bluuebunny/crossref_metadata_2025 huggingface dataset:
Segmentation of exudates to assess diabetic retinopathy by reni’s entropy based thresholding
Authors: Elsa Joseph Josline , J. Hemalatha R , Babu Bincy , R. Thamizhvani T , Josephin Arockia Dhivya A , K Sangeethapriya
Published: April 2019

Objective: Diabetic retinopathy is a critical pathological disease condition which affects the lives of millions of people everyday. Exudates found in the eye are one of the important signs of Diabetic retinopathy. This work aims to segment exudates for faster detection and treatment of Diabetic retinopathy.Methods: This paper proposes a robust and efficient method to segment exu-dates. Initial pre-processing work applies adaptive unsharp masking which sharps the areas based on the level of smoothness in the image preventing accentuation of noise. Optic disc is removed by active contour model. The exudates are then segmented by Renyi’s Entropy based thresholding which choses the optimal threshold for segmentation, exploiting Renyi’s entropy da-ta.Results: The performance of the proposed system was evaluated and found better than state of art results giving accuracy, sensitivity and specificity 94.5%, 95.1% and 96.2% respectively.Conclusion: Effective computer aided system is essential for accurate exudates detection. The proposed algorithm utilises the advantages of adaptive unsharp masking in medical image pro-cessing along with Renyi’s entropy based thresholding to detect Exudates, which performs better than traditional thresholding techniques.
AS: a novel sentimental analysis approach
Authors: Shabaz Mohammad , Kumar Ashok
Published: April 2019

It is interesting to know about the things which are unknown. Just like the emotions, feelings, opinion, sentiments. The term sentimental analysis relates to all these above discussed terms. The extraction of opinion or sentiments from the data through the analysis is called sentimental analysis. There are different kinds of approaches but deal with extraction of sentiments. But none of the approach gives the accurate results. Since sentiments are directly related to human behaviour and human behaviour is not algorithmic. In this paper we have designed another novel approach named as AS analysis. AS analysis is one of new design to overcome the limitation of positive and negative word comparison with input text after tokenization. In this approach we have designed a new formula to find the sentiments count that ranges from -1 to +1 where negative values denotes the negative sentiments and positive values denotes the positive sentiments and 0 denotes the neutral sentiments. By this approach we conclude that the results we have obtained are near to accurate since there is no measure of accuracy it varies from individual to individual, so performing sentimental analysis always gives approximate results.
Implementation of fuzzy analytical hierarchy process on notebook selection
Authors: Abadi Satria , Huda Miftachul , Basiron Bushrah , Suhaila Ihwani Siti , Azmi Jasmi Kamarul , Hehsan Aminudin , Safar Jimaain , Kilani Mohamed Ahmad , Hassan Wan Embong Wan , Marzuki Mohamad Ahmad , Shakib Mohd. Noor Sulaiman , Novita Dona , Maseleno Andino , Irviani Rita , Idris Muhammad , Muslihudin Muhamad
Published: April 2019

Notebooks are technological devices widely adopted to assist in human daily life including learning, business, communication and other tasks. Equipped with the distinctive features, notebook was facilitated more simply for one touch screen basis to enable freely in exploring the users’ creativity. This study attempts to examine the process of selecting notebook brand among the consumers. Using AHP (Analytical Hierarchy Process) to help decision support system in the selection of Notebook from decision support systems designed to enhance all decision-process through identifying problems, selecting relevant data and defining the approaches was used to evaluate the selection of alternatives in the decision-making process. The finding reveals that the visibility of decision making into the ranking of priority with alternative choice of notebook can be viewed as follows Zyrex 16%, HP 15%, Asus 14%, Apple 13%, Samsung and Axioo 11%, Acer and Toshiba with priority 10 %.
An intelligent classification model for peanut’s varieties by color and texture features
Authors: V G Narendra , S. Kini Anita , S. Kini Anita
Published: April 2019

India is the second largest producer of peanuts in the world, and they are available in different forms: Bold or Runner, Java or Spanish and Red Natal. The main peanuts varieties produced in India are Kadiri-2, Kadiri-3, BG-1, BG-2, Kuber, GAUG-1, GAUG-10, PG-1, T-28, T-64, Chandra, Chitra, Kaushal, Parkash, Amber, etc. Peanut is the prime crop for our country’s peasants to increase their agricultural income. However, our country’s international trade price of peanut is only 80% of the average market price. The automation level of testing peanut kernels’ quality is low because of workers fatigue, and most of the work is done by manpower leads costly. The peanuts are evaluated in many areas for sowing and oilseed processing; they must be identified quickly and accurately for selection of a correct variety and kernels’ quality. The proposed testing method based on image processing and computer vision is a new one which is undamaged, speedy with high distinguishing rate, repeatability and low cost and fatigue. In this paper, machine-learning classifiers (Multilayer Perceptron, Simple Logistic, Support Vector Machines, and Sequential Minimal Optimization and Logistic classifiers) are investigated to obtain the best predictive model for peanuts classification. The training and test sets are used to tune the model parameters during the training epochs by varying the complexity of the predictive models with K-fold cross-validation. After obtaining optimized models for each level of complexity, a dedicated validation set is used to validate predictive models. The developed computer vision system provided an overall accuracy rate for the best predictive model in discriminating peanuts variety are Random Forest (82.27%), Multilayer Perceptron(84.9%), and libSVM (86.07%)
IESDAD :improved energy efficient structure- free data aggregation and delivery protocol in WSN
Authors: Kaur Avneet , Sharma Neeraj
Published: April 2019

