Search results for "Artificial"
showing 10 items of 7394 documents
An Innovative Similarity Measure for Sentence Plagiarism Detection
2016
We propose and experimentally assess Semantic Word Error Rate (SWER), an innovative similarity measure for sentence plagiarism detection. SWER introduces a complex approach based on latent semantic analysis, which is capable of outperforming the accuracy of competitor methods in plagiarism detection. We provide principles and functionalities of SWER, and we complement our analytical contribution by means of a significant preliminary experimental analysis. Derived results are promising, and confirm to use the goodness of our proposal.
Effects of Topic Familiarity on Analogical Transfer in Problem-Solving: A Think-Aloud Study of Two Singular Cases
2015
We conducted a qualitative research of case studies based on think-aloud protocols. The aim was to carry out in-depth analyse secondary students¿ cognitive difficulties appearing in early stages of transfer processes in problem-solving. The task was to relate several source problems to a target problem, in order to solve it effectively. Source and target problems had different Surface and/or Structural similarities. In this paper, the solvers¿ high or low Familiarity with the problem stories on transfer processes was also focused on. Two emergent instructional phenomena are described, both associated to specific students¿ cognitive obstacles to achieve success in solving the target problem:…
Randomized Hough Transform for Ellipse Detection with Result Clustering
2005
Our research is focused on the development of robust machine vision algorithms for pattern recognition. We want to provide robotic systems the ability to understand more on the external real world. In this paper, we describe a method for detecting ellipses in real world images using the randomized Hough transform with result clustering. A preprocessing phase is used in which real world images are transformed - noise reduction, greyscale transform, edge detection and final binarization - in order to be processed by the actual ellipse detector. The ellipse detector filters out false ellipses that may interfere with the final results. Due to the fact that usually more "virtual" ellipses are de…
Adaptive treatment of anemia on hemodialysis patients: A reinforcement learning approach
2011
The aim of this work is to study the applicability of reinforcement learning methods to design adaptive treatment strategies that optimize, in the long-term, the dosage of erythropoiesis-stimulating agents (ESAs) in the management of anemia in patients undergoing hemodialysis. Adaptive treatment strategies are recently emerging as a new paradigm for the treatment and long-term management of the chronic disease. Reinforcement Learning (RL) can be useful to extract such strategies from clinical data, taking into account delayed effects and without requiring any mathematical model. In this work, we focus on the so-called Fitted Q Iteration algorithm, a RL approach that deals with the data very…
Three-dimensional object detection under arbitrary lighting conditions
2006
A novel method of 3D object recognition independent of lighting conditions is presented. The recognition model is based on a vector space representation using an orthonormal basis generated by the Lambertian reflectance functions obtained with distant light sources. Changing the lighting conditions corresponds to multiplying the elementary images by a constant factor and because of that, all possible lighting views will be elements that belong to that vector space. The recognition method proposed is based on the calculation of the angle between the vector associated with a certain illuminated 3D object and that subspace. We define the angle in terms of linear correlations to get shift and i…
Prediction Model Selection and Spare Parts Ordering Policy for Efficient Support of Maintenance and Repair of Equipment
2010
The prediction model selection problem via variable subset selection is one of the most pervasive model selection problems in statistical applications. Often referred to as the problem of subset selection, it arises when one wants to model the relationship between a variable of interest and a subset of potential explanatory variables or predictors, but there is uncertainty about which subset to use. Several papers have dealt with various aspects of the problem but it appears that the typical regression user has not benefited appreciably. One reason for the lack of resolution of the problem is the fact that it has not been well defined. Indeed, it is apparent that there is not a single probl…
Computer vision and thermal monitoring of HMPE fibre rope condition during CBOS testing
2020
Abstract Fibre rope usage in deep sea lifting operations is gaining more prominence in recent times. With rope minimum break loads (MBL) comparable to that of their steel wire counterparts, the use of high modulus polyethylene (HMPE) ropes is seen as a viable option for use in subsea construction cranes. The ropes are worn out during use and visual inspection remains one of the main methods of determining whether a fibre rope is to be retired from use, therefore a natural extension is condition monitoring through computer vision. Creep and temperature are constraining with HMPE ropes and should be monitored continuously, particularly when the rope is cyclically bent over sheaves. Additional…
Introducing the Concept of Hyperactivity in Multi Agent Systems
2013
International audience; Software Agents are no longer the simple communication gateways for devices to interconnect using one or more networks. With Multi Agent Systems contributing in a wide spectrum of intelligent systems, the Agents are in a more proactive role than just being responsible for passing messages between their respective base systems. Agent Relation Charts and the Hyperactive Transaction Model in general is one of the recent attempts of developing a multi-view design model for Multi Agent Systems. The model has made a clear distinction in the regular and intelligent activities of an agent. Based on these differences, the agents are classified into three main categories named…
An Agents and Artifacts Approach to Distributed Data Mining
2013
This paper proposes a novel Distributed Data Mining (DDM) approach based on the Agents and Artifacts paradigm, as implemented in CArtAgO [9], where artifacts encapsulate data mining tools, inherited from Weka, that agents can use while engaged in collaborative, distributed learning processes. Target hypothesis are currently constrained to decision trees built with J48, but the approach is flexible enough to allow different kinds of learning models. The twofold contribution of this work includes: i) JaCA-DDM: an extensible tool implemented in the agent oriented programming language Jason [2] and CArtAgO [10,9] to experiment DDM agent-based approaches on different, well known training sets. A…
SmartSpectra: Applying multispectral imaging to industrial environments
2005
SmartSpectra is a smart multispectral system for industrial, environmental, and commercial applications where the use of spectral information beyond the visible range is needed. The SmartSpectra system provides six spectral bands in the range 400-1000nm. The bands are configurable in terms of central wavelength and bandwidth by using electronic tunable filters. SmartSpectra consists of a multispectral sensor and the software that controls the system and simplifies the acquisition process. A first prototype called Autonomous Tunable Filter System is already available. This paper describes the SmartSpectra system, demonstrates its performance in the estimation of chlorophyll in plant leaves, …