math::probopt - Probabilistic optimisation methods
The purpose of the math::probopt package is to provide various optimisation algorithms that are based on probabilistic techniques. The results of these algorithms may therefore vary from one run to the next. The algorithms are all well-known and well described and proponents generally claim they are efficient and reliable.
As most of these algorithms have one or more tunable parameters or even variations, the interface to each accepts options to set these parameters or the select the variation. These take the form of key-value pairs, for instance, -iterations 100.
This manual does not offer any recommendations with regards to these algorithms, nor does it provide much in the way of guidelines for the parameters. For this we refer to online articles on the algorithms in question.
A few notes, however:
With the exception of LIPO, the algorithms are capable of dealing with irregular (non-smooth) and even discontinuous functions.
The results depend on the random number seeding and are likely not to be very accurate, especially if the function varies slowly in the vicinty of the optimum. They do give a good starting point for a deterministic algorithm.
The collection consists of the following algorithms:
PSO - particle swarm optimisation
SCE - shuffled complexes evolution
DE - differential evolution
LIPO - Lipschitz optimisation
The various procedures have a uniform interface:
set result [::math::probopt::algorithm function bounds args]
The arguments have the following meaning:
The argument function is the name of the procedure that evaluates the function. Its interface is:
set value [function coords]
where coords is a list of coordinates at which to evaluate the function. It is supposed to return the function value.
The argument bounds is a list of pairs of minimum and maximum for each coordinate. This list implicitly determines the dimension of the coordinate space in which the optimum is to be sought, for instance for a function like x**2 + (y-1)**4, you may specify the bounds as {{-1 1} {-1 1}}, that is, two pairs for the two coordinates.
The rest (args) consists of zero or more key-value pairs to specify the options. Which options are supported by which algorithm, is documented below.
The result of the various optimisation procedures is a dictionary containing at least the following elements:
optimum-coordinates is a list containing the coordinates of the optimum that was found.
optimum-value is the function value at those coordinates.
evaluations is the number of function evaluations.
best-values is a list of successive best values, obtained as part of the iterations.
The algorithms in the package are the following:
The "particle swarm optimisation" algorithm uses the idea that the candidate optimum points should swarm around the best point found so far, with variations to allow for improvements.
It recognises the following options:
-swarmsize number: Number of particles to consider (default: 50)
-vweight value: Weight for the current "velocity" (0-1, default: 0.5)
-pweight value: Weight for the individual particle's best position (0-1, default: 0.3)
-gweight value: Weight for the "best" overall position as per particle (0-1, default: 0.3)
-type local/global: Type of optimisation
-neighbours number: Size of the neighbourhood (default: 5, used if "local")
-iterations number: Maximum number of iterations
-tolerance value: Absolute minimal improvement for minimum value
The "shuffled complex evolution" algorithm is an extension of the Nelder-Mead algorithm that uses multiple complexes and reorganises these complexes to find the "global" optimum.
It recognises the following options:
-complexes number: Number of particles to consider (default: 2)
-mincomplexes number: Minimum number of complexes (default: 2; not currently used)
-newpoints number: Number of new points to be generated (default: 1)
-shuffle number: Number of iterations after which to reshuffle the complexes (if set to 0, the default, a number will be calculated from the number of dimensions)
-pointspercomplex number: Number of points per complex (if set to 0, the default, a number will be calculated from the number of dimensions)
-pointspersubcomplex number: Number of points per subcomplex (used to select the best points in each complex; if set to 0, the default, a number will be calculated from the number of dimensions)
-iterations number: Maximum number of iterations (default: 100)
-maxevaluations number: Maximum number of function evaluations (when this number is reached the iteration is broken off. Default: 1000 million)
-abstolerance value: Absolute minimal improvement for minimum value (default: 0.0)
-reltolerance value: Relative minimal improvement for minimum value (default: 0.001)
The "differential evolution" algorithm uses a number of initial points that are then updated using randomly selected points. It is more or less akin to genetic algorithms. It is controlled by two parameters, factor and lambda, where the first determines the update via random points and the second the update with the best point found sofar.
It recognises the following options:
-iterations number: Maximum number of iterations (default: 100)
-number number: Number of point to work with (if set to 0, the default, it is calculated from the number of dimensions)
-factor value: Weight of randomly selected points in the updating (0-1, default: 0.6)
-lambda value: Weight of the best point found so far in the updating (0-1, default: 0.0)
-crossover value: Fraction of new points to be considered for replacing the old ones (0-1, default: 0.5)
-maxevaluations number: Maximum number of function evaluations (when this number is reached the iteration is broken off. Default: 1000 million)
-abstolerance value: Absolute minimal improvement for minimum value (default: 0.0)
-reltolerance value: Relative minimal improvement for minimum value (default: 0.001)
The "Lipschitz optimisation" algorithm uses the "Lipschitz" property of the given function to find a maximum in the given bounding box. There are two variants, lipoMax assumes a fixed estimate for the Lipschitz parameter.
It recognises the following options:
-iterations number: Number of iterations (equals the actual number of function evaluations, default: 100)
-lipschitz value: Estimate of the Lipschitz parameter (default: 10.0)
The "adaptive Lipschitz optimisation" algorithm uses the "Lipschitz" property of the given function to find a maximum in the given bounding box. The adaptive variant actually uses two phases to find a suitable estimate for the Lipschitz parameter. This is controlled by the "Bernoulli" parameter.
When you specify a large number of iterations, the algorithm may take a very long time to complete as it is trying to improve on the Lipschitz parameter and the chances of hitting a better estimate diminish fast.
It recognises the following options:
-iterations number: Number of iterations (equals the actual number of function evaluations, default: 100)
-bernoulli value: Parameter for random decisions (exploration versus exploitation, default: 0.1)
The various algorithms have been described in on-line publications. Here are a few:
PSO: Maurice Clerc, Standard Particle Swarm Optimisation (2012) https://hal.archives-ouvertes.fr/file/index/docid/764996/filename/SPSO_descriptions.pdf
Alternatively: https://en.wikipedia.org/wiki/Particle_swarm_optimization
SCE: Qingyuan Duan, Soroosh Sorooshian, Vijai K. Gupta, Optimal use offo the SCE-UA global optimization method for calibrating watershed models (1994), Journal of Hydrology 158, pp 265-284
DE: Rainer Storn and Kenneth Price, Differential Evolution - A simple and efficient adaptivescheme for globaloptimization over continuous spaces (1996)
LIPO: Cedric Malherbe and Nicolas Vayatis, Global optimization of Lipschitz functions, (june 2017)
Mathematics


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{% include "head.html" %}
{{ sample_name }}
{% if log_file_path is none %} Log file {% else %} Log file {% endif %} {% if profile_file_path is none %} Pipeline profile {% else %} Pipeline profile {% endif %} {% if commands_file_path is none %} Pipeline commands {% else %} Pipeline commands {% endif %} {% if stats_file_path is none %} Stats summary file {% else %} Stats summary file {% endif %}
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classes, workshops, and teaching material
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Introduction to Computing
CS 110
Fall 2021: Teaching Assistant
This course serves as an introduction to computer programming, covering key concepts involved in using a high-level language and the program development process. The instructor for this course is Swami Iyer.
- Course materials, including the syllabus, lecture notes, and assignments, can be accessed here.
- For class discussions and questions, please visit our Piazza page.
- Assignments and grading can be tracked via Gradescope.
Artificial intelligence
CS 670
Spring 2019: Teaching Assistant
This is a graduate-level course on artificial intelligence, designed for master’s and PhD students, and is instructed by Prof. Wei Ding.
- I was responsible for the creation and grading of individual assignments:
- Additionally, I developed and evaluated a term project focused on - time series prediction:
- Furthermore, I presented a in-class lectures related to Generative_Adversarial_Networks(GAN):
- The course materials can be accessed here.
CS Seminar
CS Seminar
Fall 2017, Spring 2018, Summer 2018, Fall 2018: Lecturer
The CS Seminar provides academic support to students enrolled in various computer science courses, such as Intermediate Computing with Data Structures (CS210), Advanced Data Structures and Algorithms (CS310), and Theory of Computation (CS420). Following the program of study detailed in each course syllabus, it offers customized tutoring on an individual basis or in small groups to cater to specific student needs. By attending the CS Seminar, students benefit from additional practice with content specific to their respective courses.
- I delivered weekly 60-minute presentations, covering the material for computer science courses.
- I dedicated 30 minutes to offering practical guidance and answering specific questions.
- I also allocated 30 minutes to previewing upcoming course content, assignments, and discussing potential future challenges.
- syllabus:
Artificial intelligence
CS 670
Fall 2017: Teaching Assistant
This is a graduate-level course on artificial intelligence, designed for master’s and PhD students, and is instructed by Prof.Wei Ding.
- I was responsible for the creation and grading of individual assignments:
- Additionally, I developed and evaluated a term project focused on feature selection in extreme rainfall forecasting:
- Furthermore, I presented two in-class lectures related to extreme rainfall forecasting using feature selection. The topics included:
- The course materials can be accessed here.
Science Gateway Seminar
CS 187
Spring 2017: Mentor
This course, a freshman seminar within the College of Science and Mathematics, is centered on the theme of inquiry-based learning for both students and faculty. It is taught by Prof. Wei Ding.
Big Data Analytics
CS 697
Fall 2016: Teaching Assistant
This is a graduate-level course on big data analysis, instructed by Prof. Wei Ding.
- I developed and evaluated a term project focused on - crime hot-spots forecasting:
- I presented several in-class lectures related to crime hot-spots forecasting and Arcmap usage. The topics included:
- The course materials can be accessed here.
Introduction to Computing
Fall 2021: Teaching Assistant
This course serves as an introduction to computer programming, covering key concepts involved in using a high-level language and the program development process. The instructor for this course is Swami Iyer.
- Course materials, including the syllabus, lecture notes, and assignments, can be accessed here.
- For class discussions and questions, please visit our Piazza page.
- Assignments and grading can be tracked via Gradescope.
Artificial intelligence
Spring 2019: Teaching Assistant
This is a graduate-level course on artificial intelligence, designed for master’s and PhD students, and is instructed by Prof. Wei Ding.
- I was responsible for the creation and grading of individual assignments:
- Additionally, I developed and evaluated a term project focused on - time series prediction:
- Furthermore, I presented a in-class lectures related to Generative_Adversarial_Networks(GAN):
- The course materials can be accessed here.
CS Seminar
Fall 2017, Spring 2018, Summer 2018, Fall 2018: Lecturer
The CS Seminar provides academic support to students enrolled in various computer science courses, such as Intermediate Computing with Data Structures (CS210), Advanced Data Structures and Algorithms (CS310), and Theory of Computation (CS420). Following the program of study detailed in each course syllabus, it offers customized tutoring on an individual basis or in small groups to cater to specific student needs. By attending the CS Seminar, students benefit from additional practice with content specific to their respective courses.
- I delivered weekly 60-minute presentations, covering the material for computer science courses.
- I dedicated 30 minutes to offering practical guidance and answering specific questions.
- I also allocated 30 minutes to previewing upcoming course content, assignments, and discussing potential future challenges.
- syllabus:
Artificial intelligence
Fall 2017: Teaching Assistant
This is a graduate-level course on artificial intelligence, designed for master’s and PhD students, and is instructed by Prof.Wei Ding.
- I was responsible for the creation and grading of individual assignments:
- Additionally, I developed and evaluated a term project focused on feature selection in extreme rainfall forecasting:
- Furthermore, I presented two in-class lectures related to extreme rainfall forecasting using feature selection. The topics included:
- The course materials can be accessed here.
Science Gateway Seminar
Spring 2017: Mentor
This course, a freshman seminar within the College of Science and Mathematics, is centered on the theme of inquiry-based learning for both students and faculty. It is taught by Prof. Wei Ding.
Big Data Analytics
Fall 2016: Teaching Assistant
This is a graduate-level course on big data analysis, instructed by Prof. Wei Ding.
- I developed and evaluated a term project focused on - crime hot-spots forecasting:
- I presented several in-class lectures related to crime hot-spots forecasting and Arcmap usage. The topics included:
- The course materials can be accessed here.


