Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

A procedure is proposed for the determination of the residence time distribution (RTD) of curved tubes taking into account the non-ideal detection of the tracer. The procedure was applied to two holding tubes used for milk pasteurization in laboratory scale. Experimental data was obtained using an ionic tracer. The signal distortion caused by the detection system was considerable because of the short residence time. Four RTD models, namely axial dispersion, extended tanks in series, generalized convection and PER + CSTR association, were adjusted after convolution with the E-curve of the detection system. The generalized convection model provided the best fit because it could better represent the tail on the tracer concentration curve that is Caused by the laminar velocity profile and the recirculation regions. Adjusted model parameters were well cot-related with the now rate. (C) 2010 Elsevier Ltd. All rights reserved.

AN ASSESSMENT ON THE USE OF THE DEBYE-HUCKEL EQUATION FOR THE THERMODYNAMIC MODELING OF AQUEOUS SYSTEMS CONTAINING POLYMERS AND SALTS

In this work, a study on the role of the long-range term of excess Gibbs energy models in the modeling of aqueous systems containing polymers and salts is presented. Four different approaches on how to account for the presence of polymer in the long-range term were considered, and simulations were conducted considering aqueous solutions of three different salts. The analysis of water activity curves showed that, in all cases, a liquid-phase separation may be introduced by the sole presence of the polymer in the long-range term, regardless of how it is taken into account. The results lead to the conclusion that there is no single exact solution for this problem, and that any kind of approach may introduce inconsistencies.

Treatment of Aqueous Effluents Containing Phenol by the O(3), O(3)-UV, and O(3)-H(2)O(2) Processes: Experimental Study and Neural Network Modeling

In this work, the oxidation of the model pollutant phenol has been studied by means of the O(3), O(3)-UV, and O(3)-H(2)O(2) processes. Experiments were carried out in a fed-batch system to investigate the effects of initial dissolved organic carbon concentration, initial, ozone concentration in the gas phase, the presence or absence of UVC radiation, and initial hydrogen peroxide concentration. Experimental results were used in the modeling of the degradation processes by neural networks in order to simulate DOC-time profiles and evaluate the relative importance of process variables.

Integrated analysis of cooling water systems: Modeling and experimental validation

Cooling towers are widely used in many industrial and utility plants as a cooling medium, whose thermal performance is of vital importance. Despite the wide interest in cooling tower design, rating and its importance in energy conservation, there are few investigations concerning the integrated analysis of cooling systems. This work presents an approach for the systemic performance analysis of a cooling water system. The approach combines experimental design with mathematical modeling. An experimental investigation was carried out to characterize the mass transfer in the packing of the cooling tower as a function of the liquid and gas flow rates, whose results were within the range of the measurement accuracy. Then, an integrated model was developed that relies on the mass and heat transfer of the cooling tower, as well as on the hydraulic and thermal interactions with a heat exchanger network. The integrated model for the cooling water system was simulated and the temperature results agree with the experimental data of the real operation of the pilot plant. A case study illustrates the interaction in the system and the need for a systemic analysis of cooling water system. The proposed mathematical and experimental analysis should be useful for performance analysis of real-world cooling water systems. (C) 2009 Elsevier Ltd. All rights reserved.

Investigation of the residence time distribution in a plate heat exchanger with series and parallel arrangements using a non-ideal tracer detection technique

The objective was to study the flow pattern in a plate heat exchanger (PHE) through residence time distribution (RTD) experiments. The tested PHE had flat plates and it was part of a laboratory scale pasteurization unit. Series flow and parallel flow configurations were tested with a variable number of passes and channels per pass. Owing to the small scale of the equipment and the short residence times, it was necessary to take into account the influence of the tracer detection unit on the RID data. Four theoretical RID models were adjusted: combined, series combined, generalized convection and axial dispersion. The combined model provided the best fit and it was useful to quantify the active and dead space volumes of the PHE and their dependence on its configuration. Results suggest that the axial dispersion model would present good results for a larger number of passes because of the turbulence associated with the changes of pass. This type of study can be useful to compare the hydraulic performance of different plates or to provide data for the evaluation of heat-induced changes that occur in the processing of heat-sensitive products. (C) 2011 Elsevier Ltd. All rights reserved.

