Groups, graphs and mutually unbiased bases

A new characteristic free approach to constructing large sets of mutually unbiased bases in Hilbert space is developed. We associate with a seed set of bases a finite subgroup of which defines a strongly regular graph. Large sets of mutually unbiased bases are obtained as the cliques of the graph.

Clock synchronization state graphs based on clock precision difference

Consistent and stable global states of clock synchronization are very important in distributed and parallel systems. This paper presents an innovative strategy and method to obtain stable global clock synchronization state graphs in asynchronous Internet environments. Our model will introduce the concept of clock precision difference as a means to evaluate running states of all clocks in this system and make this system  self-adaptive well. Finally, we introduce the concept of clock precision difference into global states analysis of clock synchronization and construct clock synchronization state graphs in order to evaluate distributed clock synchronization states. We also present detailed simulations of the strategy and mathematical analysis used on real Internet environments.

Consumer knowledge and attitudes to salt intake and labelled salt information

The objective of this study was to investigate consumers’ knowledge of health risks of high salt intake and frequency of use and understanding of labelled salt information. We conducted a cross-sectional survey in shopping centres within Metropolitan Melbourne. A sample of 493 subjects was recruited. The questionnaire assessed salt related shopping behaviours, attitudes to salt intake and health and their ability to interpret labelled sodium information. Four hundred and seventy four valid surveys were collected (65% female, 64% being the main shopper). Most participants knew of the relationship between salt intake and high blood pressure (88%). Sixty five percent of participants were unable to correctly identify the relationship between salt and sodium. Sixty nine percent reported reading the salt content of food products when shopping. Salt label usage was significantly related to shoppers concern about the amount of salt in their diet and the belief that their health could improve by lowering salt intake. Approximately half of the sample was unable to accurately use labelled sodium information to pick low salt options. Raising consumer awareness of the health risks associated with high salt consumption may increase salt label usage and purchases of low salt foods. However, for food labels to be effective in helping consumers select low salt foods a more ‘user friendly’ labelling format is needed.

Intersection and partition graphs

This thesis reviews previous work done on both general partition graphs and existential partition graphs, which are a generalised form of general partition graphs, and extends some of the results.

Two-photon endomicroscopy for 3D imaging of cancer cells labelled with gold nanorods

Biofunctional nanorods are developed to specifically target cancer cells. The cervical cancer cells, HeLa cells, are labeled by these biofunctional gold nanorods. Those cancer cells can be detected by a multi-photon-excited photoluminescence endomicroscope, which proves that the cancers can be in vivo diagnosed by using biofunctional gold nanorods with nonlinear endomicroscopy.

Malware variant detection using similarity search over sets of control flow graphs

Static detection of polymorphic malware variants plays an important role to improve system security. Control flow has shown to be an effective characteristic that represents polymorphic malware instances. In our research, we propose a similarity search of malware using novel distance metrics of malware signatures. We describe a malware signature by the set of control flow graphs the malware contains. We propose two approaches and use the first to perform pre-filtering. Firstly, we use a distance metric based on the distance between feature vectors. The feature vector is a decomposition of the set of graphs into either fixed size k-sub graphs, or q-gram strings of the high-level source after decompilation. We also propose a more effective but less computationally efficient distance metric based on the minimum matching distance. The minimum matching distance uses the string edit distances between programs' decompiled flow graphs, and the linear sum assignment problem to construct a minimum sum weight matching between two sets of graphs. We implement the distance metrics in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of a limited false positive rate and our system detects more malware variants when compared to the detection rates of other algorithms.

On the incremental learning and recognition of the pattern of movement of multiple labelled objects in dynamic scenes

In this paper we discuss combining incremental learning and incremental recognition to classify patterns consisting of multiple objects, each represented by multiple spatio-temporal features. Importantly the technique allows for ambiguity in terms of the positions of the start and finish of the pattern. This involves a progressive classification which considers the data at each time instance in the query and thus provides a probable answer before all the query information becomes available. We present two methods that combine incremental learning and incremental recognition: a time instance method and an overall best match method.

Learning discriminative sequence models from partially labelled data for activity recognition

Recognising daily activity patterns of people from low-level sensory data is an important problem. Traditional approaches typically rely on generative models such as the hidden Markov models and training on fully labelled data. While activity data can be readily acquired from pervasive sensors, e.g. in smart environments, providing manual labels to support fully supervised learning is often expensive. In this paper, we propose a new approach based on partially-supervised training of discriminative sequence models such as the conditional random field (CRF) and the maximum entropy Markov model (MEMM). We show that the approach can reduce labelling effort, and at the same time, provides us with the flexibility and accuracy of the discriminative framework. Our experimental results in the video surveillance domain illustrate that these models can perform better than their generative counterpart (i.e. the partially hidden Markov model), even when a substantial amount of labels are unavailable.

The L(2,1)-labelling problem for cubic Cayley graphs on dihedral groups

A k-L(2,1)-labelling of a graph G is a mapping f:V(G)→{0,1,2,…,k} such that |f(u)−f(v)|≥2 if uv∈E(G) and f(u)≠f(v) if u,v are distance two apart. The smallest positive integer k such that G admits a k-L(2,1)-labelling is called the λ-number of G. In this paper we study this quantity for cubic Cayley graphs (other than the prism graphs) on dihedral groups, which are called brick product graphs or honeycomb toroidal graphs. We prove that the λ-number of such a graph is between 5 and 7, and moreover we give a characterisation of such graphs with λ-number 5.

Power graphs : a survey

This article gives a survey of all results on the power graphs of groups and semigroups obtained in the literature. Various conjectures due to other authors, questions and open problems are also included.

Promising pre-clinical validation of targeted radionuclide therapy using a [131I] labelled iodoquinoxaline derivative for an effective melanoma treatment

Targeted internal radionuclide therapy (TRT) would be an effective alternative to current therapies for dissemi- nated melanoma treatment. At our institution, a class of iodobenzamides has been developed as potent melanoma- seeking agents. This review described the preclinical vali- dations of a quinoxaline derivative molecule (ICF01012) as tracer for TRT application. It was selected for its high, specific and long-lasting uptake in tumour with rapid clear- ance from non-target organs providing suitable dosimetry parameters for TRT. Extended in vivo study of metabolic profiles confirmed durable tumoural concentration of the unchanged molecule form. Moreover melanin specificity of ICF01012 was determined by binding assay with syn- thetic melanin and in vivo by SIMS imaging. Then, we showed in vivo that [131I] ICF01012 treatment drastically inhibited growth of B16F0, B16Bl6 and M4Beu tumours whereas [131I] NaI or unlabelled ICF01012 treatment was without significant effect. Histological analysis showed that residual tumour cells exhibit a significant loss of aggres- siveness after treatment. This anti-tumoural effect was associated with a lengthening of the treated-mice survival time and an inhibition of lung dissemination for B16Bl6 model. Results presented here support the concept of TRT using a [131I] labelled iodoquinoxaline derivative for an effective melanoma treatment.