VOLUME 9

15 Jan

Biodegradation Capacity of Bacillus Sp. VC2 for Polythene Degradation

Authors- Christian Venisha V., Rathod Zalak R., Makwana Sonal K., Thakkar Aarti V.

Abstract- Plastics are vital hydrocarbons occurring both in natural as well as in synthetic forms. The present study describes the isolation of bacteria from soil and sludge with the ability to degrade biodegradable plastics. Biodegradable plastic was buried in the glass bottle with three layers of different soil like Rhizospheric soil, Sludge and Garden soil for 4 months. The bacteria was then isolated and identified on the basis of biochemical studies as Bacillus sp. VC2. The bacteria Bacillus sp. VC2 breaks the polymers and used as sole carbon source for their metabolic activities was estimated by FTIR analysis

A Study of Two Area Inter-connected Power System

Authors- M.Tech. Student Nihal Mishra , Asst. Prof. Rohit Gupta , Associate Prof. Anand Singh

Abstract- Because of mechanical contamination our living climate demolished. An electric lattice framework has may essential hardware like generator, engine, transformers and burdens. There is consistently be an irregularity between sending end and accepting end framework which cause framework insecure. So this mistake and deficiency causing issue ought to be settled and adjusted as quickly as time permits else it makes flaws and framework blunder and fall of productivity of the entire force framework. The primary issue created from this deficiency is deviation of recurrence cause shakiness to the force framework and may make perpetual harm the framework. Accordingly this instrument concentrated in this paper make the framework stable and equilibrium by managing recurrence at both sending and getting end power framework utilizing programmed age control utilizing different regulators considering a two zone warm force framework.

Efficiency and Connectivity Enhancement in Wireless Sensor Networks

Authors- M.Tech. Scholar Nishu Damral, Asst. Prof. Sonal Sood

Abstract- – In our work, we have to study the method for traffic management in wireless sensor networks to improve efficiency and enhance end to end connectivity using delay tolerant networks. In such type of networks, different number of nodes are grouped , the information is collected and directed from source to destination following the routing protocol. We have used map based movement approach for path choosing and to analyze the shortest path for information delivery to avoid overhead ratio. This technique is useful when a fraction of sensor nodes are deployed with information that has to set up a secure connection as the operation of the network progresses. Network efficiency is improved specially incase of total network disruption during natural calamities or disasters where end to end connectivity with security is crucial .

Neural Networks: Types and Applications

Authors- M.Tech. Scholar Aparna Mohan

Abstract- – Deep learning consists of different types of neural networks, which are used for different purposes. There are many commonly used topologies in neural networks. Perceptron, Feed Forward, Radial Basis Network, Deep Feed Forward, Recurrent Neural Network etc are some of the topology types. Neural Network can be defined as deep learning using artificial intelligence.

Survey on Dynamic Adhoc on Demand Distance Vector Routing Protocol Designed for Mobile Adhoc Network

Authors- Asst. Prof. Rahul Mukherjee

Abstract- – A Mobile Ad-hoc Network (MANET) is an assembly of wireless mobile nodes forming a temporary network without using any centralized access point, infrastructure, or centralized administration. Data transmission between two nodes in MANET’s may requires multiple hops as the node’s transmission range is limited. Mobility of the different nodes makes the situation even more complicated. Multiple routing protocols especially for these conditions have been developed during the last few years, to find optimized routes from a source to some destination.

Analysis of Hippe (M40) Biodiesel on Tribological Property of IC Engine Components

Authors- Post Doctoral Fellow Dr. Venkata Sundar Rao K, Prof. & Head Dr. Shreeprakash B

Abstract- – The internal combustion engine is a heat engine that converts chemical energy into mechanical energy, usually made available on a rotating output shaft. Chemical energy of the fuel is first converted to thermal energy by means of combustion or oxidation with air inside the engine. This thermal energy raises the temperature and pressure of the gases and the high-pressure gas then expands against the mechanical mechanisms of the engine. This expansion is converted by the mechanical linkages of the engine to a rotating crankshaft, which is the output of the engine. The crankshaft, in turn, is connected to a transmission and/or power train to transmit the rotating mechanical energy to the desired final use. In the present work, the surface roughness of the IC Engine components has been recorded for diesel and blend of 60% Diesel+40% Hippe oil. The use of the blend of 60% Diesel+40% Hippe oil has better tribological properties of the IC Engine components as compared to the diesel as a fuel. Hence the blend of 60% Diesel+40% Hippe oil could be used as an alternative bio-fuel to reduce the pollution effects and material wear of the components

Preliminary Phytochemical Investigation of Extraction from Citrus limon

Authors- Rathod Zalak R., Christian Venisha V., Makwana Sonal K., Saraf Meenu S.

