Estimation and control for an open-source quadcopter

This paper describes modelling, estimation and control of the horizontal translational motion of an open-source and cost effective quadcopter — the MikroKopter. We determine the dynamics of its roll and pitch attitude controller, system latencies, and the units associated with the values exchanged with the vehicle over its serial port. Using this we create a horizontal-plane velocity estimator that uses data from the built-in inertial sensors and an onboard laser scanner, and implement translational control using a nested control loop architecture. We present experimental results for the model and estimator, as well as closed-loop positioning.

Facilitating Malaysia towards innovative society : arguing the case for open access policy

The Malaysian National Innovation Model blueprint states that there is an urgent need to pursue an innovation-oriented economy to improve the nation’s capacity for knowledge, creativity and innovation. In nurturing a pervasive innovation culture, the Malaysian government has declared the year 2010 as an Innovative Year whereby creativity among its population is highly celebrated. However, while Malaysian citizens are encouraged to be creative and innovative, scientific data and information generated from publicly funded research in Malaysia is locked up because of rigid intellectual property licensing regimes and traditional publishing models. Reflecting on these circumstances, this paper looks at, and argue why, scientific data and information should be made available, accessible and re-useable freely to promote the grassroots level of innovation in Malaysia. Using innovation theory as its platform of argument, this paper calls for an open access policy for publicly funded research output to be adopted and implemented in Malaysia. Simultaneously, a normative analytic approach is used to determine the types of open access policy that ought to be adopted to spur greater innovation among Malaysians.

Tools and methods for capturing Twitter data during natural disasters

During the course of several natural disasters in recent years, Twitter has been found to play an important role as an additional medium for many–to–many crisis communication. Emergency services are successfully using Twitter to inform the public about current developments, and are increasingly also attempting to source first–hand situational information from Twitter feeds (such as relevant hashtags). The further study of the uses of Twitter during natural disasters relies on the development of flexible and reliable research infrastructure for tracking and analysing Twitter feeds at scale and in close to real time, however. This article outlines two approaches to the development of such infrastructure: one which builds on the readily available open source platform yourTwapperkeeper to provide a low–cost, simple, and basic solution; and, one which establishes a more powerful and flexible framework by drawing on highly scaleable, state–of–the–art technology.

Cyclic imides and an open-chain amide carboxylic acid from the facile reaction of cis-cyclohexane-1,2-dicarboxylic anhydride with the isomeric monofluoroanilines

The structures of the cyclic imides cis-2-(2-fluorophenyl)-3a,4,5,6,7,7a-hexahydroisoindole-1,3-dione, C14H14FNO2, (I), and cis-2-(4-fluorophenyl)-3a,4,5,6,7,7a-hexahydroisoindoline-1,3-dione, C14H14FNO2, (III), and the open-chain amide acid rac-cis-2-[(3-fluorophenyl)carbamoyl]cyclohexane-1-carboxylic acid, C14H16FNO3, (II), are reported. Cyclic imides (I) and (III) are conformationally similar, with comparable ring rotations about the imide N-Car bond [the dihedral angles between the benzene ring and the five-membered isoindole ring are 55.40 (8)° for (I) and 51.83 (7)° for (III)]. There are no formal intermolecular hydrogen bonds involved in the crystal packing of either (I) or (III). With the acid (II), in which the meta-related F-atom substituent is rotationally disordered (0.784:0.216), the amide group lies slightly out of the benzene plane [the interplanar dihedral angle is 39.7 (1)°]. Intermolecular amide-carboxyl N-HO hydrogen-bonding interactions between centrosymmetrically related molecules form stacks extending down b, and these are linked across c by carboxyl-amide O-HO hydrogen bonds, giving two-dimensional layered structures which lie in the (011) plane. The structures reported here represent examples of compounds analogous to the phthalimides or phthalanilic acids and have little precedence in the crystallographic literature.

Business Process Data Compliance

Most approaches to business process compliance are restricted to the analysis of the structure of processes. It has been argued that full regulatory compliance requires information on not only the structure of processes but also on what the tasks in a process do. To this end Governatori and Sadiq[2007] proposed to extend business processes with semantic annotations. We propose a methodology to automatically extract one kind of such annotations; in particular the annotations related to the data schema and templates linked to the various tasks in a business process.

