bluuebunny/crossref_metadata_2025 huggingface dataset:
Indirect Vector Controlled Asynchronous Motor Drive’s Dynamic Performance and Analysis with A New Modified MPPT Controller
Authors: Pakkiraiah B , Paul Ratnakanth Pallam , Haribabu Ch , Chandra Sekhar O
Published: May 2018

Generation of electricity from the PV system has nowadays chosen as a best energy collecting source, due to its abundance availability and also to save the conventional energy sources to the future generation. Because all the conventional sources are coming to an extinct. That is the reason, everybody are looking towards the available renewable energy resources like wind, solar, bio mass, ocean, tidal and geothermal. But, upon those, solar and wind sources are maximum preferred sources, due to their easy availability and easy way of collection of energy. This paper presents a modeling of solar photovoltaic (PV) array with a new modified maximum power point tracking (MPPT) controller, which enhances the PV system performance even at abnormal weather conditions. That the existed MPPT controllers were developed based upon the ideal characteristics of constant irradiance with variable temperature and constant temperature with variable irradiance. To overcome the above problem a practical data is considered for designing of MPPT controller which is based upon variable irradiance. But here, it is developed with the variable irradiance and variable temperature with better performance of the system. The output obtained from the PV with a new modified MPPT is given to the boost converter with an inverter to find the dynamic performance of an indirect vector controlled asynchronous motor drive under different operating conditions. For inverter control, a space vector modulation (SVM) algorithm is used, in which the calculation of switching times is proportional to the instantaneous values of the reference phase voltages. The dynamic performance responses like phasor current, torque and speed of the drive by the new modified MPPT along with SVM controlling technique of the inverter are compared and analyzed with the existed method for different operating conditions.
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.
Sensor Enabled Wearable Technological Tool to Detect Breast Abnormality
Authors: Kavitha M , Venkata Krishna P
Published: May 2018

Our Historical records say that, Women are back bone to every family. Generally we observe that health risk rate in women increases depends on age. Statistical medical reports proven that, early identification of health risks will increase the survival rate of patient. From last sixty years, we heard that breast cancer is one of the big health dare for women after forty years of age. Early phase detection of breast tumor is a big research issue in both developed and developing countries. Due to the limits in existing breast abnormality detecting tools like mammography, thermography, ultrasound, MRI there is a need to introduce smart, cost effective, patient comfortable, non-ionic radiated compact testing tool to detect breast abnormality at early stage. In this work I am going to propose an advanced sensor enabled wearable technological tool design to detect breast abnormality. This tool is portable, patient comfortable, light weight, cost effective and suitable for dense breast, pregnant women and surgically altered breasts, younger women also.
Text independent emotion recognition for Telugu speech by using prosodic features
Authors: Mannepalli Kasiprasad , Maloji Suman , Narahari Sastry Panyam , Danthala Swetha , Mannepalli Durgaprasad
Published: May 2018

The human speech delivers different types of information about the speaker and speech. From the speech production side, the speech signal carries linguistic information such as the meaningful message and the language and emotional, geographical and the speaker’s physiological characteristics of the speaker information are conveyed. This paper focuses on automatically identifying the emotion of a speaker given a sample of speech. the speech signals considered in this work are collected from Telugu speakers. The features like pitch, pitch related prosody, energy and formants. The overall recognition accuracy obtained is 72% in this work.
A compact disc loaded curved elliptical shaped ultra-wideband MIMO antenna
Authors: Satyanarayana EVV , Kumar Vivek , Mallikarjun Reddy D , Siva Paravathi T , Chandrasekhar Rao J
Published: May 2018

The ultra wide band (UWB) Multiple-Input- Multiple-Output (MIMO) antenna with coplanar waveguide (CPW) having size of 18 x 23 x 0.8mm3 is designed for ultra-wideband (UWB) applications. The designed MIMO antenna contains two symmetrical circular disc loaded curved elliptical monopoles on top of the substrate and common ground plane with Y slot and extended T-shaped stub on bottom of substrate. The T- shape stub is placed on the ground plane to have the better antenna impedance matching and to enhance the isolation between the two antenna ports. To further improve the isolation in between the ports 1 and 2, and also on the ground plane a Y-shaped slot is fixed. Good impedance matching (|S11| < -10dB) in the range from 2.8GHz to 12 GHz is provided by the proposed antenna, and an enhanced isolation of -27dB, low ECC of below 0.002, an acceptable gain of about 7 dBi and an efficiency of above 90%. The obtained result proves that the designed antenna is more appropriate for the portable devices.
Fractal Antenna Design for Multiple Applications
Authors: M Vasujadevi , Akhil Teja K , Divya G , Sai Shanmukh VV , R Dheeraj K
Published: May 2018

