| fld {pbdML} | R Documentation |
Compute the 2-class Fisher's linear discriminant either in serial or parallel.
fld(x, g, checkg = TRUE)
x |
The data in the form of a matrix or ddmatrix. |
g |
The group variable in the form of a matrix/vector or a ddmatrix. The values should be 0 and 1 exclusively. |
checkg |
Logical; should the values of g be confirmed to exclusively be 0's and 1's. |
Note that a ddmatrix x and ordinary matrix/vector pairing is possible, but the reverse (matrix/vector x and ddmatrix g) is not.
A list of class 'fld' containing the prior probabilities, group means, w vector, and c scalar. In the distributed case, the priors and c scalar are both global, while the other values are distributed.
Drew Schmidt
Duda, R. O., Hart, P. E., & Stork, D. G. (2012). Pattern classification, chapter 5. John Wiley & Sons.
## Not run: x <- matrix(rnorm(30), 10) g <- sample(0:1, size=10, replace=TRUE) fld(x, g) ## End(Not run)


Guess 100!
Try to guess the number! You have 100 tries.
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Introduction¶
… one framework to rule them all!¶
Introduction¶
The pycopancore package is a python implementation of the copan:CORE modeling framework as described in this paper. The framework is designed to allow an easy implementation of World-Earth (i.e., global social-ecological) models by using different model components of environmental, social-metabolic or cultural submodels and combining them with newly developed components. The implementation and simulation of World-Earth models within the framework can use different types of modeling techniques such as differential equations, stochastic and deterministic events and therefore allows to compare different model and component types and implementations.
pycopancore is developed at the Potsdam Institute for Climate Impact Research (PIK). Responsible senior scientists at PIK are Jobst Heitzig & Jonathan F. Donges.
Disclaimer¶
This software is provided for free as a beta version still under active development. It has not been completely tested and can therefore not guarantee error-free functioning. Please help us further improving the code by reporting possible bugs via the github issue tracker!
Quick start guide¶
Installation¶
For running pycopancore, an installation with python > 3.6 with some additional packages is required.
An easy way to install python is to use the Anaconda environment.
The package can be installed by downloading the repository and and running the setup.py script with
`
$ pip install
`
from the root directory of the package. The script should automatically install all the required and missing packages.
For developers, the recommended way of installing is to run in the package main directory
`
$ pip install -e
`
This creates a link instead of copying the files, so modifications in this directory are modifications in the installed package.
Running a model¶
To run one of the preconfigured models, execute a python script in the studies folder, for example
`bash
python run_seven_dwarfs.py
`
Documentation¶
The documentation can be accessed under https://pik-copan.github.io/pycopancore and provides an introduction to the framework, its different entity and process types, a full documentation of the API as well as a step-by-step tutorial.
To create a local html version of the documentation, access the docs directory and type
`
> make html
`
The documentation can then be accessed under docs/_build/html/index.html.
To be able to create the automatic UML-Diagrams, pylint and graphviz needs to be installed. To finally create the diagrams, use
`
> make uml
`
Code of Good Practice¶
When contributing to the project, please follow the guidelines below:
- For every class/function write a proper docstring before committing.
- Use static values as little as possible. Preferably define a variable in the header of the file instead.
- For functions describing processes in the model_components, papers from the scientific literature that use these functional forms should be referenced in the code documentation.
- Use as many assert statements as possible, even if they are computationally expensive. For actual runs, these checks can be switched off using the -O flag of the Python Interpreter.
- Use proper (and long) variable names. Auto-completion will help typing them.
- If a similar set of command is used twice, write a function for it right away.
- Design the metadata used in the Variable class according to the CF conventions.
- When writing class and method docstrings, already specify types and bounds for arguments and return values in the sphinx-compatible PyContracts way.
- Write in code-of-conduct: Everything but “models” and “model_components” should be well described with docstrings”
- Consider the recommendations in the PEP 8 style guide for python code.
Additional guidelines: - Staff of the Potsdam Institute for Climate Impact research, please read and follow the “Guidelines for Ensuring Good Scientific Modelling Practice at PIK”. - Use NetCDF, the CF conventions and PIK’s Typed Data Transfer to store (input and) output data and share it with other models.
Tests¶
We are using the python testing framework pytest with pylama for style and error checking. Please write corresponding unittests while developing and make sure that all test pass by executing
`
py.test
`
in the root of the project tree.
Requires
- pytest
- pylama
- pylint
- pylama_pylint
- pytest-cov, to check of test coverage
Licence and Development¶
pycopancore is licenced under the BSD 2-Clause License. See the LICENCE file for further information.
The versioning of pycopancore has been chosen to be administrated on the github.com system as the future prospect of this model strongly encourages outside contributions. Any release version will be pushed on the inhouse versioning systems, gitlab and / or svn.


The HTML DOM allows JavaScript to change the style of HTML elements.
The HTML DOM allows you to execute code when an event occurs.
Events are generated by the browser when "things happen" to HTML elements:
You will learn more about events in the next chapter of this tutorial.
document.getElementById(id).style.property = new style
This example changes the style of the HTML element with id="id1", when the user clicks a button:
Changing the HTML style:
Hello World!
Hello World!


Hi, I'm Sandra Chea, a student/intern/researcher based in Los Angeles, California!
I am currently a sophomore majoring in electrical engineering. Besides spending my time doing homework set after set, I use my two clubs (Robotics and Racing Club) as outlets of relaxation as I contribute to practical designs. I especially appreciate all the great people I've met here as well as the strong collaborative culture that Caltech offers.
My main goal right now is to search for opportunities that will allow me to explore the differents paths that electrical engineering has. My current interests include circuit and PCB design, but there are still so many other areas that I have not had the chance to get my hands dirty in and learn more about. I hope that as I continue to absorb valuable information from different experiences, I can build up a strong arsenal of skills that allow me to be a well rounded engineer.


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Agora is an open space designed to aggregate evidence in support of AD target discovery initially developed by the National Institute on Aging-funded Accelerating Medicines Partnership in Alzheimer’s Disease (AMP-AD) consortium. Agora enables researchers to view evidence for whether or not selected genes are associated with AD and to access a list of over a hundred nascent drug targets for AD that were nominated by AD researchers. The results accessible through Agora represent the culmination of more than five years of research from the dozens of scientists that are part of the AMP-AD consortium. Agora will be frequently updated to incorporate the latest analyses from AMP-AD and its affiliate AD research consortia. The initial release includes differential expression and coexpression network meta-analyses across four human RNA-sequence data sets. Future releases will expand to include human proteomic and metabolomic analyses, comparative evaluations of disease signatures across species, and integration of druggability and tractability information to guide selection of targets for early drug discovery. Analyses developed within other consortia in the NIA’s AD Translational Research portfolio including MODEL-AD, M2OVE-AD, and AD Resilience will also be integrated into future iterations. Agora is funded by the National Institute on Aging. It is developed and maintained by Sage Bionetworks. If you have suggestions or feedback about Agora, please contact us.
AMP-AD is a precompetitive public private partnership led by the National Institutes for Health’s (NIH) National Institute on Aging (NIA) and managed by the Foundation for the NIH (FNIH). AMP-AD brings together the government, industry and non-profit sectors to transform the way disease-relevant therapeutic targets are discovered and validated.
Data contributed by the AMP-AD consortia are available in the AMP-AD Knowledge Portal. The AMP-AD Knowledge Portal is a platform to access data, analytical results and tools generated within the National Institute of Aging’s AD Translational Research Program. All projects within this program operate as an open science collaboration and openly share resources early in the research life cycle for evaluation and reuse. The Portal is named for the first consortium to be initiated, the Accelerating Medicines Partnership in Alzheimer’s Disease Target Discovery and Preclinical Validation Project (AMP-AD). The majority of the content in the Portal is genomic data generated from human samples or experimental model systems. In addition to this, the Portal also contains bioinformatic analytical results including some generated by teams within individual projects and some generated through multi-team working groups. Bioinformaticians can download these resources for use in their own research. You will need a Synapse account to access the data in the AMP AD Knowledge Portal. To establish a Synapse account, please follow the instructions on this page. Differential expression and gene coexpression analyses included in Agora were derived from the RNA-Seq data from AMP-AD. This RNA-Seq data was generated from over 2100 samples from post-mortem brains of more than 1100 individuals. In total there are seven distinct brain regions assayed (DLPFC, TCX, CBE, PHG, IFG, STG, FP) from three studies (ROSMAP, MayoRNAseq, and MSBB). All data was processed through a harmonized computational pipeline. The data is publicly available including RNA-seq differential expression summary statistics and RNA-seq network coexpression analysis. The data used in Agora has been derived from the above data and are available for download in Synapse as JSON formatted files here.
Each of the AMP-AD teams is working to identify nascent AD drug targets. Initial target nominations are identified based on computational analysis of high-dimensional genomic, proteomic, and metabolomics data, and coexpression networks derived from human samples. From these, teams select a subset to evaluate in experimental model systems.Target nominations are dynamically updated by individual teams as additional supporting evidence is collected. The nominated targets represent early signals in the discovery of biological processes that may be useful for AD treatment or prevention. These nascent targetsare designed to complement existing targets that are currently under active drug discovery and development across the industry. By releasing these early results for external review, AMP-AD seeks to encourage external researchers to integrate these results into independent investigations, or actively contribute external evidence for target prioritization within Agora. As additional evidence mounts, we anticipate expanding this target list to include nominations from other sources.
Seven academic and nonprofit teams have contributed to the data and analyses presented in Agora. Learn more about these teams here.


