bluuebunny/crossref_metadata_2025 huggingface dataset:
Computational Modeling on Heat Transfer Enhancement and Fluid Flow Behavior of Al 2 O 3 Water Nanofluid through a Circular Duct
Authors:   School of Mechanical Engineering, KIIT University, Bhubaneswar, India., Ghose Prakash , Sahu* Kunja Bihari ,   School of Mechanical Engineering, KIIT Deemed to be University, Bhubaneswar, India., Sahu Ajay Kumar ,   School of Mechanical Engineering, KIIT University, Bhubaneswar, India.
Published: March 2020

In this work, heat transfer behaviour from a isothermal-walled micro channel has been investigated by using Al2O3-water nanofluid as working fluid. A computational simulation has been carried out for high Reynolds number flow, having different volume fraction of nanoparticles added to it such as; 0%, 1%, 4% and 6%. It has been observed that the properties such as; density, thermal conductivity and viscosity increase with increase in nanoparticles. On the other hand, with increase in the volume fraction of nanoparticles, the specific heat decreases. It also has been observed that the heat transfer from the hot wall increases with Reynolds number and addition of nanoparticles to the nanofluid as well. The friction factor for the flow system decreases with increase the Reynolds number, but for different nanofluids its value is very much closer to each other. With increase in volume fraction of nanoparticles, the pumping power increases. Moreover, with increase in Reynolds number, pumping power increases.
Critical Findings on Restoration of Magnetic Resonance Images
Authors:   Research Scholar, School of Computer Science and Engineering at Lovely Professional University, Punjab., More* Sujeet , Singla Dr. Jimmy ,   Associate Professor, School of Computer Science and Engineering, Lovely Professional University, Punjab.
Published: March 2020

The explosion of numerous medical images lead to the development of many different techniques to provide an accurate result. Although the signal to noise ratio (SNR), resolution and speed of magnetic resonance imaging technology have increased, still magnetic resonance images are affected by noise, contrast, and artifacts. To provide the image content or features relevant to diagnosis, contrast enhancement and reduction of noise with preservation of actual content should be carried out. The purpose of this paper is to present a critical review of different types of noises with an overview of diverse techniques for denoising and contrast enhancement for magnetic resonance images and discuss the advantages and limitations of these techniques with broad ideology.
Effect of Refrigeration and Air Conditioning Faculty Development Training Programme on Technical Teachers
Authors:   Department of Mechanical Engineering, NITTTR, Chennai, Tamil Nadu, India, Kumar* M. Senthil
Published: March 2020

Teacher Training is needed for teachers those teaching technical subjects. Pedagogical training programmes and subject knowledge enhancing training programmes are necessary for technical teachers. Nowadays, skill oriented training programmes are essential for polytechnic, engineering and other technical institute teachers. In teaching profession, faculty development training programmes are important for career development and content updating. In this paper, the content updating training programme in Refrigeration and Air conditioning was taken and discussed the knowledge enhancement of the teachers by conducted the evaluation tests before and after the training programme. The knowledge of the teachers in refrigeration and air conditioning areas were improved due to this faculty development programme.
Hybrid CNN Classification for Sentiment Analysis under Deep Learning
Authors:   Research Scholar, School of Computer Science and Engineering, VIT University, Chennai, India., D.* Christy Daniel , L. Shyamala ,   Associate Professor, School of Computer Science and Engineering, VIT University, Chennai, India.
Published: March 2020

Sentiment Analysis (SA) is a popular field in Natural Language Processing (NLP) which focuses on the human emotions by analyzing the lexical and syntactic features. This paper presents an efficient method to find and extract the strong emotions for the sentiment classification using the proposed hybrid Convolutional Neural Networks - Global Vectors - Complex Sentence Searching - ABstract Noun Searching (CNN-GloVe-CSS-ABNS) model. The strong emotions are mostly found in the abstract nouns than the adjectives and adverbs present in the sentences. This research aims in extracting the complex sentences with abstract nouns for the sentiment classification from the twitter data. To extract the complex sentences, the proposed Complex Sentence Searching (CSS) algorithm was used. On the other hand, another proposed algorithm named, ABstract Noun Searching (ABNS) algorithm was used for identifying the abstract nouns in the sentences based on their position in the sentences. The results of this study presents that the proposed CNN-GloVe-CSS-ABNS model outperforms the other proposed models as well as the existing models, by producing an of accuracy 94.87 per cent in sentiment classification.
Performance Analysis of 33KW Grid Connected Solar Roof Top Power Plant
Authors:   EEE Department, S.R.K.R Engineering College, Bhimavaram, India., Rao* Yadavalli S V Venkateswara , Veerraju Dr. M Sai ,   EEE Department, S.R.K.R. Engineering College, Bhimavaram, India.
Published: March 2020

