Acoustic hazard detection for pedestrians with obscured hearing

Pedestrians’ use of mp3 players or mobile phones can pose the risk of being hit by motor vehicles. We present an approach for detecting a crash risk level using the computing power and the microphone of mobile devices that can be used to alert the user in advance of an approaching vehicle so as to avoid a crash. A single feature extractor classifier is not usually able to deal with the diversity of risky acoustic scenarios. In this paper, we address the problem of detection of vehicles approaching a pedestrian by a novel, simple, non resource intensive acoustic method. The method uses a set of existing statistical tools to mine signal features. Audio features are adaptively thresholded for relevance and classified with a three component heuristic. The resulting Acoustic Hazard Detection (AHD) system has a very low false positive detection rate. The results of this study could help mobile device manufacturers to embed the presented features into future potable devices and contribute to road safety.

Graph rigidity for near-coplanar structure from motion

Recent algorithms for monocular motion capture (MoCap) estimate weak-perspective camera matrices between images using a small subset of approximately-rigid points on the human body (i.e. the torso and hip). A problem with this approach, however, is that these points are often close to coplanar, causing canonical linear factorisation algorithms for rigid structure from motion (SFM) to become extremely sensitive to noise. In this paper, we propose an alternative solution to weak-perspective SFM based on a convex relaxation of graph rigidity. We demonstrate the success of our algorithm on both synthetic and real world data, allowing for much improved solutions to marker less MoCap problems on human bodies. Finally, we propose an approach to solve the two-fold ambiguity over bone direction using a k-nearest neighbour kernel density estimator.

Identification of early-stage colorectal cancer patients at risk of relapse post-resection by immunobead reverse transcription-PCR analysis of peritoneal lavage fluid for malignant cells

Purpose: Colorectal cancer patients diagnosed with stage I or II disease are not routinely offered adjuvant chemotherapy following resection of the primary tumor. However, up to 10% of stage I and 30% of stage II patients relapse within 5 years of surgery from recurrent or metastatic disease. The aim of this study was to determine if tumor-associated markers could detect disseminated malignant cells and so identify a subgroup of patients with early-stage colorectal cancer that were at risk of relapse. Experimental Design: We recruited consecutive patients undergoing curative resection for early-stage colorectal cancer. Immunobead reverse transcription-PCR of five tumor-associated markers (carcinoembryonic antigen, laminin γ2, ephrin B4, matrilysin, and cytokeratin 20) was used to detect the presence of colon tumor cells in peripheral blood and within the peritoneal cavity of colon cancer patients perioperatively. Clinicopathologic variables were tested for their effect on survival outcomes in univariate analyses using the Kaplan-Meier method. A multivariate Cox proportional hazards regression analysis was done to determine whether detection of tumor cells was an independent prognostic marker for disease relapse. Results: Overall, 41 of 125 (32.8%) early-stage patients were positive for disseminated tumor cells. Patients who were marker positive for disseminated cells in post-resection lavage samples showed a significantly poorer prognosis (hazard ratio, 6.2; 95% confidence interval, 1.9-19.6; P = 0.002), and this was independent of other risk factors. Conclusion: The markers used in this study identified a subgroup of early-stage patients at increased risk of relapse post-resection for primary colorectal cancer. This method may be considered as a new diagnostic tool to improve the staging and management of colorectal cancer. © 2006 American Association for Cancer Research.

