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.

Opportunities for forest finance under the International climate change regime

The international climate change regime has the potential to increase revenue available for forest restoration projects in Commonwealth nations. There are three mechanisms which could be used to fund forest projects aimed at forest conservation, forest restoration and sustainable forest management. The first forest funding opportunity arises under the clean development mechanism, a flexibility mechanism of the Kyoto Protocol. The clean development mechanism allows Annex I parties (industrialised nations) to invest in emission reduction activities in non-Annex 1 (developing countries) and the establishment of forest sinks is an eligible clean development mechanism activity. Secondly, parties to the Kyoto Protocol are able to include sustainable forest management activities in their national carbon accounting. The international rules concerning this are called the Land-Use, Land-Use Change and Forestry Guidelines. Thirdly, it is anticipated that at the upcoming Copenhagen negotiations that a Reduced Emissions from Deforestation and Degradation (REDD) instrument will be created. This will provide a direct funding mechanism for those developing countries with tropical forests. Payments made under a REDD arrangement will be based upon the developing country with tropical forest cover agreeing to protect and conserve a designated forest estate. These three funding options available under the international climate change regime demonstrate that there is potential for forest finance within the regime. These opportunities are however hindered by a number of technical and policy barriers which prevent the ability of the regime to significantly increase funding for forest projects. There are two types of carbon markets, compliance carbon markets (Kyoto based) and voluntary carbon markets. Voluntary carbon markets are more flexible then compliance markets and as such offer potential to increase revenue available for sustainable forest projects.

Statutory-backed continuous disclosure regime and corporate disclosure behaviour : does corporate governance matter?

Since 1 December 2002, the New Zealand Exchange’s (NZX) continuous disclosure listing rules have operated with statutory backing. To test the effectiveness of the new corporate disclosure regime, we compare the change in quantity of market announcements (overall, non-routine, non-procedural and external) released to the NZX before and after the introduction of statutory backing. We also extend our study in investigating whether the effectiveness of the new corporate disclosure regime is diminished or augmented by corporate governance mechanisms including board size, providing separate roles for CEO and Chairman, board independence, board gender diversity and audit committee independence. Our findings provide a qualified support for the effectiveness of the new corporate disclosure regime regarding the quantity of market disclosures. There is strong evidence that the effectiveness of the new corporate disclosure regime was augmented by providing separate roles for CEO and Chairman, board gender diversity and audit committee independence, and diminished by board size. In addition, there is significant evidence that share price queries do impact corporate disclosure behaviour and this impact is significantly influenced by corporate governance mechanisms. Our findings provide important implications for corporate regulators in their quest for...

Statutory-backed continuous disclosure regime and corporate disclosure behaviour : does corporate governance matter?

Since 1 December 2002, the New Zealand Exchange’s (NZX) continuous disclosure listing rules have operated with statutory backing. To test the effectiveness of the new corporate disclosure regime, we compare the change in quantity of market announcements (overall, non-routine, non-procedural and external) released to the NZX before and after the introduction of statutory backing. We also extend our study in investigating whether the effectiveness of the new corporate disclosure regime is diminished or augmented by corporate governance mechanisms including board size, providing separate roles for CEO and Chairman, board independence, board gender diversity and audit committee independence. Our findings provide a qualified support for the effectiveness of the new corporate disclosure regime regarding the quantity of market disclosures. There is strong evidence that the effectiveness of the new corporate disclosure regime was augmented by providing separate roles for CEO and Chairman, board gender diversity and audit committee independence, and diminished by board size. In addition, there is significant evidence that share price queries do impact corporate disclosure behaviour and this impact is significantly influenced by corporate governance mechanisms. Our findings provide important implications for corporate regulators in their quest for a superior disclosure regime.

A semi-supervised graph-based algorithm for detecting outliers in online-social-networks

In this paper, we propose a semi-supervised approach of anomaly detection in Online Social Networks. The social network is modeled as a graph and its features are extracted to detect anomaly. A clustering algorithm is then used to group users based on these features and fuzzy logic is applied to assign degree of anomalous behavior to the users of these clusters. Empirical analysis shows effectiveness of this method.

The Rise of the BASIC Group Within the International Climate Regime : The Challenge of Ensuring Equitable Mitigation Obligations

The chapter examines the current emission reduction obligations within the climate regime. It looks at the formation and rise of the BASIC negotiation group within the international climate COP negotiations and examines the role that BASIC nations are now playing shaping international mitigation policy.

Reusable surface confined semi-conducting metal-TCNQ and metal-TCNQF4 catalysts for electron transfer reactions

The synthesis of organic semiconducting materials based on silver and copper-TCNQ (TCNQ = 7,7,8,8-tetracyanoquinodimethane) and their fluorinated analogues has received a significant amount of attention due to their potential use in organic electronic applications. However, there is a scarcity in the identification of different applications for which these interesting materials may be suitable candidates. In this work, we address this by investigating the catalytic properties of such materials for the electron transfer reaction between ferricyanide and thiosulphate ions in aqueous solution, which to date has been almost solely limited to metallic nanomaterials. Significantly it was found that all the materials investigated, namely CuTCNQ, AgTCNQ, CuTCNQF4 and AgTCNQF4, were catalytically active and, interestingly, the fluorinated analogues were superior. AgTCNQF4 demonstrated the highest activity and was tested for its stability and re-usability for up to 50 cycles without degradation in performance. The catalytic reaction was monitored via UV-vis spectroscopy and open circuit potential versus time measurements, as well as an investigation of the transport properties of the films via electrochemical impedance spectroscopy. It is suggested that morphology and bulk conductivity are not the limiting factors, but rather the balance between the accumulated surface charge from electron injection via thiosulphate ions on the catalyst surface and transfer to the ferricyanide ions which controls the reaction rate. The facile fabrication of re-usable surface confined organic materials that are catalytically active may have important uses for many more electron transfer reactions.

