 35, no. 10. [4] F.Godtliebsen,H. M. Kirchesch,K. Møllersen, T. G. Schopf, and ,(2010)``Unsupervised segmentation for digital dermoscopic images,'' Skin Res.Technol., vol. 16, no. 4, pp. 401_407. [5] M. S. Atkins, T. K. Lee, N. H. Nguyen,(2010) and ``Segmentation of light and dark hair in dermoscopic images: A hybrid approach using a universal kernel,'' Proc. SPIE, vol. 7623, p. 76234N. [6] Q. Abbas, I. Fondon, and M. Rashid,(2011) ``Unsupervised skin lesions border detection via two-dimensional image analysis,''Comput. Methods Programs Biomed., vol. 104, no. 3, pp. e1_e15. [7] Dimitri Dubovitski, Jonathan Blackledge,(2011) “Mole test: A Web-based Skin Cancer Screening System”, Intensive 2011: The Third International Conference on Resource Intensive Applications and Services, vol: 978-1-61208-006-2, pp. 22 – 29. [8] M.d.KhaladAbuMahmoud,Wighton.P,(2011)“The Automatic Identification of Melanoma by Wavelet and Curve let Analysis: Study Based on Neural Network Classification”, 11th IEEE International Conference on Hybrid Intelligent Systems (HIS), pp: 680- 685. [9] A.Karargyris,O.Karargyris,andDERMA/Care,(2012)Advanced image-processing mobile application for monitoring skincancer,'' in Proc. IEEE 24th Int. Conf. Tools Artif. Intell. (ICTAI), pp. 1_7. [10] Nilkamal S. Ramteke, Shweta V. Jain,(2013) “Analysis of Skin Cancer Using Fuzzy and Wavelet Technique –Review & Proposed New Algorithm” International Journal of Engineering Trends and Technology(IJETT) ,Volume 4, Issue 6 [11] Sookpotharom Supot,(2014) “Skin Lesion Detection of Dermoscopy Images Using Estimate Localization Technique”, pg. no. 833-836. [12] http://www.healthline.com/health/skin-lesions [13] http://en.wikipedia.org/wiki/Skin_cancer

Discrete Cosine Transform is the most widely used transform recorded in the history especially for image and video compression. DCT can be efficiently carried out using a well-known iterative algorithm called CORDIC to perform vector rotations. An efficient CORDIC based fast algorithm for DCT is presented with some notable advantages like data flow similar to Cooley - Tukey FFT, identical post-scaling factor and rotation angles in arithmetic sequence. CORDIC types are reduced to one by choosing trigonometric formula. This algorithm overcomes the problem of non-synchronization among the CORDIC rotation angles. This is achieved by using Carry Save Adder (CSA) in the Processing Elements (PE) in the place of full adders and the two different PEs are used to exploit four PEs. The delay reduces drastically by using modified 4:2 Carry Save Adder architecture

Keywords : Compression, CORDIC, DCT, Carry Save Adder, Carry Look-ahead Adder, Processing Elements

Recent

[1] Ahemed, N., Nagarajan, T.andRao, K.R. (1974). Discrete Cosine Transform. IEEE Trans. Comput. C-23, 90-94. [2] Chen, C.T., Chen, L.G.,Chiueh, T.D. and Hsiao,J.H. (1995). High throughput CORDIC-based systolic array design for the discrete cosine transform.IEEE Trans. Circuits Syst. Video Technol. 5 (3), 218-225. [3] Chen, C.H., Liu, B.D., and Yang, J.F. (2004). Direct recursive structures for computing radix-r two dimensional DCT/IDCT/DST/IDST.IEEE Trans. Circuits Syst.–I: Regul.Pap.51, 10. [4] Fanucci, L.,Saletti, R. and Saponara, S. (2001). Parameterized and reusable VLSI macro cells for low-powerof 2-D Discrete-Cosine-Transform.Microeletron.J.32, 1035-1045. [5] Huang, H., andXiao. L., CORDIC based fast algorithm for power-of-two point DCT and its efficient VLSI implementation.Microelectronics J., Vol. 45, Issue 11, 1480-1488, Nov. 2014. [6] Hou, H.S. (1997). A fast recursive algorithm for computing the discrete cosine transform.IEEE Trans. Acoust. Speech Signal Process.ASSP-35, 1445-1461. [7] Huang, H., andXiao, L. (2013). Variable length reconfigurable algorithms and architectures for DCT/IDCT based modified unfolded CORDIC.The Open Electrical & Electronic Engineering Journal 7, (Supple 1: M8), 71-81. [8] Kaddachi, M.L.,Soudani, A.,Lecuire, V., Makkaoui, L., Moureaux, J.M. and Torki, K. (2012).Design and performance analysis of a zonal DCT-based image encoder for wireless camera sensor networks.Microelectron.J. 43, 809-817. [9] Narasimha, M.J., and Peterson, A.M. (1978). On the computation of the discrete cosine transform.IEEE Trans. Commun. 26 (6), 934-936. [10] Pan, S.B., andPark,R.H. (1997).Unified systolic arrays for computation of DCT/DST/DHT. IEEE Trans. Circuit Syst. Video Technol. 7 (2), 413-419. [11] RiyaGarg, SumanNehra and B.P. Singh., (Mar. 2013). Low power 4-2 Compressor for Arithmetic Circuits.IJRTE,Vol. 2, Issue 1, ISN: 2277-3878. [12] Radhakrishnan, D.,Preethy, A.P. (2000). Low Power CMOS Pass Logic 4-2 Compressor for High-Speed Multiplication.Proc. IEEE Midwest Symp. On Circuits and Systems, pp. 1-3. [13] RiyaGarg, SumanNehra and Singh, B.P. (2013).Low power Full Adder using 9T Structure.International Journal on Recent Trends in Engineering and Technology, Vol. 8, No. 2, pp. 7-10. [14] RiyaGarg, SumanNehra and Singh, B.P. (2013).A New Design of Full Adder based on XNOR-XOR Circuit.International Journal of Computer Application, Vol. 8, No. 2, pp. 7-10.

