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#include <fastformat/bundles/windows_resource_bundle.hpp>
Public Types | |
| typedef bundle_exception | parent_class_type |
| The parent exception class type. | |
| typedef missing_resource_id_exception | class_type |
| This type. | |
| typedef parent_class_type::string_type | string_type |
| The string type. | |
Public Member Functions | |
| missing_resource_id_exception (int id) | |
| Constructs an exception with the given message. | |
| missing_resource_id_exception (char const *msg, DWORD code, ff_char_t const *id, ff_char_t const *resourceType) | |
| Constructs an exception with the given message, Windows error code, resource id and resource type. | |
| missing_resource_id_exception (char const *msg, DWORD code, int id, ff_char_t const *resourceType) | |
| Constructs an exception with the given message, Windows error code, resource id and resource type. | |
Public Attributes | |
| const int | id |
| The identifier of the resource that could not be loaded. | |
| const DWORD | code |
| The windows error code associated with the load failure. |
| typedef bundle_exception parent_class_type |
| missing_resource_id_exception | ( | int | id | ) | [inline, explicit] |
Constructs an exception with the given message.
| id | The identifier of the resource that could not be loaded |
| missing_resource_id_exception | ( | char const * | msg, | |
| DWORD | code, | |||
| ff_char_t const * | id, | |||
| ff_char_t const * | resourceType | |||
| ) | [inline] |
Constructs an exception with the given message, Windows error code, resource id and resource type.
| msg | The message associated with the exception at the throw site | |
| code | The Windows error code associated with the condition that resulted in the throwing of the exception | |
| id | The identifier of the resource that could not be loaded | |
| resourceType | The type of the resource that could not be loaded |
| missing_resource_id_exception | ( | char const * | msg, | |
| DWORD | code, | |||
| int | id, | |||
| ff_char_t const * | resourceType | |||
| ) | [inline] |
Constructs an exception with the given message, Windows error code, resource id and resource type.
| msg | The message associated with the exception at the throw site | |
| code | The Windows error code associated with the condition that resulted in the throwing of the exception | |
| id | The identifier of the resource that could not be loaded | |
| resourceType | The type of the resource that could not be loaded |
| const int id |
The identifier of the resource that could not be loaded.
| const DWORD code |
The windows error code associated with the load failure.
|
|
|
| FastFormat Library documentation © Matthew Wilson, 2006-2012 |


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The tag "{{ name }}" contains the following articles:
{% else %}It seems that there is no articles in the tag {{ name }}.
{% endif %}


Oklahoma judge reduces amount Johnson & Johnson must pay state to help clean up opioid crisis by ...
by EndPlayOKLAHOMA CITY - OKLAHOMA CITY (AP) - Oklahoma judge reduces amount Johnson & Johnson must pay state to help clean up opioid crisis by $107M to $465M.


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Senior is geared towards fast-paced play and has games on Monday nights
Double-X provides a more relaxed environment including a place for families to play together and have some fun on Tuesday nights


