Linux ubuntu server

Existen en la actualidad gran variedad de distribuciones libres del Sistema Operativo Linux, el cual ha ganado un espacio preponderante por sus características de multiusuario, multitarea, estabilidad, seguridad, conectividad, escalabilidad y compatibilidad con gran variedad de aplicaciones. Una de las distribuciones más usadas en diferentes ámbitos, entre ellos el científico, académico, industrial y comercial, es la distribución UBUNTU, ésta ha sido patrocinada por la empresa Canonical Ltda, organización británica propiedad del sudafricano Mark Shuttleworth. UBUNTU posee múltiples herramientas de configuración de servicios tales como DHCP (Dynamic Host Configuration Protocol), DNS (Domain Name System), LDAP y SAMBA, PROXY y el servidor WEB APACHE, entre otros. Por ello su funcionalidad es bastante amplia en lo referente a procesos de configuración de servicios para estaciones de trabajo y servidores. Organización británica propiedad del sudafricano Mark Shuttleworth. UBUNTU posee múltiples herramientas de configuración de servicios tales como DHCP (Dynamic Host Configuration Protocol), DNS (Domain Name System), LDAP y SAMBA, PROXY y el servidor WEB APACHE, entre otros. Por ello su funcionalidad es bastante amplia en lo referente a procesos de configuración de servicios para estaciones de trabajo y servidores

Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems

This paper presents a voltage sensitivity analysis with respect to the real power injected with renewable energies to determine the optimal integration of distributed generation (DG) in distribution systems (DS). The best nodes where the power injections improve voltages magnitudes complying with the constraints are determined. As it is a combinatorial problem, particle swarm optimization (PSO) and simulated annealing (SA) were used to change injections from 10% to 60% of the total power load using solar and wind generators and find the candidate nodes for installing power sources. The method was tested using the 33-node, 69-node and 118-node radial distribution networks. The results showed that the best nodes for injecting real power with renewable energies were selected for the distribution network by using the voltage sensitivity analysis. Algorithms found the best nodes for the three radial distribution networks with similar values in the maximum injection of real power, suggesting that this value maintains for all the power system cases. The injections applied to the different nodes showed that voltage magnitudes increase significantly, especially when exceeding the maximum penetration of DG. The test showed that some nodes support injections up to the limits, but the voltages increase considerably on all nodes

Feature selection by multi-objective optimization: application to network anomaly detection by hierarchical self-organizing maps.

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organizing Maps (GHSOM) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labeled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.This work has been funded by FEDER funds and the Ministerio de Ciencia e Innovación of the Spanish Government under Project No. TIN2012-32039

Navegador ontológico matemático-NOMAT

The query algorithms in search engines use indexing, contextual analysis and ontologies, among other techniques, for text search. However, they do not use equations due to their writing complexity. NOMAT is a prototype of mathematical expression search engine that seeks information both in thesaurus and internet, using ontological tool for filtering and contextualizing information and LaTeX editor for the symbols in these expressions. This search engine was created to support mathematical research. Compared to other Internet search engines, NOMAT does not require prior knowledge of LaTeX, because has an editing tool which enables writing directly the symbols that make up the mathematical expression of interest. The results obtained were accurate and contextualized, compared to other commercial and no-commercial search engines.Los algoritmos de consulta de los motores de búsqueda utilizan indexación, análisis contextual y ontologías, entre otras técnicas, para la búsqueda de texto. Sin embargo, no utilizan ecuaciones debido a su complejidad de escritura. Nomat es un prototipo de motor de búsqueda de expresión matemática que busca información tanto en tesauro como en Internet, utilizando la Herramienta ontológica para filtrar y contextualizar información y editor de látex para los símbolos de estas expresiones. Este buscador fue creado para apoyar la investigación matemática. En comparación con otros motores de búsqueda de Internet, Nomat no requiere conocimientos previos de látex, ya que cuenta con una herramienta de edición que permite escribir directamente los símbolos que componen la expresión matemática de interés. Los resultados obtenidos fueron precisos y contextualizados, en comparación con otros motores de búsqueda comerciales y no comerciales

