For seismic exploration, the coupling problem between different physical fields is unavoidable. The operation of the coupling interface is very tricky. For this challenge, we propose a unified numerical approach to overcome it. Specifically, we construct a model framework, which contains various physical phenomena, and solve it by using the discontinuous Galerkin (DG) method allowing for the jump of the solution across the interface between the fluids and the solid materials. The viscoelasticity and fracture are first incorporated into the coupled model. The model includes the anisotropy, viscoelasticity, and fracture properties. The Riemann solver is employed to handle the coupling interfaces: the acoustic-elastic contact, the acoustic-viscoelastic contact, and the elastic-viscoelastic contact. Any additional treatment is not required for the complex coupling interface. Several examples are used to demonstrate the validity and flexibility of the proposed numerical scheme and the corresponding results show that our approach can handle more complex coupled models efficiently.

In embryonic development and organogenesis, cells sharing identical genetic codes acquire diverse gene expression states in a highly reproducible spatial distribution, crucial for multicellular formation and quantifiable through positional information. To understand the spontaneous growth of complexity, we constructed a one-dimensional division-decision model, simulating the growth of cells with identical genetic networks from a single cell. Our findings highlight the pivotal role of cell division in providing positional cues, escorting the system toward states rich in information. Moreover, we pinpointed lateral inhibition as a critical mechanism translating spatial contacts into gene expression. Our model demonstrates that the spatial arrangement resulting from cell division, combined with cell lineages, imparts positional information, specifying multiple cell states with increased complexity-illustrated through examples in C.elegans. This study constitutes a foundational step in comprehending developmental intricacies, paving the way for future quantitative formulations to construct synthetic multicellular patterns.

We present an innovative physics-informed numerical flux within the framework of the discontinuous Galerkin (DG) method for solving elastic wave equations in 2-D heterogeneous media that include interfaces between elastic materials. The first-order velocity–stress equations are used, which can be written in the formulation of hyperbolic system and can be easily incorporated into the framework of DG method. Numerical flux is carefully proposed to maintain the physical laws on both sides of the interface where material parameters are discontinuous. We compare the newly suggested numerical flux with both the classic local Lax–Friedrichs flux and the exact upwind flux. The latter is derived from solving the Riemann problem and adheres to the Rankine–Hugoniot condition. In the comparison, we find that our flux is formally similar to the classic local Lax–Friedrichs flux, but the numerical behavior is different from it; its numerical performance is similar to the exact upwind flux. The biggest advantage of the numerical flux we propose is that it does not need to accurately solve the Riemann problem, but it can maintain the physical continuity conditions near the interface with material discontinuities. We present three numerical examples of elastic wave propagation in heterogeneous media, including horizontal and inclined interfaces, and the Marmousi model. The numerical results demonstrate the effectiveness of this flux.

We present a p-adaptive discontinuous Galerkin (DG) approach for solving second-order elastic and acoustic wave equations. An arbitrary anisotropic medium is considered, and the first- to fourth-order polynomials are used. The second-order wave equation is first transformed into a unified first-order hyperbolic system that is suitable for the DG method. In the following, we describe the p-adaptive DG algorithm in detail. The adaptation criterion using the area indicator is adopted, and the order of polynomial applied for each subdomain in the whole computational domain is marked before time evolution. The adaptation used for wave propagation simulation is practical and flexible, and various numerical fluxes can be directly incorporated into this p-adaptive DG algorithm. Two numerical examples are used to demonstrate the performance of the proposed adaptive scheme.

Transversely isotropic (TI) medium is a widely studied anisotropic solid medium in seismology. The numerical simulation of seismic wave propagation in TI media is an effective tool to analyze the mechanism of seismic waves in complex anisotropic media. In this study, we introduce a double-weighted Runge–Kutta discontinuous Galerkin (RKDG) method for numerically solving wave propagation problems in 3-D TI media with surface topography. This method incorporates the discontinuous Galerkin spatial discretization with an explicit double-weighted two-step iteration time discretization. The local Lax–Friedrichs flux is used as the numerical flux in the formulations. This method can solve the first-order velocity–stress seismic wave equations, including TI media and more general anisotropic media. Due to the large scale of 3-D problems, parallel technology is adopted. Regions with irregular boundaries are discretized into unstructured tetrahedral meshes. Numerical experiments for various anisotropic media, including the vertical and tilted TI media, are presented. The results demonstrate the effectiveness of the double-weighted RKDG method in wavefield simulations in 3-D complicated anisotropic media.

