The Tragedy Of The Titanic Disaster

Jon Krakauer’s Into Thin Air has many people making life-or-death decisions in a matter of minutes. In the midst of a disaster, many people will make decisions that are illogical.

The research and analysis conducted in this project will show evidence of meeting the requirements of program outcome three by assessing the human factors and elements that are directly associated with the situation facing airlines – post 9/11.

Hospital Readmissions are costly to the government, hospitals, and patients. Some of these pricey readmissions can be avoided by providing the appropriate care for the patients that are at a higher risk of readmission. Many studies have used predictive analytical approaches to discover which patients are more likely to be readmitted. Most of said studies use some form of regression to analyze all patients. We took a different route and used an advanced decision tree (Gradient Boosted Tree) as we found it to be more fitting for the data we collected. With COPD as a constant factor in our patients, we were able to develop a specific model for a subsection of all hospital readmissions. With COPD being a fix variable, our model was able to dig deeper into other

In most cases, ships have a capacity for passengers’ safety to be onboard to avoid heavy casualties in event of accidents. Furthermore, there were marked sex and social class differences in survival among passengers on the Titanic. All passengers from the different social class derived the large part of the survival from the behavior of the passengers.

About a hundred years have passed since the British passenger liner met its fatal end in the North Atlantic on April 15, 1912. The RMS Titanic plummeted two miles to the ocean floor after clashing into an iceberg during its journey to the Port of New York. Over 1,500 people drowned in this unfortunate event. Ever since the sinking, numerous books and remarkable films have been made, telling the story of the ship and its passengers. The wreck of the ship was found in 1985 by the coast of Newfoundland, in the North Atlantic Ocean. Over the years, Titanic’s story has gained unbelievable public exposure and warns people about the danger of not being cautious enough. The Steamship, Titanic, was the end-result of fierce competition among competitor shipping lines in the early 1900s. The White Star Line company competed with Cunard, a British company with two ships that ranked in the categories for the most sophisticated and luxurious during their time. One of Cunard’s masterpieces, Lusitania, met its devastating end in 1915 when a torpedo was fired by a German U-boat and sunk the ship. The sinking killed about 1,200 out of 1,959 people on board and was the gateway to the United States’ entry into World War I. We chose this topic to write about because of the overwhelming impact that the event had on American history. The three categories on the Titanic are: the creation of the boat, passengers and luxury on board, and the night of the unfortunate tragedy.

Disasters aren’t called disasters for nothing. This is portrayed in the sinking of the Titanic. Some disasters are people's fault, and some are natures. This was not the case in the sinking of the R.M.S. Titanic. Bruce Ismay was the owner of the Titanic, and possibly a coward onboard. As the Titanic went down, Ismay jumped on one of the last lifeboats, and survived the sinking. Most of the world thought this was a bad move on his part, as women and children are supposed to survive, if no one else. From then on, he was called the coward of the Titanic.

Every day the surgical interventions are associated with medicine, and the area of critical care medicine is no exception. The goal of this work is to assist health professionals in predicting these interventions. Thus, when the Data Mining techniques are well applied it is possible, with the help of medical knowledge, to predict whether a particular patient should or not should be re-operated upon the same problem. In this study, some aspects, such as heart disease and age, and some data classes were built to improve the models created. In addition, several scenarios were created, with the objective can predict the resurgery patients. Regarding the primary objective, the resurgery patients’ prediction, the most important metric is the sensitivity,

Some would say that one’s social status or financial abilities makes them worth more than one another. Titanic passengers were divided into three separate classes, determined not only by the price of their ticket, but by their wealth; the third class passengers consisted of immigrants and diverse groups of different nationalities, who were moving to the United States and Canada to find a better way of life (Brewster 25). Spike Milligan once stated, “Only the third class tourist class passengers’ deck was it a sultry overcast morning, but then if you do things on the cheap you must expect these things.” The treatment of the third class passengers on the infamous ship The Titanic was shameful and unjust due to their eating and sleeping conditions, mistreatment, and repercussions during the sinking.

2:20 A.M. on April 15, 1912 one of the greatest ships sank it was named The Titanic.

An unsinkable sink that killed 1500 people. The voyage of the Titanic ended in a watery grave. There were many primary and secondary sources about the Titanic sinking. The articles change the perception of the way people think about the Titanic sinking.

The concept of artificial intelligence was first labeled by a man named Alan Turing in 1950, he believed that the future would hold the possibility for man to communicate with computers and sustain a conversation (Atkinson, Solar 1). Although, we have reached the point where it is possible to hold a simple preprogrammed conversation with a computer and give them the ability to learn, there is still a long way to go in making computers fully artificially intelligent. Atkinson and Solar continue to describe some real world applications of artificial intelligence such as, “Data mining technologies, fraud detection, and industrial-strength optimization” (8). In these examples, forms of artificial intelligence like cognitive reasoning abilities are already being used making the demand for them higher.

There are five steps involved in creating a decision tree. The first step is to identify and set limits to the problem, for example whether or not the gallbladder of a person without symptoms should be removed. The second step is to diagram the options. This can be done by starting with the patient’s current clinical status, then laying out the different options and the outcomes that could come from each option. The third step is to obtain information on each option. In this step, the possibility of each outcome occurring should be assessed and then the outcomes should be separated into desirable and undesirable outcomes. The fourth step is to compare utility values and the fifth step is to perform sensitivity analysis (97-98).

The selection and implementation of the appropriate data - mining technique is the main task in this phase. This process is not straightforward; usually, in practice, the implementation is based on several models, and selecting the best one is an additional task. By simple definition, in classification/clustering we analyze a set of data and generate a set of grouping rules which can be used to classify future data. One of the important problems in data mining is the Classification-rule learning which involves finding rules that partition given data into predefined classes. An association rule is a rule which implies certain association relationships among a set of objects in a database. In sequential Analysis, we seek to discover patterns that occur in sequence. This deals with data that appear in separate

There are different types of machine learning logarithms available to solve the classification problems. To carry out this experiment

Weka (Waikato Environment for Knowledge Analysis) is a collection of machine learning algorithms developed on Java platform by University of Waikato, New Zealand. It is a data analyzing tool used for data modeling and predictive analysis. It is licensed under GNU General Public License. As it is implemented in Java it is platform independent. It is a comprehensive collection of various data preprocessing and modeling techniques. Some of the operations performed using Weka like classification, clustering etc. are discussed here. It provides implementation of various algorithms which can be applied on any kind of datasets.