The sudden development in in wireless applications has leveled up the use of antennas. Multiband antennas are used to operate at different frequencies for the reliability in various applications. This paper presents design of a novel fractal antenna for multiband applications. Attributes of proposed antenna are simulated using Ansoft HFSS. Due to the homogeneous property in the design of proposed fractal receiving wire it has the various multiband applications. Proposed Antenna design consists of FR4_epoxy material with dielectric constant of 4.4, height 1.6 mm. The operating frequency is taken as 2.4GHz. The antenna is simulated. The proposed antenna resonates at different frequencies. The results are measured and return losses are compared. Here the geometry of fractal antenna is analyzed for the C band resonating at 6.2 GHz, X band resonating at 11.9 GHz and Ku band resonating at 13.8 GHz for S11<-10db.
Vehicular Fog Computing: The Need for a New Paradigm and its Issues
Authors: Sri Gnana Deepika G , Sai Kiran P
Published: May 2018

Smart vehicles participating in VANET have high computing capabilities which lead the demand to support more applications that give safety and effective measures to people. The vehicles in VANET are taking the help of cloud services for communication, computation and storage which benefits in economical way and we call that as vehicular cloud computing (VCC). Due to certain limitations in VCC and also demand for more quality of service applications in smart vehicles a new paradigm called vehicular fog computing (VFC) is proposed which helps to overcome limitations in VCC and provide more quality services to users participating in VANET. Some of the security challenges and possible attacks in VFC are also stated.
IoET: From Paradox To Paradigm
Authors: Kumar Yogi Manas , Uma Darapu , Mahesh Kumar K , Bhanu Prakash P
Published: May 2018

The current importance and future promises of the Internet of Things(IoT), Internet of Everything(IoET) are diligently discussed in this paper. The analysis clearly distinguishes between IoT and IoET which are mostly considered to be the same by novices. Upon examining the current advancement in the fields of IoT, IoET, the paper presents scenarios or the possible future expansion of their applications also considering security aspects as same.
Image classification using Deep learning
Authors: Manoj krishna M , Neelima M , Harshali M , Venu Gopala Rao M
Published: May 2018

The image classification is a classical problem of image processing, computer vision and machine learning fields. In this paper we study the image classification using deep learning. We use AlexNet architecture with convolutional neural networks for this purpose. Four test images are selected from the ImageNet database for the classification purpose. We cropped the images for various portion areas and conducted experiments. The results show the effectiveness of deep learning based image classification using AlexNet.
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.
Analysis on IoT based dynamic street light control system
Authors: Srinivas M , Naga Siva Ram T , Kanthi Aishwarya P , L. Priyanka K
Published: May 2018

The Dynamic street lightening system is designed for energy saving through automation, which is best ever solution for electric consumption as the manual operation for the lightening system for the smart cities is difficult to operate also because of human negligence and maintenance cost is more. Light dependent resistor is used to sense the light intensity measure and transmits the statistics to micro controller and work accordingly that is if the intensity of light increases then the light will be in off mode and if the intensity of light decreases then the light will be in on mode. Through internet connection the status of street lights can be identified through a communication channel called GSM. If at all any light fails to work then alert message is send to the mobile through GSM mobile terminal. This reduces heat emissions, power consumption, maintenance, replacement costs and carbon monoxide emissions.
Implementation of Fast Convolution using Robust Vedic Multiplier of Radix-2
Authors: Paradhasaradhi Damarla , Haridhar Bharinala , V. Sreekanth Reddy A , Sri Charan Dudipalli , Lekhaz Atyam
Published: May 2018

Convolution is an algorithm which is mainly used in video, audio and image processing. Convolution calculation is simple in steps however it consumes a lot of memory as well as power in the computational process. It is a mathematical algorithm which is also used in the applications like filtering, edge detection, de-noising, compression etc., as it can be exploit computational power. In this paper, we implemented the speed of discrete linear convolution using robust Vedic multiplier which is one of the fastest multipliers with two finite-length sequences. By implementing convolution with Vedic multiplier power, area and delay are reduced. This implementation process can be realized by simplifying the convolution building block.
Spam Detection on Online Social Media Networks
Authors: N.V.G. Sirisha G , V.Padma Raju G , Amruta G
Published: May 2018

