bluuebunny/crossref_metadata_2025 huggingface dataset:
High gain tapered slot antenna design and link budget analysis for inter-satellite link at 60GHz
Authors: Saisandeep Banda , Rao Morla Venkateshwara , Ahmadsaidulu Shaik , S.L. Prasanna Ch , Rao Tirumalasetty Venkata , . .
Published: April 2019

The latest solution for Global Connectivity is Inter-satellite communication. Inter-satellite communication will able to connect two or more satellites directly and hence efficient data transfer is possible with less delay. Choice of frequency is key concern for inter-satellite communication. In this paper, precisely mentioned about importance of millimeter range frequency band for inter-satellite links (ISL) and more focused on the Tapered Slot antenna (TSA) design at 60 GHz. In the design, Substrate Integrated Waveguide SIW feed and corrugation techniques is used to achieve high gain and narrow beam width. Power Divider is used to design two-element TS antenna of 23 dB. For further outlook of antenna design link analysis is also calculated.
Internet of things (IoT) based health monitoring system and challenges
Authors: Sathya M , Madhan S , Jayanthi K
Published: April 2019

Among the applications that Internet of Things (IoT) facilitated to the world, Healthcare applications are most important. In general, IoT has been widely used to interconnect the advanced medical resources and to offer smart and effective healthcare services to the people.  The advanced sensors can be either worn or be embedded into the body of the patients, so as to continously monitor their health. The information collected in such manner, can be analzed, aggregated and mined to do the early prediction of diseases.  The processing algorithms assist the physicians for the personalization of treatment and it helps to make the health care economical, at the same time, with improved outcomes. Also, in this paper, we highlight the challenges in the implementation of IoT health monitoring system in real world.
Uncertainties quantification and modelling of different rheological models in estimation of pressure losses during drilling operation
Authors: P. A. L Anawe , Adewale Folayan J.
Published: April 2019

The determination of pressure losses in the drill pipe and annulus with a very high degree of precision and accuracy is sacrosanct for proper pump operating conditions and correct bit nozzle sizes for maximum jet impact and forestalling of possible kicks and eventual blow outs during drilling operation. The two major uncertainties in pump pressure estimation that are being addressed in this research work are the flow behavior index (n) and the consistency index factor (k). It is in this light that the accuracy of various rheological models in predicting pump pressure losses as well as the uncertainties associated with each model was investigated. In order to come by with a decisive conclusion, two synthetic based drilling fluids were used to form synthetic muds known as sample A and B respectively. Inference from results shows that the Newtonian model underestimated the pump pressure by 78.27% for sample A and 82.961% by for sample B. While the Bingham plastic model overestimated the total pump pressure by 100.70% for sample A and 48.17% for sample B. Three different power law rheological model approaches were used to obtain the flow behavior index and consistency factor of the drilling fluids. For the power law rheological model approaches, an underestimation error of 23.5743% was encountered for the Formular method for sample A while the proposed consistency index averaging method reduces the error to 14.9306%. The Graphical method showed a reasonable degree of accuracy with underestimation error of 5.6435%. Sample B showed an underestimation error of 47.8234% by using the power law formula method while the Consistency averaging method reduced the error to 20.7508. The graphical method showed an underestimation error of 0.4318%.
Network anomaly detection for protecting web services from the application layer bandwidth flooding attack
Authors: V Raghavender K , P.Premchand Dr
Published: April 2019

Web servers are generally situated in an efficient server center where these servers associate with the outside Web straightforwardly through spines. In the interim, the application layer Bandwidth flooding attack (ALBFA) assaults are basic dangers to the Web, especially to those business web servers. As of now, there are a few strategies intended to deal with the ALBFA assaults, however the greater part of them can't be utilized as a part of substantial spines. In this paper, we propound another technique namely BFADM to identify ALBFA assaults. Our work separates itself from past techniques by considering ALBFA assault discovery in overwhelming spine movement. Moreover, the recognition of ALBFA assaults is effortlessly deceived by streak swarm activity. Keeping in mind the end goal to beat this issue, our propounded technique develops a Constant Recurrence Vector and genuine opportune describes the movement as an arrangement of models. By looking at the entropy of ALBFA assaults and blaze swarms, these models can be utilized to perceive the genuine ALBFA assaults. We coordinate the above discovery standards into a modularized resistance design, which comprises of a head-end sensor, an identification module and an activity channel. With a quick ALBFA discovery speed, the channel is equipped for letting the true blue demands through however the assault movement is ceased.
A New Diversity Technique for Imbalance Learning Ensembles
Authors: . Hartono , Sitompul Opim Salim , Nababan Erna Budhiarti , . Tulus , Abdullah Dahlan , Ahmar Ansari Saleh
Published: April 2019

