TwIST Algorithm Research Articles

External Validation of the TWIST Algorithm for Predicting Walking Independence Post-Acute Stroke: An Irish Prospective Cohort Study

Abstract Background Early prediction of walking dependency post-stroke is important for clinician and patient decision-making. National stroke guidelines recommend using the ‘Time to Walking Independently after Stroke’ (TWIST) model to predict walking independence post-stroke. External validation of the TWIST model is required prior to its clinical integration. This study aimed to evaluate whether the TWIST model is a valid predictor of walking independence post-stroke in an Irish population. Methods This prospective cohort study recruited patients admitted to a tertiary hospital with an acute stroke from July-November 2023. The Trunk Control Test (TCT) and paretic-limb hip extensor strength (Medical Research Council (MRC) scale) were assessed within 3 days post-stroke. Walking independence (Functional Ambulatory Category) was measured at 6 or 12 weeks post-stroke based on TWIST algorithm predictions. Predictive performance was measured using the area under the curve (AUC), accuracy, sensitivity, specificity, positive and negative predictive value. Results Sixty-one participants (38 male, median (interquartile range) age 74 years (68-86) and National Institutes of Health Stroke Scale 7 (4-11.5)) were included. The AUC (95% CI) was 0.88 (0.81-0.96) and 0.7 (0.21-1) at 6 and 12 weeks post-stroke respectively. Predictive accuracy (95% CI) was higher at 6 weeks (88.52% (77.78-95.26)) than 12 weeks post-stroke (86.96% (66.41-97.22)). Overall, the TWIST model made accurate predictions for 83.61% (71.91-91.85) of participants. Conclusion The TWIST model demonstrated fair-good predictive performance when externally validated. However, it performed poorly at 12 weeks post-stroke for those with poor post-stroke trunk control (TCT < 40) but moderate hip extensor strength (≥ 3 MRC scale). Further research is needed to explore its utility in this subgroup. Implication of Findings The TWIST model may benefit clinicians and patients by accurately predicting walking independence post-stroke. Further research is needed to explore its utility in specific subgroups, particularly those with poor post-stroke trunk control but moderate hip extensor strength.

An aircraft landing gear walk suppression method based on runway identification

The main landing gear walk is a longitudinal fore and aft movement of the strut caused by the brake system, and usually the vibration frequency does not exceed 10Hz. Gear walk is not only detrimental to the structural safety of the landing gear but also impairs the aircraft braking system's efficiency, so this vibration must be suppressed. Conventional anti-skid braking system (ABS) cannot recognize the friction characteristics of the tires and the road, so the tire-road friction changes drastically, which is the direct reason for gear walk. To address this problem, this paper first proposes a runway identification method to determine the optimal slip ratio for different runways, thereby achieving efficient anti-skid control and avoiding drastic changes in tire-road friction. A common anti-skid braking algorithm used in aircraft today is the pressure-bias modulation (PBM) algorithm, which is a rule-based deceleration-rate type of anti-skid algorithm. To solve the problem of landing gear vibration caused by unstable brake pressure of PBM, this paper proposes a slip-ratio based antiskid control method based on the super twist algorithm (STA). We constructed a simulation model in MATLAB/Simulink and conducted simulation tests, and the simulation results proved that the gear walking suppression method is effective.

A STA Current-Constrained Control for PMSM Speed Regulation System with Function Disturbance Observer

The non-cascade permanent magnet synchronous motor control system has the advantages of simple structure and less adjustable parameters, but the non-cascade structure needs to solve the problem of over-current protection. In this paper, a current constrained control method is used to limit the starting current to a safe range. At the same time, to ensure the robustness and rapidity of the system, a super twist current constraint controller (CCSTA) is generated by combining super twist algorithm (STA) with current constraint control; Considering the diversity of internal and external disturbances, a functional disturbance observer (FDOB) is proposed to compensate the matched and unmatched disturbances, which further improves the robustness of the system.

Harmonic and unbalanced voltage compensation with VOC‐based three‐phase four‐leg inverters in islanded microgrids

This study proposes a novel method that combines sliding mode control (SMC) and virtual oscillator control (VOC) to eliminate voltage harmonics and unbalance caused by non-linear and unbalanced loads in a three-phase low-voltage microgrid. The conventional VOC is modified to fit the three-phase four-leg inverter systems and a novel SMC control is designed using the high-pass filter technique and linearised super twist algorithm. The proposed control method can keep the voltage harmonics and unbalance at the point of common coupling within the IEEE standard limits, under heavily non-linear and unbalanced load conditions. The validity of the proposed method is verified by both offline simulations in Matlab/Simulink and Control Hardware-in-the Loop simulations using an OPAL-RT platform.

