1,713 research outputs found

    A Social Approach for Target Localization: Simulation and Implementation in the marXbot Robot

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    Foraging is a common benchmark problem in collective robotics in which a robot (the forager) explores a given environment while collecting items for further deposition at specific locations. A typical real-world application of foraging is garbage collection where robots collect garbage for further disposal in pre-defined locations. This work proposes a method to cooperatively perform the task of finding such locations: instead of using local or global localization strategies relying on pre-installed infrastructure, the proposed approach takes advantage of the knowledge gathered by a population about the localization of the targets. In our approach, robots communicate in an intrinsic way the estimation about how near they are from a target; these estimations are used by neighbour robots for estimating their proximity, and for guiding the navigation of the whole population when looking for these specific areas. We performed several tests in a simulator, and we validated our approach on a population of real robots. For the validation tests we used a mobile robot called marXbot. In both cases (i.e., simulation and implementation on real robots), we found that the proposed approach efficiently guides the robots towards the pre-specified targets while allowing the modulation of their speed

    Hábitos alimenticios del pez sable Trichiurus lepturus en el Golfo de Urabá, Caribe colombiano

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    We studied the feeding habits of the commercial fish Trichiurus lepturus, a mesopredator with an important role in the energy flow in the coastal trophic webs, in order to contribute to the knowledge of its ecology, tool for its conservation, and an input for the management of fisheries in the Gulf of Urabá, northwestern Colombia. Using gillnets, 320 fish were captured, from which 208 stomachs containing food were extracted, and their contents separated and identified. The food spectrum of the species is integrated by 26 elements, belonging to three great taxonomic groups: fish, crustaceans and mollusks. Engraulid fishes are the main food component at all sampling sites, mosly Centengraulis edentulus and several Anchoa species. There was a trophic overlap among sites, and the importance of mangrove areas for feeding was evident. However, no seasonal or sex variation in diet composition was found, since Engraulids are one of the most abundant fish resources throughout the year in the Colombian Caribbean.Se estudiaron los hábitos alimenticios del pez comercial Trichiurus lepturus, un mesodepredador con un papel importante en el flujo de energía en las redes tróficas costeras, con el objeto de contribuir al conocimiento de su ecología, herramienta para su conservación e insumo para el ordenamiento pesquero del Golfo de Urabá, en el noroeste de Colombia. Usando redes de enmalle se capturaron 320 individuos, de los que se obtuvieron 208 estómagos con contenido. El espectro alimenticio de la especie está integrado por 26 ítems, pertenecientes a tres grandes grupos taxonómicos: peces, crustáceos y moluscos. Entre estos, los engráulidos (Engraulidae) son el principal componente en todos los sitios de muestreo, sobresaliendo Centengraulis edentulus y varias especies del género Anchoa. Se encontró un traslape de presas entre los sitios, siendo evidente la importancia de las áreas de manglar para alimentación. Sin embargo, no hubo variación estacional ni diferencias entre sexos en la composición de la dieta, dado que los engráulidos, su principal presa, son uno de los recursos pesqueros más abundantes en el Caribe colombiano

    Augmenting a convolutional neural network with local histograms ::a case study in crop classification from high-resolution UAV imagery

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    The advent of affordable drones capable of taking high resolution images of agricultural fields creates new challenges and opportunities in aerial scene understanding. This paper tackles the problem of recognizing crop types from aerial imagery and proposes a new hybrid neural network architecture which combines histograms and convolutional units. We evaluate the performance of the proposed model on a 23-class classification task and compare it to other models. The result is an improvement of the classification performance

    Integration of a MicroCAT Propulsion System and a PhoneSat Bus into a 1.5U CubeSat