A Bayesian approach for estimating detection times in horses : exploring the pharmacokinetics of a urinary acepromazine metabolite

We describe the population pharmacokinetics of an acepromazine (ACP) metabolite (2-(1-hydroxyethyl)promazine) (HEPS) in horses for the estimation of likely detection times in plasma and urine. Acepromazine (30 mg) was administered to 12 horses, and blood and urine samples were taken at frequent intervals for chemical analysis. A Bayesian hierarchical model was fitted to describe concentration-time data and cumulative urine amounts for HEPS. The metabolite HEPS was modelled separately from the parent ACP as the half-life of the parent was considerably less than that of the metabolite. The clearance ($Cl/F_{PM}$) and volume of distribution ($V/F_{PM}$), scaled by the fraction of parent converted to metabolite, were estimated as 769 L/h and 6874 L, respectively. For a typical horse in the study, after receiving 30 mg of ACP, the upper limit of the detection time was 35 hours in plasma and 100 hours in urine, assuming an arbitrary limit of detection of 1 $\mu$g/L, and a small ($\approx 0.01$) probability of detection. The model derived allowed the probability of detection to be estimated at the population level. This analysis was conducted on data collected from only 12 horses, but we assume that this is representative of the wider population.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

Immunohistochemical detection of survivin in canine lymphoma

Survivin is a member of the family of proteins known as 'inhibitors of apoptosis proteins'. Survivin has a role in cellular decisions concerning division and survival and is frequently expressed in neoplastic cells. The aim of the present study was to investigate immunohistochemically the expression of survivin in normal canine tissues and in canine lymphoma. A representative range of fetal and adult normal tissues as well as biopsy samples from dogs with lymphoma were assembled in tissue arrays. The lymphomas were classified according to the revised Kiel and to the Revised European American Lymphoma - World Health Organization (REAL-WHO) schemes. Polyclonal and monoclonal antisera cross-reactive with canine survivin identified cytoplasmic expression of the molecule in a broad range of normal canine cells. The same reagents demonstrated cytoplasmic labelling of more than 5% of cells in all 83 lymphoma samples tested with polyclonal antiserum and in 67 of 82 (82%) of samples tested with monoclonal antiserum. Survivin was expressed by a wide range of canine lymphoma subtypes, but the expression of this molecule in normal canine tissues must be considered if novel therapies targeting survivin are applied to the management of canine lymphoma. © 2010 Elsevier Ltd.

A fragment of the LG3 peptide of endorepellin is present in the urine of physically active mining workers : a potential marker of physical activity

Biomarker analysis has been implemented in sports research in an attempt to monitor the effects of exertion and fatigue in athletes. This study proposed that while such biomarkers may be useful for monitoring injury risk in workers, proteomic approaches might also be utilised to identify novel exertion or injury markers. We found that urinary urea and cortisol levels were significantly elevated in mining workers following a 12 hour overnight shift. These levels failed to return to baseline over 24h in the more active maintenance crew compared to truck drivers (operators) suggesting a lack of recovery between shifts. Use of a SELDI-TOF MS approach to detect novel exertion or injury markers revealed a spectral feature which was associated with workers in both work categories who were engaged in higher levels of physical activity. This feature was identified as the LG3 peptide, a C-terminal fragment of the anti-angiogenic / anti-tumourigenic protein endorepellin. This finding suggests that urinary LG3 peptide may be a biomarker of physical activity. It is also possible that the activity mediated release of LG3 / endorepellin into the circulation may represent a biological mechanism for the known inverse association between physical activity and cancer risk / survival.

Development of a high-speed sensing and detection system for automatic removal of packages with leaky seals from a high-speed food processing and packaging line