Gait rehabilitation after stroke: review of the evidence of predictors, clinical outcomes and timing for interventions.

The recovery of walking capacity is one of the main aims in stroke rehabilitation. Being able to predict if and when a patient is going to walk after stroke is of major interest in terms of management of the patients and their family's expectations and in terms of discharge destination and timing previsions. This article reviews the recent literature regarding the predictive factors for gait recovery and the best recommendations in terms of gait rehabilitation in stroke patients. Trunk control and lower limb motor control (e.g. hip extensor muscle force) seem to be the best predictors of gait recovery as shown by the TWIST algorithm, which is a simple tool that can be applied in clinical practice at 1week post-stroke. In terms of walking performance, the 6-min walking test is the best predictor of community ambulation. Various techniques are available for gait rehabilitation, including treadmill training with or without body weight support, robotic-assisted therapy, virtual reality, circuit class training and self-rehabilitation programmes. These techniques should be applied at specific timing during post-stroke rehabilitation, according to patient's functional status.

Finding the key length of a Vigenère cipher: How to improve the twist algorithm

A Vigenère cipher applies a single short key repeatedly to encrypt a plaintext. If a cryptanalyst correctly finds out the key length, the ciphertext can be divided into multiple instances of shift cipher and be broken by frequency analysis. To determine the key length, the twist algorithm, an alternate method to the standard Kasiski and Friedman tests, was recently proposed. In this article, we propose the twist+ algorithm, an improved twist algorithm, which can estimate the key length more accurately than the original twist algorithm.

Intensity modulation-based spectral polarization measurement method of coded aperture

This paper presents a spectral polarization measurement method for single-frame imaging. The method is based on intensity-modulated, coded aperture measurement, comprising a spectral polarization intensity modulation and a compressive sensing spectral imaging system. The incident light is modulated by two multistage phase retarders and a polarizer, and the spectrum’s Stokes parameters are shifted to different frequency channels. The spectrum of the modulated light is obtained by a spectral imaging system composed of a coded aperture and a dispersive prism. The modulated spectral information is reconstructed using the TwIST algorithm, and the Stokes elements can be demodulated from it. Taking a pixel as an example, numerical simulations of the modulation of incident light intensity modulation, spectral reconstruction, and demodulation of Stokes parameters show that the method can acquire spectral polarization information of sparse images. This process needs only one measurement of the object and is therefore capable of high-speed acquisition.

Sliding mode approach for formation control of multi-agent systems with unknown nonlinear interactions

This paper proposes nonlinear control approaches to solve a leader-follower formation of multi-agent system with unknown nonlinear interactions. Two distributed sliding mode control approaches are suggested here to track a leader in a desired formation with compensating unknown nonlinear terms. The nonlinear interaction terms can appear in multi-agent systems due to physical connections or cooperation between agents. Also the uncertainty in coefficient of control input is considered. Super twist algorithm is suggested for investigating this problem. Some Lyapunov functions are modified and employed to prove maintaining the formation of group, using the proposed sliding mode controllers. A simulation result for slung load transporting with quad-rotors is presented to demonstrate the capability of the proposed approaches.

Compressed 3D Image Information and Communication Security

AbstractEnsuring information and communication security in military messages, government instructions, scientific experiments, as well as in personal data processing, is critical. In this study, a new hybrid classical–quantum cryptographic scheme to protect image information and communication security is developed by combining a quantum key distribution (QKD) and compressed sensing (CS). This method employs a QKD system to generate true random codes among the remote legitimate users and utilizes these random codes to encrypt and decrypt compressed 3D image information based on the CS algorithm. Therefore, this new technique can provide computational security in the image information transmission process by the encryption and decryption of CS algorithm, and the information and communication security can be evaluated in real time by monitoring the QKD system. Furthermore, this technique can directly transmit and reconstruct the compressed 3D image information based on the modified TwIST algorithm, and thus fewer random codes are required in QKD system, which can improve the information transmission bandwidth. Consequently, this technique not only provides a new application of a QKD system but also extends the CS‐based image reconstruction from 2D to 3D. This study may open a new opportunity in the field of information and security communication.

