Volume-5 , Issue-1 , Apr 2017, ISSN 2321-3256 (Electronic Version) Go Back

• Open Access   Article

  Improvement in Gain and Bandwidth using Current Mode Technique

  N. Nikalje, S.R. Devane

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.1 , pp.1-5, Apr-2017

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  Nowadays in Modern wireless Receiver, high speed data availability and increased usage of wireless devices has increased challenges in improving battery life. In voltage mode circuits shows poor performance in various parameter like gain, bandwidth, power consumption. To overcome of this disadvantage current mode are much more beneficial. Due to exponential increase in users, bandwidth requirement also increased. In any communication system, current mode receiver will be beneficial from high data rate receiving point of view. In this paper, a current mode receiver which can operate at very low voltage and provide high frequency at the output. For this, a current-mode device is modeled and using this modeled device, the various circuit blocks are simulated using H-SPICE software. The proposed current mode receiver can work at very low voltages and consume less power, compare to voltage mode receiver.

  Key-Words / Index Term
  CM (current-mode), VM (voltage-mode), power consumption, CC (current conveyor), CFA (current feedback amplifier)

  References
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  [3]. U.P. Khot, N.A. Bhagat, “Current Mode based Communication System”, International journal of innovative research in electrical electronics instrumentation and control engineering, vol.3, Issue.3, pp.1-8, 2015.
  [4]. T.S. Rathore, U.P. Khot, “Voltage Mode-to-Current Mode Transformation”, IJET, Vol.4, no.5, pp.349-363, 2012.
  [5]. T. Dostal, D. Biolek, K. Vrba, “Ad-joint Voltage-Current Mode Transformation For Circuits Based On Modern Current Conveyors”, Proceedings of the Fourth IEEE International Caracas Conference on Devices Circuits and Systems, Netherlands, pp.17-19, 2002.
  [6]. M. Kumar, “Low-Voltage Current-Mode Analog Cells”, IIT Bombay, India, pp.1-4, 2002.
  [7]. K.K. Singh, G. Srivastava, R.S. Mishra, D. Tiwari, “Current Conveyor: A Novel Active Building Block Prevailing Op-Amp Limitations”, IJITEE, Vol.2, Issue.2, pp.48-50, 2013.
  [8]. W. Tangsrirat, “Electronically Tunable Multi-Terminal Floating Nullor and Its Applications”, Radio engineering, Vol.17, No.4, pp.4-7, 2008.
  [9]. AP. Singh, SK. Pandey, M. Kumar, “Operational Trans conductance Amplifier for Low Frequency Application”, International Journal of Computer Technology and Applications, Vol.3, Issue.3, pp.1064-1065, 2012.
  [10]. E. Sumathi, M.S. Sheelam, B. Arunkumar, “Advanced Sensor less Control of Brushless DC Motor using Terminal Voltage Sensing Method”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.98-102, 2014.
  [11]. TS. Rathore, KP. Uday, “Voltage Mode-to-Current Mode Transformation”, International Journal of Engineering and Technology, Vol.4, No.5, pp.349-370, 2012.
  [12]. Esma Uzunhisarcikli, “The Use Of Adjoint Transformation Method To Transformation Current Mode From Voltage Mode In Universal Active Element Based Filters”, G.U. Journal of text Science, Vol.17, Issue.3, pp. 179-187, 2004.
  

  Citation
  N. Nikalje, S.R. Devane, "Improvement in Gain and Bandwidth using Current Mode Technique," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.1-5, 2017

• Open Access   Article

  ROI Based Medical Image Compression

  SD. Kasute, M. Kolhekar

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.1 , pp.6-11, Apr-2017

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  Abstract
  Bio-medical image processing is considered as one of the broad field as compared to other fields. It includes image forming, biomedical signal gathering, image processing, picture processing and the features extracted from images used for medical diagnosis. It contains analysis of the image, enhancement of the image and display of images captured via Ultrasound, MRI and X-Ray technologies. A Region Of Interest (ROI) is defined as a portion of an image that we want to extract from the image or perform some other operations on it. The objective of the paper is to compress the ROI in lossless manner using Set Partitioning In Hierarchical Tree (SPIHT) algorithm and Non-ROI i.e; background region in a lossy manner using Discrete Wavelet Transform (DWT). A detailed analysis is carried out by using the parameters like Compression Ratio (CR), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR).