Contamination of packaged foods due to micro-organisms entering through air leaks can cause serious public health issues and cost companies large amounts of money due to product recalls, consumer impact and subsequent loss of market share. The main source of contamination is leaks in packaging which allow air, moisture and microorganisms to enter the package. In the food processing and packaging industry worldwide, there is an increasing demand for cost effective state of the art inspection technologies that are capable of reliably detecting leaky seals and delivering products at six-sigma. The new technology will develop non-destructive testing technology using digital imaging and sensing combined with a differential vacuum technique to assess seal integrity of food packages on a high-speed production line. The cost of leaky packages in Australian food industries is estimated close to AUD $35 Million per year. Contamination of packaged foods due to micro-organisms entering through air leaks can cause serious public health issues and cost companies large sums of money due to product recalls, compensation claims and loss of market share. The main source of contamination is leaks in packaging which allow air, moisture and micro-organisms to enter the package. Flexible plastic packages are widely used, and are the least expensive form of retaining the quality of the product. These packets can be used to seal, and therefore maximise, the shelf life of both dry and moist products. The seals of food packages need to be airtight so that the food content is not contaminated due to contact with microorganisms that enter as a result of air leakage. Airtight seals also extend the shelf life of packaged foods, and manufacturers attempt to prevent food products with leaky seals being sold to consumers. There are many current NDT (non-destructive testing) methods of testing the seal of flexible packages best suited to random sampling, and for laboratory purposes. The three most commonly used methods are vacuum/pressure decay, bubble test, and helium leak detection. Although these methods can detect very fine leaks, they are limited by their high processing time and are not viable in a production line. Two nondestructive in-line packaging inspection machines are currently available and are discussed in the literature review. The detailed design and development of the High-Speed Sensing and Detection System (HSDS) is the fundamental requirement of this project and the future prototype and production unit. Successful laboratory testing was completed and a methodical design procedure was needed for a successful concept. The Mechanical tests confirmed the vacuum hypothesis and seal integrity with good consistent results. Electrically, the testing also provided solid results to enable the researcher to move the project forward with a certain amount of confidence. The laboratory design testing allowed the researcher to confirm theoretical assumptions before moving into the detailed design phase. Discussion on the development of the alternative concepts in both mechanical and electrical disciplines enables the researcher to make an informed decision. Each major mechanical and electrical component is detailed through the research and design process. The design procedure methodically works through the various major functions both from a mechanical and electrical perspective. It opens up alternative ideas for the major components that although are sometimes not practical in this application, show that the researcher has exhausted all engineering and functionality thoughts. Further concepts were then designed and developed for the entire HSDS unit based on previous practice and theory. In the future, it would be envisaged that both the Prototype and Production version of the HSDS would utilise standard industry available components, manufactured and distributed locally. Future research and testing of the prototype unit could result in a successful trial unit being incorporated in a working food processing production environment. Recommendations and future works are discussed, along with options in other food processing and packaging disciplines, and other areas in the non-food processing industry.

A radiological method to determine the accuracy of motion capture marker placement on palpable anatomical landmarks through a shoe

The accuracy of marker placement on palpable surface anatomical landmarks is an important consideration in biomechanics. Although marker placement reliability has been studied in some depth, it remains unclear whether or not the markers are accurately positioned over the intended landmark in order to define the static position and orientation of the segment. A novel method using commonly available X-ray imaging was developed to identify the accuracy of markers placed on the shoe surface by palpating landmarks through the shoe. An anterior–posterior and lateral–medial X-ray was taken on 24 participants with a newly developed marker set applied to both the skin and shoe. The vector magnitude of both skin- and shoe-mounted markers from the anatomical landmark was calculated, as well as the mean marker offset between skin- and shoe-mounted markers. The accuracy of placing markers on the shoe relative to the skin-mounted markers, accounting for shoe thickness, was less than 5mm for all markers studied. Further, when using the developed guidelines provided in this study, the method was deemed reliable (Intra-rater ICCs¼0.50–0.92). In conclusion, the method proposed here can reliably assess marker placement accuracy on the shoe surface relative to chosen anatomical landmarks beneath the skin.

