Discovery of activity structures using the hierarchical hidden Markov model

In building a surveillance system for monitoring people behaviours, it is important to understand the typical patterns of people's movement in the environment. This task is difficult when dealing with high-level behaviours. The flat model such as the hidden Markov model (HMM) is inefficient in differentiating between signatures of such behaviours. This paper examines structure learning for high-level behaviours using the hierarchical hidden Markov model (HHMM).We propose a two-phase learning algorithm in which the parameters of the behaviours at low levels are estimated first and then the structures and parameters of the behaviours at high levels are learned from multi-camera training data. Our algorithm is then evaluated using data from a real environment, demonstrating the robustness of the learned structure in recognising people's behaviour.

The role of the ord arid intrusion in the historical and contemporary genetic division of long-tailed finch subspecies in northern Australia

The effect of separation by biogeographic features followed by secondary contact can blur taxonomic boundaries and produce complex genetic signatures. We analyzed population structure and gene flow across the range of the long-tailed finch (Poephila acuticauda) in northern Australia (1) to test the hypothesis that Ord Arid Intrusion acted as the causative barrier that led to divergence of P. acuticauda subspecies, (2) to determine whether genetic data support the presence of a gradual cline across the range or a sudden shift, both of which have been suggested based on morphological data, and (3) to estimate levels of contemporary gene flow within this species complex. We collected samples from 302 individuals from 10 localities. Analyses of 12 microsatellite loci and sequence data from 333 base pairs of the mitochondrial control region were used to estimate population structure and gene flow, using analysis of molecular variance (AMOVA), haplotype network analysis, frequency statistics, and clustering methods. Mitochondrial sequence data indicated the presence of three genetic groups (regions) across the range of P. acuticauda. Genetic diversity was highest in the east and lowest in the west. The Ord Arid Intrusion appears to have functioned as a biogeographic barrier in the past, according to mtDNA evidence presented here and evidence from previous studies. The absence of isolation by distance between adjacent regions and the lack of population genetic structure of mtDNA within regions indicates that genetic changes across the range of P. acuticauda subspecies are characterized by discrete breaks between regions. While microsatellite data indicate a complete absence of genetic structure across this species’ range, it appears unlikely that this results from high levels of gene flow. Mitochondrial data do not support the presence of contemporary gene flow across the range of this species.

From food to offspring down : tissue-specific discrimination and turn-over of stable isotopes in herbivorous waterbirds and other avian foraging guilds

Isotopic discrimination and turn-over are fundamental to the application of stable isotope ecology in animals. However, detailed information for specific tissues and species are widely lacking, notably for herbivorous species. We provide details on tissue-specific carbon and nitrogen discrimination and turn-over times from food to blood, feathers, claws, egg tissues and offspring down feathers in four species of herbivorous waterbirds. Source-to-tissue discrimination factors for carbon (δ¹³C) and nitrogen stable isotope ratios (δ¹⁵N) showed little variation across species but varied between tissues. Apparent discrimination factors ranged between −0.5 to 2.5‰ for δ¹³C and 2.8 to 5.2‰ for δ¹⁵N, and were more similar between blood components than between keratinous tissues or egg tissue. Comparing these results with published data from other species we found no effect of foraging guild on discrimination factors for carbon but a significant foraging-guild effect for nitrogen discrimination factors.

Turn-over of δ¹³C in tissues was most rapid in blood plasma, with a half-life of 4.3 d, whereas δ¹³C in blood cells had a half-life of approximately 32 d. Turn-over times for albumen and yolk in laying females were similar to those of blood plasma, at 3.2 and 6.0 d respectively. Within yolk, we found decreasing half-life times of δ¹³C from inner yolk (13.3 d) to outer yolk (3.1 d), related to the temporal pattern of tissue formation.

We found similarities in tissue-specific turn-over times across all avian species studied to date. Yet, while generalities regarding discrimination factors and tissue turn-over times can be made, a large amount of variation remains unexplained.

