Path Tracing Method Research Articles

Efficient participating media rendering with differentiable regularization

Highly scattering media, such as milk, skin, and clouds, are common in the real world. Rendering participating media is challenging, especially for high-order scattering dominant media, because the light may undergo a large number of scattering events before leaving the surface. Monte Carlo-based methods typically require a long time to produce noise-free results. Based on the observation that low-albedo media contain less noise than high-albedo media, we propose reducing the variance of the rendered results using differentiable regularization. We first render an image with low-albedo participating media together with the gradient with respect to the albedo, and then predict the final rendered image with a low-albedo image and gradient image via a novel prediction function. To achieve high quality, we also consider the gradients of neighboring frames to provide a noise-free gradient image. Ultimately, our method can produce results with much less overall error than equal-time path tracing methods.

Learning subsurface scattering solutions of tightly-packed granular media using optimal transport

Many materials, such as sand, rice, wheat, or other kinds of seeds, consist of numerous individual grains that determine the visual appearance of these materials. When generating images of these mixtures, the primary challenge is to simulate the interaction of light with each individual grain. While subsurface scattering effects are crucial for producing realistic images, the computation of light transport using standard path tracing methods for each grain can be prohibitively expensive. Although there have been several methods developed to address this issue, they all assume that bounding spheres of individual grains do not intersect. This restriction limits the application of these methods to almost spherical grains. Nonetheless, various grains, such as seeds and rice, are non-spherical, making this assumption lead to impractical stackings in situations involving coarse-grained materials. We address this issue by presenting a subsurface scattering model that utilizes a neural network and is trained using an optimal transport framework. Our model surpasses path tracing approaches conclusively, allowing for efficient rendering of granular mixtures that were previously unfeasible. Additionally, this method can be utilized in large-scale procedural generated scenes based on sphere packings and obtains similar results as previous methods in these cases.

Comparison of fast daylighting climate-based simulation methods for parametric design: two-phase, three-phase method and path tracing

ABSTRACT Computer modeling and simulation are essential for predicting architectural solutions performance. When integrated into the design process; they are known as performance-based design. During the design process, fast analytical cycles are required. However, daylighting simulations are challenging due to computational processing and time requirements. This paper presents a comparative study of fast daylight simulation methods, two-phase, three-phase and path tracing, in a hypothetical commercial building located in Miami, Florida. Five types of static glass and one electrochromic glass were tested with six parametric models of a translucent horizontal shading device. Daysim was used as reference. The two-phase method produced results similar to the reference results with faster processing times for static facades. For dynamic facades, the path tracing method with the tested interface enabled faster simulations and parametric variations. However, the three-phase method yielded a lower average error.

Survey on NLOS Identification and Error Mitigation for UWB Indoor Positioning

Ultra-wideband (UWB) positioning systems often operate in a non-line-of-sight (NLOS) environment. NLOS propagation has become the main source of ultra-wideband indoor positioning errors. As such, how to identify and correct NLOS errors has become a key problem that must be solved in high-accuracy indoor positioning technology. This paper firstly describes the influence of the NLOS propagation path on localization accuracy and the generation method of ultra-wideband signals, and secondly classifies and analyzes the currently available algorithms for ultra-wideband non-line-of-sight (NLOS) identification and error suppression. For the identification of NLOS, the residual analysis judgement method, statistical feature class identification method, machine learning method and geometric feature judgement method are discussed. For the suppression of NLOS propagation errors, weighting-based methods, filtering-based methods, line-of-sight reconstruction algorithms, neural network algorithms, optimization methods with constraints, and path tracing methods are discussed. Finally, we conclude the paper and point out the problems that need to be solved in NLOS indoor positioning.

