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Research Paper

Key escrow with certificateless elliptic curve division for the gathering of shared information in versatile systems

In the current years, Internet of Things (IoT) is a most rising idea in Internet and Communication Technology (ICT) area. Getting to of information over the Internet through the unique portable system is the prime concern. Different business groups outsource their information in the cloud framework to lessen the information secure administration overhead. The information verification and uprightness are a portion of the fundamental security and trust prerequisites in the cloud disseminated condition. Key Escrow with Certificateless Elliptic Curve Segmentation (KE-CECS) method is a novel information security instrument that gives information verification to information transmission over IoT based Mobile Network condition. Certificateless ECC has advanced as a prime research zone because of capacity to understand the key escrow personality based issue in information administration plans. The improvement of Certificateless Signature ECC for light-weighted keen gadgets mounted in IoT based Mobile Networks has turned out to be a standout amongst the most focused research works. This paper displays another mystery division matching based Certificateless Signature plot without Map to Point hash capacity and blending. The new KE-CECS is most secured against both Type-I and Type-II foes under the solid division sharing ECC presumption individually. Execution assessment and correlation utilizing reproduction investigation demonstrate that the proposed KE-CECS beats different certificateless plans in the versatile system's condition.

Published by: B Sugumar , M Ramakrishnan

Author: B Sugumar

Paper ID: V4I2-1812

Paper Status: published

Published: April 13, 2018

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Research Paper

Experimental investigation of heat transfer by natural convection through staggered fin array at different positions

The special surface arrangement of fins or special fin geometry may enhance heat transfer rate. The staggered arrangement of fins is the special fin arrangement which gives enhanced heat transfer coefficient essential due to effective flow distribution. The arrangement selected for the topic is an experimental investigation of staggered fin arrays. They are compared with different fin array. The fin arrangement under study has constant length, width, fin thickness with different fin spacing. The design of fin arrays includes four types of arrangements i.e. continuous, 33.33%, 40% and 50% percentage lengthwise staggering of vertical fin arrays and with 38 and 48mm in height on the horizontal plate. The fin arrays with continues type compared with three lengthwise staggering are investigated experimentally under natural convection for different heater inputs and observations. The average heat transfer coefficients and average Nusselt number are calculated for each array also respective graphs are plotted. The results are presented by the calculation of Nusselt number versus the product of Grashoff number and Prandtl number graphs. Also, the results classified with flow visualization techniques. The work classified with calculating that heat transfer increases with increasing percentage staggering in the staggered arrangement of fins.

Published by: Akhilesh Patil, S. H. Gupta

Author: Akhilesh Patil

Paper ID: V4I2-1832

Paper Status: published

Published: April 13, 2018

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Research Paper

Segmentation of cartilage from knee MRI images using the watershed algorithm

We present here watershed segmentation method for the segmentation of knee cartilage. Watershed segmentation is a state of the art method and involves great simplicity of application. MRI images of the knee cartilages are used for segmenting and early detection of the osteoarthritis. MRI images offer better visualization of the soft tissues like cartilage still visualization of the tissues prone to damage is needed to be detected earlier. However, the method incorporates noise while segmentation stills its great simplicity attracts researchers for its use.

Published by: Fanendra Kumar Patel, Manoj Singh

Author: Fanendra Kumar Patel

Paper ID: V4I2-1838

Paper Status: published

Published: April 13, 2018

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Research Paper

Robotic arm control using human interface through color detection

In present times, industries face common obstacles like shortage of time and workers which leads to inefficient production. A feasible solution for this problem can be achieved using robotics. Robots save a lot of time and robots are designed for specific tasks according to one's needs. Furthermore, we can make use of image processing methods for better results. This paper presents a way to control a robotic arm through detection of a specific color. In this paper, we have proposed a method by which a webcam detects a particular colored-patch attached to a human arm using the color coding techniques in MATLAB. The coordinates of that colored-patch with respect to the video output screen are sent to the microcontroller, which in turn results in the movement of the robotic arm. The process is quick and inexpensive, for individual and industrial applications, thereby increasing the growth of the industry. The robot can be interfaced using various micro-controller, here we have used the Arduino Uno which is a microcontroller board based on the ATmega328. Arduino controlled robot is interfaced with the computer which mimics hand gestures according to the movement of the colored-patches present on the human arm. The movement of the arm is detected on the basis of the movement of the colored object present on it, using a webcam and MATLAB functions. According to the movement of the arm, the robot, which is being interfaced with the computer, is also moved in desired directions. This results in an inexpensive and effective way for controlling the robot via an interface between the human and the machine.

Published by: Neeru Tyagi, Mayank Sandhu

Author: Neeru Tyagi

Paper ID: V4I2-1855

Paper Status: published

Published: April 13, 2018

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Thesis

Deep learning technique to reduce the volume of missing data

The challenges are learning from data with missing values and finding shared representations for multimodal data to improve inference and prediction. The proposed method uses deep learning technique to reduce the volume of missing data which occur due to low battery and transmission loss. In order to find missing data imputation and new modality prediction, the original incomplete raw data is trained and tested using the stacked autoencoder to predict the corresponding missing value. Deep Multimodal Encoding methods use intra and intermodal learning to compute a new modality prediction. Deep Multimodal Encoding (DME) can achieve a Root Mean Square Error (RMSE) of the missing data imputation which is only 20% of the traditional methods. The performance of Deep Multimodal Encoding is robust to the existence of missing data.

Published by: V. Arivu Pandeeswaran, Dr. P. Kumar, R. Sivakumar

Author: V. Arivu Pandeeswaran

Paper ID: V4I2-1878

Paper Status: published

Published: April 13, 2018

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Research Paper

Alcohol sensing based engine locking system

In today’s era where we are blessed with fast-moving automobiles which makes our movement easy as well as fast, it also poses a grave danger of accidents and one of the main causes of such fatal accidents is the case of drunken driving where the person loses his control over the automobile and can become a danger to himself and the surroundings. Controlling such cases manually is practically very difficult. And thus we came up with an idea of controlling such accidents, we in this project have used the idea of gaseous material sensing for sensing the fumes of alcohol in the breath of the person who is driving. As we know that stopping a person from drinking in today’s world is near to impossible so why not stop them from driving after drinking !!!. Our project here will be installed on the steering wheel of the car where the breath of the person driving comes, it will sense the amount of alcohol consumed by him in mg/liter and if the level exceeds then the engine will be stopped and thus decreasing the chance of an accident. This prototype of our can be further modified into a smaller size and with more efficient sensing.

Published by: I Rahul Rao, Saurabh Sinha

Author: I Rahul Rao

Paper ID: V4I2-1800

Paper Status: published

Published: April 13, 2018

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