  Key-Words / Index Term
  Region Of Interest (ROI), X-Ray, MRI, SPIHT, DWT, CR, MSE, PSNR

  References
  [1]. D.S. Thomas, M. Moorthi, R. Muthalagu, “Medical Image Compression Based On Automated ROI Selection For Telemedicine Application” International Journal of Engineering and Computer Science, Vol.3 Issue1, pp.3638-3642, 2014.
  [2]. P. Ranjan, P.R. Khan, "Review of improved A.I. based Image Segmentation for medical diagnosis applications", International Journal of Computer Sciences and Engineering, Vol.4, Issue.11, pp.75-81, 2016.
  [3]. NS. Korde, A.A. Gurjar, “Wavelet Based Medical Image Compression For Telemedicine Application”, American Journal of Engineering Research, Vol.3, Issue.1, pp-106-111, 2014.
  [4]. R. Singh, S Agarwal, "Theoretic Study of Various Image Compression Techniques: A Survey", International Journal of Computer Sciences and Engineering, Vol.3, Issue.5, pp.341-344, 2015.
  [5]. S. Agarwal, "Edge Detection in blurred images using Ant Colony Optimization Techniques", International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.2, pp.21-24, 2013.
  [6]. Monisha Sharma, " An Efficient Medical Image Compression By SPIHT And EZW Based On ROI And NROI Using Wavelet Decomposition", International Journal of Engineering Research & Technology, Vol. 2 Issue.7, pp.1600-1605, 2013.
  [7]. TMP. Rajkumar, MV. Latte, “ROI Based Encoding of Medical Images: An Effective Scheme Using Lifting Wavelets and SPIHT for Telemedicine”, International Journal of Computer Theory and Engineering, Vol.3, Issue.3, pp.338-342, 2011.
  [8]. M. Yang, N. Bourbakis, "An Overview of Lossless Digital Image Compression Techniques", 48th Midwest symposium on Circuits and systems, Covington, pp.1099-1102, 2005.
  [9]. VK. Padmaja, B. Chandrasekhar, “Literature Review of Image Compression Algorithm”, International Journal of Scientific & Engineering Research, Vol.3, Issue.6, pp.1-6, 2012.
  [10]. A. Mudgal, R. Singh, "A Hybrid Method of Medical Image De-nosing Using Subtraction Transform and Radial Biases Neural Network", International Journal of Computer Sciences and Engineering, Vol.3, Issue.9, pp.54-59, 2015.
  [11]. LK. Griffeth, “Use of PET/CT scanning in cancer patients: technical and practical considerations”. Proceedings of Baylor University Medical Cente, Vol.18, Issue4, pp.321-330, 2005.
  [12]. A. Said, W.A. Pearlman, “ A New Fast and Efficient Image Codec Based on Set Partitioning In Hierarchical Trees,” IEEE Trans. Circuits & Systems for Video Technology, Vol.6, Issue.3, pp. 243-250, 1996.
  [13]. Architecture for Content Based Image Retrieval Using Modified SVM and knn-GA", International Journal of Computer Sciences and Engineering, Vol.2, Issue.10, pp.41-45, 2014.
  [14]. Premal B. Nirpal, "Image Compression using Discrete Cosine Transform, Block Truncation Coding and Gaussian Pyramidal Approach", International Journal of Computer Sciences and Engineering, Vol.3, Issue.4, pp.21-25, 2015.
  [15]. J. Ma, T. Zhang and M. Dong, "A Novel ECG Data Compression Method Using Adaptive Fourier Decomposition With Security Guarantee in e-Health Applications", IEEE Journal of Biomedical and Health Informatics, Vol. 19, No. 3, pp. 986-994, 2015.
  [16]. Pratik Chavada, “Region of Interest Based Image Compression”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 2, Issue.1, pp.1-6, 2014.
  [17]. Bhavna Pancholi, “Tutorial review on existing image compression techniques”, International Journal Of Engineering and Computer Science, Vol.3, Issue.8, pp.7882-7889, 2014.
  [18]. Sarvarinder Singh, “ Review: ROI Based Medical Image Compression using DCT and HAAR Wavelet”, International Journal of Advanced Research in Computer and Communication Engineering, Vol.4, Issue.8, pp.223-243, 2015.
  

