Pipeline Configuration Research Articles

Real-Time Hybrid Multi-Sensor Fusion Framework for Perception in Autonomous Vehicles.

There are many sensor fusion frameworks proposed in the literature using different sensors and fusion methods combinations and configurations. More focus has been on improving the accuracy performance; however, the implementation feasibility of these frameworks in an autonomous vehicle is less explored. Some fusion architectures can perform very well in lab conditions using powerful computational resources; however, in real-world applications, they cannot be implemented in an embedded edge computer due to their high cost and computational need. We propose a new hybrid multi-sensor fusion pipeline configuration that performs environment perception for autonomous vehicles such as road segmentation, obstacle detection, and tracking. This fusion framework uses a proposed encoder-decoder based Fully Convolutional Neural Network (FCNx) and a traditional Extended Kalman Filter (EKF) nonlinear state estimator method. It also uses a configuration of camera, LiDAR, and radar sensors that are best suited for each fusion method. The goal of this hybrid framework is to provide a cost-effective, lightweight, modular, and robust (in case of a sensor failure) fusion system solution. It uses FCNx algorithm that improve road detection accuracy compared to benchmark models while maintaining real-time efficiency that can be used in an autonomous vehicle embedded computer. Tested on over 3K road scenes, our fusion algorithm shows better performance in various environment scenarios compared to baseline benchmark networks. Moreover, the algorithm is implemented in a vehicle and tested using actual sensor data collected from a vehicle, performing real-time environment perception.

High-throughput detection and tracking of cells and intracellular spots in mother machine experiments.

The analysis of bacteria at the single-cell level is essential to characterization of processes in which cellular heterogeneity plays an important role. BACMMAN (bacteria mother machine analysis) is a software allowing fast and reliable automated image analysis of high-throughput 2D or 3D time-series images from experiments using the 'mother machine', a very popular microfluidic device allowing biological processes in bacteria to be investigated at the single-cell level. Here, we describe how to use some of the BACMMAN features, including (i) segmentation and tracking of bacteria and intracellular fluorescent spots, (ii) visualization and editing of the results, (iii) configuration of the image-processing pipeline for different datasets and (iv) BACMMAN coupling to data analysis software for visualization and analysis of data subsets with specific properties. Among software specifically dedicated to the analysis of mother machine data, only BACMMAN allows segmentation and tracking of both bacteria and intracellular spots. For a single position, single channel with 1,000 frames (2-GB dataset), image processing takes ~6 min on a regular computer. Numerous implemented algorithms, easy configuration and high modularity ensure wide applicability of the BACMMAN software.

Overview and Empirical Analysis of ISP Parameter Tuning for Visual Perception in Autonomous Driving.

Image quality is a well understood concept for human viewing applications, particularly in the multimedia space, but increasingly in an automotive context as well. The rise in prominence of autonomous driving and computer vision brings to the fore research in the area of the impact of image quality in camera perception for tasks such as recognition, localization and reconstruction. While the definition of “image quality” for computer vision may be ill-defined, what is clear is that the configuration of the image signal processing pipeline is the key factor in controlling the image quality for computer vision. This paper is partly review and partly positional with demonstration of several preliminary results promising for future research. As such, we give an overview of what is an Image Signal Processor (ISP) pipeline, describe some typical automotive computer vision problems, and give a brief introduction to the impact of image signal processing parameters on the performance of computer vision, via some empirical results. This paper provides a discussion on the merits of automatically tuning the ISP parameters using computer vision performance indicators as a cost metric, and thus bypassing the need to explicitly define what “image quality” means for computer vision. Due to lack of datasets for performing ISP tuning experiments, we apply proxy algorithms like sharpening before the vision algorithm processing. We performed these experiments with a classical algorithm namely AKAZE and a machine learning algorithm for pedestrian detection. We obtain encouraging results, such as an improvement of 14% accuracy for pedestrian detection by tuning sharpening technique parameters. We hope that this encourages creation of such datasets for more systematic evaluation of these topics.

