Fully complex-valued ELM classifiers for human action recognition

In this paper, we present a fast learning neural network classifier for human action recognition. The proposed classifier is a fully complex-valued neural network with a single hidden layer. The neurons in the hidden layer employ the fully complex-valued hyperbolic secant as an activation function. The parameters of the hidden layer are chosen randomly and the output weights are estimated analytically as a minimum norm least square solution to a set of linear equations. The fast leaning fully complex-valued neural classifier is used for recognizing human actions accurately. Optical flow-based features extracted from the video sequences are utilized to recognize 10 different human actions. The feature vectors are computationally simple first order statistics of the optical flow vectors, obtained from coarse to fine rectangular patches centered around the object. The results indicate the superior performance of the complex-valued neural classifier for action recognition. The superior performance of the complex neural network for action recognition stems from the fact that motion, by nature, consists of two components, one along each of the axes.

Multiobjective discrete particle swarm optimization for multisensor image alignment

A new technique is proposed for multisensor image registration by matching the features using discrete particle swarm optimization (DPSO). The feature points are first extracted from the reference and sensed image using improved Harris corner detector available in the literature. From the extracted corner points, DPSO finds the three corresponding points in the sensed and reference images using multiobjective optimization of distance and angle conditions through objective switching technique. By this, the global best matched points are obtained which are used to evaluate the affine transformation for the sensed image. The performance of the image registration is evaluated and concluded that the proposed approach is efficient.

Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems

An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.

Voice source characterization using pitch synchronous discrete cosine transform for speaker identification

A characterization of the voice source (VS) signal by the pitch synchronous (PS) discrete cosine transform (DCT) is proposed. With the integrated linear prediction residual (ILPR) as the VS estimate, the PS DCT of the ILPR is evaluated as a feature vector for speaker identification (SID). On TIMIT and YOHO databases, using a Gaussian mixture model (GMM)-based classifier, it performs on par with existing VS-based features. On the NIST 2003 database, fusion with a GMM-based classifier using MFCC features improves the identification accuracy by 12% in absolute terms, proving that the proposed characterization has good promise as a feature for SID studies. (C) 2015 Acoustical Society of America

Characterization of a Laser-Discrete Quenched Steel Substrate/Chromium System by Dissolving Coatings

A laser-discrete quenched steel (LDQS) substrate/as-deposited chromium (top high-contraction (HC) and underlying low-contraction (LC) chromium) system was investigated by dissolving coatings in order to reveal the mechanism that the service life of the coated parts is largely improved using the hybrid technique of laser pre-quenching plus chromium post-depositing. It was found that the surface characteristics of the substrate, LC and HC chromium layer can be simultaneously revealed owing to the dissolution edge effect of chromium coatings. Moreover, the periodical gradient morphologies of the LDQS substrate are clearly shown: the surfaces of laser transformation-hardened regions are rather smooth; a lot of fine micro-holes exist in the transition zones; there are many micro-dimples in the original substrate. Furthermore, the novel method of dissolving coatings with sharp interfaces may be used to reveal the structural features of a substrate/coating system, explore the effect of the substrate on the initial microstructure and morphologies of coatings, and check the quality of the coated-parts.

Stochastic Structural Model of Rock and Soil Aggregates by Continuum-Based Discrete Element Method

This paper first presents a stochastic structural model to describe the random geometrical features of rock and soil aggregates. The stochastic structural model uses mixture ratio, rock size and rock shape to construct the microstructures of aggregates,and introduces two types of structural elements (block element and jointed element) and three types of material elements (rock element, soil element, and weaker jointed element)for this microstructure. Then, continuum-based discrete element method is used to study the deformation and failure mechanism of rock and soil aggregate through a series of loading tests. It is found that the stress-strain curve of rock and soil aggregates is nonlinear, and the failure is usually initialized from weaker jointed elements. Finally, some factors such as mixture ratio, rock size and rock shape are studied in detail. The numerical results are in good agreement with in situ test. Therefore, current model is effective for simulating the mechanical behaviors of rock and soil aggregates.

