Power quality improvements in low voltage distribution networks containing distributed energy resources

In this thesis various schemes using custom power devices for power quality improvement in low voltage distribution network are studied. Customer operated distributed generators makes a typical network non-radial and affect the power quality. A scheme considering different algorithm of DSTATCOM is proposed for power circulation and islanded operation of the system. To compensate reactive power overflow and facilitate unity power factor, a UPQC is introduced. Stochastic analysis is carried out for different scenarios to get a comprehensive idea about a real life distribution network. Combined operation of static compensator and voltage regulator is tested for the optimum quality and stability of the system.

Large-scale habitat mapping using vision-based AUVs : experiences, challenges & vehicle design

This paper overviews the development of a vision-based AUV along with a set of complementary operational strategies to allow reliable autonomous data collection in relatively shallow water and coral reef environments. The development of the AUV, called Starbug, encountered many challenges in terms of vehicle design, navigation and control. Some of these challenges are discussed with focus on operational strategies for estimating and reducing the total navigation error when using lower-resolution sensing modalities. Results are presented from recent field trials which illustrate the ability of the vehicle and associated operational strategies to enable rapid collection of visual data sets suitable for marine research applications.

Towards coordinated vision-based docking using an Autonomous Surface Vehicle

This paper describes the development and experimental evaluation of a novel vision-based Autonomous Surface Vehicle with the purpose of performing coordinated docking manoeuvres with a target, such as an Autonomous Underwater Vehicle, on the water’s surface. The system architecture integrates two small processor units; the first performs vehicle control and implements a virtual force obstacle avoidance and docking strategy, with the second performing vision-based target segmentation and tracking. Furthermore, the architecture utilises wireless sensor network technology allowing the vehicle to be observed by, and even integrated within an ad-hoc sensor network. The system performance is demonstrated through real-world experiments.

Representing team behaviours from noisy data using player role

Due to their unobtrusive nature, vision-based approaches to tracking sports players have been preferred over wearable sensors as they do not require the players to be instrumented for each match. Unfortunately however, due to the heavy occlusion between players, variation in resolution and pose, in addition to fluctuating illumination conditions, tracking players continuously is still an unsolved vision problem. For tasks like clustering and retrieval, having noisy data (i.e. missing and false player detections) is problematic as it generates discontinuities in the input data stream. One method of circumventing this issue is to use an occupancy map, where the field is discretised into a series of zones and a count of player detections in each zone is obtained. A series of frames can then be concatenated to represent a set-play or example of team behaviour. A problem with this approach though is that the compressibility is low (i.e. the variability in the feature space is incredibly high). In this paper, we propose the use of a bilinear spatiotemporal basis model using a role representation to clean-up the noisy detections which operates in a low-dimensional space. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labeled data.

High and low fear phenotypes show differences in phosphorylated (p44/42 ERK) MAPK-expressing neurons in the lateral amygdala

Post traumatic stress disorder (PTSD) is a serious medical condition effecting both military and civilian populations. While its etiology remains poorly understood it is characterized by high and prolonged levels of fear responding. One biological unknown is whether individuals expressing high or low conditioned fear memory encode the memory differently and if that difference underlies fear response. In this study we examined cellular mechanisms that underlie high and low conditioned fear behavior by using an advanced intercrossed mouse line (B6D2F1) selected for high and low Pavlovian fear response. A known requirement for consolidation of fear memory, phosphorylated mitogen activated protein kinase (p44/42 (ERK) MAPK (pMAPK)) in the lateral amygdala (LA) is a reliable marker of fear learning-related plasticity. In this study, we asked whether high and low conditioned fear behavior is associated with differential pMAPK expression in the LA and if so, is it due to an increase in neurons expressing pMAPK or increased pMAPK per neuron. To examine this, we quantified pMAPK-expressing neurons in the LA at baseline and following Pavlovian fear conditioning. Results indicate that high fear phenotype mice have more pMAPK-expressing neurons in the LA. This finding suggests that increased endogenous plasticity in the LA may be a component of higher conditioned fear responses and begins to explain at the cellular level how different fear responders encode fear memories. Understanding how high and low fear responders encode fear memory will help identify novel ways in which fear-related illness risk can be better predicted and treated.