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java.lang.Object com.netflix.config.DynamicPropertyFactory
public class DynamicPropertyFactory
A factory that creates instances of dynamic properties and associates them with an underlying configuration
or DynamicPropertySupport
where the properties could be changed dynamically at runtime.
It is recommended to initialize this class with a configuration or DynamicPropertySupport before the first call to
getInstance()
. Otherwise, it will be lazily initialized with a ConcurrentCompositeConfiguration
,
where a SystemConfiguration and DynamicURLConfiguration
will be added. You can also disable installing the default configuration
by setting system property "archaius.dynamicProperty.disableDefaultConfig" to be true
.
If system property "archaius.dynamicPropertyFactory.registerConfigWithJMX" is set to true
, when this class is initialized with a configuration,
the configuration will also be exposed to JMX via an instance of BaseConfigMBean
, where you can update the properties
via jconsole.
Example:
import com.netflix.config.DynamicProperty; class MyClass { private static DynamicIntProperty maxWaitMillis = DynamicPropertyFactory.getInstance().createIntProperty("myclass.sleepMillis", 250); // ... // add a callback when this property is changed maxWaitMillis.addCallback(new Runnable() { public void run() { int currentValue = maxWaitMillis.get(); // ... } }); // ... // Wait for a configurable amount of time for condition to become true. // Note that the time can be changed on-the-fly. someCondition.wait(maxWaitMillis.get()); // ... }
Please note that you should not cache the property value if you expect the value to change on-the-fly. For example, in the following code the change of the value is ineffective:
int maxWaitMillis = DynamicPropertyFactory.getInstance().createIntProperty("myclass.sleepMillis", 250).get(); // ... someCondition.wait(maxWaitMillis);
| Field Summary | |
|---|---|
static java.lang.String |
DISABLE_DEFAULT_CONFIG
System property to determine whether DynamicPropertyFactory should be lazily initialized with default configuration for getInstance() . |
static java.lang.String |
DISABLE_DEFAULT_SYS_CONFIG
System property to disable adding SystemConfiguration to the default ConcurrentCompositeConfiguration |
static java.lang.String |
ENABLE_JMX
Boolean system property to define whether a configuration MBean should be registered with JMX so that properties can be accessed via JMX console. |
static java.lang.String |
SYS_CONFIG_NAME
|
static java.lang.String |
THROW_MISSING_CONFIGURATION_SOURCE_EXCEPTION
System property name that defines whether getInstance() should throw
MissingConfigurationSourceException if there is no proper configuration source
at the time of call. |
static java.lang.String |
URL_CONFIG_NAME
|
| Method Summary | |
|---|---|
static java.lang.Object |
getBackingConfigurationSource()
Get the backing configuration from the factory. |
DynamicBooleanProperty |
getBooleanProperty(java.lang.String propName,
boolean defaultValue)
Create a new property whose value is a boolean and subject to change on-the-fly.. |
DynamicBooleanProperty |
getBooleanProperty(java.lang.String propName,
boolean defaultValue,
java.lang.Runnable propertyChangeCallback)
Create a new property whose value is a boolean and subject to change on-the-fly. |
DynamicDoubleProperty |
getDoubleProperty(java.lang.String propName,
double defaultValue)
Create a new property whose value is a double and subject to change on-the-fly.. |
DynamicDoubleProperty |
getDoubleProperty(java.lang.String propName,
double defaultValue,
java.lang.Runnable propertyChangeCallback)
Create a new property whose value is a double and subject to change on-the-fly. |
DynamicFloatProperty |
getFloatProperty(java.lang.String propName,
float defaultValue)
Create a new property whose value is a float and subject to change on-the-fly.. |
DynamicFloatProperty |
getFloatProperty(java.lang.String propName,
float defaultValue,
java.lang.Runnable propertyChangeCallback)
Create a new property whose value is a float and subject to change on-the-fly. |
static DynamicPropertyFactory |
getInstance()
Get the instance to create dynamic properties. |
DynamicIntProperty |
getIntProperty(java.lang.String propName,
int defaultValue)
Create a new property whose value is an integer and subject to change on-the-fly.. |
DynamicIntProperty |
getIntProperty(java.lang.String propName,
int defaultValue,
java.lang.Runnable propertyChangeCallback)
Create a new property whose value is an integer and subject to change on-the-fly. |
DynamicLongProperty |
getLongProperty(java.lang.String propName,
long defaultValue)
Create a new property whose value is a long and subject to change on-the-fly.. |
DynamicLongProperty |
getLongProperty(java.lang.String propName,
long defaultValue,
java.lang.Runnable propertyChangeCallback)
Create a new property whose value is a long and subject to change on-the-fly. |
DynamicStringProperty |
getStringProperty(java.lang.String propName,
java.lang.String defaultValue)
Create a new property whose value is a string and subject to change on-the-fly. |
DynamicStringProperty |
getStringProperty(java.lang.String propName,
java.lang.String defaultValue,
java.lang.Runnable propertyChangeCallback)
Create a new property whose value is a string and subject to change on-the-fly. |
static DynamicPropertyFactory |
initWithConfigurationSource(org.apache.commons.configuration.AbstractConfiguration config)
Initialize the factory with an AbstractConfiguration. |
static DynamicPropertyFactory |
initWithConfigurationSource(DynamicPropertySupport dynamicPropertySupport)
Initialize the factory with a DynamicPropertySupport . |
static boolean |
isInitializedWithDefaultConfig()
Return whether the factory is initialized with the default ConcurrentCompositeConfiguration. |
static boolean |
isThrowMissingConfigurationSourceException()
|
static void |
setThrowMissingConfigurationSourceException(boolean value)
Set the boolean value to indicate whether getInstance() should throw
MissingConfigurationSourceException if there is no proper configuration source
at the time of call. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
public static final java.lang.String URL_CONFIG_NAME
public static final java.lang.String SYS_CONFIG_NAME
public static final java.lang.String ENABLE_JMX
public static final java.lang.String THROW_MISSING_CONFIGURATION_SOURCE_EXCEPTION
getInstance()
should throw
MissingConfigurationSourceException
if there is no proper configuration source
at the time of call.
public static final java.lang.String DISABLE_DEFAULT_SYS_CONFIG
public static final java.lang.String DISABLE_DEFAULT_CONFIG
getInstance()
. Default is false (not set).
| Method Detail |
|---|
public static DynamicPropertyFactory initWithConfigurationSource(org.apache.commons.configuration.AbstractConfiguration config)
The initialization will register a ConfigurationListener with the configuration so that DynamicProperty
will receives a callback and refresh its value when a property is changed in the configuration.
If the factory is already initialized with a default configuration source (see getInstance()
), it will re-register
itself with the new configuration source passed to this method. Otherwise, this method will throw IllegalArgumentException
if it has been initialized with a different and non-default configuration source. This method should be only called once.
config
- Configuration to be attached with DynamicProperty
java.lang.IllegalArgumentException
- if the factory has already been initialized with a non-default configuration sourcepublic static boolean isInitializedWithDefaultConfig()
public static java.lang.Object getBackingConfigurationSource()
ConcurrentCompositeConfiguration
if the default configuration is installed.
For example:
Configuration config = DynamicPropertyFactory.getInstance().getBackingConfigurationSource(); if (DynamicPropertyFactory.isInitializedWithDefaultConfig()) { ConcurrentCompositeConfiguration composite = (ConcurrentCompositeConfiguration) config; // ... }
DynamicPropertySupport
, or null if DynamicPropertyFactory has not been initialized.public static void setThrowMissingConfigurationSourceException(boolean value)
getInstance()
should throw
MissingConfigurationSourceException
if there is no proper configuration source
at the time of call.
value
- to setpublic static boolean isThrowMissingConfigurationSourceException()
getInstance()
should throw
MissingConfigurationSourceException
if there is no proper configuration source
at the time of call.public static DynamicPropertyFactory initWithConfigurationSource(DynamicPropertySupport dynamicPropertySupport)
DynamicPropertySupport
.
The initialization will register a PropertyListener
with the DynamicPropertySupport so that DynamicProperty
will receives a callback and refresh its value when a property is changed.
If the factory is already initialized with a default configuration source (see getInstance()
), it will re-register
itself with the new configuration source passed to this method. Otherwise, this method will throw IllegalArgumentException
if it has been initialized with a non-default configuration source. This method should be only called once.
dynamicPropertySupport
- DynamicPropertySupport to be associated with the DynamicProperty
java.lang.IllegalArgumentException
- if the factory has already been initialized with a different and non-default configuration sourcepublic static DynamicPropertyFactory getInstance() throws MissingConfigurationSourceException
initWithConfigurationSource(AbstractConfiguration)
and initWithConfigurationSource(DynamicPropertySupport)
),
it will fist try to initialize itself with a default ConcurrentCompositeConfiguration
, with the following two
sub configurations:
true
DynamicURLConfiguration
, which at a fixed interval polls
a configuration file (see URLConfigurationSource.DEFAULT_CONFIG_FILE_NAME
on classpath and a set of URLs specified via a system property
(see URLConfigurationSource.CONFIG_URL
).
You can disable the initialization with the default configuration by setting system property "archaius.dynamicProperty.disableDefaultConfig" to "true".
MissingConfigurationSourceException
- if throwMissingConfigurationSourceException is true and
an error occurred in creating the default configuration.public DynamicStringProperty getStringProperty(java.lang.String propName, java.lang.String defaultValue)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpublic DynamicStringProperty getStringProperty(java.lang.String propName, java.lang.String defaultValue, java.lang.Runnable propertyChangeCallback)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpropertyChangeCallback
- a Runnable to be called when the property is changedpublic DynamicIntProperty getIntProperty(java.lang.String propName, int defaultValue)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpublic DynamicIntProperty getIntProperty(java.lang.String propName, int defaultValue, java.lang.Runnable propertyChangeCallback)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpropertyChangeCallback
- a Runnable to be called when the property is changedpublic DynamicLongProperty getLongProperty(java.lang.String propName, long defaultValue)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpublic DynamicLongProperty getLongProperty(java.lang.String propName, long defaultValue, java.lang.Runnable propertyChangeCallback)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpropertyChangeCallback
- a Runnable to be called when the property is changedpublic DynamicBooleanProperty getBooleanProperty(java.lang.String propName, boolean defaultValue)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpublic DynamicBooleanProperty getBooleanProperty(java.lang.String propName, boolean defaultValue, java.lang.Runnable propertyChangeCallback)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpropertyChangeCallback
- a Runnable to be called when the property is changedpublic DynamicFloatProperty getFloatProperty(java.lang.String propName, float defaultValue)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpublic DynamicFloatProperty getFloatProperty(java.lang.String propName, float defaultValue, java.lang.Runnable propertyChangeCallback)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpropertyChangeCallback
- a Runnable to be called when the property is changedpublic DynamicDoubleProperty getDoubleProperty(java.lang.String propName, double defaultValue)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpublic DynamicDoubleProperty getDoubleProperty(java.lang.String propName, double defaultValue, java.lang.Runnable propertyChangeCallback)
propName
- property namedefaultValue
- default value if the property is not defined in underlying configurationpropertyChangeCallback
- a Runnable to be called when the property is changed
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Mapping MDP to games and find optimal policies
From game to MDP realization
In the last blog, I have introduced MDP, which is a general environment mathematical-based abstraction, can be represented to almost every perfect environments (no system or random uncertainties). Games or simulation-based environments can be considered perfect environment that we can realize MDP on these environments. Note that there are many other environment abstractions beside MDP that RL can be applied e.g LQR, Partial Observable MDP.
In this blog, I use Easy21 as an test-bed game environment for many RL algorithms (agents) to learn optimal policies. Easy21 is similar to the BlackJack example in Sutton and Barto RL book, however, the rules are different and non standard. Easy21 environment is also an exercise of David Silver - UCL Course on RL, more about its game specification can be found here.
We can define the state $s$ of Easy21 MDP as vector of accumulated player score and initial dealer score (first black card draw by dealer). As you can see, player score must be in range from 1 to 21 and initial dealer score is in range from 1 to 10. Therefore, we will have total of 21x10 states, and hence we can apply Value Iteration (VI) or Policy Iteration (PI) without worrying about tractability of the algorithm. However, that would be the case only when we can realize the state transition probability matrix of this MDP easily, in this case, it does not. This is also the reason I choose this environment to demonstrate that some environments may have low number of states but are difficult to realize its dynamic and we have to use model-free RL methods to learn its optimal policy.
To explain why, we will attempt to compute 210x210 state transition matrix $P$ of Easy21. Let us consider the probability to transition from state $(10, 5)$ to $(11, 5)$ (remember that initial dealer score is unchange), how many ways can we accumulate score to get from 10 to 11? If we only add up the score, the answer is 1 and the transition probability is the probability that we draw card number one $P_{s,s'}=\frac{1}{10}$. However, in Easy21 we can add up or minus the score by drawing black or red card respectively, hence there are infinite ways to accumulate score from 10 to 11 (e.g 10 + 1, 10 - 3 + 4, etc) and transition probability is $P_{s, s'}=\sum\prod P_i$. Therefore, computing state transition matrix $P$ becomes intractable. In general, these are the informal steps that we usually do in MDP realization:
- Define state space $S$. In games, it's usually the same type with observation $O$ or direct observable output from environment.
- Infer action space $A$ from each state $s \in S$. (e.g in Easy21, at each state we can "hit" or "stick"
- Compute state transition probability matrix $P$ from enviroment dynamic.
- Three ways to define reward function: terminal rewards, intermediate rewards or both. It's depend on the requirements of the RL problem.
It is clear that we cannot apply VI or PI to solve optimal policy for this game. In next sections, I will introduce some popular value-based model-free RL algorithm with different schemes to learn Easy21 optimal policies. In the next blogs, policy-based RL algorithms will be introduced and evaluated.
Approaches to find optimal policies
In this section, I implement Monte-Carlo Control and TD($\lambda$) Sarsa algorithm to learn optimal policies of Easy21 under two different settings: table lookup $Q$ function and downsampling $Q$ function approximation. In addition, for balancing between exploration and exploitation, I update policy by $\epsilon$-greedy with GLIE schedule. Pseudocode for algorithm is presented in each section. If you are interested in actual implementation, it can be found in my repository.
Table lookup Q: Every-visit Monte-Carlo (MC) Control
Although the state-space of Easy21 is small enough to sweep full backup to calculate $Q$ at each state-action pair, we do not know the state transition matrix. In this case, we sample the series of state-action-reward tuple $(s, a, r, s', a')$ by letting RL agent interacts with environment based on its current policy. In MC Control, we update $Q(s_t, a_t)$ by adding error between new return $G_t$ and current $Q(s_t, a_t)$ scaled by a regulated step size $\alpha_t$:
$$ Q(s_t, a_t) = Q(s_t, a_t) + \alpha_t(G_t - Q(s_t, a_t)) $$ where $$ G_t = \sum_{\tau=t}^T\gamma^{\tau-t}r_{\tau} $$ $$ \alpha_t = \frac{1}{N(s_t, a_t)} $$Intuitively, each $Q(s_t, a_t)$ is an average of return $G_t$ as running sum so far through many episodes, the average can add new member easily by scaling new error with $\alpha_t$. We define average return as running sum like this to be compatible with iterative algorithm. Note that $N(s_t, a_t)$ counts every time agent visit state $s_t$ and do action $a_t$. After each episode, we can update policy following new action function $Q$ by $\epsilon$-greedy scheme:
$$ \epsilon = \frac{N_0}{N_0 + N(s_t)}$$ $$ \pi(a|s) = \begin{cases} \frac{\epsilon}{m} + 1 - \epsilon & a^* = argmax_{a \in A}Q(s,a) \\ \frac{\epsilon}{m} & otherwise \end{cases} $$Updating policy with $\epsilon$-greedy scheme will ensure that $Q$ function does not converge to local minima by only exploiting. The convergence properties will be dicussed in next sections. Pseudocode for MC Control can be seen as below:
I run MC Control on Easy21 enviroment implemented as an extension of OpenAI gym framework. Source code of Easy21 enviroment can be found here After 500000 episodes, the value function $V$ starts to converge as shown below. Note that I derive value function $V$ from $Q$ by $V(s) = max_aQ(s,a)$, the policy is also derived by the same manner.
.
Table lookup Q: TD($ \lambda $) Sarsa
Like MC Control, TD($ \lambda $) Sarsa also learns optimal policy by sampling experiences. However, we does not add scaled error between full return $G_t$ and current $Q(s_t, a_t)$. Instead, intuitively, we move $Q(s_t, a_t)$ toward new bootstrapped $Q$ by applying Bellman equation. We do not need to wait for reaching terminal state of each episode to update $Q(s_t, a_t)$, we update on-the-go whenever we reach state $s_t$ and do action $a_t$. This scheme is more suitable for agents to learn continuous tasks in real world (may have no terminal state or needing immediate reacts).
$$ Q(s_t, a_t) = Q(s_t, a_t) + \alpha_t(q_t^{\lambda} - Q(s_t, a_t)) $$ where $q_t^{\lambda}$ is a weighted sum n-steps returns $q_t^{(n)}$: $$ q_t^{\lambda} = (1 - \lambda)\sum_{n=1}^{\infty}\lambda^{n-1}q_t^{(n)} $$We can think $q_t^{\lambda}$ as an average of close to far bootstrapped returns, it combines the characteristics of MC update and TD(0) update. $q_t^{\lambda}$ conveys how good the state-action pair that agent estimates combines with true sample from enviroment. We can see it more clearly in pseudocode of Backward view Td($\lambda$) Sarsa:
I also run TD($\lambda$) Sarsa on Easy21 enviroment with 500000 episodes and $\lambda = 0$, the value function $V$ starts to converge as shown below. I also measure mean square error between $Q$ function learnt from Sarsa and "true" $Q$ function from MC control.
Approximated Q: TD($ \lambda $) Sarsa
In the case where the state space of MDP is very large, we could approximate $Q$ by a model. For instance, linear approximation of $Q$ would be features dot model parammeters $Q(s, a) = \phi(s, a)^T\theta$. I would like to apply linear approximation on $Q$ of this simple enviroment to demonstrate how linear function approximation is done. The feature is chose as description in Easy21 exercise. With function approximation, we do not update $Q$ directly, because model parammeters now represented the function $Q$. We update model parameters as follow:
$$ \theta = \theta + \alpha_t(q_t^{\lambda} - Q(s_t, a_t, \theta))\nabla_{\theta}Q(s_t, a_t, \theta) $$Pseudo code for function approximation of TD($\lambda$) Sarsa is the same as table lookup Q, we just need to replace update rule as specified.
We will evaluate this algorithm by measuring mean square error between $Q$ function learnt and "true" $Q$ function from MC control.
Discussion
We usually only use MC Control as a base-line for computing optimal $Q$ function for any MDP. MC Control has great learning characteristics:
- Unbiased estimation of Q (average of returns is unbiased).
- For large enough episodes, $Q$ function computed by MC Control will converge to minimum mean square error of true $Q$ function.
However, MC Control $Q$ estimation has large variance, it also needs large amount of samples to start converging and it's not suitable for online learning. In reality, one episode may never end, TD($\lambda$) Sarsa is the better option for online learning, because TD($\lambda$) Sarsa uses bootstrapped estimation of current state Q (backward view TD no need to wait for end of episode). TD($\lambda$) $Q$ estimation converges to maximum likelihood estimation of environment MDP and has much lower variance compared to MC control.
When the state space is large, it is essential that we must downsample approximation state space to ensure tractability. However, as can be seen in evaluation, in exchange of speed as expected, approximated $Q$ function is hard to converge and introduces variance. Downsampling MDP like this may not capture the true characteristics of environment.
Next blogs I will present about Policy-based algorithms in some openAI gym environment. These algorithms are promising for large state space with uncertainties in real world application.


