bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aadhar Based Electronic Voting Machine
Authors: Janarthanan M , Reddy Mj Vishnu Theja , Reddy Ch Ravi Shankar , Reddy N Varunesh , Nikhil K 
Published: November 2019

Abstract
The “AADHAR BASED ELECTRONIC VOTING MACHINE” describes an easy and secure electoral voting system for Indian election. Here two levels of authentication is done. Using RFID based aadhar card and by taking fingerprints because both the levels are unique for every user. User id and fingerprint are to be matched in given database or else he/she cannot eligible to cast the vote. The process of this system is done in a simple way, first user RFID card is scanned for user details then fingerprint is taken to verify and using keypad can press the number of his/her favourite candidate to cast the vote after that lcd will displays a confirmation message. This will be the high secured system than our present voting system because authentication identity is verified by two levels before casting a vote. Directly votes will be counted so that the time taken by election commission to announce results will be fast and in short period.
Design of Porous Structures for Scaffold Synthesis and its FEA
Authors: Mahesh CH M N , Devaprasad Ashley Minu , Muthu P. , Moorthy Thrinayan 
Published: November 2019

Abstract
Injuries are experienced in many forms and take time to heal depending on the severity. Some injuries are recovered from naturally/quickly, while others take longer periods of time. Scaffolds are porous structures which provide a platform for cells to regenerate on. They provide support in times when individuals cannot regenerate tissues on their own. The materials of scaffolds can be varied to determine the best mechanical property for implanting in the body. In our study, we have tested stress and strain of PCL and titanium material for six proposed designs. From our study, we were able to conclude that the ‘sphere’ provided the most stability whereas the ‘eccentric pores’ design was the least stable. These results were persistent for both the materials studied with Ti6Al4V having the greatest properties. As a result, we concluded that titanium is the best material to be used in terms of scaffolds, by implanting it as an eccentric pores and spheres.
Securing Hadoop Distributed File System using Intelligence based Sensitivity bits
Authors: Suganya S. , Selvamuthukumaran S. , Swaminathan S. , Kalaichelvi V. 
Published: November 2019

Abstract
Hadoop is a widely used analytical tool for analyzing large volume of data which are in terms of Exa & Zetta bytes. Hadoop Distributed File System(HDFS) is a well-known storage system which provides distributed storage using commodity hardware. Since Big Data consists of highly sensitive data like Electronic Health Records, Financial Data etc., harnessing big data access and security plays a vital role. The bottom most layer of security can be provided by encryption. Since the data stored is highly unstructured, wider in variety and the velocity at which data is stored is also unpredictable, traditionally used ciphers like AES, RSA, RC4 etc. will not work efficiently on Big Data. The solution must have to consider at-risk sensitive data, variety of data which needs intelligence to classify the data. When data blocks are stored in data nodes, with each block 4-bits called sensitivity bits has to be added. Two bits indicate the level of sensitivity and two more bits indicate the type of data. These 4-bits are used by the map and reduce functions to effectively encrypt the required data blocks alone and not all, in a time efficient manner by using the available commodity hardware.
CROSS DOMAIN OPINION MINING USING MAXIMUM ENTROPY BASED CLASSIFIER
Authors: Manimekalai V. , Gomathi S. , Rohini  
Published: November 2019

