Search results for "Intelligence"
showing 10 items of 6959 documents
Fuzzy portfolio optimization under downside risk measures
2007
This paper presents two fuzzy portfolio selection models where the objective is to minimize the downside risk constrained by a given expected return. We assume that the rates of returns on securities are approximated as LR-fuzzy numbers of the same shape, and that the expected return and risk are evaluated by interval-valued means. We establish the relationship between those mean-interval definitions for a given fuzzy portfolio by using suitable ordering relations. Finally, we formulate the portfolio selection problem as a linear program when the returns on the assets are of trapezoidal form.
Experimental validation of optimisation strategies in hydroforming of T-shaped tubes
2008
For three dimensional tube hydroforming operations (i.e. T or Y shaped tubes) the calibration of both material feeding history and internal pressure path during the process is crucial and many approaches to such optimization were presented; the authors developed some procedures to optimize pressure paths and punch velocity histories with the application of an integrated method FEM - Gradient based optimization tools. In this paper, an experimental validation campaign of the utilized optimization strategies is presented with the aim to assess the effectiveness of the developed procedures. An optimization procedure (gradient based techniques) was applied on the process parameters leading to t…
AIOC2: A deep Q-learning approach to autonomic I/O congestion control in Lustre
2021
Abstract In high performance computing systems, I/O congestion is a common problem in large-scale distributed file systems. However, the current implementation mainly requires administrator to manually design low-level implementation and optimization, we proposes an adaptive I/O congestion control framework, named AIOC 2 , which can not only adaptively tune the I/O congestion control parameters, but also exploit the deep Q-learning method to start the training parameters and optimize the tuning for different types of workloads from the server and the client at the same time. AIOC 2 combines the feedback-based dynamic I/O congestion control and deep Q-learning parameter tuning technology to …
Infrared image processing and its application to forest fire surveillance
2007
This paper describes an scheme for automatic forest surveillance. A complete system for forest fire detection is firstly presented although we focus on infrared image processing. The proposed scheme based on infrared image processing performs early detection of any fire threat. With the aim of determining the presence or absence of fire, the proposed algorithms performs the fusion of different detectors which exploit different expected characteristics of a real fire, like persistence and increase. Theoretical results and practical simulations are presented to corroborate the control of the system related with probability of false alarm (PFA). Probability of detection (PD) dependence on sign…
New evidence for chunk-based models in word segmentation.
2014
International audience; : There is large evidence that infants are able to exploit statistical cues to discover the words of their language. However, how they proceed to do so is the object of enduring debates. The prevalent position is that words are extracted from the prior computation of statistics, in particular the transitional probabilities between syllables. As an alternative, chunk-based models posit that the sensitivity to statistics results from other processes, whereby many potential chunks are considered as candidate words, then selected as a function of their relevance. These two classes of models have proven to be difficult to dissociate. We propose here a procedure, which lea…
FISH: Face Intensity-Shape Histogram representation for automatic face splicing detection
2019
Abstract Tampered images spread nowadays over any visual media influencing our judgement in many aspects of our life. This is particularly critical for face splicing manipulations, where recognizable identities are put out of context. To contrast these activities on a large scale, automatic detectors are required. In this paper, we present a novel method for automatic face splicing detection, based on computer vision, that exploits inconsistencies in the lighting environment estimated from different faces in the scene. Differently from previous approaches, we do not rely on an ideal mathematical model of the lighting environment. Instead, our solution, built upon the concept of histogram-ba…
A System for Simultaneous People Tracking and Posture Recognition in the context of Human-Computer Interaction
2005
The paper deals with an artificial-vision based system for simultaneous people tracking and posture recognition In the context of human-computer Interaction. We adopt no particular assumptions on the movement of a person and on Its appearance, making the system suitable to several real-world applications. The system can be roughly subdivided Into two highly correlated phases: tracking and recognition. The tracking phase Is concerned with establishing coherent relations of the same subject between frames. We adopted the Condensation algorithm due to Its robustness In highly cluttered environments. The recognition phase adopts a modified elgenspace technique In order to classify between sever…
Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation
2016
This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are proposed. A technique called the ACTwg employs genre-adaptive semantic computing of mood-related social tags, whereas ACTwg-SLPwg combines semantic computing and audio-based modelling, both in a genre-adaptive manner. The proposed techniques are experimentally evaluated at predicting listener ratings related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outpe…
WORDY: a Semi-automatic Methodology aimed at the Creation of Neologisms based on a Semantic Network and Blending Devices
2017
In this paper, we propose a semi-automatic tool, named WORDY, that implements a methodology aimed at speeding-up the pro- cess of creation of neologisms. The approach exploits a semantic network, which is explored through the spreading activation methodology and ex- ploits three blending linguistic techniques together with a proper ranking function in order to support companies in the creation of neologisms ca- pable of evoking semantic meaningful associations to customers.
Entity Recommendation for Everyday Digital Tasks
2021
| openaire: EC/H2020/826266/EU//CO-ADAPT Recommender systems can support everyday digital tasks by retrieving and recommending useful information contextually. This is becoming increasingly relevant in services and operating systems. Previous research often focuses on specific recommendation tasks with data captured from interactions with an individual application. The quality of recommendations is also often evaluated addressing only computational measures of accuracy, without investigating the usefulness of recommendations in realistic tasks. The aim of this work is to synthesize the research in this area through a novel approach by (1) demonstrating comprehensive digital activity monitor…