bluuebunny/crossref_metadata_2025 huggingface dataset:
Dc electrical properties of semiconducting cobalt oxide substituted lead vanadate glasses
Authors: K. Brahmananda Rao K. , V. Ramesh K. , Tejeswara Rao P.
Published: July 2019

Semiconducting lead vanadate glasses with CoO substitution represented as xCoO-(50-x) PbO-50V2O5 with x=5,10 and 15 mol% were prepared by melt quenching technique. They were characterized by X-ray diffraction (XRD), Scanning electron microscopy (SEM), differential thermal analysis (DTA) and DC electrical conductivity. The overall features of these XRD curves reveal the amorphous nature of present glasses. SEM investigations were conducted for the micro structural characterization of V2O5 crystal phases. Density was observed to decrease with an increase in CoO content. The dc electrical conductivity of the present system increases as the concentration of substitution of CoO increases with 5molpercentage to 15molpercentage.
Big data and semantic web, challenges and opportunities a survey
Authors: Ahmed Jeelani , Muqeem Ahmed Dr.
Published: July 2019

In recent years, vast and complex amounts of data are being created and making it difficult for traditional data processing applications to manage them. The coming of the Internet prompted monstrous spike in the volume of information being made and made accessible. World Wide Web consortium W3C and international standardization body of the web spread the Semantic Web. It is an extended form of current web which provide easier way to search, reuse, combine and share information. In the last few years, major businesses corporations have demonstrated interest in incorporating semantic web technology with big data for added value. Indeed this incorporation has some benefits as well; it increases end-users ability to self-manage data from various sources, it on focuses changing business environments and varying user needs and handles concepts and relationships, manages terminology while connecting different data from varied data sources. For Social Network Analysis (SNA) new methods are needed by combining Big Data and Semantic Web technologies as a way to utilize and add capacities to existing frameworks. Moreover, the fast changing business requirements and latest industry culture of Agile Development needs a robust yet flexible solution for Business Intelligence and by using distributed enterprise level ontologies Data Warehousing can be incorporated. This paper is an attempt to focus on effects of incorporating Big Data with Semantic web, how Semantic Web making Big Data smarter, revisit the Big Data and Semantic Web challenges and opportunities, relationship between them and finally we summarizes with future direction of this integration
Snap and split: an android application for bill payment using tesseract OCR
Authors: Kata Sugamya , Pabboju Suresh , Babu Vinaya , Medishetti Anudeep
Published: July 2019

Snap and split is a mobile application which uses Optical character recognition to recognize the bill from a printed sheet. It provides an option to tag users and telling them about the shared bill by pushing a notification. Users can tap and pay the bills instantly.Tesseract is one of the best image recognition tools present and uses separate packs for various languages.
Biomimicry architecture: new dimensions of creativity an exploratory approach in academia
Authors: F. M. Mohamed Mohamed , . .
Published: July 2019

The Universe around us stands as a proof of the greatness of God. Everything around us, small or huge, tiny or great, all confirms the fact that this universe has a creator who initiated it and kept running and maintaining it. No one can ignore such fact. Allah has created all aspects of beauty and perfection. Despite the vast technological and scientific development that humanity witness these days, yet we still discover new indications of God's creativity and miraculous formations every day. This fact was the source of inspiration for architectur- al designers in coming up with new inventions and creations that help regeneration and natural environmental sustainability. “Biomimic- ry” is certainly one of these approaches that consider nature as its inspiration towards a different –hopefully, a better - future for humani- ty. This research sheds some light on a vision that took place in fall2014 at the department of architecture, Effat University, KSA. A senior studio (studio7) was targeted to explore the potential of weaving the “Biomimicry” approach within the syllabus of that studio. This initiative had been proposed by the team supervising this studio as an exploratory one before the call from “Makkah Techno-valley Company (MTV)” to design a Research Center (RIM) was launched. The RIM project aspires to play a major role in offering a support- ive environment for youth in Saudi Arabia enhancing their abilities and developing their skills to experience achievement within “MTV” main campus. The study aimed at exploring the possibilities of implementing such an approach within a GCC country with its entire unique educational context.
Performance comparison of SRAM cells in 45NM technology in the presence of a memory cell control circuit
Authors: Jagadale Sanket , Phapale Aniket , V. Sai Varun Sasthry T. , S. Kanchana Bhaaskaran V.
Published: July 2019

