Graphical Modeling Research Articles

Deep probabilistic graphical modeling for robust multivariate time series anomaly detection with missing data

Multivariate time series anomaly detection with missing data is one of the most pending issues for industrial monitoring. Due to scarcity of labeled anomalies, most advanced data-driven anomaly detection approaches fall in the unsupervised learning paradigm. As a premise in the presence of missing data, one needs to improve the data quality through data imputation with a separate model. Our concern lies in the consistency between data imputation and unsupervised learning for robust anomaly detection, regarding accurately discovering the spatiotemporal dependence among multiple variables over time. However, the existing practice tends to overlook this consistency and decouple the training process for these two closely linked tasks. This article novelly proposes a probabilistic multivariate time series anomaly detection framework that unifies data imputation and unsupervised learning. A deep probabilistic graphical model abbreviated SCNF is first devised for unsupervised density estimation. A tailored expectation maximization-based optimization scheme is then developed to achieve the joint training of data imputation and unsupervised learning with missing data. The efficacy is experimentally corroborated in several industrial applications, including chemical process, water treatment and network traffic. Briefly, the joint training framework enhances the AUROC of SCNF by averagely 6.34% for three applications under 50% data missing rate.

The Impact of the War on the Economic and Legal Environment of the Regions in terms of Ensuring National Security

The main objective of the article was to study the impact of the war on the economic and legal environment of the Ukrainian regions in terms of ensuring national security. The research methodology involves the use of modern methods of graphical modeling. The scope of study was the system of economic and legal relations that emerged in the course of hostilities. With the outbreak of hostilities, there are certain legal consequences for the belligerents: diplomatic and consular relations are terminated; economic, commercial, monetary and other business and agreements with legal and natural persons of Russia are terminated and prohibited, as a special regime can be applied to citizens of a hostile state; the declaration of a state of war leads to a change in the legal regime of the territories. However, most armed conflicts are not accompanied by a legal declaration of a state of war, which, nevertheless, introduces significant changes in the legal relations of the parties. Accordingly, the key aspects of the impact of war on the economic and legal environment in terms of security guarantees were characterized.

Modeling of Coke Distribution in a Dry Quenching Zone.

Herein, a method for the coke dry quenching (CDQ) process has been proposed and its optimization has been carried out, which will minimize the disadvantages of this process. This optimization was carried out to develop a technology for uniform coke distribution in the quenching chamber. A model of the real charging device for quenching coke from the Ukrainian enterprise PrJSC "Avdiivka Coke" was developed, and several shortcomings of its operation were shown. It is proposed to use a coke distributor in the form of a bell and a modified bell (specially shaped holes). Graphic mathematical models of the operation of these two devices were developed, and the efficiency of the last of the developed distributors was shown.

Investigating anabolic-androgenic steroid dependence and muscle dysmorphia with network analysis among male weightlifters

BackgroundAnabolic-androgenic steroid (AAS) dependence has numerous adverse health consequences, and may be driven in part by body image concerns, primarily muscle dysmorphia. This study aims to further understand and identify potential clinical targets using network analyses of AAS dependence and muscle dysmorphia symptoms in males who used AAS and weightlifting controls.MethodsA sample of 153 men who currently or previously used AAS and 88 weight-lifting controls were recruited through social media and relevant online forums, and via posters and flyers distributed in select gyms in Oslo, Norway. Symptoms of AAS dependence and muscle dysmorphia were assessed using clinical interviews and standardized questionnaires. Severity of muscle dysmorphia symptoms were compared between the groups using independent samples t-tests. The following symptom networks were computed using Gaussian graphical modeling or mixed graphical modeling: (1) AAS dependence symptoms among men with AAS use (2) muscle dysmorphia symptoms among men with AAS use and weight-lifting controls in two separate networks, which were compared using a network comparison test, and (3) AAS dependence and muscle dysmorphia symptoms among men with AAS use.ResultsIn a network of AAS dependence symptoms, continuing use despite physical and mental side effects, using longer than planned, tolerance, and work/life interference were the most central symptoms. When comparing symptom structures of muscle dysmorphia between those who used AAS and controls, the most central symptoms in each group were exercise dependence and size/symmetry concerns, respectively. Men with AAS use demonstrated elevated muscle dysmorphia symptoms compared to controls, indicating that both the severity and structure of symptoms differ between these groups. In a network including both AAS dependence and muscle dysmorphia symptoms, no significant connections between symptom groups were identified.ConclusionsAAS dependence is complex, with correlated somatic and psychological challenges driving the symptom network, indicating that alleviating physical and mental health concerns during both AAS use and cessation is an important clinical target. Muscle dysmorphia symptoms related to taking action (diet, exercise, and supplement use) appear to cluster together more for those who use AAS than those who do not.

