Desenvolvimento e avaliação de novas abordagens de modelagem de processos de separação em leito móvel simulado

O Leito Móvel Simulado (LMS) é um processo de separação de compostos por adsorção muito eficiente, por trabalhar em um regime contínuo e também possuir fluxo contracorrente da fase sólida. Dentre as diversas aplicações, este processo tem se destacado na resolução de petroquímicos e principalmente na atualidade na separação de misturas racêmicas que são separações de um grau elevado de dificuldade. Neste trabalho foram propostas duas novas abordagens na modelagem do LMS, a abordagem Stepwise e a abordagem Front Velocity. Na modelagem Stepwise as colunas cromatográficas do LMS foram modeladas com uma abordagem discreta, onde cada uma delas teve seu domínio dividido em N células de mistura interligadas em série, e as concentrações dos compostos nas fases líquida e sólida foram simuladas usando duas cinéticas de transferência de massa distintas. Essa abordagem pressupõe que as interações decorrentes da transferência de massa entre as moléculas do composto nas suas fases líquida e sólida ocorram somente na superfície, de forma que com essa suposição pode-se admitir que o volume ocupado por cada molécula nas fases sólida e líquida é o mesmo, o que implica que o fator de residência pode ser considerado igual a constante de equilíbrio. Para descrever a transferência de massa que ocorre no processo cromatográfico a abordagem Front Velocity estabelece que a convecção é a fase dominante no transporte de soluto ao longo da coluna cromatográfica. O Front Velocity é um modelo discreto (etapas) em que a vazão determina o avanço da fase líquida ao longo da coluna. As etapas são: avanço da fase líquida e posterior transporte de massa entre as fases líquida e sólida, este último no mesmo intervalo de tempo. Desta forma, o fluxo volumétrico experimental é utilizado para a discretização dos volumes de controle que se deslocam ao longo da coluna porosa com a mesma velocidade da fase líquida. A transferência de massa foi representada por dois mecanismos cinéticos distintos, sem (tipo linear) e com capacidade máxima de adsorção (tipo Langmuir). Ambas as abordagens propostas foram estudadas e avaliadas mediante a comparação com dados experimentais de separação em LMS do anestésico cetamina e, posteriormente, com o fármaco Verapamil. Também foram comparados com as simulações do modelo de equilíbrio dispersivo para o caso da Cetamina, usado por Santos (2004), e para o caso do Verapamil (Perna 2013). Na etapa de caracterização da coluna cromatográfica as novas abordagens foram associadas à ferramenta inversa R2W de forma a determinar os parâmetros globais de transferência de massa apenas usando os tempos experimentais de residência de cada enantiômero na coluna de cromatografia líquida de alta eficiência (CLAE). Na segunda etapa os modelos cinéticos desenvolvidos nas abordagens foram aplicados nas colunas do LMS com os valores determinados na caracterização da coluna cromatográfica, para a simulação do processo de separação contínua. Os resultados das simulações mostram boa concordância entre as duas abordagens propostas e os experimentos de pulso para a caracterização da coluna na separação enantiomérica da cetamina ao longo do tempo. As simulações da separação em LMS, tanto do Verapamil quando da Cetamina apresentam uma discrepância com os dados experimentais nos primeiros ciclos, entretanto após esses ciclos iniciais a correlação entre os dados experimentais e as simulações. Para o caso da separação da cetamina (Santos, 2004), a qual a concentração da alimentação era relativamente baixa, os modelos foram capazes de predizer o processo de separação com as cinéticas Linear e Langmuir. No caso da separação do Verapamil (Perna, 2013), onde a concentração da alimentação é relativamente alta, somente a cinética de Langmuir representou o processo, devido a cinética Linear não representar a saturação das colunas cromatográficas. De acordo como o estudo conduzido ambas as abordagens propostas mostraram-se ferramentas com potencial na predição do comportamento cromatográfico de uma amostra em um experimento de pulso, assim como na simulação da separação de um composto no LMS, apesar das pequenas discrepâncias apresentadas nos primeiros ciclos de trabalho do LMS. Além disso, podem ser facilmente implementadas e aplicadas na análise do processo, pois requer um baixo número de parâmetros e são constituídas de equações diferenciais ordinárias.

