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Elf Princess Warrior – Wildecoast Saga 5- now available!!
Caught up in a vicious civil war, elven princess Gwaethe Arenil is desperate to save her peace-loving faction and reunite her people. Help presents itself in the form of Captain Jacques Vorasava, the dashing human Brightcastle commander. But does Jacques's aid come with more dangers than Gwaethe can accept, both for her people and her heart?
As the threat from the enemy elven faction forces them to work together, conflicts between their cultures push them apart. In a land of polarized opinion and intolerance, can Jacques and Gwaethe forge a new reality where their love can be accepted?
This story continues themes and characters from The Elf King's Lady.
The Master and the Sorceress – Wildecoast Saga 4
Lady Katrine Aranati is a witch whose reckless life hides the desolate pit that lies within. She dreams of a time when she can be happy and wonders if Master James Tomel could be the one to lead her out of the darkness. James feels an instant attraction for Katrine but she represents chaos and danger- everything he is trying to avoid.
When they are thrown together on a trip to Brightcastle, the desire that burns between them can no longer be denied but James has a secret that will shock Katrine to the core. Can her heart find a home with James or will he choose safety over passion?
This story continues on from The Lady and the Pirate
The Lady and the Pirate- Wildecoast Saga Book 3- available now on Amazon
Lady Esta Aranati leads a double life as noblewoman and smuggler to keep her struggling estate and its workers solvent. What does she have in common with Samael Delacost, pirate and rogue, terror of the high seas? And how can she possibly fight the dangerous attraction she develops for him. He is a man searching for his family but what he finds places him in more danger than his life on the ocean. Esta lures him like the famous sea nymphs but every step he takes towards her pulls him further from the world he understands. Can they put their past lives behind them and build a future where they can both be happy?
Catch up with Nikolas Cosara and mermaid Merielle from The Lord and the Mermaid in this rollicking sea faring romance.
The Lady and the Pirate was packed with adventure, dangerous battles and a tumultuous tale of fear of loss, and fear of love. It had a great background story, and as well as the hero being the epitome of raw masculinity, the heroine was strong and feisty!
An enjoyable read.
Princess in Exile! The long-awaited sequel to Princess Avenger…available now on Amazon
Princess Alecia Zialni flees her arranged marriage with the help of the dangerous Vard Anton, shapeshifter and former army captain. Blinded by love, they believe they can have a life together but every encounter with the mercenaries sent to find them, pushes Vard towards his least controllable form- the gigantic brown bear.
Desperate to find a mentor who will help him control his transformations, Vard and Alecia travel to a forgotten city where a powerful sorcerer resides. But this wizard is in league with the dark elves and the lovers soon discover he has his own dangerous agenda.
Will Vard and Alecia escape the clutches of the sorcerer who would use Alecia's position to advance the dark elven cause? Can their love survive despite Alecia's fear of Vard's animal transformations? What secret does the princess hold that has the power to destroy the trust Vard has in her?
The answers to all this and more are contained in the pages of Princess in Exile, the dark sequel to Princess Avenger.
Available here! Smashwords and Amazon
The Elf King's Lady– available now from Momentum and on Amazon
In the midst of a war between elves and men, two unlikely companions find love. But in this battle of ages, can they defy the very blood that courses through their veins?
The human kingdom of Thorius is once again under threat from the dark elven menace. General Kain Jazara has sworn to protect Thorius from all danger, magical or otherwise – but first he must rescue the highborn family of alluring healer Lady Alique Zorba.
Thrown together in their quest to save Alique's family, and eventually themselves, from the merciless elven clan, the pragmatic General and the impulsive Lady Alique discover an undeniable passion. But when Kain's world is torn apart by a personal revelation, he turns his back on both Alique and his homeland.
Can Kain find a path back to love and victory in time? Or will he allow revelations from his family's mysterious past to destroy his relationship, his happiness, and his kingdom?
5 out of 5 stars! A new delightful incursion in Thorius world February 22, 2018
JANER Machado reviewed The Elf King's Lady: Wildecoast Saga Book 2
The world of Thorius, with its political intrigues and torrid affairs, is a very entertaining site to visited. It's a fantasy land, so we have elves, mermaids, pirates, princes and princesses and all the major elements for a saucy and funny reading. The Elf king's lady is the moment for rendezvous to Alique Zorba, a beautiful, stubborn but sometimes frivolous lady. She meets her match in Kain and the development of their love story is also a chance of self discovery for hers. Alique will understand that feelings go beyond the appearances and love and family are much more important than an high place in Thorius court. We also meet again Nicholas and Merielle (Wildecoast I), happily married and causing frisson in Thorius society. It is a delight to read about them and wonder about next adventures in this world. Can't wait for more!
The Lord and the Mermaid– available now from Momentum and on Amazon
Fans of C.L. Wilson will love this fantasy romance about two lovers from different worlds who will break the laws of land and sea in their quest to be together.
Mermaid Merielle has fled the sea, disgusted at the actions of her people and desperate to build a life for herself on land. But to truly live as a woman, she must find a human man to fall in love with her.
Lord Nikolas Cosara has lost his brother at sea, and is driven to discover whether his sibling has died at the dangerously seductive hands of a mermaid. But when Nik finds Merielle washed up on the beach, he reluctantly saves her. Despite his antipathy for her kind, Nik is drawn to Meri, who is slowly working her way into his damaged heart.
Can Nik surrender to his love for Meri before her hopes of a human life are lost forever? Or will a devastating secret bring all her efforts to naught?
Reader Comments
Loraine Oliver reviewed The Lord and the Mermaid: Wildecoast Saga Book 1 (The Wildecoast Saga)
… Reviewed by Loraine Oliver A reviewer for Wicked Women Blog July 2, 2015
I received an ARC of this book to review for Net Galley.
The Lord and the Mermaid by Bernadette Rowley is part 1 of The Wildecoast Saga. I look forward to the next book in this series.
The Mermaid Merielle has fled her family as she can no longer allow herself to be part of the things her people do to humans on the ocean, so she flees in the face of a storm and she winds up washed up in the surf wrapped in a pile of seaweed near death.
Lord Nikolas Cosara, a man of the sea, bitter and disillusioned after his brother has disappeared, and he fears has been the victim of the mermaids, finds Merielle washed up in the seaweed. Part of him wants to leave her there to die and part of him can't in good conscience do it. So he brings the mermaid home with him, to nurse her back to health and hopefully find out something from this beautiful but disillusioned mermaid about his brother. Merielle is afraid to tell him anything as he is bitter and disillusioned already.
They both start developing feelings for each other even though he is bitter and she is harboring secrets, and after Merielle reveals something extremely important to Nikolas, he is even worse towards her and she feels that she will not be able to stay with him any longer although she has come to love him.
This book was really good and I enjoyed the interactions between Nikolas and Merielle, and although I felt sorry for Merielle in the way Nikolas was to her, I could understand Nikolas's feelings toward her.
The characters were well developed, the plot was good and there was a lot of sexual and emotional angst between the characters that kept the book interesting and moving at a steady pace.
I highly recommend reading this book, it goes quickly and is perfect for a nice day of reading. Read it and find out what Merielle is hiding from Nikolas and what happens!
I gave this book 4**** stars
@beautyandlace: 'a lovely story of second chances, moving on and finding hope with the added bonus of hot lords and stunning mermaids. Being a romance there is also steam and sizzle, and not a little tension.'
Read more: http://bookgirl.beautyandlace.net/book-review-the-lord-and-the-mermaid#ixzz3ccGtFEQw
Follow us: @beautyandlace on Twitter | BeautyandLaceOnline on Facebook
The Lady's Choice– available now on Amazon
Lady Benae Branasar will sacrifice her 'happily ever after' for an arranged marriage with a powerful prince who will save her estates and her people. Or so she imagines. But can she turn her back on her feelings for the prince's squire, Ramón Zorba? Ramon is a man Benae could easily love but he is obsessed with the prince's daughter and at first tries hard to ignore the beautiful and fiery Benae. As they are drawn inexorably together, Benae and Ramón must choose between keeping their personal vows and being true to each other.
This is the second edition of The Lady's Choice, previously published by Penguin Australia in 2013
Princess Avenger – Brightcastle Saga Book 1- available now
Princess Alecia Zialni is no ordinary noblewoman but a crusader for Brightcastle's miserable subjects, disguising herself to exact revenge and minister to the poor. So it is irksome in the extreme when the dark and dangerous Captain Vard Anton rescues her from a mercenary she has attacked. Alecia manages to slip from his grasp only to discover he has been appointed her protector.
How is she to maintain her secret life with Vard watching her every move? More importantly, how can she safeguard her heart from this mesmerising man?
Vard knows he cannot remain Alecia's protector and fulfil his mission to kill her father, Prince Zialni. Neither can he defend her when his control of his animal transformations is so tenuous.
Will the attraction that sizzles between the courageous princess and the daring captain be enough to overcome Vard's obligation to his changeling heritage and Alecia's duty to the Kingdom?
This is the second edition of Princess Avenger, previously published by Penguin Australia in 2012.
You can listen to Bernadette chat about Princess Avenger and her writing here: youtu.be/AIGKqR5JC5w
Comments from Readers of Princess Avenger:
Monique T. I really enjoyed the book and became completely engrossed in the story. I felt a connection with the characters and found myself being swept away with the emotion and passion pouring out of the pages. I would read for chapters on end and forget where reality was, drawn into the life of the princess, feeling like I was right there next to her hiding in the dark alleyways.
Robyn A. Just letting you know what a great read that was.. Sat there wanting more when it was finished. So you will have to hurry and get book 2 written.
Kstar- 5 stars on Amazon Fantastic, wonderful read, the princess is compelling and her male counterparts stand beside her the whole way through, beautiful and compelling, this is the strong equality of characters that we have needed in fantasy. I loved the fantasy parts of it (I will not spoil) and they enhance the characters and add to the story-line, rather than them being an afterthought like in many other fantasy novels. The Romance is beautiful and enough to capture your breath, groan in frustration and rejoice when you read it. A stunning book i will read again and again.
Brooke T. I couldn't put it down!!! So hooked!!
Beth. This was an intriguing, interesting and enjoyable read.
Shauni. Fabulous BOOK!! I only hope there is more to come!! What a delightful find! Bernadette Rowley shares a beautiful story with us, full of fantasy, magic, power, corruption.. and the one princess that is determined to save her world. If you can get your hands on this book.. read it!!14 Comments


