This document discusses sangaku, which refers to wooden tablets used in Japan from the 17th to 19th centuries to record geometry problems and their solutions. The problems involved practical calculations related to construction and were displayed at Buddhist temples and Shinto shrines. The document provides several examples of sangaku geometry problems and their solutions. It also lists references for further information on this topic.
Secretary of State for Environment, Food and Rural Affairs
<owl:Class rdf:about="http://reference.data.gov.uk/id/department/defra/grade/">
<rdfs:subClassOf rdf:resource="http://reference.data.gov.uk/def/central-government/CivilServicePost"/>
</owl:Class>
DEFRA is a Ministerial Department
<owl:Class rdf:about="http://reference.data.gov.uk/def/central-government/MinisterialDepartment">
<rdfs:subClassOf rdf:resource="http://reference.data.gov.uk/def/central-government/Department"/>
<r
Google in education_scandinavia_summit_2013Dan Taylor
The document provides information about an upcoming Google in Education Summit taking place on August 24-25 at www.dksummit.org. The summit will include sessions on using Google Apps in the classroom and for administration, as well as opportunities to network, try Chromebooks, become a certified trainer, and learn about Google education products. Attendees will include teachers, lecturers, administrators, and IT staff from both schools and higher education.
Google in Education summits in 2013 by AppsEventsDan Taylor
The document advertises Google in Education Summits in 2013, which provide opportunities for educators and business users to gain knowledge about Google Apps, network with other professionals, learn from experts, try Chromebooks, present sessions, and promote products or services. Details are given for summit dates and locations in several European countries and Asia between April and October 2013.
Google in education_european_summit_2013Dan Taylor
The document provides information about an upcoming Google in Education Summit taking place in Prague on October 12-13. It notes the summit will run from 9am-4pm on Saturday and 9am-2pm on Sunday, with social events both evenings. Attendees can gain knowledge relevant to their jobs, network with other educators, try Chromebooks, present sessions, and learn about Google education products and certification. The summit is aimed at teachers, lecturers, administrators, and IT staff from both schools and higher education. It will include over 30 sessions at various levels on using Google Apps in education. More information and registration can be found at the listed website.
The document provides information about an Apps Summit taking place on March 21-22, 2013. The summit will be held over two days from 9am to 4pm on the first day and 9am to 2pm on the second day, with social events both evenings. Attendees can gain knowledge relevant to their jobs, learn about moving their institution to Google Apps, network with other Google Apps enthusiasts, try Chromebooks, present a session, and more. The summit is aimed at management, IT managers and staff, and will include sessions for all levels. More information and registration is available at the provided website.
This document discusses sangaku, which refers to wooden tablets used in Japan from the 17th to 19th centuries to record geometry problems and their solutions. The problems involved practical calculations related to construction and were displayed at Buddhist temples and Shinto shrines. The document provides several examples of sangaku geometry problems and their solutions. It also lists references for further information on this topic.
Secretary of State for Environment, Food and Rural Affairs
<owl:Class rdf:about="http://reference.data.gov.uk/id/department/defra/grade/">
<rdfs:subClassOf rdf:resource="http://reference.data.gov.uk/def/central-government/CivilServicePost"/>
</owl:Class>
DEFRA is a Ministerial Department
<owl:Class rdf:about="http://reference.data.gov.uk/def/central-government/MinisterialDepartment">
<rdfs:subClassOf rdf:resource="http://reference.data.gov.uk/def/central-government/Department"/>
<r
Google in education_scandinavia_summit_2013Dan Taylor
The document provides information about an upcoming Google in Education Summit taking place on August 24-25 at www.dksummit.org. The summit will include sessions on using Google Apps in the classroom and for administration, as well as opportunities to network, try Chromebooks, become a certified trainer, and learn about Google education products. Attendees will include teachers, lecturers, administrators, and IT staff from both schools and higher education.
