Cedric Ka Fai Yiu

Effects of scan circle displacement in optical coherence tomography retinal nerve fibre layer thickness measurement: a RNFL modelling study

ObjectiveTo study the effect of optical coherence tomography (OCT) scan circle displacement on retinal nerve fibre layer (RNFL) measurement errors using cubic spline models.MethodsForty-nine normal subjects were included in the analysis. In one randomly selected eye in each subject, RNFL thickness around the optic disc was measured by taking 16 circular scans of different sizes (scan radius ranged from 1 to 2.5 mm). The RNFL profile in each eye was constructed with a mathematical model using a smoothing spline approximation. Scan circle (diameter 3.4 mm) RNFL measurements (total average, superior, nasal, inferior, and temporal RNFL thicknesses) obtained from eight directions (superior, superonasal, nasal, inferonasal, inferior, inferotemporal, temporal, and superotemporal) displaced at different distances (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, and 0.7 mm) from the disc centre were then computed by a computer program and compared to the ‘reference standard’ where the scan circle is centred at the optic disc. RNFL measurement error was calculated as the absolute of (RNFL thickness (displaced) – RNFL thickness (reference standard)).ResultsThe respective mean average, superior, nasal, inferior, and temporal RNFL measurement errors were 2.3±2.0, 4.9±4.5, 4.1±3.8, 6.2±7.6, and 3.8±3.5 μm upon 0.1 mm scan circle displacement, and 12.1±11.4, 27.8±18.4, 21.7±18.6, 34.8±22.9, and 15.2±10.7 μm upon 0.7 mm scan circle displacement. Significant differences of average and quadrant RNFL thicknesses were evident between centred and displaced scan circle measurements (all with P<0.001). RNFL measurement error increased in a monotonic fashion with increasing distance away from the disc and the change was direction-dependent.ConclusionsRNFL measurement error varies with the direction and distance of scan displacement. The superior and the inferior RNFL measurements are most vulnerable to scan displacement errors, whereas the average RNFL thickness is the least susceptible. Obtaining a well-centred scan is essential for reliable RNFL measurement in OCT.

Computer simulation of progressive retinal nerve fiber layer loss in glaucoma: performance of event and trend analyses.

PURPOSE Although event analysis (EA) and trend analysis (TA) have been widely adopted to evaluate glaucoma progression in clinical trials, there is poor agreement between the strategies and no consensus on strategy selection in clinical practice. With computer simulation of progressive loss of the retinal nerve fiber layer (RNFL), the authors compared the performance of TA and EA for the detection of glaucoma progression. METHODS RNFL progression was modeled with reference to the individuals test-retest variability and the pattern and rate of progression. The sensitivity and specificity of each scenario were computed from 5000 simulated datasets. Simulation results were validated with longitudinal RNFL measurements obtained from 107 glaucoma and glaucoma suspect patients who had a median follow-up period of 38 months. RESULTS TA generally attained a sensitivity ≥80% earlier than EA, although EA with a group reproducibility coefficient had a higher sensitivity than TA for eyes with a large test-retest variability in the early follow-up period, albeit at a lower specificity. The specificity of TA was 95% and ranged between 80% and 100% for EA. Independent of test-retest variability and the pattern and rate of progression, TA had an accuracy ≥80% earlier than EA. In the longitudinal study, the detection rate was 42%, 35%, and 3% for TA, whereas it was 11% to 40%, 12% to 28%, and 3% to 23% for EA at 36 months of follow-up in eyes with small, average, and large test-retest variabilities, respectively. CONCLUSIONS Although test-retest variability is an important determinant in progression analysis, TA generally outperformed EA for the detection of RNFL progression in glaucoma.

Coordinating Supply Chains With a General Price-Dependent Demand Function: Impacts of Channel Leadership and Information Asymmetry

This paper studies the effects of channel leadership and information asymmetry on supply chain coordination (SCC) of a single-manufacturer (M) single-retailer (R) supply chain, which sells a product with a general stochastic price-dependent-demand function. Three all-units quantity discount (QD) contracts are examined: (1) the manufacturer-led QD (MQD); (2) the retailer-led QD (RQD); and (3) the vendor managed inventory QD (VQD), which represent different channel leaderships. The problems are constructed as multistage sequential games. We find that any VQD that coordinates the supply chain has an equivalent RQD counterpart, and hence only MQD and RQD need to be examined for SCC. For the symmetric information scenario, both MQD and RQD can achieve coordination and the respective conditions for RQD are distribution free, but not for the MQD case. Only RQD, but not MQD, can always achieve Pareto improvement. For the asymmetric information scenario, MQD achieves coordination only if the actual supply chains optimal quantity is known by M, but this condition is not needed for RQD. There is a unique RQD that achieves SCC, and hence the profit division between channel members is fixed. To overcome this inflexibility issue, we demonstrate that R can offer a menu of two RQDs to M. However, Pareto improvement is not always guaranteed by using RQD. Since QD contracts are widely adopted in practice, this paper lays the foundation to advance our knowledge on how channel leadership affects performance under both the information symmetric and asymmetric cases.