HTML is what forms the web. It contains text (what you see) and markup (what determines how it looks)
TAGStags are how a computer and a browser will read information the way we want it. Each tag means something else and is always enclosed by <>. Most of the times we must place a tag at the beginning and close it at the end of the element you want to affect.
some examples of tags are:we don't need to remember all these tags, they are easily found online in websites like this one
In order to incorporate links, images or video elements into our HTML, different tags and formulas must be used. Find some examples heresome tags such as break or paragraph might have similar effects on content and text since they both separate sentences bringing them to a different level. The difference is that the first one is called inline while the last one is referred to as block.
DIFFERENCE BETWEEN INLINE AND BLOCKThese are the basic elements, but a complete HTML would include a doctype, html, head, title, body and it will look something like this


AP Top Sports News at 5:40 a.m. EST
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US eliminated from Davis Cup Finals despite win over Italy
Browns' Garrett awaits ruling after hearing for suspension
Steelers' Rudolph: ‘No acceptable excuse' for role in brawl
Doncic has 33 first-half points, Mavs hammer Warriors 142-94


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ephemeral
C# Library to handle time intervals (composite start and end)
- Support for open and closed (time) intervals.
- Support for common operations like Covers(), Intersect(), Join(), etc..
- Support for collections of intervals.
Interval Example
var now = DateTimeOffset.UtcNow;
Interval yesterday = Interval.CreateOpen(now.AddDays(-1), now);
Interval today = yesterday.Shift(TimeSpan.FromDays(1));
yesterday.Overlaps(today); // returns true
Interval Collection Example
IDisjointIntervalSet collection = new DisjointIntervalSet();
collection.Add(yesterday);
collection.Add(today);
collection.Start == yesterday.Start; // true
collection.End == today.End; // true
var collection2 = yesterday.Union(today);
collection1.equals(collection2); // true
var consolidatedCollection = collection2.Consolidate();
collection2.Count(); // 2
consolidatedCollection.Count(); // 1


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General Knowledge Quiz
Answer the questions carefully
1)The capital of India is:
2)The star of the Solar System is:
3)1+1=
2
1
11
0110
4)Continents of the world include:
Asia
India
Australia
China
5)Choose for the following:
A)Current Prime Minister of India:
John Cena
Narendra Modi
Powerstar
Ram Nath Kovind
B)who is the best faculty for Software Engineering?
Ilakiyaselvan Sir
None
Finish Test
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JSDraw2 - A Javascript Chemical Structure Editor/Viewer
Editor:
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Get Molfile
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All Classes
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<unnamed package>
mnist
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network.activationFunctions
network.connections
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Hello there! I'm Kunyi Lu.
I'm currently a software development engineer at Amazon.💡
I have been working in machine learning and computer vision field for 4 years.💡
I just graduated from University of Michigan
I led a 5-member team to develop an Android APP that can identify the handwritten phone number on express sheet and notify the receiver to take delivery by sending message automatically.
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I implemented a novel deep network for video frame inpainting which generates more accurate and visually pleasing predictions than multiple strong baselines. I designed multiple experiments to demonstrate our model's ability to perform well on complex video depicting challenging scenes and a wide variety of actions.


public class PIDController
extends java.lang.Object
| Constructor and Description |
|---|
PIDController(double Kp,
double Ki,
double Kd)
Allocates a PIDController with the given constants for kp, ki, and kd.
|
PIDController(double setpoint,
double Kp,
double Ki,
double Kd)
Allocates a PIDController with the given constants for kp, ki, and kd and a default setpoint.
|
PIDController(double setpoint,
double tolerance,
double Kp,
double Ki,
double Kd)
Allocates a PIDController with the given constants for kp, ki, and kd and a default setpoint and tolerance.
|
PIDController(double setpoint,
double tolerance,
double Kp,
double Ki,
double Kd,
double Kf)
Allocates a PIDController with the given constants for kp, ki, and kd and a default setpoint and tolerance.
|
| Modifier and Type | Method and Description |
|---|---|
boolean |
atSetpoint()
Returns true if the error is within the tolerance of the setpoint.
|
static double |
clamp(double value,
double low,
double high) |
double |
getD(double input)
Returns the next output of the PID controller using only derivative gain.
|
double |
getError()
Returns the difference between the setpoint and the measurement.
|
double |
getF()
Returns the feed forward of the system.
|
double |
getI(double input)
Returns the next output of the PID controller using only integral gain.
|
double |
getKd()
Get the Differential coefficient.
|
double |
getKf()
Get the Feed Forward coefficient.
|
double |
getKi()
Get the Integral coefficient.
|
double |
getKp()
Get the Proportional coefficient.
|
double |
getP(double input)
Returns the next output of the PID controller using only proportional gain.
|
double |
getPD(double input)
Returns the next output of the PID controller using both proportional and derivative gain.
|
double |
getPF(double input)
Returns the next output of the PID controller using both proportional and feed forward gain.
|
double |
getPI(double input)
Returns the next output of the PID controller using both proportional and integral gain.
|
double |
getPID(double input)
Returns the next output of the PID controller using proportional, integral and derivative gain.
|
double |
getPIDF(double input)
Returns the next output of the PID controller using both proportional, integral, derivative and feed forward gain.
|
double |
getSetpoint()
Returns the current setpoint of the PIDController.
|
double |
getTolerance()
Returns the current tolerance of the PIDController.
|
void |
setAll(double Kp,
double Ki,
double Kd)
Sets the PID Controller gain parameters.
|
void |
setKd(double Kd)
Sets the Differential coefficient of the PID controller gain.
|
void |
setKf(double Kf)
Sets the Feed Forward coefficient of the PID controller gain.
|
void |
setKi(double Ki)
Sets the Integral coefficient of the PID controller gain.
|
void |
setKp(double Kp)
Sets the Proportional coefficient of the PID controller gain.
|
void |
setSetpoint(double setpoint)
Sets the setpoint for the PIDController.
|
void |
setTolerance(double tolerance)
Sets the error which is considered tolerable for use with atSetpoint().
|
public PIDController(double setpoint, double tolerance, double Kp, double Ki, double Kd, double Kf)
setpoint
- The period between controller updates in secondstolerance
- The period between controller updates in seconds..Kp
- The proportional coefficient.Ki
- The integral coefficient.Kd
- The derivative coefficient.Kf
- the feed forward coefficient.public PIDController(double setpoint, double tolerance, double Kp, double Ki, double Kd)
setpoint
- The period between controller updates in secondstolerance
- The period between controller updates in seconds..Kp
- The proportional coefficient.Ki
- The integral coefficient.Kd
- The derivative coefficient.public PIDController(double setpoint, double Kp, double Ki, double Kd)
setpoint
- The control loop's setpoint.Kp
- The proportional coefficient.Ki
- The integral coefficient.Kd
- The derivative coefficient.public PIDController(double Kp, double Ki, double Kd)
Kp
- The proportional coefficient.Ki
- The integral coefficient.Kd
- The derivative coefficient.public double getP(double input)
input
- the current input of the control looppublic double getI(double input)
input
- the current input of the control looppublic double getD(double input)
input
- the current input of the control looppublic double getF()
public double getPI(double input)
input
- the current input of the control looppublic double getPD(double input)
input
- the current input of the control looppublic double getPF(double input)
input
- the current input of the control looppublic double getPID(double input)
input
- the current input of the control looppublic double getPIDF(double input)
input
- the current input of the control looppublic boolean atSetpoint()
This will return false until at least one input value has been computed.
public void setSetpoint(double setpoint)
setpoint
- The desired setpoint.public void setTolerance(double tolerance)
tolerance
- Position error which is tolerable.public void setKp(double Kp)
Kp
- proportional coefficientpublic void setKi(double Ki)
Ki
- integral coefficientpublic void setKd(double Kd)
Kd
- differential coefficientpublic void setKf(double Kf)
Kf
- feed forward coefficientpublic void setAll(double Kp, double Ki, double Kd)
Set the proportional, integral, and differential coefficients.
Kp
- The proportional coefficient.Ki
- The integral coefficient.Kd
- The derivative coefficient.public double getSetpoint()
public double getTolerance()
public double getError()
public double getKp()
public double getKi()
public double getKd()
public double getKf()
public static double clamp(double value, double low, double high)


A group module
Brief description. If this is not present, the detailed description gets interpreted as brief in 1.8.18. FFS.
All entries inside should have include information. (Unless the includes are disabled globally or the file is not documented.)
Enums
- enum Enum { }
- An enum.
Typedefs
- using Int = int
- A typedef.
Functions
- void foo()
- A function.
Variables
- const int Var constexpr
- A variable.
Defines
- #define A_DEFINE
- A define.