The wireless sensor is deployed to sense large amount of data from the far places. With the large deployment of the sensor networks, it faces major issues like energy consumption, dynamic routing and security. The Energy efficient structure-free data aggregation and delivery (ESDAD) is the protocol which is hierarchal in nature. The ESDAD protocol can be further improved to increase lifetime of wireless sensor networks. The base station localizes the position of each sensor node and defines level of each node for the data transmission. In the ESDAD protocol, the next hop node is selected based on cost function for the data transmission. In this research work, improved in ESDAD protocol is proposed in which gateway nodes are deployed after each level for the data transmission. The sensor node will sense the information and transmit it to gateway node. The gateway node aggregates data to the base station and simulation results show that improved ESDAD protocol performs well in terms of energy consumption and number of throughput.
Profile of cold-formed steel for compression member design a basic combination performance
Authors: Septiropa Zamzami , Hanim Osman Mohd. , Baharuddin Abd. Rahman Ahmad , Azreen Mohd Ariffin Mohd. , Huda Miftachul , Maseleno Andino
Published: April 2019

Experiment previously showed several findings that the strength of cold-formed steel cross-section are not the same, where web strength and flange strength do not give the same response when receiving the axial load. This occurs not only because of a shift in the center point of the force due to deformation of the cross section, but also due to different strengths in cross-section, especially on the web section and flange section. To find out more details of this case, the experiment carried out the tensile test for mechanics property and compression test with an axial load to find which parts are weaknesses, then used as a reference in combining the profile. The compression test results showed significant increase in compression capability between single profile with double profile back to back (Dbb) or double profile flange to flange (Dff) with ratio 1: 2.24 and 1: 2.44 respectively. There is a non-linear increase in the value of Aeff and Ieff when becomes combine profiles (double, quadruple, hexatruple), so this can be the basis for increasing the combine profile capacity to be able to withstand larger loads. This experiment can show a basic performance of CFS, where are weak section parts of a profile can be used as a reference to put combine profile to increase compression capacity. With a numerical analysis approach compared to the experimental results, the combination of Cold-formed steel profile is established as a column for the low-rise building structure.
Color code method design evaluation and data analysis
Authors: Dzelzkaleja Laura
Published: April 2019

Nowadays, with the growing attention to Educational data mining, it important to use the data analysis results to improve course assessment and improve the e-learning process. A new Color code method for understanding students’ learning process has been introduced in the previous research. The method uses three color codes: red for "problem", yellow for "work in progress" and green for "job done". The method has proven to work in a classroom environment and recently implemented in the edX learning platform. In this paper the button design is tested in four student groups and the button press data analyzed taking into consideration students’ gender and exam marks. Research show that 18% of the students used buttons without difference in gender and that highest button usage activity had the least course non-finishers and the highest number of students that got the highest mark. Survey showed that button design needs some improvement.
Faster pedagogical framework for steam education based on educational robotics
Authors: Damaševičius Robertas , Maskeliūnas Rytis , Blažauskas Tomas
Published: April 2019

Globalization and sustainable development requires shifting education targets from acquisition of structures knowledge to the mastery of skills. Robot-aided learning can used as a tool of creativity in AHSS (Arts, Humanities and Social Sciences) classes thus attracting the attention of learners to cross-disciplinary subjects with elements of STEM (Science, Technology, Engineering, and Mathematics), which is expanded to STEAM (STEM + All). The presented FASTER pedagogical framework is based on the combination of project-based teaching, educational robotics and team based learning for achieving educational aims and supporting creativity in class. We describe the practical use of the framework in a university course, with specific examples of student projects. Finally, we discuss the educational implications of the framework and beyond.
Self-organizing cognitive model synthesis with deep learning support
Authors: Raikov A , Ermakov A , Merkulov A
Published: April 2019

