Java 8 came out early last yearā āand Java 7 is now, at the end of life, making Java 8 the only Oracleā āsupported option. However, since developers value stability over trendiness, many of us are still working with Java 7, or even 6. Letās look at some features of Java 8, and provide some arguments to persuade your code to upgrade with best practices.ā
Slides for Lecture 1 of the course: Introduction to Programming with Python offered at ICCBS.
It covers the following topics:
1.) Variables, Statements and Expressions
2.) Functions
3.) Flow Control
Java 8 came out early last yearā āand Java 7 is now, at the end of life, making Java 8 the only Oracleā āsupported option. However, since developers value stability over trendiness, many of us are still working with Java 7, or even 6. Letās look at some features of Java 8, and provide some arguments to persuade your code to upgrade with best practices.ā
Slides for Lecture 1 of the course: Introduction to Programming with Python offered at ICCBS.
It covers the following topics:
1.) Variables, Statements and Expressions
2.) Functions
3.) Flow Control
Object Oriented Programming Lab Manual Abdul Hannan
Ā
Object oriented programing Lab manual for practicing and improve the coding skills of object oriented programming.
Published by Mohammad Ali Jinnah University Islamabad.
Object Oriented Programming Lab Manual Abdul Hannan
Ā
Object oriented programing Lab manual for practicing and improve the coding skills of object oriented programming.
Published by Mohammad Ali Jinnah University Islamabad.
Chi-squared Goodness of Fit Test Project Overview and.docxmccormicknadine86
Ā
Chi-squared Goodness of Fit Test Project
Overview and Rationale
This assignment is designed to provide you with hands-on experience in generating
random values and performing statistical analysis on those values.
Course Outcomes
This assignment is directly linked to the following key learning outcomes from the course
syllabus:
ā¢ Use descriptive, Heuristic and prescriptive analysis to drive business strategies and
actions
Assignment Summary
Follow the instructions in this project document to generate a number of different random
values using random number generation algorithm in Excel, the Inverse Transform. Then
apply the Chi-squared Goodness of Fit test to verify whether their generated values belong
to a particular probability distribution. Finally, complete a report summarizing the results
in your Excel workbook. Submit both the report and the Excel workbook.
The Excel workbook contains all statistical work. The report should explain the
experiments and their respective conclusions, and additional information as indicated in
each problem. Be sure to include all your findings along with important statistical issues.
Format & Guidelines
The report should follow the following format:
(i) Introduction
(ii) Analysis
(iii) Conclusion
And be 1000 - 1200 words in length and presented in the APA format
Project Instructions:
The project consists of 4 problems and a summary set of questions. For each problem, tom
hints and theoretical background is provided.
Complete each section in a separate worksheet of the same workbook (Excel file). Name
your Excel workbook as follows:
ALY6050-Module 1 Project ā Your Last Name ā First Initial.xlsx
In the following set of problems, r is the standard uniform random value (a continuous
random value between 0 and 1).
Problem 1
Generate 1000 random values r. For each r generated, calculate the random value šæšæ by:
šš = āš³š³š³š³(šš),
where āLnā is the natural logarithm function.
Investigate the probability distribution of X by doing the following:
1. Create a relative frequency histogram of X.
2. Select a probability distribution that, in your judgement, is the best fit for X.
3. Support your assertion above by creating a probability plot for X.
4. Support your assertion above by performing a Chi-squared test of best fit with a 0.05
level of significance.
5. In the word document, describe your methodologies and conclusions.
6. In the word document, explain what you have learned from this experiment.
Hints and Theoretical Background
A popular method for generating random values according to a certain probability
distribution is to use the inverse transform method. In this method, the cumulative
function of the distribution (F(x)) is used for such a random number generation. More
specifically, a standard uniform random value r is generated first. Most software
environments are capable of generating such a value. In E
Chi-squared Goodness of Fit Test Project Overview and.docxbissacr
Ā
Chi-squared Goodness of Fit Test Project
Overview and Rationale
This assignment is designed to provide you with hands-on experience in generating
random values and performing statistical analysis on those values.
Course Outcomes
This assignment is directly linked to the following key learning outcomes from the course
syllabus:
ā¢ Use descriptive, Heuristic and prescriptive analysis to drive business strategies and
actions
Assignment Summary
Follow the instructions in this project document to generate a number of different random
values using random number generation algorithm in Excel, the Inverse Transform. Then
apply the Chi-squared Goodness of Fit test to verify whether their generated values belong
to a particular probability distribution. Finally, complete a report summarizing the results
in your Excel workbook. Submit both the report and the Excel workbook.