Now-a-days people are generally using social networking sites for communicating with the other users and for sharing information across the world. The online social networking sites are becoming the significant tools and are providing a common medium for number of users to communicate with each other. The large amount of information that is accessible on the social networking sites retain the cyber attackers, who generally exploit the information available for their benefits. They generally infect the user’s system, appeal the victims to click on malicious links, advertise some products only to gain money. Spam profiles are becoming major security threat used by cyber criminals and also a source of unwanted ads. Twitter is one among several social networking sites which are expanding on daily basis. Spam detection in twitter has become one of the major problems these days. A twitter spam account user nature is analyzed with a target to improve detection of social spam. An innovative technique based on deep learning technology is used for the identification of spam accounts in twitter. These techniques have an advantage that they use raw data to learn high level features on their own, unlike the traditional machine learning algorithms which require native features for the application of classification model.
Incremental Mining of Popular Patterns from Transactional Databases
Authors: Vijay Kumar G , Sreedevi M , Bhargav K , Mohan Krishna P
Published: May 2018

From the day the mining of frequent pattern problem has been introduced the researchers have extended the frequent patterns to various helpful patterns like cyclic, periodic, regular patterns in emerging databases. In this paper, we get to know about popular pattern which gives the Popularity of every items between the incremental databases. The method that used for the mining of popular patterns is known as Incrpop-growth algorithm. Incrpop-tree structure is been applied in this algorithm. In incremental databases the event recurrence and the event conduct of the example changes at whatever point a little arrangement of new exchanges are added to the database. In this way proposes another calculation called Incrpop-tree to mine mainstream designs in incremental value-based database utilizing Incrpop-tree structure. At long last analyses have been done and comes about are indicated which gives data about conservativeness, time proficient and space productive.
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.
CMOS based Power Efficient Digital Comparator with Parallel Prefix Tree Structure
Authors: Lakshmi Prasanna J , Sahiti V , Raghuveera E , Ravi Kumar M
Published: May 2018

A 128-Bit Digital Comparator is designed with Digital Complementary Metal Oxide Semiconductor (CMOS) logic, with the use of Parallel Prefix Tree Structure [1] technique. The comparison is performed on Most Significant Bit (MSB) to the Least Significant Bit (LSB). The comparison for the lower order bits carried out only when the MSBs are equal. This technique results in Optimized Power consumption and improved speed of operation. To make the circuit regular, the design is made using only CMOS logic gates. Transmission gates were used in the existing design and are replaced with the simple AND gates. This 128-Bit comparator is designed using Cadence TSMC 0.18µm technology and optimized the Power dissipation to 0.28mW and with a Delay of 0.87μs.
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.
Designing Talking ATM System for People with Visual Impairments
Authors: Magdum Damodar , Patil Tejaswini , Maloji Suman Dr , T.B. Mohite Patil Dr
Published: May 2018

In this paper, we discuss process of design and development of talking ATM for visually impaired people. Automated Teller Machine (ATM) has become vital part of our life to perform financial transactions without intervention of human banker. ATM facilitates cash withdrawal, balance check, mini statement and fund transfer. But, these banking services using ATM cannot be directly used by some set of people of society such as people with low vision, visually impaired, illiterate as lack of accessing ATM through screens. Even they can be defrauded at ATM centers. To digitally include these set of people, talking ATMs are evolved. Talking ATM provides accessibility to ATM services by providing audio component. Many ATMs employ headphone jack that facilitates user to do transaction with security. The audio information is generated either using pre-recorded speech corpus or through speech synthesis engine. The paper summarizes how ATM works, need, proposed solution of talking ATM for visually impaired users, design and development talking ATM using concatenated Text To Speech.
An Efficient IoT Based Smart Irrigation System and Plant Diseases Detection: A Review
Authors: NagaGeetha M , N.V.K Ramesh Dr
Published: May 2018

The irrigation control and monitoring of the involved variables on the plant growth are actions that farmers must implement in their crops to save water resources and assessing the growth of the plant. In this paper, the literature is conducted on several authors’ works, their modern way of doing agriculture with IoT and image processing combination, thus the paper gives information about various techniques, algorithms, and architectures employed to detect the crop diseases in advance so that proper care can be taken to avoid it. Hence incorporating IoT with image processing gives improved detection ability in the agricultural system. The survey comprises several authors’ workouts of automated Irrigation and crop diseases Detection practices which are currently in use..
Automatic segmentation of multiple lesions in ultrasound breast image
Authors: R Chelladurai , R Selvakumar , Poonguzhali S
Published: May 2018

