bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of cognitive vehicle assistance and driver safety control management
Authors: Ankamma rao B , Harika Devi M , Veni Kommuri Krishna 
Published: May 2018

In this paper we present new approach for automobiles safety driving system involving the multiple sensor monitoring an area around vehicle and conveying alert the driver. There is some distance between two vehicles if apply break we can lose the control our vehicle. The proposed system works like that it has the four Ultrasonic sensors are fixed four sides of car they will detect the cars and obstacles within in the monitored area based on how much distance they are near to car and alert the driver via leds.an alcohol sensor fixed in the steering if he driver drink alcohol it will detect and switch off the vehicle ignition. The IR sensor monitors the eye blinks the driver. If the driver sleeps it makes ring the buzzer.
A Systematic Review on Integrity and Security in Adoption of Cloud Computing Technologies
Authors: Kumar Mojjad Ramesh , D.B.K.Kamesh Dr , B.K.S. Durga K , Sainath N , Kavitha A 
Published: May 2018

Distributed computing has waved the technological era in the year 2013 at a meeting in San Francisco, with sellers giving a lot of items and administrations that outfit IT which manages to convey request to cloud turmoil. Distributed computing pattern is expanding quickly for making the distributed computing well verse. The initial step for the association is to distinguish correct zone where the cloud issues exist. Surprisingly, the role of distributed computing has uplifted the era of business and government issues which lead to challenges towards security. The role of cloud technology improvements lead to display give business – supporting innovations in a proficient manner than any time in recent memory .the move from server to benefit based innovation got an intense change figuring innovation. However these improvements have made novel security challenges, including certain issues whose impact is a rising.[1] This paper displays a diagram and investigation of distributed computing, with a few security dangers, security issues, as of now utilized cloud innovations and security arrangements.
Explore Big Data and Forecasting Future Values using Univariate Arima Model in R
Authors: Sagar Imambi S , Vidyullatha P , V.B.T.Santhi M , Haran Babu P 
Published: May 2018

Electronic equipment and sensors spontaneously create diagnostic data that needs to be stocked and processed in real time. It is not only difficult to keep up with huge amount of data but also reasonably more challenging to analyze it. Big Data is providing many opportunities for organizations to evolve their processes they try to move beyond regular BI activities like using data to populate reports. Predicting future values is one of the requirements for any business organization. The experimental results shows that time series model with ARIMA (3,0,1)(1,0,0) is best fitted for predicting future values of the sales.
Data migration in cloud computing using honey encryption
Authors: Ravindranadh K , Sai Kiran Mallarapu , Durga Sai Pavan Kumar B , Priyanka D 
Published: May 2018

Cloudcomputing provides variouskindsof servicesfor storingdata, load balancing betweencloudsandprovides an infrastructure for developing applicationsandmanaging them.Duetovariousattractive services provided by various cloudservice providers, users migrating their data from their storage systemtocloudserviceprovider.Whilemigratingdatatoa cloudservice provider there will be security and privacy protection concerns arises.Byconsideringthese concerns we are proposing a secure privacy protection migration usinghoney-encryptioncryptographicalgorithmfordata whichis outsourceddatatocloudandweareusingmigrationprotocolwhile migratingdatafromexisting serverstoragesystemtocloud server storage systemwhichensures dataintegrityand data confidentiality.
Closed loop controlled boost converter using a pid controller for solar wind power system installation
Authors: Sharma Prakhar , Kumar Pankaj , Sharma Himanshu , Pal Nitai 
Published: May 2018

Deployment of renewable energy resources on distributed energy system has reduced the reliance and transmission losses from the utility grid. It also helps to improve the system stability near the load center. Solar and wind are the two highly utilized green energy resources in present scenario. However, the fluctuations of solar irradiation, temperature, wind velocity are the preeminent issue for this type of systems which affects the efficiency of the solar and wind energy system. It requires the interfacing unit to stabilize the output voltage. The proposed work deals with the close loop boost converter with PID controller, which is used to attain a stabilized voltage despite of parameter changes and load disturbances. Designed system will help to analyze the better stable output voltage with efficient system having minimum fluctuation.
A review of different techniques utilized for-casting crop yield
Authors: Bhardwaj Priya , Singh Mrityunjay 
Published: May 2018

The farming structures the establishment of Indian economy. The harvest creation mainly depends on atmospheric conditions such as climate change, rain, soil etc., that impacts on yield improvement. The most of existing algorithms for crop yield prediction utilizes the existing data mining (DM) techniques for forecasting. This paper exhibits an overview on some of the existing techniques mostly used for crop yield prediction.
IoTbased smart and flexible lightning in streets
Authors: Anitha Raju , Nishitha M , Akhila K , Sai Anusha K , Srilekha G 
Published: May 2018

