Fully 3D refraction correction dosimetry system

The irradiation of selective regions in a polymer gel dosimeter results in an increase in optical density and refractive index (RI) at those regions. An optical tomography-based dosimeter depends on rayline path through the dosimeter to estimate and reconstruct the dose distribution. The refraction of light passing through a dose region results in artefacts in the reconstructed images. These refraction errors are dependant on the scanning geometry and collection optics. We developed a fully 3D image reconstruction algorithm, algebraic reconstruction technique-refraction correction (ART-rc) that corrects for the refractive index mismatches present in a gel dosimeter scanner not only at the boundary, but also for any rayline refraction due to multiple dose regions inside the dosimeter. In this study, simulation and experimental studies have been carried out to reconstruct a 3D dose volume using 2D CCD measurements taken for various views. The study also focuses on the effectiveness of using different refractive-index matching media surrounding the gel dosimeter. Since the optical density is assumed to be low for a dosimeter, the filtered backprojection is routinely used for reconstruction. We carry out the reconstructions using conventional algebraic reconstruction (ART) and refractive index corrected ART (ART-rc) algorithms. The reconstructions based on FDK algorithm for cone-beam tomography has also been carried out for comparison. Line scanners and point detectors, are used to obtain reconstructions plane by plane. The rays passing through dose region with a RI mismatch does not reach the detector in the same plane depending on the angle of incidence and RI. In the fully 3D scanning setup using 2D array detectors, light rays that undergo refraction are still collected and hence can still be accounted for in the reconstruction algorithm. It is found that, for the central region of the dosimeter, the usable radius using ART-rc algorithm with water as RI matched medium is 71.8%, an increase of 6.4% compared to that achieved using conventional ART algorithm. Smaller diameter dosimeters are scanned with dry air scanning by using a wide-angle lens that collects refracted light. The images reconstructed using cone beam geometry is seen to deteriorate in some planes as those regions are not scanned. Refraction correction is important and needs to be taken in to consideration to achieve quantitatively accurate dose reconstructions. Refraction modeling is crucial in array based scanners as it is not possible to identify refracted rays in the sinogram space.

l(1)-K-SVD: A robust dictionary learning algorithm with simultaneous update

We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

A Stochastic Approximation Algorithm for Quantile Estimation

In this paper, we present two new stochastic approximation algorithms for the problem of quantile estimation. The algorithms uses the characterization of the quantile provided in terms of an optimization problem in 1]. The algorithms take the shape of a stochastic gradient descent which minimizes the optimization problem. Asymptotic convergence of the algorithms to the true quantile is proven using the ODE method. The theoretical results are also supplemented through empirical evidence. The algorithms are shown to provide significant improvement in terms of memory requirement and accuracy.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

A Novel Approach for Multispectral Satellite Image Classification Based on the Bat Algorithm

Among the multiple advantages and applications of remote sensing, one of the most important uses is to solve the problem of crop classification, i.e., differentiating between various crop types. Satellite images are a reliable source for investigating the temporal changes in crop cultivated areas. In this letter, we propose a novel bat algorithm (BA)-based clustering approach for solving crop type classification problems using a multispectral satellite image. The proposed partitional clustering algorithm is used to extract information in the form of optimal cluster centers from training samples. The extracted cluster centers are then validated on test samples. A real-time multispectral satellite image and one benchmark data set from the University of California, Irvine (UCI) repository are used to demonstrate the robustness of the proposed algorithm. The performance of the BA is compared with two other nature-inspired metaheuristic techniques, namely, genetic algorithm and particle swarm optimization. The performance is also compared with the existing hybrid approach such as the BA with K-means. From the results obtained, it can be concluded that the BA can be successfully applied to solve crop type classification problems.

Application of the Conjugate Gradient Optimization Algorithm of Neural Network on Laser Machining

在应用激光技术加工复杂曲面时,通常以采样点集为插值点来建立曲面函数,然后实现曲面上任意坐标点的精确定位。人工神经网络的BP算法能实现函数插值,但计算精度偏低,往往达不到插值精确要求,造成较大的加工误差。提出人工神经网络的共轭梯度最优化插值新算法,并通过实例仿真,证明了这种曲面精确定位方法的可行性,从而为激光加工的三维精确定位提供了一种良好解决方案。这种方法已经应用在实际中。

A quality-guided displacement tracking algorithm for ultrasonic elasticity imaging.

Displacement estimation is a key step in the evaluation of tissue elasticity by quasistatic strain imaging. An efficient approach may incorporate a tracking strategy whereby each estimate is initially obtained from its neighbours' displacements and then refined through a localized search. This increases the accuracy and reduces the computational expense compared with exhaustive search. However, simple tracking strategies fail when the target displacement map exhibits complex structure. For example, there may be discontinuities and regions of indeterminate displacement caused by decorrelation between the pre- and post-deformation radio frequency (RF) echo signals. This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator. Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.

Simulating shock to detonation transition: Algorithm and results

An algorithm based on flux-corrected transport and the Lagrangian finite element method is presented for solving the problem of shock dynamics. It is verified through the model problem of one-dimensional strain elastoplastic shock wave propagation that the algorithm leads to stable, non-oscillatory results. Shock initiation and detonation wave propagation is simulated using the algorithm, and some interesting results are obtained. (C) 1999 Academic Press.

