Mathematical Modeling of the Influence of Hydrothermal Processes in the Water Reservoir

In this paper presents the mathematical model of hydrothermal processes in thermal power plant with different wind direction scenarios in the water reservoir, which is solved by the Navier - Stokes and temperature equations for an incompressible fluid in a stratified medium. Numerical algorithm based on the method of splitting by physical parameters. Three dimensional Poisson equation is solved with Fourier method by combination of tridiagonal matrix method (Thomas algorithm).

Biosorption of Heavy Metals Contaminating the Wonderfonteinspruit Catchment Area using Desmodesmus sp.

A vast array of biological materials, especially algae have received increasing attention for heavy metal removal. Algae have been proven to be cheaper, more effective for the removal of metallic elements in aqueous solutions. A fresh water algal strain was isolated from Zoo Lake, Johannesburg, South Africa and identified as Desmodesmus sp. This paper investigates the efficacy of Desmodesmus sp.in removing heavy metals contaminating the Wonderfonteinspruit Catchment Area (WCA) water bodies. The biosorption data fitted the pseudo-second order and Langmuir isotherm models. The Langmuir maximum uptakes gave the sequence: Mn2+>Ni2+>Fe2+. The best results for kinetic study was obtained in concentration 120 ppm for Fe3+ and Mn2+, whilst for Ni2+ was at 20 ppm, which is about the same concentrations found in contaminated water in the WCA (Fe3+115 ppm, Mn2+ 121 ppm and Ni2+ 26.5 ppm).

Influence of Different Mixing Ratios of Adhesives for Wood Bondline Quality

The research study was based on an evaluation of the ability of glued test samples to pass the criterion of sufficient bondline adhesion under the exposure conditions defined in EN 302- 1. Additionally, an infrared spectroscopic analysis of the evaluated adhesives (phenol-resorcinol-formaldehyde PRF and melamine-ureaformaldehyde MUF) with different mix ratios was carried out to evaluate the possible effects of a faulty technological process.

A Context-Aware based Authorization System for Pervasive Grid Computing

This paper describes the authorization system architecture for Pervasive Grid environment. It discusses the characteristics of classical authorization system and requirements of the authorization system in pervasive grid environment as well. Based on our analysis of current systems and taking into account the main requirements of such pervasive environment, we propose new authorization system architecture as an extension of the existing grid authorization mechanisms. This architecture not only supports user attributes but also context attributes which act as a key concept for context-awareness thought. The architecture allows authorization of users dynamically when there are changes in the pervasive grid environment. For this, we opt for hybrid authorization method that integrates push and pull mechanisms to combine the existing grid authorization attributes with dynamic context assertions. We will investigate the proposed architecture using a real testing environment that includes heterogeneous pervasive grid infrastructures mapped over multiple virtual organizations. Various scenarios are described in the last section of the article to strengthen the proposed mechanism with different facilities for the authorization procedure.

Rigid and Non-rigid Registration of Binary Objects using the Weighted Ratio Image

This paper presents the application of a signal intensity independent similarity criterion for rigid and non-rigid body registration of binary objects. The criterion is defined as the weighted ratio image of two images. The ratio is computed on a voxel per voxel basis and weighting is performed by setting the raios between signal and background voxels to a standard high value. The mean squared value of the weighted ratio is computed over the union of the signal areas of the two images and it is minimized using the Chebyshev polynomial approximation.

Implementation of Security Algorithms for u-Health Monitoring System

Data security in u-Health system can be an important issue because wireless network is vulnerable to hacking. However, it is not easy to implement a proper security algorithm in an embedded u-health monitoring because of hardware constraints such as low performance, power consumption and limited memory size and etc. To secure data that contain personal and biosignal information, we implemented several security algorithms such as Blowfish, data encryption standard (DES), advanced encryption standard (AES) and Rivest Cipher 4 (RC4) for our u-Health monitoring system and the results were successful. Under the same experimental conditions, we compared these algorithms. RC4 had the fastest execution time. Memory usage was the most efficient for DES. However, considering performance and safety capability, however, we concluded that AES was the most appropriate algorithm for a personal u-Health monitoring system.