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Chinese University Scholarships
To encourage and reward outstanding international students who study English medium MBBS program at their respective universities, most of the universities represented by CUCAS have set up an "Excellent Scholarship for International Students".
Local Government Scholarships
China's provincial and municipal governments offer scholarships for international students pursuing degree education including English medium MBBS program in local universities. Applicants should submit their scholarship applications directly to the university.
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The list below gathers a set of engineering best practices for
developing software systems with machine learning (ML) components.
These practices were identified by engaging with ML engineering teams and
reviewing relevant academic and
grey literature.
We are continuously running a global survey
among ML engineering teams to measure the adoption of these practices.
The various practices are grouped into 6 categories, as illustrated in the diagram above, and listed below.
The practices are labeled with their difficulty, their effects, and the requirements for
trustworthy ML they
help to satisfy.
{% assign sorted_practices = site.best_practices | sort:"index" %}


Warning: require_once(engine.php): failed to open stream: No such file or directory in /home/CarelX/public_html/hack/reset.php on line 5
Fatal error: require_once(): Failed opening required 'engine.php' (include_path='.:/usr/lib/php:/usr/local/lib/php') in /home/CarelX/public_html/hack/reset.php on line 5


{% extends 'base.html' %} {% block seo %} {% include 'snippets/seo_tags.html' with title='ʕ•ᴥ•ʔ Bear Blog' url='https://bearblog.dev' description='Free, no-nonsense, super-fast blogging.' tags="blog, blogging, write, writing" %} {% endblock %} {% block nav %} {% endblock %} {% block content %}
There is a website obesity crisis. Bloated websites full of scripts, ads, and trackers slowing your readers down while they try to read your well-crafted content.


First Name:
Last Name:
Gender:
Male
Female
Skills:
JavaScript
jQuery
C#
Country:
USA
INDIA
UK
Summary:
Hey I am the best programmer


I am interested in data science, business and management, and engineering. I enjoy working at the intersection of all three, finding ways to use data and my technical skills to build interesting businesses. No matter what I’m working on, I love learning new things, and I find a broad range of topics to be fodder for new ideas and opportunities. Engaging with difficult, layered problems is fun, and I thrive on working at the fringes of what has never been done before.
I currently work at Innosight, an innovation and strategy consulting firm in Lexington, Mass. Cofounded by Harvard Business School professor Clayton Christensen, we focus on helping established companies adapt to industry dynamics and harness the power of disruptive innovation. I personally specialize in R&D strategy for high technology, heavy industry, and biopharma. I am interested in the ways business model innovation can combine with breakthroughs in basic science or technology to create growth opportunities for new businesses and products. I have worked with pharmaceutical, consumer electronics, and manufacturing clients to create research accelerators and implement R&D programs. I have extensive experience in managing and directing the R&D process in the context of high technical and market uncertainty.
Prior to Innosight, I completed engineering internships in the aerospace and petroleum industries, where I helped to develop new capabilities in advanced manufacturing techniques and technologies. I was also a co-founder of an alternative energy startup at MIT.
I received SM and SB degrees in Mechanical Engineering from the Massachusetts Institute of Technology. My graduate research centered on applying disruptive innovation theories to energy and robotics research, trying to understand the research capabilities and technological breakthroughs that underly successful disruptive innovations. My other research interests include robotics, manufacturing, data science, and energy.
In my spare time, I am a voracious reader. I especially enjoy reading history and biographies. I enjoy traveling with my wife, visiting art museums, and experiencing life in Cambridge, Mass (when the snow isn’t over our heads).
© 2016. All rights reserved. "Then you will know the data, and the data will set you free." winstonlarson@gmail.com


From Data to Dashboards in a Day
Details Sign up on Eventbrite not Meetup https://www.eventbrite.com/e/95552487061/ Overview From data to dashboards in a day. Learn the art and science of developing interesting, informative, and interactive dashboard in today’s most popular analytics and visualization tool Tableau. This workshop will discuss the workflow, tools, and design concepts you need to create engaging dashboard reports. The design of a dashboard can be the difference between a dashboard that is hardly used versus one that becomes a popular tool of decision-makers.


Welcome to boot-web, a simple web server framework with
Node
.
contact me with<EMAIL_ADDRESS>or visit
www.yaozhiguo.site


{% extends "base.html" %} {% block title %}Create a Decoy Link{% endblock %} {% block body %}
Many services on the web offer link previews through website metadata.
For example, if you share a link on WhatsApp, Twitter or Discord, you might see a title, short description and/or an image in the message.
This website allows you to create links to websites that yield custom previews.
To make a link look prettier. Or to rickroll your friends. I'll leave that decision up to you.
{% endblock %}


---
layout: post
title: CloudAve
date: '2009-07-08T11:43:58-07:00'
tags:
tumblr_url: http://alexhwilliams.tumblr.com/post/137886362/cloudave
---
CloudAve
A blog with a smart approach - independence maintained by not accepting advertising. Content available via Creative Commons. Cost to maintain the blog covered through sponsorship from Zoho.


