Journal of Intelligent & Fuzzy Systems - Volume 34, issue 5

Authors: Peralta-Malváez, Lizbeth | López-Rincón, Omar | Rojas-Velázquez, David | Valencia-Rosado, Luis Oswaldo | Rosas-Romero, Roberto | Etcheverry, Gibran

Article Type: Research Article

Abstract: Newborn cry features extraction for affections detection and classification has been intensively developed during the last ten to fifteen years. In this work, methods from the system identification area have been implemented in order to obtain ten Linear Predictive Coefficients (LPCs) plus a nonlinear one stated as Bilinear Intermittent Factor (BIF) per 20 ms analysis window for 40 normal and loss hearing (deaf) newborn cries each. In order to show the contribution of the nonlinear feature, a Kernel Discriminant Analysis (KDA) is performed and afterwards, two classifications tests employing Supported Vector machines (SVMs) as a standard and the Expectation Maximization (EM) …algorithm over a Mixture of Experts (ME) operation, considering the BIF as an expert or parent of the LPCs, allows to obtain a 99.84% classification. Show more

Keywords: Newborn cry classification, nonlinear features, Mixture of Experts, KDA, SVMs, EM

DOI: 10.3233/JIFS-169510

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3281-3289, 2018

Authors: Flores, Jorge Garcia | Meza, Iván | Colin, Émilie | Gardent, Claire | Gangemi, Aldo | Pineda, Luis A.

Article Type: Research Article

Abstract: What if service robots could tell the story of the task they’ve just realized like a story? The aim of our work is to provide service robots with natural language capabilities to produce a Robot Experience Story for its human interlocutors. Robxp stories are narratives composed of the robot’s holistic perception of a recently performed task: navigation, visual perceptions and action descriptions. We contribute with a narrate dialog model specifying the composition of situations necessary for a service robot to transform its task history record into a narrative knowledge representation. We provide SitLog algorithms allowing to analyze the …robot’s situation and behaviors sequence in order to generate a robxp story of the task. Both the dialogue model and the algorithms can be embedded as compositional behaviors in any other SitLog task structure. We instantiated our model into the Golem service robot framework on an experimental task. We believe Robxp stories generation could be integrated as a standard behavior for more complex service robot tasks. Show more

Keywords: Robot experience stories, SitLog, service robot, narrative generation

DOI: 10.3233/JIFS-169511

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3291-3300, 2018

Authors: Pineda, Luis A. | Rodríguez, Arturo | Fuentes, Gibrán | Hernández, Noé | Reyes, Mauricio | Rascón, Caleb | Cruz, Ricardo | Vélez, Ivette | Ortega, Hernando

Article Type: Research Article

Abstract: In this paper a strategy for incorporating a flexible and reliable high-level inference module in service robots is presented. This module is a part of the robot’s cognitive architecture which coordinates perception, inference and action within the robot’s communication and interaction cycle. The present approach relies on an explicit representation of the structure of the task performed by the robot. There are three kinds of inferences that the robot can use opportunistically along the task: (1) diagnosis, (2) decision making and (3) planning; each kind can be used in specific situations of the task structure or performed in arbitrary situations …with recovery purposes when there is an interaction failure. In this latter case the three kinds of inference are performed sequentially in what we call the daily-life inference cycle . The inference cycle allows the incorporation of basic emotions in the robot’s behavior. A case study incorporating these functionalities in the robot Golem-III is presented. The paper is concluded with a reflection on the opportunistic use of inference schemes to support flexible and robust behavior, including the expression of emotions, in service robots. Show more

Keywords: Inference in service robots, robust behavior in service robots, robotics cognitive architecture, the Golem-III robot

DOI: 10.3233/JIFS-169512

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3301-3311, 2018

Authors: Pérez-Espinosa, Humberto | Martínez-Miranda, Juan | Avila-George, Himer | Espinosa-Curiel, Ismael

