Computer Science

The main objective of higher education is to provide quality education to students One way to achieve highest level of quality is to identify factors affecting performance and then trying to resolve weaknesses of factors The objective of proposed research work is to find out if there are any patterns in the available data that could be useful for predicting students performance

The thesis aims to describe data types methods and algorithms that are to be used in data Mining and machine learning The work deals with analysis of tools WEKA,KNIME,RAPID MINER and Orange

The basic pitfalls in image analysis is edge detection Edge characteristics and boundaries are useful in image segmentation Edges play an important role in many applications of image processing in particular for machine vision systems that analyze scenes of man made objects under controlled conditions

It is used for data to analyze the use in various applications and implementing data mining techniques using cluster analysis.

Cooperative communication has received tremendous interest for wireless networks. Most existing works on cooperative communications are focused on link-level physical layer issues. Consequently, the impacts of cooperative communications on network-level upper layer issues, such as topology control, routing and network capacity, are largely ignored. In this article, we propose a Capacity- Optimized Cooperative (COCO) topology control scheme to improve the network capacity in MANETs by jointly considering both upper layer network capacity and physical layer cooperative communications.

This paper proposes an improved LSB based steganography technique for images imparting better information security for hiding secret information in images. There is a large variety of steganography techniques some are more complex than others and all of them have respective strong and weak points, LSB Steganography known, focusing on the case when gray scale bitmaps are used as cover images.

Self Destructing Data In Cloud And HDD Based on Active Storage Framework

Impact of Edge Detection Algorithm in Image Processing

Digital marketing is the marketing of products or services using digital technologies, mainly on the Internet, but also including mobile phones, display advertising, and any other digital medium. Digital marketing’s development since the 1990sand 2000shas changed the way brandsand businesses use technology for marketing. As digital platforms are increasingly incorporated into marketing plans and everyday life, and as people use digital devices instead of visiting physical shops, digital marketing campaigns are becoming more prevalent and efficient. This paper mainly focuses on conceptual understanding of digital marketing, how digital marketing helps today’s business and some cases in the form of examples
This project will through a light on DIGITAL MARKETING , its trend in past and present and
its future in the globalised world. As marketing has become a very important tool for every
industry to reach the consumer it’s become very complex as to decide what is the right medium
for marketing. As the world has modernized dramatically in the last decade digital media has
reached every home and hence become a very important vehicle for marketing. This project will
cover digital marketing trends and its future, general problem faced and few suggestion to
overcome it along with few cases
With the ever increasing development in technology, the use of Digital Marketing, Social Media Marketing, Search Engine Marketing is also increasing. Digital Marketing is used by the marketers to promote the goods and services to the marketplace. Digital Marketing place an important role in increasing the sales of goods and services. The purpose of this research is to study the impact of Digital Marketing, how it’s an important tool for both marketers and consumers. We have also studied the impact of Digital Marketing and its influence on consumer buying behavior.

Artificial Intelligence is the science and engineering of making intelligent machines, aimed at providing machines with the ability to think, reach, and surpass human-level intelligence. In this paper, we begin with an introduction to the general field of artificial intelligence, then progress to the birth, history and theorise of artificial intelligence. We then explore the main streams in the field, along with the advancement, evolution and it’s applications for various aspects of our life. The paper will cover central and current research related to artificial intelligence, including reinforcement learning, robotics, computer vision, and symbolic logic. In parallel, we highlight the unique advantages for future technologies, focusing on opportunities, limitations, and ethical questions. To conclude, we describe several current areas of research within the field
and recommendations for future research.

Generally, Artificial Intelligence systems function based on a Knowledge Base of facts and rules that characterize the system's domain of proficiency. The elements of a Knowledge Base consist of independently valid (or at least plausible) chunks of information. The system must automatically organize and utilize this information to solve the specific problems that it encounters. This organization process can be generally characterized as a Search directed toward specific goals. The search is made complex because of the need to determine the relevance of information and because of the frequent occurence of uncertain and ambiguous data.

