bluuebunny/crossref_metadata_2025_split huggingface dataset:
Eye Controlled Robotic Chair with Night Vision Camera
Authors: Harish Babu G , N. Venkatram Dr 
Published: May 2018

According to Census 2011, in India the population is 121 Cr, from the aggregate residents 2.68 Cr individuals are impaired i.e 2.21 percent of the aggregate residents. From the 2.68 Cr impaired individuals 20 percent of the people disability in movement. Our project is an attempt to make lives of the people suffering from this phenomenon simple. In this framework controlling of wheel chair is depends upon the movements of patient’s Eye [1]. A camera is placed before the user, to catch the picture of the eye & footmarks the locale of eye pupil. Camera used here is Night vision camera which works during night time and as well as daytime and will also work during low lightings. As per the position of eye pupil, wheel chair will be coordinated to move left, appropriate, forward and in reverse. The previous algorithms which are developed for this type of project doesn’t support for the people with squint eye and supports only for the people with 2 perfect pupils, and those algorithms are works only in clear light conditions but this project supports for the people with squint eye as well as people with 2 perfect pupils and works during low lightings. The person can stop the chair by closing his eyes whenever he needs. Moreover, a ultrasonic sensor is ascended in front, so that it can recognize the snags and naturally stop the wheel chair. A GPS module is inserted which finds the location of the wheel chair. A GSM module is inserted which sends the messages in case of emergency situations. This project provides an option called voice module which is inserted and works based on the commands of the patients.
Optimal Scheduling of Micro Grid for Plug-In Electrical Vehicle
Authors: Vijay Kumar K , Bharath Kumar T 
Published: May 2018

Owing to several advantages of Plug-in Electric Vehicles (PEVs) like less noise, emission less, good efficiency and the reduced cost has attention to the governments, researchers and manufactures in recent time. The Plug-in Electric Vehicle (PEV) plays a vital role in replacement of conventional vehicles in future, because of penetration of renewable energy resources in conventional generation. The modernized of micro grid is happening due to usage of clean energy for EV charging. The cost of electric vehicle charging is challenging issue in the development of plug-in electric vehicle. The coordination between renewable generation and conventional generation is very much needed in near future. The dynamic nature of renewable energy resources causes frequent interrupts in electric vehicle charging. The problem of nonlinear power generation with renewable resources is overcome by electric vehicle battery storage system which enables the EV battery to charge during low demand period and gets discharged into the micro grid during high demand periods. This paper developed an optimal schedule for stationary Plug-in Electric Vehicle charging in operation with micro grid. The obtained optimal schedule provides balance between active and reactive power in generation and load as well. The integration of renewable energy resources is achieved through solar, wind in Vehicle-2-Grid (V2G) approach which is used to safeguard to renewable energy resources by store additional energy produced during peak load period and feeding back to the micro grid during low load period. As a result the stable operation of the micro grid and EV charging with low cost is achieved in this paper.
Parallel processing on Big Data in the context of Machine Learning and Hadoop Ecosystem: A Survey
Authors: Vishwanath Brahmane Anilkumar , Murugan R 
Published: May 2018

Emergent Big Data applications have become gradually more essential. In reality, a lot of institutes, businesses and in general entire society from diverse segments depend more and more on information take out from enormous quantity of raw information, statistics and numbers. On the other hand, in Big Data perspective, customary information methods and policies are not as much of capable. They prove a time-consuming receptiveness and are short of quantifiability, measurability, presentation and accurateness. To solve the composite Big Data constraints and difficulties, a large amount effort has been carried out. As an effect, different categories of packages, distributions and technologies have been developed. In this paper an evaluation is done, this studies recent technologies developed for Big Data. It aims to assist to choose and adopt the exact combination of diverse Big Data technologies according to their technological, scientific needs and particular applications requirements. It provides not only a worldwide sight of most important Big Data technologies but also relationship according to special organizational, classifications levels such as Information Storage Level, Information Processing Level, Information Querying Level, Information Access Level and Management Level. It classifies and talks about main tools and its features, advantages, restrictions and treatments.
Comparison of Scheduling Algorithms in The Design of Fault Tolerant Real Time Systems
Authors: Swarna Latha Gade Mary , Sreenivasa Ravi K 
Published: May 2018

