Indexing

Abstract:  This paper tackles, studying and introducing a new types of Kc – spaces that are called be βKc_i-spaces where (i = 1 , 2 , 3 ) .  As well as discussion the important results which are arriving to during this studying.

Abstract: Object Classification is an important task within the field of computer vision. Image classification refers to the labelling of images into one of a number of predefined categories. Classification includes image sensors, image pre-processing, object detection, object segmentation, feature extraction and object classification. Many classification techniques have been developed for image classification. In this survey various classification techniques are considered; Artificial Neural Network (ANN), Decision Tree (DT), Support Vector Machine (SVM) and Fuzzy Classification.

Abstract: Lexicographic Linear Goal programming within a pre-emptive priority structure including Column-dropping Rule has been one of the useful techniques considered in solving multiple objective problems. The basic ideas to solve goal programming are transforming goal programming into single-objective linear programming. An optimal solution is attained when all the goals are reached as close as possible to their aspiration level, while satisfying a set of constraints. One of the Goal Programming algorithm – the Lexicographic method including Column-dropping Rule and the method of LINGO software are discussed in this paper. Finally goal programming model are applied to the actual management decisions, multi-objective programming model are established and used LINGO software and Column-dropping Rule to achieve satisfied solution.

Abstract: Efficient task scheduling method can meet users' requirements, and improve the resource utilization, then increase the overall performance of the cloud computing environment.  Cloud computing has new features, such as flexibility, Virtualization and etc., in this paper we propose a two levels task scheduling method based on load balancing in cloud computing. This task scheduling method meet user's requirements and get high resource utilization that simulation results in Cloud Sim simulator prove this.

Abstract: This paper presents an evaluation of open source e-learning platforms with the aim of finding the most suitable platform for extending to an adaptive one. The extended platform will be utilized in an operational teaching environment. Therefore, the overall functionality of the platform is as important as the adaptation capabilities, and the evaluation treats both issues in this paper .in this paper we will explain the proper and best learning platform for Users . In this we will compare one of the best learning platforms (Moodle and Blackbox) both are all of them best virtual learning platform. We will compare both virtual system its functionality and using best tool. This paper is focused on the Moodle Architecture and comparative study of Moodle, thus we discusses comparisons it between different virtual learning platform at last conclusion we  will describe which learning  platform is best for users.

Abstract: This paper displays the main 6 information mining calculations distinguished by the IEEE Global Conference on Data Mining (ICDM: C4.5, k-Means, SVM, Apriori, EM, Page Rank. These main 6 calculations are among the most persuasive information mining calculations in the examination community. With each calculation, we give a depiction of the calculation, examine the effect of the calculation, and review current and further research on the calculation. These 6 calculations spread grouping, bunching, measurable learning, affiliation examination, and connection mining, which are all among the most vital subjects in information mining innovative work.

Abstract: The Security is the most important aspect of  Database, for maintain the integrity and as well as security of the system image watermarking is technique proposed at the year of 1996, in this paper we also implement image watermarking using 2-D biorthogonal Wavelt. The importance of transmitting digital information in digital watermarking system and the dissymmetric digital watermarking framework lived on media content communication is also being discussed in this paper. Then we apply   watermarking embedding algorithm to keep the balance between watermarks’ imperceptibility and its robustness while the data is being sent on the communication channel.

Abstract:  Agile is suitable for Small projects as contrasted with the large projects. There is some problem in the execution of large projects. Large Projects are not easy to execute. When we use agile methodologies, Large projects are very difficult to implement. To construct a product framework by utilizing agile methodologies we found that the large projects need more practices as compare them with Small projects.
In this paper, I will present an arrangement of latest and changed development practices, which will help in building up a large project. The Agile Framework for Large Projects (AFLP) was connected to four industry cases. The AFLP gives a structured approach to programming associations to adopt agile practices and evaluate the outcomes. The system incorporates an extended Scrum procedure and agile practices, which consist of agility and critical success factors in agile software projects under that chosen from the XP, Scrum and Crystal Clear.