Lowering power consumption and increasing the noise margin have become the two most important aspects to be considered in SRAM design. Additionally, a stable operation with good memory retention capability has gained greater importance in obtaining good yield at low-voltage and low-power SRAM designs, due to the fact that parameter variations play a major role in scaled technologies. In this paper, the 6T SRAM, 7T low power SRAM and 7T multi threshold low power SRAM designs are designed, to incorporate power gating technique. The architecture of each of the SRAM designs and their working are analyzed thoroughly. The outputs of the read, write and hold operations with transient response are observed and the power dissipation and static noise margin (SNM) of the each of the SRAM cells is calculated and compared. The paper also presents new power reduction solution through the cell control circuit which reduces the unwanted and spurious switching activities during read and writes operations. The paper demonstrates the reduction of the power con- sumption through the use of cell control circuit.
Implementation of machine learning techniques to control the speed of the vehicles
Authors: S. Satyanarayana M. , T.M Aruna , G.N Divyaraj
Published: July 2019

Accidents have become major issue in Developing countries like India now a day. As per the Surveys 60% of the accidents are happening due to over speed. Though the government has taken so many initiatives like Traffic Awareness & Driving Awareness Week etc.., but still the percentage of accidents are not getting reduced. In this paper a new technique has been introduced to reduce the percentage of accidents. The new technique is implemented using the concept of Machine Learning [1]. The Machine Learning based systems can be implemented in all vehicles to avoid the accidents at low cost [1]. The main objective of this system is to calculate the speed of the vehicle at three various locations based on the place where the vehicle speed must be controlled and if the speed is greater than the designated speed in that road then the vehicle automatically detects the problem and same will be intimated to the driver to control the speed of the vehicle. If the speed is less or equal to the designated speed in that road then the vehicle will be passed without any disturbance. The system will be giving beep sound along with color indication to driver in each and every scenario. The other option implemented in this system is if the driver is driving the vehicle in the night and if he feel drowsy the system detects it immediately and alarm sound will be initiated to wake up the driver. This system though it won’t avoid 100% accidents at least it will reduce the percentage of accidents. This system is not only to avoid accidents it will also intelligently control the speed of the vehicles and creates awareness amongst the drivers.
VHDL Implementation of low power turbo coded OFDM physical layer for wireless communication
Authors: Shrimali Yanita , Ballabh Sharma Janki , S. Meena R.
Published: July 2019

Orthogonal Frequency Division Multiplexing (OFDM) is exceptionally favored system for rapid information transmission over remote channel. In this paper, VHDL implementation of low power turbo-coded OFDM (TCOFDM) Physical layer architecture is presented. In this architecture a low power memory-less pipelined FFT processor and Log-map turbo encoder/decoders are used to provide high throughput and lower complexity. Log-map turbo decoder provides high speed with good error correction capacity, while FFT/IFFT processor with single delay feedback (SDF) memory less architecture provide improved area and power efficiency. Proposed TCOFDM system is implemented using Xilinx ISE Design suite in the simulation results shows that the proposed scheme is having low power, high speed, high throughput and smaller area in comparison to other schemes.
Seismic and blast loading performance of a gypsum panelled prefabricated building
Authors: G Gayathri , M Mini K , S Sruthy
Published: July 2019

Urge for modern technologies and limited space leads to the idea of light weight building technology that can resist major loading condi- tions and can even be used in lands with very poor soil profile. For proper understanding of the structural response, building needs to be evaluated for natural hazards like seismic and manmade calamities like blast loading along with the normal forces acting on the structure. Whole building and structural components are also to be evaluated to study the progressive collapse of the building. This paper includes the study of static, seismic and blast loading effects on a conventional and a prefabricated building. The structural components and con- nections are also evaluated to forecast the strength of a prefabricated building using FE method. Gypsum wall panel incorporated with glass fibres and casted with cavities, as hollow and filled, are used as building panel. This study is useful in suggesting an innovative technology which is light in weight and cost effective with composite structural components.
Tree replanter: a solar powered approach
Authors: V Aromal , G.L Gokulnath , Prasad Geena
Published: July 2019

Tree Transplantation is referred to as the procedure of unearthing the trees and replanting them from one location to another with the objective of re-growing the tree to a new location. This involves moving the tree with the root ball-system thereby protecting while tak-ing up the wider roots. In the proposed design, we use electromagnetic linear actuators working with solar energy instead of hydraulic or pneumatic actuators which consume fossil fuels. Here, a three-blade system is used to unearth the tree wherein the rare blades are opened to encircle the tree and the blades are positioned around the tree to ensure that the root ball is at an equal distance from all sides of the trunk. The blades are closed to remove the tree with the root ball intact. The tree with the spade is adjusted to the truck for safe transport.
Genetic algorithm based ANN to predict compressive strength of siphon for different fiber volume fraction
Authors: Santosh Kumar Gottapu , Rajasekhar K
Published: July 2019

