Search results for "Machine"
showing 10 items of 2592 documents
Derrida, Heidegger, Pascal, et la question de l'animal
2012
L'article essaye de retrouver un fil qui lie Derrida à Pascal à propos du statut de l'humain et du rapport entre l'homme et l'animal. Cette reconstruction passe par la lecture d'Heidegger de la part de Derrida et par la lecture heideggerienne de Pascal.
The Robotic Construction Kit as a Tool for Cognitive Stimulation in Children and Adolescents: The RE4BES Protocol
2019
Through numerous experiences, the robotics has been demonstrated to have good potential in the field of strengthening social skills in children with Special Educational Needs and in particular with autism spectrum disorder. There are still not many experimental studies on the cognitive enhancement and social skills of children with special needs conducted with robotics construction kits that, requiring both the construction of the robot body and the programming of its “mind“, bring into play a multiplicity of cognitive and social skills. For the aforementioned reasons our team from the University of Palermo and from the Center MetaIntelligenze ONLUS developed the treatment protocol RE4BES, …
Prioritisation of alternatives with analytical hierarchy process plus response latency and web surveys
2014
This paper introduces a new method that combines the well-known analytical hierarchy process (AHP) with a response latency metric. The response latency is the time taken by respondents to make choices over pairwise comparisons. The analytical calculation of relative importance weights of the alternatives is made by using a response latency model previously validated in several case studies. This combination aims to overcome some drawbacks of the traditional AHP related to the use of a rating scale (the so-called Saaty scale), and it is a natural way to involve response latency in established decisionmaking methods. This new method can be profitably adopted in web surveys where it is easy to…
Discovery of novel trichomonacidals using LDA-driven QSAR models and bond-based bilinear indices as molecular descriptors
2008
Few years ago, the World Health Organization estimated the number of adults with trichomoniasis at 170 million worldwide, more than the combined numbers for gonorrhea, syphilis, and chlamydia. To combat this sexually transmitted disease, Metronidazole (MTZ) has emerged, since 1959, as a powerful drug for the systematic treatment of infected patients. However, increasing resistance to MTZ, adverse effects associated to high-dose MTZ therapies and very expensive conventional technologies related to the development of new trichomonacidals necessitate novel computational methods that shorten the drug discovery pipeline. Therefore, bond-based bilinear indices, new 2-D bond-based TOMOCOMD-CARDD M…
Automatic differentiation of melanoma from dysplastic nevi.
2015
International audience; Malignant melanoma causes the majority of deaths related to skin cancer. Nevertheless, it is the most treatable one, depending on its early diagnosis. The early prognosis is a challenging task for both clinicians and dermatologist, due to the characteristic similarities of melanoma with other skin lesions such as dysplastic nevi. In the past decades, several computerized lesion analysis algorithms have been proposed by the research community for detection of melanoma. These algorithms mostly focus on differentiating melanoma from benign lesions and few have considered the case of melanoma against dysplastic nevi. In this paper, we consider the most challenging task a…
An in vitro evaluation of the effect of sandblasting and laser surface treatment on the shear bond strength of a composite resin to the facial surfac…
2015
Objectives: The present study was conducted to evaluate the optimal method of enhancing the bond strength of a composite resin to the facial surface of the primary anterior stainless steel crowns using various surface treatments namely Nd: YAG laser surface treatment, sandblasting , alloy primer application and no surface treatment. Study Design: The study sample consisted of 60 primary anterior stainless steel crowns (UnitekTM size R 4), with 15 samples randomly divided into the 4 study groups, embedded in acrylic blocks. The facial surface of these surface treated crowns was utilized as the bonding surface to which 2.5mm diameter composite resin cylinders were bonded for the evaluation of…
Active Learning Methods for Efficient Hybrid Biophysical Variable Retrieval
2016
Kernel-based machine learning regression algorithms (MLRAs) are potentially powerful methods for being implemented into operational biophysical variable retrieval schemes. However, they face difficulties in coping with large training data sets. With the increasing amount of optical remote sensing data made available for analysis and the possibility of using a large amount of simulated data from radiative transfer models (RTMs) to train kernel MLRAs, efficient data reduction techniques will need to be implemented. Active learning (AL) methods enable to select the most informative samples in a data set. This letter introduces six AL methods for achieving optimized biophysical variable estimat…
Rapid parameter estimation of discrete decaying signals using autoencoder networks
2021
Machine learning: science and technology 2(4), 045024 (2021). doi:10.1088/2632-2153/ac1eea
Causal inference in geosciences with kernel sensitivity maps
2020
Establishing causal relations between random variables from observational data is perhaps the most important challenge in today's Science. In remote sensing and geosciences this is of special relevance to better understand the Earth's system and the complex and elusive interactions between processes. In this paper we explore a framework to derive cause-effect relations from pairs of variables via regression and dependence estimation. We propose to focus on the sensitivity (curvature) of the dependence estimator to account for the asymmetry of the forward and inverse densities of approximation residuals. Results in a large collection of 28 geoscience causal inference problems demonstrate the…
Nonlinear Distribution Regression for Remote Sensing Applications
2020
In many remote sensing applications, one wants to estimate variables or parameters of interest from observations. When the target variable is available at a resolution that matches the remote sensing observations, standard algorithms, such as neural networks, random forests, or the Gaussian processes, are readily available to relate the two. However, we often encounter situations where the target variable is only available at the group level, i.e., collectively associated with a number of remotely sensed observations. This problem setting is known in statistics and machine learning as multiple instance learning (MIL) or distribution regression (DR). This article introduces a nonlinear (kern…