BHAJI ON THE BEACH A film review by Hans Huttel Copyright 1993 Hans Huttel
[as seen at the Edinburgh Film Festival, Friday August 20, 1993] Directed by Gurinder Chadha. Country of origin: United Kingdom (1993)
What do women talk about when there are no men around? Hey, what do *Indian* women talk about when there are no men around?
In this film, the directing debut of Gurinder Chadha, we finally get the answer to this last question. BHAJI ON THE BEACH is another good example of a project that has been partially funded by Channel Four (MY BEAUTIFUL LAUNDRETTE and in particular THE CRYING GAME are two Channel Four-co-sponsored films that those outside the UK will probably be familiar with.)
The film is about a group of Indian women from Birmingham on a day trip to that great bastion of British tackiness, the seaside town of Blackpool. All the well-known archetypal characters are present on the bus. There's the old, Victorian aunt who keeps asking what the world is coming to. There's the independent, leather-jacket-wearing woman (who of course organised the event and drives the bus). There's the young middle-class woman who has just discovered that she is pregnant with a guy that she hasn't told her her parents about because he is black. There are the 15-year old girls who are only after one thing: boys! There is the young, single mother with an obsessive ex-husband. There is the middle-aged woman who was a lively, talented girl when in college but is now, 30 years later, stuck with a fat, balding husband and a career selling newspapers in his corner shop. All familiar stereotypes, here with the twist that they are Indian.
(And then of course there is a "real" Indian woman from Bombay who manages to make the other women look very old-fashioned!)
But it isn't going to be an entirely untroubled outing! The obsessive ex-husband goes to Blackpool to get back his ex-wife and their child, helped by his two brothers, a shell-suit wearing yob and a very reluctant "nice guy." The Afro-Caribbean guy who got the young middle-class woman pregnant doesn't know what to do when she breaks the news, but finally he gets on his motorbike and drives up to Blackpool. As to what happens next... I am not going to tell you. Go see the film when it opens!!
Yes, I am sure to disappoint some of you: I liked this film. It is certainly not a kitchen-sink drama; even though the film deals with some pretty serious subjects and is never afraid to treat them seriously, the film never gets depressing and there is plenty of comic relief along the way. There is actually something typically British about the approach and the humour. (After all, it is set in Blackpool.) Yes, the characters are almost all Indian and female but they are also pretty universal (and there is none of the misanthropy of a Hanif Kureishi here). The same goes for the storyline, actually. You definitely don't have to be Indian or female to enjoy this film.
-- Hans Huttel email<EMAIL_ADDRESS>University of Edinburgh phone: (+44) (0)31-650-5997 Edinburgh EH9 3JZ, UK
.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Statistical analysis in medical, biological, and environmental research often aims to draw meaningful stories from complex and incomplete data which measure effects and relationships whose drivers are rarely well understood. When dealing with data which may be influenced by underlying factors, measured or not measured, many possible sources of variability can influence the response. Analyses which attempt to encapsulate all sources of correlation, measuring all possible effects between covariates in elaborate and impressive models, may also depend upon rarely fulfilled assumptions of independence or normality. Bayesian methods can provide an alternative approach whereas the number of assumptions is reduced and the degree of certainty in a given result is available.
The current research focuses on the use of overfitted mixture models (specifically, Gaussian mixture models) as a tool for extracting data-driven, coherent stories from complex data with the aid of a study in Alzheimer's Disease. Overfitted mixtures provide a straightforward, theoretically supported approach for the analysis of data which comes from any number of underlying groups. They can be used both to estimate the number of groups and their parameters, but also to identify noise, outliers, skewness, and other artefacts common to real data. When combined with careful consideration of a specific research question, the hierarchical nature of the Bayesian result provides a framework from which specific features of interest can be easily extracted.
Results from this research demonstrate how the use of simple, low-assumption methods can sometimes help provide clear answers (or at least clues) to complex questions, as well as introduce recently developed tools and computational solutions for the analysis of overfitted mixture models.


{waveshaper-mod-cluster.png width=373}
This contains a standard {Waveshaper_mod_select mod select} {_parameter} and a corresponding {Waveshaper_mod_depth mod depth} {_slider}. Note that the depth on the slider is shown in cycles for the various FM {Waveshaper_shape shapes}, and in percent for the saws and pulse shapes. These have no effect if the shape is set to pink noise, white noise, or impulse.


@(title: String)(content: Html)
In line with a European court of Justice judgement, Google are removing search results for specific pages in relation to specific search terms made using European versions of the search engine. Google do not identify complainants, so this tool allows recipients of Right to be forgotten notifications to identify likely complainants via a search on the url of affected pages.


Success Engineer @ Chef Software
Chef provides ChefDK to setup a workstation for Chef development.
chef
- CLI tool to streamline workflow
berkshelf
- Cookbook dependency manager
kitchen
- Cookbook integration testing framework
chefspec
- Unit testing (rspec extensions)
foodcritic
- Linting tool
knife
- CLI tool for interacting with Chef Server
ohai
- System profiling tool
chef-client
- The thing that does the things!
Recipes are not scripts. They are not a procedural list of commands to run.
Chef will manage only the things you tell it to manage.
#!/bin/bash
sudo yum install httpd
sudo cp config_files/httpd.conf /etc/httpd/
sudo service httpd restart
recipe.rb
package 'httpd'
service 'httpd'
cookbook_file '/etc/httpd/httpd.conf' do
source 'httpd.conf'
notifies :restart, 'service[httpd]'
end
The Chef DSL is pure Ruby, so Ruby can be used at will in recipes, resources and libraries.
Data about the node that chef is currently running on.
Access/set in multiple ways.
Resource are provided as a DSL for describing system state. They should be idempotent whenever possible.
Resources provide a layer of abstraction.
package 'apache2' do
action :install
end
file '/var/www/html/index.html' do
content 'Hello world!
'
mode '0755'
owner 'apache'
group 'apache'
end
service 'apache2' do
action [ :enable, :start ]
end
Resources are the representation of the desired state and available properties.
Providers are the implementation of how to bring a system into a desired state.
Most built in resources have multiple providers for different operating systems. Chef will load the proper provider for the system based on Ohai's detection of the operating system. This can be overridden per resource if needed.
What's wrong with the with recipe we looked at earlier?
Let's make it better!
attributes.rb
default[:mycookbook][:apache][:package_name] = 'apache2'
default[:mycookbook][:apache][:service_name] = 'apache2'
default[:mycookbook][:web_content] = 'Hello world!
'
recipe.rb
package node[:mycookbook][:apache][:package_name] do
action :install
end
file '/var/www/html/index.html' do
content node[:mycookbook][:web_content]
mode '0755'
owner 'apache'
group 'apache'
end
service node[:mycookbook][:apache][:service_name] do
action [ :enable, :start ]
end
chef-client is the where the magic happens.
Chef server provides a central management point and information repository. It is NOT required!
Chef Zero is awesome sauce if you do not need/want to manage a Chef server.
The chef-client uses a two pass model to configure a system.
foodcritic is a tool for checking for good Chef style. Comes with built in rules that can be configured. Custom rules are also available in the community.
rubocop is a general Ruby linting tool.
ChefSpec is an RSpec extension that allows you to test through compile time. Tests run fast, and are straightforward to write. Great for catching unintended regressions in logic.
Node data may be stubbed manually, or Fauxhai may be used to simulate a particular platform.
Test Kitchen provides a framework for provisioning machines to run your actual code against, and then executing tests against them.
The most common testing tools are ServerSpec and InSpec (both RSpec based), but a bash tool (BATS) exists as well.
Roles provide a way of setting a run_list and some attributes that can be applied to nodes. These are commonly mapped to node functionality (eg. webserver, appserver, etc)
Environments provide a way of setting attributes and pinning cookbook versions for a set of nodes. Commonly along the lines of (dev, QA, prod, etc)
Data bags give you another way to store data.
users/user1.json
{
"id": "user1",
"username": "user1",
"shell": "bash"
}
recipe.rb
new_user = data_bag_item('users', 'user1')
user new_user['username'] do
shell new_user['shell']
end
There are a couple of options for managing secrets in Chef natively.
Chef can also integrate with external secret management systems such as Hashicorp Vault.
One of the most compelling reasons to use a Chef server is the ability to search your infrastructure. This can be done from the command line or from a recipe.
Command line:
knife search node 'role:webserver AND chef_environment:QA'
Recipe:
search(:node, 'role:webserver AND chef_environment:QA').each do |n|
puts n['ipaddress']
end


{% extends "layout.html" %} {% block title %}Zero-OS Hub{% endblock %} {% block content %}
Do you want to publish your Zero-OS flist to our hub? It's easy.
All you need is a .tar.gz archive of your files and upload it here. Have fun.
.tar.gz


Alert Window
Dialog Window
Progress Window
Wait Window
Prompt Window
Multiline Prompt Window
Hide on mask click:
Choose icon:
Error
Information
Question
Warning
Icon Dialog Window
Log:
Continue ?
Operation Successful !
Loading...


webpack starter
✨ A lightweight foundation for your next webpack based frontend project.
Test
7
8
9
*
4
5
6
-
1
2
3
+
0
.
/
=


Create a team to play a specific level in Lego Dimensions. Select the level from the list and let the team builder guide you through the creation process. The team builder includes not yet released waves as well.
You can always modify the abilities or skip one if you don't have the character for it.
You can either select the abilities by a level, world or arena to play or make your custom selection.
http://dimensions-builder.com/team-builder/{{urlAbilities}}
With this link you can share or store your ability selection. Post this link anywhere you want.
Click on a character to remove it from your team.
Click on a character to add {{skills[currentSkillIndex].name}} and other abilities to your team.
Characters are shown in order of rarity of the ability. In case of vehicles abilities from all build-stages count. The 'obvious choices' are all required characters with unique abilities.


