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These were the fossils that were displayed in the museum section of the visitors centre.
A few of these images are replica fossils of ones that were found here and others are real fossils that have been found and displayed.
I took a photo of a replica fossil being sold in the gift shop as although it is not real it still mimicked an Ammonite fossil which has an interesting spiral shape.
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27/04/24 - Interesting Points on Streets
This weekend I went to Southampton, where despite the grey weather and plain architecture, the streets had many interesting elements to them. I took photographs to document for my project as primary research.
As soon as you exit the train station, there is a beautiful and colourful mural painted over the side of what appear to be abandoned office blocks. This automatically makes the city feel more welcoming, however the contrast is very stark. I feel it is obvious in the positioning and aim of the mural; to make Southampton look nicer than it is, like putting lipstick on a pig.
However, the creativity continues as you walk towards to high street and shopping centre, as there is poems and historical facts engraved into the wide curb, which is interesting to look at when you are walking, much like the Lemn Sissay poem.
On this walk, there was also a graffiti wall, a small green area and sculptures, which definitely added something cool and appealing to what otherwise would have been a boring walk from the station to the shopping centre. They also had traditional signposts, which aren’t around much anymore. I really liked these, and we actually used them a couple of times and so they served a purpose as well.
This creativity stopped as it got to the shopping area, however on the other side of the station, there was another mural with a QR code to find out more about the art. QR codes are very in trend at the moment, so I think this was a good way to share information without being overwhelming. It also gives you the opportunity to save the website on your phone and look at it whilst you are on the train.
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This was me testing the whole label for the can to see how the spacing and sizing works in adobe dimensions a newly learned program.
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PJ Harvey - "A Child's Question, August"
PJ Harvey has shared the first single, “A Child’s Question, August”, off her upcoming album “I Inside The Old Year Dying” out July 7th via Partisan.
TRACKLIST:1. Prayer at the Gate2. Autumn Term3. Lwonesome Tonight4. Seem an I5. The Nether-edge6. I Inside the Old Year Dying7. All Souls8. A Child’s Question, August9. I Inside the Old I Dying10. August11. A Child’s Question, July12. A Noiseless…
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Great day to go to Houston,TX & Charlotte, NC. (at Sky Harbor Airport Term3) https://www.instagram.com/p/CkqV2WirFulHTExSvrU0MK7Bi6IbThuKvyyOts0/?igshid=NGJjMDIxMWI=
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Network Architecture in Best Project Center
Now, we describe the neural network architecture used in this paper. CNNs have shown to be useful in computer vision. Recently, they are applied to problems of natural language processing (NLP) domain also. Proposed a neural network architecture which can be applied to many NLP tasks such as named entity recognition, parsing, part-of-speech tagging, and chunking used CNN for sentence classification. The best project center in nagercoil, layers present in our CNN architecture are: input layer, convolution layer, pooling layer, hidden layer, and an output layer. Each tweet is comprised group of words. We use dense representation of the words in our work.
Dense representations of the words can be obtained in many different ways. Some of the common ways are: the word vectors which are randomly initialized, pretrained distributional word embeddings of word2vec, or global vector (Glove), fast Text embeddings, or dependence-based embeddings. The tweet vector is formed by concatenating the individual word vectors of the tweet. If the dimension of word vector is d and the length of the tweet is l then the dimension of tweet matrix is l × d. This tweet matrix is input to the first layer of CNN.
Let a tweet be comprised the sequence of words: fiterm1, term2, term3, . . . , termn. Then, the tweet vector is represented as
Tv = w1 ◦ w2 ◦ w3 ◦ . . . ◦ wn (1)
where wi is the word embedding vector of termi, and ◦ is the concatenation operator. Each wi ∈ Rd is associated with its corresponding pretrained word vector. Next layer is the convolution layer. Activation functions like tanh, relu, and sigmoid are used to get the convolution feature maps. Single filter or multiple filters can be applied depending on the task. Filter length can be 1, 3, 5, and so on.