Numerical Simulations of Cross-Flow around Four Square Cylinders in an In-Line Rectangular Configuration

A two-dimensional numerical simulation of crossflow around four cylinders in an in-line rectangular configuration is studied by using the lattice Boltzmann method (LBM). Special attention is paid to the effect of the spacing between the cylinders. The Reynolds number ( Re ) is chosen to be e 100 R = and the spacing ratio L / D is set at 0.5, 1.5, 2.5, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 and 10.0. Results show that, as in the case of four cylinders in an inline rectangular configuration , flow fields show four different features depending on the spacing (single square cylinder, stable shielding flow, wiggling shielding flow and a vortex shedding flow) are observed in this study. The effects of spacing ratio on physical quantities such as mean drag coefficient, Strouhal number and rootmean- square value of the drag and lift coefficients are also presented. There is more than one shedding frequency at small spacing ratios. The mean drag coefficients for downstream cylinders are less than that of the single cylinder for all spacing ratios. The present results using the LBM are compared with some existing experimental data and numerical studies. The comparison shows that the LBM can capture the characteristics of the bluff body flow reasonably well and is a good tool for bluff body flow studies.

Ground Heat Exchanger Modeling Developed for Energy Flows of an Incompressible Fluid

Ground-source heat pumps achieve higher efficiencies than conventional air-source heat pumps because they exchange heat with the ground that is cooler in summer and hotter in winter than the air environment. Earth heat exchangers are essential parts of the ground-source heat pumps and the accurate prediction of their performance is of fundamental importance. This paper presents the development and validation of a numerical model through an incompressible fluid flow, for the simulation of energy and temperature changes in and around a U-tube borehole heat exchanger. The FlexPDE software is used to solve the resulting simultaneous equations that model the heat exchanger. The validated model (through a comparison with experimental data) is then used to extract conclusions on how various parameters like the U-tube diameter, the variation of the ground thermal conductivity and specific heat and the borehole filling material affect the temperature of the fluid.

Scheduling a Flexible Flow Shops Problem using DEA

This paper considers a scheduling problem in flexible flow shops environment with the aim of minimizing two important criteria including makespan and cumulative tardiness of jobs. Since the proposed problem is known as an Np-hard problem in literature, we have to develop a meta-heuristic to solve it. We considered general structure of Genetic Algorithm (GA) and developed a new version of that based on Data Envelopment Analysis (DEA). Two objective functions assumed as two different inputs for each Decision Making Unit (DMU). In this paper we focused on efficiency score of DMUs and efficient frontier concept in DEA technique. After introducing the method we defined two different scenarios with considering two types of mutation operator. Also we provided an experimental design with some computational results to show the performance of algorithm. The results show that the algorithm implements in a reasonable time.

A Multi-Objective Model for Supply Chain Network Design under Stochastic Demand

In this article, the design of a Supply Chain Network (SCN) consisting of several suppliers, production plants, distribution centers and retailers, is considered. Demands of retailers are considered stochastic parameters, so we generate amounts of data via simulation to extract a few demand scenarios. Then a mixed integer two-stage programming model is developed to optimize simultaneously two objectives: (1) minimization the fixed and variable cost, (2) maximization the service level. A weighting method is utilized to solve this two objective problem and a numerical example is made to show the performance of the model.

Langmuir–Blodgett Films of Polyaniline for Efficient Detection of Uric Acid

Langmuir–Blodgett (LB) films of polyaniline (PANI) grown onto ITO coated glass substrates were utilized for the fabrication of Uric acid biosensor for efficient detection of uric acid by immobilizing Uricase via EDC–NHS coupling. The modified electrodes were characterized by atomic force microscopy (AFM). The response characteristics after immobilization of uricase were studied using cyclic voltammetry and electrochemical impedance spectroscopy techniques. The uricase/PANI/ITO/glass bioelectrode studied by CV and EIS techniques revealed detection of uric acid in a wide range of 0.05 mM to 1.0 mM, covering the physiological range in blood. A low Michaelis–Menten constant (Km) of 0.21 mM indicates the higher affinity of immobilized Uricase towards its analyte (uric acid). The fabricated uric acid biosensor based on PANI LB films exhibits excellent sensitivity of 0.21 mA/mM with a response time of 4 s, good reproducibility, long shelf life (8 weeks) and high selectivity.

