bluuebunny/crossref_metadata_2025 huggingface dataset:
Stacked Bidirectional Long Short Term Memory Models To Predict Protein Secondary Structure
Authors:   Research Scholar, Computer Science and Engineering, Annamalai University, India., Thendral* R. , Sigappi AN. ,   Ph.D, Computer Science and Engineering from Annamalai University, India.
Published: January 2020

Protein Secondary Structure (PSS) is one of most complex problem in biology PSS is important for determining tertiary structure in the future, for studying protein fiction and drug design. However, Experimental PSS approaches are time consuming and difficult to implement, and its most essential to establish effective computing methods for predicting on protein sequence structure. Accuracy of prediction performance has been recently improved due to the rapid expansion of protein sequences and the design of libraries in deep learning techniques. In this research proposed a deep recurring network unit method called stacked bidirectional long-term memory (Stacked BLSTM) units to predict 3-class protein secondary structure from protein sequence information using a bidirectional LSTM layer. To evaluate the output of Stacked BLSTM, using publicly available datasets from the RCSB server. This study indicates that performance of our method is better than the of that latest stranded public dataset. The accuracy achieved is more than 89%.
Flower Recognition System Based On Image Segmentation Algorithms
Authors:   Assistant Professor, Department of Electronics And Telecommunication, Bharati Vidyapeeth (Deemed to be University) College Of Engineering, Pune, India., Sawant* Aarti
Published: January 2020

Image segmentation is now established as the robust technique in image processing. Important features from image are extracted by using image processing tool. In order to extract important features from an image, segmentation provides a rapid solution. Digitizing the image and differentiating it into multiple segments to outline region of interest is known as image segmentation. Segmentation algorithms are differentiated based on colour, gray values or textures of an image are discontinuity and similarity. In this article ,we present different segmentation algorithms along with their experimental results.
Classification using Artificial Neural Network Optimized with Bat Algorithm
Authors:   Computer Science Engineering,, GJUS&T, Hisar, India., Kumar* Mr. Narender , Kumar Dharmender ,   Computer Science Engineering,, GJUS&T, Hisar, India.
Published: January 2020

In machine learning, there are two approaches: supervised and unsupervised learning. Classification is a technique which falls under the supervised learning. Out of many classification models, the most popularly used is the Artificial Neural Network. While neural networks work fine in classification and training a machine, the accuracy of the result might still be under question. To improve the accuracy and speed of result, the optimisation of artificial neural network is done. For this, ANN can be hybridised with a metaheuristic algorithm known as the Bat Algorithm. The benefits of optimising a neural network are mainly the improvement in accuracy of classification, interpretation of the data, reduction in cost and time consumption for getting accurate results etc. In present paper, a comparison between the results of an ANN-Backpropagation model and the proposed ANN-Bat model is done for medical diagnosis. The results were in the favour of the ANN-Bat approach which was significant in reducing the time taken to yield an output as well as the accuracy.
Customer Churn Prediction and Upselling using MRF (Modified Random Forest) technique
Authors:   Asst. Professor, Department of CSE, Rajarajeswari College of Engineering Bangalore, India., P* Swetha , R B Dayananda ,   Professor, Dept. of CSE, K.S Institute of Technology, Bangalore, India.
Published: January 2020

Customer Churn Prediction has become one of the eminent topic in the telecom industry, it has gained a lot of attention in the research industry due to fierce competition from the various, and hence companies have focused on the larger size of the data for churning and upselling prediction. The model of customer churn prediction detects and identify the customer who are willing to terminate the subscription, customer churn prediction and upselling can be done through the data mining process. Hence, In this paper we have introduce a model Named MRF(Modified Random Forest), this model helps in enhancing the accuracy and also helps in ignoring the regression issue. Our methodology has been performed on the provided orange Datasets. For the evaluation of our algorithm comparative analysis between the existing and proposed methodology is done considering the two scenario i.e. churn and upselling. Later our model is compared with the various existing churn prediction model, the result of the analysis indicates that our model outperforms the existing method including the standard random forest in terms of AUC and classification accuracy.
Text Polarity Detection using Multiple Supervised Machine Learning Algorithms
Authors:   Information Technology, Narula Institute of Technology, Kolkata, India., Kar* Sagnik , Saha Mousumi ,   Computer Science & Engineering, Narula Institute of Technology, Kolkata, India., Biswas Tamasree ,   Information Technology, Narula Institute of Technology, Kolkata, India.
Published: January 2020

Sentiment analysis is the classifying of a review, opinion or a statement into categories, which brings clarity about specific sentiments of customers or the concerned group to businesses and developers. These categorized data are very critical to the development of businesses and understanding the public opinion. The need for accurate opinion and large-scale sentiment analysis on social media platforms is growing day by day. In this paper, a number of machine learning algorithms are trained and applied on twitter datasets and their respective accuracies are determined separately on different polarities of data, thereby giving a glimpse to which algorithm works best and which works worst..
Intelligent Transportation using Deep Learning
Authors:   CSE, Dnyanshree Institute of Engineering and Technology, Satara, Maharashtra, India., Gujar* Mr. Vijay Bhanudasd
Published: January 2020

