253 resultados para feature bearing angle


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Fast calculation of quantities such as in-cylinder volume and indicated power is important in internal combustion engine research. Multiple channels of data including crank angle and pressure were collected for this purpose using a fully instrumented diesel engine research facility. Currently, existing methods use software to post-process the data, first calculating volume from crank angle, then calculating the indicated work and indicated power from the area enclosed by the pressure-volume indicator diagram. Instead, this work investigates the feasibility of achieving real-time calculation of volume and power via hardware implementation on Field Programmable Gate Arrays (FPGAs). Alternative hardware implementations were investigated using lookup tables, Taylor series methods or the CORDIC (CoOrdinate Rotation DIgital Computer) algorithm to compute the trigonometric operations in the crank angle to volume calculation, and the CORDIC algorithm was found to use the least amount of resources. Simulation of the hardware based implementation showed that the error in the volume and indicated power is less than 0.1%.

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This paper presents an analytical model to study the effect of stiffening ribs on vibration transmission between two rectangular plates coupled at right angle. Interesting wave attenuation patterns were observed by placing the stiffening rib either on the source or on the receiving plate. The result can be used to improve the understanding of vibration and for vibration control of more complex structures such as transformer tanks and machine covers.

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In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

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Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

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Orebodies at Ok Tedi contain a number of different fluorine bearing minerals. Some of these minerals report to concentrate and are responsible for the presence of the penalty element, fluorine, within the concentrate. Previous analytical work has tended to examine geological samples for content, rather than determine the metallurgical behaviour of the different mineralogical species. This investigation utilised X-Ray Diffraction combined with Scanning Electron Microscope/Electron Microprobe to identify the fluorine bearing minerals in flotation test products. Seven fluorine bearing minerals were identified, viz., talc, phlogopite, amphibole (tremolite and actinolite), sphene, apatite, biotite and clay. Talc was found exclusively in the skarn ore type. Phlogopite and amphiboles (tremolite and actinolite) were found to occur in both skarn and porphyry ores, while sphene, apatite, biotite and clay were found only in the porphyry ores. Of the fluorine bearing minerals observed, only talc exhibited natural hydrophobicity to any significant degree. Phlogopite and the amphibole minerals were found to be hydrophillic, whilst the remaining minerals occurred in insufficient quantities to determine the flotation behaviour. Ok Tedi copper concentrate fluorine content prior to skarn ore treatment in the mill (typically 350ppm) was previously identified as deriving from phlogopite, while talc was believed to be the source of intermittent high concentrate fluorine contents when skarn ores were treated. This paper provides supporting evidence for this belief, and reports the nature of fluorine bearing mineral flotation behaviour.

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Fire safety has become an important part in structural design due to the ever increasing loss of properties and lives during fires. Fire rating of load bearing wall systems made of Light gauge Steel Frames (LSF) is determined using fire tests based on the standard time-temperature curve given in ISO 834. However, modern residential buildings make use of thermoplastic materials, which mean considerably high fuel loads. Hence a detailed fire research study into the performance of load bearing LSF walls was undertaken using a series of realistic design fire curves developed based on Eurocode parametric curves and Barnett’s BFD curves. It included both full scale fire tests and numerical studies of LSF walls without any insulation, and the recently developed externally insulated composite panels. This paper presents the details of fire tests first, and then the numerical models of tested LSF wall studs. It shows that suitable finite element models can be developed to predict the fire rating of load bearing walls under real fire conditions. The paper also describes the structural and fire performances of externally insulated LSF walls in comparison to the non-insulated walls under real fires, and highlights the effects of standard and real fire curves on fire performance of LSF walls.

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The future emergence of many types of airborne vehicles and unpiloted aircraft in the national airspace means collision avoidance is of primary concern in an uncooperative airspace environment. The ability to replicate a pilot’s see and avoid capability using cameras coupled with vision based avoidance control is an important part of an overall collision avoidance strategy. But unfortunately without range collision avoidance has no direct way to guarantee a level of safety. Collision scenario flight tests with two aircraft and a monocular camera threat detection and tracking system were used to study the accuracy of image-derived angle measurements. The effect of image-derived angle errors on reactive vision-based avoidance performance was then studied by simulation. The results show that whilst large angle measurement errors can significantly affect minimum ranging characteristics across a variety of initial conditions and closing speeds, the minimum range is always bounded and a collision never occurs.

