Time‐parallel implicit integrators for the near‐real‐time prediction of linear structural dynamic responses

The time‐parallel framework for constructing parallel implicit time‐integration algorithms (PITA) is revisited in the specific context of linear structural dynamics and near‐real‐time computing. The concepts of decomposing the time‐domain in time‐slices whose boundaries define a coarse time‐grid, generating iteratively seed values of the solution on this coarse time‐grid, and using them to time‐advance the solution in each time‐slice with embarrassingly parallel time‐integrations are maintained. However, the Newton‐based corrections of the seed values, which so far have been computed in PITA and related approaches on the coarse time‐grid, are eliminated to avoid artificial resonance and numerical instability. Instead, the jumps of the solution on the coarse time‐grid are addressed by a projector which makes their propagation on the fine time‐grid computationally feasible while avoiding artificial resonance and numerical instability. The new PITA framework is demonstrated for a complex structural dynamics problem from the aircraft industry. Its potential for near‐real‐time computing is also highlighted with the solution of a relatively small‐scale problem on a Linux cluster system. Copyright © 2006 John Wiley & Sons, Ltd.     

RTSVC: Real‐time system for visual control of robots

This article presents an image processing system that can work in hard real‐time. Compared with systems that use the traditional multiprocessor architecture approach, this computer system takes advantage on recent technological advances and it is designed to work with a single processor PC under RTLinux. Its programming environment is similar to C programming language and it offers a friendly graphical user interface. The performance of the system is illustrated by means of experiments applied to visual guidance of mobile robots via velocity fields using a fixed high‐speed camera. The experiments were carried out with a strict sampling frequency of 100 Hz. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 251–256, 2008; Published online in Wiley InterScience (www.interscience.wiley.com).     

EM algorithm‐based adaptive custom thresholding for image denoising in wavelet domain

In this article, a novel denoising technique based on custom thresholding operating in the wavelet transform domain is proposed. The denoising process is spatially adaptive and also sub‐band adaptive. To render the denoising algorithm space adaptive, a Vector Quantization (VQ)‐based algorithm is used. The design of the VQ is based on Expectation Maximization (EM) algorithm. The results of the algorithm is demonstrated on SAR images corrupted by speckle noise. Experimental results show that Custom thresholding function outperforms the traditional soft, hard, and Bayes threshoding functions, improving the denoised results significantly in terms of Peak Signal to Noise Ratio (PSNR). © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 175–178, 2009     

Two implementations of IRK integrators for real‐time multibody dynamics

Recently, several authors have proposed the use of implicit Runge–Kutta (IRK) integrators for the dynamics of multibody systems. On the other hand, Newmark‐type or structural integrators have shown to be appropriate when real‐time performance is demanded in that field. Therefore, the following question arises: might the IRK integrators be suitable for real‐time purposes? And, provided the answer is positive: might they be preferable to the Newmark‐type family? This paper reports an investigation which has been conducted by the authors in order to get insight into the two questions formulated above. Since, based on previous experiences, it can be suspected that the performance of the integrators may be dependent on the type of dynamic formulation applied, the following three formulations have been considered for the study: a global penalty formulation in dependent natural co‐ordinates (many constraints), a topological semi‐recursive penalty formulation in dependent relative co‐ordinates (few constraints), and a topological semi‐recursive formulation in independent relative co‐ordinates (no constraints). As representative of the IRK family, a two‐stage SDIRK integrator has been selected due to its low associated computational burden, while, on the side of the structural integrators, the trapezoidal rule has been chosen. Two alternative implementations have been proposed to combine the dynamic formulations and the SDIRK integrator. A very demanding maneuver of the whole model of a vehicle has been simulated through all the possible combinations dynamic‐formulation/integrator, for different time‐steps. Conclusions have been drawn based on the obtained results, which provide some practical criteria for those interested in achieving real‐time performance for large and complex multibody systems. Copyright © 2005 John Wiley & Sons, Ltd.     