  Citation
  SD. Kasute, M. Kolhekar, "ROI Based Medical Image Compression," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.6-11, 2017

• Open Access   Article

  Railway Management System using IR sensors and Internet of Things Technology

  BS. Dhande, US. Pacharaney

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.1 , pp.12-15, Apr-2017

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  In Indian railways, accidents are still major concern in terms of safety of people which are caused due to unmanned rail road crossing and unidentified cracks in railway tracks. By looking at such conditions, we need to implement new technology in order to reduce accidents map. The main purpose of this paper is to provide safety at unmanned railway crossing and detection of faulty tracks. Unmanned level crossing is IR sensors base system and crack detection is a dynamics approach which combines the use of GPS (global positioning system) module to collect geographical coordinate of faulty tracks and GSM (global system for mobile communication) modem to send geographical coordinate of location. Here, we have introduced IOT (Internet of Things) which controlled the crack detection system dynamically.

  Key-Words / Index Term
  unmanned gate crossing, GSM modem, GPS module , IR transmitter and Receiver, Internet of Things technology

  References
  [1]. AK. Dewangan, M Gupta, P. Patel , “Automation of railway gate control Using Frequency Modulation Technique”, International Journal of Electrical Electronics Engineering, vol.2, Issue.9, pp.288-298, 2012.
  [2]. TL. Beach, PM. Kinter, “Devlopment and use of GPS Ionospheric Scintillation Monitor”, IEEE Transaction of Geoscience and Remote sensing, vol.39, Issue.5, pp.9180928, 2001.
  [3]. Arun P, Sabarinath G , Madhukumar S, “Implementation of Zig-bee based train Anti-Coliision and Level crossing protection system for Indian Railway”, International Journal of latest trends in Engineering and Technology, vol,2, issue.1, pp.1-7, 2013.
  [4]. ACYM. Kottalil, Abhijith S, Ajmal MM, Abhilash LJ, Ajith Bab , “Automatic Railway Gate Control System”, International Journal of Advanced Research in Electrical and Instrumentation Engineering, Vol.3, Issue.2, pp.23-31, 2014.
  [5]. Takashi Kunifuji, Jun Nishiyam, Hiroyuki Sugagara, Tetsuya Okada ,Yamato Fukuta , Masayuki Mastsumoto, “A Railway Signal Control System by Optical LAN and Networks”, Journal of Networks, Vol. 3, No.7, pp. 8-15,2008.
  [6]. Burra.Raju ,B.Sreenivas , “Alarm system of Railway Gate Crossing based on GPS and GSM”, International Journal of scientific Engineering and Research, vol.1, issue.1, pp.107-109, 2013.
  [7]. S. Biswas, RH. Bhuiyan, S.Hoque, R. Hasan, TN. khan, “Pressure sensed Fast Response Anti-Collision system for Automated Railway Gate control”, American Journal of Engineering Research, Vol.2, Issue.11, pp.163-173, 2013.
  [8]. Selvamraju Somalraju ,Vigneshwar mrunali, Gourav saha, D. Vaidehi, “Robust Railwa Crack Detection Scheme (RRCDS)Using LED-LDR Assembly”, IEEE International Conference.on Networking sensing and control, Vol.6, Issue.3, pp.453-460, 2012.
  [9]. G. Sivaiah, PK. Rao, "Providing Efficient Driving Directions Using GPS and Driver`s Ability", International Journal of Computer Sciences and Engineering, Vol.2, Issue.9, pp.18-21, 2014.
  [10]. Qiao Jian-hua, Li Lin-Sheng, Zhang Jing -gang , “Design of Rail surface Crack Detecting system Based on Linear CCD Sensor,” IEEE Conf. on Networking Sensing and Control, Vol.14, No.4, pp.961-970, 2008.
  [11]. K. Marsus, PM Ilius, M. Hossen, PM Rakibul, “ Programmable Logic Controller Based Automatic Railway gate control and Remote Monitoring System”, Canadian Journal on Electrical and Electronics Engineering, Vol.4, Issue.2, pp.1-8, 2013.
  [12]. K. Vijayakumar,S.R. Wylie, J.D. Cullen, C.C. Wright, AI. Shamma, “Non-invasive rail track track detection system using Microwave sensor”, Journal of Applied Physics, Vol.9, Issue.11, pp.1743-1749, 2009.
  [13]. H. Tsunashima, T. Kojima, Y. Mastumoto, T. Mizuma “Condition Monitoring of Railway Track and Driver Using In-service Vehicle”, IET International conference on Railway condition Monitoring, Derby (UK), pp.1-19, 2008.
  [14]. RJ. Greene, JR. Yates, EA. Patterson , “Crack Detection in rail using infrared methods”, Optical Engineering, Vol.46, Issue.5, 510-513, 2007.
  