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The thermal decomposition and dehydroxylation process of coal-bearing strata kaolinite–potassium acetate intercalation complex (CSKK) has been studied using X-ray diffraction (XRD), infrared spectroscopy (IR), thermal analysis, mass spectrometric analysis and infrared emission spectroscopy. The XRD results showed that the potassium acetate (KAc) have been successfully intercalated into coal-bearing strata kaolinite with an obvious basal distance increase of the first basal peak, and the positive correlation was found between the concentration of intercalation regent KAc and the degree of intercalation. As the temperature of the system is raised, the formation of KHCO3, KCO3 and KAlSiO4, which is derived from the thermal decomposition or phase transition of CSKK, is observed in sequence. The IR results showed that new bands appeared, the position and intensities shift can also be found when the concentration of intercalation agent is raised. The thermal analysis and mass spectrometric analysis results revealed that CSKK is stable below 300 °C, and the thermal decomposition products (H2O and CO2) were further proved by the mass spectrometric analysis. A comparison of thermal analysis results of original coal-bearing strata kaolinite and its intercalation complex gives new discovery that not only a new mass loss peak is observed at 285 °C, but also the temperature of dehydroxylation and dehydration of coal bearing strata kaolinite is decreased about 100 °C. This is explained on the basis of the interlayer space of the kaolinite increased obviously after being intercalated by KAc, which led to the interlayer hydrogen bonds weakened, enables the dehydroxylation from kaolinite surface more easily. Furthermore, the possible structural model for CSKK has been proposed, with further analysis required in order to prove the most possible structures.

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Detailed investigation of an intermediate member of the reddingite–phosphoferrite series, using infrared and Raman spectroscopy, scanning electron microcopy and electron microprobe analysis, has been carried out on a homogeneous sample from a lithium-bearing pegmatite named Cigana mine, near Conselheiro Pena, Minas Gerais, Brazil. The determined formula is (Mn1.60Fe1.21Ca0.01Mg0.01)∑2.83(PO4)2.12⋅(H2O2.85F0.01)∑2.86 indicating predominance in the reddingite member. Raman spectroscopy coupled with infrared spectroscopy supports the concept of phosphate, hydrogen phosphate and dihydrogen phosphate units in the structure of reddingite-phosphoferrite. Infrared and Raman bands attributed to water and hydroxyl stretching modes are identified. Vibrational spectroscopy adds useful information to the molecular structure of reddingite–phosphoferrite.

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Relevance feature and ontology are two core components to learn personalized ontologies for concept-based retrievals. However, how to associate user native information with common knowledge is an urgent issue. This paper proposes a sound solution by matching relevance feature mined from local instances with concepts existing in a global knowledge base. The matched concepts and their relations are used to learn personalized ontologies. The proposed method is evaluated elaborately by comparing it against three benchmark models. The evaluation demonstrates the matching is successful by achieving remarkable improvements in information filtering measurements.

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A building information model (BIM) provides a rich representation of a building's design. However, there are many challenges in getting construction-specific information from a BIM, limiting the usability of BIM for construction and other downstream processes. This paper describes a novel approach that utilizes ontology-based feature modeling, automatic feature extraction based on ifcXML, and query processing to extract information relevant to construction practitioners from a given BIM. The feature ontology generically represents construction-specific information that is useful for a broad range of construction management functions. The software prototype uses the ontology to transform the designer-focused BIM into a construction-specific feature-based model (FBM). The formal query methods operate on the FBM to further help construction users to quickly extract the necessary information from a BIM. Our tests demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

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Finding and labelling semantic features patterns of documents in a large, spatial corpus is a challenging problem. Text documents have characteristics that make semantic labelling difficult; the rapidly increasing volume of online documents makes a bottleneck in finding meaningful textual patterns. Aiming to deal with these issues, we propose an unsupervised documnent labelling approach based on semantic content and feature patterns. A world ontology with extensive topic coverage is exploited to supply controlled, structured subjects for labelling. An algorithm is also introduced to reduce dimensionality based on the study of ontological structure. The proposed approach was promisingly evaluated by compared with typical machine learning methods including SVMs, Rocchio, and kNN.