Solar Roof tops are being progressively used worldwide now a days to install solar panels to generate electricity. One such step has been taken by S.R.K.R Engineering College to generate power through solar roof tops by installing a 33KWp On-grid solar power system (Latitude 16.54° N and Longitude 81.50° E) during April-2016. This grid connected PV system is installed at an area of 345 sq. m and the PV modules are tilted at an angle of 18° on the top of a 3 staired building. This paper analyses the Performance of a 33KWp On-grid photovoltaic system which is monitored between Jan-2019 to Dec-2019. Some part of electricity generated by the system is consumed by the college and the remaining power was fed in to the state grid. The tariff for the grid connected system is based on the energy consumed from the grid and the energy supplied in to the grid. The data is collected from the Data-logger of the inverter which is having an IP address. This data is collected according to the IEC protocol which suggests to collect the data for every 15 minutes. The data is collected from the inverter in this format and is stored as a csv file every day. This data along with the meteorological data collected from the coordinates of the site are analyzed by using pvsyst simulation software. The performance of this system is found for the third year in operation. . The analysis of the PV system has been done to enumerate its performance at each and every component and thereby develop solution to mitigate the problems. The different parameters including efficiencies of panels, inverter, array’s initial yield, final array yield, and the performance ratio of PV system are analyzed.
GA SMC Technique for Photovoltaic Systems under Non Homogenous Meteorological Conditions
Authors:   Department of Electrical Engineering, Mohammadia School of Engineering, Mohammed V University of Rabat, Rabat, Morocco., Ahmed* Cheikhne Cheikh , Cherkaoui Mohamed ,   Department of Electrical Engineering, Mohammadia School of Engineering, Mohammed V University of Rabat, Rabat, Morocco., Mokhlis Mohcine ,   Department of Electrical Engineering, Mohammadia School of Engineering, Mohammed V University of Rabat, Rabat, Morocco., Bahij Mouad ,   Department of Electrical Engineering, Mohammadia School of Engineering, Mohammed V University of Rabat, Rabat, Morocco.
Published: March 2020

When the photovoltaic sources are subjected to the partial shading (PS) effect, the PV modules are consequently subjected to the different levels of the irradiation. Indeed, when the phenomenon of the partial shading occurs, the Power-Voltage curve of the PV panel presents several points of maximum power. These points are divided between local and global, where the global maximum point presents the superior maximum, and the local maximum points present the inferior maximums compared to the global one. In fact, the classical Maximum Power Point Tracking (MPPT) techniques can not distinguish the global maximum power point, but can track only the first maximum found at the right hand of the Power-Voltage curve. Thus, in some cases, the classical techniques can cause the high drop of power. To solve this issue, this paper proposes a new approach based on the genetic algorithm (GA), because of its ability to optimize the solar panels’ output power production under the PSC. This optimization method is combined with the robust Sliding Mode Controller (SMC). Here, the GA is used in order to locate and generate the reference voltage corresponding to the global maximum power. While the sliding mode controller is used in order to track the reference voltage by acting on the duty cycle of the SEPIC converter. To examine the performance of the proposed method, the comparison with some hybrid controller, which are P&O-SMC, P&O-BSC, INC-BSC and INC-SMC, is performed. The results show the tracking performances of the proposed method, which are the accuracy and rapidity. Moreover, the results illustrates the ability of the proposed hybrid controller to detect the partial shading and to distinguish the Global Maximum Power Point.
Hybrid Response Surface Method African Buffalo Optimization Technique for Ultrasonic Production of Biodiesel from Waste Cooking Oil using Li doped CaO Nan o catalyst
Authors:   Mechanical Engineering Department, Sant Longowal Institute of Engineering and Technology, Longowal-148106, Sangrur District, Punjab, India, Kumar* Upender , Gupta Prof. Pardeep ,   Professor and Dean, Mechanical Engineering Department, Sant Longowal Institute of Engineering and Technology, Longowal-148106, Sangrur District, Punjab, India
Published: March 2020

In the current era, there is an increasing emphasis on green fuels for a clean environment. Authors in this work have tried to devise an innovative method to optimize ultrasonic production of biodiesel from used cooking oil, using composite technique combining Response surface Methodology and African Buffalo optimization. In this research work, heterogeneous catalyst Lithium doped CaO has been obtained from a new natural source by high-temperature thermal decomposition of Musa Balbisiana root ash and tested its Conversion efficiency for conversion of waste cooking oil into methyl esters. It was observed that the catalyst is really effective for the production of biodiesel from even high Free Fatty Acid waste cooking oil. For optimization of production parameters authors have used ABO complemented with RSM to maximize the biodiesel production yield. The maximum biodiesel yield of 96.67% was achieved using ABO which is about 15% higher than provided by RSM which is 81.01%. The highest biodiesel yield of 96.67 % is obtained at 15:1 Molar Ratio with 3.5% catalyst wt. percent, 60 Degree C Temp. in 45 Minutes with an error of 2.5 % in yield prediction by ABO. The work may be utilized by industries and researchers to use ultrasonic reactors optimally to extract better biodiesel volume in very short time instead of presently used slow mechanical stirring tank reactors.
Churn Prediction using Machine Learning-An Analytical CRM Application
Authors:   Assistant Professor in Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India., Margret* Ms. M. Kavitha , Monishapriyadharshini Ms. M. ,   IV year CSE, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India., Nathies Mr. S. ,   IV year CSE, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India., Sriram Mr. C. ,   IV year CSE, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India.
Published: March 2020

