NCETT-2017- National Conference On Emerging Trends and Technologies

"NCETT 2017 Conference Papers "

Importance of Big Data and Hadoop[ ]


Users are generating more and more information today, filling an ever growing collection of storage devices. The information may be about customers, web sites, security, or company logistics. As this information grows, so does the need for businesses to sift through the information for insights that will lead to increased sales, better security, lower costs, etc. The Hadoop system was developed to enable the transformation and analysis of vast amounts of structured and unstructured information. It does this by implementing an algorithm called Map Reduce across compute clusters that may consist of hundreds or even thousands of nodes. In this presentation Hadoop will be looked at from a storage perspective. The presentation will describe the key aspects of Hadoop storage, the built-in Hadoop file system (HDFS), and other options for Hadoop storage that exist in the commercial, academic, and open source communities.

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Applications and Benefits of Mobile Computing[ ]


Mobile computing is becoming increasingly important due to the rise in the number of portable computers and the desire to have continuous network connectivity to the Internet irrespective of the physical location of the node. Mobile computing offers significant benefits for organizations that choose to integrate the technology into their fixed organizational information system. Ranging from wireless laptops to cellular phones and Wi-Fi/Bluetooth enabled PDA’s to wireless sensor networks, mobile computing has become ubiquitous in its impact on our daily lives. Mobile computing is a versatile and potentially strategic technology that improves information quality and accessibility, increases operational efficiency, and enhances management effectiveness. The goal of this paper is to point out some of the limitations, characteristics, applications and issues of mobile computing.

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USING HEALTH CARE WITH CLOUD COMPUTING[ ]


Cloud computing is a recent and fast growing area of development in healthcare. Ubiquitous, on-demandaccess to virtually endless resources in combination with a pay-per-use model allow for new ways of developing, delivering and using services. Cloud computing is often used in an “OMICS-context”, e.g. for computing in genomics,beyond this traditional domain proteomics and molecular medicine, while other field of application still seem to be underrepresented. Thus, the objectiveof this scoping review was to identify the current state and hot topics in research on cloud computing in healthcare.

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Cryptography Algorithms For Providing Security To Data While Transferring Over Network[ ]


Data Security & Cryptography is a concept to protect data while transmission over network. Data Security is the main aspect of secure data transmission over unreliable network. Network security involves the authorization of access to data in a network, which is controlled by the network administrator. Users choose or are assigned an ID and password or other authenticating information that allows them access to information and programs within their authority. Network security covers a variety of computer networks, both public and private, that are used in everyday jobs conducting transactions and communications among businesses, government agencies and individuals. Networks can be private, such as within a company, and others which might be open to public access. Data security is involved in organizations, enterprises, and other types of institutions. In this paper we also studied cryptography along with its principles. Cryptographic systems with ciphers are described. The cryptographic models and algorithms are outlined.

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Analysis on securing the data over the Internet of Things (IoT)[ ]


The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic idea is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. IoT is rapidly developing, but there are some uncertainties about its security and privacy which would affect its growth. In this paper, we have analyzed the security issues and challenges and we have provided well defined security architecture as a confidentiality of the user’s privacy and security

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Query Minimization Methods[ ]


SQL statements can be used to retrieve data from any database. If you've worked with databases for any amount of time retrieving information, it's practically given that you've run into slow running queries. Sometimes the reason for the slow response time is due to the load on the system, and other times it is because the query is not written to perform as efficiently as possible which is the much more common reason. For better performance we need to use best, faster and efficient queries. This paper covers how these SQL queries can be optimized for better performance. Query optimization subject is very wide but we will try to cover the most important points. In this paper I am not focusing on, in- depth analysis of database but simple query tuning tips & tricks which can be applied to gain immediate performance gain.

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Security issues in SaaS of cloud computing[ ]


Cloud computing is becoming increasingly popular in distributed computing environment. Locking at the impact it as on numerous business applications as well as this makes IT resources available,known as cloud computing ,opens opportunities to small ,medium- sized ,and large companies. Data storage and processing using cloud environments is becoming a trend worldwide. Software as a Service (SaaS) one of major models of cloud which may be offered in a public, private or hybrid network. If we look at the impact SaaS has on numerous business applications as well as in our day to day life, we can easily say that this established technology is here to stay. Cloud computing can be seen as Internet-based computing. By using a cloud computing specimen can have positive as well as negative effects on the security of service consumer’s data. Many of the important features that make cloud computing very attractive, have not just challenged the existing security system, but have also exposed new security risks. In this paper we are going to showcase some major security issues of current cloud computing environments.

