Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Improvement of Energy Efficiency in a Gold Mining Industry: Case Study of a Russian Gold Mining Company

The issue of energy efficiency is attracting more and more attention of academia, business and policy makers worldwide due to increasing environmental concerns, depletion of non-renewable energy resources and unstable energy prices. The significant importance of energy efficiency within gold mining industry is justified by considerable energy intensity of this industry as well as by the high share of energy costs in the total operational costs. In the context of increasing industrial energy consumption energy efficiency improvement may provide significant energy savings and reduction of CO2 emission that is highly important in order to contribute to the global goal of sustainability. The purpose of this research is to identify the ways of energy efficiency improvement relevant for a gold mining company. The study implements single holistic case study research strategy focused on a Russian gold mining company. The research involves comprehensive analysis of company’s energy performance including analysis of energy efficiency and energy management practices. This study provides following theoretical and managerial contributions. Firstly, it proposes a methodology for comparative analysis of energy performance of Russian and foreign gold mining companies. Secondly, this study provides comprehensive analysis of main energy efficiency challenges relevant for a Russian gold mining company. Finally, in order to overcome identified challenges this research conceives a guidance for a gold mining company for implementation of energy management system based on the ISO standard.

Investigating the potential of thecamoebians (testate amoebae) as bio-indicators of impact of oil sands mining operations on freshwater environments in Northeastern Alberta, Canada

Thecamoebian (testate amoeba) species diversity and assemblages in reclamation wetlands and lakes in northeastern Alberta respond to chemical and physical parameters associated with oil sands extraction. Ecosystems more impacted by OSPM (oil sands process-affected material) contain sparse, low-diversity populations dominated by centropyxid taxa and Arcella vulgaris. More abundant and diverse thecamoebian populations rich in difflugiid species characterize environments with lower OSPM concentrations. These shelled protists respond quickly to environmental change, allowing year-to-year variations in OSPM impact to be recorded. Their fossil record thus provides corporations with interests in the Athabasca Oil Sands with a potential means of measuring the progression of highlyimpacted aquatic environments to more natural wetlands. Development of this metric required investigation of controls on their fossil assemblage (e.g. seasonal variability, fossilization potential) and their biogeographic distribution, not only in the constructed lakes and wetlands on the oil sands leases, but also in natural environments across Alberta.

Bee Communities in Restored Landfill Sites of Niagara Region

This study examined the impact of habitat restoration on bee communities (Hymenoptera: Apidae) of the Niagara Region, Ontario, Canada. Bee abundance and diversity was studied in three restored landfill sites: the Glenridge Quarry Naturalization Site (GQNS) in St. Catharines, Elm Street Naturalization Site in Port Colborne, and Station Road Naturalization Site in Wainfleet during 2011 and 2012. GQNS represented older sites restored from 2001-2003. Elm and Station sites represented newly restored landfills as of 2011. These sites were compared to control sites at Brock University where bee communities are well established and again to other landfills where no stable habitat was available before restoration. The objective of this study is to investigate the impact of restoration level on bee abundance and diversity in restored landfill sites of the Niagara Region. Based on the increased disturbance hypothesis (InDH) and the intermediate disturbance hypothesis (IDH), I hypothesized that bee abundance and diversity will follow two patterns. First pattern according to InDH suggest that as the disturbance decrease the bee abundance and diversity will increased. Second pattern according to the IDH bee abundance and diversity will be the highest at the intermediate level of disturbance. A total of 7 173 bees were collected using pan traps and flower collections, from May to October 2011 and 2012. Bees were classified to five families, 21 genera and sub-genera, containing at least 78 species. In 2011 bee abundance was not significantly different among restoration levels while in 2012 bee abundance was significant difference among restoration level. According to family there were no significant difference in Halictidae and Apidae abundance among restoration level while Colletidae and Megachilidae abundance were varied among restoration levels. The bee species richness was highest in the newly restored sites followed by restored control sites, and then the control site. The current study demonstrates that habitat restoration results in rapid increases in bee abundance and diversity for newly restored sites, and, further, that it takes only 2-3 years for bee assemblages in newly restored sites to arrive at the same levels of abundance and diversity as in nearby control sites where bee communities are well established.

Glacial stratigraphy and micromorphology of the Pine Point Pb-­‐Zn mining district, Northwest Territories

This investigation aims to gain a better understanding of the glacial history of the Pine Point Mining district, Northwest Territories, by examining the sedimentological properties of the glacial sediments including, geochemical analysis, heavy mineral concentrate analysis, clast macro-­‐fabrics, pebble lithologies, and micromorphological investigation. Four till units were identified, and three were associated with identified erosional bedrock features and streamlined landforms in the area, indicating a minimum of three ice flow directions. Sedimentological properties suggest that these units were all Type-­B tectomict/mélange till, emplaced as part of a soft subglacial deformable bed. The lack of ice-­‐marginal advance and retreat sequences within the studied till, suggests the Middle Wisconsinan Laurentide Ice margin was likely north and west of the Pine Point area, as opposed to along the margin of the Canadian Shield and Western Sedimentary Basin where it has been suggested to have existed.

Union Pacific Railway from Kansas City , Omaha, St. Joseph to Denver, San Francisco, Portland, Helena, Butte, Boise, Leadville, Durango, Deadwood and all cities and mining camps in the west schedule

Union Pacific Railway from Kansas City , Omaha, St. Joseph to Denver, San Francisco, Portland, Helena, Butte, Boise, Leadville, Durango, Deadwood and all cities and mining camps in the west schedule, Jan. 15, 1882.

Travels in México, during the years 1843 and 44 ; including a description of California, the principal cities and mining districts of that republic the Oregón territory, etc.

UANL

McNeill's code : Arranged to meet the requirements of mi ning, metallurgical and civil engineers ; directors of mining, smetling and other companies...

UANL

Constituting "Community" at the onset of the Pascua Lama Mining Project

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

The Gandarela Mountain Range and the “resistance space” against iron ore mining threat: a focus on the contrapositions

Full Text / Article complet

Environmental impact of sand mining

This thesis Entitled Environmental impact of Sand Mining :A case Study in the river catchments of vembanad lake southwest india.The entire study is addressed in nine chapters. Chapter l deals with the general introduction about rivers, problems of river sand mining, objectives, location of the study area and scope of the study. A detailed review on river classification, classic concepts in riverine studies, geological work of rivers and channel processes, importance of river ecosystems and its need for management are dealt in Chapter 2. Chapter 3 gives a comprehensive account of the study area - its location, administrative divisions, physiography, soil, geology, land use and living and non-living resources. The various methods adopted in the study are dealt in Chapter 4. Chapter 5 contains river characteristics like drainage, environmental and geologic setting, channel characteristics, river discharge and water quality of the study area. Chapter 6 gives an account of river sand mining (instream and floodplain mining) from the study area. The various environmental problems of river sand mining on the land adjoining the river banks, river channel, water, biotic and social / human environments of the area and data interpretation are presented in Chapter 7. Chapter 8 deals with the Environmental Impact Assessment (EIA) and Environmental Management Plan (EMP) of sand mining from the river catchments of Vembanad lake.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

Applying Data mining using Statistical Techniques for Career Selection

For years, choosing the right career by monitoring the trends and scope for different career paths have been a requirement for all youngsters all over the world. In this paper we provide a scientific, data mining based method for job absorption rate prediction and predicting the waiting time needed for 100% placement, for different engineering courses in India. This will help the students in India in a great deal in deciding the right discipline for them for a bright future. Information about passed out students are obtained from the NTMIS ( National technical manpower information system ) NODAL center in Kochi, India residing in Cochin University of science and technology