Probabilistic modelling of free spanning pipelines considering multiple failure modes

Free Spanning occurs due to unevenness of seabed, artificial supports and etc. Based on DNV-OS-F101, free spanning may cause Vortex-Induced Vibration (VIV), local buckling and pipeline bursting. The purpose of this study is to present a methodology for assessing free spanning pipelines in terms of Probability of Failure (POF). In order to assess VIV fatigue of subsea pipelines, a Finite-Element Reliability based method with aim of Artificial Neural Network (ANN) is proposed. For training ANN, 560 different ABAQUS FE scenarios with different pipeline configurations are defined, and their results are transferred to MATLAB. According to the recommended criteria, ANN is optimized. For determining reliability level of VIV fatigue, Monte-Carlo Sampling (MCS) is used to optimize ANN, and POF is determined consequently. In addition, using recommended method by DNV-RP-F105, Fatigue Life Capacity (FLC) of pipeline is determined for different conditions. For assessment of pipeline bursting and local buckling, recommended models by DNV-OS-F101 is adopted to determine their relevant POF using First-Order Reliability Method (FORM) and MCS. Furthermore, the effect of different operating pressure on reliability level of pipeline is investigated. Finally, in order to determine the effect of each parameter on POF of pipeline bursting and local buckling sensitivity analysis is carried out, using alpha index.

Analytical Model for the Structural Behavior of Pipelines During Lowering-In

Since pipelines experience the largest deformation during lowering-in, structural analysis for this construction sequence should be performed to ensure structural safety. In this study, a new analytical model named the “segmental pipeline model” was developed to predict the structural behavior of the pipeline. This analytical model consists of several segmental elements to represent various boundary and contact conditions. Therefore, the segmental pipeline model can consider the geometric configuration and characteristics of pipelines that appear during lowering-in. Adopting the Euler-Bernoulli beam and two-parameter beam on elastic foundation theory, the new model takes the effect of the soil and axial forces acting on the pipelines into account. This paper compares the displacements, sectional bending moments and shear forces of the pipeline obtained from the analytical model and finite element (FE) analysis, where good agreement was demonstrated. Also, the paper presents three examples to demonstrate the applicability of the analytical model.

Supervised methods to extract clinical events from cardiology reports in Italian.

Clinical narratives are a valuable source of information for both patient care and biomedical research. Given the unstructured nature of medical reports, specific automatic techniques are required to extract relevant entities from such texts. In the natural language processing (NLP) community, this task is often addressed by using supervised methods. To develop such methods, both reliably-annotated corpora and elaborately designed features are needed. Despite the recent advances on corpora collection and annotation, research on multiple domains and languages is still limited. In addition, to compute the features required for supervised classification, suitable language- and domain-specific tools are needed. In this work, we propose a novel application of recurrent neural networks (RNNs) for event extraction from medical reports written in Italian. To train and evaluate the proposed approach, we annotated a corpus of 75 cardiology reports for a total of 4365 mentions of relevant events and their attributes (e.g., the polarity). For the annotation task, we developed specific annotation guidelines, which are provided together with this paper. The RNN-based classifier was trained on a training set including 3335 events (60 documents). The resulting model was integrated into an NLP pipeline that uses a dictionary lookup approach to search for relevant concepts inside the text. A test set of 1030 events (15 documents) was used to evaluate and compare different pipeline configurations. As a main result, using the RNN-based classifier instead of the dictionary lookup approach allowed increasing recall from 52.4% to 88.9%, and precision from 81.1% to 88.2%. Further, using the two methods in combination, we obtained final recall, precision, and F1 score of 91.7%, 88.6%, and 90.1%, respectively. These experiments indicate that integrating a well-performing RNN-based classifier with a standard knowledge-based approach can be a good strategy to extract information from clinical text in non-English languages.