If filter length is one, then the context of the words in the sentence is ignored, and target word feature map is calculated. If filter length is three, then target word feature map is calculated by considering target word, one word left and one word right to the target word. Here, context is preserved. Similarly, if filter length is five, then target word, two words left, and two words right of target word are considered. After finding convolution feature maps, most important activation should be selected.
This is done by pooling layer. Normally max pooling is used in NLP tasks whereas mean pooling and min pooling are also used in computer vision. We apply max pooling on the convolution layer. Next layer is fully connected hidden dense layer. Finally, sigmoid activation function is applied to classify the given tweet. We used l2 regularization to avoid overfitting. The parameters used in our method are as follows: Number of filters: 250, dropout: 0.2, batch size: 32, optimizer: Adam, and loss function: binary cross entropy.
Word Embeddings: We now describe the details of the word embeddings used in our work. Word embeddings are the distributional representation of words in lower dimensional space. Best project center in Tirunelveli, these word embeddings can be obtained by using word2vec model. There are two methods to train word embeddings in word2vec: continuous bag of words (CBOWs), and skip-gram. In CBOW, target word is predicted using the context whereas in skip-gram context is predicted using target word. CBOW is faster than skip-gram. However, skip-gram performance is better than CBOW. Have created word embeddings of Google news corpus by using word2vec model. This corpus contains 3 million words and phrases with 300 dimensions.
Glove for word representation is described the model is created using two methods, global matrix factorization and local context window. Pretrained Twitter specific glove embeddings are available. Twitter word embeddings are created using 2 Billion tweets. It contains 27 Billion tokens, 1.2 Million vocabulary uncased and several variations of dimensions (25, 50, 100, and 200). We have created the word embeddings of HSpam14 using word2vec model with the skip-gram method and 200 dimensions. We have also used Edinburgh corpus Twitter word embeddings which are trained on 10 million tweets with 100 dimensions and 400 dimensions.
#Engineering Project center in Tirunelveli#Best project center in Tirunelveli#Best project center in nagercoil
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Term3 : Oral assessment”No Bully” https://www.instagram.com/p/Cgx-IP8KoY-/?igshid=NGJjMDIxMWI=
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p6 sst scheme of work term3
p6 sst scheme of work term3
p6 sst scheme of work term3
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These images show part of the process of me binding my journal. These include putting holes for the thread, Japanese stab stitching the book and adding the mull to strengthen the bind.
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26/04/24 - Times Square
I was speaking to my dad about my COVL project, explaining that I wanted to potentially look at billboards that change, keeping it interesting for people walking on the street and getting people to look up off their phones. I told him about my research for the D&AD project, The Man in the Clock at Schipol Airport, and he suggested to look at Times Square as that is an example of successful billboarding. He went to New York a few years ago, and sent me some photos he took of Times Square. I want to look more into these as a potential outcome for this project.
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#BookReview#RootRotAcademy#Term3#RheaWatson#AcademyRomance#ReverseHaremRomance#UrbanFantasy#Magic#Witch#Vampire#Fae#Warlock
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Posted @withregram • @russellchildrensballetschool Spring Term Registration for CURRENT students goes live March 26th!! Our Spring Term (Term 3) runs for 10 weeks starting April 19th until June 26th. NEW students can register starting April 1st. #rcbsdance #rcbsregistration #russellchildrensballetschool #springregistration #term3 #dancefamily #balletjazztaphiphop #teenytots https://www.instagram.com/p/CMvWWNTF3ig/?igshid=1xoh8l2f4pom5
#rcbsdance#rcbsregistration#russellchildrensballetschool#springregistration#term3#dancefamily#balletjazztaphiphop#teenytots
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On my 240th rostered shift at this school with 6 children😊 #PupilFreeDay #OSHCCoordinator #OneTeamCampAustralia🇦🇺 #Term3 #Week4 (at Mullum Primary School) https://www.instagram.com/p/CEvwavkDtlO/?igshid=qhb7wq0oo744
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