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Fundamentals of Deep Learning – Introduction to Recurrent Neural Networks
Let me open this article with a question – "working love learning we on deep", did this make any sense to you? Not really – read this one – "We love working on deep learning". Made perfect sense! A little jumble in the words made the sentence incoherent. Well, can we expect a neural network to make sense out of it? Not really! If the human brain was confused on what it meant I am sure a neural network is going to have a tough time deciphering such text.
There are multiple such tasks in everyday life which get completely disrupted when their sequence is disturbed. For instance, language as we saw earlier- the sequence of words define their meaning, a time series data – where time defines the occurrence of events, the data of a genome sequence- where every sequence has a different meaning. There are multiple such cases wherein the sequence of information determines the event itself. If we are trying to use such data for any reasonable output, we need a network which has access to some prior knowledge about the data to completely understand it. Recurrent neural networks thus come into play.
In this article I would assume that you have a basic understanding of neural networks, in case you need a refresher please go through this article before you proceed.
Table of Contents
- Need for a Neural Network dealing with Sequences
- What are Recurrent Neural Networks (RNNs)?
- Understanding a Recurrent Neuron in Detail
- Forward Propagation in a Recurrent Neuron in Excel
- Back propagation in a RNN (BPTT)
- Implementation of RNN in Keras
- Vanishing and Exploding Gradient Problem
- Other RNN Architectures
Need for a Neural Network dealing with Sequences
Before we deep dive into the details of what a recurrent neural network is, let's ponder a bit on if we really need a network specially for dealing with sequences in information. Also what are kind of tasks that we can achieve using such networks.
The beauty of recurrent neural networks lies in their diversity of application. When we are dealing with RNNs they have a great ability to deal with various input and output types.
- Sentiment Classification – This can be a task of simply classifying tweets into positive and negative sentiment. So here the input would be a tweet of varying lengths, while output is of a fixed type and size.
- Image Captioning – Here, let's say we have an image for which we need a textual description. So we have a single input – the image, and a series or sequence of words as output. Here the image might be of a fixed size, but the output is a description of varying lengths
- Language Translation – This basically means that we have some text in a particular language let's say English, and we wish to translate it in French. Each language has it's own semantics and would have varying lengths for the same sentence. So here the inputs as well as outputs are of varying lengths.
So RNNs can be used for mapping inputs to outputs of varying types, lengths and are fairly generalized in their application. Looking at their applications, let's see how the architecture of an RNN looks like.
What are Recurrent Neural Networks?
Let's say the task is to predict the next word in a sentence. Let's try accomplishing it using an MLP. So what happens in an MLP. In the simplest form, we have an input layer, a hidden layer and an output layer. The input layer receives the input, the hidden layer activations are applied and then we finally receive the output.
Let's have a deeper network, where multiple hidden layers are present. So here, the input layer receives the input, the first hidden layer activations are applied and then these activations are sent to the next hidden layer, and successive activations through the layers to produce the output. Each hidden layer is characterized by its own weights and biases.
Since each hidden layer has its own weights and activations, they behave independently. Now the objective is to identify the relationship between successive inputs. Can we supply the inputs to hidden layers? Yes we can!
Here, the weights and bias of these hidden layers are different. And hence each of these layers behave independently and cannot be combined together. To combine these hidden layers together, we shall have the same weights and bias for these hidden layers.
We can now combines these layers together, that the weights and bias of all the hidden layers is the same. All these hidden layers can be rolled in together in a single recurrent layer.
So it's like supplying the input to the hidden layer. At all the time steps weights of the recurrent neuron would be the same since its a single neuron now. So a recurrent neuron stores the state of a previous input and combines with the current input thereby preserving some relationship of the current input with the previous input.
Understanding a Recurrent Neuron in Detail
Let's take a simple task at first. Let's take a character level RNN where we have a word "Hello". So we provide the first 4 letters i.e. h,e,l,l and ask the network to predict the last letter i.e.'o'. So here the vocabulary of the task is just 4 letters {h,e,l,o}. In real case scenarios involving natural language processing, the vocabularies include the words in entire wikipedia database, or all the words in a language. Here for simplicity we have taken a very small set of vocabulary.
Let's see how the above structure be used to predict the fifth letter in the word "hello". In the above structure, the blue RNN block, applies something called as a recurrence formula to the input vector and also its previous state. In this case, the letter "h" has nothing preceding it, let's take the letter "e". So at the time the letter "e" is supplied to the network, a recurrence formula is applied to the letter "e" and the previous state which is the letter "h". These are known as various time steps of the input. So if at time t, the input is "e", at time t-1, the input was "h". The recurrence formula is applied to e and h both. and we get a new state.
The formula for the current state can be written as –
Here, Ht is the new state, ht-1 is the previous state while xt is the current input. We now have a state of the previous input instead of the input itself, because the input neuron would have applied the transformations on our previous input. So each successive input is called as a time step.
In this case we have four inputs to be given to the network, during a recurrence formula, the same function and the same weights are applied to the network at each time step.
Taking the simplest form of a recurrent neural network, let's say that the activation function is tanh, the weight at the recurrent neuron is Whh and the weight at the input neuron is Wxh, we can write the equation for the state at time t as –
The Recurrent neuron in this case is just taking the immediate previous state into consideration. For longer sequences the equation can involve multiple such states. Once the final state is calculated we can go on to produce the output
Now, once the current state is calculated we can calculate the output state as-
Let me summarize the steps in a recurrent neuron for you-
- A single time step of the input is supplied to the network i.e. xt is supplied to the network
- We then calculate its current state using a combination of the current input and the previous state i.e. we calculate ht
- The current ht becomes ht-1 for the next time step
- We can go as many time steps as the problem demands and combine the information from all the previous states
- Once all the time steps are completed the final current state is used to calculate the output yt
- The output is then compared to the actual output and the error is generated
- The error is then backpropagated to the network to update the weights(we shall go into the details of backpropagation in further sections) and the network is trained
Let's take a look of how we can calculate these states in Excel and get the output.
Forward Propagation in a Recurrent Neuron in Excel
Let's take a look at the inputs first –
The inputs are one hot encoded. Our entire vocabulary is {h,e,l,o} and hence we can easily one hot encode the inputs.
Now the input neuron would transform the input to the hidden state using the weight wxh. We have randomly initialized the weights as a 3*4 matrix –
Step 1:
Now for the letter "h", for the the hidden state we would need Wxh*Xt. By matrix multiplication, we get it as –
Step 2:
Now moving to the recurrent neuron, we have Whh as the weight which is a 1*1 matrix as and the bias which is also a 1*1 matrix as
For the letter "h", the previous state is [0,0,0] since there is no letter prior to it.
So to calculate -> (whh*ht-1+bias)
Step 3:
Now we can get the current state as –
Since for h, there is no previous hidden state we apply the tanh function to this output and get the current state –
Step 4:
Now we go on to the next state. "e" is now supplied to the network. The processed output of ht, now becomes ht-1, while the one hot encoded e, is xt. Let's now calculate the current state ht.
Whh*ht-1 +bias will be –
Wxh*xt will be –
Step 5:
Now calculating ht for the letter "e",
Now this would become ht-1 for the next state and the recurrent neuron would use this along with the new character to predict the next one.
Step 6:
At each state, the recurrent neural network would produce the output as well. Let's calculate yt for the letter e.
Step 7:
The probability for a particular letter from the vocabulary can be calculated by applying the softmax function. so we shall have softmax(yt)
If we convert these probabilities to understand the prediction, we see that the model says that the letter after "e" should be h, since the highest probability is for the letter "h". Does this mean we have done something wrong? No, so here we have hardly trained the network. We have just shown it two letters. So it pretty much hasn't learnt anything yet.
Now the next BIG question that faces us is how does Back propagation work in case of a Recurrent Neural Network. How are the weights updated while there is a feedback loop?
Back propagation in a Recurrent Neural Network(BPTT)
To imagine how weights would be updated in case of a recurrent neural network, might be a bit of a challenge. So to understand and visualize the back propagation, let's unroll the network at all the time steps. In an RNN we may or may not have outputs at each time step.
In case of a forward propagation, the inputs enter and move forward at each time step. In case of a backward propagation in this case, we are figuratively going back in time to change the weights, hence we call it the Back propagation through time(BPTT).
In case of an RNN, if yt is the predicted value ȳt is the actual value, the error is calculated as a cross entropy loss –
Et(ȳt,yt) = – ȳt log(yt)
E(ȳ,y) = – ∑ ȳt log(yt)
We typically treat the full sequence (word) as one training example, so the total error is just the sum of the errors at each time step (character). The weights as we can see are the same at each time step. Let's summarize the steps for backpropagation
- The cross entropy error is first computed using the current output and the actual output
- Remember that the network is unrolled for all the time steps
- For the unrolled network, the gradient is calculated for each time step with respect to the weight parameter
- Now that the weight is the same for all the time steps the gradients can be combined together for all time steps
- The weights are then updated for both recurrent neuron and the dense layers
The unrolled network looks much like a regular neural network. And the back propagation algorithm is similar to a regular neural network, just that we combine the gradients of the error for all time steps. Now what do you think might happen, if there are 100s of time steps. This would basically take really long for the network to converge since after unrolling the network becomes really huge.
In case you do not wish to deep dive into the math of backpropagation, all you need to understand is that back propagation through time works similar as it does in a regular neural network once you unroll the recurrent neuron in your network. However, I shall be coming up with a detailed article on Recurrent Neural networks with scratch with would have the detailed mathematics of the backpropagation algorithm in a recurrent neural network.
Implementation of Recurrent Neural Networks in Keras
Let's use Recurrent Neural networks to predict the sentiment of various tweets. We would like to predict the tweets as positive or negative. You can download the dataset here.
We have around 1600000 tweets to train our network. If you're not familiar with the basics of NLP, I would strongly urge you to go through this article. We also have another detailed article on word embedding which would also be helpful for you to understand word embeddings in detail.
Let's now use RNNs to classify various tweets as positive or negative.
# import all libraries import keras from keras.models import Sequential from keras.layers import Dense, Activation, Dropout from keras.layers.convolutional import Conv1D from keras.preprocessing.text import Tokenizer from keras.preprocessing.sequence import pad_sequences import pandas as pd import numpy as np import spacy nlp=spacy.load("en") #load the dataset train=pd.read_csv("../datasets/training.1600000.processed.noemoticon.csv" , encoding= "latin-1") Y_train = train[train.columns[0]] X_train = train[train.columns[5]] # split the data into test and train from sklearn.model_selection import train_test_split trainset1x, trainset2x, trainset1y, trainset2y = train_test_split(X_train.values, Y_train.values, test_size=0.02,random_state=42 ) trainset2y=pd.get_dummies(trainset2y) # function to remove stopwords def stopwords(sentence): new=[] sentence=nlp(sentence) for w in sentence: if (w.is_stop == False) & (w.pos_ !="PUNCT"): new.append(w.string.strip()) c=" ".join(str(x) for x in new) return c # function to lemmatize the tweets def lemmatize(sentence): sentence=nlp(sentence) str="" for w in sentence: str+=" "+w.lemma_ return nlp(str) #loading the glove model def loadGloveModel(gloveFile): print("Loading Glove Model") f = open(gloveFile,'r') model = {} for line in f: splitLine = line.split() word = splitLine[0] embedding = [float(val) for val in splitLine[1:]] model[word] = embedding print ("Done."),len(model),(" words loaded!") return model # save the glove model model=loadGloveModel("/mnt/hdd/datasets/glove/glove.twitter.27B.200d.txt") #vectorising the sentences def sent_vectorizer(sent, model): sent_vec = np.zeros(200) numw = 0 for w in sent.split(): try: sent_vec = np.add(sent_vec, model[str(w)]) numw+=1 except: pass return sent_vec #obtain a clean vector cleanvector=[] for i in range(trainset2x.shape[0]): document=trainset2x[i] document=document.lower() document=lemmatize(document) document=str(document) cleanvector.append(sent_vectorizer(document,model)) #Getting the input and output in proper shape cleanvector=np.array(cleanvector) cleanvector =cleanvector.reshape(len(cleanvector),200,1) #tokenizing the sequences tokenizer = Tokenizer(num_words=16000) tokenizer.fit_on_texts(trainset2x) sequences = tokenizer.texts_to_sequences(trainset2x) word_index = tokenizer.word_index print('Found %s unique tokens.' % len(word_index)) data = pad_sequences(sequences, maxlen=15, padding="post") print(data.shape) #reshape the data and preparing to train data=data.reshape(len(cleanvector),15,1) from sklearn.model_selection import train_test_split trainx, validx, trainy, validy = train_test_split(data, trainset2y, test_size=0.3,random_state=42 )
#calculate the number of words nb_words=len(tokenizer.word_index)+1 #obtain theembedding matrix embedding_matrix = np.zeros((nb_words, 200)) for word, i in word_index.items(): embedding_vector = model.get(word) if embedding_vector is not None: embedding_matrix[i] = embedding_vector print('Null word embeddings: %d' % np.sum(np.sum(embedding_matrix, axis=1) == 0)) trainy=np.array(trainy) validy=np.array(validy) #building a simple RNN model def modelbuild(): model = Sequential() model.add(keras.layers.InputLayer(input_shape=(15,1))) keras.layers.embeddings.Embedding(nb_words, 15, weights=[embedding_matrix], input_length=15, trainable=False) model.add(keras.layers.recurrent.SimpleRNN(units = 100, activation='relu', use_bias=True)) model.add(keras.layers.Dense(units=1000, input_dim = 2000, activation='sigmoid')) model.add(keras.layers.Dense(units=500, input_dim=1000, activation='relu')) model.add(keras.layers.Dense(units=2, input_dim=500,activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy']) return model #compiling the model finalmodel = modelbuild() finalmodel.fit(trainx, trainy, epochs=10, batch_size=120,validation_data=(validx,validy))
If you would run this model, it may not provide you with the best results since this is an extremely simple architecture and quite a shallow network. I would strongly urge you to play with the architecture of the network to obtain better results. Also, there are multiple approaches to how to preprocess your data. Preprocessing shall completely depend on the task at hand.
Vanishing and Exploding Gradient Problem
RNNs work upon the fact that the result of an information is dependent on its previous state or previous n time steps. Regular RNNs might have a difficulty in learning long range dependencies. For instance if we have a sentence like "The man who ate my pizza has purple hair". In this case, the description purple hair is for the man and not the pizza. So this is a long dependency.
If we backpropagate the error in this case, we would need to apply the chain rule. To calculate the error after the third time step with respect to the first one –
∂E/∂W = ∂E/∂y3 *∂y3/∂h3 *∂h3/∂y2 *∂y2/∂h1 .. and there is a long dependency.
Here we apply the chain rule and if any one of the gradients approached 0, all the gradients would rush to zero exponentially fast due to the multiplication. Such states would no longer help the network to learn anything. This is known as the vanishing gradient problem.
Vanishing gradient problem is far more threatening as compared to the exploding gradient problem, where the gradients become very very large due to a single or multiple gradient values becoming very high.
The reason why Vanishing gradient problem is more concerning is that an exploding gradient problem can be easily solved by clipping the gradients at a predefined threshold value. Fortunately there are ways to handle vanishing gradient problem as well. There are architectures like the LSTM(Long Short term memory) and the GRU(Gated Recurrent Units) which can be used to deal with the vanishing gradient problem.
Other RNN architectures
As we saw, RNNs suffer from vanishing gradient problems when we ask them to handle long term dependencies. They also become severely difficult to train as the number of parameters become extremely large. If we unroll the network, it becomes so huge that its convergence is a challenge.
Long Short Term Memory networks – usually called "LSTMs" – are a special kind of RNN, capable of learning long-term dependencies. They were introduced by Hochreiter & Schmidhuber. They work tremendously well on a large variety of problems, and are now widely used. LSTMs also have this chain like structure, but the repeating module has a slightly different structure. Instead of having a single neural network layer, there are multiple layers, interacting in a very special way. They have an input gate, a forget gate and an output gate. We shall be coming up with detailed article on LSTMs soon.
Another efficient RNN architecture is the Gated Recurrent Units i.e. the GRUs. They are a variant of LSTMs but are simpler in their structure and are easier to train. Their success is primarily due to the gating network signals that control how the present input and previous memory are used, to update the current activation and produce the current state. These gates have their own sets of weights that are adaptively updated in the learning phase. We have just two gates here, the reset an the update gate. Stay tuned for more detailed articles on GRUs.
End Notes
I hope that this article would have given you a head start with the Recurrent Neural Networks. In the upcoming articles we shall deep dive into the complex mathematics of Recurrent Neural Networks along with the detailed descriptions of LSTMs and GRUs. Try playing with the architecture of these RNNs and be amazed by their performance and applications. Do share your findings and approach in the comments section.