This paper presents the applicability of Genetic Algorithm based Artificial Neural Network (GAANN) for predicting Compressive strength of Slurry Infiltrated Fibrous Concrete (SIFCON) prepared with manufactured sand for different fibre volume fraction (8%, 10% and 12%) as input vector. The network has been trained with data obtained from experimental work. The proposed GAANNs model is successfully used for predicting compressive strength of SIFCON (output vector) for various fibre volume fractions (2%, 4%, 6%, 14%, 16%, 18%, 20% and 22%) at 7 days, 28 days and 56 days of curing respectively. After successful learning GA based ANN model pre- dicted the compressive strength property satisfying all the constrains with an accuracy of about 85%.The various stages involved in the development of genetic algorithm based neural network are addressed in depth in this paper.
Analysis of large volume data processing using clustering algorithms
Authors: B Sarada. , Murthy. M Vinayaka , Rani. V Udaya
Published: July 2019

The study of large dataset with velocity, variety and volume which is also known as Big data. When the dataset has limited number of clusters, low dimensions and small number of data points the existing traditional clustering algorithms can be used.. As we know this is the internet age, the data is growing very fast and existing clustering algorithms are not giving the acceptable results in terms of time complexity and spatial complexity. So there is a need to develop a new approach of applying clustering of large volume of data processing with low time and spatial complexity through MapReduce and Hadoop frame work applying to different clustering algorithms, k-means, Canopy clustering and proposed algorithm .The analysis shows that the large volume of data processing will take low time and spatial complexity when compared to small volume of data.
An approach to achieve high efficiency for large volume data processing using multiple clustering algorithms
Authors: B Sarada. , Murthy. M Vinayaka , Rani. V Udaya
Published: July 2019

Now a days data is increasing exponentially daily in terms of velocity, variety and volume which is also known as Big data. When the dataset has small number of dimensions, limited number of clusters and less number of data points the existing traditional clustering al- gorithms will give the expected results. As we know this is the Big Data age, with large volume of data sets through the traditional clus- tering algorithms we will not be able to get expected results. So there is a need to develop a new approach which gives better accuracy and computational time for large volume of data processing. The Proposed new System Architecture is a combination of canopy, Kmeans and RK sorting algorithm through Map Reduce Hadoop frame work platform. The analysis shows that the large volume of data processing will take less computational time and higher accuracy, and the RK sorting does not require swapping of elements and stack spaces.
Properties of geopolymer pervious concrete made with GGBS
Authors: Babu Chokkalingam Ramesh , Subbu L Prakkash , Raj R Thangavel , Sawant M Shubham , . .
Published: July 2019

Pervious concrete is a light weight concrete containing voids in the range of 14 to 31%. The usage of pervious concretes has been in- creased due to its merits on pollution control and environmental considerations. The pervious concretes are also used to reduce the storm water runoff and recharges the underground water table. Eventhough the pervious concrete has lot of merits, it also has consider- able demerits related to strength issues. In order to achieve the strength high cement content mixes may be incorporated which is not a viable solution. In this paper, geopolymer technology has been used to develop pervious concrete. Geopolymer pervious concrete is pro- duced using GGBS as raw material and sodium hydroxide and sodium silicate as activator solution. Five mixes have been developed with varying GGBS content of 450, 460, 470, 480 and 490 kg/m3. The cement to aggregate ratio is fixed at 1:3 for all the mixtures and the water cement ratio is kept constant at 0.3. The compressive strength revealed that strength of around 20 MPa was attained for all the mixtures and strength increases with respect to the increase in GGBS content. There was not significant changes in the permeability property since the aggregate cement ratio is maintained for all the mixtures.
A review of recent developments in geopolymer concrete
Authors: Chithambar Ganesh A. , M. Muthukannan Dr.
Published: July 2019

Geopolymer concrete is proved to have high strength, lesser shrinkage, resistance against reinforcement corrosion, acid and sulphate resistance, freeze-thaw resistance, fire resistance and resistance to alkali-aggregate reaction. There are many parameters which influence the strength characteristics of Geopolymer Concrete. They are types and fineness of Source alumino silicate material used, concentration and type of alkaline activators used, curing temperature and curing time, utilization of M-sand etc. High performance characteristics could be achieved through the correct choice of these parameters. This review paper focuses on the influence of different variables on the properties of geopolymer concrete and the progress in the field of geopolymer concrete. Consequently many research papers pertaining to the geopolymer have been reviewed in this state of art paper.
Synthesis of silicon-based polymers for solid state lithium polymer batteries
Authors: Vangol Pratap , Baksy Aronya
Published: July 2019

This paper proposes the utilization of silicon based polymers for solid state lithium polymer batteries, thereby allowing batteries to be more rugged by decreasing electrolyte volatility and also making them eco-friendly.
Multi-objective optimization of WEDM process parameters for taper cutting of AISI D2 tool steel
Authors: L. Uday Kiran K , Nagaveni T , Saraswathamma K , Prasad AMK , Chandra Mohan Reddy G
Published: July 2019