Design of Restoration Method Based on Compressed Sensing and TwIST Algorithm

In order to improve the subjective and objective quality of degraded images at low sampling rates effectively,save storage space and reduce computational complexity at the same time, this paper proposes a joint restoration algorithm of compressed sensing and two step iterative threshold shrinkage (TwIST). The algorithm applies the TwIST algorithm which used in image restoration to the compressed sensing theory. Then, a small amount of sparse high-frequency information is obtained in frequency domain. The TwIST algorithm based on compressed sensing theory is used to accurately reconstruct the high frequency image. The experimental results show that the proposed algorithm achieves better subjective visual effects and objective quality of degraded images while accurately restoring degraded images.

Esoteric Twist: An Efficient in-Place Streaming Algorithmus for the Lattice Boltzmann Method on Massively Parallel Hardware

We present and analyze the Esoteric Twist algorithm for the Lattice Boltzmann Method. Esoteric Twist is a thread safe in-place streaming method that combines streaming and collision and requires only a single data set. Compared to other in-place streaming techniques, Esoteric Twist minimizes the memory footprint and the memory traffic when indirect addressing is used. Esoteric Twist is particularly suitable for the implementation of the Lattice Boltzmann Method on Graphic Processing Units.

Pattern Recognition for Flank Eruption Forecasting: An Application at Mount Etna Volcano (Sicily, Italy)

A volcano can be defined as a complex system, not least for the hidden clues related to its internal nature. Innovative models grounded in the Artificial Sciences, have been proposed for a novel pattern recognition analysis at Mt. Etna volcano. The reference monitoring dataset dealt with real data of 28 parameters collected between January 2001 and April 2005, during which the volcano underwent the July-August 2001, October 2002-January 2003 and September 2004-April 2005 flank eruptions. There were 301 eruptive days out of an overall number of 1581 investigated days. The analysis involved successive steps. First, the TWIST algorithm was used to select the most predictive attributes associated with the flank eruption target. During his work, the algorithm TWIST selected 11 characteristics of the input vector: among them SO2 and CO2 emissions, and also many other attributes whose linear correlation with the target was very low. A 5 × 2 Cross Validation protocol estimated the sensitivity and specificity of pattern recognition algorithms. Finally, different classification algorithms have been compared to understand if this pattern recognition task may have suitable results and which algorithm performs best. Best results (higher than 97% accuracy) have been obtained after performing advanced Artificial Neural Networks, with a sensitivity and specificity estimates over 97% and 98%, respectively. The present analysis highlights that a suitable monitoring dataset inferred hidden information about volcanic phenomena, whose highly non-linear processes are enhanced.

Fast digital image encryption based on compressive sensing using structurally random matrices and Arnold transform technique

A new fast digital image encryption method based on compressed sensing approach using structurally random matrices and Arnold transform is proposed. Considering the natural images to be compressed in any domain, the fast compressed sensing based approach saves computational time, increases the quality of the image and reduces the dimension of the digital image by choosing one-fourth of the measurements. First, dimension reduction is utilized to compress the digital image with scrambling effect. Second, Arnold transformation is used to give the reduced digital image into more complex form. Then, the complex image is again encrypted by double random phase encoding process embedded with a host image; two random keys with fractional Fourier transform are been used as a secret keys. At the receiver, the decryption process is recovered by using TwIST algorithm. Experimental results including peak-to-peak signal-to-noise ratio between the original and reconstructed image are shown to analyze the validity of this technique and demonstrated our proposed method to be secure, fast, complex and robust.

Implementing compressive fractional Fourier transformation with iterative kernel steering regression in double random phase encoding

This paper proposes a novel approach in double random phase encryption based on compressive fractional Fourier transform along with the kernel steering regression. The method increases the complexity of the image by using fractional Fourier transform and taking fewer measurements from the image data. Numerical results are given to analyze the validity of this technique. Considering natural images to be sparse in some domain, we apply a compressive sensing (CS) approach by using a TwIST algorithm. The encryption process has kernel steering regression algorithm for denoising and compressive sensing technique for image compression along with the fractional Fourier transform that makes the image in more complex form.