Percepción logística empresarial de los sectores productivos agrícola y textil en Colombia

Desde el año 2007 se ha venido presentando un crecimiento progresivo en Colombia, donde la participación del comercio exterior en el PIB (Producto Interno Bruto) ha aumentado, según cifras del Departamento Nacional de Planeación (DNP). En contraste a esto, Colombia últimamente se ha caracterizado por presentar falencias en su desempeño logístico, las cuales se ven reflejadas en el LPI (Logistics Performance Index), una herramienta desarrollada por el Banco Mundial que mide el desempeño de la cadena de suministro de un país. El Gobierno y sus ministerios han velado por mejorar la competitividad del país, y advierten una serie de tratados y acuerdos internacionales que facilitarán el intercambio de productos junto con el fortalecimiento de la industria; a lo cual, las empresas colombianas deberán encaminar sus esfuerzos y al interior de la organización deberán tomar partida en cuanto a la capacitación del personal en temas logísticos, la administración de los costos y la eficiencia en los procesos. Así pues, mediante la realización de un estudio de la percepción que tienen los empresarios actuales en materia de logística, donde se evalúan distintas variables relacionadas con la administración de la cadena de suministro; se podrá entender holísticamente la problemática del sector, específicamente de los sectores agrícola y textil: dos sectores influyentes en el PIB nacional, generadores de empleo y con una gran cantidad de empresas asociadas. Igualmente, proponer medidas de mejora cercanas a la realidad, que contribuyan con el buen desempeño de las empresas en todo el curso de su cadena de suministro, con actividades involucradas como la planeación, las compras, el abastecimiento, las operaciones, la producción, el almacenamiento, los despachos y la distribución. Finalmente, se logrará tener un acercamiento al perfil logístico que deberán tener estas empresas en el marco de la competitividad, contando con herramientas que de una u otra manera permitan a los empresarios la toma de decisiones acertadas en pro de la organización y sus partes interesadas.

Protocolo interno para la oferta de bienes y servicios y contratación de mano de obra de las comunidades

Los actores involucrados dentro de los proyectos de exploración y perforación de pozos petroleros son variados y tienen necesidades diferentes. El éxito y satisfactorio desarrollo de los proyectos va ligado en gran medida a temas de orden social entre los diferentes actores, que están definidos por regulaciones legislativas, de costumbres comerciales y culturales, políticas de responsabilidad social y procedimientos internos de las compañías involucradas (Operadoras, Prestadoras de Servicios Petroleros, Contratistas y Subcontratistas) Después de analizar la situación de la industria, los resultados de Halliburton SRL Sucursal Colombia, los problemas y sobrecostos generados por temas de orden social. Se identificó que la mayoría de ellos eran causados por falta de comunicación, desconocimiento de elementos clave de las políticas de responsabilidad social de los clientes, desconocimiento de la importancia de la responsabilidad social como práctica y desconocimiento de la normatividad legal vigente aplicable a la industria y a la actividad que desarrolla la compañía. De las necesidades y problemáticas descritas anteriormente surge la idea de crear una herramienta que permita llenar los vacíos de información identificados, alinear a las partes involucradas dentro del proceso y ser una guía para el inicio, desarrollo y cierre de proyectos de exploración y perforación de pozos petroleros que desarrolle Halliburton con sus clientes.

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

A new all-round density functional based on spin states and SN2 barriers

We report here a new empirical density functional that is constructed based on the performance of OPBE and PBE for spin states and SN 2 reaction barriers and how these are affected by different regions of the reduced gradient expansion. In a previous study [Swart, Sol̀, and Bickelhaupt, J. Comput. Methods Sci. Eng. 9, 69 (2009)] we already reported how, by switching between OPBE and PBE, one could obtain both the good performance of OPBE for spin states and reaction barriers and that of PBE for weak interactions within one and the same (SSB-sw) functional. Here we fine tuned this functional and include a portion of the KT functional and Grimme's dispersion correction to account for π- π stacking. Our new SSB-D functional is found to be a clear improvement and functions very well for biological applications (hydrogen bonding, π -π stacking, spin-state splittings, accuracy of geometries, reaction barriers)

