Sushma S.J.,Visvesvaraya Technological University |
2015 International Conference on Emerging Research in Electronics, Computer Science and Technology, ICERECT 2015 | Year: 2015
Image preprocessing and image enhancement plays a critical role in medical image processing. Considering the case study of breast cancer detection, it was found that there are various schemes of optimization techniques which is either training based or leads to recursive iterations leading to computationally complex process. Hence, the proposed system implements a unique and novel optimization technique called as Image Enhancement using Bio-inspired Algorithms. Different from existing bio-inspired algorithm, the proposed system doesn't use any training sequences, or depends on single fitness function or performs recursive operation for exploring elite population. The algorithm performs automatic segmentation process followed by three level of enhancement operation for achieving local to global best optimization without using any forms of recursive functions. The outcomes are visually defined and well resolution to prove success factor. © 2015 IEEE.
Nagabhushan S.V.,BMSIT |
Subramanya K.N.,RVCE |
Proceedings of the 2013 3rd IEEE International Advance Computing Conference, IACC 2013 | Year: 2013
Effective procurement is one of the key challenges faced in the Supply Chain Management process. With the increase in awareness among customers, manufacturers emphasize more on quality of the product. In order to produce a quality product at an economical rate, the other attributes of a product often play more important role in deciding the procurement of raw materials than the price alone. Multi-attribute Reverse Auction mechanism is proved to be very effective in addressing this challenge efficiently. But the inherit problem of an optimal supplier selection within a cobweb of constraints is often very difficult to address. Any solution proposed to address this issue needs to be technologically feasible to provide a faster, efficient and effective result. One such solution which promises higher market efficiency through an effective information exchange of buyer's preferences and supplier's offerings is Analytic Hierarchy Process (AHP). This paper presents a framework for purchasing a single item online from multiple suppliers using AHP method. A case study is presented along with numerical analysis, which illustrates the AHP method of supplier selection. © 2013 IEEE.
Anala M.R.,RVCE |
Shetty J.,RVCE |
Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 | Year: 2013
Server virtualization is an emerging technology that provides efficient resource utilization and cost-saving benefits. It consolidates many physical servers into a single physical server saving the hardware resources, physical space, power-consumption, air conditioning capacity and man power to manage the servers. Thus virtualization assists 'Green Technology'. Live migration is an essential feature of virtualization that allows transition of a running virtual machine from one system to another without halting the virtual machine. Live migration extends the list of benefits server virtualization provides. Almost all virtualization softwares now include support for live migration of virtual machine. Live migration is in its infant stage where security of live migration is yet to be analyzed. The usages of live migration and security exploits over it have both increased over time. The security concern of live migration is a major factor for its adoption by the IT industry. In this paper we discuss the attack model on the virtualization system and design and implement a security framework for secure live migration of virtual machines. The framework is an integrated security solution that addresses role based access policy, network intrusion, firewall protection and encryption for secure live migration process. © 2013 IEEE.
Holla S.,RVCE |
2015 IEEE International Conference on Computer Graphics, Vision and Information Security, CGVIS 2015 | Year: 2015
The underwater study and communication have gained attention due to the military, commercial and biological purpose. The video monitoring of the underwater activity is carried out by video processing node (VPN) which form a sensor network. The VPN must be power efficient and less complex. The video coding standard such as MPEG and H.26X have a computationally more complex encoder for their working and are not suitable for many to one application like VPN. For applications such as underwater VPN, low power surveillance networks and wireless video cameras, the encoder needs to be simpler. Distributed Video Coding (DVC) is a technique which can be used for these applications. The underwater acoustic medium is affected by parameters such as absorption, attenuation and ambient noise parameters. These can be mitigated via modelling and using appropriate modulation technique. The primary objective of the current research was to design and develop DVC technique based on Slepian-Wolf and Wyner-Ziv theorems, which is resilience to transmission errors and has a high compression efficiency. The main concern of the design was to shift the motion estimation part from encoder end to the decoder through which low complexity is obtained at encoder. The channel characterization including study of absorption and ambient noise parameters are carried out with the help of empirical formulae. The simulation results show that the performance of the DVC Codec developed is close to the performance of conventional codec which provides good reconstruction with a high PSNR with up-To 70% level of compression. The architecture conforms to be stable for variation in size of GOP. The ARPS provides better estimation by taking less computational steps for calculating global minimum. The complete system developed assures 10% increase in bit error rate (BER) performance. However, the developed system needs to be validated for the real-Time scenario. © 2015 IEEE.
Devaraj D.,R.V.C.E. |
Proceedings of 2014 International Conference on Contemporary Computing and Informatics, IC3I 2014 | Year: 2015
Diabetic retinopathy (DR) is the retinal disease caused by diabetes that involves damage to the small blood vessels in the posterior of the eye. Early stage of DR may not cause symptoms. But the progression of the disease leads to the proliferative stage. This causes leakage of protein and blood in the retina. Blood vessel segmentation is a helpful tool in the treatment of diabetic retinopathy. Many studies have been carried out in the last decade in order to derive an accurate blood vessel detection and segmentation in retinal images because vascular anomalies are one of the strongest signs of DR. An user friendly graphical user interface (GUI) which is MATLAB based that segments the blood vessels by means of adaptive median thresholding is proposed in this paper. From the segmented image, various features of blood vessels like area, mean, standard deviation, energy, entropy and histogram are calculated, in order to distinguish the image as normal or abnormal. With respect to the ground truth, performance measures like accuracy, specificity and sensitivity are calculated. The GUI is implemented using MATLAB and the feature parameters are calculated. The average accuracy, specificity and sensitivity were found to be 0.95, 0.99 and 0.77 respectively for drive images using Adaptive median thresholding. © 2014 IEEE.
