Soft Computing: Theory Innovations and Problem Solving Benefits

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    UJA Human Activity Recognition multi-occupancy dataset
    ( 2021-01-05) Espinilla, Macarena ; De-La-Hoz-Franco, Emiro ; Bernal Monroy, Edna Rocio ; Ariza-Colpas, Paola ; Mendoza-Palechor, Fabio
    The main purpose of Activity Recognition Systems - ARS is to improve the quality of human life. An ARS uses predictive models to identify the activities that individuals are performing in different environments. Under data-driven approaches, these models are trained and tested in experimental environments from datasets that contain data collected from heterogeneous information sources. When several people interact (multi-occupation) in the environment from which data are collected, identifying the activities performed by each individual in a time window is not a trivial task. In addition, there is a lack of datasets generated from different data sources, which allow systems to be evaluated both from an individual and collective perspective. This paper presents the SaMO – UJA dataset, which contains Single and Multi-Occupancy activities collected in the UJAmI Smart Lab of the University of Jaén (Spain). The main contribution of this work is the presentation of a dataset that includes a new generation of sensors as a source of information (acceleration of the inhabitant, intelligent floor for location, proximity and binary-sensors) to provide a new point of view on the multi-occupancy problem
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    Machine Learning for Software Engineering: a Bibliometric Analysis from 2015 to 2019
    ( 2021-01-05) Heradio, Ruben ; Fernandez-Amoros, David ; Cerrada, Cristina ; Cobo, Manuel J.
    The increase of computer processor speed and the ubiquitous availability of data coming from a diversity of sources (e.g., version control systems, software developers forums, operating system logs, etc.) have boosted the interest in applying machine learning to software engineering. Accordingly, the research literature on this topic has increased rapidly. This paper provides a comprehensive overview of that literature for the last five years. To do so, it examines 1,312 records gathered from Elsevier Scopus, identifying (i) the most productive authors and their collaboration networks, (ii) the countries and institutions that are leading research, (iii) the journals that are publishing the most papers, and (iv) the most important research themes and the highest impacted articles for those themes.
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    A preliminary study of a citizen participation system based on consensus for Decision-making Processes
    ( 2021-01-05) Mata, Francisco ; Verdejo, Angeles ; Pérez, Luis ; Porcel, Carlos
    In this work, we present a novel approach to a citizen participation system based on consensus reaching processes in the context of Smart Cities. One of the characteristics of the Smart Cities is to involve the citizens in their community’s decision-making. The system that we propose here, allows government representatives to raise proposals to the citizen and permit citizens to give their opinions about the proposed problems. As a novelty, citizens can express their opinions with different preference structures (preference orderings, utility values, and fuzzy linguistic preference relations) to make more flexible the system and to close the opinion expression domains to the knowledge degree of users. Moreover, the decision-making is carried out by means of a consensus reaching process to achieve a minimum level of agreement before making a decision. In this way, the final decisions will be better accepted by citizens. To present this preliminary approach, functional and non-functional system requirements along with a few use cases according to the classical development of Software Engineering are shown.
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    A Distribution of Information Granularity to Deal With Inconsistency in Multi-Criteria and Heterogeneous Group Decision Making
    ( 2021-01-05) Cabrerizo, Francisco ; Pérez, Ignacio ; Morente Molinera, Juan Antonio ; Herrera-Viedma, Enrique
    A distribution of information granularity has been implemented in several group decision making approaches to improve the individual consistency in the recent past. However, these approaches cannot be applied for solving decision processes carried out in multi-criteria and heterogeneous contexts. To overcome this shortcoming, we develop a new group decision making model in this study. First, considering fuzzy preference relations, the information granularity is built by means of distributing the flexibility degrees, which are required to improve the consistency, to the individuals. Second, it can handle group decision making processes in which several criteria, having distinct importance weights, are considered. Third, it considers that the preferences communicated by a decision maker have a not identical importance weight for every criterion. To illustrate the proposed group decision making model, a study is carried out via a numerical example. The observations show that this group decision making model can produce consistent decisions.
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    Introduction to the Minitrack on Soft Computing: Theory Innovations and Problem Solving Benefits
    ( 2021-01-05) Pérez, Ignacio ; Cabrerizo, Francisco ; Herrera-Viedma, Enrique