Admission control schemes for TCP elastic traffic in class-based networks

En aquesta tesi proposem dos esquemes de xarxa amb control d'admissió per al trànsit elàstic TCP amb mecanismes senzills. Ambdós esquemes són capaços de proporcionar throughputs diferents i aïllament entre fluxos, on un "flux" es defineix com una seqüència de paquets relacionats dins d'una connexió TCP. Quant a l'arquitectura, ambdós fan servir classes de paquets amb diferents prioritats de descart, i un control d'admissió implícit, edge-to-edge i basat en mesures. En el primer esquema, les mesures són per flux, mentre que en el segon, les mesures són per agregat. El primer esquema aconsegueix un bon rendiment fent servir una modificació especial de les fonts TCP, mentre que el segon aconsegueix un bon rendiment amb fonts TCP estàndard. Ambdós esquemes han estat avaluats satisfactòriament a través de simulació en diferents topologies de xarxa i càrregues de trànsit.

A formalization for multi-agent decision support in cooperative environments. A framework for situated agents

La tesis propone un marco de trabajo para el soporte de la toma de decisiones adecuado para soportar la ejecución distribuida de acciones cooperativas en entornos multi-agente dinámicos y complejos. Soporte para la toma de decisiones es un proceso que intenta mejorar la ejecución de la toma de decisiones en escenarios cooperativos. Este proceso ocurre continuamente en la vida diaria. Los humanos, por ejemplo, deben tomar decisiones acerca de que ropa usar, que comida comer, etc. En este sentido, un agente es definido como cualquier cosa que está situada en un entorno y que actúa, basado en su observación, su interpretación y su conocimiento acerca de su situación en tal entorno para lograr una acción en particular.Por lo tanto, para tomar decisiones, los agentes deben considerar el conocimiento que les permita ser consientes en que acciones pueden o no ejecutar. Aquí, tal proceso toma en cuenta tres parámetros de información con la intención de personificar a un agente en un entorno típicamente físico. Así, el mencionado conjunto de información es conocido como ejes de decisión, los cuales deben ser tomados por los agentes para decidir si pueden ejecutar correctamente una tarea propuesta por otro agente o humano. Los agentes, por lo tanto, pueden hacer mejores decisiones considerando y representando apropiadamente tal información. Los ejes de decisión, principalmente basados en: las condiciones ambientales, el conocimiento físico y el valor de confianza del agente, provee a los sistemas multi-agente un confiable razonamiento para alcanzar un factible y exitoso rendimiento cooperativo.Actualmente, muchos investigadores tienden a generar nuevos avances en la tecnología agente para incrementar la inteligencia, autonomía, comunicación y auto-adaptación en escenarios agentes típicamente abierto y distribuidos. En este sentido, esta investigación intenta contribuir en el desarrollo de un nuevo método que impacte tanto en las decisiones individuales como colectivas de los sistemas multi-agente. Por lo tanto, el marco de trabajo propuesto ha sido utilizado para implementar las acciones concretas involucradas en el campo de pruebas del fútbol robótico. Este campo emula los juegos de fútbol real, donde los agentes deben coordinarse, interactuar y cooperar entre ellos para solucionar tareas complejas dentro de un escenario dinámicamente cambiante y competitivo, tanto para manejar el diseño de los requerimientos involucrados en las tareas como para demostrar su efectividad en trabajos colectivos. Es así que los resultados obtenidos tanto en el simulador como en el campo real de experimentación, muestran que el marco de trabajo para el soporte de decisiones propuesto para agentes situados es capaz de mejorar la interacción y la comunicación, reflejando en un adecuad y confiable trabajo en equipo dentro de entornos impredecibles, dinámicos y competitivos. Además, los experimentos y resultados también muestran que la información seleccionada para generar los ejes de decisión para situar a los agentes, es útil cuando tales agentes deben ejecutar una acción o hacer un compromiso en cada momento con la intención de cumplir exitosamente un objetivo colectivo. Finalmente, algunas conclusiones enfatizando las ventajas y utilidades del trabajo propuesto en la mejora del rendimiento colectivo de los sistemas multi-agente en situaciones tales como tareas coordinadas y asignación de tareas son presentadas.