Breast cancer is one of the leading cancer that affects woman all around the world. Nowadays ultra sound imaging technique is used to diagnose various cancer because of its non-ionizing, on-invasive, and cheap cost. Breast lesion region in ultrasound images are classified depending upon the contour, shape, size and textural features of the segmented region. Seed point is the initial step in segmentation of lesion regions and if that point is located outside the lesion region, it leads to wrong segmentation which results in misclassification of the lesion regions. To avoid this, most of the time the seed point is located manually. In order to avoid this manual intervention, we are proposing a novel method in locating the seed point and also segmenting the breast lesion region automatically. In this method, the image is processed with tan function for effective distinguishing of breast lesion and normal region. Then using the trained neural network, the seed point is automatically located inside the lesion region and from the seed point the region of the lesion is grown and segmented automatically. Most of the past works on automatic segmentation of lesion had concentrated only in single lesion region, but using this proposed method, we were able to automatically segment multiple lesion regions in the image. Outcome of the proposed method is to detect automatically and dynamically separate the lesion region in the range between 90% to 97.5% of images.
Modeling and Implementation of MPPT based Wind Energy System Using Cuckoo Search
Authors: SK Kaleem , Subbanna S Rama
Published: May 2018

This paper presents adjustable speed generators for wind turbines. In order to improve the potential and performance of wind turbine system this paper proposes a concept DFIG. Generally wind nature is not fixed it varies linearly w.r.t time, hence, a MPPT controller is proposed in this paper. This paper presents the DFIG wind energy system. A Control strategy implemented and controlled by framing rotor reference frame axis in terms of direct and quadrature axis coordinates. A PI based RSC and GSC controllers are introduced to control the power through the wind system to grid. This proposed model is implemented and verified by using Matlab/Simulink.
Sentiment Analysis of Movie Review using Machine Learning Techniques
Authors: Uma Ramya V , Thirupathi Rao K
Published: May 2018

Today's online world was fully filled up with blogs, views, comments, posts through various websites and social-surfs. People were habituated with posting every incident into blogs, messed with comments like text and emotions, which are a mixed bag of sad, happy, worry, cry etc. Analysing such data was called as Sentimental Analysis. To analysis, these unordered data we use new emerged technology algorithms. Machine learning a transpire technology which is engaged with almost all the fields, where its algorithms are more powerful that give with better faultless results. In this paper, we are analyzing tweets based on movie reviews using the Multinomial Logistic Regression, Naïve Bayes, and SVM algorithms to compare score value to show the best text analysis algorithm.
Student Information System and Performance Retrieval Through Dashboard
Authors: V.Phani Krishna K , Mani Kumar M , S.G.Aruna Sri P
Published: May 2018

The principle focal point of information mining is to gather diverse information from databases or information ware houses and the data gathered that had never been known, it is legitimate and operational. Instructive establishments can utilize this to keep up all the data of understudy scholastics effectively which is basically imperative. The execution of understudies in their scholastics is a defining moment for their brightest vocation. Foreseeing understudy scholarly execution has been a basic research point in Educational Data Mining (EDM) which utilizes machine learning and information mining methods to look at information from illuminating settings. Estimating understudy scholarly execution is trying since it relies upon different elements. Grouping and Prediction are among the significant procedures in information mining and assumes an essential part in EDM. The requirement for this is to empower the college to mediate and give help to low achievers as right on time as conceivable. In this examination we build up a grouping model usingC4.5 calculation for area savvy execution assessment framework for designing understudies. It additionally brings network between educators, understudies and guardians by keeping them refreshed with their kid execution consistently. The entire framework will be accessible through a protected, online interface inserted in school sit.
A Novel Filtered Based Grid partitioning multiple reducers skyline computation using Hadoop framework
Authors: Venkateswara rao P , Mohammed Ali Hussain Dr
Published: May 2018

