558 resultados para Real-world
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This publication consists of a volume of papers presented at the workshop of the CIB Task Group 58: Clients and Construction Innovation, held on May 18- 19, 2009 at the University of Alberta in Edmonton, Canada. The workshop theme, “Leveraging Innovation for Sustainable Construction”, reflects a growing concern among clients for perspectives, approaches, and tools that will secure the practice of construction economically, socially, and environmentally. This collection encompasses some of the most incisive assessments of the challenges facing the construction industry today from a range of researchers and industry practitioners who are leading the way for tomorrow’s innovations. It provides a useful documentation of the ongoing conversation regarding innovation and sustainability issues and a foundation of knowledge for future research and development. The papers contained in this volume explore the workshop’s overarching theme of how to leverage innovation to increase the sustainability of the construction process and product. Participants sought to generate discussion on the topics of innovation and sustainability within the construction field, to share international examples of innovation from the research community and from industry, and to establish a point of reference for ongoing enquiry. In particular, our contributors have noted the value of learning through practice in order to orient research based on real-world industry experience. Chapters two and three present complementary models of sustainable research programs through the three parts collaboration of government, industry, and academia. Chapters four and five explore new tools and forms of technological innovation as they are deployed to improve construction project management and set the direction for advances in research. Chapters six, seven, and eight closely study practical examples of innovation in large-scale construction projects, showing with concrete results the impact of applying creative methods and best practices to the field. Innovation and sustainability in construction are truly global efforts; these papers illustrate how we can draw on international examples and cooperative organizations to address these important issues for long-term benefit of the industry.
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Background This paper presents a novel approach to searching electronic medical records that is based on concept matching rather than keyword matching. Aim The concept-based approach is intended to overcome specific challenges we identified in searching medical records. Method Queries and documents were transformed from their term-based originals into medical concepts as defined by the SNOMED-CT ontology. Results Evaluation on a real-world collection of medical records showed our concept-based approach outperformed a keyword baseline by 25% in Mean Average Precision. Conclusion The concept-based approach provides a framework for further development of inference based search systems for dealing with medical data.
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This paper investigates the effects of limited speech data in the context of speaker verification using a probabilistic linear discriminant analysis (PLDA) approach. Being able to reduce the length of required speech data is important to the development of automatic speaker verification system in real world applications. When sufficient speech is available, previous research has shown that heavy-tailed PLDA (HTPLDA) modeling of speakers in the i-vector space provides state-of-the-art performance, however, the robustness of HTPLDA to the limited speech resources in development, enrolment and verification is an important issue that has not yet been investigated. In this paper, we analyze the speaker verification performance with regards to the duration of utterances used for both speaker evaluation (enrolment and verification) and score normalization and PLDA modeling during development. Two different approaches to total-variability representation are analyzed within the PLDA approach to show improved performance in short-utterance mismatched evaluation conditions and conditions for which insufficient speech resources are available for adequate system development. The results presented within this paper using the NIST 2008 Speaker Recognition Evaluation dataset suggest that the HTPLDA system can continue to achieve better performance than Gaussian PLDA (GPLDA) as evaluation utterance lengths are decreased. We also highlight the importance of matching durations for score normalization and PLDA modeling to the expected evaluation conditions. Finally, we found that a pooled total-variability approach to PLDA modeling can achieve better performance than the traditional concatenated total-variability approach for short utterances in mismatched evaluation conditions and conditions for which insufficient speech resources are available for adequate system development.
