Characterization and Mapping of Patterned Ground in the Saginaw Lowlands, Michigan: Possible Evidence for Late-Wisconsin Permafrost

We identified, mapped, and characterized a widespread area (gt;1,020 km2) of patterned ground in the Saginaw Lowlands of Michigan, a wet, flat plain composed of waterlain tills, lacustrine deposits, or both. The polygonal patterned ground is interpreted as a possible relict permafrost feature, formed in the Late Wisconsin when this area was proximal to the Laurentide ice sheet. Cold-air drainage off the ice sheet might have pooled in the Saginaw Lowlands, which sloped toward the ice margin, possibly creating widespread but short-lived permafrost on this glacial lake plain. The majority of the polygons occur between the Glacial Lake Warren strandline (~14.8 cal. ka) and the shoreline of Glacial Lake Elkton (~14.3 cal. ka), providing a relative age bracket for the patterned ground. Most of the polygons formed in dense, wet, silt loam soils on flat-lying sites and take the form of reticulate nets with polygon long axes of 150 to 160 m and short axes of 60 to 90 m. Interpolygon swales, often shown as dark curvilinears on aerial photographs, are typically slightly lower than are the polygon centers they bound. Some portions of these interpolygon swales are infilled with gravel-free, sandy loam sediments. The subtle morphology and sedimentological characteristics of the patterned ground in the Saginaw Lowlands suggest that thermokarst erosion, rather than ice-wedge replacement, was the dominant geomorphic process associated with the degradation of the Late-Wisconsin permafrost in the study area and, therefore, was primarily responsible for the soil patterns seen there today.

Desynchronization and Traceability Attacks on RIPTA-DA Protocol

Recently Gao et al. proposed a lightweight RFID mutual authentication protocol [3] to resist against intermittent position trace attacks and desynchronization attacks and called it RIPTA-DA. They also verified their protocol’s security by data reduction method with the learning parity with noise (LPN) and also formally verified the functionality of the proposed scheme by Colored Petri Nets. In this paper, we investigate RIPTA-DA’s security. We present an efficient secret disclosure attack against the protocol which can be used to mount both de-synchronization and traceability attacks against the protocol. Thus our attacks show that RIPTA-DA protocol is not a RIPTA-DA.

On Merging Business Process Management and Geographic Information Systems : Modeling and Execution of Ecological Concerns in Processes

Business Process Management describes a holistic management approach for the systematic design, modeling, execution, validation, monitoring and improvement of organizational business processes. Traditionally, most attention within this community has been given to control-flow aspects, i.e., the ordering and sequencing of business activities, oftentimes in isolation with regards to the context in which these activities occur. In this paper, we propose an approach that allows executable process models to be integrated with Geographic Information Systems. This approach enables process models to take geospatial and other geographic aspects into account in an explicit manner both during the modeling phase and the execution phase. We contribute a structured modeling methodology, based on the well-known Business Process Model and Notation standard, which is formalized by means of a mapping to executable Colored Petri nets. We illustrate the feasibility of our approach by means of a sustainability-focused case example of a process with important ecological concerns.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

Improved Kalman filter initialisation using neurofuzzy estimation

It is traditional to initialise Kalman filters and extended Kalman filters with estimates of the states calculated directly from the observed (raw) noisy inputs, but unfortunately their performance is extremely sensitive to state initialisation accuracy: good initial state estimates ensure fast convergence whereas poor estimates may give rise to slow convergence or even filter divergence. Divergence is generally due to excessive observation noise and leads to error magnitudes that quickly become unbounded (R.J. Fitzgerald, 1971). When a filter diverges, it must be re initialised but because the observations are extremely poor, re initialised states will have poor estimates. The paper proposes that if neurofuzzy estimators produce more accurate state estimates than those calculated from the observed noisy inputs (using the known state model), then neurofuzzy estimates can be used to initialise the states of Kalman and extended Kalman filters. Filters whose states have been initialised with neurofuzzy estimates should give improved performance by way of faster convergence when the filter is initialised, and when a filter is re started after divergence

