The Benefits of Re-Evaluating Real-Time Fulfillment Decisions

At the time of a customer order, the e-tailer assigns the order to one or more of its order fulfillment centers, and/or to drop shippers, so as to minimize procurement and transportation costs, based on the available current information. However this assignment is necessarily myopic as it cannot account for all future events, such as subsequent customer orders or inventory replenishments. We examine the potential benefits from periodically re-evaluating these real-time order-assignment decisions. We construct near-optimal heuristics for the re-assignment for a large set of customer orders with the objective to minimize the total number of shipments. We investigate how best to implement these heuristics for a rolling horizon, and discuss the effect of demand correlation, customer order size, and the number of customer orders on the nature of the heuristics. Finally, we present potential saving opportunities by testing the heuristics on sets of order data from a major e-tailer.

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Bandwidth allocation based on real time calculations using the convolution approach

This paper focuses on one of the methods for bandwidth allocation in an ATM network: the convolution approach. The convolution approach permits an accurate study of the system load in statistical terms by accumulated calculations, since probabilistic results of the bandwidth allocation can be obtained. Nevertheless, the convolution approach has a high cost in terms of calculation and storage requirements. This aspect makes real-time calculations difficult, so many authors do not consider this approach. With the aim of reducing the cost we propose to use the multinomial distribution function: the enhanced convolution approach (ECA). This permits direct computation of the associated probabilities of the instantaneous bandwidth requirements and makes a simple deconvolution process possible. The ECA is used in connection acceptance control, and some results are presented

Towards a real-time vision-based navigation system for a small-class UUV

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory

A new approach to real time traffic sign recognition based on colour information

The automatic interpretation of conventional traffic signs is very complex and time consuming. The paper concerns an automatic warning system for driving assistance. It does not interpret the standard traffic signs on the roadside; the proposal is to incorporate into the existing signs another type of traffic sign whose information will be more easily interpreted by a processor. The type of information to be added is profuse and therefore the most important object is the robustness of the system. The basic proposal of this new philosophy is that the co-pilot system for automatic warning and driving assistance can interpret with greater ease the information contained in the new sign, whilst the human driver only has to interpret the "classic" sign. One of the codings that has been tested with good results and which seems to us easy to implement is that which has a rectangular shape and 4 vertical bars of different colours. The size of these signs is equivalent to the size of the conventional signs (approximately 0.4 m2). The colour information from the sign can be easily interpreted by the proposed processor and the interpretation is much easier and quicker than the information shown by the pictographs of the classic signs

Scalable real-time crisis mapping and analytics of social media streams for disaster management and breaking news

Real-time geoparsing of social media streams (e.g. Twitter, YouTube, Instagram, Flickr, FourSquare) is providing a new 'virtual sensor' capability to end users such as emergency response agencies (e.g. Tsunami early warning centres, Civil protection authorities) and news agencies (e.g. Deutsche Welle, BBC News). Challenges in this area include scaling up natural language processing (NLP) and information retrieval (IR) approaches to handle real-time traffic volumes, reducing false positives, creating real-time infographic displays useful for effective decision support and providing support for trust and credibility analysis using geosemantics. I will present in this seminar on-going work by the IT Innovation Centre over the last 4 years (TRIDEC and REVEAL FP7 projects) in building such systems, and highlights our research towards improving trustworthy and credible of crisis map displays and real-time analytics for trending topics and influential social networks during major news worthy events.

Carga viral de seis tipos de Virus del Papiloma Humano de alto riesgo y su asociacion con lesiones cervicales