Design of broadband beamformers with low complexity

In this article, we consider the design of broadband beamformers with low complexity. In fact, the design problem is multi-objective in nature, trading off between speech distortion and noise suppression. Finding a balance between these two objectives is important in order to achieve a desired sound quality. These measures are introduced as the objectives here. The design can then be obtained via a bi-objective integer programming problem, where the coefficients of the filters are expressed as sums of signed powers-of-two terms. We study two different integer spaces and penalty functions for solving the problem. Then, an algorithm based on a discrete filled function is developed for finding the optimal design. In order to illustrate the effectiveness of the algorithm, real data is used and two broadband beamformers are demonstrated.

Optimal Submission Problem in a Limit Order Book with VaR Constraints

We consider an optimal selection problem for bid and ask quotes subject to a value-at-Risk (VaR) constraint when arrivals of the buy and sell orders are governed by a Poisson process. The problem is formulated as a constrained utility maximization problem over a finite time horizon. Using a diffusion approximation to Poisson arrivals of market orders, the dynamic programming principle can be applied here. We propose an efficient procedure to solve this constrained utility maximization problem based on a successive approximation algorithm. Numerical examples with and without the VaR constraint are used to illustrate the effect of the risk constraint on the dealers choices. We also conduct numerical experiments to analyze the impacts of the risk constraint on dealers terminal profit.

Hybrid reconfigurable architecture for low power digital signal processing system

This paper presents an architecture for a hybrid reconfigurable device which is specifically optimized for acoustic applications. In the proposed architecture, Fine-grained units are used for implementing control logic and bit-oriented operations, while parameterised and reconfigurable word-based coarse-grained units incorporating word-oriented lookup tables and fast fourier transformation (FFT) are used to implement datapaths. In order to facilitate comparison with existing FPGA devices, the virtual embedded block (VEB) scheme is proposed to model embedded blocks using existing FPGA tools. This methodology involves adopting existing FPGA resources to model the size, position and delay of the embedded elements. We show significant power reduction when comparing with existing reconfigurable device implementing the same acoustic applications.

A Flexible Fuzzy Regression Method for Addressing Nonlinear Uncertainty on Aesthetic Quality Assessments

Development of new products or services requires knowledge and understanding of aesthetic qualities that correlate to perceptual pleasure. As it is not practical to develop a survey to assess aesthetic quality for all objective features of a new product or service, it is necessary to develop a model to predict aesthetic qualities. In this paper, a fuzzy regression method is proposed to predict aesthetic quality from a given set of objective features and to account for uncertainty in human assessment. The proposed method overcomes the shortcoming of statistical regression, which can predict only quality magnitudes but cannot predict quality uncertainty. The proposed method also attempts to improve traditional fuzzy regressions, which simulate a single characteristic with which the estimated uncertainty can only increase with the increasing magnitudes of objective features. The proposed fuzzy regression method uses genetic programming to develop nonlinear structures of the models, and model coefficients are determined by optimizing the fuzzy criteria. Hence, the developed model can be used to fit the nonlinearities of sample magnitudes and uncertainties. The effectiveness and the performance of the proposed method are evaluated by the case study of perceptual images, which are involved with different sampling natures and with different amounts of samples. This case study attempts to address different characteristics of human assessments. The outcomes demonstrate that more robust models can be developed by the proposed fuzzy regression method compared with the recently developed fuzzy regression methods, when the model characteristics and fuzzy criteria are taken into account.

A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions

Commercial speech recognizers have made possible many speech control applications such as wheelchair, tone-phone, multifunctional robotic arms and remote controls, for the disabled and paraplegic. However, they have a limitation in common in that recognition errors are likely to be produced when background noise surrounds the spoken command, thereby creating potential dangers for the disabled if recognition errors exist in the control systems. In this paper, a hybrid noise suppression filter is proposed to interface with the commercial speech recognizers in order to enhance the recognition accuracy under variant noisy conditions. It intends to decrease the recognition errors when the commercial speech recognizers are working under a noisy environment. It is based on a sigmoid function which can effectively enhance noisy speech using simple computational operations, while a robust estimator based on an adaptive-network-based fuzzy inference system is used to determine the appropriate operational parameters for the sigmoid function in order to produce effective speech enhancement under variant noisy conditions. The proposed hybrid noise suppression filter has the following advantages for commercial speech recognizers: (i) it is not possible to tune the inbuilt parameters on the commercial speech recognizers in order to obtain better accuracy; (ii) existing noise suppression filters are too complicated to be implemented for real-time speech recognition; and (iii) existing sigmoid function based filters can operate only in a single-noisy condition, but not under varying noisy conditions. The performance of the hybrid noise suppression filter was evaluated by interfacing it with a commercial speech recognizer, commonly used in electronic products. Experimental results show that improvement in terms of recognition accuracy and computational time can be achieved by the hybrid noise suppression filter when the commercial recognizer is working under various noisy environments in factories.

Indoor beamformer design using room simulators

Broadband microphone array provides an important means of hands-free speech acquisition via spatial beamforming techniques. There are many different approaches for the design of near-field broadband beamformers. One method is based on the wave propagation model using a direct path transfer function. However, as signals are corrupted by different interfering noise, room reverberation plays a particular important role for indoor applications even if there is no another speaker around. Image-source method is one simple but effective approach for room acoustic simulation. It is also possible to employ a wave-based model for the simulation. In this paper, we will study different room simulators and employ them for the design of indoor beamformers.