Investigation on scour protection of submarine piggyback pipeline

This paper presents the results of laboratory experiments and numerical simulations to investigate the effect of different piggyback pipeline configuration on the morphology of local seabed scour subject to steady currents. Piggyback pipeline configuration investigated includes the commonly used piggyback pipeline, namely a small pipe attached on the top of large pipe and new form of piggyback pipeline proposed in this study in which a small pipe is attached to the large pipe on the upstream and downstream side, respectively. Pressure gradient, drag coefficient, lift coefficient and scour extent around pipelines are measured and analyzed for a range of pipelines and current conditions. Results show that the vortex strength downstream of the commonly used piggyback pipeline is larger than that for a single as well as the new piggyback pipeline under the same condition. This new type piggyback pipeline can effectively reduce the depth and width of the scour hole. In particular, when the ratio of the small pipe diameter over the large pipe diameter is greater than 0.3, little scour under this new type piggyback pipeline occurs for the test conditions. The bed topography downstream of the pipe has also been altered to favor the backfill.

Investigation on scour scale of piggyback pipeline under wave conditions

Laboratory experiments are presented to investigate the effect of different piggyback pipeline configurations on the morphology of local scour under wave conditions. Scour depth and width around the pipelines under regular and irregular waves are measured and analyzed for a range of pipeline and wave conditions; such as the spacing between two pipes (G), gap between the main pipe and seabed (e), pipe diameter (D), wave height (H) and period (T). Experimental results reveal that both the scour depth and width around piggyback pipeline is much larger than those around single pipe under the same wave conditions. Scour depth increases with the increase of the Keulegan-Carpenter (KC) number and decreases with increase of G and e. When e exceeds 0.5D, scour depth tends to approach 0. When spacing G is greater than 0.4D, the destabilization from small pipe to large one is greatly reduced, resulting in scour depth around piggyback pipeline being close to that around single pipe. Similar to scour depth, scour width broadens with the increase of KC number increasing and decreases with the increase of G. Experiments also show that the effect of e on scour depth is greater than that of G under the same test conditions, while their impact on scour width is opposite. Furthermore, scour width under irregular waves is extended slightly compared with regular wave for otherwise the identical conditions.

Feasible numerical method for analysis of offshore pipeline in installation

Feasible numerical method for a structural analysis of a pipeline configuration during the installation process is presented. The method considers the whole pipeline, which is partially suspended and partially laid-on a seabed, as a single continuous segment, and is valid for a complete range of laying angles between 0°–90°, i.e., valid for both S-lay and J-lay configurations. The method accounts for a pipeline–seabed interaction and the pipeline is modeled by means of nonlinear large deformation beam theory. The numerical solution is carried out in an incremental-iterative manner by following the actual pipeline installation process, and thus allowing efficient treatment of pipeline-seabed interaction circumventing the further complexities with contact detection. At each increment, the length of the pipeline is increased and new sequential equilibrium configuration is assessed by direct minimization of a total potential energy approximated as a Riemann sum, which yields algebraic system of nonlinear finite difference equations that is further solved by iterations with Newton-Raphson technique. The simplicity, flexibility and robustness of the proposed method allow to enhance the efficiency of engineering calculations and design. Accounting for a bending stiffness in a suspended part allows analyzing variations in laying angle and lay tension independently. The method convergence is validated and compared with Abaqus. The results are in an excellent agreement. Moreover, the comparison with Abaqus shows that for the selected parameters the assumption that the pipeline is inextensible and unshearable is very reasonable. Representative parametric study is conducted to demonstrate the feasibility of the method. Parametric study considers the effects of laying angle (0°–90°), lay tension, laying water depth (up to 3000 m) and seabed stiffness.

Modelling solids friction for fluidized dense-phase pneumatic conveying

Fluidized dense-phase pneumatic conveying of powders has a number of benefits in various industries such as coal-fired thermal power plants, chemical, cement, pharmaceutical, petrochemical plants, etc. However, reliable designing of fluidized dense phase pneumatic conveying system is significantly difficult due to the complex and turbulent nature of the flow. In the present work, power station fly ash was conveyed through different pipeline configurations. Governing equations were developed for the fluidized dense-phase flow in the pneumatic conveying system and were solved using Runge-Kutta-Fehlberg method (RKF45). The results revealed that the particle velocity and actual gas velocity and the ratio of the two velocities increase along the direction of flow, while an opposite trend was observed for the solids volumetric concentration. A particle velocity model has been developed using solid loading ratio and dimensionless velocity terms. This particle velocity model, when employed in the existing two-layer model format for solids friction factor, has provided improved scale-up predictions (under diameter and length scale-up conditions) compared to the original two-layer model.

