Can you describe him for me? A technique for semantic person search in video

From a law enforcement standpoint, the ability to search for a person matching a semantic description (i.e. 1.8m tall, red shirt, jeans) is highly desirable. While a significant research effort has focused on person re-detection (the task of identifying a previously observed individual in surveillance video), these techniques require descriptors to be built from existing image or video observations. As such, person re-detection techniques are not suited to situations where footage of the person of interest is not readily available, such as a witness reporting a recent crime. In this paper, we present a novel framework that is able to search for a person based on a semantic description. The proposed approach uses size and colour cues, and does not require a person detection routine to locate people in the scene, improving utility in crowded conditions. The proposed approach is demonstrated with a new database that will be made available to the research community, and we show that the proposed technique is able to correctly localise a person in a video based on a simple semantic description.

Explicit, latent and meta-criteria : types of criteria at play in professional judgement practice

This paper engages with debates about whether comprehensive prior specification of criteria and standards is sufficient for informed professional judgement. A preoccupation has emerged with the specificity and explication of criteria intended to regulate judgement. This has resulted in criteria-compliance in the use of defined standards to validate judgements and improve reliability and consistency. Compliance has become a priority, the consequence being the prominence of explicit criteria, to the lack of acknowledgement of the operation of latent and meta-criteria within judgement practice. This paper examines judgement as a process involving three categories of assessment criteria in the context of standards-referenced systems: explicit, latent and meta-criteria. These are understood to be wholly interrelated and interdependent. A conceptualisation of judgement involving the interplay of the three criteria types is presented with an exploration of how they function to focus or alter assessments of quality in judgements of achievement in English and Mathematics.

The integrated land use and transportation indexing model : assessing the sustainability of the Gold Coast, Australia

Urban sustainability and sustainable urban development concepts have been identified as the ultimate goal of many contemporary planning endeavours and have become central concepts on which the urban development policies are formulated. In the confinement of these concepts, land use and transport integration has been highlighted as one of the most important policy objectives considering the interrelationship between them and available intervention means of planning. While its interpretation varies, in Australia, it has been embraced as integration of land use and transport planning/policies and been an integral part of regional and local plans. Accordingly, a number of principles have been defined to guide its implementation, to name a few, planning for compact and connected urban development, encouraging active transport modes, creation of mixed-use activity centres and public transport precincts, provision of high quality public transport services, and enhancing character and amenity of urban areas. However, there is lack of an evaluation framework to measure the extent of achievement of implementation of these principles. In pursuit of filling this gap, this study aims to devise an evaluation framework to measure the performance of urban settings according to the integration principles in South East Queensland, Australia context and to demarcate problematic areas which can be intervened by planning tools...

Real, complex, and binary semantic vectors

This paper presents a combined structure for using real, complex, and binary valued vectors for semantic representation. The theory, implementation, and application of this structure are all significant. For the theory underlying quantum interaction, it is important to develop a core set of mathematical operators that describe systems of information, just as core mathematical operators in quantum mechanics are used to describe the behavior of physical systems. The system described in this paper enables us to compare more traditional quantum mechanical models (which use complex state vectors), alongside more generalized quantum models that use real and binary vectors. The implementation of such a system presents fundamental computational challenges. For large and sometimes sparse datasets, the demands on time and space are different for real, complex, and binary vectors. To accommodate these demands, the Semantic Vectors package has been carefully adapted and can now switch between different number types comparatively seamlessly. This paper describes the key abstract operations in our semantic vector models, and describes the implementations for real, complex, and binary vectors. We also discuss some of the key questions that arise in the field of quantum interaction and informatics, explaining how the wide availability of modelling options for different number fields will help to investigate some of these questions.

