Google ºÝºÝߣs is Google's presentation software that allows for collaboration. It has many of the same features as PowerPoint such as themes, templates, fonts, and the ability to embed videos and animations. Presentations can be accessed from any device and are automatically saved. Ideas for classroom use include creating thank you presentations where each student adds a slide, using screen recordings to create flipped lessons, and making visual outlines or storyboards. Students can also create virtual vocabulary lists or tour guides using images from Google Earth.
Tic aplicada a la gesti¨®n y prevenci¨®n delLaura Loaiza
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El documento describe c¨®mo las tecnolog¨ªas de la informaci¨®n y la comunicaci¨®n (TIC's) pueden aplicarse a la gesti¨®n y prevenci¨®n de riesgos. Explica que las TIC's son parte integral de los sistemas de gesti¨®n de riesgos y pueden usarse para mejorar la seguridad y salud en el trabajo. Concluye que la prevenci¨®n de riesgos es responsabilidad de todos y afecta a toda la organizaci¨®n.
The Maryland PTA outlines its 2015 legislative agenda which focuses on advocating for strong public funding of education, continued improvement of public schools, and safe and nurturing environments for children. The agenda addresses maintaining funding levels, promoting family and community involvement, ensuring equitable and high-quality education for all students, supporting strong academic standards and teacher training, and advocating for children's health, safety, and welfare.
Scott Blandford is a Military Police member with 10 years of experience in supervisory roles including traffic enforcement, patrol supervision, and currently supervising the Resource Management Section. He has extensive training in law enforcement, security, investigations and military policing through courses with the RCMP, OPP, Toronto Police and more. He has a background in construction and is interested in applying for a position with the recipient's organization.
Scott Blandford was born in 1977 in Newmarket, Ontario. He spent his childhood in Port Bolster until moving to Lindsay, Ontario in grade 4. He struggled in school but found success in martial arts, earning black belts in karate and jujitsu. After not graduating high school, he worked various jobs including in a slaughterhouse, machine shop, and concrete industry. He eventually became a bar manager but decided to change careers. He attended police foundations college and was accepted into the Canadian Military Police. He served across Canada and overseas in Kuwait before deciding to leave the military to focus on being a single father of three children. He is now pursuing other career opportunities as the military is no longer a good fit for
Tic aplicada a la gesti¨®n y prevenci¨®n delLaura Loaiza
?
El documento describe c¨®mo las tecnolog¨ªas de la informaci¨®n y la comunicaci¨®n (TIC's) pueden aplicarse a la gesti¨®n y prevenci¨®n de riesgos en el trabajo. Explica que las TIC's son parte integral de los sistemas de gesti¨®n de riesgos y seguridad, y su importancia radica en que permiten una prevenci¨®n efectiva que beneficia a todos los trabajadores al reducir los riesgos laborales.
This document contains 8 assignment sheets related to mechanical engineering concepts including:
1. Free body diagrams and reactions at supports
2. Internal reaction diagrams for beams
3. Axially loaded bars including stresses and deflections
4. Bending of bars including stresses, deflections, and internal reaction diagrams
5. Torsion of bars including shear stresses and angles of twist
6. Thin walled pressure containers including stress components and allowable pressures
7. Stress transformation including Mohr's circle and principal stresses
8. A problem involving stresses in a thin walled steel pressure container
The assignments cover a range of load cases and ask students to calculate stresses, deflections, reactions and other mechanical properties.
This document provides instructions for creating a basic Google ºÝºÝߣs presentation. It outlines steps to create a new presentation, rename the title, apply a theme, and add text and an image. Additional resources are listed for learning more about using features in Google ºÝºÝߣs like inserting slides, changing layouts, presentation mode, and general tips for making effective presentations.
This document provides an overview of a tutorial on using Amazon Machine Learning (ML) to build a predictive model. The tutorial involves the following key steps: 1) Preparing training data from the UCI Census dataset, 2) Creating an ML training datasource, 3) Creating and training an ML model, 4) Reviewing the model's performance and setting a prediction threshold, 5) Using the model to generate predictions, and 6) Cleaning up resources. The homework assignment asks students to repeat steps 1-4 and then write a Python script to generate real-time and batch predictions using the Amazon ML APIs instead of the graphical interface.
This document contains 8 assignment sheets related to mechanical engineering concepts including:
1. Free body diagrams and reactions at supports
2. Internal reaction diagrams for beams
3. Axially loaded bars including stresses and deflections
4. Bending of bars including stresses, deflections, and internal reaction diagrams
5. Torsion of bars including shear stresses and angles of twist
6. Thin walled pressure containers including stress components and allowable pressures
7. Stress transformation including Mohr's circle and principal stresses
8. A problem involving stresses in a thin walled steel pressure container
The assignments cover a range of load cases and ask students to calculate stresses, deflections, reactions and other mechanical properties.
This document provides instructions for creating a basic Google ºÝºÝߣs presentation. It outlines steps to create a new presentation, rename the title, apply a theme, and add text and an image. Additional resources are listed for learning more about using features in Google ºÝºÝߣs like inserting slides, changing layouts, presentation mode, and general tips for making effective presentations.
This document provides an overview of a tutorial on using Amazon Machine Learning (ML) to build a predictive model. The tutorial involves the following key steps: 1) Preparing training data from the UCI Census dataset, 2) Creating an ML training datasource, 3) Creating and training an ML model, 4) Reviewing the model's performance and setting a prediction threshold, 5) Using the model to generate predictions, and 6) Cleaning up resources. The homework assignment asks students to repeat steps 1-4 and then write a Python script to generate real-time and batch predictions using the Amazon ML APIs instead of the graphical interface.
