Explication with the passge has been faxed. Passing is through Pride & Prejudice and also the thesis is normally entered beneath Essay Case

Explication with the passge has been faxed. Passing is through Pride & Prejudice and also the thesis is normally entered beneath Essay Case Pride and even Prejudice: Any Mother’s Love In the work of fiction Pride together with Prejudice, the debate of the story remains on the Victorian household with a few daughters located relatively normally in the country. They are not rich, but they are able to continue a few housemaids and thus are the surfacing middle group of community. However , this became also a time when potentials for women were definitely restricted to matrimony, governess or even workhouse utilizing only the best two choices to excellent girls. Competitors for husbands was fantastic and Mrs. Bennett, mom of the four girls, uses much of the story obsessing regarding her daughters’ prospects. Mrs. Bennett’s materialistic, selfish character and tough desire to get married to off their daughters is usually displayed with her reaction to the news concerning Elizabeth plus Mr. Read more

Using Technological know-how Globally Composition Example

Using Technological know-how Globally Composition Example Employing Technology Globally al Rassemblement Question 4: (iv) If the choice manufactured in (ii) is not really global, and what will be benefits if it is world. How in another way will be the technology used exhibit your hard work applied inside a global supplier or an industry that has intercontinental participants?
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Korea’s Tesco just supplies food within the state (Bergen, 2011). Therefore , it is not a global provider. Going universal would require many corrections for the organization. For example , Market has to be delivered within a almost instantly of the purchaser placing an order. The exact implication is if the company Read more

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Explication on the passge continues to be faxed. Verse is through Pride & Prejudice and also thesis will be entered underneath Essay Instance Pride as well as Prejudice: A Mother’s Really like In the story Pride and even Prejudice, major of the storyline remains on the Victorian household with 5 daughters residing relatively comfortably in the country. They are not rich, however are able to hold a few housemaids and thus are the growing middle training of contemporary society. However , he did this also a time period when options available for women were being restricted to relationship, governess as well as workhouse using only the 1st two options available to excellent girls. Levels of competition for husbands was fantastic and Mrs. Bennett, the parent of the all five girls, pays much of the new obsessing pertaining to her daughters’ prospects. Mrs. Bennett’s materialistic, selfish nature and strong desire to marry off your girlfriend daughters is usually displayed on her reaction to the news in relation to Elizabeth plus Mr. Read more

Climate Difference in Africa Essay or dissertation Example

Climate Difference in Africa Essay or dissertation Example The actual paper “Climate Change in Africa” is an excellent example of an composition on the environmental studies. Environment is the investigation of atmospheric conditions to a particular place over a any period of time of time. Atmospheric patterns may vary from yr to year or so, from one decades to another, through century to an alternative century or any other longer time scale that could be specified. Therefore , climatic modify refers to the organization of a different climatic express as a result of steady change in situation such as conditions and precipitations.unemployedprofessors The damage changes is usually as a result of also natural or human causes(McMichael, 10). An example of a natural trigger may include; disparities in the piles of planet orbital factors and volcanic eruptions. Fossil fuels burnt with industries for generation regarding electricity, using up and liberating of facilities, industrial process which total gases just like chlorine as well as methane towards the atmosphere could be the human factors behind climate alter. Read more


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Machine Learning in Travel Industry

dlc. Travel Tech

Unless you’ve been living under a rock, ignoring every big tech advance in the past few years, you must have heard of machine learning!
For example, the recommendations made by Netflix and Amazon, the personal
assistants competing in our iOS and Androids devices, and  the futuristic self-driving cars are all forms of machine learning. Basically, machine learning is empowering the current artificial intelligence revolution. But what is it exactly? And how does the travel industry use it?

What is machine learning?

Machine learning is an application of Artificial intelligence (AI) which provides systems the ability to automatically learn and improve from experience, without being explicitly programmed.

