A database for person re-identification in multi-camera surveillance networks

Person re-identification involves recognising individuals in different locations across a network of cameras and is a challenging task due to a large number of varying factors such as pose (both subject and camera) and ambient lighting conditions. Existing databases do not adequately capture these variations, making evaluations of proposed techniques difficult. In this paper, we present a new challenging multi-camera surveillance database designed for the task of person re-identification. This database consists of 150 unscripted sequences of subjects travelling in a building environment though up to eight camera views, appearing from various angles and in varying illumination conditions. A flexible XML-based evaluation protocol is provided to allow a highly configurable evaluation setup, enabling a variety of scenarios relating to pose and lighting conditions to be evaluated. A baseline person re-identification system consisting of colour, height and texture models is demonstrated on this database.

Sustainable education buildings in Australia : a green star review

In order to promote green building practice in Australia, the Green Building Council of Australia (GBCA) launched the Green Star rating tools for various types of buildings built since 2003. Of these, the Green Star-Education rating tool addresses sustainability issues during the design and construction phrases of education facility development. It covers a number of categories, including Management, Indoor Environment Quality, Energy, Transport, Water, Materials, Land Use & Ecology, Emissions and Innovation. This paper reviews the use of the Green Star system in Australian education facilities construction and the potential challenges associated with Green Star- Education implementation. Score sheets of 34 education projects across Australia that achieved Green Star certification were collected and analysed. The percentage of green star points obtained within each category and sub-category (credits) for each project were analysed to illustrate the achievement of credits. The results show that management-related credits and ecology-related credits are the easiest and most difficult to obtain respectively. The study also indicted that 6 Green Star education projects obtained particularly high percentages in the Innovation category. The investigation of points obtained in each category provides prospective Green Star applicants with insights into credit achievement for future projects.

Ambient media for the third place in urban environments

As ambient computing blends into the fabric of the modern urban environment developing a positive interplay between people, places, and technology to create enlivened, interactive cities becomes a necessary priority in how we imagine, understand, design, and develop cities. Designing technology for art, culture and gastronomic experiences, that are rich in community, can provide the means for collaborative action to (re)create cities that are lively, engaging, and promote a sense of well being as well as belonging.

Risks of Carbon Fraud

Carbon credit markets are in the early stages of development and media headlines such as these illustrate emerging levels of concern and foreboding over the potential for fraudulent crime within these markets. Australian companies are continuing to venture into the largely unregulated voluntary carbon credit market to offset their emissions and / or give their customers the opportunity to be ‘carbon neutral’. Accordingly, the voluntary market has seen a proliferation of carbon brokers that offer tailored offset carbon products according to need and taste. With the instigation of the Australian compliance market and with pressure increasing for political responses to combat climate change, we would expect Australian companies to experience greater exposure to carbon products in both compliance and voluntary markets. This paper examines the risks of carbon fraud in these markets by reviewing cases of actual fraud and analysing and identifying contexts where risks of carbon fraud are most likely.

Sequential slotted amplify-and-forward with partial relay isolation

In this paper, we propose a novel relay ordering and scheduling strategy for the sequential slotted amplify-and-forward (SAF) protocol and evaluate its performance in terms of diversity-multiplexing trade-off (DMT). The relays between the source and destination are grouped into two relay clusters based on their respective locations. The proposed strategy achieves partial relay isolation and decreases the decoding complexity at the destination. We show that the DMT upper bound of sequential-SAF with the proposed strategy outperforms other amplify and forward protocols and is more practical compared to the relay isolation assumption made in the original paper [1]. Simulation result shows that the sequential-SAF protocol with the proposed strategy has better outage performance compared to the existing AF and non-cooperative protocols in high SNR regime.

Sequential slotted amplify-decode-and-forward

In this paper, we propose a novel slotted hybrid cooperative protocol named the sequential slotted amplify-decodeand-forward (SADF) protocol and evaluate its performance in terms of diversity-multiplexing trade-off (DMT). The relays between the source and destination are divided into two different groups and each relay either amplifies or decodes the received signal. We first compute the optimal DMT of the proposed protocol with the assumption of perfect decoding at the DF relays. We then derive the DMT closed-form expression of the proposed sequential-SADF and obtain the proximity gain bound for achieving the optimal DMT. With the proximity gain bound, we then found the distance ratio to achieve the optimal DMT performance. Simulation result shows that the proposed protocol with high proximity gain outperforms other cooperative communication protocols in high SNR regime.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Spatio temporal feature evaluation for action recognition

Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

An English-translated parallel corpus for the CJK Wikipedia collections

In this paper, we describe a machine-translated parallel English corpus for the NTCIR Chinese, Japanese and Korean (CJK) Wikipedia collections. This document collection is named CJK2E Wikipedia XML corpus. The corpus could be used by the information retrieval research community and knowledge sharing in Wikipedia in many ways; for example, this corpus could be used for experimentations in cross-lingual information retrieval, cross-lingual link discovery, or omni-lingual information retrieval research. Furthermore, the translated CJK articles could be used to further expand the current coverage of the English Wikipedia.