  Citation
  BS. Dhande, US. Pacharaney, "Railway Management System using IR sensors and Internet of Things Technology," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.12-15, 2017

• Open Access   Article

  Real Time Road Inspection System with Distance Intimation Technique

  S. Kshirsagar, M. Jadhav, C. Bhagwat

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.1 , pp.16-19, Apr-2017

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  Abstract
  The vibration based road condition detection device, which consists of an Arduino based sensing module, is designed. First, the Arduino based sensing module will be designed to evaluate the road conditions in real-time and send the evaluation result, through the GPS using wireless medium. While the Server receives the data from sensing module, the data will mark the position with abnormal road condition on Google Maps utilizing GPS. As a result, the driver can change their route for commute and Government can use this potholes locational data for future repairing and development.

  Key-Words / Index Term
  Accelerometer (MEMS) Sensor, Bumps, GPS, Potholes, Arduino Based System

  References
  [1]. K. Chen, M. Lu, X. Fan, M. Wei and J. Wu, "Road condition monitoring using on-board Three-axis Accelerometer and GPS Sensor", 2011 6th International ICST Conference on Communications and Networking, China, pp. 1032-1037, 2011.
  [2]. V. Maniraj, S. Malarvizhi, "A Real Time fraud Rank Identification using Semantic Relation Analysis on Mobile Web Application", International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.372-378, 2016.
  [3]. R. Bhoraskar, N. Vankadhara, B. Raman, P. Kulkarni, "Wolverine: Traffic and road condition estimation using smartphone sensors", 2012 Fourth International Conference on Communication Systems and Networks, Bangalore, pp. 1-6, 2012.
  [4]. Jigar Kothari, Trupti Shah, Bhavin Nagaria, Apurv Choubey, SaiDeepthi Pabba, "Automated Real Time In-Store Retail Marketing Using Beacon", International Journal of Computer Sciences and Engineering, Vol.4, Issue.2, pp.110-113, 2016.
  [5]. P. Mohan, VN. Padmanabhan, R. Ramjee R, “Nericell: rich monitoring of road and traffic conditions using mobile smartphones”, 6th ACM conference on Embedded network sensor systems, NY, pp. 323-336, 2008.
  [6]. P. Singh, N. Juneja, S. Kapoor, “sing Mobile Phone Sensors to Detect Driving Behavior”, Proceedings of the 3rd ACM Symposium on Computing for Development , Bangalore, pp.34-39, 2013
  [7]. L. Sun, “Optimum design of road-friendly vehicle suspension systems subjected to rough pavement surfaces”, Applied Mathmatical Modellinh, Vol. 26, Issue.5, pp. 635-652, 2002.
  [8]. L. Sun, T. Kennedy, “Spectral analysis and parametic study of stochastic pavement loads”, Journal of Engineering Mechanics, Vol.128, Issue.3, pp. 318-327, 2002.
  [9]. L. Sun, “Simulation of Pavement Roughness and IRI Based on Power Spectral Density”, Mathematics and Computers in Simulation, Vol.61, Issue.2, pp.77-88, 2003.
  