Mitochondrial DNA offers unique insights into invasion history of the common starling

Mitochondrial DNA (mtDNA) can be a powerful genetic marker for tracing origins and history of invasive populations. Here, we use mtDNA to address questions relevant to the understanding of invasion pathways of common starlings (Sturnus vulgaris) into Western Australia (WA) and discuss the utility of this marker to provide information useful to invasive species management. Mitochondrial sequence data indicate two geographically restricted genetic groups within Australia. Evidence of dispersal from genetically distinct sources outside the sampled range of starlings in Australia suggests increased vigilance by management agencies may be required to prevent further incursions from widely separated localities. Overall, genetic diversity in Australia was lower than in samples from the native range. Within Australia, genetic diversity was lowest in the most recently colonized area in the west, indicating that demographic bottlenecks have occurred in this area. Evidence of restricted dispersal between localities on the edge of the range expansion (ERE) in WA and other Australian sampling localities suggests that localized control within the ERE may be effective in preventing further range expansion. Signatures of spatial and demographic expansion are present in mismatch analyses from sampling localities located at the ERE, but neutrality indices did not support this finding, suggesting that the former may be more sensitive to recent expansion. Additionally, mismatch analyses support the presence of admixture, which is likely to have occurred pre-introduction. We compare our findings with those from a microsatellite study of the same samples and discuss how the mtDNA analyses used here offer valuable and unique insights into the invasion history of introduced species.

A novel sensing technique for monitoring pitting corrosion of stainless steel type 316L

A novel electrochemically integrated multi-electrode array namely the wire beam electrode(WBE) in combination with noise signatures analysis has been designed to monitor pittingcorrosion of one of the best corrosion resistance ferrous alloys, stainless steel type 316L.From the direct correlation of electrochemical potential noise signatures and galvanic currentdistribution maps during pitting corrosion processes, two characteristic noise patterns wereobserved prior to stable pit formation: (i) the characteristic ‘peak’ of rapid potential transient,towards less negative direction, followed by recovery (termed noise signature I) was found tocorrelate with the disappearance of unstable anode; (ii) the characteristic noise pattern ofquick potential changes towards less negative direction followed by no recovery (termed noisesignature II) was found to correspond with the massive disappearance of minor anodes leadingto formation of highly localized major anodes in the galvanic current distribution maps.

Fault detection and diagnosis of induction motors using motor current signature analysis and a hybrid FMM-CART model

In this paper, a novel approach to detect and classify comprehensive fault conditions of induction motors using a hybrid fuzzy min-max (FMM) neural network and classification and regression tree (CART) is proposed. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. A series of real experiments is conducted, whereby the motor current signature analysis method is applied to form a database comprising stator current signatures under different motor conditions. The signal harmonics from the power spectral density are extracted as discriminative input features for fault detection and classification with FMM-CART. A comprehensive list of induction motor fault conditions, viz., broken rotor bars, unbalanced voltages, stator winding faults, and eccentricity problems, has been successfully classified using FMM-CART with good accuracy rates. The results are comparable, if not better, than those reported in the literature. Useful explanatory rules in the form of a decision tree are also elicited from FMM-CART to analyze and understand different fault conditions of induction motors.

Application of the fuzzy min-max neural network to fault detection and diagnosis of induction motors

In this paper, an application of the motor current signature analysis (MCSA) method and the fuzzy min–max (FMM) neural network to detection and classification of induction motor faults is described. The finite element method is employed to generate simulated data pertaining to changes in the stator current signatures under different motor conditions. The MCSA method is then used to process the stator current signatures. Specifically, the power spectral density is employed to extract harmonics features for fault detection and classification with the FMM network. Various types of induction motor faults, which include stator winding faults and eccentricity problems, under different load conditions are experimented. The results are analyzed and compared with those from other methods. The outcomes indicate that the proposed technique is effective for fault detection and diagnosis of induction motors under different conditions.

