Feature-based tracking of urethral motion in low-resolution trans-perineal ultrasound

This paper describes a novel algorithm for tracking the motion of the urethra from trans-perineal ultrasound. Our work is based on the structure-from-motion paradigm and therefore handles well structures with ill-defined and partially missing boundaries. The proposed approach is particularly well-suited for video sequences of low resolution and variable levels of blurriness introduced by anatomical motion of variable speed. Our tracking method identifies feature points on a frame by frame basis using the SURF detector/descriptor. Inter-frame correspondence is achieved using nearest-neighbor matching in the feature space. The motion is estimated using a non-linear bi-quadratic model, which adequately describes the deformable motion of the urethra. Experimental results are promising and show that our algorithm performs well when compared to manual tracking.

Humor político audiovisual en Colombia: de los gloriosos años noventa en televisión a internet como alternativa

El humor político alrededor del mundo ha sido un recurso para criticar el poder y la esfera política con la mordacidad que otros escenarios no permiten y con lenguajes que generan empatía con el público. En la capacidad de criticar a todos los poderes –y poderosos- por igual, sin condescendencias, recae la credibilidad de esa crítica, la cual se debe poder hacer sin censura en una sociedad pluralista y democrática. En Colombia, el humor político en televisión emergió y vivió su época dorada en la década de los noventa, hasta que su principal exponente, Jaime Garzón, fue asesinado. Este trabajo de grado buscó indagar por qué, a pesar de que nuevos productos de crítica política con humor surgieron en el país, hoy no hay ese tipo de oferta en la televisión abierta nacional. La respuesta a ese interrogante se pudo encontrar en múltiples factores, como un nuevo modelo económico en la industria de la televisión, un ambiente político polarizado y la ausencia o falta de promoción de talentos detrás de los libretos. Asimismo, en medio de esta coyuntura, se plantea que internet ha sido un vehículo para expresar, incluso de manera anónima, lo que miembros de la sociedad creen que anda mal con el poder y la política.

Estrategia y plan de mercadeo de la empresa YouTube

Esta investigación describe la situación de cómo Youtube se ha convertido a partir de sus estrategias y plan de mercadeo en la plataforma número uno en variedad de clips de películas, vídeos musicales, video de blogs, entre otros; llegando a popularizarse como una red social. Las redes sociales han desarrollado una nueva forma de comunicar y son una herramienta fundamental para la creación de conocimiento colectivo, es el caso de YouTube buscador de contenido audiovisual y red social que permite a millones de usuarios conectarse alrededor del mundo. Esta plataforma rompe las barreras culturales y de comunicación que anteriormente existían a falta de internet. En este sentido se pretende analizar a YouTube desde una perspectiva administrativa enfocada en el área de mercadeo.

DIDÁCTICA DE LA GEOGRAFÍA Y DIDÁCTICA SUPERIOR

El artículo reflexiona sobre el aporte de la didáctica en el proceso de enseñanza – aprendizaje, enfatizando en su carácter teórico – práctica.  Diferencia entre una didáctica general y una didáctica específica.La Didáctica Crítica propone al profesor en Geografía como un maestro en el  saber y actuar, en el cumplimiento de sus deberes, responsabilidades y habilidades.  La enseñanza de la Geografía precisadel apoyo de numerosos instrumentos de alta tecnología, que constituyen valiosos aportes didácticos, la  incorporación de  las Tecnologías de  Información y Comunicación  (TICʼs)    es una necesidad. La formación a nivel universitario debe ofrecer las destrezas  y habilidades en la creación y composiciónde medios audiovisuales para la enseñanza  de la Geografía.  La Geografía contribuye eficazmente al desarrollo de capacidades, actitudes y competencias genéricas esenciales sobre las que ha de basarse la formación ciudadana y la educación de valores.Palabras claves: Geografía, didáctica de  la Geografía, saber geográfico, metodología de enseñanza, método didáctico.AbstractThe article reflects on the contribution from didactics in the process of teaching-learning, emphasizing in its theoretical character – practice. It differentiates between general didactics and specific didactics. Critical didactics suggests that the Geography professor, as an expert, knows and acts according to his or her duties, responsibilities and abilities.The teaching of the Geography draws upon the support of high-tech tools, which constitute valuable didactic contributions, so that incorporation of the Technology Information and Communication (TICʼs) is a necessity to be the mode of communication. Formation at the university level ought to offer talents and abilities in the creation and composition of audio-visual media in the teaching of geography. Geography effectively contributes to development of capabilities, attitudes and competencies generic essential for citizen formation and the education of values.Key Words: Geography,  didactics  of Geography,  geographical  knowledge,  teaching methodology, didactic method