The goal of this paper is to advance intelligent transportation program through the creation of a data collection system, a Convolutional Neural Network (CNN) model for intelligent transportation, and a simulator to test the trained CNN model. The data collection system collects data from a vehicle- steering wheel angle, speed, and images of the road from three separate angles at the time of the data collection. A CNN model is then trained with the collected data. The trained CNN model is then tested on a simulator to evaluate its effectiveness.
Curvelet Transform Based EEG Signal Analysis Using Pca
Authors:   Department of IT, Sreenidhi Institute of Science and Technology, Yamnampet, Ghatkesar, Hyderabad, India., Shaik Subhani , Kakulapati* V. ,   Department of IT, Sreenidhi Institute of Science and Technology, Yamnampet, Ghatkesar, Hyderabad, India.
Published: January 2020

The knowledge of Brain-Computer Interface (BCI) provides a direct exchange of information from the human brain and external devices. In BCI design structure, electroencephalography (EEG) identifies to be the major deliberately calculate the recordings of brain activity. Our proposed method is used to extract and analyze the characteristics of the EEG signal. They organize signal for BCI can be discriminate against and serve up human emotions. The projected method recognizes EEG information retrieving and computing feature extraction and classification. These signals have dissimilar frequency stages for Data waves, theta, alpha and beta. The combination of curvelet transforms (CT) and the principal component analysis (PCA) compute the dimensionality minimize and optimal characteristic extraction. The categorization of EEG signals, ANN (Artificial Neural Network) impact on this process of classification. This paper also provides a similarity between the projected two tools PCA and CT, with a combination of ANN.
Strength and Stiffness of Recycled Concrete Aggregates
Authors:   Formerly with Protective Technology Research Centre, NTU-Singapore, Professor in Civil Engineering, Shri Rawatpura Sarkar University, Raipur (CG), India., Kulkarni* Ankur Arun
Published: January 2020

As the construction is in its highest pace, the demand of raw material especially coarse aggregate is in great demand. At the same time the renovation, demolition and refurbishing of old structures is a continuous process, it is resulting in significant source of recycled concrete aggregate (RCA). Bit uncertainty and great variation in properties of RCA has restricted its wide use in all engineering construction activities. From point of view of conservation of natural resources, use of recycled concrete aggregate reduces use of natural aggregates, utilization of waste and results in energy saving. Thus extensive study is carried out to ascertain the effects of use of recycled concrete aggregate (RCA) on strength and stiffness of concrete. The rejected precast concrete, unused ready mixed concrete and concrete from demolished old structures is considered for RCA. Compressive strength and stiffness gain tests are conducted for both natural and recycled concrete aggregate (RCA) is carried out and the results are presented in this paper. Direct volume replacement method is used for replacing a selected quantity of natural coarse aggregates (NCA) by an equal volume of recycled concrete aggregate (RCA).
Image Enhancement using Recursive Separate Standard Intensity Deviation Based Clipped Sub Image Histogram Equalization
Authors:   Department of electronics, Kuvempu University, Jnanashyadri, Shimoga, India., K S* Sandeepa , Jagadale Basavaraj N ,   Department of Electronics, Kuvempu University, Jnanasahyadri, Shimoga, India., Bhat J S ,   Indian Institute of Information Technology, Surat,, India.
Published: January 2020

To improve image contrast, this paper introduces a recursive separate standard intensity deviation based clipped sub image histogram equalization method. This is an extension of standard intensity deviation value based sub image histogram equalization algorithm, in terms of histogram separation and equalization. In existing equalization methods do not effectively utilizes the information from different region in equalization process. In this scheme, the image histogram is bisected based on standard intensity deviation value. The further separation is carried out based on the specific region threshold value and the resulting four sub histograms are equalized individually. This is an effective method for enhancing, low exposure, medical and mammogram images and for addressing the over-enhancement problem. The performance evaluation of the proposed method is presented with the help of average information and visual quality assessment and the proposed algorithm outperforms existing recursive algorithms based on histogram equalization.
Optimized Design of Diesel Generators Based Chilled Water Cooling System for Intelligent Hospitals and Hotels
Authors:   PHD Research Scholar, VTU, Belgavi, India., Bagade* Mr. Sunil D. , Rampure Dr. Prasad B. ,   Principal in KLE College of Engineering and Technology, Chikodi, Karnataka, India.
Published: January 2020

