| Papers [1-14] of 100 :: [Page 1 of 8] | | Go to page : 1 2 3 4 5 6 7 8 —> | Search results on "MINING OCEAN RESOURCES": |
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Mining The Ocean's Resources, 2002.
Offshore drilling and its consequences.
2,400 words (approx. 9.6 pages), 6 sources, £ 61.95
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Abstract
This paper deals with offshore drilling of oil and its consequences on environment and marine life.
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Data and Text Mining, 2007.
A discussion on how data and text mining tools are revitalizing the librarian profession.
4,555 words (approx. 18.2 pages), 30 sources, MLA, £ 82.95
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Abstract
The paper discusses how the many advances in data and text mining are already revolutionizing the librarian profession. The paper explores how the ability of data mining tools to extract, transfer and load (ETL) massive amounts of data at a single time, is changing how all tasks in an organization get completed.
Outline:
Executive Summary
Content Integration Is Key
Data Mining
i) Principles of Data Mining
ii) Data Mining Timeline
Data Mining Implications for Librarianship
Text Mining
i) Text Mining Timeline
ii) Data Mining versus Text Mining
iii) Mining Blogs: An Example of How Text Mining Works
Text Mining Implications for Librarianship
Conclusion
From the Paper
"At the intersection of text mining, linguistic analysis, statistical analysis, and latent semantic indexing techniques (Wikipedia Latent Semantic Indexing 2006). is the future of text mining that has the power to discover and report trending in highly unstructured content. At the center of text-mining's' rapid growth is the increasing sophistication of Natural Language Processing (CRM Buyer 2005). IBM and their significant research efforts in natural language processing are well documented on their website, as are the efforts and investments Microsoft is making."
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Data Mining, 2005.
The paper is about data mining, which is the process of finding trends and patterns in data, often within a database.
3,546 words (approx. 14.2 pages), 10 sources, MLA, £ 68.95
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Abstract
Data mining has become a very important concept today and is used by companies all over the world to increase their profits and target the right market. The paper talks about the different aspects of data mining, tools used, and future trends in data mining. Data mining benefits are discussed in detail, and an entire discussion related to the trends in data mining is presented.
1-Background
2-Introduction
3-Data Mining Growth and Tools
4-The Data Mining Process
5-Data Mining Market Place Trends
6-The Data in Data Mining and Meta Data
7-Types of Data Mining Problems
8-Privacy and Ethical Sensitivity in Data Mining Results
9-Future Prospects of Data Mining
10-Works Cited
From the Paper
"Data, particularly in the vast diversity and immense quantity that it is available to modern business, was till recently almost very hard to find and understand. Yet, the comprehension of data is the most crucial step to extracting the knowledge that it contains. The scenario has drastically changed today where data is much more easily available and has become more "meaningful" with the utilization of Data Mining. Today, technology offers business managers powerful new tools for gleaning knowledge from data-the essentials of data mining. Data mining has become increasingly important to mainstream companies to become more competitive both in their workings and their customer based relationships. Data mining, as such is of great interest because it is imperative for organizations to grasp the competitive value of information contained within their data repositories. There are a number of pertinent benefits of data mining. First of all, data mining provides the tools and techniques that are essential for optimization of customer relationships. Secondly, data mining provides an automatic method of discovering patterns in data. Thirdly, but not the least, data mining tools can identify the relationships that are actually present in historical data."
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Data Mining in Business Research, 2008.
A review on data mining's growth and a discussion on the different factors involved in text mining.
2,307 words (approx. 9.2 pages), 20 sources, MLA, £ 49.95
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Abstract
This paper relates that the use of data mining, its adjunct technologies for text mining and the ability to interpret, analyze and create linguistic models from unstructured content is revolutionizing the concept of data mining away from being purely used for structured content in data warehouses to now encompass unstructured content found throughout organizations globally.
The paper then provides insights into various areas of data mining, and the currently high levels of growth analytics use and applications software are experiencing as a result.
