FAB-MAP + RatSLAM : appearance-based SLAM for multiple times of day

Appearance-based mapping and localisation is especially challenging when separate processes of mapping and localisation occur at different times of day. The problem is exacerbated in the outdoors where continuous change in sun angle can drastically affect the appearance of a scene. We confront this challenge by fusing the probabilistic local feature based data association method of FAB-MAP with the pose cell filtering and experience mapping of RatSLAM. We evaluate the effectiveness of our amalgamation of methods using five datasets captured throughout the day from a single camera driven through a network of suburban streets. We show further results when the streets are re-visited three weeks later, and draw conclusions on the value of the system for lifelong mapping.

Characterisation of Ni carbonate-bearing minerals by UV-Vis-NIR spectroscopy

Four nickel carbonate-bearing minerals from Australia have been investigated to study the effect of Ni for Mg substitution. The spectra of nullaginite, zaratite, widgiemoolthalite and takovite show three main features in the range of 26,720–25,855 cm−1 (ν1-band), 15,230–14,740 cm−1 (ν2-band) and 9,200–9,145 cm−1 (ν3-band) which are characteristic of divalent nickel in six-fold coordination. The Crystal Field Stabilization Energy (CFSE) of Ni2+ in the four carbonates is calculated from the observed 3A2g(3F) → 3T2g(3F) transition. CFSE is dependent on mineralogy, crystallinity and chemical composition (Al/Mg-content). The splitting of the ν1- and ν3-bands and non-Gaussian shape of ν3-band in the minerals are the effects of Ni-site distortion from regular octahedral. The effect of structural cation substitutions (Mg2+, Ni2+, Fe2+ and trivalent cations, Al3+, Fe3+) in the carbonate minerals is noticed on band shifts. Thus, electronic bands in the UV–Vis–NIR spectra and the overtones and combination bands of OH and carbonate ion in NIR show shifts to higher wavenumbers, particularly for widgiemoolthalite and takovite.

Crystallographic characterization of the first reported crystalline form of the potent hallucinogen (R)-2-amino-1-(8-bromobenzo[1,2-b;5,4-b']difuran-4-yl)propane or `bromodragonfly': the 1:1 anhydrous proton-transfer compound with 3,5-dinitrosalicylic acid

The 1:1 proton-transfer compound of the potent substituted amphetamine hallucinogen (R)-1-(8-bromobenzo[1,2-b; 4,5-b']difuran-4-yl)-2-aminopropane (common trivial name 'bromodragonfly') with 3,5-dinitrosalicylic acid, 1-(8-bromobenzo[1,2-b;4,5-b']difuran-4-yl)-2-mmoniopropane 2-carboxy-4,6-dinitrophenolate, C13H13BrNO2+ C7H3N2O7- forms hydrogen-bonded cation-anion chain substructures comprising undulating head-to-tail anion chains formed through C(8) carboxyl O-H...O(nitro) associations and incorporating the aminium groups of the cations. The intra-chain cation-anion hydrogen-bonding associations feature proximal cyclic R33(8) interactions involving both a N+-H...O(phenolate) and the carboxyl O--H...O(nitro)associations. Also present are aromatic pi-pi ring interactions [minimum ring centroid separation, 3.566(2)A; inter-plane dihedral angle, 5.13(1)deg]. A lateral hydrogen-bonding interaction between the third aminium proton and a carboxyl O acceptor link the chain substructures giving a two-dimensional sheet structure. This determination represents the first of any form of this compound and confirms that it has the (R) absolute configuration. The atypical crystal stability is attributed both to the hydrogen-bonded chain substructures provided by the anions, which accommodate the aminium proton-donor groups of the cations and give cross-linking, and to the presence of cation--anion aromatic ring pi-pi interactions.

Exploiting multiple feature sets in data-driven impostor dataset selection for speaker verification

This study assesses the recently proposed data-driven background dataset refinement technique for speaker verification using alternate SVM feature sets to the GMM supervector features for which it was originally designed. The performance improvements brought about in each trialled SVM configuration demonstrate the versatility of background dataset refinement. This work also extends on the originally proposed technique to exploit support vector coefficients as an impostor suitability metric in the data-driven selection process. Using support vector coefficients improved the performance of the refined datasets in the evaluation of unseen data. Further, attempts are made to exploit the differences in impostor example suitability measures from varying features spaces to provide added robustness.

Darjeeling, a feature-rich VM for the resource poor

The programming and retasking of sensor nodes could benefit greatly from the use of a virtual machine (VM) since byte code is compact, can be loaded on demand, and interpreted on a heterogeneous set of devices. The challenge is to ensure good programming tools and a small footprint for the virtual machine to meet the memory constraints of typical WSN platforms. To this end we propose Darjeeling, a virtual machine modelled after the Java VM and capable of executing a substantial subset of the Java language, but designed specifically to run on 8- and 16-bit microcontrollers with 2 - 10 KB of RAM. The Darjeeling VM uses a 16- rather than a 32-bit architecture, which is more efficient on the targeted platforms. Darjeeling features a novel memory organisation with strict separation of reference from non-reference types which eliminates the need for run-time type inspection in the underlying compacting garbage collector. Darjeeling uses a linked stack model that provides light-weight threads, and supports synchronisation. The VM has been implemented on three different platforms and was evaluated with micro benchmarks and a real-world application. The latter includes a pure Java implementation of the collection tree routing protocol conveniently programmed as a set of cooperating threads, and a reimplementation of an existing environmental monitoring application. The results show that Darjeeling is a viable solution for deploying large-scale heterogeneous sensor networks. Copyright 2009 ACM.