Data mining and machine learning techniques designed to solve classification problems require balanced class distribution. However, in reality sometimes the classification of datasets indicates the existence of a class represented by a large number of instances whereas there are classes with far fewer instances. This problem is known as the class imbalance problem. Classifier Ensembles is a method often used in overcoming class imbalance problems. Data Diversity is one of the cornerstones of ensembles. An ideal ensemble system should have accurrate individual classifiers and if there is an error it is expected to occur on different objects or instances. This research will present the results of overview and experimental study using Hybrid Approach Redefinition (HAR) Method in handling class imbalance and at the same time expected to get better data diversity. This research will be conducted using 6 datasets with different imbalanced ratios and will be compared with SMOTEBoost which is one of the Re-Weighting method which is often used in handling class imbalance. This study shows that the data diversity is related to performance in the imbalance learning ensembles and the proposed methods can obtain better data diversity.
Role of Crisis Management in Construction Projects
Authors: J Rajprasad , V Thamilarasu , N Mageshwari
Published: April 2019

Crisis management is the method which is formed by the organization to overcome the crisis. Crisis management is important, which helps in the completion of the construction project on time. It gives a theory of how to manage the crisis management with the factors which leads to crisis in the construction project. However, only when the work flow continues without any interruption even during crisis that crisis management method is effective. For forming an effective crisis management technique, the probability of crisis in construction projects must be identified as each factor have their unique effects. Depending upon major factors like technical, labour, organizational, material, time, equipment, communication, financial and other factors which are responsible for the cause of crisis in projects are considered. The research is carried out through questionnaire survey analysis made among the various project managers from different construction project site.
Lightning strokes and its effects on historical monuments, heritage properties and important landmarks a detailed perspective of traditional and scientific methods of lightning protection systems
Authors: Sreedhar Srisailam , Srinivasan Venkatesh
Published: April 2019

Lightning is one of the inevitable disastrous natural phenomena which present serious threat to tall structures including ancient monuments and electrical systems. Though researchers have carried out a wide gamut of research studies to analyze the extent of damage due to direct lightning strikes on important buildings and structures, the focus of this research is on understanding the effects of lightning on tall structures of historical importance and landmark monuments of significance. In this context, different types of Lightning Protection Systems (LPS) are being used to protect tall structures from lightning flashes. However, several complexities related to the appropriate choice of LPS continue to confront researchers since characteristics of lightning such as stroke current, striking distance, return stroke modelling, geometry of the structure etc. pose considerable challenges. This research study presents a detailed chronological overview of lightning strikes on ancient structures, cause and effects, review on LPS strategies along with its impacts on tall structures, historical monuments and landmarks. In addition, a detailed analysis based on a specific case study of a typical historical monument is carried out to ascertain the critical significance of the stipulated zone of protection essential for historical monuments and various risks involved during implementation.
A Development Framework for Social Media Interaction in Learning Management System
Authors: Ravisekaran Kalaivani , Ramakrishnan Sivakumar
Published: April 2019

Learning Management System (LMS) plays a vital role and an imprortant part in technology-enhanced learning. It presents different services to enhance the education procedure in ubiquitous learning condition. But, it is found that in existing education MS a extend range of education procedure and process are presented. But, it needs to be developed with some ubiquitous additional functionality. So the current research we proposed a struture for LMS to integrate social media services to make the LMS enrich in ubiquitous condition. This structure approves efficient social and intellectual interaction between users in ubiquitous Learning Management System environment.
Request Schedule Oriented Compression Cache Memory
Authors: D.Kesavan G , N.Karthikayan P
Published: April 2019

Using cache memory the overall memory access time to fetch data gets reduced. As use of cache memory is related to a    system's performance, the caching process should take less time. To speed up caching process, there are many cache optimization techniques available. Some of the cache optimization process are Reducing Miss Rate, Reducing Miss Penalty, Re-ducing the time to hit in the cache etc. Re-cent advancement paved way for compressing data in cache, accessing recent data use pat-tern etc. All the techniques focus on increasing cache capacity or replacement policies in cache resulting in more hit ratio. There are many cache related compression and optimization techniques available which address only capacity and replacement related              optimization and their related issues. This paper deals with scheduling the requests of cache memory as per compressed cache organization. So that cache searching and indexing speed gets reduced considerably and service the request in a faster manner. For capacity and replacement improvements Dictionary sharing based caching is used. Through this scheme multiple requests are foreseen using pre-fetcher and are searched as per cache organization, promoting easier indexing process.The benefit comes from both compressed storage and also easier storage ac-cess.
Non Verbal Communication for Analyzing the Malpractice in Examinations– An Overview
Authors: T Kujani , T Sathya , R Bhuvanya , S Uma
Published: April 2019

