ARK multi-user

This paper presents a monitor-based prototype for the visualisation and interaction of an Augmented Reality (AR) system, which recently developed at CCG and demonstrated during the SIACG2002 conference held in Guimarães, Portugal. ARK – Augmented Reality Kiosk - is a set-up based on the prototypes developed in the European Virtual Showcases project to which direct interaction has been added. A normal monitor and a half-silvered mirror constitute the usual set-up for the kiosk. By integrating a half-silvered mirror and a black virtual hand, the CCG solution solves the occlusion problem that normally occurs when a user interacts with a virtual environment displayed by a monitor or other projection system. Conceived with limited monetary resources this portable solution can be deployed in different application contexts as, for instance, culture heritage. This paper presents an extension of the solution to a multi-user platform for a Portuguese museum

A software framework for the development of projection-based augmented reality systems

Despite the large amount of methods and applications of augmented reality, there is little homogenization on the software platforms that support them. An exception may be the low level control software that is provided by some high profile vendors such as Qualcomm and Metaio. However, these provide fine grain modules for e.g. element tracking. We are more concerned on the application framework, that includes the control of the devices working together for the development of the AR experience. In this paper we present a software framework that can be used for the development of AR applications based on camera-projector pairs, that is suitable for both fixed, and nomadic setups.Peer ReviewedPostprint (author's final draft

Seconds-scale coherence in a tweezer-array optical clock

Optical clocks based on atoms and ions achieve exceptional precision and accuracy, with applications to relativistic geodesy, tests of relativity, and searches for dark matter. Achieving such performance requires balancing competing desirable features, including a high particle number, isolation of atoms from collisions, insensitivity to motional effects, and high duty-cycle operation. Here we demonstrate a new platform based on arrays of ultracold strontium atoms confined within optical tweezers that realizes a novel combination of these features by providing a scalable platform for isolated atoms that can be interrogated multiple times. With this tweezer-array clock, we achieve greater than 3 second coherence times and record duty cycles up to 96%, as well as stability commensurate with leading platforms. By using optical tweezer arrays --- a proven platform for the controlled creation of entanglement through microscopic control --- this work further promises a new path toward combining entanglement enhanced sensitivities with the most precise optical clock transitions

"Influence Sketching": Finding Influential Samples In Large-Scale Regressions

There is an especially strong need in modern large-scale data analysis to prioritize samples for manual inspection. For example, the inspection could target important mislabeled samples or key vulnerabilities exploitable by an adversarial attack. In order to solve the "needle in the haystack" problem of which samples to inspect, we develop a new scalable version of Cook's distance, a classical statistical technique for identifying samples which unusually strongly impact the fit of a regression model (and its downstream predictions). In order to scale this technique up to very large and high-dimensional datasets, we introduce a new algorithm which we call "influence sketching." Influence sketching embeds random projections within the influence computation; in particular, the influence score is calculated using the randomly projected pseudo-dataset from the post-convergence Generalized Linear Model (GLM). We validate that influence sketching can reliably and successfully discover influential samples by applying the technique to a malware detection dataset of over 2 million executable files, each represented with almost 100,000 features. For example, we find that randomly deleting approximately 10% of training samples reduces predictive accuracy only slightly from 99.47% to 99.45%, whereas deleting the same number of samples with high influence sketch scores reduces predictive accuracy all the way down to 90.24%. Moreover, we find that influential samples are especially likely to be mislabeled. In the case study, we manually inspect the most influential samples, and find that influence sketching pointed us to new, previously unidentified pieces of malware.Comment: fixed additional typo

Color Capable Sub-Pixel Resolving Optofluidic Microscope and Its Application to Blood Cell Imaging for Malaria Diagnosis

Miniaturization of imaging systems can significantly benefit clinical diagnosis in challenging environments, where access to physicians and good equipment can be limited. Sub-pixel resolving optofluidic microscope (SROFM) offers high-resolution imaging in the form of an on-chip device, with the combination of microfluidics and inexpensive CMOS image sensors. In this work, we report on the implementation of color SROFM prototypes with a demonstrated optical resolution of 0.66 µm at their highest acuity. We applied the prototypes to perform color imaging of red blood cells (RBCs) infected with Plasmodium falciparum, a particularly harmful type of malaria parasites and one of the major causes of death in the developing world

MScMS-II: an innovative IR-based indoor coordinate measuring system for large-scale metrology applications

According to the current great interest concerning large-scale metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance are assuming a more and more important role among system requirements. This paper describes the architecture and the working principles of a novel infrared (IR) optical-based system, designed to perform low-cost and easy indoor coordinate measurements of large-size objects. The system consists of a distributed network-based layout, whose modularity allows fitting differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load. The overall system functionalities, including distributed layout configuration, network self-calibration, 3D point localization, and measurement data elaboration, are discussed. A preliminary metrological characterization of system performance, based on experimental testing, is also presente

Discriminative Tandem Features for HMM-based EEG Classification

Abstract—We investigate the use of discriminative feature extractors in tandem configuration with generative EEG classification system. Existing studies on dynamic EEG classification typically use hidden Markov models (HMMs) which lack discriminative capability. In this paper, a linear and a non-linear classifier are discriminatively trained to produce complementary input features to the conventional HMM system. Two sets of tandem features are derived from linear discriminant analysis (LDA) projection output and multilayer perceptron (MLP) class-posterior probability, before appended to the standard autoregressive (AR) features. Evaluation on a two-class motor-imagery classification task shows that both the proposed tandem features yield consistent gains over the AR baseline, resulting in significant relative improvement of 6.2% and 11.2 % for the LDA and MLP features respectively. We also explore portability of these features across different subjects. Index Terms- Artificial neural network-hidden Markov models, EEG classification, brain-computer-interface (BCI)