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Research And Challenges For Cloud Computing Security Issues[ ]


In this paper publisher accomplish about cloud computing architecture for providing computing service via internet is called the cloud computing and on demand pay per user access to a pool of shared resources namely networks, storage, servers, services and applications, without physically acquiring them. There are three Verities of services like.(saas, paas, iass). Business organizations, private, public organizations and also government sectors, healthcare, entertainment, educational organizational moving towards the cloud computing the main thing is cloud computing saves the cost, efficiency and it saves the time. Cloud computing totally depends on internet without having internet cloud computing is impossible to access data from the cloud. Data is organized and maintained and stored in data centers, cloud providers like, Google, Amazon, Salesforce.som and Microsoft etc. There are various research challenges also there for adopting cloud computing such as well managed service level agreement (SLA), privacy, interoperability and reliability. The major security thread is which include data leakage insecure interface, sharing of resources data maintainability and availability and inside attack or limited and it controls over the data incur. this paper analysis key researches and challenges and presents in cloud computing comprises to improve their bottom line in this service economic in this paper analysis key researches and challenges and presents in cloud computing comprises to improve their bottom line in this service economic nature.

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Reviews on Eye blink detection[ ]


We are surrounded by technologies; spend more and more time with visual display unit (VDU) devices such as computers, laptops, TV screens, mobile phones and tablets. Use of VDU devices is often associated with eye and visual problems. Normally eye should blink 10 – 15 times per minute. But the rate of spontaneous eye blinking while using computer reduces significantly (up to 60% reduction). Blinking helps us to spread the tear film, moisten and disinfect the surface of the eye, due to which the reduced blink rate causes dryness of our eyes which causes dryness, redness, burning, sandy-gritty eye irritation or sensitivity to light and eye fatigue. These symptoms are also known as Dry Eye, which is a major part of the Computer Vision Syndrome (CVS). CVS is a set of problems related to the computer use including dry eyes, eyestrain, headache, blurred vision, neck pain and backache. The easiest way to avoid the symptoms of Dry Eye is to blink regularly. There are only few available hardware or software solutions which try to prevent from dry eye symptoms. This paper gives a brief overview of Gabor’s filters and Circular Hough Transformation for a method for extracting circles from images.

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Emerging Issues of Green Computing in IT[ ]


During recent years, attention in ‘Green Computing‘ has moved research into energy saving techniques for home computers to enterprise systems' Client and Server machines. It is needed to find a way to handle computers and its devices for save the environment and society from such E-hazards. This study provides a brief account of Green Computing. The emphasis of this study is on current trends in Green Computing; challenges in the field of Green Computing and the future trends of Green Computing. Since, it is a qualitative research; the researcher used Individual interviews and Observations to collect relevant information to fulfill this research. IT industry is putting efforts in all its sectors to achieve Green computing. Equipment recycling, reduction of paper usage, virtualization, cloud computing, power management, Green manufacturing are the key initiatives towards Green computing.

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Feature Extraction Using Mel Frequency Cepstrum Coefficients for Automatic Speech Recognition[ ]


The most natural mode of communication for human being is Speech. The task of speech recognition is to convert speech into a sequence of words by a computer program. Automatic speech recognition (ASR) will plays a vital role in taking technology to the people. Find many applications of speech recognition such as direct voice input in aircraft, data entry, speech-to-text processing, voice user interfaces such as voice dialing. Generally ASR system can be divided into two different parts, namely feature extraction and feature recognition. In this paper we present MATLAB based feature extraction using Mel Frequency Cepstrum Coefficients (MFCC) for ASR. IT also describes the development of an efficient speech recognition system using different techniques such as Mel Frequency Cepstrum Coefficients (MFCC).

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Cryptography: Boon or Bane - A Review[ ]


In this present world, everything is being digitalized. The most important thing is the data. Everything is represented as data. Sometimes the data is considered to be the sensitive or private ones. Sensitive data contains the data that is not to be shared to others without proper permissions. But, in this present world the data is theft by unauthorized ones. In these situations, to save the privacy of the data - it is to be encrypted to make it unreadable before digitalizing and needs to be decrypted to make the same readable. This can be achieved by “cryptography”. This paper is a review paper about the data security and for whom it is a boon and bane for whom.