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    NASA Ames Research Center and the George Washington University have developed an electric propulsion subsystem that can be integrated into the PhoneSat bus. Experimental tests have shown a reliable performance by firing three different thrusters at various frequencies in vacuum conditions. The three thrusters were controlled by a SmartPhone that was running the PhoneSat software. The subsystem is fully operational and it requires low average power to function (about 0.1 W). The interface consists of a microcontroller that sends a trigger pulses to the PPU (Plasma Processing Unit), which is responsible for the thruster operation. Frequencies ranging from 1 to 50Hz have been tested, showing a strong flexibility. A SmartPhone acts as the main user interface for the selection of commands that control the entire system. The micro cathode arc thruster MicroCAT provides a high 1(sub sp) of 3000s that allows a 4kg satellite to obtain a (delta)V of 300m/s. The system mass is only 200g with a total of volume of 200(cu cm). The propellant is based on a solid cylinder made of Titanium, which is the cathode at the same time. This simplicity in the design avoids miniaturization and manufacturing problems. The characteristics of this thruster allow an array of MicroCATs to perform attitude control and orbital correcton maneuvers that will open the door for the implementation of an extensive collection of new mission concepts and space applications for CubeSats. NASA Ames is currently working on the integration of the system to fit the thrusters and PPU inside a 1.5U CubeSat together with the PhoneSat bus into a 1.5U CubeSat. This satellite is intended to be deployed from the ISS in 2015 and test the functionality of the thrusters by spinning the satellite around its long axis and measure the rotational speed with the phone byros. This test flight will raise the TRL of the propulsion system from 5 to 7 and will be a first test for further CubeSats with propulsion systems, a key subsystem for long duration or interplanetary CubeSat missions

    Modular Pulsed Plasma Electric Propulsion System for Cubesats

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    Current capabilities of CubeSats must be improved in order to perform more ambitious missions. Electric propulsion systems will play a key role due to their large specific impulse. Compared to other propulsion alternatives, their simplicity allows an easier miniaturization and manufacturing of autonomous modules into the nano and pico-satellite platform. Pulsed Plasma Thrusters (PPTs) appear as one of the most promising technologies for the near term. The utilization of solid and non-volatile propellants, their low power requirements and their proven reliability in the large scale make them great candidates for rapid implementation. The main challenges are the integration and miniaturization of all the electronic circuitry into a printed circuit board (PCB) that can satisfy the strict requirements that CubeSats present. NASA Ames and the George Washington University have demonstrated functionality and control of three discrete Micro-Cathode Arc Thrusters (CAT) using a bench top configuration that was compatible with the ARC PhoneSat Bus. This demonstration was successfully conducted in a vaccum chamber at the ARC Environmental Test Laboratory. A new effort will integrate a low power Plasma Processing Unit and two plasma thrusters onto a single printed circuit board that will utilize less than 13 U of Bus volume. The target design will be optimized for the accommodation into the PhoneSatEDISON Demonstration of SmallSatellite Networks (EDSN) bus as it uses the same software interface application, which was demonstrated in the previous task. This paper describes the design, integration and architecture of the proposed propulsion subsystem for a planned Technology Demonstration Mission. In addition, a general review of the Pulsed Plasma technology available for CubeSats is presented in order to assess the necessary challenges to overcome further development

    Micro Cathode Arc Thruster for PhoneSat: Development and Potential Applications

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    NASA Ames Research Center and the George Washington University are developing an electric propulsion subsystem that will be integrated into the PhoneSat bus. Experimental tests have shown a reliable performance by firing three different thrusters at various frequencies in vacuum conditions. The interface consists of a microcontroller that sends a trigger pulse to the Pulsed Plasma Unit that is responsible for the thruster operation. A Smartphone is utilized as the main user interface for the selection of commands that control the entire system. The propellant, which is the cathode itself, is a solid cylinder made of Titanium. This simplicity in the design avoids miniaturization and manufacturing problems. The characteristics of this thruster allow an array of CATs to perform attitude control and orbital correction maneuvers that will open the door for the implementation of an extensive collection of new mission concepts and space applications for CubeSats. NASA Ames is currently working on the integration of the system to fit the thrusters and the PPU inside a 1.5U CubeSat together with the PhoneSat bus. This satellite is intended to be deployed from the ISS in 2015 and test the functionality of the thrusters by spinning the satellite around its long axis and measure the rotational speed with the phone gyros. This test flight will raise the TRL of the propulsion system from 5 to 7 and will be a first test for further CubeSats with propulsion systems, a key subsystem for long duration or interplanetary small satellite missions

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Search for new physics with dijet angular distributions in proton-proton collisions at root S = 13 TeV

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