SLIM: a flexible web application for the reproducible processing of environmental DNA metabarcoding data

BackgroundHigh-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) has become a routine tool for biodiversity survey and ecological studies. By including sample-specific tags in the primers prior PCR amplification, it is possible to multiplex hundreds of samples in a single sequencing run. The analysis of millions of sequences spread into hundreds to thousands of samples prompts for efficient, automated yet flexible analysis pipelines. Various algorithms and software have been developed to perform one or multiple processing steps, such as paired-end reads assembly, chimera filtering, Operational Taxonomic Unit (OTU) clustering and taxonomic assignment. Some of these software are now well established and widely used by scientists as part of their workflow. Wrappers that are capable to process metabarcoding data from raw sequencing data to annotated OTU-to-sample matrix were also developed to facilitate the analysis for non-specialist users. Yet, most of them require basic bioinformatic or command-line knowledge, which can limit the accessibility to such integrative toolkits. Furthermore, for flexibility reasons, these tools have adopted a step-by-step approach, which can prevent an easy automation of the workflow, and hence hamper the analysis reproducibility.ResultsWe introduce SLIM, an open-source web application that simplifies the creation and execution of metabarcoding data processing pipelines through an intuitive Graphic User Interface (GUI). The GUI interact with well-established software and their associated parameters, so that the processing steps are performed seamlessly from the raw sequencing data to an annotated OTU-to-sample matrix. Thanks to a module-centered organization, SLIM can be used for a wide range of metabarcoding cases, and can also be extended by developers for custom needs or for the integration of new software. The pipeline configuration (i.e. the modules chaining and all their parameters) is stored in a file that can be used for reproducing the same analysis.ConclusionThis web application has been designed to be user-friendly for non-specialists yet flexible with advanced settings and extensibility for advanced users and bioinformaticians. The source code along with full documentation is available on the GitHub repository (https://github.com/yoann-dufresne/SLIM) and a demonstration server is accessible through the application website (https://trtcrd.github.io/SLIM/).

The Cascade Control of Natural Gas Pipeline Systems

With the boost of natural gas consumption, an automatic gas pipeline scheduling method is required to replace the dispatchers in decision making. Since the state space model is the fundamental work of modern control theory, it is possible that the classical controller synthesis method can be used for the complicated gas pipeline controller design. In this paper, a cascade control algorithm is proposed based on the state space model that is used for the transient flow simulation of the natural gas pipelines. A linear quadratic regulator is designed following the classical optimal control theory. Finally, the transient process with different control methods shows the effectiveness of the cascade control using information of the entire pipeline. According to the hardware configuration of natural gas pipelines, automatic scheduling process is ready to deploy as one step to the intelligent natural gas pipelines.

Influence of channels transverse profiling on the heat transfer intensity in the intake system of internal combustion engine

Gas-dynamic perfection and intensity of heat exchange of intake systems determine the efficiency of the piston engine. The results of numerical simulation and experimental study of the heat transfer of gas streams in the intake system of engines having different configurations are presented in the article. Methods of modeling, experimental setup, geometric configuration of pipelines and measuring base are described in the paper. The investigations were carried out under steady-state air flow in the system. The results of mathematical modeling were verified using experimental studies. It is established that the use of profiled sections in the intake system leads to a decrease in the heat transfer rate up to 20 % at low air flow rates (up to 40 m/s) and an increase in the heat transfer rate up to 9 % at high speeds.

