Automated Ranking of Hints

The importance of hints in an intelligent tutoring system is well understood. The problems however related to their delivering are quite a few. In this paper we propose delivering of hints to be based on considering their usefulness. By this we mean that a hint is regarded as useful to a student if the student has succeeded to solve a problem after the hint was suggested to her/him. Methods from the theory of partial orderings are further applied facilitating an automated process of offering individualized advises on how to proceed in order to solve a particular problem.

An Anatomically-Based Model of the Nerves in the Human Foot

Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.

Real-Time Image Analysis of Capsule Endoscopy for Bleeding Discrimination in Embedded System Platform

Image processing for capsule endoscopy requires large memory and it takes hours for diagnosis since operation time is normally more than 8 hours. A real-time analysis algorithm of capsule images can be clinically very useful. It can differentiate abnormal tissue from health structure and provide with correlation information among the images. Bleeding is our interest in this regard and we propose a method of detecting frames with potential bleeding in real-time. Our detection algorithm is based on statistical analysis and the shapes of bleeding spots. We tested our algorithm with 30 cases of capsule endoscopy in the digestive track. Results were excellent where a sensitivity of 99% and a specificity of 97% were achieved in detecting the image frames with bleeding spots.

Combining Variable Ordering Heuristics for Improving Search Algorithms Performance

Variable ordering heuristics are used in constraint satisfaction algorithms. Different characteristics of various variable ordering heuristics are complementary. Therefore we have tried to get the advantages of all heuristics to improve search algorithms performance for solving constraint satisfaction problems. This paper considers combinations based on products and quotients, and then a newer form of combination based on weighted sums of ratings from a set of base heuristics, some of which result in definite improvements in performance.

Delay-Dependent Stability Analysis for Neutral Type Neural Networks with Uncertain Parameters and Time-Varying Delay

In this paper, delay-dependent stability analysis for neutral type neural networks with uncertain paramters and time-varying delay is studied. By constructing new Lyapunov-Krasovskii functional and dividing the delay interval into multiple segments, a novel sufficient condition is established to guarantee the globally asymptotically stability of the considered system. Finally, a numerical example is provided to illustrate the usefulness of the proposed main results.

Generalized Morphological 3D Shape Decomposition Grayscale Interframe Interpolation Method

One of the main image representations in Mathematical Morphology is the 3D Shape Decomposition Representation, useful for Image Compression and Representation,and Pattern Recognition. The 3D Morphological Shape Decomposition representation can be generalized a number of times,to extend the scope of its algebraic characteristics as much as possible. With these generalizations, the Morphological Shape Decomposition 's role to serve as an efficient image decomposition tool is extended to grayscale images.This work follows the above line, and further develops it. Anew evolutionary branch is added to the 3D Morphological Shape Decomposition's development, by the introduction of a 3D Multi Structuring Element Morphological Shape Decomposition, which permits 3D Morphological Shape Decomposition of 3D binary images (grayscale images) into "multiparameter" families of elements. At the beginning, 3D Morphological Shape Decomposition representations are based only on "1 parameter" families of elements for image decomposition.This paper addresses the gray scale inter frame interpolation by means of mathematical morphology. The new interframe interpolation method is based on generalized morphological 3D Shape Decomposition. This article will present the theoretical background of the morphological interframe interpolation, deduce the new representation and show some application examples.Computer simulations could illustrate results.

High Strain Rate Characteristics of the Advanced Blast Energy Absorbers

The main aim of the presented experiments is to improve behaviour of sandwich structures under dynamic loading, such as crash or explosion. Several cellular materials are widely used as core of the sandwich structures and their properties influence the response of the entire element under impact load. To optimize their performance requires the characterisation of the core material behaviour at high strain rates and identification of the underlying mechanism. This work presents the study of high strain-rate characteristics of a specific porous lightweight blast energy absorbing foam using a Split Hopkinson Pressure Bar (SHPB) technique adapted to perform tests on low strength materials. Two different velocities, 15 and 30 m.s-1 were used to determine the strain sensitivity of the material. Foams were designed using two types of porous lightweight spherical raw materials with diameters of 30- 100 *m, combined with polymer matrix. Cylindrical specimens with diameter of 15 mm and length of 7 mm were prepared and loaded using a Split Hopkinson Pressure Bar apparatus to assess the relation between the composition of the material and its shock wave attenuation capacity.

Skin Detection using Histogram depend on the Mean Shift Algorithm

In this paper, we were introduces a skin detection method using a histogram approximation based on the mean shift algorithm. The proposed method applies the mean shift procedure to a histogram of a skin map of the input image, generated by comparison with standard skin colors in the CbCr color space, and divides the background from the skin region by selecting the maximum value according to brightness level. The proposed method detects the skin region using the mean shift procedure to determine a maximum value that becomes the dividing point, rather than using a manually selected threshold value, as in existing techniques. Even when skin color is contaminated by illumination, the procedure can accurately segment the skin region and the background region. The proposed method may be useful in detecting facial regions as a pretreatment for face recognition in various types of illumination.