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Birgitta Ohlsson participates in Belgrade Pride
Press Release 2012-06-11
Between 30th September and 6th October a Pride festival will again be organised in the Serbian capital Belgrade. Swedish Minister for EU-affairs Birgitta Ohlsson is one of the opening speakers.
– Pride parades are a litmus test for freedom in Europe. For me, as Minister for EU-affairs and as representative of Sweden, it is extremely important to show solidarity with all the victims of persecution who can not show their love openly, says Birgitta Ohlsson.
Civil Rights Defenders has been working against discrimination of vulnerable groups and for lesbian, gay, bisexual and transgender (LGBT) equality and rights in the Balkans for over a decade. The organisation is one of the main organisers of Pride and a unifying factor for the Serbian LGBT community.
– Birgitta Ohlsson's participation in Belgrade Pride is an important gesture of solidarity, at a time when it is difficult or even impossible to organise Pride festivals in many parts of Europe. It strengthens local activists and sends a clear signal to the Serbian authorities that the world sees what is happening and that politicians from countries like Sweden care about the respect for human rights in Serbia, says Robert Hårdh, Civil Rights Defenders Executive Director, who will travel to Belgrade together with Birgitta Ohlsson.
Last year, the National Security Council banned all public manifestations on the current weekend, including the Pride parade, on the grounds that national security was endangered. The National Security Council is made up of Serbia's President, Prime Minister, Minister of Justice, Defense Minister, Minister of the Interior and some of the top leaders in the army and security services.
In 2010 the police protected participants from more than 5,000 violent counter-demonstrators, and the damage to property was estimated at more than 1 million Euro. In 2009 the parade was cancelled after threats from extremist groups.
For more information please contact:
Robert Hårdh, Executive Director, +46 709 14 63 14
Natasha Jevtic Esbjörnson, Head of Communications, +46 709 14 63 43
Tags: Birgitta Ohlsson and Pride.
Regions: Serbia and Sweden.

subset: commoncrawl


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Independent Contractor Status -
How to Demonstrate that you are Self Employed
Independent Contractor Status - Introduction
As time passes it is becoming increasingly difficult to distinguish between different ways of working. If you are working as an independent contractor it is of vital importance that you understand the criteria that the government, and in particular the tax authorities use to distinguish employees from those with genuine independent contractor status.
If you get this judgment wrong there can be significant financial penalties because you will have been paying tax as a self employed person, most likely at a lower average rate than an employee.
If your local tax authority (IRS in the US; HMRC in the UK) ultimately determine that you should have been paying tax as an employee, then not only will you have to pay the difference in tax but you will probably be liable for interest on tax that has been underpaid and possibly some penalties too.
How to demonstrate your independent contractor status
The onus is on self employed individuals to understand the criteria used to determine self employed status and to form a judgment as to whether the way he or she is operating is in line with those criteria.
There are a number of resources available on this site (summarised below) to guide you in making that judgment, but ultimately, you should seek independent professional advice from your accountant or tax planner to confirm that you have correctly interpreted the rules.
Operating model
First take a look at the different operating models, working through the continuum from employee through contractor and consultant. Establish where you are operating on the continuum and take some time to think through the tax status of each of the entities in the contracting or consulting relationships that you have.
Contractor Tests
The main tests of independent contractor status are set out here. There are twenty tests in total and you should regard them as a framework within which to judge where your own operations actually sit.
It is important to realize that it is not necessary to satisfy every one of the test criteria but that, on balance, the majority of criteria should be satisfied.
In forming a judgment, the tax authorities will assess the way you're working and form a balanced opinion based on the number of criteria you are able to satisfy and the strength of the evidence put forward in support of each test point.
IR35 considerations
In the UK, HM Revenue & Customs are alive to the possibility that the substance of the relationship between some contractors and buyers of their services is in essence that of employee and employer, rather than being an arm's length business-to-business relationship.
In these cases, HMR&C can challenge the contractor under the IR35 legislation and if successful reclaim any underpaid tax with interest and penalties. The tests used for IR35 are broadly similar to the US IRS tests set out on the contractors test page.
1099 independent contractor relationships
For the same reasons as it is important for a contractor to be able to evidence his independent status insofar as it relates to his business relationship with his clients, it is equally important for the main (lead) contractor to be able to evidence the independent status of his subcontractors.
In other words, the lead contractor needs to be able to evidence that his subcontractors genuinely do have independent status rather than operating as his own employees. Follow the link for more information on the 1099 independent contractor agreement. and be sure to take independent professional advice.
The investment of some time and effort in reviewing the way you are operating will significantly reduce the likelihood that your independent contractor status will be challenged.
Furthermore, if it is challenged, then familiarity with the main criteria will significantly improve the probability that you will be able to successfully defend your position.
Jump back from Independent Contractor Status to ICB.com Home page