Due to the exponential growth of multi-dimensional skyline objects, the computational memory and efficiency of the traditional skyline measures also increases on large spatial datasets. Skyline query computation has attracted a major research problem recently, due to its exponential time and space complexities over imbalanced datasets. A large number of sequential skyline query processing models have been implemented to evaluate the spatial pattern discovery on limited datasets. It is practically expensive and time consuming process to predict various spatial patterns from a large spatial candidate sets. Another major limitation with the sequential spatial pattern mining models is that a large number of spatial candidate sets are generated with duplicate event sets. In the proposed model, a novel parallel skyline processing using MapReduce framework is implemented on large spatial uncertain datasets. In this model, a filtered based k-nearest neighbor approach is used to eliminate the sparsity or empty patterns using the hadoop framework. Experimental results proved that the proposed model has high computational efficiency in terms of time and candidate sets are concerned.
Trust Based Security Model for IoT and Fog based Applications.
Authors: Abhijit J Patil , G. Syam Prasad Dr
Published: May 2018

Wireless sensor networks (WSN’s) are becoming increasingly popular in the current Era. WSN and Smart Devices are key enablers for the Internet of things (IoT) and Fog Computing based applications and it brings IoT applications with enhanced capabilities for sensing and actuation. IOT is a very growing area and having wide scope for research. Integration of WSNs into IoT is today’s need. Adoptions to cloud computing, increasing use of automation of tools, Integration of internet into most activities of human had reached to the stage where Internet of Things based applications are becoming more popular today. Many new applications are now being developed in the field of IoT. The broad areas of application are Home automation, Smart cities, Retail, Agriculture, Manufacturing, Healthcare, Habitat Monitoring, Security and Surveillance etc. With this wide scope the applications are prone to many security threats. Providing Security for IoT and Fog computing-based applications is a Research Challenge. This paper tries to discuss with the common security attacks, Reasons, their counter measures and research directions. We are also proposing a Trust based Security model for implementing application layer level security in IoT and fog.
Innovative Data Transmission and Routing Strategies of Wireless Body Area Sensor Networks: Taxonomy, Review, Issues and Constraints of State of the Art Contributions in Recent Literature
Authors: Anirudh Reddy R , N.Venkat Ram Dr
Published: May 2018

Wireless body area sensor networks (WBASN) is an effective solution that has proposed in terms of improving the solutions and their varied benefits that have been achieved from the usage of WBASN solutions in communication, healthcare domain. From the review of stats on rising number of wireless devices and solutions that are coming up which is embraced by the people as wearable devices, implants for medical diagnostic solutions, etc. reflect the growing demand for effective models. However, the challenge is about the effective performance of such solutions with optimal efficiency. Due to certain intrinsic factors like numerous standards that are available, and due to the necessity for identifying the best solutions that are based on application requirements. Some of the key issues that have to be considered in the process of WBASN are about the impacts that are taking place from the wireless medium, the lifetime of batteries in the WBASN devices and the other significant condition like the coexistence of the systems among varied other wireless networks that are constituted in the proximity. In this study, scores of models that have propose pertaining to MAC protocols for WBASN solutions have reviewed to understand the efficacy of the existing systems, and a scope for process improvement has explored for conducting in detail research and developing a solution.
Decision Making Framework for Decentralized Virtual Machine Placement in Cloud Computing
Authors: B.Rathod Suresh , Krishna Reddy V
Published: May 2018

In distributed cloud environment hosts are configured with Local Resource Monitors (LRM). This LRM monitors the underlying hosts’ resource usage, runs independently and balances the underling host’s load by migrating Virtual Machine (VM) instance. For the dynamic environment, each hosts has varying resource requirement, hosts load cannot remain constant. LRM at each host takes decision for VM migration considering static threshold on its own and other hosts current CPU utilization. This result in chances of getting selected same host for VM placement by multiple hosts to reduce resource usage of underlying hosts. The decision making at each server causes the problem of same host identification by multiple hosts during VM placement and consumes extra CPU power and network bandwidth consumption towards each server. This paper addresses the above said issue by proposing decentralized decision making framework for cloud considering hybrid Peer to Peer (P2P) network topology. Proposed solution results avoiding above said issues and balances the load across servers in DC.
Implementation of asymmetric processing on multi core processors to implement IOT applications on GNU/Linux framework
Authors: Jain. S Poonam , S Pooja , Roy. K Sripath , K Abhilash , B V Arvind
Published: May 2018