Use of a semantically grained database system for distribution and control within design environments

This paper presents a technique to share the data stored in an object-oriented database aimed at designing environments. This technique shares data between two related databases, called the Original and Product databases, and is composed of three processes: data separation, evolution and integration. Whenever a block of data needs to be shared, it is spread into both databases, resulting in a block on the original database, and another into the Product database, with special links between them controlled by the Object Manager. These blocks do not need to be maintained identical during the evolution phase of the sharing process. Six types of links were defined, and by choosing one, the designer control the evolution and reintegration of the block in both databases. This process uses the composite object concept as the unit of control. The presented concepts can be applied to any data model with support to composite objects.

Separable Hyperstructure and Delayed Link Binding

As the amount of material on the World Wide Web continues to grow, users are discovering that the Web's embedded, hard-coded, links are difficult to maintain and update. Hyperlinks need a degree of abstraction in the way they are specified together with a sound underlying document structure and the property of separability from the documents they are linking. The case is made by studying the advantages of program/data separation in computer system architectures and also by re-examining some selected hypermedia systems that have already implemented separability. The prospects for introducing more abstract links into future versions of HTML and PDF, via emerging standards such as XPath, XPointer XLink and URN, are briefly discussed.

CLOSE—A Data-Driven Approach to Speech Separation

This paper studies single-channel speech separation, assuming unknown, arbitrary temporal dynamics for the speech signals to be separated. A data-driven approach is described, which matches each mixed speech segment against a composite training segment to separate the underlying clean speech segments. To advance the separation accuracy, the new approach seeks and separates the longest mixed speech segments with matching composite training segments. Lengthening the mixed speech segments to match reduces the uncertainty of the constituent training segments, and hence the error of separation. For convenience, we call the new approach Composition of Longest Segments, or CLOSE. The CLOSE method includes a data-driven approach to model long-range temporal dynamics of speech signals, and a statistical approach to identify the longest mixed speech segments with matching composite training segments. Experiments are conducted on the Wall Street Journal database, for separating mixtures of two simultaneous large-vocabulary speech utterances spoken by two different speakers. The results are evaluated using various objective and subjective measures, including the challenge of large-vocabulary continuous speech recognition. It is shown that the new separation approach leads to significant improvement in all these measures.

Max separation clustering for feature extraction from Optical Emission Spectroscopy Data

This paper proposes max separation clustering (MSC), a new non-hierarchical clustering method used for feature extraction from optical emission spectroscopy (OES) data for plasma etch process control applications. OES data is high dimensional and inherently highly redundant with the result that it is difficult if not impossible to recognize useful features and key variables by direct visualization. MSC is developed for clustering variables with distinctive patterns and providing effective pattern representation by a small number of representative variables. The relationship between signal-to-noise ratio (SNR) and clustering performance is highlighted, leading to a requirement that low SNR signals be removed before applying MSC. Experimental results on industrial OES data show that MSC with low SNR signal removal produces effective summarization of the dominant patterns in the data.

Case study: object and ground point separation on a river bank using airborne based LIDAR data

In the past decade, airborne based LIght Detection And Ranging (LIDAR) has been recognised by both the commercial and public sectors as a reliable and accurate source for land surveying in environmental, engineering and civil applications. Commonly, the first task to investigate LIDAR point clouds is to separate ground and object points. Skewness Balancing has been proven to be an efficient non-parametric unsupervised classification algorithm to address this challenge. Initially developed for moderate terrain, this algorithm needs to be adapted to handle sloped terrain. This paper addresses the difficulty of object and ground point separation in LIDAR data in hilly terrain. A case study on a diverse LIDAR data set in terms of data provider, resolution and LIDAR echo has been carried out. Several sites in urban and rural areas with man-made structure and vegetation in moderate and hilly terrain have been investigated and three categories have been identified. A deeper investigation on an urban scene with a river bank has been selected to extend the existing algorithm. The results show that an iterative use of Skewness Balancing is suitable for sloped terrain.