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SACRAMENTO, Oct. 2, 2018 – As of September 7, there were 19,086,589 Californians registered to vote. This is the highest total number of registered voters heading into a Gubernatorial General Election in state history. 75.81% of eligible Californians are registered to vote.
There are 1,451,713 more registered voters than there were at the same point during the previous Gubernatorial Election cycle (2014).
"There are nearly 1.5 million more voters on the rolls than there were heading into our last Gubernatorial Election four years ago," Secretary of State Padilla said. "The next step for our registered Californians is turning out to vote. The General Election is next month, so it's time for voters to make a plan to vote, either in person or by mail. I'm also calling on elections officials and community leaders to help inform voters about their options for participating. California voters have access to a number of helpful tools and resources including the recently releasedVoter Information Guide website and Quick Guide to Props."
"There is still time for eligible Californians to register to vote or update their registration, especially if you've moved since the last election. Updating your voter registration can be done quickly online at RegisterToVote.ca.gov. If you are not sure of your registration status, you can easily check it at VoterStatus.sos.ca.gov," Padilla added.
October 22 is the traditional voter registration deadline for the November 6, 2018 General Election. If an eligible Californian misses the October 22 deadline, they can complete the "conditional voter registration" process and vote the same day. However, this option is only available at county elections offices and select satellite locations (vary by county).


