Clustering in wireless sensor networks has been widely discussed in the literature as a strategy to reduce power consumption. However, aspects such as cluster formation and cluster head (CH) node assignment strategies have a significant impact on quality of service, as energy savings imply restrictions in application usage and data traffic within the network. Regarding the first aspect, this article proposes a hierarchical routing protocol based on the k-d tree algorithm, taking a partition data structure of the space to organize nodes into clusters. For the second aspect, we propose a reactive mechanism for the formation of CH nodes, with the purpose of improving delay, jitter, and throughput, in contrast with the low-energy adaptive clustering hierarchy/hierarchy-centralized protocol and validating the results through simulation.

In recent years, users are widely intend to express and share their opinions over the Internet. However, due to the characters of social media, it appears negative use of social media. Cyberbullying is one of the abuse behavior in the Internet as well as a very serious social problem. Under this background and motivation, it can help to prevent the happen of cyberbullying if we can develop relevant techniques to discover cyberbullying in social media. Thus, in this paper we propose an approach based on social networks analysis and data mining for cyberbullying detection. In the approach, there are three main techniques for cyberbullying discovery will be studied, including keyword matching technique, opinion mining and social network analysis. In addition to the approach, we will also discuss the experimental design for the evaluation of the performance.

El alto volumen de datos, el tiempo de procesamiento y la visualización de información, son problemas que hoy en día debe enfrentar las organizaciones en el sector de tecnología, en particular el subsistema comercial. En esta investigación se desarrolló un modelo para la toma de decisiones basado en la interacción de los criterios y las etapas del ciclo de ventas. Se usó una herramienta especializada en inteligencia de negocios que facilitó el manejo de grandes volúmenes de datos, su procesamiento y la visualización de la información. Dentro de los resultados obtenidos se encontró una significativa reducción en el tiempo de obtención de la información, pasando de horas a minutos. The high volume of data, the processing time and the visualization of information are problems that organizations in the technology sector, particularly the commercial subsystem, must face today. In this research, a model for decision-making based on the interaction of criteria and stages of the sales cycle was developed. A specialized business intelligence tool was used that facilitated the handling of large volumes of data, its processing and the visualization of information. Among the results obtained, a significant reduction was found in the time of obtaining the information, it went from hours to minutes.