Volume 6 (2016): Edizione 4 (October 2016)

Fuzzy signatures were introduced as special tools to describe and handle complex systems without their detailed mathematical models. The input parameters of these systems naturally have uncertainties, due to human activities or lack of precise data. These uncertainties influence the final conclusion or decision about the system. In this paper we discuss the sensitivity of the weigthed general mean aggregation operator to the uncertainty of the input values, then we analyse the sensitivity of fuzzy signatures equipped with these aggregation operators. Finally, we apply our results to a fuzzy signature used in civil enginnering.

This paper presents an attempt to solve the problem of choosing the best combination among the M combinations of shortest paths in optical translucent networks. Fixed routing algorithms demands a single route to each pair of nodes. The existence of multiple shortest paths to some pairs of nodes originates the problem of choose the shortest path which fits better the network requests. The algorithm proposed in this paper is an adaptation of Ant Colony Optimization (ACO) metaheuristic and attempt to define the set of routes that fits in an optimized way the network conditions, resulting in reduced number of blocked requests and better adjusted justice in route distribution. A performance evaluation is conducted in real topologies by simulations, and the proposed algorithm shows better performance between the compared algorithms.

If conventional feature selection methods do not show sufficient effectiveness, alternative algorithmic schemes might be used. In this paper we propose an evolutionary feature selection technique based on the two-criterion optimization model. To diminish the drawbacks of genetic algorithms, which are applied as optimizers, we design a parallel multicriteria heuristic procedure based on an island model. The performance of the proposed approach was investigated on the Speech-based Emotion Recognition Problem, which reflects one of the most essential points in the sphere of human-machine communications. A number of multilingual corpora (German, English and Japanese) were involved in the experiments. According to the results obtained, a high level of emotion recognition was achieved (up to a 12.97% relative improvement compared with the best F-score value on the full set of attributes).

In this paper, we propose an optimal viewpoint selection system for monitoring robots to search for the optimal viewpoint of a scene with the highest aesthetic property. Using the information of the targets, we propose a novel method for predicting human aesthetic sense for a scene. We construct evaluation functions based on certain known composition rules using three factors, namely, target size, visual balance, and composition fitting value. Then a score, which is a reflection of human evaluation, will be obtained using these functions. The optimal viewpoint will be selected from a number of candidates around the target group, by evaluating the aesthetic properties of scenes for each candidate viewpoint. Finally, once the optimal viewpoint is confirmed, path planning and path following controls are implemented for the robots during the moving process.

This paper reports on an ongoing project between members of the computer science and special education departments of Bradley University and Murray State University, detailing the robotic platforms developed and investigated as a potential tool to improve social interactions among individuals with Autism Spectrum Disorders (ASD). Development of a fourth generation robotic agent is described, which uses economically available robotic platforms (Lego NXT) as Socially Assistive Robotics (SAR), combined with direct instruction pedagogy and social scripts to support an alternative educational approach to teaching social behavior. Specifically, in this fourth generation, changes to the physical design of the robots were made to improve the maintainability, reliability, maneuverability, and aesthetics of the robots. The software architecture was designed for modularity, configurability, and reusability of the software.