Because of the increased design complexity and advanced fabrication technologies, number of tests and corresponding test data volume increases rapidly. As the large size of test data volume is becoming one of the major problems in testing System on- a-Chip (SOC). Test data volume reduction is an important issue for the SOC designs. Several compression coding schemes had been proposed in the past. Run Length Coding was one of the most familiar coding methodologies for test data compression. Golomb coding was used in existing compression side. The compression ratio of golomb code was found to be lesser than the combined Alternative Variable Run-length code (AVR) and nine code compression (9C) methods. The proposed combined AVR and 9C codes are used for reducing the test data volume. The experiment is conducted for proposed methods using ISCAS’89 benchmark circuits. The experimental results shows that, the proposed method is highly efficient when compared with the existing methods.

Keywords : SOC, Integrated coding, FSM, Test Data Compression, efficiency

Recent

[1] Abramovici, M., Breuer, M.A. and Friedman, A.D. (1990). Digital System Testing and Testable Design, IEEE press. The Institute of EEE, Inc. [2] Aiman, H., El-Maleh, Raslan, H. and Al-Abaji. (2002). Extended Frequency-Directed Run-Length Code with Improved Application to System-on –a-Chip Test Data Compression, Int. Conf: on Electronics, Circuits and Systems, 2:449-452. [3] Chandra, A., Chakrabarty, K. (2001). Frequency-directed run-length (FDR) codes with application to System-on-a-Chip test data compression, in Proc. VLSI Test Symp., pp.42-47. [4] Chandra, A., Chakrabarty, K. (2002). Reduction of SOC Test Data Volume, Scan Power and Testing Time Using Alternative Run-length Codes, DAC’02: Proceeding of the 39th conference on Design automation. [5] Jin Shang and Liyong Zhang (2013). Test Data Compression Scheme Based on Compatible Data Block Coding, Information Technology Journal 12(1): 204-208. [6] Kalamani, C. and Paramasivam, K. (2013). Survey of Low PowerTesting Using Compression Techniques, IJECT Vol 4, Issue 4. [7] Kalamani, C. and Paramasivam, K. (2014). A Combined Compatible Block Coding and Run Length Coding Techniques for Test Data Compression, World Applied Sciences Journal 32 (11): 2229-2233. [8] Lei, S., Hou, X., Shao, Z., Liang, F. (2008). A Class of SIC circuits: Theory and application in BIST design, IEEE Trans. Circuit system II 55(2) pp. 161-165. [9] Pranab K. Nag., Anne Gattiker. and Sichao Wei. (2002). Modelling the Economics of Testing: A DFT Perspective, in IEEE Design & Test of Computers. [10] Priyanka Kalode and Richa Khandelwal (2012). Test Data Compression Based on Golomb, Signal & Image Processing: AnInternational Journal (SIPIJ) Vol.3, No.2. [11] Shurti Chadha and Harpreet Vohra. (2015). Enhanced Compression Code for SOC Test Data Volume Reduction, IJCEM International Journal of Computational Engineering & Management, Vol. 18 Issue 3, pp. 14-18. [12] Tehranipoor, M., Nourani, M., Chakrabarty, K. (2005). Nine-coded compression technique for testing embedded cores in SoC’s, IEEE Tranx.Very Large Scale Integr. (VLSI) Syst.13 (6)719-730. [13] TAUBA, N.A. (2016). Survey of Test Vector Compression Techniques, IEEE transaction Design & Test of Computers, pp. 294-303. [14] Usha, S. Mehta, Kankar, S. Dasgupta. and Niranjan, M. Devashrayee. (2010). Hamming distance based reordering and column wise bit stuffing with difference vector: A better scheme for test data compression with run-length based codes, 23rd International Conference on VLSI design. [15] Ye, B., Zhao, Q., Zhou, D., Wang, X., Luo, M. (2011). Test data compression using alternative variable run-length code, Integr.VLSIJ.44 (2)103-110.