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Julia Greer
Professor of Materials Science, Mechanics, and Medical Engineering at Caltech
Julia R. Greer received her undergraduate degree in Chemical Engineering (with a minor in Music) from MIT, after which she worked as an intern in Components Research Department of Intel Corp. while pursuing a M.S. In Materials Science at Stanford University, where she built a novel X-ray diffractometer in order to study mechanical properties of materials in computer microprocessors. Subsequently, after working at Intel's Mask Operations Department for 2 years, Julia received a Ph.D. in Materials Science and Engineering from Stanford University studying size effects in plasticity of metals at the nano-scale with Professor William D. Nix. Prior to starting her appointment as a faculty member at Caltech in June of 2007, Julia was a post-doctoral fellow at PARC, Palo Alto Research Center, from August of 2005 until May of 2007. In order to broaden her expertise, she worked on investigating the behavior of organic semiconductor - thin film transistors (OTFTs) as well as nano-ink-derived metals for jet-printing in flexible electronics with Dr. Robert A. Street. Throughout her scientific career, Julia has also been pursuing her "secondary career" as a concert pianist - having studied at the Moscow's Gnessin School of Music, the Eastman School of Music, the San Francisco Conservatory of Music, and at Stanford. She has performed numerous solo recitals (most recently at Caltech's "Off the Clock" event in 2011), chamber music concerts (most recently in Lagerstrom Series at Caltech with violinist C. Kovalchik), as well as as a soloist with an orchestra (most recent performance of Brahms' Piano Concerto No. 2 with the Redwood Symphony).


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"You can observe a lot by watchin'."Yogi Berra
I was going through a tough time. In retrospect, it sounds like an insensitive thing to say. There are people who have no job and nowhere to stay for the night, and I was a physician who had a busy practice and good health to spare. Yet… I was going through an acrimonious divorce. I had three daughters who were understandably resentful that their lives had been turned upside down. I found out how expensive it was to pay for two homes; two phone bills; two and sometimes three of everything.
Most of all, I considered myself a failure. The privileged child who had found school and medicine so easy to grasp had to face the fact that personal talent does not assure success in life. How had I gotten myself in this situation?
The best life advice, at any time, is to get over today the best way you can. I understood this on a conscious level, but I kept thinking about my future. How do I make sure that this does not happen again? Is there something wrong with me? Will I ever be happy with a mate?
There should be a law that severely punishes anyone who starts dating soon after (or before) a divorce is final. It is highly advisable to be alone for a few months. Take care of yourself; do your own cooking; pay your own bills; understand that the world does not end if you lack intimacy for more than a week. Our society is not set up this way. Most people venture out into dating quickly, as if to convince themselves that the sooner that they can rectify past poor choices, the more successful they will be. As if time were a-wasting. Being a man who hates to ask for or follow directions, I started to see a few women.
Good people; all of them. There was nothing "wrong"" with any of them. It's just that I kept getting this feeling that we were auditioning for each other. That they were not getting to see, or understand, who I was. And vice versa. With one exception. My nurse and office manager acted like herself, probably because we had known each other for years, and it would have looked deceitful had we tried to become an alternative soul after 6PM.
It is a horrible idea to date people that you work with. In Spanish there is a saying about not pooping on the same table that you eat. It is an even greater infraction to become intimate with someone who responds to you at work. So that is exactly what I did. There was a large part of me that told me that this was not an even playing field for her. Yet I persisted. Of course, I had doubts, but things were going so well that I tried to ignore them. I felt very relaxed in her presence.
Several months passed, and I was still uncertain. Something had to be wrong; there had to be a hidden character trait that would prove to be poisonous. I just had not seen it yet. Baseball season came around, and I asked her to go to a game with me.
For those who do not know me: I am Puerto Rican. 99% of Puerto Rican babies learn how to say "ball" and "hit" long before they say "mama." The few who start out by blabbering "papa" are immediately referred to a pediatrician before it is too late to correct their behavior. To make matters worse, I live in Saint Louis, a city whose inhabitants believe that Stan Musial had divine powers. My first wife could not tell a bunt from a sac fly. I understood that this was not the reason that we could not get along, but who knows?
She wore jeans, and sneakers, and a Cardinals cap. Check. She sat in her seat and immediately put her feet up on the chair in front of her. Check. She ordered a beer, and then another one. Check. It was a well-pitched game. When a Cardinals player stroked the first hit of the game, she let out a loud "Yeah!" at the same time that she stood up and clapped her hands. Check. Then came the whistle: loud; shrill; the kind that can pierce your eardrums. I have never been able to learn how to whistle. In an instant I knew that this was THE turning point.
"Will you marry me?"
There have been thousands of games since then. Even when we are behind by seven runs in the bottom of the ninth, she is there with me. Together with the sneakers, the beer, and the whistles. A few years ago, I got her one of those expensive Cardinals shirts (Yadi's, of course) for her birthday. It was received with more emotion than if I had given her a diamond ring. When a player from Triple A is promoted to The Show, she knows that this guy was not there yesterday.
"Who is this guy?"
Our new outfielder.
"Is he from the Minors?"
Yes, he was tearing it up in Memphis.
"He's cute."
I do not think that this is why he got called up.
"I like his butt. He has a nice butt. Reminds me of Tommy Herr."
You say that about all of them.
"I do not know why it is. Baseball players are cute and have nice butts. I wonder why."
If he cannot hit a slider his butt will not help him. Let us hope that he can adapt.
"He's still cute."
Yesterday our long-delayed season got under way. Peace and wafts of magic are in the air. We have hope. For three hours there is nothing wrong with the world. Almost forty years later, we sit in front of the TV and we feel that time has not touched us. That the choice that we made that long ago was, without a doubt, the best thing that ever happened to us.


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The company WALDRICH, located in COBURG and founded in 1920 by the engineer Adolf Waldrich, has a long experience in the field of Machine Tools.
WALDRICH COBURG is one of the world leaders in the development and manufacture of high quality machine tools in the fields of milling, turning and grinding.
Among its prestigious machines we must remember the range TAURUS.


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Our Mission
The mission of the Payroll Department is to pay University employees in an accurate and timely manner, to ensure that payments are in compliance with all Federal and State regulations, and to provide a clear audit trail of all transactions.
What We Do
The Payroll Department processes wage payments to university employees, and reconciles all earnings, taxes, deductions and benefits. The Payroll Department audits and processes hourly employee time sheets, payroll requests, direct deposit information, employee tax withholding forms, garnishments, and various other deductions. Payroll initiates requests for payment to vendors of various employee deductions and benefits. The Payroll Department also oversees the student employment process: training and supporting supervisors and student workers in the filling out of Student Employment Contracts as well as the web entry time sheets in OnePort.
Monthly Payroll
The Payroll Department processes a monthly payroll for all permanent employees (faculty and staff) and for temporary flat-rate employees. The pay date for the monthly payroll is always the last business day of the month with the exception of December, when the pay date falls earlier in the month.
Bi-Weekly Payroll
The Payroll Department processes a bi-weekly payroll for all student employees and for temporary hourly employees. For a calendar of the bi-weekly payrolls, please visit the Bi-Weekly Payroll Calendar page.
Tax Compliance
The Payroll Department regularly reviews all applicable payroll tax regulations in order to maintain compliance with Federal and State law.
NRA Tax Compliance
The Payroll Department works in conjunction with the State Controller's Office and Windstar Technologies in order to remain compliant when processing payments to non-resident alien employees.
W-2 Processing
The Payroll Department processes W-2s for all university employees. W-2s are mailed out no later than January 31st to the employee's home address. Active employees who have given consent to receive their W-2s electronically, can access their W-2 online through Banner Self Service in an IRS approved PDF format.
Voluntary Deductions
UNC Asheville offers a variety of voluntary payroll deductions for permanent employees. For a complete list of deductions please click on the "Deduction Information" tab.
Direct Deposit
The Payroll Department sucessfully transitioned all employees to Direct Deposit in 2007. This eliminated the expense of processing paper checks and their distribution.
All employees were transitioned to receiving their Direct Deposit notifications via email in January 2011. This eliminated the printing and distributing of over 22,000 notices annually.
Banner Payroll
From January 2010 through July 2010 the Payroll Department, in conjunction with Human Resources, sucessfully migrated all employees from the State's Central Payroll System to the Banner HR/Payroll system. Banner Payroll is now fully integrated with the university's finance system. This migration has resulted in more precise and timely tracking of employee pay and benefits as well as giving us the flexibility to pay hourly employees on a bi-weekly, rather than monthly cycle.
Web Time Entry for Hourly Employees
Web Time Entry for hourly temporary and student employees was successfully implemented in 2010. Hourly employees now have the abiltiy to electronically record their time worked on a web based time sheet and submit it directly to their supervisor using just a few quick keystrokes. Supervisors can electronically monitor employee time sheet progress, approve time sheets for payment, and review time sheet history.
Web Time Entry has not only eliminated multitudes of paper time sheets, but has eliminated hours of manual processing so that hourly employees can now be paid on bi-weekly, rather than monthly basis.
Electronic W-2s
For the first time, in January 2013, UNC Asheville employees had the opportunity to sign up to receive their 2012 W-2 statement online through Banner Self Service in an IRS approved PDF format. Forty-four percent of employees elected to receive their W-2 online rather than through the mail. Not only did this save printing and mailing costs, but it helped improve our efforts towards environmental sustainability.