Enter text and then manually markup using the SSML data
attribute
format (described at:
https://github.com/mhakkinen/SSMLinHTMLproposal),
by selecting the sample
button below, or entering text, then highlighting text, and selecting one of the SSML toolbar
actions to be
applied to the text. The appropriate
SSML JSON attribute will be added. Once your text is ready, click the speak button.
Your platform must have an speech synthesizer that supports SSML if you using Windows or other
platforms with
native SSML supporting synthesizers.
If using MacOS, the JSON-ized SSML will be mapped to the Apple Speech markup.
Copy text to here and use buttons to edit
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CrimPapers
Articles published on 13 August 2018
On 13 August 2018, 9 new articles were published in 7 journals.
Penalization and Multidimensional Poverty: Improving Our Understanding of Poverty Amongst Offenders in Ciudad Juarez, Mexico
Responding to the Structural Violence of Migrant Domestic Work: Insights From Participatory Action Research With Migrant Caregivers in Canada
Review of Broadening the Scope of Human-Trafficking Research: A Reader, Edited By Erin C. Heil and Andrea J. Nichols, Durham, Nc, Carolina Academic Press, 2017, 296 Pp., $40 (paperback), Isbn: 978-1-61163-765-6 by Jeanne Sarson
What Do Ems Professionals Know About Human Trafficking? An Exploratory Study by Elizabeth A. Donnelly, Karen Oehme, Dwayne Barris, Rebecca Melvin
Police Moonlighting and Gender Difference: Exploring Paid Detail Security For Men and Women Officers in North American Police Departments
Standardization and the Production of Justice in Summary Criminal Courts: A Post-Human Analysis by Lucy Welsh, Matt Howard
Testimonial Injustice and Vulnerability: A Qualitative Analysis of Participation in the Court of Protection by Jaime Lindsey
Associations Between Risky Lifestyles and Involvement in Violent Crime During Adolescence by Alexander Engström
System Backgrounds, Psychosocial Characteristics, and Service Access Among Dually Involved Youth: A Los Angeles Case Study by Carly B. Dierkhising, Denise Herz, Rebecca A. Hirsch, Sam Abbott


Clean air research converts toxic air pollutant into industrial chemical
| Source: | University of Manchester |
| Summary: | A toxic pollutant produced by burning fossil fuels can be captured from the exhaust gas stream and converted into useful industrial chemicals using only water and air thanks to a new advanced material. |
A toxic pollutant produced by burning fossil fuels can be captured from the exhaust gas stream and converted into useful industrial chemicals using only water and air thanks to a new advanced material developed by an international team of scientists.
New research led by The University of Manchester, has developed a metal-organic framework (MOF) material that provides a selective, fully reversible and repeatable capability to capture nitrogen dioxide (NO2), a toxic air pollutant produced particularly by diesel and bio-fuel use. The NO2 can then be easily converted into nitric acid, a multi-billion dollar industry with uses including, agricultural fertilizer for crops; rocket propellant and nylon.
MOFs are tiny three-dimensional structures which are porous and can trap gasses inside, acting like cages. The internal empty spaces in MOFs can be vast for their size, just one gram of material can have a surface area equivalent to a football pitch.
The highly efficient mechanism in this new MOF was characterised by researchers using neutron scattering and synchrotron X-ray diffraction at the Department of Energy's Oak Ridge National Laboratory and Berkeley National Laboratory, respectively. The team also used the National Service for Electron Paramagnetic Resonance Spectroscopy at Manchester to study the mechanism of adsorption of NO2 in MFM-520. The technology could lead to air pollution control and help remedy the negative impact nitrogen dioxide has on the environment.
Asin Nature Chemistry, the material, named MFM-520, can capture nitrogen dioxide at ambient pressures and temperatures — even at low concentrations and during flow — in the presence of moisture, sulfur dioxide and carbon dioxide. Despite the highly reactive nature of the pollutant, MFM-520 proved capable of being fully regenerated multiple times by degassing or by treatment with water in air — a process that also converts the nitrogen dioxide into nitric acid.
"This is the first MOF to both capture and convert a toxic, gaseous air pollutant into a useful industrial commodity." said Dr Sihai Yang, a lead author and a senior lecturer at The University of Manchester's Department of Chemistry. "It is also interesting that the highest rate of NO2 uptake by this MOF occurs at around 45 degrees Centigrade, which is about the temperature of automobile exhausts."
Professor and Vice-President and Dean of the Faculty of Science and Engineering at The University of Manchester Martin Schröder, a lead author of the study, said: "The global market for nitric acid in 2016 was USD $2.5 billion, so there is a lot of potential for manufacturers of this MOF technology to recoup their costs and profit from the resulting nitric acid production. Especially since the only additives required are water and air."
As part of the research, the scientists used neutron spectroscopy and computational techniques at ORNL to precisely characterize how MFM-520 captures nitrogen dioxide molecules.
"This project is an excellent example of using neutron science to study the structure and activity of molecules inside porous materials," said Timmy Ramirez-Cuesta, co-author and coordinator for the chemistry and catalysis initiative at ORNL's Neutron Sciences Directorate. "Thanks to the penetrating power of neutrons, we tracked how the nitrogen dioxide molecules arranged and moved inside the pores of the material, and studied the effects they had on the entire MOF structure."
"The characterisation of the mechanism responsible for the high, rapid uptake of NO2 will inform future designs of improved materials to capture air pollutants." said Jiangnan Li, the first author and a PhD student at The University of Manchester.
In the past, capturing greenhouse and toxic gases from the atmosphere was a challenge because of their relatively low concentrations and because water in the air competes and can often affect negatively the separation of targeted gas molecules from other gases. Another issue was finding a practical way to filter out and convert captured gases into useful, value-added products. The MFM-520 material offers solutions to many of these challenges.
make a difference: sponsored opportunity
Story Source:
Materials provided by University of Manchester.
Note: Content may be edited for style and length.
Journal Reference:
- Jiangnan Li, Xue Han, Xinran Zhang, Alena M. Sheveleva, Yongqiang Cheng, Floriana Tuna, Eric J. L. McInnes, Laura J. McCormick McPherson, Simon J. Teat, Luke L. Daemen, Anibal J. Ramirez-Cuesta, Martin Schröder, Sihai Yang. Capture of nitrogen dioxide and conversion to nitric acid in a porous metal–organic framework. Nature Chemistry, 2019; 11 (12): 1085 DOI: 10.1038/s41557-019-0356-0
Cite This Page:
| MLA | University of Manchester. "Clean air research converts toxic air pollutant into industrial chemical." ScienceDaily. ScienceDaily, 22 November 2019. <www.sciencedaily.com/releases/2019/11/191122113301.htm>. |
| APA | University of Manchester. (2019, November 22). Clean air research converts toxic air pollutant into industrial chemical. ScienceDaily. Retrieved November 25, 2019 from www.sciencedaily.com/releases/2019/11/191122113301.htm |
| Chicago | University of Manchester. "Clean air research converts toxic air pollutant into industrial chemical." ScienceDaily. www.sciencedaily.com/releases/2019/11/191122113301.htm (accessed November 25, 2019). |


{{ 'This version of AngularJS Seed is v%VERSION%.' | interpolate }}
This is version Foundation is v4.3.1.
This is version HTML5 Boilerplate vis 4.2.0.


Are you sure that this is the correct server name or ip address?You can change that later if its not.
Please configure connection to the Web Chat server provider. Type the name of the server or its ip address.


Gordon Ramsay 'paid Ed Sheeran £500,000' to perform at daughter Tilly’s 18th birthday
The TV chef parted with a large amount of money to ensure his daughter had a party to remember
by Irishmirror.ieGordon Ramsay reportedly 'spent £500,000' on the entertainment for daughter Tilly's 18th birthday bash last week.
The TV chef, 53, paid the massive amount to Ed Sheeran so that he would perform for Tilly's milestone birthday as the Shape of You hitmaker is her favourite artist.
“Tilly’s bash was next level. It was clear Gordon had spared no expense in making sure it really was a night to remember,' a party insider told The Sun .
“Ed is Tilly’s favourite singer so it meant the world to her that he was there, even though his set didn’t come cheap.
 There was even a 007 ice sculpture which you could drink shots out of.”
The publication also claim that it cost Gordon a whopping £500,000 to get the red-haired musician on board for the intimate gig.
Tilly's birthday party came after she risked the wrath of the sweary chef when she went public with her new boyfriend on Instagram earlier this month.
She shared two sweet black and white photos with an unnamed boy as they did some sightseeing in South Africa.
In one photo they pose with their arms around each other, and in the next Tilly, a budding chef herself, looked giggly as she nestled in close.
Her post shocked her famous dad, who wrote "WTF" in the Instagram comments.
Tilly's brother Jack had anticipated their father's reaction, writing: "@gordongram interrogation time."
Their sister Megan joined in, saying: "We have all been there Tills - gotta face up to it."
One person commented asking if the boy was Tilly's boyfriend and she said "maybe".
No wonder it comes as a surprise to Gordon, who just weeks ago revealed that Tilly is dating Gino D'Acampo's son Luciano.
He said Tilly, who has her own CBBC show Matilda and the Ramsay Bunch, grew close to Gino's boy, 17, while their dads were filming new TV show Men Behaving Badly.
Gordon shared news of his daughter romance's with the offspring of his pal Gino, 43, during an appearance on The Jonathan Ross Show.
When he was asked about rumours the teenagers had grown close, famously foul-mouthed Gordon described the situation as a "f***ing nightmare".
Gordon said: "We were driving through San Francisco and FaceTiming Luciano, and all of a sudden Tilly pops up behind them, and they are out having lunch.
"I think they are friends."
Do you have a story to sell? Get in touch with us at<EMAIL_ADDRESS>or call us direct 0207 29 33033


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Product owner
Bill Mahoney
Art director
Saba Cabrera
Tech Lead
Shae Le
UX Designer
Skylah Lu
Developer
Griff Richards
Developer
Stan John
We are team of creatively diverse. driven. innovative individuals working in various locations from the world.
Product owner
Bill Mahoney
Art director
Saba Cabrera
Tech Lead
Shae Le
UX Designer
Skylah Lu
Developer
Griff Richards
Developer
Stan John


Akan names come from a traditional naming system for people from countries such as Togo, Ivory Coast and Ghana. A child’s name is determined by factors surrounding his or her birth. For example, the day of their birth or the manner in which they were born may determine which name they get irrespective of their gender.These Akan names signify the day one is born. According to Akan tradition, each child is born with a name associated to their soul. The day the child is born is therefore determined by the soul. The well thought and organized naming system of the Akan’s was initiated by the ancestors and has attracted so many people’s attention as they desire to know more about these names.


