Side information creation for efficient Wyner-Ziv video coding: Classifying and reviewing

Video coding technologies have played a major role in the explosion of large market digital video applications and services. In this context, the very popular MPEG-x and H-26x video coding standards adopted a predictive coding paradigm, where complex encoders exploit the data redundancy and irrelevancy to 'control' much simpler decoders. This codec paradigm fits well applications and services such as digital television and video storage where the decoder complexity is critical, but does not match well the requirements of emerging applications such as visual sensor networks where the encoder complexity is more critical. The Slepian Wolf and Wyner-Ziv theorems brought the possibility to develop the so-called Wyner-Ziv video codecs, following a different coding paradigm where it is the task of the decoder, and not anymore of the encoder, to (fully or partly) exploit the video redundancy. Theoretically, Wyner-Ziv video coding does not incur in any compression performance penalty regarding the more traditional predictive coding paradigm (at least for certain conditions). In the context of Wyner-Ziv video codecs, the so-called side information, which is a decoder estimate of the original frame to code, plays a critical role in the overall compression performance. For this reason, much research effort has been invested in the past decade to develop increasingly more efficient side information creation methods. This paper has the main objective to review and evaluate the available side information methods after proposing a classification taxonomy to guide this review, allowing to achieve more solid conclusions and better identify the next relevant research challenges. After classifying the side information creation methods into four classes, notably guess, try, hint and learn, the review of the most important techniques in each class and the evaluation of some of them leads to the important conclusion that the side information creation methods provide better rate-distortion (RD) performance depending on the amount of temporal correlation in each video sequence. It became also clear that the best available Wyner-Ziv video coding solutions are almost systematically based on the learn approach. The best solutions are already able to systematically outperform the H.264/AVC Intra, and also the H.264/AVC zero-motion standard solutions for specific types of content. (C) 2013 Elsevier B.V. All rights reserved.

On the use of IEEE 802.15.4/Zigbee for time-sensitive wireless sensor network applications

Mestrado em Engenharia Electrotécnica e de Computadores

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

Direct Color Sensor, Optical Amplifier and Demux Device Integrated on a Single Monolithic SiC Photodetector

A pi'n/pin a-SiC:H voltage and optical bias controlled device is presented and its behavior as image and color sensor, optical amplifier and demux device is discussed. The design and the light source properties are correlated with the sensor output characteristics. Different readout techniques are used. When a low power monochromatic scanner readout the generated carriers the transducer recognizes a color pattern projected on it acting as a direct color and image sensor. Scan speeds up to 10(4) lines per second are achieved without degradation in the resolution. If the photocurrent generated by different monochromatic pulsed channels is readout directly, the information is demultiplexed. Results show that it is possible to decode the information from three simultaneous color channels without bit errors at bit rates per channel higher than 4000 bps. Finally, when triggered by light of appropriated wavelength, it can amplify or suppress the generated photocurrent working as an optical amplifier (C) 2009 Published by Elsevier Ltd.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

Comparing the content of instruments assessing environmental factors using the International Classification of Functioning, Disability and Health

Purpose: To describe and compare the content of instruments that assess environmental factors using the International Classification of Functioning, Disability and Health (ICF). Methods: A systematic search of PubMed, CINAHL and PEDro databases was conducted using a pre-determined search strategy. The identified instruments were screened independently by two investigators, and meaningful concepts were linked to the most precise ICF category according to published linking rules. Results: Six instruments were included, containing 526 meaningful concepts. Instruments had between 20% and 98% of items linked to categories in Chapter 1. The highest percentage of items from one instrument linked to categories in Chapters 2–5 varied between 9% and 50%. The presence or absence of environmental factors in a specific context is assessed in 3 instruments, while the other 3 assess the intensity of the impact of environmental factors. Discussion: Instruments differ in their content, type of assessment, and have several items linked to the same ICF category. Most instruments primarily assess products and technology (Chapter 1), highlighting the need to deepen the discussion on the theory that supports the measurement of environmental factors. This discussion should be thorough and lead to the development of methodologies and new tools that capture the underlying concepts of the ICF.