System identification, estimation and control for a cost effective open-source quadcopter

This paper describes system identification, estimation and control of translational motion and heading angle for a cost effective open-source quadcopter — the MikroKopter. The dynamics of its built-in sensors, roll and pitch attitude controller, and system latencies are determined and used to design a computationally inexpensive multi-rate velocity estimator that fuses data from the built-in inertial sensors and a low-rate onboard laser range finder. Control is performed using a nested loop structure that is also computationally inexpensive and incorporates different sensors. Experimental results for the estimator and closed-loop positioning are presented and compared with ground truth from a motion capture system.

Association between prostinogen (KLK15) genetic variants and prostate cancer risk and aggressiveness in Australia and a meta-analysis of GWAS data

Background: Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease. Objectives: We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Methods and Data Sources: Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study. Results: Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p, 0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77-0.93; p = 2.7610 24). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells. Conclusions: Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes.

Validation of de-identified record linkage to ascertain hospital admissions in a cohort study

Background Cohort studies can provide valuable evidence of cause and effect relationships but are subject to loss of participants over time, limiting the validity of findings. Computerised record linkage offers a passive and ongoing method of obtaining health outcomes from existing routinely collected data sources. However, the quality of record linkage is reliant upon the availability and accuracy of common identifying variables. We sought to develop and validate a method for linking a cohort study to a state-wide hospital admissions dataset with limited availability of unique identifying variables. Methods A sample of 2000 participants from a cohort study (n = 41 514) was linked to a state-wide hospitalisations dataset in Victoria, Australia using the national health insurance (Medicare) number and demographic data as identifying variables. Availability of the health insurance number was limited in both datasets; therefore linkage was undertaken both with and without use of this number and agreement tested between both algorithms. Sensitivity was calculated for a sub-sample of 101 participants with a hospital admission confirmed by medical record review. Results Of the 2000 study participants, 85% were found to have a record in the hospitalisations dataset when the national health insurance number and sex were used as linkage variables and 92% when demographic details only were used. When agreement between the two methods was tested the disagreement fraction was 9%, mainly due to "false positive" links when demographic details only were used. A final algorithm that used multiple combinations of identifying variables resulted in a match proportion of 87%. Sensitivity of this final linkage was 95%. Conclusions High quality record linkage of cohort data with a hospitalisations dataset that has limited identifiers can be achieved using combinations of a national health insurance number and demographic data as identifying variables.

Interleukin-13 promotes susceptibility to chlamydial infection of the respiratory and genital tracts

Chlamydiae are intracellular bacteria that commonly cause infections of the respiratory and genital tracts, which are major clinical problems. Infections are also linked to the aetiology of diseases such as asthma, emphysema and heart disease. The clinical management of infection is problematic and antibiotic resistance is emerging. Increased understanding of immune processes that are involved in both clearance and immunopathology of chlamydial infection is critical for the development of improved treatment strategies. Here, we show that IL-13 was produced in the lungs of mice rapidly after Chlamydia muridarum (Cmu) infection and promoted susceptibility to infection. Wild-type (WT) mice had increased disease severity, bacterial load and associated inflammation compared to IL-13 deficient (−/−) mice as early as 3 days post infection (p.i.). Intratracheal instillation of IL-13 enhanced bacterial load in IL-13−/− mice. There were no differences in early IFN-g and IL-10 expression between WT and IL-13−/− mice and depletion of CD4+ T cells did not affect infection in IL-13−/− mice. Collectively, these data demonstrate a lack of CD4+ T cell involvement and a novel role for IL-13 in innate responses to infection. We also showed that IL-13 deficiency increased macrophage uptake of Cmu in vitro and in vivo. Moreover, the depletion of IL-13 during infection of lung epithelial cells in vitro decreased the percentage of infected cells and reduced bacterial growth. Our results suggest that enhanced IL-13 responses in the airways, such as that found in asthmatics, may promote susceptibility to chlamydial lung infection. Importantly the role of IL-13 in regulating infection was not limited to the lung as we showed that IL-13 also promoted susceptibility to Cmu genital tract infection. Collectively our findings demonstrate that innate IL-13 release promotes infection that results in enhanced inflammation and have broad implications for the treatment of chlamydial infections and IL-13-associated diseases.

