Improved Shape Parameter Estimation in Pareto Distributed Clutter with Neural Networks

The main problem faced by naval radars is the elimination of the clutter input which is a distortion signal appearing mixed with target reflections. Recently, the Pareto distribution has been related to sea clutter measurements suggesting that it may provide a better fit than other traditional distributions. The authors propose a new method for estimating the Pareto shape parameter based on artificial neural networks. The solution achieves a precise estimation of the parameter, having a low computational cost, and outperforming the classic method which uses Maximum Likelihood Estimates (MLE). The presented scheme contributes to the development of the NATE detector for Pareto clutter, which uses the knowledge of clutter statistics for improving the stability of the detection, among other applications

Selección óptima del factor de ajuste CA-CFAR para clutter marino de potencia K estadísticamente variable

The presence of the sea clutter interfering signal sets limitations on the quality of radar detection in coastal and ocean environments. The CA-CFAR processor is the classic solution for detecting radar targets. It usually operates keeping constant its adjustment factor during the entire operation period. As a consequence, the scheme does not take into account the slow statistical variations of the background signal when performing the clutter discrimination. To solve this problem, the authors conducted an intensive processing of 40 million computer generated clutter power samples in MATLAB. As a result, they found the optimal adjustment factor values to be applied in 40 possible clutter statistical states, suggesting thus the use of the CA-CFAR architecture with a variable adjustment factor. In addition, a curve fitting procedure was performed, obtaining mathematical expressions that generalize the results for the whole addressed range of clutter statistical states. The experiments were executed with a 64 cells CA-CFAR and found the adjustment factor values for three common false alarms probabilities. The K distribution was used as clutter model, thanks to its wide popularity. This paper facilitates the handling of the K power distribution avoiding the use of Gamma and Bessel functions, commonly found in developments related to the K model. Moreover, requirements for building an adaptive clutter detector in K power clutter with a priori knowledge of the shape parameter were fulfill. Also, several recommendations are given to continue the development of a more overall solution which will also include the estimation of the shape parameter.La presencia de la señal interferente de clutter marino establece limitaciones en la calidad de la detección de radar en ambientes costeros y de alta mar. El procesador CA-CFAR es la solución clásica para detectar blancos de radar. Usualmente mantiene su factor de ajuste constante todo el período de operación. Como consecuencia, el esquema no toma en consideración las variaciones estadísticas de la señal de fondo cuando realiza la discriminación del clutter. Para resolver este problema, los autores realizaron un procesamiento intensivo de 40 millones de muestras de clutter de intensidad, generadas en computadora a través de MATLAB. Como resultado, encontraron los valores óptimos del factor de ajuste a ser aplicados para 40 posibles estados estadísticos del clutter, sugiriendo el uso de la arquitectura CA-CFAR con un factor de ajuste variable. Adicionalmente, fue llevado a cabo un ajuste de curvas, obteniéndose expresiones matemáticas que generalizan los resultados en todo el intervalo de considerado de estados estadísticos del clutter. Los experimentos se ejecutaron con un CA-CFAR de 64 celdas y apuntaron a encontrar los valores del factor de ajuste para tres probabilidades de falsa alarma comunes. La distribución K fue elegida como el modelo usado para el clutter, gracias a su amplia popularidad. Este artículo facilita el manejo de la distribución K de intensidad, evitando el uso de funciones Gamma y Bessel, comúnmente encontradas en desarrollos relacionados con el modelo K. Además, fueron cumplidos los requerimientos necesarios para construir un detector adaptativo en clutter de potencia K con conocimiento previo del parámetro de forma. Al mismo tiempo, fueron dadas varias recomendaciones para continuar el desarrollo de una solución más general que también incluirá la estimación del parámetro de forma

Detector CFAR de promediación con corrección del factor de ajuste a través del método de los momentos para la distribución Log-Normal