In the field of geophysics, the Helmholtz decomposition (HD) formula is mainly numerically discretized by the finite difference method (FDM), which limits its application to a uniform regular grid only. Few scholars note wavefield separation on unstructured grids. In this study, we aim to develop a wavefield separation algorithm to separate P- and S-wavefields on nonuniform grids. Our scheme is based on an isotropic elastic wave equation. We first transform the HD formula into a weak integral form using the discontinuous Galerkin method (DGM). Then, we consider two types of unstructured meshes—triangle and quadrangle, which are more suitable for complex structures. Moreover, to reduce time costs, the single graphic processor unit (GPU) device is used to improve the computational efficiency. We perform a unified DGM operator by transforming unstructured triangles and quadrangles into standard reference elements using coordinate transformation. Our proposed HD operator enables us to effectively separate P- and S-wavefields on unstructured meshes. We carry out the wavefield separation simulation and calculate the numerical solutions in the homogeneous carbonate model, Graben model, and SEG/EAGE model. The homogeneous model verifies the correctness, availability, and superiority of our proposed separated operator, and the other numerical results show excellent performance for P/S-wavefield separation on unstructured meshes.

Elastic wavefield separation has attracted much attention in the field of geophysics, but the focus is mainly on a single solid medium, which is hardly used in the coupled medium. We propose an effective discontinuous Galerkin (DG) approach with the exact Riemann solver for modeling decoupling P- and S- wavefield propagation in coupling solid-fluid media. We apply the selective strong attenuation to P- or S-waves by the viscoelastic theory while keeping the other wave mode. The viscoelastic wave equation is first cast into the decoupling wave equation. Following, we derive a novel exact Riemann solver that can accurately couple with the fluid and the decoupling elastic media. Finally, we use the DG method to solve P/S decoupling wave equations in triangular and tetrahedral meshes. The original wavefield is accurately decomposed into P and S wavefields, whose phases and amplitudes are consistent with those of the elastic data. Several numerical experiments are used to demonstrate the accuracy and capacity of our developed P/S-separated approach.

Poroelastic wave equations incorporating fluid information have been paid much attention to, however, the conventional perfectly matched layer (PML) scheme fails to absorb poroelastic waves in numerical modeling. In this work, we construct a unified framework of the combination of the low- and high-order unsplit complex-frequency-shifted (CFS) -PMLs with the discontinuous Galerkin (DG) method in poroelastic media. We have derived three kinds of PML-corrected poroelastic wave equations, including the split PML formula, the low-order unsplit CFS-PML formula, and the high-order unsplit CFS-PML formula, which are all first-order hyperbolic form. We give a general scheme for transforming the second-order poroelastic equation into a first-order hyperbolic system. These PML-corrected formulations can be numerically solved by the DG method for simulating wave propagation in single-, double-, and triple-porosity media. Several numerical experiments in isotropic and anisotropic multi-porosity media are used to demonstrate the effectiveness of the low- and high-order unsplit auxiliary differential equation (ADE) CFS-PML boundary conditions for wavefield simulation. The model with a sinusoidal irregular interface is discretized into unstructured triangular meshes, and its results are to validate the flexibility of a combination of the low- and high-order unsplit CFS-PMLs with the DG method for simulation of seismic wave propagation in poroelastic media.

Adaptive surface-related multiple subtraction is an important step of surface-related multiple elimination (SRME) method. Generally, the traditional methods match the predicted multiples with the original data using obtained filter. In this letter, we propose a matching algorithm based on convolutional neural network (CNN) to strike a balance between the attenuation of multiples and the protection of primaries. Taking the predicted surface-related multiples as input, CNN’s output can better match with the original data. From the processing results of synthetic data, compared with the traditional$L_{1}$-norm or$L_{2}$-norm method, CNN method has lower calculation cost and the signal-to-noise ratio (SNR) of the primaries obtained after matching and subtraction is increased by 3 dB. The test of Pluto data and physical simulation data show that the proposed method can effectively remove surface-related multiples in seismic data.