Using Discrete Event Simulation (DES) to manage theatre operations in healthcare: An audit-based case study

This paper discusses the application of Discrete Event Simulation (DES) in modelling the complex relationship between patient types, case-mix and operating theatre allocation in a large National Health Service (NHS) Trust in London. The simulation model that was constructed described the main features of nine theatres, focusing on operational processes and patient throughput times. The model was used to test three scenarios of case-mix and to demonstrate the potential of using simulation modelling as a cost effective method for understanding the issues of healthcare operations management and the role of simulation techniques in problem solving. The results indicated that removing all day cases will reduce patient throughput by 23.3% and the utilization of the orthopaedic theatre in particular by 6.5%. This represents a case example of how DES can be used by healthcare managers to inform decision making. © 2008 IEEE.

Natural versus artificial scene classification by ordering discrete fourier power spectra

Holistic representations of natural scenes is an effective and powerful source of information for semantic classification and analysis of arbitrary images. Recently, the frequency domain has been successfully exploited to holistically encode the content of natural scenes in order to obtain a robust representation for scene classification. In this paper, we present a new approach to naturalness classification of scenes using frequency domain. The proposed method is based on the ordering of the Discrete Fourier Power Spectra. Features extracted from this ordering are shown sufficient to build a robust holistic representation for Natural vs. Artificial scene classification. Experiments show that the proposed frequency domain method matches the accuracy of other state-of-the-art solutions. © 2008 Springer Berlin Heidelberg.

Multiscale object features from clustered complex wavelet coefficients

This paper introduces a method by which intuitive feature entities can be created from ILP (InterLevel Product) coefficients. The ILP transform is a pyramid of decimated complex-valued coefficients at multiple scales, derived from dual-tree complex wavelets, whose phases indicate the presence of different feature types (edges and ridges). We use an Expectation-Maximization algorithm to cluster large ILP coefficients that are spatially adjacent and similar in phase. We then demonstrate the relationship that these clusters possess with respect to observable image content, and conclude with a look at potential applications of these clusters, such as rotation- and scale-invariant object recognition. © 2005 IEEE.

Discrete dislocation plasticity analysis of size effects in single crystals

The effect of size and slip system configuration on the tensile stress-strain response of micron-sized planar crystals as obtained from discrete dislocation plasticity simulations is presented. The crystals are oriented for either single or symmetric double slip. With the rotation of the tensile axis unconstrained, there is a strong size dependence, with the flow strength increasing with decreasing specimen size. Below a certain specimen size, the flow strength of the crystals is set by the nucleation strength of the initially present Frank-Read sources. The main features of the size dependence are the same for both the single and symmetric double slip configurations.

Centrifuge and discrete element modelling of tunnelling effects on pipelines

The paper presents centrifuge test data of the problem of tunnelling effects on buried pipelines and compares them to predictions made using DEM simulations. The paper focuses on the examination of pipeline bending moments, their distribution along the pipe, and their development with tunnel volume loss. Centrifuge results are obtained by PIV analysis and compared to results obtained using the DEM model. The DEM model was built to replicate the centrifuge model as closely as possible and included numerical features formulated specially for this task, such as structural elements to replicate the tunnel and pipeline. Results are extremely encouraging, with deviations between DEM and centrifuge test bending moment results being very small. © 2010 Taylor & Francis Group, London.

Parallels plane projection and its geometric features

A new equivalent map projection called the parallels plane projection is proposed in this paper. The transverse axis of the parallels plane projection is the expansion of the equator and its vertical axis equals half the length of the central meridian. On the parallels plane projection, meridians are projected as sine curves and parallels are a series of straight, parallel lines. No distortion of length occurs along the central meridian or on any parallels of this projection. Angular distortion and the proportion of length along meridians (except the central meridian) introduced by the projection transformation increase with increasing longitude and latitude. A potential application of the parallels plane projection is that it can provide an efficient projection transformation for global discrete grid systems.