Abstract- – The present study is aimed to investigate the phytochemicals present in hexane, chloroform, ethyl acetate, acetone and methanolic extracts obtained from fruits and leaf of Citrus limon plant. The plant material was extracted with various solvents based on their polarity by the process of maceration method. Preliminary phytochemical analysis was performed by different qualitative methods. Preliminary phytochemical analysis of the extracts revealed the presence of carbohydrates, tannins, alkaloids, saponins and phenolic compounds. The study will provide referential information for the correct identification of the bioactive compounds and suitable solvent system for separation of those compounds from the fruit and extract of Citrus limon.

IOT: A REVIEW

Authors- Research Scholar Indu Maurya

Abstract- IOT is a growing mechanization in the globe. Since various appliances are fused collectively to shape an inter-connection of an information centre. IoT mechanization is rising gradually because the gadgets associated to the web are rising instant to instant. This study talked about a variety of safety constraints wherein IoT system performs a nasty module. A lot of members talke about the safety isue of it however did not discover the systematic clarification. It is the only surprising reality that by means of rising skill there would be safety features connected through it as well as can be watched out from instance to instance. No system in the globe is hundred percent exact in the implementation area. This studt replicates illumination on the IoT as well as its safety features.

A Survey On Brain Tumor Detection Using Various Deep and Machine Learning Algorithm

Authors- Nishchay Agarwal, Lokesh Kumar, Akansha Singh, Hemant Kumar, Mukul Chauhan, Abhishek Dubey

Abstract- The human brain is the central nervous system; a collection of white fragments of cells. A group of growing cells is found abnormally in various parts of the brain known as Glial cells, neurons, lymphatic tissue, blood vessels, pituitary glands that can lead to cancer in humans. Diagnosis of a brain tumor is a particularly challenging task in the early stages of life. But now it has improved with various machine learning and in-depth reading skills. Now the release date of automatic brain tumor screening is of great interest. To diagnose a patient’s brain tumor, we look at patient data such as MRI images of the patient’s brain. Here our problem is to determine whether the tumor is present in the patient’s brain or not. The isolation, detection, and removal of the infected plant area from magnetic resonance imaging (MR) are very important but tedious and time-consuming processes performed by radiologists or clinical specialists. In this paper, we focus mainly on existing proposed machine algorithms and depth learning algorithms proposed by various authors to build brain tumor detection and classification.

Heart Disease Prediction Using Machine Learning Algorithm

Authors- B.Tech. Research Scholar Vaibhav Raj

Heart disease is a common problem which can be very severe in old ages and also in people not having a healthy lifestyle. With regular check-up and diagnosis in addition to maintaining a decent eating habit can prevent it to some extent. In this paper we have tried to implement the most sought after and important machine learning algorithm to predict the heart disease in a patient. Weighing only 300 grams, Heart is declining the mortality rate at a rapid pace from decades. The major factors that contribute to it are smoking, drinking, unbalanced diet, and many more. Even with these more technical advancements the analysis of the clinical data is a critical challenge. With the use of Machine Learning techniques, it is possible to analyse the data and interpret the cause that lead to heart diseases such as Coronary Heart Disease, Arrhythmia, and Dilated Cardiomyopathy. Many researchers are developing loT enabled hardware to predict these diseases using various ML and DM techniques. In this study, we propose a novel method to determine the disease using Cleveland Heart Disease Dataset by combining the computational power of various ML and DM algorithms and concluded that among all the algorithms, K Nearest Neighbors gives the highest accuracy of 87%. Along with this, a web app is developed using flask in python with which the user can enter the attributes and predict the heart disease.