Govinda Raju M.,RVCE |
Satishkumar A.,RVCE |
Procedia Computer Science | Year: 2016
Orthogonal Frequency Division Multiplexing (OFDM) is a highly recommended multiplexing/modulation scheme for high data rate communications due to its high spectrum efficiency and robustness against Inter Symbol Interference (ISI). The OFDM is based on dividing the available spectrum into narrow band orthogonal subcarriers and modulating data on each subcarrier. Due to long symbol period, OFDM system is more sensitive to phase noise of the oscillator compared to single carrier systems. The Phase noise of oscillators used in the transmitters & receivers results in two effects, Common Phase Error (CPE) & Inter Carrier Interference (ICI). These effects results in increasing SNR requirement at the receiver to achieve certain BER. The design & simulation of OFDM based DVB-t system with wavelet multiplexing & demultiplexing and analysis of phase noise effects on BER is presented in this paper. The performance of simulated DVB-t system is analysed by considering SNR requirement to achieve certain BER in the presence of oscillator instabilities on AWGN & mobile radio channels. The modelled Wiener phase noise is generated for different 3dB bandwidths of noise spectrum. The simulation results shows that, the SNR required to achieve a bit rate of 10-2 in wavelet multiplexing is around 6dB lower as compared to FFT counterpart. The result also reveal that PAPR is also less, however wavelet multiplexing computational intensive. © 2016 The Authors. Published by Elsevier B.V.
Shilpa D.R.,RVCE |
Procedia Computer Science | Year: 2016
Design automation is one of the key requirements of today's growing ASIC/SOC design process. The era of high speed and high density designs has led the design engineers various challenges. As the technology is scaling, one of the major concerns of VLSI design is signal integrity. Crosstalk is the major cause of signal integrity that occurs due to coupling of charge between the conducting interconnects.Most of the CAD tools available in the market addresses this issue at the post layout level. But tackling crosstalk at the stage when the design is ready for fabrication may not be always feasible in terms of area and power overheads. This paper proposes a novel CAD tool which performs an optimization to crosstalk effect at architectural level using High Level Synthesis (HLS) procedures. The proposed work performs crosstalk aware simultaneous scheduling, binding and allocation of resources in the given data flow graph using hybrid genetic and simulated annealing algorithm (GASA). The data flow graph of an intended design is fed as an input to the tool and it generates corresponding crosstalk optimized verilog code as an output. The obtained design is synthesizable in any of the commercial tool. The work is tested on 3X3 matrix multiplier and experimental result shows that there is 65.07% improvement in crosstalk delay and hence the Signal Integrity. Hence this work suggests a technique for architectural level crosstalk optimization. © 2016 The Authors. Published by Elsevier B.V.
Mini R.,Amrita University |
Sreenivasan R.,Amrita University |
2014 International Conference on Electronics, Communication and Computational Engineering, ICECCE 2014 | Year: 2014
Direct Torque controlled (DTC) induction motor drive gives direct control of stator flux and electromagnetic torque. Conventional speed sensors are replaced in sensor less DTC to improve the reliability, noise immunity and to reduce the complexity of the system. In sensor less DTC the rotor speed estimation at low speeds is degraded by the stator resistance parameter variations due to temperature, dead time effects and voltage drop in power electronics devices. The open loop speed estimation used in sensor less DTC depends on various machine parameters. The stator resistance variation at low speeds degrades the speed estimation. In this paper investigation of sensor less DTC controlled induction motor at low speed range is carried out and to improve the speed estimation at low speed closed loop Model Reference Adaptive Scheme (MRAS) is used for speed estimation. Simulation is carried out in Matlab/Simulink platform and results are compared and presented. © 2014 IEEE.
Manujakshi B.C.,Acharya Institute of Technology |
Proceedings of the 2016 IEEE International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2016 | Year: 2016
In recent years, there is a high growth in wireless sensor network (WSNs) for secure communications or sensor network applications. It has been seen that sensor applications are revised with upcoming technologies in order to meet the demands. There is a requirement of efficient design and implementation of WSNs, due to the huge SNs to allow applications which connect the physical world to the virtual world. With a wide range of applications for SNs, some of the application areas are health, military, and security will create issues in data transmissions from one sensor network to another sensor network. As sensors gathers complex data, it is quite a difficult job to understand how far it can be valuable with respect to analysis. Owing to inherent complexities e.g. size, heterogeneity, un-structuredness, etc. it may pose serious problems in futuristic sensor data analytics over cloud. This paper discusses about the techniques used in managing sensor data over cloud to understand the existing system and its effectiveness. © 2016 IEEE.
Geetha J.K.,RVCE |
2015 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015 | Year: 2015
Text Summarization is a method of reducing the original text document into a short description. This short version retains the meaning and information content of the original text document. It is a difficult task for human beings to generate the summary for very large documents manually. The linguistic and statistical features of sentence can be used to find the importance of sentences. The Latent Semantic Analysis (LSA) captures automatically the semantic relationships between the sentences as a human being thinks. In this paper Singular Value Decomposition (SVD) is used to generate the summary. SVD finds the dimensions of the sentence vectors which are principal and mutually orthogonal. These properties guaranty the relevance to original text document and non-redundancy respectively in machine generated summary. © 2015 IEEE.