Modelling the mechanical response of the reed-mouthpiece-lip system of a clarinet. Part II: A lumped model approximation

A non-linear lumped model of the reed-mouthpiece-lip system of a clarinet is formulated, in which the lumped parameters are derived from numerical experiments with a finite-difference simulation based on a distributed reed model. The effective stiffness per unit area is formulated as a function of the pressure signal driving the reed, in order to simulate the effects of the reed bending against the lay, and mass and damping terms are added as a first approximation to the dynamic behaviour of the reed. A discrete-time formulation is presented, and its response is compared to that of the distributed model. In addition, the lumped model is applied in the simulation of clarinet tones, enabling the analysis of the effects of using a pressure-dependent stiffness per unit area on sustained oscillations. The analysed effects and features are in qualitative agreement with players' experiences and experimental results obtained in prior studies.

Automated mixed dimensional modelling from 2D and 3D CAD models

The motivation for this paper is to present procedures for automatically creating idealised finite element models from the 3D CAD solid geometry of a component. The procedures produce an accurate and efficient analysis model with little effort on the part of the user. The technique is applicable to thin walled components with local complex features and automatically creates analysis models where 3D elements representing the complex regions in the component are embedded in an efficient shell mesh representing the mid-faces of the thin sheet regions. As the resulting models contain elements of more than one dimension, they are referred to as mixed dimensional models. Although these models are computationally more expensive than some of the idealisation techniques currently employed in industry, they do allow the structural behaviour of the model to be analysed more accurately, which is essential if appropriate design decisions are to be made. Also, using these procedures, analysis models can be created automatically whereas the current idealisation techniques are mostly manual, have long preparation times, and are based on engineering judgement. In the paper the idealisation approach is first applied to 2D models that are used to approximate axisymmetric components for analysis. For these models 2D elements representing the complex regions are embedded in a 1D mesh representing the midline of the cross section of the thin sheet regions. Also discussed is the coupling, which is necessary to link the elements of different dimensionality together. Analysis results from a 3D mixed dimensional model created using the techniques in this paper are compared to those from a stiffened shell model and a 3D solid model to demonstrate the improved accuracy of the new approach. At the end of the paper a quantitative analysis of the reduction in computational cost due to shell meshing thin sheet regions demonstrates that the reduction in degrees of freedom is proportional to the square of the aspect ratio of the region, and for long slender solids, the reduction can be proportional to the aspect ratio of the region if appropriate meshing algorithms are used.

Dynamic Density Forecasts for Multivariate Asset Returns

We propose a simple and flexible framework for forecasting the joint density of asset returns. The multinormal distribution is augmented with a polynomial in (time-varying) non-central co-moments of assets. We estimate the coefficients of the polynomial via the Method of Moments for a carefully selected set of co-moments. In an extensive empirical study, we compare the proposed model with a range of other models widely used in the literature. Employing a recently proposed as well as standard techniques to evaluate multivariate forecasts, we conclude that the augmented joint density provides highly accurate forecasts of the “negative tail” of the joint distribution.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.

Automated nonlinear system modelling with multiple neural networks

This article discusses the identification of nonlinear dynamic systems using multi-layer perceptrons (MLPs). It focuses on both structure uncertainty and parameter uncertainty, which have been widely explored in the literature of nonlinear system identification. The main contribution is that an integrated analytic framework is proposed for automated neural network structure selection, parameter identification and hysteresis network switching with guaranteed neural identification performance. First, an automated network structure selection procedure is proposed within a fixed time interval for a given network construction criterion. Then, the network parameter updating algorithm is proposed with guaranteed bounded identification error. To cope with structure uncertainty, a hysteresis strategy is proposed to enable neural identifier switching with guaranteed network performance along the switching process. Both theoretic analysis and a simulation example show the efficacy of the proposed method.

Dealing with non-linearity in shape modelling of articulated objects

We address the problem of non-linearity in 2D Shape modelling of a particular articulated object: the human body. This issue is partially resolved by applying a different Point Distribution Model (PDM) depending on the viewpoint. The remaining non-linearity is solved by using Gaussian Mixture Models (GMM). A dynamic-based clustering is proposed and carried out in the Pose Eigenspace. A fundamental question when clustering is to determine the optimal number of clusters. From our point of view, the main aspect to be evaluated is the mean gaussianity. This partitioning is then used to fit a GMM to each one of the view-based PDM, derived from a database of Silhouettes and Skeletons. Dynamic correspondences are then obtained between gaussian models of the 4 mixtures. Finally, we compare this approach with other two methods we previously developed to cope with non-linearity: Nearest Neighbor (NN) Classifier and Independent Component Analysis (ICA).