Abstract
The current analysis is play a dominant role in opinion mining is additionally referred to as sentiment analysis because of clear volume of opinion made net resource like discussion type, review sites, blogs, and tweets area unit on the market in digital type. Sentiment analysis is that the field of study that analyzes client opinion, feedback, sentiment analysis, attitudes and feeling from communication. At intervals fraction second, we have a tendency to classify the text in several manner in several seconds. It’s one in all the active analysis areas in linguistic communication process [NLP]. There are a unit range of techniques we want to classify the Opinion reviews. The main problematic in the sentiment analysis is to understand the usage of negation and the taxonomy of positive and negative sentiments recorded by the users in the social group. The proposed approach that extracts and classifies opinion words from one domain called source domain and predicts opinion words of another domain called target domain using a semi-supervised approach, its combines modified maximum entropy and bipartite graph clustering. A comparison of opinionclassification of reviews on four different product domains are presented. The results demonstrate that the proposed method perform relatively well in comparison to the other methods. Comparison of SentiWordNet of domain-specific and domain-independent words reveals that on an average 72.6% and 88.4% words, respectively, are correctly classified.
Device Identification and Authentication for Internet of Things using predefined characteristics
Authors: Kirubadevi T. , Ramamoorthy S. , Rajavarman V.N. 
Published: November 2019

Abstract
The Internet of Things (IoT) has been growing rapidly in the past few years. IoT constitutes various components such as smart devices, users and internet services which interact with each other to share the resources. IoT has lot of security and authentication issues. The need for device identification is still being a big challenge. There is a demand to identify the device ID operated in heterogeneous environment. The devices with different properties and characteristics needed to be managed and identified. Then consistency in the state of devices is required to manage its identity. This paper involves an approach to find or identify a device by extracting its features and combining it to record as a pattern on time basis. Thereby device authentication also becomes feasible. The Result of the simulation justifies that the patterns that are used to identify a device becomes noteworthy.
Iot Based Garden Monitoring System
Authors: Sambath M , Prasant M , Bhargav Raghava N , Jagadeesh S 
Published: November 2019

Abstract
In an agricultural country like India a lot of people will work with green thumb in mind. Most of the people loves to grow plants at home, but due to their work schedule they very often take care of plants. The only solution to this problem is smart monitoring of the plant growth by modernizing the current traditional methods of gardening. Hence the proposed system targets at smart way of monitoring the plant growth using automation and IoT technologies. Internet of things (IoT) provides various applications for crop growth and monitoring the growth conditions. Main theme of this paper is to increase the plant growth condition by maintaining the suitable moisture level and temperature with the use of moisture sensor and temperature sensor. This paper works for the crop development at low quantity water consumption by providing an automatic watering system to the user. People often waste lot of time for watering the plants so an efficient management of water should be developed. The proposed system will work based on the information send by the sensors and so proper growth for the plant will be estimated. With the help of the moisture sensor and temperature sensor details like moisture content and the temperature will be obtained and so based on those reading automatic watering will be done. The major advantage of this system is to make a suitable environment for plant growth and also to minimize the water consumption.
MRI Brain Image Segmentation and Detection Using K-NN Classification
Authors: Venkatesh  , Leo M.Judith 
Published: November 2019

Abstract
Detection of brain tumor at an early stage is important to avoid death. Brain tumor arises due to the abnormal growth of the cells. Magnetic Resonance Imaging (MRI) is a computer-based image processing technique used for detecting tumor size, location and shape. In order to classify it is important to segment MRI brain images. In this paper, MRI brain tumor is segmented using k-means clustering algorithm and various features of the segmented tumor was analyzed using Gray level Co-Occurrence matrix (GLCM). These features were used as input for the k-Nearest Neighbour (k-NN) classifier and used for the classification of tumor as Benign or Malignant. The accuracy of the proposed algorithm is 85% respectively.
Review of Meta-Heuristic Optimization based Artificial Neural Networks and its Applications
Authors: Devikanniga D. , Vetrivel K. , Badrinath N. 
Published: November 2019

Abstract
There are several meta-heuristic optimization algorithms developed on inspiration from nature. Artificial neural network proves to be efficient among other machine learning techniques. The efficiency of classification and prediction is improved by optimizing artificial neural network using the meta-heuristic optimization algorithms. The review of some of these hybrid artificial neural networks that are applied for benchmark datasets and to specific real-time experiments for classification and prediction are discussed. Upcoming sections cover the current trending research topics dealing with optimized artificial neural network concepts and provide some interesting insights for researchers to use in their respective applications domains of interest.
Toolkit for Web Development Based on Web Based Information System
Authors: Selvan S.Muthamil , Krishna Ogiboina Purna Sai , Raviteja Siginamsetty 
Published: November 2019

