Modelos de Madurez para Gestión de Sistemas de Información en HospitalesAISTI
Este documento presenta varios modelos de madurez para la gestión de sistemas de información en hospitales. Describe brevemente la teoría de los estadios de crecimiento en la que se basan los modelos de madurez, y resume algunos de los modelos más importantes introducidos desde la década de 1970, incluidos los modelos de Nolan, Galliers y Sutherland, e IDC.
The document is a real estate report for The Woodlands, TX from June/July 2012 that includes the following key information:
1) Home sales and listing inventory statistics from 2008 to 2012 that show trends in properties sold, average sold prices, days on market, and supply of inventory.
2) Charts tracking properties under contract and unsold inventory levels month-to-month from 2008 to 2012.
3) Data on average and median sold prices from June 2010 to June 2012, including the difference between the two prices and average days on market.
4) Statistics for factors like number of properties sold, average price, and price per square foot from June 2010 to June 2012.
The document outlines plans for a new non-profit organization aimed at using soccer and tutoring programs to support disadvantaged youth in New England. The organization's goals are to provide a safe place for kids, offer more sports opportunities, and provide educational support through tutoring and mentorship programs. It plans to utilize resources like local facilities, funding, volunteers, and partnerships with universities, professional teams, and athletes to operate after-school programs. The document lists examples of involvement by professional soccer players and athletes who could support initiatives through donations, clinics, and community outreach events.
Urban Soccer Symposium 2012 Building Partnerships Between University and Comm...Darius Shirzadi
This document discusses building partnerships between Project GOAL, a youth development program, and Brown University's sports programs. [1] It outlines Project GOAL's mission and objectives in using soccer to teach life skills to disadvantaged youth. [2] It describes initial contacts made between Project GOAL and Brown soccer, and challenges in creating a formal partnership, such as ensuring consistent student volunteer participation. [3] It discusses best practices developed through their collaboration, including clear communication and recognizing mutual benefits, which have led to positive outcomes for the youth in Project GOAL.
Modelos de Madurez para Gestión de Sistemas de Información en HospitalesAISTI
Este documento presenta varios modelos de madurez para la gestión de sistemas de información en hospitales. Describe brevemente la teoría de los estadios de crecimiento en la que se basan los modelos de madurez, y resume algunos de los modelos más importantes introducidos desde la década de 1970, incluidos los modelos de Nolan, Galliers y Sutherland, e IDC.
The document is a real estate report for The Woodlands, TX from June/July 2012 that includes the following key information:
1) Home sales and listing inventory statistics from 2008 to 2012 that show trends in properties sold, average sold prices, days on market, and supply of inventory.
2) Charts tracking properties under contract and unsold inventory levels month-to-month from 2008 to 2012.
3) Data on average and median sold prices from June 2010 to June 2012, including the difference between the two prices and average days on market.
4) Statistics for factors like number of properties sold, average price, and price per square foot from June 2010 to June 2012.
The document outlines plans for a new non-profit organization aimed at using soccer and tutoring programs to support disadvantaged youth in New England. The organization's goals are to provide a safe place for kids, offer more sports opportunities, and provide educational support through tutoring and mentorship programs. It plans to utilize resources like local facilities, funding, volunteers, and partnerships with universities, professional teams, and athletes to operate after-school programs. The document lists examples of involvement by professional soccer players and athletes who could support initiatives through donations, clinics, and community outreach events.
Urban Soccer Symposium 2012 Building Partnerships Between University and Comm...Darius Shirzadi
This document discusses building partnerships between Project GOAL, a youth development program, and Brown University's sports programs. [1] It outlines Project GOAL's mission and objectives in using soccer to teach life skills to disadvantaged youth. [2] It describes initial contacts made between Project GOAL and Brown soccer, and challenges in creating a formal partnership, such as ensuring consistent student volunteer participation. [3] It discusses best practices developed through their collaboration, including clear communication and recognizing mutual benefits, which have led to positive outcomes for the youth in Project GOAL.
1) A natural disaster is defined as a natural hazard that causes significant financial and human losses through its impact on the environment. Examples include floods, earthquakes, tsunamis, and epidemics.
2) Natural disasters occur when natural hazards intersect with vulnerabilities in human systems. Major causes are seismic activity, soil erosion, and the greenhouse effect.
3) Natural disasters can be categorized as either hydrometeorological, involving atmospheric/hydrological phenomena like floods and storms, or geological, involving earthquakes, tsunamis and landslides.
Project GOAL is a nonprofit organization that uses after-school soccer and tutoring programs to facilitate development for disadvantaged youth in New England. Its mission is to provide educational, athletic, and life opportunities through these programs at no cost to participants. The program serves over 250 children since 2004, helping to keep them occupied, provide mentoring, and introduce them to positive role models through soccer. However, Project GOAL relies on individual donations and foundations for support and aims to expand its programs and participation.
Presentation by Douglas Burdett about how to use podcasts to market and grow your business to the Richmond Virginia American Marketing Association on June 7, 2016
1) A natural disaster is defined as a natural hazard that causes significant financial and human losses through its impact on the environment. Examples include floods, earthquakes, tsunamis, and epidemics.