The new LN-MoM-CA-CFAR detector is introduced, exhibiting a reduced deviation of the operational false alarm probability from the value conceived in the design. The solution solves a fundamental problem of CFAR processors that has been ignored in most proposals. Indeed, most of the previously proposed schemes deal with sudden changes in the clutter level, whereas the new solution has an improved performance against slow statistical changes that occur in the background signal. It has been proven that these slow changes have a remarkable influence on the selection of the CFAR adjustment factor, and consequently in maintaining the false alarm probability. The authors took advantage of the high precision achieved by the MoM (Method of Moments) in the estimation of the Log-Normal (LN) shape parameter, and the wide application of this distribution to radar clutter modeling, to create an architecture that offers precise results and it’s computationally inexpensive at the same time. After an intensive processing, involving 100 million Log-Normal samples, a scheme, which operates with excellent stability reaching a deviation of only 0,2884 % for the probability of false alarm of 0,01, was created, improving the classical CA-CFAR detector through the continuous correction of its scale factor.Se presenta el nuevo detector LN-MoM-CA-CFAR que tiene una desviación reducida en la tasa de probabilidad de falsa alarma operacional con respecto al valor concebido de diseño. La solución corrige un problema fundamental de los procesadores CFAR que ha sido ignorado en múltiples desarrollos. En efecto, la mayoría de los esquemas previamente propuestos tratan con los cambios bruscos del nivel del clutter mientras que la presente solución corrige los cambios lentos estadísticos de la señal de fondo. Se ha demostrado que estos tienen una influencia marcada en la selección del factor de ajuste multiplicativo CFAR, y consecuentemente en el mantenimiento de la probabilidad de falsa alarma. Los autores aprovecharon la alta precisión que se alcanza en la estimación del parámetro de forma Log-Normal con el MoM, y la amplia aplicación de esta distribución en la modelación del clutter, para crear una arquitectura que ofrece resultados precisos y con bajo costo computacional. Luego de un procesamiento intensivo de 100 millones de muestras Log-Normal, se creó un esquema que, mejorando el desempeño del clásico CA-CFAR a través de la corrección continua de su factor de ajuste, opera con una excelente estabilidad alcanzando una desviación de solamente 0,2884 % para la probabilidad de falsa alarma de 0,01

CA-CFAR Adjustment Factor Correction with a priori Knowledge of the Clutter Distribution Shape Parameter

Oceanic and coastal radars operation is affected because the targets information is received mixed with and undesired contribution called sea clutter. Specifically, the popular CA-CFAR processor is incapable of maintaining its design false alarm probability when facing clutter with statistical variations. In opposition to the classic alternative suggesting the use of a fixed adjustment factor, the authors propose a modification of the CA- CFAR scheme where the factor is constantly corrected according on the background signal statistical changes. Mathematically translated as a variation in the shape parameter of the clutter distribution, the background signal changes were simulated through the Weibull, Log-Normal and K distributions, deriving expressions which allow choosing an appropriate factor for each possible statistical state. The investigation contributes to the improvement of radar detection by suggesting the application of an adaptive scheme which assumes the clutter shape parameter is known a priori. The offered mathematical expressions are valid for three false alarm probabilities and several windows sizes, covering also a wide range of clutter conditions

Modelación estadística de la textura del clutter marino en Matlab

Context: The statistical modeling of the interference signal known as sea clutter is achieved assuming the input results from the combination of two components: one for the speckle and another for the texture. The Gamma distribution is the more widely applied for the texture component. Nevertheless, several authors have defended the idea of using the Inverse Gamma and Inverse Gaussian instead.Method: In order to provide an easy access to the handling of the models and the execution of comparisons between them, the authors of the current paper simulated in MATLAB the main characteristics of these distributions. In addition, the Root-Gamma model was also included because it replaces the Gamma distribution when samples are processed in the amplitude domain. The applied method consisted in a deep bibliography review for finding the corresponding expressions for each simulated model; the method also included additional computational simulations that allowed to identify occasional errors that were committed by different authors when characterizing the models.Results: A small framework was created for stochastic simulation containing density and distribution functions, mechanisms for random variable generation, parameter estimation methods and statistical moment closed expressions, among others. Besides, complementary functions were prepared for guaranteeing the validation by comparison with results provided by third parties and through the interaction between the different components of the library.Conclusions: The created library enables the use of multiple distributions for the modeling of the electromagnetic echo received from the sea surface. This will certainly motivate the creation of new radar detectors adapted to heterogeneous conditions such as the ones existing in Cuban coastal regions, where one may find different depth levels, mangrove swamps, brackish water, islets, prominent aquatic vegetation, among others.Contexto: La modelación estadística de la señal interferente conocida como clutter marino se efectúa a través de dos componentes: uno de capilaridad y otro de textura. La distribución más utilizada para la textura es la gamma. No obstante, varios autores han defendido el uso alternativo de la inversa gamma y la inversa gaussiana.Método: Con el objetivo de brindar un acceso fácil a la manipulación de los modelos y a la realización de comparaciones entre ellos, los autores del presente artículo simularon en Matlab las características principales de estas tres distribuciones. Adicionalmente, se agregó la distribución raíz gamma que sustituye a la gamma cuando se trabaja con muestras de amplitud. El método aplicado consistió en la revisión bibliográfica para encontrar las expresiones de cada uno de los parámetros modelados, y la posterior simulación computacional que permitió detectar errores ocasionales que surgen al consultar diferentes estudios.Resultados: Se creó una pequeña librería de simulación estocástica que incluye funciones de densidad y distribución, generación de variables aleatorias, estimación de parámetros y cálculo de momentos estadísticos, entre otros. Además, se elaboraron funciones informáticas complementarias que permitieron la validación por comparación con resultados dados por terceros y mediante la interacción de los diferentes componentes de la librería.Conclusiones: La librería creada habilita el uso de múltiples distribuciones, para la modelación del eco electromagnético de la superficie marina. Esto permitirá generar nuevos detectores de radar que se adapten a condiciones heterogéneas como las encontradas en las costas cubanas, donde alternan distintos niveles de profundidad, manglares, aguas salobres, islotes, vegetación acuática prominente, entre otras