Outline:
Executive Summary
Using Data Mining in Business Research
Exploring the principles of Data Mining in Business Research
Predictive Methods in Data Mining
From the Paper
"A second predictive approach is called deviation detection. The purpose of this method is to discover the most significant changes in data from previously measured or median values. An example of the type of use for this predictive approach would be the development of strategies for selling tickets to frequent flyers who booked months in advance versus those that consistently book within a few weeks of their departure. A third approach to using data mining to predict future outcomes is using the classification approach, or technique. This predictive approach of classification uses a collection of records (training set) -- each record contains several attributes, one of them is the class (Ng & Han, 10). The task is to find a model for the class attribute as a function of other attributes, so, after that, previously unknown records can be assigned a very accurate class."
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Uranium Mining, 2006.
An overview of the controversy surrounding uranium mining with a focus on the Jabiluka mine controversy in Australia.
1,282 words (approx. 5.1 pages), 3 sources, MLA, £ 30.95
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Abstract
This paper describes the controversy surrounding the Jabiluka mine in Australia, which dates back to the early 1970s when Pancontinental Mining Limited discovered high-grade uranium deposits in Jabiluka. The paper describes efforts by environmental organizations, student groups and traditional landowners to block the uranium mining project initiated by Energy Resources Australia and the results of those efforts.
From the Paper
"While the Labor Party was in power in the 1980's, the construction of new mines was safely relegated to the back burner. However the mid 1990s marked the rebirth of uranium mining in Australia. The ERA presented its EIS (Environmental Impact Statement) to the pro-uranium mining Howard Government in 1996. In October 1997, Senator Hill approved the EIS, despite obvious flaws in the process & study. ERA sought to use the existing Ranger Mine facilities to mill Jabiluka ore. Construction commenced at the Jabiluka Site on 15th June 1998, amidst widespread opposition from environmentalists & traditional Aboriginal (Mirrar) landowners. A Jabiluka Blockade comprising of students, environmental groups, and traditional landowners was organized. At times, physical efforts by Blockade participants prevented trucks & equipments from entering the Jabiluka site."
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Data Mining, 2006.
Examines the benefits of data mining to an organization.
3,397 words (approx. 13.6 pages), 5 sources, MLA, £ 66.95
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Abstract
Data mining is the extraction of hidden predictive information from large databases. This paper examines the effect that data mining has on the current corporate climate. It defines data mining and examines the scope of its existence and effects on overall industry and the rest of the world. The paper also explains the basics of the technology behind data mining and how these tools will interact with localized software. Examples of how data mining technology can be profitably used, as well as how it will use the data warehouse architecture to evolve existing software to develop new ways to collect and interpret information, is also looked at.
From the Paper
"Model building itself is not a new technology; it is in fact something that has been around for a very long time. Since the beginning of computer technology, modeling has been a method to finding solutions. Computers work just as humans do by collecting information from a variety of differing situations and attempting to put it together in such a way that makes sense. With computers, there are more resources as well as faster integration of the information so the model building process is easy, fast and efficient. It also is much more complex than anything that a human can build which means the answer is in more depth and more accurate."
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The Valuing of Mining Projects, 2004.
This paper is a literature review and a research proposal to study the way mining projects currently are valued and to demonstrate the need for changing this method.
12,500 words (approx. 50.0 pages), 50 sources, MLA, £ 165.95
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Abstract
This paper explains that capital allocation is extremely important to mining, and the efficiency and effectiveness with which this capital is allocated will be greatly affected by the valuation of a project. The author points out that determining the best method is not the purpose of this paper; rather, using a primary and secondary approach, the study will examine current practices, review the various financial principles and methods that are currently available, and derive ideas for solutions that are somewhat more in favorable. The paper demonstrates that both the commercial and the technical aspects that have to do with mining investments have always been very high risk; however, in recent years, new elements of political risk are being created by the United States, which is considering changes in some of the mining laws that will be more stringent, making mining even more economically risky. Tables and graphs.