CRM represents (Customer Relationship Management).It is a classification of programming that covers many arrangement of utilizations that are intended to support organizations and furthermore to oversee huge numbers of the business forms like client information. CRM framework models incorporate stages worked to oversee advertising, deals, client support, and backing, all associated with assistance organizations work all the more viably. With a CRM framework, organizations can dissect client collaborations and improve their client connections. The data based forecast models utilizing AI systems have increased monstrous prevalence during the most recent couple of decades. These models have been applied in enormous number of areas like clinical conclusion, wrongdoing expectation, films rating, and so forth. Thus it is utilized in telecom industry where models of expectation have been applied for the forecast of not fulfilled clients who are probably going to change the administrations and furthermore the specialist organization. In telecom the money related expense of client agitate is tremendous henceforth numerous organizations have examined different variables, (for example, cost of the call, nature of the call, client assistance reaction time and so on.) utilizing different AI strategies. This work proposes different ML strategies for client agitate expectation.
Effect of Natural Fibers Composites as Soil Stabilizer on Flexible Pavement Design
Authors:   Assistant Professor, Department of Civil Engg, St Joseph’s College of Engineering, Chennai, India., P* Sribalaji , S Banupriya ,   Assistant Professor, Department of Civil Engg, St Joseph’s College of Engineering, Chennai, India., R Ruthra ,   Assistant Professor, Department of Civil Engg, St Joseph’s College of Engineering, Chennai, India.
Published: March 2020

The primary function of road pavement is to distribute and transmit the wheel loads at the surface to a sufficiently large area of sub grade without failure or excessive deformation. The sub grade must be stable, unyielding, properly drained and free from volume changes due to the reasons such as structural, functional, or materials failure, or a combination of these. This project is being developed to be implemented in Perur – Ukkadam by-pass road of Coimbatore,Tamilnadu, India . It is around 2.2 Kms in length. In the study area, it is observed that the pavement failure is under the category of swelling and shrinkage characteristics of soil. To overcome this failure, its necessary to improve the bearing capacity of sub grade soil . For this purpose the Natural Fiber Composites (Coir & Sisal) were used in improving the soil bearing capacity and checked for CBR test to design flexible pavement. Thus this study shows the effectiveness of Natural Fiber Composites (Coir & Sisal) in improving performance characteristics of pavements.
Machine Learning Models for Relevant Feature Identification and Classification of Thyroid Data
Authors:   Department of Computer Technology-UG ,Kongu Engineering College,Perundurai,Erode,TamilNadu,India., Nandhinidevi* S. , Poorani S. ,   Department of Computer Technology-UG ,Kongu Engineering College,Perundurai,Erode,TamilNadu,India., Brindha P. Gokila ,   Department of Computer Technology-UG ,Kongu Engineering College,Perundurai,Erode,TamilNadu,India.
Published: March 2020

Inappropriate creation of thyroid glands turn into prime subject of concern amongst Indian women. The two key chaos of thyroid which ought to be taken care at the earliest are hypothyroidism and hyperthyroidism. The improper secretion of thyroid may leads to obesity, fertility related problems, feeling depressed, etc,. Most of the thyroid problems can be managed if it has been properly treated. In recent years a number of models have been developed to investigate the thyroid-disorder. The laboratory tests are conducted to find the levels of the hormones and some of the physical examinations are used to identify the presences of thyroid. These examinations and test results are taken as the feature for developing the model. The feature importance can promote the performance of ML algorithms. The core intention of this study is to improve the classification performance by identifying the relevant features before classification. In this work, random-forest model is considered for identifying the important features and KNN algorithm is implemented for multiclass-classification to envisage the kind of thyroid chaos. Applying KNN after the feature selection improves the prediction accuracy. The developed model can be used to predict the presence of thyroid so that it can be treated accordingly.
Power Management in Hybrid Microgrid
Authors:   Research Scholar, Gujrat Technological University, Ahmedabad, India, Karkar* Hitesh M. , Trivedi Indrajit N. ,   Professor, Department of Power Electronics, Vishwakarma Government Engineering College, Ahmedabad, India., Ghosh Prasanta K. ,   Professor, Department of Electrical Engineering & Computer Science Syracuse University, Syracuse, New York, USA.
Published: March 2020