The Excel workbook contains all statistical work. The report should explain the
experiments and their respective conclusions, and additional information as indicated in
each problem. Be sure to include all your findings along with important statistical issues.
Format & Guidelines
The report should follow the following format:
(i) Introduction
(ii) Analysis
(iii) Conclusion
And be 1000 - 1200 words in length and presented in the APA format
Project Instructions:
The project consists of 4 problems and a summary set of questions. For each problem, tom
hints and theoretical background is provided.
Complete each section in a separate worksheet of the same workbook (Excel file). Name
your Excel workbook as follows:
ALY6050-Module 1 Project ā Your Last Name ā First Initial.xlsx
In the following set of problems, r is the standard uniform random value (a continuous
random value between 0 and 1).
Problem 1
Generate 1000 random values r. For each r generated, calculate the random value šæšæ by:
šš = āš³š³š³š³(šš),
where āLnā is the natural logarithm function.
Investigate the probability distribution of X by doing the following:
1. Create a relative frequency histogram of X.
2. Select a probability distribution that, in your judgement, is the best fit for X.
3. Support your assertion above by creating a probability plot for X.
4. Support your assertion above by performing a Chi-squared test of best fit with a 0.05
level of significance.
5. In the word document, describe your methodologies and conclusions.
6. In the word document, explain what you have learned from this experiment.
Hints and Theoretical Background
A popular method for generating random values according to a certain probability
distribution is to use the inverse transform method. In this method, the cumulative
function of the distribution (F(x)) is used for such a random number generation. More
specifically, a standard uniform random value r is generated first. Most software
environments are capable of generating such a value. In E
Trick or Treat?: Bitcoin for Non-Believers, Cryptocurrencies for CypherpunksDavid Evans
Ā
David Evans
DC Area Crypto Day
Johns Hopkins University
30 October 2015
This (non-research) talk will start with a tutorial introduction to cryptocurrencies and how bitcoin works (and doesnāt work) today. Weāll touch on some of the legal, policy, and business aspects of bitcoin and discuss some potential research opportunities in cryptocurrencies.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Ā
Are you looking to streamline your workflows and boost your projectsā efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, youāre in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part āEssentials of Automationā series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Hereās what youāll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
Weāll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Donāt miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Ā
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Ā
Clients donāt know what they donāt know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clientsā needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Ā
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Ā
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overviewā
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
Ā
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Ā
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But thereās more:
In a second workflow supporting the same use case, youāll see:
Your campaign sent to target colleagues for approval
If the āApproveā button is clicked, a Jira/Zendesk ticket is created for the marketing design team
Butāif the āRejectā button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Ā
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
Ā
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
Ā
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Ā
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
2. Announcements
PS1 is due Monday (electronic submission and
paper submission): donāt wait to get started!
Quiz 1 is Wednesday (in class)
Chapters 1-4 of Course Book
Chapters 1-3 of The Information
Classes 1-5 (including questions from class
notes)
I havenāt forgotten about answering your questions from PS0.
I will post my answers by tomorrow.
3. Recap: Assigning Meanings
Program ::= Īµ | ProgramElement Program
ProgramElement ::= Expression | Definition
Definition ::= (define Name Expression)
Expression ::= PrimitiveExpression | NameExpression
| ApplicationExpression | ProcedureExpression | IfExpression
PrimitiveExpression ::= Number | true | false| PrimitiveProcedure
NameExpression ::= Name
ApplicationExpression ::= (Expression MoreExpressions)
MoreExpressions ::= Īµ | Expression MoreExpressions
ProcedureExpression ::= (lambda (Parameters) Expression)
Parameters ::= Īµ | Name Parameters
IfExpression ::= (if ExpressionPred ExpressionConsequent ExpressionAlt)
This grammar generates (nearly) all surface forms in the Scheme.
language. If we have a meaning rule for each grammar rule, we can
determine the meaning of every Scheme program.
3
4. Evaluation Rules: Last Class
PrimitiveExpression ::= Number | true | false| PrimitiveProcedure
Rule 1: If the expression is a primitive, it evaluates to its pre-
defined value.
NameExpression ::= Name
Rule 2: A name evaluates to the value associated with that name.