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Our History
Organizational Structure & Contact Details
Our Mission
Our Citizen Charter
Annual Immovable Property Returns
Police Stations Jurisdiction Map
Traffic Zones Jurisdiction Map
Photo Gallery of IGP's Chandigarh
Photo Gallery of Various Events
Martyrs E-Book
Our Newsletter
Coffe Table Book (Pride & Glory)
Appreciation Letters from public
Insp. Sucha Singh
Late Insp. Sucha Singh joined Chandigarh Police as a constable on 30-04-1976 and was promoted to the rank of Inspector on 31.10.2008. While posted in the Traffic wing of Chandigarh Police he was on night Checking Duty in the area of Sub-Division Central on the intervening night of 08/09-06-2013. During checking Inspector Sucha Singh questioned one suspicious couple sitting near the District Court, Sector 17, Chandigarh. During this process, the accused stabbed him multiple times due to which he was martyred. Late Inspector Sucha Singh gave up his life valiantly so that others could live.
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SI Amarjit Singh
SI Amarjit Singh joined as Constable in Punjab Police on 28.5.73. On 25.02.1992, while he was escorting under trial terrorist Arvinder Singh @ Tanny in Police custody in PGI for treatment, some un-identified terrorists attacked this police party. SI Amarjit Singh bravely fought the terrorists till he was martyred.
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ASI Lalu Ram
ASI Lalu Ram joined as a Constable in Punjab Police on 29.6.76 and joined Chandigarh Police on deputation on 30.05.78. On 29.08.1991 while he was posted as PSO to Sh. S.S.Saini, SSP, some desperate terrorists laid an explosive booby trap, which blasted the SSP's car. ASI Lalu Ram was martyred on the spot.
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ASI Amin Chand
ASI Amin Chand joined as Constable in Chandigarh Police on 4.6.1981.On 29.08.1991, while he was posted as driver with Sh. S.S. Saini, SSP, some desperate terrorists laid an explosive booby trap which blasted the SSP's car. ASI Amin Chand was martyred on the spot.
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ASI Amarjit Singh
ASI Amarjit Singh joined as a Constable in Chandigarh police on 26.7.1976 on 08.12.1989, while posted in Police Post-36. ASI Amarjit Singh was ambushed and martyred while on patrolling duty near village Kajheri, (Kachha path) by two terrorists riding a motorcycle.
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Inspector Jagjit Singh
Insp. Jagjit Singh joined Chandigarh Police as ASI on 6.5.72, while he was posted as SHO PS-39, on 17.07.1988 he led a raid on H.No.2195/1 Sector-45, where some terrorists, armed with sophisticated weapons were taking shelter. Exhibiting exemplary courage and leadership, Inspector Jagjit Singh broke open the door and rushed inside the house. In this encounter 3 terrorists were killed. Inspector Jagjit Singh also received fatal bullet injuries and was martyred on the spot.
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For Crime Related Emergency
Dial - 100 or 0172-2749194 or 0172-2744100
For Traffic Related Emergency
Dial - 1073
For Crime Against Women & Children
Dial - 100 or
Women & Child Helpline No. 1091 or 0172-2741174
For any Senior Citizens Complaint
Dial - 100 or Senior Citizens Helpline No. 1090
For any Cyber Crime Complaint
E-mail : - email@example.com
DSP Night Duty (From 12:00 AM to 05:00 AM Daily)
Dial - 09465121000
Passport Verification Helpline


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If you're going to get us started on Top Chef, you can expect an earful on the crazy stunts this television show puts contestants through that have little or nothing to do with determining who is a really good cook. But what kills us even more is when the judges — at least some of whom are well-respected food professionals — screw up on fundamental cooking points. In one episode in which the hapless contestants were to make a "healthful" main course, a contestant who made a lobster dish was mocked, scorned, and sent home because a nameless judge (who no longer teaches sloppy straight guys how to cook) went on and on about how much cholesterol lobster has and what a terrible choice it is for "healthy" cooking. Wrong. Wrong. Wrong! Lobster is a wonderful lowfat meat that has no more cholesterol than a skinned chicken breast, and way less than any red meat.
What does this rant have to do with your pineapple question, you timidly ask? On another watch-the-pathetic-monkeys-jump-though-insane-cooking-hoops episode of Top Chef, one woman tried to make a pineapple-gelatin dessert, and wondered again and again why it did not set up. It was discussed at length when she was badgered by the all-knowing judges. But did the restaurant chef judge, the food magazine editor judge, the takes-herself-way-too-seriously-but pretty host judge, or the no-longer-teaching-sloppy-straight-guys-to-cook judge ever once say, "everyone in the whole cooking universe knows that fresh pineapple contains an enzyme that prevents gelatin from setting up?" No they did not. They just talked about what a failure it was. Duh!
Fresh pineapple contains an enzyme that prevents gelatin from setting up (so do kiwi, papaya, and melons). If you want to use pineapple with gelatin, you use canned pineapple, because pasteurization during the canning process deactivates the pesky enzyme. You can also cook pineapple to kill the enzyme, but it will no longer be firm.
Come on, Top Chef, if you're going to put drama-queen, bitter, borderline-anti-social, and intensely profane cooks through whack-job cooking tasks — and pretend that it's something to be taken seriously — at least get your facts straight!
We don't want to go too far out on a limb, but we fully expect the new season of Top Chef to have contestants cooking a three-course meal in the galley of a motorhome that is chasing tornadoes in the Midwest, serving a flambéed dessert to a tired but successful rescue party near the summit of Mt. Rainer, and producing a multi-cultural fondue feast for mid-level officials from the United Nations in the little boats in Disney World's It's a Small, Small World exhibit. Now that's how you find a top chef!


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Recently, a colleague doing work for the United Nations Development Programme in Russia requested me to send her the best guidance available on planning international hydropower projects. She was attempting to minimize impacts on biodiversity and ecosystem services. While I have been away from Hydropower for a while, I was really hard pressed to find current documents that would help her. Most reports were too general and few, if any, talked about planning and regulating hydropower projects, which can last 50 years or longer. I found this difficult to understand despite the wealth of experience in the U.S. and Canada in siting and regulating hydropower.
I quickly realized that in the hydro arena, we were still grappling with environmental, regulatory and social issues. The same is true for siting natural gas and renewable energy. However, the stakes are higher today since the World Bank Group and the Asian Infrastructure Bank are investing in hydropower in to spur economic development, address Climate Change and move countries away from fossil fuels. So I dusted off three publications below that should help both developing and developed countries to better plan and manage their hydropower and other energy projects. Here's a short explanation of each:
- Lesson Learned in 78 years (Hydropower)- this is really the U.S. historical experience to about 1998, but it's still very applicable today and can be used by all countries. It was prepared for the World Commission of Dams.
U.S. government agencies, like the Army Corps of Engineers, Bureau of Reclamation and power authorities such as TVA and BPA have developed about 50% of the U.S. hydropower. The private sector was allowed to develop the remaining 50% of hydropower projects under a licensing system which allowed the companies to operate the projects between 30 to 50 years. Conservationist actually were largely responsible for this, because they were apprehensive about the government monopolizing all of the hydropower development in the U.S. The license was like a contract between the developer and the government and dictated the construction, operation and maintenance of the project. Hydro projects require a great deal of capital, so the 30-50 year license was designed to allow the project developer to accrue revenue and pay off debt in a relatively stable fiscal environment. The Federal Power Commission now called Federal Energy Regulatory Commission or FERC regulated the construction, operation and maintenance of the project, including dam safety.
The most important aspect of this regulatory arrangement is that hydropower projects don't operate forever. Instead, 2 years prior to expiration of the original license, the hydropower developer has to file for a new license. Relicensing is not easy and as you might expect, and much can change in 30 to 50 years with respect to power needs, and environmental requirements. FERC reviews the project in the context of today's environment laws and needs and considers recommendations from environmental agencies, NGOs and the public. For example, the original licenses might have been 5 pages long, but a new license might be 100 pages long with all kinds of environmental mitigation and measures to promote non-power benefits such as flood control, irrigation, water supply, fishery protection, recreation, water quality, etc. Public participation in relicensing is extraordinarily high. Most projects are relicensed, but in a few cases smaller projects have been removed since they are not economically viable when environmental requirements are imposed on them.
- Considering Cumulative Effects under the National Environmental Policy Act- this document is especially relevant to multiple hydropower projects planned or operating on a single river or within a river basin. The cumulative effects from multiple hydropower projects could have additive adverse effects and sometimes much more than the individual effects of single projects. The document is also applicable to linear energy projects such as natural gas and oil pipelines and electric transmission lines.
- Energy Chapter of the Handbook of Environmental Assessment that I authored. The important parts of this chapter pertain to the regulation of projects. Energy project are generally long-lived assets. There is an explicit bias for the preparation of environmental reviews that emphasize mitigation and its implementation, rather than preparing voluminous documents on impacts that will collect dust. Regulatory institutional strengthening is also discussed to manage the construction, operation and implementation of the mitigation measures. There is also a preference for adaptive environmental management- i.e. implement the mitigation, determine how well is works and make adjustments to obtain better results. The concept of a review after a 30-50 year period is also explored, since debt on the project is usually completely paid down. Project developers often are better able to afford environmental mitigation also.
- Hydropower Training in Seattle, Washington on August 22-23, 2016