Cognitive models are created by experts and the process takes a lot of time. Furthermore, the result of expert work needs to be verified especially in cases when experts do not have complete information and cannot understand the problem situation quickly. As was previously shown cognitive models’ factors and their mutual relationships could be verified with applying Big Data analysis technology. This paper addresses the issue of automated cognitive models synthesis on the base of author’s convergent methodology, artificial intelligence and deep learning technology.
Postdiffset: an Eclat-like algorithm for frequent itemset mining
Authors: A.W.A. Bakar W , A. Jalil M , Man M , Abdullah Z , Mohd F
Published: April 2019

Frequent itemset mining is a major field in data mining techniques. This is because it deals with usual and normal occurrences of set of items in a database transaction. Originated from market basket analysis, frequent itemset generation may lead to the formulation of association rule as to derive correlation or patterns.  Association rule mining still remains as one of the most prominent areas in data mining that aims to extract interesting correlations, frequent patterns, association or casual structures among set of items in the transaction databases. Underlying structure of association rules mining algorithms are based upon horizontal or vertical data formats. These two data formats have been widely discussed by showing few examples of algorithm of each data formats. The works on horizontal approaches suffer in many candidate generation and multiple database scans that contributes to higher memory consumptions. In response to improve on horizontal approach, the works on vertical approaches are established. Eclat algorithm is one example of algorithm in vertical approach database format. Motivated to its ‘fast intersection’, in this paper, we review and analyze the fundamental Eclat and Eclat-variants such as tidset, diffset, and sortdiffset. In response to vertical data format and as a continuity to Eclat extension, we propose a postdiffset algorithm as a new member in Eclat variants that use tidset format in the first looping and diffset in the later looping. We present the performance of postdiffset results in time execution as to indicate some improvements has been achieved in frequent itemset mining.
Globalization and New Trends in Management – Europe Union Security Aspects
Authors: Nowakowska -Grunt Joanna , Maśloch Piotr
Published: April 2019

This article attempts to define what contemporary globalization is and present opportunities and threats this process generates. The purpose of this paper is also to show how dynamically the reality in Europe is changing and how new threats associated with economy, management and other processes.  The globalization processes of the economies worldwide and the dynamic development of trade and international cooperation create new conditions and threats, under which countries and social-political-economic organizations (e.g. EU) must operate.Experience over the last years has shown, that even the strongest supporters of openness to other values and culture, which are new for Europe, have revised their views, surprised by the scale of illegal immigrations and others EU security aspects.
Towards using cloud computing technology in Egyptian governmental organizations
Authors: M. El Haddad Basmah
Published: April 2019

Although Cloud Computing Technologies “CCT” and their benefits have been recognized for decades, there are still fears at Egyptian Governmental Organizations “EGO” to migrate to them. The paper addresses developing & enhancing IT capabilities & business model at EGOs by adopting CCT from a national planning viewpoint. It starts by explaining Cloud Computing “CC” definition, concept, characteristics, types, models, benefits and challenges. Then introduces survey results as a guide model for EGO, as done in a previous study supervised by the author, surveying their awareness of CCT, standards, and factors impacting the migration. It contributed with a “Proposed Generic Cloud Computing Architectural Framework for EGO” to be adopted nationally. It concludes that adopting CCT has a positive impact on IT from a financial & Performance viewpoints that raise its IT capabilities.
Supplier Evaluation Model on SAP ERP Application using Machine Learning Algorithms
Authors: Kohli Manu
Published: April 2019

For business enterprises, supplier evaluation is a mission critical process. On ERP (Enterprise Resource Planning) applications such as SAP, the supplier evaluation process is performed by configuring a linear score model, however this approach has a limited success. Therefore, author in this paper has proposed a two-stage supplier evaluation model by integrating data from SAP application and ML algorithms. In the first stage, author has applied data extraction algorithm on SAP application to build a data model comprising of relevant features. In the second stage, each instance in the data model is classified, on a rank of 1 to 6, based on the supplier performance measurements such as on-time, on quality and as promised quantity features. Thereafter, author has applied various machine learning algorithms on training sample with multi-classification objective to allow algorithm to learn supplier ranking classification. Encouraging test results were observed when learning algorithms,(DT) and Support Vector Machine (SVM), were tested with more than 98 percent accuracy on test data sets. The application of supplier evaluation model proposed in the paper can therefore be generalised to any other other information management system, not only limited to SAP, that manages Procure to Pay process.
Power factor control of PV generators in local distribution networks using fuzzy logic concept
Authors: A. Shalwala Raed
Published: April 2019