Data Visualization using Tableau pragmatic for COVID-19

Authors- Pankhuri Rastogi, Shivali Pundir, Santosh Yadav, Chandan Kumar

As we know that Coronavirus circumstances has untwisted across the world , data visualization & virtualization has really become important for the people to understand & see that data alike emulates reality. Amidst this global pandemic , people wants to know the answers of their inquisitive questions which are uprising in their minds & for that , Tableau is an important & impressive data visualization software , as it not only helps in visualizing the collected data quickly but simultaneously add on to do it an understandable , interactive and coherent way . In this paper, Covid-19 (Coronavirus) analysis with Tableau, we will create dashboards that will help you pin down the story within our collected data & will help you to understand that Coronavirus has entirely impacted across the globe . In this paper, we focus mainly on existing proposed data visualization algorithms and methods proposed by various authors to visualize coronavirus detection and classification.

A Review of Piston and its Function Using Tungsten Alloy

Authors- M.E. Scholar Sachin Prajapat, Dr. Pardeep Kumar Patil, Dr. Rahul Joshi, Mr. Vishal Wankhede

Piston is the part of engine which converts heat and pressure energy liberated by fuel combustion into mechanical works. Engine piston is the most complex component among the automotives. This paper illustrate design procedure for a piston for 4 stroke petrol engine for hero splendor – pro bike and its analysis by its comparison with original piston dimensions used in bike. The design procedure involves determination of various piston dimensions using analytical method under maximum power condition. In this paper the combined effect of mechanical and load is taken into consideration while determining various dimensions. The basic data of the engine are taken from a located engine type of hero splendor –pro bike.

Survey on Sentiment Analysis of Twitter Data

Authors- ME Scholar Kratika Patidar, HOD. Kamlesh Patidar

Everyday a huge amount of data has been produced over various social sites. A huge number of users share and tweet regular updates on twitter. Tweet is a short way of expressing thoughts on any topic. So, the sentiment analysis of this data is must to keep track of the tweets. Sentiment analysis is the way to carry out text mining. To analyze this data produced over the twitter there are many methods that are used. Various experiments have been done to perform sentiment analysis of this data produced over twitter. There are different levels on which the sentiment analysis can be performed. So, in this paper we are providing a survey on the sentiment analysis of twitter data which uses the supervised and unsupervised learning algorithms.

A Novel High Capacity Approach for Reversible Audio Steganography

Authors- Hariom Dudhwal,Asst. Prof. Jayshree Boaddh Asst. Prof. Jashwant Samar

The fast spread in digital information data utilization in numerous genuine applications have encouraged new and successful approaches to guarantee their security. Efficient secrecy can be achieved, at least in part, by implementing steganography techniques. The objective of steganographic frameworks is to acquire secure and robust approach to disguise high rate of secret information. This work mainly focus around digital audio steganography, which has risen as a promising source of information hiding over novel information and telecommunication technologies, for example, audio conferencing, secured voice-over-IP, and so forth. The huge number of steganographic criteria has prompted an awesome assorted variety in these framework design procedures. In this examination work, a novel high capacity approach for reversible audio steganography to enhance the performance of previous digital audio steganographic techniques and the performance of proposed approach is evaluate based on robustness, security and hiding capacity indicators. It is examined by simulation in MATLAB simulation environment that proposed technique outperforms against previous base work in terms of security and capacity.

Dementia Classification using Multiple Transfer Learning Models

Authors- Asst. Prof. Lakshmi R Suresh

Dementiais an irreversible progressive neurodegenerative disorder. Mild cognitive impairment (MCI) is the prodromal state of Dementia, which is further classifed into a progressive state (i.e., pMCI) and a stable state (i.e., sMCI). With the development of deep learning, the convolutional neural networks (CNNs) have Dementia great progress in image recognition using magnetic resonance imaging (MRI) and positron emission tomography (PET) for diagnosis. Rather than training an entire model from scratch, transfer learning approach uses the CNN model by fine-tuning them, to classify MR images into Dementia,mild cognitive impairment (MCI) and normal control (NC). The performance of this method has been evaluated over Dementia dataset by changing the learning rate of the model. Moreover, in this study, in order to demonstrate the transfer learning approach we utilize different pre trained deep learning models such as GoogLeNet, VGG-16, AlexNet and ResNet-18, and compare their efficiency to classify Dementia. The overall classification accuracy resulted by GoogLeNet for training and testing was 99.84% and 98.25% respectively, which was exceptionally more than other models training and testing accuracies.

