Incident Light Frequency-based Image Defogging Algorithm

Considering the problem of color distortion caused by the defogging algorithm based on dark channel prior, an improved algorithm was proposed to calculate the transmittance of all channels respectively. First, incident light frequency's effect on the transmittance of various color channels was analyzed according to the Beer-Lambert's Law, from which a proportion among various channel transmittances was derived; afterwards, images were preprocessed by down-sampling to refine transmittance, and then the original size was restored to enhance the operational efficiency of the algorithm; finally, the transmittance of all color channels was acquired in accordance with the proportion, and then the corresponding transmittance was used for image restoration in each channel. The experimental results show that compared with the existing algorithm, this improved image defogging algorithm could make image colors more natural, solve the problem of slightly higher color saturation caused by the existing algorithm, and shorten the operation time by four to nine times

Chemical Modification of Polybutene-1 Resins

Controlled rheology polybutene (CRPB) resins have been produced by peroxide induced degradation during reactive processing in a batch mixing operation. Two grades of commodity polybutene-1 (PB-1) resins were selected for this study. Experiments were carried out at various peroxide concentrations and the resulting materials were characterized in terms of their molecular weight distribution (MWD) by high temperature size exclusion chromatography (SEC), linear viscoelastic properties by oscillatory shear measurements and melting/crystallization behavior by differential scanning calorimetry (DSC). Similar trends were observed for materials resulting from both commodity resins in the sense that increasing peroxide concentrations resulted in reduced molecular weight (MW) and rheological properties. The melt flow rate (MFR) was measured using a melt flow indexer and it was found to increase with peroxide concentration for both resins. Linear viscoelastic properties (complex viscosity and moduli) were also found to decrease with peroxide concentration, however the flow activation energy remained approximately constant for all materials. The melting temperature decreased with peroxide concentration, however, no significant effects were found on crystallization temperature. Finally, correlations were developed between zero-shear viscosity and weight-average molecular weight (MW), as well as between polydispersity index (PDI) and cross-over frequency and modulus for all samples produced

A Corpus-based Study on Chinese EFL Learners' Acquisition of English Existential Construction

This corpus-based study examines English existential construction used by intermediate and advanced level Chinese EFL (English as a Foreign Language) learners. The corpora adopted are the sub-corpora of SWECCL2.0—TEM 4 Oral and TEM 8 Oral and a sub-corpora of COCA. The study concludes Chinese EFL learners tend to overuse English existential construction and prefer the basic tenses, simple intransitive verbs and commonly seen expressions, avoid the perfect tenses and the difficult forms. With the level of proficiency in English getting higher, Chinese students try to use fewer English existential sentences. The study also finds errors relevant to the tenses, agreements and misuse of  “there + have” pattern made in TEM 4 Oral and more difficult participle errors made in TEM 8 Oral and the main reason of errors made in English existential acquisition is due to L1 transfer/ L1 influenc

Effect of Mn Addition and Heat Treatment on the Corrosion Behaviour of Mg–Ag–Mn Alloy

The high corrosion sensitivity and the potential bio-toxicity of Mg-Ag alloys limit their wide applications for the production of implanted devices. In the present work, Mn is added into the Mg-Ag alloy to optimize its corrosion behaviour. The corrosion behaviour of Mg-Ag-Mn alloys is investigated with the underlying microstructural factors examined. The Mg-Ag alloy with 2 wt. % Mn exhibits the highest corrosion resistance after post-casting heat treatment at 440 ⁰C. The addition of Mn results in α-Mn phase with the incorporation of Fe, which suppresses the cathodic activity of impurity Fe. Further, heat treatment of the cast alloys homogenizes the distribution of Ag and promotes the precipitation of α-Mn phase. The former removes Ag segregations as potential cathodes; the latter promotes a more uniform distribution of cathodes and, therefore, prevents localized corrosion.<br/

A real-time, practical sensor fault-tolerant module for robust EMG pattern recognition