This paper is representing power management in a hybrid microgrid. The hybrid microgrid consists of PV, wind, battery, and grid. The power management strategy is mentioned in islanding and grid-connected mode. In a grid-connected system, the grid converter has to monitor and manage the power to flow between microgrid and grid. The voltage shifting based droop control technique is used in DG for proper load sharing when two sources are connected in parallel. DG units in hybrid microgrid have two switching modes including droop control and maximum power tracking (MPPT). The operation of a hybrid microgrid is operated in different thee mode. The bus voltage is the main carrier to switching the mode of a hybrid microgrid. The power management algorithm for hybrid microgrid described here. This renewable-based hybrid microgrid model can be used for different aspects like small residential and commercial buildings. The feasibility and effectiveness of this strategy for hybrid microgrid running in various modes verified by simulation result.
Enhanced Techniques for Opinion Mining
Authors:   Department of Computer Science, Bishop Heber College , Tiruchirapalli, India., Priya* R.Cynthia Monica , Sathiaseelan Dr.J.G.R. ,   Department of Computer Science, Bishop Heber College , Tiruchirapalli, India.
Published: March 2020

The exponential growth of online information sharing has led to the need to analyze them. Opinion Mining or Sentiment Analysis incorporates a systematic approach to favor analysis of the available online synthesized data .This paper includes a lexicon based approach towards analysis. The proposed SLN (Slang Negation) Algorithm follows a lexicon based approach to Opinion Mining. The slang lexicon provides the expansion of the acronyms and their scores. Three types of negations namely explicit, implicit and pseudo negation are handed. Slang and negation handling are necessary to support semantic orientation. The proposed SLN algorithm has shown significant improvement in the precision, recall, f-measure and accuracy values as compared to the use of sentiment lexicon approach.
Speech Classification for Kannada Language
Authors:   Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte, India., Rao* Supriya B , Hegde Sarika ,   Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte
Published: March 2020

Speech classification is one of the challenging issues in speech processing. In this paper, we have done speech classification for the Kannada language. We have gathered a speech database from children aged 4-6 years. The dataset collected are pre-processed and speech feature extraction is done using Mel Frequency Cepstral Coefficients (MFCC) technique. After feature extraction Kannada alphabets are classified using six different Machine Learning (ML) classifiers. The classifier accuracies are compared with each other. Amongst the Deep Learning classifiers, Recursive Neural Network (RNN) gave the highest accuracy of around 93.6 %( for 300 epochs) and Random Forest (RF) gave the highest accuracy of around 88.9% which is a Machine Learning classifier.
Simulation of Phase Angle Control and Condition Based Synchronization Techniques for Parallel Inverters
Authors:   Asst Prof, Department of EEE, Bannari Amman Institute of Technology, Sathy, Tamilnadu, India., Kumar* K V Santhosh , Kumar R Senthil ,   Professor, Department of EEE, Bannari Amman Institute of Technology, Sathy, Tamilnadu, India., Raja T Alex Stanley ,   Asst Prof, Department of EEE, Bannari Amman Institute of Technology, Sathy, Tamilnadu, India., Nandhakumar A ,   Asst Prof, Department of EEE, Bannari Amman Institute of Technology, Sathy, Tamilnadu, India.
Published: March 2020

Parallel connection of inverters is one useful method for solving the high power requirements. It reduces the current stress on inverter switches and makes the way for continuous supply to the load.Though any one of the inverter supplying the load gets faulted, the other inverter connected would supply the load. But the problem in this kind of set up is that it needs synchronization techniques for parallel operation or else the inverters will operate in unsynchronized manner and the supply would be in distorted form for the motor load leading to overheating of the load. This paper proposes two software drive control techniques for the parallel operation of inverters in synchronized condition.These software techniques are implemented and results are analysed in the MATLAB environment.
Effect due to Variation in Bend Angles of Intake Manifold on Turbulent Kinetic Energy for Diesel Engine
Authors:   Research scholar, Department of Mechanical Engineering, Jamia Millia Islamia (a central university) in New Delhi, INDIA., Haider* Abidi Shahim , M.M Hasan ,   Senior Professor, Department of Mechanical Engineering, Jamia Millia Islamia (a central university) in New Delhi, INDIA.
Published: March 2020

