Pedestrian steering behaviour modelling within the built environment

Prediction of pedestrians’ steering behaviours within the built environments under normal and non-panic situations is useful for a wide range of applications, which include social science, psychology, architecture, and computer graphics. The main focus is on prediction of the pedestrian walking paths and the influences from the surrounding environment from the engineering point of view

Sustainable Construction Engineering and Management

This Book is a Printed Edition of the Special Issue which covers sustainability as an emerging requirement in the fields of construction management, project management and engineering. We invited authors to submit their theoretical or experimental research articles that address the challenges and opportunities for sustainable construction in all its facets, including technical topics and specific operational or procedural solutions, as well as strategic approaches aimed at the project, company or industry level. Central to developments are smart technologies and sophisticated decision-making mechanisms that augment sustainable outcomes. The Special Issue was received with great interest by the research community and attracted a high number of submissions. The selection process sought to balance the inclusion of a broad representative spread of topics against research quality, with editors and reviewers settling on thirty-three articles for publication. The Editors invite all participating researchers and those interested in sustainable construction engineering and management to read the summary of the Special Issue and of course to access the full-text articles provided in the Book for deeper analyses

Recent Application in Biometrics

In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers

Behaviour monitoring: investigation of local and distributed approaches

Nowadays, the widespread availability of cheap and efficient unmanned systems (either aerial, ground or surface) has led to significant opportunities in the field of remote sensing and automated monitoring. On the one hand, the definition of efficient approaches to information collection, filtering and fusion has been the focus of extremely relevant research streams over the last decades. On the other hand, far less attention has been given to the problem of ‘interpreting’ the data, thus implementing inference processes able to, e.g., spot anomalies and possible threats in the monitored scenario. It is easy to understand how the automation of the ‘target assessment’ process could bring a great impact on monitoring applications since it would allow sensibly alleviating the analysis burden for human operators. To this end, the research project proposed in this thesis addresses the problem of behaviour assessment leading to the identification of targets that exhibit features “of interest”. Firstly, this thesis has addressed the problem of distributed target assessment based on behavioural and contextual features. The assessment problem is analysed making reference to a layered structure and a possible implementation approach for the middle-layer has been proposed. An extensive analysis of the ‘feature’ concept is provided, together with considerations about the target assessment process. A case study considering a road-traffic monitoring application is then introduced, suggesting a possible implementation for a set of features related to this particular scenario. The distributed approach has been implemented employing a consensus protocol, which allows achieving agreement about high-level, non-measurable, characteristics of the monitored vehicles. Two different techniques, ‘Belief’ and ‘Average’ consensus, for distributed target assessment based on features are finally presented, enabling the comparison of consensus effects when implemented at different level of the considered conceptual hierarchy. Then, the problem of identifying targets concerning features is tackled using a different approach: a probabilistic description is adopted for the target characteristics of interest and a hypothesis testing technique is applied to the feature probability density functions. Such approach is expected to allow discerning whether a given vehicle is a target of interest or not. The assessment process introduced is also able to account for information about the context of the vehicle, i.e. the environment where it moves or is operated. In so doing the target assessment process can be effectively adapted to the contour conditions. Results from simulations involving a road monitoring scenario are presented, considering both synthetic and real-world data. Lastly, the thesis addresses the problem of manoeuvre recognition and behaviour anomalies detection for generic targets through pattern matching techniques. This problem is analysed considering motor vehicles in a multi-lane road scenario. The proposed approach, however, can be easily extended to significantly different monitoring contexts. The overall proposed solution consists in a trajectory analysis tool, which classifies the target position over time into a sequence of ‘driving modes’, and a string-matching technique. This classification allows, as result of two different approaches, detecting both a priori defined patterns of interest and general behaviours standing out from those regularly exhibited from the monitored targets. Regarding the pattern matching process, two techniques are introduced and compared: a basic approach based on simple strings and a newly proposed method based on ‘regular expressions’. About reference patterns, a technique for the automatic definition of a dictionary of regular expressions matching the commonly observed target manoeuvres is presented. Its assessment results are then compared to those of a classic multi-layered neural network. In conclusion, this thesis proposes some novel approaches, both local and distributed, for the identification of the ‘targets of interest’ within a multi-target scenario. Such assessment is solely based on the behaviour actually exhibited by a target and does not involve any specific knowledge about the targets (analytic dynamic models, previous data, signatures of any type, etc.), being thus easily applicable to different scenarios and target types. For all the novel approaches described in the thesis, numerical results from simulations are reported: these results, in all the cases, confirm the effectiveness of the proposed techniques, even if they appear to be open to interpretation because of the inherent subjectivity of the assessment process

Semester Courses and Course Equivalents: Graduate Courses Summary

A list comprised of summaries of all graduate courses and course equivalents at Wright State University

The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed

Spatial ontologies for architectural heritage

Informatics and artificial intelligence have generated new requirements for digital archiving, information, and documentation. Semantic interoperability has become fundamental for the management and sharing of information. The constraints to data interpretation enable both database interoperability, for data and schemas sharing and reuse, and information retrieval in large datasets. Another challenging issue is the exploitation of automated reasoning possibilities. The solution is the use of domain ontologies as a reference for data modelling in information systems. The architectural heritage (AH) domain is considered in this thesis. The documentation in this field, particularly complex and multifaceted, is well-known to be critical for the preservation, knowledge, and promotion of the monuments. For these reasons, digital inventories, also exploiting standards and new semantic technologies, are developed by international organisations (Getty Institute, ONU, European Union). Geometric and geographic information is essential part of a monument. It is composed by a number of aspects (spatial, topological, and mereological relations; accuracy; multi-scale representation; time; etc.). Currently, geomatics permits the obtaining of very accurate and dense 3D models (possibly enriched with textures) and derived products, in both raster and vector format. Many standards were published for the geographic field or in the cultural heritage domain. However, the first ones are limited in the foreseen representation scales (the maximum is achieved by OGC CityGML), and the semantic values do not consider the full semantic richness of AH. The second ones (especially the core ontology CIDOC – CRM, the Conceptual Reference Model of the Documentation Commettee of the International Council of Museums) were employed to document museums’ objects. Even if it was recently extended to standing buildings and a spatial extension was included, the integration of complex 3D models has not yet been achieved. In this thesis, the aspects (especially spatial issues) to consider in the documentation of monuments are analysed. In the light of them, the OGC CityGML is extended for the management of AH complexity. An approach ‘from the landscape to the detail’ is used, for considering the monument in a wider system, which is essential for analysis and reasoning about such complex objects. An implementation test is conducted on a case study, preferring open source applications