Multi-sensor data fusion for UAV navigation during landing operations

This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

Polycaprolactone-based scaffold plus rhBMP-2 in a sheep thoracic spine fusion model

We report the application of a novel scaffold design in a sheep thoracic spine model for spine deformity correction. The combination of the calcium-phosphate coated polycaprolactone scaffolds with recombinant human bone morphogenic protein-2 (rhBMP-2) are intended as a future bone graft substitute in ensuring the stability of bony intervertebral fusion. A solid free-form fabrication process based on melt extrusion has been utilized in the manufacturing of these scaffolds. To date there are no studies examining the use of such biodegradable implants in a sheep thoracic spine model. The success of anterior scoliosis surgery in humans depends on achieving a solid bony fusion between adjacent vertebrae after the intervertebral discs have been surgically cleared and the disc spaces filled with graft material. Due to limited availability of autograft, there is much current interest in the development of synthetic scaffolds in combination with growth factors such as recombinant human bone morphogenetic protein (rhBMP-2) to achieve a solid bony fusion following scoliosis surgery.

Post-operative CT assessment of interbody fusion two years after thoracoscopic scoliosis surgery

The relationship between radiologic union and clinical outcome in thoracoscopic scoliosis surgery is not clear, as apparent non-union of a spinal fusion does not always correspond to a poor clinical result. The aim of this study was to evaluate CT fusion rates 2yrs after thoracoscopic surgery, and to explore the relationship between fusion scores and rod diameter, graft type, fusion level, implant failure, and lateral position in the disc space. This study suggests that moderate fusion scores secure successful clinical outcomes in thoracoscopic scoliosis surgery.

Integrating collaborative filtering and search-based techniques for personalized online product recommendation

The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

How does the size and shape of local populations in China compare to general anthropometric surveys currently used for product design?

Anthropometry has long been used for a range of ergonomic applications & product design. Although products are often designed for specific cohorts, anthropometric data are typically sourced from large scale surveys representative of the general population. Additionally, few data are available for emerging markets like China and India. This study measured 80 Chinese males that were representative of a specific cohort targeted for the design of a new product. Thirteen anthropometric measurements were recorded and compared to two large databases that represented a general population, a Chinese database and a Western database. Substantial differences were identified between the Chinese males measured in this study and both databases. The subjects were substantially taller, heavier and broader than subjects in the older Chinese database. However, they were still substantially smaller, lighter and thinner than Western males. Data from current Western anthropometric surveys are unlikely to accurately represent the target population for product designers and manufacturers in emerging markets like China.

Selling James Bond : product placement in the James Bond films

The character of James Bond for many people is intrinsically linked in their minds with particular brands – Aston Martin, Bollinger, Omega, Smirnoff vodka, and so on. This direct association between character and brand highlights the intrinsic role of product placement in the film industry, and in the James Bond films in particular. Selling James Bond: Product Placement in the James Bond Films provides a comprehensive overview of the history of product placement in the James Bond series – charting the progression of the practice and drawing direct correlations to significant cultural and historical events that impacted upon the number and types of products incorporated into the series. While primarily a financial arrangement, it is also important that the practice of product placement be examined and understood in relation to these cultural contexts, an area of research so far largely ignored by academic study. Through extensive content analysis of the official James Bond film series, as well as utilising directors’ commentary and industry reports, this book illustrates the strong impact specific cultural and historical events have had on the practice of product placement in the series. In doing so, it provides an exciting and in-depth “behind the scenes” look at the James Bond film series, and its complicated and sometimes contentious history of product placement. In the process, it charts the gradual emergence of product placement from the more traditional background shot to becoming so embedded in the actual film narrative that they have become simply yet another method for filmmakers to produce cultural meaning.

ACE research vignette 005 : success or failure - what makes the difference in managing new product development?

This series of research vignettes is aimed at sharing current and interesting findings from our team of international Entrepreneurship researchers. In this vignette, Dr Henri Burgers considers some of the factors that can make a difference in managing new product development.

Syntaxin 11 binds Vti1b and regulates late endosome to lysosome fusion in macrophages

Syntaxin 11 (Stx11) is a SNARE protein enriched in cells of the immune system. Loss or mutation of Stx11 results in familial hemophagocytic lymphohistiocytosis type-4 (FHL-4), an autosomal recessive disorder of immune dysregulation characterized by high levels of inflammatory cytokines along with defects in T-cell and natural killer cell function. We show here Stx11 is located on endosomalmembranes including late endosomes and lysosomes in macrophages. While Stx11 did not form a typical trans-SNARE complex, it did bind to the Q-SNARE Vti1b and was able to regulate the availability of Vti1b to form the Q-SNARE complexes Stx6/Stx7/Vtib and Stx7/Stx8/Vti1b. The mutant form of Stx11 sequestered Vti1b from forming the Q-SNARE complex that mediates late endosome to lysosome fusion. Depletion of Stx11 in activated macrophages leads to an accumulation of enlarged late endocytic compartments, increased trafficking to the cell surface and inhibition of late endosome to lysosome fusion. These phenotypes arerescued by the expression of an siRNA-resistant Stx11 construct in Stx11-depleted cells. Our results suggest that by regulating the availability of Vti1b, Stx11 regulates trafficking steps between late endosomes, lysosomes and the cell surface in macrophages.