The internet of Things (IOT) is always giving unprecedented answers for the customary issues looked by man.One of the real obstacles in city is we are spending huge expenses on street light. To control the street lights based on detection of sunlight by implemented with smart embedded system. The paper is mainly utilized for smart and climate adaptive lighting in street lights. The street lights are automatically ON during the evening time and automatically OFF during day time.The street light can be accessed to turn ON or OFF at anyplace and anytime through web.In addition to that On top of the street light we are placing camera to track the activities performed on the street and where the recordings are stored in a server. Furthermore a panic button is placed on the pole, If there is any emergency situations like harassment, robbery there is a panic button is available at the reachable height any person can press it if he is in danger. If people are unable to press the panic button, they should use voice recognition which is connected to panic button, when it recognises some commands like help, it automatically press the panic button. Whenever the panic button is pressed, the footages at that time recorded by the camera is sent straightforwardly to the cloud account. The near specific police headquarters can have access of the account by which they can see the incident’s spot. Every region's street lights are associated with the specific area's police headquarters and cloud account can be accessible by each of them. Here GSMTechnology is eliminated completely.Safety and energy consumptions can be ensured by this idea.
Advanced water level meter for alerting about floods
Authors: Sandeep Naidu Ram , Likitha Chowdary Bodapati , Ravi Teja Jujjuri , S.R. Prasad M 
Published: May 2018

This smaller scale show is performed on the premise of a programmable electronic printed circuit AT MEGA 2560, an electronic circuit associated with electrical protections that are situated at a particular stature, inside a water holder: when the water level ascents and achieves the resistors, differs the impedance, the data from water level sensor is transmitted by means of Wi-Fi to a portable workstation, at that point this data is additionally observed in cell phones, where clients can see the water level in waterways. At last, the smaller scale demonstrates is tried by test tests under a controlled domain and attractive outcomes are acquired. The principle point of this task is to plan a framework which will screen and control the water level in the dams and furthermore suggest the concerned expert when the water level surpasses the farthest point.
Analysis and prediction of student placement for improving the education standards
Authors: Anjali Devi S , Vishnu Priya M , Akhila P , Vasundhara N 
Published: May 2018

Students’ academic success can be evaluated based on their performance in the exams conducted by the institutions. In this paper, we propose a scheme where prediction of student final placement can be done based on the marks scored by them in the previous semesters. In order to predict the placement of the student we need some data to analyze. For this purpose we will supply students basic details and their previous academic information into the system which will be used to predict the placement of the student. This is done by generating association rules using apriori algorithm. Admin and user will use this system. Here user will be the student. Admin and user will use their login to access the system. Admin will add academic details of the students, like their SSC, HSC, Graduation marks (up to current semester, Back logs etc.,). User will be the student. Admin and user will use their login to access the system. Admin will add academic details of the students, like their SSC, HSC, Graduation marks (up to current semester, Back logs etc.,). This system can be used in schools, colleges and other educational institutions. This evaluation system is more accurate than other conventional methods. We are using a university data set to predict the placement of the student.
Automated segmentation of knee thermal imaging and X-ray in evaluation of rheumatoid arthritis
Authors: Snekhalatha U , Rajalakshmi T , Gobikrishnan M 
Published: May 2018

Rheumatoid arthritis (RA) is a long lasting autoimmune disorder that affects the multiple joints of human body. The aim and objective of the study was i) to implement the automated segmentation of knee x-ray image and thermal image using fuzzy c means and canny edge detection algorithm. ii) To compare both the imaging modalities by means of feature extraction and correlate with the biochemical method as standard. Fifteen subjects with RA in knee region and 15 healthy controls were included in this study. The segmentation of thermal images was performed using fuzzy c-means algorithm and x-ray segmentation was implemented using canny edge detection algorithm. The skin surface temperature weremeasured in the thermal image of knee regionin both RA and control subjects. The features wereextracted from the segmented region of the knee x-ray image. The automated segmentation implemented in thermal imaging provided better results compared to x-ray image segmentation process. The thermal imaging feature and x-ray imaging features correlated significantly with the standard parameters.
Business driven automation testing framework
Authors: Anand R. , Arulprakash M. 
Published: May 2018

Due to versatile growth of software industry, we need to invent and adapt new technologies to reduce the production cost and to increase the quality. Now a days the industry is moving towards the 100% of automation testing and is being done by the different kind of users. The same test script will be executed by the domain expert instead of a technical expert, so we can’t expect him to understand the complexity of scripts and to relate the test script with business scenarios. To simply the users view of automation testing we need a layer to hide the technical implementation and to introduce some simplified way to understand the test script and relate with business scenarios, if needed he should be able to modify the test scripts without having the technical knowledge. The gap between the customers’ expectations and the actual product behavior will be reduced using this proposed approach.
A Survey onadvances in security threats and its counter measures in cognitive radio networks
Authors: Ganesh D , Pavan Kumar T 
Published: May 2018