Either use the drop zone or the file selection button.
NOTE: If the browser plays the WAV-file instead of converting it to FLAC, change the file-extension before dropping it into the browser
| Technology → Optimization ↓ | asm.js | WASM |
|---|---|---|
| release | [release.asmjs] sync init (default) | [release.]wasm async init |
| debug | dev[.asmjs] sync init | dev.wasm async init |
| minified | min[.asmjs] async init | min.wasm async init |


{% include 'common/head.html' %} {% include 'common/nav.html' %} {% include 'common/page_nav.html' %}
Enter a name that describes the purpose of your test.
UUID of the tests, may be used to refer it
Region (Interceptor queue) in which to run the test
URL to scan
Specify scanners to use.
Specify expected report types.
Comaseparated list of emails


Second Year Syllabus (RDVV)
---BCA-21-DATA STRUCTURES USING C++ |
|
|---|---|
| Unit-I | Introduction, OOPS languages, characteristics of OOP‘s languages, application of OOP‘s, OOP‘sparadigm, concepts: object, class, data abstraction, data encapsulation, inheritance, and polymorphism.Static and dynamic binding, message passing, benefits of OOP‘s, disadvantage of OOP‘s. |
| Unit-II | C++ Programming Concepts: input and output in C++, functions in C++- value parameters,reference parameters, Parameter passing, function overloading, arrays, pointers, new and deleteoperators, class and object, access specifiers, friend functions, constructors and destructor, Operatoroverloading, Inheritance and Polymorphism. Exceptions-throwing an exception and handling anexception. |
| Unit-III | Basic Concepts – Data Structures, Algorithm Specification-Introduction, Recursive algorithms, DataAbstraction, Performance analysis- time complexity and space complexity, Asymptotic Notation-BigO, Omega and Theta notations, Complexity Analysis Examples, Introduction to Linear and NonLinear data.Stack:Definition, Array implementation of stack (static stack): Operations PUSH, POP, AndTRAVERSE. Applications of stack: Infix, Prefix, Postfix representation and evaluation using stack,Use of stack in recursive implementation.Queue:Definition, Array implementation of queue (static queue): Operations INSERT, DELETE andTRAVERSE. Introduction to Circular queue: Definition & implementation, Priority queue, Doubleended queue, Applications of queue |
| Unit-IV | Introduction to linked list: Definition, advantaged, basic operations on linked list, stacks and queuesusing linked list, doubly linked list, circular linked list, applications of linked list.Searching and Sorting Techniques: Sequential search, binary search, insertion sort, selection sort, quicksort, bubble sort, heap sort, comparison of sorting methods. |
| Unit-V | Tree: Trees-basic terminology ,binary trees, tree representations as array and linked list, basicoperations on binary tree, traversal of binary trees:- inorder, preorder, postorder. Applications of binarytree, threaded binary tree, AVL tree, Introduction to B-Tree & B+ tree. Hash Table, Collision resolutiontechnique.Graphs: Definition, Terminology, Directed, Undirected and Weighted Graph, Representation of Graph,Graph Traversal-Depth first, Breadth first search, Spanning tree, Minimum Spanning tree, Shortest pathalgorithm |
| Practicals | Note: As per the syllabus and under guidance of respective faculty every student has to performminimum 50 lab exercise covering all units with equal weightage. |
BCA-22-DATABASE MANAGEMENT SYSTEM & RDBMS |
|
|---|---|
| Unit-I | Purpose of database system, views of data, data models: relation, network, hierarchical, instancesand schemas, data dictionary, types of database languages:-DDL, DML, DCL, TCL, structure ofDBMS, advantages and disadvantages of DBMS, 3-level architecture proposal:-external, conceptual &internal levels. Database System architecture, level of abstraction, Database users and DBA,Classification of Database Management Systems, Components of database system, Traditional FileSystems vs. Modern Database Systems, Introduction and applications of DBMS, Data Independence. |
| Unit-II | Entity relationship model as a tool of conceptual design: entities & entities set, relationship,relationship set & relationship types, attributes, role, participation and mapping constraints, keys,strong and weak entities, Advance ER Model Features: generalization, specialization & aggregation,reducing ER diagram to tables, Roles, Participation. |
| Unit-III | Fundamentals of set theoretical notations: relations, domains, attributes, tuples, concept of keys:primary key, super key, alternate key, candidate key, foreign key, fundamentals of integrity rules:entity & referential integrity ,extension and intention, relational algebra: select, project, Cartesianproduct, different types of joins: theta, equi, natural, outer joins, set operations.Evaluation of SQL, Between clause, Distinct Clause, Order by Clause, Group by Clause, SQLFunctions, Sub queries, Handling null value, Aggregate function, User Defied Function, , View.Relational Calculus, Introduction, Tuple Relational Calculus, Domain Relational Calculus.PL/SQL Programming using Oracle, Oracle Data types, Looping and Decision Making, Workingwith Stored Procedure, Trigger, Cursor, Package, Index, Synonym and Sequence. VariousProgramming Examples. |
| Unit-IV | Functional Dependencies, Good & Bad Decomposition and Anomalies as a database: Aconsequences of bad design, Universal relation, Normalization: INF, 2NF, 3NF &BCNF normalforms, multivalued dependency, join dependency, 4NF, 5NF.Relational Database design, Features of good relational database design, Codd‘s Rule, Integrityconstraints, Armstrong Axioms, Closure Set of Functional Dependency, Closure Set of Attributes |
| Unit-V | Basic concepts: -Indexing and Hashing, B-tree Index files, Hashing: Static & Dynamic hash function,Index definition in SQL: Multiple key accesses. Transaction Management, ACID properties,Serializability, Concurrency Control, Lock and types of Locks, Two Phase Locking Protocol, CheckPoints, Recovery Techniques, Deferred and Immediate data modification.Emerging Database Technology: Data Warehouse, Data Mining, Distributed database, MobileDatabase, Object Oriented Database, Geographical Database. |
| Practicals | Note: As per the syllabus and under guidance of respective faculty every student has to performminimum 25 lab. exercise covering all units with equal weightage. |
BCA-23-SOFTWARE ENGINEERING |
|
|---|---|
| Unit-I | Introduction :Software Engineering-Software Process- Generic process model-Prescriptive process modelspecialized, unified process-Agile development-Agile Process- Extreme Programming- Other agileProcess models-Software engineering Knowledge-core Principles-Principles that guide eachframework Activity |
| Unit-II | Requirements :Requirements Engineering-Establishing the Groundwork-Eliciting Requirements- Developing usecases-Building the requirements model-Negotiating, validating Requirements-Requirements AnalysisRequirements Modelling Strategies. |
| Unit-III | Design Modeling With Uml:Modeling Concepts and Diagrams - Use Case Diagrams - Class Diagrams - Interaction Diagrams -State chart Diagrams - Activity Diagrams - Package Diagrams - Component Diagrams – DeploymentDiagrams - Diagram Organization- Diagram Extensions. Design Process- Design concepts:Abstraction, Architecture, patterns, Separation of Concerns, Modularity, Information Hiding,Functional Independence, Refinement, Aspects, Refactoring, Object Oriented Design Concepts,Design Classes- Design Model: Data, Architectural, Interface, Component, Deployment Level DesignElements . |
| Unit-IV | Software Implementation :Structured coding Techniques-Coding Styles-Standards and Guidelines- Documentation GuidelinesModern Programming Language Features: Type checking-User defined data types-Data AbstractionException Handling- Concurrency Mechanism. |
| Unit-V | Testing And Maintenance Testing:Software Quality- Software Quality Dilemma- Achieving Software Quality- Testing: StrategicApproach to software Testing- Strategic Issues- Testing: Strategies for Conventional Software, Objectoriented software, Web Apps-Validating Testing- System Testing- Art of Debugging.Maintenance: Software Maintenance-Software Supportability- Reengineering- Business ProcessReengineering- Software Reengineering- Reverse Engineering- Restructuring- Forward EngineeringEconomics of Reengineering. |
BCA-24-OPERATING SYSTEM with UNIX/LINUX |
|
|---|---|
| Unit-I | Introduction to Operating Systems, Operating system services, multiprogramming, timesharing system, storage structures, system calls, multiprocessor system. Basic concepts ofCPU scheduling, Scheduling criteria, Scheduling algorithms, algorithm evaluation,multiple processor scheduling, real time scheduling I/0 devices organization, I/0 devicesorganization, I/0 devices organization, I/0 buffering. |
| Unit-II | Process concept, process scheduling, operations on processes, threads, inter-processcommunication, precedence graphs, critical section problem, semaphores, classical problemsof synchronization. Deadlock problem, deadlock characterization, deadlock prevention,deadlock avoidance, deadlock detection, recovery from deadlock, Methods for deadlockhandling |
| Unit-III | Concepts of memory management, logical and physical address space, swapping, contiguousand non-contiguous allocation, paging, segmentation, paging combined with segmentation.Concepts of virtual memory, demand paging, page replacement algorithms, allocation offrames, thrashing, demand segmentation. Security threads protection intruders-Virusestrusted system. Introduction to distributed systems and parallel processing. |
| Unit-IV | Unix operating system, background, philosophy, help facility, The file system, structure offile system, Basic Command related to file system.Utilities: more, file, wc, file comparison ( cmp, comm, diff) , lp, banner, cal, date, who, tty,sty commands. The Bourne shell: sh preceding a command by its own combining commands,pattern matching, echo, pipes, tees, shell variables and shell scripts, simple filters, Advancedfilters.The process: shell process, parent and children process status, system processes, multiplejobs , foreground and background, wait commands, pre mature termination of process, jobexecution with low priority, multiple jobs in foreground, shell layers, timing processes |
| Unit-V | Communication and scheduling, Execute at later running jobs, periodically. Programmingwith shell: system variable, profile, conditional execution, script termination, Conditional andloop control statements, set and shift statement.System Administration: super user, security, user services, floppy disk, managementoperation, files system, administration backups. |
| Practicals | Note: As per the syllabus and under guidance of respective faculty every student has to performminimum 25 lab. exercise covering all units with equal weightage. |
BCA-25-ACCOUNTING AND FINANCIAL MANAGEMENT |
|
|---|---|
| Unit-I | Introduction: Financial Accounting-definition and Scope, objectives of Financial Accounting,Accounting v/s Book Keeping Terms used in accounting, users of accounting information andlimitations of Financial Accounting. |
| Unit-II | Conceptual Frame work: Accounting Concepts, Principles and Conventions, Accounting Standardsconcept, objectives, benefits, brief review of Accounting Standards in India, Accounting Policies,Accounting as a measurement discipline, valuation Principles, accounting estimates |
| Unit-III | Recording of transactions: Voucher system; Accounting Process, Journals, Subsidiary Books, Ledger,Cash Book, Bank Reconciliation Statement, Trial Balance. Depreciation: Meaning, need &importance of depreciation, methods of charging depreciation.(WDV & SLM). |
| Unit-IV | Preparation of final accounts: Preparation of Trading and Profit & Loss Account and Balance Sheet ofsole proprietary business.Introduction to Company Final Accounts: Important provisions of Companies Act, 1956 in respect ofpreparation of Final Accounts. Understanding of final accounts of a Company |
| Unit-V | Computerised Accounting: Computers and Financial application, Accounting Software packages. Anoverview of computerized accounting system - Salient features and significance, Concept of groupingof accounts, Codification of accounts, Maintaining the hierarchy of ledger, Generating AccountingReports. |
BCA-26-COMPUTER ORIENTED NUMERICAL METHODS |
|
|---|---|
| Unit-I | NUMERICAL COMPUTATIONS :Computer Arithmetic: Floating Point Number Operations, Normalization and their consequences.Iterative Methods : Bisection Methods, False Position Methods, Newton Raphson Method, SecantMethod, Graffes Root Squaring Method, Convergence of Solution |
| Unit-II | Simultaneous Liner Equation : Solution of Simultaneous Liner Equation – Gauss Elimination Method,Gauss – Seidal Method, Gauss – Jordan Elimination Method, Triangularization Method & PivotingCondensation, III Conditioned Equation & Refinement of solutionCurve Fitting : Curve Fitting Method, Least Curve Fitting, Non Linear Curve Fitting. |
| Unit-III | Difference Operators And Interpolation: Definition Of Forward, Backward, Shifting, Divided,Difference Central and Averaging Operators and their Relationships. Newton‘s Forward InterpolationFormula, Newton‘s backward Interpolation Formula Newton‘s divided Interpolation Formula.Lagrange‘s Interpolation Formula. |
| Unit-IV | Numerical Differentiation: Numerical Differentiation using Newton‘s Forward Interpolation Formula,Newton‘s Backward Interpolation Formula Newton‘s divided Interpolation Formula. NumericalIntegration : General Quadrature Formula, Newton- Cote‘s Formula, Trapezoidal Rule, Simpson‘sone Third Rule, Simpson‘s Three Eight Rule. |
| Unit-V | Numerical Solutions of Ordinary Differential Equations : Euler‘s Method , Euler‘s Modifies Method.Tailor‘s Series Method, Picard‘s Method, RungaKutta Second Order and Fourth order Method. |