Threshold-free object and ground point separation in LIDAR data

Light Detection And Ranging (LIDAR) is an important modality in terrain and land surveying for many environmental, engineering and civil applications. This paper presents the framework for a recently developed unsupervised classification algorithm called Skewness Balancing for object and ground point separation in airborne LIDAR data. The main advantages of the algorithm are threshold-freedom and independence from LIDAR data format and resolution, while preserving object and terrain details. The framework for Skewness Balancing has been built in this contribution with a prediction model in which unknown LIDAR tiles can be categorised as “hilly” or “moderate” terrains. Accuracy assessment of the model is carried out using cross-validation with an overall accuracy of 95%. An extension to the algorithm is developed to address the overclassification issue for hilly terrain. For moderate terrain, the results show that from the classified tiles detached objects (buildings and vegetation) and attached objects (bridges and motorway junctions) are separated from bare earth (ground, roads and yards) which makes Skewness Balancing ideal to be integrated into geographic information system (GIS) software packages.

Development of system separation strategy using synchrophasor data

In the current market system, power systems are operated at higher loads for economic reasons. Power system stability becomes a genuine concern in such operating conditions. In case of failure of any larger component, the system may become stressed. These events may start cascading failures, which may lead to blackouts. One of the main reasons of the major recorded blackout events has been the unavailability of system-wide information. Synchrophasor technology has the capability to provide system-wide real time information. Phasor Measurement Units (PMUs) are the basic building block of this technology, which provide the Global Positioning System (GPS) time-stamped voltage and current phasor values along with the frequency. It is being assumed that synchrophasor data of all the buses is available and thus the whole system is fully observable. This information can be used to initiate islanding or system separation to avoid blackouts. A system separation strategy using synchrophasor data has been developed to answer the three main aspects of system separation: (1) When to separate: One class support machines (OC-SVM) is primarily used for the anomaly detection. Here OC-SVM was used to detect wide area instability. OC-SVM has been tested on different stable and unstable cases and it is found that OC-SVM has the capability to detect the wide area instability and thus is capable to answer the question of “when the system should be separated”. (2) Where to separate: The agglomerative clustering technique was used to find the groups of coherent buses. The lines connecting different groups of coherent buses form the separation surface. The rate of change of the bus voltage phase angles has been used as the input to this technique. This technique has the potential to exactly identify the lines to be tripped for the system separation. (3) What to do after separation: Load shedding was performed approximately equal to the sum of power flows along the candidate system separation lines should be initiated before tripping these lines. Therefore it is recommended that load shedding should be initiated before tripping the lines for system separation.

Evaluation of separation management algorithms in Class G airspace

Use of Unmanned Aerial Vehicles (UAVs) in support of government applications has already seen significant growth and the potential for use of UAVs in commercial applications is expected to rapidly expand in the near future. However, the issue remains on how such automated or operator-controlled aircraft can be safely integrated into current airspace. If the goal of integration is to be realized, issues regarding safe separation in densely populated airspace must be investigated. This paper investigates automated separation management concepts in uncontrolled airspace that may help prepare for an expected growth of UAVs in Class G airspace. Not only are such investigations helpful for the UAV integration issue, the automated separation management concepts investigated by the authors can also be useful for the development of new or improved Air Traffic Control services in remote regions without any existing infrastructure. The paper will also provide an overview of the Smart Skies program and discuss the corresponding Smart Skies research and development effort to evaluate aircraft separation management algorithms using simulations involving realworld data communication channels, and verified against actual flight trials. This paper presents results from a unique flight test concept that uses real-time flight test data from Australia over existing commercial communication channels to a control center in Seattle for real-time separation management of actual and simulated aircraft. The paper also assesses the performance of an automated aircraft separation manager.