2) Natural disasters occur when natural hazards intersect with vulnerabilities in human systems. Major causes are seismic activity, soil erosion, and the greenhouse effect.
3) Natural disasters can be categorized as either hydrometeorological, involving atmospheric/hydrological phenomena like floods and storms, or geological, involving earthquakes, tsunamis and landslides.
Project GOAL is a nonprofit organization that uses after-school soccer and tutoring programs to facilitate development for disadvantaged youth in New England. Its mission is to provide educational, athletic, and life opportunities through these programs at no cost to participants. The program serves over 250 children since 2004, helping to keep them occupied, provide mentoring, and introduce them to positive role models through soccer. However, Project GOAL relies on individual donations and foundations for support and aims to expand its programs and participation.
Presentation by Douglas Burdett about how to use podcasts to market and grow your business to the Richmond Virginia American Marketing Association on June 7, 2016
2. 1. Voorstellen
Sensornet
2. Waarom
monitoren
?
3. Voorbeeldcasus
Gilze
en
Rijen
(helikopters)
4. Waarom
herkenning
?
5. Van
data
naar
informaHe
6. Resultaat
3. VOORSTELLEN
Duurzaam en betrouwbaar beleid is
gebaseerd op verifieerbare feiten en doet
daarmee recht aan alle belangen
Voor iedereen direct inzichtelijk op
hoofdlijnen en tegelijk transparant
tot op detail niveau.
4. Als
algemene
regel
kan
worden
gesteld
dat
de
immissiemeetmethode
nauwkeuriger
is
dan
de
emissie-‐
overdrachtsmethode,
mits
de
representaHeve
bedrijfssituaHe
op
de
juiste
wijze
in
de
uitwerking
is
verdisconteerd.
De
nauwkeurigheid
van
de
immissiemeetmethode
wordt
in
belangrijke
mate
bepaald
door
de
deskundigheid
waarmee
de
methode
wordt
toegepast.
Tevens
is
de
invloed
van
stoorgeluid
van
belang.
RepresentaHef
en
deskundig
meten,
maar
dan
SLIM
WAAROM
MONITOREN
?
6. MEETPERIODE
Vaak
is
één
(of
enkele)
relaHef
korte
meHngen
voldoende
voor
een
representaHef
oordeel
In
veel
gevallen
is
lang
meten
(monitoren)
zeer
gewenst
Wisselende
omstandigheden
Incidenten
CombinaHes
9. BRON-‐
VS.
STOORGELUID
Vliegtuiggeluid
automaHsch
classificeren
(bronherkenning)
Nu:
DriehoeksmeHng,
Geluidpatronen
en
transponderdata
Grotere
en
moderne
vliegtuigen
hebben
een
transponder
die
meetgegevens
zeer
betrouwbaar
maken
Helikopters
of
vliegtuigen
behorend
bij
defensie
hebben
geen
transponder.
10. MACHINAAL
TRAINEN
KunstmaHge
intelligenHe
Verzamelen
van
geluiden
volgens
de
“standaard
per
klasse”;
Patroonherkenning
naar
“fingerprints”
middels
gecontroleerde
training;
Data-‐acquisiHe
Geluidsopname
'Fingerprint'
bepalen
'Fingerprints'
per
klasse
verzamelen
Per
klasse
een
model
trainen
12. DATA
VERZAMELEN
Database
vullen
met
samples
van
helikopters
(2
typen)
en
niet-‐helikopters
Spanningsveld:
spreiding
vs
nauwkeurigheid
1e
keer
labelen
is
mensenwerk
14. METHODE
Data-‐acquisiHe
Geluidsopname
'Fingerprint'
bepalen
'Fingerprint'
toetsen
aan
klassen
Waarschijnlijkheid
per
klasse
Daarna
dezelfde
weg
bewandelen
met
nieuwe
realHme
geluidinput
Hoogwaardige
signaalbewerking
Waarschijnlijkheid
/
vergelijking
opnamen
met
“standaard
per
klasse”
15. METHODE
Techniek
is
nimmer
foutloos
!
De
input
van
standaard
per
klasse
moet
voldoende
breed
zijn
en
toch
representaHef.
Te
smal:
te
veel
wordt
afgekeurd
(false
negaHves)
Te
breed:
te
veel
wordt
goedgekeurd
(false
posiHves)
Onze
aanpak:
Database,
aangevuld
met
trainen
“on
the
job”
=
>
maximale
representaHviteit
Ook
negaHeve
resultaten
worden
geleerd
Training
met
50
(+)
en
100
(-‐)
geei
al
zeer
consistente
resultaten
KruisvalidaHes
minder
noodzakelijk
19. VAN
(VEEL)
DATA
NAAR
INFORMATIE
Van
(veel)
data….
MeHngen
per
seconde
=
31,5
miljoen
regels/jaar
Meerdere
posiHes
en
ook
meerdere
parameters
RepresentaHef,
maar
(te)
veel
voor
handmaHge
verwerking
(Euro’s
!)
Niet
alHjd
dergelijk
detailniveau
gewenst
(Beleid)
…..naar
informaHe
Herkenning
van
nusge
data
(en
minder
nusge)
Middels
deskundigheid
naar
geautoma-seerde
analyses