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Standard JDK Tools and Utilities
Experimental JDK Tools and Utilities
NOTE - The tools described in this section are unsupported and experimental in nature and should be used with that in mind. They might not be available in future JDK versions.
Troubleshooting Documentation
NOTE - The Windows and Solaris, Linux, and OS X references pages for some tools have minor differences in configuration and usage -- for example, the character used to specify directory separators may be different.
The following documents contain important information you will need to know to get the most out of the JDK tools.
| Document Type | Platform |
|---|---|
| JDK File Structure | [Solaris, Linux, and OS X] [Windows] |
| Setting the Classpath | [Solaris, Linux, and OS X] [Windows] |
| How Classes are Found | [All supported platforms] |
The man page for each tool reflects the latest behavior for that tool, but the following page details the tools changes specific to a release.
These tools are the foundation of the JDK. They are the tools you use to create and build applications.
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| appletviewer | Run and debug applets without a web browser. | [Solaris, Linux, and OS X] [Windows] |
| extcheck | Utility to detect Jar conflicts. | [Solaris, Linux, and OS X] [Windows] |
| jar | Create and manage Java Archive (JAR) files. See Java Archive Files page for the JAR specification. |
[Solaris, Linux, and OS X] [Windows] |
| java | The launcher for Java applications. In this
release, a single launcher is used both for development and
deployment. The old deployment launcher, jre, is no longer provided. |
[Solaris, Linux, and OS X] [Windows] |
| javac | The compiler for the Java programming language. | [Solaris, Linux, and OS X] [Windows] |
| javadoc | API documentation generator. See Javadoc Tool page for doclet and taglet APIs. |
[Solaris, Linux, and OS X] [Windows] |
| javah | C header and stub generator. Used to write native methods. | [Solaris, Linux, and OS X] [Windows] |
| javap | Class file disassembler | [Solaris, Linux, and OS X] [Windows] |
| jdb | The Java Debugger. See JPDA for the debugger architecture specifications. |
[Solaris, Linux, and OS X] [Windows] |
| jdeps | Java class dependency analyzer | [Solaris, Linux, and OS X] [Windows] |
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| keytool | Manage keystores and certificates. | [Solaris, Linux, and OS X] [Windows] |
| jarsigner | Generate and verify JAR signatures. | [Solaris, Linux, and OS X] [Windows] |
| policytool | GUI tool for managing policy files. | [Solaris, Linux, and OS X] [Windows] |
These security tools help you obtain, list, and manage Kerberos tickets.
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| kinit | Tool for obtaining Kerberos v5 tickets. Equivalent functionality is available on the Solaris operating system via the kinit tool. For example, for Solaris 11, see the kinit reference page. | [Windows] |
| klist | Command-line tool to list entries in credential cache and key tab. Equivalent functionality is available on the Solaris operating system via the klist tool. For example, for Solaris 11, see the klist reference page. | [Windows] |
| ktab | Command-line tool to help the user manage entries in the key table. Equivalent functionality is available on the Solaris operating system via the kadmin tool. For example, for Solaris 11, see the kadmin reference page. | [Windows] |
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| native2ascii | Convert text to Unicode Latin-1. | [Solaris, Linux, and OS X] [Windows] |
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| rmic | Generate stubs and skeletons for remote objects. | [Solaris, Linux, and OS X] [Windows] |
| rmiregistry | Remote object registry service. | [Solaris, Linux, and OS X] [Windows] |
| rmid | RMI activation system daemon. | [Solaris, Linux, and OS X] [Windows] |
| serialver | Return class serialVersionUID. | [Solaris, Linux, and OS X] [Windows] |
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| tnameserv | Provides access to the naming service. | [Solaris, Linux, and OS X] [Windows] |
| idlj | Generates .java files that map an OMG IDL interface and enable an application written in the Java programming language to use CORBA functionality. | [Solaris, Linux, and OS X] [Windows] |
| orbd | Provides support for clients to transparently locate and invoke persistent objects on servers in the CORBA environment. ORBD is used instead of the Transient Naming Service, tnameserv. ORBD includes both a Transient Naming Service and a Persistent Naming Service. The orbd tool incorporates the functionality of a Server Manager, an Interoperable Naming Service, and a Bootstrap Name Server. When used in conjunction with the servertool, the Server Manager locates, registers, and activates a server when a client wants to access the server. | [Solaris, Linux, and OS X] [Windows] |
| servertool | Provides ease-of-use interface for the application programmers to register, unregister, startup, and shutdown a server. | [Solaris, Linux, and OS X] [Windows] |
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| javapackager | Performs tasks related to packaging and signing Java and JavaFX applications. | [Linux and OS X] [Windows] |
| pack200 | Transforms a JAR file into a compressed
pack200 file using the Java gzip
compressor. The compressed packed files are highly compressed JARs,
which can be directly deployed, saving bandwidth and reducing
download time. |
[Solaris, Linux, and OS X] [Windows] |
| unpack200 | Transforms a packed file produced by
pack200 into a JAR file. |
[Solaris, Linux, and OS X] [Windows] |
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| javaws | Command line tool for launching Java Web Start and
setting various options. See Java Web Start Guide for more information. |
[Solaris, Linux, and OS X] [Windows] |
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| jcmd | JVM Diagnostic Commands tool - Sends diagnostic command requests to a running Java Virtual Machine. | [Solaris, Linux, and OS X] [Windows] |
| jconsole | A JMX-compliant graphical tool for monitoring a
Java virtual machine. It can monitor both local and remote JVMs. It
can also monitor and manage an application. See Monitoring and Management for the Java Platform for more information. |
[Solaris, Linux, and OS X] [Windows] |
| jmc | The Java Mission Control (JMC) client includes tools to monitor and manage your Java application without introducing the performance overhead normally associated with these types of tools. | [Solaris, Linux, and OS X] [Windows] |
| jvisualvm | A graphical tool that provides detailed information about the Java technology-based applications (Java applications) while they are running in a Java Virtual Machine. Java VisualVM provides memory and CPU profiling, heap dump analysis, memory leak detection, access to MBeans, and garbage collection. See Java VisualVM for more information. | [Solaris, Linux, and OS X] [Windows] |
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| schemagen | Schema generator for Java Architecture for XML Binding. | [Solaris, Linux, and OS X] [Windows] |
| wsgen | Tool to generate JAX-WS portable artifacts. | [Solaris, Linux, and OS X] [Windows] |
| wsimport | Tool to generate JAX-WS portable artifacts. | [Solaris, Linux, and OS X] [Windows] |
| xjc | Binding compiler for Java Architecture for XML Binding. | [Solaris, Linux, and OS X] [Windows] |
You can use the following tools to monitor JVM performance statistics. The tools described in this section are unsupported and experimental, and should be used with that in mind. They may not be available in future JDK versions.
These tools are supported on all platforms except Windows 98 and Windows ME.
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| jps | Experimental: JVM Process Status Tool - Lists instrumented HotSpot Java virtual machines on a target system. | [Solaris, Linux, and OS X] [Windows] |
| jstat | Experimental: JVM Statistics Monitoring Tool - Attaches to an instrumented HotSpot Java virtual machine and collects and logs performance statistics as specified by the command line options. | [Solaris, Linux, and OS X] [Windows] |
| jstatd | Experimental: JVM jstat Daemon - Launches an RMI server application that monitors for the creation and termination of instrumented HotSpot Java virtual machines and provides a interface to allow remote monitoring tools to attach to Java virtual machines running on the local system. | [Solaris, Linux, and OS X] [Windows] |
Some of these tools are not currently available on Windows platforms.
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| jinfo | Experimental - Configuration Info for Java - Prints configuration information for a given process or core file or a remote debug server. | [Solaris, Linux, and OS X] [Windows] |
| jhat | Experimental - Heap Dump Browser - Starts a web server on a heap dump file (for example, produced by jmap -dump), allowing the heap to be browsed. | [Solaris, Linux, and OS X] [Windows] |
| jmap | Experimental - Memory Map for Java - Prints shared object memory maps or heap memory details of a given process or core file or a remote debug server. | [Solaris, Linux, and OS X] [Windows] |
| jsadebugd | Experimental - Serviceability Agent Debug Daemon for Java - Attaches to a process or core file and acts as a debug server. | [Solaris, Linux, and OS X] [Windows] |
| jstack | Experimental - Stack Trace for Java - Prints a stack trace of threads for a given process or core file or remote debug server. | [Solaris, Linux, and OS X] [Windows] |
Refer to the Java™ SE Troubleshooting web site for descriptions of tools, options, and other information to use in analyzing problems. The documents at this site contain suggestions about what to try before submitting a bug report and what data to collect for a report.
The following tools can be used to run scripts that interact with the Java platform.
| Tool Name | Brief Description | Links to Reference Pages |
|---|---|---|
| jjs | Runs the Nashorn command-line script shell. | [Solaris, Linux, and OS X] [Windows] |
| jrunscript | Experimental - Script shell for Java - Runs a script. This tool is unsupported and experimental in nature and should be used with that in mind. It might not be available in future JDK versions. | [Solaris, Linux, and OS X] [Windows] |