Abstract
this paper intends to exhibit the social and authoritative parts of electronic data frameworks. Presently we are in the 21st century and two decades will be finished soon. A century ago has been considered as the ascending of Information and correspondence innovation. These days there is expanding advancement of online data frameworks for social and hierarchical divisions Electronic data frameworks in light of web innovations which shares distinctive kinds of Internet convention and assumes an essential part to gather, putting away, gathering and imparting information from various sources and spread data initially. The speed and productivity of electronic data framework which incorporates both neighborhood and worldwide systems, databases and diverse sorts of program for data preparing makes social and hierarchical life less demanding for individuals. The online applications keep up activities of administration. Such applications incorporates quality administration forms, life cycle of authoritative objective, actualizing and sharing creation plan This electronic innovation affects social connection, social conduct and different association issues.
Rehabilitation Therapy for Semi-Paralytic People
Authors: Arikatla Jaya Lakshmi , Putta Navya Sudha , Akula Mallaiah , Rama Mynampati 
Published: November 2019

Abstract
Paralysis is the loss of muscle which functions as a part of the body. Paralysis can affect any part of the body at any movement of an individual’s lifecycle.. It happens when something turnout wrong with the way messages to pass between the brain and muscles. Paralysis can be generalized or localized. It can be either complete or partial type of paralysis. Completely paralyzed people can’t have control over their muscles in the affected areas. Paralyzed people can’t be in a position to move from one position to the other. So, it would be very difficult for them to go for the checkups and fulfill their necessities. This is the biggest problem which people are facing to go for the checkups and observe their health condition. To avoid this problem, in this project a mobile based game therapy is developed. This is a passive rehabilitation exercise for the disabled patients. This exercise tries to activate neuroplasticity. By using this mobile game patient can regain movement in his body especially in muscles. By using this game doctor can be able to check the day to day readings and can analyze the improvement of the muscle strength and prescribe the suggestions accordingly. The improvement in muscles starts very slowly but, trusts the game as long as the patient is playing this game the complete concentration will be towards the game so that the patient can restore daily the functionality of his nerves and muscles easily.
Automation Control of Metro Traction Using Plc and Scada
Authors: Roseline J. Femila , Leela G.V.Siva , Pravallika K.R.S. 
Published: November 2019

Abstract
The high level of error which may lead to scads of damage which may be human life or material damage, inefficiency in supporting changes such as development of new high-performance vehicles Acquisition, time consuming inefficient system of operation leads one to consider an automated railway system. An automated control system which is introduced in this paper with the help of PLC and SCADA monitoring will have a significant effect in the permitting of having an increased speed form of transportation, augmenting services which can increase the full load capacity of a given network, while flexibility in the network will help in developing a system which can be improvised to change traffic control based on the traffic variations. The system provides other prominent benefits over there room temperature counterpart in reduced size, weight (increased power density), efficiency, switching speed, reliability which will result in an overall weight, space, time saving and a save mode travel in the current society.
Symmetrizability of Integer Interval Cartan Matrices
Authors: Dineshkumar C. , Gayathri K. 
Published: November 2019

Abstract
In this paper, we extend Cartan matrix to Integer Interval Cartan matrix by using interval arithmetic operation. We compute symmetrizability condition to the Interval Cartan matrix. It also satisfies the condition for this extention of Integer Interval Cartan matrix; here we focus on the theorem along with the illustration.
A Mixed Objective Assignment Problem
Authors: Ramesh P. , Abdul Razak K. 
Published: November 2019

