Scarring after burn injuries remains one of the major challenges in burn medicine and is the subject of current research. Accurate and high-quality assessment of scars is needed to enable exact ...outcome evaluation of different treatments. Our aim was to evaluate the most common subjective scar evaluation scores—the POSAS (Patient and Observer Scar Assessment Scale) and VSS (Vancouver Scar Scale)—in comparison with the objective device Mexameter® for colour evaluation.
A prospective monocentre study was performed, which included 120 examined scar areas of 60 patients with third degree burns who had received skin grafts between 1975 and 2018 with a total burned surface area (TBSA) > 2%. Two different scar areas in comparison with one healthy skin area concerning ‘colour’, ‘pigmentation’, and ‘vascularization’ were evaluated by the Mexameter® MX 18, the OSAS, and the VSS by the same examiner, as well as the PSAS by the patient.
The mean TBSA of the 60 patients was 24.3%. In the OSAS, 61% of the scars were evaluated as ‘hyper-’, 19% as ‘hypo-’, and 19% as ‘mix-pigmented’. Furthermore, 65% of the scars were estimated as highly vascularized. In the Mexameter®, the melanin index values of the scar areas compared to the healthy skin areas showed a small difference of 12 (p < 0.05). The mean difference of erythema between the scar and the healthy skin areas was 84 (p < 0.001). For the Mexameter®, moderate correlations were found when comparing ‘erythema’ with the OSAS category ‘vascularization’ (r = 0.33, p < 0.05) and ‘melanin’ with the OSAS parameter ‘pigmentation’ (r = 0.28, p < 0.05). When comparing the Mexameter® measurements to the OSAS questionnaire, 27% of the scars were wrongly evaluated as ‘hyperpigmented’ by the observer and 21% as ‘hypervascularized’, while showing low measurements in the device. Additionally, a novel Mexameter® ordinal scare scale was calculated.
In this study, we were able to show on a relatively large patient population that with the Mexameter®, the subjectivity of the scar colour assessment by examiner/patient can be overcome, but precise differentiation can still be ensured with subjective evaluation tools. We further introduced a novel Mexameter® Scar Scale. It is necessary to further investigate the vast range of objective devices and develop scar panels for with an incorporation of objective and subjective devices to further improve reliability with reduced bias in terms of scar assessment.
•Colour evaluation of scars and healthy skin with POSAS,VSS) compared to theMexameter®.•Precise differentiation of the colour properties of the scar can be ensured with the Mexameter®.•Presentation of a novel Mexameter® scar scale.
In forward blind source separation (FBSS) scenarios, subband adaptive filtering (SAF) algorithms provide fast convergence due to the SAF decorrelation ability. However, existing SAF algorithms suffer ...from a signal delay stemmed from the utilization of the synthesis filters. To solve this problem, we propose a delayless multisampled multiband-structured subband FBSS (DMSFBSS) algorithm by inserting a delayless multisampled multiband SAF structure. For a fixed SAF step-size, there is also a tradeoff between the convergence speed and steady-state error. We break this relationship by further developing an optimal DMSFBSS (ODMSFBSS) algorithm that minimizes the mean squared deviation (MSD) of DMSFBSS with respect to the subband gain vectors, to provide simultaneously fast convergence and low steady-state behavior. Intrinsically, the ODMSFBSS algorithm is an extension of the Kalman filtering theory over the subband-based FBSS structure. We also present an analysis of the algorithm stability. A vectorized implementation of the ODMSFBSS algorithm is proposed to reduce the computational complexity from <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(L^{2}) </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(L) </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">L </tex-math></inline-formula> is the length of the adaptive filter. Since adaptive FBSS scenarios require a voice activity detection (VAD) technique to control the alternating update of two adaptive filters, we develop two VAD approaches not relying on the priori knowledge of the speech source signal, thereby guaranteeing the practicability of the proposed ODMSFBSS algorithm. Simulation results in high and low SNR environments confirm that the proposed ODMSFBSS algorithm outperforms existing state-of-the-art algorithms.
Video surveillance system is a system that has a very important place in the framework of ensuring the required level of safety on the road infrastructure and plays an important role in the ...management of road networks. At present, video surveillance systems cover relatively large parts of road infrastructure such as motorways, tunnels, bridges, trunk roads, city centers, car parks etc. The aim is to obtain a large amount of data, from which it is possible in case of need to extract specific information, e.g. video recording about traffic situations and traffic composition and useful information about vehicles. It is also possible to work out a very accurate reconstruction of the accidental events by using video recording and higher engineering tools. For this reason, it is important to pay attention to the application of innovative methods in the effective design and planning of location of the camera system and its individual elements. In this paper we focused on the presentation of a method based on the fusion of point clouds obtained by the technology of 3D laser scanning and PC-Crash software tool for the needs of security management. The main aim of this paper is to verify the usability of 3D scanning technology for security practice. Especially the advantages and benefits that this method brings are highlighted.
The least mean square (LMS) algorithm of graph signal processing (GSP) can be used for sensor signal processing due to its simplicity and low computational complexity, and the recursive least squares ...(RLS) algorithm of GSP can be applied to sensor signal processing since it has fast convergence rate. However, the GSP LMS algorithm has poor convergence performance, and the tracking performance of the GSP RLS algorithm turns weak after signal mutation. To solve the mentioned problems, we focus on the data-reuse strategy, aiming to improve the convergence/tracking performance of the related algorithms by reusing the same set of data several times, and thus, the GSP data-reuse LMS (GSP-DR-LMS) algorithm and the GSP data-reuse RLSs (GSP-DR-RLSs) algorithm are proposed. Moreover, to make the GSP-DR-LMS algorithm achieve better coordination between steady-state error and convergence rate, we propose the variable step size (VSS) strategy applicable to the GSP-DR-LMS algorithm, and thus, the GSP VSS-DR LMS algorithm is proposed. In addition, the performance analysis of the related algorithms is performed. Ultimately, we verify the superiority of the proposed algorithms in terms of convergence/tracking performance by performing computer simulations.