The expression, regulation and function of kallikrein 4 in prostate cancer

Prostate cancer is a significant health problem faced by aging men. Currently, diagnostic strategies for the detection of prostate cancer are either unreliable, yielding high numbers of false positive results, or too invasive to be used widely as screening tests. Furthermore, the current therapeutic strategies for the treatment of the disease carry considerable side effects. Although organ confined prostate cancer can be curable, most detectable clinical symptoms occur in advanced disease when primary tumour cells have metastasised to distant sites - usually lymph nodes and bone. Many growth factors and steroids assist the continued growth and maintenance of prostatic tumour cells. Of these mitogens, androgens are important in the development of the normal prostate but are also required to sustain the growth of prostate cancer cells in the early stage of the disease. Not only are androgens required in the early stage of disease, but also many other growth factors and hormones interact to cause uncontrolled proliferation of malignant cells. The early, androgen sensitive phase of disease is followed by an androgen insensitive phase, whereby androgens are no longer required to stimulate the growth of the tumour cells. Growth factors such as transforming growth factor  and  (TGF/), epidermal growth factor (EGF), basic fibroblast growth factor (bFGF), insulin-like growth factors (IGFs), Vitamin D and thyroid hormone have been suggested to be important at this stage of disease. Interestingly, some of the kallikrein family of genes, including prostate specific antigen (PSA), the current serum diagnostic marker for prostate cancer, are regulated by androgens and many of the aforementioned growth factors. The kallikrein gene family is a group of serine proteases that are involved in a diverse range of physiological processes: regulation of local blood flow, angiogenesis, tissue invasion and mitogenesis. The earliest members of the kallikrein gene family (KLK1-KLK3) have been strongly associated with general disease states, such as hypertension, inflammation, pancreatitis and renal disease, but are also linked to various cancers. Recently, this family was extended to include 15 genes (KLK1-15). Several newer members of the kallikrein family have been implicated in the carcinogenesis and tumour metastasis of hormone-dependent cancers such as prostate, breast, endometrial and ovarian cancer. The aims of this project were to investigate the expression of the newly identified kallikrein, KLK4, in benign and malignant prostate tissues, and prostate cancer cell lines. This thesis has demonstrated the elevated expression of KLK4 mRNA transcripts in malignant prostate tissue compared to benign prostates. Additionally, expression of the full length KLK4 transcript was detected in the androgen dependent prostate cancer cell line, LNCaP. Based on the above finding, the LNCaP cell line was chosen to assess the potential regulation of full length KLK4 by androgen, thyroid hormone and epidermal growth factor. KLK4 mRNA and protein was found to be up-regulated by androgen and a combination of androgen and thyroid hormone. Thyroid hormone alone produced no significant change in KLK4 mRNA or protein over the control. Epidermal growth factor treatment also resulted in elevated expression levels of KLK4 mRNA and protein. To assess the potential functional role(s) of KLK4/hK4 in processes associated with tumour progression, full length KLK4 was transfected into PC-3 cells - a prostate cancer cell line originally derived from a secondary bone lesion. The KLK4/hK4 over-expressing cells were assessed for their proliferation, migration, invasion and attachment properties. The KLK4 over-expressing clones exhibited a marked change in morphology, indicative of a more aggressive phenotype. The KLK4 clones were irregularly shaped with compromised adhesion to the growth surface. In contrast, the control cell lines (parent PC-3 and empty vector clones) retained a rounded morphology with obvious cell to cell adhesion, as well as significant adhesion to their growth surface. The KLK4 clones exhibited significantly greater attachment to Collagen I and IV than native PC-3s and empty vector controls. Over a 12 hour period, in comparison to the control cells, the KLK4 clones displayed an increase in migration towards PC-3 native conditioned media, a 3 fold increase towards conditioned media from an osteoblastic cell line (Saos-2) and no change in migration towards conditioned media from neonatal foreskin fibroblast cells or 20% foetal bovine serum. Furthermore, the increase in migration exhibited by the KLK4 clones was partially blocked by the serine protease inhibitor, aprotinin. The data presented in this thesis suggests that KLK4/hK4 is important in prostate carcinogenesis due to its over-expression in malignant prostate tissues, its regulation by hormones and growth factors associated with prostate disease and the functional consequences of over-expression of KLK4/hK4 in the PC-3 cell line. These results indicate that KLK4/hK4 may play an important role in tumour invasion and bone metastasis via increased attachment to the bone matrix protein, Collagen I, and enhanced migration due to soluble factors produced by osteoblast cells. This suggestion is further supported by the morphological changes displayed by the KLK4 over-expressing cells. Overall, this data suggests that KLK4/hK4 should be further studied to more fully investigate the potential value of KLK4/hK4 as a diagnostic/prognostic biomarker or in therapeutic applications.

