Photographic database development of Nigerian fisheries: a complementary source of information documentation

The paper traces the history of the different documentation media used for information dissemination. Such early media are clay tablets, papyrus, and vellum or parchment codex. The invention of printing however revolutionized the information industry, enabling the production of books in multiple copies. Photography came into documentation mainly to preserve rare materials and those that easily deteriorate. This paper reports the efforts of National Institute for Freshwater Fisheries Research (NIFFR) and Kainji Lake Fisheries Promotion Project (KLFPPP), Nigeria, to develop an Object Oriented Database (OOD) using photographs. The photographs are stored in digitized form on commercial computers, using the program ACDSee 32 for classification, description and retrieval. Specifically the paper focuses on photographs in fisheries as visual communication and expression. Presently, the database contains photo documents about the following aspects of Kainji Lake fisheries: fishing gears and crafts, fish preservation methods

Near-field x-ray phase contrast imaging and phase retrieval algorithm

Theoretical analyses of x-ray diffraction phase contrast imaging and near field phase retrieval method are presented. A new variant of the near field intensity distribution is derived with the optimal phase imaging distance and spatial frequency of object taken into account. Numerical examples of phase retrieval using simulated data are also given. On the above basis, the influence of detecting distance and polychroism of radiation on the phase contrast image and the retrieved phase distribution are discussed. The present results should be useful in the practical application of in-line phase contrast imaging.

Optical intrinsically fuzzy mathematical morphology for gray-scale image processing

Intrinsically fuzzy morphological erosion and dilation are extended to a total of eight operations that have been formulated in terms of a single morphological operation--biased dilation. Based on the spatial coding of a fuzzy variable, a bidirectional projection concept is proposed. Thus, fuzzy logic operations, arithmetic operations, gray-scale dilation, and erosion for the extended intrinsically fuzzy morphological operations can be included in a unified algorithm with only biased dilation and fuzzy logic operations. To execute this image algebra approach we present a cellular two-layer processing architecture that consists of a biased dilation processor and a fuzzy logic processor. (C) 1996 Optical Society of America

Automatically exposing OpenLifeData via SADI semantic Web Services

Background: Two distinct trends are emerging with respect to how data is shared, collected, and analyzed within the bioinformatics community. First, Linked Data, exposed as SPARQL endpoints, promises to make data easier to collect and integrate by moving towards the harmonization of data syntax, descriptive vocabularies, and identifiers, as well as providing a standardized mechanism for data access. Second, Web Services, often linked together into workflows, normalize data access and create transparent, reproducible scientific methodologies that can, in principle, be re-used and customized to suit new scientific questions. Constructing queries that traverse semantically-rich Linked Data requires substantial expertise, yet traditional RESTful or SOAP Web Services cannot adequately describe the content of a SPARQL endpoint. We propose that content-driven Semantic Web Services can enable facile discovery of Linked Data, independent of their location. Results: We use a well-curated Linked Dataset - OpenLifeData - and utilize its descriptive metadata to automatically configure a series of more than 22,000 Semantic Web Services that expose all of its content via the SADI set of design principles. The OpenLifeData SADI services are discoverable via queries to the SHARE registry and easy to integrate into new or existing bioinformatics workflows and analytical pipelines. We demonstrate the utility of this system through comparison of Web Service-mediated data access with traditional SPARQL, and note that this approach not only simplifies data retrieval, but simultaneously provides protection against resource-intensive queries. Conclusions: We show, through a variety of different clients and examples of varying complexity, that data from the myriad OpenLifeData can be recovered without any need for prior-knowledge of the content or structure of the SPARQL endpoints. We also demonstrate that, via clients such as SHARE, the complexity of federated SPARQL queries is dramatically reduced.

OntoFeed um leitor de Feeds com extensão ontológica.