Abstract
A general assignment problem includes N tasks that intend assign to N workers to what place each laborer has the sufficiency to do all tasks. The objective is to confront the optimum assignment of a number of tasks (jobs) to an enlarge number of services (or persons) at a minimum cost. In this freebie the objectives are proposed as mixed objective which is triangular fuzzy number. Yager’s ranking approach has been used for grade the fuzzy numbers. The Hungarian method is used to solve the problem. The results of the numerical example prove that a fine conciliation solution can be reached effectively.
Digital Image Watermarking Using Optimization and Encryption
Authors: Hema Rajini N 
Published: November 2019

Abstract
In this paper, with the technique of chaotic encryption-based blind digital image watermarking, we introduce a new grey wolf optimization. Discrete cosine transform (DCT) is employed before embedding the watermark within the host image. The image at host is split into 8x8 which is a non-overlapping blocks before employing DCT application, and the watermark bit is included through modifying the differences between the neighboring blocks DCT coefficients. Then, grey wolf optimization algorithm (GWO) is employed. Arnold transform is used along with the chaotic encryption to provide additional watermark security. The presented model is applied to a collection of benchmark images and the results validated the performance in terms of PSNR. The presented method attains maximum PSNR value on entirely given test images.
Synthesis, Electrochemical impedance analysis of silver-doped zinc oxide nanocrystallites
Authors: Giruba M , Christina Rhoda J , Chellammal S , Ravichandran K 
Published: November 2019

Abstract
By using Co-Precipitation method, we have been prepared hexagonal structure of silver-doped Zinc Oxide (ZnO) nanocrystallites at room temperature. The structural characterization was carried out like Powder X-ray Diffraction (XRD). Scanning Electron Microscopy was used to study morphological analysis and EDX used to identify elements presented in prepared samples. Using the Scherrer formula, average size can be calculated. The XRD matched with JCPDS. The aim of the present work is to study the effect of electrochemical impedance frequency dependence properties of pure and silver-doped zinc oxide nanocrystallites were discussed in this paper.
Smart Controlled Electronic Devices Using Brain Functional Conductivity
Authors: Subash R. , Jebakumar R. , Vishnu V. , Shravan R. 
Published: November 2019

Abstract
Envision a future where everything can be controlled with simply our brain. With the development of humankind on the utilization of various electronic gadgets in everyday life, man needs to have simple dealing with to these electronic gadgets and most straightforward one is the conceivable mind wave command to electronic devices. As the technology getting advances mode of interacting with the electronic devices also getting advancement day by day. Beginning with a mechanical switch based controlling of electronic devices got IoT based wireless controlling facility. The currently proposed method is making the provision of controlling of devices just with a thought in the brain. We will be having an EEG sensor mounted on the head to capture the signal which in turn processed and used for triggering the relay to control the device.
A NARX Model to Predict Myocardial Ischemic Beats from ECG Using Features Extracted by ICA and WPD
Authors: Niranjana Murthy H. S. 
Published: November 2019

Abstract
This paper presents a methodology for predicting Myocardial Ischemic Beats from ECG signal using a Nonlinear Autoregressive Neural Network with Exogenous inputs (NARX) model. This technique utilizes the features extracted by integrating independent component analysis (ICA) and Wavelet packet decomposition (WPD) on ECG for detecting Myocardial Ischemic beats. At first, the denoised ECG beat segments are projected on the bases to create the independent component (IC) vectors. Further, these IC vectors are disintegrated by WPD. The feature set for distinguishing ischemic beats is extracted by calculating entropy, mean and standard deviation from wavelet coefficients. These features are input to NARX model for uncovering ischemic beats from normal beats. Several architectures of NARX models were tested for predicting myocardial ischemic beats. The efficacy of NARX architectures are assessed by comparing MSE and correlation coefficient. The NARX model with 2 hidden neurons and 2 delay lines provided the best results with a MSE of 0.0002 and correlation coefficient 0.99, which implies that the NARX neural network has huge potential in the prognosis of Myocardial Ischemic Beats.
Design and Synchronization of Chaotic System using Threshold Controller Coupling
Authors: Biswas Namrata , Raja Mohamed I. 
Published: November 2019