One of the positive results for enhancing turbulence is to improve swirl, which is an important factor of air motion in a diesel engine. Other than enhancing mixing and improvement in combustion processes it also influences heat transfer, combustion quality, and engine raw emissions. To improve swirl intensities in-cylinder parameters like velocity, pressure, temperature and turbulence intensity are to be considered. There are two ways to create a swirl, modification in the intake system and valve design. So this work done contains modifications in the design of manifold to enhance turbulence during the intake stroke. Designs of manifold having different bend angle of 15o, 30o, 45o, 60o and 75o were used, all parts of numerical analysis were carried out on Ansys Fluent. The 200mm long intake model having a 20 mm diameter, with a bend on 160mm along length was used to find out the best bend angle configuration from the above orientations. K-epsilon model was used to simulate flow dynamics; variations turbulent kinetic energy was studied. After analyzing these results it was concluded that best-optimized design (in terms of turbulent kinetic energy) to get better swirl was for 75o. This work gives the understanding to find new techniques for further improvement in mixing by increasing turbulent kinetic energy. This work emphasizes on the techniques to enhance turbulent kinetic energy of any flow, and can also be applied to different fields related to mixing of fluids other than diesel engine.
Improving Processing Speed of Real Time Stereo Matching u sing Heterogenous CPU GPU Model
Authors:   Systems and Computers Engineering Dept. , Faculty of Engineering , Al-Azhar University, Cairo, Egypt., Al-Marakeby* A. , Zaki M. ,   Systems and Computers Engineering Dept. , Faculty of Engineering , Al-Azhar University, Cairo, Egypt.
Published: March 2020

This paper presents an improvement of the processing speed of the stereo matching problem. The time required for stereo matching represents a problem for many real time applications such as robot navigation , self-driving vehicles and object tracking. In this work, a real-time stereo matching system is proposed that utilizes the parallelism of Graphics Processing Unit (GPU). An area based stereo matching system is used to generate the disparity map. Four different sequential and parallel computational models are used to analyze the time consumed by the stereo matching. The models are: 1) Sequential CPU, 2) Parallel multi-core CPU, 3) Parallel GPU and 4) Parallel heterogenous CPU/GPU. The dense disparity image is calculated, and the time is highly reduced using the heterogenous CPU/GPU model, while maintaining the same accuracy of other models. A static partitioning of CPU and GPU workload is properly designed based on time analysis. Different cost functions are used to measure the correspondence and to generate the disparity map. A sliding window is used to calculate the cost functions efficiently. A speed of more than 100 frames per second(f/s) is achieved using parallel heterogenous CPU/GPU for 640 x 480 image resolution and a disparity range equals 50.
Factors A ffecting Farmer ’Autonomy and Sustainability of Smallholder Coffee Farming u sing SEM Lisrel
Authors:   Department of Agricultural Extension, Faculty of Agriculture, Jember University, Jember, Indonesia., Sudarko*  , Sumardjo*  ,   Department of Communication Science and Community Development, Faculty of Human Ecology, IPB University, Bogor, Indonesia., Fatchiya Anna ,   Department of Communication Science and Community Development, Faculty of Human Ecology, IPB University, Bogor, Indonesia., Tjitropranoto Prabowo ,   Department of Communication Science and Community Development, Faculty of Human Ecology, IPB University, Bogor, Indonesia.
Published: March 2020

Coffee is an important commodity in international trade. However, coffee farming in Indonesia is mostly managed by smallholder farmers who still apply traditional technology. This study was aimed to: (1) analyze the level of institutional role, agribusiness capacity, autonomy of farmer, and sustainability of smallholder coffee farming; (2) analyze factors affecting autonomy of farmers and sustainability of smallholder coffee farming. This research was carried out in Bondowoso and Malang Regency, East Java, Indonesia through the approach of survey conducted on 376 coffee farmers of all smallholder farmings of Robusta and Arabica coffee. Samples were collected by multistage random sampling done in the two regencies. Survey method was used in this study. Data were collected during July-October 2019 using the method of questionnaire, interview, and observation. Data were analyzed by descriptive and inferential method through SEM Lisrel. Result of the study showed that institutional support was categorized as low, while agribusiness capacity, autonomy of farmers, sustainability were included in moderate category. Factors found to affect the level of farmer’ autonomyof farmers were the support of institutional role and agribusiness capacity of farmers. Factors directly affected the sustainability of smallholder coffee farming was autonomy of farmers, whereas the role of institution and agribusiness capacity of farmers were found to indirectly affect sustainability. To strengthen autonomy of coffee farmers towards the sustainability of smallholder coffee farming, agribusiness capacity building and strengthening is necessary. Therefore, all stakeholders (government, private institution, and community) will immediately design such program that involves the synergy of multi-institutions related to smallholder coffee farmers.
Fast Encryption f or Multi Hop Wireless Sensor Networks u sing Gaussian Transposition Cipher
Authors:   Department of CSE, St. Ann’s College of Engineering and Technology, Chirala, India, Thirupathaiah* Dr. Amarthaluri , Venkateswarlu IB ,   Department of CSE, St. Ann’s College of Engineering and Technology, Chirala, India
Published: March 2020