Nonverbal communication can specify the psychosomatic behavior of people involved in interpersonal communication. Many researchers have specified the importance of gesture intimation. In the paper, we shall apply the previously used computer vision hardware and Machine Learning techniques for capturing the postures students undergoing examination in the classroom atmosphere. The main       intention is to classify the people who involved in misbehavior such as copying, prompting answers, sharing the answer scripts and any other such practices. Current situation prevailing is though a physical monitor, invigilator is available in the exam hall the students     attempt to misbehave in various ways mentioned above. We discuss about the techniques to be employed to get an analysis of the       behavior of each student involved in exam.
Upgraded Spatial Gray Level Dependence Matrices for Textural Analysis in Colon Cancer Tissues
Authors: Saroja B , Selwin Mich Priyadharson A
Published: April 2019

Colon or Bowel or Colorectal Cancer (CRC) is commonly determined by diagnosing a sample of colon tissue and further analysed by medical imaging. The colon tissue classification method count on specific changes between texture features extracted from benign and malignant regions. The variations in the image acquisition methods effects the colon tissue analysis. In this paper, an Upgraded Spatial Gray Level Dependence Matrices (U-SGLDM) is emphasized to extract textural features. The licensed image set of all applicable types of tissues within colon cancer are used for experimentation. Several texture feature sets are extracted to show the significant differences among the eight colon cancer biopsy images in the image data set. The fractal dimension-Hurst Coefficient is added to U-SGLDM for long range assessment. The Prominence of the analysis evoked in the representation of histopathological image structure over longer periods.
Deep learning in the field of disease diagnosis
Authors: S. Harish Kumar K , Micheal Jerald Dijo , Emmanuel A
Published: April 2019

A good treatment is dependent on the accuracy of the diagnosis. The cure for the disease starts with the process of diagnosis. All these years, the grade and standard of the medical field has been increasing exponentially, yet there has been no significant downfall in the rate of unintentional medical errors. These errors can be avoided using Deep learning algorithm to predict the disease. The Deep Learning algorithm scans analyses and compares the patient's report with its dataset and predicts the nature and severity of the disease. The test results from the patient’s report are extracted by using PDF processing. More the medical reports analyzed, more will be the intelligence gained by the algorithm. This will be of great assistance to the doctors as they can interpret their diagnosis with the results predicted by the algorithm.
A New Authentication Scheme with Elliptical Curve Cryptography for Internet of Things (IoT) Environments
Authors: Durairaj M , Muthuramalingam K
Published: April 2019

Internet of Things (IoT) consists of a large number of connected objects that are communicating with each other. To support trusted communication between IoT objects, the authentication procedures should be used and applied to the communicating entities. Internet of Things (IoT) is an emerging technology, which makes the remote sensing and control across the heterogeneous network a reality, and has good prospects in industrial applications. As an essential infrastructure, Wireless Sensor Networks (WSNs) play a crucial role in industrial IoT. Due to the resource-constrained feature of sensor nodes, the design of security and efficiency balanced authentication scheme for WSNs becomes a significant challenge in IoT applications. In this paper, an anonymous authentication scheme for WSNs in an Internet of Things environments.
Design of library application system
Authors: . Wulandari , Aminin Sudirman , Ihsan Dacholfany M. , Mujib Abdul , Huda Miftachul , Mohd. Nasir Badlihisham , Maseleno Andino , Sundari Eni , . Fauzi , Masrur M.
Published: April 2019

Library application is a computer program designed specifically to manage the data of borrowing and returning books in order to be presented more quickly. In addition, for the achievement of the purpose of the operation itself is to facilitate students by providing facilities. In making this application there were some important data such as Member data, Books, Transactions, and Admin. From the data were expected to be the basis made for this application in order to present the information needed quickly and precisely, and to improve the performance of librarians. Requirements as a member of the library is a Student of SMP Negeri 1 Talangpadang, then create a regis                                                                                                                                                                                                                                                                                                                                                                                     tration form to become a member of SMP Negeri 1 Talangpadang Students. The expected result of making this system was that the data that had been stored and managed manually can begin to be computerized so as to further advance the performance and facilitate librari-ans in carrying out activities related to the library itself.
An allotment of H1B work visa in USA using machine learning
Authors: Thakur Pooja , Singh Mandeep , Singh Harpreet , Singh Rana Prashant
Published: April 2019