Abstract:In this paper, we use ψ-operator in order to get a new version of local function. The concepts of maps, dense, resolvable and Housdorff have been investigated in this paper, as well as modified to be useful in general

الخلاصة: استخدمنافيهذاالبحثالعمليةابسايمنأجلالحصولعلىنسخهجديدهمنالدالةالمحلية.وقدتمالتحقيقفيمفاهيمالدوال, الكثافة,المجموعاتالقابلةللحلوفضاءالهاوسدورف,وكذلكتعديلهالتكونمفيدةبشكلعام. 

Abstract: Vehicular ad hoc networks (VANETs) can provide scalable and cost-effective solutions for applications such as traffic safety, dynamic route planning, and context-aware advertisement using short-range wireless communication. To function properly, these applications require efficient routing protocols. However, existing mobile ad hoc network routing and forwarding approaches have limited performance in VANETs. This dissertation shows that routing protocols which account for VANET-specific characteristics in their designs, such as position and mobility of Vehicle, can provide good performance for a large spectrum of applications.
Increased vehicular traffic demands smart vehicles which can interact with each other and roadside infrastructure to prevent accidents. Vehicular Ad-hoc Network (VANET) provides this flexibility to the vehicles.  In this desertion we initially analyze the performance of AODV and OLSR, and further we improve the performance of AODV by selecting the node on the basis of trust value of the successive nodes, we also reduce the neighbor hood expiry time and correspondingly update the route table of AODV, with this purposed approach we would be able to reduce the end-to-end delay of AODV sufficiently also the performance of AODV increase in terms of Throughput and packet delivery ratio.

Abstract: Distributed computing is a situated of IT administrations that are given to a client more than a system on a rented premise and with the capacity to scale up or down their administration necessities. Generally cloud registering administrations are conveyed by an outsider supplier who possesses the foundation. It favorable circumstances to specify yet a couple incorporate versatility, strength, adaptability, productivity and outsourcing non-center exercises. Distributed computing offers an imaginative plan of action for associations to receive IT benefits without forthright speculation. Notwithstanding the potential increases accomplished from the distributed computing, the associations are moderate in tolerating it because of security issues and difficulties connected with it. Security is one of the significant issues which hamper the development of cloud. The thought of giving over vital information to another organization is troubling; such that the shoppers should be cautious in comprehension the dangers of information breaks in this new environment. This paper presents a point by point examination of the distributed computing security issues furthermore, difficulties concentrating on the distributed computing sorts and the administration conveyance sorts.

Abstract: Data ambiguity is major problem in the information retrieval ambiguity is due to the loss in the data dimension it causes lot of problem in various real life application. Database may incomplete due to missing dimension and value. In previous work is totally based on the missing value. We focus on the   problem is to find the missing dimension in our work. Missing dimension leads towards the problem in the traditional query approach. Missing dimension information create computational problem, so large number of possible combinations of missing dimensions need to be examined to check similarity between the query object  and the data objects . Our aim is to reduce the all recovery version to increase the system performance as number of possible recovery data is reduces the time to estimate the true result is also reduces.    

Abstract: Smartphones have become very common. It has claims in all the fields such as private use, in government groups such as defence, military etc. It has become common because of occurrence of huge number of applications. Smartphones convey large amount of personal material, such as user’s private details, contacts, messages, emails, credit card information, etc. This delicate- materialpresent, needs security and privacy. The project suggests the idea of securing the Private information such as contacts, browsing history, cookies, credit card information etc, present on the user profile of a personalized search engine. Security is provided by locking and wiping the data of the phone from a remote server, in the event of phone getting lost or stolen. To achieve this, message authentication code technique is used. The authenticity and integrity of the message is proved by a short piece of information. Integrity governs accidental and intentional message changes and authenticity governs the message’s origin. It stops malicious users from launching denial of service attacks. A Secure Hash Algorithm is used to produce a hash value which Converts plaintext to encoded message and outputs a MAC. The MAC defends both message data integrity and its authenticity by permitting receivers who also possess the secret key to detect any changes to message content.