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Fun With Neural Networks in Go
My rekindled interest in Machine Learning turned my attention to Neural Networks or more precisely Artificial Neural Networks (ANN). I started tinkering with ANN by building simple prototypes in R. However, my basic knowledge of the topic only got me so far. I struggled to understand why certain parameters work better than others. I wanted to understand the inner workings of ANN learning better. So I built a long list of questions and started looking for answers.
"I have no special talents. I am only passionately curious." – Albert Einstein
This blog post is mostly theoretial and at times quite dense on maths. However, this should not put you off. The theoretical knowledge is often undervalued and ignored these days. I am a big fan of it. If nothing else, understanding the theory helps me avoid getting frustrated with seemingly inexplicable results. There is nothing worse than not being able to reason about the results you program produces. This especially more important in machine learning which is by default an ill-posed maths problem. This post is merely a summary of the notes I made when exploring ANN learning. It's by no means a comprehensive summary. Nevertheless, I hope you will find it useful and maybe you'll even learn something new.
If you find any mistakes please don't hesitate to leave a comment below. I will be more than happy to learn from you and address any inaccuracies in the text. Let's get started!
Artificial Neural Networks (ANN)
There are various kinds of artificial neural networks. Based on a task particular ANN performs we can roughly divide them into the following groups:
- Regression - ANN outputs (predicts) a number based on input data
- Robotics - ANN uses sensor outputs as inputs and produces some output[s]
- Vision - ANN processes digital images trying to understand them in some way
- Optimization - ANN finds the best set of values to solve some optimization problem
- Classification - ANN classifies data into arbitrary number of predefined groups
- Clustering - ANN clusters data into groups without any apriori knowledge
In this post I will only focus on classification neural networks which are often referred to simply as classifiers. More specifically, I will talk about Feedforward ANN classifiers. Most of the concepts I will discuss in this post are applicable to other kinds of ANN, too. I will assume you have a basic understanding of what a Feedforward ANN is and what components it consists of. I will summarize the most important concepts on the following lines. If you want to dig in more depth, there is plenty of resources available online. You can see an example of a 3-layer feedforward ANN on the image below:
The above feedforward network has three layers: input, hidden and output. Each layer has several neurons: in input layer, in hidden layer and in the output layer. Feedforward neural network is a fully connected network: all the neurons in neighbouring layers are connected to each other. Each neuron has a set of network weights assigned which serve to calculate a weighted input (let's mark it as z) to the neuron's activation function. You can see how this works if we zoom in on nne neuron:
From the image above it should be hopefully obvious that network weights allow to control the output of particular neuron (activation) and thus the overall behaviour of the neural network. Input neurons have unit weights (i.e. each weight is equal to ) and their activation function is [often] what's referred to as identity function. Identity activation function simply "mirrors" the neuron input to its output i.e. . The feedforward network shown on the first image above has two output neurons; it can be used a simple binary classifier. ANN classifiers can have arbitrary number of outputs. Before we dive more into how the ANN classifiers work, let's talk a little bit about what a classification task actually is.
Note: The above mentioned ANN diagram doesn't make the presence of neural network bias unit obvious. Bias unit is present in every layer of feedforward neural network. Its starting value is often set to , although some research documents that initializing the bias input to a random value from uniform Gaussian distribution with (mean) and (variance) can do just fine if not better. Bias plays an important role in neural networks! In fact, bias units are at the core of one of the most important machine learning algorithms. For now, let's keep in mind that bias is present in every layer of feedforward neural network and plays an important role in neural networks.
Classification can be [very] loosely defined as a task which tries to place new observations into one of the predefined classes of objects. This implies an apriori knowledge of object classes i.e. we must know all classes of objects into which we will be classifying newly observed objects. A schoolbook example of a simple classifier is a spam filter. It marks every new incoming email either as a spam or not spam. Spam filter is a binary classifier i.e. it works with two classes of objects: spam or not spam. In general we are not limited to two classes of objects; we can easily design classifiers that can work with arbitrary number of classes.
Note: In practice, most spam filters are implemented using Bayeseian learning i.e. using some advanced Bayesian network or its variation. This does not mean that you can't implement spam filter using ANN, but I thought I'd point this out.
In order for ANN to classify new data into a particular predefined class of objects we need to train it first. Classifiers are often trained using supervised learning algorithms. Supervised learning algorithms require a labeled data set. Label data set is a data set where each data sample has a particular class "label" assigned to it. In case of spam filter we would have a data set which would contain a large number of emails each of which would be known in advance to be either spam or not spam. Learning algorithm adjusts neuron weights in hidden and output layers so that the new input samples are classified to the correct group. Supervised learning algorithms differ from "regular" computer science algorithms in way that instead of turning inputs into outputs they consume both inputs and outputs and "produce" parameters that allow to fit new inputs into outputs:
Learning algorithm literally teaches the ANN about different kinds of objects so that it can eventually classify newly observed objects automatically without any further help. This is exactly how we as humans learn, too. Someone has to tell us first what something is before we can make any conclusion about something new we observe. If you dive a little bit into neuroscience you will find out that our brain is a very powerful classifier. Classification is a skill we are born with and we often don't even realize it. Take for example how often do we refer to insect as flies, mosquitos etc. We hardly ever use their real biological names. It's too costly for our brain to remember the name of every single object in the world. Our brain classifies these objects into existing groups automatically without our too much thinking. Before this happens automatically we are "trained" (taught), so that our brain doesn't classify flies as something like airplanes.
Neural network training is a process during which the network "learns" neuron weights from a labeled data set using some learning algorithm. There are two kinds of learning algorithms: supervised and unsupervised. ANN classifiers are often trained using the former, though often the combination of both is often used in practice. This blog post will discuss the most powerful supervised learning algorithms used for training feedforward neural networks: Backpropagation.
Behind every learning (not just ANN learning) is a concept of reward or penalty. Either you are rewarded when you learnt something (measured by answering particular set of questions) or you are penalized if you didn't (failed to answer the question or answered it incorrectly). Backpropagation, like many other machine learning algorithms, uses the penalty approach. To measure how good the ANN classifier is we define a cost function sometimes referred to as objective function. The closer the output produced by ANN is to the expected value, the lower the value of the cost function for a particular input is i.e. we are penalized less if we produce correct output.
At the core of the backpropagation algorithm is partial derivative of the cost function with respect to its weights and biases i.e. , where is the cost function and and are network weights and biases. Backpropagation effectively measures how much the cost changes with regards to changing network weights and biases. Neural networks are quite complex and understanding how they work can be challenging. Backpropagation summarises the overall ANN behavior in a few simple equations. In this sense backpropagation provides a very powerful tool to understand ANN behavior.
I'm not going to explain how backpropagation works in this post in too much detail. There is plenty of resources available online if you want to dig more into it. In a gist, backpropagation calculates errors in outputs of neurons in each network layer all the way back from the output layer to the output of the first hidden layer. It then adjusts the weights and biases of the network (this is the actual learning) in a way that minimizes the error in the output layer computed by the cost function . The error of the output layer is the most important one for the result, but we need to calculate the errors of each particular layer as these errors propagate through the network and thus affect the network output.
I would encourage you to dive more into the underlying theory. There is a real geeky calculus beauty to the algorithm which will give you a very good understanding of one of the most important machine learning algorithms out there. Instead of explaining the algorithm in much detail, I decided to summarize it in two points which I believe are the most crucial for understanding the behavior of feedforward neural network classifiers:
- Cost function is a function of the output layer i.e. it is a function of output neuron activations.
- Learning slows down if any of the "input" neurons is "low-activation", or if any of the "output" neuron has saturated.
The first point should hopefully be pretty intuitive from the earlier network diagram. We push some input through the network, which produces some output by the output layer neurons. This output is used to calculate the error (cost) with regards to the expected output (label) acccording to the chosen cost function.
Let's zoom in at the second point: learning slowdown. Learning slowdown, in the context of ANN, means the slowdown of the network weights (and bias) change during the run of the training algorithm. Like I said before, backpropagation changes the network weights with regards to the calculated error for given input and expected output. Change of the weights is the core of the learning. When the weights stop changing during backpropagation, the learning stops as the cost no longer changes, hence we can improve the output of the network. By doing a little bit of calculus we could show that backpropagation learning depends on derivation of the activation function. We could sum this up using a simple equation below:
where is the cost function, is the activation (i.e. the output produced by the neuron) of neuron that is an input to network weight of another neuron in the next layer and is the error of the neuron output from the weight . The picture below should give you a better idea about the equation above:
We could further show that the error depends on a derivation of the activaion of the intermediary neuron in the output produced by neuron with weights (remember derivation is always defined in some point - in our case that point is output produced by a particular neuron). The most important implication of this equation for network learning is that the change of cost with regards to change of weights depends on the activation input into weight , , and on activation function derivation in the point equal to output of the neuron with weights . Clearly, activation function plays a crucial role in how fast the neural networks can learn, so it's a topic worth exploring further.
One of the most well known activation functions is sigmoid function often referred to simply as sgmoid. Sigmoid is well known to be used in logistic regression. Sigmoid holds some very interesting properties which make it a natural choice of neuron activation function in ANN classifiers. If we look closely on the sigmoid function on the graph below we can see that it resembles a continuous approximation of step function found in transistor switches which can be used to signal binary output (on or off). In fact, we could show that by tuning sigmoid parameters we could get a pretty good approximation of the step fuction. The ability to simulate a simple switch with boolean behavior is handy for classifiers which need to decide whether the newly observed data belongs to a particular class of objects or not.
I mentioned earlier that if the output neuron saturates then the network stops learning. Saturation means there is no rate change happening which means the derivative in any saturation point is . This means that the partial derivation of cost function by weights in the equation mentioned earlier tends to get to . This is exactly the case with sigmoid function. Notice on the graph above how sigmoid eventually saturates on (when ) or (when ). Sigmoid suddenly doesn't seem like the best choice for the activation function, at least not for the network output neurons. Luckily, by choosing a particular kind of cost function we can subdue the effect of neuron saturation to some degree. Let's have a look at what would such cost function look like.
Cost function and neuron activations
Cost function is a crucial concept for many machine learning algorithms, not just backpropagation. It measures the error of computed output for a given input with regards to expected result. Cost function output must be non-negative by definition. As I will show you later on, good choice of the cost function can hugely improve the performance of ANN learning whilst a bad choice can lead to suboptimal results. There are several kinds of cost functions available. Probably the most well known one is quadratic cost function.
Quadratic cost function calculates mean squared error (MSE) for a given input and expected output:
where is the number of training samples, is the desired output, represents the number of layers in ANN, so is the activation of the output layer neuron for a particular input.
Whilst MSE is suitable for many tasks in machine learning, we could prove that it's not the best choice of the cost function for ANN classifiers. At least not for the ones that use the sigmoid activation in the output layer. The main reason for that is that this combination of activation and cost can slow down ANN learning.
We could, however, show by performing a bit of calculus that if the output neurons are linear i.e. their activation function is defined as , then the quadratic cost function will not cause learning slowdown and thus it can be an appropriate choice of cost function. So why don't we ditch the sigmoid and go ahead with the linear activations and quadratic cost function combination instead? It turns out linear activations can still be pretty slow in comparison to other activation functions we will discuss later on.
So what should we do if our output layer neurons use sigmoid activation function? We need to find a better cost function than the quadratic cost, which will not slow down the learning! Luckily, there is one we can use instead. It's called cross-entropy function.
Cross-entropy cost function
Cross-entropy is one of the most widely used cost functions in ANN classifiers. It is defined as follows:
where is the total number of training samples, is expected output for a particular input and is an output activation for the given input.
It's important to point out that if you do decide to use the cross entropy cost function you must design your neural network in the way that contains as many outputs as there are classes of objects. Additionally the expected outputs should be mapped into one-of-N matrix. Having this in mind, you can start seeing some sense in the cross entropy function. Befor I explain in more defatil that cross-entropy cost addresses the problem of learning slowdown when using the sigmoid activation, I want to highlight some important properties it holds:
- it's a non-negative function (mandatory requirement for any cost function)
- it's a convex function (this helps to prevent getting stuck in local minimum during learning)