Wire electrical discharge machining (WEDM) process is one of the most popular method for the producing complex geometries in hard and wear resistant materials such as those used in tooling industry. This taper cutting involves in making of inclined surface, and it is particularly significant in the manufacturing of tooling that requires draft angles. In the present paper, experiments were conducted in order to find the effect of process parame- ters such as taper angle, geometrical thickness and servo voltage on response variables such as angular error and cutting speed on AISI D2 tool steel using statistical design of experiments. The experiments were planned using Central Composite design (CCD) which is part of Response Surface Methodology (RSM) – involving three variables with five levels. Multi objective optimization was conducted for maximizing the Cutting speed and minimizing the angular error using genetic algorithm. The optimization procedure leads to creation of non-dominated optimal points which gave an insight regarding the optimal operating conditions of the process.
Glass fiber reinforced concrete (GFRC) - strength and stress strain behavior for different grades of concrete
Authors: Kumar Poloju Kiran , Rahul Chiranjeeevi , Anil Vineetha
Published: July 2019

Concrete is a frail building material in strain. Characteristically, because of variety in temperature small cracks will be available in concrete. In addition, solid experiences low rigidity, constrained flexibility and little protection from splitting. Plain concrete will create splits because of plastic shrinkage, drying shrinkage and different reasons also .The advancement of these small scale breaks causes flexible miss happen-ing in concrete. The solid with no fiber is considered as fragile and feeble material. Related to glass fiber use there lies numerous techno efficient inquiries that settles on the decision of GFRC over strengthened cement troublesome. This paper exhibits the change in the mechan-ical quality properties and flexibility properties of Glass Fiber Reinforced Concrete. An Experimental program was done with and without utilizing glass fiber in various rate 0 to 0.09 percentages in conventional concrete keeping in mind the end goal to enhance the mechanical properties, stretch strain conduct and arrangement of splits. In light of the outcomes acquired from the trial comes about the conclusion is that both fiber and cementitious lattice can hold their physical and substance properties and they deliver a blend of properties that can't be accomplished when these segments are acting alone.
An enhanced rule mining algorithm to detect suspects of crime against women in the state of Tamil Nadu
Authors: Usha D. , Chitradevi D.
Published: July 2019

Crime against women in India has become a prominent topic of argument in the recent years and the issue has been brought to the foreground for concern due to the increasing trend in crimes performed against women. It is the major challenge to the investigators to detect and prevent crimes, particularly crime against women. Most of the crimes get reported and a massive dataset is being generated every year. Analyzing the crime reports can help the law enforcement officers to take preventive measures for reducing the crime, but processing this voluminous data is backbreaking and error prone. So, the application of various data mining techniques can help in visualizing the crime trend. Crime is one of the interesting applications where data mining plays an important role in terms of prediction and analysis in the interest of society. This paper covers in detail analysis of modus operandi of committing crimes and effective use of data mining techniques and algorithms in narrow down to identify the criminals at a short span of time.
A study on fatigue life of RC bridge and its improvement methods
Authors: B Neha , S Sruthy , T.M Rahul
Published: July 2019

Fatigue is a crucial factor which affects the total life and serviceability of highway bridges. There are several factors that contribute to the development of fatigue in RC bridges. Among them, traffic loads, wind loads and corrosion of reinforcement are some of the important factors to name a few. In order to address these fatigue issues and improve the fatigue life of highway bridges, many improvement meth- ods have been suggested in the literature. This study attempts to investigate the effectiveness of various improvement methods suggested in the literature. The improvement methods that has been included in this study are externally bonded reinforcement and deck overlay. To accomplish the objective, an existing highway bridge was selected based on the structural details and traffic data and then various improvement methods were applied to analyze its improvement in fatigue life. For analysis, an embedded reinforcement modeling was carried out in ANSYS followed by a nonlinear analysis in ANSYS workbench. The results of the study were found to be in alignment with AASTHO LRFD (2007), IRC SP 60(2002), IRC 6 (2014), IRC SP 37 (2010) and IRC 37 (2012) codal provisions.
Performance analysis of paper, BER and snr of OFDM for different modulation techniques: a survey
Authors: Y.K Shobha , H.G Rangaraju
Published: July 2019

The subcarriers must be kept orthogonal to each other, which are called as an Orthogonal Frequency Division Multiplexing to achieve a better performance by using multi carrier modulation. But an injury to reputation of an OFDM method is of its enormous Peak power ratio. This paper is purely based on performance analysis of PAPR, BER and SNR by using different modulation techniques and different schemes
Challenges and issues faced by IT industries to maintain environmental sustainability
Authors: Sarita Rathi Ms. , Shyamalendu Niyogi Prof.Dr. , Jasvinder Kaur Dr.
Published: July 2019