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In the current era of global economic instability, business and industry have already identified a widening gap between graduate skills and employability. An important element of this is the lack of entrepreneurial skills in graduates. This Teaching Fellowship investigated two sides of a story about entrepreneurial skills and their teaching. Senior players in the innovation commercialisation industry, a high profile entrepreneurial sector, were surveyed to gauge their needs and experiences of graduates they employ. International contexts of entrepreneurship education were investigated to explore how their teaching programs impart the skills of entrepreneurship. Such knowledge is an essential for the design of education programs that can deliver the entrepreneurial skills deemed important by industry for future sustainability. Two programs of entrepreneurship education are being implemented at QUT that draw on the best practice exemplars investigated during this Fellowship. The QUT Innovation Space (QIS) focuses on capturing the innovation and creativity of students, staff and others. The QIS is a physical and virtual meeting and networking space; a connected community enhancing the engagement of participants. The Q_Hatchery is still embryonic; but it is intended to be an innovation community that brings together nascent entrepreneurial businesses to collaborate, train and support each other. There is a niche between concept product and business incubator where an experiential learning environment for otherwise isolated ‘garage-at-home’ businesses could improve success rates. The QIS and the Q_Hatchery serve as living research laboratories to trial the concepts emerging from the skills survey. The survey of skills requirements of the innovation commercialisation industry has produced a large and high quality data set still being explored. Work experience as an employability factor has already emerged as an industry requirement that provides employee maturity. Exploratory factor analysis of the skills topics surveyed has led to a process-based conceptual model for teaching and learning higher-order entrepreneurial skills. Two foundational skills domains (Knowledge, Awareness) are proposed as prerequisites which allow individuals with a suite of early stage entrepreneurial and behavioural skills (Pre-leadership) to further leverage their careers into a leadership role in industry with development of skills around higher order elements of entrepreneurship, management in new business ventures and progressing winning technologies to market. The next stage of the analysis is to test the proposed model through structured equation modelling. Another factor that emerged quickly from the survey analysis broadens the generic concept of team skills currently voiced in Australian policy documents discussing the employability agenda. While there was recognition of the role of sharing, creating and using knowledge in a team-based interdisciplinary context, the adoption and adaptation of behaviours and attitudes of other team members of different disciplinary backgrounds (interprofessionalism) featured as an issue. Most undergraduates are taught and undertake teamwork in silos and, thus, seldom experience a true real-world interdisciplinary environment. Enhancing the entrepreneurial capacity of Australian industry is essential for the economic health of the country and can only be achieved by addressing the lack of entrepreneurial skills in graduates from the higher education system. This Fellowship has attempted to address this deficiency by identifying the skills requirements and providing frameworks for their teaching.
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Although mobile phones are often used in public urban places to interact with one’s geographically dispersed social circle, they can also facilitate interactions with people in the same public urban space. The PlaceTagz study investigates how physical artefacts in public urban places can be utilised and combined with mobile phone technologies to facilitate interactions. Printed on stickers, PlaceTagz are QR codes linking to a digital message board enabling collocated users to interact with each other over time resulting in a place-based digital memory. This exploratory project set out to investigate if and how PlaceTagz are used by urban dwellers in a real world deployment. We present findings from analysing content received through PlaceTagz and interview data from application users. QR codes, which do not contain any contextual information, piqued the curiosity of users wondering about the embedded link’s destination and provoked comments in regards to people, place and technology.
In the pursuit of effective affective computing : the relationship between features and registration
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For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a "dense" form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a "coarse" form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.
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This paper describes a novel method for determining the extrinsic calibration parameters between 2D and 3D LIDAR sensors with respect to a vehicle base frame. To recover the calibration parameters we attempt to optimize the quality of a 3D point cloud produced by the vehicle as it traverses an unknown, unmodified environment. The point cloud quality metric is derived from Rényi Quadratic Entropy and quantifies the compactness of the point distribution using only a single tuning parameter. We also present a fast approximate method to reduce the computational requirements of the entropy evaluation, allowing unsupervised calibration in vast environments with millions of points. The algorithm is analyzed using real world data gathered in many locations, showing robust calibration performance and substantial speed improvements from the approximations.