The researcher’s perspective on procuring public works projects

Purpose: As part of a comprehensive research study looking at implementing PPPs, interviews with experienced researchers were conducted to realize their views on private sector involvement in public works projects. Design / methodology / approach: Amongst these interviews, five were launched with academics from Hong Kong and Australia, and two were conducted with Legislative Councillors of the Hong Kong Special Administration Region (HKSAR) government. Findings: The interview findings show that both Hong Kong and Australian interviewees had previously conducted some kind of research in the field of PPP. The interviewees highlighted that “Different risk profiles” and “Private sector more innovative / efficient” were the main differences between projects that were procured by PPP and traditionally. Other differences include risk transfer. In a PPP arrangement the public sector passes on a substantial amount of the project risks to the private sector, whereas in a traditional case the public sector would take the largest responsibility in bearing these risks. Another common feature of the private sector is that they tend to be more efficient and innovative when compared to the public sector hence their expertise is often reflected in PPP projects. The interviewees agreed that the key performance indicators for PPP projects were unique depending on the individual project. The critical success factors mentioned by both groups of interviewees included “Transparent process”, “Project dependent” and “Market need”. Due to the fact that PPP projects tend to be large scaled costly projects, adequate transparency in the process is necessary in order to demonstrate that a fair selection and tendering process is conducted. A market need for the project is also important to ensure that the project will be financially secure and that the private sector can make a reasonable profit to cover their project expenditure. Originality / value: The findings from this study have enabled a comparative analysis between the views of researchers in two completely different jurisdictions. With the growing popularity to implement PPP projects, it is believed that the results presented in this paper would be of interest to the industry at large.

Thermogravimetric analysis of selected coal-bearing strata kaolinite

Two kinds of coal-bearing kaolinite from China were analysed by X-ray diffraction (XRD), Thermogravimetric analysis-mass spectrometry (TG-MS), infrared emission spectroscopy. Thermal decomposition occurs in a series of steps attributed to (a) desorption of water at 68 °C for Datong coal bearing strata kaolinite and 56 °C for Xiaoxian with mass losses of 0.36 % and 0.51 % (b) decarbonization at 456 °C for Datong coal bearing strata kaolinite and 431 °C for Xiaoxian kaolinite, (c) dehydroxylation takes place in two steps at 589 and 633 °C for Datong coal bearing strata kaolinite and at 507 °C and 579 °C for Xiaoxian kaolinite. This mineral were further characterised by infrared emission spectroscopy (IES). Well defined hydroxyl stretching bands at around 3695, 3679, 3652 and 3625 cm-1 are observed. At 650 °C all intensity in these bands is lost in harmony with the thermal analysis results. Characteristic functional groups from coal are observed at 1918, 1724 and 1459 cm-1. The intensity of these bands decrease by thermal treatment and is lost by 700 °C.

A vibration based method to update axial shortening of load bearing elements

Axial shortening in vertical load bearing elements of reinforced concrete high-rise buildings is caused by the time dependent effects of shrinkage, creep and elastic shortening of concrete under loads. Such phenomenon has to be predicted at design stage and then updated during and after construction of the buildings in order to provide mitigation against the adverse effects of differential axial shortening among the elements. Existing measuring methods for updating previous predictions of axial shortening pose problems. With this in mind, a innovative procedure with a vibration based parameter called axial shortening index is proposed to update axial shortening of vertical elements based on variations in vibration characteristics of the buildings. This paper presents the development of the procedure and illustrates it through a numerical example of an unsymmetrical high-rise building with two outrigger and belt systems. Results indicate that the method has the capability to capture influence of different tributary areas, shear walls of outrigger and belt systems as well as the geometric complexity of the building.

Polydipsia : a feature of peritoneal dialysis

Background Some dialysis patients fail to comply with their fluid restriction causing problems due to volume overload. These patients sometimes blame excessive thirst. There has been little work in this area and no work documenting polydipsia among peritoneal dialysis (PD) patients. Methods We measured motivation to drink and fluid consumption in 46 haemodialysis patients (HD), 39 PD patients and 42 healthy controls (HC) using a modified palmtop computer to collect visual analogue scores at hourly intervals. Results Mean thirst scores were markedly depressed on the dialysis day (day 1) for HD (P<0.0001). The profile for day 2 was similar to that of HC. PD generated consistently higher scores than HD day 1 and HC (P = 0.01 vs. HC and P<0.0001 vs HD day 1). Reported mean daily water consumption was similar for HD and PD with both significantly less than HC (P<0.001 for both). However, measured fluid losses were similar for PD and HC whilst HD were lower (P<0.001 for both) suggesting that the PD group may have underestimated their fluid intake. Conclusion Our results indicate that HD causes a protracted period of reduced thirst but that the population's thirst perception is similar to HC on the interdialytic day despite a reduced fluid intake. In contrast, the PD group recorded high thirst scores throughout the day and were apparently less compliant with their fluid restriction. This is potentially important because the volume status of PD patients influences their survival.

Fingerprint analysis using wavelet transform with application to compression and feature extraction

The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.