Inteligência coopetitiva setorial: uma proposta de modelo

The business environment context points at the necessity of new forms of management for the sustainable competitiveness of organizations through time. Coopetition is characterized as an alternative in the interaction of different actors, which compete and cooperate simultaneously, in the pursuit of common goals. This dual relation, within a gain-increasing perspective, converts competitors into partners and fosters competitiveness, especially that of organizations within a specific sector. The field of competitive intelligence has, in its turn, assisted organizations, individually, in the systematization of information valuable to decision-making processes, which benefits competitiveness. It follows that it is possible to combine coopetition and competitive intelligence in a systematized process of sectorial intelligence for coopetitive relations. The general aim of this study is, therefore, to put forth a model of sectorial coopetitive intelligence. The methodological outlining of the study is characterized as a mixed approach (quantitative and qualitative methods), of an applied nature, of exploratory and descriptive aims. The Coordination of the Strategic Roadmapping Project for the Future of Paraná's Industry is the selected object of investigation. Protocols have been designed to collect primary and secondary data. In the collection of the primary ata, online questionary were sent to the sectors selected for examination. A total of 149 answers to the online questionary were obtained, and interviews were performed with all embers of the technical team of the Coordination, in a total of five interviewees. After the collection, all the data were tabulated, analyzed and validated by means of focal groups with the same five members of the Coordination technical team, and interviews were performed with a representative of each of the four sectors selected, in a total of nine participants in the validation. The results allowed the systematization of a sectorial coopetitive intelligence model called ICoops. This model is characterized by five stages, namely, planning, collection, nalysis, project development, dissemination and evaluation. Each stage is detailed in inputs, activities and outputs. The results suggest that sectorial coopetition is motivated mainly by knowledge sharing, technological development, investment in R&D, innovation, chain integration and resource complementation. The importance of a neutral institution has been recognized as a facilitator and incentive to the approximation of organizations. Among the main difficulties are the financing of the projects, the adhesion of new members, the lack of tools for the analysis of information and the dissemination of the actions.

Inteligência coletiva e gestão do conhecimento: uma aplicação na rede social Facebook

Social networks rely on concepts such as collaboration, cooperation, replication, flow, speed, interaction, engagement, and aim the continuous sharing and resharing of information in support of the permanent social interaction. Facebook, the largest social network in the world, reached, in May 2016, the mark of 1.09 billion active users daily, draining 161.7 million hours of users’ attention to the website every day. These users share 4.75 billion units of content daily. The research presented in this dissertation aims to investigate the management of knowledge and collective intelligence, from the introduction of mechanisms that aim to enable users to manage and organize current information in the feeds from Facebook groups in which they participate, turning Facebook into a collective knowledge and information management device that goes far beyond mere interaction and communication among people. The adoption of Design Science Research methodology is intended to instill the "genes" of collective intelligence, as presented in the literature, in the computational artifact being developed, so that intelligence can be managed and used to create even more knowledge and intelligence to and by the group. The main theoretical contribution of this dissertation is to discuss knowledge management and collective intelligence in a complementary and integrated manner, showing how efforts to obtain one also contribute to leveraging the other.

Navegação de um robô móvel baseado em um modelo de consciência artificial

This work presents a study about a the Baars-Franklin architecture, which defines a model of computational consciousness, and use it in a mobile robot navigation task. The insertion of mobile robots in dynamic environments carries a high complexity in navigation tasks, in order to deal with the constant environment changes, it is essential that the robot can adapt to this dynamism. The approach utilized in this work is to make the execution of these tasks closer to how human beings react to the same conditions by means of a model of computational consci-ousness. The LIDA architecture (Learning Intelligent Distribution Agent) is a cognitive system that seeks tomodel some of the human cognitive aspects, from low-level perceptions to decision making, as well as attention mechanism and episodic memory. In the present work, a computa-tional implementation of the LIDA architecture was evaluated by means of a case study, aiming to evaluate the capabilities of a cognitive approach to navigation of a mobile robot in dynamic and unknown environments, using experiments both with virtual environments (simulation) and a real robot in a realistic environment. This study concluded that it is possible to obtain benefits by using conscious cognitive models in mobile robot navigation tasks, presenting the positive and negative aspects of this approach.

Protocolo de roteamento para redes oportunistas utilizando otimização por enxame de partículas

In this research work, a new routing protocol for Opportunistic Networks is presented. The proposed protocol is called PSONET (PSO for Opportunistic Networks) since the proposal uses a hybrid system composed of a Particle Swarm Optimization algorithm (PSO). The main motivation for using the PSO is to take advantage of its search based on individuals and their learning adaptation. The PSONET uses the Particle Swarm Optimization technique to drive the network traffic through of a good subset of forwarders messages. The PSONET analyzes network communication conditions, detecting whether each node has sparse or dense connections and thus make better decisions about routing messages. The PSONET protocol is compared with the Epidemic and PROPHET protocols in three different scenarios of mobility: a mobility model based in activities, which simulates the everyday life of people in their work activities, leisure and rest; a mobility model based on a community of people, which simulates a group of people in their communities, which eventually will contact other people who may or may not be part of your community, to exchange information; and a random mobility pattern, which simulates a scenario divided into communities where people choose a destination at random, and based on the restriction map, move to this destination using the shortest path. The simulation results, obtained through The ONE simulator, show that in scenarios where the mobility model based on a community of people and also where the mobility model is random, the PSONET protocol achieves a higher messages delivery rate and a lower replication messages compared with the Epidemic and PROPHET protocols.