Cognitive radio is a promising wireless communication technology that improves spectrum utilization and offers many benefits for internet users. Cognitive radio networks utilizes the available limited resources in a more efficient and flexible way. The main objective of the Cognitive network is to efficiently utilize the unutilized spectrum and meet the demand of the secondary users. some of the important features of cognitive of Cognitive radio networks are dynamic spectrum access, self organizing and flexibility. As Cognitive radio networks are flexible in nature, it will be effected by various security attacks which in turn affects the performance of the network. Furthermore Cognitive radio networks transmit the spectrum in several licensed bands and it also performs dynamic spectrum allocation. Cognitive radio and Cognitive radio networks are wireless in nature these face conventional attacks. In this survey we address various attacks in different layers , new threats and challenges that Cognitive networks face, current available solutions to address layer attacks. In addition applications, open problems and future Research challenges are also specified.
A survey on trade-off between storage and repair traffic in distributed storage systems
Authors: Sowmia D , Muruganantham B 
Published: May 2018

Distributed storage systems give dependable access to information through excess spread over independently unreliable hubs. Application scenarios incorporate server farms, distributed capacity frameworks, and capacity in remote systems. This paper gives a study on the cloud storage model of networked online storage where data is stored in virtualized pools of storage which are generally hosted by third parties. Hosting companies operate large data centersand people who require their data to be encouraged buy or lease accumulating limit from them. The server cultivate overseers, outside of anyone's ability to see, virtualize the advantages according to the necessities of the customer and reveal them as limit pools, which the customers would themselves have the capacity to use to store records or data objects. . The data is stored across various locations, when the user wants to retrieve them, it could be done by any of the encryption methods. At last, in view of existing procedures, promising future research bearings are recommended.
Design and comparative analysis of inexact speculative adder and multiplier
Authors: Hari Kishore K , K. V.Prasad B , Manoj Sai Teja Y , Akhila D , Nikhil Sai K , Sravan Kumar P 
Published: May 2018

A Carry look ahead adder is a sort of the summer used in the logic design of the digital systems. The CLA boost up the speed by decreasing the measure of duration needed to calculate the carry bits. The CLA based outline of the inexact speculative adder is pipelined architecture to incorporate couple of logic paths along its basic way and in this manner, improving the recurrence of operation. This paper presents the comparative analysis of the pipelined inexact speculative adder and the general carry look ahead adder and showed that the delay is reduced to 48.27% when compared to carry look ahead adder and also we have designed the pipelined multiplier using the Inexact speculative adders and observed that the delay is reduced to 48.32% when compared to the normal multiplier. This entail Xilinx ISE Design Suite 14.5 Tool.
Survey on short-term load forecasting using hybrid neural network techniques
Authors: Dalela Shaive , Verma Aditya , L.Amutha A 
Published: May 2018

Load forecasting is an issue of great importance for the reliable operation of the electric power system grids. Various forecasting methodologies have been proposed in the international research bibliography, following different models and mathematical approaches. In the current work, several latest methodologies based on artificial neural networks along with other techniques have be discussed, in order to obtain short-term load forecasting. In this paper, approaches taken by different researchers considering different parameters in means of predicting the lease error has been shown. The paper investigates the application of artificial neural networks (ANN) with fuzzy logic (FL), Genetic Algorithm(GA), Particle Swarm Optimization(PSO) and Support Vector Machines(SVM) as forecasting tools for predicting the load demand in short term category. The extracted outcomes indicate the effectiveness of the proposed method, reducing the relative error between real and theoretical data
Band notched self complementaryultra wideband antenna for wireless applications
Authors: Ramakrishna Ch , A.E.Satish Kumar G , Chandra Sekhar Reddy P 
Published: May 2018

This paper presents a band notched WLAN self complementaryultra wide band antenna for wireless applications. The proposed antenna encounters a return loss (RL) less than -10dB for entire ultra wideband frequency range except band notched frequency. This paper proposes a hexagon shape patch, edge feeding, self complementary technique and defective ground structure. The antenna has an overall dimensionof 28.3mm × 40mm × 2mm, builton substrate FR4 with a relative dielectric permittivity 4.4. And framework is simulated finite element method with help of high frequency structured simulator HFSSv17.2.the proposed antenna achieves a impedance bandwidth of 8.6GHz, band rejected WLAN frequency range 5.6-6.5 GHz with vswr is less than 2.
A Complex shaped crucible frame structure modelling and finite element analysis for stress and deformation
Authors: V. Dhandapani N , Manimaran R , C. Uvaraja V , Sridhararan R 
Published: May 2018

