Advances in Character Recognition

This book presents advances in character recognition, and it consists of 12 chapters that cover wide range of topics on different aspects of character recognition. Hopefully, this book will serve as a reference source for academic research, for professionals working in the character recognition field and for all interested in the subject

Development of a new temperature-controlled oedometer

A new temperature-controlled oedometer has been designed at Imperial College London and commissioned to investigate the thermo-hydro-mechanical (THM) behaviour of soils. The proposed application of the research is the design of underground structures which heat or cool the surrounding soil, such as ground source heating/cooling systems, and geological disposal facilities for nuclear waste. High-quality laboratory test data, which are currently lacking, are required for understanding thermal effects on soil, and for calibrating THM constitutive models, used for modelling soil-structure interactions. In the new equipment, the temperature of the tested specimen is controlled between 5°C and 70°C with a temperature-controlled water bath. For heating above ambient temperature, the water bath is heated directly using three 150W heaters. For cooling below ambient temperature, an external chiller unit is used, in combination with a heat exchanger. Water is continuously circulated through a hollow plate, directly below the specimen, which minimises the temperature gradient across the specimen. A full, thermal and mechanical calibration of the equipment has been carried out. Vertical thermal and mechanical compliance is determined by repeating the full heating/loading path for the proposed test, with no soil specimen in place. The thermal and mechanical corrections are applied separately, not in combination, because of the much larger magnitude of mechanical strains (and associated error). The instrumentation (load cell and displacement transducers) is raised above the lid of the water bath to isolate it from temperature changes. The differential, thermal, lateral expansion of the confining ring and soil has been considered in the calculation of the soil volume, as too has the thermal expansion of the solid phase of the soil in the calculation of the void ratio. The effect of friction, tilting, and compressible components of the equipment (filter papers and porous stones), has been investigated. Based on these tests, the use of filter papers is discouraged for testing in general, and for thermal testing in particular. New methodologies for performing thermal tests using the new equipment have been developed and are presented here. These cover calibration, testing, and data-processing, and make explicit exactly how all measured and calculated values are obtained, including how the calibration is determined and applied. Soil tests have been performed to develop and validate the calibration, testing, and data-processing methodologies, using bentonite clay, Leighton Buzzard sand, and KSS clay (a mixture of kaolin, silt and sand). The results from the final series of thermal tests, on KSS, constitute a high-quality data-set, which could be used to calibrate a constitutive model, such as the IC Thermal model used in the Imperial College Finite Element Program (ICFEP). The effect of repeated thermal cycling on normally-consolidated and over-consolidated soil, and the effect of temperature and temperature history on soil behaviour has been tested. The new temperature-controlled oedometer, together with the new calibration, testing, and data-processing methodologies, can now be used to obtain high-quality data on the one-dimensional thermo-hydro-mechanical properties of other soils.Open Acces

Internal combustion engine sensor network analysis using graph modeling

In recent years there has been a rapid development in technologies for smart monitoring applied to many different areas (e.g. building automation, photovoltaic systems, etc.). An intelligent monitoring system employs multiple sensors distributed within a network to extract useful information for decision-making. The management and the analysis of the raw data derived from the sensor network includes a number of specific challenges still unresolved, related to the different communication standards, the heterogeneous structure and the huge volume of data. In this paper we propose to apply a method based on complex network theory, to evaluate the performance of an Internal Combustion Engine. Data are gathered from the OBD sensor subset and from the emission analyzer. The method provides for the graph modeling of the sensor network, where the nodes are represented by the sensors and the edge are evaluated with non-linear statistical correlation functions applied to the time series pairs. The resulting functional graph is then analyzed with the topological metrics of the network, to define characteristic proprieties representing useful indicator for the maintenance and diagnosis

OAFuser: Towards Omni-Aperture Fusion for Light Field Semantic Segmentation of Road Scenes

Light field cameras can provide rich angular and spatial information to enhance image semantic segmentation for scene understanding in the field of autonomous driving. However, the extensive angular information of light field cameras contains a large amount of redundant data, which is overwhelming for the limited hardware resource of intelligent vehicles. Besides, inappropriate compression leads to information corruption and data loss. To excavate representative information, we propose an Omni-Aperture Fusion model (OAFuser), which leverages dense context from the central view and discovers the angular information from sub-aperture images to generate a semantically-consistent result. To avoid feature loss during network propagation and simultaneously streamline the redundant information from the light field camera, we present a simple yet very effective Sub-Aperture Fusion Module (SAFM) to embed sub-aperture images into angular features without any additional memory cost. Furthermore, to address the mismatched spatial information across viewpoints, we present Center Angular Rectification Module (CARM) realized feature resorting and prevent feature occlusion caused by asymmetric information. Our proposed OAFuser achieves state-of-the-art performance on the UrbanLF-Real and -Syn datasets and sets a new record of 84.93% in mIoU on the UrbanLF-Real Extended dataset, with a gain of +4.53%. The source code of OAFuser will be made publicly available at https://github.com/FeiBryantkit/OAFuser.Comment: The source code of OAFuser will be made publicly available at https://github.com/FeiBryantkit/OAFuse