Abstract
A new autonomous chaotic system is designed from the Lorenz family of systems and studied its dynamics both theoretically and numerically. Then two such systems are synchronized using a threshold controller as the coupling element by which complete and asynchronization is achieved. The new system is investigated using MATLAB Simulink and Multisim. The results show that based on the control parameter value the system switches from complete to asynchronization.
Stain Removal Through Color Normalization of Haematoxylin and Eosin Images: A Review
Authors: Lakshmanan B. , Anand S. , Jenitha T. 
Published: November 2019

Abstract
Histopathology images are used for the diagnosis and examination of cancer cells. Preparing and scanning histopathology slides consist of numerous steps of which staining are an important process. But these staining procedures cause multitude problems as there may be variations in the slides due to multiple reasons. Color variations in histopathology images can occur due to inconsistent staining of biopsy tissue, color responses of different scanners or difference in raw materials and manufacturing techniques used by stain. These factors hamper the generalization of automatic image analysis method. Hence there is a need for standardizing the image before analysis by performing stain normalization which is achieved by removing the stains for visual enhancement. Color normalization techniques play a vital in the developing computerized decision support system. In this paper, a detailed study and performance evaluation of various color normalization techniques such as Histogram Specification, Macenko Method, Reinhard Method on histopathology images are presented. In these normalization procedures the mean color of the target image is transferred onto the source image. Quality performance of different stain normalization techniques is evaluated based on Entropy and Structure Similarity Index Measure (SSIM). In this work, we record the time complexity of the color normalization algorithms. The normalization techniques are tested on histopathological images from UCSB dataset and Mitosis Atypia 2014 dataset. This article reviews and summarizes the color normalization techniques on histopathological images for visual improvement.
Credit Card Transaction Based on Face Recognition Technology
Authors: Dhikhi T , Rana Ajay , Thakur Anurag , Kapoor Karan 
Published: November 2019

Abstract
This paper proposes a method for credit card transaction system which will make use of face recognition and face detection technology, using Haar Cascade and GLCM algorithm. The main problem faced by credit card users is attack to lot of privacy issues such as credit card. This generally happens when users give their credit card number to unknown people or when the card is lost. So, we are proposing a system that will reduce the risk of credit card frauds. The system we are proposing will match the image of user’s face with dataset of respective user. A database will be maintained for authentication purpose. If the image matches, that means user is genuine and he will be allowed to proceed otherwise, the user will be denied to do the transaction.
Automatic detection of flying bird species using computer vision techniques
Authors: Vishnuvardhan R. , Deenadayalan G. , Vijaya Gopala Rao M.V. , Jadhav Sheetal P , Balachandran Adithya 
Published: November 2019

Abstract
Bird population is an important factor that may affect ecology of the an area. The main aim is to create a solution for counting different species of birds present in an area and classify them into categories. There are around 1300 species of birds found in India and there can be chance that a new species which remained unidentified till now. We can calculate the number of bird species available in a locality and keep a track whether any species are in risk of being endangered. Calculating the bird population can help the ecologist to search the problem which may endanger them. Manual labor for counting and searching for new species is time consuming and error prone. In the present work, The method of solution is to create a computer vision system using machine learning techniques or deep learning method for a better accurate results. Automatic Bird detection system is primarily useful in providing optimal bird count in region with counting, the system also classifies the bird based upon its species and features.after detecting the bird, the segregates the data according to the bird’s features. This data which is stored in the database can be accessed by scientists, photographers, and also by surveying units as this data provides important information about the number of birds in the area, the type of birds, Their features, and also this data helps scientists in predicting the environmental changes in the particular area by analysing the type of birds visiting the area based upon seasonal changes.