This Win was completed more than {{ edit_days }} days ago, so is now locked and cannot be edited.
{% if win.advisors %}
| Name |
Team Type |
HQ Team, Region or Post |
{% for advisor in win.advisors %}
| {{ advisor.name }} |
{{ advisor.team_type }} |
{{ advisor.hq_team }} |
{% endfor %}
{% else %}
No contributing teams and advisers.
{% endif %}
{% include "wins/partials/win-details-element.html" with name="Country" val=win.country %}
{% include "wins/partials/win-details-element.html" with name="Date won" val=win.date|date:"M Y" %}
{% include "wins/partials/win-details-element.html" with name="How the company was supported in achieving the win" val=win.description %}
{% include "wins/partials/win-details-element.html" with name="Overseas customer" val=win.name_of_customer %}
{% include "wins/partials/win-details-element.html" with name="Business deal that best describes the win" val=win.business_type %}
{% include "wins/partials/win-details-element.html" with name="Medium-sized and high potential companies" val=win.business_potential_display %}
{% include "wins/partials/win-details-element.html" with name="Export experience" val=win.export_experience_display %}
Export value
Total export value over the next 5 years.
-
{{ win.breakdowns.exports.0.year | default:" " }}
£{{ win.breakdowns.exports.0.value | intcomma | default:0 }}
-
{{ win.breakdowns.exports.1.year | default:" " }}
£{{ win.breakdowns.exports.1.value | intcomma | default:0 }}
-
{{ win.breakdowns.exports.2.year | default:" " }}
£{{ win.breakdowns.exports.2.value | intcomma | default:0 }}
-
{{ win.breakdowns.exports.3.year | default:" " }}
£{{ win.breakdowns.exports.3.value | intcomma | default:0 }}
-
{{ win.breakdowns.exports.4.year | default:" " }}
£{{ win.breakdowns.exports.4.value | intcomma | default:0 }}
-
Total
£{{ win.total_expected_export_value | intcomma | default:0 }}
Business success value
Total business success value over the next 5 years.
{# this should show all 5 years even if we don't have data... #}
-
{{ win.breakdowns.nonexports.0.year | default:" " }}
£{{ win.breakdowns.nonexports.0.value | intcomma | default:0 }}
-
{{ win.breakdowns.nonexports.1.year | default:" " }}
£{{ win.breakdowns.nonexports.1.value | intcomma | default:0 }}
-
{{ win.breakdowns.nonexports.2.year | default:" " }}
£{{ win.breakdowns.nonexports.2.value | intcomma | default:0 }}
-
{{ win.breakdowns.nonexports.3.year | default:" " }}
£{{ win.breakdowns.nonexports.3.value | intcomma | default:0 }}
-
{{ win.breakdowns.nonexports.4.year | default:" " }}
£{{ win.breakdowns.nonexports.4.value | intcomma | default:0 }}
-
Total
£{{ win.total_expected_non_export_value | intcomma | default:0 }}
Outward Direct Investment value
Total Outward Direct Investment value over the next 5 years.
{# this should show all 5 years even if we don't have data... #}
-
{{ win.breakdowns.odi.0.year | default:" " }}
£{{ win.breakdowns.odi.0.value | intcomma | default:0 }}
-
{{ win.breakdowns.odi.1.year | default:" " }}
£{{ win.breakdowns.odi.1.value | intcomma | default:0 }}
-
{{ win.breakdowns.odi.2.year | default:" " }}
£{{ win.breakdowns.odi.2.value | intcomma | default:0 }}
-
{{ win.breakdowns.odi.3.year | default:" " }}
£{{ win.breakdowns.odi.3.value | intcomma | default:0 }}
-
{{ win.breakdowns.odi.4.year | default:" " }}
£{{ win.breakdowns.odi.4.value | intcomma | default:0 }}
-
Total
£{{ win.total_expected_odi_value | intcomma | default:0 }}
{% include "wins/partials/win-details-element.html" with name="Expected value related to goods or services" val=win.goods_vs_services %}
{% include "wins/partials/win-details-element.html" with name="Goods or services that are being exported" val=win.name_of_export %}
{% include "wins/partials/win-details-element.html" with name="Sector" val=win.sector %}
{% include "wins/partials/win-details-element.html" with name="HVC code, if applicable" val=win.hvc|default:"None" required=False %}
{% include "wins/partials/win-details-element.html" with name="HVO Programme, if applicable" val=win.hvo_programme|default:"None" required=False %}
{% include "wins/partials/win-details-element-legacy-field.html" with name="Have HVO Specialists been involved" val=win.has_hvo_specialist_involvement %}
{% include "wins/partials/win-details-element-legacy-field.html" with name="Is this win Prosperity Fund related" val=win.is_prosperity_fund_related %}
{% include "wins/partials/win-details-element-legacy-field.html" with name="Does the win relate to e-exporting" val=win.is_e_exported %}
{% include "wins/partials/win-details-element.html" with name="Type of support 1" val=win.type_of_support_1 %}
{% include "wins/partials/win-details-element.html" with name="Type of support 2" val=win.type_of_support_2 required=False %}
{% include "wins/partials/win-details-element.html" with name="Type of support 3" val=win.type_of_support_3 required=False %}
{% include "wins/partials/win-details-element.html" with name="Associated programme 1" val=win.associated_programme_1 required=False %}
{% include "wins/partials/win-details-element.html" with name="Associated programme 2" val=win.associated_programme_2 required=False %}
{% include "wins/partials/win-details-element.html" with name="Associated programme 3" val=win.associated_programme_3 required=False %}
{% include "wins/partials/win-details-element.html" with name="Associated programme 4" val=win.associated_programme_4 required=False %}
{% include "wins/partials/win-details-element.html" with name="Associated programme 5" val=win.associated_programme_5 required=False %}


Hi {{loginService.getUser().firstname}}! , In this
Social-Connect application you can navigate to following listed features. from nav menu, sidenave menu, or from
Drop Down menu, Kindly use Desktop View for better experience.
You can add friends from Add-Friend option on sidenav.
You can View your friends & their Profile from Friends
option on sidenav.
You can View your posts, add posts, edit profile, from
My-Timeline option on sidenav.
You can View your Profile, your posts, add posts, from
My-Profile option on drop-down menu.
You can Remove Friend from Remove-Friend option on
sidenav.
You can View Your post Images in gallery View from
Photo-Gallery option on sidenav.
You can search and play Youtube videos from
Search-Video option on sidenav.
You can get the latest updated Covid
Informations with Tabular & Chart representation on Covid-Info option on sidenav.
You can Find Your location details, and can
search any location on google maps with satellite view from Find-Location option on sidenav.
You can change background image and can
change Navmenu color Setting option from dropdown menu.


Economy : "The system by which country's money and goods are produced and used."
Money? Goods? Where to insert them in CV's? For money, we will use Betza's zorkmid currency. For goods, at least some good candidates are the pieces and the available moves in each turn. Of course, if you are in a capitalist mood, you can use your imagination to create and sell new goods.
I leave here some notions and concepts until many goods things - I
hope - are created from them!
| Loans | |
| Money | |
| Interest | |
| Unemployment | |
| Monopoly | |
| Oligopoly | |
| Inflation | |
| Deflation | |
| Share | |
| Stock Market |
There are some variants where you can keep some of your moves, in order to use them later (eg, Progressive Piggy Back).
Why not introduce the symmetric concept? Loans!
Loaning in PieceLand
note: rule 3 and 4 implies that you cannot buy a queen.
Of course, money is always important in a complex social system. Betza made a game using this concept, csipgs chess. Here goes another try:
variants: changing the initial zkd value, change the cost list (add powers,
change values, ...)
back to index
Money can be seen as having two functions - as a mean of exchanging and as a mean of saving. If you keep money in a bank, you will have a "reward" for letting your savings circulate once again in the economy, that reward is called interest.
The interest of some moves
back to index
Unemployment is also an important concept in economic analysis. How can we insert it in a CV?
Do you want a job?
back to index
When a single company (or a government) gets the control of all or most of a business activity, so that other organizations cannot easily compete with them, we have a monopoly.
This horse business is mine!
More frequent is the oligopoly, where there is a control by an association of a small group of companies.
Taking turns
back to index
Another known concept is inflation, ie, the average rate
at which prices increase.
Hard Times
When inflation becomes negative, we call it deflation.
Great Expectations
back to index
I talk to Ralph Betza about this, and he sent some nice ideas:
Traditional equities for cash: I think that right now the price of Knight moves is a little low, so I'll buy one and keep it in reserve....
Futures Market, or Selling short: I think Bishop moves are overpriced, so I'll sell one that I don't have and buy it back later when the price drops.
Derivatives: I own a Rook move, which is currently worth 1 zorkmid. For 0.05 zorkmids I will sell you a contract that allows you to buy my Knight move for 1.05 zorkmids any time within the next 10 moves. If the price goes up to more than 1.2, you will profit.
So, the next step must be the stock market!
What are the main concepts that we can use? The first one is the share
(or stock), ie, one unit of ownership of a company. Since we do not have companies
here, just pieces and stuff related, can we see a piece as a companie? What would mean if
a player owns 75% of a black bishop??? In that case, you could adquire a piece with 51% of
its shares? Time to make a portfolio (ie, a combined holding of many kinds of financial
securities)!
Making a portfolio
back to index
Another interesting concept is the option. Here is part of the definition that I
found at http://www.lyonsrange.com/cse/info1.htm.
The right of choice [snip] to buy or sell a particular commodity or stock or
currency at a particular future date at a particular price, called the exercise price. The
buyer of an option is not obliged to buy or sell at the exercise price; he will do so only
if it suits him. [snip] Options protect an investor from unfavourable fluctuations in
price.
From the same source, here is the definition of selling short:
Sale of shares, which he doesn't possess, by a spectacular. He usually borrows the
shares from his stockbroker, promising to replace them at a future date, hoping that the
price will fall by then. If the price falls, he buys the shares at the lower rate, and
makes a profit on the difference. If the price has risen on the other hand, he has to buy
the shares at the higher price, and sustains a loss.
As somebody said: "A thing is worth what people will pay; and people will pay what they think it is worth."
To introduce these ideas, there must be a way to give a dynamical value for each
resource in question. What are they?
| Player's moves | |
| Moving/capturing powers | |
| Strenght difference between armies (that means you can use an eventual opponent superiority to your advantage) | |
| Number of pieces of a certain type | |
| Some positions (two white rooks in the 7th row, a pawn just next the promotion line) | |
A question remains! How to do it? One possibility lies on:
back to index
back to top