| Interface | Description |
|---|---|
| Configuration |
Static configuration.
|
| Configuration.Context |
This should be removed if possible, as its creation was premature - intended for a use-case that we have
not implemented.
|
| ConfigurationContextResolver |
Creates a new configuration context relative to the request.
|
| ConfigurationContextResolverFactory |
A factory that creates
ConfigurationContextResolver s. |
| ConfigurationFactory |
Factory for creating a Configuration.
|
| Converter |
A function that converts a source to targetType.
|
| ServiceFactory<E> |
A generic factory that can be implemented in order to facilitate creating objects whose type is not known
until read from configuration.
|
| Class | Description |
|---|---|
| Configuration.MapBackedConfiguration |
Allows a configuration object to be programmatically created.
|
| Exception | Description |
|---|---|
| ConfigurationException |
This exception is thrown when there is a configuration problem.
|
| ConversionException |
An exception thrown when an attempt at converting a value from one type to another failed.
|
| MissingConfigurationException |
Exception thrown when some required configuration property is missing.
|
| NoSystemPropertyDefined |
Extension of
ConfigurationException thrown when a system variable is undefined. |
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How does one create the best climatology? What if the time series is shorter than the recommended 30 years?
Lets look at all the SACTN data that’s longer than 30 years first. Can each site’s annual signal be represented by a sine/cosine curve derived from a Fourier analysis? First I find all the sites within the South African Coastal Temperature Network that are approximately 30 years or more in duration.
# load("~/SACTNraw/data/4_products/SACTN_daily_v4.2.RData")
load("/Volumes/GoogleDrive/My Drive/SACTN/SACTNraw/data/4_products/SACTN_daily_v4.2.RData")
daily.in <- SACTN_daily_v4.2
rm(SACTN_daily_v4.2)
long_sites <- daily.in %>%
group_by(index) %>%
summarise(n = n()) %>%
filter(n >= 365 * 30) %>%
ungroup()
Now, for each site that has ≥30 years of data, I create a daily climatology by taking the mean for each Julian day, using all data across the full duration of each time series.
daily <- daily.in %>%
filter(index %in% long_sites$index) %>%
mutate(index = as.character(index)) %>%
# droplevels() %>%
group_by(index) %>%
mutate(doy = yday(date)) %>%
group_by(index, doy) %>%
summarise(temp = mean(temp, na.rm = TRUE)) %>%
ungroup()
I make a function that will fit a Fourier series with seven basis functions (3 sine, 3 cosine and the constant) to the data. This is the same approach I used to create the smooth climatology in “Climatologies and baseline” elsewhere on this site, and it is also the one favoured in the creation of the daily Optimally Interpolated Sea Surface Temperature climatology (Banzon et al. 2014). Here it is wrapped in a function so I can easily apply it to each time series.
fFun <- function(data) {
require(fda)
b7 <- create.fourier.basis(rangeval = range(data$doy), nbasis = 7)
# create smooth seasonal climatology
b7.smth <- smooth.basis(argvals = data$doy, y = data$temp, fdParobj = b7)$fd
data.smth <- eval.fd(data$doy, b7.smth)
return(data.smth)
}
# currently this function fails when the 1st of January is an NA
# which sites have NAs?
excl.sites <- c(daily[is.na(daily$temp), 1])$index
daily.nest <- daily %>%
filter(!index %in% excl.sites) %>%
nest(-index)
daily.smth <- daily.nest %>%
mutate(smoothed = map(data, fFun)) %>%
unnest(data, smoothed)
plt1 <- daily.smth %>%
ggplot(aes(x = doy, y = temp)) +
geom_point(shape = "+", colour = "red", alpha = 0.6, size = 1) +
geom_line(aes(y = smoothed, group = index), size = 0.6, colour = "black") +
facet_wrap(~index) +
labs(x = "Julian day", y = "Temperature (°C)", title = "SACTN: daily climatology",
subtitle = "Fourier series: 7 basis functions")
ggsave(plt1, file = "fig/SACTN_Fourier7.png", width = 12, height = 9, dpi = 120)
There are instances when we might need to create climatologies when we don’t have access to time series of 30 years or longer. To look at this problem, I created a quick resampling analysis to see what the effect of time series length is on the resultant climatology. In this instance I used a Fourier analysis (see Banzon et al., 2014) to calculate six modes within an annual cycle, and used these to reconstruct a smooth climatology. This technique is quite forgiving of SST seasonalities that depart from typical sinusoidal profiles, such as which we find along upwelling areas (I have tested this on our coastal seawater temperatures).
I used the Western Australian data that’s packaged with the python and R marine heat wave scripts. Later I’ll test this more widely on other time series. The WA time series is 32 years long. I treat all temperatures over the duration of the time series as a pool of data, separately for each day-of-year (doy); i.e. doy 1 has 32 temperatures, doy 2 also has 32 temperatures, etc. I assume that the temperature on doy 1 of 1982 is independent of that on doy 1 in every other year (etc.), so the sample of doy 1 temperatures is therefore independent and identically distributed (i.i.d.). I further assume that there’s no autocorrelation from day-to-day (definitely erroneous, but I don’t think it matters here).
For each day’s pool of samples I then randomly take 10 samples and find the mean of that. This is the same as averaging over 10 years to obtain the mean for each of the 365 days (one year). Note that I did not apply the 11 day sliding window as per the heat wave function (windowHalfWidth), and rather opted to treat each doy independently as per Banzon et al. (2014). I repeat this 100 times, and so I effectively have estimates of a 100 annual cycles. I then do the same with 20 samples and 30 samples taken from the pool of available samples for each doy.
In total I now have 300 annual cycles: 100 of them representing a 10-year long times series, 100 representing a 20-year long time series, and 100 for a 30 year time series. To each of them, separately, I then fit the smooth climatology assembled from their Fourier components.
The attached plots show the outcome. The three panels represent 10, 20 and 30 year long time series. In Figure 2, each of the 100 daily time series is plotted as a line graph. In Figure 3, the red crosses show, for each doy, each of the 100 mean temperatures that I obtained. The black lines are of course the smooth climatologies–there is also 100 of these lines on each of the three panels.
So, using resampling and a Fourier analysis we can get away with using shorter time series. I can see later what happens if I shrink even further the time series down to only five years long. I will also test how well the python and R heatwave scripts’ internal climatology functions (windowHalfWidth and smoothPercentile) are able to produce reliable climatologies from short time series.
library(heatwaveR)
sst.in <- as_tibble(heatwaveR::sst_WA)
sst <- sst.in %>%
mutate(doy = yday(as.Date(t))) %>%
nest(-doy)
meanFun <- function(data) {
m <- mean(data$temp, na.rm = TRUE)
return(m)
}
sstRepl <- function(sst) {
sst.sampled <- sst %>%
mutate(sample_10 = map(data, sample_n, 10, replace = TRUE),
sample_20 = map(data, sample_n, 20, replace = TRUE),
sample_30 = map(data, sample_n, 30, replace = TRUE)) %>%
mutate(sample_10_m = map(sample_10, meanFun),
sample_20_m = map(sample_20, meanFun),
sample_30_m = map(sample_30, meanFun)) %>%
select(-data, -sample_10, -sample_20, -sample_30) %>%
unnest(sample_10_m, sample_20_m, sample_30_m)
return(sst.sampled)
}
library(purrr)
sst.repl <- purrr::rerun(100, sstRepl(sst)) %>%
map_df(as.data.frame, .id = "rep") %>%
gather(key = "ts.len", value = "temp", -rep, -doy)
plt2 <- ggplot(data = sst.repl, aes(x = doy, y = temp)) +
geom_line(aes(group = rep), alpha = 0.3, size = 0.1) +
facet_wrap(~ts.len, nrow = 3) +
labs(x = "Julian day", y = "SST (°C)", title = "Raw daily climatology",
subtitle = "100 daily climatological means")
ggsave(plt2, file = "fig/WA_100_simul.png", width = 12, height = 6, dpi = 120)
sst.repl.nest <- sst.repl %>%
nest(-rep, -ts.len)
sst.repl.smth <- sst.repl.nest %>%
mutate(smoothed = map(data, fFun)) %>%
unnest(data, smoothed)
plt3 <- ggplot(data = sst.repl.smth, aes(x = doy, y = smoothed)) +
geom_point(aes(y = temp), shape = "+", colour = "red", alpha = 0.1, size = 1) +
geom_line(aes(group = rep), alpha = 0.3, size = 0.1) +
facet_wrap(~ts.len, nrow = 3) +
labs(x = "Julian day", y = "SST (°C)", title = "WA SST: daily climatology",
subtitle = "Fourier series: 7 basis functions")
ggsave(plt3, file = "fig/WA_Fourier7.png", width = 12, height = 6, dpi = 120)
The heatwaveR climatology tool creates the mean and 90th percentiles (threshold) for all the data within a sliding window with certain window width (by default 11 days centred on a day-of-year), and then this is followed by a running mean smoother for both the mean and the threshold. Using the approach I created for the Fourier series, lets do the same here.
sstRepl2 <- function(sst) {
sst.sampled <- sst %>%
mutate(sample_10 = map(data, sample_n, 10, replace = TRUE),
sample_20 = map(data, sample_n, 20, replace = TRUE),
sample_30 = map(data, sample_n, 30, replace = TRUE))
return(sst.sampled)
}
sst.repl2 <- purrr::rerun(100, sstRepl2(sst)) %>%
map_df(as.data.frame, .id = "rep")
parseDates <- function(data, rep_col, len) {
parsed <- data %>%
mutate(id = rep_col,
y = year(t),
m = month(t),
d = day(t)) %>%
group_by(rep, doy) %>%
mutate(y = seq(1983, by = 1, len = len)) %>%
mutate(t = ymd(paste(y, m, d, sep = "-"))) %>%
select(-y, -m, -d) %>%
na.omit() # because of complications due to leap years
return(parsed)
}
sample_10 <- sst.repl2 %>%
unnest(sample_10) %>%
parseDates("sample_10", len = 10) %>%
group_by(id, rep) %>%
nest() %>%
mutate(smoothed = map(data, function(x) ts2clm(x, climatologyPeriod = c("1983-01-01", "1992-12-31")))) %>%
unnest(smoothed)
sample_20 <- sst.repl2 %>%
unnest(sample_20) %>%
parseDates("sample_20", len = 20) %>%
group_by(id, rep) %>%
nest() %>%
mutate(smoothed = map(data, function(x) ts2clm(x, climatologyPeriod = c("1983-01-01", "2002-12-31")))) %>%
unnest(smoothed)
sample_30 <- sst.repl2 %>%
unnest(sample_30) %>%
parseDates("sample_30", len = 30) %>%
group_by(id, rep) %>%
nest() %>%
mutate(smoothed = map(data, function(x) ts2clm(x, climatologyPeriod = c("1983-01-01", "2012-12-31")))) %>%
unnest(smoothed)
sst.repl2.smth <- bind_rows(sample_10, sample_20, sample_30)
plt4 <- sst.repl2.smth %>%
ggplot(aes(x = doy, y = temp)) +
# geom_point(shape = "+", colour = "red", alpha = 0.1, size = 1) +
geom_line(data = filter(sst.repl2.smth, t <= "1984-01-01"), aes(y = seas, group = rep), alpha = 0.3, size = 0.1) +
facet_wrap(~id, nrow = 3) +
labs(x = "Julian day", y = "SST (°C)", title = "WA SST: daily climatology",
subtitle = "MHW climatology, default settings")
ggsave(plt4, file = "fig/rand_mat_smoothed_2.png", width = 12, height = 6, dpi = 120)
Banzon, Viva F., Richard W. Reynolds, Diane Stokes, and Yan Xue. 2014. “A 1/4°-Spatial-resolution daily sea surface temperature climatology based on a blended satellite and in situ analysis.” Journal of Climate 27 (21): 8221–8. https://doi.org/10.1175/JCLI-D-14-00293.1.
sessionInfo()
This reproducible R Markdown analysis was created with workflowr 1.1.1