Improved Shape Parameter Estimation in K Clutter with Neural Networks and Deep Learning

The discrimination of the clutter interfering signal is a current problem in modern radars’ design, especially in coastal or offshore environments where the histogram of the background signal often displays heavy tails. The statistical characterization of this signal is very important for the cancellation of sea clutter, whose behavior obeys a K distribution according to the commonly accepted criterion. By using neural networks, the authors propose a new method for estimating the K shape parameter, demonstrating its superiority over the classic alternative based on the Method of Moments. Whereas both solutions have a similar performance when the entire range of possible values of the shape parameter is evaluated, the neuronal alternative achieves a much more accurate estimation for the lower Fig.s of the parameter. This is exactly the desired behavior because the best estimate occurs for the most aggressive states of sea clutter. The final design, reached by processing three different sets of computer generated K samples, used a total of nine neural networks whose contribution is synthesized in the final estimate, thus the solution can be interpreted as a deep learning approximation. The results are to be applied in the improvement of radar detectors, particularly for maintaining the operational false alarm probability close to the one conceived in the design

Evaluation of CFAR detectors performance

The operation of coastal and off-shore radars is affected because the targets are surrounded by a background filled with sea clutter. According on the Neyman-Pearson criterion, radar detectors must always try to maintain a constant false alarm probability before trying to improve other system variables. Using the MATLAB mathematic software, the authors evaluated the performance of the CA, OS, MSCA, AND, OR and ISCFAR processors concerning their ability to maintain the constant false alarm probability conceived in the design. After testing the schemes with different test profiles whose samples were Rayleigh distributed, it was concluded that most of the alternatives exhibit problems when facing certain situations that may appear in real environments. Consequently, recommendations on which solution is best to use are offered for guaranteeing a reduced deviation of the operational false alarm probability from the value conceived in the design when processing heterogeneous clutter. La operación de los radares costeros y oceánicos se ve afectada porque los blancos se encuentran embebidos en un fondo de clutter marino. De acuerdo con el criterio de Neyman-Pearson, los detectores de radar siempre buscan garantizar un valor determinado de probabilidad de falsa alarma antes de mejorar otras variables del sistema. Utilizando la herramienta matemática MATLAB, los autores evaluaron el desempeño de los procesadores CA, OS, MSCA, AND, OR e IS-CFAR con respecto al mantenimiento de la probabilidad de falsa alarma concebida a priori en el diseño. Luego de someter los esquemas a diferentes perfiles de prueba con clutter distribuido Rayleigh, se concluyó que la mayoría de las alternativas presentan problemas ante determinadas situaciones que pueden aparecer con relativa frecuencia en ambientes reales. Consecuentemente, se ofrecen recomendaciones sobre cuál es el mejor esquema para emplear y garantizar una desviación reducida de la probabilidad de falsa alarma operacional con respecto a la de diseño cuando se enfrenta clutter heterogéneo

Analítica del Aprendizaje y Gamificación para Fortalecer la habilidad “Reading” en la asignatura de Inglés.