A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

Quantity of documentation of maltreatment risk factors in injury-related paediatric hospitalisations

Background While child maltreatment is recognised as a global problem, solid epidemiological data on the prevalence of child maltreatment and risk factors associated with child maltreatment is lacking in Australia and internationally. There have been recent calls for action to improve the evidence-base capturing and describing child abuse, particularly those data captured within the health sector. This paper describes the quantity of documentation of maltreatment risk factors in injury-related paediatric hospitalisations in Queensland, Australia. Methods This study involved a retrospective medical record review, text extraction and coding methodology to assess the quantity of documentation of risk factors and the subsequent utility of data in hospital records for describing child maltreatment and data linkage to Child Protection Service (CPS). Results There were 433 children in the maltreatment group and 462 in the unintentional injury group for whom medical records could be reviewed. Almost 93% of the any maltreatment code sample, but only 11% of the unintentional injury sample had documentation identified indicating the presence of any of 20 risk factors. In the maltreatment group the most commonly documented risk factor was history of abuse (41%). In those with an unintentional injury, the most commonly documented risk factor was alcohol abuse of the child or family (3%). More than 93% of the maltreatment sample also linked to a child protection record. Of concern are the 16% of those children who linked to child protection who did not have documented risk factors in the medical record. Conclusion Given the importance of the medical record as a source of information about children presenting to hospital for treatment and as a potential source of evidence for legal action the lack of documentation is of concern. The details surrounding the injury admission and consideration of any maltreatment related risk factors, both identifying their presence and ruling them out are required for each and every case. This highlights the need for additional training for clinicians to understand the importance of their documentation in child injury cases.

Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

Sharing environmental data : the role of an information policy framework and copyright licensing

Advances in information and communication technologies have brought about an information revolution, leading to fundamental changes in the way that information is collected or generated, shared and distributed. The importance of establishing systems in which research findings can be readily made available to and used by other researchers has long been recognized in international scientific collaborations. If the data access principles adopted by international scientific collaborations are to be effectively implemented they must be supported by the national policies and laws in place in the countries in which participating researchers are operating.

Juggling information policy, rights to information and copyright licensing to enhance the accessibility and reusability of spatial data : the Australian experience

There is still no comprehensive information strategy governing access to and reuse of public sector information, applying on a nationwide basis, across all levels of government – local, state and federal - in Australia. This is the case both for public sector materials generally and for spatial data in particular. Nevertheless, the last five years have seen some significant developments in information policy and practice, the result of which has been a considerable lessening of the barriers that previously acted to impede the accessibility and reusability of a great deal of spatial and other material held by public sector agencies. Much of the impetus for change has come from the spatial community which has for many years been a proponent of the view “that government held information, and in particular spatial information, will play an absolutely critical role in increasing the innovative capacity of this nation.”1 However, the potential of government spatial data to contribute to innovation will remain unfulfilled without reform of policies on access and reuse as well as the pervasive practices of public sector data custodians who have relied on government copyright to justify the imposition of restrictive conditions on its use.

Enabling access to research data in developing countries : designing a policy and practice framework for Malaysia’s Public Research Universities

Members of the World Trade Organisation (WTO) are obliged to implement the Agreement on Trade-related Intellectual Property Rights 1994 (TRIPS) which establishes minimum standards for the protection and enforcement of intellectual property rights. Almost two decades after TRIPS was adopted at the conclusion of the Uruguay Round of trade negotiations, it is widely accepted that intellectual property systems in developing and least-developed countries must be consistent with, and serve, their development needs and objectives. In adopting the Development Agenda in 2007, the World Intellectual Property Organisation (WIPO) emphasised the importance to developing and least-developed countries of being able to obtain access to knowledge and technology and to participate in collaborations and exchanges with research and scientific institutions in other countries. Access to knowledge, information and technology is crucial if creativity and innovation is to be fostered in developing and least-developed countries. It is particularly important that developing and least-developed countries give effect to their TRIPS obligations by implementing intellectual property systems and adopting intellectual property management practices that enable them to benefit from knowledge flows and support their engagement in international research and science collaborations. However, developing and least-developed countries did not participate in the deliberations leading to the adoption in 2004 by Organisation for Economic Co-operation and Development (OECD) member countries of the Ministerial Declaration on Access to Research Data from Public Funding, nor have they formulated policies on access to publicly funded research outputs such as those developed by the National Institutes of Health in the United States, the United Kingdom Research Councils or the Australian National Health and Medical Research Council. These issues are considered from the viewpoint of Malaysia, a developing country whose economy has grown strongly in recent years. Lacking an established policy covering access to the outputs of publicly funded research, data sharing and licensing practices continue to be fragmented. Obtaining access to research data requires arrangements to be negotiated with individual data owners and custodians. Given the potential for restrictions on access to impact negatively on scientific progress and development in Malaysia, measures are required to ensure that access to knowledge and research results is facilitated. This paper proposes a policy framework for Malaysia‘s public research universities that recognises intellectual property rights while enabling the open access to research data that is essential for innovation and development. It also considers how intellectual property rights in research data can be managed in order to give effect to the policy‘s open access objectives.