The realization of nondestructive detection and classification of pavement distress is of great significance for putting forward a reasonable maintenance scheme and prolonging the service life of the road. In this paper, the advanced air-coupled 3D ground-penetrating radar (3D-GPR) was used to detect Li-Ma Expressway (Jiangsu Province, China) to achieve the purpose of rapid, accurate, and nondestructive testing. Through on-site coring at the corresponding radar anomaly signal, it is verified that the 3D-GPR can identify the characteristics of pavement distress. To address the issue of a large amount of 3D-GPR images required to be processed and low efficiency of current manual classification, VGG16 and ResNet50 models were established based on deep convolutional neural network to classify four pavement distresses automatically. The results showed that the maximum accuracy, precision, and recall obtained from the VGG16 model training results were 98.73%, 97.98%, and 96.17%, respectively. In addition, The overall processing time of VGG16 to identify 2525 radar images with$200 \times 200$pixels is 232 s. And VGG16 was selected as the automatic classification model of 3D-GPR image for pavement distress of Li-Ma Expressway.

Cyanobacteria bloom is a serious public health threat and a global challenge. Literature on the bloom prediction and forecasting has been accumulating and the emphasis appears to have been on the relation between the blooms and environmental factors, whilst the complexity of the bloom mechanism makes it difficult to reach adequate output of the models. Rapid development of next generation sequencing techniques provides a way in which comprehensive and quick examination of the microbial community can be achieved, especially for the bloom community structure. This facilitates using of merely the sequence data along with the machine learning techniques to predict and forecast the bloom occurrence. But there has been rare report on this theme in the literature. In this case study, machine learning approaches were applied with the metagenomic data as the only input (rather than with environmental data) to predict the Cyanobacteria blooms. k-NN classification, SVM classification and k-means clustering were applied and their efficiencies were evaluated using relevant indices. Feature selection was performed and the yielded sub datasets were worked on seriatim. In the predicting experiment with k-NN approach, the final year's data among the 8 years OTU time series were used as target data and various combination of the preceding years' data were used as predictor data; the output came with the best values of 1.00 and 100% for the evaluation indices F1 score and sensitivity, specificity, precision, and accuracy, for the 7 preceding years' predictor input, among the experiment results. This case study demonstrated the feasibility of using machine learning approaches in the Cyanobacteria bloom prediction with only metagenomic sequence data, and the importance of feature selection processing in obtaining better output of the machine learning approaches. The metagenomic data based machine learning approaches are efficient, economic, and faster, possessing the advantage and potential for being adopted as a promising means in the bloom prediction practice.

We present an efficient middleware-based fault-tolerant Ethernet (FTE) prototype developed for process control networks. This unique approach requires no change of commercial-off-the-shelf (COTS) hardware (switch, hub, Ethernet physical link and network interface card (NIC)) and software (Ethernet driver and protocol), yet it is transparent to application software. The FTE performs failure detection and recovery for handling multiple points of network failures and supports communications with non FTE-native devices. In this demonstration, we focus on presenting the failure detection and recovery behavior under various failure modes and scenarios. Further, multiple failure handling, node departure and non FTE-native node and FTE node communication scenarios will be presented. The FTE protocol status will be displayed using an FTE user interface on a COTS-based network system.

We present an efficient middleware-based fault-tolerant Ethernet (FTE) developed for process control networks. Our approach is unique and practical in the sense that it requires no change to commercial off-the-shelf hardware (switch, hub, Ethernet physical link, and network interface card) and software (commercial Ethernet NIC card driver and standard protocol such as TCP/IP) yet it is transparent to IP-based applications. The FTE performs failure detection and recovery for handling multiple points of network faults and supports communications with non-FTE-capable devices. Our experimentation shows that FTE performs efficiently, achieving less than 1-ms end-to-end swap time and less than 2-sec failover time, regardless of the concurrent application and system loads. In this paper, we describe the FTE architecture, the challenging technical issues addressed, our performance evaluation results, and the lessons learned in design and development of such an open-network-based fault-tolerant network.

