Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Secondary structure element alignment kernel method for prediction of protein structural classes

In this paper, we aim at predicting protein structural classes for low-homology data sets based on predicted secondary structures. We propose a new and simple kernel method, named as SSEAKSVM, to predict protein structural classes. The secondary structures of all protein sequences are obtained by using the tool PSIPRED and then a linear kernel on the basis of secondary structure element alignment scores is constructed for training a support vector machine classifier without parameter adjusting. Our method SSEAKSVM was evaluated on two low-homology datasets 25PDB and 1189 with sequence homology being 25% and 40%, respectively. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies on these two data sets are 86.3% and 84.5%, respectively, which are higher than those obtained by other existing methods. Especially, our method achieves higher accuracies (88.1% and 88.5%) for differentiating the α + β class and the α/β class compared to other methods. This suggests that our method is valuable to predict protein structural classes particularly for low-homology protein sequences. The source code of the method in this paper can be downloaded at http://math.xtu.edu.cn/myphp/math/research/source/SSEAK_source_code.rar.

Role-based process view derivation and composition

The process view concept deploys a partial and temporal representation to adjust the visible view of a business process according to various perception constraints of users. Process view technology is of practical use for privacy protection and authorization control in process-oriented business management. Owing to complex organizational structure, it is challenging for large companies to accurately specify the diverse perception of different users over business processes. Aiming to tackle this issue, this article presents a role-based process view model to incorporate role dependencies into process view derivation. Compared to existing process view approaches, ours particularly supports runtime updates to the process view perceivable to a user with specific view merging operations, thereby enabling the dynamic tracing of process perception. A series of rules and theorems are established to guarantee the structural consistency and validity of process view transformation. A hypothetical case is conducted to illustrate the feasibility of our approach, and a prototype is developed for the proof-of-concept purpose.

Measurement of transit network accessibility based on access stop choice behaviour

This research improved the measurement of public transport accessibility by capturing; travellers' behaviour; diversity of public transport mode; and the subjectivity of travellers' decision in the complex transport networks. The results of this research not only highlighted the importance of considering public transport network characteristics but also, revealed the impact of public transport diversity in the modelling of public transport accessibility. The research developed a hybrid discrete choice model with a nested logit structure to treat the correlation among the public transport mode choices and, a logit correction factor to rectify the correlation among the stop choices.

Synthesis, characterization, and electronic structure studies of cubic Bi1.5ZnTa1.5O7 for photocatalytic applications

Bi1.5ZnTa1.5O7 (BZT) has been synthesized using an alkoxide based sol-gel reaction route. The evolution of the phases produced from the alkoxide precursors and their properties have been characterized as function of temperature using a combination of thermogravimetric analysis (TGA) coupled with mass spectrometry (MS), infrared emission spectrometry (IES), X-ray diffraction (XRD), ultraviolet and visible (UV-Vis) spectroscopy, Raman spectroscopy, and N2 adsorption/desorption isotherms. The lowest sintering temperature (600∘C) to obtain phase pure BZT powders with high surface area (14.5m2/g) has been determined from the thermal decomposition and phase analyses.The photocatalytic activity of the BZT powders has been tested for the decolorization of organic azo-dye and found to be photoactive under UV irradiation.The electronic band structure of the BZT has been investigated using density functional theory (DFT) calculations to determine the band gap energy (3.12 eV) and to compare it with experimental band gap (3.02 eV at 800∘C) from optical absorptionmeasurements. An excellent match is obtained for an assumption of Zn cation substitutions at specifically ordered sites in the BZT structure.

Structures of three different neutral polysaccharides of Acinetobacter baumannii, NIPH190, NIPH201, and NIPH615, assigned to K30, K45, and K48 capsule types, respectively, based on capsule biosynthesis gene clusters

Neutral capsular polysaccharides (CPSs) were isolated from Acinetobacter baumannii NIPH190, NIPH201, and NIPH615. The CPSs were found to contain common monosaccharides only and to be branched with a side-chain 1→3-linked β-d-glucopyranose residue. Structures of the oligosaccharide repeat units (K units) of the CPSs were elucidated by 1D and 2D 1H and 13C NMR spectroscopy. Novel CPS biosynthesis gene clusters, designated KL30, KL45, and KL48, were found at the K locus in the genome sequences of NIPH190, NIPH201, and NIPH615, respectively. The genetic content of each gene cluster correlated with the structure of the CPS unit established, and therefore, the capsular types of the strains studied were designated as K30, K45, and K48, respectively. The initiating sugar of each K unit was predicted, and glycosyltransferases encoded by each gene cluster were assigned to the formation of the linkages between sugars in the corresponding K unit.