Heart Disease Prediction Using Machine Learning

Authors- Alam Khan, Amit Rai, Alka Joshi,Gaurav Kumar, Ram Narayan

It is well knоwn thаt the heаrt is оne оf the mоst imроrtаnt аnd сruсiаl раrts оf the humаn bоdy. The diаgnоsis оf heаrt diseаse thrоugh the trаditiоnаl methоd hаs nоt been соnsidered reliаble in mаny аsрeсts. In tоdаy’s erа, there аre numbers оf ML аlgоrithms аnd mоdels рresent tо dig оut meаningful infоrmаtiоn tо diаgnоse аnd deсiding. In this рарer, vаriоus mасhine leаrning mоdels like Suрроrt Veсtоr Mасhine (SVM), Lоgistiс regressiоn, K NN(K Neаrest Neighbоur), Nаïve Bаyes, Deсisiоn Tree, аnd Rаndоm Fоrest is emрlоyed. The mоst оbjeсtive оf оur wоrk wаs tо рrediсt the раtient is hаving аny heаrt рrоblem оr nоt sо аfter testing these mоdels, the mоdel with greаter ассurасy is tаken fоr рrediсting the finаl result. Tоdаy the heаlthсаre industry is infоrmаtiоn-riсh hоwever still very рооr in knоwledge оr mоstly the dаtа аre nоt рubliсаlly аvаilаble. This рарer hаs used а Сlevelаnd dаtаset соntаining 303 individuаls аnd 14 аttributes like аge, sex, сhest раin (ср), resting blооd рressure (trestрs), сhоlesterоl (сhоl), etс. With the helр оf these аttributes, оur Rаndоm Fоrest Mоdel with аn ассurасy оf 88% рrоvide the finаl result tо the end-user оn аn interасtive web-аррliсаtiоn designed using HTML, СSS, Flаsk frаmewоrk, аnd JаvаSсriрt. With the helр оf this раtients саn diаgnоsis themselves аt zerо соst. This wоrk will helр the end user tо get the рreliminаry рrediсtiоn оf their heаrt diseаse аnd will sаve them frоm severe соmрliсаtiоns.

A Review on Halotolerant and Halophilic Phosphate-Solubilizing Biofertilizers on Canola(Brassica napus L.)

Authors- Bhadaniya Nidhi, Patel Aakruti, Metaliya Divya, Rathod Zalak.R, Saraf Meenu S.

Phosphorus is the second important key element after Nitrogen and most commonly limiting the growth of crops.Phosphorus-solubilizing microorganisms solubilize inorganic insoluble phosphorus and make them available to the crops. Therefore P-solubilization is a promising strategy for increasing the absorption of phosphorus and thereby reducing the use of chemical fertilizers. A pot experiment was designed to determine the effect of two plant growth-promoting rhizobacteria and their co inoculation on growth criteria of Canola (Brassica napus L.) plant. The result of this pot study showed that inoculation with two plant growth-promoting rhizobacteria (Azotobacter chrococcum and/or Alcaligenes faecalis) increased crop productivity and showed the enhancement in the soluble sugars and proteins even in the saline soil. This review shows that the use of phosphate solubilizing microorganisms as a biofertilizers which are environment friendly instead of chemical fertilizers is beneficial for the future aspects and use of halotolerant plant growth-promoting rhizobacteria increase the growth of crops under salinity stress condition.

Implementation and Performance Analysis of Reconfigurable Montgomery Modular Multiplier

Authors- M.Tech. Scholar Shunhangini Singh, Asst. Prof. Priyanka Jain, Dr. Anshuj Jain(HOD)

Multiplier plays a key operation to check the performance of any processor. This work proposes a simple and efficient Montgomery multiplication algorithm such that the low-cost and high-performance Montgomery modular multiplier can be implemented accordingly. The proposed Montgomery modular multiplier receives and outputs the data with binary representation and uses only one-level carry-save adder (CSA) to avoid the carry propagation at each addition operation. Experimental results show that the proposed Montgomery modular multiplier can achieve higher performance and significant area time product improvement when compared with previous designs.