Vertical distribution of bacterial and archaeal communities along discrete layers of a deep-sea cold sediment sample at the East Pacific Rise (similar to 13 degrees N)

The community structure and vertical distribution of prokaryotes in a deep-sea (ca. 3,191 m) cold sediment sample (ca. 43 cm long) collected at the East Pacific Rise (EPR) similar to 13 degrees N were studied with 16SrDNA-based molecular analyses. Total community DNA was extracted from each of four discrete layers EPRDS-1, -2, -3 and -4 (from top to bottom) and 16S rDNA were amplified by PCR. Cluster analysis of DGGE profiles revealed that the bacterial communities shifted sharply between EPRDS-1 and EPRDS-2 in similarity coefficient at merely 49%. Twenty-three sequences retrieved from DGGE bands fell into 11 groups based on BLAST and bootstrap analysis. The dominant groups in the bacterial communities were Chloroflexi, Gamma proteobacteria, Actinobacterium and unidentified bacteria, with their corresponding percentages varying along discrete layers. Pairwise Fst (F-statistics) values between the archaeal clone libraries indicated that the archaeal communities changed distinctly between EPRDS-2 and EPRDS-3. Sequences from the archaeal libraries were divided to eight groups. Crenarchaea Marine Group I (MGI) was prevalent in EPRDS-1 at 83%, while Uncultured Crenarchaea group II B (UCII B) abounded in EPRDS-4 at 61%. Our results revealed that the vertically stratified distribution of prokaryotic communities might be in response to the geochemical settings and suggested that the sampling area was influenced by hydrothermalism. The copresence of members related to hydrothermalism and cold deep-sea environments in the microbial community indicated that the area might be a transitional region from hydrothermal vents to cold deep-sea sediments.

Fuzzy-Rough Sets Assisted Attribute Selection

R. Jensen and Q. Shen. Fuzzy-Rough Sets Assisted Attribute Selection. IEEE Transactions on Fuzzy Systems, vol. 15, no. 1, pp. 73-89, 2007.

Valuing maternity care: a comparison of stated preference methods with an application to cost-benefit analysis

This research investigates whether a reconfiguration of maternity services, which collocates consultant- and midwifery-led care, reflects demand and value for money in Ireland. Qualitative and quantitative research is undertaken to investigate demand and an economic evaluation is performed to evaluate the costs and benefits of the different models of care. Qualitative research is undertaken to identify women’s motivations when choosing place of delivery. These data are further used to inform two stated preference techniques: a discrete choice experiment (DCE) and contingent valuation method (CVM). These are employed to identify women’s strengths of preferences for different features of care (DCE) and estimate women’s willingness to pay for maternity care (CVM), which is used to inform a cost-benefit analysis (CBA) on consultant- and midwifery-led care. The qualitative research suggests women do not have a clear preference for consultant or midwifery-led care, but rather a hybrid model of care which closely resembles the Domiciliary Care In and Out of Hospital (DOMINO) scheme. Women’s primary concern during care is safety, meaning women would only utilise midwifery-led care when co-located with consultant-led care. The DCE also finds women’s preferred package of care closely mirrors the DOMINO scheme with 39% of women expected to utilise this service. Consultant- and midwifery-led care would then be utilised by 34% and 27% of women, respectively. The CVM supports this hierarchy of preferences where consultant-led care is consistently valued more than midwifery-led care – women are willing to pay €956.03 for consultant-led care and €808.33 for midwifery-led care. A package of care for a woman availing of consultant- and midwifery-led care is estimated to cost €1,102.72 and €682.49, respectively. The CBA suggests both models of care are cost-beneficial and should be pursued in Ireland. This reconfiguration of maternity services would maximise women’s utility, while fulfilling important objectives of key government policy.