Diego Godín: It doesn't matter if Barcelona are already qualified
by EFE- The Inter defender wants to help his team reach the last 16 of the Champions League
Inter Milan defender Diego Godin says his team are not expecting an easy ride against a Barcelona side who have already qualified for the last 16 of the Champions League.
The Serie A giants must better Borussia Dortmund's result against Slavia Prague when they face Barça on Tuesday if they want to reach the knockout rounds.
Barça are already through as group winners and have taken advantage of their situation to rest Lionel Messi, Gerard Pique and Sergi Roberto for the trip to Milan.
“The objective is the match tomorrow, we don’t think beyond that," Godin told reporters on Monday. "Barcelona are one of the best teams in the world, always winning at least one trophy every season.
“There’s enthusiasm. It is up to us to qualify from the group, we have to make our fans proud and give everything we’ve got. We have to do that to qualify against a team that are used to getting deep into the tournament. It doesn’t matter if they are already qualified.”
Godin also spoke about striker Lautaro Martinez, whose form this season has seen him linked with a move to Barça as a long-term replacement for Luis Suarez.
“Lautaro has grown so much, he is about to explode,” Godin added. “He feels really important and is physically very strong.
 Today, he’s at Inter and I’m happy he’s here us to help us win. He can still grow and improve. I hope can continue to help us with goals and push the team on in general.”


--- layout: archive title: Zulip Chat Archive permalink: /stream/113489-new-members/topic/add.20one.20more.20to.20sum.html ---
Hi all, is there a tactic that just takes care of this? \sum_{i<n+1}a(i) = \sum_{i<n}a(i) + a(n) Thanks!
lemma sum_succ_is_add_last_term (a:ℕ→α )( n:ℕ ): (sum (range (n+1)) a = sum (range n) a + a (n+1)) := sorry,
sum_range_succ
He asked for a tactic. The answer is thus library_search
.
Perfect, thanks! (What is library_search? Something where I could've found this on my own?)
Try replacing this sorry,
by by library_search
.
do you have to do anything special to make that work in the web viewer?
you have to use the right web viewer. The official Lean one has a very old mathlib. The one I link to has a bang up to date one, thanks to the amazing efforts of the leanprover-community people. Oh -- you also need to import tactic
.
ahh thanks.
What is library_search? Something where I could've found this on my own?
Here it is in the mathlib tactic docs. See also suggest
.
Last updated: Apr 24 2020 at 19:02 UTC


Interface IMixedRealityController
Mixed Reality Toolkit controller definition, used to manage a specific controller type
Namespace: Microsoft.MixedReality.Toolkit.Core.Interfaces.DataProviders.Controllers
Assembly: cs.temp.dll.dll
Syntax
public interface IMixedRealityController
Properties
ControllerHandedness
The designated hand that the Input Source is managing, as defined by the SDK / Unity.
Declaration
Handedness ControllerHandedness { get; }
Property Value
| Type | Description |
|---|---|
| Handedness |
Enabled
Is the controller enabled?
Declaration
bool Enabled { get; set; }
Property Value
| Type | Description |
|---|---|
| Boolean |
InputSource
The registered Input Source for this controller
Declaration
IMixedRealityInputSource InputSource { get; }
Property Value
| Type | Description |
|---|---|
| IMixedRealityInputSource |
Interactions
Mapping definition for this controller, linking the Physical inputs to logical Input System Actions
Declaration
MixedRealityInteractionMapping[] Interactions { get; }
Property Value
| Type | Description |
|---|---|
| MixedRealityInteractionMapping[] |
IsPositionApproximate
Indicates the accuracy of the position data being reported.
Declaration
bool IsPositionApproximate { get; }
Property Value
| Type | Description |
|---|---|
| Boolean |
IsPositionAvailable
Indicates that this controller is currently providing position data.
Declaration
bool IsPositionAvailable { get; }
Property Value
| Type | Description |
|---|---|
| Boolean |
Remarks
This value may change during usage for some controllers. As a best practice, be sure to check this value before using position data.
IsRotationAvailable
Indicates that this controller is currently providing rotation data.
Declaration
bool IsRotationAvailable { get; }
Property Value
| Type | Description |
|---|---|
| Boolean |
Remarks
This value may change during usage for some controllers. As a best practice, be sure to check this value before using rotation data.
TrackingState
Outputs the current state of the Input Source, whether it is tracked or not. As defined by the SDK / Unity.
Declaration
TrackingState TrackingState { get; }
Property Value
| Type | Description |
|---|---|
| TrackingState |
Visualizer
The controller's "Visual"
Declaration
IMixedRealityControllerVisualizer Visualizer { get; }
Property Value
| Type | Description |
|---|---|
| IMixedRealityControllerVisualizer |


we have fixed this
closed
by Christina Chortaria at 2022-03-12 15:15:06.closed
by Christina Chortaria at 2022-03-12 15:16:57.closed
by Christina Chortaria at 2022-03-12 15:17:41.@dependabot rebase
mentioned
by Dependabot at 2022-03-12 15:11:18.referenced
by Christina Chortaria at 2022-03-12 15:11:56.merged
by Christina Chortaria at 2022-03-12 15:11:56.closed
by Christina Chortaria at 2022-03-12 15:11:57.head_ref_deleted
by Christina Chortaria at 2022-03-12 15:11:57.@dependabot rebase
mentioned
by Dependabot at 2022-03-12 14:35:50.referenced
by Christina Chortaria at 2022-03-12 14:36:04.merged
by Christina Chortaria at 2022-03-12 14:36:04.closed
by Christina Chortaria at 2022-03-12 14:36:05.head_ref_deleted
by Christina Chortaria at 2022-03-12 14:36:05.The current incarnation of the issue appears to be in the requests gem, so I'm closing this ticket in favor of https://github.com/pulibrary/requests/issues/1120
closed
by Jane Sandberg at 2022-03-11 22:06:11.deployed
by None at 2022-03-11 23:01:07.closed
by Christina Chortaria at 2022-03-12 09:00:39.referenced
by Christina Chortaria at 2022-03-12 09:00:39.merged
by Christina Chortaria at 2022-03-12 09:00:39.closed
by Christina Chortaria at 2022-03-12 09:00:40.head_ref_deleted
by Christina Chortaria at 2022-03-12 09:00:40.


{% extends "public/components/base.html" %} {% block title %}Open States API Registration{% endblock %} {% block description %}Open States strives to improve civic engagement at the state level by providing data and tools regarding state legislatures.{% endblock %} {% block content %}
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{{include "./public/html-header"}}
网页出错啦，先回主页吧~
Oops, you are lost! No worries, we will bring you home now :)