Notice that if for some input then the first term in the above equation sum addition disappears. Equally if the same thing happens with the second term. We can therefore break down the cross-entropy cost function into following definition:
where is expected output and is neural network output. Plotting the graphs for both cases should give us even better understanding.
In the first case we are expecting the output of our network to be . The further the ANN output is from the expected value (), the higher the error and the higher the cost output:
In the second case, we are expecting the output of our network to be . The closer the output of our network is to the expected output (), the smaller the cost and vice versa:
Based on the graphs above we can see that cross-entropy tends to converge towards zero the more accurate the output of our network gets. This is exactly what we would expect from any cost function.
Let's get back to the issue of learning slowdown. We know that at the heart of the backpropagation algorithm is a partial derivative of cost function by weights and biases. With a bit of calculus we can prove that when using cross-entropy as our cost function and sigmoid for activation in the output layer, the resulting partial derivative does not depend on the rate of change of activation function. It merely depends on the output produced by it. By choosing the cross-entropy we can avoid the learning slowdown caused by the saturation of the sigmoid activation function.
If your output neurons use sigmoid activation it's almost always better to use corss-entropy cost function.
Hyperbolic tangent activation function (tanh)
Before we move on to the next parargraph, let's talk shortly about another activation function whose properties are similar to the sigmoid function: hyperbolic tangent, often referred to simply as tanh. Tanh is in fact just a rescaled version of sigmoid. We can easily see that on the plot below:
Similar to the sigmoid, tanh also saturates, but in different values: and . This means you might have to "normalize" the output of the tanh neurons. Once your tanh outputs are normalized you can use the cross-entropy cost function in backpropagation algorithm. Some empirical evidence suggests that using tanh instead of sigmoid provides better results for some learning tasks. However, there is no rigorous proof that tanh outperforms sigmoid neurons, so my advice to you would be to test both and see which one performs better for your particular classification task.
Softmax activation and log-likelihood cost function
By using cross-entropy function in combination with sigmoid activation we got rid of the problem with saturation, but the learning still depends on the output of the activation function itself. The smaller the output the slower the learning gets. We can do better as we will see later on, but first I would like to talk a little bit about another activation function which has found a lot of use in ANN classifiers and in deep neural networks: softmax function, often referred to simply as softmax. Softmax has some interesting properties that make it an appealing choice of the output layer neurons in ANN classifiers. Softmax is defined as below:
where is activation of -th neuron and is input into activation of -th neuron. The denominator in the softmax equation simply sums "numerators" across all neurons in the layer.
It might not be entirely obvious why and when should we use softmax instead of sigmoid or linear activation functions. As always, the devil lies in the details. If we look closely at the softmax definition, we can see that each activation represents its proportion with regards to all activations in the same layer. This has an interesting consequence for the other neuron activations. If one of the activations increases the other ones decrease and vice versa i.e. if one of the neurons is dominant, it "subdues" the other neuron outputs. In other words: any particular output activation depends on all the other neuron activations when using the softmax function i.e. particular neuron output no longer depends just on its weights like it was the case with sigmoid or linear activations.
Softmax activations of all neurons are positive numbers since the exponential function is always positive. Furthermore, if we sum softmax activations across all neurons in the same layer, we will see that they add up to :
Given the above described properties we can think of the output of softmax (by output we mean an array of all softmax activation in particular network layer) as a probability distribution. This is an excellent property to have in ANN classifiers. It's very convenient to think of an output neuron activations as a probability that particular output belongs to a particular class of objects. For example we can think of in the output layer as an estimate of the probability that the output belongs to the -th object class. We could not make such assumption using sigmoid function as it can be proved that the sum of all activations of sigmoid function in the same layer does not always add up to .
We have shown earlier that by clever choice of cost function (cross-entropy) we can avoid learning slowdown in ANN classifiers when using sigmoid activations. We can pull the same trick with softmax function. Again, it will require a different cost function than the cross-entropy. We call this function log-likelihood. Log-likelihood is defined as below:
where is the last network layer and denotes that the expected output is defined by class .
Just like cross-entropy, log-likelihood requires us to encode our outputs into on-of-N matrix. Let's have a closer look at this cost function like we did with cross-entropy. The fact that the output of softmax can be thought of as a probability distribution tells us two things about the cost function:
- The closer the particular output is to the expected value is, the closer its output is to and the closer the cost tends to get to .
- The further the particular output is from the expected value, the closer its output is to and the cost tends to grow to infinity.
The log-likelihood behaves exactly like we would expect the cost function to behave. This can be seen on the plot below:
So how does softmax address learning slowdown? By performing a bit of calculus we could once again show that partial derivative of log-likelihood by weights (), which is a at the core of backpropagation algorithm, merely depends on the output produced by activation output just like it was the case with sigmoid and cross-entropy. In fact, softmax activation and log-likelihood perform quite similar as sigmoid and cross-entropy. So when should you use which one? The answer is it depends. A lot of influential research in ANN space tends to use softmax and log-likelihood combo which has a nice property if you want to interpret the output activations as probabilities of belonging to a particular class of objects.
Rectifier linear unit (ReLU)
Before we move on from the topic of activation functions, I must mention one last option we have at our disposal: rectifier linear unit, often referred to simply as ReLU. ReLU function is defined as follows:
ReLU has been an active subject of interest of ANN research. Over the years it has become a very popular choice of activation function in deep neural networks used for image recognition. ReLU is quite different from all the previously discussed activation functions. As you might have noticed on the plot above, ReLU does not suffer from saturation like tanh or sigmoid functions as long as its input is greater than . When the ReLU input is negative, the ReLU neurons stop learning completely. To address this, we can use a similar function which is a variation of ReLU: Leaky ReLU (LReLU).
LReLU is defined as follows:
where is a small constant which "controls" a slope of LReLU output for the case of negative values. The actual value of the constant can differ for different use cases. The best I can advise you is to experiment with different values and pick the one that gives you the best results. LReLU provides some improvement in learning in comparison to the basic ReLU, however the improvement can be negligible. Worry not, there seems to be a better alternative.
You can find plots of both ReLU and LReLU on the picture below:
A group of Microsoft researchers achieved some outstanding results in image recognition tasks using another variation of ReLU called Parametric Rectifier Linear Unit (PReLU). You can read more about the PReLU in the following paper. You will find out, PReLU is just a "smarter" version of LReLU. Whilst LReLU forces you to choose the slope constant before you kick off the learning, PReLU can learn the slope constant during backpropagation. Furthermore, whilst LReLU slope constant is static i.e. it stays the same for all neurons during the whole training, PReLU can have different slope values for different neurons at different states of the training!
The question now is, which one of the ReLU activations should we use? Unfortunately there does not seem to exist any rigorous proof or theory about how to choose the best type of rectifier linear units and for which tasks it is the most suitable choice of neuron activation. The current state of knowledge is based heavily on empirical results that show that rectifier units can improve the performance of restricted boltzman machines, acoustic models and many other tasks. You can read more about evaluation of different types of rectifier activation function used in convolutional networks in the following paper.
Weights initialization
Choosing the right neuron activations with appropriate cost function can clearly influence the performance of ANN. But we can go even further. I found out during my research the network weights initialization can play an important role in the speed of learning. This was a bit of a revelation to me. I would normally go ahead and initialize all neuron weights in all hidden layers to values from Gaussian distribution with mean and standard deviation without too much thinking. It turns out there is a better way to initialize the weights which can increase the speed of learning!
So what is wrong with choosing and parameters of Gaussian distribution I mentioned earlier? Imagine a situation when a significant number of neuron inputs are . This is not an unusual situation. As you could see earlier, sigmoid or ReLU can easily produce values if the neurons inputs are . When that's the case, the weighted output of the neurons (i.e. the input into the neuron activation function) in the next layer can produce values of Gaussian distribution whose standard deviation is (the actual value depends on number of neurons). The problem with large standard deviation of activation input is that it causes the saturation of the neuron outputs. As we learnt earlier this has a consequence of learning slowdown.
We can avoid this problem by choosing a better set of Gaussian distribution parameters for weight initialization. There is no exact formula what should the standard deviation of weight initialzation be, but some research suggests that by choosing the standard deviation to be around the inverse of the square root of number of input weights () should give you better performance than the uniformly distributed values I mentioned at the beginning of this discussion. If we plot the values of both network weights distributions for both cases it could look something like the plot below:
You should spot straight away that the distribution we are aiming for is much sharper i.e. its bell curve is much steeper. Low standard distribution helps to avoid neuron saturation and speeds up ANN learning, which is what we are striving for. You may have noticed that I did not mention how to initialize weights of bias neurons. It turns out, the weights initialization of bias neuron does not play any significant role in ANN learning so it should be ok to stick to the original standard deviation without worrying too much.
Learning optimization
The goal of ANN learning algorithm is to find network weights for which the output of the cost function is as minimal as possible. This is clearly an optimization problem: we need to find weights that niminimize the output of the cost function. One of the most famous optimization algorithm used to solve this problem is called gradient descent. I'm not going to discuss the gradient descent algorithm here. Again, there is plenty of resources online if you want to understand it. And I would strongly advise you to do so, as gradient descent has huge number of applications, not only in machine learning.
Instead, I would like to mention some alternative solutions. In particular, I would like to talk shortly about some advanced optimization algorithms you can use instead of gradient descent. There are several options available at our disposal. Probably the most well known is Broyden–Fletcher–Goldfarb–Shanno, often referred to simply as BFGS and its limited memory alternative L-BFGS. Another alternative would be Conjugate gradient.
Why do I mention these advanced optimization methods? First of all, majority people are well aware of the gradient descent and so was I when I started doing my research. At some point I came across Yann LeCun's paper on efficient backpropagation which discusses them in broader detail. These algorithms can seem very complicated, but their efficient implementations are available in many numerical toolboxes. Their biggest advantage is they don't require much tuning. At least not as much as gradient descent. There is no need to pick many parameters except for number of iterations we want to run them for. They just work and if implemented properly they often outperform gradient descent. They are often more suitable choice for large machine learning problems which deal with huge data sets than gradient descent. If these algorithms are so good why do so many people still rely on good old gradient descent or any of its variations?
The answer, as it often is in the world of science (or life in general), is the complexity. Like I already mentioned, some of these algorithms are quite advanced and not easy to understand for some people. This can make their debugging quite hard. Often their implementations differ between various toolboxes which makes their debugging even harder. Finally, gradient descent performance is often acceptable and much better understood. It's good to be aware that these algorithms exist and are available to use.
Neural networks in Go
Armed with the newly gained knowledge I could finally have a better understanding of neural networks. But I didn't want to stay in theory. After all a certain wise man once said something which I find incredibly true:
"What I can not create I do not understand" – Richard Feynman
I've been a big fan of Go language for a while and I wondered on and off how well does it perform in numerical computations. After doing a bit of research I found the awesome gonum project that contains a great wealth of numerical packages. I took them for a spin and to my great joy, I found out that the gonum packages are pretty damn fast as long as you take advantage of the vectorised operations. Gonum is one of the biggest gems in the Go ecosystem, so do not hesitate and spend some time exploring the packages in it - you won't regret!
The result of my hacks is a small project. I am well aware of the awesome projects like go-ml or golearn and many many others. The main reason why I decided create my own implementation despite many a people discouraging me as it being a waste of time was for purely learning experience and therefore the project itself should therefore be treated accordingly :-) You might find it useful and maybe it will even inspire you to hack on your own, improved implementation. The learning experience I got from this was priceless!
We have finally reached the end of the post. Thank you very much for reading! It's been a long ride! We learnt about various techniques that can help us speed up ANN learning. We learnt about learning slowdown and how we can address it by choosing appropriate combination of neuron activations and cost function. Based on the research I've done, it seems the most popular choice of neuron activation function in classification tasks is some varioation of ReLU for the hidden layer neurons (to model system's non-linearities) and softmax activation for the output layer neurons. The presence of softmax in the output layer "dictates" the use of log-likelihood cost function. As always, YMMV and the particular choice might differ based on the taks your network performs. All you need to do is to roll up your sleeves and make some experiments.
Writing this blog post has been amazing personal journey for me. It made me revisit some old knowledge of neural networks theory and learn tonnes of new stuff from many research papers I had not heard of before. I hope you have enjoyed reading thist post as much as I have writing it. If you have any comments, do not hesitate to leave them below.


