Much of the work in the ICU revolves around information that is recorded by electronic devices. Such devices typically incorporate simple alarm functions that trigger when a value exceeds predefined limits. Depending on the parameter followed, these "boundary based" alarms tend to produce vast numbers of false alarms. Some are the result of false reading and some the result of true but clinical...

In 1985 Tulving introduced the remember-know procedure, whereby subjects are asked to distinguish between memories that involve retrieval of contextual details (remembering) and memories that do not (knowing). Several studies have been reported showing age-related declines in remember hits, which has typically been interpreted as supporting dual-process theories of cognitive aging that align re...

OBJECTIVES The purpose of this descriptive study was to investigate the current situation of clinical alarms in intensive care unit (ICU), nurses' recognition of and fatigue in relation to clinical alarms, and obstacles in alarm management. METHODS Subjects were ICU nurses and devices from 48 critically ill patient cases. Data were collected through direct observation of alarm occurrence and ...

The primary objective of this note is to reduce the false alarms in multivariate statistical process control (MSPC). The issue of false alarms is inherent within MSPC as a result of the definition of control limits. It has been observed that under normal operating conditions, the occurrence of “outof-control” data, i.e. false alarms, conforms to a Bernoulli distribution. Therefore this issue ca...

The study investigates the role of NWP filtering for the remote sensing of Cumulonimbus 1 Clouds (Cbs) by implementation of 14 different experiments, covering Central Europe. These 2 experiments compiles different stability filter settings as well as the use of different channels for 3 the InfraRed (IR) brightness temperatures. As stability filter parameters from Numerical Weather 4 Prediction ...

Intrusion Detection Systems (IDSs) which have been deployed in computer networks to detect a wide variety of attacks are suffering how to manage of a large number of triggered alerts. Thus, reducing false alarms efficiently has become the most important issue in IDS. In this paper, we introduce the semi-supervised learning mechanism to build an alert filter, which will reduce up to 85% false al...

Patient Monitoring Information Systems generate alarms that are designed to make the clinician aware of the condition of a patient, but frequent false alarm occurrence can result in alarm fatigue and reduce the probability of a clinician to respond to the alarms. The purpose of this paper is to develop a simulation model to investigate the effect of false alarms and different alarm routing poli...

This project implements a vehicle detection and tracking system. This framework uses Haar cascade classifier for vehicle detection, and uses car-light features for validation. In order to smooth the detection and refine the detection result further, Kalman tracking is applied to every car hypothesis, additionally, a three-stage tracking is employed. Experiment shows that the car-light validatio...

The design of control, estimation or diagnosis algorithms most often assumes that all available process variables represent the system state at the same instant of time. However, this is never true in current network systems, because of the unknown deterministic or stochastic transmission delays introduced by the communication network. During the diagnosing stage, this will often generate false...