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A Study on Current Mobile Operating Systems[ ]


This paper presents a detail review on current mobile operating systems like IOS from Apple, Android from Google, windows 10 mobile from Microsoft Company, BlackBerry 10 from BlackBerry Ltd, Tizen from Linux Foundation, Sail fish OS from Sailfish Alliance, Mer, Jolla and Sailfish community contributors, Ubuntu Touch from Canonical Ltd. and Ubuntu community contributors. In this paper we have compared all the features, facilities, performance and verdict about these mobile operating systems.

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A A3P FRAMEWORK TO PROTECT USER UPLOADED DATA IN CLOUD[ ]


With the increasing volume of images share through social sites by users, maintaining privacy has become a major problem, as demonstrated by a recent wave of publicized incidents where users inadvertently shared personal information. In light of theseincidents, the need of tools to help users control access to their shared content is apparent. Toward addressing this need, we propose an Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images.Social network users expect the social networks that they use to preserve their privacy. Traditionally, privacy breaches have been understood as malfunctioning of a given system. However, in online social networks, privacy breaches are not necessarily a malfunctioning of a system but a byproduct of its workings. The users are allowed to create and share content about themselves and others. When multiple entities start distributing content without a control, information can reach unintended individuals and inference can reveal more information about the user.

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Evaluation of Sorting Algorithms, Mathematical and Empirical Analysis of sorting Algorithms[ ]


Sorting is an important data structure in many real life applications. A number of sorting algorithms are in existence till date. This paper continues the earlier thought of evolutionary study of sorting problem and sorting algorithms concluded with the chronological list of early pioneers of sorting problem or algorithms. Latter in the study graphical method has been used to present an evolution of sorting problem and sorting algorithm on the time line.

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Optimal Redundancy Design Of Stochastic LAN Devices Failures In Private Clouds[ ]


The cloud computing infrastructure need to be selected with optimal number of devices whose reliabilities are stochastic in nature so that the offered cloud service are uninterrupted. Public and private cloud deployment models differ. Public clouds, such as those from Amazon Web Services or Google Compute Engine, share a computing infrastructure across different users, business units or businesses. Whereas the private cloud infrastructure is to be carefully designed keeping in mind of the budget spent, mean lifetime of the offered service as well as the nature of the devices used to built the cloud. A novel attempt is made to build cloud infrastructure by making use of sdp(stochastic dynamic programming) techniques to offer reliable services.

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Robotic System and Artificial Intelligence[ ]


The invention of computers or machines, their capability to perform various tasks went on growing exponentially. Humans have developed the power of computer systems in terms of their diverse working domains, their increasing speed, and reducing size with respect to time. A branch of Computer Science named Artificial Intelligence pursues creating the computers or machines as intelligent as human beings. Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems.

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Self-organizing behavior of Wireless Ad Hoc Networks[ ]


Self-organization is a great concept for building scalable systems consisting of huge numbers of subsystems. The primary objectives are coordination and collaboration on a global goal. Until now, many self-organization methods have been developed for communication networks in general and ad hoc networks in particular. Nevertheless, the term self-organization is still often misunderstood or misused. This paper contributes to the ad hoc community by providing a better understanding of self-organization in ad hoc networks. The main contribution of this paper is a categorization of self-organization methodologies.

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Hyper spectral Remote Sensing and GIS for Forestry Management: a Survey[ ]


Hyperspectral sensors are devices that acquire images with narrow bands (less than 20nm) with continuous measurement. It extracts spectral signatures of objects or materials to be observed. Hyperspectral have more than 200 bands. Hyperspectral remote sensing has been used over a wide range of applications, such as agriculture, forestry, geology, ecological monitoring, atmospheric compositions and disaster monitoring. This review details concept of hyperspectral remote sensing; processing of hyperspectral data. It also focuses on the application of hyperspectral imagery in agricultural development. For example, hyperspectral image processing is used in the monitoring of plant diseases, insect pests and invasive plant species; the estimation of crop yield; and the fine classification of crop distributions.