1. SVEU?ILI?TE U SPLITU
FAKULTET ELEKTROTEHNIKE, STROJARSTVA I
BRODOGRADNJE
IZVJE?TAJ O SEMESTARSKOM PROJEKTU
ARDUINO EMF DETEKTOR
Marija Sunara i Tea ?karica
Split, lipanj 2013.
2. Elektromagnetsko zra?enje je fizikalna pojava ?irenje elektri?nih i magnetskih valova,
odnosno ultrasitnih ?estica zvanih fotoni. Energija fotona je ve?a ?to je ve?a frekvencija
titraja valova i ?to je kra?a valna duljina.
Elektromagnetski spektar se dijeli na dva dijela:
? Neioniziraju?e zra?enje ¨C zbog slabe energije mo?e biti ?tetno pri dugom izlaganju
? Ioniziraju?e zra?enje (X-zrake, gama zrake..) ¨C mo?e ?tetno djelovati na ljudske
stanice.
O ?emu se radi u ovom projektu?
Arduino EMF detektor je senzor koji detektira ja?inu elektromagnetskog zra?enja. Pri izradi
projekta kori?tena oprema je: Arduino, LED diode, 3.3M otpornici, ?ica koja ima ulogu
antene, USB kabel za Arduino, ra?unalo.
Arduino je jedan od open-source elektroni?kih prototipova platformi temeljen na fleksibilnom
i jednostavnom za kori?tenje hardveru i softveru. Namjenjen je za umjetnike, dizajnere, ljude
koji se bave razli?itim hobijima i bilo koga tko je zainteresiran za stvaranje interaktivnih
objekata ili okru?enja. Sljede?a slika prikazuje Arduino Uno koji je kori?ten u ovom projektu.
Slika 1. Arduino Uno
3. LED (engl. Light Emitting Diode), tj. svjetle?a dioda posebna je vrsta poluvodi?ke diode koja
emitira svjetlost kada je propusno polarizirana, tj. kada kroz nju te?e struja. Prilikom direktne
rekombinacije para elektron-?upljina, emitira se foton svjetla. Takvo svojstvo imaju
poluvodi?i galijev-arsenid (GaAs), galijev-fosfid (GaP) i silicijev-karbid (SiC). Ta pojava se
naziva elektroluminiscencija. Boja emitiranog svjetla ovisi o poluvodi?u, kao i o primjesama
u njemu i varira od infracrvenog preko vidljivog do ultraljubi?astog dijela spektra. Sljede?a
slika prikazuje nekoliko LED dioda.
Slika 2. LED diode
Otpornici za LED diode su napravljeni tako da svaka boja na otporniku predstavlja odre?enu
otpornost mjerenu u omima [?]. Za 3.3M otpornike u ovom projektu su kori?teni otponici 3x
(crvena, crvena, ?uta, zlatna boja) jer je ta vrijednost otpornika bila najbli?a na?oj potrebnoj
vrijednosti. Sljede?a slika prikazuje nekoliko otpornika za LED diode.
4. Slika 3. Otpornici za LED diode
Sljede?a slika prikazuje primjer ra?unanja vrijednosti otpornosti preko boja na otporniku.
Slika 4. Primjer ra?unanja otpornosti po bojama na otporniku
Internetske stranice koje su kori?tene u projektu i programi koji su instalirani su sljede?i:
Thing Speak, Active Python, Aron Alai.
Thing Speak je stranica koja prikuplja podatke s ra?unala i mo?e upisivati neke nove
podatke, community.thingspeak.com .
5. Active Python je program koji koriste milijuni programera ?irom svijeta, jednostavna je
instalacija i osigurana je kvaliteta koda, http://www.activestate.com/activepython/downloads ,
slijedi start, run, upisati cmd, OK, pypm install, pypm install pyserial.
Aron Alai je stranica na kojoj je kod za ovaj projekt:
// Aaron ALAI EMF Detector April 22nd 2009 VERSION 1.0
// aaronalai1@gmail.com
// *future note, put in averaging function to average val which should result in a more
// smooth response from the led. I will give you a hint on how to make an averaging function;
// it involves the use of an array
int inPin = 5; // analog 5
int val = 0; // where to store info from analog 5
int pin11 = 11; // output of red led
void setup() {
Serial.begin(9600);
}
void loop() {
val = analogRead(inPin); // reads in the values from analog 5 and
//assigns them to val
if(val >= 1){
val = constrain(val, 1, 100); // mess with these values
val = map(val, 1, 100, 1, 255); // to change the response distance of the device
analogWrite(pin11, val); // *note also messing with the resistor should change
// the sensitivity
}else{ // analogWrite(pin11, val); just tuns on the led with
// the intensity of the variable val
analogWrite(pin11, 0); // the else statement is just telling the microcontroller
// to turn off the light if there is no EMF detected
}
Serial.println(val); // use output to aid in calibrating
}
Arduino EMF detektor radi na tom principu ?to svojom antenom prepoznaje podru?ja gdje
postoji jako elektromagnetsko zra?enje te ?alje signale LED diodama koje svijetle ja?e ili
slabije ovisno o jakosti elektromagnetskog polja u tom podru?ju. Prednosti Arduino EMF
detektora su ?to je jako jeftin i jednostavan za konstruirati, te je vrlo koristan jer detektira
elektromagnetska zra?enja koja su ina?e opasna za zdravlje ?ovjeka. Nedostatak Arduino
EMF detektora je taj ?to je slabo eksponiran u javnosti, stoga se u bliskoj budu?nosti mo?emo
samo nadati da ?e ovaj i sli?ni projekti zainteresirati mlade i poduzetne ljude.