Most of the real time systems have the timing constraints. The main important timing constraints of any real time systems are to meet the deadlines of its application tasks. Not only satisfying the timing constraints of any real-time system, but also the functional correctness of application needs to be guaranteed. Meeting the dead line of application is no use if it deviates from its precise output. Timing constraints of the system can be satisfied by choosing proper task scheduling algorithms and the reliability of the system can be reached by providing fault-tolerance. In this paper, various fault scheduling algorithms like fixed priority, EDF(Earliest dead line first), LLF (Least Laxity First),Rate monotonic etc have been studied and compare the parameters like Worst-case execution times, response time, task missed deadlines, Number of preemption, number of context switches, Deadlock and processor utilization factor.
Improvement of position and orientation of Unmanned Arial Vehicle (UAV) with INS/ GPS
Authors: Appala Raju V , Vasundhara P , ChandraKanth Reddy V , Sai Aiswarya A 
Published: May 2018

This paper deals with the methods performing state estimation .that is position and orientation of Unmanned Arial Vehicle (UAV) using GPS, gyro, accelerometers and magnetometer sensors. Various methods are designed for position and orientation measurements of UAV. In this paper we proposed extended kalman filter based inertial navigation system using quaternions and 3D magnetometer. Initially we load UAV truth data from a file ,generate noisy UAV sensor measurements and perform UAV state estimation and display UAV state estimate results with proposed method compares with previously exited method extended kalman filter based altitude and heading reference system using quaternion and 3D magnetometer simulation .Results shows that EKF-INS method gives better position and orientation of UAV.
A Study on Potential of Big Visual Data Analytics in Construction Arena
Authors: Geetha Bhargava Mandava , Vidyullatha P , Venkateswara Rao P , Sucharita V 
Published: May 2018

In most construction and Infrastructure management projects, it is important to ensure and maintain the performance, safety as well as quality in the work to execute the construction in expected period , for monitoring the above parameters i.e. Performance, Safety, Quality and as well as Security, requires data to analyze, determine and test the algorithms, due to eternal increase amount of captured data thorough modern improvements in technology i.e. devices, camera equipped vehicles, Sensors, etc. accommodates an innovative scope to capture present status of construction sites at a less cost analogized to more alternative techniques such as laser scanning technique. Vast endeavours on documenting as-built status, nevertheless, stay at retrieving the visual data and updating Building Information Model (BIM). Hundreds of images and videos are captured but most of the data becomes scrap without proper localize with plan document and time. To take full benefits of visual data for construction status analytics where performance analytics is also included in it, three aspects (reliable, relevance and speed) of capturing, analysing and reporting visual data are captious and tracking development in construction sites needs two direction communication between field crew and management so that performances and changes issues related to task management, completion and outlook can be convey effectively. This paper deals with the investigation of current techniques for influence with help of arising BIM and big data in performance monitoring at construction from reliable, relevance and speed.
Parametric optimization of Edm on Hastelloy C-276 Using Taguchi L18 Technique
Authors: Khadar Basha SK , Kolli Murahari , V.Jagannadha Raju M 
Published: May 2018