H1B work visas are utilized to contract profoundly talented outside specialists at low wages in America which help firms and impact U.S economy unfavorably. In excess of 100,000 individuals for every year apply tight clamp for higher examinations and also to work and number builds each year. Selections of foreigners are done by lottery system which doesn’t follow any full proofed method and so results cause a loophole between US-based and foreign workers. We endeavor to examine petitions filled from 2015 to 2017 with the goal that a superior prediction model need to develop using machine learning which helps to foresee the aftereffect of the request of ahead of time which shows whether an appeal to is commendable or not. In this work, we use seven classification models Decision tree, C5.0, Random Forest, Naïve Bayes, Neural Network and SVM which predict the status of a petition as certified, denied, withdrawal or certified with-drawls. The predictions of these models are checked on accuracy parameter. It is found that C5.0 outperform with the best accuracy of 94.62 as a single model but proposed model gives better results of 95.4 accuracies which is built by machine ensemble method and this is validated by 10 fold cross-validation.
Spatial and temporal clustering analysis on chlorophyll-a data distribution
Authors: Fitrianah Devi
Published: April 2019

The motivation of this study is to serve as an alternative approach to most chlorophyll analysis studies that utilize overlay analysis with chlorophyll-a imaging. Mostly, the chlorophyll overlay analysis take many steps in processes, not to mention the bigger the observation duration for the data, the longer it takes to process. In this study, a spatial and temporal clustering analysis was conducted to obtain areas that have abundant chlorophyll-a. The spatial distribution was determined using the DBSCAN algorithm, while the temporal distribution was deter-mined via the fuzzy c-means algorithm. From this study, we can obtain information on the distribution of chlorophyll-a clearly based on the location and the time through a given visualization in advanced. There is no need to do overlaying chlorophyll-a imaging one by one. The results of the spatial and temporal clustering provide an easy-to-read visualization regarding information on the chlorophyll-a distribution based on location and time.
Strategies for Recovery and Maintain of A Biped Walking Robot Balance
Authors: Pop N , Vladareanu L , Wang H , Ungureanu M , Migdalovici M , Vladareanu V , Feng Y , Lin M , P. Mastan E , El Emary Ibrahiem
Published: April 2019

Recovering and maintaining the balance of the biped walking robots play an important role in their operation. In this article we will analyze some strategies for balancing in the sagittal plane, in the presence of external disturbances and changing the proportions between leg’s length and trunk’s length (golden section), and/or adding weights (boot type) between the ankle and the knee so that the center of gravity is as low as possible. For equilibrium recovery, we suggest that the biped walking model be equipped with actuator that provides a torque at the hip. or/and at the ankle. The strategy of balance has a goal to move the disturbed system to the desired equilibrium state. We chose to study, the model of a double linear pendulum inverted under-actuated, with one passive and one active joint. Each case study and usage of these strategies is validated by Webots and is applied for NAO robot.
The governance of Internet and game theory
Authors: Lefebvre Olivier
Published: April 2019

The professional milieu of telecommunications is livened up by controversies lasting decades.  The controversy about access charges (or termination rates, the price paid by an operator to another when the subscriber’s call ends on its network) is ending, while the controversy about Net neutrality is starting. The article focuses on a “fragment”: the regulator’s action. Game theory is useful to answer two questions: (1) why does the regulator decide the decrease and cancellation of access charges (justification)? (2) How does he do it (tactical feasibility)? When the access charges decrease and are cancelled the retail prices decrease and the consumers’ surplus increases. And concerning the tactical feasibility, the regulator can let untouched the profits when he decides some decrease of the access charges (direct effect), then the retail prices decrease when there is a new Nash equilibrium (strategic effect). The operators cannot protest, neither during the first stage (the profits are untouched) neither during the second stage (it would be to admit that access charges are useful to have higher profits thanks to high retail prices, which is detrimental to consumers).One brings some explanation of the move towards access charges lowered or cancelled. Examples are: (1) the peering in the governance of Internet and (2) what is called the Eurotariff (for instance, roaming charges for users of mobile phones in Europe have been cancelled).
Test case prioritization and selection technique in continuous integration development environments: a case study
Authors: Xiao Lei , Miao Huaikou , Zhong Ying
Published: April 2019

Regression testing is a very important activity in continuous integration development environments. Software engineers frequently integrate new or changed code that involves in a new regression testing. Furthermore, regression testing in continuous integration development environments is together with tight time constraints. It is also impossible to re-run all the test cases in regression testing. Test case prioritization and selection technique are often used to render continuous integration processes more cost-effective. According to multi objective optimization, we present a test case prioritization and selection technique, TCPSCI, to satisfy time constraints and achieve testing goals in continuous integration development environments. Based on historical failure data, testing coverage code size and testing execution time, we order and select test cases. The test cases of the maximize code coverage, the shorter execution time and revealing the latest faults have the higher priority in the same change request. The case study results show that using TCPSCI has a higher cost-effectiveness comparing to the manually prioritization.
Context Similarity Strategy for Text Data Plagiarism Detection
Authors: Bhavani Dasari Durga , Venu Gopala Rao. K Dr
Published: April 2019