Comorbidity adjustment index for the international classification of diseases, 10

OBJECTIVE: To develop a Charlson-like comorbidity index based on clinical conditions and weights of the original Charlson comorbidity index. METHODS: Clinical conditions and weights were adapted from the International Classification of Diseases, 10th revision and applied to a single hospital admission diagnosis. The study included 3,733 patients over 18 years of age who were admitted to a public general hospital in the city of Rio de Janeiro, southeast Brazil, between Jan 2001 and Jan 2003. The index distribution was analyzed by gender, type of admission, blood transfusion, intensive care unit admission, age and length of hospital stay. Two logistic regression models were developed to predict in-hospital mortality including: a) the aforementioned variables and the risk-adjustment index (full model); and b) the risk-adjustment index and patient's age (reduced model). RESULTS: Of all patients analyzed, 22.3% had risk scores >1, and their mortality rate was 4.5% (66.0% of them had scores >1). Except for gender and type of admission, all variables were retained in the logistic regression. The models including the developed risk index had an area under the receiver operating characteristic curve of 0.86 (full model), and 0.76 (reduced model). Each unit increase in the risk score was associated with nearly 50% increase in the odds of in-hospital death. CONCLUSIONS: The risk index developed was able to effectively discriminate the odds of in-hospital death which can be useful when limited information is available from hospital databases.

Urubu: energy scavenging in wireless sensor networks

For the past years wireless sensor networks (WSNs) have been coined as one of the most promising technologies for supporting a wide range of applications. However, outside the research community, few are the people who know what they are and what they can offer. Even fewer are the ones that have seen these networks used in real world applications. The main obstacle for the proliferation of these networks is energy, or the lack of it. Even though renewable energy sources are always present in the networks environment, designing devices that can efficiently scavenge that energy in order to sustain the operation of these networks is still an open challenge. Energy scavenging, along with energy efficiency and energy conservation, are the current available means to sustain the operation of these networks, and can all be framed within the broader concept of “Energetic Sustainability”. A comprehensive study of the several issues related to the energetic sustainability of WSNs is presented in this thesis, with a special focus in today’s applicable energy harvesting techniques and devices, and in the energy consumption of commercially available WSN hardware platforms. This work allows the understanding of the different energy concepts involving WSNs and the evaluation of the presented energy harvesting techniques for sustaining wireless sensor nodes. This survey is supported by a novel experimental analysis of the energy consumption of the most widespread commercially available WSN hardware platforms.

