A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Jayanthi, S.
- Parallel Learning Reinforcement-A Case Study
Authors
1 Dept. of Mathematics, BMS College of Engineering, Bangalore, IN
2 Dept. of Phyics, BMS College of Engineering, Bangalore, IN
Source
Journal of Engineering Education Transformations, Vol 28, No 4 (2015), Pagination: 96-101Abstract
Even though Mathematics, the queen of all sciences, is necessary for the engineers to master, their basic knowledge in mathematics, before taking the first year course is crucial. There is an urgent need for strengthening the students' fundamentals in mathematics, especially that of the fresh entrants into the engineering course. A novel methodology consisting of identifying those students with poor comprehension, coaching them during extra hours along with the regular course, improving their caliber and evaluating their performance to quantify the success of the process was carried out successfully in the department of mathematics, BMS College of Engineering. The result of the student's survey is discussed in this paper.Keywords
Parallel Learning, Diagnostic Test, Remedial Class.- An Energy Based Clustering for Data Gathering using Multiple Sensor Cars in WSN
Authors
Source
Networking and Communication Engineering, Vol 8, No 4 (2016), Pagination: 127-131Abstract
Nowadays, Data Gathering using mobile element plays an important role in wireless sensor network. The mobile element can gather data in two ways. First, Data can be collected from the sensor nodes using single hop relaying. This maximizes the energy consumption and minimizes the lifetime of the network. Secondly, the data can be collected using Multi-hop relaying scheme. This minimizes the energy consumption of a single sensor node and maximizes the network lifetime which in turn reduces the data loss and minimizes the delay. But there is a problem on routing the data packets from sensor node to base station. This paper proposes an Energy based Clustering for Data Gathering Using Multiple Sensor Cars (EC-DGMSC) in Wireless Sensor Networks which assembles the sensors into group and an aggregation node (Cluster Head-CH) is elected for each group. The Sensor Car (SenCar) gathers data dynamically from the CH, once the energy level of CH falls below the threshold then new CH will be selected from the cluster. Thus, the proposed framework reduces the energy consumption of the sensors as well as extends the network lifetime compared to existing systems.
Keywords
Clustering, Cluster Head, Data Gathering, Multi-Hop Relay, Single-Hop Relay, SenCar, Wireless Sensor Networks.- Privacy Protection and Interruption Avoidance for Cloud-Based Medical Data Sharing
Authors
1 Department of Computer Applications, S.A. Engineering College, IN
Source
Data Mining and Knowledge Engineering, Vol 11, No 4 (2019), Pagination: 53-56Abstract
In this paper and analyse a behaviour-rule specification-based technique for intrusion detection of medical devices embedded in a Medical Cyber Physical System (MCPS) in which the patient's safety is of the utmost importance. A methodology to transform behaviour rules to a state machine, so that a device that is being monitored for its behaviour can easily be checked against the transformed state machine for deviation from its behaviour specification.
Using vital sign monitor medical devices as an example; In demonstrate that our intrusion detection technique can effectively trade false positives off for a high detection probability to cope with more sophisticated and hidden attackers to support ultra-safe and secure MCPS applications. Moreover, through a comparative analysis, A demonstrate that our behaviour-rule specification-based IDS technique outperforms two existing anomaly-based techniques for detecting abnormal patient behaviours in pervasive healthcare applications.
Keywords
Privacy Protection, Data Sharing, NTRU, Collaborative IDS.References
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- Anderson, Andres, Yigaw, KassyeYitbarek & Karlsen, Randi, ”Privacy preserving health data processing”, IEEE 16th international conference on e-health networking, applications and services,2014.
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- Improving Home Automation Security; Integrating Face Recognition Using LBPH Algorithm in Door Lock System
Authors
1 Department of Computer Applications, S.A. Engineering College, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 11, No 4 (2019), Pagination: 72-75Abstract
The home automation security is growing field now-a-days. This paper says about accessing the modern smart home with security system. In this security system double verification process is used. Double verification is done through Password and Face Recognition. In this paper I taken two doors mainly and assumed as primary door and secondary door. Primary door (access to the living room) and Secondary door (entire access to the home); both are controlled by Raspberry pi board to perform the door open operation. LCD panel and Raspberry pi-3 camera placed on primary door with LCD panel enter password and get access to the primary door and raspberry pi camera will capture the image and compare with database using LBPH algorithm if captured image matches with database then provide access to the secondary door. If I need to access the entire home, I need to satisfy the double verification process.