Wireless sensor network research enriched with diverse applications from industry to daily life. Widespread of sensor-based applications mandated for user authentication and secure communication. However, sensor nodes are limited energy and resources and hence secure communication for sensor nodes became a challenging task. This paper presents a fast encryption scheme for secure communication in wireless sensor networks. The proposed scheme consists of three phases namely registration, network deployment, and data transmission. In this work, a Gaussian transposition cipher for the generation of strong key. This cipher uses Gaussian noise, modified rail fence cipher and transposition. Fast encryption has achieved using XOR-based encryption and hence the proposed scheme incurs low computational cost. The proposed scheme resistant to various security attacks.
Electric Vehicles Acceptance and Knowledge Identification in India using Naive Bayes and k-Nearest Neighbor Classifiers
Authors:   PG Student, Department of Computer Science and I.T., Amrita School of Arts and Sciences, Kochi, India., R.* Vishnu M. , Ashok Rahul ,   PG Student, Department of Computer Science and I.T., Amrita School of Arts and Sciences, Kochi, India., Nitha L. ,   Assistant Professor, Department of Computer Science and I.T., Amrita School of Arts and Sciences, Kochi, India.
Published: March 2020

In order to identify the effect electric vehicles have made in India, we ensue a survey under trend analysis to find a panacea and overall understanding people have about electric vehicles. We used Naive Bayesian and k-Nearest Neighbor for analyzing customer opinion regarding the use of electric vehicles. As pollutants keep on polluting the aerosphere it's more and more appropriate to start using electric vehicles. Electric vehicle support in India is low as of now but is expected to have sufficient support as of 2030. The main objective of our research is to identify the electric vehicles acceptance by people and to identify the knowledge people have about electric vehicles. The result was mainly based on retail price and sufficient support being made available. We used Weka 3.8.4 for experimenting the result. The results found out that positive environmental effects on a large amount of customers for choosing electric vehicles. Customer focuses on price and appropriate charging facilities while they choose to buy electric vehicles. In finding the result, the k-nearest neighbor method showed more accurate results than Naive Bayes when done on large datasets.
Task Based V irtual M achine Placement in Cloud
Authors:   Department of CSE, Koneru Lakshmaiah Educational Foundation, Guntur, India., Rao* D. Babu , Sri Ch. Swathi ,   Department of CSE, Koneru Lakshmaiah Educational Foundation, Guntur, India, Babu V. Rajesh ,   Department of CSE, Koneru Lakshmaiah Educational Foundation, Guntur, India, Rao S. V. Koteswara ,   Department of CSE, Koneru Lakshmaiah Educational Foundation, Guntur, India
Published: March 2020

Cloud computing offers many advantages by optimizing various parameters to meet the complex requirements.Some of the problems of cloud computing are utilization of resources and less energy consumption. More research and resources heterogeneity complicates the consolidation problem inside cloud architecture. VM placement refers to an ideal mapping of a task to virtual machines (VM) and virtual machines to physical machines (PM). The task-based VM placement algorithm is introduced in this research work. Here tasks are divided in accordance with their requirements, and then search for appropriate VM, again searching for appropriate PM, where selected VM could be sent. The algorithm decreases the use of resources by devaluation of the number of dynamic PMs while further decreases the rate of dismissal of make span and assignment. CloudSim test System is used to evaluate our algorithm in this research work. The outcomes of this implementation show the effectiveness of some current algorithms such as Round robin and Shortest Job First (SJF) algorithms.
Automated Software Design Reusability using a Unique Machine Learning Technique
Authors:   Associate Professor, Department of Information Science and Engineering, New Horizon College of Engineering,, Mangayarkarasi* Dr. P.
Published: March 2020

The era of machine learning (ML) has brought significant advancement into the traditional approaches of software development and services. Software reusability and design automation is a key requirement that can be handled through the integration of artificial intelligence (AI) capabilities with the traditional approach of software development lifecycle (SDLC) practices. The study introduces a novel approach of ML, which can assist inappropriate selection of reusable software components, which in the long run, can optimize the operational cost in the context of development practices and also speed up the service delivery performance of software engineering activities. The proposed model is validated through a numerical analysis that shows the effectiveness of the system in terms of both classification accuracy and computational efficiency.
Full and Reduced Reference Image Quality Assessment of Panoramic View using Novel Hybrid Image Stitching Method
Authors:   Department of Electronics and Telecommunication Engineering, Sandip Institute of Technology & Research Centre, Nashik, Affiliated to Savitribai Phule Pune University, Pune, India., Vaidya* Omkar S. , Gandhe Sanjay T. ,   Department of Electronics and Telecommunication Engineering, Sandip Institute of Technology & Research Centre, Nashik, Affiliated to Savitribai Phule Pune University, Pune, India.
Published: March 2020