Table of Contents
Introduction
Statement of the Problem
Purpose of the Study
Importance of the Study
Rationale for the Study
Overview of the Study
Review and Analysis of the Literature
Methodology
Data Analysis
From the Paper
"Larger companies, naturally, are much more sophisticated in the ways that they analyze their capital budgets. Companies that have sales greater than 500 million often use combinations of all three of the DCF techniques that are available. Many of these companies also performed escalated dollar analyses and constant dollar analyses that depended not only on financing alternatives but also on time constraints. Companies also used even more advanced techniques in performing various valuations into mining projects, but this was not seen to be on a consistent basis. Some of these techniques included computer simulations on various investment activity similar to Monte Carlo analyses and a specific way of utilizing options pricing into valuing of copper properties."
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Data Mining, 2004.
An exploration of the tools and equipment used in data mining.
3,476 words (approx. 13.9 pages), 12 sources, MLA, £ 68.95
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Abstract
This paper presents an overview of data mining tools commercially available today. These tools are invaluable in helping commercial ventures, scientists, economists, medical practices, and even weather forecasters detect patterns and data sets in vast quantities of information that they have collected. After an overview of what data mining is and how it is utilized, the writer focuses on specific data mining tools on the market. A description of characteristics and the leading products of the type of tool are examined. Finally, a detailed look at a specific product, which uses neural network-based data mining tools, is examined in depth.
From the Paper
"Data mining is the process of seeking and extracting knowledge buried in large volumes of raw data. The importance of collecting data that reflects business or scientific activities is well recognized today. (Brodley, Lane, Stough 1999) Most large and mid range companies now utilize various commercially available data warehousing software for collecting and managing the large quantities of information that they collect. Before data mining technology, the bottleneck in turning raw data into useful information was how to accurately and quickly extract knowledge from the collected raw data. Analysis by humans without special tools cannot make sense of enormous volumes of data that require processing in order to make informed business or scientific decisions. Data mining automates the process of finding relationships and patterns in raw data and delivers results that can be either utilized in an automated decision support system or assessed by human analysts. (Brodley, Lane, Stough)"
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Coal Mining In Hunter Valley, 2007.
This paper examines the issue of coal mining in Hunter Valley, Australia.
1,470 words (approx. 5.9 pages), 10 sources, MLA, £ 33.95
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Abstract
In this article, the writer notes that within the global environment there are nearly always situations and circumstances of special interest within the environmental sciences, as changes in industry occur all over the world and have varying impacts on the environment, both locally and globally. The writer points out that one issue of just such importance and of particular personal importance is the issue of Coal Mining in Hunter Valley New South Wales, Australia. The writer discusses the proposed development of an open pit coal mine in one of the few remaining tracks of naturally preserved land in the region, in fact the largest containing nearly 600 living elements of flora and fauna many of which are threatened, and the global nature of the debate that has ensued. The writer notes that conclusion of the matter is likely to end with approval for the Centennial Mining Co., as they, as well as most others, are assured that their extensive work to develop the plans and impact reports for the Anvil mine location will result in success since the state government is clearly projected to approve the development of the mine in Anvil Hill.
Outline:
Introduction
Background
Proposal For Change
From the Paper
"One of the most challenging issues at work today in the environmental sciences is of coarse sustainable development. We stand at the precipice of a period of global transition, where challenges to the old, including but not limited to challenges to the global dependence on fossil fuels and a demand to transition to sustainable resources are in conflict. The transition will surely prove to be a difficult one, even though it would not seem that it should be given the seriousness of the environmental issues at hand. It is proposed by many environmental scientists that environmental devastation caused in part by the emissions of greenhouse gasses that deplete the earths protection from the sun and will eventually lead to mass climate change that could create a situation of extinction not only for the environment but for humans, much like the one theoretical extinction of historical proportions that are currently being studied, that of the dinosaurs. The transition is a challenge in a broad sense because the foundation of energy resources if squarely placed upon the use of fossil fuels and many individuals and organizations stand to lose a great deal in the short run for a long term goal that will likely never gain for them at all."