Green should be implemented not only at the disposal stage of a computer and laptop but it should also be implemented at manufacturing and consumption stages. Companies like IBM, HP, HCL, Microsoft, Wipro, Cognizant etc. are working on the green design of a computer. HCL is taking many initiatives such as Green Edge, green services and green peace to reduce the effect of toxic chemicals and hazardous materials. Green Edge is a framework on which HCL is working to improve the manufacturing process of products to make them green and economically viable. TCS is reducing the impact of their and their customer’s activities by adopting the 3-R strategy, which helps to reduce, reuse and recycle the waste produced by them. The goal of TCS is to achieve zero wastage till 2020. Cognizant’s initiative is Go Green. Go Green is launched in 2008; its main purpose is to recycle the waste and to save and reduce energy consumption. While taking these initiatives IT industries are facing many issues and challenges to produce toxic free products. Some of those challenges and issues are discussed in the paper.
Designing controller for single area power plant using model order reduction method
Authors: Chandra Gauri , Mathew Lini , Negi Richa
Published: July 2019

A two-step method for designing controller for a single area power plant (SAPP) is proposed. In the first step, a lower-order (lth-order) model for a higher-order (hth-order) power plant is obtained using dominant pole retention and Padé approximation method and a controller is designed for this model. This controller is then implemented to original higher-order power system in the next step. The method preserves stability and disturbance rejection is also satisfactory.
Composite braking module for an electric vehicle
Authors: K.R Bharath , M.K Sreenivasan , Sivaraman Gokul , Vineeth Kumar Reddy Bededala
Published: July 2019

The efficycle, is a hybrid tricycle which runs on manual and electric power. This paper proposes a method to design a braking load to dissipate the excess energy produced when there is no more requirement for the battery to be charged by regenerative braking. This module was designed for an operating voltage of 8V, resistance value of 0.16 ohm and with a maximum current capacity of 200 A. This resistor was coupled with a buck converter to step down the voltage across the battery to a value convenient for operation of the dissipation resistor.
A Method For Detecting Duplicate And Near-Duplicate Images Penetration
Authors: Ramesh Shahabadkar Dr. , S Sai Satyanarayana Reddy Dr. , Devika P.
Published: July 2019

A method for detection of duplicate or near-duplicate image penetration from images in the similar group by distribution of color and other attributes of the image. Distinctive sceneries of the images penetration are identified. Each couple of images penetration with at least one distictive scenary is mutual; the distictive scenary of each image penetration is allied to normalize whether the couple is duplicates or near-duplicates.
Homomorphic encryption security - a review
Authors: Phani Prasad J. , Seetha Ramulu B. , Amarnatha Reddy E.
Published: July 2019

As the Data and Technology is increasing exponentially the security and privacy issues are becoming a major concern in the present scenario, lot of security mechanisms are in to real time and practice, but even there are some bottlenecks with the existing security techniques. In this work we are giving the essence and importance of an encryption scheme called homomorphic encryption and its related issues.Â
Attribute Based Image Retrieval and Segmentation using On-tological Approaches
Authors: Mamatha Ch , V. Anandam Dr. , Chatterjee Priyadarshini , Vijaya Kumari Hepshiba
Published: July 2019

Content based image retrieval is gaining more and more importance as it is an apt approach to retrieve an image. The image is retrieved based on certain texture. Ontology is a branch of Meta Physics that helps in analyzing an input image based on certain textures. Ontology helps to retrieve an image based on its properties. Ontology describes a domain. With that domain, we can proceed further to understand the relation between the features present in the domain. There are biological-ontologies to analyze biological outcomes. The field of information technology can be combined with biological ontology to study the results of different biological effects. With the systematic concept of ontology that includes rules, classes, relations etc we can understand an image better that eventually helps in accurate image retrieval. Ontology can be generic or domain specific. In this paper we will be using domain specific ontology used to analyze the features of digital images along with image segmentation to retrieve an image. We will be testing our proposed system using the colored images of mammals. In case of image segmentation we will using the general techniques already existing.Â Â
Towards Cloud of Things from Internet of Things
Authors: Vaishnavi D. , Rahman Shawon , Ramalingam D.
Published: July 2019

The techniques Internet of things (IoT) and Cloud Computing (CC) are becoming a part of our day-to-day life; where IoT connects a billion numbers of devices to share the information by communicating each other and CC grants convenient, on-demand scalable network access in order to utilize the computing resources and it facilitates dynamic data integration from diverse sources. Both techniques are having their own pros and cons. So, a novel paradigm called cloud of things (CoT) is modeled by integrating the both CC and IoT, which enables a large number of applications to get advantages of IoT as well as CC. This paper delivers the basics of the technologies, motivations to model the cloud of things and its benefits. Also, it discusses the implementation challenges.Â Â
A dynamic programming approach to manage virtual machines allocation in cloud computing
Authors: Ouammou Abdellah , Hanini Mohamed , Ben Tahar Abdelghani , El Kafhali Said
Published: July 2019

