Numerous internet-based applications produce data streams. A data stream is a succession of available data that may shift over time. Data from the Internet of Things (IoT), social media, traffic lights, financial institutions, phone records, sensor data, banking and healthcare systems are examples of data streams. Obtaining knowledge from data streams presents defiances. The noise reduction process is one of them. Detecting and reducing noise is essential to improve the performance of any machine intelligence technique. In this paper, we create a performance evaluation of four different noise detection algorithms on data stream clustering that are implemented in MOA: Micro-cluster-based Continuous Outlier Detection (MCOD), AbstractC, SimpleCOD and AnyOut. We use each of these techniques to assess the quality of clustering produced by the clustering algorithm known as ClusCTA-MEWMA (Clustering based on Centroid Tracking and Exponentially Weighted Moving Average Chart Detection Method). We reference this algorithm as CM. We set up and monitor experiments using datasets created using a random data generator. The results evidence that CM gets better model quality with with Micro-cluster-based Continuous Outlier Detection algorithm.

Nowadays, the water is the most valuable natural resource. Not only humans depend on it; cities, industry, agriculture, among others also do. Water is present in different kinds of sources such as rivers, aqueduct, and wells. For example, water wells has been used on multiple applications such as harvest, human consumption, irrigation, and industry since centuries ago. However, monitoring and control the well is an exhausting duty. For instance, monitoring the pH quality is fundamental for the agriculture, food industry, food chain and farmers healthy. On the other hand, with the inclusion of Internet of Things (IoT) in many economical sectors, this paper takes advantage of this approaches to obtain a cheap solution that helps farmers around the World. Our main contributions are design and deploy a low-cost system based on IoT and cloud-based real-time databases which could be used by farmers to reduce and prevent pollute water consumption.

Every day the devices connected autonomously to the communication networks are increased. New applications arise for this type of interconnected objects, thus offering new alternatives for solutions of any kind, through the use of technology based on ubiquitous computing. That is why this work is inspired by these new technologies for its application in the educational field, with the purpose of contributing to the imposition of the use of IoT as a tool1 in the classroom.

Food security and global sustainability are important challenges for the current planet evolution, being the communities and ecosystems separated from the big cities, the most vulnerable. On the other hand, and in accordance with what is stated by the sustainable development objectives, there is a hypothesis about the supply of energy that can bring benefits and challenges for the communities, and for which the intervention of actors of the academy, the state, is required, the company, the civil society in search of a sustainable development. In the search for energization solutions for communities, it is necessary to carry out engineering designs that consider various socioeconomic variables, in which the incorporation of Information and Communication Technologies can favor the structuring and organization of data related to these different variables.

Research Project done to find out about the existing connection between knowledge and attitude towards sexuality by using ICT strategies in adolescents from 14 to 16 years old attending two public high schools with the objective of increasing the possibilities of offering teenagers with better tools to prevent unintended pregnancy and therefore promote critical thinking in them. The method used was experimental quantitative research with testing, post-testing, and implementation of didactic ICT teaching strategies as well as traditional techniques such as the use of the `Pedagogical Suitcase', a teaching project sponsored by the Colombian Department of Education to promote Sexual Health among citizens. The main results did not show significant differences between the experimental group and the traditional group when the workshops about Sexual Health were over. However, there are differences in favor of the use of ICT strategies. In the experimental group there was a greater decrease in the number of students with low knowledge ranging from 6.5% to 2.2% compared to what happened to the control group which decreased from 8.7% to 6.5%. Regarding dimensions of attitudes towards sexuality, there were changes favoring feelings, behaviors, and thoughts, as well as those presented in the experimental group. Finally, it was concluded that the implementation of didactic ICT strategies in the education of sexuality in adolescents, favors the increment in the level of knowledge and favorable attitudes towards sexuality.

One of the objectives of the Smart Cities is the efficient and sustainable use of transport infrastructures. Sustainability is understood as the application of new technologies to minimize the loss of time and energy, and at the same time, to improve the satisfaction of citizens. Achieving this objective calls for making use of the mobility data collected from the existing transport infrastructure and services, as well as from the citizens themselves. After the data collection process, information must be stored (use of open data bases) and made accessible (available) to specialized applications and users. This paper highlights the opportunity to take advantage of emerging technologies, like the open source data platform CKAN, or to use services for data linked queries (SPARQL endpoint). As an example of application of these technologies to the transport domain, two use cases are presented: the proposed implementation of an information access point and a national project called “CONECTA”.

This paper studies the possibility of classifying coffee beans by using their features of color, shape and size. The process of acquiring the images were done in controlled lighting conditions.Based on segmented images, color, shape and size provide information about the physical alteration in green coffee beans, during the growing and drying process that affect the flavor and taste of the drink by Developing a computer program to sort coffee beans by typesIn the case of color images are analyzed in RGB space, which were preprocessor in order to reduce noise and separate from the background and enhance its features. The location was used for an algorithm for identifying and setting contours ellipse, an algorithm Mahalanobis distance classifier, an algorithm called Flood of growth, for the segmentation of those defective grains.The emergence of methods that take advantage of technological advances is an option whose benefits encourage the study of new possibilities. The classification of coffee beans throughout the analysis of images is a very promising because it is a minimally invasive method and the exposure of the grains are not visible to look deteriorates significantly.Many farmers sort their coffee beans by hand but only a few thousand dollars invested in a automatic sorting optical machine such us Sortex or Xeltron. In this paper we develop algorithms based on image processing techniques for the classification of defective beans

In Colombia doesn't exist a digital exchange standard for financial information, the problem arises when the information is reported before regulation entities that asks enterprises for this information in different formats hardening their consolidation. This work describes the process developed by the Research Group Prisma from UNAB in concordance with his relationship with state organizations and with collaboration from an I+D organization for the progress in this country in XBRL (eXtensible Business Reporting Language) [4], and for the development of one of their products.

The present paper describes the main characteristics and components of the tool developed for integrating the definition of profiles for semantic web services. This tool is based on the languages DAML-S and OWL-S and it includes the ontology visualization and consistency verification that specify the concepts a web service interacts with. Starting from a service description interpreted by a computer and by the means used for accessing the service, it is possible to find out which software agents use the service. The tool can generate information in different formats, such as the SVG format proposed by the W3C, for representing graphic information based on XML. The tool was developed in Java language and is being used for the visualization of ontologies and for the semantic description of services in traffic information systems that the LISITT group (Laboratorio Integrado de Sistemas Inteligentes y Tecnologías de la información de Tráfico) developed at the Robotics Institute at the University of Valencia.

This paper describes the main contributions in relation with the develop of an XBRL (Extensible Business Reporting Language) taxonomy proposed by the PRISMA research group at University UNAB. This taxonomy has been developed for public institutions in Colombia. This taxonomy is based on the information exchange of financial information. It is also described the creation of a wiki system which includes real information of existing XBRL projects in the world and the creation of a demostration center of XBR reports.