Google in Education summits in 2013 by AppsEventsDan Taylor
The document advertises Google in Education Summits in 2013, which provide opportunities for educators and business users to gain knowledge about Google Apps, network with other professionals, learn from experts, try Chromebooks, present sessions, and promote products or services. Details are given for summit dates and locations in several European countries and Asia between April and October 2013.
Google in education_european_summit_2013Dan Taylor
The document provides information about an upcoming Google in Education Summit taking place in Prague on October 12-13. It notes the summit will run from 9am-4pm on Saturday and 9am-2pm on Sunday, with social events both evenings. Attendees can gain knowledge relevant to their jobs, network with other educators, try Chromebooks, present sessions, and learn about Google education products and certification. The summit is aimed at teachers, lecturers, administrators, and IT staff from both schools and higher education. It will include over 30 sessions at various levels on using Google Apps in education. More information and registration can be found at the listed website.
The document provides information about an Apps Summit taking place on March 21-22, 2013. The summit will be held over two days from 9am to 4pm on the first day and 9am to 2pm on the second day, with social events both evenings. Attendees can gain knowledge relevant to their jobs, learn about moving their institution to Google Apps, network with other Google Apps enthusiasts, try Chromebooks, present a session, and more. The summit is aimed at management, IT managers and staff, and will include sessions for all levels. More information and registration is available at the provided website.
The document summarizes details about the Google in Education UK Summit taking place on April 27-28, 2013, including that it will be held over two days with evening social events, aims to provide knowledge for various education jobs through 30+ sessions at different experience levels, and encourages attending for networking, trying Chromebooks, presenting, and promoting products or services to forward-thinking educators. Attendees can register at www.uksummit.org/registration for more information.
Google in education_netherlands_belgium_summitDan Taylor
The document provides information about an upcoming Google in Education Summit taking place on April 13-14 at an unspecified location. The summit will include sessions on Saturday from 9am to 4pm and Sunday from 9am to 2pm, with social events in the evenings. Attendees can gain knowledge relevant to their jobs, network with other educators, try Chromebooks, become certified trainers, and learn about Google education products. The summit is aimed at teachers, lecturers, administrators, and IT staff from both schools and higher education.
This document discusses human ecology and the impact of human activity on the environment. It covers the nature of human ecology, the relationship between humans and nature, and contemporary issues in human ecology. Humans have a powerful ability to modify their environment and affect ecological processes. The growth of the human population to over 6 billion people has resulted in significant anthropogenic impacts including particulate pollution, destruction of stratospheric ozone by CFCs, and increased greenhouse gases causing global warming. These impacts disrupt global climate patterns and increase natural disasters. The document examines these impacts to gain knowledge on improving human-environment conditions.
This document discusses the rules for forming plurals of nouns in English. Most nouns form their plural by adding -s, but there are many irregular forms and exceptions. Additional rules apply for nouns ending in consonant+y, f or fe, s, sh, ch, x, or a consonant followed by o. Context and exceptions are important to consider for plural forms.
The document describes the five generations of computers. The first generation used vacuum tubes, took up entire rooms, and relied on machine language. The second generation introduced transistors and magnetic core memory, were smaller and more reliable. The third generation used integrated circuits which increased speed and efficiency and keyboards/monitors were introduced. The fourth generation used microprocessors, making computers smaller, cheaper and more powerful. The fifth generation is still being developed and aims to create thinking machines using artificial intelligence.
From big data to big decisions. Copyright (c) 2014 Quantellia LLCLorien Pratt
1) The document discusses how companies can make better use of data and analytics to improve decision making and business outcomes.
2) It notes that on average, companies realize only a 6% return on investment from decisions, which is below the cost of capital. Better use of data is needed to improve returns.
3) The document presents a new "decision intelligence" framework that uses data, analytics, and machine learning to understand how different decisions and external factors impact outcomes and goals, in order to optimize decisions.
The document outlines 4 lessons learned from a company's first version of customer development. The lessons are: 1) Start simply with paper prototypes before building software; 2) Understand your product's most important attribute; 3) Customer development does not require a designer; and 4) It's okay if not everyone likes your idea. The overarching lesson is that the discovery phase should focus on learning from customers and iterating based on feedback, rather than perfect execution.