  Citation
  S. Kshirsagar, M. Jadhav, C. Bhagwat, "Real Time Road Inspection System with Distance Intimation Technique," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.16-19, 2017

• Open Access   Article

  Diagnosis of Brain Hemorrhage Using Artificial Neural Network

  V. Davis, S. Devane

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.1 , pp.20-23, Apr-2017

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  Abstract
  Brain hemorrhage is a type of stroke which is caused due to bursting of artery in the brain and thus causing bleeding in the surrounding tissues. The major technique which is used for diagnosis of brain hemorrhage is through Computed Tomography (CT) scan. This dissertation investigates the possibility of diagnosing brain hemorrhage using an image segmentation of CT scan images using watershed algorithm and using the inputs extracted from the brain CT image to an artificial neural network for classification. The output generated as the type of brain hemorrhages, can be used to verify diagnosis also as a learning tool for trainee radiologists to minimize errors.

  Key-Words / Index Term
  Brain hemorrhage, Intracerebral Hemorrhage, Subdural Hemorrhage, Extradural Hemorrhage, Subarachnoid Hemorrhage, Computed Tomography, X-rays

  References
  [1] R. Ganesan, S. Radhakrishnan, “Segmentation of Computed Tomography Brain Images Using Genetic Algorithm”, International Journal of Soft Computing ,Vol.4, Issue.4, pp.157-161, 2009.
  [2] D. Moitra, R. Mandal , "Review of Brain Tumor Detection using Pattern Recognition Techniques", International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.121-123, 2017.
  [3] K. Sarkar, R.K. Mandal, A. Mandal, S. Sarkar, "Least Centre Distance Based MAXNET Architecture to Obtain Threshold for Brain Tumor Edema Segmentation From FLAIR MRI", International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.112-120, 2017.
  [4] MM. Kyaw, “Computer Aided Detection system For Hemorrhage Contained Region”, International Journal of Computational Science and Information Technology (IJCSITY), vol.1, Issue.1, pp.1-16, 2013.
  [5] AH. Ali, SI. Abdulsalam, IS. Nema, “Detection And Segmentation of Hemorrhage stroke Using Textural Analysis on Brain CT images”, International Journal of Soft Computing and Engineering, Vol.5, Issue.1, pp.11-14, 2015.
  [6] V. Vani, M.K. Geetha , "Automatic Tumor Classification of Brain MRI Images", International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.144-151, 2016.
  [7] Z. Ying,R. Naidu, C.R. Crowford, “Dual Energy Computed Tomography For Exclusive Detection”, Journal of X-ray Science and Technology, Vol.14, Issue.1, pp235-256, 2006
  [8] M. Chawla, “A Method for Automatic Detection and Classification of Stroke from Brain CT Images”, 31stAnnual International Conference of the IEEE EMBS, Minneapolis, pp. 3581-3584, 2009..
  
  
  [9] CA. Devi, S.P. Rajagopala, “Brain Stroke Classification Based on Multilayer Perceptron Using Watershed Segment and Gabor Filter”, Journal of Theoretical and Applied Information Technology, Vol.56, Issue.3, pp. 410-416, 2013.
  [10] Anju Bala, “An Improved Watershed Image Segmentation Technique using MATLAB”, International Journal of Scientific and Enginnering Research, Vol.3, Issue.6, 2012.
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  [12] DK. Kharat, Pradyumna, M. B. Nagori, “Brain Tumor Classification Using Neural Network Based Methods”, International Journal of Computer Science and Informatics,Vol.1, Issue.4, pp.2231-5292 2012,
  [13] Fatima, M. Sridevi, S. Naaz, K. Anjum, “Diagnosis and Classification of Brain Hemorrhage Using CAD System”, Indian Journal of Scientific Research, Vol.12, Issue.1, pp.121-125,2015.
  