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Paper Presentation on Data Mining for Internet Of Things[ ]


The massive data generated by the Internet of Things (IoT) are considered of high business value, and data mining algorithms can be applied to IoT to extract hidden information from data. In this paper, we give a systematic way to review data mining in knowledge view, technique view, and application view, including classification, clustering, association analysis, time series analysis and outlier analysis. And the latest application cases are also surveyed. As more and more devices connected to IoT, large volume of data should be analyzed, the latest algorithms should be modified to apply to big data. We reviewed these algorithms and discussed challenges and open research issues. At last a suggested big data mining system is proposed.

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A Review on Big Data Privacy and Security[ ]


Big data is a convergence of new hardware and algorithms that allow us to discover new patterns in large data sets-patterns we can apply to making better predictions and, ultimately, better decisions. Today, organizations are putting Big Data into practice in such diverse fields as healthcare, smart cities, energy and finance.. Big data can be characterized by 3 V’s i.e., Volume, Velocity, Variety. Big data analytics is the term used to describe the process of researching massive amounts of complex data in order to reveal hidden patterns or identify secret correlations. However, there is an obvious challenge between the security and privacy of big data and the widespread use of big data. This paper focuses on privacy and security concerns in big data, differentiates between privacy and security and privacy and requirements in big data. There have been a number of privacy-preserving mechanisms developed for privacy protection at different stages (for example, data generation, data storage, and data processing) of a big data life cycle. The goal of this paper is to provide a major review of the privacy preservation mechanisms in big data and present the challenges for existing mechanisms. This paper also presents recent techniques of privacy preserving in big data like differential privacy, privacy preserving big data publishing. This paper refer privacy and security aspects healthcare in big data. Comparative study between various recent techniques of big data privacy is also done as well.

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Cyber Security Issues and Challenges in India[ ]


Cyber Security plays an important role in the field of information technology .Securing the information have become one of the biggest challenges in the present day.Cyber security can be a useful term but tends to defy precise definition. It is also sometimes inappropriately conflated with other concepts such as privacy, information sharing, intelligence gathering, and surveillance.In this paper the management of risk to information systems is considered fundamental to effective cyber security. The risks associated with any attack depend on three factors: threats (who is attacking), vulnerabilities (how they are attacking), and impacts (what the attack does).The government role in cyber security involves both securing government systems and assisting in protecting non-government systems.

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Cloud in Banking Sector[ ]


Cloud computing is known as on-demand computing and one of the latest developments in the IT industry. It provides the full scalability, reliability, high performance and relatively low cost feasible solution as compared to dedicated infrastructures. Security of Cloud computing is a sub-domain of network security, computer security and information security. This paper presents the role to improve cloud security and how cloud computing is impacting the Banking sector and what that management need to focus on when developing a strategy for their organization’s adoption of cloud computing.

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SECURE CLOUD STORAGE[ ]


As an emerging technology and business paradigm, Cloud Computing has taken commercial computing by storm. Cloud computing platforms provide easy access to a company’s high-performance computing and storage infrastructure through web services. We consider the problem of building a secure cloud storage service on top of a public cloud infrastructure where the service provider is not completely trusted by the customer. We describe, at a high level, several architectures that combine recent and non-standard cryptographic primitives in order to achieve our goal. We survey the benefits such an architecture would provide to both customers and service providers and give an overview of recent advances in cryptography motivated specifically by cloud storage.

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BIGDATA PROCESSING: AN INTEGRATIVE MODELING[ ]


More than 2.5 extra bytes of data are created everyday based on the user information automatically generated over Internet. Social networks, mobile devices, emails, blogs, videos, banking transactions and other consumer interaction, are now driving the successful marketing campaigns, by establishing a new digital channel between the brands and their audiences. Powerful tools are needed to store and explore this daily expending Big Data, in order to submit an easy and reliable processing of user information. Expected quick and high quality results are as much important as priceless investments for marketers and industrials. Traditional modeling tools face their limits in this challenge, as the information keeps growing in volume and variety, thing that can be handled only by non-relational data modeling techniques.

