Ricerc@Sapienza

This paper presents a selection of research topics related to nano-electromagnetic compatibility (nano-EMC) issues in emerging carbon nanoelectronics. Carbon-based nano-interconnect modeling and analysis are first introduced. Then, the key techniques of carbon nanotube-filled through-silicon vias and carbon- based passive devices are discussed.

In this article, we study the completion time of the PUSH-PULL variant of rumor spreading, also known as randomized broadcast.We show that if a network has n nodes and conductance φ then, with high probability, PUSH-PULL will deliver themessage to all nodes in the graph within O(logn/φ) many communication rounds. This bound is best possible. We also give an alternative proof that the completion time of PUSH-PULL is bounded by a polynomial in logn/φ, based on graph sparsification.

We study maximal identifiability, a measure recently introduced in Boolean Network Tomography to characterize networks' capability to localize failure nodes in end-to-end path measurements. Under standard assumptions on topologies and on monitors placement, we prove tight upper and lower bounds on the maximal identifiability of failure nodes for specific classes of network topologies, such as trees, bounded-degree graphs, d-dimensional grids, in both directed and undirected cases.

Mobile biometrics technologies are nowadays the new frontier for secure use of data and services, and are considered particularly important due to the massive use of handheld devices in the entire world. Among the biometric traits with potential to be used in mobile settings, the iris/ocular region is a natural candidate, even considering that further advances in the technology are required to meet the operational requirements of such ambitious environments. Aiming at promoting these advances, we organized the Mobile Iris Challenge Evaluation (MICHE)-I contest.

The paper presents experiments with the home-made, low-cost prototype of a sensor-equipped pen for handwriting-based biometric authentication. The pen allows to capture the dynamics of user writing on normal paper, while producing a kind of password (passphrase) chosen in advance. The use of a word of any length instead of the user's signature makes the approach more robust to spoofing, since there is no repetitive pattern to steal. Moreover, if the template gets violated, this is much less harmful than signature catch.

The analysis of the shape and geometry of the human hand has long represented an at- tractive field of research to address the needs of digital image forensics. Over recent years, it has also turned out to be effective in biometrics, where several innovative research lines are pursued. Given the widespread diffusion of mobile and portable devices, the possibil- ity of checking the owner identity and controlling the access to the device by the hand image looks particularly attractive and less intrusive than other biometric traits.

We study a number of graph exploration problems in the following natural scenario: an algorithm starts exploring an undirected graph from some seed vertex; the algorithm, for an arbitrary vertex v that it is aware of, can ask an oracle to return the set of the neighbors of v.

In this paper we study the well-known family of Random Utility Models, developed over 50 years ago to codify rational user behavior in choosing one item from a finite set of options. In this setting each user draws i.i.d. from some distribution a utility function mapping each item in the universe to a real-valued utility. The user is then offered a subset of the items, and selects theone of maximum utility. A Max-Dist oracle for this choice model takes any subset of items and returns the probability (over the distribution of utility functions) that each will be selected.

In this paper we focus on gender classification from face images. Despite advances in equipment as well as methods, automatic face image processing for recognition or even just for the extraction of demographics, is still a challenging task in unrestricted scenarios. Our tests are aimed at carrying out an extensive comparison of a feature based approach with two score based ones. When directly using features, we first apply different operators to extract the corresponding feature vectors, and then stack such vectors. These are classified by a SVM-based approach.

Mobile biometrics represent the new frontier of authentication. The most appealing feature of mobile devices is the wide availability and the presence of more and more reliable sensors for capturing biometric traits, e.g., cameras and accelerometers. Moreover, they more and more often store personal and sensitive data, that need to be protected. Doing this on the same device using biometrics to enforce security seems a natural solution. This makes this research topic attracting and generally promising.