Our site was made in efforts to help those who do not have access to information on college and how to apply. We are encouraging other students to pursue higher education, and prepare for their college education. Some are made out to believe that college is not achievable due to it being extremely expensive, but with the help from our site, it will inform students on how to make college possible for themselves. Thanks to Girls Who Code, four girls were brought together from around the Bay Area and came together to create College Insider. Girls Who Code is a free program that exposes rising junior and senior girls into Computer Science. This program helps break the gender gap within the STEM field, and encourages women to not undermine their abilities. It teaches women that it is okay to pursue a career that involves critical thinking and logic.
Ariana Danao
Hello, my beautiful friends! I hope you have found our website resourceful and easy to use. As a rising senior, I have expereienced many of the peers around me that did not believe they could achieve a higher education. Our website is such an important tool to have because not everyone has easy access to this information. Anyone can go to college and we have the information to prove this statement true! Because of Girls Who Code, I was able to help create this website to help other students who may stumble upon this website...(to be continued)
Indu Gaddamadugu
Hello, thank you for taking the time to visit our website! My name is Indu and I am a senior at Dougherty Valley High School. I am incredibly passionate about providing equal opportunities for everyone, no matter their situation, which is why I am very proud of our website, College Insider. These days manystudents pay thousands of dollars for a college counselor; we aim to give everyone the opportunity of pursuing a higher education by providing resources such as college planning templates and financial aid information. I got into coding recently through Girls Who Code. This organization has taught me the importance of being confident in my abilities. Because of Girls Who Code, I am able to make a difference in people's lives through this website. When I'm not coding, I am often found at the gym practicing my powerlifting, taking pictures, or teaching taekwondo. Again, thanks for visiting!
Jennifer Flores
Hello, my name is Jennifer.
Tyra North
Hello, my name is Tyra
TBA


Species sensitivity distributions are cumulative probability distributions which are fitted to toxicity concentrations for multiple species. The ssdtools package uses Maximum Likelihood to fit log-normal, log-logistic, log-Gumbel, Gompertz, gamma or Weibull distributions. Multiple distributions can be averaged using Information Criteria. Confidence intervals can be calculated for the fitted cumulative distribution function or specific hazard concentrations (percentiles). Confidence intervals are currently produced by bootstrapping.
| Version: | 0.0.3 |
| Depends: | R (≥ 3.4.0) |
| Imports: | checkr, fitdistrplus, FAdist, ggplot2, graphics, grid, scales, stats, VGAM |
| Suggests: | covr, knitr, rmarkdown, testthat, tibble, tidyr, readr, purrr, dplyr |
| Published: | 2018-11-25 |
| Author: | Joe Thorley [aut, cre, ctr], Carl Schwarz [aut, ctr], Ali Azizishirazi [ctb], Angeline Tillmanns [ctb], Stephanie Hazlitt [ctb], Kathleen McTavish [ctb], Emilie Doussantousse [ctb], Heather Thompson [ctb], Andy Teucher [ctb], Province of British Columbia [cph] |
| Maintainer: | Joe Thorley <joe at poissonconsulting.ca> |
| BugReports: | https://github.com/bcgov/ssdtools/issues |
| License: | Apache License (== 2.0) | file LICENSE |
| URL: | https://github.com/bcgov/ssdtools |
| NeedsCompilation: | no |
| Language: | en-US |
| Materials: | README NEWS |
| CRAN checks: | ssdtools results |
| Reference manual: | ssdtools.pdf |
| Vignettes: |
ssdtools User Manual |
| Package source: | ssdtools_0.0.3.tar.gz |
| Windows binaries: | r-devel: ssdtools_0.0.3.zip, r-release: ssdtools_0.0.3.zip, r-oldrel: ssdtools_0.0.3.zip |
| OS X binaries: | r-release: ssdtools_0.0.3.tgz, r-oldrel: ssdtools_0.0.3.tgz |
| Old sources: | ssdtools archive |
Please use the canonical form https://CRAN.R-project.org/package=ssdtools to link to this page.


BeerFellows
Here are the drink results:
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The turnaround cycles get shorter and it looks like the sales department run out of (patience|answers|clues|excuses). I got a reply from the technical department:
Case ID: 1392853
Dear Mr Wissel
Thank you for the reply.
I will address your concerns on the transfer loss due to overheads (such
as cable condition, distance from exchanges, etc), as you are familiar
with all the factors that affect a broadband connection's downloading
speed.
You may wish to know that our Broadband 3500Kbps plans can only be
used on ADSLs activated line for 3500Kbps. If the existing line served
by exchange MUX has a dB loss of more than 30, it is not within
specification. Under such case the line will be converted to local MUX.
I seek your understanding that although we own the cables,
condition of line wiring within users' premises may vary. When you sign
up for our 3500kbps plan, we will need to ensure that the line
condition is within the required specification.
Thus, I regret once again that we are not able to guarantee that you
will receive the maximum download speed.
Getting close... So I asked back:
Hi Support,
thank you for your reply. I realize being persistent enough finally gets me the answers I'm looking for.
To rephrase my question: I want to know if the LINE can support 3500Kbps. I didn't ask if I can achieve maximum download speed all the time.
So the current conclusion is:
a) The signal loss between ADSL modem and MUX must be lower that 30db to be able to support 3500Kbsp. And ideally a measurement would be performed on a hot day since copper cables have higher losses with higher temperatures.
b) Cable length and quality is a big issue. If cabling in my block the MDF room looks like the one above it might not work at all.
What do I need to do to get a measurement and assessment of the line quality? Since there is a specification, there must be a measurement to verify it.
I seek your kind understanding, that I want a verification BEFORE I sign up as a customer. You have sufficient fine print in your contracts, so I would end up paying the subscription even if the line doesn't match the specifications.
So how?
stw


Hello and welcome! Here you can find everything you need during our project
from all your files to how to contact me. You'll have full access to this area
throughout the whole project and for 6 months after completion. However all of your
files will still live on in your Dropbox folder.
If you have any small questions or comments throughout the project, you can
email me. For anything larger
it's best to wait until our next catch up call so we can go through it properly.
Our call is scheduled for every {{page.client.schedule.meeting}}
I will be available on this project {{page.client.schedule.days}}
Occasionally I take time off for holidays so if this is due to happen during our project
I will let you know in good time. Other than that you can expect intermittent availability
around all major holidays including Christmas, New Year, Easter and (ok, not a major
holiday) my birthday - (end of August)


Expect an alert to be present.
An expectation to locate an element and check if the selection state specified is in that state. locator is a tuple of (by, path) is_selected is a boolean
An expectation for the element to be located is selected. locator is a tuple of (by, path)
An expectation for checking if the given element is selected. element is WebElement object is_selected is a Boolean.”
An Expectation for checking an element is visible and enabled such that you can click it.
An expectation for checking the selection is selected. element is WebElement object
An expectation for checking whether the given frame is available to switch to. If the frame is available it switches the given driver to the specified frame.
An Expectation for checking that an element is either invisible or not present on the DOM.
locator used to find the element
An expectation for checking that there is at least one element present on a web page. locator is used to find the element returns the list of WebElements once they are located
An expectation for checking that an element is present on the DOM of a page. This does not necessarily mean that the element is visible. locator - used to find the element returns the WebElement once it is located
Wait until an element is no longer attached to the DOM. element is the element to wait for. returns False if the element is still attached to the DOM, true otherwise.
An expectation for checking if the given text is present in the specified element. locator, text
An expectation for checking if the given text is present in the element’s locator, text
An expectation for checking that the title contains a case-sensitive substring. title is the fragment of title expected returns True when the title matches, False otherwise
An expectation for checking the title of a page. title is the expected title, which must be an exact match returns True if the title matches, false otherwise.
An expectation for checking that an element, known to be present on the DOM of a page, is visible. Visibility means that the element is not only displayed but also has a height and width that is greater than 0. element is the WebElement returns the (same) WebElement once it is visible
An expectation for checking that an element is present on the DOM of a page and visible. Visibility means that the element is not only displayed but also has a height and width that is greater than 0. locator - used to find the element returns the WebElement once it is located and visible


Disclaimer: This website was created solely for my own practice. If you would like to see a professional profile, please see myLinkedIninstead.
I AM HUNGRY
HI MICHAEL
Next goal: add styling and content to the site


Innova Art utilises Cascade50’s insightful and accessible dashboards to maximise the efficiency of their sales teams across the globe.
Nevelle Bower
CEO Innova Art Limited
"Cascade50 is a very informative and intuitive piece of software that been an invaluable tool for Innova Art. It allows us to quickly understand, communicate and distribute our financial, sales and product performance. This is something that we have found that accounts packages typically struggle with or just cannot do out of the box if at all."
From America to Singapore, Innova Art are utilising the power of Cascade50’s intuitive dashboards; improving the company’s productivity and efficiency.
As a business, Innova Art is at the forefront, developing new and exciting digital print media across the world. While traditional manufacturers focus on tweaking the same types of products, Innova is forward looking and strives to listen to today’s global marketplace.
Communicating and engaging with the company’s global sales teams with the timeliest, most insightful and accessible data was a logistical challenge for the company.
Geographical and digital barriers prevented Innova Art’s sales teams from accessing the most optimal data available for their decision making.
In order to solve this issue, Innova Art required a data platform that could provide their sales teams with timely and accessible data across the globe without the need to constantly generate time-consuming spreadsheets from Sage 50 or simply go without this valuable information.
With Cascade50 connected to the Sage 50 data, the company set up its individual users and permissions and provided dashboard access across Innova Art’s business. The company’s global sales teams now have the tools to maximise their sales potential.
Each team member has instant access to their exclusive customers’ purchasing decisions and trends; increasing sales efficiency.
Cascade50 enables Innova Art to instantly spot and target under purchasing clients across their vast global client range. The platform grants Innova Art more accessible visibility and insight over their customer relationships across the globe.
Most importantly, Cascade50 enables Innova Art to find opportunities to grow the business.
Cascade50 transforms your Sage 50 data into Insightful, vibrant, and easy-to-use dashboards.
Gain an insightful and vibrant view of the business with an extensive library of intuitive and easy-to-use dashboards that cover everything from sales to finance and purchasing.