As a result of the dynamic nature of Virtual Machine allocation in cloud computing, it is not easy to manage system resources or choose the best configuration based solely on human experience.Â  In this work, we used stochastic modelling instead of comprehensive experiments to evaluate the best resource management of the system. In such complex systems, choosing the best decision is a challenge, for this reason we have designed a heuristic algorithm, specifically, dynamic programming as a resource management and programming tool that finds a way that attempts to satisfy the conflicting objectives of high performance and low power consumption. As a scenario for using this algorithm, we addressed the problem of virtual machine allocation, a subset of physical machines is designated as "reserve", and the reserves are actives when the number of jobs in the system is sufficiently high. The question is how to decide when to activate the reserves. The simulation results demonstrated the benefit of using our framework to identify the policy for consolidation or for a low energy consumption and in order to have a good quality of service in the system
Evaluating the QoS Cognizance in Composition of Cloud Services: A Systematic Literature Review
Authors: V L N Sujith A , A Rama Mohan Reddy Dr. , K Madhavi Dr.
Published: July 2019

Enterprise level computing constantly investigates novel approaches that maximize their profits and minimize their expenses. With the rapid growth of cloud computing XaaS â€“ â€˜anything as a serviceâ€™, service providers are enabled with the rapid deployment of virtual services to service requestors. Because of the enormous growth in the variety of the services and based on the demand of the virtualized resources, cloud service providers are facing tough competition to facilitate the composite service requests made by the service requestors. QoS (Quality of Service)Â  is considered to be a preliminary factor while composing a new cloud service out of heterogeneous and distributed atomic services. Therefore service composition is promising area that focuses on the design and development of the automated approaches to deal with diverse phases of service composition techniques that include service discovery, negotiation, service selection and optimization of the atomic services. This paper provides anatomy ofÂ  existing studies addressing the problem of cloud service composition that enable to identify intended objectives of the technique along with diverse QoS aware problem solving approaches. Furthermore, the key areas of the improvement in cloud service composition are identified for future research.Â
Runtime Parallelization of Static and Dynamic Irregular Array of Array References
Authors: Singh Anjanaa Parwat , Naga Maruthia N. , Gujjunooria Sagar , Orugantib Madhu
Published: July 2019

The advancement of computer systems such as multi-core and multiprocessor systems resulted in much faster computing than earlier. However, the efficient utilization of these rich computing resources is still an emerging area. For efficient utilization of computing resources, many optimization techniques have been developed, some techniques at compile time and some at runtime. When all the information required for parallel execution is known at compile time, then optimization compilers can reasonably parallelize a sequential program. However, optimization compiler fails when it encounters compile time unknowns in the program. A conventional solution for such problem can be performing parallelization at runtime. In this article, we propose three different solutions to parallelize a loop having an irregularity in the array of array references, with and without dependencies. More specifically, we introduce runtime check based parallelization technique for the static irregular references without dependency, Inspector-Executor based parallelization technique for static irregular references with dependencies, and finally Speculative parallelization technique (BitTLS) for dynamic irregular references with dependencies. For pro ling the runtime information, shared and private data structures are used. To detect the dependencies between footprints and for synchronization of threads at runtime, we use bit level operations. A window based scheduling policy is employed to schedule the iterations to the threads.Â Â Â
Sensors in IoE: A Review
Authors: Srinivas K. , A.Jabbar M. , S. Neeraja K.
Published: July 2019

Internet of everything (IoE) is the popular technology in the industry. IoE platforms deliver various kinds of intelligence using sensors. Sensors are autonomous and work as smarter. In this paper we have portrayed the different types of sensors, with their applications in various domains. This paper also discusses the factors that determine the suitability of sensors, various challenges, and solutions for sensors in IoE.Â Â
Predicting User Behaviour on E-Commerce Site Using Ann
Authors: Sai Srinivas Aditya , Ramasubbareddy Somula , S.S Manivannan , K Govinda
Published: July 2019

One of the major tasks for the modern business is learning to use all of the data available to them in a way that is both expressive and actionable. However, the potential for using data produced by a website is often left unfamiliar, and as a result, the objectives and feedbacks of individual digital customers can be unheeded. On the average website, there is a plenty of data to be collected about who interrelates with your site and how. By leveraging all of this statistics, we can gain perceptions into customer actions. Machine learning methods can be used to define which customers may be fascinated in achieving a result on your site.
Sensing Technologies used for Monitoring and Detecting Insect Infestation in Stored Grain
Authors: Kaushik Rekha , Singhai Jyoti
Published: July 2019