Formal modelling and analysis of DNP3 secure authentication

Supervisory Control and Data Acquisition (SCADA) systems are one of the key foundations of smart grids. The Distributed Network Protocol version 3 (DNP3) is a standard SCADA protocol designed to facilitate communications in substations and smart grid nodes. The protocol is embedded with a security mechanism called Secure Authentication (DNP3-SA). This mechanism ensures that end-to-end communication security is provided in substations. This paper presents a formal model for the behavioural analysis of DNP3-SA using Coloured Petri Nets (CPN). Our DNP3-SA CPN model is capable of testing and verifying various attack scenarios: modification, replay and spoofing, combined complex attack and mitigation strategies. Using the model has revealed a previously unidentified flaw in the DNP3-SA protocol that can be exploited by an attacker that has access to the network interconnecting DNP3 devices. An attacker can launch a successful attack on an outstation without possessing the pre-shared keys by replaying a previously authenticated command with arbitrary parameters. We propose an update to the DNP3-SA protocol that removes the flaw and prevents such attacks. The update is validated and verified using our CPN model proving the effectiveness of the model and importance of the formal protocol analysis.

Nanolines on silicon surfaces

Although a wide range of periodic surface nets can be grown on low index silicon surfaces, only a few of these have quasi-one dimensional symmetry. If high index silicon surfaces, such as (553) and (557), are used instead, the surface unit cell contains steps. It is possible to fabricate a number of quasi-one dimensional nanoline systems on the terraces and some of these have nested energy bands near the Fermi level. These nano-scale systems may support exotic many-electron states produced by enhanced electron correlations and a reduction in electron screening in one spatial dimension. In this paper, our groups' experimental and theoretical studies of nanolines phases, grown on both low index and vicinal silicon surfaces are reviewed. These studies give us insight into the electronic properties of artificial nanoline structures.

Stock-recruitment relationships of the tiger prawns (Penaeus esculentus and Penaeus semisulcatus) in the Australian Northern Prawn Fishery

This paper investigates the stock-recruitment and equilibrium yield dynamics for the two species of tiger prawns (Penaeus esculentus and Penaeus semisulcatus) in Australia's most productive prawn fishery: the Northern Prawn Fishery. Commercial trawl logbooks for 1970-93 and research surveys are used to develop population models for these prawns. A population model that incorporates continuous recruitment is developed. Annual spawning stock and recruitment indices are then estimated from the population model. Spawning stock indices represent the abundance of female prawns that are likely to spawn; recruitment indices represent the abundance of all prawns less than a certain size. The relationships between spawning stock and subsequent recruitment (SRR), between recruitment and subsequent spawning stock (RSR), and between recruitment and commercial catch were estimated through maximum-likelihood models that incorporated autoregressive terms. Yield as a function of fishing effort was estimated by constraining to equilibrium the SRR and RSR. The resulting production model was then used to determine maximum sustainable yield (MSY) and its corresponding fishing effort (f(MSY)). Long-term yield estimates for the two tiger prawn species range between 3700 and 5300 t. The fishing effort at present is close to the level that should produce MSY for both species of tiger prawns. However, current landings, recruitment and spawning stock are below the equilibrium values predicted by the models. This may be because of uncertainty in the spawning stock-recruitment relationships, a change in carrying capacity, biased estimates of fishing effort, unreliable catch statistics, or simplistic assumptions about stock structure. Although our predictions of tiger prawn yields are uncertain, management will soon have to consider new measures to counteract the effects of future increases in fishing effort.

Spatial and temporal distribution of tropical phytoplankton species and biomass in the Gulf of Carpenteria, Australia

The biomass and species composition of tropical phytoplankton in Albatross Bay, Gulf of Carpentaria, northern Australia, were examined monthly for 6 yr (1986 to 1992). Chlorophyll a (chl a) concentrations were highest (2 to 5.7 mu g l(-1)) in the wet season at inshore sites, usually coinciding with low salinities (30 to 33 ppt) and high temperatures (29 to 32 degrees C). At the offshore sites chi a concentrations were lower (0.2 to 2 mu g l(-1)) and did not vary seasonally. Nitrate and phosphate concentrations were generally low (0 to 3.68 mu M and 0.09 to 3 mu M for nitrate and phosphate respectively), whereas silicate was present in concentrations in the range 0.19 to 13 mu M. The phytoplankton community was dominated by diatoms, particularly at the inshore sites, as determined by a combination of microscopic and high-performance liquid chromatography (HPLC) pigment analyses. At the offshore sites the proportion of green flagellates increased. The cyanobacterium genus Trichodesmium and the diatom genera Chaetoceros, Rhizosolenia, Bacteriastrum and Thalassionema dominated the phytoplankton caught in 37 mu m mesh nets; however, in contrast to many other coastal areas studied worldwide there was no distinct species succession of the diatoms and only Trichodesmium showed seasonal changes in abundance. This reflects a stable phytoplankton community in waters without pulses of physical and chemical disturbances. These results are discussed in the context of the commercial prawn fishery in the Gulf of Carpentaria and the possible effect of phytoplankton on prawn larval growth and survival.