An analysis of Australia's legal regime for imposing liability on manufacturers of pharmaceutical drugs

Following a trial in June 2009 where the Federal Court heard submissions regarding whether Merck Sharpe and Dohme Australia should be held liable for an increased risk of cardiovascular conditions noted in patients who had taken the anti-inflammatory drug Vioxx, a judgment was handed down against MSDA in March 2010. MSDA appealed to the Full Federal Court, where they were successful. Special leave to appeal to the High Court of Australia was rejected in May 2012. This article will examine the themes raised in the trial judgment and the appropriateness of Australia’s statutory consumer protection regime through the lens of pharmaceutical drug injuries and side effects.

Dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer

The effects of suspension parameters and driving conditions on dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer are investigated in this study. A novel nonlinear model of a multi-axle semi-trailer with longitudinal-connected air suspensions is formulated based on fluid mechanics and thermodynamics and validated through test results. The effects of road surface conditions, driving speeds, air line inside diameter and connector inside diameter on dynamic load-sharing capability of the semi-trailer were analyzed in terms of load-sharing criteria. Simulation results indicate that, when larger air lines and connectors are employed, the DLSC (Dynamic Load-Sharing Coefficient) optimization ratio reaches its peak value when the road roughness is medium. The optimization ratio fluctuates in a complex manner as driving speed increases. The results also indicate that if the air line inside diameter is always assumed to be larger than the connector inside diameter, the influence of air line inside diameter on load-sharing is more significant than that of the connector inside diameter. The proposed approach can be used for further study of the influence of additional factors (such as vehicle load, static absolute air pressure and static height of air spring) on load-sharing and the control methods for multi-axle air suspensions with longitudinal air line.

Semi-parametric forecasting of spikes in electricity prices

The occurrence of extreme movements in the spot price of electricity represents a significant source of risk to retailers. A range of approaches have been considered with respect to modelling electricity prices; these models, however, have relied on time-series approaches, which typically use restrictive decay schemes placing greater weight on more recent observations. This study develops an alternative, semi-parametric method for forecasting, which uses state-dependent weights derived from a kernel function. The forecasts that are obtained using this method are accurate and therefore potentially useful to electricity retailers in terms of risk management.

A qualitative investigation of drug use among Pakistani road users

Background Statistics on drug use by Pakistani drivers are not available, yet considerable numbers of drivers are believed to be drug addicted. The National Drug Abuse Assessment 2006/07, conducted by the United Nation Office on Drugs and Crime and the Ministry of Narcotics Control Pakistan reported that opiate users numbered 628,000, of which 77%were chronic heroin abusers. Injecting drug users have reportedly doubled in the decade to 2006 and drug use has been linked with many major crashes involving professional drivers. Aims This study explored a broad range of risk taking behaviours of road users, including drug use. It also investigated associations between risky road use and fatalism and other cultural beliefs. Methods This paper reports findings relating to drug driving in the cities of Lahore, Rawalpindi and Islamabad. Thirty semi-structured interviews were conducted with bus, truck, and taxi drivers, policy makers and field police officers. Results Interviews suggested widespread use of illicit drugs, particularly among bus, truck and taxi drivers. Reasons for drug use included recreational purposes, stimulants during long driving episodes, and substance addiction. Furthermore, the use of drugs and any association with road crashes was generally viewed as linked to fatalism rather than to any fault of an individual. In other words, people did not believe there was an association between drug use and road crashes, even if they had personally experienced such. Police knowledge of drug use among drivers was evident, although there is no formal drug driving testing regime in Pakistan. Discussion and conclusions The substantial increase in drug use among the population in recent years highlights a significant public health challenge in Pakistan. This qualitative research, although recognized as not representative of the broader population, suggests that there is significant cause for concern about drug driving, especially among professional drivers, and a need for further investigation and intervention.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

A comparative study of the semi-elastic and fully-elastic MapReduce models

MapReduce is a computation model for processing large data sets in parallel on large clusters of machines, in a reliable, fault-tolerant manner. A MapReduce computation is broken down into a number of map tasks and reduce tasks, which are performed by so called mappers and reducers, respectively. The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation in cloud computing. From the computational point of view, the mappers/reducers placement problem is a generation of the classical bin packing problem, which is NP-complete. Thus, in this paper we propose a new heuristic algorithm for the mappers/reducers placement problem in cloud computing and evaluate it by comparing with other several heuristics on solution quality and computation time by solving a set of test problems with various characteristics. The computational results show that our heuristic algorithm is much more efficient than the other heuristics and it can obtain a better solution in a reasonable time. Furthermore, we verify the effectiveness of our heuristic algorithm by comparing the mapper/reducer placement for a benchmark problem generated by our heuristic algorithm with a conventional mapper/reducer placement which puts a fixed number of mapper/reducer on each machine. The comparison results show that the computation using our mapper/reducer placement is much cheaper than the computation using the conventional placement while still satisfying the computation deadline.