Improving automatic detection of obstructive sleep apnea through nonlinear analysis of sustained speech

We present a novel approach for the detection of severe obstructive sleep apnea (OSA) based on patients' voices introducing nonlinear measures to describe sustained speech dynamics. Nonlinear features were combined with state-of-the-art speech recognition systems using statistical modeling techniques (Gaussian mixture models, GMMs) over cepstral parameterization (MFCC) for both continuous and sustained speech. Tests were performed on a database including speech records from both severe OSA and control speakers. A 10 % relative reduction in classification error was obtained for sustained speech when combining MFCC-GMM and nonlinear features, and 33 % when fusing nonlinear features with both sustained and continuous MFCC-GMM. Accuracy reached 88.5 % allowing the system to be used in OSA early detection. Tests showed that nonlinear features and MFCCs are lightly correlated on sustained speech, but uncorrelated on continuous speech. Results also suggest the existence of nonlinear effects in OSA patients' voices, which should be found in continuous speech.

Automatic generation of models for abdominal aortic aneurysms and intraluminal thrombus based on hexahedral meshes

To propose an automated patient-specific algorithm for the creation of accurate and smooth meshes of the aortic anatomy, to be used for evaluating rupture risk factors of abdominal aortic aneurysms (AAA). Finite element (FE) analyses and simulations require meshes to be smooth and anatomically accurate, capturing both the artery wall and the intraluminal thrombus (ILT). The two main difficulties are the modeling of the arterial bifurcations, and of the ILT, which has an arbitrary shape that is conforming to the aortic wall.

knOWLearn: a reuse-based approach for building ontologies in a semi-automatic way

In this poster paper we present an overview of knOWLearn, a novel approach for building domain ontologies in a semi-automatic fashion.

Automatic generation of real-time deformable parametric model of the aorta for a VR-based catheterism guidance system

The purpose of this work is twofold: first, to develop a process to automatically create parametric models of the aorta that can adapt to any possible intraoperative deformation of the vessel. Second, it intends to provide the tools needed to perform this deformation in real time, by means of a non-rigid registration method. This dynamically deformable model will later be used in a VR-based surgery guidance system for aortic catheterism procedures, showing the vessel changes in real time.

On the automatic integration of hardware accelerators into FPGA-based embedded systems

This paper proposes an automatic framework for the seamless integration of hardware accelerators, starting from an OpenMP-based application and an XML file describing the HW/SW partitioning. It extends a fully software architecture by generating and integrating the cores, along with the proper interfaces, and the code for scheduling and synchronization. Experimental results show that it is possible to validate different solutions only by varying the input code.

Automatic Generation of Identical Routing Pairs for FPGA Implemented DPL Logic

Side Channel Attacks (SCAs) typically gather unintentional (side channel) physical leakages from running crypto-devices to reveal confidential data. Dual-rail Precharge Logic (DPL) is one of the most efficient countermeasures against power or EM side channel threats. This logic relies on the implementation of complementary rails to counterbalance the data-dependent variations of the leakage from dynamic behavior of the original circuit. However, the lack of flexibility of commercial FPGA design tools makes it quite difficult to obtain completely balanced routings between complementary networks. In this paper, a controllable repair mechanism to guarantee identical net pairs from two lines is presented: i. repairs the identical yet conflict nets after the duplication (copy & paste) from original rail to complementary rail, and ii. repairs the non-identical nets in off-the-stock DPL circuits; These rerouting steps are carried out starting from a placed and routed netlist using Xilinx Description Language (XDL). Low level XDL modifications have been completely automated using a set of APIs named RapidSmith. Experimental EM attacks show that the resistance level of an AES core after the automatic routing repair is increased in a factor of at least 3.5. Timing analyses further demonstrate that net delay differences between complementary networks are minimized significantly.

A novel method for radio propagation simulation based on automatic 3D environment reconstruction

In this paper, a novel method to simulate radio propagation is presented. The method consists of two steps: automatic 3D scenario reconstruction and propagation modeling. For 3D reconstruction, a machine learning algorithm is adopted and improved to automatically recognize objects in pictures taken from target region, and 3D models are generated based on the recognized objects. The propagation model employs a ray tracing algorithm to compute signal strength for each point on the constructed 3D map. By comparing with other methods, the work presented in this paper makes contributions on reducing human efforts and cost in constructing 3D scene; moreover, the developed propagation model proves its potential in both accuracy and efficiency.

Intelligent automatic overtaking system using vision for vehicle detection

There is clear evidence that investment in intelligent transportation system technologies brings major social and economic benefits. Technological advances in the area of automatic systems in particular are becoming vital for the reduction of road deaths. We here describe our approach to automation of one the riskiest autonomous manœuvres involving vehicles – overtaking. The approach is based on a stereo vision system responsible for detecting any preceding vehicle and triggering the autonomous overtaking manœuvre. To this end, a fuzzy-logic based controller was developed to emulate how humans overtake. Its input is information from the vision system and from a positioning-based system consisting of a differential global positioning system (DGPS) and an inertial measurement unit (IMU). Its output is the generation of action on the vehicle’s actuators, i.e., the steering wheel and throttle and brake pedals. The system has been incorporated into a commercial Citroën car and tested on the private driving circuit at the facilities of our research center, CAR, with different preceding vehicles – a motorbike, car, and truck – with encouraging results.