Diagnosing cancer with Computational IntelligenceSimon van Dyk
An introduction to key Computational Intelligence (CI) concepts, using Hello World as an introductory example, and moving onto Diagnosing Cancer with Neural Networks.
The problem of diagnosing cancer is actually a very simple problem for CI to solve, yet it's impact can be large. It really is just up to what kind of data we have access to, that will determine our creativity in the problems we can solve with CI.
Enjoy
This document provides an overview of machine learning concepts including:
1. Machine learning aims to create computer programs that improve with experience by learning from data. It involves tasks like classification, regression, and clustering.
2. Data comes in different types like text, numbers, images and is generated in massive quantities daily from sources like Google, Facebook, and sensors.
3. Machine learning algorithms are either supervised, using labeled training data, or unsupervised, using unlabeled data. Common supervised techniques are decision trees, neural networks, and support vector machines while clustering is a major unsupervised technique.
This document provides an overview of machine learning concepts. It defines machine learning as creating computer programs that improve with experience. Supervised learning uses labeled training data to build models that can classify or predict new examples, while unsupervised learning finds patterns in unlabeled data. Examples of machine learning applications include spam filtering, recommendation systems, and medical diagnosis. The document also discusses important machine learning techniques like k-nearest neighbors, decision trees, regularization, and cross-validation.
A short talk on what makes Functional Programming - and especially Haskell - different.
We'll take a quick overview of Haskell's features and coding style, and then work through a short but complete example of using it for a Real World problem.
http://lanyrd.com/2011/geekup-liverpool-may/sdykh/
The lengths of pregnancies are normally distributed with mean µ = .docxoreo10
The lengths of pregnancies are normally distributed with mean µ = 268 days and standard deviation σ = 15 days.
25. (a) If one pregnant woman is chosen at random, find the probability that her length of pregnancy is between 260 and 278 days.
(b) Find the number of days above which lie the longest 1.5% of all pregnancies.
9/16/2016 xyzHomework Assessment
http://www.xyzhomework.com/imathas/assessment/printtest.php 1/3
Name: Ian Tapia2.5
#1 Points possible: 1. Total attempts: 3
Find for the function.
#2 Points possible: 1. Total attempts: 3
The number (in thousands) of cat flea collars demanded each year when the price of a collar is dollars is
expressed by the function . The collars are currently selling for each and the annual
number of sales is . Find the approximate decrease in sales of the collar if the price of each collar is
raised by .
The approximate decrease in sales is about collars.
#3 Points possible: 1. Total attempts: 3
Find for the function.
#4 Points possible: 1. Total attempts: 3
The monthly revenue (in dollars) of a telephone polling service is related to the number of completed
responses by the function
If the number of completed responses is increasing at the rate of forms per month, find the rate at which
the monthly revenue is changing when .
The monthly revenue is changing by .
y'
2y3 − x4 = − 8
y' =
x p
x
3 + 250p2 = 15, 500 $4
22, 572
$1
y'
3√(y − 1)2 = − 2 + 3x
y' =
R x
R(x) = − 13000 + 15√4x2 + 20x 0 ≤ x ≤ 1000
10
x = 500
$
9/16/2016 xyzHomework Assessment
http://www.xyzhomework.com/imathas/assessment/printtest.php 2/3
#5 Points possible: 1. Total attempts: 3
Find for at the point .
At ,
#6 Points possible: 1. Total attempts: 3
Find for at the point .
At ,
#7 Points possible: 1. Total attempts: 3
Find for at the point .
At ,
#8 Points possible: 1. Total attempts: 3
The cost (in dollars) of manufacturing number of highquality computer laser printers is
Currently, the level of production is printers and that level is increasing at the rate of printers per
month. Find the rate at which the cost is increasing each month.