PATH-TRACING SEMANTIC NETWORKS TO INTERPRET CHANGES IN SEMANTIC 3D CITY MODELS

Abstract. Recent years have seen a significant and rapid rise in the development and deployment of many urban digital twins worldwide. Urban digital twins provide a central platform for incorporating data and knowledge from different sources and fields, and can thus be used for many urban-related processes such as urban planning, analysis, monitoring and visualization. One of the key requirements of digital twins in general and urban digital twins in particular is the continuous, bidirectional data flow between the physical entity and its digital counterpart. Consequently, this requires the ability to both detect and understand changes between different temporal versions of the physical and digital entities. In the context of smart cities and semantic 3D city models however, only a few studies have addressed this so far. This is due to the facts that: (1) Semantic 3D city models (mostly encoded in CityGML) contain multifaceted information modelled in a complex inheritance hierarchy, which complicates their change detection process; (2) As cities constantly evolve over time, matching their datasets often results in a large number of changes, which must be further analysed and processed to produce meaningful information; (3) Individual changes in the datasets are multi-layered as well as often correlated and cannot be fully understood without considering their context in the city model; and (4) Different types of changes are perceived and interpreted differently by different stakeholders, meaning that the outcome of the change detection and interpretation process must ultimately serve the human factor. Therefore, to address these challenges, this research proposes a Path-tracing Semantic Network (PSN) to interpret detected changes in semantic 3D city models. The framework represents the multidimensional nature of changes together with stakeholders in a semantic network, where their interrelations can be analysed explicitly using graph-based path-tracing methods.

Optimizing the Price of Electrical Energy Transactions on the Microgrid System Using the Shortest Path Solution

Microgrid networks that reduce greenhouse gas emissions have increased electrical energy. In electrical energy transactions, a strategy is needed to create the lowest electricity sales price optimization for consumers. Currently, optimizing the price of electricity transactions is a challenge because few still discuss offering the cheapest electricity prices. In the wheeling System Transaction (shared use of utility-owned electricity networks), optimizing the price of electrical energy transactions is still a challenge that must be resolved. This is because there is no algorithm developed to solve this problem. This research will develop an algorithm to optimize electricity price sales using the shortest path and Power Flow Tracing methods. Developing the shortest path algorithm can provide recommendations for each area that conducts electrical energy transactions. Then, electrical energy transactions are determined based on the lowest price, the most negligible loss, and the shortest distance to get the optimal price.

Propagation path tracing of hydraulically created fractures based on microseismic monitoring

To evaluate the effect of hydraulic fracturing in a low-permeability reservoir, a propagation path tracing method for hydraulically created fractures was established based on microseismic monitoring data. First, the numerical simulation of the wave propagation process, grid search, and error-weight coefficient method was combined to locate the microseismic source. Then, the moment tensor inversion method was used to determine the tensile angle and source mechanism of hydraulically created fractures. Next, the tensile angle was used as the weight-index to determine the size of the mixed-source mechanism fracture combined with the shear and tensile source size quantization model. Finally, the spatial topological relationship between fractures was determined by comprehensively considering the spatial location and radius of the fractures, to realize the propagation path tracing of hydraulically created fractures. These tracking results can be used as one of the bases for the evaluation of the hydraulic fracturing effect.

Reliability measures of a non‐series parallel system of (m, nc${n_c}$, l) order with Weibull Failure Laws

AbstractHere, a non series‐parallel system of (m, , l) order is developed by introducing “l” additional components linked to arbitrary non‐adjacent and components of “m” parallel subsystems each containing components connected in series. The maximum number of effective duplication paths between IN and OUT terminals is formed using Logic Diagram Technique (LDT). Each path contains components whose successful operation can lead to successful operation of the system. The superior paths are discarded keeping in view of the fact that these paths have no effect on reliability of the system. The Path Tracing Method (PTM) is used to derive expressions for reliability and mean time to system failure (MTSF) by considering Weibull failure laws for the components. An illustration is given to highlight the application of the present study. The behavior of reliability of the system has been shown numerically and graphically for arbitrary values of the scale parameter (λ), shape parameter (β), number of additional components (l), scale parameter of additional component (), and shape parameter of additionalcomponent ( and operating time t = 5.