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For many years, computer vision has lured researchers with promises of a low-cost, passive, lightweight and information-rich sensor suitable for navigation purposes. The prime difficulty in vision-based navigation is that the navigation solution will continually drift with time unless external information is available, whether it be cues from the appearance of the scene, a map of features (whether built online or known a priori), or from an externally-referenced sensor. It is not merely position that is of interest in the navigation problem. Attitude (i.e. the angular orientation of a body with respect to a reference frame) is integral to a visionbased navigation solution and is often of interest in its own right (e.g. flight control). This thesis examines vision-based attitude estimation in an aerospace environment, and two methods are proposed for constraining drift in the attitude solution; one through a novel integration of optical flow and the detection of the sky horizon, and the other through a loosely-coupled integration of Visual Odometry and GPS position measurements. In the first method, roll angle, pitch angle and the three aircraft body rates are recovered though a novel method of tracking the horizon over time and integrating the horizonderived attitude information with optical flow. An image processing front-end is used to select several candidate lines in a image that may or may not correspond to the true horizon, and the optical flow is calculated for each candidate line. Using an Extended Kalman Filter (EKF), the previously estimated aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and location of the horizon in the image. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To evaluate the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42° and 0.71° respectively when compared with a truth attitude source. The Cessna 172 flight resulted in pitch and roll error standard deviations of 1.79° and 1.75° respectively. In the second method for estimating attitude, a novel integrated GPS/Visual Odometry (GPS/VO) navigation filter is proposed, using a structure similar to a classic looselycoupled GPS/INS error-state navigation filter. Under such an arrangement, the error dynamics of the system are derived and a Kalman Filter is developed for estimating the errors in position and attitude. Through similar analysis to the GPS/INS problem, it is shown that the proposed filter is capable of recovering the complete attitude (i.e. pitch, roll and yaw) of the platform when subjected to acceleration not parallel to velocity for both the monocular and stereo variants of the filter. Furthermore, it is shown that under general straight line motion (e.g. constant velocity), only the component of attitude in the direction of motion is unobservable. Numerical simulations are performed to demonstrate the observability properties of the GPS/VO filter in both the monocular and stereo camera configurations. Furthermore, the proposed filter is tested on imagery collected using a Cessna 172 to demonstrate the observability properties on real-world data. The proposed GPS/VO filter does not require additional restrictions or assumptions such as platform-specific dynamics, map-matching, feature-tracking, visual loop-closing, gravity vector or additional sensors such as an IMU or magnetic compass. Since no platformspecific dynamics are required, the proposed filter is not limited to the aerospace domain and has the potential to be deployed in other platforms such as ground robots or mobile phones.
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Even though titanium dioxide photocatalysis has been promoted as a leading green technology for water purification, many issues have hindered its application on a large commercial scale. For the materials scientist the main issues have centred the synthesis of more efficient materials and the investigation of degradation mechanisms; whereas for the engineers the main issues have been the development of appropriate models and the evaluation of intrinsic kinetics parameters that allow the scale up or re-design of efficient large-scale photocatalytic reactors. In order to obtain intrinsic kinetics parameters the reaction must be analysed and modelled considering the influence of the radiation field, pollutant concentrations and fluid dynamics. In this way, the obtained kinetic parameters are independent of the reactor size and configuration and can be subsequently used for scale-up purposes or for the development of entirely new reactor designs. This work investigates the intrinsic kinetics of phenol degradation over titania film due to the practicality of a fixed film configuration over a slurry. A flat plate reactor was designed in order to be able to control reaction parameters that include the UV irradiance, flow rates, pollutant concentration and temperature. Particular attention was paid to the investigation of the radiation field over the reactive surface and to the issue of mass transfer limited reactions. The ability of different emission models to describe the radiation field was investigated and compared to actinometric measurements. The RAD-LSI model was found to give the best predictions over the conditions tested. Mass transfer issues often limit fixed film reactors. The influence of this phenomenon was investigated with specifically planned sets of benzoic acid experiments and with the adoption of the stagnant film model. The phenol mass transfer coefficient in the system was calculated to be km,phenol=8.5815x10-7Re0.65(ms-1). The data obtained from a wide range of experimental conditions, together with an appropriate model of the system, has enabled determination of intrinsic kinetic parameters. The experiments were performed in four different irradiation levels (70.7, 57.9, 37.1 and 20.4 W m-2) and combined with three different initial phenol concentrations (20, 40 and 80 ppm) to give a wide range of final pollutant conversions (from 22% to 85%). The simple model adopted was able to fit the wide range of conditions with only four kinetic parameters; two reaction rate constants (one for phenol and one for the family of intermediates) and their corresponding adsorption constants. The intrinsic kinetic parameters values were defined as kph = 0.5226 mmol m-1 s-1 W-1, kI = 0.120 mmol m-1 s-1 W-1, Kph = 8.5 x 10-4 m3 mmol-1 and KI = 2.2 x 10-3 m3 mmol-1. The flat plate reactor allowed the investigation of the reaction under two different light configurations; liquid and substrate side illumination. The latter of particular interest for real world applications where light absorption due to turbidity and pollutants contained in the water stream to be treated could represent a significant issue. The two light configurations allowed the investigation of the effects of film thickness and the determination of the catalyst optimal thickness. The experimental investigation confirmed the predictions of a porous medium model developed to investigate the influence of diffusion, advection and photocatalytic phenomena inside the porous titania film, with the optimal thickness value individuated at 5 ìm. The model used the intrinsic kinetic parameters obtained from the flat plate reactor to predict the influence of thickness and transport phenomena on the final observed phenol conversion without using any correction factor; the excellent match between predictions and experimental results provided further proof of the quality of the parameters obtained with the proposed method.