BACKGROUND: Unreliability of surface EMG recordings over time is a challenge for applying the EMG pattern recognition (PR)-controlled prostheses in clinical practice. Our previous study proposed a sensor fault-tolerant module (SFTM) by utilizing redundant information in multiple EMG signals. The SFTM consists of multiple sensor fault detectors and a self-recovery mechanism that can identify anomaly in EMG signals and remove the recordings of the disturbed signals from the input of the pattern classifier to recover the PR performance. While the proposed SFTM has shown great promise, the previous design is impractical. A practical SFTM has to be fast enough, lightweight, automatic, and robust under different conditions with or without disturbances. METHODS: This paper presented a real-time, practical SFTM towards robust EMG PR. A novel fast LDA retraining algorithm and a fully automatic sensor fault detector based on outlier detection were developed, which allowed the SFTM to promptly detect disturbances and recover the PR performance immediately. These components of SFTM were then integrated with the EMG PR module and tested on five able-bodied subjects and a transradial amputee in real-time for classifying multiple hand and wrist motions under different conditions with different disturbance types and levels. RESULTS: The proposed fast LDA retraining algorithm significantly shortened the retraining time from nearly 1 s to less than 4 ms when tested on the embedded system prototype, which demonstrated the feasibility of a nearly “zero-delay” SFTM that is imperceptible to the users. The results of the real-time tests suggested that the SFTM was able to handle different types of disturbances investigated in this study and significantly improve the classification performance when one or multiple EMG signals were disturbed. In addition, the SFTM could also maintain the system’s classification performance when there was no disturbance. CONCLUSIONS: This paper presented a real-time, lightweight, and automatic SFTM, which paved the way for reliable and robust EMG PR for prosthesis control

An Algorithm for Idle-State Detection in Motor-Imagery-Based Brain-Computer Interface

For a robust brain-computer interface (BCI) system based on motor imagery (MI), it should be able to tell when the subject is not concentrating on MI tasks (the “idle state”) so that real MI tasks could be extracted accurately. Moreover, because of the diversity of idle state, detecting idle state without training samples is as important as classifying MI tasks. In this paper, we propose an algorithm for solving this problem. A three-class classifier was constructed by combining two two-class classifiers, one specified for idle-state detection and the other for these two MI tasks. Common spatial subspace decomposition (CSSD) was used to extract the features of event-related desynchronization (ERD) in two motor imagery tasks. Then Fisher discriminant analysis (FDA) was employed in the design of two two-class classifiers for completion of detecting each task, respectively. The algorithm successfully provided a way to solve the problem of “idle-state detection without training samples.” The algorithm was applied to the dataset IVc from BCI competition III. A final result with mean square error of 0.30 was obtained on the testing set. This is the winning algorithm in BCI competition III. In addition, the algorithm was also validated by applying to the EEG data of an MI experiment including “idle” task

A real-time, practical sensor fault-tolerant module for robust EMG pattern recognition

BackgroundUnreliability of surface EMG recordings over time is a challenge for applying the EMG pattern recognition (PR)-controlled prostheses in clinical practice. Our previous study proposed a sensor fault-tolerant module (SFTM) by utilizing redundant information in multiple EMG signals. The SFTM consists of multiple sensor fault detectors and a self-recovery mechanism that can identify anomaly in EMG signals and remove the recordings of the disturbed signals from the input of the pattern classifier to recover the PR performance. While the proposed SFTM has shown great promise, the previous design is impractical. A practical SFTM has to be fast enough, lightweight, automatic, and robust under different conditions with or without disturbances.MethodsThis paper presented a real-time, practical SFTM towards robust EMG PR. A novel fast LDA retraining algorithm and a fully automatic sensor fault detector based on outlier detection were developed, which allowed the SFTM to promptly detect disturbances and recover the PR performance immediately. These components of SFTM were then integrated with the EMG PR module and tested on five able-bodied subjects and a transradial amputee in real-time for classifying multiple hand and wrist motions under different conditions with different disturbance types and levels.ResultsThe proposed fast LDA retraining algorithm significantly shortened the retraining time from nearly 1s to less than 4ms when tested on the embedded system prototype, which demonstrated the feasibility of a nearly “zero-delay” SFTM that is imperceptible to the users. The results of the real-time tests suggested that the SFTM was able to handle different types of disturbances investigated in this study and significantly improve the classification performance when one or multiple EMG signals were disturbed. In addition, the SFTM could also maintain the system’s classification performance when there was no disturbance.ConclusionsThis paper presented a real-time, lightweight, and automatic SFTM, which paved the way for reliable and robust EMG PR for prosthesis control