On Building a Memory Evolutive System for Application to Learning and Cognition Modeling

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

A sensor array based on mass and capacitance transducers for the detection of adulterated gasolines

The simultaneous use of different sensors technologies is an efficient method to increase the performance of chemical sensors systems. Among the available technologies, mass and capacitance transducers are particularly interesting because they can take advantage also from non-conductive sensing layers, such as most of the more interesting molecular recognition systems. In this paper, an array of quartz microbalance sensors is complemented by an array of capacitors obtained from a commercial biometrics fingerprints detector. The two sets of transducers, properly functionalized by sensitive molecular and polymeric films, are utilized for the estimation of adulteration in gasolines, and in particular to quantify the content of ethanol in gasolines, an application of importance for Brazilian market. Results indicate that the hybrid system outperforms the individual sensor arrays even if the quantification of ethanol in gasoline, due to the variability of gasolines formulation, is affected by a barely acceptable error. (C) 2009 Elsevier B.V. All rights reserved.

MODELING THE UNVOICED COMPONENT IN THE CANONICAL REPRESENTATION OF SPEECH

The canonical representation of speech constitutes a perfect reconstruction (PR) analysis-synthesis system. Its parameters are the autoregressive (AR) model coefficients, the pitch period and the voiced and unvoiced components of the excitation represented as transform coefficients. Each set of parameters may be operated on independently. A time-frequency unvoiced excitation (TFUNEX) model is proposed that has high time resolution and selective frequency resolution. Improved time-frequency fit is obtained by using for antialiasing cancellation the clustering of pitch-synchronous transform tracks defined in the modulation transform domain. The TFUNEX model delivers high-quality speech while compressing the unvoiced excitation representation about 13 times over its raw transform coefficient representation for wideband speech.

Modeling and Filtering Double-Frequency Jitter in One-Way Master-Slave Chain Networks

One-way master-slave (OWMS) chain networks are widely used in clock distribution systems due to their reliability and low cost. As the network nodes are phase-locked loops (PLLs), double-frequency jitter (DFJ) caused by their phase detectors appears as an impairment to the performance of the clock recovering process found in communication systems and instrumentation applications. A nonlinear model for OWMS chain networks with P + 1 order PLLs as slave nodes is presented, considering the DFJ. Since higher order filters are more effective in filtering DFJ, the synchronous state stability conditions for an OWMS chain network with third-order nodes are derived, relating the loop gain and the filter coefficients. By using these conditions, design examples are discussed.

Proposal for DICOM Multiframe Medical Image Integrity and Authenticity

This paper presents a novel algorithm to successfully achieve viable integrity and authenticity addition and verification of n-frame DICOM medical images using cryptographic mechanisms. The aim of this work is the enhancement of DICOM security measures, especially for multiframe images. Current approaches have limitations that should be properly addressed for improved security. The algorithm proposed in this work uses data encryption to provide integrity and authenticity, along with digital signature. Relevant header data and digital signature are used as inputs to cipher the image. Therefore, one can only retrieve the original data if and only if the images and the inputs are correct. The encryption process itself is a cascading scheme, where a frame is ciphered with data related to the previous frames, generating also additional data on image integrity and authenticity. Decryption is similar to encryption, featuring also the standard security verification of the image. The implementation was done in JAVA, and a performance evaluation was carried out comparing the speed of the algorithm with other existing approaches. The evaluation showed a good performance of the algorithm, which is an encouraging result to use it in a real environment.

Local search multiuser detection

In this work, a wide analysis of local search multiuser detection (LS-MUD) for direct sequence/code division multiple access (DS/CDMA) systems under multipath channels is carried out considering the performance-complexity trade-off. It is verified the robustness of the LS-MUD to variations in loading, E(b)/N(0), near-far effect, number of fingers of the Rake receiver and errors in the channel coefficients estimates. A compared analysis of the bit error rate (BER) and complexity trade-off is accomplished among LS, genetic algorithm (GA) and particle swarm optimization (PSO). Based on the deterministic behavior of the LS algorithm, it is also proposed simplifications over the cost function calculation, obtaining more efficient algorithms (simplified and combined LS-MUD versions) and creating new perspectives for the MUD implementation. The computational complexity is expressed in terms of the number of operations in order to converge. Our conclusion pointed out that the simplified LS (s-LS) method is always more efficient, independent of the system conditions, achieving a better performance with a lower complexity than the others heuristics detectors. Associated to this, the deterministic strategy and absence of input parameters made the s-LS algorithm the most appropriate for the MUD problem. (C) 2008 Elsevier GmbH. All rights reserved.