Passivity-based Trajectory-tracking for Marine Craft with Disturbance Rejection

This paper presents a Hamiltonian model of marine vehicle dynamics in six degrees of freedom in both body-fixed and inertial momentum coordinates. The model in body-fixed coordinates presents a particular structure of the mass matrix that allows the adaptation and application of passivity-based control interconnection and damping assignment design methodologies developed for robust stabilisation of mechanical systems in terms of generalised coordinates. As an example of application, we follow this methodology to design a passivity-based tracking controller with integral action for fully actuated vehicles in six degrees of freedom. We also describe a momentum transformation that allows an alternative model representation that resembles general port-Hamiltonian mechanical systems with a coordinate dependent mass matrix. This can be seen as an enabling step towards the adaptation of the theory of control of port-Hamiltonian systems developed in robotic manipulators and multi-body mechanical systems to the case of marine craft dynamics.

Efficient estimation for rank-based regression with clustered data

Rank-based inference is widely used because of its robustness. This article provides optimal rank-based estimating functions in analysis of clustered data with random cluster effects. The extensive simulation studies carried out to evaluate the performance of the proposed method demonstrate that it is robust to outliers and is highly efficient given the existence of strong cluster correlations. The performance of the proposed method is satisfactory even when the correlation structure is misspecified, or when heteroscedasticity in variance is present. Finally, a real dataset is analyzed for illustration.

Wavelet-based multiresolution analysis of Wivenhoe Dam water temperatures

Water temperature measurements from Wivenhoe Dam offer a unique opportunity for studying fluctuations of temperatures in a subtropical dam as a function of time and depth. Cursory examination of the data indicate a complicated structure across both time and depth. We propose simplifying the task of describing these data by breaking the time series at each depth into physically meaningful components that individually capture daily, subannual, and annual (DSA) variations. Precise definitions for each component are formulated in terms of a wavelet-based multiresolution analysis. The DSA components are approximately pairwise uncorrelated within a given depth and between different depths. They also satisfy an additive property in that their sum is exactly equal to the original time series. Each component is based upon a set of coefficients that decomposes the sample variance of each time series exactly across time and that can be used to study both time-varying variances of water temperature at each depth and time-varying correlations between temperatures at different depths. Each DSA component is amenable for studying a certain aspect of the relationship between the series at different depths. The daily component in general is weakly correlated between depths, including those that are adjacent to one another. The subannual component quantifies seasonal effects and in particular isolates phenomena associated with the thermocline, thus simplifying its study across time. The annual component can be used for a trend analysis. The descriptive analysis provided by the DSA decomposition is a useful precursor to a more formal statistical analysis.

Modeling strategies in longitudinal data analysis: Covariate, variance function and correlation structure selection

A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

Inter-lamellar shear resistance confers compressive stiffness in the intervertebral disc: An image-based modelling study on the bovine caudal disc

The intervertebral disc withstands large compressive loads (up to nine times bodyweight in humans) while providing flexibility to the spinal column. At a microstructural level, the outer sheath of the disc (the annulus fibrosus) comprises 12–20 annular layers of alternately crisscrossed collagen fibres embedded in a soft ground matrix. The centre of the disc (the nucleus pulposus) consists of a hydrated gel rich in proteoglycans. The disc is the largest avascular structure in the body and is of much interest biomechanically due to the high societal burden of disc degeneration and back pain. Although the disc has been well characterized at the whole joint scale, it is not clear how the disc tissue microstructure confers its overall mechanical properties. In particular, there have been conflicting reports regarding the level of attachment between adjacent lamellae in the annulus, and the importance of these interfaces to the overall integrity of the disc is unknown. We used a polarized light micrograph of the bovine tail disc in transverse cross-section to develop an image-based finite element model incorporating sliding and separation between layers of the annulus, and subjected the model to axial compressive loading. Validation experiments were also performed on four bovine caudal discs. Interlamellar shear resistance had a strong effect on disc compressive stiffness, with a 40% drop in stiffness when the interface shear resistance was changed from fully bonded to freely sliding. By contrast, interlamellar cohesion had no appreciable effect on overall disc mechanics. We conclude that shear resistance between lamellae confers disc mechanical resistance to compression, and degradation of the interlamellar interface structure may be a precursor to macroscopic disc degeneration.