For the intelligent applications like Hotels and Hospitals, there is requirement of efficient chilled water system in terms of energy consumption reduction, cost minimization, reduction in Carbon Dioxide (CO2) emissions. As the loads in hotels and applications increases, the performances of water cooling systems becomes the worst that leads to excessive consumption of energy and emission of CO2, thus it needs the efficient load management strategies as well. In this paper, we first analysed the challenges of energy and CO2 efficiency of water cooling system in the intelligent hospitals and hotels from systematic point of view and then introduced the effective scheduling strategies for both hotel and hospitals. Further, the key focus in this paper is to design water cooling system using the diesel generators by considering the real time applications hospitals and hotels. Since the coolant temperature is having the significant effects on the performance of cooling engine and the CO2 emissions, therefore we introduced the diesel generators with coolant system to investigate such effects. For the cold water supply load management, we designed the Particle Swarm Optimization (PSO) based scheduling strategy at last. This paper exhibits the plan and its simulation results that analysed in terms of ESR (Energy Saving Ratio), CSR (Cost Saving Ratio), and CRR (Carbon dioxide Reduction Ratio) for the Internal Combustion Engine (ICE) capacity on heating and cooling systems.
An Efficient Cascaded CNN Architecture for Brain Tumor Detection in MRI Images
Authors:   Department of Computer Science University of Madras, Chennai-25, Tamilnadu, India., Chithra* PL. , Dheepa G. ,   Department of Computer Science University of Madras, Chennai-25, Tamilnadu, India.
Published: January 2020

This research work proposed an automated tumor detection system based on cascaded Convolutional Neural Network (CNN) architecture. In this, each input has convolved separately with three kernels (3 x 3, 5 x 5 and 7 x 7) and their three output feature maps are cascaded to be processed into the hierarchy of two convolution and pooling layers followed by fully connected (FC) layer. In FC layer, the softmax classification technique has performed to find the pixel-wise classification and to detect whether the particular image consisting of tumor or not. This proposed work is tested with BRATS-2018 dataset of both Low-Grade Gliomas (LGG) and High-Grade Gliomas (HGG) brain images. Further, this work has evaluated using different metrics namely accuracy, precision, recall, F1-score, specificity and sensitivity. Thus, this method outperforms well with 96% accuracy, 98% precision, 98% F1-score and 99% sensitivity, demonstrating that the tumor identification has achieved 5% better accuracy than the existing tumor detection methods
Topology Optimization of Spiral Bevel Gear for Differential
Authors:   Mechanical Department, Silver Oak University, Ahmedabad, India, Patel Mit , Khatod* Vinay ,   Automobile Department, Ganpat University, Mehsana, India,, Patel Amit ,   Automobile Department, Ganpat University, Mehsana, India, Prajapati Bharat ,   Mechatronics Department, Ganpat University, Mehsana, India, Patel Pavan ,   Mechatronics Department, Ganpat University, Mehsana, India,
Published: January 2020

The Spiral Bevel gear used in differential should be enough stiff to resist the vibrations and stresses encountered during its operation. The gear must also have sufficient strength to bear the bending stresses occurring in the differential assembly in its course of operation. This research is typically focused in designing a differential gear with least weight and minimal stresses. The model of the gear is designed in the Solidworks version 2015 while its analysis is carried in ANSYS 14.5. The number of parameters and levels involved in designing are more; the number of probable models is too many. To choose the optimal parameter among the list of choices, TAGUCHI method along with Finite Element Analysis (FEA) is used. By application of TAGUCHI method, not only the time required to design all the probable models is reduced, but also the time required to analyze all the models is cut down. Orthogonal Array has been incorporated to change the parameters necessary for reducing the weight of the gear. To get the best possible model of gear, FEA is then performed on the designed models. This process not only saves production time, but also prevents material wastage and production cost.
Transient CFD Modeling of Blood Flow Simulation through Left Coronary Artery
Authors:   M.Tech (Thermal Engineering) Student, Department of Mechanical Engineering, GRIET, Hyderabad, Telangana, India., Kumar* Dharshanm Anil , lavu Gopinath. ,   Asst. prof., Department of Mechanical Engineering, GRIET, Hyderabad, Telangana, India.
Published: January 2020

From the past twenty years, cardiac strokes have become one of the most common causes of death. Coronary artery disease means blockage of at least one course that supplies blood to the heart. These blockages are caused by the accumulation of plaque in the artery walls. That LDL cholesterol can restrict blood flow in the arteries and it directs to myocardial infarction; The CFD simulation is increasingly performed to study fluid phenomena inside the human vascular system. This simulation aims to develop a CFD model of coronary arteries and observe blood through the arteries, Estimate some of the hemodynamic parameters of the blood during the systolic and diastolic phase hemodynamic parameters were quantified and flow patterns are visualized visualized using CFD in the presence of plaques and forecast pressure rate, velocity in the arteries.
On the Use of Laser Beam Welding for Austenitic Stainless Steel Type 316L and Stainless Steel Type 304 for Aerospace Applications.
Authors:   Department of Mechanical Engineering, Anna University, Dindigul, India., Lingadurai K. , Mukesh* R. ,   Department of Aerospace Engineering, ACS College of Engineering, Bangalore, India, Siddesha H.S. ,   Department of Mechanical Engineering, ACS College of Engineering, Bangalore, India, Sivasubramaniyam R. ,   Department of Mechanical Engineering, ACS College of Engineering, Bangalore, India., V Yashaswini ,   Department of Aeronautical Engineering, ACS College of Engineering, Bangalore, India.
Published: January 2020