The personal information you provide to the PRIME application is collected by the British Columbia Ministry of Health under the authority of s. 26(a) and 26(c) of the Freedom of Information and Protection of Privacy Act (FOIPPA) and s. 22(1)(b) of the Pharmaceutical Services Act for the purpose of managing your access to, and use of, PharmaNet. If you have any questions about the collection or use of this information, call
Health Insurance BC toll free at


LOGNAME(1) User Commands LOGNAME(1) NAME logname - print user´s login name SYNOPSIS logname [OPTION] DESCRIPTION Print the name of the current user. --help display this help and exit --version output version information and exit AUTHOR Written by FIXME: unknown. REPORTING BUGS Report logname bugs to<EMAIL_ADDRESS>GNU coreutils home page: <http://www.gnu.org/software/coreutils/> General help using GNU software: <http://www.gnu.org/gethelp/> Report logname translation bugs to <http://translationproject.org/team/> COPYRIGHT Copyright © 2011 Free Software Foundation, Inc. License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>. This is free software: you are free to change and redistribute it. There is NO WARRANTY, to the extent permitted by law. SEE ALSO The full documentation for logname is maintained as a Texinfo manual. If the info and logname programs are properly installed at your site, the command info coreutils 'logname invocation' should give you access to the complete manual. GNU coreutils 8.12.197-032bb September 2011 LOGNAME(1)


There are 40502 total genes for the gene annotations for Release 75 and Release 86. There are 1506 common Gene IDs between the two gene annotations for Release 75 and Release 86. There are 18770 common genes with the same Gene Name and the same Chromosomal Start and End position. There are 5221 genes that have the same Gene ID and different Gene Names.
There are 40596 total transcripts for the gene annotations for Release 75 and Release 86. There are 5221 common Transcript IDs between the two gene annotations for Release 75 and Release 86. There were no transcripts found with the same transcript id and the same chromosomal start and end position.
| GENES | |||
|---|---|---|---|
| Release 75 | Number | Release 86 | Number |
| Total Genes | 20251 | Total Genes | 20251 |
| protein_coding | 11601 | protein_coding | 2760 |
| rRNA | 477 | pseudogene | 1237 |
| snoRNA | 1837 | snoRNA | 1237 |
| snRNA | 1663 | ensembl | 15550 |
| miRNA | 678 | ||
| Mt-rRNA | 2 | ||
| Mt-tRNA | 22 |
| TRANSCRIPT | |||
|---|---|---|---|
| Release 75 | Number | Release 86 | Number |
| ensembl | 16326 | ensembl | 4706 |
| miRNA | 678 | snRNA | 1663 |
| Mt-rRNA | 2 | misc_RNA | 705 |
| Mt-tRNA | 22 | snoRNA | 1837 |
| protein coding | 2031 | protein coding | 10910 |
| pseudogene | 1237 |