Advent development of anti-plagiarism solutions has supported varied range of elementary forms of textual recycling, however, considering the magnum of content that is being generated, a tool alone might be ineffective in preventing complex forms of plagiarism. Some of the issues that are envisaged with the plagiarized articles in many of the open-access journals emphasize the point that critical deficiencies of varied kind of solutions that are existing aren’t being resourceful in identifying the manipulation that is taking place in the form of paraphrasing and editing. Manipulative editing has become a major menace even in the case of predatory journals and is leading to issues of publication ethics. Certain preventive strategies that have evolved in the recent past are relying on semantic solutions, comprehensive texts evaluation, graphics, reference lists, key words, digital technologies. It is right time for enforcing adherence to global editorial guidance and towards implementing a comprehensive set of strategies to address the issue of plagiarism.
Customer Data Clustering using Density based algorithm
Authors: Sekhar Babu B , Lakshmi Prasanna P , Vidyullatha P
Published: April 2019

This paper is about Clustering different segments of customers and their patterns of behaviour over different time intervals which are a very important application for business to maintain Business to Customer (B2C) Relationship. For clustering different segments of customers the input data will be taken from various business organizations like smart retail stores, and other stores. We take the input data from a particular amount of time like a year's data. All this data will be taken from the organization's databases. It has been observed that maintaining the old customers generate more profit when compared to attracting new ones. So, Customer retention is the important factor in our project. The main objective is to identify the elements with high profit and value to group them into different clusters. This will help to identify the high-value low-risk customers.  From the results obtained, we can be able to propose some strategies to the organization that helps in retaining the old customers and improve the profits.
An Efficient Data Replication Scheme for Hadoop Distributed File System
Authors: Lakshmi Siva Rama Krishna T , Priyanka J , Nikhil Teja N , Mahiya Sultana Sd , Jabber B
Published: April 2019

A Distributed file system (DFS) is a storage component of a distributed system (DS). DS consists of multiple autonomous nodes connected via a communication network to solve large problems and to achieve more computing power. One of the design requirement of any DS is to provide replicas. In this paper, we propose a new replication algorithm which is more reliable than the existing replication algorithm used in DFS. The advantages of our proposed replication algorithm by incrementing nodes sequentially (RAINS) is that it distributes the storage load equally among all the nodes sequentially and it guarantees a replica copy in case two racks in a DS are down. This feature is not available in the existing DFS. We have compared existing replication algorithm used by Hadoop distributed file system (HDFS) with our proposed RAINS algorithm. The experimental results indicate that our proposed RAINS algorithm performs better when more number of racks failed in the DS.
Assessment and Analysis of Software Reliability Using Machine Learning Techniques
Authors: Krishna Mohan G , Yoshitha N , L.N.Lavanya M , Krishna Priya A
Published: April 2019

Software reliability models access the reliability by fault prediction. Reliability is a real world phenomenon with many associated real time problems and to obtain solutions to problems quickly, accurately and acceptably a large no. of soft computing techniques has been developed. We attempt to address the software failure problems by modeling software failure data using the machine learning techniques such as support vector machine (SVM) regression and generalized additive models. The study of software reliability can be categorized into three parts: modeling, measurement, improvement. Programming unwavering quality demonstrating has developed to a point that important outcomes can be acquired by applying appropriate models to the issue; there is no single model all inclusive to every one of the circumstances. We propose different machine learning methods for the evaluation of programming unwavering quality, for example, artificial neural networks, support vector machine calculation approached. We at that point break down the outcomes from machine getting the hang of demonstrating, and contrast them with that of some summed up direct displaying procedures that are proportional to programming dependability models.
Security Issues and Challenges in IOT: a Comprehensive Study
Authors: Bhargavi M , M.Nagabhushana Rao Dr
Published: April 2019

The Internet of Things (IoT) is a revolutionary model, with rising wireless sensor network technology. In IoT network devices are connected and communicated with each other or with human. IoT is extremely available to security assaults. In recent years, the internet of things has a continuous support in research. In the upcoming scenario, IoT will play an important role and changes our day-to-day life, principles as well as industry models. In this paper we provide ensuring security of data exchange, IoT architecture and IoT Security architecture, applications, drawbacks of IoT. We study about various security issues, Problems, normal and Denial of service attacks in different layers, issues and research defy in IoT are also discussed.
Secure Quantum Key Distribution Encryption method for Efficient Data Communication in Wireless Body Area Sensor Net-works
Authors: Sai Suguna Y , Kavya Reddy B , Keerthi Durga V , Roshini A
Published: April 2019