Ocean currents influence the genetic structure of an intertidal mollusc in southeastern Australia – implications for predicting the movement of passive dispersers across a marine biogeographic barrier

Major disjunctions among marine communities in southeastern Australia have been well documented, although explanations for biogeographic structuring remain uncertain. Converging ocean currents, environmental gradients, and habitat discontinuities have been hypothesized as likely drivers of structuring in many species, although the extent to which species are affected appears largely dependent on specific life histories and ecologies. Understanding these relationships is critical to the management of native and invasive species, and the preservation of evolutionary processes that shape biodiversity in this region. In this study we test the direct influence of ocean currents on the genetic structure of a passive disperser across a major biogeographic barrier. Donax deltoides (Veneroida: Donacidae) is an intertidal, soft-sediment mollusc and an ideal surrogate for testing this relationship, given its lack of habitat constraints in this region, and its immense dispersal potential driven by year-long spawning and long-lived planktonic larvae. We assessed allele frequencies at 10 polymorphic microsatellite loci across 11 sample locations spanning the barrier region and identified genetic structure consistent with the major ocean currents of southeastern Australia. Analysis of mitochondrial DNA sequence data indicated no evidence of genetic structuring, but signatures of a species range expansion corresponding with historical inundations of the Bassian Isthmus. Our results indicate that ocean currents are likely to be the most influential factor affecting the genetic structure of D. deltoides and a likely physical barrier for passive dispersing marine fauna generally in southeastern Australia.

Localized corrosion and inhibition studies using the wire beam electrode in conjunction with the electrochemical noise analysis and the scanning reference electrode techniques

Several new technical developments have been made based on the combined use of the wire beam electrode (WBE), electrochemical noise analysis (ENA) and the scanning reference electrode technique (SRET). These have included: (i) The WBE-R n method- the combined use of the WBE and the noise resistance (Rn) to map the rates and patterns of uniform or localized corrosion; (ii) The WBE-Noise Signatures method- the combined use of the WBE and the noise signature to detect the origination and propagation of localized corrosion; and (iii) The WBE-SRET method- the combined use of the WBE and SRET to investigate localized corrosion from both the metallic and electrolyte phases of a corroding metal surface. This paper presents a brief review on these novel methods and their applications for detecting general and localized corrosion, for mapping the rates of corrosion, and for studying corrosion inhibitors.

Hub-based reliable gene expression algorithm to classify ER+ and ER- breast cancer subtypes

Identifying gene signatures that are associatedwith the estrogen receptor based breast cancer samples is achallenging problem that has significant implications in breastcancer diagnosis and treatment. Various existing approaches foridentifying gene signatures have been developed but are not ableto achieve the satisfactory results because of their severallimitations. Subnetwork-based approaches have shown to be arobust classification method that uses interaction datasets suchas protein-protein interaction datasets. It has been reported thatthese interaction datasets contain many irrelevant interactionsthat have no biological meaning associated with them, and thusit is essential to filter out those interactions which can improvethe classification results. In this paper, we therefore, proposed ahub-based reliable gene expression algorithm (HRGE) thateffectively extracts the significant biologically-relevantinteractions and uses hub-gene topology to generate thesubnetwork based gene signatures for ER+ and ER- breastcancer subtypes. The proposed approach shows the superiorclassification accuracy amongst the other existing classifiers, inthe validation dataset.

Malwise-an effective and efficient classification system for packed and polymorphic malware

Signature-based malware detection systems have been a much used response to the pervasive problem of malware. Identification of malware variants is essential to a detection system and is made possible by identifying invariant characteristics in related samples. To classify the packed and polymorphic malware, this paper proposes a novel system, named Malwise, for malware classification using a fast application-level emulator to reverse the code packing transformation, and two flowgraph matching algorithms to perform classification. An exact flowgraph matching algorithm is employed that uses string-based signatures, and is able to detect malware with near real-time performance. Additionally, a more effective approximate flowgraph matching algorithm is proposed that uses the decompilation technique of structuring to generate string-based signatures amenable to the string edit distance. We use real and synthetic malware to demonstrate the effectiveness and efficiency of Malwise. Using more than 15,000 real malware, collected from honeypots, the effectiveness is validated by showing that there is an 88 percent probability that new malware is detected as a variant of existing malware. The efficiency is demonstrated from a smaller sample set of malware where 86 percent of the samples can be classified in under 1.3 seconds.

Does reduced mobility through fragmented landscapes explain patch extinction patterns for three honeyeaters?