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Daisy Ridley on the "Massive Quiet" of Star Wars Ending and What's Next
Daisy Ridley talks at 100 miles an hour, and she'd tell you so herself—in between apologizing for waffling (her words, not mine!) and regaling you with delicious little anecdotes about Barbra Streisand or Harrison Ford. Beaming at me through my laptop screen at 10 a.m. on the dot, the British actor's high energy is matched only by an equally high, super-tight ponytail. Barefaced and glowing and wearing a maroon Adidas sweatshirt, she manages to carry off a look that could only be most accurately referenced as Sporty Spice. Her attire isn't the A-list norm for a press interview IRL. As she is the former female lead in the Star Wars franchise, we're accustomed to seeing Ridley on the red carpet in Oscar de la Renta gowns and sharp Alexander McQueen suits with perfectly preened hair and flawless makeup, but we don't live in normal times. Straight after our call, Ridley will be doing her daily indoor workout that she developed for herself at the beginning of lockdown last year. "I always had loads of energy," she says, half-joking that it was the reason her parents shipped her off to boarding school when she was 9 years old.
Photo:Stephanie Galea; STYLING: Hermès vest, shirt, and skirt
That same energy, however, can sometimes be misunderstood. Recently, a story about Ridley simmered away on the internet after she spoke of a director labeling her on-set energy as "quite aggressive" and a makeup artist telling her that she was "intimidating." It occurs to me as soon as we start talking that this just might be the tired trope of other people's insecurities coming to the fore in the presence of a self-assured, no-BS kind of woman. Ridley is forthright and spirited but entirely charming. "I'm pretty sure my response was, 'I don't know that that's to do with me?' 'Cos I don't think it is," she says of the interaction with the makeup artist. "I think it is to do with other people. I know I'm very direct, more direct than other people probably. I probably ask uncomfortable questions because I prefer if there's any sort of strangeness between friends to talk about it and get it over and done with rather than just let it lie." As for the director's comments, she didn't necessarily take them as negative, but they were, nonetheless, difficult to process, and Ridley found herself questioning how she came across. "The thing I find as well is that people are very comfortable telling me how I am. People are always like, 'You're the honest one.You're this one. You're that one.' Maybe directness comes across as confidence or something, so then, people think you're willing to take that critique. You would never say to someone else, 'Oh, you're just really unconfident! How you are is super passive!'"
Photo:Stephanie Galea; STYLING: Koché jacket; Van Cleef & Arpels Perlée Pearls of Gold Bracelet ($4450) and Vintage Alhambra Ring ($3650)
Would the same kind of personality from one of her male colleagues be so scrutinized? Perhaps not. Although, Ridley doesn't like to divide the sexes up into such monochromatic stereotypes. "I found it when I met—sorry, name drop—Barbra Streisand!" she says. "The way she has been referenced as being controlling and what have you, like, she's amazing. She's am-a-zing. And I'm sure on-set she knew what she wanted. When she was directing, she knew how to get it, and that was it."
Photo:Stephanie Galea. Wardrobe: Stella McCartney shirt and shorts; Van Cleef & Arpels Magic Alhambra Earrings ($7150); Toga boots.
No woman is one-dimensional, and despite the strength she presents, Ridley is equally candid about her weaknesses. She tells me that she didn't "like herself" for a very long time but that a quote she heard about evaluating yourself by the five people closest to you resonated enough for her to start on a journey of self-appreciation. "The five closest people to me are fucking awesome, so I was like 'I must be alright!'" she says. "If you can't love yourself… what a waste of time. You've got a whole lifetime of you living with your own thoughts." So now Ridley can, without embarrassment, say, "I quite like who I am."
Photo:Stephanie Galea; STYLING: Louis Vuitton trench coat; Perfect Moment leggings; Alexander McQueen boots
The fact is, without this powerful combination of enthusiasm, intensity, and focus, Ridley might not have landed one of the biggest movie roles in one of the biggest film franchises of all time. If you Google it, you can watch one of her many audition screenings with director J.J. Abrams, where both her urgency and ability to emote are plain to see. But last year, that five-year, three-blockbuster journey ended, and she was left with a rather galactic void to fill. Following the premieres, press junkets, and chat-show circuit, she recalls staying in a hotel and being unable to sleep. "I was like, 'What am I supposed to do now?'" She spent much of January 2020 feeling a little bit lonely, a little bit weepy, and a little bit unlike herself. "I guess it was sort of like grieving. These relationships and this amount of time had come to an end. It really felt like I was letting go of something emotionally," she says. She hadn't been home properly in years and had to recalibrate to the "massive quiet" of not necessarily having a crazy schedule or being surrounded by dozens and dozens of others.
Photo:Stephanie Galea; STYLING: Alaïa top and skirt; Hunza G swimsuit; Van Cleef & Arpels Vintage Alhambra Necklace ($8500)
I couldn't help but wonder what a busy person like Ridley, who "loves to be at work regardless of what it is," has coped with the lethargic pace of the past year. Any projects that were slated to begin filming were put on hold, while others were slowly finished. At the start of our conversation, Ridley implied she had done almost nothing but watch TV shows for "research" throughout the entirety of 2020 (The Undoing and The Americans are the two she rated), but it turns out she may have been selling her pandemic accomplishments a bit short. By the time we ended our chat, I learned that she had also trained to be a doula and had weekly dialect coaching sessions to hone her American accent, which she used to record voiceovers for the upcoming adventure video game Twelve Minutes in a socially distanced studio with James McAvoy on one side and Willem Dafoe on the other via Facetime. Oh, and she's on a 280-something-day streak learning French on Duolingo.
Photo:Stephanie Galea; STYLING: Alexander McQueen suit and boots
After a year-long (and impressively productive) pause, Ridley is ready to enter the next phase of her acting career, beginning with the sci-fi thriller Chaos Walking with Tom Holland. The adaption of the Patrick Ness novel is gripping, fast-paced, and timely. Ridley plays Viola, a person seeking a better land and life whose spaceship crashes onto a planet infected by a disease called The Noise. The Noise only affects men, broadcasting out loud their innermost thoughts for everyone to hear—every innermost thought. It's an allegory for our reality in terms of a rogue virus wreaking havoc, but it also puts a mirror up to social media, where every comment or whim can be unleashed in an instant. Ridley quit Instagram back in 2016 and hasn't looked back. "I think people use it really well. It's an amazing tool for connection, particularly now. It's just not for me."
Chaos Walking is indeed another out-of-this-world story, and as it is her first major follow-up to Star Wars, one could easily think the actor has been forever typecast in the sci-fi/adventure genre. Not so. Ridley's future slate includes two period dramas set in and around World War II, including the recently announced A Woman of No Importance in which she plays American spy Virginia Hall. After riding the superhighway of Star Wars, she is looking forward to veering off-road into uncharted territories. She'd love to do something "really British" or be part of a cult TV water-cooler moment, but for now, she's going with the flow. "I don't have a plan of 'I want to do this, now I've done this, [and] I want to do this,'" she explains. "There's a lot that I'm hopeful for if I can pull it off." With her aforementioned drive and focus, I think she'll be just fine.
Photographer: Stephanie Galea for Who What Wear
Stylist: Natalie Wansbrough-Jones
Hairstylist: Dayaruci at The Wall Group using Oribe
Makeup Artist: Kelly Cornwell at Nylon Artists using Shiseido
Manicurist: Karen Louise
Shop the Look