Abstract: Now  these  days  keyword  search to relational data  set  becomes  an  area  of  research within the data base and Information Retrieval. There is no standard process of information retrieval, which will clearly show the accurate result also it shows keyword search with ranking. Execution time is retrieving of data is more in existing system. We propose a system for increasing performance of relational keyword search systems. In the proposed system we combine schema-based and graph-based approaches and propose a Relational Keyword Search System to overcome the mentioned disadvantages of existing systems and manage the information and user access the information very efficiently. Keyword Search with the ranking requires very low execution time. Execution time of retrieving information and file length during Information retrieval can be display using chart.

Abstract: CHOKe is a simple and stateless active queue management (AQM) scheme. Highly attractive property of Choke is that it can protect responsive TCP flows from unresponsive UDP flows. Packets currently queued in buffer, to penalize the high bandwidth flows. It can be implemented by using RED algorithm. In RED algorithm when packets arrives at a congested router. CHOKe draws a packet at a random from the FIFO buffer and compares it with the arriving packet. If both belong to same flow, then they are both dropped; else randomly chosen packet is left intact and  arriving packet is admitted into the buffer with a probability that depend on the level of congestion. These algorithms are typically implemented in the transport protocols (e.g., TCP) of end-hosts. To ensure global fairness, such schemes require all users to adopt them and respond to network congestion properly.

Abstract:  Internet banking allows banks to provide information and offer services to their customers conveniently using the internet technology. However, studies have shown that customers have perceptions that impact on the uptake and continuous usage of the platform. The purpose of this study is to understand the effect of customer perceptions on usage of internet banking in commercial banks in Kenya. This study used descriptive research design while a stratified random sampling technique was used to select subjects to represent the target population which was made up of 1,837,312 customers of commercial banks within Nairobi County. An estimated 384 respondents were targeted to participate in the study. 272 questionnaires representing a 71% response rate were received and analysed. Based on the findings of the research it was concluded that customers have perception that have an effect on usage of internet banking. Customers both users and potential, are still apprehensive about the security of internet banking transactions and privacy of their sessions while online. Due to increased phishing, on online scams and frauds perpetrated online customers are reluctant to adopt or continue using internet banking. It is the responsibility of commercial banks to sensitize their customers and assure them that it is safe to access internet banking from both a private and public network. They should provide customers with guidelines on how to safe guard their information and secure their log on credential while using both private and public network

Abstract:  The rapid growth of wireless content access implies the need for content placement and scheduling at wireless base stations. Here study a system under which users are divided into clusters based on their channel conditions, and their requests are represented by different queues at logical front ends. Requests might be elastic (implying no hard delay constraint) or inelastic (requiring that a delay target be met). Correspondingly, we have request queues that indicate the number of elastic requests, and deficit queues that indicate the deficit in inelastic service. In this project, content caching and scheduling are monitored. The user will send request to the server when the base station doesn’t have that file. The user who receives the file will become the base station for that file. To reduce memory consumption, when other user request the same file the base station send s that file delete it. The receiving user will become the base station for that file.

Abstract: An edge dominating set D of a fuzzy graph G= (σ, µ) is a non-split edge dominating set if the induced fuzzy sub graph H= (<E-D>, σ¢, µ¢) is connected. The split edge domination number γ¢_ns(G)_or γ¢_ns is the minimum fuzzy cardinality of a non-split edge dominating set. In this paper we study a non-split edge dominating set of fuzzy graphs and investigate the relationship of γ¢_ns(G)with other known parameter of G.  