Path Tracing Method to Evaluate the Signature Reliability Function of a Complex System

This paper aims to compute the efficiency of a complex communication system (double-bridge). In this model, which applies the Path Tracing Method for evaluating the reliability function of the complex communication system, the process of analyzing the system’s reliability has been used to lower the failure rate of the complex system in order to optimize its competence. The illustrative system is subdivided into nine minimal paths that are arranged in series-parallel combinations. Using the Path Tracing Method, the system’s reliability, minimal signature, tail signature, signature, Barlow–Proschan index, expected time, expected cost, and sensitivity were determined. The results assist in the creation of a probabilistic approach to analyze and probabilistic method to evaluate the system signature and reliability in a way that is highly useful.

Accurate and fast simulation of remote sensing images at top of atmosphere with DART-Lux

DART model is one of the most comprehensive and accurate radiative transfer (RT) models to simulate remotely sensed signals in the Earth-atmosphere system. Its standard RT modelling mode, called DART-FT, relies on the discrete ordinates method. Its recently developed Monte Carlo mode using an unbiased bidirectional path tracing method, called DART-Lux, increases hundredfold DART efficiency to simulate images. Since DART-Lux does not simulate yet atmospheric RT, a hybrid method has been designed to accurately and fast simulate remote sensing images at top of atmosphere (TOA). It couples the atmospheric RT modelling of DART-FT with the very efficient Earth surface RT modelling of DART-Lux. For that, a new sky light modelling, an innovative BRF camera modelling and an adapted radiative coupling framework have been designed. The efficiency and accuracy of this hybrid method have been validated using DART-FT as a reference. Here, we present this validation for a realistic forest stand. Simulation time is reduced by a factor of 750 with a relative difference of solar plane reflectance factor smaller than 1%. This hybrid method opens new perspectives for the use of 3D modelling in remote sensing applications. It is already part of the DART version freely available for scientists (https://dart.omp.eu).

Assessment of availability of street light system: A study of Warri, Delta State, Nigeria

The study computes the availability of street lighting system in Warri. This system under study consists of subsystems that are known as workstations. A generator and sets of street light make up a workstation. The power source and the street lighting were modeled into series and parallel combinations. Reliability Block Diagrams and Path Tracing Method were employed assuming independent failure of the components. The availability of the set of street lightings, workstations and hence the availability of the system were determined. Results of the study show that users in Cemetery road had the least availability of 62.19% for the period. The implication is that users travelling along this road experienced wide variation of light that could lead to accidents.
 Keywords: Availability, Street Lighting and Reliability block diagram

Cinematic Rendering Technique in Adult Congenital Heart Disease

Abstract Cinematic rendering (CR) is a recently introduced 3D-visualization technique that generates photorealistic images with higher depth and shape perception than volume rendering (VR). In CR, each pixel of the rendering is generated by integration of the light scattered in all the directions along the primary light ray beam using a path-tracing method. CR has several potential applications in adult congenital heart disease (ACHD), particularly in the characterization of complex anomalies, assessment of relationship to adjacent structures and education. In this article, we review the principles of CR, compare it with VR and illustrate the applications in ACHD.

Epigenome-Wide Tobacco-Related Methylation Signature Identification and Their Multilevel Regulatory Network Inference for Lung Adenocarcinoma.

Tobacco exposure is one of the major risks for the initiation and progress of lung cancer. The exact corresponding mechanisms, however, are mainly unknown. Recently, a growing body of evidence has been collected supporting the involvement of DNA methylation in the regulation of gene expression in cancer cells. The identification of tobacco-related signature methylation probes and the analysis of their regulatory networks at different molecular levels may be of a great help for understanding tobacco-related tumorigenesis. Three independent lung adenocarcinoma (LUAD) datasets were used to train and validate the tobacco exposure pattern classification model. A deep selecting method was proposed and used to identify methylation signature probes from hundreds of thousands of the whole epigenome probes. Then, BIMC (biweight midcorrelation coefficient) algorithm, SRC (Spearman's rank correlation) analysis, and shortest path tracing method were explored to identify associated genes at gene regulation level and protein-protein interaction level, respectively. Afterwards, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis and GO (Gene Ontology) enrichment analysis were used to analyze their molecular functions and associated pathways. 105 probes were identified as tobacco-related DNA methylation signatures. They belong to 95 genes which are involved in hsa04512, hsa04151, and other important pathways. At gene regulation level, 33 genes are uncovered to be highly related to signature probes by both BIMC and SRC methods. Among them, FARSB and other eight genes were uncovered as Hub genes in the gene regulatory network. Meanwhile, the PPI network about these 33 genes showed that MAGOH, FYN, and other five genes were the most connected core genes among them. These analysis results may provide clues for a clear biological interpretation in the molecular mechanism of tumorigenesis. Moreover, the identified signature probes may serve as potential drug targets for the precision medicine of LUAD.