Article Type: Research Article

Abstract: The advances in social robotics have extended the possibilities of their use in different applications and have also increased the sectors of users to which those applications can benefit. An attractive population of users is children. Recently, there has been a trend towards research in the design of interactive systems for children, as well as in the study of modeling the interaction between children and this type of systems. In this work, we present a study carried out with the objective of analyzing the affective response of children when interacting with a robot using speech-based communication. We collected data through …an experiment using a Wizard of Oz scenario where we induced different affective reactions in the participants. Two type of data were collected and analyzed: 1) a set of evaluators manually created annotations of emotions and attitudes to determine the distribution of emotions during the experiments and evaluate how difficult is the training of automatic classifiers to discriminate different affective states from the acoustic properties of the children’s voices; 2) we used the children’s responses from a self-evaluation questionnaire about their perceptions and preferences towards the robots, modeled with different personalities, to assess whether there are relevant differences according to their different age’s range. We obtained a large children’s speech database that would be a valuable resource for the study of paralinguistic and interaction aspects. Despite the imbalance of the database, we were able to obtain good results for the classification of emotions and attitudes. We also find some relevant differences in how young and older children note the differences in the behaviors of the robots according to the modeled personality. Differences based on children’s age were also found in the preferences towards the two different robots. Show more

Keywords: Children speech analysis, paralinguistic information, emotion recognition, social robots

DOI: 10.3233/JIFS-169513

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3313-3324, 2018

Authors: González-Hernández, Francisco | Zatarain-Cabada, Ramon | Barrón-Estrada, Maria Lucia | Rodríguez-Rangel, Hector

Article Type: Research Article

Abstract: This work presents the application of a convolutional neural network (CNN) used to identify emotions through taken images to students, which are learning Java language with an Intelligent Learning Environment. The CNN contains three convolutional layers, three max-pooling layers, and three neural networks with intermediate dropout connections. The CNN was trained using different emotional databases. One of them was a posed database (RaFD) and two of them were spontaneous databases created specially by us with a content focused on learning-centered emotions. The results show a comparison among three emotion recognition systems. One applying a local binary pattern approach with facial …patches, another applying a geometry-based method, and the last one applying the convolutional network. The analysis presented satisfactory results; the CNN obtained a 95% accuracy for the RaFD database, an 88% accuracy for a learning-centered emotion database and a 74% accuracy for a second learning-centered emotion database. Results are compared against the classifiers support vector machine, k-nearest neighbors, and artificial neural network. Show more

Keywords: Convolutional neural network, educational emotion recognition, face expression database, machine learning, feature extraction

DOI: 10.3233/JIFS-169514

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3325-3336, 2018

Authors: Garcia-Lopez, Francisco Javier | Batyrshin, Ildar | Gelbukh, Alexander

Article Type: Research Article

Abstract: In this paper we measure the relationship between messages in the social media and the stock market prices. First, we measure the correlation and association between the amount of stock related tweets and different financial indicators such as prices, returns and transaction volume. Then, we analyze the content of the messages and test whether the tweets generated during different trends of price change (up, down or steady) can be distinguished by automatic classifiers. Our corpus consist on messages related to nine IT companies and also their daily prices and volume during trading hours for over a period of three months. …Two textual representations were used, bag of words and word embeddings. The tweets were automatically tagged using two thresholds to bin the changes in price. We have found a correlation between the amount of daily messages and the volume of financial transactions. We also found negative association (more specifically, what we define as local trend association) between tweet volume and financial indicators that were not found by using only the correlation analysis. Our main contribution is that the messages generated during a positive, negative and neutral trend can be distinguished by state of the art classifiers. Show more

Keywords: Stock market, twitter, machine learning, bag of words, word embeddings

DOI: 10.3233/JIFS-169515

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3337-3347, 2018

Authors: Ramírez-Chacón, Miguel | Hidalgo-Silva, Hugo | Chávez, Edgar

Article Type: Research Article

Abstract: Many multimedia objects accept an abstract representation as point sets, or point clouds , in the plane. Searching for objects in a collection is traduced to searching for matching point clouds. In this paper algorithms and data structures are given for indexing and searching point clouds. The indexes are implemented using off-the-shelf, popular, software components. Experimental tests were performed on large databases, including a synthetic database of 10 million point clouds (1000 points per cloud) and the MIR Flickr-1M database, which contains 1 million high-resolution images. The performance of the proposed indexes was evaluated according to: Average search time, construction …time, recall@k, memory usage and performance under insertions and deletions. A thorough comparison was performed between the fastest method available in the literature and a repertoire of implementations. The most competitive index is three orders of magnitude faster than the state of the art, in the image database, with recall  @ 1 ≥0.989 for 20% insertions and deletions. Show more

Keywords: Point cloud search, similarity search index, multimedia indexing

DOI: 10.3233/JIFS-169516

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3349-3358, 2018

Authors: Arana-Llanes, Julia Y. | González-Serna, Gabriel | Pineda-Tapia, Rodrigo | Olivares-Peregrino, Víctor | Ricarte-Trives, Jorge J. | Latorre-Postigo, José M.