  Citation
  V. Davis, S. Devane, "Diagnosis of Brain Hemorrhage Using Artificial Neural Network," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.20-23, 2017

• Open Access   Article

  A Rainfall Prediction Model Using Articial Neural Network

  L. Shaikh, K. Sawlani

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.1 , pp.24-28, Apr-2017

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  Abstract
  Back propagation algorithm is most commonly used in neural network projects because it works faster than earlier approaches to learning and for its accuracy. Back propagation is a workhorse of learning in neural network. In back-propagation algorithm, there are two facets in its learning cycle, one to generate input pattern and another one to adjust the output by changing the weights of the network. There are many applications of feed forward neural network such as weather and financial predictions, face and signature detections etc. Thispaper describes the training, testing of data sets and finding the number of hidden neurons using back propagation algorithm for better performance. In the research, rainfall prediction in the region of Mumbai has been analyzed using feed forward network. In formulating artificial neuralnetwork based predictive models three layered network has beenconstructed.

  Key-Words / Index Term
  feed forward Network, artificial neural network, back propagation algorithm, multilayer artificial neural network component

  References
  [1]. M. Tektaş, “Weather forecasting using ANFIS and ARIMA models”, Environmental Research, Engineering and Management, Vol.51, Issue.1, pp.5-10, 2010.
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  [3]. SA. Kalogiru, C. Neocleous, CN. Constantinos, SC. Michaelides, NC. Schizas, “A time series construction of precipitation records using artificial neural networks, In Proceedings of EUFIT, Germany, pp. 2409-2413. 1997.
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  [14]. E. Vamsidhar, “Prediction of rainfall Using BackpropagationNeural Network Model”, International Journal on ComputerScience and Engineering Vol. 02, No. 04, pp.1119-1121, 2010.
  

  Citation
  L. Shaikh, K. Sawlani, "A Rainfall Prediction Model Using Articial Neural Network," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.24-28, 2017

• Open Access   Article

  An Efficient PAPR Reduction Technique for OFDM

  R. Deshpande, DJ. Pete

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.1 , pp.29-33, Apr-2017

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  Abstract
  This Orthogonal Frequency Division Multiplexing (OFDM) is an efficient multiplexing & a bandwidth efficient modulation scheme in wireless communications.However, OFDM faces the high Peak-to Average Power Ratio (PAPR) problem that is a major drawback of this multicarrier system which leads to power inefficiency in the RF section of the transmitter.Thus, the OFDM signals with high PAPR could seriously be distorted by the non-linearity of the HPA, resulting in degradation of both spectral efficiency (SE) and energy efficiency (EE) performances. Our paper will review a few techniques to reduce the high PAPR to combat multipath fading and signal distortion which will facilitate better data transmission.

