English Speech Feature Recognition Based On Digital Means

In order to improve the effect of English speech recognition, based on digital means, this paper combines the actual needs of English speech feature recognition to improve the digital algorithm. Moreover, this paper combines fuzzy recognition algorithm to analyze English speech features, and analyzes the shortcomings of traditional algorithms, and proposes the fuzzy digitized English speech recognition algorithm, and builds an English speech feature recognition model on this basis. In addition, this paper conducts time-frequency analysis on chaotic signals and speech signals, eliminates noise in English speech features, improves the recognition effect of English speech features, and builds an English speech feature recognition system based on digital means. Finally, this paper conducts grouping experiments by inputting students' English pronunciation forms, and counts the results of the experiments to test the performance of the system. The research results show that the method proposed in this paper has a certain effect.

Quantitative and Semi-quantitative Methods for Assessing the Degree of Methylene Blue Staining in Sentinel Lymph Nodes in Dogs

Background: To develop a digital algorithm for quantitative assessment of surface methylene blue staining in whole lymph nodes and validate a semi-quantitative visual scoring method for patient-side use.Methods: Lymph nodes from canine patients with spontaneous tumors undergoing sentinel lymph node mapping were prospectively assessed ex vivo and photographed. Using an open-source computer-based imaging software, an algorithm was developed for quantification of staining based on a signal-to-background ratio. Next, two blinded observers evaluated images and assigned a semi-quantitative visual score based on surface staining (0—no blue stain, 1−1–50% stained, and 2−51–100% stained) and those results were compared to the established quantitative standard.Results: Forty-three lymph nodes were included. Image analysis successfully quantified blue staining and differentiated from normal lymph node tissue in all cases. Agreement between observers using the Kappa coefficient demonstrated strong agreement (k = 0.8581, p < 0.0001) between semi-quantitative visual scoring and image analysis. There was substantial interobserver and intraobserver agreement for the scoring system (k = 0.7340, p < 0.0001 and k = 0.8983, p < 0.0001, respectively).Conclusion: A digital algorithm using an open-source software was simple and straightforward to use for quantification of blue staining. The use of a semi-quantitative visual scoring system shows promise for a simple, objective, repeatable assessment of methylene blue staining at the time of surgery. This study demonstrates reliable and repeatable methods for blue staining quantification thereby providing a novel and objective reporting mechanism in scientific research involving sentinel lymph node mapping.

Hybrid PSO-RBFNN and Proposed Algorithms of DDDWT for the Heart Disease Classification

This paper introduced a Particle Swarm Optimization-Radial Basis Function Neural Networks (PSO-RBFNN)-based system for heart disease detection that used the PSO algorithm to optimize RBFNN parameters. The newly developed signal digital algorithm presents the results of a new image contrast enhancement approach using Double Density Discrete Wavelet transform DDDWT for extraction of features, using adaptive DDDWT for the elimination of noise, and the use of PSO and ANN methods to classify the output from the Electrocardiogram (EGGS). It also provides identification of all techniques and MATLAB codes used to improve the processes. This approach merged the global search power of the PSO algorithm with the high efficiency of RBFNN's local optimums, overcome the inconsistency of the PSO algorithm and the RBFNN downside, quickly leading to a local minimum. The results show that, as compared to other approaches, the PSO-RBFNN model of heart disease diagnosis is highly accurate in detecting and predicting.

A Generalized Control Model and Its Digital Algorithm for Aerospace Electrohydraulic Actuators

It is difficult to describe precisely, and thus control satisfactorily, the dynamics of an electrohydraulic actuator to drive a high thrust liquid launcher engine, whose structural resonant frequency is usually low due to its heavy inertia and its complicated mass distribution. A generalized model is therefore put forward for maximum simplification and sufficient approximation, where a second-order transfer function is used to model the heavy mass-spring nature of the large engine body outside of the rod position loop, another second-order transfer function with two zeros and two poles representing the hydro-mechanical composite resonance effect in the closed rod position loop. A combined control strategy is applied to meet the stringent specification of static and dynamic performances, including a notch filter, a piecewise or nonlinear proportional, integral and differential (PID) controller and a feed-forward compensation. The control algorithm is implemented in digital signal processors with the same software structure but different parameters for different aerospace actuators. Compared to other approaches, this one makes it easier to grasp the system resonance nature, and, most importantly, the traditional dynamic pressure feedback (DPF) is replaced with the convenient digital algorithm, bringing prominent benefits such as a simplified design, reduced hardware cost and inherent higher reliability. The approach has been validated by simulation, experiments and successful flights.

Validating a semi-quantitative method to assess the degree of methylene blue staining in sentinel lymph nodes

PurposeTo develop a digital algorithm and validate a semi-quantitative scoring method for surface methylene blue (MB) staining in whole lymph nodes (LN).MethodsLymph nodes from canine models undergoing sentinel lymph node (SLN) mapping were prospectively assessed ex vivo and photographed. Two blinded observers evaluated all images and assigned a semi-quantitative score based on surface staining (0 – no blue stain, 1 – 1-50% stained, 2 – 51-100% stained). A standard reference for degree of blue staining was based on signal-to-background ratios using computer-based imaging software with an output measurement of percentage of staining of the LN. Agreement between observers was assessed using the Kappa coefficient.Results124 lymph nodes were included and demonstrated strong agreement (K = 0.8007, p < 0.0001) between results of semi-quantitative scoring and image analysis. Also, strong interobserver and intraobserver agreement was observed for the scoring system (K = 0.8051, p < 0.0001 and K = 0.9493, p < 0.0001, respectively).DiscussionAgreement between the observer-based scoring system and imaging software illustrates a validated method in assessing MB staining, without the need for analysis software. The use of a semi-quantitative scoring system shows promise for a simple, objective assessment of MB staining in surgery and for future study. Lymph nodes can have variable surface colour, which can make assessment of blue staining challenging for novice observers in certain cases. This study describes a digital algorithm for quantitative analysis of blue staining in LN thereby providing a novel and objective reporting mechanism in scientific research involving SLN mapping.

DIGITAL HEARING AID SIGNAL PROCESSING SYSTEM USING ANDROID PHONE

Objective: The objective of this research is to propose an Android-based digital hearing aid signal processing algorithm with following key features:(1) Regenerated audio match the patient-specific pattern of hearing loss, (2) noise reduction, and (3) provide flexibility to the users.Methods: The proposed signal processing algorithm is designed based on the specific hearing loss of the hearing disorder patient using inverse Fouriertransform; besides, noise reduction feature is included in the digital algorithm design as well. Proposed digital algorithm has been implemented intoan Android-based smartphone and its performance has been tested under real-time condition.Results: Simulation results show that the frequency response of the proposed digital hearing aid signal processing algorithm is in agreement withthe initial theoretical design that was carried out based on the hearing impaired patient’s audiogram. The proposed algorithm has been implementedin the Android-based smartphone and tested in real time. Results show that most of the patients are satisfied with the regenerated audio quality.According to patient’s comments, the regenerated audio is clear and the users are allowed to control the volume level. Besides, no obvious hearinglatency can be detected.Conclusion: Audio signals generated by the proposed digital signal processing algorithm show similar audio signal frequency response in boththeoretical design and MATLAB simulation results. The only difference between the design and simulation results is the amplification levels. Theproposed algorithm provides flexibility to the users by allowing them to choose the desired amplification level. In real-time testing, the proposedAndroid-based digital hearing aid is able to reduce noise level from the surrounding and the output processed speech match the patient-specifichearing loss.