Search results for "artificial intelligence"
showing 10 items of 6122 documents
Multifunctions determined by integrable functions
2019
Integral properties of multifunctions determined by vector valued functions are presented. Such multifunctions quite often serve as examples and counterexamples. In particular it can be observed that the properties of being integrable in the sense of Bochner, McShane or Birkhoff can be transferred to the generated multifunction while Henstock integrability does not guarantee it.
Decompositions of Weakly Compact Valued Integrable Multifunctions
2020
We give a short overview on the decomposition property for integrable multifunctions, i.e., when an &ldquo
Algebraic aspects and coherence conditions for conjoined and disjoined conditionals
2019
We deepen the study of conjoined and disjoined conditional events in the setting of coherence. These objects, differently from other approaches, are defined in the framework of conditional random quantities. We show that some well known properties, valid in the case of unconditional events, still hold in our approach to logical operations among conditional events. In particular we prove a decomposition formula and a related additive property. Then, we introduce the set of conditional constituents generated by $n$ conditional events and we show that they satisfy the basic properties valid in the case of unconditional events. We obtain a generalized inclusion-exclusion formula and we prove a …
Introducing a novel mesh following technique for approximation-free robotic tool path trajectories
2017
Abstract Modern tools for designing and manufacturing of large components with complex geometries allow more flexible production with reduced cycle times. This is achieved through a combination of traditional subtractive approaches and new additive manufacturing processes. The problem of generating optimum tool-paths to perform specific actions (e.g. part manufacturing or inspection) on curved surface samples, through numerical control machinery or robotic manipulators, will be increasingly encountered. Part variability often precludes using original design CAD data directly for toolpath generation (especially for composite materials), instead surface mapping software is often used to gener…
Hierarchical Syntactic Models for Human Activity Recognition through Mobility Traces
2019
AbstractRecognizing users’ daily life activities without disrupting their lifestyle is a key functionality to enable a broad variety of advanced services for a Smart City, from energy-efficient management of urban spaces to mobility optimization. In this paper, we propose a novel method for human activity recognition from a collection of outdoor mobility traces acquired through wearable devices. Our method exploits the regularities naturally present in human mobility patterns to construct syntactic models in the form of finite state automata, thanks to an approach known asgrammatical inference. We also introduce a measure ofsimilaritythat accounts for the intrinsic hierarchical nature of su…
A Context-Aware System for Ambient Assisted Living
2017
In the near future, the world's population will be characterized by an increasing average age, and consequently, the number of people requiring for a special household assistance will dramatically rise. In this scenario, smart homes will significantly help users to increase their quality of life, while maintaining a great level of autonomy. This paper presents a system for Ambient Assisted Living (AAL) capable of understanding context and user's behavior by exploiting data gathered by a pervasive sensor network. The knowledge inferred by adopting a Bayesian knowledge extraction approach is exploited to disambiguate the collected observations, making the AAL system able to detect and predict…
An Ambient Intelligence System for Assisted Living
2017
Nowadays, the population's average age is constantly increasing, and thus the need for specialized home assistance is on the rise. Smart homes especially tailored to meet elderly and disabled people's needs can help them maintaining their autonomy, whilst ensuring their safety and well-being. This paper proposes a complete context-aware system for Ambient Assisted Living (AAL), which infers user's actions and context, analyzing its past and current behavior to detect anomalies and prevent possible emergencies. The proposed system exploits Dynamic Bayesian Networks to merge raw data coming from heterogeneous sensors and infer user's behavior and health conditions. A rule-based reasoner is ab…
A Deep Learning Approach for Energy Efficient Computational Offloading in Mobile Edge Computing
2019
Mobile edge computing (MEC) has shown tremendous potential as a means for computationally intensive mobile applications by partially or entirely offloading computations to a nearby server to minimize the energy consumption of user equipment (UE). However, the task of selecting an optimal set of components to offload considering the amount of data transfer as well as the latency in communication is a complex problem. In this paper, we propose a novel energy-efficient deep learning based offloading scheme (EEDOS) to train a deep learning based smart decision-making algorithm that selects an optimal set of application components based on remaining energy of UEs, energy consumption by applicati…
Markerless 2D kinematic analysis of underwater running : A deep learning approach
2018
Kinematic analysis is often performed with a camera system combined with reflective markers placed over bony landmarks. This method is restrictive (and often expensive), and limits the ability to perform analyses outside of the lab. In the present study, we used a markerless deep learning-based method to perform 2D kinematic analysis of deep water running, a task that poses several challenges to image processing methods. A single GoPro camera recorded sagittal plane lower limb motion. A deep neural network was trained using data from 17 individuals, and then used to predict the locations of markers that approximated joint centres. We found that 300–400 labelled images were sufficient to tra…
Gray coding cubic planar maps
2016
International audience; The idea of (combinatorial) Gray codes is to list objects in question in such a way that two successive objects differ in some pre-specified small way. In this paper, we utilize beta-description trees to cyclicly Gray code three classes of cubic planar maps, namely, bicubic planar maps, 3-connected cubic planar maps, and cubic non-separable planar maps. (C) 2015 Elsevier B.V. All rights reserved.