Epidemic K-Means clustering

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. This work proposes a fully decentralised algorithm (Epidemic K-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art distributed K-Means algorithms based on sampling methods. The experimental analysis confirms that the proposed algorithm is a practical and accurate distributed K-Means implementation for networked systems of very large and extreme scale.

Fault tolerant decentralised K-Means clustering for asynchronous large-scale networks

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks, such as massively parallel processors and clusters of workstations. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. The lack of scalable and fault tolerant global communication and synchronisation methods in large-scale systems has hindered the adoption of the K-Means algorithm for applications in large networked systems such as wireless sensor networks, peer-to-peer systems and mobile ad hoc networks. This work proposes a fully distributed K-Means algorithm (EpidemicK-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art sampling methods and shows that the proposed method overcomes the limitations of the sampling-based approaches for skewed clusters distributions. The experimental analysis confirms that the proposed algorithm is very accurate and fault tolerant under unreliable network conditions (message loss and node failures) and is suitable for asynchronous networks of very large and extreme scale.

Fast adaptive real-time classification for data streams with concept drift

An important application of Big Data Analytics is the real-time analysis of streaming data. Streaming data imposes unique challenges to data mining algorithms, such as concept drifts, the need to analyse the data on the fly due to unbounded data streams and scalable algorithms due to potentially high throughput of data. Real-time classification algorithms that are adaptive to concept drifts and fast exist, however, most approaches are not naturally parallel and are thus limited in their scalability. This paper presents work on the Micro-Cluster Nearest Neighbour (MC-NN) classifier. MC-NN is based on an adaptive statistical data summary based on Micro-Clusters. MC-NN is very fast and adaptive to concept drift whilst maintaining the parallel properties of the base KNN classifier. Also MC-NN is competitive compared with existing data stream classifiers in terms of accuracy and speed.

Connectivity recovery in epidemic membership protocols

Epidemic protocols are a bio-inspired communication and computation paradigm for extreme-scale network system based on randomized communication. The protocols rely on a membership service to build decentralized and random overlay topologies. In a weakly connected overlay topology, a naive mechanism of membership protocols can break the connectivity, thus impairing the accuracy of the application. This work investigates the factors in membership protocols that cause the loss of global connectivity and introduces the first topology connectivity recovery mechanism. The mechanism is integrated into the Expander Membership Protocol, which is then evaluated against other membership protocols. The analysis shows that the proposed connectivity recovery mechanism is effective in preserving topology connectivity and also helps to improve the application performance in terms of convergence speed.

An enhanced content selection mechanism for personalization of video news programmes

In this paper, we propose a content selection framework that improves the users` experience when they are enriching or authoring pieces of news. This framework combines a variety of techniques to retrieve semantically related videos, based on a set of criteria which are specified automatically depending on the media`s constraints. The combination of different content selection mechanisms can improve the quality of the retrieved scenes, because each technique`s limitations are minimized by other techniques` strengths. We present an evaluation based on a number of experiments, which show that the retrieved results are better when all criteria are used at time.

Desenvolvimento de um middleware para comunicação via web services e sua aplicação em sistemas de aquisição de dados industriais

The control of industrial processes has become increasingly complex due to variety of factory devices, quality requirement and market competition. Such complexity requires a large amount of data to be treated by the three levels of process control: field devices, control systems and management softwares. To use data effectively in each one of these levels is extremely important to industry. Many of today s industrial computer systems consist of distributed software systems written in a wide variety of programming languages and developed for specific platforms, so, even more companies apply a significant investment to maintain or even re-write their systems for different platforms. Furthermore, it is rare that a software system works in complete isolation. In industrial automation is common that, software had to interact with other systems on different machines and even written in different languages. Thus, interoperability is not just a long-term challenge, but also a current context requirement of industrial software production. This work aims to propose a middleware solution for communication over web service and presents an user case applying the solution developed to an integrated system for industrial data capture , allowing such data to be available simplified and platformindependent across the network

Java applets for a WWW-HTML-based course in power electronics

This paper introduces Java applet programs for a WWW (world wide web)-HTML (hypertext markup language)-based multimedia course in Power Electronics. The applet programs were developed with the purpose of providing an interactive visual simulation and analysis of idealized uncontrolled single-phase, and three-phase rectifiers. In addition, this paper discusses the development and utilization of JAVA applet programs to solve some design-oriented equations for rectifier applications. The major goal of these proposed JAVA applets was to provide more facilities for the students increase their pace in Power Electronics course, emphasizing waveforms analysis, and providing conditions for an on-line comparative analysis among different hands-on laboratory experiences, via a normal Internet TCP/IP connection. Therefore, using the proposed JAVA applets, which were embedded in a WWW-HTML-based course in Power Electronics, was observed an important improvement of the apprenticeship for the content of this course. Therefore, the course structure becomes fluid, allowing a true on-line course over the WWW, motivating students to learn its content, and apply it in some applications-oriented projects, and their home-works.

Real-time crowd density estimation using images

This paper presents a technique for real-time crowd density estimation based on textures of crowd images. In this technique, the current image from a sequence of input images is classified into a crowd density class. Then, the classification is corrected by a low-pass filter based on the crowd density classification of the last n images of the input sequence. The technique obtained 73.89% of correct classification in a real-time application on a sequence of 9892 crowd images. Distributed processing was used in order to obtain real-time performance. © Springer-Verlag Berlin Heidelberg 2005.