  Key-Words / Index Term
  PAPR, RF, OFDM, SE, EE

  References
  [1] S. Kunal, N. Mohan, G. Kavita, K. Monali, D. Pooja, “Improving throughput in Wireless LAN using Load Balancing Approach”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.4, pp.38-43, 2014.
  [2] F. Schaich and T. Wild, “Waveform contenders for 5G — OFDM vs. FBMC vs. UFMC”, 2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP), Athens, pp. 457-460, 2014.
  [3] Mamta Bisht and Alok Joshi, “Various Techniques to Reduce PAPR in OFDM Systems: A Survey”, International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol.8., No.11, pp.105-208,2015.
  [4] Parneet Kaur, Ravinder Singh, “Complementary Cumulative Distribution Function for Performance Analysis of OFDM Signals”, IOSR Journal of Electronics and Communication Engineering (IOSRJECE), Vol.2. Issue.5, pp.5-7, 2012.
  [5] Pawan Sharma, Seema Verma, “PAPR Reduction of OFDM Signals using Selective Mapping with Turbo Codes”, Intnl.Jrnl. of Wireless and Mobile Networks, vol.3, no.4, pp.12-19, 2011.
  [6] Chinkalkumar B. Patel, “A New SLM Scheme with Clipping for PAPR Reduction in OFDM Systems”, Intnl. Jrnl. for Scientific Research and Development, Vol.3, Issue.2, pp.154-161, 2015.
  [7] Ibrahim Abdullah, “Comparative Study of PAPR Reduction Techniques in OFDM”, ARPN Jrnl. Of Systems and Software, vol.1, no.8, pp.11-16, 2011.
  [8] Kavita Mhatre, UP Khot, “Efficient Selective Mapping PAPR Reduction Technique”, Intnl. Conference on Advanced Computing Technology and Applications, India, pp.620-627, 2015
  [9] Kishore Kumar, RR Nagaralli, “Introduction to SLM and Clipping Techniques and its Comparative Analysis to Reduce PAPR in OFDM Systems”, Intnl. Jrnl. Of Electrical and Computer Engineering, vol.1, issue 4, pp.321-327, 2015.
  [10] Maan Singh, Vijay Kumar, “Signal Scrambling Techniques for PAPR Reduction in OFDM Systems”, International Journal of Engineering and Computer Science, vol.2, issue 1, pp.311-317, 2013.
  [11] N.R. Raajan, S. Prabha, D. Meenakshi, “Improved Performance in OFDM Systemsby PAPR Reduction Techniques”, International Conference on Computer Communication and Informatics, India, pp.1-4, 2013.
  [12] Suverna Sengar, PP. Bhattacharya, “Performance Improvement in OFDM Systems by PAPR Reduction”, Intnl. Jrnl. Of Signal and Image Processing, vol.3, no.2, pp.1-9, 2012.
  [13] Lingyin Wang, Ju Liu, Wenbo Wan and Jingkai Liu, “Scrambling scheme based on information hiding for PAPR reduction of OFDM signals with PSK inputs”, 2011 IEEE 13th International Conference on Communication Technology, Jinan, pp.462-465, 2011.
  [14] Y. C. Wang and Z. Q. Luo, “Optimized Iterative Clipping and Filtering for PAPR Reduction of OFDM Signals,” in IEEE Transactions on Communications, vol. 59, no. 1, pp. 33-37, January 2011
  [15] Dov Wulich, “Definition of Efficient PAPR in OFDM”, IEEE Signal Communication Letters, Vol.9, No.9, pp.8320834, 2005.
  [16] S. Singh, A.S. Buttar, “Carrier Frequency Offset Estimation Techniques in OFDM System: A Survey”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.74-77, 2014.
  [17] NV. Jadhav, SC. Panchal, MR. Rotti, “Client Server Network Management System for WLAN (Wi-Fi) with Remote Monitoring”, International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.1, pp.22-25, 2013.
  

  Citation
  R. Deshpande, DJ. Pete, "An Efficient PAPR Reduction Technique for OFDM," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.29-33, 2017

• Open Access   Article

  Design and Development of Reconfigurable Multiprocessor Architecture for Embedded Systems

  SM. Kalyankar, SD. Sawarkar

  Review Paper | Journal (IJSRNSC)

  Vol.5 , Issue.1 , pp.34-37, Apr-2017

  Abstract

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  Abstract
  In Today’s world, Embedded systems are the brains of almost all digital and industrial control systems.Modern digital systems demand increasing electronic resources, so the multiprocessor platforms are a suitable solution for them which provides better results in terms of area, speed, and power consumption compared to traditional uniprocessor digital systems. Reconfigurable multiprocessor systems are a particular type of embedded system, implemented using reconfigurable hardware. In this paper, Design methods and challenges are discussed. Advances in FPGA technology are leading to more powerful systems in terms of processing and flexibility. Flexibility is one of the strong points of this kind of system, and multiprocessor systems can even be reconfigured at run time, allowing hardware to be adjusted to the demands of the application. Multiprocessor Systems-on-Chip (MPSoC) represent an important trend in digital embedded electronic systems. Although hardware support for parallel computationis increasingly available in embedded processing platforms, there is a distinct lack of effective software support. One of the most important issues with regards to such systems is communication between processors. Now communication in different controllers can be done mainly by two ways i.e. by using I2C and SPI protocol. But there are some limitations of these two protocols which are discussed in this paper and how it can be overcome by using our proposed protocol. Here, in this project, a new method for communication is proposed for an embedded system having multiple peripherals on the board. The adapted arrangement is parallel and hence is more faster way to communicate. This Paper will provide in-depth description of the Reconfigurable Distributed Computing Arrangement of On-board Multiprocessor Communication for Embedded Systems and will investigate its merits & demerits.

