Search results for "rover"
showing 10 items of 368 documents
Alexithymia and the implicit self-concept of extraversion in women
2016
Abstract Findings from studies using self-reports suggest a negative association between the personality traits of alexithymia and extraversion. Self-report measures are assumed to assess aspects of the explicit self-concept of personality. Indirect measures, such as the Implicit Association Test (IAT), were developed to tap into the implicit self-concept of personality. The present study examined for the first time the relationship between self-reported alexithymia and the implicit self-concept of extraversion. The 20-item Toronto Alexithymia Scale and an Implicit Association Test (IAT) assessing extraversion were administered to 86 healthy women along with the NEO Five-factor Inventory (N…
Personalidad y Autoestima: Un análisis sobre el importante papel de sus relaciones
2018
The five factor model has been established as one of the main approaches in the study of personality. After its emergence, one of the most important aspects to be analyzed has been its relationship with self-esteem, considering the central role that the latest has in the model. In spite of the large empirical support existing about this relationship, the need of a deeper understanding of its theoretical nature has been pointed out. The aim of our work joins the previous research, in analyzing the existence of relationships between personality factors and self-esteem. The sample was 576 university students, between 18- 35 years old. The present findings show that self-esteem is negatively as…
Automatic image-based identification and biomass estimation of invertebrates
2020
1. Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and expert-based identification of taxa pose strong limitations on how many insect samples can be processed. In turn, this affects the scale of efforts to map and monitor invertebrate diversity altogether. Given recent advances in computer vision, we propose to enhance the standard human expert-based identification approach involving manual sorting and identification with an automatic image-based technology. 2. We describe a robot-enabled image-based ident…
Human experts vs. machines in taxa recognition
2020
The step of expert taxa recognition currently slows down the response time of many bioassessments. Shifting to quicker and cheaper state-of-the-art machine learning approaches is still met with expert scepticism towards the ability and logic of machines. In our study, we investigate both the differences in accuracy and in the identification logic of taxonomic experts and machines. We propose a systematic approach utilizing deep Convolutional Neural Nets with the transfer learning paradigm and extensively evaluate it over a multi-pose taxonomic dataset with hierarchical labels specifically created for this comparison. We also study the prediction accuracy on different ranks of taxonomic hier…
Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer
2023
Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR from histopathological images of colorectal cancer. The method is based on convolutional neural networks which were trained to classify colorectal cancer tissue in hematoxylin-eosin stained samples into three classes: stroma, tumor and other. The models were trained using a data set that consists of 1343 whole slide images. Three different training setups were applied with a transfer learning approach using domain-specific data i.e. an external colorectal cancer histopathological data set. The three most accurate models were chosen as a classifie…
Classification of Heart Sounds Using Convolutional Neural Network
2020
Heart sounds play an important role in the diagnosis of cardiac conditions. Due to the low signal-to-noise ratio (SNR), it is problematic and time-consuming for experts to discriminate different kinds of heart sounds. Thus, objective classification of heart sounds is essential. In this study, we combined a conventional feature engineering method with deep learning algorithms to automatically classify normal and abnormal heart sounds. First, 497 features were extracted from eight domains. Then, we fed these features into the designed convolutional neural network (CNN), in which the fully connected layers that are usually used before the classification layer were replaced with a global averag…
Automatic Content Analysis of Computer-Supported Collaborative Inquiry-Based Learning Using Deep Networks and Attention Mechanisms
2020
Computer-supported collaborative inquiry-based learning (CSCIL) represents a form of active learning in which students jointly pose questions and investigate them in technology-enhanced settings. Scaffolds can enhance CSCIL processes so that students can complete more challenging problems than they could without scaffolds. Scaffolding CSCIL, however, would optimally adapt to the needs of a specific context, group, and stage of the group's learning process. In CSCIL, the stage of the learning process can be characterized by the inquiry-based learning (IBL) phase (orientation, conceptualization, investigation, conclusion, and discussion). In this presentation, we illustrate the potential of a…
Idioms and fictional orality in Toni Cucarella’s narrative
2021
En aquest article s’estudien les unitats fraseològiques en quatre obres de Toni Cucarella en relació amb l’oralitat ficcional. La tradició d’estudis sobre l’oralitat ficcional analitza els recursos que evoquen l’oralitat en textos escrits o audiovisuals. Entre aquests recursos, en els darrers anys s’ha destacat la importància de certes unitats fraseològiques que són pròpies de la llengua oral i, en aparéixer en textos escrits, evoquen la llengua oral, com un mitjà per caracteritzar de manera versemblant els personatges. Analitzem la recurrència de les unitats fraseològiques i els motius que poden explicar aquesta recurrència. Les unitats fraseològiques més recurrents són les locucions verba…
Adagia quaecumque ad hanc diem exierunt / Pauli Manutii studio atque industria ... ; sublatis etiam falsis interpretationibus & non nullis quae nihil…
1575
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Robustness, Stability, and Fidelity of Explanations for a Deep Skin Cancer Classification Model
2022
Skin cancer is one of the most prevalent of all cancers. Because of its being widespread and externally observable, there is a potential that machine learning models integrated into artificial intelligence systems will allow self-screening and automatic analysis in the future. Especially, the recent success of various deep machine learning models shows promise that, in the future, patients could self-analyse their external signs of skin cancer by uploading pictures of these signs to an artificial intelligence system, which runs such a deep learning model and returns the classification results. However, both patients and dermatologists, who might use such a system to aid their work, need to …