Microphone array beamforming approach to blind speech separation

In this paper, we present a microphone array beamforming approach to blind speech separation. Unlike previous beamforming approaches, our system does not require a-priori knowledge of the microphone placement and speaker location, making the system directly comparable other blind source separation methods which require no prior knowledge of recording conditions. Microphone location is automatically estimated using an assumed noise field model, and speaker locations are estimated using cross correlation based methods. The system is evaluated on the data provided for the PASCAL Speech Separation Challenge 2 (SSC2), achieving a word error rate of 58% on the evaluation set.

Reliability of routinely collected hospital data for child maltreatment surveillance

Background: Internationally, research on child maltreatment-related injuries has been hampered by a lack of available routinely collected health data to identify cases, examine causes, identify risk factors and explore health outcomes. Routinely collected hospital separation data coded using the International Classification of Diseases and Related Health Problems (ICD) system provide an internationally standardised data source for classifying and aggregating diseases, injuries, causes of injuries and related health conditions for statistical purposes. However, there has been limited research to examine the reliability of these data for child maltreatment surveillance purposes. This study examined the reliability of coding of child maltreatment in Queensland, Australia. Methods: A retrospective medical record review and recoding methodology was used to assess the reliability of coding of child maltreatment. A stratified sample of hospitals across Queensland was selected for this study, and a stratified random sample of cases was selected from within those hospitals. Results: In 3.6% of cases the coders disagreed on whether any maltreatment code could be assigned (definite or possible) versus no maltreatment being assigned (unintentional injury), giving a sensitivity of 0.982 and specificity of 0.948. The review of these cases where discrepancies existed revealed that all cases had some indications of risk documented in the records. 15.5% of cases originally assigned a definite or possible maltreatment code, were recoded to a more or less definite strata. In terms of the number and type of maltreatment codes assigned, the auditor assigned a greater number of maltreatment types based on the medical documentation than the original coder assigned (22% of the auditor coded cases had more than one maltreatment type assigned compared to only 6% of the original coded data). The maltreatment types which were the most ‘under-coded’ by the original coder were psychological abuse and neglect. Cases coded with a sexual abuse code showed the highest level of reliability. Conclusion: Given the increasing international attention being given to improving the uniformity of reporting of child-maltreatment related injuries and the emphasis on the better utilisation of routinely collected health data, this study provides an estimate of the reliability of maltreatment-specific ICD-10-AM codes assigned in an inpatient setting.

A sequential Monte Carlo approach to the sequential design for discriminating between rival continuous data models

Here we present a sequential Monte Carlo approach to Bayesian sequential design for the incorporation of model uncertainty. The methodology is demonstrated through the development and implementation of two model discrimination utilities; mutual information and total separation, but it can also be applied more generally if one has different experimental aims. A sequential Monte Carlo algorithm is run for each rival model (in parallel), and provides a convenient estimate of the marginal likelihood (of each model) given the data, which can be used for model comparison and in the evaluation of utility functions. A major benefit of this approach is that it requires very little problem specific tuning and is also computationally efficient when compared to full Markov chain Monte Carlo approaches. This research is motivated by applications in drug development and chemical engineering.

Urban, suburban, and rural variations in separation/divorce rape/sexual assault : results from the National Crime Victimization Survey

To date, no large study has looked at whether separation/divorce sexual assault varies across urban, suburban, and rural areas. The authors use 1992-2009 NCVS (National Crime Victimization Survey) data to estimate the percentage of separation/divorce sexual assault against women in urban, suburban, and rural communities. In addition, the authors identify and compare the relative risk of sexual assault victimization for women across areas. Findings indicate that a higher percentage of rural divorced/separated women were victims of rape/sexual assault than were urban divorced/separated women. In addition, rural separated women are victims of intimate rape/sexual assault at significantly higher rates than their suburban and urban counterparts.