Advances in gene ontology utilization improve statistical power of annotation enrichment.

Gene-annotation enrichment is a common method for utilizing ontology-based annotations in gene and gene-product centric knowledgebases. Effective utilization of these annotations requires inferring semantic linkages by tracing paths through edges in the ontological graph, referred to as relations. However, some relations are semantically problematic with respect to scope, necessitating their omission or modification lest erroneous term mappings occur. To address these issues, we created the Gene Ontology Categorization Suite, or GOcats—a novel tool that organizes the Gene Ontology into subgraphs representing user-defined concepts, while ensuring that all appropriate relations are congruent with respect to scoping semantics. Here, we demonstrate the improvements in annotation enrichment by re-interpreting edges that would otherwise be omitted by traditional ancestor path-tracing methods. Specifically, we show that GOcats’ unique handling of relations improves enrichment over conventional methods in the analysis of two different gene-expression datasets: a breast cancer microarray dataset and several horse cartilage development RNAseq datasets. With the breast cancer microarray dataset, we observed significant improvement (one-sided binomial test p-value = 1.86E-25) in 182 of 217 significantly enriched GO terms identified from the conventional path traversal method when GOcats’ path traversal was used. We also found new significantly enriched terms using GOcats, whose biological relevancy has been experimentally demonstrated elsewhere. Likewise, on the horse RNAseq datasets, we observed a significant improvement in GO term enrichment when using GOcat’s path traversal: one-sided binomial test p-values range from 1.32E-03 to 2.58E-44.

Real-time optical 3D reconstruction based on Monte Carlo integration and recurrent CNNs denoising with the 3D light field display.

A general integral imaging generation method based on the path-traced Monte Carlo (MC) method and recurrent convolutional neural networks denoising is presented. According to the optical layer structure of the three-dimensional (3D) light field display, screen pixels are encoded to specific viewpoints, then the directional rays are cast from viewpoints to screen pixels to preform the path integral. In the process of the integral, advanced illumination is used for high-quality elemental image array (EIA) generation. Recurrent convolutional neural networks are implemented as an auxiliary post-processing for the EIA to eliminate the noise of the 3D image in MC integration. 4K (3840 × 2160) resolution, 2 sample/pixel and the ray path tracing method are realized in the experiment. Experimental results demonstrate that the structural similarity metric (SSIM) value and peak signal-to-noise ratio (PSNR) gain of the reconstructed 3D image and target 3D image exceed 90% and 10 dB within 10 frames, respectively. Besides, real-time frame rate is more than 30 fps, showing the super efficiency and quality in optical 3D reconstruction.

Methodology of Robust Optimal Design of the Multistage Axial Compressor on the Basis of Discrete Analogue-Related Data

Consideration was given to the formulation and methodology of the direct nonlinear design problem of structural dimensional circuits in conditions of a priori parametric uncertainty. It was shown that the solution of the direct nonlinear design problem of structural dimensional circuits can be reduced to the multicriteria problems of stochastic optimization with mixed conditions. Mathematical models and methods of the solution of multicriteria problems of stochastic optimization with mixed conditions were analyzed. A.N. Tikhonov method of the regulation of solution of incorrectly formulated problems was used as a computation method for the synthesis of quasi-solutions of incorrectly formulated problems. An effective memetic algorithm for the synthesis of the solutions of MV-problems was suggested. It is based on the genetic algorithm combined with the randomized path tracing method. The suggested methodology allows us to search for rational solutions of the multicriteria problems of system modification through the creation of hierarchic two-level scheme for the synthesis of solutions that includes the construction of robust surrogate models of the systems and processes with subsequent robust estimation of sought values for the parametric data uncertainty. As an example, we obtained the solution data for the problem of robust optimal design of two-stage axial compressor in conditions of a stochastic nature of the input data obtained using the interactive decision support computer system «Concept_Pro_St ® ».

