Learners’ navigation behavior identification based on trace analysis

Identifying learners’ behaviors and learning preferences or styles in a Web-based learning environment is crucial for organizing the tracking and specifying how and when assistance is needed. Moreover, it helps online course designers to adapt the learning material in a way that guarantees individualized learning, and helps learners to acquire meta-cognitive knowledge. The goal of this research is to identify learners’ behaviors and learning styles automatically during training sessions, based on trace analysis. In this paper, we focus on the identification of learners’ behaviors through our system: Indicators for the Deduction of Learning Styles. We shall first present our trace analysis approach. Then, we shall propose a ‘navigation type’ indicator to analyze learners’ behaviors and we shall define a method for calculating it. To this end, we shall build a decision tree based on semantic assumptions and tests. To validate our approach, and improve the proposed calculation method, we shall present and discuss the results of two experiments that we conducted.     

Resource Allocation for Concrete Batch Plant Operation: Case Study

A concrete batch plant is an important element in any concrete construction process, whether it is working as a central mixing plant onsite or is offsite supplying ready mixed concrete to a project. This study tackles the problem of optimizing plant production to maximize profit and, if possible, revenue. A linear programming model has been designed to optimize the plant operation. The maximum production rate for each type of concrete can be obtained by solving the model under the given constraints. A sensitivity analysis is conducted to provide management with a flexible range of prices per cubic yard (cubic meter) and material storage limits. In addition, a model has been designed to determine the optimal number of transit mixers based upon the required quantity of concrete. A chart has been developed to determine the quantities of concrete ingredient materials required daily to organize the available storage space and to plan their delivery.     

Complex fuzzy c-means algorithm

In this paper a new clustering algorithm is presented: A complex-based Fuzzy c-means (CFCM) algorithm. While the Fuzzy c-means uses a real vector as a prototype characterizing a cluster, the CFCM??s prototype is generalized to be a complex vector (complex center). CFCM uses a new real distance measure which is derived from a complex one. CFCM??s formulas for the fuzzy membership are derived. These formulas are extended to derive the complex Gustafson?CKessel algorithm (CGK). Cluster validity measures are used to assess the goodness of the partitions obtained by the complex centers compared those obtained by the real centers. The validity measures used in this paper are the Partition Coefficient, Classification Entropy, Partition Index, Separation Index, Xie and Beni??s Index, Dunn??s Index. It is shown in this paper that the CFCM give better partitions of the data than the FCM and the GK algorithms. It is also shown that the CGK algorithm outperforms the CFCM but at the expense of much higher computational complexity.     

Interval-based global optimization in engineering using model reformulation and constraint propagation

This paper deals with the preliminary design problem when the product is modeled as an analytic model. The analytic models based method aims to use mathematical equations to address both multi-physic and economic characteristics of a product. The proposed approach is to convert the preliminary design problem into a global constrained optimization problem. The objective is to develop powerful optimization methods enough to handle complex analytical models. We propose to adapt an approach to solve this problem based on interval analysis, constraint propagation and model reformulation. In order to understand the optimization algorithm used for engineering design problems, some basic definitions and properties of interval analysis are introduced. Then, the basic optimization algorithms for both unconstrained and constrained problems are introduced and illustrated. The next section introduces the reformulation technique as main accelerating device. An application of the reformulation device and its global optimization algorithm on the optimal design of electrical actuators is presented.     

Enhanced confined light transmission by single subwavelength apertures in metallic films

The diffraction of light that emerges from a metallic circular aperture is studied. Near- and far-field results are presented. Spectral angular transmitted intensities are performed versus the incident wavelength for four kinds of aperture. It is shown that, for a definite configuration, a large enhancement of transmission--compared with the basic case of a single hole--occurs combined with a spectacular angular confinement of light. Such effects are, for example, of great interest in optical near-field microscopy for which the probe is a nanosource.     

Photographic study of pool boiling CHF from a downward-facing convex surface

Heat transfer measurements and photographic studies are performed to capture the detailed evolution of the liquid–vapor interface near critical heat flux (CHF) for a 90-degree downward-facing convex surface. The test surface, with a width of 3.2 mm and a 102.6-mm radius, consists of a series of nine heaters that dissipate equal power. Instrumentation within each heater facilitates localized heat flux and temperature measurements along the convex surface, and transparent front and back windows enable optical access to a fairly two-dimensional liquid–vapor interface. Near CHF, vapor behavior along the convex surface is cyclical, repeatedly forming a stratified vapor layer at the bottom of the convex surface, which stretches as more vapor is generated, and then flows upwards along from the surface. Subsequently, heaters at the bottom of the convex surface, followed by the other heaters, are wetted with liquid before the nucleation/coalescence/stratification/release process is repeated. This study proves that despite the pronounced thickening of the vapor layer as it propagates upwards along the convex surface, CHF always commences on the bottom of the surface.     

Variable window adaptive Kernel Principal Component Analysis for nonlinear nonstationary process monitoring

On-line control of nonlinear nonstationary processes using multivariate statistical methods has recently prompt a lot of interest due to its industrial practical importance. Indeed basic process control methods do not allow monitoring of such processes. For this purpose this study proposes a variable window real-time monitoring system based on a fast block adaptive Kernel Principal Component Analysis scheme. While previous adaptive KPCA models allow only handling of one observation at a time, in this study we propose a way to fast update or downdate the KPCA model when a block of data is provided and not only one observation. Using a variable window size procedure to determine the model size and adaptive chart parameters, this model is applied to monitor two simulated benchmark processes. A comparison of performances of the adopted control strategy with various Principal Component Analysis (PCA) control models shows that the derived strategy is robust and yields better detection abilities of disturbances.     

Quantification of metallothionein-like proteins in the mussel Mytilus galloprovincialis using RP-HPLC fluorescence detection

A HPLC-fluorescence method, using the fluorophore SBD-F (ammonium-7-fluorobenz-2-oxa-1,3-diazole-4-sulfonate), was adapted for the quantification of metallothioneins and their isoforms from the Moroccan mussel Mytilus galloprovincialis. The method was first optimized using a rabbit liver metallothionein. The effects of EDTA, tris(2-carboxyethyl)phosphine, and SBD-F on the labeling efficiency were studied. The optimized method was then applied to evaluate the amount of metallothionein in the mussels either exposed to cadmium in the laboratory or collected from the Casablanca coast, Morocco. The concentrations of metallothioneins measured in the field samples describe the degree of contamination of the sites and are reflected by distinct isoform patterns.