Search results for "Soft"

Positive mood induction procedures for virtual environments designed for elderly people

2012

Positive emotions have a significant influence on mental and physical health. Their role in the elderly’s wellbeing has been established in numerous studies. It is therefore worthwhile to explore ways in which elderly people can increase the number of positive experiences in their daily lives. This paper describes two Virtual Environments (VEs) that were used as mood induction procedures (MIPs) for this population. In addition, the VEs’ efficacy at increasing joy and relaxation in elderly users is analyzed. The VEs contain exercises for generating positive-autobiographic memories, mindfulness and slow breathing rhythms. The total sample comprised 18 participants over 55 years old who used t…

Population and Query Interface for a Content-Based Video Database

2002

In this paper we describe the first full implementation of a content-based indexing and retrieval system for MPEG-2 and MPEG-4 videos. We consider a video as a collection of spatiotemporal segments called video objects; each video object is a sequence of video object planes. A set of representative video object planes is used to index each video object. During the database population, the operator, using a semi-automatic outlining tool we developed, manually selects video objects and insert some semantical information. Low-level visual features like color, texture, motion and geometry are automatically computed. The system has been implemented on a commercial relational DBMS and is based on…

Set Membership (In) Validation of nonlinear positive models for biological systems

2006

The complexity of biology needs quantitative tools in order to support and validate biologists intuition and traditional qualitative descriptions. In this paper, Nonlinear Positive models with constraints for biological systems are validated/invalidated in a worst-case deterministic setting. These models are usefull for the analysis of the DNA and RNA evolution and for the description of the population dynamics of viruses and bacteria. The conditional central estimate and the Uncertainty Intervals are determined in order to validate/invalidate the model. The effectiveness of the proposed procedure has been illustrated by means of simulation experiments.

Smartphone data analysis for human activity recognition

2017

In recent years, the percentage of the population owning a smartphone has increased significantly. These devices provide the user with more and more functions, so that anyone is encouraged to carry one during the day, implicitly producing that can be analysed to infer knowledge of the user’s context. In this work we present a novel framework for Human Activity Recognition (HAR) using smartphone data captured by means of embedded triaxial accelerometer and gyroscope sensors. Some statistics over the captured sensor data are computed to model each activity, then real-time classification is performed by means of an efficient supervised learning technique. The system we propose also adopts a …

2015

Primary neuronal cultures share many typical features with the in vivo situation, including similarities in distinct electrical activity patterns and synaptic network interactions. Here, we use multi-electrode array (MEA) recordings from spontaneously active cultures of wildtype and GAD67-GFP transgenic mice to evaluate which spike parameters differ between GABAergic interneurons and principal, putatively glutamatergic neurons. To analyze this question we combine MEA recordings with optical imaging in sparse cortical cultures to assign individual spikes to visually-identified single neurons. In our culture system, excitatory and inhibitory neurons are present at a similar ratio as described…

A distributed visualization system for crowd simulations1

2011

The visualization system of large-scale crowd simulations should scale up with both the number of visuals views of the virtual world and the number of agents displayed in each visual. Otherwise, we could have large scale crowd simulations where only a small percentage of the population is displayed. Several approaches have been proposed in order to efficiently render crowds of animated characters. However, these approaches either render crowds animated with simple behaviors or they can only support a few hundreds of user-driven entities. In this paper, we propose a distributed visualization system for large crowds of autonomous agents that allows the visualization of crowds animated with co…

Expert system for predicting unstable angina based on Bayesian networks

2013

The use of computer-based clinical decision support (CDS) tools is growing significantly in recent years. These tools help reduce waiting lists, minimise patient risks and, at the same time, optimise the cost health resources. In this paper, we present a CDS application that predicts the probability of having unstable angina based on clinical data. Due to the characteristics of the variables (mostly binary) a Bayesian network model was chosen to support the system. Bayesian-network model was constructed using a population of 1164 patients, and subsequently was validated with a population of 103 patients. The validation results, with a negative predictive value (NPV) of 91%, demonstrate its …

Application of a Bayesian Spatiotemporal Surveillance Method to NYC Syndromic Data

2014

Incorporating prior knowledge (e.g., the spatial distribution of zip codes and background population effects) into a model using Bayesian methods could potentially improve outbreak detection. We adapted a previously described Bayesian model-based spatiotemporal surveillance technique to daily respiratory syndrome counts in NYC Emergency Department data in 2009, the year of the H1N1 influenza pandemic. Citywide, 56 alarms were produced across 15 zip codes, all during days of elevated respiratory visits. Future work includes evaluating our choice of baseline length, considering other alarm thresholds, and conducting a formal evaluation of the method across five syndromes in NYC.

Anomaly Detection in Dynamic Social Systems Using Weak Estimators

2009

Anomaly detection involves identifying observationsthat deviate from the normal behavior of a system. One ofthe ways to achieve this is by identifying the phenomena thatcharacterize “normal” observations. Subsequently, based on thecharacteristics of data learned from the “normal” observations,new observations are classified as being either “normal” or not.Most state-of-the-art approaches, especially those which belongto the family parameterized statistical schemes, work under theassumption that the underlying distributions of the observationsare stationary. That is, they assume that the distributions thatare learned during the training (or learning) phase, thoughunknown, are not time-varyin…

An Initial Security Analysis of the Personal Transaction Protocol

2003

Our society is becoming increasingly dependent on the rapid access and processing of information. The number of handheld mobile devices with access to the Internet and network-based software and services is exploding. Research indicates [1] that by the end of 2002 there will be over 1 billion mobile phone owners globally with Internet access, and that this number is going to grow exponentially in the nearest future. By 2006 the number of interconnected mobile device users is expected exceed the worldwide Internet subscriber population. It is estimated that in a few years there will be three times as many of these devices worldwide as personal computers.