Abstract: Big data deals with large volume of complex growing data set with multiple autonomous sources. With the growing technologies, data storage and data collection capacity goes increases day-by-day, big data are now rapidly expanding in all fields. It tends to increase services on internet. So, the service relevant data become too vast to process by traditional approaches. In the view of these challenges, this survey paper presents HACE theorem, which characterize big data features and Collaborative filtering techniques used in recommender systems. Recommender system is an application deals with information overloaded, used to recommend items to the user. Nowadays Service relevant data become too big to be effectively processed by traditional approaches, so one solution to this challenge is Clustering Based Collaborative Filtering. This approach recruits similar services in the same cluster to recommend services collaboratively.

Abstract:  An Algorithm is mix of guidelines without further order in offered request to take care of the predetermined issue. Sorting considered as the crucial operation for masterminding the rundown of components in a specific request either in rising or diving request in view of their key quality. Sorting system like: Insertion, Bubble, and Selection all have the quadratic time multifaceted ideal models O (N2) that breaking point their utilization as per the amount of parts. The objective of this paper audited different type of sorting algorithm like Insertion Sort, Selection, Bubble, Merge sort their execution investigation as for their time complexity nature.

Abstract: In wireless sensor network generally concentrate on minimization of energy Consumption, Also reducing energy saving and end to end delay. Reduced the end to end delay is one of the main challenges in the Wireless Sensor Networks. In TDMA providing reliable packet transmission and two transmission scheduling schemes are used to maximize the end-end reliability within a delay bound in packet transmission called dedicated scheduling and shared scheduling. In addition, they formulate solutions for implementing two algorithms into two basic routing algorithms, single-path routing and any-path routing algorithm. The proposed system presented energy efficient sleep scheduling algorithm for reducing the energy for delay constrained in WLAN. This algorithm to maximize the energy saving for packet delay constraints and it determines sleep period and wake up time to be minimized, the aim of this project is proposed to maximize the length of sleep time under packet deadline constraints using green call algorithm.  

Abstract: Ramanujan’s lost notebook contains many results on mock theta functions. In particular, the lost notebook contains eight identities for tenth order mock theta functions. Previously many authors proved the first six of Ramanujan’s tenth order mock theta function identities. It is the purpose of this paper to prove the seventh and eighth identities of Ramanujan’s tenth order mock theta function identities which are expressed by mock theta functions and also a definite integral. The properties of modular forms are used for the proofs of theta function identities and L. J. Mordell’s transformation formula for the definite integral.

Abstract:  With development of the information technology, the scale of data is increasing quickly. The massive data poses a great challenge for data processing and classification. In order to classify the data, there were several algorithm proposed to efficiently cluster the data. One among that is the random forest algorithm, which is used for the feature subset selection. The feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of features. It is achieved by classifying the given data. The efficiency is calculated based on the time required to find a subset of features, the effectiveness is related to the quality of the subset of features. The existing system deals with fast clustering based feature selection algorithm, which is proven to be powerful, but when the size of the dataset increases rapidly, the current algorithm is found to be less efficient as the clustering of datasets takes quiet more number of time. Hence the new method of implementation is proposed in this project to efficiently cluster the data and persist on the back-end database accordingly to reduce the time. It is achieved by scalable random forest algorithm. The Scalable random forest is implemented using Map Reduce Programming (An implementation of Big Data) to efficiently cluster the data. In works on two phases, the first step deals with the gathering the datasets and persisting on the datastore and the second step deals with the clustering and classification of data.  This process is completely implemented using Google App Engine’s hadoop platform, which is a widely used open-source implementation of Google's distributed file system using MapReduce framework for scalable distributed computing or cloud computing. MapReduce programming model provides an efficient framework for processing large datasets in an extremely parallel mining. And it comes to being the most popular parallel model for data processing in cloud computing platform. However, designing the traditional machine learning algorithms with MapReduce programming framework is very necessary in dealing with massive datasets.