This book will introduce you to the Python programming language. It’s aimed at beginning
Programmers, but even if you’ve written programs before and just wants to add Python to your list
Of languages, Introducing Python will get you started.
It’s an unhurried introduction, taking small steps from the basics to more involved and varied topics. I mix cookbook and tutorial styles to explain new terms and ideas, but not too many at once. Real Python code is included early and often.
Even though this is an introduction, I include some topics that might seem advanced, such as No SQL databases and message-passing libraries. I chose these because they can solve some problems better than standard solutions. You’ll download and install external Python packages, which is good to know when the “batteries included” with Python don’t fit your application. And it’s fun to try something new.
I also include some examples of what not to do, especially if you’ve programmed in other languages and try to adapt those styles to Python. And I won’t pretend that Python is perfect; I’ll show you what to avoid

This book will introduce you to the Python programming language. It�s aimed at beginning
Programmers, but even if you�ve written programs before and just wants to add Python to your list
Of languages, Introducing Python will get you started.
It�s an unhurried introduction, taking small steps from the basics to more involved and varied topics. I mix cookbook and tutorial styles to explain new terms and ideas, but not too many at once. Real Python code is included early and often.
Even though this is an introduction, I include some topics that might seem advanced, such as No SQL databases and message-passing libraries. I chose these because they can solve some problems better than standard solutions. You�ll download and install external Python packages, which is good to know when the �batteries included� with Python don�t fit your application. And it�s fun to try something new.
I also include some examples of what not to do, especially if you�ve programmed in other languages and try to adapt those styles to Python. And I won�t pretend that Python is perfect; I�ll show you what to avoid.

YOU CAN WIN YOUR FEATURE

Cyber Security is the internet and the internet because of the leak of important data through the internet and indicates that the term is called cyber security. Computer Security covers all processes and processes the protect the information of the secrecy, integrity and information availability of both digital equipment, information and services, unwanted or unauthorized access, alteration or destruction, and transit and rest location. Cyberspaces ant its basic infrastructure are weakening a wide range of risk against both physical and cyber threats and risks.

ANALYZING AND TRACING OF VARIOUS PACKET DROPPING ATTACKS USING CONTAINING ORDER ROUGH SET.

A STUDY ON AFFECTIVE KNOWLEDGE BASED ON EMOTIONAL INTELLIGENCE

Human Computer interface is the power underlying developments that move into items and techniques that individuals utilize, it for work or delight. A new line human computer interface is the power underlying developments that move into items and techniques that individuals utilize, if for work or delight. Human components are both a science and a field of designing . I is concerned with human poroficiencies, Impediments, and execution, and with the outline of frameworks that are proficient, safe, agreeable, and even pleasant for the humans who use them. It is additionally a craft in the feeling of regarding and advertising innovative courses for specialists to apply their aptitudes in planning frameworks.

A STUDY ON AFFECTIVE KNOWLEDGE BASED ON EMOTIONAL INTELLIGENCE

The aim of our paper is to fill this literature gap devising resource allocation policies for cloud virtualized environments able to identify performance and energy tradeoffs, providing a priori availability guarantees for cloud end users. Keywords:Cloud Computing, Dependability, Faults, Resource Allocation,Resource Management.

In general, Web based search interfaces; it can be difficult to formulate queries that simultaneously combine temporal, spatial, and relevant data filters. We investigate how coordinated visualizations can enhance search and exploration of information on the World Wide Web by easing the formulation of these types of queries.Drawing from visual information seeking and exploratory search, we introduce Pictcath - interactive query visualizations of Web-based information that operate with online information within a Web browser. Pictcath provide the information
seeker with visual overviews of Web resources and offer a way to visually filter the data. Our goal is to facilitate the construction of dynamic search queries that combine filters from more than one data dimension. We present a prototype information exploration system featuring three linked Pictcath, and used it to visually explore news items from online RSS feeds.
Keywords:
Pictcath, Information visualization, World Wide Web, information retrieval, exploratory search, visual information Searching.

