Browsing by Subject "pattern recognition"

In this paper, we propose an emotional model for robots in a multi-robot system, in order to allow emerging behaviors. The emotional model uses four universal emotions: anger, disgust, sadness, and joy, assigned to each ...

Web service composition requires high levels of integration and reliability of the services involved in its operation, which must meet specific quality criteria to ensure their proper execution and deployment. The discovery ...

This paper presents three different approaches to recognize driving style based on a hierarchical-model. Specifically, it proposes a hierarchical model for the recognition of the driving style for advanced driver-assistance ...

Analysis of the emotions in a multi-robot system in emergent contexts
...
Gil, Angel | 2021-01-12

In this paper, we propose an emotional model for robots in a multi-robot system, in order to allow emerging behaviors. The emotional model uses four universal emotions: anger, disgust, sadness, and joy, assigned to each robot based on the level of satisfaction of its basic needs. These four universal emotions lie on a spectrum where depending where the emotion of the robot lies, can affect its behavior and of its neighboring robots. The more negative the emotion is, the more individualistic it becomes in its decisions (anger, sadness or disgust). The more positive the robot is in its emotion, the more it will consider the group and global goals (joy). Each robot is able to recognize another robot′s emotion in the system based on their current state, using the AR2P (AR2P for its acronym in Spanish: Algoritmo Recursivo de Reconocimiento de Patrones) recognition algorithm. In this way, it can use this information of the emotions to decide with whom collaborate. Specifically, the paper addresses emotions’ influence on the behavior of the system, at the individual and collective levels, and the emotions’ effects on the emergent behaviors of the multi-robot system. The paper explores the emerging behavior in two multi-robot scenarios; nectar harvesting and object transportation. The results show that the emotions are important to the emergent behavior in a multi-robot system.

LEER
Qos-based pattern recognition approach for web service discovery: Ar_wsds(Article)
...
Adarme Jaimes, Marco Antonio | 2021-08-31

Web service composition requires high levels of integration and reliability of the services involved in its operation, which must meet specific quality criteria to ensure their proper execution and deployment. The discovery and selection of web services currently face optimization problems. Many services might satisfy a requirement with similar quality criteria. Because of this, software developers have to choose the most appropriate services for a given composition, complicated by the rapid increase in providers and services available in the cloud. Service composition also implies coupling according to a composition flow and non-functional requirement criteria. Such requirements make selection and composition a complex task not previously solved in the literature. This paper presents Ar_WSDS, a computational approach for web services discovery and selection in cloud environments, which bases its implementation on the brain’s pattern recognition systematic functioning. This process allows classifying web services through recognition modules created dynamically based on their quality parameters, resulting in a set of web services suitable for a web service composition. This approach allows a solution to the selection problem using less complex tasks. This paper introduces an architectural and procedural definition that provides the web service description with a pattern to recognize and select services using different recognition levels. We simulated our approach and evaluated it using a dataset from the QWS project that offers a set of quality criteria collected from different providers. The web services are recognized and classified using different quality criteria for the composition and each of their services. The results demonstrate the effectiveness of the discovery and selection process compared to other approaches. Furthermore, Ar_WSDS allows us to recognize and filter out web services with ambiguity and similarity in their provider information, a process that minimizes the discovery space for services.

LEER
Recognition of the driving style in vehicle drivers
...
Cordero, Jorge | 2020-05-02

This paper presents three different approaches to recognize driving style based on a hierarchical-model. Specifically, it proposes a hierarchical model for the recognition of the driving style for advanced driver-assistance systems (ADAS) for vehicles. This hierarchical model for the recognition of the style of the car driving considers three aspects: the driver emotions, the driver state, and finally, the driving style itself. In this way, the proposed hierarchical pattern is composed of three levels of descriptors/features, one to recognize the emotional states, another to recognize the driver state, and the last one to recognize the driving style. Each level has a set of descriptors, which can be sensed in a real context. Finally, the paper presents three driving style recognition algorithms based on different paradigms. One is based on fuzzy logic, another is based on chronicles (a temporal logic paradigm), and the last is based on an algorithm that uses the idea of the recognition process of the neocortex, called Ar2p (Algoritmo Recursivo de Reconocimiento de Patrones, for its acronym in Spanish). In the paper, these approaches are compared using real datasets, using different metrics of interest in the context of the Internet of the Things, in order to determine their capabilities of reasoning, adaptation, and the communication of information. In general, the initial results are encouraging, specifically in the cases of chronicles and Ar2p, which give the best results.

LEER

Repositorio Digital

Browsing by Subject "pattern recognition"

Analysis of the emotions in a multi-robot system in emergent contexts

Qos-based pattern recognition approach for web service discovery: Ar_wsds(Article)

Recognition of the driving style in vehicle drivers

Envíos recientes

Analysis of the emotions in a multi-robot system in emergent contexts

Qos-based pattern recognition approach for web service discovery: Ar_wsds(Article)

Recognition of the driving style in vehicle drivers

Portales Institucionales

Enlaces de Interés

Contactos

Browsing by Subject "pattern recognition"

Analysis of the emotions in a multi-robot system in emergent contexts ﻿

Qos-based pattern recognition approach for web service discovery: Ar_wsds(Article) ﻿

Recognition of the driving style in vehicle drivers ﻿

Envíos recientes

Analysis of the emotions in a multi-robot system in emergent contexts

Qos-based pattern recognition approach for web service discovery: Ar_wsds(Article)

Recognition of the driving style in vehicle drivers

Portales Institucionales

Analysis of the emotions in a multi-robot system in emergent contexts

Qos-based pattern recognition approach for web service discovery: Ar_wsds(Article)

Recognition of the driving style in vehicle drivers