Sistematización de la información sobre dendroenergía existente en la región del Pacífico y Central de Nicaragua, período 1993-2012

La leña es la forma más simple de biomasa utilizada en los hogares del mundo. En Nicaragua, casi el cincuenta por ciento de los nicaragüenses cocinan con leña y carbón. Esta demanda de leña ha provocado sobre explotación del bosque seco del Pacifico de Nicaragua, ocasionando degradación progresiva del bosque. La información dendroenergética de los focos de producción de leña se encuentra dispersa y desorganizada, esto justifica la realización del presente estudio de sistematización, que servirá para establecer lineamientos básicos sobre las pautas a seguir al momento de la planificación, seguimiento y evaluación de proyectos y/o programas dendroenergéticos. La información se recolectó a través de entrevistas dirigidas a responsables administrativos o técnicos de cada entidad relevante del sector dendroenerg ético. Adicionalmente se recolectó información bibliográfica de documentos físicos y electrónicos. La información se organizó en cuatro tópicos: Leyes/políticas: se identificó la necesidad de la formulación y adición de leyes y/o políticas que promuevan y faciliten la inversión en proyectos de generación eléctrica renovable; Investigaciones/estudios/publicaciones: se observa buena cantidad de investigaciones y documentos educativos, sin embargo, están desactualizados y sin contenido ambiental completo; Organización, poca vinculación de las instancias gubernamentales del sector con los actores locales como las asociaciones, cooperativas y productores individuales; Producción/comercialización, limitada a actividades de plantación y producción de plántulas con fines energéticos. En conclusión, el sector dendroenergético en Nicaragua es poco atractivo a la inversión por los procedimientos administrativos, las normas jurídicas y la falta de mecanismos de incentivos y créditos. Las cooperativas y asociaciones no están bien vinculadas entre ellas, lo que no les permite incidir en políticas a favor del sector. Sin embargo, se detectan aspectos positivos, como La Estrategia de Leña y Carbón y la inserción en muchos hogares de las estufas mejoradas como mecanismo de ahorro dendroenergético.

Caracterización de sistemas de producción ganadera en las Comarcas de Copalar y San Pedro del Norte, Municipio de Bocanas de Paiwás, Zelaya Central

El presente trabajo se realizó con el objetivo de contribuir al desarrollo ganadero del micro región por medio de la caracterización de las actividades ganaderas de las Comarcas de Copalar y San Pedro del norte. El estudio se llevó a cabo en dos fases: Una fase preliminar de “diagnóstico, en la que se determinó, la disponibilidad y uso actual de los recursos en las fincas, tecnologías y características generales de los canales de comercialización y precios de los productos pecuarios generados por la actividad ganadera de las Comarcas. La segunda fase comprendió el procesamiento y computación de la información. La información relativa a los recursos pecuarios se procesó para cada uno de los eslabones de la cadena y en base a ello se estimaron los diferentes parámetros técnicos, productivos, reproductivos y elementos fuentes de ingresos y egresos determinándose así la rentabilidad de cada uno de los eslabones de la cadena. En los aspectos técnicos se determinó que la actividad de las fincas es la ganadería; ya que en promedio, el 92% de las áreas totales se destinan a esta actividad; existiendo solamente pastos naturales. Las cargas animales encontradas fluctuaron en un rango de 0.24 u.a/mz a 0.49 u.a/mz, siendo inferiores a las disponibilidades de pastos ; resultando las disponibilidades positivas. Las especies de pastos encontrados en mayor proporción en estas fincas son Asia (Panicum maximum) y Retana (Ischaemun indicum). En cuanto al manejo de potreros; encontramos que presentan un área promedio por potrero entre 27-29 mz. y realizan rotación de potreros cada 15-30 días. En relación al control de maleza se realizan chapeas más rondas dos veces al año y quemas cada dos, tres años.

Estudio descriptivo de hembras bovinas gestantes sacrificadas en el Matadero Central S.A. "MACESA", Juigalpa, Nicaragua

El presente estudio se realizó con el objetivo de Generar información útil para determinar el impacto económico del sacrificio de hembras gestantes en el Matadero Central S.A. MACESA en Juigalpa, Chontales. Se realizó un estudio observacional de tipo transversal que mide la prevalencia de la enfermedad, y por eso suelen denominarse estudios d e prevalencia. Se tomaron todas las hembras sacrificadas en el matadero desde enero a junio 2007. Obteniéndose los siguientes resultados; de un total de 45,325 animales sacrificados de ambos sexos, correspondió a hembras un 13,6 % y de estas la prevalencia de gestantes fue del 34.43%. Del total de vacas gestantes sacrificadas, el 49.4% se encontraba en el primer tercio de la gestación, 37.5% en el segundo tercio y 13.04% en el tercer tercio respectivamente. Las patologías encontradas fueron, quistes ováricos, infantilismo, cérvix desviada, endometritis , maceración fetal y prolapso vaginal, por orden de importancia. Se deja de percibir la cantidad de $5, 301,376 dólares americanos, por sacrificar hembras gestantes y disminución del hato nacional en 12,260 animales.

A species conserving genetic algorithm for multimodal function optimization

This paper introduces a new technique called species conservation for evolving parallel subpopulations. The technique is based on the concept of dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the species seed. Species seeds found in the current generation are saved (conserved) by moving them into the next generation. Our technique has proved to be very effective in finding multiple solutions of multimodal optimization problems. We demonstrate this by applying it to a set of test problems, including some problems known to be deceptive to genetic algorithms.