ATAC2GRN: optimized ATAC-seq and DNase1-seq pipelines for rapid and accurate genome regulatory network inference

BackgroundChromatin accessibility profiling assays such as ATAC-seq and DNase1-seq offer the opportunity to rapidly characterize the regulatory state of the genome at a single nucleotide resolution. Optimization of molecular protocols has enabled the molecular biologist to produce next-generation sequencing libraries in several hours, leaving the analysis of sequencing data as the primary obstacle to wide-scale deployment of accessibility profiling assays. To address this obstacle we have developed an optimized and efficient pipeline for the analysis of ATAC-seq and DNase1-seq data.ResultsWe executed a multi-dimensional grid-search on the NIH Biowulf supercomputing cluster to assess the impact of parameter selection on biological reproducibility and ChIP-seq recovery by analyzing 4560 pipeline configurations. Our analysis improved ChIP-seq recovery by 15% for ATAC-seq and 3% for DNase1-seq and determined that PCR duplicate removal improves biological reproducibility by 36% without significant costs in footprinting transcription factors. Our analyses of down sampled reads identified a point of diminishing returns for increased library sequencing depth, with 95% of the ChIP-seq data of a 200 million read footprinting library recovered by 160 million reads.ConclusionsWe present optimized ATAC-seq and DNase-seq pipelines in both Snakemake and bash formats as well as optimal sequencing depths for ATAC-seq and DNase-seq projects. The optimized ATAC-seq and DNase1-seq analysis pipelines, parameters, and ground-truth ChIP-seq datasets have been made available for deployment and future algorithmic profiling.

INFILL MATERIALS OF EPOXY GROUT FOR PIPELINE REHABILITATION AND REPAIR

The oil and gas industry uses carbon steel pipelines as the basic element in transporting crude oil and gas. These pipelines are subjected to deterioration due to several factors, including third party damage, material and construction defects, natural forces and corrosion. Deterioration of underground pipelines due to corrosion can lead to serious pipeline failures such as leakage and explosion. Hence, methods to repair such damage have been developed in order to extend the durability of pipelines. This paper reports on the current development of infill materials of epoxy grouts used for pipeline external repair. Assessment of the defects should be completed by pipeline operators to identify list of parameters including pipeline operating characteristic, geometries and materials of pipeline, and configuration and location of pipeline to make the best option of repair techniques. Therefore, selection of an appropriate rehabilitation system is crucial in preventing the future failure of pipeline structure. A simple guideline is required to optimize the information in the selection of suitable materials for pipeline repair works. The selection of suitable materials will help in preventing the future failure of pipeline structures due to inappropriate selection of infill materials.

Survey and empirical comparison of different approaches for text extraction from scholarly figures

Different approaches have been proposed in the past to address the challenge of extracting text from scholarly figures. However, until recently, no comparative evaluation of the different approaches had been conducted. Thus, we performed an extensive study of the related work and evaluated in total 32 different approaches. In this work, we perform a more detailed comparison of the 7 most relevant approaches described in the literature and extend to 37 systematic linear combinations of methods for extracting text from scholarly figures. Our generic pipeline, consisting of six steps, allows us to freely combine the different possible methods and perform a fair comparison. Overall, we have evaluated 44 different linear pipeline configurations and systematically compared the different methods. We then derived two non-linear configurations and a two-pass approach. We evaluate all pipeline configurations over four datasets of scholarly figures of different origin and characteristics. The quality of the extraction results is assessed using F-measure and Levenshtein distance, and we measure the runtime performance. Our experiments showed that there is a linear configuration that overall shows the best text extraction quality on all datasets. Further experiments showed that the best configuration can be improved by extending it to a two-pass approach. Regarding the runtime, we observed huge differences from very fast approaches to those running for several weeks. Our experiments found the best working configuration for text extraction from our method set. However, they also showed that further improvements regarding region extraction and classification are needed.

On developing improved modelling for particle velocity and solids friction for fluidized dense-phase pneumatic transport systems

