Implementation of Pulse Compression for Space Applications
Pulse Compression is one of the key steps in the signal processing of a Radar system. Radar system uses Pulse compression techniques to provide the benefits of larger range detection and high range resolution. This is gained by modulating the transmitted signal and after that matching the received echo with the transmitted signal. Matched filter is used as the pulse compression filter which provides high SNR at the output. Matched Filter is a time reversed and conjugated version of the received radar signal. There are several methods of pulse compression that have been used in the past, out of which most popular technique is Linear Frequency Modulation (LFM). This paper deals with the design to develop and simulate pulse compression and matched filter algorithm in MATLAB to study the LFM pulse compression technique. Matched filter is used as the pulse compression filter which provides high SNR at the output. Matched Filter is mathematically equivalent to convolving the received signal with a conjugated time-reversed version of the reference signal. The main application of pulse compression Radars includes tracking of launch vehicles, unwanted particles in space, Missile guidance etc. Here, in this paper we are discussing the pulse compression application in tracking the launch vehicle so as to check whether it had followed the predetermined path or not.
Published by: Arya V. J, Subha .V
Author: Arya V. J
Paper ID: V3I3-1372
Paper Status: published
Published: May 25, 2017
Preventing the Anonymous Authentication Using Cashma Technique
Security in web based session management is a serious concern, due to the recent increase in the frequency and complexity of cyber attacks. Traditionally most of the system are based on the pairs of username and password which verify the identification of the user only at the login phase. Once the user can be identified, no checks are performed during the working sessions, which are terminated by an explicit logouts or expire after an idle activity period of the user. In this approach a single shot of verification is less efficient and the user identity is permanent during the entire session. To overcome this aspect, a secure protocol authentication is used for continuous user verification. This protocol makes adaptive time outs and periodically request the user to input his authentication attributes over and over. For this adaptive method, CASHAMA authentication system is used which provides different verification methods such as Keystroke timing, Mathematical event and CASHMA certificate. The use of this CASHMA system will provide secure web service and prevent the loss of data.
Published by: Santhosh, Prof. Dr. V. JayaRaj
Author: Santhosh
Paper ID: V3I3-1379
Paper Status: published
Published: May 25, 2017
Renal Cell Carcinoma Nuclear Grading Using 2d Textural Features for Kidney Images
Cancer identification system is proposed based on the features present in the kidney images. Different algorithms such as CLACHE (Contrast limited adaptive histogram equalization), GLCM (gray level Co-occurrence matrices) and SVM (support vector machine) algorithm are used for the identification of cancer. CLACHE algorithm is used for the enhancement of the image. GLCM algorithm is used to improve the overall accuracy of the system and to extract the textural features. SVM algorithm is used to classify the different grading levels to identify the cancer present in the image. Images that are acquired for the identification of cancer are noisy. Noise is removed by the ROI extraction. Then the images are enhanced using CLACHE algorithm. Once the images are enhanced, features are extracted using GLCM. 21 textural features are extracted. Out of the 21 features extracted two best features are selected. The two best features are compared with the trained features for the increase in the accuracy of the system. After that based on the features different grading levels are obtained for the identification of the cancer. Grade 1 indicates the presence of cancer in starting stage, grade 2 indicates the presence of cancer in the moderate stage, grade 3 indicates the presence of cancer in the mild stage, grade 4 indicates the presence of cancer in the severe stage. In this study, 2D textural features are extracted and using these extracted features cancer identification is done which improves the overall accuracy of the system.
Published by: Jayashree G. R, Dr. K. M Ravi Kumar, Ravi Kiran .R
Author: Jayashree G. R
Paper ID: V3I3-1377
Paper Status: published
Published: May 25, 2017
Tumor and Edema Segmentation Using Efficient MFCM and MRG Algorithm
Momentarily, categorizing of brain tumor and segmentation is truly an exciting task in MRI. Numerous researches work in generating divergent plus interesting techniques and algorithms for this specified work of medical image processing. On behalf of enhancing a precise brain tumor extraction, we provide an effective methodology for both classification and segmentation i.e., separation of brain MRI images as well as labeling of brain MRI images in terms of edema, tumor, white matter (WM),gray matter (GM) plus cerebrospinal fluid (CSF). At this instant and in our recommended system of brain tumor detection encompasses six segments, i.e. pre-processing, filtering, Image registration, Feature extraction, Classification, Segmentation. At this moment, in case of preprocessing, the input MRI image is firstly fetched from the MRI database and as well subjected to skull stripping for rejecting the undesirable area from the image. In addition, by the utilizing Gaussian filter, the skull stripped image has been smoothened. Subsequently by utilizing Automatic image registration the filtered images are recorded into one coordinate system wherever the movement of the head is a situation often encountered during the imaging process. Shape, intensity and texture are the features that will be extricated from the registered images.On the basis of extricated features, the Brain MRI images are characterized into normal or abnormal images. Finally by utilizing the modified FCM segmentation algorithm tumor portion is extracted and edema is segmented applying modified region enhancing from the abnormal images. Therefore in case of normal image, the Gray matter, the white matter and the cerebrospinal fluid can be segmented. The outcomes are analyzed for illustrating the representation of the suggested classification plus segmentation methodology with prevailing techniques.
Published by: Rehna Kalam, M. Abdul Rahman
Author: Rehna Kalam
Paper ID: V3I3-1357
Paper Status: published
Published: May 25, 2017
A Novel Technique to Remove Duplicacy of Files and Encrypt the Data Files Symmetrically In Cloud Environment
With the help of cloud computing users are allowed to store, retrieve and share their data from anywhere. Cloud computing provides sharing of hardware, software and infrastructural storage to different users at a time. Encryption of cloud is a need of new technology because clouds have data of different clients so encryption on cloud is essential for data security but cloud computation is also important so to reduce duplicacy is one more parameter , which is reduce by digest in this paper and encryption with the help of AES and blowfish.
Published by: Sandeep Kaur
Author: Sandeep Kaur
Paper ID: V3I3-1353
Paper Status: published
Published: May 25, 2017
Replace of Asphalt with Waste Polythene in Bitumen Road
In India consumption of Plastic is 15 million tons up to 2015 and is set to be the third largest consumer of plastics in the world. India is a top 20 number country that dump maximum plastic in the ocean. As per a survey conducted by Central Pollution Control Board (CPCB) in 60 cities of the country the quantum of plastic waste generation is estimated to be 15,342.6 tons per day. Plastic is a non-biodegradable material and researchers found that the material can remain on earth for 4500 years without degradation
Published by: Mr. Yakub Ansari, Prof. F. I Chavan, Prof. M. Husain, Prof. Vajed Shaikh
Author: Mr. Yakub Ansari
Paper ID: V3I3-1352
Paper Status: published
Published: May 25, 2017
