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There can be an inclination amongst some governments and non-governmental organisations (NGOs) to view the resource sector with some cynicism. Junior mining companies sometimes engage with local communities (or not), leave without...
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There can be an inclination amongst some governments and non-governmental organisations (NGOs) to view the resource sector with some cynicism. Junior mining companies sometimes engage with local communities (or not), leave without a trace (or perhaps with tracks, trails and trenches) and offer only a brief hope for betterment (or long-standing court battles over environmental or community issues) causing strong emotive reactions. None of the major miners have managed to avoid controversy in their own corporate histories either; of course, none ever could. The art of crafting reform to mineral regulation throughout the world has become a balancing act for the international resource lawyer. The mining company requires certainty when investing in exploration, development or expansion projects in a foreign country to offset the substantial uncertainty inherent in the exploration and mining processes themselves. One needs clear rules which are consistently applied that assure the developer that it may explore, develop and produce any discovery without interference of government or any other person and can measure with some accuracy the expected investment and the anticipated reward. This paper examines several mining codes in the Middle East and offers a critical assessment of their relative opportunity and risk to the developer. It examines each risk in comparative detail, including in comparison to a set of principles found in an exemplary mining code adopted by Madagascar in 2005. The principles of a model mining code (MMC) have been determined after examining more than 50 mining codes from around the world and benefit from the work of MineHutte and the Fraser Institute, which offer ratings for mining regulatory regimes based on different criteria.
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It is common practice for software developers to use examples to guide development efforts. This largely unwritten, yet standard, practice of "develop by example" is often supported by examples bundled with library or framework pa...
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It is common practice for software developers to use examples to guide development efforts. This largely unwritten, yet standard, practice of "develop by example" is often supported by examples bundled with library or framework packages, provided in textbooks, and made available for download on both official and unofficial web sites. However, the vast number of examples that are embedded in the billions of lines of already developed library and framework code are largely untapped. We have developed XSnippet, a context-sensitive code assistant framework that allows developers to query a sample repository for code snippets that are relevant to the programming task at hand. In particular, our work makes three primary contributions. First, a range of queries is provided to allow developers to switch between a context-independent retrieval of code snippets to various degrees of context-sensitive retrieval for object instantiation queries. Second, a novel graph-based code mining algorithm is provided to support the range of queries and enable mining within and across method boundaries. Third, an innovative context-sensitive ranking heuristic is provided that has been experimentally proven to provide better ranking for best-fit code snippets than context-independent heuristics such as shortest path and frequency. Our experimental evaluation has shown that XSnippet has significant potential to assist developers, and provides better coverage of tasks and better rankings for best-fit snippets than other code assistant systems.
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Generally, the gold mining industry has a negative image because it is potentially highly polluting, its costs often externalized on local communities that host its operations. Recently, there has been growing activism in most cou...
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Generally, the gold mining industry has a negative image because it is potentially highly polluting, its costs often externalized on local communities that host its operations. Recently, there has been growing activism in most countries where rich gold deposits exist. Although the industry has many drawbacks, it can potentially confer many benefits, especially for the people of the developing world, by providing employment and foreign exchange. In the context of the mining sustainable development debate, this paper examines the environmental performance of the gold mining industry in developing countries, and its impacts on resident populations and communities.
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Identifiers play an important role in helping developers analyze and comprehend source code. However, many identifiers exist that are inconsistent with the corresponding code conventions or semantic functions, leading to flawed id...
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Identifiers play an important role in helping developers analyze and comprehend source code. However, many identifiers exist that are inconsistent with the corresponding code conventions or semantic functions, leading to flawed identifiers. Hence, identifiers need to be renamed regularly. Even though researchers have proposed several approaches to identify identifiers that need renaming and further suggest correct identifiers for them, these approaches only focus on a single or a limited number of granularities of identifiers without universally considering all the granularities and suggest a series of sub-tokens for composing identifiers without completely generating new identifiers. In this article, we propose a novel identifier renaming prediction and suggestion approach. Specifically, given a set of training source code, we first extract all the identifiers in multiple granularities. Then, we design and extract five groups of features from identifiers to capture inherent properties of identifiers themselves and the relationships between identifiers and code conventions, as well as other related code entities, enclosing files, and change history. By parsing the change history of identifiers, we can figure out whether specific identifiers have been renamed or not. These identifier features and their renaming history are used to train a Random Forest classifier, which can be further used to predict whether a given new identifier needs to be renamed or not. Subsequently, for the identifiers that need renaming, we extract all the related code entities and their renaming change history. Based on the intuition that identifiers are co-evolved as their relevant code entities with similar patterns and renaming sequences, we could suggest and recommend a series of new identifiers for those identifiers. We conduct extensive experiments to validate our approach in both the Java projects and the Android projects. Experimental results demonstrate that our approach could identify identifiers that need renaming with an average F-measure of more than 89%, which outperforms the state-of-the-art approach by 8.30% in the Java projects and 21.38% in the Android projects. In addition, our approach achieves a Hit@10 of 48.58% and 40.97% in the Java and Android projects in suggesting correct identifiers and outperforms the state-of-the-art approach by 29.62% and 15.75%, respectively.