El grito de Calibán. Del cinematógrafo al proyecto teleSur: la construcción de lo latinoamericano en la comunicación audiovisual regional

This essay analyzes on the importance of TeleSur TV Station (founded in 2005), in the historical context of the development of audio-visual means of communication in Latin America, as well as the debates about the influence of mass media in the process of cultural identity raising-up. It proposes the thesis that the project of Tele- Sur plays a key role in the shaping of a new international order on communication that allows the protection of the cultural diversity of Latin American nations and democratizes the world’s information flows in the neoliberal globalization stage.

Implementazione di un sistema di traduzione automatica: un caso di studio per la traduzione italiano-cinese

Il lavoro di tesi presentato è nato da una collaborazione con il Politecnico di Macao, i referenti sono: Prof. Rita Tse, Prof. Marcus Im e Prof. Su-Kit Tang. L'obiettivo consiste nella creazione di un modello di traduzione automatica italiano-cinese e nell'osservarne il comportamento, al fine di determinare se sia o meno possibile l'impresa. Il trattato approfondisce l'argomento noto come Neural Language Processing (NLP), rientrando dunque nell'ambito delle traduzioni automatiche. Sono servizi che, attraverso l'ausilio dell'intelligenza artificiale sono in grado di elaborare il linguaggio naturale, per poi interpretarlo e tradurlo. NLP è una branca dell'informatica che unisce: computer science, intelligenza artificiale e studio di lingue. Dal punto di vista della ricerca, le più grandi sfide in questo ambito coinvolgono: il riconoscimento vocale (speech-recognition), comprensione del testo (natural-language understanding) e infine la generazione automatica di testo (natural-language generation). Lo stato dell'arte attuale è stato definito dall'articolo "Attention is all you need" \cite{vaswani2017attention}, presentato nel 2017 a partire da una collaborazione di ricercatori della Cornell University.\\ I modelli di traduzione automatica più noti ed utilizzati al momento sono i Neural Machine Translators (NMT), ovvero modelli che attraverso le reti neurali artificiali profonde, sono in grado effettuare traduzioni o predizioni. La qualità delle traduzioni è particolarmente buona, tanto da arrivare quasi a raggiungere la qualità di una traduzione umana. Il lavoro infatti si concentrerà largamente sullo studio e utilizzo di NMT, allo scopo di proporre un modello funzionale e che sia in grado di performare al meglio nelle traduzioni da italiano a cinese e viceversa.

Elaboração de plano educacional aos usuários portadores de diabetes da equipe de saúde da família de Itaú de Minas-MG

O diabetes mellitus é uma doença crônica de alta prevalência e elevada taxa de mortalidade no mundo, sendo considerado como um problema de saúde publica. O objetivo deste estudo foi o de elaborar um plano educacional para os portadores de diabetes para um melhor acompanhamento do tratamento e conseqüente melhora da qualidade de vida. principal meta do aprendizado é treinar o portador de diabetes, a tomar decisões efetivas em seu autocuidado, tornando-se assim um gerente de seu próprio tratamento. Os pacientes receberão orientações básicas de acordo com um conteúdo programático por uma equipe multiprofissional envolvidos no processo, devem ser expositivas e práticas, com material didático adequado, uso de linguagem simples, recorrer a material audio-visual, cartazes e gravuras. Com um melhor conhecimento a respeito da doença o paciente diabético buscará uma melhor qualidade de vida, pois como resultado terá um melhor controle metabólico que é indispensável à prevenção das complicações agudas e crônicas da doença.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