Wireless sensor networks has found its advancement in sensing the physiological parameters of human body through WBAN. Such nodes are either implanted or surface mounted on the human body in a particular position. The main purpose of these networks is to send the data generated by the wearable device outside the WLAN or the Internet. The BAN will continuously monitor the psychological changes like blood volume pressure (BVP), Brain signals etc. Uncertainty in the normal values will result in transmit all the information to the respective recipient to take required treatment. If an emergency is detected, the doctor instantly updates the patient’s health by sending a specific message. There is limited confidentiality, so the intruders will gather sensitive data. Public key cryptography can be used to create an unprotected communication channel. It also provides a convenient way to implement keys. This paper is focusing on a unique key generation technique called Quantum key distribution, which is used to create symmetric key method by using quantum properties of optics to transfer information from one Client to another in One-Time Pad manner. The special feature of the technique is to guarantee that the key cannot be intercepted during transmission without alerting the users to provide high authentication for received data.
Internet of Things on Smart Villages
Authors: Nagabhushan Rao M , Nikitha Sai K , Lakshmi Deepika C , Karthik C
Published: April 2019

The idea of internet of things plays an important role in the development of future technology. IOT is the basic vision for the future success growth in finding the new technologies. The logical basis for a course of action behind the IOT working is the result of combining or uniting all the sources of communication technologies. All the devices which are present in the system are made to function with each other , just to perform their job in a balanced manner. Due to the increase in population, it lets the city and villages to facilitate and function in a better and smarter way. Therefore, above lines put together a reason for the invention of idea of smart cities. For this to work, these cities performed two different functions. First function is all about only fetching the information from both sensors and other remote devices. Second function analyzes the information which is observed from the above function and appropriate actions are made. This paper explains the idea about smart villages, it is focused completely on villages to study them and then provide the solution for those affected areas. It also helps in the improvement of their quality of life.
IOT Based Home Automation System with Cloud Organizing
Authors: Hrushikesava Raju S , M.Nagabhushana Rao Dr , Sudheer N , Kavitharani P
Published: April 2019

Internet of things may be a growing network of everyday object-from industrial machine to client home appliances which will share data and complete tasks whereas you're busy with different activities. The IoT aims to unify everything in our world below a typical infrastructure, giving United States of America not solely management of things around United States of America, however conjointly keeping United States of America knowing of the state of the items. Home automation with the proliferation of IoT is changing into a reality currently, and a range of players like, Apple, Amazon, Google, Samsung, are all convergence into this area to produce the platform and solutions for sensible homes. In light-weight of this, gift study addresses IoT ideas through systematic review of pedantic analysis papers, company white papers, skilled discussions with specialists and on-line databases. The most objective of this paper is to produce an outline of web of Things, architectures, and very important technologies and their usages in our standard of living.
An Integrated Approach Towards Vulnerability Assessment & Penetration Testing for a Web Application
Authors: Siva Prasad K , K. Raja Sekhar Dr , P. Rajarajeswari Dr
Published: April 2019

Current digitized world has surpassed the days of mere existence of internet. Furnishing the services through web has become the most often element to be implemented by almost every sector. These ever-changing technologies has also brought about, devastating evading techniques compromising the fragility of the web application. Assessing the existing vulnerabilities of a web application and testing all possible penetrations would be tedious if the tools used are bearing a cost factor. This paper suggests an integrated approach of assessing the vulnerabilities in any web application using free and open source tools where the reports are generated with respect to vulnerabilities and their categories and level of severity. The tools are integrated and correlated for producing the accurate results in better manner similar to the results produced by the commercial ones. The analysis has been done by considering the reports released by OWASP, OSSTMM, ISSAF, CVE, Exploit Database and Microsoft Vulnerability Research. The report produced after vulnerability assessment has been taken for testing different penetrations for a single application. The identified vulnerabilities are therefore exploited for testing the penetrations of a web application. The report will be generated finally stating all possible exploitable vulnerabilities that are encountered in a web application. The final report generated would help the developers to fix the vulnerable issues.
Url redirect links and its importance calculated using parallel programming to drastically reduced the execution time
Authors: Dande Madhu , Subramanian Lakshmi Narayanan Bala , Diwadi Abhishek
Published: April 2019

Web URL Redirect Utility validates the URL links and generates the reports with details like number of hops, status and its importance. URL Redirect Utility will help the development team to fix the issue as well do the profiling for the URL links. The Utility will find the performance bottlenecks of the url links with that can improve the performance of each web page. URL redirect Utility designed and developed using dotnet MVC framework with parallel programming approach. Considered test scenario with an 20000 number of URLs which will be validated less than 20 min(1,200,000 msec) by running the utility in parallel which traditionally(sequential) takes more than 28.45 hours (102,420,000 msec ) to complete the execution. Efficiency of the Utility execution is 100% and execution time has reduced to 98 to 99% effort.
A study on the trend of cloud service and security through text mining technique
Authors: Taek Park Seong , Won Lee Sung , Gu Kang Tae
Published: April 2019

