Antimicrobial, antioxidant and anti-inflammatory properties of Valeriana jatamansi and Nardostachys jatamansi
For a long period of time, plants have been a valuable source of natural products for maintaining human health. In the last decade, there has been a more intensive study for natural therapies. The use of plant compounds for pharmaceutical purposes is gradually increasing in the world. The Himalaya is credited all over the world as a treasure of medicinal and aromatic plants, which in turn prove as a treasure of bioactive agents. Among these, a good fraction of species is critically endangered. Valerian originated from the Latin word “Valere” meaning ‘to be in good health’. Valerian and Nardostachys (a substitute) belong to the Valerianaceae (now Caprifoliaceae) family. Due to similar species name and some common components, these plants are used as the substitute of each other. The root extracts of Valeriana jatamansi and Nardostachys jatamansi in various solvents are investigated for their antimicrobial property using the agar diffusion method. The antioxidant properties of both plant root extracts are analyzed using DPPH assay. The root extracts are further subjected to Lipoxygenase enzyme inhibition assay (a kit based method) to determine the anti-inflammatory properties. Methanolic extracts of Valerian show better antimicrobial effect compared to Nardostachys. It also shows the better anti-oxidant property. In contrast, antifungal and the anti-inflammatory property are shown by Nardostachys is better as compared to Valerian. According to the results obtained, it can be concluded that the plants cannot be really used a substitute; as they show different properties.
Published by: N. H. Joglekar, Dr. S. S. Barve
Author: N. H. Joglekar
Paper ID: V5I4-1275
Paper Status: published
Published: July 31, 2019
Performance characteristics of 4-stroke single cylinder diesel engine, fueled with tyre pyrolysis oil and diesel
The present rate of consumption of GASOLINE would lead to a severe shortage of it within a further few decades. An urgency of finding an alternative fuel in its place has led to several types of research around the world. A study was carried out to evaluate the use of various TYRE PYROLYSIS OIL (TPO) blends with diesel fuel. Performance and emission characteristics of TPO blends with diesel on a single-cylinder direct-injection engine are presented in this study. In the initial stage, the test was conducted on four strokes single-cylinder diesel engines by using diesel and baseline data was generated. A constant speed will be maintained throughout the experiment. Then commercially available TPO was blended with diesel fuel at some volumetric ratios [(5% TPO ,95% DO) (10% TPO ,90%DO) (15% TPO ,85%DO) (20% TPO ,80%DO) (25% TPO ,75%DO) (30%TPO, 70%DO) (35% TPO ,65%DO) (40%TPO ,60%DO)] which will be going to give the performance characteristics and also to assess at what volumetric ratio the indicated thermal efficiency will be maximum and ISFC will be less when compared to only diesel blends. How will be the exhaust gas emissions which will be studied here, if the emissions are more then we will add some additives to decrease the emissions in further work.
Published by: K. Mohan Laxmi, M. Venkatesh, A. Satish Kumar
Author: K. Mohan Laxmi
Paper ID: V5I4-1271
Paper Status: published
Published: July 31, 2019
Performance comparison of DCO and ACO optical OFDM techniques
Orthogonal Frequency Division Multiplexing (OFDM) assumes a huge job in the modem media communications system. The range of wireless communication is limited, but this technology has many advantages over its counterparts. To cater to the advantages of OFDM a new concept known as optical OFDM came into realization. Using advantages of both optical communication and OFDM long-distance transmission is possible. This paper discusses the two variants of optical OFDM namely DC biased optical OFDM (DCO-OFDM) and asymmetrically clipped optical OFDM (ACO-OFDM) along with their basic advantages and mathematical description. The Peak to Average Power Ratio (PAPR) mitigation techniques are discussed and simulation results are presents under various schemes.