Strange right? The co occurrence of “Machine” and “learn and improve from experience” in the same sentence, as if we’re talking about a human being , we kinda are, after all the goal of artificial intelligence is to mimic the human intelligence.

So, how does the machine learn after all?

This question is not yet easy to answer here, but let’s start by breaking down the big problem which is machine learning to different smaller set of main sub problems, the first one is called Supervised learning, the other one is Un-Supervised learning (there are other types but we’ll focus on those two to keep it simple).

Supervised machine learning, imagine you have a booking website, you’ll find yourself with a huge data about travel related reviews on hotels, places to visit etc. and you want to know the general sentiment on one of the hotels that you host on your website (maybe to list the hotels with the most positive feedback at the top of your search results).

Our supervised learning models can solve such task, these algorithms will look at as much as it can see from your customer positive and negative reviews, learning in the way the patterns that make a user review positive, this pattern may be finding the word “very” and the word “good” in the same phrase means that the sentence is positive, and it learns as well the pattern that makes a user review negative.

That’s why it’s called supervised, because our learning algorithms look at the data in a supervised way, they already have the answer (each phrase is positive or negative) and they try and learn the pattern that generates that answer, then our learning models are ready to be set free and look at new unseen hotel reviews and predict whether these reviews are positive or negative.


Un-supervised learning, unlike the previous type of learning, this one doesn’t use known outcomes to guide the learning. These algorithms can find patterns and relationships automatically in our data.

Imagine you want to send travel packages offers for your customers in a specific season maybe during the summer, but different people will react differently to the same package, unsupervised algorithms may come handy in these types of problems, where you want to cluster your customers into different customer segments and you don’t have any outcomes to guide the learning, then send each customer segment the package that they will probably love.


Machine learning at dlc. Travel Tech

Here at dlc. We’re integrating machine learning into our core apps, here’s a few examples:

a. Leads ranking – in Tangram CRM, you can classify new customers as hot or cold lead, in other words probability of whether the customer is gonna confirm a reservation or not.

b. Time Series Forecasting – Given historical data, we can provide predicted values to travel agencies that would forecast future revenue or total number of customers over time.

c. Recommender Systems – Recommend packages to customers, based on the information available about user, packages and user preferences.

d. Chatbots – Automated chat machines that can understand typed up words and sentences and communicate with customers to provide sales services.

If you’re interested to know more about the wonders of AI, check out this previous blog out.


How AI is Revolutionizing The Travel Industry.


A storm is coming. One that might possibly change the world for good; the same way we started using electricity for anything and everything back in 1882. That storm is called Artificial Intelligence (AI); and  every single working industry, in one way or another, is doing its best to make good use of it, including the travel industry.

While it’s true that the ideology and Science behind AI has been around for many years, it’s only now that we are really starting to see companies actually diffusing it into their regular work-flow.

In short, how a particular AI generally works is that it studies past data about a particular subject and tries to learn on its own the hidden patterns and trends. For example, a hotel’s dataset might show that Brazilians like to book expensive rooms in the month of June. A good AI would take notice of that, along with countless other patterns, that might not make logical sense to us, humans, but are essential to make predictions of how future customers would act.


The main reason for the sudden popularity is that AI is more ‘usable’ now. Reasons for that include:

  • Data is now in abundance and continue to increase exponentially.
  • The cost of storing data is decreasing exponentially.
  • Data gathered from IOT (Internet of Things) is available now in almost every electrical device.
  • The spread of computer hardwares which can run complicated algorithms quickly.

See the below chart as an example of the exponential growth of data:

Zooming in on the travel industry, we can find several examples on how AI has been particularly disruptive. Some of these examples are dynamic pricing, railway booking service, disruptive management and time series forecast.

The first example is PROS ; a company that utilizes an idea called dynamic pricing. PROS provides technology for popular airlines around the world, where the AI would first study consumer behavior on which flights they like to book, when and where. Then, when a future consumer wants to book a flight, it would automatically provide prices that he would be most comfortable with. For example, consumers on low budgets might be provided with lower priced flights, while consumers who were previously unhappy on cheap flights, might be provided with more expensive, but much more comfortable flights.