Due to development in machining science the use of composites and alloys is a great deal for every industry. Hastelloy C276 the most versatile corrosion resistant nickel based super alloy which is used for industrial applications is considered for doing the experiments .The high nickel and molybdenum content provides better corrosion resistance at extreme environments. In this report, the experiments are performed by using Taguchi L18 technique and their results are used for performance of each process parameters on their output responses. The process parameters considered for experimentation are discharge current, pulse- on- time, type of electrode and pulse off time for the output responses of material removal rate and surface roughness. Eco-friendly (drinking water) is used as a dielectric fluid. The experiments are designed and conducted using Taguchi L18 technique and analyze the influence of each process parameters on machining performance characteristics. Further, mathematical equations were developed using the statistical software MINITAB17.0.ANOVA is used for analyzing the experimental results obtained. It was observed from the response table that the average values of MRR and SR for pulse on time, discharge current, electrode are identified as important process parameters.
Classification of skin cancer images using TensorFlow and inception v3
Authors: Sai V Bhavya , Rao G Narasimha , M Ramya , Sree Y Sujana , T Anuradha 
Published: May 2018

It is easy for a human eye to distinguish the images of similar appearance but classifying the images like that of cancer affected skin requires more expertise. And as the skin cancer cases are increasing globally, it requires more number of human experts. To overcome this problem, many people are working on constructing machine learning classifiers which can detect skin cancer automatically by classifying skin images. This paper concentrates on developing an approach for predicting skin cancer by classifying images using deep convolution neural network. The proposed work is tested on standard cancer dataset and obtained more than 85% accuracy.
Zonal stable election protocol for heterogeneous wireless sensor networks
Authors: Appala Raju V , Sri Harsha V , Bhanu Deepthi N , Prasanth N 
Published: May 2018

Wireless sensor networks play a key role in communication. They are comprised of hundreds sensor nodes with limited energy. So energy utilization major issue in WSN for performing the given task. So most of the protocols are concentrate on energy consumption .Zonal mechanism is one popular WSN routing technique. In this work we are mostly concentrating on optimization of stable election protocol for heterogeneous wireless sensor networks and compare the performance with LEACH and SEP. Most of the work to find stability period, alive nodes and dead nodes, throughput in LEACH, SEP, ZSEP. We are stimulated in MATLAB tool. Stimulation results prove that improvement in stability period and through put is better in ZSEP when compared to LEACH and SEP.
Low power and high speed GDI based convolution using Vedic multiplier
Authors: Priyanka C , Manoj Kumar N , Sai Priya L , Vaishnavi B , Rama Krishna M 
Published: May 2018

Convolution is having extensive area of application in Digital Signal Processing. Convolution supports to evaluate the output of a system with arbitrary input, with information of impulse response of the system. Linear systems features are totally stated by the systems impulse response, as ruled by the mathematics of convolution. Primary necessity of any application to work fast is that rise in the speed of their basic building block. Multiplier, adder is said to be the important building blocks in the process of convolution. As these blocks consumes plentiful time to obtain the response of the system. Several methods are designed to progress the speed of the Multiplier and adder, among all GDI (Gate Diffusion Input) is under emphasis because of faster working and low power consumption. In this paper GDI based convolution is implemented using Vedic multiplier and adder in T-SPICE Software which increases the speed and consumes less power compared to CMOS technology.
Prevention of Spoofing Offensive in Wireless Sensor Networks
Authors: Lakshmi Sowmya U , Sai Kumar reddy M , Madhu Babu K , K.V.D.Kiran Dr 
Published: May 2018

Remote sensor systems are powerless against assaults identified with data fraud and wholesale fraud. Albeit different techniques have been forced to recognize and find assailants, it doesn't concentrate on keeping the hub from assaulting. In this paper, we propose to demonstrate how the hostile of wholesale fraud and pantomime, for example, the surge hostile, happens when the surge hostile sends exhaust parcels to upset the information sent by the hub and side tracks the foe bundles at various way. Utilizing the neighboring hub signature confirmation strategy by mailing the keys to the hubs by key supplier whatever keeps the hub from being assaulted. The most limited way between the source hub and the goal hub was chosen utilizing the AODV. Counteractive action instrument will be exceptionally valuable for snappy distinguishing proof of assailants and furthermore enhance the execution of the structure.
A Survey: Computing Iceberg Queries
Authors: Ravi Pallam , Haritha D , Niranjan P 
Published: May 2018