Nickel Speciation Of Residual Oil Ash
EPA Grant Number: R827649C002Subproject: this is subproject number 002 , established and managed by the Center Director under grant R827649
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Center for Air Toxic Metals® (CATM®)
Center Director: Groenewold, Gerald
Title: Nickel Speciation Of Residual Oil Ash
Investigators: Galbreath, Kevin C. , Huffman, Gerald P. , Huggins, Frank E. , Toman, Donald L. , Won, John , Zygarlicke, Christopher J.
Institution: University of North Dakota
EPA Project Officer: Stelz, Bill
Project Period: October 15, 1999 through October 14, 2002
Project Amount: Refer to main center abstract for funding details.
RFA: Center for Air Toxic Metals (CATM) (1998) RFA Text | Recipients Lists
Research Category: Targeted Research
Objective:
The speciation of Ni emitted from residual-oil-fired utility boilers requires investigation because the possible presence of small respirable particles containing nickel subsulfide (Ni3S2) is a health concern. An experimental approach was used to investigate the Ni speciation of residual oil combustion ash. Ash from a low- and high-sulfur (0.33 and 1.80 wt%, respectively) residual oil was produced using a laboratory-scale combustion system at excess O2 concentrations of I 1 and 2 or 3 mol%. Ni speciation analyses were performed using XAFS spectroscopy, sequential extraction-ASV, and CPEV.
Research goals are threefold:
- Identify and quantify the chemical forms of Ni in No. 6 fuel oil combustion ash
- Investigate the effects of fuel sulfur (S) and excess 0, concentrations on Ni speciation
- Evaluate the comparability of Ni speciation analysis results obtained by sequential extraction-ASV, CPEV, and XAFS spectroscopy
Approach:
Combustion tests were conducted using a CEPS, a 42-MJ/hr combustion system, to elucidate differences in the Ni speciation of ashes produced from low- and high-S fuel oils at excess O2 concentrations of I 1 and 2 or 3 mol%. Detailed descriptions of the CEPS are provided in the CATM 1994-1995 Annual Report [l] and in a previous CATM Newsletter [2]. Bulk ash samples were collected at the inlet of the convection pass section of the CEPS using glass-fiber filters. The ash samples were analyzed first using XAFS spectroscopy because it is a nondestructive technique. Ni K-edge XAFS spectroscopy measurements were conducted on beam line X-19A of the National Synchrotron Light Source, Brookhaven National Laboratory, New York. XAFS spectra of reagent-grade Ni compounds were acquired and used essentially as "fingerprints" for identifying different Ni species. The five-step extraction procedure in the table below was also used for determining Ni speciation. Ni in each extract was quantified by ASV of nickel dimethylglyoxime collected on a hanging mercury drop electrode with a CH-620 electroanalytical system in square-wave voltammetry mode. Ni concentration was obtained by the method of standard additions. In addition to analyzing the Ni extraction fractions, total Ni was determined. Although this method currently cannot be used to discriminate between nickel sulfide and subsulfide species, CPEV was used to distinguish between Ni3S2 and NiS. Mineral and synthetic standards of Ni3S2 and NiS as well as ash and extraction residues were mixed with microcrystalline graphite powder and fashioned into CPEs. Cyclic voltammetry and linear sweep voltammetry were performed using a CH-620 electroanalyzer to identify Ni3S2 and NiS.
Progress
XAFS spectroscopy, sequential extraction-ASV, and CPEV measurements indicate that soluble NiSO4 and not the more toxic Ni3S2 ,species predominate in low- and high-S residual oil ashes produced experimentally at excess 0, concentrations of 5 1% and 2 or 3 mol%. As indicated in the following table, the sequential extraction-ASV method detected the presence of significant proportions of NiO that was not detected using XAFS spectroscopy, even though the spectra of NiO are very distinctive from those for the dominant NiSO4 species. In future research, residue from the first step of the extraction procedure in the table on p. 44 will be analyzed using XAFS spectroscopy to corroborate the existence of NiO in residual oil ash. Fuel S content did not significantly affect Ni speciation; however, increasing excess 02 concentrations promoted Ni sulfation. The sequential extraction-ASV method also indicated the presence of very small proportions, <2%, of nickel sulfide. Analyses of a high-sulfur oil ash sample and the extraction residues from this ash by CPEV suggest that the nickel sulfide is present as NiS and not Ni3S2. The proportions of sulfidic nickel (NixSy) and NiO measured in these ash samples produced experimentally are much lower, while the relative proportions of soluble Ni are much greater than previous sequential extraction-ASV measurements of oil ashes collected from utility-scale boilers. Potential sources of these differences in Ni speciation include the sampling methods employed and the actual physicochemical properties of the ashes produced in a laboratory-scale versus utility-scale combustion system. Research is currently under way to identify the cause(s) of disagreement in Ni speciation results.
Rationale:
Knowledge of the chemical speciation of Ni in the ash emitted from oil-fired boilers is important with regard to potential human exposure and adverse health effects. Specifically, the presence of small respirable particles containing Ni3S2 is of primary concern from a human health standpoint. The chemical speciation of Ni emissions has been investigated recently using a modified EPA Method 5 sampling train in conjunction with a sequential extraction-ASV method. This method is based on treating a relatively small (1 O-l 00 mg) but representative ash sample to successive leaching steps to separate the analyte Ni species from the sample matrix. Ni in the extracted fractions is then analyzed using ASV, an electroanalytical technique. Ni speciation results from this method suggest that as much as -25% of the total Ni emitted from oil-fired utility boilers occurs as a sulfide or subsulfide phase (e.g., NiS2, Ni3S4, NiS, Ni7S6, Ni3S2) while the remaining 75% is apportioned among NiO, soluble Ni species (e.g., NiSO4, NiCl2, and NiCO3), nickel silicate(s), and elemental nickel (Ni0). The capabilities of CPEV and XAFS spectroscopy to directly determine Ni speciation are being used to evaluate these sequential extraction-ASV speciation results. Although extraction methods determine speciation indirectly, they are necessary to make trace element speciation determinations more quantitative and readily available.
Supplemental Keywords:
Scientific Discipline, Air, Toxics, Chemical Engineering, Environmental Chemistry, HAPS, Environmental Monitoring, 33/50, Engineering, Chemistry, & Physics, Environmental Engineering, residual oil-fired utility boiler, nickel speciation, oil fired utility boiler, nickel & nickel compounds, Nickel Compounds, residual oil ashProgress and Final Reports:
2002 Progress ReportMain Center Abstract and Reports:
R827649 Center for Air Toxic Metals® (CATM®) Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R827649C001 Development And Demonstration Of Trace Metals Database
R827649C002 Nickel Speciation Of Residual Oil Ash
R827649C003 Atmospheric Deposition: Air Toxics At Lake Superior
R827649C004 Novel Approaches For Prevention And Control For Trace Metals
R827649C005 Wet Scrubber System
R827649C006 Technology Commercialization And Education
R827649C007 Development Of Speciation And Sampling Tools For Mercury In Flue Gas
R827649C008 Process Impacts On Trace Element Speciation
R827649C009 Mercury Transformations in Coal Combustion Flue Gas
R827649C010 Nickel, Chromium, and Arsenic Speciation of Ambient Particulate Matter in the Vicinity of an Oil-Fired Utility Boiler
R827649C011 Transition Metal Speciation of Fossil Fuel Combustion Flue Gases
R827649C012 Fundamental Study of the Impact of SCR on Mercury Speciation
R827649C013 Development of Mercury Sampling and Analytical Techniques
R827649C014 Longer-Term Testing of Continuous Mercury Monitors
R827649C015 Long-Term Mercury Monitoring at North Dakota Power Plants
R827649C016 Development of a Laser Absorption Continuous Mercury Monitor
R827649C017 Development of Mercury Control Technologies
R827649C018 Developing SCR Technology Options for Mercury Oxidation in Western Fuels
R827649C019 Modeling Mercury Speciation in Coal Combustion Systems
R827649C020 Stability of Mercury in Coal Combustion By-Products and Sorbents
R827649C021 Mercury in Alternative Fuels
R827649C022 Studies of Mercury Metabolism and Selenium Physiology


The Datastore is the facility used to persist the data of the applications.
In the standard Triangular development configuration this is provided by the Server (GAE version), both local and on the Google App Engine.
Locally the data is stored as a file in directory ... \war\WEB-INF\appengine-generated\
as files local_db.bin
and
datastore-indexes-auto.xml
.
On the Google App Engine Site. the BigTable technology is used to store and replicate the data.
Data is stored on the Datastore using the Key Structure and using the record format defined by
Record Structure. It also maintains an internal integer key called the GekID
.
The administrative records for the SuperUser, AdminUsers and Users are also stored there using a special key structure protected by the Server from unauthorized access.
Refer to Datastore Related to see how to access the raw records.


The font used to render text.
The Font type represents the description of a font.
Creates a new Font.
The new constructor returns a Font composed of the components from each argument.
A sequential value.
The CachedFaceId property is an internal value representing a path to resolved font data.
Path to a font family.
The Family property points to a font file.
The weight of font text.
The Weight property determines the thickness of the text. The value is a standard OpenType weight value, where 400 is regular, 700 is bold, 100 is thin, and 900 is heavy.
Whether the text is italic.
The Style property determines whether the text is italic. 0 means normal, and 1 means italic.
Returns whether two Font values are equal.
The equal operator returns true if both operands are Font, and each corresponding component is equal.


Welcome to Pizzeria!
Choose your pizza
Size:
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Type:
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Add extra toppings:
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Cheese
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Your order:
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Dear Friend, ASSISTANCE Kindly allow me the modesty of introducing myself. I am GEORGE KABILA,the son of the former head of state/president of Congo-Kinshasha (then called Zaire) Mr.Laurent Desire Kabila. I am contacting you in other to ask for your assistance on this confidential Business proposal with full financial benefit for both of us. Before I go into further details please be informed that I am writing without any other person(s) pre-knowledge of my contacting you on this transaction. Therefore I will appreciate same attitude to be maintained all through. I have the sum of USD20.7Million from a secret sale of Diamond by my father before he was assassinated by one of his body guard (Rashid) on January 16th 2001, which I will like you to receive on my behalf due to Security reasons, as my narration below will explain. But before I continue be well informed that your share in this transaction has been calculated as 15% of the total sum of USD$20.7M, 5% for expenses and the rest for my family and I. My father as a real African traditionalist was a polygamist thereby having married to so many wives, and my mother being the second wife of my father, My step brother Joseph, who is currently the president of my country, is the son of the first wife and he does not have any knowledge about this deal. Already president Joseph is using his power to colonize all the money and private property, which my late father left behind for the entire family. Now my mother and I are left with nothing in the inheritance of my late father's wealth. Our situation is seriously critical that we need your assistance to help us receive this money overseas for proper investment. Let me quickly assure you that this transaction is 100% risk free because the diamond sales are packaged from the unset in a pattern that shows no direct trace or linkage with us (Kabila family). At present the money is deposited and is secured with a holding company under deposit account. I am waiting for your swift and favourable response, and in case you have any question(s), do not hesitate to contact me. My alternative e mail address is<EMAIL_ADDRESS>Best Regards. George Kabila.


