This chapter explores diagnosis of the breast tissues as normal, benign, or malignant in digital mammography, using computer-aided diagnosis (CAD). System for the early diagnosis of breast cancer can be used to assist radiologists in mammographic mass detection and classification. This chapter presents an evaluation about performance of extracted features, using gray-level co-occurrence matrix applied to all detailed coefficients. The nonsubsampled contourlet transform (NSCT) of the region of interest (ROI) of a mammogram were used to be decomposed in several levels. Detecting masses is more difficult than detecting microcalcifications due to the similarity between masses and background tissue such as F) fatty, G) fatty-glandular, and D) dense-glandular. To evaluate the system of classification in which k-nearest neighbors (KNN) and support vector machine (SVM) used the accuracy for classifying the mammograms of MIAS database between normal and abnormal. The accuracy measures through the classifier were 94.12% and 88.89% sequentially by SVM and KNN with NSCT.

A description of the implementation of integrated practical work in a remote laboratory was presented in this paper. The student, in real time, can access an online web page in order to manipulate a practical work of digital electronics. This work is based on the use of an embedded system PcDuino. The hardware architecture and software solutions are described, as well as the supervision tool that allows the student to follow changes in the output states of the Practical Work remotely.

The developments in technology and communication networks have enabled the possibility of establishing virtual and remote labs, providing new opportunities for students on campus and at a distance overcoming some of the limitations of hands-on labs. The impact of innovations on students' performance can be analyzed statistically by looking at specific skills or indicators, respectively. This paper addresses the lack of empirical evidence supporting electronics education innovations in three practical teaching methods, namely, hands-on, simulation, and online remote real labs. The paper reports on the application of a methodology that takes into account the interaction between students and teachers at different levels of abstraction to evaluate a DC motor laboratory practice, on 150 students at the Polydisciplinary Faculty of Beni Mellal in Morocco. In this work the students' attitudes towards a specific practical method depend on its usefulness, usability, motivation and quality of understanding; these parameters were measured using a questionnaire that considers the relationship between the student, the teacher and the practical work environment. The data collected in each type of experiment environment were was tabulated and analyzed by statistical methods. The results validate the students' satisfaction towards the environments of practical works and identify some aspects that need to be improved in future works.

<p class="0abstract">Practical manipulations are a core part of engineering training education systems. Remote labs are a new method used for teaching and practicing experimental manipulation using the performance of information and communication technologies. This paper presents a study of two remote labs architecture using low cost embedded systems that could be addressed to the 3rd year bachelor degree students on renewable energy and others on electronics courses. The first manipulation is based on Arduino microcontroller to monitor an irrigation system powered by photovoltaic panels. In addition, the second manipulation uses a powerful PcDuino, to control remotely a logic electronic experience. A simple interface is developed to allow students and instructors to access to these manipulations. This study is aimed to improve the present education systems in the Moroccan universities by managing the practical manipulation for a large number of students, especially in the open-access faculties. Finally, this architecture can be easily extended to other disciplines and courses.</p>

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