Currently wide range of aircraft parts have been welded by using laser beam welding. In this paper we have analyzed the strength of laser beam welded joint of stainless steel materials 316 L and 304. The Micro and Macro welding techniques are used for dissimilar stainless steel materials. The metal sheets are welded with a laser power of 1000 w with a bead width of 0.5 mm on both sides of the sheet by using micro laser beam welding and the macro laser beam welding is used to weld the metal sheets with 1800 w laser power along with a bead width of 3mm on one side of the sheet. The strength and mechanical properties of laser beam welded samples are found out by subjecting it to various tests such as Tension test, Bend test and Hardness test. Since stainless steel used in the aircraft parts are subjected to high temperature in the engine exhaust part, these samples are heated to temperature of 1040ºC. Aircraft icing occurs on parts of aircraft, where temperature falls below 0ºC, hence laser beam welded samples are cooled to a temperature of -30ºC. The behavior of laser beam weld portions under these conditions are studied. The Microstructure of the welded sample is obtained from the Scanning electron microscope is also discussed. The results obtained from the tensile test are compared with the structural analysis done using Finite Element Analysis. From the results we found that, macro welded sample is having good tensile strength of 582.753 MPa and no cracks were occurred during the bending test.
GPS System Based Low Cost Maritime Boundary Identification Device
Authors:   Assistant Professor, Department of Electrical and Electronics Engineering at Sri Ramakrishna Engineering College, Coimbatore., Divya* N. , Gandhi R.R.Rubia ,   Assistant Professor, Department of Electrical and Electronics Engineering of Sri Ramakrishna Engineering College, Coimbatore., Abinaya I. ,   Assistant Professor, Department of Electrical and Electronics Engineering of Sri Ramakrishna Engineering College, Coimbatore., Karthik M. ,   Assistant Professor, Department of Electrical and Electronics Engineering of Sri Ramakrishna Engineering College, Coimbatore., Kumar R. Mohan ,   Assistant Professor, Department of Electrical and Electronics Engineering of Sri Ramakrishna Engineering College, Coimbatore.
Published: January 2020

The aim is to build a friendly environment for the Indian fishermen preventing them from facing many hardships. This can be done using GPS(Global Positioning System) that provides navigation, positioning and other time details in all the weather conditions for everyone and everywhere.GPS system being used for map-making, commerce, surveillance. But this paper helps in preventing the violence created between India-Sri Lanka caused for crossing the border IMBL(Indian Maritime Boundary Line) which is unintentional. The important purpose of this paper is to alert the fishermen before crossing the country’s border. If they travelled beyond the border an alert message will be transmitted or sent to the base station by using an X-bee transmitter. This system is developed to help the lives of the fishermen and not to move beyond Indian Boundaries. On the whole it is a plan of creating a suitable device for civilian navigation at low cost.
Backstay Effect of Diaphragm in Tall Building
Authors:   PG Student Nitte Meenakshi Institute of Technology Bengaluru, India., Nandi* Ankan Kumar , C Jairaj ,   Assistant Professor Nitte Meenakshi Institute of Technology Bengaluru, India.
Published: January 2020

Seismic analysis of structural systems with floor diaphragms has been a requisite in the recent past. The duty of a structural engineer is to be prudent about the behavior of every structural system adopted. Amongst the structural systems that are adopted world over, diaphragm with rigid and semi-rigid floor plate are adopted widely in the analysis. This research focuses on the backstay effect i.e. podium structural interaction with the tower area and consideration of retaining wall as increment of lateral stiffness as specified in latest tall building code IS6700:2016 for low and high rise structures. In the current study models were prepared with low to high rise storeys with rigid and flexible diaphragms considering backstay diaphragm placing tower at center and corner. The models were subjected to seismic forces; response spectrum along with the combination of the gravity loads. The structural responses like natural periods, base shear, displacement and inter storey drift were also studied.
Behaviour of Light Weight Brick with the Influence of EPS Beads and Silica Fume
Authors:   Research Scholar, Department of Civil Engineering, ITM University Gwalior, India., Mallick* Adeeb Arif , Agarwal Sohit ,   Assistant Professor, Department of Civil Engineering, ITM University Gwalior, India., Pandey Mukesh ,   Professor, Department of Civil Engineering, ITM University Gwalior, India.
Published: January 2020

The principal reason behind this experimental investigation carried out here is to diminish the dead load of structures with the potential use of light weight bricks. EPS beads and silica fume are light in nature. The investigation work enhanced, with numerous literature study to find out the utilization of Expanded polystyrene(EPS) beads and silica fume in light weight brick can be used in military bases in cold regions due to its low thermal insulating quality. The main objective of this research is to prepare a light weight brick by partial substitution of Cement with silica fume and the replacement of fine aggregate with EPS beads. A total of 70 bricks containing two different sizes of EPS beads say Type A and Type B with different proportions (0%, 7%, 14%, 21%) of each Type were casted in order to check the mechanical properties such as compressive strength, water absorption, efflorescence, workability, and thermal conductivity of the brick. The compressive strength test was carried out at 7, 14 and 28 days of curing. As the percentage of EPS beads in the brick increased the strength of brick decreased while with the increase of EPS beads in the brick the water absorption as well as the thermal conductivity of brick decreased. There were slight presence of Efflorescence in some of the bricks while in most of the brick there were no efflorescence found.
Leaf Disease Detection of SoyBean Plant using Machine Learning Algorithms
Authors:   Assistant Professor, Department of IT, M.Kumarasamy College Of Engineering, Karur, Sowmiya* Mrs.M. , Thilagavathi Mrs.C. ,   Assistant Professor, Department of IT, M.Kumarasamy College Of Engineering, Karur
Published: January 2020