The cost is increasing at about per month.
y' 3x5 + 2y4 − 3 = 26 ( − 1, − 2)
( − 1, − 2) y' =
y' (xy)3 / 2 = 64 (8, 2)
(8, 2) y' =
y' x − 3 + y − 3 = −
7
8
(2, − 1)
(2, − 1) y' =
C x
C(x) = 18x4 / 3 + 12x2 / 3 + 400, 000
729 400
$
9/16/2016 xyzHomework Assessment
http://www.xyzhomework.com/imathas/assessment/printtest.php 3/3
#9 Points possible: 1. Total attempts: 3
For the circle ,
find when .
find the slope of the tangent line where .
The slope of the tangent line at is .
find the points at which .
at
If the radius starts increasing at a constant rate of cm/sec, how fast is the area increasing when
cm?
The area is increasing at square cm per second.
#10 Points possible: 1. Total attempts: 3
Find for the function.
#11 Points possibl ...
Surviving and Thriving in Technical InterviewsJeremy Lindblom
Technical interviews can a difficult and stressful part of finding employment. Regardless of whether or not you receive the job offer, you can make the technical interview process a good experience every time. In this session, you will learn some tips for your next technical interview, and also analyze some example interview and coding questions to learn how to think about and answer questions in a way that shows off your abilities.
Auto-Encoders and PCA, a brief psychological backgroundAmgad Muhammad
A Psychological background on how we think and store memory to explain the motivation behind the Autoencoders and then comparing the performance, in terms of reconstruction error, of the PCA against the Autoencoders.
The document discusses functional programming concepts in Ruby. It begins by stating that functional programming and Enumerable methods can be useful in Ruby. It then provides examples of various Enumerable methods like zip, select, partition, map, and inject. It encourages thinking functionally by avoiding side effects, mutating values, and using functional parts of the standard library. The document concludes by suggesting learning a true functional language to further improve functional programming skills.
1) The document describes a gentle introduction to deep learning presented by Jose Fernando Rodrigues-Jr from the University of Sao Paulo, Brazil.
2) It discusses key aspects of deep learning including the factors that enabled recent progress, examples of promising results in areas like computer vision and medicine, and the 2018 Turing Award winners' contributions to the field.
3) It also provides explanations of fundamental concepts such as the principles of artificial neurons and neural networks as functions, as well as how training a neural network is an optimization problem to determine the best parameters or weights.
This document discusses using Python for easy artificial intelligence. It provides examples of using Python to:
1. Solve puzzles like the eight queens problem and alphametics puzzles with techniques like exhaustive search and constraint propagation.
2. Build a neural network model of a database to perform tasks like generalization, handling missing data, and extrapolation based on incomplete information.
3. Implement the game Mastermind to experiment with different guessing strategies and make the problem of deducing a hidden code as efficient as possible.
This document provides an overview of machine learning concepts including:
1) The main types of machine learning problems are classification, regression, clustering, and optimization.
2) Supervised, unsupervised, and reinforcement learning are the main approaches to teach a machine.
3) Building machine learning models involves data collection/preparation, model training/testing, and deployment of the trained model.
The document summarizes details about the Google in Education UK Summit taking place on April 27-28, 2013, including that it will be held over two days with evening social events, aims to provide knowledge for various education jobs through 30+ sessions at different experience levels, and encourages attending for networking, trying Chromebooks, presenting, and promoting products or services to forward-thinking educators. Attendees can register at www.uksummit.org/registration for more information.
Google in education_netherlands_belgium_summitDan Taylor
The document provides information about an upcoming Google in Education Summit taking place on April 13-14 at an unspecified location. The summit will include sessions on Saturday from 9am to 4pm and Sunday from 9am to 2pm, with social events in the evenings. Attendees can gain knowledge relevant to their jobs, network with other educators, try Chromebooks, become certified trainers, and learn about Google education products. The summit is aimed at teachers, lecturers, administrators, and IT staff from both schools and higher education.