Abstract: Traditional approaches for document classification need data which is labelled for the construction reliable classifiers which are even accurate. Unfortunately, data which is already labelled are rarely available, and often too costly to obtain. For the given learning task for which data which is trained is unavailable, abundant labelled data may be there for a different and related domain. One would like to use the related labelled data as auxiliary information to accomplish the classification task in the target domain. Recently, the paradigm of transfer learning has been introduced to enable effective learning strategies when auxiliary data obey a different probability distribution. A co-clustering based classification algorithm has been previously proposed to tackle cross-domain text classification. In this work, we extend the idea underlying this approach by making the latent semantic relationship between the two domains explicit. This goal is achieved with the use of Wikipedia. As a result, the pathway that allows propagating labels between the two domains not only captures common words, but also semantic concepts based on the content of documents. We empirically demonstrate the efficacy of our semantic-based approach to cross-domain classification using a variety of real data.

Abstract: We extend some existing results on the zeros of polar derivatives of polynomials by considering more general coefficient conditions. As special cases the extended results yield much simpler expressions for the upper bounds of zeros than those of the existing results.
Mathematics Subject Classification: 30C10, 30C15.

Abstract: Cloud computing provides an economical and efficient solution for sharing data among the cloud users in the group , users sharing data in a multi-attorney manner preserving data and identity privacy from an untrusted cloud, it  is still a challenging issue, due to frequent change of the membership in the group. In this paper, we propose a multi-attorney data sharing scheme for the dynamic groups in the cloud. By combing group signature and Tripple DES encryption techniques, any cloud user anonymously share the data with others. In addition, we analyze the security of our scheme with rigorous proofs, and demonstrate the efficiency of our scheme in experiments.

Abstract: Study of processing techniques applicable to full color images. Although the process followed by the human brain in perceiving and interpreting color is a phenomenon that is fully understood, the physical nature of color can be expressed on the formal basis supported by experimental and theoretical results. By examining some principal areas it can be applied for detecting, Capturing, Comparing the images. The objective of this article is to educate newcomer to basic and fundamental techniques of detecting & Comparing images and to find out the compared result. All fundamental algorithms of color image processing will be discussed and quality of processed image output comparison will be shown to find out comparison.

Abstract: Google employs algorithms in such a way that it holds the capability of sensing what one might want to see, out of the keyword that we have entered. In other words Google’s algorithms accept our query as input and produce results in the form of webpages that may count up to many thousands or even millions.
There are certain criteria upon which the algorithm filters our search results. The technical term used to represent such criteria is ‘clues’. These clues are unique signals that help in determining what really we are looking for. They include information like the terms and condition of a website, how recent has the content been modified, the region in which the user exists, how good the title of a pages looks and rank of the page.
Google’s developers focus on refining the quality of result produced by employing different ‘clues’, that also determine if a page or website stands at position 1 in search results.
While the overall preview of how the algorithm works has been specified, a Google algorithm is not as easy as it meets the eye. Google algorithms are complicated and increase in the level of complexity as the search for a user’s query gets refined from level to level.

Abstract: Hadoop is a open source software framework for storage and processing large scale of datasets on clusters of commodity hardware. Hadoop provides a reliable shared storage and analysis system, here storage provided by HDFS and analysis provided by MapReduce. MapReduce frameworks are foraying into the domain of high performance of computing with stringent non-functional requirements namely execution times and throughputs. MapReduce provides simple programming interfaces with two functions: map and reduce. The functions can be automatically executed in parallel on a cluster without requiring any intervention from the programmer. Moreover, MapReduce offers other benefits, including load balancing, high scalability, and fault tolerance. The challenge is that when we consider the data is dynamically and continuously produced, from different geographical locations. For dynamically generated data, an efficient algorithm is desired, for timely guiding the transfer of data into the cloud over time for geo-dispersed data sets, there is need to select the best data center to aggregate all data onto given that a MapReduce like framework is most efficient when data to be processed are all in one place, and not across data centers due to the enormous overhead of inter-data center data moving in the stage of shuffle and reduce. Recently, many researchers tend to implement and deploy data-intensive and/or computation-intensive algorithms on MapReduce parallel computing framework for high processing efficiency.