O problema que justifica o presente estudo refere-se à falta de semântica nos mecanismos de busca na Web. Para este problema, o consórcio W3 vem desenvolvendo tecnologias que visam construir uma Web Semântica. Entre estas tecnologias, estão as ontologias de domínio. Neste sentido, o objetivo geral desta dissertação é discutir as possibilidades de se imprimir semântica às buscas nos agregadores de notícia da Web. O objetivo específico é apresentar uma aplicação que usa uma classificação semi-automática de notícias, reunindo, para tanto, as tecnologias de busca da área de recuperação de informação com as ontologias de domínio. O sistema proposto é uma aplicação para a Web capaz de buscar notícias sobre um domínio específico em portais de informação. Ela utiliza a API do Google Maps V1 para a localização georreferenciada da notícia, sempre que esta informação estiver disponível. Para mostrar a viabilidade da proposta, foi desenvolvido um exemplo apoiado em uma ontologia para o domínio de chuvas e suas consequências. Os resultados obtidos por este novo Feed de base ontológica são alocados em um banco de dados e disponibilizados para consulta via Web. A expectativa é que o Feed proposto seja mais relevante em seus resultados do que um Feed comum. Os resultados obtidos com a união de tecnologias patrocinadas pelo consórcio W3 (XML, RSS e ontologia) e ferramentas de busca em página Web foram satisfatórios para o propósito pretendido. As ontologias mostram-se como ferramentas de usos múltiplos, e seu valor de análise em buscas na Web pode ser ampliado com aplicações computacionais adequadas para cada caso. Como no exemplo apresentado nesta dissertação, à palavra chuva agregaram-se outros conceitos, que estavam presentes nos desdobramentos ocasionados por ela. Isto realçou a ligação do evento chuva com as consequências que ela provoca - ação que só foi possível executar através de um recorte do conhecimento formal envolvido.

Os esquemas de FORÇA e a metáfora da GUERRA: uma análise sociocognitiva dos usos do mas em mediação

Neste estudo qualitativo, objetiva-se descrever os usos do conector mas em um corpus de mediação endoprocessual, à luz da Linguística Cognitiva, baseando-se, sobretudo, na Teoria da Metáfora Conceptual e nos conceitos de categorização, esquemas imagéticos e modelos cognitivos idealizados (MCIs). Investigam-se as bases cognitivas que fundamentam os sentidos do mas e a função argumentativa desse conector na mediação, a partir de duas hipóteses gerais, a saber: (i) defende-se que o conector mas funciona como um gatilho para a ativação do MCI de guerra, em termos do qual é conceptualizado o conceito de discussão, como afirmam Lakoff e Johnson (2002[1980]); e (ii) acredita-se que tal conector possa ser caracterizado como uma categoria radial, formada a partir dos diferentes esquemas imagéticos que fundamentam as ocorrências desse elemento na interação. Tendo em vista essas hipóteses, objetiva-se: (i) apontar as funções argumentativas do mas na mediação, sinalizadas pelos mapeamentos metafóricos ativados durante a discussão e (ii) descrever os sentidos evidenciados pelos usos do mas no gênero analisado, os quais são evocados pelos diferentes esquemas imagéticos em que se baseiam. Os resultados indicam que esse conector pode ser compreendido como uma categoria radial, formada a partir de esquemas de força distintos. Além disso, verifica-se que os três usos mais próximos ao centro da categoria relacionam-se fortemente a um confronto ou a uma disputa de posição entre os participantes da interação, enquanto os três mais periféricos são estreitamente ligados a uma estratégia de manutenção da posição argumentativa do falante. Considera-se que esta pesquisa possa colaborar para o estudo do conector mas, devido à observação do comportamento semântico-discursivo desse item em um gênero pouco contemplado, a mediação; e, devido à escolha do paradigma adotado, que permite analisar o conector em todas as suas ocorrências, não havendo necessidade de separar os usos chamados de interfrásticos daqueles denominados inícios acessórios ou pré-começos

The design and implementation of dialogue control in voice operated database inquiry systems

This paper describes work performed as part of the U.K. Alvey sponsored Voice Operated Database Inquiry System (VODIS) project in the area of intelligent dialogue control. The principal aims of the work were to develop a habitable interface for the untrained user; to investigate the degree to which dialogue control can be used to compensate for deficiencies in recognition performance; and to examine the requirements on dialogue control for generating natural speech output. A data-driven methodology is described based on the use of frames in which dialogue topics are organized hierarchically. The concept of a dynamically adjustable scope is introduced to permit adaptation to recognizer performance and the use of historical and hierarchical contexts are described to facilitate the construction of contextually relevant output messages. © 1989.

Segmentation and recognition using structure from motion point clouds

We propose an algorithm for semantic segmentation based on 3D point clouds derived from ego-motion. We motivate five simple cues designed to model specific patterns of motion and 3D world structure that vary with object category. We introduce features that project the 3D cues back to the 2D image plane while modeling spatial layout and context. A randomized decision forest combines many such features to achieve a coherent 2D segmentation and recognize the object categories present. Our main contribution is to show how semantic segmentation is possible based solely on motion-derived 3D world structure. Our method works well on sparse, noisy point clouds, and unlike existing approaches, does not need appearance-based descriptors. Experiments were performed on a challenging new video database containing sequences filmed from a moving car in daylight and at dusk. The results confirm that indeed, accurate segmentation and recognition are possible using only motion and 3D world structure. Further, we show that the motion-derived information complements an existing state-of-the-art appearance-based method, improving both qualitative and quantitative performance. © 2008 Springer Berlin Heidelberg.