One of the most important operational requirements for any electrical power network for both distribution and transmission level is voltage control. Many studies have been carried out to improve or develop new voltage control techniques to facilitate safe connection of distributed generation. In Saudi Arabia, due to environmental, economic and development perspectives, a wide integration of photovoltaic (PV) genera-tion in distribution network is expected in the near future. This development in the network may cause voltage regulation problems due to the interaction with the existing conventional control system. In a previous paper, a control system has been described using a fuzzy logic control to set the on-line tap changer for the primary substation. In this paper a new control system is proposed for controlling the power factor of individual PV invertors based on observed correlation between net active and reactive power at each connection. A fuzzy logic control has been designed to alter the power factor for the remote invertors from the secondary substation to keep the feeder voltage within the permissible limits. In order to confirm the validity of the proposed method, simulations are carried out for a realistic distribution network with real data for load and solar radiation. Results showing the performance of the new control method are presented and discussed.
A Novel Approach for Prediction of Heart Disease: Machine Learning Techniques
Authors: Srinivas V , Aditya K , Prasanth G , G.Babukarthik R , Satheeshkumar S , Sambasivam G
Published: April 2019

Heart disease and machine learning are the two different words where one is related to medical field and another one to artificial intelligence. In medical filed most of them are facing the problems with the heart disease and machine learning is developing area in computer science. Heart disease is general called cardiac disease where it gives the more data or information, it is to be collected to give the reports for the patients and the machine learning also requires the data for predicting and to solve the problems. Machine learning techniques are used in prediction of heart diseases where it gives the faster prediction with less computation time and better accuracy to progress their health. Heart disease prediction requires lot of data for predicting and in cloud computing also we have more data and the data available in cloud it is difficult to analyze. So we use machine learning algorithms or techniques to predict the heart disease and the in the similar way we can apply these algorithms or techniques to predict or analyze the data that is available in cloud. In this paper we are going to use machine learning algorithms called Backpropagation Algorithm and later we use optimization algorithm later. Backpropagation algorithm deals with the artificial neural networks. Backpropagation is a method used to calculate the error contribution of each neuron after a batch of data (in image recognition, multiple images) is processed. This is used by an enveloping optimization algorithm to adjust the weight of each neuron, completing the learning process for that case. Machine learning algorithms and techniques are used for recognize the intensity of risk issues in humans and it helps the patients to take safety measures in well advances to save the patient’s life.
Simultaneous Scheduling Through Heuristic Algorithms
Authors: Nageswara Rao M , Lokesh K , Harish V , Sai Bharath Ch , Venkatesh Y , Kumari. S Vara
Published: April 2019

Flexible Manufacturing System (FMS) is a compli-cated system because of work environments, recu-peration frameworks, mechanized putting away, and material dealing with gadgets like robots and AGVs. In this paper, an endeavor is made by con-sidering both the machine and vehicle planning angles in FMS for minimization of the make trav-erse. Game plan is ensnared with the arrangement of incomplete assets to assignments in finished time. It is like Information-gathering process. It is related with the cost, operations, time and several objectives of the industry. In this work, RAPID ACCESS (RA) heuristic algorithm is adopted to solve the scheduling problems in FMS. Eighty, two problems and their existing solutions with different approaches are examined. The RA heuristic algo-rithm provides better solutions with less computa-tional time.
A Unified Frame Work to Integrate Hadoop and IOT to Resolve the Issues of Storage, Processing with Leveraging Capacity of Analytics
Authors: Syam Prasad Gudapati , Rajesh P , Wasim Akram Sk
Published: April 2019

The new trend in the research and real time applications is Internet of Things (IOT). The functional benefits of IOT are ranging from smart house to smart cities. The main purpose of IOT is to integrate various devices logically and interacting between the devices without human intervention. The current discussion mainly focuses on leveraging the capacity of analytics in IOT and resolves the storage issues of the bulk data generated by IOT. The proposed idea gives the usage of Hadoop platform to store the data and from that data performing analytics for the sake of better utilization of IOT communications. The importance is explained with some real time scenarios where there is perfect blend of Hadoop platform and IOT. To store the various categories of the data Hadoop Distributed File System (HDFS) can be used, and to ingest the data from external platforms we can make use of Sqoop or Flume. The data available in HDFS can be used to process with the usage of Map Reduce (MR)technique. Once the data is available in  HDFS the analytics can be performed with Hive, Pig or R in the context of Machine learning or data mining techniques. The outcome of the proposed idea is integration of Hadoop and IOT platforms with a unified frame work which accommodates the integration of Hadoop and IOT, storage provisions to handle bulk data, processing of the stored data and applying analytics so as to effectively serve various stake holders.
An Efficient Method in Real Time for Water Quality Monitoring Using Internet of Things
Authors: Bhagavan K , Vamsi Krishna R , Chandu Lakshmi Gangadhar A , Arun M
Published: April 2019