Abstract: Here we define a new category which we call “the category of abelian groups over the category of rings” and we denote it by M. This category is the collection of modules over different rings. We have discussed some properties of this category in details. Some results of Ab (the category of abelian groups), Ring (the category of rings) have been proved and used in the proofs of the properties of M in this paper. Also we have defined another new category which we call “the category of semi abelian groups over the category of semi rings” and we have denoted it by M’.  We discussed some properties of M’.

Abstract: Nowadays, shortage of electricity is a very serious problem due to insufficient production. The wastage of electricity can be avoided by switching off the electrical appliances when not in use. This can be achieved by using Smart home system which automatically turns off loads when not in use, the system can save energy in homes and offices. The system will automatically switch off based on the presence of people at home. Another major issue is that there might be occurrence of theft when nobody is present at home. The theft can be avoided by using MEMS accelerometer which intimates the user through registered mobile number when there is an unexpected break of windows or door through the GSM modem. The system in addition also has a provision for the user to fix energy consumption reading and when the user consumption exceeds a fixed reading, a message would be sent to the users registered mobile number through the GSM modem. Applications for this system include workstations, open office cubicles, home offices, and home entertainment systems.

Abstract: Analysis of cancer datasets is one of the important research in data mining techniques. In the present work, classification techniques such as CART, Random Forest, LMT, and Naive Bayesian are used. The result predicts that Random forest method using training dataset outperforms the remaining methods. The random forest method using training dataset have less value of absolute relative error. Relative absolute error of LMT is high for cancer survival dataset. Value of absolute relative error is greater than 50% for almost all the algorithms except for random forest method using training dataset.

Abstract: Tracking and detecting the crowd is the main problem in the current era hence we are making video scenes method .Detection of many individual objects has been improved over recent years. It has been challenging to detect and track the tasks due to occlusions and variation in people appearance. Facing these challenges, we suggest to leverage information on the global structure of the scenes and to resolve jointly. We explore the constraints of the crowd density and detection of optimization using joint energy function. We show how the optimization of such energy function improves to track and detect in floating crowds. We validate our approach on a challenging video dataset of crowded scenes. The addition of different features which is relevant  to tracking peoples such as movement, size, height and the observation models in the particle filters and followed by a clustering methods. It minimizes the communication cost and Data Retrieval is easy.

Abstract: Recent era efforts have been taken in the field of social based Question and Answer (Q&A) which is used to search the answers for the non – factorial questions. But traditional search engines like Google, Bing is used to answer only for the factorial questions where we can get direct answer from the data base servers. The web search engine for the (Q&A) system does not dependent on the broadcasting methods and centralized server for identifying friends on the social network. The problem is recovered by using mobile Q&A system in that mobile nodes are help full for accessing internet because these techniques are used to generate low node overload, higher server bandwidth cost and highest cost of mobile internet access. Lately technical experts proposed a new method called Distributed Social – Based Mobile Q&A system (SOS) which makes very faster and quicker responses to the asker. SOS enables the mobile user’s to forward the question in the decentralized manner in order get effective, capable, and potential answers from the users. SOS is the light weighted knowledge engineering technique which is used find correct person who ready and willing to answer questions hence this type of search are used reduce searching time and computational cost of the mobile nodes. In this paper we proposed a new method called mobile Q&A system in the cloud based environment through which the data has been as been transmitted form cloud server to the centralized server at any time.

Abstract: Hosting data query services with the deployed cloud computing infrastructure increase the scalability and high performance evaluations with low cost. However, some data owners might not be interested to the save their in the cloud environment because of data confidentiality and query processing privacy should be guaranteed by the cloud service providers. Secured Query should able to provide very high efficient of query processing and also should reduce in – house workload. In this paper we proposed RASP data perturbation techniques combines various objectives like random noise injection, dimensionality expansion, efficient encryption and random projection, henceforth RASP methodology are also used to preserves multidimensional ranges. KNN – R algorithm used to work with RASP range for processing KNN queries. The experimental result of our project carried out to define realistic security and threat model approaches for improved efficient and security.