My Learning Plan
Career Goals and Future Plan
My long term goal is too have a full time job coding in an office while also creating my own business for myself part-time. When/if I manage to create a worthwhile business, I would switch to doing that full-time and then being contracted out to do odd jobs for people depending on my workload. My music is a big part of my life, and this change of career into a pathway that is much more flexible long term, will make sure I don't miss out on big performances.
Strengths
I have quite a creative mind and love putting that to use. This is something that will definitely come in handy in coding. I can problem solve and figure things out.
Weaknesses
I am quite a perfectionist and when I create a plan/design in my head or on paper, I strive to achieve what is on there even if it's above my current skill set. I over work myself and find it hard to say no. This impacts my sleep and health as I will stay up until I complete the task that I had intended to. I can't always stay focused on the screen but I think that is due to what I was doing previously. I would be on my feet at work for about 12 hours a day so staring a screen and being still seems very unnatural to me.
Human Skills
I would like to work on putting myself first. I tend to make sure everyone around me has what they should first. But this means i've thought about what I want last and by then it's too late or i've run out of time. I would also like to get better at asking for help. I like to think I can do everything but it doesn't always work out that way.
Time Management
I will go over what is expected each week on a Monday morning and plan my time for the week on each task throughout the day. If I've under estimated myself I will try my best to get it all done. Otherwise I will ask other students and facilitators what I could be doing better. I am trying to limit my distractions around me as well.
Seeking Help
If I have been on a problem for too long I will ask on Slack or my coding friends for help. I have learnt from Sprint 2 that I shouldn't wait too long as there will always be more challenging tasks ahead.
Facilitation Team Expectation
I would like to have constructive feedback weekly from the check ins with my facilitator on things I could improve on but also things I seem to have a good grasp of and to not worry about them
Extra-Curricular
I have orchestra weekly on Monday nights and I have to practice the music as well. I use that as my time away from the computer. I also like to go for motorbike rides if the weather permits.


--- title: "2.5 — Property Acquisition and Use — Class Content" citeproc: false bibliography: ../../static/bib/references.bib csl: ../../static/bib/chicago-syllabus-no-bib.csl output: blogdown::html_page: template: ../../pandoc/toc-title_html.template toc: true editor_options: chunk_output_type: console ---
Thursday, March 4, 2021
Continuing on addressing what an efficient property system would look like, having already discussed remedies, we examine several other questions: what can and can’t owners do with their property and how are new property rights established.


About Us
This group was founded on the premise that cats are what own us. All members agree that we cannot plan our days without a swift swat of the cat paw to dictate our moves.
Events are held semi-annually in a location that is generally TBD.
A support section is up-and-coming, for those of you facing cat issues.
Chances are that there is a Cat Fancier© member in your area. Admin can help provide contact info for a small fee.
Meow.


ConEmu-Maximus5 was brought to life and is supported by almost single developer efforts. The most valuable resource is time actually, hundreds of hours. But of course there are other expenses, minor or considerable: hardware used for developing and testing, digital certificate for signing ConEmu binaries (current one was obtained from Certum.pl), hosting...
You can show your appreciation and support further development and maintaining by contributing with bugreporting, localization, funding (look below), helping with documentation, coding, voting or anything else, spreading the word for example.
| Become a sponsor on GitHub | BTC: 1KiXxByfz53QNMSfrudZf5yTJvMKKY4Cn4 |
<EMAIL_ADDRESS>Z190363130005
, E294160643493
, R407008788841


{%- if page.key and site.comments.hashover.src -%} You must have JavaScript enabled to use the comments. {%- endif -%}


My honours project is a physically-based renderer called Moka. It is written in C++17 and OpenGL, and will demonstrate the many techniques employed by a commercial game engine to achieve photorealistic rendering of materials in real-time. It features a microfacet BRDF based on UE4's model as described by Brian Karis. Irradiance environment mapping is used for the ambient and diffuse terms, while Karis' split-sum approximation is used for specular image based lighting.
View On GitHubA high-speed zero-gravity racing game for four players. The game features a late 90's aesthetic reminiscent of WipeOut. Players must complete a set number of laps before their opponents to win, however each ship is extremely fragile and will explode upon strong impacts with other players or the environment, losing precious time. Particular care was taken to create a driving experience similar to that of a commercial racing game, with smooth camera effects and an FOV that increases with speed.
View On GitHubTinyBox is the game engine that powers red metal. It is a custom C++ framework that targets both Windows and Linux desktops. It uses the excellent SDL2 library as a platform abstraction layer, allowing us to target both platforms with minimal code changes. A custom OpenGL renderer is used for all rendering, while bullet is used for physics. The engine features high-level 2D and 3D graphics facilities. It also defines an entity component system modelled after the Unity engine, which allows quick prototyping and loose coupling.
View On GitHubA simple graphics project demonstrating the blinn-phong shading model with normal mapping, multiple light casters and point-light PCF shadow mapping.
View On GitHubAn expansion upon the previous graphics project that integrated with the Oculus SDK for VR support. Bullet physics was introduced to add an interactive element to the project, allowing players to push around game objects in the scene with the motion controllers. Parallax occlusion mapping was introduced alongside perspective PCF shadow mapping for the player's handheld torch.
View On GitHubAn impulse-based 2D rigid body dynamics engine written in C++. This project demonstrates simple collision detection between AABBs and OBBs alongside an implementation of Erin Catto's simplified impulse-based physics model.
View On GitHub
A 2D side-scrolling fighting party game for up to four players. Featuring a roster of four
characters with unique abilities, the rules of each match in this game are picked at
random. Settings, game modes and a wildcard element are randomly selected by the players
using a slot machine before each match. This game brought my teammates and I to the UK
national finals of the Microsoft Imagine Cup Games competition!
I developed this game as part of a team of two programmers and an artist during my HND. It
was difficult to balance the demands of the course with the competition, but it was a lot
of fun and I gained a lot of experience working in a project team because of it!
Hi! My name is Stuart Adams, and I am a software engineer. I will be graduating in May from the
University of the West of Scotland. I'm a dedicated programmer always looking to better myself.
My main interests are graphics, gameplay and engine programming. If it involves writing
high-performance C++, I'm into it! I enjoy learning new low-level system APIs, creating
high-quality graphics and creating polished gameplay experiences. Programming is awesome!
I love helping people and passing on what I've learned. I founded the new UWS Game Development
Society to provide advice and support for game development students and alumni. I want to do
more, and I am interested in becoming an ambassador for software engineering.