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摘要 :AbstractDRC's 2002 Mining Code has attracted Large-Scale Mining (LSM) through favorable fiscal conditions, but is detrimental to Artisanal and Small-scale Mining (ASM). The Code specifies that ASM should take place in Artisanal...
展开AbstractDRC's 2002 Mining Code has attracted Large-Scale Mining (LSM) through favorable fiscal conditions, but is detrimental to Artisanal and Small-scale Mining (ASM). The Code specifies that ASM should take place in Artisanal Exploitation Zones (AEZ), but far too few AEZ were created to accommodate the large number of artisanal miners. This has triggered an explosive situation, as many artisanal miners operate in mining concessions granted to LSM companies. While LSM companies justify their operations referring to statutory law, miners claim traditional rights to the land. We study how this situation of legal pluralism plays out in Kamituga, a gold mining area in South-Kivu. To what extent do the artisanal miners and the LSM company stick to their opposing frames of reference? To what extent do they look for compromises? Can these compromises give way to the re-making of institutions?Highlights?DRC's 2002 Mining Code has attracted Large-Scale Mining (LSM).?Many artisanal miners operate in mining concessions granted to LSM companies.?LSM companies justify their operations referring to statutory law, miners claim traditional rights.?We show how interaction in this context of legal pluralism gives way to the re-making of institutions.]]>
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Abstract Court judgments contain valuable information on how statutory laws and past court precedents are interpreted and how the interdependence structure among them evolves in the courtroom. Data-mining the evolving structure of...
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Abstract Court judgments contain valuable information on how statutory laws and past court precedents are interpreted and how the interdependence structure among them evolves in the courtroom. Data-mining the evolving structure of such customs and norms that reflect myriad social values from a large-scale court judgment corpus is an essential task from both the academic and industrial perspectives. In this paper, using data from approximately 110,000 court judgments from Japan spanning the period 1998–2018 from the district to the supreme court level, we propose two tasks that grasp such a structure from court judgments and highlight the strengths and weaknesses of major machine learning models. One is a prediction task based on masked language modeling that connects textual information to legal codes and past court precedents. Another is a dynamic link prediction task where we predict the hidden interdependence structure in the law. We make quantitative and qualitative comparisons among major machine learning models to obtain insights for future developments.
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To accelerate software development, developers frequently search and reuse existing code snippets from a large-scale codebase, e.g., GitHub. Over the years, researchers proposed many information retrieval (IR)-based models for cod...
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To accelerate software development, developers frequently search and reuse existing code snippets from a large-scale codebase, e.g., GitHub. Over the years, researchers proposed many information retrieval (IR)-based models for code search, but they fail to connect the semantic gap between query and code. An early successful deep learning (DL)-based model DeepCS solved this issue by learning the relationship between pairs of code methods and corresponding natural language descriptions. Two major advantages of DeepCS are the capability of understanding irrelevant/noisy keywords and capturing sequential relationships between words in query and code. In this article, we proposed an IR-based model CodeMatcher that inherits the advantages of DeepCS (i.e., the capability of understanding the sequential semantics in important query words), while it can leverage the indexing technique in the IR-based model to accelerate the search response time substantially. CodeMatcher first collects metadata for query words to identify irrelevant/noisy ones, then iteratively performs fuzzy search with important query words on the codebase that is indexed by the Elasticsearch tool and finally reranks a set of returned candidate code according to how the tokens in the candidate code snippet sequentially matched the important words in a query. We verified its effectiveness on a large-scale codebase with ～41K repositories. Experimental results showed that CodeMatcher achieves an MRR (a widely used accuracy measure for code search) of 0.60, outperforming DeepCS, CodeHow, and UNTF by 82%, 62%, and 46%, respectively. Our proposed model is over 1.2K times faster than DeepCS. Moreover, CodeMatcher outperforms two existing online search engines (GitHub and Google search) by 46% and 33%, respectively, in terms of MRR. We also observed that: fusing the advantages of IR-based and DL-based models is promising; improving the quality of method naming helps code search, since method name plays an important role in connecting query and code.
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The phone numbers listed on a Web page displayed on a mobile phone can be useful information for instant reservations or general inquiries. Although current software technology for smart phones can recognize and highlight phone nu...
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The phone numbers listed on a Web page displayed on a mobile phone can be useful information for instant reservations or general inquiries. Although current software technology for smart phones can recognize and highlight phone numbers on a page and auto-dial them when clicked, the extraction accuracy often drops significantly due to many cases of data that are falsely recognized as phone numbers. Furthermore, there are many situations in which the area code is missing, preventing the mobile phone from auto-dialing correctly. To resolve these problems, this paper proposes an intelligent phone number extraction and area code mining technique for smart phones in a mobile environment. A series of experiments performed using Android smart phones showed that our method greatly improved the accuracy of phone number mining and the speed of auto-dialing in a mobile Web environment.
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