DAMEWARE - Data Mining & Exploration Web Application Resource

Astronomy is undergoing through a methodological revolution triggered by an unprecedented wealth of complex and accurate data. DAMEWARE (DAta Mining & Exploration Web Application and REsource) is a general purpose, Web-based, Virtual Observatory compliant, distributed data mining framework specialized in massive data sets exploration with machine learning methods. We present the DAMEWARE (DAta Mining & Exploration Web Application REsource) which allows the scientific community to perform data mining and exploratory experiments on massive data sets, by using a simple web browser. DAMEWARE offers several tools which can be seen as working environments where to choose data analysis functionalities such as clustering, classification, regression, feature extraction etc., together with models and algorithms.Comment: User Manual of the DAMEWARE Web Application, 51 page

Knowledge transfer inside the regional economic system: the case of eighty years of economic history of the Russian North-East

Economic role of the knowledge transfer is studied on the example of the Russian North-East and its two basic branches that is exploration and mining which form the core of the regional economy (regional mining system). Russian North-East can be considered as isolated industrial district with the basic gold mining activity. The scale of this activity has been determined regional socio-economic development for the last 80 years. The major information for this study has been taken from GIS on the spatial structure of exploration and mining branches in the Russian North-East on the district level for the last 80 years. On the basis of revealed regularities and specifics in the interregional knowledge transfer we have formed general understanding of this process. We have analyzed major channels of knowledge transfer from exploration as the branch generating new knowledge on the mineral resources to mining in which this knowledge is utilized. We have determined major systems of knowledge transfer from one branch to the other under different periods of regional economic history. We have examined how territorial structures of exploration and mining industries had been changed inside the regional system for the last 80 years. Main characteristics of knowledge transfer inside the regional mining system influence its productivity (volume of extraction, speed of development of the new deposits, etc.). Effective communication between exploration and mining industry, knowledge transfer from the geologists to the miners is critically important for the sustainable work of the regional mining system.

Learning what matters - Sampling interesting patterns

In the field of exploratory data mining, local structure in data can be described by patterns and discovered by mining algorithms. Although many solutions have been proposed to address the redundancy problems in pattern mining, most of them either provide succinct pattern sets or take the interests of the user into account-but not both. Consequently, the analyst has to invest substantial effort in identifying those patterns that are relevant to her specific interests and goals. To address this problem, we propose a novel approach that combines pattern sampling with interactive data mining. In particular, we introduce the LetSIP algorithm, which builds upon recent advances in 1) weighted sampling in SAT and 2) learning to rank in interactive pattern mining. Specifically, it exploits user feedback to directly learn the parameters of the sampling distribution that represents the user's interests. We compare the performance of the proposed algorithm to the state-of-the-art in interactive pattern mining by emulating the interests of a user. The resulting system allows efficient and interleaved learning and sampling, thus user-specific anytime data exploration. Finally, LetSIP demonstrates favourable trade-offs concerning both quality-diversity and exploitation-exploration when compared to existing methods.Comment: PAKDD 2017, extended versio

Asian Pacific Marine Minerals and Industry Structure

Eventual development of marine minerals potential in the Asian Pacific would likely draw on the technology, skills, and experience of the emerging international seabed mining industry. As a result of strategic behavior by its firms, this small-numbers industrial "strategic group" has created a level of capacity for seabed mining exploration and research and development (R&D) that far exceeds the near-term level of activity expected in seabed mining. The paper reports on the nature of preproduction industrial structure (or "protostructure") in seabed mining and draws implications for efforts to develop the resource potential of Asian Pacific marine minerals. Seabed minerals exploration and R&D services might be offered to Asian Pacific nations at bargain prices (below unit cost) by firms with first-starter advantages in the emerging industry. However, cautionary notes are included about constraints on the economic potential of the region's deep-sea minerals such as manganese nodules, polymetallie sulfides, and cobalt crusts.Environmental Economics and Policy, International Relations/Trade, Resource /Energy Economics and Policy,

Analyzing factors affecting Alaska's salmon permit values: evidence from Bristol Bay drift gillnet permits

Thesis (M.S.) University of Alaska Fairbanks, 2017The effects of total earnings, total costs and mining exploration on permit prices in Alaska are investigated using an autoregressive distributed lag (ARDL) approach to cointegration. I take specific account of regional and gear specific salmon fisheries -- that is, Bristol Bay drift gillnet permits -- in our modelling. I find that there is a stable long-run relationship among permit prices, total earnings, and total costs. It is also found that, in both the short- and long-run, total earnings have a positive and significant relationship with permit prices, while total costs have a negative and significant relationship. Although the mining exploration in the region has a negative and significant effect on permit prices in the short-run, the effect does not seem to last in the long-run

Socioeconomic Impacts of Potential Wishbone Hill Coal Mining Activity

The purpose of this study is to assess some of the significant socioeconomic effects of potential coal mining activity at Wishbone Hill. The analysis scenario assumes a 16-year period of startup and mine production using two known deposits that are currently permitted by the State of Alaska for mineral exploration. “Mine Area 1” would be mined during years 2-7 and “Mine Area 2” would be mined during years 8-16. Mining would only take place at one of these areas during any given time. We considered four kinds of effects: Jobs and income, fiscal impacts, property values, and traffic.Matanuska - Susitna Borough Economic Development DepartmentIntroduction / Coal Mining Scenario / Projected Jobs and Income / Fiscal Impacts / Property Values / Traffic / References / Appendix: Notes on Methodolog

Mining in Alaska - environmental impact and pollution control

Environmental factors affecting mining are difficult to establish in Alaska due to the absence of large scale hard rock mining activities at the present time. Currently, experience is gathered from (and to a large degree based on) construction of above ground facilities such as roads, pipelines, and buildings. Past mining activities appear to have had little lasting effect on the natural environment, the exceptions being mine tailings and surface structures. This report, sponsored by the U. S. Bureau of Mines, present general engineering activities, considers the interaction of permafrost and underground mining, summarizes available literature and indicates possible environmental problems that might be encountered in Alaska based on Scandinavian experiences in large-scale northern mining operations. How the Scandinavians are solving their problems is also discussed.This paper was sponsored by the U. S. Bureau of Mines, Contract No. 0133059.Abstract -- Acknowledgements -- Table of contents -- List of illustrations -- List of tables -- Introduction -- Climatic parameters -- Alaska climatic regions -- Construction and mining activities in the Arctic -- General -- Cold weather construction practices -- Permafrost and underground mining operations -- Environmental considerations -- Mining and exploration parameters -- Conclusions -- Recommendations -- Bibliography -- Appendices -- Appendix A: Bibliography - Lost River area -- Appendix B: Mining and environmental considerations as practiced in Norway and Sweden -- Appendix C: Mining vs. the environment -- Figure 1. Alaska climatic regions -- Figure 2. Index map showing mining districts examined -- List of tables -- Table 1. Dates of break-up and freeze-up