This document discusses human ecology and the impact of human activity on the environment. It covers the nature of human ecology, the relationship between humans and nature, and contemporary issues in human ecology. Humans have a powerful ability to modify their environment and affect ecological processes. The growth of the human population to over 6 billion people has resulted in significant anthropogenic impacts including particulate pollution, destruction of stratospheric ozone by CFCs, and increased greenhouse gases causing global warming. These impacts disrupt global climate patterns and increase natural disasters. The document examines these impacts to gain knowledge on improving human-environment conditions.
This document discusses the rules for forming plurals of nouns in English. Most nouns form their plural by adding -s, but there are many irregular forms and exceptions. Additional rules apply for nouns ending in consonant+y, f or fe, s, sh, ch, x, or a consonant followed by o. Context and exceptions are important to consider for plural forms.
The document describes the five generations of computers. The first generation used vacuum tubes, took up entire rooms, and relied on machine language. The second generation introduced transistors and magnetic core memory, were smaller and more reliable. The third generation used integrated circuits which increased speed and efficiency and keyboards/monitors were introduced. The fourth generation used microprocessors, making computers smaller, cheaper and more powerful. The fifth generation is still being developed and aims to create thinking machines using artificial intelligence.
From big data to big decisions. Copyright (c) 2014 Quantellia LLCLorien Pratt
1) The document discusses how companies can make better use of data and analytics to improve decision making and business outcomes.
2) It notes that on average, companies realize only a 6% return on investment from decisions, which is below the cost of capital. Better use of data is needed to improve returns.
3) The document presents a new "decision intelligence" framework that uses data, analytics, and machine learning to understand how different decisions and external factors impact outcomes and goals, in order to optimize decisions.
The document outlines 4 lessons learned from a company's first version of customer development. The lessons are: 1) Start simply with paper prototypes before building software; 2) Understand your product's most important attribute; 3) Customer development does not require a designer; and 4) It's okay if not everyone likes your idea. The overarching lesson is that the discovery phase should focus on learning from customers and iterating based on feedback, rather than perfect execution.
Diagnosing cancer with Computational IntelligenceSimon van Dyk
An introduction to key Computational Intelligence (CI) concepts, using Hello World as an introductory example, and moving onto Diagnosing Cancer with Neural Networks.
The problem of diagnosing cancer is actually a very simple problem for CI to solve, yet it's impact can be large. It really is just up to what kind of data we have access to, that will determine our creativity in the problems we can solve with CI.
Enjoy
This document provides an overview of machine learning concepts including:
1. Machine learning aims to create computer programs that improve with experience by learning from data. It involves tasks like classification, regression, and clustering.
2. Data comes in different types like text, numbers, images and is generated in massive quantities daily from sources like Google, Facebook, and sensors.
3. Machine learning algorithms are either supervised, using labeled training data, or unsupervised, using unlabeled data. Common supervised techniques are decision trees, neural networks, and support vector machines while clustering is a major unsupervised technique.
This document provides an overview of machine learning concepts. It defines machine learning as creating computer programs that improve with experience. Supervised learning uses labeled training data to build models that can classify or predict new examples, while unsupervised learning finds patterns in unlabeled data. Examples of machine learning applications include spam filtering, recommendation systems, and medical diagnosis. The document also discusses important machine learning techniques like k-nearest neighbors, decision trees, regularization, and cross-validation.
A short talk on what makes Functional Programming - and especially Haskell - different.
We'll take a quick overview of Haskell's features and coding style, and then work through a short but complete example of using it for a Real World problem.
http://lanyrd.com/2011/geekup-liverpool-may/sdykh/
The lengths of pregnancies are normally distributed with mean µ = .docxoreo10
The lengths of pregnancies are normally distributed with mean µ = 268 days and standard deviation σ = 15 days.
25. (a) If one pregnant woman is chosen at random, find the probability that her length of pregnancy is between 260 and 278 days.
(b) Find the number of days above which lie the longest 1.5% of all pregnancies.
9/16/2016 xyzHomework Assessment
http://www.xyzhomework.com/imathas/assessment/printtest.php 1/3
Name: Ian Tapia2.5
#1 Points possible: 1. Total attempts: 3
Find for the function.