In this day and age, Internet of Things (IoT) and Remote Sensing (RS) procedures are being utilized as a part of various regions of research for observing, gathering and breaking down information from remote areas. Drinking water is a valuable product for every single individual as drinking water utilities confront a considerable measure of new difficulties progressively activity. These difficulties start in light of restricted water assets, developing populace, maturing foundation and so on in this way there is a requirement for better techniques to screen the water quality. Keeping in mind the end goal to guarantee the protected and providing of drinking water the quality ought to be checked progressively. In this paper we intend to present the arrangement and development of a minimal attempt framework for genuine observing of water quality in an IoT situation. The structure comprises of a few sensors which are utilized for estimating physical and substance parameters of water [1]. The frameworks, for example, temperature, pH, turbidity, conductivity, broke down oxygen of the water can be estimated. Utilizing this framework a man can recognize toxins from a water body from anyplace in the world.
Reservoir Computing for Healthcare Analytics
Authors: S Pathak Shantanu , Rajeswara Rao D
Published: April 2019

In this data age tools for sophisticated generation and handling of data are at epitome of usage. Data varying in both space and time poses a breed of challenges. Challenges they possess for forecasting can be well handled by Reservoir computing based neural networks. Challenges like class imbalance, missing values, locality effect are discussed here. Additionally, popular statistical techniques for forecasting such data are discussed. Results show how Reservoir Computing based technique outper-forms traditional neural networks.
A Survey on Using Biometrics for Cloud Security
Authors: Ruth Ramya K , N.V.Saikrishna D , Sravya Nandini T , Tanmai Gayatri R
Published: April 2019

Cloud computing the most emerging data storage and processing technology. Today many organizations are using cloud-based data storage because of their complex data management. Even though cloud is attracting many users towards using it but there is a requirement of security concerns to be taken care of because cloud is untrusted, the data which individual stores on cloud will be transparent to cloud administrator also which may be confidential. So, while using cloud security is the primary concern. In this paper, we proposed a scheme to encrypt cloud data using user attribute-based encryption. Which is a public key crypto technique in which key will be based on the attributes of user. The attributes we used are biometrics of user who is going to upload the data.
Image Processing and Restriction of Video Downloads Using Cloud
Authors: Hari Krishna Yaram , Bharath Kumar Kanagala , Maharshi Dasari , Amudhavel J
Published: April 2019

Flower image classification using deep learning and convolutional neural network (CNN) based on machine learning in Tensor flow. Tensor flow IDE is used to implement machine learning algorithms. Flower image processing is based on supervised learning which detects the parameters of image. Parameters of the image were compared by decision algorithms. These images are classified by neurons in convolutional neural network. Video processing based on machine learning is used in restriction of downloading the videos by preventing the second response from the server and enabling the debugging of the video by removing the request from the user.
An Effective Software Reliability Estimation with Real-Valued Genetic Algorithm
Authors: G KrishnaMohan Dr , Sowmya B , Mohanvamsi K , Sandeep K
Published: April 2019

The implemented approach is powerful method for estimating reliability of the software parameters growing SRGM by utilizing an Algorithm which is known as RGA. The full form of RGA is Real-valued Genetic Algorithm. Parameters required for current SRGM, if we take an illustration, the Failures average number or identification rate of the failure utilizing the techniques which are numerical, estimation of the maximum probability or estimation of minimum square.RGA means the free form of SRGM parameter estimation limitations. Instead of these, this can be much adapted for optimizing domain continuously compared to the algorithm of the binary genetic. The operators of GA which is 2 real valued crossovers& mutation of non-uniform interfaced for enhancing SRGM parameters estimation execution and accuracy enhancement. I led tests over eight datasets which are real valued to contrast implemented scheme & techniques of the numerical & another generic algorithm which are typical. The results describes that in estimation of SRGM parameters, the RGA is the most powerful compared to the others. So that we can trust the RGA which is the right solution for getting the efficient software quality with estimation of reliable accuracy.
Effect of SBI Bank Merger on Education Loan, a Comparative Study Using Big Data Analytics
Authors: Mathur Anjali , Vinitha K , Shubham R , Gowtham K
Published: April 2019

A bank merger is a situation in which two banks or all branches of a bank join together to become one bank. The bank merger of State Bank of India was implemented on 1stApril 2017 in India. The bank merger is a good idea to centralize the customer’s data from nationwide. However, it is a difficult task for administrators and technologists. Some high level techniques are required to collect the data from the branches, of the bank present at nationwide, and merge them accordingly. For this huge data Big-Data Analysis techniques can be used to manage and access the data. The big data analytics provides algorithms to compare, classify and cluster the data at local and global level. This research paper proposes big data analytics for education loan provided by State Bank of India. The loan granting process becomes centralized after merger. It affects the processing of granting a loan, as earlier it was according to branches only. The proposed work is for comparative study of the impact of bank merger on education loan provided by State Bank of India.
A Survey on Twitter Sentimental Analysis with Machine Learning Techniques
Authors: Krishna Chaitanya G , Reddy Meka Dinesh , Surya Vamsi Vakalapudi , V S Ravi Karthik M
Published: April 2019

