Sri Ramakrishna Engineering College

About: Sri Ramakrishna Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Control theory. The organization has 1030 authors who have published 843 publications receiving 3822 citations.

Design and Development of Post Knee Arthroscopy Assist Device

Abstract: Designing and developing a device which provides a solution for knee spasms for the people who underwent surgery in the knee due to injury by enhancing the ability of motion in the knee joint and also strengthening the weak muscles. After operative procedures the patient remains in bed rest which results in passiveness in the lower limb and Range of Motion (ROM) will be reduced due to the impact of the injury. Thus, the Continuous Passive Motion (CPM) device is designed to lessen edema and swelling of the knee followed by injuries or surgeries. This device replaces the all time presence of physiotherapist and can accomplish such routine physical movements without the guidance and assistance of physiotherapist. The key feature in constructing a CPM is in the establishment of an accurate alignment with the human knee joint enabling the device to deliver similar movements as the actual body. Emergency switch is employed to the patients and they can stop the system in case of emergency or discomfort. This system comprises of Mechanical and Electronic components to full fill the necessity of the device requirements. Design and Development of Post Knee Arthroscopy Assist Device

A Novel Fuzzy-Bayesian Classification Method for Automatic Text Categorization

Abstract: Text categorization is mostly required to label the documents automatically with the predefined set of topics. It has been achieved by the large number of advanced machine learning algorithms. In the proposed system, fuzzy rule along with Bayesian classification method is proposed for automatic text categorization using the class-specific features. The proposed method selects the particular feature subset for each class. Then, these class features are applied for the classification. To achieve this, Baggenstoss‘s PDF Projection Theorem is followed to reconstruct PDF in raw data space from the class-specific PDF in low-dimensional feature space and build the fuzzy based Bayes classification rule. The noticeable significance of this method is that most feature selection criteria such as information gain and maximum discrimination which can be easily incorporated into the proposed method. The proposed classification performance is evaluated on different datasets and compared with the different feature selection methods. The experimental results illustrate that the effectiveness of the proposed method and further indicates its wide applications in text categorization.

Robust intrusion detection system based on fuzzy C means clustering scheme implemented in IoT-based wireless sensor networks

Abstract: Research in wireless networks and communication protocols have reached new heights in recent times with the advent of state-of-the-art communication techniques and gadgets. They have found widespread utility in recent times especially with the advent of cloud computing and internet of things (IoT). IoTs offer immense potential in today's scenario aiding in smart computing and automation of things focused to making life of consumers easier and simpler. However, security of information transmitted and received over wireless networks is an essential concern to preserve privacy and authenticity of information. This research issue is however quite complex as it involves security of bulk information quite private and confidential to be delivered in a wireless medium prone to hackers. This research article has investigated the various issues related to security of IoT-based wireless sensor networks and proposed a fuzzy-based clustering algorithm to effectively detect an intrusion and make the information secure.

Anodizing and its effects on mechanical properties and corrosion resistance of laser additive manufactured Ti-6Al-4V alloy

Abstract: Ti-6Al-4V components were developed in different orientations (horizontal and vertical) using an additive manufacturing technique called direct metal laser sintering and heat treated under...

L Shaped Morpho Codec for Medical Video Sequences

Abstract: L Shaped Morpho Codec (LSMC) using the concepts of Lifting Wavelet Transform applied for Medical Video sequences. Morphology dilation is applied for the significant pixel in the various sub-bands resulted during decomposing. Experiment results of LSMC are compared with Set Partitioning in Hierarchical Trees (SPIHT) and Set Partitioned Embedded bloCK coder (SPECK) for a video frame resolution of 512 * 512 pixels. Lossless bit rate obtained for the mentioned codes are even tabulated. LSMC performs well in comparing with SPIHT & SPECK.