Dual-supply voltage design using a clustered voltage scaling (CVS) scheme is an effective approach to reduce chip power. The optimal CVS design relies on a level converter implemented in a flip-flop to minimize energy, delay, and area penalties due to level conversion. A novel level-up shifter with dual supply voltage is proposed. The proposed design significantly reduces the short circuit current in conventional cross-coupled topology, improving the transient power consumption. Compared with the bootstrapping technique, the proposed circuit consumes significantly less area, making it more practical for ICs with a large number of supply voltages. TINA tool has been used to show the existing and proposed results.

Keywords : Dual Power Supply, Short Circuit Current

Recent

[1] Ameet Chavan, Eric MacDonald,” Ultra Low Voltage Level Shifters to Interface Sub and Super Threshold Reconfigurable Logic Cells” [2] Lawrence T. Clark and Shay Demmons,” Standby Power Management for a 0.18μm Microprocessor” [3] P. Corsonello, M. Lanuzza and S. Perri,” Gate-level body biasing technique for high speed sub-threshold CMOS logic gates” Int. J. Circ. Theor. Appl. (2012) [4] Fujio Ishihara, Farhana Sheikh, and Borivoje Nikolic,” Level Conversion for Dual-Supply Systems”, IEEE transactions on very large scale integration (vlsi) systems, vol. 12, no. 2, february 2004 [5] Marco Lanuzza, Pasquale Corsonello, and Stefania Perri,” Fast and Wide Range Voltage Conversion in Multisupply Voltage Designs”, IEEE transactions on very large scale integration (vlsi) systems, vol. 23, no. 2, february 2015 [6] J. Kwong, Y. K. Ramadass, N. Verma, and A. P. Chandrakasan, “A 65 nm sub-Vt microcontroller with integrated SRAM and switched capacitor DC–DC converter,” IEEE J. Solid-State Circuits, vol. 44, no. 1,pp. 115–126, Jan. 2009. [7] Marco Lanuzza, Pasquale Corsonello and Stefania Perri,” Low-Power Level Shifter for Multi-Supply Voltage Designs”, IEEE transactions on circuits and systems—II. [8] A. Chavan and E. MacDonald, “Ultra low voltage level shifters to interface sub and super threshold reconfigurable logic cells,” in Proc. IEEE Aerosp. Conf., 2008, pp. 1–6. [9] A. Hasanbegovic and S. Aunet, “Low-power subthreshold to above threshold level shifter in 90 nm process,” in Proc. NORCHIP Conf., Trondheim, Norway, 2009, pp. 1–4. [10] S. Lütkemeier and U. Rückert, “A subthreshold to above-threshold level shifter comprising a wilson current mirror,” IEEE Trans. Circuits Syst. II, Exp. Briefs, vol. 57, no. 9, pp. 721–724, Sep. 2010. [11] K. Usami et al., “Automated low-power technique exploiting multiple n supply voltages applied to a media processor,” IEEE J. Solid-State Circuits,nvol. 33, pp. 463–472, Mar. 1998. [12] R. Puri et al., “Pushing ASIC performance in a power envelope,” in Proc. Design Automation Conf., Anaheim, CA, June 2003, pp. 788–793. [13] C. Yu, W. Wang, and B. Liu, “A new level converter for low-power applications,” in Proc. Int. Symp. Circuits and Systems, Sydney, Australia, May 2001, pp. 113–116. [14] D. Markovic´, B. Nikolic´, and R.W. Brodersen, “Analysis and design of low-energy flip-flops,” in Proc. Int. Symp. Low Power Electronics and Design, Huntington Beach, CA, Aug. 2001, pp. 52–55. [15] Y. Kanno, H. Mizuno, K. Tanaka, and T. Watanabe, “Level converters with high immunity to power supply bouncing for high speed sub-1-V LSIs”, Symposium on VLSI Circuits, 2000. pp.202-203 [16] M. Lanuzza, P. Corsonello, and S. Perri, “Low-power level shifter for multi-supply voltage designs,” IEEE Trans. Circuits Syst., Exp. Briefs,vol. 59, no. 12, pp. 922–926, Dec. 2012. [17] Muker M, Shams M. Designing digital subthreshold CMOS circuits using parallel transistor stacks. Electronics Letters 2011; 47(6):372–374. [18] Verma N, Kwong J, Chandrakasan AP. Nanometer MOSFET Variation in Minimum Energy Subthreshold Circuits. IEEE Transactions on Electron Devices 2008; 55(1):163–174. [19] Dreslinski RG, Wieckowski M, Blaauw D, Sylvester D, Mudge T. Near-threshold computing: reclaiming Moore’s law through energy efficient integrated circuits. Proceedings of the IEEE 2010; 98(2):253–266. [20] Y.-S. Lin and D. M. Sylvester, “Single stage static level shifter design for subthreshold to I/O voltage conversion,” in Proc. 13th ISLPED, Aug. 2008, pp. 197–200.