Presented is an open solution based approach to fault tolerant Ethernet for process control networks. This unique approach provides fault tolerance capability that requires no change of vendor hardware (Ethernet physical link and Network Interface Card) and software (Ethernet driver and protocol), yet it is transparent to control applications. The open fault tolerant Ethernet (OFTE) developed based on this approach performs failure detection and recovery for handling single point of network failure and serves regular IP traffic. Our experimentation shows that OFTE performs efficiently, achieving less than 1 ms end to end LAN swapping time and less than 2 sec failover time, and that concurrent application and system loads have little impact on the performance of failure detection and recovery operations.

This study investigates real-time checkpointing techniques in the context of distributed process control applications where checkpointing and recovery operations must meet timing constraints, such as process deadline and plant state validity. We introduce the notion of quasidurability, which allows one to make tradeoffs between storage device reliability and the process control and recovery timing constraints. Based on this notion, we study three protocols for real-time quasi-durable checkpointing and recovery. For each protocol, we analyze its recoverability and provide the sufficient and necessary conditions for a set of devices to be feasible for checkpointing and recovery.

The uniqueness of continuous multimedia database applications lies in the fact that they require system support steady flow of media access data. In this paper we address the problem of system resource management for such applications. We introduce a session-based scheduling paradigm that, unlike traditional task scheduling, enables scheduling of all processing entities (threads, I/O processes, and buffers) across multiple system resources for guarantee of steady mediaflow. Under this paradigm, we develop an approach to on-line generation of session resource requirements based on resource allocation tradeoffs. Further, we develop a multidimensional "bin-packing" approach to allocation and scheduling of multiple resources for concurrent sessions. The goal is to minimize resource overheads and maximize the number of concurrent sessions while meeting session timing constraints and resource capacity constraints.>

Article Free Access Share on Concurrency control in federated databases: a dynamic approach Authors: San-Yih Hwang Computer Science Department, University of Minnesota, 200 Union St. SE, Minneapolis, MN Computer Science Department, University of Minnesota, 200 Union St. SE, Minneapolis, MNView Profile , Jiandong Huang Sensor and System Development Center, Honeywell, 3660 Technology Drive, Minneapolis, MN Sensor and System Development Center, Honeywell, 3660 Technology Drive, Minneapolis, MNView Profile , Jaideep Srivastava Computer Science Department, University of Minnesota, 200 Union St. SE, Minneapolis, MN Computer Science Department, University of Minnesota, 200 Union St. SE, Minneapolis, MNView Profile Authors Info & Claims CIKM '93: Proceedings of the second international conference on Information and knowledge managementDecember 1993Pages 694–703https://doi.org/10.1145/170088.170458Published:01 December 1993Publication History 3citation370DownloadsMetricsTotal Citations3Total Downloads370Last 12 Months8Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

The authors investigate solutions to the priority inversion problem in a real-time database where two-phase locking is employed for concurrency control. They examine two basic schemes for addressing the priority inversion problem, one based on priority inheritance and the other based on priority abort. The authors also study a new scheme, called conditional priority inheritance, which attempts to capitalize on the advantage of each of the two basic schemes. The performance studies, conducted on a real-time database testbed, indicated that the basic priority inheritance protocol is inappropriate for solving the priority inversion problem in real-time database systems. The authors also show that the conditional priority inheritance scheme and the priority abort scheme perform well for a wide range of system workloads.>

Results are presented of empirical evaluations carried out on the RT-CARAT testbed. This testbed was used evaluating a set of integrated protocols that support real-time transactions. A basic locking scheme for concurrency control was used to develop and evaluate several algorithms for handling CPU scheduling, data-conflict resolution, deadlock resolution, transaction wakeup, and transaction restart. The performance data indicate that the CPU scheduling algorithm is the most significant of all the algorithms in improving the performance of real-time transactions, conflict-resolution protocols which directly address deadlines and criticality can have a substantial impact on performance compared to protocols that ignore such information, both criticality and deadline distributions strongly affect transaction performance, and overheads such as locking and message communication are nonnegligible and cannot be ignored in real-time transaction analysis. It is believed that these empirical results represent the first experimental results for real-time transactions on a testbed system.>