Agricultural biodiversity, farm level technical efficiency and conservation benefits : an empirical investigation

The issues involved in agricultural biodiversity are important and interesting areas for the application of economic theory. However, very little theoretical and empirical work has been undertaken to understand the benefits of conserving agricultural biodiversity. Accordingly, the main objectives of this PhD thesis are to: (1) Investigate farmers’ valuation of agricultural biodiversity; (2) Identify factors influencing farmers’ demand for agricultural biodiversity; (3) Examine farmers’ demand for biodiversity rich farming systems; (4) Investigate the relationship between agricultural biodiversity and farm level technical efficiency. This PhD thesis investigates these issues by using primary data in small-scale farms, along with secondary data from Sri Lanka. The overall findings of the thesis can be summarized as follows. Firstly, owing to educational and poverty issues of those being interviewed, some policy makers in developed countries question whether non-market valuation techniques such as Choice Experiment (CE) can be applied to developing countries such as Sri Lanka. The CE study in this thesis indicates that carefully designed and pre-tested nonmarket valuation techniques can be applied in developing countries with a high level of reliability. The CE findings support the priori assumption that small-scale farms and their multiple attributes contribute positively and significantly to the utility of farm families in Sri Lanka. Farmers have strong positive attitudes towards increasing agricultural biodiversity in rural areas. This suggests that these attitudes can be the basis on which appropriate policies can be introduced to improve agricultural biodiversity. Secondly, the thesis identifies the factors which influence farmers’ demand for agricultural biodiversity and farmers’ demands on biodiversity rich farming systems. As such they provide important tools for the implementation of policies designed to avoid the loss agricultural biodiversity which is shown to be a major impediment to agricultural growth and sustainable development in a number of developing countries. The results illustrate that certain key household, market and other characteristics (such as agricultural subsidies, percentage of investment of owned money and farm size) are the major determinants of demand for agricultural biodiversity on small-scale farms. The significant household characteristics that determine crop and livestock diversity include household member participation on the farm, off-farm income, shared labour, market price fluctuations and household wealth. Furthermore, it is shown that all the included market characteristics as well as agricultural subsidies are also important determinants of agricultural biodiversity. Thirdly, it is found that when the efficiency of agricultural production is measured in practice, the role of agricultural biodiversity has rarely been investigated in the literature. The results in the final section of the thesis show that crop diversity, livestock diversity and mix farming system are positively related to farm level technical efficiency. In addition to these variables education level, number of separate plots, agricultural extension service, credit access, membership of farm organization and land ownerships are significant and direct policy relevant variables in the inefficiency model. The results of the study therefore have important policy implications for conserving agricultural biodiversity in Sri Lanka.

GameFlow heuristics for designing and evaluating real-time strategy games

The GameFlow model strives to be a general model of player enjoyment, applicable to all game genres and platforms. Derived from a general set of heuristics for creating enjoyable player experiences, the GameFlow model has been widely used in evaluating many types of games, as well as non-game applications. However, we recognize that more specific, low-level, and implementable criteria are potentially more useful for designing and evaluating video games. Consequently, the research reported in this paper aims to provide detailed heuristics for designing and evaluating one specific game genre, real-time strategy games. In order to develop these heuristics, we conducted a grounded theoretical analysis on a set of professional game reviews and structured the resulting heuristics using the GameFlow model. The resulting 165 heuristics for designing and evaluating real-time strategy games are presented and discussed in this paper.

Power electronic converters for high power ultrasound transducers

Piezoelectric transducers convert electrical energy to mechanical energy and play a great role in ultrasound systems. Ultrasound power transducer performance is strongly related to the applied electrical excitation. To have a suitable excitation for maximum energy conversion, it is required to analyze the effects of input signal waveform, medium and input signal distortion on the characteristic of a high power ultrasound system (including ultrasound transducer). In this research, different input voltage signals are generated using a single-phase power inverter and a linear power amplifier to excite a high power ultrasound transducer in different medium (water and oil) in order to study the characteristic of the system. We have also considered and analyzed the effect of power converter output voltage distortions on the performance of the high power ultrasound transducer using a passive filter.

Integration of opinion into customer analysis model

As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes.

Integrated configuration of enterprise systems for interoperability : towards process model and business document specification alignment

Enterprise Systems (ES) can be understood as the de facto standard for holistic operational and managerial support within an organization. Most commonly ES are offered as commercial off-the-shelf packages, requiring customization in the user organization. This process is a complex and resource-intensive task, which often prevents small and midsize enterprises (SME) from undertaking configuration projects. Especially in the SME market independent software vendors provide pre-configured ES for a small customer base. The problem of ES configuration is shifted from the customer to the vendor, but remains critical. We argue that the yet unexplored link between process configuration and business document configuration must be closer examined as both types of configuration are closely tied to one another.

Provision of customer knowledge to supply chains

Knowledge about customers is vital for supply chains in order to ensure customer satisfaction. In an ideal supply chain environment, supply chain partners are able to perform planning tasks collaboratively, because they share information. However, customers are not always able or willing to share information with their suppliers. End consumers, on the one hand, do not usually provide a retail company with demand information. On the other hand, industrial customers might consciously hide information. Wherever a supply chain is not provided with demand forecast information, it needs to derive these demand forecasts by other means. Customer Relationship Management provides a set of tools to overcome informational uncertainty. We show how CRM and SCM information can be integrated on the conceptual as well as technical levels in order to provide supply chain managers with relevant information.