BigData as name specifies, it is the large amount of data and also the term
for large or complex data sets. BigData refers to application which works on
unmatched complex data sets. Hadoop is the software for Bigdata applications.
When the data is processed in such software applications, the large amount of
halfway with plentiful information is generated and thrownaway when it is about
to finish its process. Inspired by this observation, a Distributed Cache for BigData
is proposed. In Distribute Cache, the halfway results are submitted to the cache
manager, where the data is referred from the cache manager toexecute the results
of particular applications or a large data. Distributed cache consequently improves
the completion time of MapReduce applications and saves a consequent hunk of
CPU execution time.Keywords:BigData, Hadoop, Map Reduce, Distributed Cache, Distribut
e FileSystem,Cache Management.

In recent times, performance and economic cost optimizations for workflows
from various applications in the cloud have become a warm research topic.
However, we find that most existing studies adopt wireless optimization strategies,
which fail to arrest the key optimization opportunities for different workloads
and cloud presents.This paper proposes ROS, a general Revolution- Based
Optimization Structure for workflows in the cloud. Specifically, ROS formulates
six basic workflow transformation operations. An subjective performance and
cost optimization process can be represented as a transformation plan (i.e., a
sequence of basic transformation operations).We further develop a cost model
guided planner to professionally find the optimized transformation for a predefined
objective. We develop ROS on real cloud environments including Amazon EC2
and Rackspace.
Keywords:RoS, Cloud, Trasformation Operations, Optimization Workflows.

Information Technology is used in various fields like education, business,
medicine, weather ect., but not used vastly in Agriculture Sector. Agriculture
has been the backbone of the Indian economy. With growing population and the
ever growing demand for food, the scientists and researchers across the globe are
busy trying to find innovative ways to meet there ever surging demands. There
are several factors affecting the low productivity in India like illiteracy, general
socio-economic backwardness, slow progress in reforms and efficient finance and
marketing services for farm produce. But the most important factor affecting
the low productivity is inadequate use of modern technology and information
technology (IT) for identifying nutrient balance, analyzing cropping diseases,
getting required suggestions and finding appropriate fertilizer during cultivation
at minimum cost and cropping patterns. With the evolution of cloud computing
and its subsequent popularity, the service providers are coming up with very essay
and affordable solutions for end-users. This upcoming technology is predicted to
bring revolutionary changes to the agriculture sector. This paper concerned with
the concept of cloud computing, its’s effective implementation and how effectively
it can contribute as an ICT tool to play a vital role developing the agriculture sector
in the developing countries.
Keywords:
Agriculture field, Cloud Computing, Tools, ICT

Cloud computing is a new technology model for IT services which many
businesses and organizations are adopting. It allows them to avoid locally hosting
multiple servers and equipment and constantly dealing with hardware failure,
software installs, upgrades and compatibility issues. For many organizations, cloud
computing can simplify processes and save time and money. This article defines
cloud computing and shows how it is different from other types of computing. It
also discusses how cloud computing solutions could be beneficial to libraries in
three basic areas: technology, data and community.
Keywords:
Cloud Computing, Library Automation.

It can be broadly said that a machine learns whenever it changes its structure, program, or data (based on its inputs or in response to external information) in such a manner that it’s expected future performance improves. The objective of this proposal is to build an e-healthcare framework that is discovered by converging the semantic web and web mining techniques. This e-healthcare framework would empower the patient and physician both for taking better decision for managing health. Healthcare institutions need to target the patients with proper portfolios of services. There is a wealth of data available within the healthcare systems but they lack effective analysis tools to discover hidden relationships and trends in data. By applying web mining techniques on ontology based structure of web, useful patterns and knowledge can be discovered for making intelligent decisions for the care of individuals.
Keyword: Ontology, Semantic web, Web mining, E-Healthcare, Association, Classification