Using this, PROS have reported 50% less response time, 50% less mainframe usage, 100% increase availability in requests and almost 0% rejected traffic. In other words, consumers don’t need to spend as much time and are always able to find the best offers.

Another company is called Trainline, where they say you can “Save an average of 43% when you book tickets in advance.” This UK based company provides an online rail booking service, after gathering all kinds of consumer behavior data. Future train passengers would then be provided with tickets they are most likely to choose, while informing them what the cheapest price would be, how many tickets are left, and also notify them in advance when new tickets are available.


Disruption Management is another great example. A quick look on Flight Aware might give you an idea of how many flights are canceled or disrupted each day. The Australian Airlines, Qantas, decided to try to use AI to combat these issues. The AI would collect data from airports, including weather and current delays, and predict in the future if a disruption will happen and how. Furthermore, the AI would then automatically make a back-up plan that would be most convenient for the passenger to take.

Qantas reported that using this, “15 out of 436 Qantas flights (about 3.4 percent) were canceled, as compared to 70 out of 320 (22 percent) flights by Virgin Australia [another airline]”.

One further example is flight price prediction using time series analysis. AltexSoft developed an AI tool that would analyze changes, trends, seasonality of prices over time. Then, it would use that to give recommendations to the consumer of when to book a flight, whether he should wait for the price to go down, or if waiting is actually too risky. An example is shown below:

How dlc. uses AI

Here at dlc. we have a data science team dedicated to provide technology to travel agencies that make use of AI wonders. Examples of how we use AI include:

  • Dynamic Reports – Automatically providing ease-of-use charts that automatically calculates averages for numerical data (such as prices), as well as counts of categorical data (such as the total number of people for top nations). 
  • Leads Ranking – After receiving data containing consumer requests, this aspect would predict which are most likely to confirm a reservation and which requests are not. 
  • Time Series Forecasting – Given historical data, we can provide predicted values to travel agencies that would forecast future Revenue or total number of customers over time. 
  • Chatbots – Automated chat machines that can understand typed up words and sentences and communicate with customers to provide sales services.

…and much more in the future.

How Mobile Phones Revolutionized the 3 Stages of Travelling


Mobile Phones have evolved beyond imagination in the past 10 years. Not long ago they used to be merely used for phone calls, short text messages, and Snake game! But nowadays mobile phones have massive computing power compared to even computers 10 years ago. This vast evolution has lead to the integration of mobile phones in nearly all kinds of daily life activities. They have almost become our life partners or “a way of life” in the words of the former CEO of Apple, Steve Jobs.

One of the many activities mobile phones have hijacked in our daily lives is travelling. Mobile applications have swept the travelling industry and completely reshaped the industry, this can be clearly seen as a study has shown that 85% of international travelers have some kind of mobile device with them while travelling (Frederic Gonzalo, 2016). Not only has it dominated the in-travel experience but also the pre-travelling and post-travelling experiences have been recreated with mobile phones. Let’s go more in depth in each one of the 3 stages of travelling to see how mobile phones revolutionized each one of them

     1. Pre-Travelling experience:

This phase begins at reserving your flight and hotel, used to be a hassle of phone calls, followed by a payment meeting to physically deliver the money to your travel agency has never become easier. Now with a few taps on your phone you can book and pay for your entire vacation without leaving your seat. Studies have shown that Mobile bookings in travel have grown by 1700% between 2011 and 2015, moving from 1% to 18% of online revenues (Frederic Gonzalo, 2016). Also Furthermore you receive your booking confirmation on your phone and even your boarding pass! Now most airports around the world support self check-in using QR codes on their phones, and people are starting to adapt to it, Mobile boarding pass use has become the preferred choice of 18% of passengers within the past year, and the use of mobile apps for check-in will also double from 8% of passengers preferring this option to 16% by 2016..