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Council News
by Vicente Victor Ocampo, Jr. MD
In simple and meaningful rites, the Philippine Ocular Inflammation Society ( POIS ) launched its book " Quick Guide to Uveitis " during the Opening Ceremonies of the 2017 Philippine Academy of Ophthalmology ( PAO ) Congress last December 5 at the SMX Convention Center. Editor-in-chief Dr. Franz Marie Cruz started the proceedings by delivering a compelling presentation on the highlights of the manual. This was followed by the unveiling of a life-sized version of the book by founding members Drs. Jacinto Dy-Liacco and Rosie Noche assisted by PAO President Dr. Sherman Valero and POIS President Dr. Vicente Victor Ocampo, Jr. Dr. Ocampo ended the event with his closing remarks acknowledging the many sectors responsible for turning this long-cherished dream of the society into a reality. Throughout the launch, POIS members were onstage in recognition of their valuable contribution to the timely production of the manuscript.
" Quick Guide to Uveitis " is the first locally published reference book in Ophthalmology that was written by members of a single subspecialty group. It is a collaboration of 18 Uveitis specialists from various training backgrounds throughout the country. Composed of 5 sections consisting of 19 chapters, the manual tackles 30 of the most common intraocular inflammatory diseases seen in the country like acute anterior uveitis, ocular tuberculosis and Vogt Koyonagi Harada Disease. In addition, there are 122 coloured photos and 31 tables which will enhance better understanding of the various uveitic diseases.
Almost 600 copies of " Quick Guide to Uveitis " were sold during the convention in its first 3 days of release!!
About The Author
Vincente Victor Ocampo, Jr, MD
President, Philippine Ocular Inflammation Society
PAO Council Newsletter
Sight Saving Month at the DOH Eye Center
by Ronald Steven S. Medalle II, MD-MBA
OsMak Eye Rewind: Celebrating 25 years of Ospital ng Makati's Ophthalmology Department
by Faye Corcuera, MD
POIS Participates at 2017 PAO Congress
by Vicente Victor Ocampo, Jr. MD
"Quick Guide to Uveitis" Unveiled
by Vicente Victor Ocampo, Jr. MD
Medical Mission: Antique 2017
by Jessica Daza-Robes, MD
Superheroes' Mission to Save Sight
by Jessica Daza-Robes, MD
Christmas Messages
by Ryan Rodriguez, MD, Jubaida M. Aquino, MD and Yvette Marie B. Santiago, MD
by Ryan Rodriguez, MD, Jubaida M. Aquino, MD and Yvette Marie B. Santiago, MD
Changing of the Guards
by Ryan Rodriguez, MD
Are you an eyeMD by profession but writing is your passion? The eFocalPoint is in need of contributors.
Join us in our mission to educate, inform, and entertain with the aim of strengthening camaraderie in the ophthalmology community.
Email us at email@example.com for details on how you can contribute.