Educational Java applets get in power electronics labs

This paper presents Java applet programs for a WWW (world wide web)-HTML (hypertext markup language)-based multimedia course in basic power electronics circuits. These tools make use of the benefits of Java language to provide a dynamic and interactive approach to simulate steady-state idealized rectifiers (uncontrolled and controlled; single-phase and three-phase). In addition, this paper discusses the development and the use of the Java applet programs to assist the teaching of basics rectifier power electronics circuits, and to serve as a first design tool for basics power electronics circuits in the experiments of the laboratories. In order to validate the developed simulation applets, the results were confronted with results obtained from a well-know simulator package PSPICE. © 2005 IEEE.

A video-based biometric authentication for e-learning web applications

In the last years there was an exponential growth in the offering of Web-enabled distance courses and in the number of enrolments in corporate and higher education using this modality. However, the lack of efficient mechanisms that assures user authentication in this sort of environment, in the system login as well as throughout his session, has been pointed out as a serious deficiency. Some studies have been led about possible biometric applications for web authentication. However, password based authentication still prevails. With the popularization of biometric enabled devices and resultant fall of prices for the collection of biometric traits, biometrics is reconsidered as a secure remote authentication form for web applications. In this work, the face recognition accuracy, captured on-line by a webcam in Internet environment, is investigated, simulating the natural interaction of a person in the context of a distance course environment. Partial results show that this technique can be successfully applied to confirm the presence of users throughout the course attendance in an educational distance course. An efficient client/server architecture is also proposed. © 2009 Springer Berlin Heidelberg.

Towards interoperability in P2Pworld: An indexing middleware for multi-protocol peer-to-peer data sharing

Despite the abundant availability of protocols and application for peer-to-peer file sharing, several drawbacks are still present in the field. Among most notable drawbacks is the lack of a simple and interoperable way to share information among independent peer-to-peer networks. Another drawback is the requirement that the shared content can be accessed only by a limited number of compatible applications, making impossible their access to others applications and system. In this work we present a new approach for peer-to-peer data indexing, focused on organization and retrieval of metadata which describes the shared content. This approach results in a common and interoperable infrastructure, which provides a transparent access to data shared on multiple data sharing networks via a simple API. The proposed approach is evaluated using a case study, implemented as a cross-platform extension to Mozilla Firefox browser, and demonstrates the advantages of such interoperability over conventional distributed data access strategies. © 2009 IEEE.

Application of ontologies in peer-to-peer database with routing queries based on ant colony algorithm

A significant set of information stored in different databases around the world, can be shared through peer-topeer databases. With that, is obtained a large base of knowledge, without the need for large investments because they are used existing databases, as well as the infrastructure in place. However, the structural characteristics of peer-topeer, makes complex the process of finding such information. On the other side, these databases are often heterogeneous in their schemas, but semantically similar in their content. A good peer-to-peer databases systems should allow the user access information from databases scattered across the network and receive only the information really relate to your topic of interest. This paper proposes to use ontologies in peer-to-peer database queries to represent the semantics inherent to the data. The main contribution of this work is enable integration between heterogeneous databases, improve the performance of such queries and use the algorithm of optimization Ant Colony to solve the problem of locating information on peer-to-peer networks, which presents an improve of 18% in results. © 2011 IEEE.

Architecture for peer-to-peer databases with routing queries using ant colony algorithm and semantic support

In a peer-to-peer network, the nodes interact with each other by sharing resources, services and information. Many applications have been developed using such networks, being a class of such applications are peer-to-peer databases. The peer-to-peer databases systems allow the sharing of unstructured data, being able to integrate data from several sources, without the need of large investments, because they are used existing repositories. However, the high flexibility and dynamicity of networks the network, as well as the absence of a centralized management of information, becomes complex the process of locating information among various participants in the network. In this context, this paper presents original contributions by a proposed architecture for a routing system that uses the Ant Colony algorithm to optimize the search for desired information supported by ontologies to add semantics to shared data, enabling integration among heterogeneous databases and the while seeking to reduce the message traffic on the network without causing losses in the amount of responses, confirmed by the improve of 22.5% in this amount. © 2011 IEEE.

Optimization of query results in peer-to-peer database supported by semantics

The development of new technologies that use peer-to-peer networks grows every day, with the object to supply the need of sharing information, resources and services of databases around the world. Among them are the peer-to-peer databases that take advantage of peer-to-peer networks to manage distributed knowledge bases, allowing the sharing of information semantically related but syntactically heterogeneous. However, it is a challenge to ensure the efficient search for information without compromising the autonomy of each node and network flexibility, given the structural characteristics of these networks. On the other hand, some studies propose the use of ontology semantics by assigning standardized categorization of information. The main original contribution of this work is the approach of this problem with a proposal for optimization of queries supported by the Ant Colony algorithm and classification though ontologies. The results show that this strategy enables the semantic support to the searches in peer-to-peer databases, aiming to expand the results without compromising network performance. © 2011 IEEE.

Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.