#2 Points possible: 1. Total attempts: 3
The number (in thousands) of cat flea collars demanded each year when the price of a collar is dollars is
expressed by the function . The collars are currently selling for each and the annual
number of sales is . Find the approximate decrease in sales of the collar if the price of each collar is
raised by .
The approximate decrease in sales is about collars.
#3 Points possible: 1. Total attempts: 3
Find for the function.
#4 Points possible: 1. Total attempts: 3
The monthly revenue (in dollars) of a telephone polling service is related to the number of completed
responses by the function
If the number of completed responses is increasing at the rate of forms per month, find the rate at which
the monthly revenue is changing when .
The monthly revenue is changing by .
y'
2y3 − x4 = − 8
y' =
x p
x
3 + 250p2 = 15, 500 $4
22, 572
$1
y'
3√(y − 1)2 = − 2 + 3x
y' =
R x
R(x) = − 13000 + 15√4x2 + 20x 0 ≤ x ≤ 1000
10
x = 500
$
9/16/2016 xyzHomework Assessment
http://www.xyzhomework.com/imathas/assessment/printtest.php 2/3
#5 Points possible: 1. Total attempts: 3
Find for at the point .
At ,
#6 Points possible: 1. Total attempts: 3
Find for at the point .
At ,
#7 Points possible: 1. Total attempts: 3
Find for at the point .
At ,
#8 Points possible: 1. Total attempts: 3
The cost (in dollars) of manufacturing number of highquality computer laser printers is
Currently, the level of production is printers and that level is increasing at the rate of printers per
month. Find the rate at which the cost is increasing each month.
The cost is increasing at about per month.
y' 3x5 + 2y4 − 3 = 26 ( − 1, − 2)
( − 1, − 2) y' =
y' (xy)3 / 2 = 64 (8, 2)
(8, 2) y' =
y' x − 3 + y − 3 = −
7
8
(2, − 1)
(2, − 1) y' =
C x
C(x) = 18x4 / 3 + 12x2 / 3 + 400, 000
729 400
$
9/16/2016 xyzHomework Assessment
http://www.xyzhomework.com/imathas/assessment/printtest.php 3/3
#9 Points possible: 1. Total attempts: 3
For the circle ,
find when .
find the slope of the tangent line where .
The slope of the tangent line at is .
find the points at which .
at
If the radius starts increasing at a constant rate of cm/sec, how fast is the area increasing when
cm?
The area is increasing at square cm per second.
#10 Points possible: 1. Total attempts: 3
Find for the function.
#11 Points possibl ...
Surviving and Thriving in Technical InterviewsJeremy Lindblom
Technical interviews can a difficult and stressful part of finding employment. Regardless of whether or not you receive the job offer, you can make the technical interview process a good experience every time. In this session, you will learn some tips for your next technical interview, and also analyze some example interview and coding questions to learn how to think about and answer questions in a way that shows off your abilities.
Auto-Encoders and PCA, a brief psychological backgroundAmgad Muhammad
A Psychological background on how we think and store memory to explain the motivation behind the Autoencoders and then comparing the performance, in terms of reconstruction error, of the PCA against the Autoencoders.
The document discusses functional programming concepts in Ruby. It begins by stating that functional programming and Enumerable methods can be useful in Ruby. It then provides examples of various Enumerable methods like zip, select, partition, map, and inject. It encourages thinking functionally by avoiding side effects, mutating values, and using functional parts of the standard library. The document concludes by suggesting learning a true functional language to further improve functional programming skills.
1) The document describes a gentle introduction to deep learning presented by Jose Fernando Rodrigues-Jr from the University of Sao Paulo, Brazil.
2) It discusses key aspects of deep learning including the factors that enabled recent progress, examples of promising results in areas like computer vision and medicine, and the 2018 Turing Award winners' contributions to the field.
3) It also provides explanations of fundamental concepts such as the principles of artificial neurons and neural networks as functions, as well as how training a neural network is an optimization problem to determine the best parameters or weights.