text: Hi and welcome! Everyone on this list must be out hiking or on vacation. Some trail info is available on the Trail Updates at the following Web site; http://www.florida-trail.org If you are interested in a particular section ask on this list and someone usually answers. New maps for the Fl Trail are promised in the near future. From Here to There On the Florida Trail is an account by the authors, Susan Roquemore and Joan Hobson of there thru hike of the Trail. A guidebook with trail descriptions is available thru the Fl Trail Assoc. which also prints a bimonthly newsletter with various hikes around the state. What section of the AT are you planning to do? I section hiked the AT from '89 - '93. Have a great hike. Triathlon Grandma firstname.lastname@example.com wrote: > > Hi all just join this list and recieved my first message today so i > know that someone is out there. I am in the tampa area and will be > doing a section hike on the at next month. While looking for AT info I > keep coming across mention of the Florida trail However have not found > any web pages that map the trail or give locations for its sections. Are > there any? > If so let me know. Iam looking for some good weekend and week long > hikes for next winter here in Florida. Glad this list is here. > > buddha > > * From the Florida Trail Mailing List | http://www.backcountry.net * * From the Florida Trail Mailing List | http://www.backcountry.net * ============================================================================== To: <firstname.lastname@example.com>, <firstname.lastname@example.com>


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You will need
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Verify whether or not the e-mail with a specific name simply. And there are a few proven ways. The simplest way to write a letter on the box. The contents of it can be absolutely any. All major email services have a system of reverse notifications. And if the letter cannot be delivered because of absence of the recipient – you will receive a report.
The second method takes a little more time, but will give a perfect result. Try to register a mailbox with the given name. If it already exists, the system will not allow you to enter his name upon registration. The only disadvantage is you first have to figure out which site you can register mailboxes this format.
If you don't fit both ways, you can use the services to check for the existence verify existence of a mailbox.


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After a small break from portable video games so I could finish reading some books, I'm finally back on playing Persona Q. This game is pure fan-service for Persona 3/4 fans. And I mean fan-service in a very positive way.
I am taking my time with the game and I recently finished the first dungeon.
While I was having my break from Persona Q, I noticed that I just couldn't stop humming the battle theme. It is so catchy and it really pumps you up every time you engage an enemy. One nice feature is having the battle theme coming in 3 versions, 2 of them you can hear in the game.
The DARK HOUR/影時間 version when you're using the Persona 3 main protagonist
The MIDNIGHT CHANNEL/ヨナカテレビ version when you're using the Persona 4 main protagonist
The 3rd version is available in the arranged OST, Persona Q: Sound…
View original post 74 more words


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Former art chair Harvey named head of Applied Arts at Royal College of Art
Rebecca Harvey, former professor and chair of the Department of Art, was recently named head of Applied Arts at the Royal College of Art in London, which is considered by the QS World University Rankings as the top postgraduate art and design university in the world.
In addition to this new appointment, Harvey will continue to serve the Ohio State community in a new role as Applied Arts and Engineering/International Liaison, which will allow her to work with both the College of Arts and Sciences and the College of Engineering to cultivate collaboration between Ohio State and other London institutions, particularly the Royal College of Art.
As head of Applied Arts, Harvey is charged with overseeing the development of the Royal College of Art's Ceramics and Glass program and its Metals and Jewelry program, which are being merged into one department. She will help develop the institution's goal of growing and expanding its program and foster international relations. Her tenure officially began Sept. 12.
In accepting the position, Harvey, who'd been at Ohio State for nearly 25 years, thought of how she could leverage her new post into a joint opportunity between Ohio State and the Royal College of Art. It seemed the perfect time, she said, to put into place a long-discussed bridge between the disciplines of art and engineering. Harvey spoke often with mechanical and aerospace engineering professor Blaine Lilly about how to connect students' research to the world and how to give them more opportunities to work beyond and through disciplinary boundaries.
There was an enthusiastic response from both Arts and Sciences and Engineering, and Harvey's position as Applied Arts and Engineering International Liaison materialized. Within the role, she hopes to develop connections between Ohio State and the Royal College of Art to facilitate student and faculty exchanges, study abroad opportunities and interdisciplinary ventures between arts and engineering.
"We'd been getting some really interesting data lately that shows our biggest population of students after our art majors are engineering majors. It makes perfect sense; they're students who like to build things and make things and test things," Harvey said. "I've had lots of great discussions with engineering faculty about the importance of experiential learning and learning by making and learning by doing. … My work as international liaison becomes a way of extending the planned ties between the two units. I think that this becomes really important — providing a space for new ways of working and new methodologies."
Harvey plans to spend much of her first year building and fostering relationships that can serve as bridges to new internship and research opportunities, both within the Royal College of Art and their partner institutions and beyond into the broader community. She is particularly focused on opportunities that allow individuals to cross-disciplinary boundaries. Ohio State has a large alumni base in London and a broad slate of study abroad opportunities. Harvey sees her first steps as identifying people and potential areas of synergy.
I'm hugely attached to Ohio State," Harvey said. "To have this ability to go off and do this really interesting thing and still maintain this connection to Ohio State and be able to add opportunities to Ohio State and add opportunities to the Royal College of Art, for me that was the big win-win."
Harvey earned her BFA in crafts from the University of the Arts before earning her MFA in ceramics from Cranbrook Academy of Art.


