Search results for "UML"
showing 10 items of 407 documents
Defining classifier regions for WSD ensembles using word space features
2006
Based on recent evaluation of word sense disambiguation (WSD) systems [10], disambiguation methods have reached a standstill. In [10] we showed that it is possible to predict the best system for target word using word features and that using this 'optimal ensembling method' more accurate WSD ensembles can be built (3-5% over Senseval state of the art systems with the same amount of possible potential remaining). In the interest of developing if more accurate ensembles, w e here define the strong regions for three popular and effective classifiers used for WSD task (Naive Bayes – NB, Support Vector Machine – SVM, Decision Rules – D) using word features (word grain, amount of positive and neg…
Containers in Software Development: A Systematic Mapping Study
2019
Over the past decade, continuous software development has become a common place in the field of software engineering. Containers like Docker are a lightweight solution that developers can use to deploy and manage applications. Containers are used to build both component-based architectures and microservice architectures. Still, practitioners often view containers only as way to lower resource requirements compared to virtual machines. In this paper, we conducted a systematic mapping study to find information on what is known of how containers are used in software development. 56 primary studies were selected into this paper and they were categorized and mapped to identify the gaps in the cu…
A Note on Laws of Motion for Aggregate Distributions
2020
I derive the law of motion for the aggregate distribution directly from the laws of motion for the individuals’ states. By relying on concepts from measure theory, the derivation is concise and intuitive. I address random shocks both at the micro level and at the macro level. Micro-level shocks completely cancel at the aggregate level provided that a law of large numbers applies. Therefore, the law of motion for the aggregate distribution is a deterministic process in the absence of macro-level uncertainty. If there are macro-level risks, the law of motion for the aggregate distribution exhibits a stochastic component additionally. I illustrate the formalism in a model of wealth accumulatio…
Deriving Enhanced Universal Dependencies from a Hybrid Dependency-Constituency Treebank
2018
The treebanks provided by the Universal Dependencies (UD) initiative are a state-of-the-art resource for cross-lingual and monolingual syntax-based linguistic studies, as well as for multilingual dependency parsing. Creating a UD treebank for a language helps further the UD initiative by providing an important dataset for research and natural language processing in that language. In this paper, we describe how we created a UD treebank for Latvian, and how we obtained both the basic and enhanced UD representations from the data in Latvian Treebank which is annotated according to a hybrid dependency-constituency grammar model. The hybrid model was inspired by Lucien Tesniere’s dependency gram…
Discovering single classes in remote sensing images with active learning
2012
When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. Moreover, the efficiency of the search is also an issue, since the samples labeled as background are not used by target detectors such as the support vector data description (SVDD). In this work we propose a competitive and effective approach to identify the most relevant training samples for one-class classification based on the use of an active learning strategy. The SVDD classifier is first trained with insufficient target examples. It is t…
Recognition of Falls and Daily Living Activities Using Machine Learning
2018
A robust fall detection system is essential to support the independent living of elderlies. In this context, we develop a machine learning framework for fall detection and daily living activity recognition. Using acceleration data from public databases, we test the performance of two algorithms to classify seven different activities including falls and activities of daily living. We extract new features from the acceleration signal and demonstrate their effect on improving the accuracy and the precision of the classifier. Our analysis reveals that the quadratic support vector machine classifier achieves an overall accuracy of 93.2% and outperforms the artificial neural network algorithm. Re…
Investment Decision Making and Risk
2013
Abstract The aim of the paper is to present how investment decisions are made and what investment risk is, what role it has in the investment decision. The decision itself is a subjective act, but it is based on both subjective and objective factors. Risk is an important component of every investment, thus it is necessary to analyse it as both, the objective component of the investment, and as the subjective factor of the investment decision making.
An Investigation of the Roles of Group Identification, Perceived Ability, and Evaluative Conditions in Stereotype Threat Experiences
2019
The Multi-Threat Framework distinguishes six qualitatively distinct stereotype threats. Up to now, few studies have been performed to identify the situational and individual determinants of different stereotype threat experiences. This study investigates the role of group identification, perceived ability, and evaluative conditions (private/public) in six stereotype threat experiences for 261 French Physical Education Students. The results show that the expression level of the different stereotype threats does not vary according to evaluative conditions. In contrast, group identification affects all the forms of stereotype threats, and for three forms of stereotype threats, this effect is …
Assessing the Relationship Between Attitudinal and Perceptual Component of Body Image Disturbance Using Virtual Reality
2018
Body image disturbance (BID) affects quality of life even in the absence of clinically diagnosable eating pathology, and numerous studies have shown its crucial role in the emergence and maintenance of eating disorders. This study aimed at exploring attitudinal and perceptual components of BID using a novel virtual reality (VR)-based paradigm. A community sample of women (N = 27) recreated in VR their perceived body in both an allocentric (third-person view) and egocentric (first-person view) perspective. Specifically, women were able to choose between a wide range of three-dimensional bodies spanning body mass index 12.5-42.5 kg/m2. Attitudinal indexes of BID (body dissatisfaction, body un…
Is an attention-based associative account of adjacent and nonadjacent dependency learning valid?
2014
Pacton and Perruchet (2008) reported that participants who were asked to process adjacent elements located within a sequence of digits learned adjacent dependencies but did not learn nonadjacent dependencies and conversely, participants who were asked to process nonadjacent digits learned nonadjacent dependencies but did not learn adjacent dependencies. In the present study, we showed that when participants were simply asked to read aloud the same sequences of digits, a task demand that did not require the intentional processing of specific elements as in standard statistical learning tasks, only adjacent dependencies were learned. The very same pattern was observed when digits were replace…