Nature is an important phenomenon of this physical world. This nature includes plants, trees, animal, humans and several other organisms. Amongst them plants are the most important organisms in the world. They are specialist of creating their food by themselves and also they are the notable components in food chain. They also serve the nature and its organisms in a tremendous way. Hence it is necessary to protect our nature in an efficient manner so as to maintain the food chain. Our technology development has given much advancement in the field of agriculture. This paper deals with the analysis of various machine learning algorithms, by applying the algorithms on the plant data set. Sample sizes of collected data set are used to train the algorithm and the results are evaluated accordingly to estimate the better implementation of machine learning algorithm.
A compact Single-Phase Single stage AC-AC Impedance Source Converter
Authors:   Department, Electrical Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India., Jahangeer*  , Sonar Santosh ,   Assistant Professor, Department, Electrical and Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India.
Published: January 2020

The paper presents a compact AC-AC single phase voltage regulator based on Impedance network. The proposed topology has ability to perform buck and boost operation in a single stage .The circuit is simple, highly efficient and more importantly reduced manufacturing cost due to its minimal number of active and passive components. The Impedance network has dual function of boosting and filtering. The proposed topology employs two bidirectional switches operating at high frequency PWM pulses. The high frequency switching reduces the size of the Impedance network. The gain of the system is controlled by controlling the duty cycle of the bidirectional switches. The operating mechanism of the proposed topology along with simulation and experimental results are presented.
Scene Recognition using Significant Feature Detection Technique
Authors:   Pursuing M.E from National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, India., Singla* Er. Priya , Mehrais Dr. Rajesh ,   Head of Curriculum Development Center, National Institute of Technical Teacher Training & Research, Chandigarh, India.
Published: January 2020

Scene classification is basic problem in robotics and computer vision application. In Scene classification focused on complete view or event that contains both low and high level features. The main purpose of scene classification is to diminish the semantic gap in between social life & computer system. The main issue in scene classification is recognizing tall buildings, mountain, open country and inside city. We applied combination algorithms of feature extraction on trained datasets. Our proposed algorithm is hybrid combination of SIFT+ HOG named as HFCNN. As compare with the existing CNN architecture, HFCNN perform betters with high accuracy rate. Accuracy rate for proposed architecture is more than 96% as calculated with better time consumption and cost effective.
Identification and Implementation Perspective on the Stratification Algorithms in the Prognostication of Heart Disease using Machine Learning Techniques
Authors:   PG Student, Department of CS,GIS,GITAM (Deemedto be University), Visakhapatnam, India, Lakshmi* D Vijay , Yasudha K ,   Department of CS,GIS,GITAM (Deemed to be University), Visakhapatnam, India, kakollu Vanitha ,   Department of CS,GIS,GITAM (Deemed to be University), Visakhapatnam, India
Published: January 2020

Analysis of patient’s data is always a great idea to get accurate results on using classifiers. A combination of classifiers would give an accurate result than using a single classifier because one single classifier does not give accurate results but always appropriate ones. The aim is to predict the outcome feature of the data set. The “outcome” can contain only two values that is 0 and 1. 0 means patient doesn’t have heart disease and 1 means patient have heart diseases. So, there is a need to build a classification algorithm that can predict the Outcome feature of the test dataset with good accuracy. For this understanding the data is important, and then various classification algorithm can be tested. Then the best model can be selected which gives highest accuracy among all. The built model can then be given to the software developer for building the end user application using the selected machine learning model that will be able to predict the heart disease in a patient.
Data Analytics for Monitoring the Satisfactory Parameters of Airline Passengers using Machine Learning Algorithms in Python
Authors:   Assistant Professor, School of Engineering, Department of Computer Science Engineering, Vels Institute of Science Technology and Advanced Studies (VISTAS), Chennai. India., Parvez. Shaik Javed , Sahayadhas* Arun ,   Associate Professor, School of Engineering, Department of Computer Science Engineering, Vels Institute of Science Technology and Advanced Studies (VISTAS), Chennai. India.
Published: January 2020