2. During the Travelling experience:

Mobile phones have completely replaced the need for tour guides. Now you can access maps on your mobile phone and throw away the old paper maps you used to get from a stand in a souvenir shop. There are many applications which given some parameters like duration of stay, dates, and your interests can put together a full program for your trip which will cover all your needs, like google trips or visit a city. Moreover there are applications which even help you find shops that are near you and sort them by price like the infamous Yelp! According to a Survey done by Opera Media works 85% of respondents said they use mobile devices to book travel activities. 1 in 3 respondents said they use specific mobile applications, such as TripAdvisor and Yelp, to research accommodations and activities.

3. Post-Travelling experience:

Most people keep dwelling on the trip with nostalgia, and what better way to preserve memories than photos and videos that are always with you in your pocket. All the huge companies in the mobile industry have provided solutions in this area. For example, Apple introduced memories in its embedded photos application which creates a mashup video of images taken on the trip, Facebook introduced a standalone application called memories which allowed people who were with you on your trip to share photos with you so there would be only one common album were all your photos and memories would exist even the ones you did not take!

Moments: The Evolution of Cameras.

By Youssuf Radi- Backend Developer Intern.

Photography. An art form invented in 1830s, becoming publicly recognized ten years later. Today, photography is one of the largest growing hobbies in the world. Photography has come a long way in its relatively short history. In almost 200 years, the camera developed from a plain box that took blurry photos to the high-tech mini computers we use in our DSLRs and smartphones today.

The story of photography is fascinating and it’s possible to go into detail. Today we take a step back and look at how this fascinating technique was created and developed, because proudly knowing the past is the primary way to create a great future.

Camera Obscura

The basic concept of photography has been around since about the 5th-century B.C.E. It wasn’t until an Arabian scientist Hassan Ibn Al-Haytham developed something called the camera obscura (which is Latin for the Dark Room) in the 11th-century that the art was born.

Camera Obscura is essentially a dark, closed space in the shape of a box with a hole on one side of it. The hole has to be small enough in proportion to the box to make the camera obscura work properly.






The Invention of the Camera

The first photo picture – as we know it – was taken in 1825 by a French inventor Joseph Niepce. It depicts a view from the window at Le Gras.

the photo had to last for eight hours, so the sun in the picture had time to move from east to west, appearing to shine on both sides of the building in the picture.

In 1839 Sir John Herschel came up with a way of making the first glass negative as opposed to metal. The same year he coined the term Photography deriving from the Greek “fos” meaning light and “grafo” – to write.

Finally, after decades of refinements and improvements, the mass use of cameras began with Eastman’s Kodak’s camera. It went on to the market in 1888 with the slogan “You press the button, we do the rest”.

In 1901 the Kodak Brownie was introduced, becoming the first commercial camera in the market. The camera took black and white shots only.

The first 35mm still camera developed by Oskar Barnack of German Leica Camera. Using a film for colored photos.



The twin lens reflex (TLR) camera started in 1870. This type of camera has two lenses. The top lens composes and focuses. The bottom lens actually creates the shot.


The Single Lens Reflex (SLR) camera uses optical film to capture pictures and images. The mirror and prism system used in the SLR cameras send the light through the lens of the camera

Mirrorless Camera

Just Like Mobile Phones no Mirrors are used to view the photo Using the sensor directly to view the photo and record it if needed

Camera’s Principles


Exposure refers to the amount of light that enters the camera and hits the digital sensor. Basically, it is a measure of how dark or bright a photograph is. 







The aperture refers to the size of the opening in the lens through which the light

enters the camera. The size of this opening can be adjusted

and the aperture size is measured in f-stops.








shutter speed

The shutter speed refers to the length of time the opening in the

lens remains open to let light into the camera and onto the sensor.









The ISO refers to how sensitive the digital sensor in your camera is to light. The lower the ISO number, the less sensitive it is to light. Setting a higher ISO number increases the sensitivity of your camera sensor to light.