An Optimization Method for CNC Laser Combination Cutting of Irregular Plate Remainders

The key research question in this study is how to cut pieces in irregular plate remainders, because there are many irregular plate leftovers created during the CNC (Computer Numerical Control) process. This will increase material utilization and allow plate leftovers to be reused. One of the issues being researched is how to arrange plate remainders on the surface of the CNC machine; this issue is known as combination layout optimization. The other issue being researched is combination cutting-path optimization of plate remainders, which aims to determine the cutting path of parts of plate remainders. A genetic algorithm based on the gravity-center NFP (No-Fit Polygon) method was applied to optimize the layout pattern, and then the geometric coordinates of a part included in one plate remainder after packing were obtained by geometric transformation with the help of a three-layer graphic data correlation model, which quickly identified the inside and outside contours of parts. A colony algorithm based on the mathematical model of cutting-path optimization was used to optimize the cutting path of the parts in the plate remainders. Finally, some simulation tests were performed to illustrate the feasibility and effectiveness of the proposed method. The results of the algorithm for packing irregular shapes for some instances show that our algorithm outperforms the other algorithms. On most instances, the average plate utilization ratio using our algorithm, after running 20 times, is improved by 1% to 9% in comparison to the best plate utilization ratio using the tree search algorithm. The best idle travel of an example achieved by the algorithm in this paper is 7632 mm after running the cutting-path optimization algorithm 20 times, while that of the traditional equivalent TSP (Traveling Salesman Problem) algorithm is 11,625 mm, which significantly demonstrates the efficiency of the algorithm.

South American terrestrial biomes as geocomplexes: a geobotanical landscape approach

The classic and current perception of biome in its various meanings is fundamentally based on vegetation types that are considered as discrete or independent and fragmented entities in the landscape. Vegetation units are characterized by their physiognomy, which is based on the dominant life forms and mainly determined by climatic conditions. However, vegetation units are associated and mutually interacting at a landscape level. They are determined by local or regional, climatic, topographic and edaphic gradients within a given territory or geographic area. In this work, we propose a new conceptual and methodological approach aiming to better understand the biome concept in a landscape framework, developing ideas already partially advanced by us. In this sense, we consider the biome as a landscape complex (geocomplex), that spatially includes one to several vegetation geoseries which, in turn, each comprise the following possible geomorphologically linked vegetation series: i) the potential natural climatophilic vegetation (zonal vegetation) and their seral successional stages which occur repeatedly in the landscape; ii) edapho-xerophyllous vegetation (azonal vegetation such as occurs on rocky outcrops or sandy soils); and iii) edapho-hygrophilic vegetation (azonal vegetation such as flooded vegetation on river banks). Based on surveys and field data (more than ca. 300 transects) obtained by the authors in most South American countries from 1990 to the present, 33 South American geocomplex biomes and 16 macrobiomes were identified and synoptically characterized, through graphic general zonation models (phyto-topographic type-profiles) extrapolated from numerous observations along representative bioclimatical, geomorphological and biogeographically stratified transects. Field data and transect-plots are currently being processed to be included into the “GIVD database”. Taxonomic reference: Tropicos.org, Missouri Botanical Garden (https://tropicos.org) [accessed 1 Feb 2023]. In Memoriam: Salvador Rivas-Martínez

Design of Graphic Concept Model for Specialty Coffee Packaging Labels

There are still many micro-business actors who package their products with the appearance of less attractive packaging. However, it is not easy for micro-business actors to create product packaging ideas that is able to be accepted by the broad market. This study aimed to determine the attributes of packaging labels, determine the most influential graphic elements, and generate tone and manner for label specialty coffee packaging. Label attribute was analyzed with FAST and Pairwise Comparison methods. The graphic element was analyzed with the QFD method. The visual perception was analyzed with the Mind Mapping method quantified by the PCA method. It was concluded that experts expect more product information clarity and the impression of premium products on coffee packaging labels. In addition, experts also expect convenience in reading the information needed on packaging labels. Based on graphic element analysis, the priorities of the graphic element of packaging were 1) identity of the coffee product; 2) text hierarchy; 3) color labels; and 4) typical label style. The must-have tone and manner for specialty coffee packaging labels were familiar (friendly), premium, simple, and special.