Keywords: KNN Query Services, Privacy Range Query, OPE (Order Preserving Encryption), OBDA (Ontology Based Data Access), and CRT (Cryptographic Transformation).

Abstract: Using hard AI problems for security is emerging as an exciting new paradigm, but has been underexplored. This approach present a new security primitive based on hard AI problems, namely, a novel family of graphical password systems built on top of Captcha technology, which is called Captcha as graphical passwords (CaRP). CaRP is both a Captcha and a graphical password scheme. CaRP addresses a number of security problems altogether, such as online guessing attacks, relay attacks, and, if combined with dual-view technologies, shoulder-surfing attacks. Notably, a CaRP password can be found only probabilistically by automatic online guessing attacks even if the password is in the search set.

Abstract: Path follower is a machine that can follow a path. The path can be visible like a black line on a white surface (or vice-versa) or it can be invisible like a magnetic field. Sensing a line and direction the robot to stay on course, while constantly correcting wrong moves using feedback mechanism forms a simple yet effective closed loop system. As a programmer you get an opportunity to ‘teach’ the robot how to follow the line thus giving it a human-like property of responding to stimuli. Practical applications of a line follower: Automated cars running on roads with embedded magnets; guidance system for industrial robots moving on shop floor etc. Projectile stun guns have been developed as less-lethal devices that law enforcement officers can use to control potentially violent subjects, as an alternative to using firearms. These devices apply high voltage, low amperage, and pulsatile electric shocks to the subject, which causes involuntary skeletal muscle contraction and renders the subject unable to further resist. A stun gun is an electrical self defense weapon that uses high voltage to stop an attacker. Touching a person with the prongs on the stun gun quickly immobilizes the attacker. However, because the amperage of a stun gun is very low, no serious or permanent injury is inflicted.

Abstract: Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviours, allowing businesses to make proactive, knowledge-driven decisions. The automated, prospective analyses offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems.
They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. Data mining techniques are the result of a long process of research and product development. This evolution began when business data was first stored on computers, continued with improvements in data access, and more recently, generated technologies that allow users to navigate through their data in real time. Data mining takes this evolutionary process beyond retrospective data access and navigation to prospective and proactive information delivery.

Abstract:  Smart phone provides many multimedia services for mobile users. Most of these smart phones are equipped with multiple wireless network interfaces (that support real time video processing. How to use efficiently and cost-effectively utilize multiple links to improve video streaming quality over multiple wireless access networks . In order to maintain high video streaming quality while reducing the wireless service cost, In Video quality-adaptive streaming, the optimal video streaming process with multiple links is formulated as a Markov Decision Process (MDP). The reward function is designed to consider the quality of service (QoS) requirements for video traffic, such as the startup latency, playback fluency, average playback quality, playback smoothness and wireless service cost. To solve the MDP in real time, Quality-adaptive streaming propose an Adaptive search Depth algorithm to obtain a sub-optimal solution.

Abstract: In today’s commercial, industrial and domestic world, Automation plays an important role, it is actually an arrangement of different elements in order to regulate, direct, sense and command itself to achieve a desired result. “Automatic Fire Fighting Robot” project employs the electrical thermostat technology for the controlling the fire 24 hrs. The system is cost effective, has a wide applications which when implement can show good and effective result. It can be use deliberately in industrial applications, commercial and in domestic sectors where the requirement of automatic work demands. Synchronization of various equipment involve in the system i.e Thermostat Sensor, water jet, wireless remote and wireless android device WiFi enabled Camera. This is mean to simulate the real world operation of Robot performing a fire extinguishing function. Fuzzy logic provided an appropriate solution to the otherwise complex task of mathematically deriving an exact model for the non-linear control system upon which conventional control techniques could then be applied. Making Robot wireless increases the effective area of operation, thereby making it possible to control the robot from remote location.  Keeping all above factors in mind the Robot is capable of being remotely controlled and live video buffering i.e possessing a multimedia interface was convinced and developed.

