Search results for "Tree"

Process-and context-sensitive research on academic knowledge practices

2007

The Contextual Activity Sampling System (CASS) methodology and CASS-Query tools have been developed for the investigation of learning and working practices. The CASS-methods and tools provide contextualized data that allow the analyzing and modeling of within-person changes across time. This paper describes a pilot study with 3G mobiles used by eight engineering students. Students answered questionnaires concerning their ongoing study projects, academic emotions, and collaboration, with a mobile phone five times a day for a period of two weeks (70 queries per person). Variation in their emotions were examined by time-series analysis. Students were also interviewed before and after the CASS-…

Analytical approach extending the Granier method to radial sap flow patterns

2020

Abstract The Granier thermal dissipation (TD) method is probably the most applied method to compute the transpiration flux of trees, due to its simplicity and effective compromise between theory and data availability. Starting from the heat transfer equations at the basis of Granier’s method, the objective of this paper is to derive an analytical solution for the transpiration flux to extend the sap flow equations to the radial domain. We adopted a flexible approach to cope with the differences in radial sapflow density (SFD) profile shapes that are known to occur in relation to wood anatomy (diffuse porous vs. ring- or non-porous xylem). With this purpose, we investigated the robustness of…

Ant Colony Optimisation-Based Classification Using Two-Dimensional Polygons

2016

The application of Ant Colony Optimization to the field of classification has mostly been limited to hybrid approaches which attempt at boosting the performance of existing classifiers (such as Decision Trees and Support Vector Machines (SVM)) — often through guided feature reductions or parameter optimizations.

Assembly Assistance System with Decision Trees and Ensemble Learning

2021

This paper presents different prediction methods based on decision tree and ensemble learning to suggest possible next assembly steps. The predictor is designed to be a component of a sensor-based assembly assistance system whose goal is to provide support via adaptive instructions, considering the assembly progress and, in the future, the estimation of user emotions during training. The assembly assistance station supports inexperienced manufacturing workers, but it can be useful in assisting experienced workers, too. The proposed predictors are evaluated on the data collected in experiments involving both trainees and manufacturing workers, as well as on a mixed dataset, and are compared …

Learning of Cooperative Behaviour in Robot Populations

2016

This paper addresses convergence and equilibrium properties of game theoretic learning algorithms in robot populations using simple and broadly applicable reward/cost models of cooperation between robotic agents. New models for robot cooperation are proposed by combining regret based learning methods and network evolution models. Results of mean-field game theory are employed in order to show the asymptotic second moment boundedness in the variation of cooperative behaviour. The behaviour of the proposed models are tested in simulation results, which are based on sample networks and a single lane traffic flow case study.

A Hierarchical Learning Scheme for Solving the Stochastic Point Location Problem

2012

Published version of a chapter in the book: Advanced Research in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31087-4_78 This paper deals with the Stochastic-Point Location (SPL) problem. It presents a solution which is novel in both philosophy and strategy to all the reported related learning algorithms. The SPL problem concerns the task of a Learning Mechanism attempting to locate a point on a line. The mechanism interacts with a random environment which essentially informs it, possibly erroneously, if the unknown parameter is on the left or the right of a given point which also is the current guess. The first pioneering work […

2021

Classification approaches that allow to extract logical rules such as decision trees are often considered to be more interpretable than neural networks. Also, logical rules are comparatively easy to verify with any possible input. This is an important part in systems that aim to ensure correct operation of a given model. However, for high-dimensional input data such as images, the individual symbols, i.e. pixels, are not easily interpretable. Therefore, rule-based approaches are not typically used for this kind of high-dimensional data. We introduce the concept of first-order convolutional rules, which are logical rules that can be extracted using a convolutional neural network (CNN), and w…

Collision detection for 3D rigid body motion planning with narrow passages

2017

In sampling-based 3D rigid body motion planning one of the major subroutines is collision detection. Especially for problems with narrow passages many samples have to be checked by a collision detection algorithm. In this application, the runtime of the motion planning algorithm is dominated by collision detection and the samples have the very specific characteristic that many of them are in collision and have small penetration volumes. In our work, we introduce a data structure and an algorithm that makes use of this characteristic by combining well-known data structures like a distance field and an octree with the swap algorithm by Llanas et al. For 3D rigid body motion planning with narr…

Combined column-and-row-generation for the optimal communication spanning tree problem

2018

Abstract This paper considers the exact solution of the optimal communication spanning tree problem (OCSTP), which can be described as follows: Given an undirected graph with transportation costs on every edge and communication requirements for all pairs of vertices, the OCSTP seeks for a spanning tree that minimizes the sum of the communication costs between all pairs of vertices, where the communication cost of a pair of vertices is defined as their communication requirement multiplied by the transportation cost of the unique tree path that connects the two vertices. Two types of compact formulations for OCSTP were presented in the literature. The first one is a four-index model based on …

Automatic Location of Sources of Electrical Activation from Electroanatomical Maps

2016

Electro-anatomical mapping is a widely used technique used by electrophysiologists to understand patient's activation pattern. The system measures activation time at different locations but does not provide information on underlying electrical pathways or triggering points, such as Purkinje-myocardial junctions or ectopic foci. We present a method to estimate the locations of Purkinje-myocardial junctions from a discrete set of endocardial samples. Using less than 1000 endocardial samples it can recover locations and activation times of the most influencing Purkinje myocardial junctions from Purkinje trees of up to 500 junctions. A simulation study revealed that using the estimated Purkinje…