Background/Objectives: The purpose of this study is to recognize the significance of security of cloud service activation and success and to draw the direction and importance for the development of Korean cloud service. Cloud computing service makes it possible to conduct a test easily and quickly at a low cost, to be scalable with an inexpensive cost, and to curb unnecessary expenses.Methods/Statistical analysis: This study collected news articles from NAVER with the use of crawling technique. The collected data were pre-processed (cleaned), and then 25 words with a high priority were analyzed in the category of the first half of 2015, the second half of 2015, and the first half of 2016.Findings: To find the trend of cloud computing service security, this study collected news articles and analyzed them after data cleaning. The analysis revealed that there was a difference in importance of each period. In the first half of 2015, the 2nd half of 2015, and the 1st half of 2016, the common noun words extracted were cloud, service, security, and enterprise in order.The difference was that the word 'environment' was found in the 1st half of 2015, the word 'management' in the 2nd half of 2015, and the words 'customer' and 'use' in the 1st half of 2016.Improvements/Applications: According to the analysis, there was a difference in importance by year. It is considered that the study results will be able to serve as the guidelines for establishing a systematic plan of cloud service security in the firms and institutions providing cloud service.
State of the art in image processing & big data analytics: issues and challenges
Authors: Vahini Ezhilraman S , Srinivasan Sujatha
Published: April 2019

Image processing, in the contemporary domain, is now emerging as a novel and an innovative space in computing research and applications. Today, the discipline of “computer science” may be termed as “image science”, why because in every aspect of computer application, either science or humanities or management, image processing plays a vital role in varied ways. It is broadly now used in all the industries, organizations, administrative divisions; various social organizations, economic/business institutions, healthcare, defense and so on. Image processing takes images as input and image processing techniques are used to process the images and the output is modified images, video, or collection of text, or features of the images. The resultant output by most image processing techniques creates a huge amount of data which is categorized as Big-data. In this technique, bulky information is processed and stored as either structured or unstructured data as a result of processing images through computing techniques. In turn, Big Data analytics for mining knowledge from data created through image processing techniques has a huge potential in sectors like education, government organizations, healthcare institutions, manufacturing units, finance and banking, centers of retail business. This paper focuses on highlighting the recent innovations made in the field of image processing and Big Data analytics. The integration and interaction of the two broad fields of image processing and Big Data have great potential in various areas. Research challenges identified in the integration and interaction of these two broad fields are discussed and some possible research directions are suggested.
An improved novel Hill cipher using RCLT Title of the article
Authors: Hema V , M. Ganaga Durga Dr
Published: April 2019

Security is the only buoyant to the frailest link. In this communication world, the implementation of sturdy cryptographic and integrity checking algorithms is the smart solution to the frailest link. So, the proposed paper provides the new-fangled pattern of cryptographic scheme in concert with Number Theory which safeguard the integrity and confidentiality of intricate data and communications. By using this system, client’s burden of security issues associated with the data hosting in the untrusted remote server is abridged. By manipulating some features of the Galois Field, a new method of key generation is proposed. The proposed system is resilient against the various attacks and cannot be understood by the intruders. It is simple yet robust and will surely improve the overall security with higher efficiency.
Comparison of intrusion detection system based on feature extraction
Authors: Laxkar Pradeep , Chakrabarti Prasun
Published: April 2019

In network traffic classification redundant feature and irrelevant features in data create problems. All such types of features time-consuming make slow the process of classification and also affect a classifier to calculate accurate decisions such type of problem caused especially when we deal with big data. In this paper, we compare our proposed algorithm with the other IDS algorithm.
Design of devops solution for managing multi cloud distributed environment
Authors: Jambunathan Baskaran , Y. Kalpana Dr
Published: April 2019

DevOps is the emerging field in the area of IT infrastructure management and cloud automation. Organization are spending time and money in terms of continuous improvement and optimization in their infrastructure management and finding to avenues for efficiency and produc-tivity improvement, reduce redundancy and optimise cost in the area of development and deployment of their enterprise application. More importantly, organisation have multiple environment to manage and hence need to have a mechanism to continuously monitor and optimize operational task and improve collaboration with various teams across organization. In addition, many companies are migrating or migrated on to cloud, some are having multiple cloud environments across regions, and hence managing it is even more difficult and need to have a mechanism to address the key challenges and risk in managing devOps in multicloud. . In this article, we would like to discuss the key challenges and how it can be addressed in a multi cloud environment and proposing an integrated solution addressing all challenges with right set of tools and framework design which enables devops in multi cloud efficiently.
Rectenna circuit at 6.13 GHz to operate the sensor devices
Authors: Saxena Anurag , K. Singh V , . Mohini , Bhardwaj Sonam , Soo Chae Gyoo , Sharma Ashis , Kumar Bhoi Akash
Published: April 2019