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How to Install Thin Stone Veneer
Here is the one document that explains the recommended process in detail.
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How to Plan and Install Thin Stone Veneer Columns In this video David Croteau explains
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What Moisture Control Cavity Weep System Should I Use?
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Mix of Boston Blend Mosaic, Boston Blend Round, Boston Blend Square & Rec, and Boston Blend Ledge Stone Formula: Mix & Match Colors and Shapes
Quick Installation Tips
In your showroom you have a fireplace (see below), with a lot more tan colors than the Boston blend in the other samples. Is this random based on when you get the stone, up to the mason to pick and choose stones, or something else?
See this FAQ on its own page (useful for sharing).
A customer writes…
Hi, I was in a few weeks ago looking at stone and had a few quick questions.In the displays of the Boston Blend Ashlar vs Ledge the Ashlar seems much "tighter".Is this an illusion or just how these displays were put together?
See this FAQ on its own page (useful for sharing).
Stoneyard Thin Veneer is a natural product, not man-made from concrete. The stone is at least one million years old, has been through countless freezes and thaws so there will be no problem with expansion and contraction, and will not fade. Unlike man-made faux stone, it is the same color throughout.
The stone is cut and crafted from either natural New England Fieldstone or stone cut from a quarry in the New England area of the U.S.
When installing thin veneer outdoors, it is essential to use proper installation methods such as cement board and a water barrier to prevent water from getting behind the stone.
See this FAQ on its own page (useful for sharing).
Industry sales of stacked stone panels have been rising steadily each year for the last five years. While we cut and split individual natural thin stone from New England – all day every day – we see customers from every region of the country choosing stacked stone panels. Here are the pros and cons of these panels.PRO: Stones are cut, fit, and glued together into an interlocking panel with no mesh backing. This significantly reduces onsite cutting and allows for a much quicker install.
CON: The panels still have to be handled carefully during installation to avoid breakage.
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CON: If you don't stagger the panels, you will see a stepped stairway seam.
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See this FAQ on its own page (useful for sharing).
Stoneyard.com's New England Fieldstone was created by Mother Nature, making it one of the greenest building products available. In addition, all of our stone comes from within a 75-mile radius of our Littleton, MA location, reducing the amount of shipping and thereby leaving a small carbon footprint.
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3. Products That Avoid Toxic or Other Emissions
- Natural or minimally processed products – Products that are natural or minimally processed can be green because of low energy use and low risk of chemical releases during manufacture. These can include wood products, agricultural or nonagricultural plant products, and mineral products such as natural stone and slate shingles.
- Alternatives to ozone-depleting substances – Included are categories where the majority of products still contain or use HCFCs.
- Alternatives to hazardous products – Some materials provide a better alternative in an application dominated by products for which there are concerns about toxic constituents, intermediaries, or by-products. Fluorescent lamps with low mercury levels are included here, along with form release agents that won't contaminate water or soils with toxicants. Also included here are alternatives to products made with chlorinated hydrocarbons such as polyvinyl chloride (PVC) and brominated fire retardants.
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- Products that reduce pollution or waste from operations – Alternative wastewater disposal systems reduce groundwater pollution by decomposing organic wastes or removing nutrients more effectively. Masonry fireplaces burn fuel-wood more completely with fewer emissions than conventional fireplaces and wood stoves. Recycling bins and compost systems enable occupants to reduce their solid waste generation.
4. Products That Save Energy or Water
- Building components that reduce heating and cooling loads – Examples include structural insulated panels (SIPs), insulated concrete forms (ICFs), autoclaved aerated concrete (AAC) blocks, and high-performance windows and glazings. In the case of windows, the base standard for energy performance of windows is an NFRC-rated unit U-factor. If the windows are made from an environmentally attractive material (e.g., high recycled content or superb durability), the energy standard can be less stringent. If the frame material is nongreen, such as PVC (vinyl), the energy standard should be more stringent.
- Equipment that conserves energy and manages loads – With energy-consuming equipment, such as water heaters andrefrigerators, dishwashers, and clothes washers,etc you can use standards set by Energy Star to judge the water or energysavings.
- Renewable energy and fuel cell equipment – Equipment and products that enable us to use renewable energy instead offossil fuels and conventional electricity are highly beneficial from an environmental standpoint. Examples include solarwater heaters, photovoltaic systems, and wind turbines. Fuel cells are also included here, even though fuel cells today nearly always use natural gas or another fossil fuel as the hydrogen source-they are considered green because emissions are lower than combustion-based equipment and because the use of fuel cells will help us eventually move beyond fossil fuel dependence.
- Fixtures and equipment that conserve water – All toilets and most showerheads today meet the federal water efficiency standards, some are more efficient than others but not all of these products perform the same.
5. Products That Contribute to a Safe, Healthy Built Environment
- Products that do not release significant pollutants into the building – Included here are zero- and low-VOC paints, caulks, and adhesives, as well as products with very low emissions, such as nonformaldehyde manufactured wood products.
- Products that block the introduction, development, or spread of indoor contaminants – Certain materials and products are green because they prevent the generation or introduction of pollutants-especially biological contaminants-into occupied space.
- Products that remove indoor pollutants – Certain ventilation products, filters, radon mitigation equipment, and other equipment and devices that help to remove pollutants or introduce fresh air. Because ventilation equipment is now fairly standard, only products that are particularly efficient or quiet, or that have other environmental benefits are considered green.
- Products that warn occupants of health hazards in the building – Included here are carbon monoxide (CO) detectors, lead paint test kits, and other IAQ test kits.
- Products that improve light quality – There is a growing body of evidence that natural daylight is beneficial to our health and productivity. Products that enable us to bring daylight into a building, including tubular skylights, specialized commercial skylights, and fiber-optic daylighting systems, are all green by nature.
- Products that help control noise – Noise, both from indoor and outside sources, adds to stress and discomfort. A wide range of products are available to help absorb noise, prevent it from spreading, masking it, and even reducing it with sound-cancellation technologies.
- Products that enhance community well-being – Looking beyond the walls of a building, many products can contribute to safer neighborhoods, increasing walkability and making high-density communities appealing.
Source: US Green Building Council, Green Building Inc., NAHB, ENERGY STAR
See this FAQ on its own page (useful for sharing).
David Croteau, owner and mason at Stoneyard™, explains the steps needed to create a full-scale mockup for customer approval prior to installing thin veneer in this 4-part video series on how to create a Thin Veneer Mockup:
See this FAQ on its own page (useful for sharing).
The temperature needs to remain at 40 degrees or higher for 72 hours to cure. We can recommend Laticrete Hi Bond Rapid which will speed up the cure time, but 72 hours is still advised.
There is a simple rule to follow when the temperature is low during installation: The 18º (8 ºC) Rule – for every 18ºF below 70ºF (8ºC below 21ºC), portland cement and epoxy based materials take twice as long to cure.
See this FAQ on its own page (useful for sharing).
No masonry shelf is needed. Stoneyard™ Thin Veneer can be installed directly on cement board or brick.
See this FAQ on its own page (useful for sharing).
With the LATICRETE system you do not need to point.
See this FAQ on its own page (useful for sharing).
A diamond blade on a right angle grinder or wet saw. We recommend installation by a Certified Thin Veneer Installer.
See this FAQ on its own page (useful for sharing).
For each linear foot of corners installed you will get approximately 0.75 SF of coverage.
See this FAQ on its own page (useful for sharing).
If you are covering a corner with stone then…yes. Our natural stone thin veneer corners give your project the appearance of full thickness stone.
See this FAQ on its own page (useful for sharing).
How to Install a Dry Laid Fieldstone Retaining Wall
See this FAQ on its own page (useful for sharing).
Use our on-line product calculators to determine coverage or send us project details and plans using our contact form.
See this FAQ on its own page (useful for sharing).
Please read Installing Thin Stone Veneer for more information.
See this FAQ on its own page (useful for sharing).
Our natural thin veneer stones are individual stones. We also have stone panels.
See this FAQ on its own page (useful for sharing).
Building Veneer is 4 times heavier than Thin Veneer weighing in at 60 lbs/sf.
See this FAQ on its own page (useful for sharing).
14 lbs/sf or less (average of 13 lbs).
See this FAQ on its own page (useful for sharing).
We would be happy to mail some pieces out to you. Order samples on the individual product page for the stone you are interested in. Seeing the actual stone will help you compare color and texture.
See this FAQ on its own page (useful for sharing).
Yes by purchasing in increments of 5 sf or 168 sf. If you are ordering crates of Boston Blend™ Thin Veneer, for example, you can order an additional crate (168 sf) of Greenwich Grey or Colonial Tan to add more grey or tan to the mix to achieve the desired color blend.
See this FAQ on its own page (useful for sharing).
Flats are packaged in 168 square foot crates or 5 square foot boxes.
Corners are packaged in 150 linear foot crates, 75 linear foot crates, or 5 linear foot boxes.
See this FAQ on its own page (useful for sharing).