Survey Paper on Reversible Arithmetic Unit Based on Programmable Gate Structure

Authors- M.Tech. Scholar Sameer Suman, Dr. Anshuj Jain (HOD)

Power crisis is a vital problem in today’s world. In recent years, the growing market of electronic systems suffers from power dissipation and delay removal problem. Bennett et al. proved that the one-to-one mapping between the inputs and outputs of reversible circuit drastically reduces the power consumption and delay consumed of a circuit. There are four major design parameters of reversible circuits. First is the gate count which is the number of gate are used in the circuit. Second is the quantum delay. Third is the number of ancilla inputs which are constant inputs which are used to maintain the reversibility of the device. Fourth is the number of garbage outputs i.e. output signals which are not used as inputs to other gates and are only there to maintain reversibility. In this paper the survey of design central processing unit based on reversible gate and parameter.

Design and Implementation of Data Mining Techniques Used In Criminal Activities for Predictive Analysis

Authors- M.Tech. Scholar Meenu Rai, Associate Prof. Bhawana Pillai

In most of the crime detection and hotspot analysis methods, the crime data are processed using different processing techniques to provide accurate analysis. However, there are many problems that lead to poor performance. The major limitations in the literature are the class imbalance problem and multi-objective problems that occur due to the varying classes resulting in the generation of wrong synthetic minority samples. The utilization of graph based clustering methods results in complete graph processing even when the graph has minor changes, thus becoming complicated for further use. The class imbalance problem has to be resolved and the accuracy of the clustering is needed to be enhanced by introducing an efficient integrated sampling and clustering approach for effective serial crime detection. The near-optimal crime detection is needed to be enhanced by not only considering the crime data but also the social crime datasets collected, thus improving the chances of serial crime detection.

A Implementation of Fiber Reinforced Concrete Using Glass Fiber Reinforced Concrete (GFRC)

Authors- Abdul Rasheed, Asst. Prof. Anuj Verma, Asst. Prof. Mohd Rashid

Fiber reinforced concrete (FRC) is Portland cement concrete reinforced with more or less randomly distributed fibres. Glass fiber reinforced concrete (GFRC) comprises hydration products of cement, or cement plus sand, and the glass fibers. Glass fibers are used are used as reinforcement for concrete. The experimental program is designed to check the effect of length of glass fiber on mechanical properties on M30 grade of concrete i.e. workability, compressive strength, split tensile strength and flexural strength and results will be compared with conventional concrete. Total 17 cubes of size 150mm x 150mm x 150mm, 17 beams of size 100mm x 100mm x 500mm and 17 cylindersof size 150 mm diameter and 300 mm height were casted and tested. It is found that The addition of glass fibers to the concrete not only modifies various properties of concrete like tensile strength, compressive strength but also enhances the binding properties, micro cracking control and also increases spalling resistance. The crack width is reduced to a greater extent. It imparts ductility to a certain extent which can be seen in experimental testing of beams. It tends the beam to bend and thus warning well before failure thereby enhancing safety.

A Analysis Of Collapse Behavior Of G+3 Rcc Building

Authors- Research Scholar Vikalp Sankla, H.O.D Rahul Sharma, Prof. Akash jaiswal

The structural behavior and analysis of multi-storey building components and supporting transfer girders have received added emphasis due to its importance in connection with buildings. The supported transmitter girder acts as either a full-tension member, deep beam, or as a normal beam bent, based on the shape of the upper framework and relevant requirements, including the depth ratio of the transmitter girder (distance), rigidity of the support column, and shear-wall thickness. Progressive collapse is one of the main reasons for the failure of structure. It takes place through burn, blow, or vehicle impact due to removal/ harm to a column or shear wall. This research tested the vulnerability of the structure to progressive collapse using ETABS. Progressive collapse load combination was implemented in compliance with GSA directives. At the floor level and basement of the building corner, edge, and medium columns were withdrawn separately. In order to enhance building efficiency during earthquakes, viscoelastic dampers may be used. The impact of viscoelastic dampers on the progressive resistance to collapse is measured in the present analysis. For critical systems, this analysis may be helpful.