Sentiment or emotion behind a tweet from Twitter or a post from Facebook can help us answer what opinions or feedback a person has. With the advent of growing user-generated blogs, posts and reviews across various social media and online retails, calls for an understanding of these afore mentioned user data acts as a catalyst in building Recommender systems and drive business plans. User reviews on online retail stores influence buying behavior of customers and thus complements the ever-growing need of sentiment analysis. Machine Learning helps us to read between the lines of tweets by proving us with various algorithms like Naïve Bayes, SVM, etc. Sentiment Analysis uses Machine Learning and Natural Language Processing (NLP) to extract, classify and analyze tweets for sentiments (emotions). There are various packages and frameworks in R and Python that aid in Sentiment Analysis or Text Mining in general.
An Expert System to Mitigate Problems in University Using Chat Bot
Authors: Akhil S , Sai Krishna V , Kranthi M , Nihar A , S.Mastan Rao T
Published: April 2019

There has been a rapid increase in the data generated over the past few decades in all domains. As part of our research study we are considering domain of information provided by the university to the public i.e. the aspirants applying to the university as well as the students undergoing the curriculum. We are developing an advanced chat-bot which assists the students to gather information about the university. Since the information which can be provided from the official website is not up to the mark, there is a need for developing another medium for providing the necessary information. Whenever a student requires some assistance of any matter regarding university they can gather information from helpdesk, website or billboards. Sometimes the information may not be accurate and insufficient. So, in order to make the required information accessible to the students we are developing this software where students can interact with the software assistant through text and gain the information that is required by them. The software allows the student to interact with it in text basis and provides almost any information regarding University.
An Effective Method for Scheduling Virtual Machines in Cloud
Authors: Gunasekhar T , Vinaykumar V , Laharipriya J , Raghubabu P
Published: April 2019

With the rise of cloud figuring, processing assets (i.e., systems, servers, stockpiling, applications, and so forth.) are provisioned as metered on-request benefits over systems, and can be quickly dispensed and discharged with negligible management exertion. In the cloud registering worldview, the virtual machine (VM) is a standout amongst the most usually utilized asset units in which business administrations are epitomized. VM scheduling advancement, i.e., finding ideal position plans for VMs and reconfigurations as indicated by the evolving conditions, winds up testing issues for cloud framework suppliers and their clients.
Review on failure forecast in cloud for a fault tolerant system
Authors: M. Nandhini J , Gnanasekaran T
Published: April 2019

Cloud Computing is an increasingly popular computer paradigm constituting a large infrastructure involving storage, memory, servers and applications accessible via computer network. The cloud system design aims to provide on-demand services with scalability on diverse resources to ensure efficient resource utilization in addition to effectiveness. As cloud is a service-oriented infrastructure, it is critically imperative that the system is highly reliable to meet the Service Level Agreement (SLA). To achieve reliability, cloud requires a very efficient fault tolerance mechanism. Serviceability and reliability is impacted by any failure in the system. Prior prediction of faults in the system helps in overcoming failures. The Fault Tolerance in cloud involves ascertaining the resource fitness to execute scheduled task. The process involves prior screening of resources against various tasks as part of scheduling process. The scheduling process relies significantly on the virtualization of resources to maintain high efficiency.
A study on the optimal line integrated design analysis system
Authors: Kim Taesung , Lee Hyunsoo , Hong Heedong
Published: April 2019

Background/Objectives: This paper is a study on a system that standardizes processes based on smart virtual production technology strategy for manufacturing line design and development, and integrates new or existing resources and systems into one consistent and structured framework.Methods/Statistical analysis: In this paper, we standardize the process based on the digital virtual production technology strategy for manufacturing line design and development. A system that integrates new or existing resources and systems into a single, unified framework. Through this system, various events participating in the development of the manufacturing line can receive standardized work progress and communication in one consistent system. In addition, we standardized and library the scattered data to minimize the loss of data management.Findings: Users across a wide range of areas can quickly and easily perform line development from line planning to design, setup and optimization based on standardized processes and an intuitive user experience. By providing analysis results in conjunction with heterogeneous analysis engines, you can perform solution-independent business processes. The effectiveness of the proposed system was verified by applying the proposed system to the actual new and expansion manufacturing line and redesign line in the company and performing line development work.Improvements/Applications: Through this study, it is expected that the actual field data of MES (Manufacturing Execution System) and the information of planning system such as ERP (Enterprise Resource Planning) can be linked to the integrated decision support system of engineering solution.
Analysis technique of a wearable IoT health information on the MAPHIS
Authors: Man Ko Kwang , Gohn Kim Soon
Published: April 2019