  Key-Words / Index Term
  Embedded Systems, I2C,SPI, FPGA,MPSoC, Multiprocessor Communication

  References
  [1]. Myke Predko, “Programming and Customizing the 8051 Microcontroller”, Tata McGraw-Hill, Inida, pp.157-167, 1999.
  [2]. Shibu K.V., “Introduction To Embedded Systems” Published by Tata McGraw-Hill Education, Inida, pp.1-478, 2009,
  [3]. Dogan Ibrahim, “Microcontroller Projects in C for the 8051”, Newnes, pp.29-161, 2008.
  [4]. KJ. Ayala, “The 8051 Microcontroller Architecture, Programming And Applications”, WEST PUBLISHING COMPANY, USA, pp.131-197, 1993.
  [5]. Michael J. Pont, Embedded C, Edition 2002, Addison Wesley, Page: 57-87,217.
  [6]. N. Lekic, Z. Mijanovic, D. Gobovic, R. Dragovic-Ivanovic, “The simple multiprocessor communication system”, 9th International Conference on Electronics Circuits and Systems, Dubrovnik, pp.1039-1042, 2002.
  [7]. S. Iyengar, N. Apte, A. A. Roy, S. Sanyal, N. M. Singhi, WuGeng Feng, “A multiprocessor communication architecture for high speed networks”, 1993 IEEE Region 10 Conference on Computer Communication Control and Power Engineering, Beijing (China), pp.262-265, 1993.
  [8]. Karan Patel, Suraj Panigrahiya, Amit Pawar, Akash Survase, “Opencv Based Virtual Touch Screen For Robotic Navigation”, International Journal of Students Research in Technology & Management, International Journal of Students Research in Technology & Management, Vol.2, Issue.6, pp.196-198, 2015.
  

  Citation
  SM. Kalyankar, SD. Sawarkar, "Design and Development of Reconfigurable Multiprocessor Architecture for Embedded Systems," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.34-37, 2017

• Open Access   Article

  Image Merging in Transform Domain

  S. Jadav, P. Rawool, V. Shah

  Review Paper | Journal (IJSRNSC)

  Vol.5 , Issue.1 , pp.38-39, Apr-2017

  Abstract

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  Abstract
  This paper presents the three different image merging techniques and there comparative analysis. Idea of our project is to merge two images in transform domain using MATLAB. The various transform domains which are used for merging are Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). Our main aim would be merging two images using the above three domains. These two images which are to be merged are in actual blurred images. They are blurred in such a way that in first image some part on one side is blurred while in second image the other side is blurred. Image merging is required in several fields such as remote sensing using satellite imagery, biomedical, surveillance, military applications etc.

  Key-Words / Index Term
  Image Merging, Fast Fourier Transform, Discrete Cosine Transform, Discrete Wavelet Transform

  References
  [1]. SJ. Chapman, “MATLAB Programming for Engineers”, Cengage Learning, India, pp.1-762, 2015.
  [2]. P. Venkataraman, “Applied Optimization with MATLAB Programming”, John Wiley & Sons, UK, ppl1-526, 2009.
  [3]. N. Meenaksi, P. Rodrigues, “Tsunami Detection and forewarning system using Wireless Sensor Network - a Survey”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.76-79, 2014.
  [4]. A. Maurya, R. Tiwari, “Theoretic Study of Image Fusion Techniques � A Survey”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.6, pp.43-49, 2014.
  [5]. Prabhjot Singh, Anjana Sharma, “Face Recognition Using Principal Component Analysis in MATLAB”, International Journal of Scientific Research in Computer Science and Engineering, Vol.3, Issue.1, pp.1-5, 2015.
  [6]. Pritam Shaha, Niranjan Kshatriya, Rahul Borse, “Static Indoor Object Detection Using MATLAB For Visually Impaired”, International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.33-37, 2016.
  [7]. A. Gupta, E. Sharma, N. Sachan, N. Tiwari, “Door Lock System through Face Recognition Using MATLAB”, International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.3, pp.51-55, 2013.
  [8]. S. Kushwaha, RK Singh, “Study and Analysis of Various Image Enhancement Method using MATLAB”, International Journal of Computer Sciences and Engineering, Vol.3, Issue.1, pp.15-20, 2015.
  

  Citation
  S. Jadav, P. Rawool, V. Shah, "Image Merging in Transform Domain," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.38-39, 2017