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Strata Owners
SCA WA is the leader in the Strata Title Community in Western Australia and is committed to the ongoing support of members by:
- Providing Education & Professional Development
- Promoting Professionalism and a Code of Ethics
- Providing clear and relevant infromation to government, community and members.
This is driven by our core values of honesty, integrity and excellence.
Membership of SCA WA is open to anyone with an interest in strata schemes, including Strata Managers and their staff, Real Estate Agents, service providers to the strata industry, Accountants, Lawyers, Surveyors and not the least, Lot Owners in Strata Schemes. SCA WA is about bringing together professionals who understand all about the complex laws that govern strata/survey/strata property, with the people who live, and work in Strata Communities. It also provides education, advice, and advocacy to enable greater understanding of the legislative environment and individuals' rights and obligations.
Do you own and live in a strata titled property? or are you an investor with strata titled property as part of your portfolio?
As an owner of a strata titled property, you have a number of obligations, including:
- abiding by any by-laws (or rules) of the strata company
- maintain and repair the common property
- paying levies to administer the strata scheme, such as insurance, maintenance and repair of common property
- attend meetings to discuss and vote on issues, including expenses, repairs, improvements and management of the complex.
Are you considering buying a strata titled property?
Before you buy a strata titled property, check whether it is a registered strata titled lot or a proposed strata titled lot. The main difference between the two is the information that the seller must give you prior to the sale. As a minimum, the seller must give you the following:
- a copy of the strata plan, which indicates the lot being sold and provides information about the lot.
- a copy of the standard and any non-standard by-laws.
- a form called Buying and Selling a Strata Titled Lot (Form 29). Form 29 outlines your rights and obligations as an owner of a strata titled property.
- a form called Disclosure Statement: Sale of Strata Titled Lot or Proposed Strata Titled Lot (Form 28).
Form 28 sets out a list of all the information you should receive before buying a strata titled property and your rights if you do not receive the information. Only if you are happy with the content of the forms should you sign Form 28. Signing Form 28 is not an offer or contract to buy the strata titled property - it simply shows you have received and understood the information provided. For more information including retired persons strata schemes go to the Department of Commerce website
Become a Member
SCA WA has introduced membership for Lot Owners to assist with navigating the complex area that is strata titles. Lot Owners and members of Body Corporate committees also known as 'Council of Owners' may face significant challenges when learning about the many aspects of residing in, and managing, properties that fall within a Strata titles scheme.
Membership Category
- Strata Company Member - (Via its Council).
Membership is held by an owner authorised to represent the Strata Scheme.
Sign up to become a Strata Community Member
- Owner Member
Membership is held by a' Lot Owner '
Sign up to become an Owner Member
Member Benefits
- Member education program
Members receive a substantial discount on registration to information seminars such as the 'Lot Owner Forums' designed to educate on strata matters.
- Member advisory line
Obtain objective advice on day to day issues
- Access to latest Strata news and information
through member e‐bulletins, e‐news, & our national magazine, 'Inside Strata'.
- Best Practice Guides
A series of three booklets, The Appointment of Strata Company Manager, Role of the Strata Company Manager, Strata Company Financial Reports and information.
Annual Membership Fees
Owner Member
$ 66.00
Strata Company Member under 10 lots
$ 143.00
Strata Company Member 10 lots or more
$ 286.00


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Drummond Peltier
You've seen the names. These guys only need one name to clue you in to who they are. Conan. Holmes. Langford. Grayson. Zygyk. Pudge. Drummond.
What's that you say? Who? Drummond? Drummond. That's right Drummond. You know the stats. You know the records. What you may not know is the story. After some investigative reporting, Kenny was able to do what Kenny do. Kenny was able to find out the rest of the story. The story of Mr. Drummond Peltier...
Drummond was a tall kid with a killer fastball. Growing up in a wealthy family and practically raised by his housekeeper, he threw harder than anyone at his boarding school. After an amazing little league career where he went 47-0 (completing every game he pitched) he lit up the Jr High circuit going 33-0 in 3 seasons where, yep you guessed it, he completed every game. Drummond then pitched for the famed North Rockland High School team in the early 90s leading them to 3 consecutive Class A state championships. This time he went 52-0 over three seasons with, you guessed it, 52 complete games. North Rockland remains the only Class A team in New York state history to win 3 consecutive state championships.
After being the most successful high school pitcher in state history, Drummond went to LSU and along with Todd Walker, led the Tigers to their 2nd National Championship in 1993 going 7-0 (with 7 complete games) as a red shirt freshman. What about the rest of his college career? Drummond played through his full elligibility and led the Tigers to two more National Championships! When all was said and done he ended his career at LSU a remarkable 74-0 with 74 complete games and 3 National Championships. This is also where he got his nickname..."Mr. Drummond"
Perhaps equally amazing in this story was that Mr. Drummond was raising his daughter, Kimberly, as a single parent throughout his pitching dominance. Once he was drafted by the Chicago Winds he was called up and pitched his first and only game of his career where he won in the only way he knew how...by pitching a complete game. During his rookie season however, his beloved houskeeper Lucy took ill and passed away. Her death-bed wish was that Mr. Drummond would take care of her two sons, Willis and Arnold. In the end Mr. Drummond did what he had to do. He moved back to New York, leaving baseball behind, and became a single parent of 3 wonderful children.
Now Kenny ain't the sentimental type. Kenny don't be shedding no tears for no one. But one thing Kenny knows...Mr. Drummond is a saint. Probably the most dominant pitcher of his generation, he belongs in the Hall of Fame. There are all types of players in the Hall and remember, it takes Differn't Strokes to move the world. (rumor has it he has been recruited by King Lewis to pitch for his beer league softball team this season)
Kenny is sad to announce the passing of Mr. Drummond. A great pitcher, father, and generous man who will be missed. God Bless you Drummond Peltier. You were one of the greats deserving of recognition of the highest honor in the ABPA Hall of Fame!


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Accounting and auditing services are the foundation of our business. We provide quality, value-added accounting services, while adhering to the highest moral, ethical and professional standards required of our profession.
Accurate financial information keeps your business running smoothly and is key to sustaining your business well into the future. We offer personalized accounting services designed to help you identify opportunities for increased profitability and growth.


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Guitar Tabs, Chords and Lessons
Guitar Tabs, Guitar Chords and Lessons Learning Center
History of the Classical Guitar, Part 3
Before you move on to learning about guitar tabs, guitar chords or guitar tablature, read this passage about the origin of the word guitar. You will give you an advantage when you do decide to learn guitar chords, guitar tabs or tablature. Guitar tabs are fun, but learning about the origins can be even funner!
Read Next Article - Guitar Lessons Chords, Tabs and Guitar History »
« Back to Learning Center Table of Contents
©2006 Crossroads Guitar Lessons Online


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To the wall! To the wall! Let me take you there!
I'd given so much thought to yesterday's column that it never made it to print. Had been working on summary of the State Track Meet. Crowning Milo The Conqueror. My story of the weekend. Two things jumped. A huge personal best and a wall at 600 meters.
Made me reflect on my own racing career, relative as it may be. Those epiphanous efforts where a death grip held the towel, refusing to let it drop let alone throw it in. Those rascals I raced week in and week out, month in and year out, on the Texas Gulf Coast. Forgive the geographical disconnect but its the effort and the mind and the will that stars in this tale.
Only 6th best. That was my fate. You knew the field, they were friends (mostly) as well as competitors. The line, the gun, the chase. I never gave up the chase. Not once. Here's why: They had talent, I had heart, a big one. I'd run and run and run, watching their backs. Awards ceremonies always included the Top 5 in each age group. 6th. In retrospect accomplishments that now seem a little more favorable considering the size of Houston.
The most memorable races however were those where I absolutely refused to acknowledge defeat. Unimportant whether or not I won the race. Knowing that I gave absolutely everything, had no quit in me, seeing stars at the finish line. And in my log books there are happy stories where this was enough to carry me past better runners.
What am I saying today? When you meet your wall, RUN THROUGH NOT TO.