An effective representation by machine learning algorithms is to obtain the results especially in Big Data, there are numerous applications can produce outcome, whereas a Random Forest Algorithm (RF) Gradient Boosting Machine (GBM), Decision tree (DT) in Python will able to give the higher accuracy in regard with classifying various parameters of Airliner Passengers satisfactory levels. The complex information of airline passengers has provided huge data for interpretation through different parameters of satisfaction that contains large information in quantity wise. An algorithm has to support in classifying these data’s with accuracies. As a result some of the methods may provide less precision and there is an opportunity of information cancellation and furthermore information missing utilizing conventional techniques. Subsequently RF and GBM used to conquer the unpredictability and exactness about the information provided. The aim of this study is to identify an Algorithm which is suitable for classifying the satisfactory level of airline passengers with data analytics using python by knowing the output. The optimization and Implementation of independent variables by training and testing for accuracy in python platform determined the variation between the each parameters and also recognized RF and GBM as a better algorithm in comparison with other classifying algorithms.
Speed Control of Fuel Cell Driven PMSM using Sliding Mode Control Based IDDB Converter
Authors:   Assistant Professor, Department of EEE, Visakhapatnam, Andhra Pradesh, India., Kumar* J.S.V.Siva , Rao Dr. P. Mallikarjuna ,   Professor, Department of Electrical Engineering, Andhra University College of Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India.
Published: January 2020

The concern over greenhouse gas emissions and their relation to global warming is one of the main reasons for the introduction of electric vehicles into the market. This paper discusses the design and simulation of the fuel cell-based electric vehicle. These FCEVs are "Rechargeable Energy Storage System" (RESS) and provide better acceleration along with regenerative braking as well. The output voltage of the fuel cell's stack is significantly low, then expanded by using the sliding mode control Interleaved Double Boost converter. The boost converter's increased output is given to the inverter to get AC to run PMSM. Using the Space Vector PWM process, gating pulses are given to the inverter and the inverter output is provided to the PMSM drive through the LC filter to minimize ripples in the inverter output. Simulation approaches use MATLAB / Simulink to determine the results
Role of Advanced Technology in Preventing Suicide in Transgenders
Authors:   Faculty Associate & Research Scholar, KIIT Deemed to be University, Bhubaneswar, India., Priyadarshini* Sugyanta , Swain Sukanta Chandra ,   Associate Dean, KIIT Deemed to be University, Bhubaneswar,India.
Published: January 2020

The goal of this paper is to attempt understanding around suicidal ideation in transgender youth and to find out how technology prevents risk of suicidal ideation among them. A pragmatic approach is followed including face to face interview of 75 transgenders about their suicidal thoughts and how major technical advances such as cyberspace, internet, mass media, and telephonic conversation enhance resilience and reduce suicidal thoughts enduring in them. Results in this article motives that instigated suicidal ideas in Transgender youth dominantly comprised of isolation and rejection based on gender identity. Participants conquered suicidal thoughts by connecting with their loved ones for social and moral support and by socializing from private realms to discuss various sensitive and embarrassing issues which regulated their adverse behavior into self-love. 85.33% of Transgender youth out of the sample of 75 agreed to the fact that they have at least once thought of attempting suicide and 75% of the sample have given up the idea of suicide due to technology enhanced intervention by providing a social platform for discussing issues, receiving advices and support about ‘coming out’ despite staying at the fringes of the society. This experimented paper on studying emotions of depressed transgenders can be helpful in understanding the real life challenges in the life of transgender and innovation of up-to-date technology will be encouraged in prohibiting suicidal ideas among transgenders.
Recognition of Teeline Shorthand using Deep Learning.
Authors:   Department of Computer Science and Engineering Government Engineering College, Devagiri, Haveri, India., Mr. Shivaprakash*  , Burkpalli Dr. Vishwanath C ,   Department of Information Science and Engineering P.D.A. College of Engineering Gulbarga, India., Anami Dr. B. S. ,   Principal, K.L.E. Institute of Technology Hubli, India.
Published: January 2020

Recognition of the Teeline shorthand is the interesting research problem. The accurate recognition of the Teeline patterns which helps the journalists to summarize the VIPs talk during the press meets which reduces the writing time. In order to address the above issues, the proposed method addresses the automatic recognition of the Teeline symbols which is used to provide alphabets as output. The framework consists of obtaining the input image, pre-processing it, perform the background subtraction on grayscale image and prepare the dataset for recognition. To prepare the dataset, the letters are written using the digital pen, it generates the pixelsand it is recorded in the Android application. Later these pixels are used to convert them into the image dataset. The prepared database is fed to the manually designed eleven layered Convolutional Neural Network (CNN). CNN is designed in such a way that it accepts the input Teeline alphabet and it able to say the equivalent English alphabet based on the training process. It has been carried out on the MATLAB 2018b and achieved the accuracy of 95%.
Design & Development of Multiple Alternative Energy Car
Authors:   Mechanical, Indus Institute of Technology & ngineering, Ahmedabad, India, Khandwala* Drashtant , Pandya Parthiv ,   Mechanical, Indus Institute of Technology & Engineering, Ahmedabad, India., Ladani Bhargav ,   Mechanical, Indus Institute of Technology & Engineering, Ahmedabad, India., Khatri Paumil ,   Mechanical, Indus Institute of Technology & Engineering, Ahmedabad, India., Patel Jignesh ,   Assistant Prof Mechanical, Indus Institute of Technology & Engineering,Ahmedabad, India.
Published: January 2020