Graphical causal modelling: an application to identify and estimate cause-and-effect relationships

ABSTRACT This paper offers an accessible discussion of graphical causal models and how such a framework can be used to help identify causal relations. A graphical causal model represents a researcher’s qualitative assumptions. As a result of the credibility revolution, there is growing interest to properly estimate cause-and-effect relationships. Using several examples, we illustrate how graphical models can and cannot be used to identify causation from observational data. Further, we offer a replication of a previous study that explored college enrolment by high school seniors who were eligible for student aid. From the original study, we use a graphical causal model to motivate the quantitative and qualitative modelling assumptions. Using a similar difference-in-difference approach based on propensity score matching, we estimate a smaller average treatment effect than the original study. The smaller estimated effect arguably stems from the graphical causal model’s delineation of the original model specification.

Neurosymbolic Models for Computer Graphics

AbstractProcedural models (i.e. symbolic programs that output visual data) are a historically‐popular method for representing graphics content: vegetation, buildings, textures, etc. They offer many advantages: interpretable design parameters, stochastic variations, high‐quality outputs, compact representation, and more. But they also have some limitations, such as the difficulty of authoring a procedural model from scratch. More recently, AI‐based methods, and especially neural networks, have become popular for creating graphic content. These techniques allow users to directly specify desired properties of the artifact they want to create (via examples, constraints, or objectives), while a search, optimization, or learning algorithm takes care of the details. However, this ease of use comes at a cost, as it's often hard to interpret or manipulate these representations. In this state‐of‐the‐art report, we summarize research on neurosymbolic models in computer graphics: methods that combine the strengths of both AI and symbolic programs to represent, generate, and manipulate visual data. We survey recent work applying these techniques to represent 2D shapes, 3D shapes, and materials & textures. Along the way, we situate each prior work in a unified design space for neurosymbolic models, which helps reveal underexplored areas and opportunities for future research.

AWL-GCN: Branch Parameter Identification Considering Grid Spatial Structure Constraints

Parameter identification plays an important role in power system. The existing parameter identification methods usually have two limitations: (1) The existing methods only consider the information of single branch and ignore the influence of adjacent branch information, and do not effectively use the topological structure constraints of the power grid. (2) The measurement data has the problems of poor numerical stability, numerical divergence and noise interference. Data contamination has become an important factor restricting the prediction accuracy of branch parameters. In order to solve these problems, this work proposes an Automatic Weighted Loss-Graph Convolution Networks model combined with the spatial structure of power grid. Based on the graphical modeling, the correlation between power grid branches is effectively used, and the adjacent branches are used to provide more effective information for the parameter identification of a branch, which improves the identification accuracy. In addition, the model enhances the local characteristics through the power grid structure information constraints, realizes the local optimal fitting, and constructs a self tradeoff loss function to weaken the impact of pollution data (data noise and data loss) on the model. The test results show that compared with the traditional method, this method has higher accuracy and stronger robustness.

QPEC: QGIS Toolkit for Evaluating Geospatial Data Positional Accuracy according to the Brazilian Cartographic Accuracy Standard

This paper presents the development of a QGIS plugin to support evaluating the planimetric positional quality for point and linear features based on the metrics established by Brazilian legislation. For this purpose, we used the QGIS environment Graphical Modeler, which consists of an interface to concatenate a series of processes into a single algorithm. The set of tools, called QPEC, allows for performing the statistical tests from the automatic identification of the sample size and discrepancies. In order to demonstrate the implemented functionalities, a case study was carried out. In this illustrative example, the vector files from the Cartographic and Cadastral System of the Municipality of Salvador - BA (SICAD) were the reference data, and their homologous OpenStreetMap (OSM) features were the analysed database. The results obtained are presented in the attributes table. In addition, the spatial distribution of the discrepancies is visualised through the visual variable colour value in a quartile classification. The creation of this toolset corroborates the feasibility of developing more visual, automated and complete interfaces to support users of geospatial data in analysing the quality of the information available, especially when it involves free applications with open-source code.