Reliability of clinical measurement for assessing spinal fusion: An experimental sheep study

Study Design. A sheep study designed to compare the accuracy of static radiographs, dynamic radiographs, and computed tomographic (CT) scans for the assessment of thoracolumbar facet joint fusion as determined by micro-CT scanning. Objective. To determine the accuracy and reliability of conventional imaging techniques in identifying the status of thoracolumbar (T13-L1) facet joint fusion in a sheep model. Summary of Background Data. Plain radiographs are commonly used to determine the integrity of surgical arthrodesis of the thoracolumbar spine. Many previous studies of fusion success have relied solely on postoperative assessment of plain radiographs, a technique lacking sensitivity for pseudarthrosis. CT may be a more reliable technique, but is less well characterized. Methods. Eleven adult sheep were randomized to either attempted arthrodesis using autogenous bone graft and internal fixation (n = 3) or intentional pseudarthrosis (IP) using oxidized cellulose and internal fixation (n = 8). After 6 months, facet joint fusion was assessed by independent observers, using (1) plain static radiography alone, (2) additional dynamic radiographs, and (3) additional reconstructed spiral CT imaging. These assessments were correlated with high-resolution micro-CT imaging to predict the utility of the conventional imaging techniques in the estimation of fusion success. Results. The capacity of plain radiography alone to correctly predict fusion or pseudarthrosis was 43% and was not improved using plain radiography and dynamic radiography with also a 43% accuracy. Adding assessment by reformatted CT imaging to the plain radiography techniques increased the capacity to predict fusion outcome to 86% correctly. The sensitivity, specificity, and accuracy of static radiography were 0.33, 0.55, and 0.43, respectively, those of dynamic radiography were 0.46, 0.40, and 0.43, respectively, and those of radiography plus CT were 0.88, 0.85, and 0.86, respectively. Conclusion. CT-based evaluation correlated most closely with high-resolution micro-CT imaging. Neither plain static nor dynamic radiographs were able to predict fusion outcome accurately. © 2012 Lippincott Williams & Wilkins.

Sequential Fusion Using Correlated Decisions for Controlled Verification Errors

Fusion techniques have received considerable attention for achieving lower error rates with biometrics. A fused classifier architecture based on sequential integration of multi-instance and multi-sample fusion schemes allows controlled trade-off between false alarms and false rejects. Expressions for each type of error for the fused system have previously been derived for the case of statistically independent classifier decisions. It is shown in this paper that the performance of this architecture can be improved by modelling the correlation between classifier decisions. Correlation modelling also enables better tuning of fusion model parameters, ‘N’, the number of classifiers and ‘M’, the number of attempts/samples, and facilitates the determination of error bounds for false rejects and false accepts for each specific user. Error trade-off performance of the architecture is evaluated using HMM based speaker verification on utterances of individual digits. Results show that performance is improved for the case of favourable correlated decisions. The architecture investigated here is directly applicable to speaker verification from spoken digit strings such as credit card numbers in telephone or voice over internet protocol based applications. It is also applicable to other biometric modalities such as finger prints and handwriting samples.

Sequential fusion of decisions from adaptive and random samples for controlled verification of errors

Fusion techniques have received considerable attention for achieving performance improvement with biometrics. While a multi-sample fusion architecture reduces false rejects, it also increases false accepts. This impact on performance also depends on the nature of subsequent attempts, i.e., random or adaptive. Expressions for error rates are presented and experimentally evaluated in this work by considering the multi-sample fusion architecture for text-dependent speaker verification using HMM based digit dependent speaker models. Analysis incorporating correlation modeling demonstrates that the use of adaptive samples improves overall fusion performance compared to randomly repeated samples. For a text dependent speaker verification system using digit strings, sequential decision fusion of seven instances with three random samples is shown to reduce the overall error of the verification system by 26% which can be further reduced by 6% for adaptive samples. This analysis novel in its treatment of random and adaptive multiple presentations within a sequential fused decision architecture, is also applicable to other biometric modalities such as finger prints and handwriting samples.

Sequential fusion of decisions with favorable dependence for controlled verification errors

Statistical dependence between classifier decisions is often shown to improve performance over statistically independent decisions. Though the solution for favourable dependence between two classifier decisions has been derived, the theoretical analysis for the general case of 'n' client and impostor decision fusion has not been presented before. This paper presents the expressions developed for favourable dependence of multi-instance and multi-sample fusion schemes that employ 'AND' and 'OR' rules. The expressions are experimentally evaluated by considering the proposed architecture for text-dependent speaker verification using HMM based digit dependent speaker models. The improvement in fusion performance is found to be higher when digit combinations with favourable client and impostor decisions are used for speaker verification. The total error rate of 20% for fusion of independent decisions is reduced to 2.1% for fusion of decisions that are favourable for both client and impostors. The expressions developed here are also applicable to other biometric modalities, such as finger prints and handwriting samples, for reliable identity verification.

From product innovation to organizational innovation – and what that has to do with Business Process Management

One of the key trends that we currently witness not only in academic circles but also in industry - all throughout Australia at least – is that “Innovation” is becoming an important driver for business projects, for change agendas – and in turn, for Business Process Management initiatives.

Fusion of morphological images for airborne target detection

Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.