71,579 research outputs found

    Effect of PAO-based Îł-Fe2O3 and surfactant concentration on viscosity characteristic

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    This is a preliminary study on the viscosity characteristics of polyalphaolefin (PAO)- based Îł-Fe2O3 under zero magnetic fields. By varying the concentration of magnetic nanoparticles (MNPs), PAO-based Îł-Fe2O3 with different concentrations were synthesized by co-precipitation method. The effect of this factor on the viscosity characteristic of Îł-Fe2O3 (< 30 nm) was investigated on the basic of a series of rheological measurement. The use of oleic acid (OA) as a coating agent and surfactant was also investigated by varying its concentration. The results show the concentration of MNPs and the amount of OA has obvious effect on viscosity characteristics of PAO-based Îł-Fe2O3. In the case of comparison between the concentrations of MNPs, higher concentration of MNPs increased the viscosity of the PAO-based Îł-Fe2O3 and exhibit nearly Newtonian behavior. The large amount of OA also exhibits the increment on viscosity characteristic of MNPs. The experimental data were compared with the Bingham and Casson model and the results revealed that the rheology of the polyalphaolefin (PAO)-based Îł-Fe2O3 fitted the Casson model better

    Goods and services tax (GST) on construction capital cost and housing property price

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    Good and Service Tax (GST) an indirect broad-based conswnpti.on tax. Following with the implementation of GST in Malaysia on 1st April 2015, it is suspected that the construction capital cost and housing property price will increase accordingly. This study is aim to review the GST effect associated on construction capital cost and it influences towards housing developer and housing property price. Additionally, this study highlights what was the developer point of view on the GST given to them and also the housing price further proposes initiatives to the housing developers. Argument of GST effect is useful for the public administrators so that to re-consider the rate of GST and also beneficial to the construction parties to account with the GST implementation. As conclusion, this study review that GST do give an impact towards the construction capital cost, housing developer and housing property price in terms of knock-on effect

    Goods and services tax (GST) on construction capital cost and housing property price

    Get PDF
    Good and Service Tax (GST) an indirect broad-based conswnpti.on tax. Following with the implementation of GST in Malaysia on 1st April 2015, it is suspected that the construction capital cost and housing property price will increase accordingly. This study is aim to review the GST effect associated on construction capital cost and it influences towards housing developer and housing property price. Additionally, this study highlights what was the developer point of view on the GST given to them and also the housing price further proposes initiatives to the housing developers. Argument of GST effect is useful for the public administrators so that to re-consider the rate of GST and also beneficial to the construction parties to account with the GST implementation. As conclusion, this study review that GST do give an impact towards the construction capital cost, housing developer and housing property price in terms of knock-on effect

    Applying MDL to Learning Best Model Granularity

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    The Minimum Description Length (MDL) principle is solidly based on a provably ideal method of inference using Kolmogorov complexity. We test how the theory behaves in practice on a general problem in model selection: that of learning the best model granularity. The performance of a model depends critically on the granularity, for example the choice of precision of the parameters. Too high precision generally involves modeling of accidental noise and too low precision may lead to confusion of models that should be distinguished. This precision is often determined ad hoc. In MDL the best model is the one that most compresses a two-part code of the data set: this embodies ``Occam's Razor.'' In two quite different experimental settings the theoretical value determined using MDL coincides with the best value found experimentally. In the first experiment the task is to recognize isolated handwritten characters in one subject's handwriting, irrespective of size and orientation. Based on a new modification of elastic matching, using multiple prototypes per character, the optimal prediction rate is predicted for the learned parameter (length of sampling interval) considered most likely by MDL, which is shown to coincide with the best value found experimentally. In the second experiment the task is to model a robot arm with two degrees of freedom using a three layer feed-forward neural network where we need to determine the number of nodes in the hidden layer giving best modeling performance. The optimal model (the one that extrapolizes best on unseen examples) is predicted for the number of nodes in the hidden layer considered most likely by MDL, which again is found to coincide with the best value found experimentally.Comment: LaTeX, 32 pages, 5 figures. Artificial Intelligence journal, To appea

    Automatic Structural Scene Digitalization

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    In this paper, we present an automatic system for the analysis and labeling of structural scenes, floor plan drawings in Computer-aided Design (CAD) format. The proposed system applies a fusion strategy to detect and recognize various components of CAD floor plans, such as walls, doors, windows and other ambiguous assets. Technically, a general rule-based filter parsing method is fist adopted to extract effective information from the original floor plan. Then, an image-processing based recovery method is employed to correct information extracted in the first step. Our proposed method is fully automatic and real-time. Such analysis system provides high accuracy and is also evaluated on a public website that, on average, archives more than ten thousands effective uses per day and reaches a relatively high satisfaction rate.Comment: paper submitted to PloS On

    The AAU Multimodal Annotation Toolboxes: Annotating Objects in Images and Videos

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    This tech report gives an introduction to two annotation toolboxes that enable the creation of pixel and polygon-based masks as well as bounding boxes around objects of interest. Both toolboxes support the annotation of sequential images in the RGB and thermal modalities. Each annotated object is assigned a classification tag, a unique ID, and one or more optional meta data tags. The toolboxes are written in C++ with the OpenCV and Qt libraries and are operated by using the visual interface and the extensive range of keyboard shortcuts. Pre-built binaries are available for Windows and MacOS and the tools can be built from source under Linux as well. So far, tens of thousands of frames have been annotated using the toolboxes.Comment: 6 pages, 10 figure

    Children, Humanoid Robots and Caregivers

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    This paper presents developmental learning on a humanoid robot from human-robot interactions. We consider in particular teaching humanoids as children during the child's Separation and Individuation developmental phase (Mahler, 1979). Cognitive development during this phase is characterized both by the child's dependence on her mother for learning while becoming awareness of her own individuality, and by self-exploration of her physical surroundings. We propose a learning framework for a humanoid robot inspired on such cognitive development
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