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Battery-ultracapacitor hybrid system for electric vehicles using new bidirectional quadratic DC-DC converter

Hybrid energy storage system is used with the objective of taking advantage of the best characteristics of each device, creating a system that is superior, than any of the devices used alone. Due to operational requirements of distributed generation systems, energy storage devices like batteries and super-capacitors, need bidirectional DC-DC converters to allow charge or discharge according to with the necessary conditions. A new battery-ultracapacitor hybrid energy storage system is proposed for electric vehicles. The main objectives of using ultra-capacitors in alongside batteries are: improving performance, increase the system efficiency and extend the battery life. In many applications, conventional bidirectional converters are inadequate since the specified range of input voltages and the specified range of output voltages call for an extremely large range of conversion ratios. A new bidirectional quadratic converter with high voltage gain in both step-down and step-up operation modes is used along with the ultra-capacitor. This converter is also characterized by a simple control technique since it is only necessary to control one power semiconductor for each mode. The additional power semiconductors remain always on or always off. In this project, an Ultra Capacitor is integrated with the battery in an Electric Vehicle using the new bidirectional quadratic buck-boost converter to improve the dynamic performance of the vehicle system and enhancing the battery life. The system model and the implemented control strategy has been simulated in MATLAB/SIMULINK software. The hardware of the proposed system is made. The control strategy is implemented using TMS320F28027.

Published by: Jithin K Mathews, Sija Gopinathan, Sera Mathew

Author: Jithin K Mathews

Paper ID: V4I3-1616

Paper Status: published

Published: May 28, 2018

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Research Paper

Statistical approach to study the lithostratigraphic sequence in the Proterozoic Kolhans

Lithofacies succession in the Proterozoic Kolhan Group has been studied statistically using modified Cross-Association Analysis, Markov chain model, and Entropy function. The lithofacies analysis based on the field descriptions and their vertical packaging has been done for assessing the sediment depositional framework and the environment of deposition. Six lithofacies arranged, in two genetic sequences, have been recognized within the succession. The result of Markov chain and cross-association analysis indicates that the deposition of the lithofacies is in the Markovian and non-cyclic process and represents asymmetric fining- upward. The chi-square test has been done to test for randomness in hypotheses for lithofacies transition at the confidence level of 95%. The entropy analysis has been done to evaluate the randomness of occurrence of lithofacies in a succession. Two types of entropies are related to every state; one is relevant to the Markov matrix expressing the upward transitions (entropy after deposition), and the other, relevant to the matrix expressing the downward transitions (entropy before deposition). The total energy regime calculated from the entropy analysis showing maximum randomness, suggests that changing pattern in the deposition has been a result of rapid to the steady flow. This results from a change in the depositional pattern from deltaic to lacustrine deposit and sediment bypassing that finally generated non-cyclicity in the sequence.

Published by: Rohini Das

Author: Rohini Das

Paper ID: V4I3-1632

Paper Status: published

Published: May 28, 2018

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Research Paper

Lung cancer detection system by fusion of CT and MRI images

Lung cancer is one of the common types of cancer in the world. It is hard to detect cancer and the affected level at an early stage. CT and MRI help us to detect this type of cancers at an early stage. Fusion of a CT and MRI images can be done for obtaining best results. However, in previous works, this method of diagnosis has not been carried out. In this proposed work combining of CT and MRI images can be done and the level of cancer in the lungs can be identified. Image fusion is used to identify the common features between the two images this can be used to improve the quality of the images for easy identification.

Published by: Gokulapriya V, M. Marikkannan

Author: Gokulapriya V

Paper ID: V4I3-1526

Paper Status: published

Published: May 28, 2018

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Research Paper

An hybrid of PET and NIRS of non-invasive technique with clustering for detecting brain tumor

Segmentation is the process of partitioning the digital image into many segments which depends on pixels. It helps to identify objects or an irrelevant object in a particular area. The segmentation was based on color, texture and threshold methods. The main focus of this work is not only identifying the defected area in the brain but also analyzing the approximate location. So the clustering method is applied for grouping the similar objects. The non-invasive technique is a safe imaging technique uses today in research facilities and hospitals throughout the world. The comparing of non-invasive techniques like Positron Emission Tomography (PET) scan and the hybrid of Near-Infrared Spectroscopy (NIRS) and Electro-Encephalography (EEG) brain interfaces gives the best result to find the approximate location of the detected area in the brain with accuracy and stability.

Published by: Eniya Priya Darsini K

Author: Eniya Priya Darsini K

Paper ID: V4I3-1587

Paper Status: published

Published: May 28, 2018

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Research Paper

Highly accurate DAS for detecting speed limit signs

Driver Assistance Systems (DAS) are the systems to help the driver in the driving process. This work checks the road in front of a vehicle and detects speed limit sign. Highly reliable and accurate classification is done through three main phases named acquisition, detection, and recognition. Optical Character Recognition (OCR) technique is used in this algorithm to recognize traffic sign templates. This proposed system results in more accuracy over existing DAS. The capacities and vigor of the proposed system are tried against various situations.

Published by: Gifty Saju, Anna Prethibha Shobak

Author: Gifty Saju

Paper ID: V4I3-1451

Paper Status: published

Published: May 28, 2018

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Research Paper

Maternal parenting quality: It’s effect on infant mental health

Early years of life are highly influenced by the quality of relationships with parents, which have a lasting impression on future mental health. The parenting quality of infants those who were ‘normal/ at low risk’ and those who were ‘at risk’ and its effect on the mental health of infants was studied on a sample of 97 mother-infant dyads from rural and urban Dharwad, Karnataka, India. The parent-child interactions during play (with available play materials) were videotaped for 12-15 minutes duration at their home. The parenting quality was assessed using Keys to Interactive Parenting Scale by Comfort and Gordon (2006) which measures three constructs of parenting viz. building relationships, promoting learning and supporting confidence. The mental health of infants was measured using Ages and Stages Questionnaire-Socio-emotional by Squires et.al (2002) and the socioeconomic status (SES) was measured using SES Scale developed by Agarwal et.al (2005). The results revealed that the mothers of infants at ‘low risk’ were high on parenting quality. Child characteristics such as age and ordinal position, maternal characteristics such as age, education, occupation and age at marriage significantly predicted the infant mental health (37%). The maternal parenting quality alone predicted infant mental health (5%) which was in-turn correlated to maternal age, education, occupation, and SES. Hence there is a great need to provide intervention to mothers of infants who are ‘at risk’ and also to those mothers who are low on parenting quality so that the future generation blooms without any stressors that can damage the infant mental health.

Published by: Pavitra Bhat, Dr. Pushpa Khadi

Author: Pavitra Bhat

Paper ID: V4I3-1625

Paper Status: published

Published: May 28, 2018

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