Railway Bridge Track Surveying System for Accident Reduction
Abstract -As railroad bridges and tracks are very important infrastructures, which has direct effect on railway transportation, there safety is utmost priority for railway industry. This project aims at monitoring the tracks on the bridges along with structural health condition of the bridge for accidents reduction. In this paper we introduces railway tracks and bridge monitoring system using wireless sensor networks based on ARM processor. We designed the system including sensor nodes arrangement , collecting data, transmission method and emergency signal processing mechanism of the wireless sensor network.. The proposed system reduces the human intervention, which collects and transmit data . The desired purpose of the proposed system is to monitor railway infrastructure for accident reduction and its safety.
Published by: Vinod Bolle, Santhosh kumar banoth, Puja Khangar
Author: Vinod Bolle
Paper ID: V2I5-1150
Paper Status: published
Published: September 12, 2016
Hybrid Algorithm for Cluster Head Selection Based on Energy in MANET
— In the existing system is only find in cluster head using cluster based routing protocol algorithm. This algorithm is not based in energy level of cluster head selection. The cluster head can communicate with other cluster heads, member nodes and gateways. That time the cluster head energy level is low. So the cluster head can’t communicate with other nodes. That the same time the congestion will be occurs and packet can’t be transfer in the nodes. It will take more time to complete the packet transmission. This approach illustrates that the proposed method is a routing protocol. The proposed research we have used no of connection in a group or cluster. Every cluster has a cluster head and the cluster head directly interconnect with the improper place. The results of proposed method are comparison with existing Leach Protocol. Here base connection is located to equal distance of a cluster and it’s directly communicating to the cluster connection. When a cluster or group is selected after that it’s force level is not considered. This method is increasing to life instance of network. As compare LEACH and Proposed method, we have noticed proposed methodhave better force, life time, less delay, better transmission and consumed less time. LEACH Protocol is based on the cluster to make comparison of native parameters so that we design the proposed methodl cluster based. Cluster used no of group to increase the performance. This consist many advantages which are listed below. Existing Number of groups are low. We can analyses more number of groups here. Every group’s stage check in this proposed research. Proposed method routing protocol have better result as compared to LEACH protocol. As cluster-head dies, series is rebuilt to bypass the deceased node. So the initial topology is not affected. Head node receives all the aggregated data moreover transmits further to cluster-head.
Published by: Updesh Gangwar, Ravi Shankar Shukla
Author: Updesh Gangwar
Paper ID: V2I5-1148
Paper Status: published
Published: September 9, 2016
Mammogram Image Nucleus Segmentation and Classification using Convolution Neural Network Classifier
Breast Cancer is one of the dangerous diseases which lead in resulting deaths among women. This is due to the presence of cancerous cells that are produced in extra amount of proportion which can replace the neighboring non-cancerous cells or it can infect all over the body. As the breast cancer concerns women mostly at the age of 40, they are asked to attain the regular mammographic screening, since mammography is most reliable method for cancer detection at early stages. Mammogram is the most common method used for breast imaging. It helps in examine the presence of cancer at early stages and help in reducing the mortality rate by 25-30% in screened women. There occur many different types of breast cancer such as: mass, micro calcification clusters, architectural distortion and asymmetry breast tissue. This dissertation carries the masses problem and deals with its shape and texture feature for classification. Various type of techniques and methodologies are present in mammography which helps to find out the presence of cancer and also multiple ways to detect it in its early stage so that the patient affected by it could not lead to death. Mammography is the most common, safe and inexpensive methodology suggested whose standard image database could be used for training the learning machine. In this dissertation nucleus segmentation is used to find out the region of interest (ROI). The result of ROI is further used for extracting the valuable shape and textural features by using geometrical features, GLCM and GLDM for classifying the cancer through the machine learning approach i.e. CNN (Convolution neural networks). CNN remove the overlapping of features obtained after segmentation. Hence, CNN is used to evaluate the performance through defining accuracy, precision, and recall and also compare the results with existing logistic regression and neural network classification technique.
Published by: Prabhjot kaur
Author: Prabhjot kaur
Paper ID: V2I5-1147
Paper Status: published
Published: September 9, 2016
Image Encryption using Huffman Coding for Steganography, Elliptic Curve Cryptography and DWT for Compression
An abstract is a brief summary of a research article or in-depth analysis of a particular subject or discipline, and is often used to help the reader quickly ascertain the paper's purpose. Images can be encrypted in several ways, by using different techniques and different encryption methods. In this paper, I am using Huffman Coding method for image steganography, Elliptic Curve Cryptography for image encryption and Discrete Wavelet Transform for image compression. In my work I am using steganography, encryption and compression all together on the image data. After applying all these techniques on image data it results in an encryption method which is highly secure. For the implementation of the proposed work we are using Matlab software.
Published by: Lavisha Sharma, Anuj Gupta
Author: Lavisha Sharma
Paper ID: V2I5-1146
Paper Status: published
Published: September 5, 2016
A Study on Friction Stir Welding of Various Aluminum Alloys
The comprehensive body of knowledge that has built up with respect to the friction stir welding (FSW) of aluminum alloys since the technique was invented in 1991 is reviewed on this paper. The basic principles of FSW are described, including metal flow and thermal history, before discussing how process parameters affect the weld microstructure and the likelihood of defects. Finally, the range of mechanical properties that can be achieved is discussed. It is demonstrated that FSW of aluminum is becoming an increasingly mature technology with numerous commercial applications. Keywords - Friction stir welding, metal flow, process parameters, mechanical properties
Published by: Neeraj Kumar, Virender Kumar
Author: Neeraj Kumar
Paper ID: V2I5-1143
Paper Status: published
Published: September 2, 2016
Call Admission Control (CAC) with Load Balancing Approach for the WLAN Networks
-- The cell migrations take place between the different network operators, and require the significant information exchange between the operators to handle the migratory users. The new user registration requires the pre-shared information from the user’s equipment, which signifies the user recognition before registering the new user over the network. In this thesis, the proposed model has been aimed at the development of the new call admission control mechanism with the sub-channel assignment. The very basic utilization of the proposed model is to increase the number of the users over the given cell units, which is realized by using the sub-channel assignment to the users of the network. The proposed model is aimed at solving the issue by assigning the dual sub channels over the single communication channel. Also the proposed model is aimed at handling the minimum resource users by incorporating the load balancing approach over the given network segment. The load balancing approach shares the load of the overloaded cell with the cell with lowest resource utilization. The proposed model performance has been evaluated in the various scenarios and over all of the BTS nodes. The proposed model results have been obtained in the form of the resource utilization, network load, transmission delay, consumed bandwidth and data loss. The proposed model has shown the efficiency obtained by using the proposed call admission control (CAC) along with the new load balancing mechanism. The proposed model has shown the robustness of the proposed model in handling the cell overloading factors.
Published by: Neetika Lalotra, Devasheesh Sharma
Author: Neetika Lalotra
Paper ID: V2I5-1142
Paper Status: published
Published: September 1, 2016