外延薄膜生长的实时监测分析研究

利用反射式高能电子衍射(RHEED)在超高真空中对SrTiO3(100)、LaAlO3(100)、Si(100)单晶基片进行分析,讨论了衍射花样与晶体表面结构的对应关系,计算出表面的晶体学参数,同时采用激光分子束外延技术同质外延生长SrTiO3薄膜，根据RHEED衍射图样及强度振荡曲线实时监控薄膜的生长。     

Stable time step estimates for mesh‐free particle methods

Real‐time computational biomechanics for medicine usually uses explicit time integration, because of its efficiency and suitability for parallel implementation. Explicit time integration is only conditionally stable and therefore requires an estimation of the maximum stable time step that can be used. In this paper we develop a method of estimating the stable time step for mesh‐free particle methods for a specific case of mass lumping: the mass associated with an integration point is distributed equally to all nodes found in the support domain of that integration point. Two estimates of the stable time step for each integration point are developed: one that is very accurate but more costly to compute and one less accurate but easier to implement. The results are also valid for the FEM and beyond computational biomechanics for medicine. Copyright © 2012 John Wiley & Sons, Ltd.     

Online multiaxial fatigue damage evaluation method by real‐time cycle counting and energy‐based critical plane criterion

To realize online multiaxial fatigue damage assessment for the mechanical components in service, an online multiaxial cycle counting method is proposed coupled with the segment processing technique and Wang‐Brow's relative equivalent strain concept. Meanwhile, considering all the stress and strain components, which contribute to the fatigue damage on the critical plane, a multiaxial fatigue damage model without any weight coefficients is also proposed in an equivalent form of shear strain energy. Then, an online fatigue damage evaluation method for multiaxial random loading is developed by combining with the proposed damage model and online cycle counting method. The experimental results showed that the proposed online cycle counting method can be successfully applied to the calculation of multiaxial fatigue damage under random loading. Moreover, the proposed online multiaxial fatigue damage evaluation method can provide satisfactory predictions.     

基于动态图像理解的生物式水质检测传感器

采用能综合反映水域水质状况的鱼类作为水质生物指示器,通过计算机视觉实时检测生物式水质传感器内的鱼体,采用动态图像理解技术分析鱼类的生态状况指标,如存活量、活动量以及投放药物后鱼类所产生的异常行为等,以判断水质的安全程度;通过传感器的特殊结构设计, 自动区分存活的、濒临死亡的、已死亡的鱼, 以方便获得鱼类生态状况的视频图像.最后,给出了一种集生物水质检测、机械设计、计算机视觉、动态图像理解及无线网络通信等技术于一体的生物式水质检测传感器的设计方法,并给出实验结果.     

LCM工艺实时监测技术的影响因素

为了提高复合材料液体成型(LCM) 工艺构件的质量稳定性和降低成本, 建立了直流电实时监测系统。实验表明, 该监测系统能够准确地反映监测点处树脂流动前锋的到达及其固化过程。研究了主要工艺因素对监测信号的影响规律, 发现系统对不同的树脂体系的响应差别较大, 监测饱满值随工艺温度的升高而增大, 随监测铜丝裸露长度的增加而增大, 纤维体积含量和纤维铺放角度对监测信号的影响不大。      

An Adaptive Real‐Time 3D Single Particle Tracking Method for Monitoring Viral First Contacts

Here, an adaptive real‐time 3D single particle tracking method is proposed, which is capable of capturing heterogeneous dynamics. Using a real‐time measurement of a rapidly diffusing particle's positional variance, the 3D precision adaptive real‐time tracking (3D‐PART) microscope adjusts active‐feedback parameters to trade tracking speed for precision on demand. This technique is demonstrated first on immobilized fluorescent nanoparticles, with a greater than twofold increase in the lateral localization precision (≈25 to ≈11 nm at 1 ms sampling) as well as a smaller increase in the axial localization precision (≈ 68 to ≈45 nm). 3D‐PART also shows a marked increase in the precision when tracking freely diffusing particles, with lateral precision increasing from ≈100 to ≈70 nm for particles diffusing at 4 µm² s^?1, although with a sacrifice in the axial precision (≈250 to ≈350 nm). This adaptive microscope is then applied to monitoring the viral first contacts of virus‐like particles to the surface of live cells, allowing direct and continuous measurement of the viral particle at initial contact with the cell surface.     