Knowledge discovery, tasks are deals with huge no of records. Queries are needed to identify unique attributes values and their aggregate that is above a predefined threshold from this huge number of records. This type of queries is called iceberg queries. Iceberg queries requires huge amount of main memory and takes longer time to answer the query. As computer system has limited amount of main memory, the processing of iceberg queries is a challenging task. This paper discusses different methods that are in literature for processing iceberg queries , we also explore pros and cons of these methods and future scope.
Applicataion of ormsby wavelet for generation of synthetic seismic signals
Authors: Sai Sumanth E , Joseph V , K S Ramesh Dr , S Koteswara Rao Dr 
Published: May 2018

Investigation of signals reflected from earth’s surface and its crust helps in understanding its core structure. Wavelet transforms is one of the sophisticated tools for analyzing the seismic reflections. In the present work a synthetic seismic signal contaminated with noise is synthesized and analyzed using Ormsby wavelet[1]. The wavelet transform has efficiently extracted the spectra of the synthetic seismic signal as it smoothens the noise present in the data and upgrades the flag quality of the seismic data due to termers. Ormsby wavelet gives the most redefined spectrum of the input wave so it could be used for the analysis of the seismic reflections.
Route Map of Privacy Preservation to IOT
Authors: Pravin N. Kathavate Mr , J. Amudhavel Dr 
Published: May 2018

Data anonymization is the main feature of privacy preservation, and it assists in eradicating the privacy hazard in data preparation in various applications including IoT. Pseudonymity and Anonymization are two significant security factors that were adopted when sensitive data are shared. In medical field, data is usually distributed horizontally with diverse regions carrying a similar set of characteristics for various anonymization techniques. Accordingly, this paper intends to formulate a review on privacy preservation in IoT. Here, the literature analyses on diverse techniques associated with data hiding, data preservation and data anonymization along with data restoration properties. It reviews 60 research papers and states the significant analysis. Initially, the analysis depicts the chronological review of the overall contribution of different types of anonymization protocols in diverse applications. Subsequently, the analysis also focuses on various features such as applications, measures, key generation and data preservation in healthcare, etc. Furthermore, this paper provides the detailed performance study regarding data hiding and restoration process in each contribution. Finally, it extends the various research issues which can be useful for the researchers to accomplish further research on data preservation in IoT.
A novel planar dual polarized millimetre wave antenna for KU band applications
Authors: B Sowjanya , V Saiteja G , Krishna Mrudhvi , Krishna M , Bhagavan A 
Published: May 2018

A dual polarized antenna array to operate in Ku band is analysed and designed. Cross polarization is the major factor considered. The second requirement is the uni-layer fabrication used for any vertical interconnection accesses. Circular microstrip patches are chosen as the radiating elements. The antenna is fed through the two orthogonal linear edges and shown in microstrip line pattern. Reduction of sidelobes is done by using dolphchebychev distribution. scattering parameters procedure is done to get efficient stimulation. The properties of antenna array simulation are fixed over a bandwidth having center frequency 500MHz. Hence proven, showing that a cross polarised antenna is used for ku band frequencies or millimeter wave applications. The design procedure and parameters are explained clearly to utilize the fact that the antenna array could be reduced.
A Study on Light Weight Cryptography Algorithms for Data Security in IOT
Authors: Sri Lakshmi M , Srikanth V 
Published: May 2018

IOT - things like the smart devices and sensors that connects and communicates through Internet. IOT applications like smart home, smart vehicles, smart retail, which makes the mankind’s life easier. There is a prediction that we will be having million of devices connects to the Internet. Since the sensitive devices like baby monitoring devices, health monitoring devices are the part of interconnected world there is the necessity to address the consequence of the security aspects of the IOT. The built-in nature of the IOT is to trace user’s identity easily, so the security and privacy concerns like stealing the data, disruption of operations and even the loss of life are becoming critical issues in today’s IOT applications. Due to the resource constrained environment in IOT the conventional algorithms is not enough to ensure the data security. So we need a less computational cost in terms of power consumption and memory management and more efficient cryptography algorithms which are discussed in this paper.
IoT Application, A Survey
Authors: Devi Kotha Harika , Mnssvkr Gupta V 
Published: May 2018