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Life Safety
Free - Resistor Color Code PDF - Click and Save to Your Phone
Can You Help Me Connect Devices to a Loop?
There are many types of devices and there are many types of loops. Read the manual for the fire panel, and read the instruction sheets that come with the devices to find out exactly how to connect everything together.
Greetings Douglas,
I'm J K from another country. Can you please help me connect devices to a loop? Can you install detector and a pull station on the same loop as a sounder, or are they separate loops?
Thank you,
There are many types of fire alarm system loops. The loops are meant to carry signals from the devices to the panel, or the loops are meant to carry signals from the panel to the devices. With many fire alarm systems, though, the loop is meant to carry signals both directions: from the devices to the panel and from the panel to the devices.
Often, the detectors and pull stations are connected to one loop and the sounders are connected to another loop, but how the devices are connected is determined by the manufacturer.
What kind of loop it is and how to connect to the loop will be different from one manufacturer and model of fire alarm system to the next. The way the equipment is connected will be determined by how the manufacturer has designed the panel, how the manufacturer has designed the loop, and how the manufacturer has designed the devices that connect to the loop.
With the fire alarm panel and with each device, the manufacturer has included an installation sheet or installation manual. These sheets and manuals show how the system is to be installed. This installation information material even has diagrams showing how to wire in the devices and the panel to the loop.
Thoroughly read the installation sheets and the installation manual. Not only does this material have wiring diagrams, but this material has explanations and specifications on each piece of equipment and device used in the fire alarm system.
If you are still having problems understanding the system, you can send me the make and model of the fire alarm panel, as well as the devices. When I know more, I can explain what's going on further.
Douglas Krantz
Further Question
Mr. Krantz
This is the panel. Please take a look at it.
Thank you,
This is a conventional fire alarm panel. It came with an installation manual.
You need to get the installation manual and read the manual because it shows you how to connect the detectors, the pull stations, and the sounders.
Did you install the panel in the wall? Whoever installed the panel in the wall will have the installation manual. If they lost the installation manual, or need to keep the manual themselves, they are the ones that can get a new instruction manual from Notifier (the name of the company that made the panel).
The detectors and the pull stations are what cause the panel to sound the alarm. They send signals to the fire alarm panel, so they are input devices.
The sounders receive signals from the panel, so they are outputs from the panel.
The inputs to the panel are on separate loops. The outputs from the panel will be on separate loops.
Make It Work - Conventional Fire Alarms
You can get more information on the loop wiring by looking at:
Why Use Conventional Class B Wiring?
This wiring will be used for both the input and output wiring. Below the article itself is a button to get a free Class B Wiring diagram.
The drawings in the instruction manual will also show you how the loops should be wired.
Make It Work - Conventional Fire Alarms
Make It Work - Conventional Fire Alarms
Douglas Krantz
Life Safety
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Douglas Krantz's Technician's Corner


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From 1871 to 1957, the top two floors of Judd Hall housed Wesleyan's natural history museum. Named for Orange Judd, Class of 1847, a prominent agricultural editor and publisher, as well as a generous donor, the brownstone structure was one of the first buildings in the United States designed specifically for undergraduate science instruction. In an era when most scientific teaching was based on the close study of specimens rather than laboratory experiments, the natural history museum was an indispensable curricular resource. Some faculty of the time compared it to the library in importance and instructional value. By the late 1870s, Wesleyan faculty were basing their own research on museum specimens, in addition to using it to support their teaching.
Modeled on the Renaissance European tradition of the "cabinet of curiosities," Wesleyan's museum was the home of a rich array of artifacts of truly amazing variety. While there are no specific records of lions, tigers, and bears, early photographs clearly show a camel, a walrus, and a buffalo. Vast numbers of birds, insects, and minerals, especially those from central Connecticut, are the expected mainstay of such a teaching collection. Perhaps more surprising are the South Sea Island weapons and tools, the coins, the ancient glass, the kangaroos, and—of course!—the mummy, a character about whom so many tales survive that it will be the subject of a future column.
Wesleyan had been collecting artifacts since its inception. In fact, among the purchases of buildings, books, and other materials deemed essential for opening the university in 1831 was a collection of a thousand mineral specimens that belonged to Dr. Joseph Barratt. These inaugural museum pieces cost $400, a princely sum at the time. In 1833, a group of "friends of the University" bought another mineral collection to support teaching in Wesleyan's first natural science course, taught by John Johnston. Everyone got into the collecting act. From the president, to faculty in all disciplines, to underclassmen on holiday, to local citizens: donors to Wesleyan's growing collections were an enthusiastic and generous group. By the time Judd Hall was designed, storage and display space for all these artifacts was sorely needed.
Of course, the collecting mania did not diminish with the opening of the new building. Collecting policies and practices in those early days of the official museum were fluid at best. G. Brown Goode, Class of 1870, the first curator of the museum, wrote tellingly in an article in the March 22, 1871, College Argus:
"There are few persons who will not, during the coming summer, meet with valuable specimens. Let them collect what they find? Mammals, birds, birds' nests and eggs, frogs, snakes, salamanders, turtles, fishes, skeletons and bones of every description, especially skulls, insects, 'bugs,' spiders, worms, crabs, star fish, sea anemones, vegetable productions of every kind, fossils, minerals—nothing can come amiss?. A word as to the preservation of Zoological specimens. When possible they should be brought to the Museum in a fresh state?. The locality and date of collection should always be carefully noted."
Despite his initially somewhat unfocused approach to developing the museum's holdings, Goode turned out to be a talented curator. He successfully undertook organizing, cataloging, and expanding Wesleyan's disparate collections. Under Goode, the museum grew to well over 100,000 artifacts. Few American college collections of the time came close. After six years on the job, he left alma mater for a curatorial position at the National Museum of the Smithsonian Institution. A decade later, he was the National Museum's director. Throughout Goode's career at the Smithsonian, Wesleyan enjoyed a very favorable exchange program with it.
As science education evolved, emphasis shifted from work with specimens to laboratory research. By the turn of the century, Wesleyan's natural history museum was no longer central to science instruction. Plans developed to close or move it. In 1926, geology professor William North Rice wrote to President McConaughy about his vision of the museum as a valuable element in serving the local community: "A college owes a duty not only to those who are enrolled as its students, but to the community in which it is situated." Indeed, in the later years of the museum's presence in Judd Hall, it was most frequently visited by local school children. When the museum was officially closed in 1957, some of its holdings were sold, but many were stored in a variety of places throughout the university. Today the geology collections and related materials are administered by the archaeology department, and some of the other collections are in storage. All are awaiting rediscovery by a broader audience in the new university teaching museum planned for future construction.
—Suzy Taraba '77, University Archivist


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PPSC Lecturer's Past Papers and Preparations Data for All Subjects
Very important data, Famous Books and Past Papers for PPSC Lecturer's All Subjects are uploaded here. Previous PPSC Past Papers 2015, 2017 of all subjects are availble here. Tests preparation books, MCQS, Repeated MCQS in previous papers of PPSC are also posted. You can read online or download in yours mobile or computers and prepare your tests.


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Free Ephemera Download: Season's Greetings Christmas Postcards
Travel back to the turn of the century and celebrate a white Christmas with these postcard images. From a quick note wishing the family a "Merry Christmas" to friends riding to church in a horse-drawn sleigh, these images are sure to set the mood for a cheerful holiday season. Click on the links below each thumbnail to download your free ephemera.
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Posted: Tuesday, November 21st, 2017 @ 8:00 am
Categories: Free Downloads, Holidays.
Tags: Christmas postcards, Christmas time, free clipart download, free ephemera download, Season's Greetings, turn of the century postcards, vintage postcards.
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Another experiment recently did was compress three grayscale images into one file. The reason for this would be of course file size and load time. A real-case scenario where you might need to load 3 grayscale images of the same size is loading textures for a 3D app. For instance, your model might be color dynamically, but you need to load a diffuse map, a specular map, and a bump map – all of these would be the same dimension and would be black and white.
So all you need to do is take your three grayscale images into photoshop and layer them on top of one another. Then use the gradient map image adjustment to have each image range from red, green, or blue to black. Have the base layer be flat black, and set each of the three layers to screen. Then, once that image is loaded into Flash, you can extract each color channel and set it back to black and white with the ColorMatrixFilter. You just need to set the matrix so that each of the R,G,B rows are [0,0,0,0,255] and the last row (the alpha) is [1,0,0,0,0] for red, [0,1,0,0,0] for green, or [0,0,1,0,0] for blue. The just smoosh that transparent white image into a black bitmap, and you're set.
Again, not entirely useful for every day cases, and it does cut down on how easy and dynamic the loaded content is, but if you're hurting due to file size and load time, this could be something to keep in mind. In case you're wondering – the layered color image I used in my example is 188 KB, and the blue channel saved as its own grayscale file is 132 KB.