Nonlinear analysis for the pre- and post-yield behaviour of a composite structure with the refined plastic hinge approach

The computational technique of the full ranges of the second-order inelastic behaviour evaluation of steel-concrete composite structure is not always sought forgivingly, and therefore it hinders the development and application of the performance-based design approach for the composite structure. To this end, this paper addresses of the advanced computational technique of the higher-order element with the refined plastic hinges to capture the all-ranges behaviour of an entire steel-concrete composite structure. Moreover, this paper presents the efficient and economical cross-section analysis to evaluate the element section capacity of the non-uniform and arbitrary composite section subjected to the axial and bending interaction. Based on the same single algorithm, it can accurately and effectively evaluate nearly continuous interaction capacity curve from decompression to pure bending technically, which is the important capacity range but highly nonlinear. Hence, this cross-section analysis provides the simple but unique algorithm for the design approach. In summary, the present nonlinear computational technique can simulate both material and geometric nonlinearities of the composite structure in the accurate, efficient and reliable fashion, including partial shear connection and gradual yielding at pre-yield stage, plasticity and strain-hardening effect due to axial and bending interaction at post-yield stage, loading redistribution, second-order P-δ and P-Δ effect, and also the stiffness and strength deterioration. And because of its reliable and accurate behavioural evaluation, the present technique can be extended for the design of the high-strength composite structure and potentially for the fibre-reinforced concrete structure.

Morphology-based interslice interpolation on manual segmentations of joint bones and muscles in MRI

This paper presents a validation study on the application of a novel interslice interpolation technique for musculoskeletal structure segmentation of articulated joints and muscles on human magnetic resonance imaging data. The interpolation technique is based on morphological shape-based interpolation combined with intensity based voxel classification. Shape-based interpolation in the absence of the original intensity image has been investigated intensively. However, in some applications of medical image analysis, the intensity image of the slice to be interpolated is available. For example, when manual segmentation is conducted on selected slices, the segmentation on those unselected slices can be obtained by interpolation. We proposed a two- step interpolation method to utilize both the shape information in the manual segmentation and local intensity information in the image. The method was tested on segmentations of knee, hip and shoulder joint bones and hamstring muscles. The results were compared with two existing interpolation methods. Based on the calculated Dice similarity coefficient and normalized error rate, the proposed method outperformed the other two methods.

Analysis of an inter-centre, web-based radiation oncology peer-review case conference

Purpose Peer-review programmes in radiation oncology are used to facilitate the process and evaluation of clinical decision-making. However, web-based peer-review methods are still uncommon. This study analysed an inter-centre, web-based peer-review case conference as a method of facilitating the decision-making process in radiation oncology. Methodology A benchmark form was designed based on the American Society for Radiation Oncology targets for radiation oncology peer review. This was used for evaluating the contents of the peer-review case presentations on 40 cases, selected from three participating radiation oncology centres. A scoring system was used for comparison of data, and a survey was conducted to analyse the experiences of radiation oncology professionals who attended the web-based peer-review meetings in order to identify priorities for improvement. Results The mean scores for the evaluations were 82·7, 84·5, 86·3 and 87·3% for cervical, prostate, breast and head and neck presentations, respectively. The survey showed that radiation oncology professionals were confident about the role of web-based peer-reviews in facilitating sharing of good practice, stimulating professionalism and promoting professional growth. The participants were satisfied with the quality of the audio and visual aspects of the web-based meeting. Conclusion The results of this study suggest that simple inter-centre web-based peer-review case conferences are a feasible technique for peer review in radiation oncology. Limitations such as data security and confidentiality can be overcome by the use of appropriate structure and technology. To drive the issues of quality and safety a step further, small radiotherapy departments may need to consider web-based peer-review case conference as part of their routine quality assurance practices.

Steel–concrete–steel sandwich system in Arctic offshore structure: Materials, experiments, and design

The gravity based structure (GBS) with external Steel–Concrete–Steel (SCS) sandwich ice-resistant wall has been developed for the Arctic oil and gas drilling. This paper firstly reported the experimental studies on the mechanical properties of steel and concretes under Arctic low temperature. With the test data, design equations were developed to incorporate the influences of the low temperature on these mechanical properties. Two types of Arctic GBS structure with flower-conical SCS sandwich shell type and plate type of ice-resistant wall have been developed for the Arctic offshore structure. Besides the studies on the materials, two SCS sandwich prototype shells and plates were, respectively, prepared and tested under patch loading that simulated the localized ice-contact pressure. The structural behaviors of the SCS sandwich structure under patch loading were reported and discussions were made on the influences of different parameters on the structural behavior of the structure. Analytical models were developed to predict the punching shear resistances of the SCS sandwich structure through modifying the code provisions. The accuracies of the developed analytical models were checked through validations against 27 tests in the literature. Corresponding design procedures on resistances of SCS sandwich structure were recommended based on these discussions and validations.