This document discusses using Python for easy artificial intelligence. It provides examples of using Python to:
1. Solve puzzles like the eight queens problem and alphametics puzzles with techniques like exhaustive search and constraint propagation.
2. Build a neural network model of a database to perform tasks like generalization, handling missing data, and extrapolation based on incomplete information.
3. Implement the game Mastermind to experiment with different guessing strategies and make the problem of deducing a hidden code as efficient as possible.
This document provides an overview of machine learning concepts including:
1) The main types of machine learning problems are classification, regression, clustering, and optimization.
2) Supervised, unsupervised, and reinforcement learning are the main approaches to teach a machine.
3) Building machine learning models involves data collection/preparation, model training/testing, and deployment of the trained model.
The document discusses reviewing for a test on polynomials tomorrow. It provides 5 warm-up problems on fractions, percentages and mental math. It then previews the 5 problems that will be on the test, which involve adding, subtracting and factoring polynomial expressions.
Slides from my PyCon 2011 talk, "Exhibition of Atrocity," a confessional of my sins against the Python programming language.
Abstract: http://us.pycon.org/2011/schedule/presentations/138/
Video: http://www.pycon.tv/#/video/49
roman_numerals_buggy/package.bluej
#BlueJ package file
dependency1.from=RomanNumeralsTest
dependency1.to=RomanNumerals
dependency1.type=UsesDependency
package.editor.height=400
package.editor.width=560
package.editor.x=733
package.editor.y=118
package.numDependencies=1
package.numTargets=2
package.showExtends=true
package.showUses=true
target1.editor.height=700
target1.editor.width=900
target1.editor.x=623
target1.editor.y=216
target1.height=50
target1.name=RomanNumeralsTest
target1.naviview.expanded=false
target1.showInterface=false
target1.type=UnitTestTarget
target1.width=140
target1.x=70
target1.y=70
target2.editor.height=700
target2.editor.width=900
target2.editor.x=578
target2.editor.y=92
target2.height=50
target2.name=RomanNumerals
target2.naviview.expanded=false
target2.showInterface=false
target2.type=ClassTarget
target2.width=120
target2.x=70
target2.y=10
roman_numerals_buggy/README.TXT
------------------------------------------------------------------------
This is the project README file. Here, you should describe your project.
Tell the reader (someone who does not know anything about this project)
all he/she needs to know. The comments should usually include at least:
------------------------------------------------------------------------
PROJECT TITLE:
PURPOSE OF PROJECT:
VERSION or DATE:
HOW TO START THIS PROJECT:
AUTHORS:
USER INSTRUCTIONS:
roman_numerals_buggy/RomanNumerals.classpublicsynchronizedclass RomanNumerals {
public void RomanNumerals();
public String toRoman(int);
}
roman_numerals_buggy/RomanNumerals.ctxt
#BlueJ class context
comment0.params=n
comment0.target=java.lang.String\ toRoman(int)
numComments=1
roman_numerals_buggy/RomanNumerals.javaroman_numerals_buggy/RomanNumerals.javapublicclassRomanNumerals
{
publicString toRoman(int n){
String r ="";
while( n >0){
if(n>=1000){
r +="M";
n -=1000;
}elseif( n >500){
r +="D";
n -=500;
}elseif(n>=100){
r +="C";
n -=100;
}elseif(n>=50){
r +="L";
n -=50;
}elseif(n >=10){
r +="X";
n -=10;
}elseif(n >=5){
r +="V";
n -=5;
}else{
r +="I";
n -=1;
}
}
return r;
}
}
roman_numerals_buggy/RomanNumeralsTest.classpublicsynchronizedclass RomanNumeralsTest extends junit.framework.TestCase {
public void RomanNumeralsTest();
protected void setUp();
protected void tearDown();
public void test_1();
public void test_3();
public void test_8();
public void test_27();
public void test_2011();
public void test_44();
public void test555();
public void test500();
}
roman_numerals_buggy/RomanNumeralsTest.ctxt
#BlueJ class context
comment0.params=
comment0.target=RomanNumeralsTest()
comment0.text=\r\n\ Default\ constructor\ for\ test\ class\ RomanNumeralsTest\r\ ...