Introducción: La infección por un tipo de Virus del Papiloma Humano de alto riesgo (VPH-AR), es el factor principal en el desarrollo de Cáncer de Cérvix (CC). La carga viral puede modular esta asociación, por lo que resulta importante su cuantificación y el establecimiento de su relación con lesiones precursoras de CC. Metodología: 60 mujeres con lesiones escamosas intraepiteliales (LEI) y 120 mujeres sin LEI, confirmadas por colposcopia, fueron incluidas en el estudio. Se determinó la carga viral de 6 tipos de VPH-AR, mediante PCR en tiempo real. Se estimaron OR crudos y ajustados para evaluar la asociación entre la carga viral de cada tipo y las lesiones cervicales. Resultados: 93.22% de mujeres con LEI y 91.23% de mujeres negativas, fueron positivas para al menos un tipo de VPH. VPH-18 y VPH-16 fueron los tipos más prevalentes, junto con VPH-31 en mujeres sin LEI. No se encontraron diferencias estadísticamente significativas de las cargas virales entre éstos dos grupos, aunque se observó un mayor carga viral en lesiones para algunos tipos virales. Una mayor frecuencia de lesiones se asoció a infecciones con carga baja de VPH-16 (ORa: 3.53; IC95%: 1.16 – 10.74), en comparación a mujeres con carga alta de VPH-16, (ORa: 2.63; IC95%: 1.09 – 6.36). En infecciones por VPH-31, la presencia de carga viral alta, se asoció con una menor frecuencia de lesiones (ORa: 0.34; IC95%: 0.15 – 0.78). Conclusiones: La prevalencia tipo-específica de VPH se corresponde con las reportadas a nivel mundial. La asociación entre la carga viral del VPH y la frecuencia de LEI es tipo específica y podría depender de la duración de la infección, altas cargas relacionadas con infecciones transitorias, y bajas cargas con persistentes. Este trabajo contribuye al entendimiento del efecto de la carga viral en la historia natural del CC; sin embargo, estudios prospectivos son necesarios para confirmar estos resultados.

Alteraciones en el material genético de pintores de carros expuestos a solventes orgánicos en una localidad de Bogotá

Los solventes orgánicos son sustancias químicas que por sus propiedades físico-químicas son fácilmente inhalados o absorbidos por la piel, pueden causar daños de diversa índole en la salud. En Colombia existen normas que contemplan las medidas de protección, sin embargo persiste la informalidad en el sector de pintores de autos, por lo cual los trabajadores expuestos, a largo plazo pueden ver afectada su salud. En este estudio se analizó la relación entre individuos expuestos laboralmente a los solventes orgánicos versus no expuestos con respecto a la longitud de sus telómeros y formación de fragilidades. Se emplearon muestras de sangre extraídas por venopunción, recolectada en dos tubos: uno con Heparina, destinado al cultivo de linfocitos, para obtener cromosomas metafásicos y evaluar en ellos la presencia de fragilidades; el otro tubo con EDTA, fue empleado para la extracción de ADN y se utilizó para obtener los valores de longitud telomérica mediante la técnica de PCR cuantitativa. Los análisis estadísticos se realizaron aplicando la prueba de rangos de Wilcoxon, en el caso de la presencia de fragilidades se analizó la razón No.Fragilidades/No.Metafases, aplicando el método de Wilcoxon se encontró que existe diferencia estadísticamente significativa entre expuestos y no expuestos (p = 0,036), en donde los expuestos presentan mayor frecuencia de fragilidades. Por otra parte el valor relativo de longitud telomérica del grupo de expuestos fue mayor que el observado en el grupo de no expuestos, esta diferencia fue estadísticamente significativa (Wilcoxon, p = 0.002).

Aplicaci??n del protocolo de valoraci??n del rango vocal en cantantes populares del Colegio de M??sica de Medell??n mediante el m??dulo Real Time Pitch

Resumen en ingl??s. Resumen basado en el de la publicaci??n

Integration of knowledge-based, qualitative and numeric tools for real time dynamic systems supervision

The proposal presented in this thesis is to provide designers of knowledge based supervisory systems of dynamic systems with a framework to facilitate their tasks avoiding interface problems among tools, data flow and management. The approach is thought to be useful to both control and process engineers in assisting their tasks. The use of AI technologies to diagnose and perform control loops and, of course, assist process supervisory tasks such as fault detection and diagnose, are in the scope of this work. Special effort has been put in integration of tools for assisting expert supervisory systems design. With this aim the experience of Computer Aided Control Systems Design (CACSD) frameworks have been analysed and used to design a Computer Aided Supervisory Systems (CASSD) framework. In this sense, some basic facilities are required to be available in this proposed framework: ·

Real-Time software control of neural stimulation in a closed loop Animat system

A recent area for investigation into the development of adaptable robot control is the use of living neuronal networks to control a mobile robot. The so-called Animat paradigm comprises a neuronal network (the ‘brain’) connected to an external embodiment (in this case a mobile robot), facilitating potentially robust, adaptable robot control and increased understanding of neural processes. Sensory input from the robot is provided to the neuronal network via stimulation on a number of electrodes embedded in a specialist Petri dish (Multi Electrode Array (MEA)); accurate control of this stimulation is vital. We present software tools allowing precise, near real-time control of electrical stimulation on MEAs, with fast switching between electrodes and the application of custom stimulus waveforms. These Linux-based tools are compatible with the widely used MEABench data acquisition system. Benefits include rapid stimulus modulation in response to neuronal activity (closed loop) and batch processing of stimulation protocols.