Internet of Things brought in a bigger computing challenges where there came a need for running tasks in a multi-sensor and large data processing is involved. In order to implement this requirement multiprocessors are being used for implementation of IoT Gateways. There comes a need for specific tasks having a resource dedicated for its job. To fulfill this we face a hurdle in choosing dedicated processor or shared processor in a Symmetric Processing Architecture. Dedicated processor are the one in which all the tasks are being processed on a single core where as in fair share processors specific processes are assigned to specific cores. Symmetric processing makes use of dedicated processors where as Asymmetric processor makes use of shared processors. Asymmetric Multi Processing can be used in real time applications in order to solve real time problems, one such platform is IOT. In this paper we have evaluated Asymmetric processing on GNU/Linux Platform to test multiple threads running on different multi-core processors architectures to realize the same for running IOT applications having higher computational requirements in the future.
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.
Sub sampling based software GPS receiver
Authors: Harshali M , Venu Gopala Rao M
Published: May 2018

This paper focuses on reducing the processing time of software GPS receiver using sub-sampling techniques. As the GPS signals are wide band signals, sampling frequency is very high. Sub-sampling enables to reduce time for processing. From the simulation results, it is observed that the sampling frequency can be reduced up to 2.5 MHz without loss of tracked signal. The processing time is reduced for software GPS receiver after sub-sampling. The overall reduction in processing time is from 3.456647 sec to 2.15946 sec respectively for sampling frequency 5 MHz , 2.5 MHz. Thus time saved is 37% of the original one.
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.
A Literature Survey on Data Mining Approach to Effectively Handle Cancer Treatment
Authors: Hari Nallamala Sri , Kumar Pathuri Siva , Suvarna Vani Koneru Dr
Published: May 2018

The effective treatment of cancer is not very easy since diagnosis of cancer involves many stages of treatment with gradually changing lifestyles. Physicians play vital role in identifying the correct cause and feel ambiguity for making perfect decisions about hundreds of data available from the internet resource. IDA (Intelligent Data Analysis) which is a part from Data Mining techniques is quiet useful to most of the physicians for decision making about types of cancers. IDA facilitates physicians to classify, detect and analyze the cancer outcome to patients. Healthcare Management System also aids the practitioners to practically search, analyze and compare the result analysis of the patient with existing data in the HMS and guide proper treatment to the cancer affected patient. Health care data analysis comprises enormous data with diversity of health information. One among the most important points that pull down the practitioner’s confidence is that utility of latest software and most sophisticated computing machines. This put them in to the state of confusion for proper and elegant decision making for treating the cancer affected patients. Problems in user interaction, lack of awareness in data mining, improper knowledge in electronic guidelines makes physicians to work with old methods of treatment. Traditional medical practicing and modern methods of computing do not match either because of ignorance. IDA and HMS have significant impact for cancer treatment with speedy diagnosis and faster recovery. This also shows great impact on costs, clinical outcomes and proper guidelines for clinical approach. The prime motto of this survey article is to analyze the survey application, bring out the importance of comparison strategies of IDA to improve decision making for medical practitioner for effective cancer treatment.
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.
Verifying of Autonomous Domestic Robot in AI using JASON
Authors: K V Krishnam Raju Dr
Published: May 2018

The systems that are having self-thinking capability are called autonomous systems. Autonomous systems are used in several modern applications such as the personal, business and industrial systems. The domestic robot is an autonomous system which can be ordered by its owner. The main goal of the domestic robot is to serve drinks to its owner. The functionality is quite simple. The robot goes to the fridge, gets the drink and serves to the owner. The robot also takes care of the health of the owner by limiting the supply of cool drink. The main of this work is to verify whether the domestic robot is meeting its goals or not.
TOA-based source localization using ML estimation
Authors: Prasad Gundu Ram , Pardhasaradhi P , Koteswara Rao S , Gopi Tilak V
Published: May 2018

This paper proposes the Time of arrival (TOA) measurement model for finding the position of a stationary emitting source for Line-of-Sight (LOS) scenario. Here Maximum Likelihood Estimation (MLE) is used as the positioning algorithm. For approximation of the roots of the solution, which directly corresponds to the source location, the optimization techniques used are Gauss-Newton, Gradient descent and Newton-Raphson methods. Two different cases are considered for investigation in this paper. The first case compares the three different optimization techniques in terms of convergence rate. In the second case the error values obtained from two different scenarios are compared, one involving a single trial only, while the second scenario uses Monte Carlo method of simulations. Firstly, the error values, for both the coordinates (two-dimensional), obtained by getting the difference between the measured source positions and the initially guessed source position are obtained for a single trial. Later using Monte Carlo simulation method, the Root-Mean-Square (RMS) error values, for both the coordinates (two-dimensional), for the optimization techniques are obtained. To improve the performance of the algorithm, Monte Carlo simulation has been used for multiple trials.
Virtual Reality in Systematic Life
Authors: G V S Narayana Mr , SubbaRao Gogulamudi Mr , M Kavitha Mrs , D Usha Rani Mrs , Arun Kumar P
Published: May 2018