A decision support system for sustainable urban development : the integrated land use and transportation indexing model

Broad, early definitions of sustainable development have caused confusion and hesitation among local authorities and planning professionals. This confusion has arisen because loosely defined principles of sustainable development have been employed when setting policies and planning projects, and when gauging the efficiencies of these policies in the light of designated sustainability goals. The question of how this theory-rhetoric-practice gap can be filled is the main focus of this chapter. It examines the triple bottom line approach–one of the sustainability accounting approaches widely employed by governmental organisations–and the applicability of this approach to sustainable urban development. The chapter introduces the ‘Integrated Land Use and Transportation Indexing Model’ that incorporates triple bottom line considerations with environmental impact assessment techniques via a geographic, information systemsbased decision support system. This model helps decision-makers in selecting policy options according to their economic, environmental and social impacts. Its main purpose is to provide valuable knowledge about the spatial dimensions of sustainable development, and to provide fine detail outputs on the possible impacts of urban development proposals on sustainability levels. In order to embrace sustainable urban development policy considerations, the model is sensitive to the relationship between urban form, travel patterns and socio-economic attributes. Finally, the model is useful in picturing the holistic state of urban settings in terms of their sustainability levels, and in assessing the degree of compatibility of selected scenarios with the desired sustainable urban future.

Semantic judgement of medical concepts : combining syntagmatic and paradigmatic information with the tensor encoding model

This paper outlines a novel approach for modelling semantic relationships within medical documents. Medical terminologies contain a rich source of semantic information critical to a number of techniques in medical informatics, including medical information retrieval. Recent research suggests that corpus-driven approaches are effective at automatically capturing semantic similarities between medical concepts, thus making them an attractive option for accessing semantic information. Most previous corpus-driven methods only considered syntagmatic associations. In this paper, we adapt a recent approach that explicitly models both syntagmatic and paradigmatic associations. We show that the implicit similarity between certain medical concepts can only be modelled using paradigmatic associations. In addition, the inclusion of both types of associations overcomes the sensitivity to the training corpus experienced by previous approaches, making our method both more effective and more robust. This finding may have implications for researchers in the area of medical information retrieval.

A micro-level indexing model for assessing urban ecosystem sustainability

Purpose – As a consequence of rapid urbanisation and globalisation, cities have become the engines of population and economic growth. Hence, natural resources in and around the cities have been exposed to externalities of urban development processes. This paper introduces a new sustainability assessment approach that is tested in a pilot study. The paper aims to assist policy-makers and planners investigating the impacts of development on environmental systems, and produce effective policies for sustainable urban development. Design/methodology/approach – The paper introduces an indicator-based indexing model entitled “Indexing Model for the Assessment of Sustainable Urban Ecosystems” (ASSURE). The ASSURE indexing model produces a set of micro-level environmental sustainability indices that is aimed to be used in the evaluation and monitoring of the interaction between human activities and urban ecosystems. The model is an innovative approach designed to assess the resilience of ecosystems towards impacts of current development plans and the results serve as a guide for policymakers to take actions towards achieving sustainability. Findings – The indexing model has been tested in a pilot case study within the Gold Coast City, Queensland, Australia. This paper presents the methodology of the model and outlines the preliminary findings of the pilot study. The paper concludes with a discussion on the findings and recommendations put forward for future development and implementation of the model. Originality/value – Presently, there is a few sustainability indices developed to measure the sustainability at local, regional, national and international levels. However, due to challenges in data collection difficulties and availability of local data, there is no effective assessment model at the microlevel that the assessment of urban ecosystem sustainability accurately. The model introduced in this paper fills this gap by focusing on parcel-scale and benchmarking the environmental performance in micro-level.

Finding additional semantic entity information for search engines

Entity-oriented search has become an essential component of modern search engines. It focuses on retrieving a list of entities or information about the specific entities instead of documents. In this paper, we study the problem of finding entity related information, referred to as attribute-value pairs, that play a significant role in searching target entities. We propose a novel decomposition framework combining reduced relations and the discriminative model, Conditional Random Field (CRF), for automatically finding entity-related attribute-value pairs from free text documents. This decomposition framework allows us to locate potential text fragments and identify the hidden semantics, in the form of attribute-value pairs for user queries. Empirical analysis shows that the decomposition framework outperforms pattern-based approaches due to its capability of effective integration of syntactic and semantic features.

How activation, entanglement, and searching a semantic network contribute to event memory

Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.