class: center, middle, inverse, title-slide # Validation and Resampling Methods ## Machine Learning in Economics ### Hüseyin Taştan ### Yildiz Technical University --- class: my-medium-font <style type="text/css"> .remark-slide-content { font-size: 28px; padding: 1em 4em 1em 4em; } .my-large-font { font-size: 40px; } .my-small-font { font-size: 25px; } .my-medium-font { font-size: 30px; } </style> # Outline - [Estimating test error](#testerror) - [Validation set approach](#validation) - [Leave-One-Out Cross-Validation](#loocv) - [*k*-fold Cross-Validation](#kfoldcv) - [Cross-Validation using Time Series Data](#tscv) - [Bootstrap](#bootstrap) --- name: testerror # Training and Test Error Revisited .center[![:scale 80%](img/biasvar1.PNG)] --- # Example .pull-left[ As an example, consider the following polynomial regression: `$$y=\beta_0 + \beta_1 x + \beta_2 x^2 + \ldots + \beta_p x^p +\epsilon$$` (Dataset = AUTO, y=mpg (miles per gallon), x=horsepower) * Question: What is the degree of polynomial that gives the best predictions (that is, for which the MSE is the minimum)? ] .pull-right[ ![:scale 100%](img/mpg1.PNG) ] --- name: validation # Estimating Test Error: Validation Set Approach * Typically, we have a single data set in practice. We usually don't have a separate test data that we can use to estimate prediction accuracy. * We can do the following: Divide data set into two parts: training data and validation (or hold-out) data. .center[![:scale 60%](img/valid0.PNG)] * The model is estimated using only training data. Then, predictions are computed using only validation data and test error is calculated. (blue training set) --- class: my-small-font # Example: Polynomial Regression .center[![:scale 85%](img/mpgvalid1.PNG)] * The data set is split into two parts randomly and MSE is computed using only validation set. - Left: A single validation set - Right: Validation set approach repeated 10 times. Notice high variability in resulting test MSE values. --- # Validation set approach: advantages and disadvantages - Simple and easy to implement - But test MSE can have high variability (as shown in previous graph) - Because we split the data into two equal parts randomly and used only training part in the estimation, the performance of the models worsen (as there are fewer observations) - As a result, the test MSE may be over-estimated * What are the alternatives? * Leave-one-out Cross-Validation * `\(k\)`-fold Cross-Validation --- name: loocv # Leave-one-out Cross Validation (LOOCV) .pull-left[ * LOOCV uses a single observation in validation; the rest `\(n-1\)` observations are used in training * This is repeated for each observation in the sample `\(n\)` times resulting in `\(MSE_i\)`s for each. * Test error is the average of all MSEs: `$$\mathrm{CV}_{(n)}=\frac{1}{n} \sum_{i=1}^{n} \mathrm{MSE}_{i}$$` ] .pull-right[ ![:scale 100%](img/cv1.PNG) ] --- name: kfoldcv # `\(k\)`-Fold Cross Validation .pull-left[ * If `\(n\)` is large, LOOCV can be computationally cumbersome. * Alternatively, observations can be divided into `\(k\)` groups randomly (called **folds**, such as 5, 10). * We use each fold as the validation set and compute test MSE. The remaining part is used in training. We repeat this for each fold. ] .pull-right[ ![:scale 100%](img/cv2.PNG) * This process gives `\(k\)` MSE values. The average of these is the test error: `$$\mathrm{CV}_{(k)}=\frac{1}{k} \sum_{i=1}^{k} \mathrm{MSE}_{i}$$` ] --- class: my-small-font # Example ![:scale 100%](img/cv3.PNG) **Left**: MSE values using LOOCV for auto data, **Right**: Test MSE for `\(k=10\)`-fold Cross-Validation (image source: James et al., ISLR Fig-5.4, p.180) --- # Bias-Variance Trade-off in `\(k\)`-fold Cross-Validation * `\(k\)`-fold CV is computationally more advantageous compared to LOOCV - LOOCV has less bias than `\(k\)`-fold CV, but it also has high variance. - Compared to LOOCV, `\(k\)`-fold CV has lower variance. - This is because in LOOCV training sets are almost identical (remember we use n-1 observations to estimate the model). As a result, test MSEs are highly correlated resulting in higher variability. - In contrast `\(k\)`-fold CV produces tend to have less correlation resulting in lower variance - Studies show that using `\(k=5\)` or `\(k=10\)` would suffice in practice. --- # Cross-Validation in Classification Problems * CV approach can also be used classification problems where the outcome is qualitative. * But in this case we need to use classification error `$$Err_i = I(y_i\neq \hat{y}_i)$$` .pull-left[ - LOOCV: `$$\mathrm{CV}_{(n)}=\frac{1}{n} \sum_{i=1}^{n} Err_i$$` ] .pull-right[ * `\(k\)`-fold CV: `$$\mathrm{CV}_{(k)}=\frac{1}{k} \sum_{i=1}^{n} Err_i$$` ] --- name: tscv # Cross-Validation using Time Series Data * We are interested in forming out-of-sample forecasts from a time series model. * Typicall, time series are not distributed identically and independently (iid). Because the date is chronologically order, cross-validation with random sampling cannot be applied. - We can split the data into two parts and compute forecasts using only the test data: ![](Cross-validation_files/figure-html/traintest2-1.png)<!-- --> --- # Cross-Validation using Time Series Data .pull-left[**Time Series Cross-Validation** ![](Cross-validation_files/figure-html/cv1-1.png)<!-- --> For details see Hyndman, R.J., & Athanasopoulos, G. (2019) Forecasting: principles and practice, 3rd edition, OTexts: Melbourne, Australia. [https://otexts.com/fpp3/](https://otexts.com/fpp3/) ] .pull-right[ * As in LOOVC, forecasts are computed using only test data. * In the next step, observation is added to training set and estimation is repeated. This gives an new forecast. * This is repeated for all observations in the test data. Then, forecasts errors and accuracy measures can be computed. ] --- name: bootstrap # Bootstrap - Bootstrap is a general resampling technique that can be used to assess the properties of statistical estimators. - It's based on creating new data sets by repeated sampling from an existing data set - Random sampling with replacement: some values may be repeated - The estimator that we wish to assess is estimated for each bootstrap sample - At the end we can approximate the sampling distribution of the estimator. --- # Bootstrap - We assume that we have an identically and independently distributed (iid) data set from a well-defined population. - In practice, we only have a one sample from the population. - The usual approach in statistics is that inference can be based the concept of sampling distribution for an estimator. - Theoretically, sampling distribution is the distribution of all estimates that could be computed from all possible samples from the population - In large samples, and under certain conditions, it is normally distributed. --- # Bootstrap - In small samples, however, it may not be normally distributed. - Bootstrap can especially useful in small sample sizes. Also it relies on fewer assumptions (normality is not required). - Bootstrap practically treats the existing sample as if it is the population and resamples from it with replacement. - It is widely used to estimate standard errors and confidence intervals. --- # Numerical Example ```r set.seed(12345) n <- 10 x <- rnorm(n, mean=0, sd=1) xbar <- mean(x) se_xbar <- 1/sqrt(n) # theoretical std error se_xbar_est <- sqrt(var(x)/n) # sample std error # find bootstrap std error # let's do this for a single bootstrap sample x_boot1 <- sample(x, n, replace = TRUE) # sample with replacement x_boot1 ``` ``` ## [1] -0.2761841 0.6300986 -1.8179560 0.5855288 -0.4534972 -0.2761841 ## [7] -0.9193220 -0.1093033 -0.2841597 -0.4534972 ``` ```r # calculate sample mean for boot1 xbar_boot1 <- mean(x_boot1) xbar_boot1 ``` ``` ## [1] -0.3374476 ``` --- class: my-small-font # Numerical Example .pull-left[ ```r B <- 500 # number of bootstrap samples xbar_boot <- numeric(B) for (i in 1:B) { xbar_boot[i] <- mean(sample(x, n, replace = TRUE)) } sd(xbar_boot) # bootstrap std error ``` ``` ## [1] 0.2321545 ``` ```r 1/sqrt(n) # theoretical std error (sigma/sqrt(n)) ``` ``` ## [1] 0.3162278 ``` ```r sqrt(var(x)/n) # sample std error ``` ``` ## [1] 0.2573004 ``` ] .pull-right[ ```r hist(xbar_boot) ``` ![](Cross-validation_files/figure-html/unnamed-chunk-4-1.png)<!-- --> ]


Examples
Spreads
Archived
Scrolled Doc
Spreads Continuous
Scrolled Continuous
Swipe
Open from File
Renderless
Hooks
Highlights
Hypothes.is


| somgrid {class} | R Documentation |
Plotting functions for SOM results.
somgrid(xdim = 8, ydim = 6, topo = c("rectangular", "hexagonal")) ## S3 method for class 'somgrid' plot(x, type = "p", ...) ## S3 method for class 'SOM' plot(x, ...)
xdim, ydim |
dimensions of the grid |
topo |
the topology of the grid. |
x |
an object inheriting from class |
type, ... |
graphical parameters. |
The class "somgrid"
records the coordinates of the grid to be
used for (batch or on-line) SOM: this has a plot method.
The plot method for class "SOM"
plots a stars
plot of the representative at each grid point.
For somgrid
, an object of class "somgrid"
, a list with
components
pts |
a two-column matrix giving locations for the grid points. |
xdim, ydim, topo |
as in the arguments to |
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.


Portfolio
- All
- Projects
- Photography
- Art
Birthday Card
Pen Drawing
Cardcaptor Clow Card
Procreate
Japanese Tea Garden
Photography
Northeastern University
Photography
Le Rêve - The Dream
Photography
Pokemon Charmander
Procreate
Pokenmon Puzzle
Procreate


'Native Controls' API test
File chooser:
Accept types
Multiple?
File Chooser
Color chooser:
Press button to choose color:


Basic input:
Text input:
Password input:
Button:
Radio buttons:
First group 1
First group 2
Second group 1
Second group 2
Checkbox:
First selection
Second selection
Third selection


Interaction of Ecosystems, Fires, Air Quality and Climate Change in the Southeast
EPA Grant Number: R832276Title: Interaction of Ecosystems, Fires, Air Quality and Climate Change in the Southeast
Investigators: Wang, Yuhang , Liu, Yongqiang , Russell, Armistead G. , Tian, Hanqin
Institution: Georgia Institute of Technology - Main Campus , Auburn University Main Campus , USDA Forest Service
EPA Project Officer: Bloomer, Bryan
Project Period: April 1, 2005 through March 31, 2009
Project Amount: $749,047
RFA: Fire, Climate, and Air Quality (2004) RFA Text | Recipients Lists
Research Category: Climate Change , Air , Air Quality and Air Toxics , Global Climate Change
Objective:
Large amounts of biomass are burned in the Southeast. Fire emissions have been found to significantly affect air quality in the region. The effects of fire emissions will change significantly as a result of climate and land use changes. The objectives of this research are: (1) integrate process-based ecosystem, fire emissions, air quality, and regional climate models to systematically understand the complex interaction of these components in the Southeast in a climate change setting; (2) evaluate the integrated modeling system with state fire statistics, ground and satellite observations for the present and understand better the effects of fire emissions on air quality in the Southeast; (3) propagate and calculate the sensitivities of the modeling system to major inputs, and to use those sensitivities to quantify uncertainties in the system results; and (4) assess the impact of regional climate and land use changes and fire management on ecosystems and fire emissions and the consequent effects on air quality in the Southeast. Further, assess the impact of changing aerosol concentrations as a result of fire emissions and other sources on regional climate.
Approach:
We have assembled a research team with expertise in modeling regional climate, terrestrial ecosystems, fire emissions, and air quality to tackle the complex interaction among the four components. Four models/modeling systems will be used: the Terrestrial Ecosystem Model (TEM), EPA fire emission model, Models-3 components (CMAQ/MM5/SMOKE) and the Regional Climate Model (RegCM). The modeling is processed based such that fundamental understanding of the mechanistic causal relationships can be investigated. In the initial phase, we will constrain and evaluate the modeling components using state fire statistics in Georgia, Florida, and other states like South Carolina, direct satellite observations of burned area and fire counts, AIRS, IMPROVE, STN, SEARCH, and ASACA ground monitoring networks at rural sites, and satellite observations of CO and aerosol optical depth. Furthermore, the effects of long-range transport of fire emissions from the Southwest, Northwest, and Canada will be evaluated relative to regional fire emissions over the Southeast. In the second phase, we focus on understanding the interaction of regional climate, terrestrial ecosystems, fire emissions, and air quality in 2050. Model simulations will be conducted under climate change scenarios simulated by Hadley Climate Model and NCAR Climate System Model. Two different climate projections are used since we want to understand the sensitivity of our results to climate scenarios. Besides climate change, we will also consider the effects of land use change on fire and biogenic emissions. Projected changes of anthropogenic emissions will also be taken into account. We hypothesize that (1) significant changes in the seasonal and geographical distributions of fire emissions will occur as a result of climate and land-use changes; (2) biogenic emissions as those from fires will change significantly, affecting O3 and PM concentrations in the region; and (3) aerosol from fires, biogenic emissions (SOA), and other sources will have significant impact on regional climate.
Expected Results:
We expect that our findings will provide a systematic framework for modeling and understanding the interaction of ecosystems, fire emissions, air quality and climate change. Furthermore, the uncertainty in the projected consequences of climate change for fires and the impact of fire emissions on air quality will be analyzed using the framework. Lastly, we will explore the feedback of aerosols from fire emissions and other sources on regional climate.


