Finding the best mining law suitable for your needs isnt easy. With hundreds of choices can distract you. Knowing whats bad and whats good can be something of a minefield. In this article, weve done the hard work for you.
Best mining law
1. Arbitration of International Mining Disputes: Law and Practice (Oxford International Arbitration Series)
Description
International mining disputes represent a significant and growing area of disputes over natural resources, yet the unique risks inherent in the mining industry set them apart, both in the nature of the disputes and the approach taken to resolve them. International arbitration has emerged as the mechanism of choice for the resolution of such disputes. This has given rise to a wealth of arbitral decisions from which certain principles specific to the mining sector are developing.This book is the first of its kind to bring together thorough analysis of arbitral decisions and insightful commentary on both dispute resolution and the business of mining, in order to provide a comprehensive guide to arbitration in the mining sector. Part I introduces the different parties involved in international mining projects; Part II explains the main risks and challenges involved in mining projects and how they result in different types of disputes; Part III provides practical advice for parties and counsel involved in international mining disputes, including in-depth analysis of the confidentiality issues that so often arise in connection with international mining disputes and the conditions and strategies for the settlement of these disputes; and Part IV examines the substantive principles applicable to international commercial and investor-State mining disputes.
2. Mining Law and Policy: International Perspectives
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Book by Southalan, John3. Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies
Description
In 2004, the Government Accountability Office provided a report detailing approximately 200 government-based data-mining projects. While there is comfort in knowing that there are many effective systems, that comfort isnt worth much unless we can determine that these systems are being effectively and responsibly employed.
Written by one of the most respected consultants in the area of data mining and security, Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies reviews the tangible results produced by these systems and evaluates their effectiveness. While CSI-type shows may depict information sharing and analysis that are accomplished with the push of a button, this sort of proficiency is more fiction than reality. Going beyond a discussion of the various technologies, the author outlines the issues of information sharing and the effective interpretation of results, which are critical to any integrated homeland security effort.
Organized into three main sections, the book fully examines and outlines the future of this field with an insiders perspective and a visionarys insight.
- Section 1 provides a fundamental understanding of the types of data that can be used in current systems. It covers approaches to analyzing data and clearly delineates how to connect the dots among different data elements
- Section 2 provides real-world examples derived from actual operational systems to show how data is used, manipulated, and interpreted in domains involving human smuggling, money laundering, narcotics trafficking, and corporate fraud
- Section 3 provides an overview of the many information-sharing systems, organizations, and task forces as well as data interchange formats. It also discusses optimal information-sharing and analytical architectures
Currently, there is very little published literature that truly defines real-world systems. Although politics and other factors all play into how much one agency is willing to support the sharing of its resources, many now embrace the wisdom of that path. This book will provide those individuals with an understanding of what approaches are currently available and how they can be most effectively employed.
4. The Mining Law of 1872: Past, Politics, and Prospects
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Used Book in Good ConditionDescription
History has left us a classic image of western mining in the grizzly forty-niner squatting by a clear stream sifting through gravel to reveal gold. What this slice of Western Americana does not reveal, however, is thousands of miners doing the same, their gravel washing downstream, causing the water to grow dark with debris while trout choke to death and wash ashore. Instead of the havoc wreaked upon the western landscape, we are told stories of American enterprise, ingenuity, and fortune.
The General Mining Act of 1872, which declared all valuable mineral deposits on public lands to be free and open to exploration and purchase, has had a controversial impact on the western environment as, under the protection of federal law, various twentieth-century entrepreneurs have manipulated it in order to dump waste, cut timber, create resorts, and engage in a host of other activities damaging to the environment. In this in-depth analysis, legal historian Gordon Morris Bakken traces the roots of the mining law and details the way its unintended consequences have shaped western legal thought from Nome to Tombstone and how it has informed much of the lore of the settlement of the West.
5. Foreign Mining Investment Law: The Cases of Australia, South Africa and Colombia
Description
6. Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis
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Used Book in Good ConditionDescription
It is now possible to predict the future when it comes to crime. In Data Mining and Predictive Analysis, Dr. Colleen McCue describes not only the possibilities for data mining to assist law enforcement professionals, but also provides real-world examples showing how data mining has identified crime trends, anticipated community hot-spots, and refined resource deployment decisions. In this book Dr. McCue describes her use of "off the shelf" software to graphically depict crime trends and to predict where future crimes are likely to occur. Armed with this data, law enforcement executives can develop "risk-based deployment strategies," that allow them to make informed and cost-efficient staffing decisions based on the likelihood of specific criminal activity.Knowledge of advanced statistics is not a prerequisite for using Data Mining and Predictive Analysis. The book is a starting point for those thinking about using data mining in a law enforcement setting. It provides terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis, which law enforcement and intelligence professionals can tailor to their own unique situation and responsibilities.
* Serves as a valuable reference tool for both the student and the law enforcement professional
* Contains practical information used in real-life law enforcement situations
* Approach is very user-friendly, conveying sophisticated analyses in practical terms
7. Machine Learning Forensics for Law Enforcement, Security, and Intelligence
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Used Book in Good ConditionDescription
Increasingly, crimes and fraud are digital in nature, occurring at breakneck speed and encompassing large volumes of data. To combat this unlawful activity, knowledge about the use of machine learning technology and software is critical. Machine Learning Forensics for Law Enforcement, Security, and Intelligence integrates an assortment of deductive and instructive tools, techniques, and technologies to arm professionals with the tools they need to be prepared and stay ahead of the game.
Step-by-step instructions
The book is a practical guide on how to conduct forensic investigations using self-organizing clustering map (SOM) neural networks, text extraction, and rule generating software to "interrogate the evidence." This powerful data is indispensable for fraud detection, cybersecurity, competitive counterintelligence, and corporate and litigation investigations. The book also provides step-by-step instructions on how to construct adaptive criminal and fraud detection systems for organizations.
Prediction is the key
Internet activity, email, and wireless communications can be captured, modeled, and deployed in order to anticipate potential cyber attacks and other types of crimes. The successful prediction of human reactions and server actions by quantifying their behaviors is invaluable for pre-empting criminal activity. This volume assists chief information officers, law enforcement personnel, legal and IT professionals, investigators, and competitive intelligence analysts in the strategic planning needed to recognize the patterns of criminal activities in order to predict when and where crimes and intrusions are likely to take place.
8. Graph Mining: Laws, Tools, and Case Studies (Synthesis Lectures on Data Mining and Knowledge Discovery)
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Used Book in Good ConditionDescription
What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others.In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints.
Table of Contents: Introduction / Patterns in Static Graphs / Patterns in Evolving Graphs / Patterns in Weighted Graphs / Discussion: The Structure of Specific Graphs / Discussion: Power Laws and Deviations / Summary of Patterns / Graph Generators / Preferential Attachment and Variants / Incorporating Geographical Information / The RMat / Graph Generation by Kronecker Multiplication / Summary and Practitioner's Guide / SVD, Random Walks, and Tensors / Tensors / Community Detection / Influence/Virus Propagation and Immunization / Case Studies / Social Networks / Other Related Work / Conclusions