Reduced model of discrete‐time dynamic image segmentation system and its bifurcation analysis

We have developed a discrete‐time dynamic image segmentation system consisting of chaotic neurons and a global inhibitor. Our system receives an image with isolated regions and can output segmented images in time series based on oscillatory responses of chaotic neurons. In this article, we derive a reduced model to find intrinsic properties of the system of dynamic image segmentation. Using numerical method for analyzing dynamical systems, we investigated bifurcation phenomena of a fixed point observed in the reduced model. As the results, in a model of two coupled chaotic neurons, we found that a set of Neimark‐Sacker bifurcations causes the generation of an in‐phase oscillatory response, which is unsuitable for the purpose of dynamic image segmentation. The bifurcation analysis gives appropriate parameter values to exclude the generation of in‐phase oscillatory responses, i.e., our dynamic image segmentation system can work well. © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 283–289, 2009     

Brain image segmentation using a combination of expectation‐maximization algorithm and watershed transform

Watershed transformation is an effective segmentation algorithm that originates from the mathematical morphology field. This algorithm is widely used in medical image segmentation because it produces complete division even under poor contrast. However, over‐segmentation is its most significant limitation. Therefore, this article proposes a combination of watershed transformation and the expectation‐maximization (EM) algorithm to segment MR brain images efficiently. The EM algorithm is used to form clusters. Then, the brightest cluster is considered and converted into a binary image. A Sobel operator applied on the binary image generates the initial gradient image. Morphological reconstruction is applied to find the foreground and background markers. The final gradient image is obtained using the minima imposition technique on the initial gradient magnitude along with markers. In addition, watershed segmentation applied on the final gradient magnitude generates effective gray matter and cerebrospinal fluid segmentation. The results are compared with simple marker controlled watershed segmentation, watershed segmentation combined with Otsu multilevel thresholding, and local binary fitting energy model for validation. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 225–232, 2016     

Three‐stage model for robust real‐time face tracking

We propose a novel face tracking framework, the three‐stage model, for robust face tracking against interruptions from face‐like blobs. For robust face tracking in real‐time, we considered two critical factors in the construction of the proposed model. One factor is the exclusion of background information in the initialization of the target model, the extraction of the target candidate region, and the updating of the target model. The other factor is the robust estimation of face movement under various environmental conditions. The proposed three‐stage model consists of a preattentive stage, an assignment stage, and a postattentive stage with a prerecognition phase. The model is constructed by means of effective integration of optimum cues that are selected in consideration of the trade‐off between true positives and false positives of face classification based on a context‐dependant type of categorization. The experimental results demonstrate that the proposed tracking method improves the performance of the real‐time face tracking process in terms of success rates and with robustness against interruptions from face‐like blobs. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 321–327, 2007     

Self‐Powered Real‐Time Arterial Pulse Monitoring Using Ultrathin Epidermal Piezoelectric Sensors

Continuous monitoring of an arterial pulse using a pressure sensor attached on the epidermis is an important technology for detecting the early onset of cardiovascular disease and assessing personal health status. Conventional pulse sensors have the capability of detecting human biosignals, but have significant drawbacks of power consumption issues that limit sustainable operation of wearable medical devices. Here, a self‐powered piezoelectric pulse sensor is demonstrated to enable in vivo measurement of radial/carotid pulse signals in near‐surface arteries. The inorganic piezoelectric sensor on an ultrathin plastic achieves conformal contact with the complex texture of the rugged skin, which allows to respond to the tiny pulse changes arising on the surface of epidermis. Experimental studies provide characteristics of the sensor with a sensitivity (≈0.018 kPa^?1), response time (≈60 ms), and good mechanical stability. Wireless transmission of detected arterial pressure signals to a smart phone demonstrates the possibility of self‐powered and real‐time pulse monitoring system.     

Bioinspired Hydrogel Interferometer for Adaptive Coloration and Chemical Sensing

Living organisms ubiquitously display colors that adapt to environmental changes, relying on the soft layer of cells or proteins. Adoption of soft materials into an artificial adaptive color system has promoted the development of material systems for environmental and health monitoring, anti‐counterfeiting, and stealth technologies. Here, a hydrogel interferometer based on a single hydrogel thin film covalently bonded to a reflective substrate is reported as a simple and universal adaptive color platform. Similar to the cell or protein soft layer of color‐changing animals, the soft hydrogel layer rapidly changes its thickness in response to external stimuli, resulting in instant color change. Such interference colors provide a visual and quantifiable means of revealing rich environmental metrics. Computational model is established and captures the key features of hydrogel stimuli‐responsive swelling, which elucidates the mechanism and design principle for the broad‐based platform. The single material–based platform has advantages of remarkable color uniformity, fast response, high robustness, and facile fabrication. Its versatility is demonstrated by diverse applications: a volatile‐vapor sensor with highly accurate quantitative detection, a colorimetric sensor array for multianalyte recognition, breath‐controlled information encryption, and a colorimetric humidity indicator. Portable and easy‐to‐use sensing systems are demonstrated with smartphone‐based colorimetric analysis.     