Aws project
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How to install PMD and CPD
Windows
Requirements:
Download the latest binary distribution from the github releases page.
Unzip it into any directory, i.e., c:\pmd\
Linux / Unix
Requirements:
Download the latest binary distribution from the github releases page.
Unzip it into any directory:
[tom@hal tmp]$ unzip -q pmd-bin-6.0.1.zip
[tom@hal tmp]$ ls -l
total 4640
drwxrwxr-x 5 tom tom 4096 Apr 17 16:38 pmd-bin-6.0.1
-rw-rw-r-- 1 tom tom 4733312 Jun 9 15:44 pmd-bin-6.0.1.zip
[tom@hal tmp]$
Note that the PMD binary distribution file contains both PMD and CPD.
Running PMD via command line
On Linux and other UNIX based operating system…
PMD comes with several command line utilities. Previously, each of them had its own start up script, but this has been
greatly simplified since PMD 5.0. … at least for Unix systems. There is now only one script, called “run.sh”, inside
the bin/
directory of PMD distribution.
The first argument is the name of the utility you want to execute (‘pmd’, ‘designer’, …) and the other arguments are specific to the utility used.
$ ./bin/run.sh pmd -d ../../../src/main/java/ -f text -R rulesets/java/basic.xml -version 1.7 -language java
.../src/main/java/net/sourceforge/pmd/RuleSet.java:123 These nested if statements could be combined
.../src/main/java/net/sourceforge/pmd/RuleSet.java:231 Useless parentheses.
.../src/main/java/net/sourceforge/pmd/RuleSet.java:232 Useless parentheses.
.../src/main/java/net/sourceforge/pmd/RuleSet.java:357 These nested if statements could be combined
.../src/main/java/net/sourceforge/pmd/RuleSetWriter.java:66 Avoid empty catch blocks
.../src/main/java/net/sourceforge/pmd/RuleSetWriter.java:269 Useless parentheses.
Type “./run.sh pmd -d [filename|jar or zip file containing source code|directory] -f [report format] -R [ruleset file]”, i.e:
/home/user/tmp/pmd-bin-6.0.1/pmd/bin>./run.sh pmd -d /home/user/data/pmd/pmd/test-data/Unused1.java -f xml -R rulesets/java/unusedcode.xml
<?xml version="1.0"?><pmd>
<file name="/home/user/data/pmd/pmd/test-data/Unused1.java">
<violation line="5" rule="UnusedLocalVariable">
Avoid unused local variables such as 'fr'
</violation>
</file></pmd>
/home/user/tmp/pmd-bin-6.0.1/pmd/bin>
Basic usage for Windows
You can find PMD’s starter batch file pmd.bat
in the bin
subdirectory.
Type “pmd -d [filename|jar or zip file containing source code|directory] -f [report format] -R [ruleset file]”, i.e:
C:\tmp\pmd-bin-6.0.1<\pmd\bin>pmd -d c:\data\pmd\pmd\test-data\Unused1.java -f xml -R rulesets/java/unusedcode.xml
<?xml version="1.0"?><pmd>
<file name="c:\data\pmd\pmd\test-data\Unused1.java">
<violation line="5" rule="UnusedLocalVariable">
Avoid unused local variables such as 'fr'
</violation>
</file></pmd>
C:\tmp\pmd-bin-6.0.1\pmd\bin>
You can pass a file name, a directory name, or a jar or zip file name containing Java source code to PMD.
Also, the PMD binary distribution includes the ruleset files inside the jar file - even though the “rulesets/java/unusedcode.xml” parameter above looks like a filesystem reference, it’s really being used by a getResourceAsStream() call to load it out of the PMD jar file.
Options
The tool comes with a rather extensive help text, simply running with -help
!
| Option | Description | Required | Applies for language |
|---|---|---|---|
| -rulesets / -R | Comma separated list of ruleset names to use | yes | |
| -dir / -d | Root directory for sources | yes | |
| -format / -f | Report format type. Default format is `text`. | no | |
| -auxclasspath | Specifies the classpath for libraries used by the source code. This is used by the type resolution. Alternatively a `file://` URL to a text file containing path elements on consecutive lines can be specified. | no | |
| -uri / -u | Database URI for sources. If this is given, then you don't need to provide `-dir`. | no | plsql |
| -filelist | Path to file containing a comma delimited list of files to analyze. If this is given, then you don't need to provide `-dir`. | no | |
| -debug / -verbose / -D / -V | Debug mode. Prints more log output. | no | |
| -help / -h / -H | Display help on usage. | no | |
| -encoding / -e | Specifies the character set encoding of the source code files PMD is reading (i.e. UTF-8). Default is `UTF-8`. | no | |
| -threads / -t | Sets the number of threads used by PMD. Default is `1`. Set threads to '0' to disable multi-threading processing. | no | |
| -benchmark / -b | Benchmark mode - output a benchmark report upon completion; defaults to System.err | no | |
| -stress / -S | Performs a stress test. | no | |
| -shortnames | Prints shortened filenames in the report. | no | |
| -showsuppressed | Report should show suppressed rule violations. | no | |
| -suppressmarker | Specifies the string that marks the line which PMD should ignore; default is `NOPMD`. | no | |
| -minimumpriority / -min | Rule priority threshold; rules with lower priority than configured here won't be used. Default is `5` - which is the lowest priority. | no | |
| -property / -P | `{name}={value}`: Define a property for a report format. | no | |
| -reportfile / -r | Send report output to a file; default to System.out | no | |
| -version / -v | Specify version of a language PMD should use. | no | |
| -language / -l | Specify a language PMD should use. | no | |
| -failOnViolation {true|false} | By default PMD exits with status 4 if violations are found. Disable this option with '-failOnViolation false' to exit with 0 instead and just write the report. | no | |
| -cache | Specify a location for the analysis cache file to use. This can greatly improve analysis performance and is highly recommended. | no |
Exit Status
Please note that if PMD detects any violations, it will exit with status 4 (since 5.3). This behavior has been introduced to ease PMD integration into scripts or hooks, such as SVN hooks.
| 0 | Everything is fine, now violations found |
| 1 | Couldn't understand command line parameters or PMD exited with an exception |
| 4 | At least one violation has been detected unless '-failOnViolation false' is set. |
Supported Languages
- apex (Salesforce Apex)
- java
- ecmascript (JavaScript)
- jsp
- plsql
- vf (Salesforce VisualForce)
- vm (Apache Velocity)
- xml and xsl
Available Report Formats / Renderers
PMD comes with many different renderer types:
-
codeclimate: Renderer for Code Climate JSON format.
-
csv: Comma-separated values tabular format.
Properties:
- problem: Include problem column. Default: true.
- package: Include package column. Default: true.
- file: Include file column. Default: true.
- priority: Include priority column. Default: true.
- line: Include line column. Default: true.
- desc: Include description column. Default: true.
- ruleSet: Include Rule set column. Default: true.
- rule: Include Rule column. Default: true.
-
emacs: GNU Emacs integration.
-
html: HTML format.
Properties:
- linePrefix: Prefix for line number anchor in the source file.
- linkPrefix: Path to HTML source.
-
ideaj: IntelliJ IDEA integration.
Properties:
- classAndMethodName: Class and method name, pass ‘.method’ when processing a directory.
- sourcePath:
- fileName:
-
summaryhtml: Summary HTML format.
Properties:
- linePrefix: Prefix for line number anchor in the source file.
- linkPrefix: Path to HTML source.
-
text: Text format.
-
textcolor: Text format, with color support (requires ANSI console support, e.g. xterm, rxvt, etc.).
Properties:
- color: Enables colors with anything other than ‘false’ or ‘0’. Default: yes.
-
textpad: TextPad integration.
-
vbhtml: Vladimir Bossicard HTML format.
-
xml: XML format.
Properties:
- encoding: XML encoding format, defaults to UTF-8.
-
xslt: XML with a XSL transformation applied.
Properties:
- encoding: XML encoding format, defaults to UTF-8.
- xsltFilename: The XSLT file name.
-
yahtml: Yet Another HTML format.
Properties:
- outputDir: Output directory.
Incremental Analysis
Ever since PMD 5.6.0, PMD has been able to perform Incremental Analysis.
When performing Incremental Analysis for the first time, PMD will cache analysis data and results. This allows subsequent analysis to only look into those files that are new / have changed. For a typical development environment, where you are only changing a few files at a time, this can reduce analysis time dramatically.
The generated report will be exactly the same as it would if running without incremental analysis. Files included in the final report will reflect exactly those files in your filesystem. Even if untouched, files with violations will be listed with full detail.
Enabling Incremental Analysis
Incremental analysis is enabled automatically once a location to store the cache has been defined.
From Command Line that is done through the -cache
argument, but support for the feature is
available for tools integrating PMD such as Ant,
Maven, and Gradle.


Data hosted by IDC is subject to the TCIA Data Usage License and Citation Requirements
NCI Imaging Data Commons is supported by the contract number 19X037Q from Leidos Biomedical Research under Task Order HHSN26100071 from NCI.


|
Project
1.0
|
Enumerations | |
| enum | IRQInterruptIndex { INT_Initial_Stack_Pointer = 0, INT_Initial_Program_Counter = 1, INT_NMI = 2, INT_Hard_Fault = 3, INT_Reserved4 = 4, INT_Reserved5 = 5, INT_Reserved6 = 6, INT_Reserved7 = 7, INT_Reserved8 = 8, INT_Reserved9 = 9, INT_Reserved10 = 10, INT_SVCall = 11, INT_Reserved12 = 12, INT_Reserved13 = 13, INT_PendableSrvReq = 14, INT_SysTick = 15, INT_DMA0 = 16, INT_DMA1 = 17, INT_DMA2 = 18, INT_DMA3 = 19, INT_Reserved20 = 20, INT_FTFA = 21, INT_LVD_LVW = 22, INT_LLW = 23, INT_I2C0 = 24, INT_I2C1 = 25, INT_SPI0 = 26, INT_SPI1 = 27, INT_UART0 = 28, INT_UART1 = 29, INT_UART2 = 30, INT_ADC0 = 31, INT_CMP0 = 32, INT_TPM0 = 33, INT_TPM1 = 34, INT_TPM2 = 35, INT_RTC = 36, INT_RTC_Seconds = 37, INT_PIT = 38, INT_Reserved39 = 39, INT_USB0 = 40, INT_DAC0 = 41, INT_TSI0 = 42, INT_MCG = 43, INT_LPTimer = 44, INT_Reserved45 = 45, INT_PORTA = 46, INT_PORTD = 47 } |
| enum IRQInterruptIndex |
Interrupt Number Definitions


When you sign up for the mailing list, we'll send you a Steam key to "The Time Gentlemen, Please! and Ben There, Dan That! Special Edition Double Pack," a pair of ridiculous British comedy adventure games by indie developer Size Five Games. (These games may not be appropriate for children.)