Abstract— we propose secure multi-party computation protocols for collaborative data
publishing with M-privacy. All protocols are extensively analyzed and their security and
efficiency are formally proved. Experiments on real-life datasets suggest that our approach
achieves better or comparable utility and efficiency than existing and baseline algorithms
while satisfying M-privacy. We consider the collaborative data publishing problem for anonym
zing horizontally partitioned data at multiple data providers. We consider a new type of
“insider attack” by colluding data providers who may use their own data records (a subset of
the overall data) to infer the data records contributed by other data providers. The paper
addresses this new threat, and makes several contributions. First, we introduce the notion of
M-privacy, which guarantees that the anonymized data satisfies a given privacy constraint
against any group of up to m colluding data providers. Second, we present heuristic
algorithms exploiting the mono-tonicity of privacy constraints for efficiently checking M-
privacy given a group of records. Third, we present a data provider-aware anonymization
algorithm with adaptive M-privacy checking strategies to ensure high utility and M-privacy of
anonymized data with efficiency.
Index Terms— heuristic algorithms, base line algorithms, multi party communication
protocols, group mono-tonicity

In the domain of Image processing, Image mining is advancement in the field of data mining. Image mining is the extraction of hidden data, association of image data and additional pattern which are quite not clearly visible in image. It’s an interrelated field that involves, Image Processing, Data Mining, Machine Learning, Artificial Intelligence and Database. The lucrative point of Image Mining is that without any prior information of the patterns it can generate all the significant patterns. This is the writing for a research done on the assorted image mining and data mining techniques. Data mining refers to the extracting of knowledge /information from a huge database which is stored in further multiple heterogeneous databases. Knowledge/ information are communicating of message through direct or indirect technique. These techniques include neural network, clustering, correlation and association. This writing gives an introductory review on the application fields of data mining which is varied into telecommunication, manufacturing, fraud detection, and marketing and education sector. In this technique we use size, texture and dominant color factors of an image. Gray Level Co-occurrence Matrix (GLCM) feature is used to determine the texture of an image. Features such as texture and color are normalized. The image retrieval feature will be very sharp using the texture and color feature of image attached with the shape feature. For similar types of image shape and texture feature, weighted Euclidean distance of color feature is utilized for retrieving features.

Keywords: Data Mining, Image Mining, Feature Extraction, Image Retrieval, Association, Clustering, knowledge discovery database, Gray Level Co-occurrence Matrix, centroid, Weighted Euclidean Distance.

The new method proposed in this paper applies a multivariate reconstructed phase space (MRPS) for identifying multivariate temporal patterns that are characteristic and predictive of anomalies or events in a dynamic data system. The new method extends the original univariate reconstructed phase space framework, which is based on fuzzy unsupervised clustering method, by incorporating a new mechanism of data categorization based on the definition of events. In addition to modeling temporal dynamics in a multivariate phase space, a Bayesian approach is applied to model the first-order Markov behavior in the multidimensional data sequences. The method utilizes an exponential loss objective function to optimize a hybrid classifier which consists of a radial basis kernel function and a log-odds ratio component. To perform experimental evaluation on three data sets to demonstrate the feasibility and effectiveness of the proposed approach.

Keywords—Temporal pattern, reconstructed phase space, Gaussian mixture models, Optimization, Dynamic data system.

:A new decentralized access control scheme is used for data storage in clouds that supports anonymous authentication. In proposed scheme the cloud verifies the authenticity of the series without knowing the user’s identity before storing the original data. This decentralized scheme also has the added feature of access control in which only valid users with their valid attributes can able to decrypt the stored information. The proposed scheme also prevents replay attacks and supports creation; reading data stored in the cloud, modification and also address the user revocation. Moreover, in clouds this authentication and access control scheme is robust and decentralized, unlike other access control schemes designed for clouds which are centralized. The user should authenticate itself before initiating the transaction, and it also ensures that the cloud does not tamper with the original data that is outsourced. The computation, storage and communication overheads are comparable to centralized approaches. Cloud knows the access policy for each record stored in the cloud. We would like to hide the attributes and access policy of a user.
Keywords — Access control, Authentication, Secure hash algorithm, pailler algorithm