Real‐time Reliability Evaluation for an Individual Product Based on Change‐point Gamma and Wiener Process

Reliability evaluation based on degradation data has received significant attentions in recent years. However, existing works often assume that the degradation evolution over time is governed by a single stochastic process, which may not be realistic if change points exist. Here, for cases of degradation with change points, this paper attempts to capture the degradation process with a multi‐phase degradation model and find the method to evaluate the real‐time reliability of the product being monitored. Once new degradation information becomes available, the evaluation results are adaptively updated through the Bayesian method. In particular, for a two‐stage degradation process of liquid coupling devices (LCDs), a model named as change‐point gamma and Wiener process is developed, after which issues of real‐time reliability evaluation and parameters’ estimation are addressed in detail. Finally, the proposed method is illustrated by a case study of LCDs, and the corresponding results indicate that trustful evaluation results depend on the fitting accuracy in cases of multi‐phase degradation process. Copyright © 2013 John Wiley & Sons, Ltd.     

An efficient real‐time method of analysis for non‐coherent fault trees

Fault tree analysis is commonly used to assess the reliability of potentially hazardous industrial systems. The type of logic is usually restricted to AND and OR gates, which makes the fault tree structure coherent. In non‐coherent structures not only components' failures but also components' working states contribute to the failure of the system. The qualitative and quantitative analyses of such fault trees can present additional difficulties when compared with the coherent versions. It is shown that the binary decision diagram (BDD) method can overcome some of the difficulties in the analysis of non‐coherent fault trees. This paper presents the conversion process of non‐coherent fault trees to BDDs. A fault tree is converted to a BDD that represents the system structure function (SFBDD). An SFBDD can then be used to quantify the system failure parameters but is not suitable for the qualitative analysis. Established methods, such as the meta‐products BDD method, the zero‐suppressed BDD (ZBDD) method and the labelled BDD (L‐BDD) method, require an additional BDD that contains all prime implicant sets. The process using some of the methods can be time consuming and is not very efficient. In addition, in real‐time applications the conversion process is less important and the requirement is to provide an efficient analysis. Recent uses of the BDD method are for real‐time system prognosis. In such situations as events happen, or failures occur, the prediction of mission success is updated and used in the decision‐making process. Both qualitative and quantitative assessments are required for the decision making. Under these conditions fast processing and small storage requirements are essential. Fast processing is a feature of the BDD method. It would be advantageous if a single BDD structure could be used for both the qualitative and quantitative analyses. Therefore, a new method, the ternary decision diagram (TDD) method, is presented in this paper, where a fault tree is converted to a TDD that allows both qualitative and quantitative analyses and no additional BDDs are required. The efficiency of the four methods is compared using an example fault tree library. Copyright © 2008 John Wiley & Sons, Ltd.     

Real‐time ballistocardiographic artifact reduction using the k‐teager energy operator detector and multi‐channel referenced adaptive noise cancelling

The simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) recording technique has recently received considerable attention and has been used in many studies on cognition and neurological disease. EEG‐fMRI simultaneous recording has the advantage of enabling the monitoring of brain activity with both high temporal resolution and high spatial resolution in real time. The successful removal of the ballistocardiographic (BCG) artifact from the EEG signal recorded during an MRI is an important prerequisite for real‐time EEG‐fMRI joint analysis. We have developed a new framework dedicated to BCG artifact removal in real‐time. This framework includes a new real‐time R‐peak detection method combining a k‐Teager energy operator, a thresholding detector, and a correlation detector, as well as a real‐time BCG artifact reduction procedure combining average artifact template subtraction and a new multi‐channel referenced adaptive noise cancelling method. Our results demonstrate that this new framework is efficient in the real‐time removal of the BCG artifact. The multi‐channel adaptive noise cancellation (mANC) method performs better than the traditional ANC method in eliminating the BCG residual artifact. In addition, the computational speed of the mANC method fulfills the requirements of real‐time EEG‐fMRI analysis. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 209–215, 2016     

Computing bounds to real eigenvalues of real‐interval matrices

In this study, a new method with algorithms for computing bounds to real eigenvalues of real‐interval matrices is developed. The algorithms are based on the properties of continuous functions. The method can provide the tightest eigenvalue bounds and improve some former research results. Numerical examples illustrate the applicability and effectiveness of the new method. Copyright © 2007 John Wiley & Sons, Ltd.