Crucible frame structures are otherwise called as complex frame structures and its study is needed for further improvement in the emerging technology. The frame structure are frequently used an operational system support of other mechanisms of a physical construction and/or steel frame that limits the assembly's extent in this study crucible frame structures are analysed using Finite element analysis and the results are expected in terms of safety for actual use. Based on ANSYS Software, the crucible structure can be meshed (discretized into several parts are called elements). At last, we can apply the boundary conditions and calculate its maximum deformation by applying various loads.
A Fuzzy adaptive hysteresis band controller for three phase four wire UPQC
Authors: Shamshul Haq S , Lenine D , V. N. L. Lalitha S 
Published: May 2018

Unified Power Quality Compensator (UPQC) is used to protect the sensitive loads in the distribution system from voltage and current disturbances. The compensation capability of UPQC depends on the control strategies used for shunt and series converters. Conventional adaptive hysteresis controller pulse width modulation technique had failed to track exactly during transient conditions and disturbances at load and source side. In paper fuzzy adaptive hysteresis controller is proposed for three phase four wire UPQC for compensating voltage sag/swell, current harmonics, voltage harmonics and neutral current compensation. Fuzzy adaptive hysteresis controller can effectively compensate the power quality problems during the transient conditions. A comparative simulation analysis of proposed and conventional methods are presented in this paper using MATLAB/SIMULINK tool.
An approach to reduce turn around timeand waiting timeby the selection of round robin and shortest job first algorithm
Authors: Kumar Sarvesh , Kumar Gaurav , Jain Komal , Jain Aditi 
Published: May 2018

In this research,a study on operating system tells about its working, how it helps as interface between user software and system hardware .To implement this, different scheduling is used to provide multiple processing in a hardware. There are different levels of scheduler applied in different levels of process from ready queue to termination. This paper focuses on the average amount of waiting time and amount of turnaround time of processes. The proposed algorithm purely defines less waiting time and turnaround time as compared to the round robin scheduling and shortest job first scheduling algorithm.
Compensation of voltage Sag using STATCOM
Authors: Venkatesan Savitha , Nagarajan Booma 
Published: May 2018

Due to unpredicted non-linear loads, power quality problems, a raise in the transmission system. One such problem is voltage sag. Voltage sag is caused by the non-linear load which demands reactive power, but the balanced 3F source provides required reactive power of the load with reduced voltage at the receiving end. In this paper, simulation study has been performed to reducethe voltage sag issue. A transmission system with generation source with different loading conditions is considered and study has been done. A 3F medium P model transmission line is designed with a power source of 11kV. A shunt connected compensation unit called Static Synchronous Compensator (STATCOM) reduces the voltage sag in the transmission line. STATCOM provides the required reactive power demanded by the non-linear load along with the source for compensation of voltage sag. The STATCOM circuit comprises of Voltage source converter(VSC) unit and a DC source. Reactive power compensation is done by VSC unit firing angle control. The source of the STATCOM can also be from renewable energy system. This AC source is converted by a AC-DC-AC converter unit.The firing angle is controlled by the control unit which ensures the continuous and balanced power flow even under sudden change in load conditions. The simulation results depict the characteristics of the developed STATCOM.
Heart disease prediction using machine learning techniques : a survey
Authors: V. Ramalingam V , Dandapath Ayantan , Karthik Raja M 
Published: May 2018

Heart related diseases or Cardiovascular Diseases (CVDs) are the main reason for a huge number of death in the world over the last few decades and has emerged as the most life-threatening disease, not only in India but in the whole world. So, there is a need of reliable, accurate and feasible system to diagnose such diseases in time for proper treatment. Machine Learning algorithms and techniques have been applied to various medical datasets to automate the analysis of large and complex data. Many researchers, in recent times, have been using several machine learning techniques to help the health care industry and the professionals in the diagnosis of heart related diseases. This paper presents a survey of various models based on such algorithms and techniques andanalyze their performance. Models based on supervised learning algorithms such as Support Vector Machines (SVM), K-Nearest Neighbour (KNN), NaïveBayes, Decision Trees (DT), Random Forest (RF) and ensemble models are found very popular among the researchers.
Overview Role of Simulation Package in Virtual Manufacturing and for CNC Machinery
Authors: Mahesh R. , Murali J. Ganesh , Arulmurugan R. 
Published: May 2018

Computer Numerical Control Machines (CNC) totally changed the scenario in manufacturing industries in terms of production volume, easy flexibility and with fewer deviations. As customers expect high grade of accuracy, precision, reliable and prompt supply it became essential in the manufacturing sector to reduce the time for developing and proving out new products. Normally programming and proving out the same plays a significant role in the product development cycle. Nowadays several software packages are there to stimulate the tool path, sequence of operations and validation of the program to ensure flawless performance. These packages do serve additional role of optimizing the program sequence and reduce the cycle time involved to manufacture the parts concerned.