Semantic labelling for document feature patterns using ontological subjects

Finding and labelling semantic features patterns of documents in a large, spatial corpus is a challenging problem. Text documents have characteristics that make semantic labelling difficult; the rapidly increasing volume of online documents makes a bottleneck in finding meaningful textual patterns. Aiming to deal with these issues, we propose an unsupervised documnent labelling approach based on semantic content and feature patterns. A world ontology with extensive topic coverage is exploited to supply controlled, structured subjects for labelling. An algorithm is also introduced to reduce dimensionality based on the study of ontological structure. The proposed approach was promisingly evaluated by compared with typical machine learning methods including SVMs, Rocchio, and kNN.

Modelling word activation in semantic networks : three scaled entanglement models compared

Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. Previous research assumed a quantum-like model in which the semantic network was modelled as entangled qubits, however the level of activation was clearly being over-estimated. This paper explores three variations of this model, each of which are distinguished by a scaling factor designed to compensate the overestimation.

Some extensions to representation and encoding of structure in models of distributional semantics

This thesis makes several contributions towards improved methods for encoding structure in computational models of word meaning. New methods are proposed and evaluated which address the requirement of being able to easily encode linguistic structural features within a computational representation while retaining the ability to scale to large volumes of textual data. Various methods are implemented and evaluated on a range of evaluation tasks to demonstrate the effectiveness of the proposed methods.

Nonparametric semantic segmentation for 3D street scenes

In this paper we propose a method to generate a large scale and accurate dense 3D semantic map of street scenes. A dense 3D semantic model of the environment can significantly improve a number of robotic applications such as autonomous driving, navigation or localisation. Instead of using offline trained classifiers for semantic segmentation, our approach employs a data-driven, nonparametric method to parse scenes which easily scale to a large environment and generalise to different scenes. We use stereo image pairs collected from cameras mounted on a moving car to produce dense depth maps which are combined into a global 3D reconstruction using camera poses from stereo visual odometry. Simultaneously, 2D automatic semantic segmentation using a nonparametric scene parsing method is fused into the 3D model. Furthermore, the resultant 3D semantic model is improved with the consideration of moving objects in the scene. We demonstrate our method on the publicly available KITTI dataset and evaluate the performance against manually generated ground truth.

Mapping semantic knowledge for unsupervised text categorisation

Text categorisation is challenging, due to the complex structure with heterogeneous, changing topics in documents. The performance of text categorisation relies on the quality of samples, effectiveness of document features, and the topic coverage of categories, depending on the employing strategies; supervised or unsupervised; single labelled or multi-labelled. Attempting to deal with these reliability issues in text categorisation, we propose an unsupervised multi-labelled text categorisation approach that maps the local knowledge in documents to global knowledge in a world ontology to optimise categorisation result. The conceptual framework of the approach consists of three modules; pattern mining for feature extraction; feature-subject mapping for categorisation; concept generalisation for optimised categorisation. The approach has been promisingly evaluated by compared with typical text categorisation methods, based on the ground truth encoded by human experts.

