Marcello Castellano

An E-Government Cooperative Framework for Government Agencies

This paper presents an e-Government Framework that allows the cooperation among applications of different Government Agencies in order to supply new added value services (Event of life services) tailored to citizens and business needs. Moreover it promotes an internal process reengineering realized by integrating governmental legacy applications. The framework is based on the Enterprise Service Bus model and on the Web Services technology. Finally the study describes the architecture of the prototypal framework and a case study of a single desk for businesses.

The MAGIC-5 Project: medical applications on a GRID infrastructure connection

The MAGIC-5 Project aims at developing computer aided detection (CAD) software for medical applications on distributed databases by means of a GRID infrastructure connection. The use of automatic systems for analyzing medical images is of paramount importance in the screening programs, due to the huge amount of data to check. Examples are: mammographies for breast cancer detection, computed-tomography (CT) images for lung cancer analysis, and the positron emission tomography (PET) imaging for the early diagnosis of the Alzheimer disease. The need for acquiring and analyzing data stored in different locations requires a GRID approach of distributed computing system and associated data management. The GRID technologies allow remote image analysis and interactive online diagnosis, with a relevant reduction of the delays actually associated to the screening programs. From this point of view, the MAGIC-5 Collaboration can be seen as a group of distributed users sharing their resources for implementing different virtual organizations (VO), each one aiming at developing screening programs, tele-training, tele-diagnosis and epidemiologic studies for a particular pathology.

Steganography effects in various formats of images. A preliminary study

In this paper, the effects of steganography in different image formats (BMP, GIF, JPEG and DWT coded) are studied. With respect to these formats, we try to give an answer to the following questions. (1) How many bits of noise (i.e. the textual secret message) can be injected without perceptually deteriorating the quality of the image? (2) How and where should one inject these bits in order to achieve the best trade-off in terms of the length of the textual message and the preserved quality of the image?.

A Flexible Mining Architecture for Providing New E-Knowledge Services

This paper presents a flexible mining system built on a multi-tier architecture. The architecture of the system is designed on the Model-View-Controller design pattern. The aim of the paper is to define and validate a process of knowledge discovery, starting from structured and unstructured data, in a distributed and heterogeneous environment by integrating Data and Web Mining techniques. The system is able to provide new added value e-Knowledge services in order to meet the diverse e-Knowledge needs of e-business, by driving the user through the three stages of the knowledge discovery, data preparation, data and web mining and result analysis, in an innovative unique process of workflow that integrates a set of existing tools. Each e-Knowledge service represents the result of an orchestration of reusable building blocks, with well defined tasks, able to interoperate among them. Finally, a case study is shown.

Intrusion Detection Using Neural Networks: A Grid Computing Based Data Mining Approach

Scientific disciplines such as life sciences as well as security and business fields depend on Knowledge Discovery because of the increasing amount of data being collected and for the complex analyses that need to be performed on them. New techniques, such as parallel, distributed, and grid-based data mining, are often able to overcome some of the characteristics of current data sources such as their large scale, high dimensionality, heterogeneity, and distributed nature. In several of these data mining applications, neural networks can be successfully applied. Moreover, an approach using neural networks seems to be one of the most promising methods for intrusion detection in a computer system or network security today. In this paper we describe a grid computing data mining approach for an intrusion detection application based on neural networks. Detection is carried out through the analyses of internet traffic generated by users in a network computer system.

A novel Active Contour Model algorithm for contour detection in complex objects

A new active contour model (ACM) algorithm for the detection of the contour of bi-dimensional regions is presented. The algorithm is based on the simulation of an elastic band glued to the contour of the region under analysis. As a result a local convex hull is obtained, where the radius of the concave regions included by the elastic band is defined by properly tuning a parameter. A dedicated application to medical images is presented. The algorithm is part of a segmentation system able to extract the lung volume from 3D CT scans. The effectiveness of the algorithm is evaluated on a database of 15 low-dose CT scans (about 320 sectional images per CT), including 26 nodules. No pathological structure is missing after the lung volume segmentation, while a reduction of the volume to analyze is obtained to about 15% of the total volume of the original CT scan, and 25% of the chest volume.

A Knowledge Center for a Social and Economic Growth of the Territory

This paper presents a data and web mining application able to support decision makers in strategic planning for the growth of a territory. The application provides e-Knowledge services for the analysis of territorial dynamics by processing and modeling huge amount of data, in order to discover rules and patterns in a distributed and heterogeneous content environment. The application is built on an infrastructure of Business Integration, based on Service-Oriented-Architecture, and a virtual private network for the cooperation between Small and Medium Business and Local Government applications. Techniques of crawling and Web Mining are used for the extraction and analysis of unstructured and semi-structured data. For the analysis of structured data, the application covers the whole Knowledge Discovery process. The purpose of the paper is to show how to implement existing techniques in a flexible architecture for providing new added value services. Finally, a case study of Employment Analysis is presented.

A bioinformatics knowledge discovery in text application for grid computing

BackgroundA fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources.MethodsThe development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs.ResultsA middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed.ConclusionIn this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities.

A Model-View-Controller ArchitectureFor Knowledge Discovery

In this paper we present a flexible mining architecture able to define and validate a process, generally applicable in different e-business sectors, for providing new added value e-Knowledge services. The architecture is designed on the ModelView-Controller pattern in order to get a clear separation of the component functionalities and covers the whole process of Knowledge Discovery in Databases (KDD) and in Text (KDT) for the extraction of patterns starting from structured and unstructured data. When a service request comes to the system, this is received by a Controller that will call one or more Miners to provide the results. The Miners represent the Model of the system and, by using a Kernel, dynamically activate either the KDD or the KDT process, depending on the typology of the service. As View, the system makes use of the CWM standard for the representation of metadata about models and results of the mining processes. The Kernel includes two different Focuses, for the selection of structured and unstructured data. The results of the Focuses are passed to a unique Pattern Extraction step, where Web and Data Mining algorithms are collected for the analysis. Finally, an Evaluation step interprets the utility of the extracted patterns. The proposed solutions can be suited in a distributed mining environment, where a set of services are managed and made available as a means of meeting the diverse needs of the e-business world.

Biomedical Text Mining Using a Grid Computing Approach

Extracting useful information from a very large amount of biomedical texts is an important and difficult activity in biomedicine field. Data to be examined are generally unstructured and the available computational resources do not still provide adequate mechanisms for retrieving and analyse very large amount of contents. In this paper we present a rule-based system for Text Mining process applied in biomedical textual documents. This application requires a strongly use of the computational resource to perform intensive operations. We propose a grid computing approach to improve application performance.