Search results for "learning"
showing 10 items of 6669 documents
CA3–CA1 long‐term potentiation occurs regardless of respiration and cardiac cycle phases in urethane‐anesthetized rats
2023
Breathing and heartbeat synchronize to each other and to brain function and affect cognition in humans. However, it is not clear how cardiorespiratory rhythms modulate such basic processes as synaptic plasticity thought to underlie learning. Thus, we studied if respiration and cardiac cycle phases at burst stimulation onset affect hippocampal long-term potentiation (LTP) in the CA3–CA1 synapse in urethane-anesthetized adult male Sprague–Dawley rats. In a between-subjects design, we timed burst stimulation of the ventral hippocampal commissure (vHC) to systole or diastole either during expiration or inspiration and recorded responses throughout the hippocampus with a linear probe. As classic…
Sensitivity analysis of Gaussian processes for oceanic chlorophyll prediction
2015
Gaussian Process Regression (GPR) for machine learning has lately been successfully introduced for chlorophyll content mapping from remotely sensed data. The method provides a fast, stable and accurate prediction of biophysical parameters. However, since GPR is a non-linear kernel regression method, the relevance of the features are not accessible. In this paper, we introduce a probabilistic approach for feature sensitivity analysis (SA) of the GPR in order to reveal the relative importance of the features (bands) being used in the regression process. We evaluated the SA on GPR ocean chlorophyll content prediction. The method revealed the importance of the spectral bands, thus allowing the …
Host Searching by Egg Parasitoids: Exploitation of Host Chemical Cues
2010
Insect parasitoids are considered “keystone species” in many ecosystems in terms of biodiversity, ecological impact and economic importance (Vinson 1985, LaSalle and Gauld 1993, Hawkins et al. 1999). In the last decades, several reviews have been published on the relationships among plants, hosts and parasitoids, which reflect a strong interest in these insects both as models for behavioral ecologists and as important organisms for classical and applied biological control programs (Hawkins et al. 1999, Vet 1999, Bale et al. 2008). The majority of these studies have considered the larval parasitoid s, besides the extensive use of egg parasitoids in biological control (Hawkins et al. 1999). I…
Generalizability and Simplicity as Criteria in Feature Selection: Application to Mood Classification in Music
2011
Classification of musical audio signals according to expressed mood or emotion has evident applications to content-based music retrieval in large databases. Wrapper selection is a dimension reduction method that has been proposed for improving classification performance. However, the technique is prone to lead to overfitting of the training data, which decreases the generalizability of the obtained results. We claim that previous attempts to apply wrapper selection in the field of music information retrieval (MIR) have led to disputable conclusions about the used methods due to inadequate analysis frameworks, indicative of overfitting, and biased results. This paper presents a framework bas…
Anomaly detection approach to keystroke dynamics based user authentication
2017
Keystroke dynamics is one of the authentication mechanisms which uses natural typing pattern of a user for identification. In this work, we introduced Dependence Clustering based approach to user authentication using keystroke dynamics. In addition, we applied a k-NN-based approach that demonstrated strong results. Most of the existing approaches use only genuine users data for training and validation. We designed a cross validation procedure with artificially generated impostor samples that improves the learning process yet allows fair comparison to previous works. We evaluated the methods using the CMU keystroke dynamics benchmark dataset. Both proposed approaches outperformed the previou…
Using a mobile application to support children's writing motivation
2013
PurposeThe purpose of this paper is to explore the use of the prototype of a mobile application for the enhancement of children's motivation for writing. The results are explored from students' and experts' perspectives.Design/methodology/approachThis study is based on a field trial and expert evaluations of a prototype of a mobile application. The field trial data consists of questionnaire data collected from elementary school students (n=25) who used the mobile prototype. The expert evaluations (n=8) of the prototype were conducted based on usability and pedagogical heuristics. The main research question is how the mobile application motivates children to learn creative writing.FindingsTh…
Teaching Knowledge Management by Combining Wikis and Screen Capture Videos
2011
PurposeThis paper aims to report on the design and creation of a knowledge management course aimed at facilitating student creation and use of social interactive learning tools for enhanced learning.Design/methodology/approachThe era of social media and web 2.0 has enabled a bottom‐up collaborative approach and new ways to publish work on the web, promoted by tools such as YouTube video service. In this spirit a knowledge management course was designed aiming to facilitate university students to compose videos on different difficult concepts in the theory part of the course by searching for explanations on the web and by creating a Windows Media Player video focusing on the self‐defined pro…
How Students Get Going : Triggers for Students’ Learning in Project-Based Education
2018
Repeatedly documented positive student responses to project-based learning during its decades-long tradition in CS attest to the effectiveness of learning by doing. Support for reflective learning nevertheless continues to be a topic worth studying because the intensity of project work together with a high technical orientation among CS students often complicate reflective practice. A critical incident-inspired assignment was added to a project-based course to support reflective practice in spring 2017. In a previous study, the authors analyzed how students approached the assignment and whether they found it supportive for learning. The present study content-analyses the situations that tri…
A Network-Based Framework for Mobile Threat Detection
2018
Mobile malware attacks increased three folds in the past few years and continued to expand with the growing number of mobile users. Adversary uses a variety of evasion techniques to avoid detection by traditional systems, which increase the diversity of malicious applications. Thus, there is a need for an intelligent system that copes with this issue. This paper proposes a machine learning (ML) based framework to counter rapid evolution of mobile threats. This model is based on flow-based features, that will work on the network side. This model is designed with adversarial input in mind. The model uses 40 timebased network flow features, extracted from the real-time traffic of malicious and…
A Cooperative Coevolution Framework for Parallel Learning to Rank
2015
We propose CCRank, the first parallel framework for learning to rank based on evolutionary algorithms (EA), aiming to significantly improve learning efficiency while maintaining accuracy. CCRank is based on cooperative coevolution (CC), a divide-and-conquer framework that has demonstrated high promise in function optimization for problems with large search space and complex structures. Moreover, CC naturally allows parallelization of sub-solutions to the decomposed sub-problems, which can substantially boost learning efficiency. With CCRank, we investigate parallel CC in the context of learning to rank. We implement CCRank with three EA-based learning to rank algorithms for demonstration. E…