Jointly multi-user detection and channel estimation with genetic algorithm

This work aims at proposing the use of the evolutionary computation methodology in order to jointly solve the multiuser channel estimation (MuChE) and detection problems at its maximum-likelihood, both related to the direct sequence code division multiple access (DS/CDMA). The effectiveness of the proposed heuristic approach is proven by comparing performance and complexity merit figures with that obtained by traditional methods found in literature. Simulation results considering genetic algorithm (GA) applied to multipath, DS/CDMA and MuChE and multi-user detection (MuD) show that the proposed genetic algorithm multi-user channel estimation (GAMuChE) yields a normalized mean square error estimation (nMSE) inferior to 11%, under slowly varying multipath fading channels, large range of Doppler frequencies and medium system load, it exhibits lower complexity when compared to both maximum likelihood multi-user channel estimation (MLMuChE) and gradient descent method (GrdDsc). A near-optimum multi-user detector (MuD) based on the genetic algorithm (GAMuD), also proposed in this work, provides a significant reduction in the computational complexity when compared to the optimum multi-user detector (OMuD). In addition, the complexity of the GAMuChE and GAMuD algorithms were (jointly) analyzed in terms of number of operations necessary to reach the convergence, and compared to other jointly MuChE and MuD strategies. The joint GAMuChE-GAMuD scheme can be regarded as a promising alternative for implementing third-generation (3G) and fourth-generation (4G) wireless systems in the near future. Copyright (C) 2010 John Wiley & Sons, Ltd.

Evaluation of Characterization and Performance Modeling of Cementitiously Stabilized Layers in the Mechanistic-Empirical Pavement Design Guide

Cementitious stabilization of aggregates and soils is an effective technique to increase the stiffness of base and subbase layers. Furthermore, cementitious bases can improve the fatigue behavior of asphalt surface layers and subgrade rutting over the short and long term. However, it can lead to additional distresses such as shrinkage and fatigue in the stabilized layers. Extensive research has tested these materials experimentally and characterized them; however, very little of this research attempts to correlate the mechanical properties of the stabilized layers with their performance. The Mechanistic Empirical Pavement Design Guide (MEPDG) provides a promising theoretical framework for the modeling of pavements containing cementitiously stabilized materials (CSMs). However, significant improvements are needed to bring the modeling of semirigid pavements in MEPDG to the same level as that of flexible and rigid pavements. Furthermore, the MEPDG does not model CSMs in a manner similar to those for hot-mix asphalt or portland cement concrete materials. As a result, performance gains from stabilized layers are difficult to assess using the MEPDG. The current characterization of CSMs was evaluated and issues with CSM modeling and characterization in the MEPDG were discussed. Addressing these issues will help designers quantify the benefits of stabilization for pavement service life.

Modeling technique for honeycomb FRP deck bridges via finite elements

Honeycomb structures have been used in different engineering fields. In civil engineering, honeycomb fiber-reinforced polymer (FRP) structures have been used as bridge decks to rehabilitate highway bridges in the United States. In this work, a simplified finite-element modeling technique for honeycomb FRP bridge decks is presented. The motivation is the combination of the complex geometry of honeycomb FRP decks and computational limits, which may prevent modeling of these decks in detail. The results from static and modal analyses indicate that the proposed modeling technique provides a viable tool for modeling the complex geometry of honeycomb FRP bridge decks. The modeling of other bridge components (e.g., steel girders, steel guardrails, deck-to-girder connections, and pier supports) is also presented in this work.

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques - combines computer engineering concepts with areas like dermatology and oncology. Its objective is to discern images of skin cancer, specifically melanoma, from others that show only common spots or other types of skin diseases, using image recognition. This work makes use of the ABCDE visual rule, which is often used by dermatologists for melanoma identification, to define which characteristics are analyzed by the software. It then applies various algorithms and techniques, including an ellipse-fitting algorithm, to extract and measure these characteristics and decide whether the spot is a melanoma or not. The achieved results are presented with special focus on the adaptive decision-making and its effect on the diagnosis. Finally, other applications of the software and its algorithms are presented.