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Life and Mind: Philosophical Issues in Biology and Psychology
Rock, Bone, and Ruin
An Optimist's Guide to the Historical Sciences
376 pp., 6 x 9 in, 25 b&w illus.
- Hardcover
- 9780262037266
- Published: February 16, 2018
- Publisher: The MIT Press
- eBook
- 9780262344159
- Published: February 23, 2018
- Publisher: The MIT Press
An argument that we should be optimistic about the capacity of "methodologically omnivorous" geologists, paleontologists, and archaeologists to uncover truths about the deep past.
The "historical sciences"—geology, paleontology, and archaeology—have made extraordinary progress in advancing our understanding of the deep past. How has this been possible, given that the evidence they have to work with offers mere traces of the past? In Rock, Bone, and Ruin, Adrian Currie explains that these scientists are "methodological omnivores," with a variety of strategies and techniques at their disposal, and that this gives us every reason to be optimistic about their capacity to uncover truths about prehistory. Creative and opportunistic paleontologists, for example, discovered and described a new species of prehistoric duck-billed platypus from a single fossilized tooth. Examining the complex reasoning processes of historical science, Currie also considers philosophical and scientific reflection on the relationship between past and present, the nature of evidence, contingency, and scientific progress.
Currie draws on varied examples from across the historical sciences, from Mayan ritual sacrifice to giant Mesozoic fleas to Mars's mysterious watery past, to develop an account of the nature of, and resources available to, historical science. He presents two major case studies: the emerging explanation of sauropod size, and the "snowball earth" hypothesis that accounts for signs of glaciation in Neoproterozoic tropics. He develops the Ripple Model of Evidence to analyze "unlucky circumstances" in scientific investigation; examines and refutes arguments for pessimism about the capacity of the historical sciences, defending the role of analogy and arguing that simulations have an experiment-like function. Currie argues for a creative, open-ended approach, "empirically grounded" speculation.
The 'historical' sciences have been neglected by philosophers. Adrian Currie analyzes both the problems and the opportunities involved in reconstructing and understanding the unobservable deep past. His engaging discussion—ranging from the character of global ice ages through the habits of giant dinosaurs to the meaning of Mayan monuments—explores the surprising commonalities that underlie these superficially diverse sciences.
Martin Rudwick, University of Cambridge; author of Earth's Deep History and Bursting the Limits of Time
Rock, Bone, and Ruin is an extraordinarily ambitious, provocative, and generative treatment of the epistemic predicament of the historical sciences. Adrian Currie trains his philosophical eye on the research strategies of 'unlucky' historical scientists—those who contend with messy, incomplete, and opaque traces of the past—and explains how, against the epistemic odds, they establish a robust understanding of seemingly inaccessible geological events, evolutionary processes, and cultural dynamics. This is a nuanced and richly illustrated account of scientists operating under non-ideal circumstances that demonstrates what can be accomplished by taking seriously the turn to practice. It has implications that will be of interest to practitioners and it is an incisive argument for doing philosophy differently: attentive to the epistemic challenges scientists actually face, resolutely local and contextual, and unabashedly normative.
Alison Wylie, Professor, Department of Philosophy, University of British Columbia
Currie has, in this book, pointed us towards a promising way forward.
The book is an intriguing read.
Geoscientist Online
This book is a wonderful example of how to move between the relevant scientific details and the broader conceptual issues that characterize a particular set of scientific practices.
Notre Dame Philosophical Reviews
On the whole, Rock, Bone, and Ruin is a must-read for those interested in the historical sciences.
History & Philosophy of the Life Sciences


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NUCLEAR: Toshiba is considering selling its Westinghouse nuclear division after receiving an extension to files its earnings. Meanwhile, the CEO of the Charlotte-based Toshiba America Energy Systems has been replaced. (Reuters, Charlotte Business Journal)
ALSO: Despite President Donald Trump's promises of revival, Kentucky's lawmakers are acknowledging a need for alternatives to the state's coal industry as they move closer to lifting a moratorium on nuclear energy. (Associated Press)
• "The game has changed" for oil pipeline construction in Georgia and South Carolina as Republican-backed bills introduce tighter regulations for construction. (Southeast Energy News)
• All three Democratic candidates for Lieutenant Governor in Virginia now oppose the Atlantic Coast Pipeline. (Blue Virginia)
• Alabama manufacturers support President Donald Trump's call for pipelines to use U.S. steel. (AL.com)
OIL & GAS: West Virginia lawmakers scale back a proposal to exempt tanks used by the oil and gas industry from a recent safety law. (Charleston Gazette-Mail)
• An environmental group said Monday that it will sue Duke Energy for allegedly polluting a lake and two river basins with coal ash from a North Carolina power plant. (Raleigh News & Observer)
• Residents were able to review and respond to a plan for excavating what remains of a Duke Energy coal ash site in North Carolina at a public hearing on Monday. (WLOS)
GRID: Duke Energy is updating a South Carolina dam with an eye toward using it for energy storage. (WFAE)
SOLAR: A Georgia utility's $39/month charge for solar customers helped prompt a Republican-backed bill to require more transparency in how such fees are set. (PV Magazine)
UTILITIES: Public meetings are planned to discuss rate-increase requests for two Kentucky utilities to install smart meters. (Kentucky Press News Service)
• A former Virginia lawmaker says with a new presidential administration, now is the time to revisit the state's offshore oil exploration options. (Roanoke Times)
• A North Carolina nonprofit says ending fracking's methane releases is crucial to averting a climate crisis. (Raleigh News & Observer)
• Solar power represents a "new source of prosperity" for West Virginia. (Charleston Gazette-Mail)


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CIM Users Group – European Meeting
Using CIM for DSO/TSO Integration and Information Exchange
5-7 June, 2018
The UCA International Users Group invites members of the energy industry to attend the CIM Users Group – European 2018 Spring Meeting, "Using CIM for DSO/TSO Integration and Information Exchange" on 5-7 June 2018 in Ljubljana, Slovenia. Whether you are a CIM novice or expert, this meeting will provide a forum to learn more about CIM and network with colleagues.
What Is CIM?
The CIM is an international standard now globally accepted for modeling the information exchanges required in electric utilities. The CIM is independent of any individual application, middleware, or message protocols used for data exchange. The interoperability enabled by the CIM standards is a key factor for achieving the Smart Grid vision.
The CIM Users Group (CIMug) was formed to promote progress of the CIM and to share project experiences. The users group holds two meetings each year (one in Europe and one in the U.S.). Recognized experts share their insights and resolve key technical issues. Each meeting also includes pre-conference tutorials, vendor exhibits, and social networking opportunities.
Who Should Attend
Utilities, energy companies, RTO/ISOs and others involved in developing standards-based enterprise information architectures and integration frameworks to meet their business challenges will find this conference invaluable. Project managers, system architects, business and IT managers, and control center personnel will all benefit from this meeting. With the focus on Smart Grid interoperability and distribution applications, vendors with CIM-based products they plan to make available to this community will want to reserve a Vendor Table to demonstrate their products and discuss service offerings.
The meeting is open to all current or potential CIM users – you do not have to be a CIM User Group member to attend. Attendees gain first-hand access to CIM experts and come away with new insights on how to realize the power of CIM-based integration.
Meeting Location
Cankarjev dom Cultural and Congress Centre
Presernova cesta 10
Ljubljana, Slovenia


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A closer look:
The Alertness booklet includes four lessons that teach children to notice what is happening around them so they can respond appropriately.
- Keep My Eyes and Ears Open features the story of a young man overhearing a deadly plot against Paul.
- Recognize and Heed Warnings features the story of the Israelites' decision to flee or not to flee to Egypt.
- Sharpen My Spiritual Senses features the story of Simeon and Anna's long-awaited discovery of a fulfilled promise.
- Beware of Lies features the story of the liar in the Garden of Eden.
Through this study, children are motivated to observe their surroundings to recognize and heed physical and spiritual warnings.
If you have any questions on using the material or would like more information on the character calendar or curriculum, please email us at [email protected].
"Thank you for putting this character curriculum together. My children have really enjoyed having the qualities laid out in such a fun and easy way to understand . . . [It has] brought about some great discussion times in our family."
—Arletta, mother from Kansas