Background/Objectives: As u-health becomes common that monitors body condition real time in the ubiquitous environment, people are increasingly interested in promoting their health using biometric information identified by various health equipment.Methods/Statistical analysis: the concept of digital health has emerged that encompasses the followings: u-health that is expected to improve efficiency in medical service and monitor patients’ condition with wireless communication through convergence of ICT and health care industry; smart health(s-health) that manages their own workout, calorie intake and sporting activities with their smart device; and, mobile health (m-health) that uses wearable and mobile devices as a means of healthcare.Findings: In this study, we aim to develop a health care platform that receives diabetes information generated from various IoT based on remote inputs, stores, analyzes, processes and provides visualized information. The purpose of this study is to develop and test IoT-based diabetes health big-data platform for diabetes mellitus patients. To achieve this goal, we suggest the development result of service and contents oriented “An IoT-based diabetes health big-data Offloading platform” that comprehensively manages healthcare products created in many IoT-based diabetes information to build a personal health management system. We also developed android 4.x-based application so that the health management service and contents provided by a third party can be checked with the client PC as well as health management service and contents offered by web-based client application and third party can be operated in the mobile environment such as smartphone or tablet.Improvements/Applications: The results of this study are verified by applying it to patients with diabetes or suspected cases. In order to increase the efficiency of real-time processing, we used off-loading technology to utilize big data related to diabetes generated from wearable IoT device. The results of this study will be used for telemedicine in two hospitals in Malaysia after various laboratory verification procedures.
ZVS based switching technique mitigates the power losses using mosfet based full bridge dc converter
Authors: Kumara Swamy Durgam , B. V. Sanker Ram Dr
Published: April 2019

In today’s' vitality power industries Boost converters highly required to convert the normal power into improvised power. Normally vitality converters struggled with voltage pressure over the power electronics switching nature and undulation. The renewable energy of a kind that vitality Photovoltaic (PV)-cell sources, windmill and battery are the sources for the converters; in this Photovoltaic play a vital role and mostly used medium to provide converters for further processing. The vitality PV is basically acted along with solar power efficiency, which is improvised ZeroVoltage Switching [ZVS] converters. The Zero-Voltage Switching [ZVS] converters transforms the low-power DC energy to high-power or vitality DC-energy, which reduces the voltage pressure over the power electronics switching units and undulation is improving execution of the electrical system vitality efficiently and simplifying the circuit nature.
Implementation of the centralized control system for drone training
Authors: Hyun Kim Bong
Published: April 2019

Background/Objectives: The drones became a representative item in the IoT era. However, there is no drone pilot test system that can safely train this in the education field. Drones have very dangerous structural problems, so it is very necessary to practice them easily. Therefore, it is necessary to develop a system that can control the drones safely and easily while controlling them.Methods/Statistical analysis: In this paper, we will develop software for controlling a dedicated board platform that can securely perform ground testing by mounting four drones of motor and drive on a board (PCB). To this end, we supported various control IMU (Inertial Measurement Unit) boards for attitude control by using sensor which is the core technology of drone flight control. Also, Acceleration Data, Angular Velocity Data, Earth Magnetic Field Data, and Atmospheric Pressure Data for maintaining the altitude were used for the drone flight.Findings: In the implemented central control system, the AT chip is built in and designed to perform all control related to the flight of the drone. In addition, since it is an embedded system, we have programmed the attitude control using the sensor, the motor output setting, and the controller connection information. The CPU required for drones control can be replaced with various types of controllers besides Fno Arduino, UNO, Muiltiwii. For this purpose, the main PCB is designed so that the power supply terminal can be used for each CPU. Finally, it was developed as a setup program to correct the sensor and output of the drone.Improvements/Applications: The system implemented in this paper can easily control the drone. In addition, acceleration, angular velocity, geomagnetic field, air pressure sensor, GPS, etc. necessary for drone control can be utilized by stabilizing the initial set value. In other words, the zero point of the sensor can be captured and the signal appropriate to the current state of the drone can be stored in the processor.
Review on automatic text summarization
Authors: Rajasekaran Abirami , R. Varalakshmi Dr
Published: April 2019

Due to the abundant information available in different forms of sources and genres, there is an immense need to summarize the data for humans. Text Summarization has gained more popularity in this fast-growing information age. Past few years have witnessed a rapid growth in the research of summarizing the text automatically using different approaches. This paper provides an in-depth review of the vari-ous approaches, techniques, methods involved in Automatic Text Summarization.
GWO tuned multi degree of freedom PID controller for load frequency control
Authors: Charan Patel Nimai , Kumar Debnath Manoj , Prasad Bagarty Durgesh , Das Pranati
Published: April 2019