Detection and identifitication of registration and fishing gear in vessels

Illegal, unreported and unregulated (IUU) fishing is a global menace to both marine ecosystems and sustainable fisheries. IUU products often come from fisheries lacking conservation and management measures, which allows the violation of bycatch limits or unreported catching. To counteract such issue, some countries adopted vessel monitoring systems (VMS) in order to track and monitor the activities of fishing vessels. The VMS approach is not flawless and as such, there are still known cases of IUU fishing. The present work is integrated in a project PT2020 SeeItAll of the company Xsealence and was included in INOV tasks in which a monitoring system using video cameras in the Ports (Non-boarded System) was developed, in order to detect registrations of vessels. This system registers the time of entry or exit of the vessel in the port. A second system (Boarded System) works with a camera placed in each vessel and an automatic learning algorithm detects and records fishing activities, for a comparison with the vessel’s fishing report.A pesca ilegal, não declarada e não regulamentada (INDNR) é uma ameaça global tanto para os ecossistemas marinhos quanto para a pesca sustentável. Os produtos INDNR são frequentemente provenientes de pescas que não possuem medidas de conservação e de gestão, o que permite a violação dos limites das capturas ou a captura não declarada. Para contrariar esse problema, alguns países adotaram sistemas de monitoramento de embarcações (VMS) para acompanhar e monitorar as atividades dos navios de pesca. A abordagem VMS não é perfeita e, como tal, ainda há casos conhecidos de pesca INDNR. O presente trabalho encontra-se integrado num projeto PT2020 SeeItAll da empresa Xsealence. Este trabalho integrado nas tarefas do INOV no qual foi desenvolvido um sistema de monitorização das entradas dos navios nos Portos (Sistema não embarcado) no qual pretende-se desenvolver um sistema que detete as matriculas dos navios registando a hora de entrada e saída do porto com recurso da camaras de vídeo. A outra componente (sistema embarcado) é colocada em cada embarcação uma camara de video e, recorrendo a aprendizagem automática e um sistema de CCTV, são detetadas as atividades de pesca e gravadas, para posterior comparação com o relatório de pesca do navio

Semi-automatic geometric digital twinning for existing buildings based on images and CAD drawings

Despite the emerging new data capturing technologies and advanced modelling systems, the process of geometric digital twin modelling for existing buildings still lacks a systematic and completed framework to streamline. As-is Building Information Model (BIM) is one of the commonly used geometric digital twin modelling approaches. However, the process of as-is BIM construction is time-consuming and needed to improve. To address this challenge, in this paper, a semi-automatic approach is developed to establish a systematic, accurate and convenient digital twinning system based on images and CAD drawings. With this ultimate goal, this paper summarises the state-of-the-art geometric digital twinning methods and elaborates on the methodological framework of this semi-automatic geometric digital twinning approach. The framework consists of three modules. The Building Framework Construction and Geometry Information Extraction (Module 1) defines the locations of each structural component through recognising special symbols in a floor plan and then extracting data from CAD drawings using the Optical Character Recognition (OCR) technology. Meaningful text information is further filtered based on predefined rules. In order to integrate with completed building information, the Building Information Complementary (Module 2) is developed based on neuro-fuzzy system (NFS) and the image processing procedure to supplement additional building components. Finally, the Information Integration and IFC Creation (Module 3) integrates information from Module 1 and 2 and creates as-is Industry Foundation Classes (IFC) BIM based on IFC schema. A case study using part of an office building and the results of its analysis are provided and discussed from the perspectives of applicability and accuracy. Future works and limitations are also addressed

The results of initial analysis of OSTA-1/Ocean Color Experiment (OCE) imagery

Ocean view images from the Ocean Color Experiment (OCE) were produced at three widely separated locations on the Earth. Digital computer enhancement and band ratioing techniques were applied to radiometrically corrected OCE spectral data to emphasize patterns of chlorophyll distribution and, in one shallow, clear water case, bottom topography. The chlorophyll pattern in the Yellow Sea between China and Korea was evident in a scene produced from Shuttle Orbit 24. The effects of the discharge from the Yangtze and other rivers were also observed. Two scenes from orbits 30 and 32 revealed the movement of patches of plankton in the Gulf of Cadiz. Geometrical corrections to these images permitted the existing ocean current velocities in the vicinity to be deduced. The variability in water depth over the Grand Bahama Bank was estimated by using the blue-green OCE channel. The very clear water conditions in the area caused bottom reflected sunlight to produce a sensor signal which was related inversely to the depth of the water