In India, the production of grain has been steadily increasing. Improper storage of grain results in higher losses in terms of quality as well as quantity. Contamination of grain occurs due to insects and micro-organisms present in it. Their presence and growth highly depends on environmental factors. When grain gets infested, volatile compounds get accumulated and release odour. The rapid growth of sensing technology makes the early and accurate detection of insects/fungi more promising. This paper discusses about different kinds of sensing technologies such as environmental sensing, acoustic sensing, odour sensing and image sensing, their working, challenges and issues, advantages and limitations. Future trends of using sensing technology are also discussed.
Multi-Objective Optimization for scientific workflow task scheduling in IaaS Cloud
Authors: Panneerselvam Arunkumar , Subbaraman Bhuvaneswari
Published: July 2019

The use of scientific applications on cloud networks increases day by day generating volumes of data and consuming large computational power. These scientific applications find its importance in the field of astronomy, geology, genetics and bio-technology etc. Complex and mission critical scientific applications can be modeled as scientific workflows and can be executed in cloud. The tasks of the scientific applications are generally data intensive and compute intensive. Traditional computer networks are not suitable for handling scientific applications and hence ubiquitous distributed networks like cloud are prominent in hosting scientific applications. The cloud hosted scientific applications and the cloud network need to satisfy many objectives to the interest of its users. This paper explores the    multi-objective optimization applications in scientific workflow task scheduling in IaaS cloud and the related algorithms employed.
A Novel Intrusion Detection System Using Artificial Neural Networks and Feature Subset Selection
Authors: Haripriya L. , A. Jabbar M. , Seetharamulu B.
Published: July 2019

The growth of internet and network technologies has been increasing day by day.With the increase of these technologies, attacks and intrusions are also increasing. The prevention of these attacks has become an task. Intrusion Detection System (IDS) provides prevention against these attacks. Data Mining and Machine Learning techniques are used for IDS to reduce error rate and to improve accuracy and detection rate. In this paper, we proposed a novel Artificial Neural Network (ANN) classifier using Back propagation algorithm to model IDS. ANN is widely used supervised classifier for IDS. The performance of our model is evaluated by conducting experiments on KYOTO data set which is refined version of KDD99 data set. Empirical results show that proposed model is efficient with high detection rate and accuracy.
Harmonic cancellation in a Multi-level Inverter Configuration Suitable for PV Applications
Authors: Kumar Nallamekala Kiran , Venkat Raman K. , Asif Md.
Published: July 2019

Multi-level inverters are playing a major role in PV based systems because of numerous advantages like low dv/dt, better harmonic profile so on. But, conventional multi-level inverters consist of some drawbacks like capacitor balancing issues, greater requirement of capacitor banks and clamping diodes. To address these issues, a novel multi-level inverter has been presented in this paper, which can function as a seven-level, five-level and three-level inverter. The inverter circuit utilizes six switching devices and two isolated DC voltage sources.  Moreover, when it is operated as a three-level inverter, a unipolar PWM technique is applied to the circuit which shifts all the lower order harmonics to twice of switching frequency whereas in conventional multi-level inverters, all the harmonics of lower order are present around switching frequency. In addition, proposed inverter can operate even if some switching devices of the circuit fails. Also, the behavior of the inverter during the failure of some switching devices and DC source is analyzed. The proposed inverter is simulated in MATLAB/Simulink and the results are also discussed.
A Analysis of Machine Learning in Wireless Sensor Network
Authors: Chander Bhanu , Kumar.B Prem , . Kumaravelan
Published: July 2019

Advances in hardware as well as wireless network tools have positioned us at the doorstep of a new-fangled era where undersized wireless devices will endow with access to information every time, everyplace plus enthusiastically contribute in constructing smart atmosphere. The sensors in WSN’s assemble information regarding the substances they are exploited to sense. Nevertheless these sensors are restricted in their performance by restrictions of power plus bandwidth. Machine Learning methods can facilitate them in overcoming such restrictions. During the past decade, WSNs have seen progressively more rigorous implementation of highly developed machine learning algorithms for information handing out and improving network performance. Machine learning enthuse countless realistic clarifications that make best use of resource exploitation along with make longer the existence of the network. In particular, WSN designers have effectively agree to machine learning paradigms to deal with widespread purposeful problems associated to localization, data aggregation, fault detection, Security, node clustering, prediction models and energy aware routing, etc.
Data Analytics: Why Data Normalization
Authors: K. Dhana Sree Dr. , C. Shoba Bindu Dr.
Published: July 2019

The two maestros Artificial Intelligence and Machine learning are ruling the data filled world with good analytics. Many of these domain skills are used in the industry to analyze and interpret the data beyond what it actually is. Supporting the known saying find the horse before the cart is ready is what it mean to normalize the data before getting it analyzed. This article focus on what normalization actually is, why normalization is needed before data analysis and how data normalization is done.
Conceptual ClusteringAnalysis in Data Mining: A Study
Authors: Nikhila K. , Manvitha P.
Published: July 2019