A micro-level indexing model for the assessment of sustainable urban ecosystems

During the last several decades, the quality of natural resources and their services have been exposed to significant degradation from increased urban populations combined with the sprawl of settlements, development of transportation networks and industrial activities (Dorsey, 2003; Pauleit et al., 2005). As a result of this environmental degradation, a sustainable framework for urban development is required to provide the resilience of natural resources and ecosystems. Sustainable urban development refers to the management of cities with adequate infrastructure to support the needs of its population for the present and future generations as well as maintain the sustainability of its ecosystems (UNEP/IETC, 2002; Yigitcanlar, 2010). One of the important strategic approaches for planning sustainable cities is „ecological planning‟. Ecological planning is a multi-dimensional concept that aims to preserve biodiversity richness and ecosystem productivity through the sustainable management of natural resources (Barnes et al., 2005). As stated by Baldwin (1985, p.4), ecological planning is the initiation and operation of activities to direct and control the acquisition, transformation, disruption and disposal of resources in a manner capable of sustaining human activities with a minimum disruption of ecosystem processes. Therefore, ecological planning is a powerful method for creating sustainable urban ecosystems. In order to explore the city as an ecosystem and investigate the interaction between the urban ecosystem and human activities, a holistic urban ecosystem sustainability assessment approach is required. Urban ecosystem sustainability assessment serves as a tool that helps policy and decision-makers in improving their actions towards sustainable urban development. There are several methods used in urban ecosystem sustainability assessment among which sustainability indicators and composite indices are the most commonly used tools for assessing the progress towards sustainable land use and urban management. Currently, a variety of composite indices are available to measure the sustainability at the local, national and international levels. However, the main conclusion drawn from the literature review is that they are too broad to be applied to assess local and micro level sustainability and no benchmark value for most of the indicators exists due to limited data availability and non-comparable data across countries. Mayer (2008, p. 280) advocates that by stating "as different as the indices may seem, many of them incorporate the same underlying data because of the small number of available sustainability datasets". Mori and Christodoulou (2011) also argue that this relative evaluation and comparison brings along biased assessments, as data only exists for some entities, which also means excluding many nations from evaluation and comparison. Thus, there is a need for developing an accurate and comprehensive micro-level urban ecosystem sustainability assessment method. In order to develop such a model, it is practical to adopt an approach that uses a method to utilise indicators for collecting data, designate certain threshold values or ranges, perform a comparative sustainability assessment via indices at the micro-level, and aggregate these assessment findings to the local level. Hereby, through this approach and model, it is possible to produce sufficient and reliable data to enable comparison at the local level, and provide useful results to inform the local planning, conservation and development decision-making process to secure sustainable ecosystems and urban futures. To advance research in this area, this study investigated the environmental impacts of an existing urban context by using a composite index with an aim to identify the interaction between urban ecosystems and human activities in the context of environmental sustainability. In this respect, this study developed a new comprehensive urban ecosystem sustainability assessment tool entitled the „Micro-level Urban-ecosystem Sustainability IndeX‟ (MUSIX). The MUSIX model is an indicator-based indexing model that investigates the factors affecting urban sustainability in a local context. The model outputs provide local and micro-level sustainability reporting guidance to help policy-making concerning environmental issues. A multi-method research approach, which is based on both quantitative analysis and qualitative analysis, was employed in the construction of the MUSIX model. First, a qualitative research was conducted through an interpretive and critical literature review in developing a theoretical framework and indicator selection. Afterwards, a quantitative research was conducted through statistical and spatial analyses in data collection, processing and model application. The MUSIX model was tested in four pilot study sites selected from the Gold Coast City, Queensland, Australia. The model results detected the sustainability performance of current urban settings referring to six main issues of urban development: (1) hydrology, (2) ecology, (3) pollution, (4) location, (5) design, and; (6) efficiency. For each category, a set of core indicators was assigned which are intended to: (1) benchmark the current situation, strengths and weaknesses, (2) evaluate the efficiency of implemented plans, and; (3) measure the progress towards sustainable development. While the indicator set of the model provided specific information about the environmental impacts in the area at the parcel scale, the composite index score provided general information about the sustainability of the area at the neighbourhood scale. Finally, in light of the model findings, integrated ecological planning strategies were developed to guide the preparation and assessment of development and local area plans in conjunction with the Gold Coast Planning Scheme, which establishes regulatory provisions to achieve ecological sustainability through the formulation of place codes, development codes, constraint codes and other assessment criteria that provide guidance for best practice development solutions. These relevant strategies can be summarised as follows: • Establishing hydrological conservation through sustainable stormwater management in order to preserve the Earth’s water cycle and aquatic ecosystems; • Providing ecological conservation through sustainable ecosystem management in order to protect biological diversity and maintain the integrity of natural ecosystems; • Improving environmental quality through developing pollution prevention regulations and policies in order to promote high quality water resources, clean air and enhanced ecosystem health; • Creating sustainable mobility and accessibility through designing better local services and walkable neighbourhoods in order to promote safe environments and healthy communities; • Sustainable design of urban environment through climate responsive design in order to increase the efficient use of solar energy to provide thermal comfort, and; • Use of renewable resources through creating efficient communities in order to provide long-term management of natural resources for the sustainability of future generations.