{% extends "page_with_title_and_lede.html" %} {% load i18n %} {% block head_title %}Where to Stay{% endblock %} {% block heading %}Where to Stay{% endblock %} {% block body_class %}attend{% endblock %} {% block lede %} {% endblock %} {% block content %}
We do not have an official hotel block this year however there are a number of nearby hotels available.
A number of other hotels are also located in the area.
{% endblock %}


What to know about hepatitis A outbreaks in the US
Fears of hepatitis A swirled in Somerville, New Jersey, this week, after the health department there reported that a food handler in a local grocery store could have exposed shoppers to the infectious disease.
New Jersey's current hepatitis A outbreak, which began in 2018, has swelled to 504 cases as of early November.
It's also part of an ongoing nationwide outbreak of the infectious disease, which began in 2016 and has led to 27,634 infections and 16,679 hospitalizations, according to the Centers for Disease Control and Prevention.
Hepatitis A, a highly contagious liver infection that's typically spread by coming in contact with feces from a person already infected, has killed 275 people in 30 states from 2016 through Nov. 1.
Despite the New Jersey grocery store incident, and contrary to what many people believe, most people don't contract the disease from contaminated food or water.
Instead, hepatitis A tends to be spread person-to-person, with the vast majority of infections occurring among people who are homeless or inject drugs, or among men who have sex with men.
California's 2016 to 2018 outbreak, for example, spread primarily among homeless encampments along the coastline, prompting then-Gov. Jerry Brown to declare a state of emergency.
Symptoms of the disease include fatigue, sudden nausea and vomiting, dark urine, clay-colored stool and jaundice, according to the Mayo Clinic. Unlike hepatitis B and hepatitis C, which also affect the liver, hepatitis A does not cause chronic liver disease, and is not typically fatal.
The best defense against the disease is thorough hand-washing or getting the hepatitis A vaccine, which is 95% effective and lasts for 11 years.


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Class EventComponent
Event handlers to subscribe to robot events.
Implements
Inherited Members
Namespace: Anki.Vector
Assembly: Anki.Vector.dll
Syntax
public class EventComponent : Component, INotifyPropertyChanged
Properties
| Improve this Doc View SourceIsProccessingEvents
Gets a value indicating whether this instance is processing events.
public bool IsProccessingEvents { get; }
Property Type
| Boolean |
Events
| Improve this Doc View SourceAlexaAuth
Robot event when alexa authentication occurs.
public event EventHandler<AlexaAuthEventArgs> AlexaAuth
Event Type
| EventHandler<AlexaAuthEventArgs> |
AttentionTransfer
Robot event triggered after Vector finishes RCM TBD
public event EventHandler<AttentionTransferEventArgs> AttentionTransfer
Event Type
| EventHandler<AttentionTransferEventArgs> |
CameraSettingsUpdate
Robot event triggered when camera settings are updated.
public event EventHandler<CameraSettingsUpdateEventArgs> CameraSettingsUpdate
Event Type
| EventHandler<CameraSettingsUpdateEventArgs> |
ChangedObservedFaceId
Robot event for when observed face changes
public event EventHandler<RobotChangedObservedFaceIdEventArgs> ChangedObservedFaceId
Event Type
| EventHandler<RobotChangedObservedFaceIdEventArgs> |
CheckUpdateStatus
Robot event that occurs when checking for updates.
public event EventHandler<CheckUpdateStatusEventArgs> CheckUpdateStatus
Event Type
| EventHandler<CheckUpdateStatusEventArgs> |
ConnectionResponse
Occurs when connection response received.
public event EventHandler<ConnectionResponseEventArgs> ConnectionResponse
Event Type
| EventHandler<ConnectionResponseEventArgs> |
CubeBattery
Occurs when cube batter status received.
public event EventHandler<CubeBatteryEventArgs> CubeBattery
Event Type
| EventHandler<CubeBatteryEventArgs> |
CubeConnectionLost
Occurs when the cube connection is lost.
public event EventHandler<CubeConnectionLostEventArgs> CubeConnectionLost
Event Type
| EventHandler<CubeConnectionLostEventArgs> |
FaceEnrollmentCompleted
Robot event when face enrollment completed.
public event EventHandler<FaceEnrollmentCompletedEventArgs> FaceEnrollmentCompleted
Event Type
| EventHandler<FaceEnrollmentCompletedEventArgs> |
FaceScanComplete
Robot event when face scan completed.
public event EventHandler<FaceScanCompleteEventArgs> FaceScanComplete
Event Type
| EventHandler<FaceScanCompleteEventArgs> |
FaceScanStarted
Robot event when face scan started.
public event EventHandler<FaceScanStartedEventArgs> FaceScanStarted
Event Type
| EventHandler<FaceScanStartedEventArgs> |
FeatureStatus
Occurs when a feature is invoked.
public event EventHandler<FeatureStatusEventArgs> FeatureStatus
Event Type
| EventHandler<FeatureStatusEventArgs> |
JdocsChanged
Robot event when jdocs have been changed.
public event EventHandler<JdocsChangedEventArgs> JdocsChanged
Event Type
| EventHandler<JdocsChangedEventArgs> |
KeepAlive
Keep alive event from robot
public event EventHandler<KeepAliveEventArgs> KeepAlive
Event Type
| EventHandler<KeepAliveEventArgs> |
MirrorModeDisabled
Occurs when mirror mode is disabled.
public event EventHandler<MirrorModeDisabledEventArgs> MirrorModeDisabled
Event Type
| EventHandler<MirrorModeDisabledEventArgs> |
ObjectAvailable
After the ConnectCube process is started, all available light cubes in range will broadcast an availability message through the Robot.
public event EventHandler<RobotObjectAvailableEventArgs> ObjectAvailable
Event Type
| EventHandler<RobotObjectAvailableEventArgs> |
ObjectConnectionState
Connection state change of the cube
public event EventHandler<RobotObjectConnectionStateEventArgs> ObjectConnectionState
Event Type
| EventHandler<RobotObjectConnectionStateEventArgs> |
ObjectMoved
Robot event triggered when an object starts moving.
public event EventHandler<RobotObjectMovedEventArgs> ObjectMoved
Event Type
| EventHandler<RobotObjectMovedEventArgs> |
ObjectStoppedMoving
Robot event triggered when an object stops moving.
public event EventHandler<RobotObjectStoppedMovingEventArgs> ObjectStoppedMoving
Event Type
| EventHandler<RobotObjectStoppedMovingEventArgs> |
ObjectTapped
Robot event triggered when an object is tapped.
public event EventHandler<RobotObjectTappedEventArgs> ObjectTapped
Event Type
| EventHandler<RobotObjectTappedEventArgs> |
ObjectUpAxisChanged
Robot event triggered when an object’s orientation changed.
public event EventHandler<RobotObjectUpAxisChangedEventArgs> ObjectUpAxisChanged
Event Type
| EventHandler<RobotObjectUpAxisChangedEventArgs> |
ObservedFace
Robot event for when a face is observed by the robot.
public event EventHandler<RobotObservedFaceEventArgs> ObservedFace
Event Type
| EventHandler<RobotObservedFaceEventArgs> |
ObservedObject
Robot event triggered when an object is observed by the robot.
public event EventHandler<RobotObservedObjectEventArgs> ObservedObject
Event Type
| EventHandler<RobotObservedObjectEventArgs> |
PhotoTaken
Robot event when photo is taken
public event EventHandler<PhotoTakenEventArgs> PhotoTaken
Event Type
| EventHandler<PhotoTakenEventArgs> |
RobotErasedEnrolledFace
Robot event triggered when robot erased an enrolled face.
public event EventHandler<RobotErasedEnrolledFaceEventArgs> RobotErasedEnrolledFace
Event Type
| EventHandler<RobotErasedEnrolledFaceEventArgs> |
RobotEvent
Occurs for every robot event
public event EventHandler<RobotEventArgs> RobotEvent
Event Type
| EventHandler<RobotEventArgs> |
RobotObservedMotion
Robot event triggered when the robot observed motion.
public event EventHandler<RobotObservedMotionEventArgs> RobotObservedMotion
Event Type
| EventHandler<RobotObservedMotionEventArgs> |
RobotRenamedEnrolledFace
Robot event triggered when robot renamed enrolled face.
public event EventHandler<RobotRenamedEnrolledFaceEventArgs> RobotRenamedEnrolledFace
Event Type
| EventHandler<RobotRenamedEnrolledFaceEventArgs> |
RobotState
Robot event containing changes to the robot’s state.
public event EventHandler<RobotStateEventArgs> RobotState
Event Type
| EventHandler<RobotStateEventArgs> |
StimulationInfo
Robot event containing stimulation information.
public event EventHandler<StimulationInfoEventArgs> StimulationInfo
Event Type
| EventHandler<StimulationInfoEventArgs> |
UnexpectedMovement
Robot event triggered when Vector does not move as expected.
public event EventHandler<UnexpectedMovementEventArgs> UnexpectedMovement
Event Type
| EventHandler<UnexpectedMovementEventArgs> |
UserIntent
Root event triggered after processing voice commands.
Note: This event is only sent if the application has reserved control -- and thus Vector will not carry it out.
See also WakeWordEnd (to receive the intent when we haven't reserved control), and AppIntent to send an intent
public event EventHandler<UserIntentEventArgs> UserIntent
Event Type
| EventHandler<UserIntentEventArgs> |
VisionModesAutoDisabled
Robot event vision modes are automatically disabled.
public event EventHandler<VisionModesAutoDisabledEventArgs> VisionModesAutoDisabled
Event Type
| EventHandler<VisionModesAutoDisabledEventArgs> |
WakeWordBegin
Robot event triggered when Vector hears "Hey Vector"
public event EventHandler<WakeWordBeginEventArgs> WakeWordBegin
Event Type
| EventHandler<WakeWordBeginEventArgs> |
WakeWordEnd
Robot event triggered after Vector finishes listening to "Hey Vector"
public event EventHandler<WakeWordEndEventArgs> WakeWordEnd
Event Type
| EventHandler<WakeWordEndEventArgs> |