As a result of excessive air pollution caused from the vehicles the automobile industry is shifting its focus from traditional I.C. engine powered vehicle to electrically propelled vehicles. Although this shift is eco friendly when compared, it has its demerits too. Among these the range of an EV is preeminent. This research paper counters this downside of the EV by focusing on the depletion rate of the batteries, used to power the vehicle. Renewable energies like- Solar Energy & Wind Energy are used as the chief form of alternate energies by which power can be generated and connected with EV in order to help sustain and reduce the depletion rate of batteries. Along with these energies we can also use different technologies such as-Regenerative Braking, piezoelectric suspension system, etc. for reducing the depletion rate. These technologies can also be directly used for powering the secondary units such as headlights, horn, indicators, etc. This research paper revolves around this core idea and also to backhand this research we have fabricated a basic EV along with Solar & Wind module, namely the MAE-Car (Multiple Alternative Energy Car).
Design of a High-Performance Composite Triple Clamp of Motorbike
Authors:   Department of Mechanical Engineering, College of Engineering Trivandrum, India., B* Akshay , Alias Sony ,   Department of Mechanical Engineering, College of Engineering Trivandrum, India., Kumar R Ramesh ,   Department of Mechanical Engineering, Sree Chitra Thirunal College of Engineering, Trivandrum, India.
Published: January 2020

A simple and novel design concept for a CFRP composite triple clamp of a motorbike is brought out for low mass that fulfills the stiffness and strength requirement when compared to an existing steel triple clamp. In general, for any triple clamp configuration, the ideal fibre angle is chosen as the angle that subtends in the arm of the clamp with respect to the longitudinal direction (a line connecting the two fork holes). The initial design configuration is fabricated using a commercially available low modulus bi- directional carbon–epoxy laminate and tested for the evaluation of axial and transverse stiffnesses. Finite element model is then verified through the test data. Using the validated FE model, a new design with the high modulus carbon-fiber is arrived at. The proposed composite design suitable for high performance motorbike that possesses, high margin over critical load case with low mass when compared to steel clamp is provided.
Development of PBS/CDS Core-Shell Nanocomposites Through Ligand Etching for Optoelectronic Application
Authors:   Ph.D. Scholar, Department of Physics, Rjiv Gandhi University, India., Handique* K C , Barman Barnali ,   PhD, Department of Physics, Rajiv Gandhi University, India., Kalita P K ,   Professor, Department of Physics, Rajiv Gandhi University, India.
Published: January 2020

Core-shell nanocomposites are of immense interest among the research community for its potential applicabilities in various optoelectronic devices. In this work cadmium sulphide (CdS), lead sulphide (PbS) and their core shell PbS/CdS nanostructures have been synthesized through chemical bath deposition method. Their structural and optical properties are studied accordingly through diffractometric and spectrometric techniques. The phase of the core PbS is cubic zinc blende and of the shell CdS is hexagonal wurtzite confirmed from the XRD data. The optical bandgaps are calculated from the absorption spectra and are found to be 2.2eV for PbS and 2.7eV for CdS whereas for core shell PbS/CdS it reduces to 2.1 eV. The photoluminescence spectroscopy has been done on the samples and the spectra shows a blue shift of its near band gap emission for core PbS when it is coated with shell CdS which is not according to the usual behavior of core shell nanostructures. These optical properties are clearly carrying evidences of cationic ligand exchange between the cadmium and lead ion complexes. The conductivity of the prepared samples are measured at room temperature and it is found to be higher in case of PbS/CdS than the core PbS and shell CdS. The increase of bandgap and conductivity of PbS/CdS is a suitable nature for the application of this material in photovoltaic devices. The quantum yield of the core shell nanocomposites is also greatly enhanced that makes the synthesized nanostructures one of the potential candidates for the application in various optoelectronic devices.
Variable Density Sampling Trajectories for Compressive Sensed MRI
Authors:   Department, of Electonics and Communication, NMAMIT Nitte, affiliated VTU Belagavi, Udupi, India., S* Kavitha , Musthafa Dr. B. Aziz ,   Department of Computer Science, BIT Mangalore, Mangalore, India.
Published: January 2020

Diagnosis of diseases require high resolution images of human body parts. Magnetic Resonance Imaging (MRI) is a popular technology commonly used for this purpose. In addition to having several benefits, this technology has few shortcomings also. One of them is its high scanning time. In MRI acquisition of image is based on the principle of traditional sampling theorem. The novel sampling theory called as Compressive Sensing (CS) which allows the reconstruction of sparse signals from undersampled data. The application of CS onto MRI will drastically reduce the acquisition time and hence scanning time. In this manuscript analysis and application of CS on to MRI is demonstrated. Simulations are carried out using Variable Density Sampling trajectories (VDS). Then a comparative study is made in terms of Signal to Noise Ratio (SNR) and execution time based on the result obtained.
Prediction of Black Sigatoka Disease in Banana Plants By Data Mining Classification Techniques using Scikit for Python
Authors:   PG & Research Department of Computer Science, Chikkanna Government Arts college, Tirupur, India., Devi S* Srivalli , Geetha Dr.A. ,   PG & Research Department of Computer Science, Chikkanna Government Arts college, Tirupur, India.
Published: January 2020