ApplicationExpression ::= (Expression MoreExpressions)
MoreExpressions ::= Īµ | Expression MoreExpressions
Rule 3: To evaluate an application expression:
a) Evaluate all the subexpressions (in any order)
b) Apply the value of the first subexpression to the values of all the other
subexpressions.
4
5. Last class: Rules for Application
1. Primitives. If the procedure to apply is a
primitive procedure, just do it.
2. Constructed Procedures. If the procedure is
a constructed procedure, evaluate the body
of the procedure with each parameter name
bound to the corresponding input
expression value.
This only makes sense if we know what a constructed procedure is!
5
7. Constructing Procedures
lambda means āmake a procedureā
Expression ::= ProcedureExpression
ProcedureExpression ::=
(lambda (Parameters) Expression)
Parameters ::= Īµ
Parameters ::= Name Parameters
7
8. Evaluation Rule 4: Lambda
A lambda expression evaluates to a
procedure that takes the given
parameters and has the expression as
its body.
ProcedureExpression ::= (lambda (Parameters) Expression)
Parameters ::= Īµ | Name Parameters
8
10. Applying Compound Procedures
Rule 3: To evaluate an application expression:
((lambda () (a) Evaluate all the subexpressions (in any
order)
true) (b) Apply the value of the first subexpression
to the values of all the other subexpressions.
1120)
Apply Rule for constructed procedures:
Evaluate the body of the procedure with each
parameter name bound to the corresponding
input expression value.
Evaluation Rule 4. A lambda expression
evaluates to a procedure that takes the given
parameters and has the expression as its body.
11. Applying Compound Procedures
Rule 3: To evaluate an application expression:
((lambda (x) (a) Evaluate all the subexpressions (in any
order)
(+ x 1000)) (b) Apply the value of the first subexpression
to the values of all the other subexpressions.
120)
Apply Rule for constructed procedures:
Evaluate the body of the procedure with each
parameter name bound to the corresponding
input expression value.
Evaluation Rule 4. A lambda expression
evaluates to a procedure that takes the given
parameters and has the expression as its body.
12. Applying Compound Procedures
Rule 3: To evaluate an application expression:
((lambda (x) (a) Evaluate all the subexpressions (in any
order)
(+ x 1000)) (b) Apply the value of the first subexpression
to the values of all the other subexpressions.
x)
Apply Rule for constructed procedures:
Evaluate the body of the procedure with each
parameter name bound to the corresponding
input expression value.
Evaluation Rule 4. A lambda expression
evaluates to a procedure that takes the given
parameters and has the expression as its body.
13. Applying Compound Procedures
Rule 3: To evaluate an application expression:
((lambda (a) (a) Evaluate all the subexpressions (in any
order)
(lambda (b) (b) Apply the value of the first subexpression
to the values of all the other subexpressions.
(+ a b)))
Apply Rule for constructed procedures:
5) Evaluate the body of the procedure with each
parameter name bound to the corresponding
input expression value.
Evaluation Rule 4. A lambda expression
evaluates to a procedure that takes the given
parameters and has the expression as its body.
14. Applying Compound Procedures
Rule 3: To evaluate an application expression:
(((lambda (a) (a) Evaluate all the subexpressions (in any
order)
(lambda (b) (b) Apply the value of the first subexpression
to the values of all the other subexpressions.
(+ a b)))
Apply Rule for constructed procedures:
5) Evaluate the body of the procedure with each
parameter name bound to the corresponding
6) input expression value.
Evaluation Rule 4. A lambda expression
evaluates to a procedure that takes the given
parameters and has the expression as its body.
15. Do we have everything we
need to describe all
computations?
16. Language Elements
Question from Class 2:
When learning a foreign language, which
elements are hardest to learn?
Primitives
Means of Combination
Means of Abstraction
16
17. Primitives: lots of them, and hard to learn real meaning (but its
just memorization)
Means of Combination
Complex, but, all natural languages have similar ones [Chomsky]
Sentence ::= Subject Object Verb (45%)
Sentence ::= Subject Verb Object (42%) Welsh: āLladdodd y ddraig y dyn.ā
Sentence ::= Verb Subject Object (9%)
Sentence ::= Object Subject Verb (<1%)
Scheme:
Means of Abstraction: few of these, but tricky to learn
differences across languages
Tok Pisin (Papua New Guinea): mi (I), mitupela (he/she and I), mitripela
(both of them and I), mipela (all of them and I), yumitupela (you and
I), yumitripela (both of you and I), yumipela (all of you and I)
Scheme:
17