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|By Henry Pierson Curtis, The Orlando Sentinel, Fla.
Knight Ridder/Tribune Business News
May 22, 2004 - Wearing a hijab has meant not being able to work at Walt Disney World, according to a former employee who claims she lost her job because she refused to remove her Muslim head scarf.
Aicha Baha's civil-rights suit, served this week on Disney, may be the first-ever challenge of the employee dress code at the Central Florida attraction.
"To stop you from working for practicing your religion doesn't seem right to me," the Morocco-born Kissimmee resident said Friday. "There is a family here that is almost out on the street because of Disney."
The hijab is a head scarf that some Muslim women choose to wear as a sign of modesty. Disney policy prohibits the wearing of anything but Disney-issued hats and visors.
"We don't discriminate," Disney spokeswoman Veronica Clemons said, saying exceptions to the dress code for religious reasons are made on a case-by-case basis. "We do have cast members who have attire significant to their religions."
Disney policy prohibits discussion of lawsuits, she said.
Any form of discrimination over religious beliefs is prohibited by the 1964 Civil Rights Act. The federal Equal Employment Opportunity Commission requires employers to accommodate workers' religious beliefs, "unless doing so would impose an undue hardship."
Undue hardship is not defined.
Baha, 32, worked at Walt Disney World from 1997 until mid-August 2002 and wore uniforms, referred to as "costumes," in her jobs as a bellhop and a sales clerk at Disney's Caribbean Beach Resort, according to interviews and the lawsuit she filed last week in federal court in Orlando.
She did not wear the hijab during that time.
But when she took maternity leave in 2002, her faith grew and she decided to wear the hijab when she returned to work in August.
"It wasn't something just for fun," she said. "It's like God is asking you to do it."
When Baha returned to her two jobs, she wore the scarf.
One was a part-time position as a bellhop. The other was a full-time sales job with commissions in The Pearl Factory, a franchise gift shop in the resort that requires employees to follow Disney's dress code, the lawsuit states.
Her supervisors, she said, would not let her continue working either job.
Disney offered to accommodate her religious attire with a "backstage" job out of the public view, the lawsuit states.
The Pearl Factory allowed Baha to continue wearing her scarf but transferred her away from Disney property, where the dress codes didn't apply. Her sales commissions fell from $400 to $700 a week to $40 a week at the new shop in the Old Town tourist attraction on U.S. Highway 192, she said.
She quit the Old Town job because of the drop in pay; Disney fired her from the part-time post because she refused to remove the scarf, according to the lawsuit.
"Plaintiff refused to work without her religious scarf as it is part of her religious beliefs and refused to be humiliated and downgraded by accepting the less favorable position in the backstage," the lawsuit states. "She was therefore terminated."
Baha's lawyer, Frank T. Allen of Orlando, described his client as an ideal employee who had embodied multicultural diversity and tolerance that Disney appears to champion through its worldwide marketing.
"This is totally contradictory to what they're portraying," he said.
What Disney workers wear has been regulated meticulously since Disneyland opened in 1955 to produce what is now marketed as the Disney experience.
"A big part of that show is you, with your quick smile, your eagerness to help and your willingness to maintain the Disney Look that our guests have come to associate with our very special brand," Walt Disney World Resort president Al Weiss wrote in the current employee handbook. "Each of you has helped uphold our heritage in so many ways, such as through your commitment to the Disney Look."
Everything from the socks on their feet to chewing gum, frowning in public and the cut of their hair is spelled out for the theme parks' 70,000 employees. But the resulting beard-free image conflicts with the distinctive religious attire and grooming practices for devout followers of Islam, Judaism and some other religions.
Arab-American groups say discrimination against Muslim women wearing hijabs has soared since the Sept. 11, 2001, terrorist attacks. Just this week, the U.S.
Department of Justice announced that it had compelled an Oklahoma school district to permit its female students to wear hijabs in class.
"What is a surprise in this particular case, if these allegations are indeed true, are Walt Disney's response to them," said Rabiah Ahmed, a spokeswoman for the Council on American-Islamic Relations in Washington, D.C. "It being such a huge corporation, you would think they would be more sensitive to its employees' needs and diversity."
A sales clerk wearing a religious scarf should not disrupt anyone's Disney experience, according to the American-Arab Anti Discrimination Committee.
"I'm guessing she's not dressed as Snow White, just wearing the standard Walt Disney uniform," said Leila Al-Qatami, a spokeswoman for the organization. "I don't think it [the hijab] impairs or in any way detracts from a person's experience at Disney World, and so our organization believes that you should make accommodations for religious clothing."
-----To see more of The Orlando Sentinel -- including its homes, jobs, cars and other classified listings -- or to subscribe to the newspaper, go to http://www.OrlandoSentinel.com
(c) 2004. Distributed by Knight Ridder/Tribune Business News. DIS,


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Design Number DS-8314
Products featuring this design:
Nahum Paint
"The Lord is good, a refuge in times of trouble. He cares for those who trust in him."
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SeaWorld San Diego05/25/2013
We are reasonably on time but traffic here in LA is actually always bad. Now because of Memorial Day weekend it is twice as busy. We drive towards the Mexican border and it shows on the road. Because it's already getting very late we decide to skip breakfast and directly go for lunch. We are looking for a Denny's to get some lunch. The first attempt fails, it is so very busy that we can not get a table and there's a queue waiting ahead of us. So we drive a little further and at Oceanside we are in better luck. It's also busy but at least a table is available immediately. Sea World is open until 23:00 today so we do have some time.
After lunch the rest of the trip is fine although still the same amount of traffic. Arriving at SeaWorld Hellen shows her military ID and we park for free. The parking is already jam-packed, we find a spot at the very end of the huge lot. We arrive at the checkout with the printed hero vouchers and enter the park for free without any trouble. It only took a supervisor to pass because a Dutch ID from the ministry of Defense is still something new for them.
Once inside we are not that happy because it is extremely crowded. You can actually see nothing but people. In this park there are hardly any attractions and lots of shows so once at a show it's not that bad but getting from A to B is quite hard to do. There are only two roller coasters so that should be possible.
The first coaster is Journey to Atlantis (#807), a water coaster by Mack and very beautifully themed to Atlantis. It is quite a long track with two lifts and two splashes, both thankfully not overly wet. One of the lifts is a beautifully ingenious system by Mack involving two boats on one platform being transported up as an empty platform goes down which pass each other and connect to the same track again. Furthermore, a great ride. Nicely integrated in Atlantis is also the Window to the Sea aquarium with rays and sharks.
At Wild Arctic we try to see the polar bears, but it's just too full. Penguin Encounter is a lot better. What probably helps is that almost all Americans are standing on the conveyor belt while we walk ourselves behind them.
We work our way towards the Shamu Stadium for the Orca show. After a number of recent incidents, the trainers no longer enter the water together with the animals. It's great to see these mighty animals perform though. It's an entertaining show and the pace is good. Here in San Diego they have quite a few killer whales performing at the same time.
At Pets Stadium we see a similar show as the one at Universal Studios with numerous pets, although also some less common animals such as kangaroos and geese occur. Nice to see and a good story all around.
We decide not to stay for the entire day because it seems to be getting increasingly crowded. Of course we still have to stop by SeaWorld's second roller coaster. Manta (#808) is a launched roller coaster which also happens to be manufactured by the Mack firm. This coaster is not even a year old and looks great. Most of the track is located behind the loading station and is therefore not directly visible.
This rids is obviously very busy too and the queue is approximately one hour. We go for front-seat because that might only be waiting an extra two rides longer and should be worth it. When we are about to enter the ride there is a technical failure and shortly afterwards it is announced that one may wait in line but it is unknown how long it will take. This turns out to be quite a while still, to be followed by some 5 test rides but ultimately Manta re-opens again and we can finally board.
Manta is a great smooth and fine roller coaster. Although not very high (the track is 9 meters at the highest point), there is a real nice drop of 16 meters underneath a walkway and around a corner back across the same walkway. At the back of the coaster there is a second launch and even more pleasant cornering. This is a very nice coaster.
We're going back to the hotel and once again hit the road. Hellen had picked a restaurant for tonight but we will not get there on time so we ask Garmin for something on route. And sure enough, we find a seafood buffet restaurant in Carlsbad. A great choice because they have a huge selection of fish and sushi.
Knott's tomorrow.
Lunch at Denny's in Oceanview.
In the parking lot of SeaWorld we see this Hyundai Coupe. In America this is a standard color Orange Crush. In our country, we don't see this color but my Atomic Orange looks exactly alike.
Journey to Atlantis looks attractive.
Familiar looking boats of the Mack water coasters, as in Poseidon of Europa Park.
Beautiful drop from the tower.
In the back it is quite possible to remain dry.
Orca show at the Shamu Stadium.
It is noticeable that the trainers remain at an appropriate distance from the animals.
Spectacular show.
The presenters can also be seen on these two huge screens.
We were just outside the splash zone. This is why.
These animals are capable of splashing a lot of water around.
At the pet show: ropejumping dog.
Manta is a very fine roller coaster. Here at the turning point near the walkway.
The top speed is 70 km / h.
Nice system that shows which restraints are not securely closed.
Manta like most visitors well.
Most visitors like Manta very well.
Atlantis one last time.
Sushi time again.