Gender Classification via Lips: Static and Dynamic Features

Automatic gender classification has many security and commercial applications. Various modalities have been investigated for gender classification with face-based classification being the most popular. In some real-world scenarios the face may be partially occluded. In these circumstances a classification based on individual parts of the face known as local features must be adopted. We investigate gender classification using lip movements. We show for the first time that important gender specific information can be obtained from the way in which a person moves their lips during speech. Furthermore our study indicates that the lip dynamics during speech provide greater gender discriminative information than simply lip appearance. We also show that the lip dynamics and appearance contain complementary gender information such that a model which captures both traits gives the highest overall classification result. We use Discrete Cosine Transform based features and Gaussian Mixture Modelling to model lip appearance and dynamics and employ the XM2VTS database for our experiments. Our experiments show that a model which captures lip dynamics along with appearance can improve gender classification rates by between 16-21% compared to models of only lip appearance.

An automated hybrid procedure for capturing mode-jumping in postbuckling composite stiffened structures

This paper presents a robust finite element procedure for modelling the behaviour of postbuckling structures undergoing mode-jumping. Current non-linear implicit finite element solution schemes, found in most finite element codes, are discussed and their shortcomings highlighted. A more effective strategy is presented which combines a quasi-static and a pseudo-transient routine for modelling this behaviour. The switching between these two schemes is fully automated and therefore eliminates the need for user intervention during the solution process. The quasi-static response is modelled using the are-length constraint while the pseudo-transient routine uses a modified explicit dynamic routine, which is more computationally efficient than standard implicit and explicit dynamic schemes. The strategies for switching between the quasi-static and pseudo-transient routines are presented

Novel Radio Link Buffer Management Schemes for End-User Multi-class Traffic in High Speed Packet Access Networks

The requirement to provide multimedia services with QoS support in mobile networks has led to standardization and deployment of high speed data access technologies such as the High Speed Downlink Packet Access (HSDPA) system. HSDPA improves downlink packet data and multimedia services support in WCDMA-based cellular networks. As is the trend in emerging wireless access technologies, HSDPA supports end-user multi-class sessions comprising parallel flows with diverse Quality of Service (QoS) requirements, such as real-time (RT) voice or video streaming concurrent with non real-time (NRT) data service being transmitted to the same user, with differentiated queuing at the radio link interface. Hence, in this paper we present and evaluate novel radio link buffer management schemes for QoS control of multimedia traffic comprising concurrent RT and NRT flows in the same HSDPA end-user session. The new buffer management schemes—Enhanced Time Space Priority (E-TSP) and Dynamic Time Space Priority (D-TSP)—are designed to improve radio link and network resource utilization as well as optimize end-to-end QoS performance of both RT and NRT flows in the end-user session. Both schemes are based on a Time-Space Priority (TSP) queuing system, which provides joint delay and loss differentiation between the flows by queuing (partially) loss tolerant RT flow packets for higher transmission priority but with restricted access to the buffer space, whilst allowing unlimited access to the buffer space for delay-tolerant NRT flow but with queuing for lower transmission priority. Experiments by means of extensive system-level HSDPA simulations demonstrates that with the proposed TSP-based radio link buffer management schemes, significant end-to-end QoS performance gains accrue to end-user traffic with simultaneous RT and NRT flows, in addition to improved resource utilization in the radio access network.

Dynamic Buffer Management for Multimedia Services in Beyond 3G Wireless Networks

This paper investigates a dynamic buffer man-agement scheme for QoS control of multimedia services in be-yond 3G wireless systems. The scheme is studied in the context of the state-of-the-art 3.5G system i.e. the High Speed Downlink Packet Access (HSDPA) which enhances 3G UMTS to support high-speed packet switched services. Unlike earlier systems, UMTS-evolved systems from HSDPA and beyond incorporate mechanisms such as packet scheduling and HARQ in the base station necessitating data buffering at the air interface. This introduces a potential bottleneck to end-to-end communication. Hence, buffer management at the air interface is crucial for end-to-end QoS support of multimedia services with multi-plexed parallel diverse flows such as video and data in the same end-user session. The dynamic buffer management scheme for HSDPA multimedia sessions with aggregated real-time and non real-time flows is investigated via extensive HSDPA simulations. The impact of the scheme on end-to-end traffic performance is evaluated with an example multimedia session comprising a real-time streaming flow concurrent with TCP-based non real-time flow. Results demonstrate that the scheme can guar-antee the end-to-end QoS of the real-time streaming flow, whilst simultaneously protecting the non real-time flow from starva-tion resulting in improved end-to-end throughput performance