Pneumatic transport of fine powders in fluidized dense-phase pneumatic conveying of powders has become popular in several industries because it offers various advantages, such as reduced air flow and gas velocity, reduced pipeline sizing and wear rate, reduced size requirement of gas–solid separator unit etc. For the reliable design of a pneumatic conveying system precise estimation of the solids friction factor through horizontal straight pipes is essential, but it is a challenging task till date because of the highly concentrated, turbulent, and complex nature of the gas–solids mixture. In the present work, power station fly ash (median particle diameter: 22 μm; particle density: 2370 kg/m3; loose-poured bulk density: 660 kg/m3) and cement (median particle diameter: 19 μm; particle density: 2910 kg/m3; loose-poured bulk density: 1080 kg/m3) were conveyed through different pipeline configurations (i.e., 65-mm inner diameter × 254-m-long and 80/105-mm inner diameter × 407-m-long step-up pipeline). For the fluidized dense-phase flow in pneumatic conveying system, governing equations were developed and the same were solved using fourth-fifth-order Runge-Kutta-Fehlberg (RKF45) method. The results revealed that the particle velocity and actual gas velocity and the ratio of the two velocities increases along the direction of flow, while an opposite trend was found for the solids volumetric concentration. The particle velocity and actual gas velocity terms were then included in an existing pure dilute-phase model (for solid friction factor) to modify it, by incorporating sub-models for particle and actual gas velocities and impact and solids friction factor and make it suitable for dense-phase mode. The solids friction-factor model was then validated by comparing the experimental and predicted pneumatic conveying characteristics for different solids flow rates and by using it to predict the total pipeline pressure drops for larger and longer pipelines. The new model has shown reliable predictions in the dense-phase region.

Numerical Investigation of the Thermal Regime of Underground Channel Heat Pipelines Under Flooding Conditions with the Use of a Conductive-Convective Heat Transfer Model

This paper presents the results of numerical analysis of thermal regimes and heat losses of underground channel heating systems under flooding conditions with the use of a convective-conductive heat transfer model with the example of the configuration of the heat pipeline widely used in the Russian Federation — a nonpassage ferroconcrete channel (crawlway) and pipelines insulated with mineral wool and a protective covering layer. It has been shown that convective motion of water in the channel cavity of the heat pipeline under flooding conditions has no marked effect on the intensification of heat losses. It has been established that for the case under consideration, heat losses of the heat pipeline under flooding conditions increase from 0.75 to 52.39% due to the sharp increase in the effective thermal characteristics of the covering layer and the heat insulator caused by their moistening.

Design of MIMO K-Best Detection Algorithm And Its FPGA Implementation

Based on the research of MIMO Detection Algorithms theory and implementation methods, here novel k-Best MIMO detection algorithm is presented. Proposed algorithm uses an estimate technique and parallel sort approaches, which reduces the computational difficulty, and adopts pipelined configuration in parallel to save computation time. This algorithm implemented on Xilinx virtex-6. Implementation of proposed k-best multiple input multiple output detection algorithm on Field Programmable Gate Array is a challenging task by considering area and power. Computational complexity and resource utilization of this algorithm is discussed by implementing it on Virtex Field Programmable Gate Array. Field Programmable Gate Array implementation attained a good trade-off between power and area compared to the previous designs. Because of pipelined design and sorting procedure it is well suited for FPGA implementation and achieved 2.8 Gbps throughput for 64QAM modulation scheme with 4x4 systems. The flexibility of the scheme permits the high performance detection with low power consumption.

Leak Detection in Waterworks: Comparison Between STFT and FFT with an Overcoming of Limitations

AbstractDetection of leakages in pipelines is a matter of continuous research because of the basic importance for a waterworks system is finding the point of the pipeline where a leak is located and − in some cases − a nature of the leak. There are specific difficulties in finding leaks by using spectral analysis techniques like FFT (Fast Fourier Transform), STFT (Short Term Fourier Transform), etc. These difficulties arise especially in complicated pipeline configurations, e.g. a zigzag one. This research focuses on the results of a new algorithm based on FFT and comparing them with a developed STFT technique. Even if other techniques are used, they are costly and difficult to be managed. Moreover, a constraint in the leak detection is the pipeline diameter because it influences accuracy of the adopted algorithm. FFT and STFT are not fully adequate for complex configurations dealt with in this paper, since they produce ill-posed problems with an increasing uncertainty. Therefore, an improved Tikhonov technique has been implemented to reinforce FFT and STFT for complex configurations of pipelines. Hence, the proposed algorithm overcomes the aforementioned difficulties due to applying a linear algebraic approach.