1.Habitat loss and associated fragmentation are major drivers of biodiversity decline, and understanding how they affect population processes (e.g. dispersal) is an important conservation goal. In a large-scale test employing 10 × 10 km units of replication, three species of Australian birds, the fuscous honeyeater, yellow-tufted honeyeater and white-plumed honeyeater, responded differently to fragmentation. The fuscous and yellow-tufted honeyeaters are ‘decliners’ that disappeared from suitable habitat in landscapes where levels of tree-cover fell below critical thresholds of 17 and 8%, respectively. The white-plumed honeyeater is a ‘tolerant’ species whose likelihood of occurrence in suitable habitat was independent of landscape-level tree-cover. 2.To determine whether the absence of the two decliner species in low tree-cover landscapes can be explained by reduced genetic connectivity, we looked for signatures of reduced mobility and gene flow in response to fragmentation across agricultural landscapes in the Box-Ironbark region of north-central Victoria, Australia. 3.We compared patterns of genetic diversity and population structure at the regional scale and across twelve 100 km2 landscapes with different tree-cover extents. We used genetic data to test landscape models predicting reduced dispersal through the agricultural matrix. We tested for evidence of sex-biased dispersal and sex-specific responses to fragmentation. 4.Reduced connectivity may have contributed to the disappearance of the yellow-tufted honey-eater from low tree-cover landscapes, as evidenced by male bias and increased relatedness among males in low tree-cover landscapes and signals of reduced gene flow and mobility through the agricultural matrix. We found no evidence for negative effects of fragmentation on gene flow in the other decliner, the fuscous honeyeater, suggesting that undetected pressures act on this species. As expected, there was no evidence for decreased movement through fragmented landscapes for the tolerant white-plumed honeyeater. 5.We demonstrated effects of habitat loss and fragmentation (stronger patterns of genetic differentiation, increased relatedness among males) on the yellow-tufted honeyeater above the threshold at which probability of occurrence dropped. Increasing extent and structural connectivity of habitat should be an appropriate management action for this species and other relatively sedentary woodland specialist species for which it can be taken as representative.

An evaluation of API calls hooking performance

An open research question in malware detection is how to accurately and reliably distinguish a malware program from a benign one, running on the same machine. In contrast to code signatures, which are commonly used in commercial protection software, signatures derived from system calls have the potential to form the basis of a much more flexible defense mechanism. However, the performance degradation caused by monitoring systems calls could adversely impact the machine. In this paper we report our experimental experience in implementing API hooking to capture sequences of API calls. The loading time often common programs was benchmarked with three different settings: plain, computer with antivirus and computer with API hook. Results suggest that the performance of this technique is sufficient to provide a viable approach to distinguishing between benign and malware code execution

Certificateless ignatures: New schemes and security models

We present a study of security in certificateless signatures. We divide potential adversaries according to their attack power, and for the first time, three new kinds of adversaries are introduced into certificateless signatures. They are Normal Adversary, Strong Adversary and Super Adversary (ordered by their attack power). Combined with the known Type I Adversary and Type II Adversary in certificateless cryptography, we then define the security of certificateless signatures in different attack scenarios. Our new security models, together with others in the literature, provide a clear definition of the security in certificateless signatures. Two concrete schemes with different security levels are also proposed in this paper. The first scheme, which is proven secure (in the random oracle model) against Normal Type I and Super Type II adversaries, has the shortest signature length among all known certificateless signature schemes. The second scheme is secure (in the random oracle model) against Super Type I and Type II adversaries. Compared with another scheme that has a similar security level, our second scheme requires less operational cost but a little longer signature length. Two server-aided verification protocols are also proposed to reduce the verification cost on the verifier.

Forgeability of Wang-Zhu-Feng-Yau’s attribute-based signature with policy-and-endorsement mechanism

Recently, Wang et al. presented a new construction of attribute-based signature with policy-and-endorsement mechanism. The existential unforgeability of their scheme was claimed to be based on the strong Diffie-Hellman assumption in the random oracle model. Unfortunately, by carefully revisiting the design and security proof of Wang et al.’s scheme, we show that their scheme cannot provide unforgeability, namely, a forger, whose attributes do not satisfy a given signing predicate, can also generate valid signatures. We also point out the flaws in Wang et al.’s proof.