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Survey on Data Mining[ ]


This paper provides an introduction to the basic concept of data mining. Which gives overview of Data mining is used to extract meaningful information and to develop significant relationships among variables stored in large data set/data warehouse. In the case study reported in this paper, a data mining approach is applied to extract knowledge from a data set. Data mining is the process of discovering potentially useful, interesting, and previously unknown patterns from a large collection of data.Data mining is a multidisciplinary field, drawing work from areas including database technology, machine learning, statistics, pattern recognition, information retrieval, neural networks, knowledge-based systems, artificial intelligence, high-performance computing, and data visualization. We present techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability.The automated, prospective analyses offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems.

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Cloud VM Security with Machine learning based Agent[ ]


Cloud computing is an effective way of utilizing and managing IT resources and services at low cost, which is available but with few challenges to security which is to be addressed succinctly. Since virtualization forms the base of cloud computing one should ensure security of virtual-machine images that encapsulate each application of the cloud. VM Security should be introspected on process that runs in it, should ensure isolation and should not effect the process running in others VM’s and also in the same VM which may be accessing internet or web service. So to avoid this security path every VM will have an INTELLIGENT AGENT as a process or a thread that does not allow the malwares (computer viruses, worms, Trojan horses, spyware, dishonest adware, scareware, crimeware, most rootkits, and other malicious and unwanted software or program.) to run on the virtual environment of a cloud by comparing the features of the applications that are ready to run on VM with the built-in application features stored in the repository of VM.

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Cloud Computing in Education[ ]


Cloud computing is not just a buzz-word, it represents a strong direction of IT industry development. Speaking of cloud computing we should distinguish three different service models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). The scope of this work is a model of Software as a Service. This represents the lease of computing resources on a network of remote servers where applications are executed and data is stored. The application of cloud computing is very broad and growing daily because of many advantages to the users, and is driven by the increasing use of various mobile devices (laptops, tablets and Smartphone) and mobile Internet access being more available. Cloud computing is applicable in education, but it implies the acceptance of these services by all involved in the educational process. Therefore, the aim of this paper is to investigate whether there is a need between our students for applications and services in the "cloud" (SaaS), the extent to which they use them and what types of applications and services are leading. The paper analyzes and interprets the results of this study which provides indications of students’ willingness to "move to the cloud".

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BIG DATA CHALLENGES IN GENERATING RIGHT METADATA[ ]


Big data is a term for massive data sets having large, more varied and complex structure with the difficulties of storing, analyzing and visualizing for further processes or results. The process of research into massive amounts of data to reveal hidden patterns and secret correlations named as big data analytics .These useful information’s for companies or organizations with the help of gaining richer and deeper insights and getting an advantage over the competition. It refers to the data sets that are too big to be handled using the existing database management tools, are emerging in many important applications, such as Internet search, business informatics, social networks, social media, genomics, and meteorology. Big data presents a grand challenge for database and data analytics research. The primary purpose of this paper is to provide an in-depth analysis of different platforms available for performing big data analytics. This paper surveys different hardware platforms available for big data analytics and assesses the advantages and drawbacks of each of these platforms based on various metrics such as scalability, data I/O rate, fault tolerance, real-time processing, data size supported and iterative task support.For this reason, big data implementations need to be analyzed and executed as accurately as possible.

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Cyber security in E-commerce[ ]


Now a day, World Wide Web has become a popular medium to search information, business, trading and so on. Various organizations and companies are also employing the web in order to introduce their products or services around the world. Therefore E-commerce or electronic commerce is formed. E-commerce is any type of business or commercial transaction that involves the transfer of information across the internet. In this situation a huge amount of information is generated and stored in the web services. This information overhead leads to difficulty in finding relevant and useful knowledge, therefore web mining is used as a tool to discover and extract the knowledge from the web. Besides, the security issues are the most precious problems in every electronic commercial process. This massive increase in the uptake of e-commerce has led to a new generation of associated security threats. In this paper we use techniques for security purposes, in detecting, preventing and predicting cyber-attacks on virtual space.

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Shoulder Surfing Resistant Graphical Authentication System[ ]


This evolution brings great convenience but also increases the probability of exposing passwords to shoulder surfing attacks. Attackers can observe directly or use external recording devices to collect users’ credentials. To overcome this problem, we proposed a novel authentication system PassMatrix, based on graphical passwords to resist shoulder surfing attacks. With a one-time valid login indicator and circulative horizontal and vertical bars covering the entire scope of pass-images, PassMatrix offers no hint for attackers to figure out or narrow down the password even they conduct multiple camera-based attacks. We also implemented a PassMatrix prototype on Android and carried out real user experiments to evaluate its memorability and usability. From the experimental result, the proposed system achieves better resistance to shoulder surfing attacks while maintaining usability.