Evaluation of forest snow processes models (SnowMIP2)

Thirty‐three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation phase and duration of above‐freezing air temperatures are shown to be major influences on divergence and convergence of modeled estimates of the subcanopy snowpack. When models are considered collectively at all locations, comparisons with observations show that it is harder to model SWE at forested sites than open sites. There is no universal “best” model for all sites or locations, but comparison of the consistency of individual model performances relative to one another at different sites shows that there is less consistency at forest sites than open sites, and even less consistency between forest and open sites in the same year. A good performance by a model at a forest site is therefore unlikely to mean a good model performance by the same model at an open site (and vice versa). Calibration of models at forest sites provides lower errors than uncalibrated models at three out of four locations. However, benefits of calibration do not translate to subsequent years, and benefits gained by models calibrated for forest snow processes are not translated to open conditions.

Lag-1 sparing in the attentional blink: benefits and costs of integrating two events into a single episode

When people monitor a visual stream of rapidly presented stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset-the attentional blink. However, if T2 immediately follows T1, performance is often reported being as good as that at long lags-the so-called Lag-1 sparing effect. Two experiments investigated the mechanisms underlying this effect. Experiment 1 showed that, at Lag 1, requiring subjects to correctly report both identity and temporal order of targets produces relatively good performance on T2 but relatively bad performance on T1. Experiment 2 confirmed that subjects often confuse target order at short lags, especially if the two targets are equally easy to discriminate. Results suggest that, if two targets appear in close succession, they compete for attentional resources. If the two competitors are of unequal strength the stronger one is more likely to win and be reported at the expense of the other. If the two are equally strong, however, they will often be integrated into the same attentional episode and thus get both access to attentional resources. But this comes with a cost, as it eliminates information about the targets' temporal order.

Cooperative transport of extended payloads

In this paper we present experimental results for the dual robot transport of an extended payload. Two robotic rovers that were designed specifically for the extended payload transport task are described. Each rover incorporates a 4-DOF robot arm incorporating three active joints (one of which is a gripper), a passive wrist, and a mobile base which employs a rocker-bogie design. A set of behaviours has been developed to support the performance of the task, integrating simple sensing with controls. We describe the behaviours and their integration within the overall task structure. The experimental results presented focus on the manipulation elements of the task, but incorporate a complete cycle of pick-up, traversal, and putdown.

RBF equalizer design using directional evolutionary multi-objective optimization

Whilst radial basis function (RBF) equalizers have been employed to combat the linear and nonlinear distortions in modern communication systems, most of them do not take into account the equalizer's generalization capability. In this paper, it is firstly proposed that the. model's generalization capability can be improved by treating the modelling problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets. Then, as a modelling application, a new RBF equalizer learning scheme is introduced based on the directional evolutionary MOO (EMOO). Directional EMOO improves the computational efficiency of conventional EMOO, which has been widely applied in solving MOO problems, by explicitly making use of the directional information. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good performance not only on explaining the training samples but on predicting the unseen samples.

Nonlinear channel equalizer design using directional evolutionary multi-objective optimization

In this paper, a new equalizer learning scheme is introduced based on the algorithm of the directional evolutionary multi-objective optimization (EMOO). Whilst nonlinear channel equalizers such as the radial basis function (RBF) equalizers have been widely studied to combat the linear and nonlinear distortions in the modern communication systems, most of them do not take into account the equalizers' generalization capabilities. In this paper, equalizers are designed aiming at improving their generalization capabilities. It is proposed that this objective can be achieved by treating the equalizer design problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets, followed by deriving equalizers with good capabilities of recovering the signals for all the training sets. Conventional EMOO which is widely applied in the MOO problems suffers from disadvantages such as slow convergence speed. Directional EMOO improves the computational efficiency of the conventional EMOO by explicitly making use of the directional information. The new equalizer learning scheme based on the directional EMOO is applied to the RBF equalizer design. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good generalization capabilities, i.e., good performance on predicting the unseen samples.