On the expressive power of behavioral profiles

Behavioral profiles have been proposed as a behavioral abstraction of dynamic systems, specifically in the context of business process modeling. A behavioral profile can be seen as a complete graph over a set of task labels, where each edge is annotated with one relation from a given set of binary behavioral relations. Since their introduction, behavioral profiles were argued to provide a convenient way for comparing pairs of process models with respect to their behavior or computing behavioral similarity between process models. Still, as of today, there is little understanding of the expressive power of behavioral profiles. Via counter-examples, several authors have shown that behavioral profiles over various sets of behavioral relations cannot distinguish certain systems up to trace equivalence, even for restricted classes of systems represented as safe workflow nets. This paper studies the expressive power of behavioral profiles from two angles. Firstly, the paper investigates the expressive power of behavioral profiles and systems captured as acyclic workflow nets. It is shown that for unlabeled acyclic workflow net systems, behavioral profiles over a simple set of behavioral relations are expressive up to configuration equivalence. When systems are labeled, this result does not hold for any of several previously proposed sets of behavioral relations. Secondly, the paper compares the expressive power of behavioral profiles and regular languages. It is shown that for any set of behavioral relations, behavioral profiles are strictly less expressive than regular languages, entailing that behavioral profiles cannot be used to decide trace equivalence of finite automata and thus Petri nets.

Formal security analysis of the DNP3-secure authentication protocol

This thesis evaluates the security of Supervisory Control and Data Acquisition (SCADA) systems, which are one of the key foundations of many critical infrastructures. Specifically, it examines one of the standardised SCADA protocols called the Distributed Network Protocol Version 3, which attempts to provide a security mechanism to ensure that messages transmitted between devices, are adequately secured from rogue applications. To achieve this, the thesis applies formal methods from theoretical computer science to formally analyse the correctness of the protocol.

Development and evaluation of a spatial decision support system for malaria elimination in Bhutan

Background: Bhutan has reduced its malaria incidence significantly in the last 5 years, and is aiming for malaria elimination by 2016. To assist with the management of the Bhutanese malaria elimination programme a spatial decision support system (SDSS) was developed. The current study aims to describe SDSS development and evaluate SDSS utility and acceptability through informant interviews. Methods: The SDSS was developed based on the open-source Quantum geographical information system (QGIS) and piloted to support the distribution of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) in the two sub-districts of Samdrup Jongkhar District. It was subsequently used to support reactive case detection (RACD) in the two sub-districts of Samdrup Jongkhar and two additional sub-districts in Sarpang District. Interviews were conducted to ascertain perceptions on utility and acceptability of 11 informants using the SDSS, including programme and district managers, and field workers. Results: A total of 1502 households with a population of 7165 were enumerated in the four sub-districts, and a total of 3491 LLINs were distributed with one LLIN per 1.7 persons. A total of 279 households representing 728 residents were involved with RACD. Informants considered that the SDSS was an improvement on previous methods for organizing LLIN distribution, IRS and RACD, and could be easily integrated into routine malaria and other vector-borne disease surveillance systems. Informants identified some challenges at the programme and field level, including the need for more skilled personnel to manage the SDSS, and more training to improve the effectiveness of SDSS implementation and use of hardware. Conclusions: The SDSS was well accepted and informants expected its use to be extended to other malaria reporting districts and other vector-borne diseases. Challenges associated with efficient SDSS use included adequate skills and knowledge, access to training and support, and availability of hardware including computers and global positioning system receivers.

Understanding data flow and security requirements in wireless Body Area Networks for healthcare

The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.