AUTOMATIC CORONARY WALL SEGMENTATION IN INTRAVASCULAR ULTRASOUND IMAGES USING BINARY MORPHOLOGICAL RECONSTRUCTION

Intravascular ultrasound (IVUS) image segmentation can provide more detailed vessel and plaque information, resulting in better diagnostics, evaluation and therapy planning. A novel automatic segmentation proposal is described herein; the method relies on a binary morphological object reconstruction to segment the coronary wall in IVUS images. First, a preprocessing followed by a feature extraction block are performed, allowing for the desired information to be extracted. Afterward, binary versions of the desired objects are reconstructed, and their contours are extracted to segment the image. The effectiveness is demonstrated by segmenting 1300 images, in which the outcomes had a strong correlation to their corresponding gold standard. Moreover, the results were also corroborated statistically by having as high as 92.72% and 91.9% of true positive area fraction for the lumen and media adventitia border, respectively. In addition, this approach can be adapted easily and applied to other related modalities, such as intravascular optical coherence tomography and intravascular magnetic resonance imaging. (E-mail: matheuscardosomg@hotmail.com) (C) 2011 World Federation for Ultrasound in Medicine & Biology.

The resolution of complex spectral patterns by cochlear implant and normal-hearing listeners

The differences in spectral shape resolution abilities among cochlear implant ~CI! listeners, and between CI and normal-hearing ~NH! listeners, when listening with the same number of channels ~12!, was investigated. In addition, the effect of the number of channels on spectral shape resolution was examined. The stimuli were rippled noise signals with various ripple frequency-spacings. An adaptive 4IFC procedure was used to determine the threshold for resolvable ripple spacing, which was the spacing at which an interchange in peak and valley positions could be discriminated. The results showed poorer spectral shape resolution in CI compared to NH listeners ~average thresholds of approximately 3000 and 400 Hz, respectively!, and wide variability among CI listeners ~range of approximately 800 to 8000 Hz!. There was a significant relationship between spectral shape resolution and vowel recognition. The spectral shape resolution thresholds of NH listeners increased as the number of channels increased from 1 to 16, while the CI listeners showed a performance plateau at 4–6 channels, which is consistent with previous results using speech recognition measures. These results indicate that this test may provide a measure of CI performance which is time efficient and non-linguistic, and therefore, if verified, may provide a useful contribution to the prediction of speech perception in adults and children who use CIs.

Independent component analysis applied to raman spectra for classification of in vitro human coronary arteries

Optical diagnostic methods, such as near-infrared Raman spectroscopy allow quantification and evaluation of human affecting diseases, which could be useful in identifying and diagnosing atherosclerosis in coronary arteries. The goal of the present work is to apply Independent Component Analysis (ICA) for data reduction and feature extraction of Raman spectra and to perform the Mahalanobis distance for group classification according to histopathology, obtaining feasible diagnostic information to detect atheromatous plaque. An 830nm Ti:sapphire laser pumped by an argon laser provides near-infrared excitation. A spectrograph disperses light scattered from arterial tissues over a liquid-nitrogen cooled CCD to detect the Raman spectra. A total of 111 spectra from arterial fragments were utilized.

Assessment of two central auditory tests in elderly patients without hearing complaints

Speech understanding disorders in the elderly may be due to peripheral or central auditory dysfunctions. Asymmetry of results in dichotic testing increases with age, and may reflect on a lack of inter-hemisphere transmission and cognitive decline. Aim: To investigate auditory processing of aged people with no hearing complaints. Study design: clinical prospective. Materials and Methods: Twenty-two voluntary individuals, aged between 55 and 75 years, were evaluated. They reported no hearing complaints and had maximal auditory thresholds of 40 dB HL until 4 KHz, 80% of minimal speech recognition scores and peripheral symmetry between the ears. We used two kinds of tests: speech in noise and dichotic alternated dissyllables (SSW). Results were compared between males and females, right and left ears and between age groups. Results: There were no significant differences between genders, in both tests. Their Left ears showed worse results, in the competitive condition of SSW. Individuals aged 65 or older had poorer performances than those aged 55 to 64. Conclusion: Central auditory tests showed worse performance with aging. The employment of a dichotic test in the auditory evaluation setting in the elderly may help in the early identification of degenerative processes, which are common among these patients.

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

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.