Desenvolvimento de um sensor óptico para determinação de Norfloxacina

A presente dissertação descreve o desenvolvimento e a caracterização de sensores ópticos com base em membranas de poli(cloreto de vinilo), PVC, para determinação de Norfloxacina em amostras do sector da aquacultura. Estes sensores basearam-se na reacção colorimétrica entre um metal imobilizado em PVC e a Norfloxacina. O metal foi escolhido com base em ensaios prévios de reacção colorimétrica entre a Norfloxacina e várias espécies metálicas, nomeadamente, Fe(III), Al(III), Pb(II), Aluminon, Mo(II), Mn(II), Ni(II), Cu(II), Co(II), Sn(II) e V(V). A reacção mais intensa foi obtida com o Fe(III). Neste sentido, numa primeira fase foram desenvolvidos sensores baseados em Fe(III). O efeito de alguns parâmetros experimentais na resposta desses sensores foi avaliado de modo univariado. Incluem-se aqui o efeito do pH, avaliado entre 2,00 e 6,00, e o da concentração de Fe(III), variada entre cerca de 1,00x10-5 M e 2,00x10-4 M. Os melhores valores foram obtidos a pH 3, para o qual se verificou um comportamento linear entre cerca de 1,00x10-5 M e 1,70x10-4 M de Fe(III). Utilizando as condições seleccionadas anteriormente, procedeu-se à caracterização do complexo sob ponto de vista químico. Os valores obtidos apontaram para a necessidade de um excesso de Fe(III) de, pelo menos, 10 vezes, no sentido de garantir a máxima extensão de complexação. O complexo referido apresentou, nestas condições, um comportamento linear ao longo do intervalo de concentrações de cerca de 7,00x10-5 M a 7,00x10-4 M em NOR. O complexo formado foi estável ao longo de 90 minutos. As condições óptimas para análise desse complexo numa superfície sólida foram obtidas após avaliação do efeito da quantidade de Fe(III) e do tipo e quantidade de solvente mediador (o-nitrofenil octil éter, di-n-octilftalato, dibutilftalato, bis(etilhexil)sebacato, bis(etilhexil)ftalato). O bis(etilhexil)sebacato foi o solvente mediador escolhido e a relação de quantidade entre o PVC e o solvente mediador foi igual a 1:2. O procedimento de preparação do sensor sólido e subsequente optimização foi aplicado a outras espécies metálicas, para além do Fe(III), tais como, Cu(II), Mn(II) e aluminon. A conjugação de todos estes metais permitiu desenvolver um array de sensores para despistagem de Norfloxacina em águas de aquacultura. Algumas membranas sensoras foram aplicadas com sucesso no controlo de Norfloxacina em amostras de águas ambientais dopadas. Os resultados obtidos com membranas de Fe(III) e Cu(II) foram exactos, tendo-se registado valores de concentração próximos dos reais. O método proposto permitiu, por isso, a despistagem rápida e eficaz da presença de um antibiótico em águas ambientais, permitindo ainda o seu doseamento a um baixo custo. Numa perspectiva de rotina, e tendo em vista a despistagem deste antibiótico, este método revelou-se mais rápido e mais barato do que os demais métodos descritos na literatura para este efeito.

Monitorização do adoçante ciclamato de sódio através de sensor óptico

O presente trabalho pretendeu desenvolver e testar um sensor óptico para detectar ciclamato de sódio, um adoçante artificial utilizado nas bebidas em geral. A primeira abordagem neste sentido baseou-se na preparação de um sensor óptico através da formação de complexos corados entre o ciclamato e várias espécies metálicas, nomeadamente Hg(II), Ba(II), Fe(II), Ag(II), Pb(II), Cd(II), Mn (II), Ni(II), Cu(II), Co(II), Sn(II) e Mg(II). Perante a ausência de resultados satisfatórios optou-se por explorar a acção do ciclamato de sódio na transferência/partilha de um corante entre duas fases líquidas imiscíveis. As fases líquidas utilizadas foram a água e o clorofórmio. Testaram-se várias famílias de corantes mas só uma classe se mostrou com as características apropriadas para o objectivo pretendido. Dentro dessa família de corantes, seleccionou-se aquele que, à partida, garantiu o melhor desempenho. O sensor foi testado em diferentes condições de pH e também na presença de potenciais interferentes de forma a estabelecer as melhores condições de utilização. O método mostrou-se bastante simples de executar, rápido na obtenção de resultados e com boas características para ser avaliado visualmente, mas sempre de acordo com os critérios de objectividade que um trabalho deste tipo requer. Além o disso permitiu ser calibrado de uma forma rápida e simples, características essenciais para a aplicação deste método na despistagem de ciclamato em análises de rotina. O método desenvolvido foi ainda aplicado à análise de vinho dopado com diferentes concentrações de ciclamato de sódio. Destes testes verificou-se a necessidade de optimização do método através da introdução de outras substâncias na fase não aquosa diminuindo a vulnerabilidade do sensor a outros interferentes. Como conclusão, o método correspondeu às expectativas, mostrando-se viável para aplicação à análise de vinhos, ainda com uma margem significativa de desenvolvimento no sentido de o tornar mais fiável e preciso.