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The objective of this work is to analyze ludlamite (Fe,Mn,Mg)3(PO4)2⋅4H2O from Boa Vista mine, Galiléia, Brazil and to assess the molecular structure of the mineral. The phosphate mineral ludlamite has been characterized by EMP-WDS, Raman and infrared spectroscopic measurements. The mineral is shown to be a ferrous phosphate with some minor substitution of Mg and Mn. Raman bands at 917 and 950 cm−1 are assigned to the symmetric stretching mode of and units. Raman bands at 548, 564, 599 and 634 cm−1 are assigned to the ν4 bending modes. Raman bands at 2605, 2730, 2896 and 3190 cm−1 and infrared bands at 2623, 2838, 3136 and 3185 cm−1 are attributed to water stretching vibrations. By using a Libowitzky empirical function, hydrogen bond distances are calculated from the OH stretching wavenumbers. Strong hydrogen bonds in the structure of ludlamite are observed as determined by their hydrogen bond distances. The application of infrared and Raman spectroscopy to the study of ludlamite enables the molecular structure of the pegmatite mineral ludlamite to be assessed.

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Fire safety of light gauge steel frame (LSF) stud walls is important in the design of buildings. Currently LSF walls are increasingly used in the building industry, and are usually made of cold-formed and thin-walled steel studs that are fire-protected by two layers of plasterboard on both sides. Many experimental and numerical studies have been undertaken to investigate the fire performance of load bearing LSF walls under standard fire conditions. However, the standard time-temperature curve does not represent the fire load present in typical residential and commercial buildings that include considerable amount of thermoplastic materials. Real building fires are unlikely to follow a standard time-temperature curve. However, only limited research has been undertaken to investigate the fire performance of load bearing LSF walls under realistic design fire conditions. Therefore in this research, finite element thermal models of the traditional LSF wall panels without cavity insulation and the new LSF composite wall panels were developed to simulate their fire performance under recently developed realistic design fire curves. Suitable thermal properties were proposed for plasterboards and insulations based on laboratory tests and literature review. The developed models were then validated by comparing their thermal performance results with available results from realistic design fire tests, and were later used in parametric studies. This paper presents the details of the developed finite element thermal models of load bearing LSF wall panels under realistic design fire time-temperature curves and the re-sults. It shows that finite element thermal models can be used to predict the fire performance of load bearing LSF walls with varying configurations of insulations and plasterboards under realistic design fires. Failure times of load bearing LSF walls were also predicted based on the results from finite element thermal analyses.

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Objective: To determine solar load-bearing structures in the feet of feral horses and investigate morphological characteristics of the sole in feral horses and domestic Thoroughbreds. Sample: Forelimbs from cadavers of 70 feral horses and 20 domestic Thoroughbreds in Australia. Procedures: Left forefeet were obtained from 3 feral horse populations from habitats of soft substrate (SS [n = 10 horses]), hard substrate (HS [10]), and a combination of SS and HS (10) and loaded in vitro. Pressure distribution was measured with a pressure plate. Sole depth was measured at 12 points across the solar plane in feet obtained from feral horses from SS (n = 20 horses) and HS (20) habitats and domestic Thoroughbreds (20). Results: Feet of feral horses from HS habitats loaded the periphery of the sole and hoof wall on a flat surface. Feral horses from HS or SS habitats had greater mean sole depth than did domestic Thoroughbreds. Sole depth was greatest peripherally and was correlated with the loading pattern. Conclusions and Clinical Relevance: The peripheral aspect of the sole in the feet of feral horses had a load-bearing function. Because of the robust nature of the tissue architecture, the hoof capsule of feral horses may be less flexible than that of typical domestic horses. The application of narrow-web horseshoes may not take full advantage of the load-bearing and force-dissipating properties of the peripheral aspect of the sole. Further studies are required to understand the effects of biomechanical stimulation on the adaptive responses of equine feet.