Keywords
LCD Panel, LBPH, Raspberry Pi, Face Recognition.References
- F.Shawki, M. EL-Shahat, et all “microcontroller based smart home with security using GSM technology”, international journal of research, ISSN: 2319-1163
- Arun Cyril jose, Reza Malkekian and Ning ye “improving home automation security; integrating device fingerprinting into smart home”, IEEE Access, 2016.
- Nico Surantha, Wingky R. Wicaksono “Design of smart home security system using object recognition and PIR sensor”, 3rdinternational conference, 2018.
- Xin Hong, Chenhui Yang,Chunming Rong, ”Smarthome security monitor system” International symposium, 2016.
- Sandesh Kulkarni, Minakshee Bagul. Et.all “Face Recognition System Using IoT”, (IJARCET) volume 6, 2017.
- Jayashri Bangali and Arvind Shaligram” Design and Implementation of Security System for Smart home based on GSM technology”, International journal of smart home vol.7, no.6 (2013).
- Hteik Htar Lwin, Aung Soe Khaing, Hla Myo Tun” Automatic Door Access System Using Face Recognition” International journal of scientific &technology research vol. 4, issue 06, June 2015.
- Nalini Nagendran, Ashwini Kolhe” Security and Safety with Facial Recognition Feature for Next Generation Automobiles” International Journal of Recent Technology and Engineering (IJRTE), vol-7 Issue-4S, November 2018
- Kumar AS, Reddy PR. An Internet of Things approach for motion detection using Raspberry-Pi. J Int J Adv Technol Innov Res.2016: 8(19):3622–7.
- Abishek,Anurag et all ”Smart home security through NFC” Bonfring International journal of software Engineering and soft computing, vol.6,oct 2016.
- Samuel Lukas, Aditya Rama Mitra, Ririn Ikana Desanti, Dion Krisnadi "Student Attendance System in Classroom Using Face Recognition Technique" IEEE 2016.
- K. Sri Viraja, K. Bharath Kumar, C. Keerthi, G. Sandeep” IOT Based Smart Door System” International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653; Vol 6, April 2018
- Rahul Satoskar, Akarsh Mishra” Smart Door Lock and Lighting System using Internet of Things” (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 9 (5), 2018.
- Ansari AN, Sedky M, Sharma N, Tyagi A. An Internet of things approach for motion detection using Raspberry Pi. In: Intelligent Computing and Internet of Things (ICIT), 2014 International Conference on. 2015. p. 131–4.
- Ms. Renuka Chuimurkar et all “Smart Surveillance Security &Monitoring System Using Raspberry PI and PIR Sensor” International Journal of Scientific Engineering and Applied Science (IJSEAS) – Volume-2, Issue-1, January 2016
- Volume of the Brain Tumour Regions with Hybrid Segmentation
Authors
1 Assistant Professor SG, Department of ECE, Saveetha School of Engineering, Chennai, IN
2 Professor, Department of ECE, Jerusalem College of Engineering, Chennai, IN
3 Professors, Department of ECE, Rajalakshmi Engineering College, Chennai, IN
Source
Indian Journal of Public Health Research & Development, Vol 10, No 11 (2019), Pagination: 3806-3812Abstract
MR imaging gives the normal and abnormal anatomy of the brain. MR imaging plays a vital role in diagnosis, localization, quantifying the volume of the tumour and in treatment planning for the radiologists. In this we propose a method for segmentation of tumour regions of brain from a two dimensional (2D) cross sectional magnetic resonance (MR) images. In this an active contour segmentation algorithm is done regions. It uses the hybrid technique of intensity and fuzziness to segment the tumour region. The Flair MR image is used to estimate the whole region of the tumour. The MR images have a complex intensity which will not be able to give a proper segmentation if a single method is used. The segmentation is done without any training dataset. From the segmented results, the Radiologists can find the intensity of whole tumour. This method shows the significant improvement in segmentation compared to manual segmentation.Keywords
Active Conyour, Brain Tumour, FCM, Magnetic Resonance Imaging, 3D Reconstruction.- An IOT Cloud based Wearable Heart Beat and ECG Observation System that Managing the Traffic for an Ambulance
Authors
1 Department of Computer Applications, S. A. Engineering College, IN