Search results for " Applications"

Assessing 4th Grade Students’ Computational Thinking through Scratch Programming Projects

2020

Computational thinking (CT) has been introduced in primary schools worldwide. However, rich classroom-based evidence and research on how to assess and support students’ CT through programming are particularly scarce. This empirical study investigates 4th grade students’ (N = 57) CT in a comparatively comprehensive and fine-grained manner by assessing their Scratch projects (N = 325) with a framework that was revised from previous studies to aim towards enhancing CT. The results demonstrate in detail the various coding patterns and code constructs the students programmed in assorted projects throughout a programming course and the extent to which they had conceptual encounters with CT. Notab…

Information flow and WOM in social media and online communities

2017

An evolutionary restricted neighborhood search clustering approach for PPI networks

2014

Protein-protein interaction networks have been broadly studied in the last few years, in order to understand the behavior of proteins inside the cell. Proteins interacting with each other often share common biological functions or they participate in the same biological process. Thus, discovering protein complexes made of a group of proteins strictly related can be useful to predict protein functions. Clustering techniques have been widely employed to detect significant biological complexes. In this paper, we integrate one of the most popular network clustering techniques, namely the Restricted Neighborhood Search Clustering (RNSC), with evolutionary computation. The two cost functions intr…

2020

Abstract Background and objective Deep learning approaches are common in image processing, but often rely on supervised learning, which requires a large volume of training images, usually accompanied by hand-crafted labels. As labelled data are often not available, it would be desirable to develop methods that allow such data to be compiled automatically. In this study, we used a Generative Adversarial Network (GAN) to generate realistic B-mode musculoskeletal ultrasound images, and tested the suitability of two automated labelling approaches. Methods We used a model including two GANs each trained to transfer an image from one domain to another. The two inputs were a set of 100 longitudina…

Feature selection using support vector machines and bootstrap methods for ventricular fibrillation detection

2012

Early detection of ventricular fibrillation (VF) is crucial for the success of the defibrillation therapy in automatic devices. A high number of detectors have been proposed based on temporal, spectral, and time-frequency parameters extracted from the surface electrocardiogram (ECG), showing always a limited performance. The combination ECG parameters on different domain (time, frequency, and time-frequency) using machine learning algorithms has been used to improve detection efficiency. However, the potential utilization of a wide number of parameters benefiting machine learning schemes has raised the need of efficient feature selection (FS) procedures. In this study, we propose a novel FS…

M-GRASP: A GRASP With Memory for Latency-Aware Partitioning Methods in DVE Systems

2009

A necessary condition for providing quality of service to distributed virtual environments (DVEs) is to provide a system response below a maximum threshold to the client computers. In this sense, latency-aware partitioning methods try to provide response times below the threshold to the maximum number of client computers as possible. These partitioning methods should find an assignment of clients to servers that optimizes system throughput, system latency, and partitioning efficiency. In this paper, we present a new algorithm based on greedy randomized adaptive search procedure with memory for finding the best solutions as possible to this problem. We take into account several different alt…

ESL ? A New Simulation Language for Economic Models

1990

A new simulation language for modelling economic processes is presented which allows the specification of single decision units and coordinates all their activities. The basic ideas and features of this language will be described and demonstrated through small examples.

Automatic place detection and localization in autonomous robotics

2007

This paper presents an approach for the simultaneous learning and recognition of places applied to autonomous robotics. While noteworthy results have been achieved with respect to off-line training process for appearance-based navigation, novel issues arise when recognition and learning are simultaneous and unsupervised processes. The approach adopted here uses a Gaussian mixture model estimated by a novel incremental MML-EM to model the probability distribution of features extracted by image-preprocessing. A place detector decides which features belong to which place integrating odometric information and a hidden Markov model. Tests demonstrate that the proposed system performs as well as …

On the advantages of combining differential algorithms and log-polar vision for detection of self-motion from a mobile robot

2001

Abstract This paper describes the design and implementation on programmable hardware (FPGAs) of an algorithm for the detection of self-mobile objects as seen from a mobile robot. In this context, ‘self-mobile’ refers to those objects that change in the image plane due to their own movement, and not to the movement of the camera on board of the mobile robot. The method consists on adapting the original algorithm from Chen and Nandhakumar [A simple scheme for motion boundary detection, in: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1994] by using foveal images obtained with a special camera whose optical axis points towards the direction of advance. It i…

Ontology-based state representations for intention recognition in human–robot collaborative environments

2013

In this paper, we describe a novel approach for representing state information for the purpose of intention recognition in cooperative human-robot environments. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. This approach is applied to a manufacturing kitting operation, where humans and robots are working together to develop kits. Based upon a set of predefined high-level state relationships that must be true for future actions to occur, a robot can use the detailed state information described in this paper to infer the probability of subsequent actions occurring. This would allow the robot to better help the …