Code generator for integrating warehouse XML data sources.

XML---the extensible Markup Language, has been recognized as the standard for data representation and exchange on the world wide web. Vast amounts of XML data are available on the web. Since the information on the web is stored on separate web pages, it is very hard to combine pieces of information for decision support purposes. Data warehouse data integration provides a solution for integrating the different XML source data into a unique format with meaningful information for decision support systems. A data warehouse is a large integrated database organized around major subjects of an enterprise for the purpose of decision support querying. Many enterprises are creating their own data warehouse systems from scratch in different varying formats, making the issue of building a more efficient, more reliable, cost-effective and easy-to-use data warehouse system important. Building a code generator for creating a program that automatically integrates XML data sources into a target data warehouse is one solution. There is little research showing the use of the newest XML techniques in code generator for data warehouse XML data integration. This thesis proposes a Warehouse Integrator code generator for XML (WIG4X), which integrates XML data sources into a target data warehouse by first generating Java programs for data extracting, cleaning and loading XML data into the data warehouse. WIG4X system also generates the programs for creating XML views from the data warehouse. XML schema mapping strategy is employed for structural integration of each XML data source to data warehouse using a first order logic-like-language similar to that used in INFOMASTER. The content integration is handled through XML data extraction, conversion constraints, data cleaning and data loading. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .L57. Source: Masters Abstracts International, Volume: 40-06, page: 1549. Adviser: Christie Ezeife. Thesis (M.Sc.)--University of Windsor (Canada), 2002

LED-Induced Fluorescence System for Tea Classification and Quality Assessment

A fluorescence system is developed by using several light emitting diodes (LEDs) with different wavelengths as excitation light sources. The fluorescence detection head consists of multi LED light sources and a multimode fiber for fluorescence collection, where the LEDs and the corresponding filters can be easily chosen to get appropriate excitation wavelengths for different applications. By analyzing fluorescence spectra with the principal component analysis method, the system is utilized in the classification of four types of green tea beverages and two types of black tea beverages. Qualities of the Xihu Longjing tea leaves of different grades, as well as the corresponding liquid tea samples, are studied to further investigate the ability and application of the system in the evaluation of classification/quality of tea and other foods

Data-Driven Robust Control of Unknown MIMO Nonlinear System Subject to Input Saturations and Disturbances

This paper presented a new data-driven robust control scheme for unknown nonlinear systems in the presence of input saturation and external disturbances. According to the input and output data of the nonlinear system, a recurrent neural network (RNN) data-driven model is established to reconstruct the dynamics of the nonlinear system. An adaptive output-feedback controller is developed to approximate the unknown disturbances and a novel input saturation compensation method is used to attenuate the effect of the input saturation. Under the proposed adaptive control scheme, the uniformly ultimately bounded convergence of all the signals of the closed-loop nonlinear system is guaranteed via Lyapunov analysis. The simulation results are given to show the effectiveness of the proposed data-driven robust controller

Multi-Stage Reinforcement Learning for Non-Prehensile Manipulation

Manipulating objects without grasping them enables more complex tasks, known as non-prehensile manipulation. Most previous methods only learn one manipulation skill, such as reach or push, and cannot achieve flexible object manipulation.In this work, we introduce MRLM, a Multi-stage Reinforcement Learning approach for non-prehensile Manipulation of objects.MRLM divides the task into multiple stages according to the switching of object poses and contact points.At each stage, the policy takes the point cloud-based state-goal fusion representation as input, and proposes a spatially-continuous action that including the motion of the parallel gripper pose and opening width.To fully unlock the potential of MRLM, we propose a set of technical contributions including the state-goal fusion representation, spatially-reachable distance metric, and automatic buffer compaction.We evaluate MRLM on an Occluded Grasping task which aims to grasp the object in configurations that are initially occluded.Compared with the baselines, the proposed technical contributions improve the success rate by at least 40\% and maximum 100\%, and avoids falling into local optimum.Our method demonstrates strong generalization to unseen object with shapes outside the training distribution.Moreover, MRLM can be transferred to real world with zero-shot transfer, achieving a 95\% success rate.Code and videos can be found at https://sites.google.com/view/mrlm

The Pore Confinement Effect of FDU-12 Mesochannels on MoS 2

FDU-12 silica with highly ordered face-centered cubic mesoporous structure is developed as support to prepare Mo/FDU-12 catalysts for hydrodesulfurization (HDS) of dibenzothiophene (DBT). A series of Mo/FDU-12 catalysts are synthesized by using incipient wetness impregnation method with different MoO3 loadings (6, 8, 10, 12, and 15 wt.%). The objective of this work is to explore the pore confinement effect of FDU-12 mesochannels on the MoS2 morphology with various metal loadings. It is found that, as increasing MoO3 loadings from 6 to 15 wt.%, the MoS2 nanocrystallites transform from monolayer to multilayer and the morphology changes from straight layered to curved and then to ring-like and finally to spherical-like morphology due to the restriction of cage-like pore channels of FDU-12 support. The HDS results show that the catalytic activity increases first and then decreases with the best HDS performance at the MoO3 loading of 10 wt.%. In addition, we compared the HDS activity of Mo catalyst supported on FDU-12 with that on the commercial γ-Al2O3 and SBA-15; the result exhibits that FDU-12 is superior to the other two supports due to its large pore size and ordered three-dimensional open pore channels