There are various types of transmission through wire and wireless but wireless power transmission is the transmission of electrical energy without using any conductor or lead. At resonant frequency, 6.13 GHz wearable antenna is fabricated and tested. For making wearable an-tenna, textile material (substrate) i.e. Jeans is used for the simulation having dielectric constant 1.7. At the places where it is hard to transmit energy, wearable antenna is best suitable for this purpose, but before doing this RF is converted into DC with the help of the rectifier. Vari-ous types of graph in this paper are shown in the comparison between the power and efficiency. For simulating and design purpose of an-tenna CST, software is used. Implementation of antenna with rectifier circuit is known as rectenna and the rectenna circuit can be designed in Pspice software.
Power harvesting through flexible rectenna at dual resonant frequency for low power devices
Authors: K. Singh V , Saxena Anurag , Bhushan Khare Bharat , Shakya Vicky , Soo Chae Gyoo , Sharma Ashis , Kumar Bhoi Akash
Published: April 2019

In Wireless power transmission, the transmission of electrical energy can be done without using any conductor or lead. After the simulation of wearable antenna, two resonant frequencies are obtained, i.e. 9.94 GHz and 7.35 GHz. For the designing of antenna, instead of using glass epoxy material, textile material is used having dielectric constant 1.7. The places where it is difficult to transfer the electrical energy, textile antenna is useful in those places. Ambient radio frequency can be converted in DC signal through the rectifier. All the graphs related to rectenna, such as return loss, output voltage and current at load are presented in this paper. Textile antenna for energy harvesting is de-signed in CST software and further rectenna circuit can be designed in Pspice Software.
A survey on agriculture and greenhouse monitoring using IOT and WSN
Authors: Lavanya M , Srinivasan Sujatha
Published: April 2019

Internet of things (IoT) is connecting physical objects around us; those physical objects can be monitored with the help of sensors. A sensor is a device, which is used to sense physical property of an element, any events or any changes present in the environment and send the in-formation to other electronic device, frequently a computer. Many research are made on those sensor enabled IoT system to provide intelli-gent and smart services, towards smart greenhouse and smart agriculture .This paper will explore various existing IoT based agriculture and greenhouse system according to their deployment with an intension of identifying how it can be improved in future using IoT, WSN and a very recent scenario of using cloud computing.
Using unsupervised machine learning to model tax practice learning theory
Authors: Howard Miller Alfred
Published: April 2019

The aim of this study was to utilize unsupervised machine learning framework to explore a dataset comprised of assessed output by Bachelors of Business, Taxation learners over four successive semesters. The researcher sought to motivate deployment of an evidence-supported, data-driven approach to understand the scope of student learning from a bachelor’s degree in business class taxation class, as a tool for accreditation reporting purposes. Outcomes from the data analysis identified four factors; two related to tax and two related to learning. These factors are, tax theory, and tax practice, along with practical learning and theoretical learning. Research motivated a grounded theory paradigm that explained taxation class learner’s scope of acquired knowledge. The resulting four factor model is a result of the study. The emergent paradigm further explains accounting student’s readiness for career success upon graduation and provides a novel way to meet outcomes reporting requirements mandated by programmatic business accreditors such as required by the Accreditation Council for Business Schools and Programs (ACBSP).
Detection of skin cancer- A genetic algorithm approach
Authors: D. Srividya T , V. Arulmozhi Dr
Published: April 2019

In the present scenario skin cancer is found highly risk in human beings. Many forms of skin cancer are affecting the human life. Among the form of skin cancer the unpredictable diseases is Melanoma cancer. Skin cancer the fatal form is primarily diagnosed visually leads to death, if not diagnosed in its early stage. It can be identified by tedious lab testing with more time and cost. There are vast numbers of computational techniques helpful to predict diseases. A challenging task in skin lesion classification is due to the smooth variation, in the appearance of skin lesions. Image processing techniques like segmentation is used in medical science to identify the region of significance.. This paper focuses Genetic algorithms by means of adaptive parameters (adaptive genetic algorithms, AGAs), an important and promising alternative to genetic algorithms. The extent for accurate solution and convergence speed is significantly measured by employing of crossover along with mutation from which genetic algorithms appear.