Internet of Things ( IoT ) , where physical systems are connected over network to exchange information among themselves and with their surroundings. IoT helps in developing most powerful industrial systems. It finds its various applications in house hold, agriculture, and in various industrial systems. In an effort to understand the growth of IoT , this paper reviews current research trends of IoT , key technologies, and its major applications, and identifies key challenges of IoT. This paper mainly summarizes the applications of IoT in industries
Application of klauder wavelet for generation of synthetic seismic signals
Authors: Neelima S , Saritha A , S.Ramesh K , Koteswara rao S 
Published: May 2018

Analysis of reflected seismic waves gives the information about the earth and its inner core. This aids in monitoring earthquake, petroleum exploration, determination of the earth’s core structure, etc. Wavelet transforms is an efficient tool for analysis of seismic reflected signals. These transforms helps in complete extraction of the seismic signal buried in noise. In this paper an attempt is made to analyze a synthetic seismic signal by using Klauder wavelets. The synthetic seismic signal is extracted by convoluting with the Klauder wavelet. Noise is completely removed as the wavelet spans a large spectrum of signals.
Studying Cloud as IaaS for Big Data Analytics : Opportunity, Challenges
Authors: Manekar Amitkumar , Pradeepini Gera Dr 
Published: May 2018

James Watt steam engine revolution was greatest revolution in mankind history in 20th century. In 1776, the first steam engines were installed and working in commercial enterprises. This revolution minimize and make world smaller for human being, now world is connected seamlessly. “Big Data Analytics and Cloud” these two words are second numerous revolutions in 21st century. We are living in an era of information explosion. These two magical terms are nothing but relatively very new and fortunately diverted all market trends to a new era of computation in last decade. As these two emerging technology are their early childhood, many people were confused with its relevancy and applicability. Cloud Computing is Infrastructure based solution for managing data and computational framework. 2016 was a significantly more important year for this volumes data technology or Big Data eco system as large number of enterprises, and organizations are generating data, storing that data and worried about future aspect of that data. In 2017, corporate world take cognizance of their large volumes structured and unstructured data as these enterprises and organizations continuously generating large volumes data. The term big data doesn’t just refer to the massive amounts of data existing today, it also refers to the whole ecosystem of Storing or gathering data, Different types of data and analyzing that data. In traditional data ecosystem all leverages are with legacy system. Transforming or migration of these traditional ecosystems to the cloud is full of great challenges and benefits. Cloud computing is an agile and scalable resource access computation paradigm, provides heterogeneous platform seamlessly with infrastructure of internet, exclusively for the trapped and work on pre and post process of big data. Now the challenges are finding opportunity and challenges for managing, migrating and abstracting cloud based big data using cloud infrastructure for future eco system of Big Data Analysis. This paper is basically focused on this issue. We try to reevaluate the facts of existing Cloud Infrastructure as IaaS for tomorrow’s big data analytics.
A Survey of using Data Mining Techniques for Soil Fertility
Authors: Kommineni Madhuri , Perla Someswari , Bharathi Yedla Divya 
Published: May 2018

Data Mining is a technique which focuses on large data sets to extract information for prediction and discovery of hidden patterns. Data Mining is applicable on various areas like healthcare, insurance, marketing, retail, communication, agriculture. Agriculture is the backbone of country’s economy. It is the important source of livelihood. Agriculture mainly depends on climate, topography, soil, biology. Agricultural Mining is a technology which can bring knowledge to agriculture development. Data Mining in agriculture plays a role in weather forecasting, yield prediction, soil fertility, fertilizers usage, fruit grading, plant disease and weed detection. The current study presents the different data mining techniques and their role in context of soil fertility, nutrient analysis.