{% import "partials/_variables.jinja" as theme -%} {%- with theme=theme -%}
{%- include "!partials/_head.html" -%} {% block body -%} {%- include "!partials/body-prefix.html" -%} {%- include "!partials/announce.html" -%} {%- include "!partials/header.html" -%}


{% include 'dashboard/navbar.html' %}
{% include 'dashboard/sidebar.html' %}
{% block content %}{% endblock %}
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-webkit-animation-fill-mode
Specifies whether the effects of an animation are apparent before the animation starts and after it ends.
By default, an animation starts as soon as the style that describes the animation is applied to an element; however, the -webkit-animation-delay property can delay the start of an animation. Specifying a value of backwards or both for this property overrides the -webkit-animation-delay property and tells the animation to start as soon as the style is applied.
-webkit-animation-fill-mode: <mode> [, ...];
The animation's fill mode. Can be none
, forwards
, backwards
, or both
.
| none | The effects of the animation are apparent only during the defined duration of the animation. |
| forwards | The animation’s final keyframe continues to apply after the final iteration of the animation completes. |
| backwards | The animation’s initial keyframe is applied as soon as the animation style is applied to an element. This only affects animations that have a nonzero value for -webkit-animation-delay. |
| both | The animation’s initial keyframe is applied as soon as the animation style is applied to an element, and the animation’s final keyframe continues to apply after the final iteration of the animation completes. The initial keyframe only affects animations that have a nonzero value for -webkit-animation-delay. |


1.1 RStudio projects
RStudio projects (.Rproj
) are a handy solution to keep all the files related to a specific workflow, including
- R scripts (
.R
), - workspace files (
.RData
), - history files (
.Rhistory
), - required datasets,
- etc.,
together in one working directory. RStudio projects, once opened, are automatically associated with the directory the .Rproj file is located in, thus rendering unnecessary the use of setwd()
.
Starting a new project
From inside RStudio, projects are easily initialized and associated with either
- a brand new working directory,
- an existing directory or
- a local copy of a version control repository (of which more later on)
by hitting the ‘New Project…’ button from the drop-down menu at the top-right corner.
Working with projects
Once created, RStudio automatically switches to the new project (not without asking if you’d like to safe your latest changes, of course). If you desire to work with an already existing project instead, you may simply open the referring .Rproj file either via the drop-down menu in the top-right corner, or just double-click it within your system’s file explorer. Note that, amongst others, the following actions are taken when a project opens inside RStudio (taken directly from https://support.rstudio.com/hc/en-us/articles/200526207-Using-Projects):
- a new R session is started;
- the
.Rprofile
file in the project’s main directory (if any) is sourced; - the
.RData
file in the project’s main directory is loaded (if indicated by the project options); - the
.Rhistory
file in the project’s main directory is loaded into the RStudio ‘History’ pane and available for Console Up/Down arrow command history; - previously edited source documents are restored into editor tabs.
Similarly, when you quit a project,
- the related
.RData
and.Rhistory
files are being saved (if indicated by the project options); - the currently active R scripts are being saved;
- the current R session is terminated.
For any further information, you are kindly referred to the official RStudio support website on using projects.
 You are required to initialize a new (and empty) RStudio project called ‘advanced-programming-in-r’. For that purpose,
- choose a new directory rather than an existing one (don’t worry, we’ll take care of version control later) and
- initialize an empty project (pop-up dialog not shown) with GitHub version control enabled.
Now that you successfully set up your own personal RStudio project, it’s time to move on to the next crucial step towards establishing a consistently structured workflow in R: tracing your tediously developed coding work with GitHub version control.


Browser Wars
Netscape and the Battle Against Microsoft
NetScape
"The king is dead, long live Netscape Navigator!"
1993 - Mark Andreeson, from University of Illinois– and his team posted Mosaic Online for free; Internet went from scientists to mass media.
1994 – Jim Clark, American businessman, engineer and Philanthropist and Mark Andreeson founded Netscape. Netscape was launched and spread like wildfire.
1995, people were referring to the World Wide Web as Netscape.
Aug 1995 - Netscape went Public Netscape’s IPO for the stock market was very successful.
MicroSoft
"To empower every person and every organization on the planet to achieve more."
1993- 90% of World was running Microsoft windows which was started in 1975 by Bill Gates, a Harvard dropout.
June 1995- Microsoft Netscape Meeting – Microsoft’s version and Netscape’s version of the meeting was different. Microsoft stated they had a productive meeting and discussed ideas. Netscape’s version was that Microsoft gave them an ultimatum to join with Microsoft or to be done.
Dec 7th 1995 – Microsoft came out with Internet Explorer on the same day as the Pearl Harbor Attack. They were going to attack Netscape; Microsoft provided Internet Explorer for free if you bought Windows, whereas Netscape was subscription based.
Sept 1997- The Browser War is over; Microsoft was triumphant. Internet Explorer took over.
1998- Microsoft had to battle the US government. Bill Gates was seen as a threat. Netscape and other companies including the government attacked Microsoft that Microsoft was monopolizing everything. Bill Gates was put to trial for illegal practices; Bill Gates denied knowledge of meeting with Netscape in 1995. The Verdict: Microsoft was found guilty and the company had to be broken up. Then, the Federal appeals court that had agreed that Microsoft broke the law felt the verdict was too harsh and rescinded the order to split the company in two. Bill Gates then stepped down as being chief executive office and gave it to Steve Balmer. He then focused on his philanthropic work.


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While building the HTML5 wrapper for the mini apps in :blibb I hit one of the hardest problems I’ve seen with mobile: Offline support.
Offline is tough. In fact, in mobile, the ABC of this video is turned into “Assume Bad Connectivity” and no matter what you’re building today, it has to work on mobile. Don’t get it wrong, I’m not saying make it mobile, I’m saying it has to work on mobile… and here is where I hit my wall: Offline.
There are different approaches, but basically the idea is that if you’re offline you use the web database (any of the many available now) and save your temporary data there until you get back online and you sync your data back.
That idea didn’t work out with me. It makes thing too complicated. having this approach means having to implement two set of APIs, one for local and one for remote, and chances of messing up are quiet high:
if (online){
getOnlineData();
saveOnlineData();
updateOnluneData();
deleteOnlineData();
}else{
getOfflineData();
saveOfflineData();
updateOffluneData();
deleteOfflineData();
}
Will not help you much because you ever know when you are going to lose your connectivity. For us it worked much better this approach: you use always the local storage by default. Assume being offline always and sync whenever you have connection. Why? because it makes things easier and because it makes much more sense: your users don’t care about your server… nor your app, they care about their data.
getOfflineData();
saveOfflineData();
updateOffluneData();
deleteOfflineData();
if (online){
sync();
}
This approach makes development of the mini app much easier: you code against the local APIs and implement a Sync method that will sync changes in your server.


Softwaredam is committed to deliver you the best of software services to keep your business and business needs up and running. Softwaredam is run by Yosuf Haydary who is specialized mainly in, but not limited to, the mission-critical Java software stacks.
Softwaredam is officially registered at the Chamber of Commerce of The Hague under 73005770.


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Research
I am broadly interested in Robotics, Reinforcement Learning, and NLP. My motivation is to build agents with cognitive capabilities that can learn and infer like humans.
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Train Offline, Test Online: A Real Robot Learning Benchmark
Gaoyue Zhou*, Victoria Dean*, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta
Accepted to ICRA 2023
Best Paper Award at NeurIPS WBRC 2022
OpenReview |
video |
project page
We introduce a new benchmark for tabletop manipulation: Train Offline, Test Online (TOTO) and showed performance of state-of-the-art models on two tasks.
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Real World Offline Reinforcement Learning with Realistic Data Source
Gaoyue Zhou*, Liyiming Ke*, Siddhartha Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar
Accepted to ICRA 2023 and 3 NeurIPS 2022 workshops
arXiv |
video |
project page
In this work, we evaluate Offline RL algorithms' performance on real robot, on in-domain tasks and transfer learning settings.
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Putting the Con in Context: Identifying Deceptive Actors in the Game of Mafia
Samee Ibraheem*, Gaoyue Zhou*, John DeNero
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022
Oral Presentation
arXiv |
video |
project page
In this paper, we collect and release a dataset for identifying deceptive actors through the game of Mafia, as well as train models to identify such actors and reveal features of their language.
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Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
Avi Singh*, Huihan Liu*, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
International Conference on Learning Representations (ICLR), 2021
Oral Presentation (top 1.8% of submissions)
arXiv |
video |
project page
We proposed a method for pre-training a behavioral prior for reinforcement learning using data from a diverse range of tasks, and used this behavioral prior to speed up learning of new tasks.
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Modeling Eva Hild's Sculpture "Wholly"
Advised by Prof. Carlo H. Séquin
tech report
We proposed various ways to use CAD Tools for the Procedural Generation of 2-Manifold Sculpture Geometries with high-level control.
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