Khaled Taouil

Mammographic Microcalcifications Detection using Discrete Wavelet Transform

cancer can be diagnosed with an early training course by detecting the presence of microcalcifications in screening mammograms. The multiresolution analysis using discrete wavelet transform presents characteristics which can be exploited to develop tools for detection of microcalcifications. The objective of this work is to study the best type of wavelet and the optimal level of decomposition for a better detection. The approach is divided into two phases. The first phase of the algorithm consists on multiresolution analysis based on 1-D discrete wavelet transform over profiles of microcalcifications extracted from mammographic images. This analysis is carried out with several families of wavelets. The second phase of the algorithm is interested in the validation of the results of the first. In this stage, we apply 2-D discrete wavelet transform in analysis and synthesis on screening mammograms extracted from the mini-MIAS database (Mammographic Image Analysis Society) in order to detect the microcalcifications.

Community-coupled microgrids for the implementation of a smart grid in Tunisia

Smart grids are based on the use of ICT in order to optimise the quality and the cost of electricity generation, transport and distribution. Developing countries try to upgrade their electric grids to meet the evolving needs of the end consumers and face the energy challenge. The study of smart grid instauration in such countries must consider the disparity in terms of ICT infrastructures across regions or districts. The economic issues are very significant. It is so difficult to establish an optimal global solution that satisfies all electric energy market stakeholders. In this work, we propose a strategy to initiate the institution of a smart grid in Tunisia. We describe the different current offers of the Tunisian electricity market and propose a specific approach based on the use of the concept of community-coupled microgrids managed by the electricity service provider (ESP) which further enhances the relationship with the end customer and promote the use and integration of renewables.

MgSMA: An enhanced SMA for microgrid energy management

Microgrids; the current generation of the distributed electric power systems are studied intensively in several layers as a hopeful solution for satisfy the universal energy lack. One important feature of the microgrids is the integration of reliable and secure data communication platforms to manage, supervise and control the complex areas of the power systems. These communication networks are responsible for routing power system related messages to adopt critical decisions. Several researchers have taken the challenge to lead the microgrid networks reach a level of maturity as that of traditional networks, working on architectures and protocols. We provide in this paper a specification of an applicative protocol (MgSma) based on the open SMA protocol developed by the solar technology corporation and which designated originally to interconnect Sma logger device to a DERs inverter on a master-slave architecture. The MgSma protocol is based on interrogation commands depending on the nature of the slave device; producer, consumer or hybrid unit. This enhanced protocol is designed to support not only SMA inverters but a several kind of slaves integrating principally a network interface and the Mgsma feature.

Exploring Wavelets Toward an Automatic Microcalcification Detection in Breast Cancer

2D wavelet transform decomposition is widely used in computer aided detection of microcalcifications in mammograms. The aim of this paper is to investigate the better type of wavelet and its optimal potential level of decomposition that gives us better detection. Our algorithm consists of four steps: first, dimension reduction is performed on the mammography images to delimitate the ROI (region of interest). Second, microcalcification profiles are extracted from digital mammograms. Next, a 1D WT with different families of wavelet is applied on the signal up to the sixth level. Finally, comparison between details coefficients of each level is done to carry out the optimal level. To validate our result, 2D wavelet transform decomposition and reconstruction with the better wavelet and up to its optimal level is applied on digital mammograms from the DDSM (digital database for screening mammography) to carry out microcalcifications

Exploring Wavelets Subband Decomposition Toward a Computer Aided Detection of Microcalcification in Breast Cancer

2-D wavelet transform decomposition is widely used in computer aided detection of microcalcifications in mammograms. The aim of this work is to investigate the better type of wavelet and its optimal potential level of decomposition that gives us better detection. Our algorithm consists of four steps: First, dimension reduction is performed on the mammography images to delimitate the ROI (region of interest). Second, microcalcification profiles are extracted from digital mammograms. Next, a 1-D WT with different families of wavelet is applied on the signal up to the sixth level. Finally, comparison between details coefficients of each level is done to carry out the optimal level. To validate our result, 2-D wavelet transform decomposition and reconstruction with the better wavelet and up to its optimal level is applied on digital mammograms from the DDSM (digital database for screening mammography) to carry out microcalcifications