The Calculation of Electromagnetic Fields (EMF) in Substations of Shopping Centers

In nature, electromagnetic fields always appear like atmosphere static electric field, the earth's static magnetic field and the wide-rang frequency electromagnetic field caused by lightening. However, besides natural electromagnetic fields (EMF), today human beings are mostly exposed to artificial electromagnetic fields due to technology progress and outspread use of electrical devices. To evaluate nuisance of EMF, it is necessary to know field intensity for every frequency which appears and compare it with allowed values. Low frequency EMF-s around transmission and distribution lines are time-varying quasi-static electromagnetic fields which have conservative component of low frequency electrical field caused by charges and eddy component of low frequency magnetic field caused by currents. Displacement current or field delay are negligible, so energy flow in quasi-static EMF involves diffusion, analog like heat transfer. Electrical and magnetic field can be analyzed separately. This paper analysis the numerical calculations in ELF-400 software of EMF in distribution substation in shopping center. Analyzing the results it is possible to specify locations exposed to the fields and give useful suggestion to eliminate electromagnetic effect or reduce it on acceptable level within the non-ionizing radiation norms and norms of protection from EMF.

Benchmarking: Performance on ALPS and Formosa Clusters

This paper presents the benchmarking results and performance evaluation of differentclustersbuilt atthe National Center for High-Performance Computingin Taiwan. Performance of processor, memory subsystem andinterconnect is a critical factor in the overall performance of high performance computing platforms. The evaluation compares different system architecture and software platforms. Most supercomputer used HPL to benchmark their system performance, in accordance with the requirement of the TOP500 List. In this paper we consider system memory access factors that affect benchmark performance, such as processor and memory performance.We hope these works will provide useful information for future development and construct cluster system.

Carbon Isotope Discrimination, A Tool for Screening of Salinity Tolerance of Genotypes

This study carried out in order to investigate the effects of salinity on carbon isotope discrimination (Δ) of shoots and roots of four sugar beet cultivars (cv) including Madison (British origin) and three Iranian culivars (7233-P12, 7233-P21 and 7233-P29). Plants were grown in sand culture medium in greenhouse conditions. Plants irrigated with saline water (tap water as control, 50 mM, 150 mM, 250 mM and 350 mM of NaCl + CaCl2 in 5 to 1 molar ratio) from 4 leaves stage for 16 weeks. Carbon isotope discrimination significantly decreased with increasing salinity. Significant differences of Δ between shoot and root were observed in all cvs and all levels of salinity. Madison cv showed lower Δ in shoot and root than other three cvs at all levels of salinity expect control, but cv 7233-P29 had significantly higher Δ values at saline conditions of 150 mM and above. Therefore, Δ might be applicable, as a useful tool, for study of salinity tolerance of sugar beet genotypes.

Application of Generalized NAUT B-Spline Curveon Circular Domain to Generate Circle Involute

In the present paper, we use generalized B-Spline curve in trigonometric form on circular domain, to capture the transcendental nature of circle involute curve and uncertainty characteristic of design. The required involute curve get generated within the given tolerance limit and is useful in gear design.

Impulse Response Shortening for Discrete Multitone Transceivers using Convex Optimization Approach

In this paper we propose a new criterion for solving the problem of channel shortening in multi-carrier systems. In a discrete multitone receiver, a time-domain equalizer (TEQ) reduces intersymbol interference (ISI) by shortening the effective duration of the channel impulse response. Minimum mean square error (MMSE) method for TEQ does not give satisfactory results. In [1] a new criterion for partially equalizing severe ISI channels to reduce the cyclic prefix overhead of the discrete multitone transceiver (DMT), assuming a fixed transmission bandwidth, is introduced. Due to specific constrained (unit morm constraint on the target impulse response (TIR)) in their method, the freedom to choose optimum vector (TIR) is reduced. Better results can be obtained by avoiding the unit norm constraint on the target impulse response (TIR). In this paper we change the cost function proposed in [1] to the cost function of determining the maximum of a determinant subject to linear matrix inequality (LMI) and quadratic constraint and solve the resulting optimization problem. Usefulness of the proposed method is shown with the help of simulations.

Artificial Neural Network based Modeling of Evaporation Losses in Reservoirs

An Artificial Neural Network based modeling technique has been used to study the influence of different combinations of meteorological parameters on evaporation from a reservoir. The data set used is taken from an earlier reported study. Several input combination were tried so as to find out the importance of different input parameters in predicting the evaporation. The prediction accuracy of Artificial Neural Network has also been compared with the accuracy of linear regression for predicting evaporation. The comparison demonstrated superior performance of Artificial Neural Network over linear regression approach. The findings of the study also revealed the requirement of all input parameters considered together, instead of individual parameters taken one at a time as reported in earlier studies, in predicting the evaporation. The highest correlation coefficient (0.960) along with lowest root mean square error (0.865) was obtained with the input combination of air temperature, wind speed, sunshine hours and mean relative humidity. A graph between the actual and predicted values of evaporation suggests that most of the values lie within a scatter of ±15% with all input parameters. The findings of this study suggest the usefulness of ANN technique in predicting the evaporation losses from reservoirs.