Past 20 years there has been a rapid growth in virtualization. With the help of Internet of Things [IOT] we can achieve so many things in Virtual Reality [VR]. IOT is the source of connecting devices together by using an address called as IP (Internet Protocol). This will help us operate devices remotely. To simply put VR is the future world. In this paper we would like to show some improvements that can be made to the present VR devices and how can it change the standards of living of people and helps us grow in all the possible ways.
On using Aryabhatta Remainder Theorem to Decrypt a Message with RPrime and Rebalanced RSA
Authors: J.L. Padmaja Ch , S.Bhagavan V , Srinivas B
Published: May 2018

RSA is the most world widely used asymmetric cryptosystem for network transactions. Through this article, we propose a new implementation of Aryabhatta Remainder theorem (ART) in place of the existing Chinese Remainder Theorem (CRT) to solve congruencies in the decryption phase for the faster variants of RSA such as RPrime RSA and Rebalanced RSA. Through our observations, we prove that using ART for CRT has improved the overall decryption speed of RPrime and Rebalanced RSA.
Low latency Path Aware XY-X Routing Algorithm for NoC Architectures
Authors: Rao Musala Venkateswara , V Rama Krishna T
Published: May 2018

Route specific information with the SoC needs a great deal of wiring, which increases the Resistance & Capacitance (RC) component of the system. Network on Chip (NoC) is utilized as the interface to address the problems in SoC, On-chip interconnection network in NoC has gained more consideration over steadfast wiring and buses, like lower latency, scalability and high performance. Present routing algorithms in NoC is suffered from load balancing at incarnation networks under non-uniform traffic conditions, causes increase the NoC trade-offs (latency and throughput). Adaptive routing is a technique to progress the load balance, but previous adaptive routing techniques used uniform traffic patterns to form the routing decisions. This paper proposes a new approach at non- uniform traffic patterns in channel state and path specific, Path Aware Routing (PAR XY-X) uses a timeout piggybacking for acknowledgement and load shedding to avoid congestion which choose optimistic path calculation unit to connect the destination node without glue logic decisions in routing. PAR XY-X outperforms the Normal XY routing by 20% and 33% with respect to Avg.latency and throughput.
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.
Embedded Linux based agricultural field monitoring and automation using IoT
Authors: L V S Aditya Bhrugumalla , Subrahmanyam K
Published: May 2018

The main idea of this venture is to have an irrigation system which is self-controlled .it is also observed that the setup is available for a low price. Wi-Fi technology is used to design this setup. It also aims to reduce manual operation in the agricultural field. The changes taking place are noted. The results obtained are further used to develop the field. As the whole setup is online the readings and values are obtained in real-time a Liquid crystal display is used to know the readings of the conditions.
MANOVA- A Multivariate Statistical Variance Analysis for WSN Using PCA
Authors: S Varakumari , PVRD Prasad RaoDr Dr , Sirisha M , K.R.R.Mohan Rao Dr
Published: May 2018

Wireless sensor systems (WSN) have turned into a successful answer for an extensive variety of uses. Most customary WSN models comprise of static hubs that are thickly sent over a discovery region. The total administrations of a characteristic part in the Wireless Sensor Networks (WSN) area since they fundamentally diminish the measure of information transmissions required and increment the vitality proficiency in those systems. All current accumulation strategies have been created in light of scientific models or capacities, the WSN client won't approach the first perceptions. Through this report, we propose a calculation that enables the base station to admittance the discoveries by presenting a dispersed technique for calculating the Principle Components Analysis (PCA). The recommended calculation depends on the transmission workload of the middle hubs. At whatever point you utilize PCA, include approaching arrangement from a downstream customer in a bundle, and accordingly, a middle hub not just sends a parcel as opposed to retransmitting all parcels. Subsequently, we can accomplish a significant lessening in information communication. We have broken down the execution of the planned calculation concluded arithmetical reproductions. The trial comes about demonstrate that our calculation works superior to anything the conglomeration in view of last age PCA calculations, for example, PCAs regarding exactness and proficiency.