Published by: Anuj Aawasthi, Dr. Manoj Kumar Shukla
Author: Anuj Aawasthi
Paper ID: V5I4-1284
Paper Status: published
Published: July 31, 2019
Automatic target recognition and classification from synthetic aperture radar imagery using multi-stream Convolution Neural Network
The process of using a computer to identify or recognize a target from Synthetic Aperture Radar (SAR) images with or without human interference is known as Automatic Target Recognition (ATR). The recognition of target is the process of discovering the location, pose or class of a target with a particular spatial signature by using a high spectral resolution remotely sensed images, which belongs to a particular kind of object (vehicle). In recent years ATR is particular interest in military applications such as infrared surveillance and target acquisition, unmanned aerial vehicles, and autonomous missile. The traditional architecture of automatic target recognition (ATR) for synthetic aperture radar (SAR) consists of three stages: detection, discrimination, classification and recognition. In the last few years Many deep convolutional neural networks have been proposed and used for SAR-ATR and have obtained state-of-the-art results in many computer vision tasks, plus shown improvement from time to time, but most of them classify targets from target chips which is found from SAR imagery, due to limited training images in SAR-ATR, CNN yielded over-fitting when directly applied to SAR-ATR. This paper proposes a novel deep convolutional learning architecture, called Multi-Stream CNN (MS-CNN), for ATR in SAR by leveraging SAR images from multiple views. By deploying a multi-input architecture that fuses information from multiple views of the same target in different aspects enables it to make full use of limited SAR image data to improve recognition performance. In addition, the Fourier feature fusion framework derived which allows unraveling the highly nonlinear relationship between images and classes. The model proposed in this paper performs all the three tasks in the SAR-ATR architecture. The proposed CNN will train using the Moving and Stationary Target Acquisition and Recognition (MSTAR) benchmark data set and to output scores of 10 classes.
Published by: Kalkidan Gezahegn, Dr. Sudeshna Chakraborty
Author: Kalkidan Gezahegn
Paper ID: V5I4-1254
Paper Status: published
Published: July 31, 2019
Soil stabilization using waste fibre materials
The main objective of this study is to investigate the use of waste fiber materials in geotechnical applications and to evaluate the effects of waste polypropylene fibers on shear strength of unsaturated soil by carrying out direct shear tests and unconfined compression tests on two different soil samples. The results obtained are compared for the two samples and inferences are drawn towards the usability and effectiveness of fiber reinforcement as a replacement for deep foundation or raft foundation, as a cost-effective approach.
Published by: Chandramohan Pahade, Vijay Kumar Meshram
Author: Chandramohan Pahade
Paper ID: V5I4-1225
Paper Status: published
Published: July 30, 2019
Effective stabilisation of pavement subgrade using crusher dust
Roads are an important form of infrastructure in any country. Good and safe roads are important for the economic and social growth of the country. National highways are strategically planned with the objective of smooth and fast movement of goods, services, and people to different locations in the country. With this mandate the Government of India set up National Highways Authority of India (NHAI) by an act of Parliament ‘NHAI Act 1988’. National highways connect small towns and districts to capitals of the state and the country and also to places of economic importance. National highways like NH6 provide a good connection with neighboring states, and NH43 and NH200 provide the main north-south connection between Raipur, Bilaspur, and Jagdalpur. About 19 National highways pass through the state of Chhattisgarh, however, apart from these not all roads are all-weather roads and are not safe especially in monsoons. The function of any road depends on its pavement and pavement function depends on its component layer especially the sub-base layer. So, it is very important for any designer to study the natural conditions of the site before the construction of any road network. The sub-base layer is mostly made up of natural soil like gravel soil, which deforms excessively. So to increase the life span of the pavement it is important to reduce their plastic characteristics. Stabilization is one of the techniques for its improvement. Here, we are using crusher dust as a stabilizer. Plasticity characteristics were reduced and CBR values were improved by using crusher dust as a stabilizer. The addition of 20% of crusher dust makes the gravel soils meet the specification of MORTH as a sub-base material is identified from the test results.
Published by: Sakshi Singh Rana
Author: Sakshi Singh Rana
Paper ID: V5I4-1279
Paper Status: published
Published: July 30, 2019