Clustering on unsupervised learning handles with instances, which are not classified already and not having class attribute with them. Applying algorithms is to find useful but items on unknown classes. Approach of unsupervised learning is about instances are automatically making into meaningful groups basing on its similarity. This paper we study about the basic clustering       methods in data mining on unsupervised learning such as ensembles distributed clustering and its algorithms.
Improvement of Image Fusion by Integrating Wavelet Transform with Principal Component Analysis
Authors: Lokanath Reddy C. , Sripal Reddy K.
Published: July 2019

The process which combines the two or more than two related source images and gives a single output image is known as image fusion. Image fusion is mainly used to analyze the image areas where the pixel values i.e. information is low intensity. Fusion of Images has been used in different applications .Correlation property is important in image fusion analysis. Correlation can be controlled by distributing the Energy in different spectral bands. Broadly image fusion process can be categorized into three groups i.e. spatial, transform and statistical methods. The image fusion process should preserve suitable pattern information from all source (input) images. Average method, Principal component Analysis is comes under spatial domain method, which deals with directly changing the pixel values but the spatial domain method introduces a spatial distortion for fused image. Wavelet based image fusion is a transform domain method which gives better performance than the spatial method. We presented a novel fusion technique which is implemented by integrating the wavelet transform with Principal Component Analysis and compared the performance with respect to different performance metrics.
Prediction of Breast Cancer Using Big Data Analytics
Authors: Shailaja K. , Seetharamulu2 B. , A. Jabbar M.
Published: July 2019

Big data is a phrase which is used to report collection of data that vast in size and still growing exponentially with time. It covers structured unstructured and semi-structured data. Now a day’s big data is widely used in healthcare for prediction of diseases. Breast cancer is one of top cancer that occurs in a woman. It is the second main leading reason for the death of a woman in the United States and in Asian countries. If we identify this disease in early stages there is a better chance for curing. For this experiment, we used K nearest neighbor (KNN) algorithm for finding classification accuracy and it is implemented on R tool. We consider Wisconsin breast cancer (original) dataset taken from UCI machine learning repository.
Novel Microstrip Band Pass Filter for C- Band Wireless Applications
Authors: S. Sreenath Kashyap Dr. , MVV Prasad Kantipudi , Vipul M Dabhi Dr.
Published: July 2019

In this paper, a novel approach for designing the parallel coupled microstrip bandpass filter operating at C-band frequency is numerically analyzed iteratively and simulated. The physical dimensions are being finalized using standard odd- even impedance method. Various electrical parameters such as insertion loss, reflection loss are being analyzed and practical results are being compared and found same as the predicted results. The proposed design is fabricated on FR4 dielectric substrate and the experimental result shows the scientifically acceptable for C-band Applications.
Finding Frequent Patterns in Biological Networks
Authors: Rane Rahul , Kaushik Praveen
Published: July 2019

Frequent patterns help to discover the structural behavior of the complex biological network. The networks which show same global structure may have different local structure. The patterns are the actual fingerprints of the network. The pattern frequency and its significance carries very important functionality to classify and cluster the biological network. The sheer number of patterns get generated while traversing the network. Counting these patterns and determining their frequencies in the large biological network is very challenging and computationally expensive task. Previously proposed methods are bound by the size of patterns and networks size. By using approximation method like sampling, we proposed an algorithm. The results show the proposed algorithm is faster than existing algorithms. Also, the error rate is minimum, which makes the proposed method more reliable.
Recent Trends in Security and Privacy of Sensitive Data in Cloud Computing
Authors: P Dayaker , Reddy T Chandrasekhara , Diana P Honey , Mallikarjun Reddy A.
Published: July 2019

Cloud Computing (CC) is reforming many biological communities by furnishing associations with registering assets including simple organization, network, design, Romanization, and adaptability. This change in perspective raises an expansive scope of security and protection issues that must be thought about. Multi-tenure, loss of control, and trust are entering challenges in cloud processing conditions. This paper surveys the current advancements and a wide show of both earlier and frontier extends on cloud security and protection. We classify the current look into as per the cloud reference engineering coordination, asset control, physical asset, and cloud benefit administration layers, in spite of inspecting the current improvements in security safeguarding touchy information approaches in CC, such as, security risk demonstrating and protection upgrading conventions and arrangements.
Side Information Mitigation with new Phase Sequence for Hybrid PTS Scheme
Authors: Satyavathi K. , B.Rama Rao Dr. , . .
Published: July 2019

This paper focus on presenting a new phase sequence based hybrid PTS approach for OFDM systems to mitigate the problem of PAPR without use of side information. The proposed approach is the exponential constant multiplied for each phase vector so that it can accommodate more number of sub carriers. The modified phase vectors are then multiplied to the original phase vectors so as to obtain a modified version of phase vectors that includes an offset. Experimental results shows that the PAPR is reduced about 04~0.8 db when compared against the traditional PTS scheme deployed for Hybrid systems.