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The purpose of this paper is to identify the CSR practices developed by Mexican family and non-family MSMEs. The study also aims to compare the CSR practices carried out by family and non-family businesses in a country with an emergent economy.

The paper opted for an exploratory study using a sample of 384 businesses was selected in the southern state of Quintana Roo, Mexico, distributed in 245 family and 139 non-family businesses and a questionnaire was applied directly to the managers/owners.

The results show that family MSMEs develop CSR practices to a higher extent than non-family ones, mainly on environment and societal dimensions. In addition, CSR practices in family-owned enterprises develop to a higher extent when the manager/owner has more years of experience in the business, has a higher university education and the size of the business is larger.

The study was developed exclusively with a MSMEs sample with a scope only on the southern part of Quintana Roo, Mexico; the shortage of business databases and the stratification of businesses based exclusively on the number of employees. This work presents information that contributes to the state of the art, broadening the existing literature related to CSR in businesses of a country with an emergent economy and an environment where the tourism and commercial sectors predominate.

This paper provides information to government institutions for the establishment of public policies targeted for an increase of CSR activities by businesses in the area. Manager and/or owners can understand the importance of implementing CSR activities within the business as a competitive strategy. It is also important for universities, professors/researchers and for all interested parties.

This paper provides theoretical and empirical evidence about CSR practices carried out among family and non-family MSMEs in an emergent economy.

The Reflective Middleware for Acoustic Management (ReM-AM), based on the Middleware for Cloud Learning Environments (AmICL), aims to improve the interaction between users and agents in a Smart Environment (SE) using acoustic services, in order to consider the unpredictable situations due to the sounds and vibrations. The middleware allows observing, analyzing, modifying and interacting in every state of a SE from the acoustics. This work details an extension of the ReM-AM using the ontology-driven architecture (ODA) paradigm for acoustic management.

This work details an extension of the ReM-AM using the ontology-driven architecture (ODA) paradigm for acoustic management. In this paper are defined the different domains of knowledge required for the management of the sounds in SEs, which are modeled using ontologies.

This work proposes an acoustics and sound ontology, a service-oriented architecture (SOA) ontology, and a data analytics and autonomic computing ontology, which work together. Finally, the paper presents three case studies in the context of smart workplace (SWP), ambient-assisted living (AAL) and Smart Cities (SC).

Future works will be based on the development of algorithms for classification and analysis of sound events, to help with emotion recognition not only from speech but also from random and separate sound events. Also, other works will be about the definition of the implementation requirements, and the definition of the real context modeling requirements to develop a real prototype.

In the case studies is possible to observe the flexibility that the ReM-AM middleware based on the ODA paradigm has by being aware of different contexts and acquire information of each, using this information to adapt itself to the environment and improve it using the autonomic cycles. To achieve this, the middleware integrates the classes and relations in its ontologies naturally in the autonomic cycles.

The main contribution of this work is the description of the ontologies required for future works about acoustic management in SE, considering that what has been studied by other works is the utilization of ontologies for sound event recognition but not have been expanded like knowledge source in an SE middleware. Specifically, this paper presents the theoretical framework of this work composed of the AmICL middleware, ReM-AM middleware and the ODA paradigm.

The authors propose the concept of “Autonomic Cycle for innovation processes,” which defines a set of tasks of data analysis, whose objective is to improve the innovation process in micro-, small and medium-sized enterprises (MSMEs).

The authors design autonomic cycles where each data analysis task interacts with each other and has different roles: some of them must observe the innovation process, others must analyze and interpret what happens in it, and finally, others make decisions in order to improve the innovation process.

In this article, the authors identify three innovation sub-processes which can be applied to autonomic cycles, which allow interoperating the actors of innovation processes (data, people, things and services). These autonomic cycles define an innovation problem, specify innovation requirements, and finally, evaluate the results of the innovation process, respectively. Finally, the authors instance/apply the autonomic cycle of data analysis tasks to determine the innovation problem in the textile industry.

It is necessary to implement all autonomous cycles of data analysis tasks (ACODATs) in a real scenario to verify their functionalities. Also, it is important to determine the most important knowledge models required in the ACODAT for the definition of the innovation problem. Once determined this, it is necessary to define the relevant everything mining techniques required for their implementations, such as service and process mining tasks.

ACODAT for the definition of the innovation problem is essential in a process innovation because it allows the organization to identify opportunities for improvement.

The main contributions of this work are: For an innovation process is specified its ACODATs in order to manage it. A multidimensional data model for the management of an innovation process is defined, which stores the required information of the organization and of the context. The ACODAT for the definition of the innovation problem is detailed and instanced in the textile industry. The Artificial Intelligence (AI) techniques required for the ACODAT for the innovation problem definition are specified, in order to obtain the knowledge models (prediction and diagnosis) for the management of the innovation process for MSMEs of the textile industry.

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

The purpose of this paper is to perform the limiting performance analysis of a vehicle restraint system (seat belt) in order to find the optimal control force, and its pre-acting time that minimizes the risk of injury.

A discrete model of the human thorax is used. A multiobjective optimum design problem is formulated in order to minimize the risk of injuries in case of impact. Several injury criteria are minimized and are required to remain below a safety threshold value.

The authors found which of the objectives are contradictory and which are not. Several of the optimal sets of design variables are analyzed and their performance compared to one another. The results are also compared to the case of not taking in account the pre-acting time. As expected, the results in this case are worse.

As with all limiting performance analysis, the technological implementation restraints of the control force are not taken into account. As such, the solutions must be considered a benchmark to which the actual solution can be compared to.

The limiting performance analysis concept allows us to have a theoretical benchmark to which the real control performance can be compared to.

As far as the authors know, the pre-acting time, and its implications on the improvement of the performance of the control system, is an original contribution to the problem the authors tried to solve.