Article Type: Research Article

Abstract: The Computer Science department at Tecnológico Nacional de México-CENIDET, Mexico, with the collaboration of the Psychological department of the University of Castilla-La Mancha (UCLM), Spain, is on a developing process for the creation of an immersive virtual environment through virtual reality (VR) for the e-learning educational area. Such environment, works through electroencephalographic lectures (EEG) from the students, acquired by a Brain-Computer Interface (BCI), to adapt the virtual content to the profile and needs of the student on real-time basis. This system can detect the accuracy of attention and concentration levels on mental states, for the optimum development of the activities …requested on an e-learning platform; if the student is not on a suitable concentration level, the system is able to induce the student to the requested mental state. The present document shows the proposal of different recommended activities that induce the mentioned mental states and the EEG response of each one. As well, the definition of the ideal learning emotional state that will be included as a part of the future works. It is important to mention that such activities are based on psychological researches that are dedicated to measure the levels of attention, concentration and other executive functions. Show more

Keywords: EEG, attention, concentration, E-learning, human computer interaction (HCI), brain-computer interface (BCI), augmented cognition (AugCog)

DOI: 10.3233/JIFS-169517

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3359-3371, 2018

Authors: Limón, Yensen | Bárcenas, Everardo | Benítez-Guerrero, Edgard | Molero, Guillermo

Article Type: Research Article

Abstract: Context-aware systems are ubiquitous computing systems capable to adapt themselves to a dynamically changing environment. Ensuring consistency in context-aware systems has proved a challenging task due to the inherent expressive power required to model dynamical systems. In the current work, we propose the use of the μ -calculus with converse, an expressive modal logic, for modeling and verifying consistency. In particular, we propose a consistency model for a context-aware communication system. Consistency is tested in terms of the satisfiability of a μ -calculus formula. We show this consistency verification method is correct and a complexity analysis is provided. We also …describe an implementation with several experiments. Show more

Keywords: Context-aware systems, automated reasoning, modal logics

DOI: 10.3233/JIFS-169518

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3373-3383, 2018

Authors: Tiwari, Anoop Kumar | Shreevastava, Shivam | Shukla, K.K. | Subbiah, Karthikeyan

Article Type: Research Article

Abstract: Technological advancement in the area of computing has led to production of huge amount of structured as well as unstructured data. This high dimensional data is very complex to process. Feature selection is one of the widely used techniques for preprocessing of this huge data in predictive analytics. Rough set based feature selection is an approach for handling the vagueness in data and works fine on discrete data but struggles in the continuous case as it requires discretization. This process of discretization leads to information loss. Solution for this problem was given by various authors in form of fuzzy rough …set as well as intuitionistic fuzzy rough set based approaches for feature selection. Intuitionistic fuzzy set has certain benefits over the theory of traditional fuzzy sets such as its ability in a better expression of underlying information as well as its aptness to recite fragile ambiguities of the uncertainty of the objective world. The benefits offered by Intuitionistic fuzzy sets is due to the concurrent contemplation of positive, negative and hesitancy degrees for an object to belong to a set. In this paper, three novel approaches of feature reduction based on intuitionistic fuzzy rough set are presented. For this, a new intuitionistic fuzzy rough set model is established by defining a pair of lower and upper approximations. Furthermore, three new approaches of feature selection based on the degree of dependency by using score function, membership grade and cardinality of intuitionistic fuzzy numbers are introduced. Moreover, the basic results on lower and upper approximations based on rough sets are extended for intuitionistic fuzzy rough sets and analogous results are established. Moreover, a suitable algorithm is given based on our proposed approaches. Finally, the proposed algorithm is applied to an arbitrary example data set and comparison has been made with the previous fuzzy rough set based technique. The proposed algorithm is found to be better performing in terms of selected features. Show more

Keywords: Rough set, fuzzy-rough set, intuitionistic fuzzy-rough set, score function, degree of dependency, T-equivalence relation

DOI: 10.3233/JIFS-169519

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 5, pp. 3385-3394, 2018