A Universal Approach for the Intuitive Control of Mobile Robots using an AR/VR-based Interface

Mobile robots are used in a large field of scenarios, like exploring contaminated areas, repairing oil rigs under water, finding survivors in collapsed buildings, etc. Currently, there is no unified intuitive user interface (UI) to control such complex mobile robots. As a consequence, some scenarios are done without the exploitation of experience and intuition of human teleoperators. A novel framework has been developed to embed a flexible and modular UI into a complete 3-D virtual reality simulation system. This new approach wants to access maximum benefits of human operators. Sensor information received from the robot is prepared for an intuitive visualization. Virtual reality metaphors support the operator in his decisions. These metaphors are integrated into a real time stereo video stream. This approach is not restricted to any specific type of mobile robot and allows for the operation of different robot types with a consistent concept and user interface.

Flame Stability and Structure of Liquefied Petroleum Gas-Fired Inverse Diffusion Flame with Hydrogen Enrichment

The present project was conducted with the circumferential-fuel-jets inverse diffusion flame (CIDF) burner burning liquefied petroleum gas (LPG) enriched with 50% of hydrogen fuel (H2). The range of stable operation of the CIDF burner in terms of Reynolds number (from laminar to turbulent flow regions), equivalence ratio and fuel jet velocity of LPG of the 50% H2-LPG mixed fuel was identified. Experiments were also carried out to investigate the flame structures of the LPG flame and LPG enriched H2 flame. Experimental results obtained from these two flames were compared to fully explore the influence of hydrogen addition on flame stability. Flame heights obtained by burning these two kinds of fuels at various equivalence ratios were compared and correlated with the Global Momentum Ratio (GMR).

Chemical Compositions and Physico-Chemical Properties of Malted Sorghum Flour and Characteristics of Gluten Free Bread

This study investigated the effect of germination on chemical compositions, physio-chemical properties of malted (germinated) red sorghum flours and evaluated characteristics of gluten free breads from sorghum flour. Results showed that germinated sorghum flour had higher amylase activity, swelling power and solubility at 95°C, but lower in the peak, break down, final and set back viscosities than ungerminated sample (p≤0.05). Five gluten free breads made from sorghum flour blends, with different ratios of ungerminated and germinated sorghum flour, were compared for the physical properties with those made from wheat flour. Crumb hardness, cohesiveness, gumminess and chewiness of sorghum breads were found significantly higher than those of wheat bread. With increasing of ungerminated flour proportion, the bread hardness increased while the cohesiveness declined. Sorghum breads appeared red to human eyes with a*values of 10.41-15.77.Their crust and crumb colors differed significantly from those of wheat bread.

Treatment or Re-Victimizing the Victims

Severe symptoms, such as dissociation, depersonalization, self-mutilation, suicidal ideations and gestures, are the main reasons for a person to be diagnosed with Borderline Personality Disorder (BPD) and admitted to an inpatient Psychiatric Hospital. However, these symptoms are also indicators of a severe traumatic history as indicated by the extensive research on the topic. Unfortunately patients with such clinical presentation often are treated repeatedly only for their symptomatic behavior, while the main cause for their suffering, the trauma itself, is usually left unaddressed therapeutically. All of the highly structured, replicable, and manualized treatments lack the recognition of the uniqueness of the person and fail to respect his/her rights to experience and react in an idiosyncratic manner. Thus the communicative and adaptive meaning of such symptomatic behavior is missed. Only its pathological side is recognized and subjected to correction and stigmatization, and the message that the person is damaged goods that needs fixing is conveyed once again. However, this time the message would be even more convincing for the victim, because it is sent by mental health providers, who have the credibility to make such a judgment. The result is a revolving door of very expensive hospitalizations for only a temporary and patchy fix. In this way the patients, once victims of abuse and hardship are left invalidated and thus their re-victimization is perpetuated in their search for understanding and help. Keywordsborderline personality disorder (BPD), complex PTSD, integrative treatment of trauma, re-victimization of trauma victims.