Deep Raman spectroscopy for the non-invasive standoff detection of concealed chemical threat agents

Deep Raman spectroscopy has been utilized for the standoff detection of concealed chemical threat agents from a distance of 15 meters under real life background illumination conditions. By using combined time and space resolved measurements, various explosive precursors hidden in opaque plastic containers were identified non-invasively. Our results confirm that combined time and space resolved Raman spectroscopy leads to higher selectivity towards the sub-layer over the surface layer as well as enhanced rejection of fluorescence from the container surface when compared to standoff spatially offset Raman spectroscopy. Raman spectra that have minimal interference from the packaging material and good signal-to-noise ratio were acquired within 5 seconds of measurement time. A new combined time and space resolved Raman spectrometer has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than picosecond-based laboratory systems.

Fast detection of exact clones in business process model repositories

As organizations reach higher levels of business process management maturity, they often find themselves maintaining very large process model repositories, representing valuable knowledge about their operations. A common practice within these repositories is to create new process models, or extend existing ones, by copying and merging fragments from other models. We contend that if these duplicate fragments, a.k.a. ex- act clones, can be identified and factored out as shared subprocesses, the repository’s maintainability can be greatly improved. With this purpose in mind, we propose an indexing structure to support fast detection of clones in process model repositories. Moreover, we show how this index can be used to efficiently query a process model repository for fragments. This index, called RPSDAG, is based on a novel combination of a method for process model decomposition (namely the Refined Process Structure Tree), with established graph canonization and string matching techniques. We evaluated the RPSDAG with large process model repositories from industrial practice. The experiments show that a significant number of non-trivial clones can be efficiently found in such repositories, and that fragment queries can be handled efficiently.

Approximate clone detection in repositories of business process models

Evidence exists that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication may stem from the fact that the repository describes variants of the same pro- cesses and/or because of copy/pasting activity throughout the lifetime of the repository. Previous work has put forward techniques for identifying duplicate fragments (clones) that can be refactored into shared subprocesses. However, these techniques are limited to finding exact clones. This paper analyzes the prob- lem of approximate clone detection and puts forward two techniques for detecting clusters of approximate clones. Experiments show that the proposed techniques are able to accurately retrieve clusters of approximate clones that originate from copy/pasting followed by independent modifications to the copied fragments.

Toward non-invasive detection of concealed energetic materials in-field under ambient-light conditions

Spatially offset Raman spectroscopy (SORS) is demonstrated for the non-contact detection of energetic materials concealed within non-transparent, diffusely scattering containers. A modified design of an inverse SORS probe has been developed and tested. The SORS probe has been successfully used for the detection of various energetic substances inside different types of plastic containers. The tests have been successfully conducted under incandescent and fluorescent background lights as well as under daylight conditions, using a non-contact working distance of 6 cm. The interrogation times for the detection of the substances were less than 1 minute in each case, highlighting the suitability of the device for near real-time detection of concealed hazards in the field. The device has potential applications in forensic analysis and homeland security investigations.

OpenFABMAP : an open source toolbox for appearance-based loop closure detection

Appearance-based loop closure techniques, which leverage the high information content of visual images and can be used independently of pose, are now widely used in robotic applications. The current state-of-the-art in the field is Fast Appearance-Based Mapping (FAB-MAP) having been demonstrated in several seminal robotic mapping experiments. In this paper, we describe OpenFABMAP, a fully open source implementation of the original FAB-MAP algorithm. Beyond the benefits of full user access to the source code, OpenFABMAP provides a number of configurable options including rapid codebook training and interest point feature tuning. We demonstrate the performance of OpenFABMAP on a number of published datasets and demonstrate the advantages of quick algorithm customisation. We present results from OpenFABMAP’s application in a highly varied range of robotics research scenarios.