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Review Paper

A review on mouth dissolving tablets of Glimepiride

Oral route is considered as the most common and preferred technique for drug administration because it is considered as the easiest and simplest method. The route provides simplicity of drug administration in a handy way and individuals tend to be more knowledgeable about this particular route. The latest developments in Novel Drug Delivery System (NDDS) seeks for improving effectiveness and molecules security that were used previously by preparing a suitable dosage forms for administration. Now a days the problems such as dysphagia are faced by the conventional dosage forms like capsules and tablets, which results in ineffective therapy because of high incidence of non-compliance. Mouth dissolving tablets (MDTs) were developed to prevent above issues in conventional dosage forms. These MDTs have easy administration, dose uniformity, and good hardness as well as are the first preference for the travelling, geriatric, and pediatric patients. This paper provides a review for MDT because of its wide significance, as well as such drug delivery system may help for better compliance of patient along with ultimate clinical output.

Published by: Bobina Arora, Prerna Sarup, Sonia Pahuja, Navneet Kaur

Author: Bobina Arora

Paper ID: V5I3-1793

Paper Status: published

Published: June 19, 2019

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Research Paper

Agricultural drone interaction tank interface

Application of crop protection materials is one of the crucial operations in agriculture to meet ever demanding food production. The drone mounted sprayer mainly consists of BLDC motors, LiPo (Lithium Polymer) batteries, pesticide tank, pump, and supporting frame. Six BLDC motors were mounted to the hexa-copter frame to lift of 1 kg payload capacity. One LiPo batteries of 3 cells -5200mAh were used to supply the necessary current required for the propulsion system. A 1-liter capacity conical-square shaped fluid tank was used to hold the pesticide solution.

Published by: Aaditi Avinash Patil

Author: Aaditi Avinash Patil

Paper ID: V5I3-1923

Paper Status: published

Published: June 19, 2019

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Research Paper

Bidirectional Z-Source converter with hybrid system fed PMDC motor for electric vehicles

The bidirectional DC-DC converters have been widely used in micro-grids, renewable energy systems, electric vehicles and other applications to ensure the power flows from and to, or between various energy storage devices. Energy storage systems have been a major research area in which battery is one of the most widely used. A new battery ultra-capacitor hybrid energy storage system is proposed for electric vehicles. The main objectives of using ultra-capacitors alongside battery is to improve the 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 z- source converter with high voltage gain in both step-down and step-up operation modes is used here. In this work, an Ultra Capacitor is integrated with the battery in an Electric Vehicle using the new bidirectional converter to improve the dynamic performance of the vehicle system and enhancing the battery life. The simulation work is carried out using MATLAB/SIMULINK R2015 software. Hardware is made and the control strategy is implemented using TMS320F28027.

Published by: Muhsina P. Hameed, Babu Thomas, Neema S.

Author: Muhsina P. Hameed

Paper ID: V5I3-1909

Paper Status: published

Published: June 19, 2019

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Thesis

Optimization of virtual machines in cloud environment

Emergence of cloud computing has facilitated the provisioning of computing resources in an on-demand basis that can be swiftly allocated, released and reallocated with minimum management effort and cost. One important element of cloud is the virtual machine which encapsulates business services and acts as a resource carrier. An important task of cloud computing is to find an optimal placement scheme that can map the virtual machines to physical machines. With the increasing prevalence of large scale cloud computing environments, how to efficiently place VMs into available computing servers has become an essential research problem. This research works presents a Virtual Machine Placement and Load Rebalancing Based on Multi-Dimensional Resource Characteristics in Cloud Computing Systems (VMP-LR) to improve the efficiency of VM placement

Published by: Rishabh Narayan Parasar

Author: Rishabh Narayan Parasar

Paper ID: V5I3-1926

Paper Status: published

Published: June 18, 2019

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Review Paper

Multiple components detection in motherboard using Mask R-CNN

Object detection is one of the main requirements during motherboard assembly process, especially when using SMT technology. Human fatigue is the major cause of error making while manual inspection. The grasp success rate will enhance if robot can get exact position of objects than relative to the end manipulator. With the advent of deep learning techniques the accuracy for object detection has increased drastically. A major challenge in many of the object detection systems is the dependency of other computer vision techniques for helping the deep learning based approach, which will lead to the slow and non-optimal performance. In this project a completely deep learning based approach to solve the problem of object detection in an end-to-end fashion. The method, called Mask R-CNN, extends Faster R-CNN by adding a branch for predicting an object mask in parallel with the existing branch for bounding box recognition. The model developed with a pre-trained model ResNet 101 and data collected from Computer Vision Lab. Mask R-CNN is easy to generalize to other tasks and also it shows better results with COCO dataset for instance segmentation, bounding box object detection and person key point detection.

Published by: Kripa Radhakrishnan, Chaithanya C., Priya S.

Author: Kripa Radhakrishnan

Paper ID: V5I3-1922

Paper Status: published

Published: June 18, 2019

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Review Paper

Literature review on depth estimation using a single image

Depth estimation is an important component of understanding geometric relations within a scene. Different depth estimation techniques using a single image are analyzed in this survey paper. Depth estimation from a single image is often described as an ill-posed and inherently ambiguous problem. Recovering depth information in applications like 3D modeling, robotics, autonomous driving, etc. is more important when no other information such as stereo images, optical flow, or point clouds are unavailable. For the task of depth estimation using single images, learning based methods have shown very promising results.

Published by: Vyshna R. K., Dr. Priya S.

Author: Vyshna R. K.

Paper ID: V5I3-1917

Paper Status: published

Published: June 18, 2019

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