Image Stitching is becoming more popular in field of computer vision because of rapid development of efficient algorithms that replaces the high cost wider lens cameras and commercial image stitching tools. The existing methods used global geometric transformation in registration stage and hence suffered from object deformation, parallax error, ghosting effect and motion blur in output result. In this paper, newly developed Hybrid Warping of weighted linearized homography matrix and similarity transform matrix is implemented over standard image stitching database. The visual quality of stitched image using proposed method has been examined in terms of performance metrics of Full Reference Image Quality Assessment (FRIQA) such as Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Reduced Reference Image Quality Assessment (RRIQA). Also, the performance analysis of proposed method is compared against existing image stitching methods in terms of field of view and stitching time. This analysis has ascertained the outperformance of Novel Hybrid Image Stitching method.
Charge Transport in Molecular Wire-Effect of Orientation
Authors:   Amardeep, PhD, Electronics Engineering, IKGPTU Jalandhar, (Punjab) India, Amardeep*  , Lamba Dr. Vijay Kumar ,   Professor, Global College of Engineering and Technology, Kahnpur Khui, (Punjab) India.
Published: March 2020

In this work, the novel method is introduced to simulate the electrical transport of nanoscale structures. We think of an open-ended quantum system (structural electrons) accelerated by the external energy from the electron and the energy that is dispersed by a small amount of heat using warm baths (electrons) operating in the electronics. We use periodic boundary conditions and use The Density Functional Theory to also eliminate the problem of multiple particles acting on a single-field field problem. By explicitly treating corruption in the electrodes, the behaviour of the powerful is the result of our approach, with variations in propagation methods based on the Landauer process.
Implementation of Iot Based Monitoring and Controlling Solar System
Authors:   Department of ECE, Parul Institute of Technology, Limada, Vadodara, Gujarat, India., Bhatiya Vinayak k. , Tank Bharat V. ,   Asst. Prof., Department. of ECE, Parul Institute of Technology, Limda, Vadodara, Gujarat, India., Sonawala Nishant ,   Managing Director, Sonawala Integrated Circuit Industries Private Limited., Bharuch, Gujarat, India.
Published: March 2020

The IoT based system sense, controlled or monitoring remotely to the existing over network structure. With help of IoT creating connectivity computer operated system. The IoT based monitoring and controlling solar system using this system online display uses of power, voltage, current, temperature, weather condition, tracking sun light and dust cleaning with help of wipers. All this monitoring and controlling is done through ATmega328 controller, ModBus to TTL convertor, ESP8266, etc. using this system monitoring to the analysis of the daily uses of data and controlling solar wipers and sunlight toward movement of solar panel.
Tourist ’s Translator based on Digital Image Processing and Hybrid Translation
Authors:   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India., Khan* Rijwan , Kaushal Aryan ,   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India., Agarwal Ayush ,   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India, Kumar Avdhesh ,   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India.
Published: March 2020

Being a tourist in a foreign country is not easy when it comes to getting familiar with the local language. From reading signboards to getting unfairly charged while shopping, booking cabs and hotels for their stay, roaming around for sightseeing, communicating with the locals, everything requires an understanding of the local language. Nowadays, everybody has a smartphone, which proves to be the most helpful tool for travelling purposes. We aim to build up an Android application that will be capable of translating text, voice, and also textual information written on signboards from native language to the desired language, users have to use their smartphone camera for signboard translation. We are using a hybrid machine translation approach for language translation. Text recognition from the captured images of signboards is done with the help of digital image processing. The purpose of this work is to reduce the failure of any single machine translation approach and to reduce miscommunication between tourists and the local people.
Pregnancy Assistance using Ai-Based Application
Authors:   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India., Khan* Rijwan , Singh Vartika ,   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India., Singh Sachin ,   Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, Affiliated to AKTU Lucknow, India.
Published: March 2020

With the onset of industrialization from the 18th century the family structure has drastically changed from the larger joint families to smaller nuclear families. The most affected people from this change are the ladies who are now left without any elderly guidance and support through pregnancy. We through our work aim to reduce this feeling and provide the basic help and care to these pregnant women. We are using a self-designed algorithm as a way to tackle this situation and help in providing proper guidance to all our users that are pregnant.
Geotechnical Characteristics of HNPC Fly Ash
Authors:   Professor & Head, Department of Civil Engineering, Anil Neerukonda Institute of Technology and Sciences, Sangivalasa, Bheemunipatnam Mandal, Visakhapatnam District-531162, Andhra Pradesh, India, N. D.* Dr. Narasinga Rao B. , P. Suryanarayana Raju ,   Engineering Assistant, Panchayat Raj, APPWD, Tallapalem, Visakhapatnam District-531162, Andhra Pradesh, India.
Published: March 2020