Abstract : For many years, Machine Learning has focused on a key issue: the design of input features to solve prediction tasks. In this presentation, we show that many learning tasks from structured output prediction to zero-shot learning can benefit from an appropriate design of output features, broadening the scope of regression. As an illustration, I will briefly review different examples and recent results obtained in my team.
This document provides an introduction to machine learning and decision trees. It defines key concepts like deep learning, artificial intelligence, and machine learning. It then discusses different machine learning algorithms like supervised learning, unsupervised learning, and decision trees. The document explains how decision trees are built by choosing features to split on at each node based on metrics like information gain and entropy. It provides an example of calculating entropy and information gain to select the best feature to split the root node on.
From Research Objects to Reproducible Science TalesBertram Ludäscher
University of Southampton. Electronics & Computer Science. Research Seminar (Invited Talk).
TITLE: From Research Objects to Reproducible Science Tales
ABSTRACT. Rumor has it that there is a reproducibility crisis in science. Or maybe there are multiple crises? What do we mean by reproducibility and replicability anyways? In this talk I will first make an attempt at sorting out some of the terminological confusion in this area, focusing on computational aspects. The PRIMAD model is another attempt to describe different aspects of reproducibility studies by focusing on the "delta" between those studies and the original study. In addition to these more theoretical investigations, I will discuss practical efforts to create more reproducible and more transparent computational platforms such as the one developed by the Whole-Tale project: here 'tales' are executable research objects that may combine data, code, runtime environments, and narratives (i.e., the traditional "science story"). I will conclude with some thoughts about the remaining challenges and opportunities to bridge the large conceptual gaps that continue to exist despite the recognition of problems of reproducibility and transparency in science.
ABOUT the Speaker. Bertram Ludäscher is a professor at the School of Information Sciences at the University of Illinois, Urbana-Champaign and a faculty affiliate with the National Center for Supercomputing Applications (NCSA) and the Department of Computer Science at Illinois. Until 2014 he was a professor at the Department of Computer Science at the University of California, Davis. His research interests range from practical questions in scientific data and workflow management, to database theory and knowledge representation and reasoning. Prior to his faculty appointments, he was a research scientist at the San Diego Supercomputer Center (SDSC) and an adjunct faculty at the CSE Department at UC San Diego. He received his M.S. (Dipl.-Inform.) in computer science from the University of Karlsruhe (now K.I.T.), and his PhD (Dr. rer. nat.) from the University of Freiburg, in Germany.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
13. C P
S
•• S owl:equivalentClass C
•• S rdfs:subClassOf C
•• P rdfs:domain S
•• P rdfs:range S
•• C rdfs:subClassOf S
C P
14. shelter intended for humans
shelter ∃ indended for.humans
shelter AND indended for SOME humans
non-natural inanimate thing
¬ natural ¬ animate thing
NOT natural AND NOT animate AND thing
building
15. score(X, step) = (stepmax - step) × conf(X) + step × spec(X)
X
X
X
X
24. 1. What is your experience with ontologies?
Well experienced / No expert / No knowledge about ontologies
2. Are the game idea and the rules comprehensible?
Yes / Learned by doing / No
3. How many rounds did you play?
4. How many players participated in your game (including yourself)?
5. Did you enjoy playing the game?
Yes / Only in the beginning / No
6. Would you like to play the game again?
Yes / No
7. Do you think that the order of the denition fragments did make sense?
(i.e. getting more and more specic over time)
Yes / Sometimes yes, sometimes no / Mostly not
8. Did you nd it hard to answer?
Yes / Sometimes / No
9. Do you think the other players' evaluation was fair?
Yes / Sometimes not / No
10. Please point out problems that you experienced while playing. (e.g.
technical problems)
11. Please point out what could be improved, especially if you did not
enjoy playing the game.