Lived Experiences of the Elementary Teachers in a Remote School

Authors- Edna B. Equipado, Sherill Asis-Gilbasjaiswal

This study determined the lived experiences of elementary teachers in Cawayan Elementary School. It utilized qualitative research methods and applied phenomenological approach. The six teacher participants came from a chosen and identified remote school, Cawayan Elementary School in Irosin, Sorsogon. The main instrument used in this study is the interview schedule and guide questions prepared by the researchers. The guide questions are focused on the lived experiences in terms of daily sustenance, transportation, security, community relationship and how those factors affected their delivery of instruction. Certain theme was identified under each category. It was concluded that the lived experiences of the elementary teachers directly affected their delivery of instruction. The proposed three- year development plan based on the project PAGMANGNO includes wellness programs on both physical and mental health that may be organized by the respective DepEd districts particularly for de-stressing of the teachers assigned in remote areas.

Production Planning and Process Improvement in Shop Floor towards Productivity Improvement

Authors- M.Tech. Scholar Sourabh Khare, Prof.Sachin Jain

Production planning critically enables a business to balance capacity with demand so maximising its potential by using the most effective process and managerial operations, with a strong workforce, robust controls, happy customers and optimal profits. The aim of this study is to study and implement the lean tools and to reduce lead time without much affecting the current working systems in a small scale automotive component manufacturing industry. In this study, an attempt was made in increasing the capacity of a machining cell with appropriate lean techniques. The enhancement of capacity was to be completed with zero capital investment. Findings: A lean approach by using value stream mapping and line balancing was adopted to improve the performance of the manufacturing cell. By collecting the past production data and deciphering the information, gaps were identified for enhancement. Single Minute Exchange of Dies (SMED) was used to regulate the production and Kaizen was also introduced in all work stations. Leveled operator loading for output consistency was suggested. Finally capacity intensification was achieved without any major capital investment. Application/Improvements: Implementation of lean tools reduced the setup time and idle time. The overall lead time got reduced from 6.9 days to 3.6 days and total cycle time got reduced from 170 to 140 minutes and the customer demand was also met on time by the execution of lean tools.

Optimization of Process and Flow Of Goods In Logistics Supply Chain Management

Authors- M.Tech. Scholar Kamlesh Thakre, Prof.Sachin Jain

Logistics management is the part of supply chain that arranges, actualizes, and controls the proficient, powerful forward, and turns around stream and capacity of merchandise, administrations, and related data between the purpose of inception and the purpose of utilization with a specific end goal to meet client’s requirements. The main goal of the study is to investigate the implementation of bearing material supply system in local industry with simultaneous pick-up and delivery within time limitation and examine its effects on overall performance and total cost. Our aim is that the conduction of the research provides optimization of the supply chain network for the development of bearing logistics in industry as an alternative system.

To Investigate Some Critical Risk Factors in Supply Chain Management

Authors- M.Tech. Scholar Abhishek Chourey, Prof. Sachin Jain

SCM is a cross-function approach including managing the movement of raw materials into an organization, certain aspects of the internal processing of materials into finished goods ,and the movement of finished goods out of the organization and toward the end-consumer. The prime objective of this study is to Study of critical risk factors in SCM and To examine the effectuation of cost in SCM. The role of various critical risk factors in the manufacturing productivity in the organizations is also analyzed. . The literature review has indicated that there is less use critical risk factors in the small scale industries. In this study, initiative has been taken to implement the various risk factors in the manufacturing industries. After identification of the rese arch gaps, the objectives of the study are formulated. This analysis yielded some useful results which are implemented to improve the existing processes.

Survey on Optimizing Headway using Communication Based Train Control system

Authors- Student Amit Shrivastava, Prof. Anshuj Jain, Prof. Ankit Tripathi

The CBTC System should adopt and develop an information security framework, security plan and a thorough SDLC process that integrates risk management for protection against malicious and inadvertent manipulation of data transmitted over ISM bands to maintain the confidentiality, availability and/or integrity of CBTC and wireless data transmission. This plan must be regularly reviewed, updated and accepted through a process of security certification, access control, gateway security, communications security, physical security, accreditations and certifications. The manipulation may be caused by malicious activity like intrusion, hacking, phishing, wireless signal jamming, physical tampering, damaging critical communication cable or nodes; accident or natural disaster. demonstrate practically, the ability of the system to proactively detect, contain, eradicate and recover from a security breach. The CBTC shall define procedures for assured operations and continuous monitoring of the security controls.