Abstract: Here we discuss how zero objects and zero morphisms behave in an abelian category. We also provide proofs of isomorphism between the kernels and between the cokernels of a morphism. We discuss some properties of abelian category.

Abstract: Password authentication is one of the simplest and the most convenient authentication mechanisms to deal with secret data over insecure networks. Every user now holds email account for different web sites or holds a username password for their office work in their computer system. In this paper, we shall present the result of our survey through basic currently available password-authentication-related schemes. We know that Apart from getting the password hacked by some intruder, a serious threats comes from the surrounding environment, specially the colleagues, friends or visitors nearby the system. Most of them have a tendency of observing keenly while you cast your password. Here we propose a simple way to provide a new way of password through clicks that would provide a secure mechanism from both the intruders and the people nearby while you type your password in the application.

Abstract: Now a day most of the user are facing problem for providing the security to the folder, so that it will not be accesses by the unauthorized user. Taking in action all these problems I have designed a model which will provide a best security to your folders using graphical password authentication model. Graphical passwords are an alternative to alphanumeric passwords in which users click on images to authenticate themselves rather than type alphanumeric strings. We have developed one such system, called Pass Points, and evaluated it with human users.  Beginning around 1999, a multitude of graphical based password scheme which have been proposed as alternative to text based password scheme, motivated by the promise of improved password memorability and thus usability. This paper presents a detailed evaluation of the Pass Points and pattern matching password scheme which provides high level of security and provides security to your folder.

Abstract: The present work proposes a methodology for analysis of fungus in plant, using image processing techniques. The fungus kills the young seedling; it spread by air and can also infect plant. Therefore it is very important to monitor the leaf at regular intervals so as to keep track on quality of growth of plant. For analysis of fungus is focused on technique using MATLAB 7.0. The image are captured by digital camera mobile and processed using image growing, then  the part of the leaf spot has been used for the classification purpose of the trait and test. The acquired image are in jpeg format and are converted to gray scale image. The gray scale images are enhanced and make noise free. The Ostu algorithm is applied to get threshold image. The pixel neighborhood is applied to enhance the pixel of leaf to show clearly the fungus area. Clustering is applied to get infected part of the leaf. RGB image is then segmented for analysis of fungus in plant. Comparative analyses of Image Edge Detection techniques are presented. It has been observed that the Canny Edge Detection algorithm is computationally more expensive compared to Sobel Edge Detection technique.  The fungus infected area is 24.5951%.

Abstract: The dramatic growth of smartphones in recent years, the challenge of limited energy capacity of these devices has not been solved satisfactorily. However, in the era of cloud computing, the limitation on energy capacity can be eased off in an efficient way by offloading heavy tasks to the cloud. It is important for smartphone and cloud computing developers to have insights into the energy cost of smartphone applications before implementing the offloading techniques.
In this paper, we evaluate the energy cost of multimedia applications on smartphones that are connected to Multimedia Cloud Computing (MCC). In other words, we investigate the feasibility of MCC. Specifically, we compared the energy costs for uploading and downloading a audio file to and from MCC with the energy costs of encoding the same audio file on a smartphone. The aforementioned comparison was performed by using HTTP and FTP Internet protocols with 3G and Wi-Fi network interfaces.

Abstract: We are making one android application for our college. This application gives the complete details about the college like Admission procedure, various departments’ information etc. In that special job hunting section we are going to provide a new job opening in every one hour duration. The best advantage of these application will be messaging system that we are going to provide in the application. Every student will receive an SMS every hour about the job opening. If teacher wants send any kind of message any group of student, they can directly send the SMS notification to all the students with our messaging system. These help the student of college to be updated always and also attract all students to get admission in our college.