This article proposes a new control chart (called the
ABS SPRT chart) for Statistical Process Control (SPC) based on Sequential Probability Ratio Test (SPRT). This chart is able to monitor the mean ...and variance of a variable
x simultaneously by inspecting the absolute sample shift |
x−
μ
0| (where
μ
0 is the in-control mean or target value of
x). The ABS SPRT chart is designed by an optimization algorithm, aiming at minimizing the Average Extra Quadratic Loss (
AEQL) over the process shift domain. The results of intensive performance studies show that the ABS SPRT chart not only uniformly outperforms the CUSUM chart with a Variable Sample Size (VSS) feature, but is also more effective than a 2-SPRT scheme which incorporates a lower-sided SPRT chart and an upper-sided one. From a holistic viewpoint, the ABS SPRT chart detects process shifts in mean and variance faster than the VSS CUSUM chart and 2-SPRT scheme by more than 30% and 13%, respectively. Noteworthily, the design of an ABS SPRT chart is relatively easier than that of a VSS CUSUM chart, and much simpler than the design of a 2-SPRT scheme.
•A novel adaptive nonlinear ANC system based on time-domain signal reconstruction technology is proposed.•The noise signal is decomposed to reduce the degree of non-stationarity.•A multi-network ...reconstruction model is designed for reconstructing the noise signal of passenger ear-sides.•Results demonstrate that proposed ANC system can realise the fault-tolerant and robustness control.
When the primary reference signal obtained by the existing Active noise control (ANC) system is not accurate, the control effect of interior noise will be reduced or even fail. Considering the fault-tolerate and robustness of the system, the study proposes an adaptive nonlinear ANC system for interior noise, which contains noise signal decomposition, multi-network reconstruction model and Variable step-size LMS (VSS-LMS) algorithm. The noise signal decomposition method is used to address the non-stationary of the interior noise; Based on the signal components, the multi-network model for the noise signal reconstruction of passenger ear-sides is designed, which is pre-trained by a restricted Boltzmann machine for improved reconstruction accuracy and realize the adaptive extraction of signal features; And then based on the reconstruction signal components, the controller weights of corresponding components are adaptively updated by the VSS-LMS algorithm to control the passenger ear-sides noise. The effectiveness of the proposed adaptive nonlinear ANC system is validated using noise signal sources collected from a vehicle. Compared with the different ANC systems, the proposed system is superior in terms of fault-tolerant and robustness, which can guarantee stable work of the interior noise control.
In the digital world, securing data is very significant. Digital data can focus either on content secrecy or the quality of recovered secret content. Visual Secret Sharing (VSS) becomes vital when ...content secrecy is essential over quality. VSS encrypts the secret into "n" share. The individual share cannot reveal any information; the secret gets revealed only when a predefined number of shares come together. Earlier attempted probabilistic and random grid approaches of size invariant VSS compromise in quality of recovered secret. Paper presents a method as a modified deterministic approach for size invariant VSS with improved quality of recovered secret; giving minimum Mean Squared Error (MSE), maximum Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM) close to "1" as compared to other existing methods.
A 26-year-old man developed visual snow syndrome (VSS) after consuming a little less than half of a delta-8 gummy (estimated at 4 mg of delta-8 tetrahydrocannabinol). Secondary VSS and ...hallucinogen-persisting perception disorder (HPPD) are discussed, and clinicians who evaluate patients with VS and VSS should ask about delta-8 gummies as an etiology of secondary VSS.
This article studies the mean and mean-square behaviors of the M-estimate based normalized subband adaptive filter algorithm (M-NSAF) with robustness against impulsive noise. Based on the ...contaminated-Gaussian noise model, the stability condition, transient and steady-state results of the algorithm are formulated analytically. These analysis results help us to better understand the M-NSAF performance in impulsive noise. To further obtain fast convergence and low steady-state estimation error, we derive a variable step size (VSS) M-NSAF algorithm. This VSS scheme is also generalized to the proportionate M-NSAF variant for sparse systems. Computer simulations on the system identification in impulsive noise and the acoustic echo cancellation with double-talk are performed to demonstrate our theoretical analysis and the effectiveness of the proposed algorithms.
This article proposes the machine learning (ML)-based joint vital signs (VSs) and occupancy detection (OD) with an impulse radio ultra-wideband (IR-UWB) sensor. Works that have been done on VS or OD ...development using an IR-UWB are related to how VS works. In the related experiments performed, the OD and state of individuals were not sufficiently verified, and the methods were computationally complex. Issues related to the use of ML for joint VS and OD (VSOD) have also not been studied in the literature. Extensive experimental scenarios involving the application of an ML-based classifier for human OD and VS classification, which we extended toward three sub-scenarios, were evaluated. We formulated a solution for VS estimation, which was aligned, so that each network input sequence received signal corresponding to respective VS over different scenarios. The performance of the proposal was evaluated with other competing ML-based classification algorithms. Compared with other techniques, our proposed deep neural network (DNN)-based classifier achieved the best results, and it also offers benefits over other algorithms, such as not needing to extract features from the data.
PDF