A High Level Overview
In Remake, data is embedded directly in HTML.
- In Remake,
data-o
-prefixed attributes (and also the singledata-l
attribute) are responsible for attach data to HTML elements- Remake sees HTML all elements as representing either an
object
, with keys and values or anarray
that contains a list of objects
- Remake sees HTML all elements as representing either an
data-i
-prefixed attributes are responsible for changing the data in thedata-o
prefixed attributes
Remake's ultimate goal is to make HTML feel like it was designed for building web apps.
Note: Remake is not required (or even loaded) when a user can't edit the page. Its only use is making sure the data on the page stays in sync with the backend. Everything is rendered by Handlebars.js.
In practice, this usually works like this:
- The user clicks an element with a
data-i-editable
attribute - An popover will appear that to edit the data on the
closest
element with data (closest
is highlighted here because it refers to theElement.closest()
method) - The user edits the information inside the popover
- The user clicks a button to save the information inside the popover
- Data from the popover is automatically synced back into the original element
- All the data on the page will be saved (unless an element with a
data-o-key-id
is found, in which case the data will be saved to that object id)


WQMY
Tests Show Toxic Water Contamination After Tennessee Coal ...
Jan 2, 2009 . Coal sludge contains dangerously elevated concentrations of arsenic, EPA says. Cross-posted from WattHead Energy News and .
http://itsgettinghotinhere.org/2009/01/02/tests-show-toxic-water-contamination-after-tennessee-coal-sludge-disaster/
USGS - NAWQA - Water Quality in the Upper Tennessee River Basin
Jan 11, 2013 . Ground-water systems such as the carbonate systems of the Upper Tennessee River Basin are particularly susceptible to contamination from .
http://pubs.usgs.gov/circ/circ1205/major_findings.htm
List of Superfund sites in Tennessee - Wikipedia, the free ...
This is a list of Superfund sites in Tennessee designated under the . Wayne, Groundwater and private drinking water wells contaminated by PCBs and VOCs, .
http://en.wikipedia.org/wiki/List_of_Superfund_sites_in_Tennessee
Contents |
[peter o'toole my favorite year] History
Tennessee Department of Environment and Conservation - TN.gov
State of Tennessee's Resources for Storm and Flood Victims . Chemical contamination of flood waters can also occur and contamination levels may be higher .
http://www.tn.gov/environment/flood/
Earth Day 2012: Toxic Environmental Racism in Tennessee ...
Apr 22, 2012. and County governments seeking cleanup of alleged water contamination. . The Tennessee Department of Environment and Conservation .
http://www.racismreview.com/blog/2012/04/22/earth-day-2012-toxic-environmental-racism-in-tennessee-threatens-family/
Annual Water Quality Report - City of Springfield, Tennessee
our water from contaminants, and we are working with the state to determine the vulnerability of our water supply to contamination. The Tennessee Department .
http://www.springfield-tn.org/water/pdfs/water_quality_report.pdf
Division of Water Pollution Control - TN.gov
The Division of Water Pollution Control is responsible for administration of the Tennessee Water Quality Control Act of 1977 (T.C.A. 69-3-101). In addition, the .
http://www.state.tn.us/environment/wpc/
TWRA - Tennessee Wildlife Resources Agency - Fish Consumption ...
Tennessee Wildlife Resources Agency. TWRA's Region 4 - East .
http://tnfish.org/ContaminantsInFishAdvisories_TWRA/FishFleshConsumptionAdvisories_TWRA.htm
Delineation of ground-water contamination using soil-gas - USGS
CONTAMINATION USING SOIL-GAS. ANALYSES NEAR JACKSON, TENNESSEE by Roger W. Lee. ABSTRACT. An investigation of the ground-water .
http://pubs.usgs.gov/wri/wrir90-4137/pdf/wrir_90-4137_a.pdf
Toxic Terror in a Tennessee Town
Toxic Terror in a Tennessee Town Government . covered it up, twisted the facts, and penalized the victims who got sick from drinking the contaminated water?
http://www.ejrc.cau.edu/DicksonArticleRDB.html
Water Contamination Suit Filed Against Dickson County, Tennessee
Water Contamination Suit Filed Against Dickson County, Tennessee. WASHINGTON, DC, March 10, 2008 (ENS) - The Natural Resources Defense Council and .
http://www.ens-newswire.com/ens/mar2008/2008-03-10-097.asp
Tennessee Wildlife Resources Agency - Contaminants in Fish
The Tennessee Wildlife Resources Agency (TWRA) is the State .
http://tennessee.gov/twra/fish/contaminants.html
TENNESSEE RURAL WATER NEEDS REPORT ... - TN.gov
Jan 31, 2005 . This arrangement is illegal under the Tennessee Safe Drinking Water Ac p onnections have contaminated public water systems and caused .
http://www.tn.gov/environment/dws/pdf/rural_ws_report.pdf
Water Quality Rpt - Arthur-Shawanee Utility District
vulnerability of our water source to potential contamination. The. Tennessee Department of Environment and Conservation (TDEC) has prepared a Source .
http://www.arthurshawanee.utilitydistrict.com/ccr
[child does not like daycare] Digital channels
| Channel | Name | family health plan cost | furniture auction rooms ireland | Programming |
|---|---|---|---|---|
| 53.1 | water comtamination in tenn DT | s t o p organization | removing copy protection from vhs | Main water comtamination in tenn programming / MyNetworkTV |
| 53.2 | WOLF DT | 500ms time delay circuit | decoding cadillac vin numbers | Simulcast of forms of phosphorus stormwater |
| 53.3 | WSWB DT | 480i | 4:3 | Simulcast of vets center lewiston maine |
"Poster Child" for Environmental Racism Finds Justice in Dickson, TN
Dec 8, 2011 . Sheila also learned that the well her family had used for drinking water for decades had become contaminated by trichloroethylene (TCE), .
http://switchboard.nrdc.org/blogs/ahuang/if_there_is_no_struggle.html
[find senior sales executive] References
[s t o p organization] External links
- josephine county fair oregon schedule
- 3 wheel from china
- naman's catering mobile al
- ways people use duct tape
- home
- who invented the candle clock
|
|


Server Information
The server is based in Europe/Lithuania with a focus to be as Open as possible to the community.
If you play on this server, you can download the map and use it on your own server.
If you want to suggest a modlet for the server,
you can always suggest it via merge request
or participate in other discussions
in the Game Server settings Github Repository.
Suggestions to change the Game Server Settings are also welcome.
Since this project is free and open. It would be great to have support via donations.


Highlights: Bucks 115, Bulls 101
by FOX SportsCheck out the highlights from Giannis Antetokounmpo and the Milwaukee Bucks‘ 115-101 win over the Chicago Bulls.
Check out the highlights from Giannis Antetokounmpo and the Milwaukee Bucks‘ 115-101 win over the Chicago Bulls.


Fullstack Developer with a self-driven attitude towards learning new technologies and programming paradigms. Trained and certified at the University of Richmond in software engineering, including skills in JavaScript (Node.js/React) and associated front-end technologies. Previously taught Algebra skills to middle school students for four years, and co-coached a middle school robotics team. I thrive in the process of breaking down an issue to its simplest form and building it back up to be more efficient and polished. My ability to quickly solve minor code issues paired with the work ethic, durability, and dependability it takes to tackle larger issues makes me a tremendous benefit to any team effort.
What started as a simple Google search on a prospective new living location, became an application idea to help people find their new happiness, home, job, or start. The State of Happiness gives the user specific data on a selected state. This data includes overall state mental health, average household income, social life, and population. With this data users can immediatley see which state would be good to research more, and which states should be met with caution.
A simple quiz game that tests the user on their general knowledge of basic computer programming. Vocabulary and concepts include HTML, CSS, jQuery, APIs, and Google Dev Tools. Questions and answers can be edited easily to allow for adaptaion and multiple use functionality.
Is it supposed to rain? A simple question that can change a person's outlook on their entire day or even week. Bad weather usually leads to bad moods or worse. With this simple weather tracker you will be able to plan workweeks, weekends, and travel plans. A 5-Day Forecast is also included. Additionally, the application saves previously searched cities for easy repetitive access.
Security is becoming more and more important everyday. With this password generator the user can input different parameters to strengthen their chosen password. Furthermore, the user can use a slider bar to create a password from 8 - 128 characters.
When I'm not teaching middle school mathematics or strengthening my skills as a software developer you can find me outside near the James River. I enjoy bike riding, playing a plethora of ridiculous sports such as kickball, wiffleball, flag football, and co-ed volleyball.