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The demand for Business Process Management (BPM) is rapidly rising and with that, the need for capable BPM professionals is also rising. Yet, only a very few structured BPM training/ education programs are available, across universities and professional trainers globally. The ‘lack of appropriate teaching resources’ has been identified as a critical issue for BPM educators in prior studies. Case-based teaching can be an effective means of educating future BPM professionals. A main reason is that cases create an authentic learning environment where the complexities and challenges of the ‘real world’ can be presented in a narrative enabling the students to develop crucial skills such as problem solving, analysis and creativity-within-constraints, and to apply the tools and techniques within a richer and real (or proxy to real) context. However, so far well documented BPM teaching cases are scarce. This article aims to contribute to address this gap by providing a comprehensive teaching case and teaching notes that facilitates the education of selected process improvement phases, namely identification, modelling, analysis, and improvement. The article is divided into three main parts: (i) Introductory teaching notes, (ii) The case narrative, and (iii) Student activities from the case and teaching notes.
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Billing Mediation Platform (BMP) in telecommunication industry is used to process real-time streams of Call Detail Records (CDRs) which can be a massive number a day. The generated records by BMP can be deployed for billing purposes, fraud detection, spam filtering, traffic analysis, and churn forecast. Several of these applications are distinguished by real-time processing requiring low-latency analysis of CDRs. Testing of such a platform carries diverse aspects like stress testing of analytics for scalability and what-if scenarios which require generating of CDRs with realistic volumetric and appropriate properties. The approach of this project is to build user friendly and flexible application which assists the development department to test their billing solution occasionally. These generators projects have been around for a while the only difference are the potions they cover and the purpose they will be used for. This paper proposes to use a simulator application to test the BMPs with simulating CDRs. The Simulated CDRs are modifiable based on the user requirements and represent real world data.