{{ define "title" }}Istio ControlZ{{ end }} {{ define "content" }}
Make a selection in the left sidebar to inspect & control aspects of this process.
| Process Name | {{.ProcessName}} |
| Heap Size | {{.HeapSize}} bytes |
| Num Garbage Collections | {{.NumGC}} |
| Current Time | |
| Hostname | {{.Hostname}} |
| IP Address | {{.IP}} |


We're sorry but vue-single-spa-back doesn't work properly without JavaScript enabled. Please enable it to continue.


Wand is a ctypes-based simple ImageMagick binding for Python.
from wand.image import Image
from wand.display import display
with Image(filename='mona-lisa.png') as img:
print(img.size)
for r in 1, 2, 3:
with img.clone() as i:
i.resize(int(i.width * r * 0.25), int(i.height * r * 0.25))
i.rotate(90 * r)
i.save(filename='mona-lisa-{0}.png'.format(r))
display(i)
Wand has the list for users. If you want to subscribe the list, just send a mail to:
The list archive provided by Librelist is synchronized every hour.
There’s a Stack Overflow tag for Wand:
http://stackoverflow.com/questions/tagged/wand
Freely ask questions about Wand including troubleshooting. Thanks for sindikat‘s contribution.
There’s a Quora topic for Wand: Wand (ImageMagick binding). Be free to add questions to the topic, though it’s suitable for higher-level questions rather than troubleshooting.
Wand is an open source software written by Hong Minhee (initially written for StyleShare). See also the complete list of contributors as well. The source code is distributed under MIT license and you can find it at GitHub repository. Check out now:
$ git clone git://github.com/dahlia/wand.git
If you find a bug, please notify to our issue tracker. Pull requests are always welcome!
We discuss about Wand’s development on IRC. Come #wand channel on freenode network.
Check out Wand Changelog also.


(PHP 4 >= 4.0.5, PHP 5 < 5.1.0, PECL mnogosearch >= 1.0.0)
udm_alloc_agent — Allocate mnoGoSearch session
$dbaddr
[, string $dbmode
] ) : resourceAllocate a mnoGoSearch session.
dbaddr
dbaddr
- URL-style database description, with
options (type, host, database name, port, user and password) to connect
to SQL database. Do not matter for built-in text files support. Format for
dbaddr
:
DBType:[//[DBUser[:DBPass]@]DBHost[:DBPort]]/DBName/.
Currently supported DBType values are: mysql, pgsql, msql, solid, mssql, oracle,
and ibase. Actually, it does not matter for native libraries support, but
ODBC users should specify one of the supported values. If your database
type is not supported, you may use unknown instead.
dbmode
dbmode
- You may select the SQL database mode of
words storage. Possible values of dbmode
are:
single, multi, crc,
or crc-multi. When single is
specified, all words are stored in the same table. If multi
is selected, words will be located in different tables depending
of their lengths. "multi" mode is usually faster, but requires more tables
in the database. If "crc" mode is selected, mnoGoSearch will store 32 bit
integer word IDs calculated by CRC32 algorithm instead of words. This mode
requires less disk space and it is faster comparing with "single" and
"multi" modes. crc-multi uses the same storage structure
with the "crc" mode, but also stores words in different tables depending on
words lengths like in "multi" mode.
Note:
dbaddr
anddbmode
must match those used during indexing.
Returns a mnogosearch agent identifier on success, FALSE
on failure. This
function creates a session with database parameters.
Note:
In fact this function does not open a connection to the database and thus does not check the entered login and password. Establishing a connection to the database and login/password verification is done by udm_find().


Printer Test
Fallback to window.open() if WebApp Hardware Bridge is not running.
If "id" is submitted, it will be echoed back in onUpdate() thus we can trace back to jobs we submitted
If "qty" is submitted, specified copies of documents will be printed.


ChooseWifi lets the user select a WiFi network in his range.
title1 and title2 are the titles for the scanning and the selection process. They default to “Scanning” and “Select WiFi”.
The callback function returns the name and the ssid of the selected network.
You can set the force option so that the dialog cannot be closed until the user has selected an item.
Finally you can add extra items as pipe “|” separated string - ie. to add a default “[None]” entry to select no wifi network.


Hey, Dry,
April is Sexual Assault Awareness Month (SAAM), and we want you and your group to get involved, raise awareness, and create action on campus!
Sexual Assault Awareness Month occurs each year in April, and this year’s national SAAM campaign is specifically focused on the campus sexual assault epidemic.There’s a lot you can do on campus to spread the word, get people galvanized for change, and support survivors - all before the semester ends. On our blog, we’ve outlined five ways to get active this month, [ http://feministcampus.org/its-saam2015-here-are-four-ways-to-get-involved/ ] but we’ve got a special opportunity for campus leaders like you. We’ll be negotiating discounts for interested students who want to screen “The Hunting Ground” on campus this April!
“The Hunting Ground,” [ http://www.thehuntinggroundfilm.com/ ] a new documentary from the filmmakers behind “The Invisible War,” on your very own campus! “The Hunting Ground” explores the reality of sexual assault on campus - and the intimidating mess of policies and practices survivors must navigate as they seek justice. Check out the trailer below, and *if you’re interested in hosting a screening, **email us [ mailto:campusteam@feminist.org?subject=%22The%20Hunting%20Ground%22%20campus%20screening ]** by 12 PM EST on Friday, April 3 - we’ll negotiate a discount for you.*
[ https://www.youtube.com/watch?v=GBNHGi36nlM ]
Another way to get involved this month: getting acting on social media when you’re not working on the ground! Use thelsalabs.com/dia/track.jsp?key=-1&url_num=6&url=https%3A%2F%2Ftwitter.com%2Fsearch%3Fq%3D%2523endvictimblaming%26src%3Dtypd ] and/dia/track.jsp?key=-1&url_num=7&url=https%3A%2F%2Ftwitter.com%2Fsearch%3Fq%3D%2523IDAVB%26src%3Dtypd ] hashtags on April 3, the International Day Against Victim Blaming,dia/track.jsp?key=-1&url_num=8&url=https%3A%2F%2Ftwitter.com%2Fsearch%3Fq%3D%2523SAAM%26src%3Dtyah ] hashtag on April 7, the day of action against sexual assault. Check our blog for SAAM-related posts all month and follow us on Twitter, Instagram, and Facebook to get updates about actions you can bring to campus and what we’re doing here at Campus HQ to end rape culture. Want to contribute a guest blog post about SAAM this month? Shoot us an email! [ mailto:campusteam@feminist.org?subject=SAAM%20blog%20post ]
For equality,
The Feminist Campus Team
“Alyssa, Edwith, duVergne, and Nancy”
* *