Identification of Optimum Parameters of Deep Drawing of a Cylindrical Workpiece using Neural Network and Genetic Algorithm

Intelligent deep-drawing is an instrumental research field in sheet metal forming. A set of 28 different experimental data have been employed in this paper, investigating the roles of die radius, punch radius, friction coefficients and drawing ratios for axisymmetric workpieces deep drawing. This paper focuses an evolutionary neural network, specifically, error back propagation in collaboration with genetic algorithm. The neural network encompasses a number of different functional nodes defined through the established principles. The input parameters, i.e., punch radii, die radii, friction coefficients and drawing ratios are set to the network; thereafter, the material outputs at two critical points are accurately calculated. The output of the network is used to establish the best parameters leading to the most uniform thickness in the product via the genetic algorithm. This research achieved satisfactory results based on demonstration of neural networks.

Theoretical Considerations for Software Component Metrics

We have defined two suites of metrics, which cover static and dynamic aspects of component assembly. The static metrics measure complexity and criticality of component assembly, wherein complexity is measured using Component Packing Density and Component Interaction Density metrics. Further, four criticality conditions namely, Link, Bridge, Inheritance and Size criticalities have been identified and quantified. The complexity and criticality metrics are combined to form a Triangular Metric, which can be used to classify the type and nature of applications. Dynamic metrics are collected during the runtime of a complete application. Dynamic metrics are useful to identify super-component and to evaluate the degree of utilisation of various components. In this paper both static and dynamic metrics are evaluated using Weyuker-s set of properties. The result shows that the metrics provide a valid means to measure issues in component assembly. We relate our metrics suite with McCall-s Quality Model and illustrate their impact on product quality and to the management of component-based product development.

Review of a Real-Time Infectious Waste Management System Using QR Code

In the management of industrial waste, conversion from the use of paper invoices to electronic forms is currently under way in developed countries. Difficulties in such computerization include the lack of synchronization between the actual goods and the corresponding data managed by the server. Consequently, a system which utilizes the incorporation of a QR code in connection with the waste material has been developed. The code is read at each stage, from discharge until disposal, and progress at each stage can be easily reported. This system can be linked with Japanese public digital authentication service of waste, taking advantage of its good points, and can be used to submit reports to the regulatory authorities. Its usefulness was confirmed by a verification test, and put into actual practice.

From Experiments to Numerical Modeling: A Tool for Teaching Heat Transfer in Mechanical Engineering

In this work the numerical simulation of transient heat transfer in a cylindrical probe is done. An experiment was conducted introducing a steel cylinder in a heating chamber and registering its surface temperature along the time during one hour. In parallel, a mathematical model was solved for one dimension transient heat transfer in cylindrical coordinates, considering the boundary conditions of the test. The model was solved using finite difference method, because the thermal conductivity in the cylindrical steel bar and the convection heat transfer coefficient used in the model are considered temperature dependant functions, and both conditions prevent the use of the analytical solution. The comparison between theoretical and experimental results showed the average deviation is below 2%. It was concluded that numerical methods are useful in order to solve engineering complex problems. For constant k and h, the experimental methodology used here can be used as a tool for teaching heat transfer in mechanical engineering, using mathematical simplified models with analytical solutions.

Design and Control Strategy of Diffused Air Aeration System

During the past decade, pond aeration systems have been developed which will sustain large quantities of fish and invertebrate biomass. Dissolved Oxygen (DO) is considered to be among the most important water quality parameters in fish culture. Fishponds in aquaculture farms are usually located in remote areas where grid lines are at far distance. Aeration of ponds is required to prevent mortality and to intensify production, especially when feeding is practical, and in warm regions. To increase pond production it is necessary to control dissolved oxygen. Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. This paper presents a new design of diffused aeration system using fuel cell as a power source. Also fuzzy logic control Technique (FLC) is used for controlling the speed of air flow rate from the blower to air piping connected to the pond by adjusting blower speed. MATLAB SIMULINK results show high performance of fuzzy logic control (FLC).

The Wijma Delivery Expectancy/Experience Questionnaire (W-DEQ) with Turkish Sample: Confirmatory and Exploratory Factor Analysis

The propose of this study is to investigate the factor structures of the W-DEQ, originally developed on UK and Swedish women, were confirmed in Turkish samples, and to obtain a new modified factor structure appropriate to Turkish culture. Statistical analyses of the data obtained were performed using SPSS© for Windows version 13.0 and the SAS statistical software Version 9.1. Both confirmatory and exploratory factor analysis of W-DEQ were performed in the study. Factor analysis yielded four factors related to hope, fear, lack of positive anticipation and riskiness. The alpha estimates of the total W-DEQ score were somewhat higher, being 0.92 for the parous and 0.90 for the nulliparous sample. These are well above the accepted limit of 0.70 and indicate excellent levels of internal reliability, thus showing that the questions were appropriate to the Turkish culture and useful scale for the evaluation of fear of childbirth in Turkish pregnants.