ClassMATE: Enabling Ambient Intelligence in the Classroom

Ambient Intelligence (AmI) environments bring significant potential to exploit sophisticated computer technology in everyday life. In particular, the educational domain could be significantly enhanced through AmI, as personalized and adapted learning could be transformed from paper concepts and prototypes to real-life scenarios. In this paper, an integrated framework is presented, named ClassMATE, supporting ubiquitous computing and communication in a school classroom. The main objective of ClassMATE is to enable pervasive interaction and context aware education in the technologically augmented classroom of the future.

Effects of Catalyst Tubes Characteristics on a Steam Reforming Process in Ammonia

The tubes in an Ammonia primary reformer furnace operate close to the limits of materials technology in terms of the stress induced as a result of very high temperatures, combined with large differential pressures across the tube wall. Operation at tube wall temperatures significantly above design can result in a rapid increase in the number of tube failures, since tube life is very sensitive to the absolute operating temperature of the tube. Clearly it is important to measure tube wall temperatures accurately in order to prevent premature tube failure by overheating.. In the present study, the catalyst tubes in an Ammonia primary reformer has been modeled taking into consideration heat, mass and momentum transfer as well as reformer characteristics.. The investigations concern the effects of tube characteristics and superficial tube wall temperatures on of the percentage of heat flux, unconverted methane and production of Hydrogen for various values of steam to carbon ratios. The results show the impact of catalyst tubes length and diameters on the performance of operating parameters in ammonia primary reformers.

The Use of Acid-Aluminium Tolerant Bradyrhizobium japonicum Formula for

Land with low pH soil spread widely in Indonesia can be used for soybean (Glycine max) cultivation, however the production is low. The use of acid tolerant soybean and acidaluminium tolerant nitrogen-fixing bacteria formula was an alternative way to increase soybean productivity on acid soils. Bradyrhizobium japonicum is one of the nitrogen fixing bacteria which can symbiose with soybean plants through root nodule formation. Most of the nitrogen source required by soybean plants can be provided by this symbiosis. This research was conducted to study the influence of acid-aluminium tolerant B. japonicum strain BJ 11 formula using peat as carrier on growth of Tanggamus and Anjasmoro cultivar soybean planted on acid soil fields (pH 5.0- 5.5). The results showed that the inoculant was able to increase the growth and production of soybean which were grown on fields acid soil at Sukadana (Lampung) and Tanah Laut (South Kalimantan), Indonesia.

Laser Transmission through Vegetative Material

The dynamic speckle or biospeckle is an interference phenomenon generated at the reflection of a coherent light by an active surface or even by a particulate or living body surface. The above mentioned phenomenon gave scientific support to a method named biospeckle which has been employed to study seed viability, biological activity, tissue senescence, tissue water content, fruit bruising, etc. Since the above mentioned method is not invasive and yields numerical values, it can be considered for possible automation associated to several processes, including selection and sorting. Based on these preliminary considerations, this research work proposed to study the interaction of a laser beam with vegetative samples by measuring the incident light intensity and the transmitted light beam intensity at several vegetative slabs of varying thickness. Tests were carried on fifteen slices of apple tissue divided into three thickness groups, i.e., 4 mm, 5 mm, 18 mm and 22 mm. A diode laser beam of 10mW and 632 nm wavelength and a Samsung digital camera were employed to carry the tests. Outgoing images were analyzed by comparing the gray gradient of a fixed image column of each image to obtain a laser penetration scale into the tissue, according to the slice thickness.

Fuzzy Wavelet Packet based Feature Extraction Method for Multifunction Myoelectric Control

The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.