Assessing the Effects of Myxobolus cerebralis and Other Environmental Factors on the Dynamics, Abundance, and Distribution of Trout Populations in the Logan River, Utah

The presence of nonnative trout and the recent introduction of Myxobolus cerebralis in the Logan River drainage pose a threat to the native Bonneville cutthroat trout population (Oncorhynchus clarki Utah). The variability in the response of susceptible trout populations to M. cerebralis, causing agent of whirling disease, suggests that environmental factors may influence the effects of the parasite in infected environments. I investigated the relationship between temperature, discharge, substrate size, nutrient concentration (nitrogen and phosphorus), periphyton (chlorophyll a), and the relative abundance of Tubifex tubifex to the distribution, and prevalence of M. cerebralis in wild salmonid populations and sentinel fish in the mainstem of the Logan River and two of its tributaries. In addition, I investigated the potential influence of biotic (e.g., food availability, M. cerebralis prevalence) and abiotic factors (e.g., temperature) on the distribution abundance, and condition of salmonid fishes. Differences in mean temperature and discharge across sites explained most (\u3e70%) of the variability in prevalence of M. cerebralis observed along the Logan River. However, the prevalence of the parasite was not related to other factors that can influence its life cycle, such as productivity and substrate composition. The results also indicate that the fish fauna presents a longitudinal change reflected in a zonation pattern. Cutthroat trout dominates the headwaters and high-elevation reaches, while reaches at lower elevations of the mainstem and tributaries were dominated by brown trout. The transition between these species was consistent with changes in environmental characteristics. Cutthroat trout dominates the fish community in mainstream reaches with the lowest average minimum temperature and highest diel temperatures, and where small boulders and small cobbles are the predominant substrate. This study provides insights of the abiotic and biotic factors that affect the distribution, abundance, and condition of salmonid populations along the Logan River. Identifying these factors is crucial to effectively manage this and other trout streams, where ensuring the conservation of native cutthroat trout populations is a priority. Further, I present baseline information of the potential linkages between environmental factors and M. cerebralis distribution and prevelance, which could be used to develop plans to minimize the potential negative effects of this parasite on wild salmonid populations

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

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

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

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

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

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