LESS: LargE-Scale remote sensing data and image simulation framework over heterogeneous 3D scenes

Three-dimensional (3D) radiative transfer modeling of the transport and interaction of radiation through earth surfaces is challenging due to the complexity of the landscapes as well as the intensive computational cost of 3D radiative transfer simulations. To reduce computation time, current models work with schematic landscapes or with small-scale realistic scenes. The computer graphics community provides the most accurate and efficient models (known as renderers) but they were not designed specifically for performing scientific radiative transfer simulations. In this study, we propose LESS, a new 3D radiative transfer modeling framework. LESS employs a weighted forward photon tracing method to simulate multispectral bidirectional reflectance factor (BRF) or flux-related data (e.g., downwelling radiation) and a backward path tracing method to generate sensor images (e.g., fisheye images) or large-scale (e.g. 1 km2) spectral images. The backward path tracing also has been extended to simulate thermal infrared radiation by using an on-the-fly computation of the sunlit and shaded scene components. This framework is achieved through the development of a user-friendly graphic user interface (GUI) and a set of tools to help construct the landscape and set parameters. The accuracy of LESS is evaluated with other models as well as field measurements in terms of directional BRFs and pixel-wise simulated image comparisons, which shows very good agreement. LESS has the potential in simulating datasets of realistically reconstructed landscapes. Such simulated datasets can be used as benchmarks for various applications in remote sensing, forestry investigation and photogrammetry.

Gateway selection and clustering in multi‐interface wireless mesh networks considering network reliability and traffic

AbstractThis work considers the gateway selection and clustering problem in a multi‐interface wireless mesh network. The evolved reliability and traffic‐aware gateway selection scheme is here introduced to increase the performance in terms of throughput. There are 2 main phases in the proposed idea. In the first step, some Internet Gateway Candidates are selected from the mesh nodes in the network, based on the network traffic. Then, in the second step, using the path tracing method, the best of these candidates are selected as Internet gateways. Moreover, to decrease the network energy consumption, a refined evolved reliability and traffic‐aware gateway selection scheme is also proposed whose effect in simulation is shown. A clustering method is later proposed exploiting the genetic algorithm to give priority to the nodes with the shortest hop to connect to the cluster head. Simulation results demonstrate how our gateway selection and clustering scheme outperforms 2 successful approaches in terms of throughput and network energy consumption.

Aether

Implementing Monte Carlo integration requires significant domain expertise. While simple samplers, such as unidirectional path tracing, are relatively forgiving, more complex algorithms, such as bidirectional path tracing or Metropolis methods, are notoriously difficult to implement correctly. We propose Aether, an embedded domain specific language for Monte Carlo integration, which offers primitives for writing concise and correct-by-construction sampling and probability code. The user is tasked with writing sampling code, while our compiler automatically generates the code necessary for evaluating PDFs as well as the book keeping and combination of multiple sampling strategies. Our language focuses on ease of implementation for rapid exploration, at the cost of run time performance. We demonstrate the effectiveness of the language by implementing several challenging rendering algorithms as well as a new algorithm, which would otherwise be prohibitively difficult.

A Novel Reliability and Traffic Aware Gateway Selection Scheme in Wireless Mesh Networks

The increase in the users’ demand has led to massive success of wireless technology during the last two decades. Wireless mesh networks are a booming technology which have developed and grabbed attention significantly. In this paper, the problem of Internet Gateway (IGW) selection is addressed with regard to network traffic and reliability of routes and a Reliability and Traffic aware Gateway Selection scheme is proposed. To the best of our knowledge, no work in the literature has considered the impact of reliability of routes on the selection of gateways in their scenarios. Given the number of mesh nodes in the network, some Internet Gateway Candidates are selected regarding the traffic in the network. Then, the best of these candidates are selected to be equipped with gateway functionality taking into consideration of the path-tracing method. Simulation results demonstrate how our novel mechanism outperforms two successful approaches in IGW selection in terms of throughput, delay and network energy consumption.