Polymorphisms in dopamine system genes are associated with individual differences in attention in infancy

Knowledge about the functional status of the frontal cortex in infancy is limited. This study investigated the effects of polymorphisms in four dopamine system genes on performance in a task developed to assess such functioning, the Freeze-Frame task, at 9 months of age. Polymorphisms in the catechol-O-methyltransferase (COMT) and the dopamine D4 receptor (DRD4) genes are likely to impact directly on the functioning of the frontal cortex, whereas polymorphisms in the dopamine D2 receptor (DRD2) and dopamine transporter (DAT1) genes might influence frontal cortex functioning indirectly via strong frontostriatal connections. A significant effect of the COMT valine158methionine (Val158Met) polymorphism was found. Infants with the Met/Met genotype were significantly less distractible than infants with the Val/Val genotype in Freeze-Frame trials presenting an engaging central stimulus. In addition, there was an interaction with the DAT1 3′ variable number of tandem repeats polymorphism; the COMT effect was present only in infants who did not have two copies of the DAT1 10-repeat allele. These findings indicate that dopaminergic polymorphisms affect selective aspects of attention as early as infancy and further validate the Freeze-Frame task as a frontal cortex task.

Highly accurate detection of ovarian cancer using CA125 but limited improvement with serum matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling

Objectives: Our objective was to test the performance of CA125 in classifying serum samples from a cohort of malignant and benign ovarian cancers and age-matched healthy controls and to assess whether combining information from matrix-assisted laser desorption/ionization (MALDI) time-of-flight profiling could improve diagnostic performance. Materials and Methods: Serum samples from women with ovarian neoplasms and healthy volunteers were subjected to CA125 assay and MALDI time-of-flight mass spectrometry (MS) profiling. Models were built from training data sets using discriminatory MALDI MS peaks in combination with CA125 values and tested their ability to classify blinded test samples. These were compared with models using CA125 threshold levels from 193 patients with ovarian cancer, 290 with benign neoplasm, and 2236 postmenopausal healthy controls. Results: Using a CA125 cutoff of 30 U/mL, an overall sensitivity of 94.8% (96.6% specificity) was obtained when comparing malignancies versus healthy postmenopausal controls, whereas a cutoff of 65 U/mL provided a sensitivity of 83.9% (99.6% specificity). High classification accuracies were obtained for early-stage cancers (93.5% sensitivity). Reasons for high accuracies include recruitment bias, restriction to postmenopausal women, and inclusion of only primary invasive epithelial ovarian cancer cases. The combination of MS profiling information with CA125 did not significantly improve the specificity/accuracy compared with classifications on the basis of CA125 alone. Conclusions: We report unexpectedly good performance of serum CA125 using threshold classification in discriminating healthy controls and women with benign masses from those with invasive ovarian cancer. This highlights the dependence of diagnostic tests on the characteristics of the study population and the crucial need for authors to provide sufficient relevant details to allow comparison. Our study also shows that MS profiling information adds little to diagnostic accuracy. This finding is in contrast with other reports and shows the limitations of serum MS profiling for biomarker discovery and as a diagnostic tool

H∞ robust control design for unsupported paraplegic standing: experimental evaluation

This paper is concerned with the design of robust feedback H~-control systems for the control of the upright posture of paraplegic persons standing. While the subject stands in a special apparatus, stabilising torque at the ankle joint is generated by electrical stimulation of the paralyzed calf muscles. Since the muscles acting as actuators in this setup show a significant degree of nonlinearity, a robust H~-control design is used. The design approach is implemented in experiments with a paraplegic subject. The results demonstrate good performance and closed loop stability over the whole range of operation.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.