Agriculture has been evolving since humans started cultivating plants for food consumption. As the agriculture field evolves, the disease control measures too have evolved. Now in this modern era, disease in plants can be easily identified using computers. Data mining is the process of obtaining the useful information from the data. Before the electronic era, diseases in plants are identified just by seeing the symptoms of the plants. Similarly, we can identify the diseases in plants using data mining by supplying the disease symptoms data and classify them accordingly. The purpose of this paper is focusing on the prediction of the diseases from images of black sigatoka disease and uses the following methods: MultilayerPerceptrons, SVM,KNeighborsClassifier,K-NeighborsRegressor, Gaussian Process Regressor, Gaussian Process Classifier, GaussianNB, Decision Tree Classifier, Decision Tree Regressor, linear models such as Linear Regression, RidgeCV, Lasso, ElasticNet, Logistic RegressionCV, SGD Classifier, Perceptron and Passive Aggressive Classifier and ensemble models of the above classifiers. The results are compared, and multilayer perceptron model is seen to give better results for individual classifiers and ensemble of week classifiers gives better results when ensembled. In future, a new hybrid algorithm would be used from the above algorithms for attaining better accuracy. The scikit is a library used for classification, clustering, regression, dimensionality reduction,model selection and preprocessing. Our paper discusses various classifiers used in scikit-learn library for Python and their ensembling is done. This can be applied to all the classification tasks. Classification is done for classifying the black sigatoka disease in banana from healthy leaves.This disease is the most vulnerable one among banana plants.
Performance Analysis of Solar Water Heater Through Computational Techniques
Authors:   Research Scholar, Department of Computer Science Engineering, PRIST University, Thanjavur, Tamil Nadu, India, Kumaran G. Senthil , Jaisankar* S. ,   Professor, Department of Mechanical Engineering, Star Lion College of Engineering & Technology, Thanjavur, Tamil Nadu, India.
Published: January 2020

By implementing the computational techniques, the solar water performance was analysed. Employing the orthogonal design, experiments were accompanied with the input variables L/D ratio, condition of twist and time. Using the recorded measurements nusselt number and efficiency were calculated and further it was optimized in a combined objectively manner. The optimal input variables to accomplish the higher performance of solar water heater is identified. Also, the dominance of input variables was identified with the statistical analysis for the combined objective.
Edge Detection Algorithm Based on BEMD for Liver CT Images
Authors:   Department of Biomedical Engineering, School of Technology, North-Eastern Hill University, Shillong, Meghalaya, India., Mourya* Gajendra Kumar , Gogoi Dr. Manashjit ,   Department of Biomedical Engineering, School of Technology, North-Eastern Hill University, Shillong, Meghalaya, India., Handique Dr. Akash ,   Department of Radiology & Imaging, North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya, India.
Published: January 2020

Liver edge identification requires for its volume estimation from CT image and this process is a prerequisite for liver diagnosis and treatment planning. In this article, an edge detection algorithm proposed based on Bi-dimensional Empirical Mode Decomposition (BEMD) and Fourier Transform. Intrinsic mode function (IMF) extracted from BEMD and mixed with the Fourier phase of the original image to get edge profile. The proposed method extensively evaluated on Berkeley Segmentation Data Set (BSDS-500) and compared with Sobel and Canny operators. Results achieved Mean Square error 0.04±0.01 and PSNR 62.27±1.1. In conclusion, The BEMD approach capable of identifying image edges with high accuracy compared with state of the art.
Development of The AR School App for Children with Hearing Impairment Who Begin Learning Ecuadorian Sign Language using Augmented Reality
Authors:   Department of Computer Languages and Systems and Software Engineering, Universidad Politécnica de Madrid and Universidad Politécnica Salesiana, Guayaquil, Ecuador., Sánchez* Ricardo Naranjo , Pinargote Jeison ,   Department of Computer Science, Universidad Politécnica Salesiana, Guayaquil, Ecuador., Lopez Antonio ,   Department of Computer Science, Universidad Politécnica Salesiana, Guayaquil, Ecuador, Normand Loïc Martínez ,   Department of Computer Languages and Systems and Software Engineering, Universidad Politécnica de Madrid, Madrid, Spain.
Published: January 2020

Augmented reality AR has been used for many years in different fields of education. It has provided advantages in learning, However, no applications focused on the initial learning of Ecuadorian sign language for children with hearing impairments in their primary school years have been found. In this paper we present the development of a mobile application based on augmented reality, the Unity tool was used as a platform for mobile devices and the Vuforia SDK complement for augmented reality. With this application, the child can see the gesticulation of words in sign language through the use of printed templates. It also has an option to perform a quiz that will allow it to evaluate the knowledge the children acquired from the learning module. The mobile application called ARSchool based on augmented reality which is designed and adapted for people with hearing impairment, mainly for school-age children, as support for the initial learning of sign language in Ecuador. Once the application was developed, it was tested both at school and at home, in which teachers and parents made children with hearing impairments interact.