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Data Mining Methods and Applications[ ]


Data mining is a process to store large amount of data. The paper discuss data mining methods and applications. This data mining methods and applications improve our business and found extradinary results .. Data Mining is a broad term for a variety of data analysis techniques applied to the problem of extracting meaningful knowledge from large, noisy databases. An important feature present in most of these techniques is an ability to adapt to the local characteristics of the data. Such techniques are applied to electric load profiling tasks; load profiling consists of modelling the way in which daily load shape (load profile) relates to various factors such as weather, time and customer characteristics. An implementation of an adaptive load profiling methodology is presented.

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BUSINESS INTELLIGENCE AND ANALYTICS IN BIG DATA[ ]


Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioner sand researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A.BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications ,researchers, and research topics based on more than a decade of related academic and industry publications .Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework. The opportunities associated with data and analysis in different organizations have helped generate significant interest in BI&A, which is often referred to as the techniques, technologies ,systems, practices, methodologies, and applications that analyze critical business data to help an enterprise better understand its business and market and make timely business decisions. In addition to the underlying data processing and analytical technologies, BI&A includes business-centric practices and methodologies that can be applied to various high-impact applications such as e-commerce, market intelligence, e-government, healthcare, and security.

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Information about Cyber Crimes and Cyber Security: With Solutions[ ]


The rapid technological developments, our life is becoming more digitalized. Be it business, education, shopping or banking transactions everything is on the cyber space. There are some threats posed by this incredible rise in digitization which is creating a new set of global concern called as cyber crime. It is easy to fall prey to such unethical way of hacking and penetrating into personal life which is feasible at a click of a button. Cyber crimes thereby take place in many forms like illegal access and theft of data, intrusion into devices and fraud which is a big concern amongst all the users. This paper identifies the importance of being acquainted with the effects of cyber crime keeping in mind the recent activities that have taken place and offering solutions to protect oneself from it. Moreover, highlighting the need of being cyber safe and how such illegal activities can be a problem for us. The present paper reviews the current solutions to deal with the alarming rise in these criminal activities. Hi-tech technologies that need to be adopted to prevent oneself from getting webbed have been recommended in the paper. A few case studies have been discussed and innovative suggestions for future cyber security proposed.

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Technological Trends in Human Resource Management[ ]


The world of technology and mobile computing has made the concept of “traditional workspace” a thing of past. Today, employees can work from anywhere at any time. Technology has completely redefined the role of human resources all over the world. Recent advances in technology have transformed nearly every aspect of HR, right from sourcing to performance management. Some industry experts opined that technology is one factor that is impacting the HR department to a great extent.

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Concepts, Applications and Future Scope of Big Data[ ]


Big Data refers to the data or sets of records that are too large in volume to be operated using the existing database management tools and techniques. They are produced in many important applications, such as search engines, business informatics, social networks, social media, genomics, meteorology, and weather forecast. Big data presents a big challenge for database and data investigative research. The main objective of this paper is to give a brief introduction of Big Data, its architecture, characteristics and challenges. The hurdles of securing the data and democratizing it have been elaborated amongst several others such as inability in finding sound data professionals in required amounts and software that possess ability to process data at a high velocity. Through the article, the authors intend to decipher the notions in an intelligible manner embodying in text several use-cases and illustrations.

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Role Of Ratio Analysis In Business Decisions[ ]


Accounting information provided by means of financial statements- The income statement and the Balance Sheet are often in summarized form. Viewed on the surface, the truths about the results and the financial position of a business hidden in them remain veiled. To be of optimal benefit and as well enable the users make well – informed decisions, financial statements need to be analyzed by means of ratios. Therefore, in order to establish the role of ratio analysis in business decisions both the Financial Accounting and the Management will be considered .

