Search results for "Computer Science Application"
showing 10 items of 3998 documents
A Posture Sequence Learning System for an Anthropomorphic Robotic Hand
2003
The paper presents a cognitive architecture for posture learning of an anthropomorphic robotic hand. Our approach is aimed to allow the robotic system to perform complex perceptual operations, to interact with an human user and to integrate the perceptions by a cognitive representation of the scene and the observed actions. The anthropomorphic robotic hand imitates the gestures acquired by the vision system in order to learn meaningful movements, to build its knowledge by different conceptual spaces and to perform complex interaction with the human operator.
CheS-Mapper 2.0 for visual validation of (Q)SAR models
2014
Abstract Background Sound statistical validation is important to evaluate and compare the overall performance of (Q)SAR models. However, classical validation does not support the user in better understanding the properties of the model or the underlying data. Even though, a number of visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allow the investigation of model validation results are still lacking. Results We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. The approach applies the 3D viewer CheS-Mapper, an open-source application for the exploration of sm…
Visualizations for Decision Support in Scenario-based Multiobjective Optimization
2021
Reproducibility artifacts for: Babooshka Shavazipour, Manuel López-Ibáñez, and Kaisa Miettinen. Visualizations for Decision Support in Scenario-based Multiobjective Optimization. Information Sciences, 2021. doi:10.1016/j.ins.2021.07.025. Abstract: We address challenges of decision problems when managers need to optimize several conflicting objectives simultaneously under uncertainty. We propose visualization tools to support the solution of such scenario-based multiobjective optimization problems. Suitable graphical visualizations are necessary to support managers in understanding, evaluating, and comparing the performances of management decisions according to all objec…
Cantus: Construction and evaluation of a software solution for real-time vocal music training and musical intonation assessment
2016
The development of the ability to sing or play in tune is one of the most critical tasks in music training. In music education, melodic patterns are usually learned by imitative processes (modelling). Once modelled, pitch sounds are then associ-ated to a representation according to a syllabic system such as the Guidonian system - or an arbitrary single syllable - or western graphic notation system symbols. From a didactic standpoint, few advances have been made in this area besides the use of audio-supported guides and existing software, which use a microphone to analyse the input and estimate the pitch or fundamental frequency of the given tone. However, these programmes lack the necessary…
The bridge volcanic LIdar-BILLI: A review of data collection and processing techniques in the Italian most hazardous volcanic areas
2020
Volcanologists have demonstrated that carbon dioxide (CO2) fluxes are precursors of volcanic eruptions. Controlling volcanic gases and, in particular, the CO2 flux, is technically challenging, but we can retrieve useful information from magmatic/geological process studies for the mitigation of volcanic hazards including air traffic security. Existing techniques used to probe volcanic gas fluxes have severe limitations such as the requirement of near-vent in situ measurements, which is unsafe for operators and deleterious for equipment. In order to overcome these limitations, a novel range-resolved DIAL-Lidar (Differential Absorption Light Detection and Ranging) has been developed as part of…
Power Losses Minimization for Optimal Operating Maps in Power-Split HEVs: A Case Study on the Chevrolet Volt
2021
The power-split architecture is the most promising hybrid electric powertrain. However, a real advantage in energy saving while maintaining high performance can be achieved only by the implementation of a proper energy management strategy. This requires an optimized functional design before and a comprehensive analysis of the powertrain losses after, which could be rather challenging owing to the constructive complexity of the power-split transmission, especially for multi-mode architecture with multiple planetary gearing. This difficulty was overcome by a dimensionless model, already available in the literature, that enables the analysis of any power-split transmission, even in full electr…
Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography
2019
Background and objectives: Spectral Domain Optical Coherence Tomography (SD-OCT) is a volumetric imaging technique that allows measuring patterns between layers such as small amounts of fluid. Since 2012, automatic medical image analysis performance has steadily increased through the use of deep learning models that automatically learn relevant features for specific tasks, instead of designing visual features manually. Nevertheless, providing insights and interpretation of the predictions made by the model is still a challenge. This paper describes a deep learning model able to detect medically interpretable information in relevant images from a volume to classify diabetes-related retinal d…
Determinants of internet‐based corporate governance disclosure by Spanish listed companies
2008
PurposeThe purpose of this paper is to analyse the corporate governance information disclosed by Spanish listed companies on the internet, with the objective of assessing the extent and the influence of several corporate characteristics on the level of information voluntarily disclosed.Design/methodology/approachThe study took as its reference the existing literature on the examination of the quality of web sites and the importance of content as a key variable in determining web site quality. To quantify the corporate governance information disclosed by Spanish listed companies, three transparency indexes were designed. To contrast which variables determine the information provided online, …
On solving single elevator-like problems using a learning automata-based paradigm
2020
This paper concentrates on a host of problems with characteristics similar to those that are related to moving elevators within a building. These are referred to as Elevator-like problems (ELPs), and their common phenomena will be expanded on in the body of the paper. We shall resolve ELPs using a subfield of AI, namely the field of learning automata (LA). Rather than working with the well-established mathematical formulations of the field, our intention is to use these tools to tackle ELPs, and in particular, those that deal with single “elevators” moving between “floors”. ELPs have not been tackled before using AI. In a simplified domain, the ELP involves the problem of optimizing the sch…
Agent assisted interactive algorithm for computationally demanding multiobjective optimization problems
2015
Abstract We generalize the applicability of interactive methods for solving computationally demanding, that is, time-consuming, multiobjective optimization problems. For this purpose we propose a new agent assisted interactive algorithm. It employs a computationally inexpensive surrogate problem and four different agents that intelligently update the surrogate based on the preferences specified by a decision maker. In this way, we decrease the waiting times imposed on the decision maker during the interactive solution process and at the same time decrease the amount of preference information expected from the decision maker. The agent assisted algorithm is not specific to any interactive me…