Proposal to permit experimental artificial reefs inside and outside the Big Sycamore Canyon Ecological Reserve

(Document pdf contains 19 pages)

Proposal for improving fishing opportunities off Pt. Loma by construction of an artificial reef

(Document pdf contains 42 pages)

Report of Pendleton artificial reef studies with recommendations for constructing a kelp reef

(Document pdf contains 64 pages)

Beach surveys of South Carlsbad State Beach onshore of Carlsbad artificial reef

(Document pdf contains 9 pages)

A report of biological observations at Topanga artificial reef and Santa Monica Bay artificial reef

(Document pdf contains 25 pages)

Biological surveys of five southern artificial reefs: Oceanside #1, Oceanside #2, Carlsbad, Pacific Beach, and Mission Bay

(Document pdf contains 19 pages)

Observations of the biological communities at Bolsa Chica artificial reef

Bolsa Chica Artificial Reef (BCAR) was constructed in November 1986 with 10,400 tons of concrete rubble and eight concrete and steel barges. Prior to any additional augmentation of BCAR, the u.s. Army Corps of Engineers and the California Coastal Commission required the California Department of Fish and Game (CDFG) to survey the bioloqical communities on and around BCAR. In April 1992, qualitative surveys of the biological communities were conducted on one of the eight modules at BCAR and at a nearby sand-only site. One of the modules, Module D, located in 90 feet of water (MLLW), was surveyed for fish, macroinvertebrates, and turf community organisms (small plants and sessile animals). Twelve species of fish were observed, including kelp bass (Paralabrax clathratus) and barred sand bass (P. nebulifer). Eight macroinvertebrate species were observed, rock scallops (Crassedoma giganteum) being the most abundant. The turf community was comprised of thirteen invertebrate taxa, among which erect ectoprocts (Bugula spp.) were the most numerous. Two species of foliose red algae (Rhodymenia pacifica and Anisocladella pacifica) were also observed. The reef has reached an advanced stage of successional development with fish and invertebrate communities diverse and well established. However, due,.to its depth and the turbidity of surrounding waters, this reef is not likely to ever support a diverse algal community. The diversity and abundance of fish and macroinvertebrates were, as to be expected, much lower in the nearby sand-only site. Only two species of fish and seven macroinvertebrate species were observed. Of these, only the sea pen, Stylatula elongata, was common. Overall, when compared to nearby sand-only habitats, Bolsa Chica Artificial Reef appears to contribute substantially to the local biological productivity. In addition, the concrete rubble used in BCAR' s construction appears to be performing as well as the quarry rock used in all of CDFG's experimental reefs. (Document pdf contains 22 pages)

A report of biological observations at Pacific Beach artificial reef, Oceanside artificial reef, and Santa Monica Bay artificial reef

(Document pdf contains 16 pages)

A report of biological observations at Oceanside #1 and #2 artificial reefs, Carlsbad artificial reef, Pacific Beach artificial reef, and Mission Bay Park artificial reef

(Document pdf contains 22 pages)

Estudio bibliográfico de sistemas educativos en el ámbito de la inteligencia artificial

Este informe trata de reunir en un documento la revisión bibliográfica realizada como base necesaria para el desarrollo de una tesis doctoral sobre las interacciones entre profesores y alumnos en las sesiones tradicionales de aprendizaje. Nuestra investigación se enmarca en los trabajos del grupo GALAN de la Facultad de Informática de San Sebastián de la UPV-EHU, que se dedica desde sus comienzos al desarrollo de herramientas educativas flexibles dotadas de comportamiento inteligente. En este informe presentamos un estudio bibliográfico de sistemas educativos en el ámbito de la inteligencia artificial. En particular se centra en los siguientes aspectos: tutores inteligentes, sistemas educativos para la web y herramientas de ayuda al profesor. Además se incluye una revisión del modelado de usuario y un estudio de técnicas para el análisis de datos.

Pendleton Artificial Reef: annual progress report presented to Southern California Edison Company

(PDF contains 82 pages.)

Influence of Training Set Selection in Artificial Neural Network-Based Propagation Path Loss Predictions

This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented.

Técnicas de Inteligencia Artificial integradas en una aplicación de gestión para una casa rural en JQueryMobile y Protégé Frames.

Este proyecto plantea el reto de realizar una aplicación web para la gestión y control de una casa rural desde dispositivos móviles como smartphones y tabletas, con una interfaz de propietario para gestionar de manera dinámica las diferentes partes de la misma, así como la inclusión de una zona de niños donde se aplicarán tecnologías de Inteligencia Artificial en concreto representación del conocimiento mediante “frames”, donde se permitirá a los usuarios realizar preguntas al sistema para intentar adivinar un árbol que previamente la propietaria de la casa rural habrá establecido. El objetivo no es elaborar un sistema experto, tarea que requeriría muchas más horas que las que corresponden a un proyecto de fin de carrera, sino comprobar la posibilidad de integración de estas herramientas en una aplicación orientada a dispositivos móviles. Se emplearán las funcionalidades de HTML5 para la inclusión de la “zona explorador” donde los niños podrán geo localizar árboles, así como su posterior búsqueda a modo de GPS donde los usuarios podrán ver donde está situado el árbol que desean buscar y su posición actual, la cual se irá actualizando automáticamente.

Artificial fertilization of the eggs, and rearing and identification of the larvae of the anchoveta, Cetengraulis mysticetus

ENGLISH: The anchoveta, Cetengraulis mysticetus (Günther), is an important bait fish used to capture tunas in the Eastern Tropical Pacific Ocean. Contributions to the early life history of this species in the Gulf of Panama were made by Simpson (1959), who was able to identify deductively the planktonic egg of the anchoveta from 10 other anchovy eggs concurrently present. He also reared these planktonic eggs in the laboratory and described the resultant larvae to the age of 48 hours after hatching. Because of the lack of differences among the anchovy larvae, this description does not permit the identification of anchoveta larvae from those of other engraulid species. Furthermore, while adult specimens are easily recognized, up to the present it has not been possible to extend the identification of the juvenile anchoveta to specimens smaller than about 25 mm. The purpose of this study, therefore, was to identify anchoveta from the time of hatching to about 25 mm. SPANISH: La anchoveta, Cetengraulis mysticetus (Günther), es un importante pez de carnada que se emplea en la captura de los atunes en el Océano Pacífico Oriental Tropical. Simpson (1959) logró identificar deductivamente el huevo planctónico de la anchoveta al separarlo de otros diez huevos de anchoas que se encuentran al mismo tiempo, contribuyendo de esta manera a conocer los primeros estados de la historia natural de esta especie en el Golfo de Panamá. El también estableció un criadero en el laboratorio con estos huevos planctónicos y describió las larvas resultantes hasta la edad de 48 horas después de la eclosión. Debido a que no hay diferencias entre las larvas de las anchoas, esta descripción no permite identificar las larvas de la anchoveta de las otras especies de engráulidos. Más aun, a pesar de que los especímenes adultos son fácilmente reconocibles, hasta ahora no ha sido posible identificar la anchoveta juvenil de menos de unos 25 mm. Consecuentemente, el propósito del presente estudio ha sido el de identificar al anchoveta desde el momento de la eclosión hasta que tiene unos 25 mm.