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Rapid urbanisation and resulting continuous increase in traffic has been recognised as key factors in the contribution of increased pollutant loads to urban stormwater and in turn to receiving waters. Urbanisation primarily increases anthropogenic activities and the percentage of impervious surfaces in urban areas. These processes are collectively responsible for urban stormwater pollution. In this regard, urban traffic and land use related activities have been recognised as the primary pollutant sources. This is primarily due to the generation of a range of key pollutants such as solids, heavy metals and PAHs. Appropriate treatment system design is the most viable approach to mitigate stormwater pollution. However, limited understanding of the pollutant process and transport pathways constrains effective treatment design. This highlights necessity for the detailed understanding of traffic and other land use related pollutants processes and pathways in relation to urban stormwater pollution. This study has created new knowledge in relation to pollutant processes and transport pathways encompassing atmospheric pollutants, atmospheric deposition and build-up on ground surfaces of traffic generated key pollutants. The research study was primarily based on in-depth experimental investigations. This thesis describes the extensive knowledge created relating to the processes of atmospheric pollutant build-up, atmospheric deposition and road surface build-up and establishing their relationships as a chain of processes. The analysis of atmospheric deposition revealed that both traffic and land use related sources contribute total suspended particulate matter (TSP) to the atmosphere. Traffic sources become dominant during weekdays whereas land use related sources become dominant during weekends due to the reduction in traffic sources. The analysis further concluded that atmospheric TSP, polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) concentrations are highly influenced by total average daily heavy duty traffic, traffic congestion and the fraction of commercial and industrial land uses. A set of mathematical equation were developed to predict TSP, PAHs and HMs concentrations in the atmosphere based on the influential traffic and land use related parameters. Dry deposition samples were collected for different antecedent dry days and wet deposition samples were collected immediately after rainfall events. The dry deposition was found to increase with the antecedent dry days and consisted of relatively coarser particles (greater than 1.4 ìm) when compared to wet deposition. The wet deposition showed a strong affinity to rainfall depth, but was not related to the antecedent dry period. It was also found that smaller size particles (less than 1.4 ìm) travel much longer distances from the source and deposit mainly with the wet deposition. Pollutants in wet deposition are less sensitive to the source characteristics compared to dry deposition. Atmospheric deposition of HMs is not directly influenced by land use but rather by proximity to high emission sources such as highways. Therefore, it is important to consider atmospheric deposition as a key pollutant source to urban stormwater in the vicinity of these types of sources. Build-up was analysed for five different particle size fractions, namely, <1 ìm, 1-75 ìm, 75-150 ìm, 150-300 ìm and >300 ìm for solids, PAHs and HMs. The outcomes of the study indicated that PAHs and HMs in the <75 ìm size fraction are generated mainly by traffic related activities whereas the > 150 ìm size fraction is generated by both traffic and land use related sources. Atmospheric deposition is an important source for HMs build-up on roads, whereas the contribution of PAHs from atmospheric sources is limited. A comprehensive approach was developed to predict traffic and other land use related pollutants in urban stormwater based on traffic and other land use characteristics. This approach primarily included the development of a set of mathematical equations to predict traffic generated pollutants by linking traffic and land use characteristics to stormwater quality through mathematical modelling. The outcomes of this research will contribute to the design of appropriate treatment systems to safeguard urban receiving water quality for future traffic growth scenarios. The „real world. application of knowledge generated was demonstrated through mathematical modelling of solids in urban stormwater, accounting for the variability in traffic and land use characteristics.
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A number of groups around the world are working in the field of three dimensional(3D) ultrasound (US) in order to obtain higher quality diagnostic information. 3D US, in general, involves collecting a sequence of conventional 2D US images along with information on the position and orientation of each image plane. A transformation matrix is calculated relating image space to real world space. This allows image pixels and region of interest (ROI) points drawn on the image to be displayed in 3D. The 3D data can be used for the production of volume or surface rendered images, or for the direct calculation of ROI volumes.
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Virtual world platforms such as Second Life have been successfully used in educational contexts to motivate and engage learners. This article reports on an exploratory workshop involving a group of high school students using Second Life for an urban planning project. Young people are traditionally an under-represented demographic when it comes to participating in urban planning and decision making processes. The research team developed activities that combined technology with a constructivist approach to learning. Real world experiences and purposes ensured that the workshop enabled students to see the relevance of their learning. Our design also ensured that play remained an important part of the learning. By conceiving of the workshop as a ‘serious playground’ we investigated the ludic potential of learning in a virtual world.
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Premature convergence to local optimal solutions is one of the main difficulties when using evolutionary algorithms in real-world optimization problems. To prevent premature convergence and degeneration phenomenon, this paper proposes a new optimization computation approach, human-simulated immune evolutionary algorithm (HSIEA). Considering that the premature convergence problem is due to the lack of diversity in the population, the HSIEA employs the clonal selection principle of artificial immune system theory to preserve the diversity of solutions for the search process. Mathematical descriptions and procedures of the HSIEA are given, and four new evolutionary operators are formulated which are clone, variation, recombination, and selection. Two benchmark optimization functions are investigated to demonstrate the effectiveness of the proposed HSIEA.