Discovering similarities in Landsat satellite images using the Kmeans method

This article different ways for the treatment and identification of similarities in satellite images. By means of the systematic review of the literature it is possible to know the different existing forms for the treatment of this type of objects and by means of the implementation that is described, the operation of the K-means algorithm is shown to help the segmentation and analysis of characteristics associated to the color. In this type of objects, a descriptive analysis of the results thrown by the method is finally carried out

Mediación de los objetos virtuales de aprendizaje en el desarrollo de competencias matemáticas en estudiantes de ingeniería

El presente artículo analiza la contribución de los Objetos Virtuales de Aprendizaje (OVA) al desarrollo de competencias matemáticas en estudiantes de ingeniería de dos universidades de Barranquilla-Colombia. Se aplicó una prueba diagnóstica a 120 estudiantes representados en dos grupos (control y experimental). Durante un semestre académico se incorporó OVA en el área de cálculo diferencial. Al final del periodo fue aplicada una evaluación que permitió comparar el grado de apropiación de conocimientos matemáticos. Los estudiantes del grupo experimental desarrollaron habilidades matemáticas un 25.9% por encima del grupo control y el 55%, consideran que son herramientas eficaces para reforzar conocimientos de cálculo diferencial. Se concluyó que la incorporación de OVA al proceso de enseñanza-aprendizaje con la orientación del docente, motiva a los estudiantes por aprender, potencia las habilidades matemáticas de interpretación, modelación de situaciones matemáticas y ejecución de procedimientos para dar solución a distintos problemas de cálculo diferencial.In the present article the contribution of Virtual Learning Objects (VLO) to the development of mathematical competences in engineering students from two universities in Barranquilla-Colombia is analyzed. A diagnostic test was applied to 120 students represented in two groups (control and experimental). During the academic semester, VLO were incorporated in the differential-calculus subject. At the end of the period a test that allowed to compare the mathematical knowledge was applied. The students of the experimental group developed mathematical skills 25.9% above the control group, and 55% consider that Virtual Learning Objects are effective tools to improve differential-calculus knowledge. It was concluded that the incorporation of OVA to teaching-learning process with the teacher’s guidance, motivates the students to learn, enhances the mathematical skills of interpretation, mathematical situations modeling and execution of procedures to solve different differential calculus problems.Universidad de la Cost

Network Anomaly Detection with Bayesian Self-Organizing Maps

The growth of the Internet and consequently, the number of interconnected computers through a shared medium, has exposed a lot of relevant information to intruders and attackers. Firewalls aim to detect violations to a predefined rule set and usually block potentially dangerous incoming traffic. However, with the evolution of the attack techniques, it is more difficult to distinguish anomalies from the normal traffic. Different intrusion detection approaches have been proposed, including the use of artificial intelligence techniques such as neural networks. In this paper, we present a network anomaly detection technique based on Probabilistic Self-Organizing Maps (PSOM) to differentiate between normal and anomalous traffic. The detection capabilities of the proposed system can be modified without retraining the map, but only modifying the activation probabilities of the units. This deals with fast implementations of Intrusion Detection Systems (IDS) necessary to cope with current link bandwidths

Efficient approaches to agile cost estimation in software industries: a project-based case study

Agile was invented to improve and overcome the traditional deficiencies of software development. At present, the agile model is used in software development very vastly due to its support to developers and clients. Agile methodology increases the interaction between the developer-client, and it makes software product defects free. The agile model is fast and becoming more popular because of its features and flexibility. The study shows that the agile software development model is an efficient and effective software development strategy that easily accommodates user changes, but it is not free from errors or shortcomings. The study shows that COCOMO and Planning Poker are famous cost estimation procedures, but are not ingenious for agile development. We conduct a study on real-time projects from multinational software industries using different estimation approaches to estimate the project’s cost and time. We thoroughly explain these projects with the limitations of the techniques. The study has proven that the traditional and modern estimation approaches still have limitations to accurate estimation of projects