Dynamic Buffer Management for Multimedia Services in 3.5G Wireless Networks

This paper presents and investigates a dynamic
buffer management scheme for QoS control of multimedia
services in a 3.5G wireless system i.e. the High Speed Downlink
Packet Access (HSDPA). HSDPA was introduced to enhance
UMTS for high-speed packet switched services. With HSDPA,
packet scheduling and HARQ mechanisms in the base station
require data buffering at the air interface thus introducing a
potential bottleneck to end-to-end communication. Hence, for
multimedia services with multiplexed parallel diverse flows
such as video and data in the same end-user session, buffer
management schemes in the base station are essential to support
end-to-end QoS provision. We propose a dynamic buffer management
scheme for HSDPA multimedia sessions with aggregated real-time and non real-time flows in the paper. The end-to-end performance impact of the scheme is evaluated with an example multimedia session comprising a real-time streaming
flow concurrent with TCP-based non real-time flow via extensive HSDPA simulations. Results demonstrate that the scheme can guarantee the end-to-end QoS of the real-time streaming flow, whilst simultaneously protecting non real-time flow from starvation resulting in improved end-to-end throughput performance

End-to-End QoS Enhancement ofHSDPA End-User Multi-flow Traffic Using RAN Buffer Management

High speed downlink packet access (HSDPA) was introduced to UMTS radio access segment to provide higher capacity for new packet switched services. As a result, packet switched sessions with multiple diverse traffic flows such as concurrent voice and data, or video and data being transmitted to the same user are a likely commonplace cellular packet data scenario. In HSDPA, radio access network (RAN) buffer management schemes are essential to support the end-to-end QoS of such sessions. Hence in this paper we present the end-to-end performance study of a proposed RAN buffer management scheme for multi-flow sessions via dynamic system-level HSDPA simulations. The scheme is an enhancement of a time-space priority (TSP) queuing strategy applied to the node B MAC-hs buffer allocated to an end user with concurrent real-time (RT) and non-real-time (NRT) flows during a multi-flow session. The experimental multi- flow scenario is a packet voice call with concurrent TCP-based file download to the same user. Results show that with the proposed enhancements to the TSP-based RAN buffer management, end-to-end QoS performance gains accrue to the NRT flow without compromising RT flow QoS of the same end user session

A Dynamic Buffer Management Scheme for End-to-End QoS Enhancement of Multi-flow Services in HSDPA

End-user multi-flow services support is a crucial aspect of current and next generation mobile networks. This paper presents a dynamic buffer management strategy for HSDPA end-user multi-flow traffic with aggregated real-time and non-real-time flows. The scheme incorporates dynamic priority switching between the flows for transmission on the HSDPA radio channel. The end-to-end performance of the proposed strategy is investigated with an end-user multi-flow session of simultaneous VoIP and TCP-based downlink traffic using detailed HSDPA system-level simulations. Compared to an equivalent static buffer management scheme, the results show that end-to-end throughput performance gains in the non-real-time flow and better HSDPA channel utilization is attainable without compromising the real-time VoIP flow QoS constraints

Experimentally validated partial least squares model for dynamic line rating

This study presents a model based on partial least squares (PLS) regression for dynamic line rating (DLR). The model has been verified using data from field measurements, lab tests and outdoor experiments. Outdoor experimentation has been conducted both to verify the model predicted DLR and also to provide training data not available from field measurements, mainly heavily loaded conditions. The proposed model, unlike the direct measurement based DLR techniques, enables prediction of line rating for periods ahead of time whenever a reliable weather forecast is available. The PLS approach yields a very simple statistical model that accurately captures the physical performance of the conductor within a given environment without requiring a predetermination of parameters as required by many physical modelling techniques. Accuracy of the PLS model has been tested by predicting the conductor temperature for measurement sets other than those used for training. Being a linear model, it is straightforward to estimate the conductor ampacity for a set of predicted weather parameters. The PLS estimated ampacity has proven its accuracy through an outdoor experiment on a piece of the line conductor in real weather conditions.