Endeavors to develop an automated arrangement to filter unwanted memos being posted on Online Communal Web users’ walls. Generate law to filter the content established on a little criterion. Uses Contraption for Discovering established text classifiers for categorization. Select and extracts discriminate features of short memos to enhance the quality of categorization. By progress in retaining the internet (i.e., Communal Networking) has come to be one of the most area mass media to converse, allocate, transfer, deals, and allocate the data amid every single solitary client in our daily life. Posting or commenting on a discerning Expanse / Confidential spans yelled Walls that might encompass superfluous memo or a sensitive data. Till nowadays, Communal Web needs a slight backup to this requirement. To fulfill this gap, Probability arrangement requesting new thoughts for permitting the online users to have a manage manipulation on memos posted on their User walls.
Index Terms: Precision Checking, Discriminate Feature: Bag of Words, Document Property, Contextual Features, Probability Fixing, Pattern Matching, Filtering Rule, and Recommendation System.

The recent growth in the field of Information technology increase the mobile and web-based education and it act as a backbone of the knowledge in various domains..

Mobile learning for present days

In this paper we are discussing mainly about Hybrid clouds. It is a combination of public and private clouds bound together by either standardized or proprietary technology that enables data and application portability. It could be a combination of a private cloud inside an organization with one or more public cloud providers or a private cloud.
Keywords: Customization, User-defined experience, virtual machine, Computing infrastructures, Consumers computing needs,ISV,SaaS,PaaS,IaaS,Blobs,Tables,Hybrid.

An algorithmic approach for data binding to federated databases

A federated database is a logical association of independent databases that provides a single, integrated, coherent view of all resources in the federation. The federation architecture makes several distinct physical databases appear as one logical database to end-users. Federations also provide a cohesive, unified view of data derived from multiple sources. The data sources for federated systems can include databases (relational or object-based), flat files, text documents, spreadsheets and various other forms of structured and unstructured data. Moreover, the federation can be largely vendor neutral since databases from almost any vendor, including all Open Source products, can be supported (i.e. MySQL, PostgreSQL, Oracle, SQL Server, DB2, etc.).

This study researches into fixed range designation systems with diverse applications in remote sensing, specifically addressing the emerging issue of range deficiency, particularly concerning access points with reduced range delivery services for remote hubs. An analysis of the existing system reveals limitations in current approaches. To overcome these challenges, the study proposes leveraging remote cognitive radio, a dynamic range access approach that optimally utilizes existing resources. The central focus of cognitive radio is on acquiring sensing data, addressing the deficiencies observed in the existing system. The paper introduces dynamic cognitive radio transmission, employing Bayesian energy detection with range sensing features. Computational performance is rigorously analyzed through MATLAB simulations, with a specific emphasis on identification features and the false alarm rate. Through this comparative study with existing methods, utilizing Bayesian energy processing, the findings contribute to the field by significantly enhancing the efficiency of range access in remote communication systems, addressing the shortcomings identified in the current system analysis.

Multi-Kernel Learning (MKL) is developed for providing the relevant information based on current user behavior through his/her click stream data without explicitly asking for these data. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is used for detecting the victor’s stream of data in on-line sites.

The information available online is mostly present in an unstructured form and search engines are
indispensable tools especially in higher education organizations for obtaining information from
the Internet.

The purpose of Educational data Mining is to obtain the significant data patterns from an educational system which might be helpful for improving the learning experience of a learner. This research area is using different data mining techniques and assorted research approaches for understanding various aspects related to education and student.

As a result of the swift growth and dynamic content of the web, the general purpose web search engines are becoming inadequate. Although the meta-search engines helps in increasing the search coverage of the web, the huge number of irrelevant results returned by a meta-search engine is still causing problems for the users.