Ruby Security¶ ↑
The Ruby programming language is large and complex and there are many security pitfalls often encountered by newcomers and experienced Rubyists alike.
This document aims to discuss many of these pitfalls and provide more secure alternatives where applicable.
Please check the full list of publicly known CVEs and how to correctly report a security vulnerability, at: www.ruby-lang.org/en/security/ Japanese version is here: www.ruby-lang.org/ja/security/
Security vulnerabilities should be reported via an email to<EMAIL_ADDRESS>(the PGP public key), which is a private mailing list. Reported problems will be published after fixes.
$SAFE
¶ ↑
Ruby provides a mechanism to restrict what operations can be performed by
Ruby code in the form of the $SAFE
variable.
However, $SAFE
does not provide a secure environment for
executing untrusted code.
If you need to execute untrusted code, you should use an operating system level sandboxing mechanism. On Linux, ptrace or LXC can be used to sandbox potentially malicious code. Other similar mechanisms exist on every major operating system.
Marshal.load
¶ ↑
Ruby's Marshal
module provides methods for serializing and
deserializing Ruby object trees to and from a binary data format.
Never use Marshal.load
to deserialize untrusted or user
supplied data. Because Marshal
can deserialize to almost any
Ruby object and has full control over instance variables, it is possible to
craft a malicious payload that executes code shortly after deserialization.
If you need to deserialize untrusted data, you should use JSON as it is only capable of returning 'primitive' types such as strings, arrays, hashes, numbers and nil. If you need to deserialize other classes, you should handle this manually. Never deserialize to a user specified class.
YAML¶ ↑
YAML is a popular human readable data serialization format used by many Ruby programs for configuration and database persistence of Ruby object trees.
Similar to Marshal
, it is able to deserialize into arbitrary
Ruby classes. For example, the following YAML data will create an
ERB
object when deserialized:
!ruby/object:ERB src: puts `uname`
Because of this, many of the security considerations applying to Marshal are also applicable to YAML. Do not use YAML to deserialize untrusted data.
Symbols¶ ↑
Symbols are often seen as syntax sugar for simple strings, but they play a much more crucial role. The MRI Ruby implementation uses Symbols internally for method, variable and constant names. The reason for this is that symbols are simply integers with names attached to them, so they are faster to look up in hashtables.
Starting in version 2.2, most symbols can be garbage collected; these are
called mortal symbols. Most symbols you create (e.g. by calling
to_sym
) are mortal.
Immortal symbols on the other hand will never be garbage collected. They are created when modifying code:
-
defining a method (e.g. with
define_method
), -
setting an instance variable (e.g. with
instance_variable_set
), -
creating a variable or constant (e.g. with
const_set
)
C extensions that have not been updated and are still calling `SYM2ID` will
create immortal symbols. Bugs in 2.2.0: send
and +__send__+
also created immortal symbols, and calling methods with keyword arguments
could also create some.
Don't create immortal symbols from user inputs. Otherwise, this would allow a user to mount a denial of service attack against your application by flooding it with unique strings, which will cause memory to grow indefinitely until the Ruby process is killed or causes the system to slow to a halt.
While it might not be a good idea to call these with user inputs, methods
that used to be vulnerable such as to_sym
,
respond_to?
, method
,
instance_variable_get
, const_get
, etc. are no
longer a threat.
Regular expressions¶ ↑
Ruby's regular expression syntax has some minor differences when
compared to other languages. In Ruby, the ^
and $
anchors do not refer to the beginning and end of the string, rather the
beginning and end of a line.
This means that if you're using a regular expression like
/^[a-z]+$/
to restrict a string to only letters, an attacker
can bypass this check by passing a string containing a letter, then a
newline, then any string of their choosing.
If you want to match the beginning and end of the entire string in Ruby,
use the anchors \A
and \z
.
eval
¶ ↑
Never pass untrusted or user controlled input to eval
.
Unless you are implementing a REPL like irb
or
pry
, eval
is almost certainly not what you want.
Do not attempt to filter user input before passing it to eval
- this approach is fraught with danger and will most likely open your
application up to a serious remote code execution vulnerability.
send
¶ ↑
'Global functions' in Ruby (puts
, exit
,
etc.) are actually private instance methods on Object
. This
means it is possible to invoke these methods with send
, even
if the call to send
has an explicit receiver.
For example, the following code snippet writes “Hello world” to the terminal:
1.send(:puts, "Hello world")
You should never call send
with user supplied input as the
first parameter. Doing so can introduce a denial of service vulnerability:
foo.send(params[:bar]) # params[:bar] is "exit!"
If an attacker can control the first two arguments to send
,
remote code execution is possible:
# params is { :a => "eval", :b => "...ruby code to be executed..." } foo.send(params[:a], params[:b])
When dispatching a method call based on user input, carefully verify that the method name. If possible, check it against a whitelist of safe method names.
Note that the use of public_send
is also dangerous, as
send
itself is public:
1.public_send("send", "eval", "...ruby code to be executed...")
DRb¶ ↑
As DRb allows remote clients to invoke arbitrary methods, it is not suitable to expose to untrusted clients.
When using DRb, try to avoid exposing it over the
network if possible. If this isn't possible and you need to expose DRb to the world, you must configure
an appropriate security policy with DRb::ACL
.


A portal to help SMEs around the world deal with the challenges of GDPR (the General Data Protection Regulation which comes into effect in May 2018).
Capabilities will include:
Terms and conditions of use
Welcome to our website. If you continue to browse and use this website you are agreeing to comply with and be bound by the following terms and conditions of use, which together with our privacy policy govern GDPR Portal's relationship with you in relation to this website.
GDPR Portal is a trading name of Gibcroft Technology Limited.
The term 'GDPR Portal’, ‘Gibcroft Technology’ or 'us' or 'we' refers to the owner of the website whose registered office is 1 Vincent Square, London, SW1P 2PN. The term 'you' refers to the user or viewer of our website.
The use of this website is subject to the following terms of use:
The content of the pages of this website is for your general information and use only. It is subject to change without notice.
Neither we nor any third parties provide any warranty or guarantee as to the accuracy, timeliness, performance, completeness or suitability of the information and materials found or offered on this website for any particular purpose. You acknowledge that such information and materials may contain inaccuracies or errors and we expressly exclude liability for any such inaccuracies or errors to the fullest extent permitted by law.
Your use of any information or materials on this website is entirely at your own risk, for which we shall not be liable. It shall be your own responsibility to ensure that any products, services or information available through this website meet your specific requirements.
This website contains material which is owned by or licensed to us. This material includes, but is not limited to, the design, layout, look, appearance and graphics. Reproduction is prohibited other than in accordance with the copyright notice, which forms part of these terms and conditions.
All trademarks reproduced in this website which are not the property of, or licensed to, the operator are acknowledged on the website.
Unauthorised use of this website may give rise to a claim for damages and/or be a criminal offence.
Your use of this website and any dispute arising out of such use of the website is subject to the laws of England and Wales.
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Your right to privacy is an important concern to us and we wish to protect the privacy of the personally identifiable information you share with us. We also believe it is important to inform you about how we will use your personal data, and to give you choices about how your data will be used. Therefore, we encourage you to read this Privacy Policy carefully.
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public class HandPlayer
extends java.lang.Object
| Constructor and Description |
|---|
HandPlayer(int id,
java.util.ArrayList<Card> hand)
Constructor of HandPlayer
|
| Modifier and Type | Method and Description |
|---|---|
void |
addCard(Card card)
Add a card in the hand of a player
|
static boolean |
choiceActionIsOk(java.lang.String s)
Deprecated.
|
Card |
discard(Card c)
Only discard from the hand of a player.
|
Card |
discard(int place) |
Dialogue |
getMemory()
Getter of @see memory
|
static java.lang.String |
readActionPlayer()
read the next action of a player.
|
void |
setMemory(Dialogue d)
Setter of @see memory
|
java.lang.String |
showHidden()
Called for print the card of a player when it is his turn.
|
void |
swap(Card c,
Card c1)
Swap two cards in the hand of a player
|
void |
swap(int c,
int c1) |
java.lang.String |
toString()
Represent the hand of a player.
|
public HandPlayer(int id, java.util.ArrayList<Card> hand)
id
- id of the playerhand
- cards which will be in the hand of a playerjava.lang.IllegalArgumentException
- when the id of a player if inferior to 1or hand of a player is empty at the creation.public Dialogue getMemory()
public void setMemory(Dialogue d)
d
- dialogue to actualizepublic Card discard(Card c)
c
- Cards to discardpublic Card discard(int place)
place
- where the card ispublic void swap(Card c, Card c1)
c
- first card to swapc1
- second card to swappublic void swap(int c, int c1)
c
- first card to swapc1
- second card to swapswap
public void addCard(Card card)
card
- to addpublic java.lang.String showHidden()
public java.lang.String toString()
toString
in class java.lang.Object
public static java.lang.String readActionPlayer() throws java.io.IOException
java.io.IOException
- when got reading problempublic static boolean choiceActionIsOk(java.lang.String s)
s
- string to check


This function should not be used in Microsoft Excel 97 or later because sound notes are available only in Microsoft Excel 95 or earlier versions.
Records sound into or erases sound from a cell note or imports sound from another file into a cell note. This function requires that you have recording hardware installed in your computer, and you must be running Microsoft Windows version 3.1 or later, or Apple system software version 6.07 or later.
Syntax 1
Recording or erasing sound
SOUND.NOTE(cell_ref, erase_snd)
Syntax 2
Importing sound from another file
SOUND.NOTE(cell_ref, file_text, resource)
Cell_ref is a reference to the cell containing a note into which you want to record or import sounds or from which you want to erase a sound.
Erase_snd is a logical value specifying whether to erase the sound in the note. If erase_snd is TRUE, Microsoft Excel erases only the sound from the note. If FALSE or omitted, Microsoft Excel displays the Record dialog box so that you can record sound into the note.
File_text is the name of a file containing sounds.
Resource is the number or name of a sound resource in file_text that you want to import into your note.
This argument applies only to Microsoft Excel for the Macintosh.
If resource is omitted, Microsoft Excel uses the first resource in the file.
If the file does not contain a sound resource with the specified name or number, Microsoft Excel halts the macro and displays an error message.
Remarks
To find out if a cell has sound attached to it, use GET.CELL(47).
Sounds notes are not available in Microsoft Excel 97 or later.
Examples
The following macro formula erases the sound, if present, from cell A1 on the active sheet:
SOUND.NOTE(!$A$1, TRUE)
The following macro formula displays the Record dialog box so that you can record sound into a note for cell A1 on the active sheet:
SOUND.NOTE(!$A$1)
In Microsoft Excel for Windows, the following macro formula imports the sound from a file named CHIMES.WAV into a note for the cell named Doorbell on the active sheet:
SOUND.NOTE(!Doorbell, "C:\SOUNDS\CHIMES.WAV")
In Microsoft Excel for the Macintosh, the following macro formula imports a sound called Chimes from a file named SOFT SOUNDS into a note for the cell named Doorbell on the active sheet:
SOUND.NOTE(!Doorbell, "HARD DISK:SOUNDS:SOFT SOUNDS", "Chimes")
Related Functions
NOTE Creates or changes a cell note
SOUND.PLAY Plays the sound from a cell note or a file
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