This research addressed the problem of the lack of reading skills in the subject of English in tenth grade elementary school students. The main objective was to analyze how gamification, supported by learning analytics, could contribute to improve reading skills. The methodology used was quantitative with a positivist approach using statistical and theoretical methods. Two groups were formed: an experimental group that used the Quizizz gamification platform and a control group that followed traditional methods. Formative assessments focused on English text comprehension were conducted throughout the leveling. Gamification data was collected and personalized feedback was provided based on learning analytics. Results showed a significant increase in reading performance in the experimental group compared to the control group. Students who participated in gamification obtained higher scores and showed greater engagement in learning English. This study demonstrates that gamification, supported by learning analytics, can be an effective strategy for improving reading skills in learning English. This has a positive impact on the quality of education and the development of students' language skills.En esta investigación, se abordó el problema de la falta de destreza en la lectura en la asignatura de inglés en estudiantes de décimo año de básica superior. El objetivo principal fue analizar cómo la gamificación, apoyada en la analítica del aprendizaje, podría contribuir a mejorar la habilidad Reading. La metodología abordada fue la cuantitativa con un enfoque positivista con métodos estadísticos y teóricos. Se formaron dos grupos: uno experimental que utilizó la plataforma de gamificación Quizizz y otro de control que siguió métodos tradicionales. Se realizaron evaluaciones formativas centradas en la comprensión de textos en inglés a lo largo de la nivelación. Se recopilaron datos de juego y se proporcionó retroalimentación personalizada basada en la analítica del aprendizaje. Los resultados mostraron un aumento significativo en el desempeño de lectura en el grupo experimental en comparación con el grupo de control. Los estudiantes que participaron en la gamificación obtuvieron puntuaciones más altas y mostraron un mayor compromiso con el aprendizaje del inglés. Este estudio demuestra que la gamificación, respaldada por la analítica del aprendizaje, puede ser una estrategia efectiva para mejorar las habilidades de lectura en el aprendizaje del inglés. Esto tiene un impacto positivo en la calidad de la educación y en el desarrollo de habilidades lingüísticas de los estudiantes

Adiponectin, leptin, and IGF-1 are useful diagnostic and stratification biomarkers of NAFLD

[EN] Background: Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease where liver biopsy remains the gold standard for diagnosis. Here we aimed to evaluate the role of circulating adiponectin, leptin, and insulin-like growth factor 1 (IGF-1) levels as non-invasive NAFLD biomarkers and assess their correlation with the metabolome. Materials and Methods: Leptin, adiponectin, and IGF-1 serum levels were measured by ELISA in two independent cohorts of biopsy-proven obese NAFLD patients and healthy-liver controls (discovery: 38 NAFLD, 13 controls; validation: 194 NAFLD, 31 controls) and correlated with clinical data, histology, genetic parameters, and serum metabolomics. Results: In both cohorts, leptin increased in NAFLD vs. controls (discovery: AUROC 0.88; validation: AUROC 0.83; p < 0.0001). The leptin levels were similar between obese and non-obese healthy controls, suggesting that obesity is not a confounding factor. In the discovery cohort, adiponectin was lower in non-alcoholic steatohepatitis (NASH) vs. non-alcoholic fatty liver (AUROC 0.87; p < 0.0001). For the validation cohort, significance was attained for homozygous for PNPLA3 allele c.444C (AUROC 0.63; p < 0.05). Combining adiponectin with specific serum lipids improved the assay performance (AUROC 0.80; p < 0.0001). For the validation cohort, IGF-1 was lower with advanced fibrosis (AUROC 0.67, p<0.05), but combination with international normalized ratio (INR) and ferritin increased the assay performance (AUROC 0.81; p < 0.01). Conclusion: Serum leptin discriminates NAFLD, and adiponectin combined with specific lipids stratifies NASH. IGF-1, INR, and ferritin distinguish advanced fibrosis.CR was funded by FEDER through the COMPETE program and by national funds through Fundação para a Ciência e a Tecnologia (PTDC/MED-FAR/29097/2017—LISBOA-01- 0145-FEDER-029097) and by European Horizon 2020 (H2020- MSCA-RISE-2016-734719). This work was also supported by Fundação para a Ciência e Tecnologia (PD/BD/135467/2017) and Portuguese Association for the Study of Liver/MSD 2017. JB was funded by Spanish Carlos III Health Institute (ISCIII) (PI15/01132, PI18/01075 and Miguel Servet Program CON14/00129 and CPII19/00008), co-financed by Fondo Europeo de Desarrollo Regional (FEDER), Instituto de Salud Carlos III (CIBERehd, Spain), La Caixa Scientific Foundation (HR17-00601), Fundación Científica de la Asociación Española Contra el Cáncer, and European Horizon 2020 (ESCALON project: H2020-SC1-BHC-2018-2020)

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field