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ARTIFICIAL NEURAL NETWORKS ON HUMAN[ ]


This paper is an introduction to Artificial Neural Networks. Neural network simulations appear to be a recent development. However, this field was established before the advent of computers, and has survived at least one major setback and several eras. Neural networks take a different approach to problem solving than that of conventional computers which has been explained in this paper. The various types of neural networks are explained and demonstrated, applications of neural networks like ANNs in medicine are described, and a detailed historical background is provided. The connection between the artificial and the real thing is also investigated and explained. Finally, the mathematical models involved are presented and demonstrated.

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Adoption of Cognitive Technology[ ]


Time to move towards the adoption of cognitive technology. When it comes to adoption of cognitive technology, some of the leading companies are progressing rapidly from the pilot project phase to the production application phase. Those on the sidelines would do well to move from interest to adoption of this impressive group of technologies.

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Securing Big Data From Cyber Threats[ ]


Big data presents a challenge for data base and data analytical research. Big data provides the unstructured data. Big data will also help analysts to visualize cyber attacks by taking the complexityfrom various data sources and security solutions to protect data and prevent future cyber attacksTerm Big Data Analytics for Security intelligence refers to a process of analyzing and mining large amounts of data (petabytes, exabytes, zettabytes) from different sources including IP address, Emails, log files, information get from other attack investigation and many more.

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The approach to enquiry based inductivelearning practice engineering education of the Datamining[ ]


Inquiry based Inductive learning methodology is one of the best technique especially for the engineering students who are expected to solve real world problems. But it is very difficult to standardize a particular learning methodology for an institution with diverse attitude, diverse characteristics, diverse languages, diverse financial back grounds, and diverse cultural scenario with variable educational standard of the students. As the teaching methodology depends on the content and time as well as learners’ varied style of learning, the same learner may prefer inductive teaching for one topic and deductive approach for the other topic. This paper initiates a sample study that is taken for a particular institution, in the particular environment, for the particular batch and particular set of students. The sample data are collected from a classroom by distributing the questionnaire attempted by two different batches of student having questions pertaining to Inquiry based and deductive learning. The system is developed and tested twice after teaching the content using inductive method and implemented using attribute relevance, discriminant rules of class discrimination mining. The results are visualized through bar charts and shows that the two batches of learners of different years have different learning characteristics.

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A New Indexing Data Structure for Classifying Stream Data[ ]


Continuous data is common in areas. Note that very large stream data mining is very important and it becomes one of the most important data mining. For state-of-the-art stream data mining algorithms require in many cases exactly one and only one pass in order to process full training data sets. For managing very large stream data powerful and more sophisticated and state-of-the-art indexing data techniques are needed to process, search, and query the huge stream data. Ensemble ETREE technique is one of the best multidimensional indexing data structure for storing classification rules of ensemble classifiers. Ensemble data indexing tree structure reduces time complexity of classifying a new stream data record from linear time complexity to logarithmic time complexity. A new indexing technique is proposed for tree node splitting in the case of ensemble indexing tree construction. New node splitting method is convenient, easy to use, understand and process all the required results during the time of ensemble tree construction process for the important operations of tree insertion, modification and deletion. Here main goal of stream data mining algorithms is to design and develop algorithms only for processing data in pass only.

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DUPLICATE RECORD DELETION IN RELATIONAL DATABASE MANAGEMENT SYSTEMS[ ]


Relational database is defined as a set of individual units called relations. Record repetition or duplication is common in many cases of real life situations in the usages of relational databases. In relational database, if the same record is stored in more than one place then such records are termed as duplicate records. Finding duplicate records and then replacing them by the most suitable one best record or a group of best records is called a new operation, fusion operation. Whenever duplicate tuples are found in the relations of any database, those records ought to be replaced with one individual best approximate record that represents the joint information of all the duplicate tuples. Present paper proposes a new technique to find out duplicate tuples and then remove away all such duplicate tuples with the correct real world tuples. Total procedure consists of two steps. In the first step duplicate copy of tuples in the relation are classified by means of the class label and in the second step of the procedure then for each set of duplicate tuples functional dependency means or union method is applied to replace duplicate tuples with the corresponding correct real world single tuple. One opportunity is to replace one set of duplicate tuples through one correct real world tuple. Another possibility is to replace two or additional sets of duplicate tuples in the relation by one set of new and accurate real world tuples. From time to time removing of duplicate tuples in the relations of any relational database can create problems in referential integrity violations. Any such violation must be controlled and updated both syntactically as well as semantically correct in relations.

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