REQUIREMENT- AWARE STRATEGIES FOR SCHEDULING MULTIPLE DIVISIBLE LOADS IN CLUSTER ENVIRONMENTS

Ph.DDOCTOR OF PHILOSOPH

Chawls : popular dwellings in Bombay

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1981.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH.Bibliography: p. 68.by Mayank Shah.M.S

Institutional reforms in irrigation sector of Punjab, Pakistan: Proceedings of Workshop held at Faisalabad Serena on 10-11 February 2000

Institution building / Irrigated farming / Irrigation management / Participatory management / Farmer participation / Farmers' associations / Pakistan / Punjab / Hakra

Institutional reforms in irrigation sector of Punjab, Pakistan: Proceedings of Workshop held at Faisalabad Serena on 10-11 February 2000

Institution building / Irrigated farming / Irrigation management / Participatory management / Farmer participation / Farmers' associations / Pakistan / Punjab / Hakra

Data warehouse applications in modern day business

Data warehousing provides organizations with strategic tools to achieve the competitive advantage that organazations are constantly seeking. The use of tools such as data mining, indexing and summaries enables management to retrieve information and perform thorough analysis, planning and forcasting to meet the changes in the market environment. in addition, The data warehouse is providing security measures that, if properly implemented and planned, are helping organizations ensure that their data quality and validity remain intact

Resource aware load distribution strategies for scheduling divisible loads on large-scale data intensive computational grid systems

Ph.DDOCTOR OF PHILOSOPH

Customer Behavior Change Detection Based on AMR Measurements

Smart Grids are making use of information and communications technology (ICT) to improve the reliability and flexibility of traditional power grids. This technology depends more and more on methods like load modeling, state estimation, and load forecasting methods. All of these methods are aiming to benefit the whole network analysis to make it become more accurate. Among these methods, load modeling is a very important part of analysis of the whole power network and can offer a good fundamental to other analysis methods. Due to the highly stochastic nature of electricity consumption with many uncertainties, various statistical and classification techniques based on fast data collection are required to help improving the accuracy of conventional load modeling. Nowadays widely used automatic meter reading (AMR) technology in Finland makes it possible to collect customers' hourly load measurements and to use mature clustering methods to analyze those huge sets of customer data and give a better prediction. In this thesis, some basic classification and regression concepts are borrowed from statistics or machine learning field to help us to analyze the electric customer behavior between di fferent years. This thesis aims to detect either load level change or load shape change of electric customers. K-means and Fuzzy C-means (FCM) are two main methods implemented in MATLAB environment to analyze the load curves. It successfully detects various obvious load pattern changes on different customer types. For the question that when the customer behavior change happens during a year, this thesis can just offer the time information regarding at which week the change happens rather than the specific date. Because we mainly consider the obvious change that lasts for at least one week and ignore temporary changes. The change detection accuracy may be improved in future by more sophisticated methods

QUANTIFYING THE SOURCE AND PATHWAY OF DISSOLVED REACTIVE PHOSPHATE IN KARST DRAINAGE OF THE INNER-BLUEGRASS

In the Midwestern U.S. seasonal hypoxia experienced in the Gulf of Mexico and harmful algal blooms in inland freshwater ponds, lakes, and rivers are partly fueled by dissolved orthophosphate loadings from disturbed landscapes. Efforts to reduce dissolved reactive phosphate (DRP) loadings have had varying levels of success and have led to insufficient water quality improvements. Inefficiencies in conservation strategies can stem from poor understanding of phosphate source and flow pathway dynamics. This study focused on monitoring sources and flow pathways of dissolved reactive P in a karst agroecosystem with phosphatic limestone. We collected event water samples at the Camden Creek watershed outlet in Woodford County, Kentucky and characterized P sources by sampling spring water and soils across the watershed. Oxygen isotope results for orthophosphate at springs suggested significant differences in isotope signatures at high and low flows, despite similar concentrations, likely reflecting differences in connectivity to anthropogenic and ambient P sources. Multiple linear regression models to predict DRP concentrations revealed that a mass-balance unmixing approach may help distinguish between DRP pathways in a heterogeneous karst system better than commonly used hydrograph recession methods. Soils from our study site had high extractable P concentrations at both the surface and deeper soil zones, with high heterogeneity reflecting soil composition and spatial variability in management. Overall, this work provides insight into phosphate source and transport in a karst agroecosystem and provides broader implications for implementing best management strategies to reduce DRP loading in such systems