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

The origin of cyclical high- and low-Cr basalts with continental crust trace element signatures in the Kalkarindji Large Igneous Province

The 510 million year old Kalkarindji Large Igneous Province correlates in time with the first major extinction event after the Cambrian explosion of life. Large igneous provinces correlate with all major mass extinction events in the last 500 million years. The genetic link between large igneous provinces and mass extinction remains unclear. My work is a contribution towards understanding magmatic processes involved in the generation of Large Igneous Provinces. I concentrate on the origin of variation in Cr in magmas and have developed a model in which high temperature melts intrude into and assimilate large amounts of upper continental crust.

The rise of low-cost sensing for managing air pollution in cities

Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, whilst addressing the major challenges for their effective implementation.

Vision-based operations of a large industrial vehicle : autonomous hot metal carrier

Hot metal carriers (HMCs) are large forklift-type vehicles used to move molten metal in aluminum smelters. This paper reports on field experiments that demonstrate that HMCs can operate autonomously and in particular can use vision as a primary sensor to locate the load of aluminum. We present our complete system but focus on the vision system elements and also detail experiments demonstrating reliable operation of the materials handling task. Two key experiments are described, lasting 2 and 5 h, in which the HMC traveled 15 km in total and handled the load 80 times.

The mechanical and inflammatory low back pain (MIL) index: development and validation

Abstract Background The purpose of this study was the development of a valid and reliable “Mechanical and Inflammatory Low Back Pain Index” (MIL) for assessment of non-specific low back pain (NSLBP). This 7-item tool assists practitioners in determining whether symptoms are predominantly mechanical or inflammatory. Methods Participants (n = 170, 96 females, age = 38 ± 14 years-old) with NSLP were referred to two Spanish physiotherapy clinics and completed the MIL and the following measures: the Roland Morris Questionnaire (RMQ), SF-12 and “Backache Index” (BAI) physical assessment test. For test-retest reliability, 37 consecutive patients were assessed at baseline and three days later during a non-treatment period. Face and content validity, practical characteristics, factor analysis, internal consistency, discriminant validity and convergent validity were assessed from the full sample. Results A total of 27 potential items that had been identified for inclusion were subsequently reduced to 11 by an expert panel. Four items were then removed due to cross-loading under confirmatory factor analysis where a two-factor model yielded a good fit to the data (χ2 = 14.80, df = 13, p = 0.37, CFI = 0.98, and RMSEA = 0.029). The internal consistency was moderate (α = 0.68 for MLBP; 0.72 for ILBP), test-retest reliability high (ICC = 0.91; 95%CI = 0.88-0.93) and discriminant validity good for either MLBP (AUC = 0.74) and ILBP (AUC = 0.92). Convergent validity was demonstrated through similar but weak correlations between the ILBP and both the RMQ and BAI (r = 0.34, p < 0.001) and the MLBP and BAI (r = 0.38, p < 0.001). Conclusions The MIL is a valid and reliable clinical tool for patients with NSLBP that discriminates between mechanical and inflammatory LBP. Keywords: Low back pain; Psychometrics properties; Pain measurement; Screening tool; Inflammatory; Mechanical

Low probability differentials and the cryptanalysis of full-round CLEFIA-128

So far, low probability differentials for the key schedule of block ciphers have been used as a straightforward proof of security against related-key differential analysis. To achieve resistance, it is believed that for cipher with k-bit key it suffices the upper bound on the probability to be 2− k . Surprisingly, we show that this reasonable assumption is incorrect, and the probability should be (much) lower than 2− k . Our counter example is a related-key differential analysis of the well established block cipher CLEFIA-128. We show that although the key schedule of CLEFIA-128 prevents differentials with a probability higher than 2− 128, the linear part of the key schedule that produces the round keys, and the Feistel structure of the cipher, allow to exploit particularly chosen differentials with a probability as low as 2− 128. CLEFIA-128 has 214 such differentials, which translate to 214 pairs of weak keys. The probability of each differential is too low, but the weak keys have a special structure which allows with a divide-and-conquer approach to gain an advantage of 27 over generic analysis. We exploit the advantage and give a membership test for the weak-key class and provide analysis of the hashing modes. The proposed analysis has been tested with computer experiments on small-scale variants of CLEFIA-128. Our results do not threaten the practical use of CLEFIA.

Buy low, sell high

We consider online trading in a single security with the objective of getting rich when its price ever exhibits a large upcrossing, without risking bankruptcy. We investigate payoff guarantees that are expressed in terms of the extremity of the upcrossings. We obtain an exact and elegant characterisation of the guarantees that can be achieved. Moreover, we derive a simple canonical strategy for each attainable guarantee.