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Data Mining, 2002.
A study of data mining, which is the business information process for locating information.
1,005 words (approx. 4.0 pages), 7 sources, APA, £ 24.95
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Abstract
This paper examines the InfoWorld?s article by Paul Krill, ?Microsoft Pushes Data Mining in Business Intelligence Protocol? and relates the business merits of Data Mining. The paper also explores other resources on the topic that discuss its impact on business and individuals, with particular attention the Fortune 500 corporations. The paper provides a history of data mining in order to foresee its future.
From the Paper
"There is a great deal of flexibility which businesses who use data mining will have upon their marketing campaigns. By knowing the customer almost as well as the customer knows him or her self, retail businesses can adjust their sales tactics to match the needs and desires of the customers. Individuals will have more choice, and more pleasing choice too. Companies will have more options for enticing customers, and less money can be spent on sending out independent researchers ? since the data will already be at hand."
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Data Mining, 2002.
An overview of the security issues surrounding data mining.
900 words (approx. 3.6 pages), 4 sources, £ 24.95
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Abstract
This paper examines the practice of data mining. It outlines what data mining is and why it is engaged in. It also considers how data mining raises privacy concerns.
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Data Mining in E-Commerce, 2005.
Examines data mining in e-commerce.
3,220 words (approx. 12.9 pages), 9 sources, APA, £ 77.95
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Abstract
This paper examines data mining in e-commerce and discusses the various types of modeling used to make the data meaningful to e-tailers. The advantages and pitfalls of data mining and an explanation of how it has transformed e-commerce are detailed. The paper includes an abstract and table of contents.
From the Paper
"Data mining as applied to e-commerce is a breakthrough technology that can gather information in an automated fashion and build models used to predict customer purchasing decisions with remarkable accuracy ..."
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Data Mining, 2004.
This paper discusses the use of data mining, a technique using sophisticated computer software to scour a company's database looking for specific management information.
2,250 words (approx. 9.0 pages), 9 sources, APA, £ 54.95
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Abstract
This paper defines data mining to help senior management to manage and direct the company more effectively. The author points out the types of data. The paper reviews methods of data mining including the software.
From the Paper
"Domestic and global business competition is fierce. Companies must look for new tools to give them a competitive advantage. Technology has added an additional layer of competitive tools commonly called data mining technology or data mining software. For many firms seeking to improve their competitive edge, the ability to perform data mining is rapidly becoming a necessity rather than a luxury. Data mining involves the extraction of hard to find information from large databases that companies normally maintain. Data mining tools can help businesses predict future ..."
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The Sago Mining Crisis, 2008.
Analyzes the communication issues relating to the 2006 coal mine explosion at the Sago Mine, Sago, West Virginia.
2,040 words (approx. 8.2 pages), 6 sources, MLA, £ 44.95
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Abstract
This paper explains that the tragedy of the Sago Mining crisis, one of the worst mining-related disasters in United States history, goes beyond the deaths of the miners and includes a vast network of miscommunication and uncoordinated response, which were partially responsible for the wide-spread death caused by the explosion. The paper presents a case study of this crisis that includes an in-depth overview of the crisis timeline, with pre-crisis, crisis and post-crisis events, and an analysis of the crisis management plan and its implementations. The paper concludes that the crisis management failures were a lack of communication, especially underground, because of out-of-date technologies, rescue process plan and the rescue teams.
Table of Contents:
Introduction
Research Questions
Crisis Timeline
Methods of Research
Analysis
Conclusion
Implications
From the Paper
"Prior to the Sago Mine explosion, the Federal Mine Safety and Health Administration cited the Sago mine two hundred and eight separate times for regulation violations in 2005 alone. Out of these, ninety-six were considered to be significant and substantial violations. Further, the West Virginia Office of Miners' Health, Safety and Training issued 144 citations on Sago Mines in 2005, many of them for violations that were most likely factors in causing the accident (such as a failure to maintain control over methane and dust accumulation or fix shafts)."
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