Fly ash is the solid waste being produced in largest quantities from thermal power plants in India causing pollution of land and water. It requires bulk utilization which is possible in geotechnical applications such as embankments and subgrades. This necessitates the determination of the geotechnical properties of fly ash from different thermal power plants. The present paper investigates the geotechnical characteristics of fly ash from HNPC, Pedagantyada, Visakhapatnam. The physical and index properties of HNPC Fly ash (HNFA) and its OMC and MDD using I.S. Heavy compaction are first determined. The shear strength, CBR and permeability are then determined at OMC. The study also investigates the influence of polyester fibers and lime as admixture to HNFA in different percentages on Compaction and CBR properties to check their effectiveness in improving HNFA for use in embankments and subgrade. The chemical and morphological characteristics of HNFA, including its specific surface, XRD, SEM and FT-IR spectra have also been determined. The study confirms the suitability of HNFA for use in geotechnical applications and verifies the relative suitability of polyester and lime as admixtures for further improvement of the geotechnical properties of HNFA.
Novel M ethod of Nanoparticle Synthesis using Surface Grinding
Authors:   Department of Mechanical Engineering, Periyar Maniammai Institute of Science & Technology, Vallam, Thanjavur, India., Shivakumar* N. , Ramesh Dr. T. ,   Department of Mechanical Engineering, National Institute of Technology, Tiruchirappalli, India., P. Amritha P. ,   TIFAC-CORE in Cyber Security, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India., P. K. Dr. Srividhya ,   Department of Mechanical Engineering, Periyar Maniammai Institute of Science & Technology, Vallam, Thanjavur, India., Pugazhenthi A. ,   Department of Mechanical Engineering, Periyar Maniammai Institute of Science & Technology, Vallam, Thanjavur, India., Manikandan S. P. ,   Department of Mechanical Engineering, Periyar Maniammai Institute of Science & Technology, Vallam, Thanjavur, India.
Published: March 2020

Nanoparticles are of most important in all the areas because of their varied and unusual properties. nano particles could be produced using top down and bottom up approaches. We present a novel method of synthesizing nanoparticles such as C, ZnO, Al, Fe2O3. The surface grinding was taken as a fundamental process inside the proposed Nano Particle Synthesizer (NPS). Parameters such as speed of the grinding wheel, feed rate and coolant feed rate could be used for fixing the dimension and specification of our nano particles synthesizing unit. After Passing through the NPS, particles of micro and nanoparticles were collected in glass plate and characterized using Scanning Electron Microscope (SEM) to confirm the size and shape of nano particles. This method could be employed as an alternative method to High Energy Ball Milling for producing high pressure and high temperature that favors the synthesis of nano particles in specific shape and size.
A Novel Frequency Reconfigurable Microstrip Patch Antenna using Pin Diode
Authors:   Electronics and Communication Engineering ,Sri Krishna College of Engineering and Technology, Coimbatore, India., Nandalal* Dr. V. , Indumathi G. ,   Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India., Suseendran G. ,   Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India., Janani A. Athithya ,   Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
Published: March 2020

In recent study, in the growth of wireless technology single antenna that works with a specific frequency is becoming outdated. The antenna which is capable to work dynamically is encouraged. To make an antenna to work dynamically, modification in any of the antenna characteristics can be applied. In this proposed work, the antenna which can reconfigure its frequency is designed and analyzed. Microstrip patch antenna is most popular printed type antenna which is suitable for diverse applications. The antenna design consists of three PIN diodes which are placed in different positions on the patch. Depending upon the switching state of PIN diode the antenna can operate in different frequency ranges. The frequency range obtained ranges from 1.38 GHz to 3.24 GHz. Return loss value, VSWR obtained is of optimum level. The various gain of antenna is obtained in simulation. The analysis of the antenna is done in ANSYS HFSS software.
Aspect Based Opinion Mining o n Mobile Product
Authors:   Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte, India., Abraham* Shiji , Abraham Minu P. ,   Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte, India., K. R. Uday Kumar Reddy ,   Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte, India., Rodrigues Anisha P. ,   Department of Computer Science and Engineering, NMAM Institute of Technology, Nitte, India.
Published: March 2020

In this era, the web technology is growing quickly. Many people express their feedback related to products, social issues and services. As e-commerce site is becoming more popular, the customer review related to the product grows quickly. Due to this growth it is very difficult for the customer to read huge amount of data and make a decision whether to buy a product or not. It is also very difficult for the manufacturer of the product in-order to manage and focus on customer opinions. In this research we focus on mobile product review which is extracted from Kaggle site. In this experiment we have focused on one particular mobile product review that is Samsung. After data collection we do pre-processing, and further we extract aspect and corresponding opinion using Natural language processing and then categorize whether the extracted opinion is positive or negative by finding polarity for each extracted opinion of words. Finally performance evaluation is done by using two machine learning algorithm i.e. Multinomial Naive Bayesian (MNB) and K-Nearest Neighbour (K-NN) algorithm. This performance evaluation is calculated based on bag of words. Out of two algorithms K-NN gave best accuracy compared to Multinomial Naive Bayesian.