Matteo D'Aloia

Computer aided detection of microcalcifications in digital mammograms adopting a wavelet decomposition

Over recent years breast cancer prevention campaigns have resulted in widespread screening. Until now, mammography has been one of the most reliable methods for the early detection of this disease. The high correlation between the appearance of microcalcification clusters and the presence of cancer shows that Computer Aided Detection systems of microcalcifications are extremely useful and helpful in an early detection of breast cancer. Several techniques can be adopted to accomplish this task. In this paper an efficient tool for a fully automatic microcalcification cluster detection/localization is presented. Adopting this procedure, all suspect microcalcifications are preserved and background noise is reduced by thresholding mammograms through a wavelet filter, according to image statistical parameters (i.e. mean gray level pixel value and standard deviation). Moreover, in order to localize singularity points, the reconstructed image is decomposed adopting another wavelet and each decomposition level is processed using a hard threshold technique. To reduce false positive detections in microcalcification recognition, the results obtained in each level are combined with a suitable procedure. The Mammographic Image Analysis Society database is used to test the procedure. The performance obtained highlights the validity of the method; indeed, the evaluated sensitivity parameter (true positive rate) is about 98% at an average rate of 1 false positive per image.

Health Care Improvement: Comparative Analysis of Two CAD Systems in Mammographic Screening

Technological innovations have produced remarkable results in the health care sector. In particular, computer-aided detection (CAD) systems are becoming very useful and helpful in supporting physicians for early detection and control of some diseases such as neoplastic pathologies. In this paper, two different CAD systems able to detect and to localize microcalcification clusters in mammographic images are implemented. The two methods utilize an artificial neural network and a support vector machine, respectively, as classifier. Adopting the MIAS database as procedure testing, the performance of the two implemented systems are compared in terms of sensitivity, specificity, accuracy, free-response operating characteristic curves, and Cohens kappa coefficient. The obtained values for the previous parameters show the efficiency of both methods to operate as “second opinion” in microcalcification cluster detection, improving the screening process efficiency.

Controlling transient stability through line switching

Smart transmission systems have introduced new possibilities of using topology control process for increasing power system dynamic security. Nowadays, in short term analysis, transmission topology is often treated as static and network reconfiguration is performed only for optimizing power flows and market performance. Modern technological infrastructure have enabled fast communication between power system elements. In this scenario, it is foreseeable that topology control can be exploited in real-time as the last resource for avoiding system collapse. In this paper, a dynamic corrective control strategy based on line switching technique is presented. In particular, the proposed method is based on an algorithm that allows to identify transmission lines that should be switched on/off during transients and the time when the corrective action has to be applied in order to guarantee system stability. The feasibility of this approach is demonstrated through simulations on a detailed representation of the Italian transmission network.

Improving energy efficiency in building system using a novel people localization system

This paper presents an innovative Bluetooth Low Energy indoor localization system useful to improve energy efficiency in buildings. A tracking system to localize people within a building has been developed using a novel infrastructure system and a custom signal processing method. Knowledge whether people are present or not in every room enables the automatic switching-off of lighting and heating/cooling in empty room increasing the energy efficiency of building system. The implemented method achieves performance comparable to that of a traditional Bluetooth Low Energy indoor location system, nevertheless fewer devices are used. As a result, the cost of installation in existing building decreases.

Protection system monitoring for the prevention of cascading events in smart transmission grids

With the diffusion of standardized communication protocols in smart transmission systems, it is expected that digital distance relays will become active elements in monitoring and control architecture. Real-time tuning of distance relays settings will allow to overcome the classical conflict between dependability and security, or to avoid improper operation of such devices in vulnerable conditions and during major blackout events. In this paper, along with the presentation of a monitoring and control architecture that integrates such devices into SCADA/EMS, a system security monitoring function, based on simulated system trajectories and their closeness to distance relay zones, is proposed for system operation and contingency analysis.

An innovative LPWA network scheme to increase system reliability in remote monitoring

This paper presents a smart system based on Low Power Wide Area networks for a remote monitoring of technological room in unstaffed railway stations. The paper aim is the design of an efficient network scheme characterized by improved performance compared with the standard solution. Adopting an innovative smart System Control Strategy and a custom network topology, good results are reached in terms of reliability without increasing the amount of devices with respect the standard scheme.