In the literature there exist many proposed architectures for sensor fusion applications. This paper briefly reviews some of the most common approaches, i. e., the JDL fusion architecture, theWaterfall model, the Intelligence cycle, the Boyd loop, the LAAS architecture, the Omnibus model, Mr. Fusion, the DFuse framework, and the Time-Triggered Sensor Fusion Model, and categorizes them into abst...

Seven topics previously described in this column are revisited. The use of quantitative electroencephalography has been shown in a prospective study to be effective for predicting antidepressant treatment response. A novel antidepressant drug, agomelatine, has generated much controversy, and its development for the U.S. market was discontinued. A long awaited revised system for categorizing the...

OF THESIS Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science

HYDIAG is a software developed in Matlab by the DISCO team at LAAS-CNRS. It is currently a software designed to simulate, diagnose and prognose hybrid systems using model-based techniques. An extension to active diagnosis is also provided. This paper aims at presenting the native HYDIAG tool, and its different extensions to prognosis and active diagnosis. Some results on an academic example are...

Mammaplasty is a widely performed surgical procedure worldwide, utilized for breast reconstruction, in the context of cancer treatment, and aesthetic purposes. To enhance post-operative outcomes reduce risks (hematoma with required evacuation, capsular contracture, implant-associated infection others), controlled release medicaments can be achieved using drug delivery systems based on cyclodext...

Data augmentation, a technique in which a training set is expanded with class-preserving transformations, is ubiquitous in modern machine learning pipelines. In this paper, we seek to establish a theoretical framework for understanding modern data augmentation techniques. We start by showing that for kernel classifiers, data augmentation can be approximated by first-order feature averaging and ...

The problem in which the object is to add a minimum weight set of edges to a graph so as to satisfy a given condition is called the augmentation problem. This problem has a wide variety [3-5, 10, 11, 14-201. If such a given condition is concerned with the vertexor edge-connectivity of a graph then the problem is referred to as the (vertexor edge-) connectivity augmentation problem. Frank and Ch...