Report of the training in database and spatial analysis for Marine Protected Areas staff in Indonesia's BOBLME region, Medan, Indonesia, 30 June-4 July, 2015

Training included: Geographic Information System (GIS)concept and software; Global Positioning System (GPS); Ecological Gap Analysis and Marine Protected Area (MPA) design using Marine Reserve Design using Spatially Explicit Annealing (MARXAN); and cartography.

Bayesian inference for multidimensional NMR image reconstruction

Reconstruction of an image from a set of projections has been adapted to generate multidimensional nuclear magnetic resonance (NMR) spectra, which have discrete features that are relatively sparsely distributed in space. For this reason, a reliable reconstruction can be made from a small number of projections. This new concept is called Projection Reconstruction NMR (PR-NMR). In this paper, multidimensional NMR spectra are reconstructed by Reversible Jump Markov Chain Monte Carlo (RJMCMC). This statistical method generates samples under the assumption that each peak consists of a small number of parameters: position of peak centres, peak amplitude, and peak width. In order to find the number of peaks and shape, RJMCMC has several moves: birth, death, merge, split, and invariant updating. The reconstruction schemes are tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA.

Visual retrieval of concrete crack properties for automated post-earthquake structural safety evaluation

The safety of post-earthquake structures is evaluated manually through inspecting the visible damage inflicted on structural elements. This process is time-consuming and costly. In order to automate this type of assessment, several crack detection methods have been created. However, they focus on locating crack points. The next step, retrieving useful properties (e.g. crack width, length, and orientation) from the crack points, has not yet been adequately investigated. This paper presents a novel method of retrieving crack properties. In the method, crack points are first located through state-of-the-art crack detection techniques. Then, the skeleton configurations of the points are identified using image thinning. The configurations are integrated into the distance field of crack points calculated through a distance transform. This way, crack width, length, and orientation can be automatically retrieved. The method was implemented using Microsoft Visual Studio and its effectiveness was tested on real crack images collected from Haiti.

Parameter optimization for automated concrete detection in image data

Several research studies have been recently initiated to investigate the use of construction site images for automated infrastructure inspection, progress monitoring, etc. In these studies, it is always necessary to extract material regions (concrete or steel) from the images. Existing methods made use of material's special color/texture ranges for material information retrieval, but they do not sufficiently discuss how to find these appropriate color/texture ranges. As a result, users have to define appropriate ones by themselves, which is difficult for those who do not have enough image processing background. This paper presents a novel method of identifying concrete material regions using machine learning techniques. Under the method, each construction site image is first divided into regions through image segmentation. Then, the visual features of each region are calculated and classified with a pre-trained classifier. The output value determines whether the region is composed of concrete or not. The method was implemented using C++ and tested over hundreds of construction site images. The results were compared with the manual classification ones to indicate the method's validity.

Initializing Vision Based Trackers Using Semantic Texton Forests

Vision based tracking can provide the spatial location of project related entities such as equipment, workers, and materials in a large-scale congested construction site. It tracks entities in a video stream by inferring their motion. To initiate the process, it is required to determine the pixel areas of the entities to be tracked in the following consecutive video frames. For the purpose of fully automating the process, this paper presents an automated way of initializing trackers using Semantic Texton Forests (STFs) method. STFs method performs simultaneously the segmentation of the image and the classification of the segments based on the low-level semantic information and the context information. In this paper, STFs method is tested in the case of wheel loaders recognition. In the experiments, wheel loaders are further divided into several parts such as wheels and body parts to help learn the context information. The results show 79% accuracy of recognizing the pixel areas of the wheel loader. These results signify that STFs method has the potential to automate the initialization process of vision based tracking.

ID ENGINE: Image Classifier

C++ Prototype implementation of multi-modal image classification and retrieval method for construction site images

Content-Based Search Engines for Construction Image Databases

Images represent a valuable source of information for the construction industry. Due to technological advancements in digital imaging, the increasing use of digital cameras is leading to an ever-increasing volume of images being stored in construction image databases and thus makes it hard for engineers to retrieve useful information from them. Content-Based Search Engines are tools that utilize the rich image content and apply pattern recognition methods in order to retrieve similar images. In this paper, we illustrate several project management tasks and show how Content-Based Search Engines can facilitate automatic retrieval, and indexing of construction images in image databases.