In order to enhance the control action, in this article multi degree of freedom PID controllers (MDFPID) like 2DOF-PID and 3DOF-PID controllers are suggested for frequency control in a multi-unit hydro-thermal interconnected system. The finest gains of the recommended MDFPID controllers are achieved with Grey Wolf Optimization (GWO) Technique considering a time based evaluative function. The dom-inating performance of the suggested control technique is validated by relating the outcomes with a pre-published journal results. The robust behavior of the MDFPID controller is also validated by abruptly amplifying the loading of the system. The system dynamic responses are analyzed in consideration with time response parameters like minimum undershoots, settling time and peak overshoots.
Mobility models for an asynchronous wireless sensor multimedia network
Authors: Kumar D Praveen , Jerritta S Dr
Published: April 2019

In Wireless Sensor Multimedia Networks, the movement models and tracking mechanisms have important roles on Quality of data collection and network delay. The various movement models in a hierarchically connected network entities are discussed in a Wild life Habitat moni-toring scenario. The quality of routing decisions depends on how accurately we can predict the mobility pattern of nodes. A simulator test-ing the different mobility models is discussed in this paper.
Implementation levels of virtualization and security issues in cloud computing
Authors: Banushri A , R. A. Karthika Dr
Published: April 2019

Cloud is the buzz word in the industry. The initiation of virtualization technology in the infrastructure domain gives us the options to procure the benefits of the cloud deployments. Virtualization is a fast-growing infrastructure in the IT industry. Technology providers and user communities have introduced a new set of terms to describe the technologies and their features for virtualization. Virtualization characterizes the logical vision of data representation. The authority to compute in virtualized environment, storing the data at dissimilar geographies and diverse computing resources. Virtualization technology allows the creation of the virtual versions of hardware, networking resources, Operating systems and storage devices. It supports multiple OS run on single physical machine called host machine and multiple guest application run on single server called host server. Hypervisors assistance in virtualization of hardware. That is, the software interrelates with the physical system, providing virtualized environment to maintain multiple operating system running parallel using one physical server. This paper provides the information about the implementation levels of virtualization, the benefits and security problems of Virtualization in virtualized hardware environment.
High Mobility Supports Routing Protocol (HMSRP) in Mobile Ad Hoc Networks
Authors: T.Senthil Murugan Dr , . .
Published: April 2019

Now-a-days wireless communication required for infrastructure less environment due to avoiding centralized data maintenance and fixed infrastructure data transmission because these types of network not supporting in emergency situation like natural disaster, Battle field and so on. But, Mobile Ad-Hoc networks (MANETs) are support the data communication in the above mentioned situations. In MANET, network implementation and maintenance has many emerging research areas like routing, Energy management, Quality of services, etc. Even many types of protocols are proposed and identified in this area but still it is more complex for identifying quality route. One of the most important factors for identifying quality route is “Mobility”. Many researchers are proposed protocols based on routing with random mobility. In this paper, we propose a new routing protocol “High Mobility Supports Routing Protocol (HMSRP)” which is supporting high mobility. Mobility has to be calculated using directional antennas. This proposed new protocol has supports to identify the location of the node, enhance the fast data transmission and control the fast communication.  Simulation results are shown our proposed protocol is produce good results over other protocol.
Challenges in implementing industry revolution 4.0 in INDIAN manufacturing SMES: insights from five case studies
Authors: N Suresh , K Hemamala , N Ashok
Published: April 2019

Purpose-This research examines Small and Medium manufacturing Enterprises (SME’s) awareness, current capability, willingness and ability to identify the challenges involved in implementing Industry 4.0(I 4.0) at their premises.Design/methodology/approach-A set of questionnaire was framed to collect qualitative and quantitative data from five manufacturing SME’s and they were analyzed to gain insight.Findings –3 out of 5 manufacturing SME’s are aware, capable, willing and have ability to identify the challenges for implementing Industry 4.0 at their premises. The study also found that implementation of I 4.0 depends on size of the firm. Medium size manufacturing firms had started investing in Information Technology but small scale industries is still struggling to figure out their long term benefit.Practical implications – The advancement and the integration of the technologies such as Cyber Physical system, Internet Of Things, Artificial intelligence, Big data, Cloud computing and 3D printing provides greater flexibility to the manufacturing firms. In today’s global competition with a huge demand for personalized products at low price with best quality, innovation and capability to full filling batch size of one is becoming important. Hence, to meet the market demand many large-scale industries started investing in advanced technology where SME has yet to pay attention.Originality/value –Paper indicates the Indian manufacturing SME’s preparedness for Industry 4.0. It contains five cases capturing the current manufacturing practices followed in the SME’s and their capability towards implementing Industry I 4.0 in Indian environment.