ANALISIS FAKTOR PENYEBAB KETERLAMBATAN PENYELESAIAN PADA PROYEK PEMBANGUNAN APARTEMEN URBAN SIGNATURE CIRACAS

The delay in completion of construction that has exceeded the work time target according to the initial agreement is very powerful on the construction project itself. Delays in the project occur due to problems that arise in terms of materials, labor, costs, equipment, environment, and others. In this research, an analysis was carried out on what factors were the cause of the delay in the completion of the superstructure and the rating of the value of the reliability function of each work. The Fault Tree Analysis (FTA) approach would be employed, which is a method that makes use of fault tree analysis in the form of a graphic model based on the outcomes of conducted interviews. In the graphic model, there were several event symbols and logic gate symbols to connect the event symbols. On the graphic model, the simplest cut set was acquired using Boolean algebra and the Method of Obtain Cut Set (MOCUS). Based on the results of the analysis, there were 33 basic events or jobs that experienced delays, including changes in rebar supply by the Owner, limited human resources, a lot of repair work, evaluation of the project schedule, SILO SIO PH licensing, late payments, delays in material delivery, and others. Typical structural work and ladder structures, the Boolean algebra law can be applied because it has a repeating code. Meanwhile, on the roof of the engine room, the law of algebra cannot be applied since the work does not have a repeating code. The reliability function is calculated in the analysis that follows. When all three variables are accurate, the system operates as intended.

Development of an adaptive graphic web interface model for editing XML data

The ability of the end user to work with a large amount of data from a large number of heterogeneous sources and at the same time get an effective result from the work is carried out through the use of graphical web interfaces built on the basis of XML technologies that allow displaying any structure of a file presented in XML format. As a data exchange method between applications on the Web, XML still lacks capabilities for identification of web resources and a system that uses them, and capabilities to express the knowledge provided by XLM documents. In this study, a web interface has been developed (a web-based server application), as an XML records editor that provides display forms for the creation and editing of XML documents and is able to adapt to the internal resources of the system used. The technology is based on the XSD data set schema transformation by the way of XSLT transformations. Screen forms are generated on the server side and are provided to the user with all the necessary tools for correct input and/or editing of heterogeneous data. A distinguishing characteristic of this technology is the ability to display both properly and improperly formed XML data. The developed graphical interface allows any application to automatically exchange and read information from other applications without human intervention, which significantly improves performance and ease of use. This software solution could be used both as an independent data building and editing module presented in the XML format, and as a built-in module plugged into various server software for heterogeneous information management systems

Light attenuation analysis based on integral equations

The shadowing and masking of a rough surface is an important problem for reflection models in computer graphics. The widely used Smith’s geometry attenuation factor (GAF) takes a few factors such as root-mean-square (rms) into account and makes too many assumptions. In our research, we construct a brand-new calculation technique for issues involving light attenuation on a rough surface. The GAF algorithm is derived from a scattering field based on integral equations and the computational electromagnetic method. Specifically, our use of the method of moments has enabled us to tackle the problem of analytically computing the shadowing and masking on a rough surface by taking practical factors such as wavelength, surface contour, polarization, material, rms, and so on into consideration. It is more precise than Smith’s GAF theory.

Rehabilitation of rowing athletes during the formation of respiratory rhythms in course of bone tissue prosthetics

Athletes who are engaged in rowing are subject to a number of occupational health problems that require not only long-term rehabilitation, but also long-term recovery. The aspect of the restoration of disturbed breathing rhythms and the activity of the cardiovascular system is of particular relevance. Since disorders of the cardiovascular system usually take place when associated physical damage occurs, the issue of forming a model of medical intervention during operations and rehabilitation activities is of primary importance. The novelty of the study is determined by the fact that the formation of a system of rehabilitation measures should be determined by the requirements for achievement of previously shown results. The authors determine the structure of the model, its practical application and the formation of a graphic model on its basis that will be used when replacing parts of the skeletal support. It was determined that this allows to form not only the stable functioning support, but also the respiratory systems, and thus lay the foundation for the athlete’s further physical rehabilitation for practical activities and return to sports. Practical significance of the subject matter is determined by the need to form adaptive potential, which will allow athletes to maintain positive dynamics of performances in the future at the level of international competitions.

A Multiverse Graph to Help Scientific Reasoning from Web Usage: Interpretable Patterns of Assessor Shifts in GRAPHYP

The digital support for scientific reasoning presents contrasting results. Bibliometric services are improving, but not academic assessment; no service for scholars relies on logs of web usage to base query strategies for relevance judgments (or assessor shifts). Our Scientific Knowledge Graph GRAPHYP innovates with interpretable patterns of web usage, providing scientific reasoning with conceptual fingerprints and helping identify eligible hypotheses. In a previous article, we showed how usage log data, in the form of ‘documentary tracks’, help determine distinct cognitive communities (called adversarial cliques) within sub-graphs. A typology of these documentary tracks through a triplet of measurements from logs (intensity, variety and attention) describes the potential approaches to a (research) question. GRAPHYP assists interpretation as a classifier, with possibilistic graphical modeling. This paper shows what this approach can bring to scientific reasoning; it involves visualizing complete interpretable pathways, in a multi-hop assessor shift, which users can then explore toward the ‘best possible solution’—the one that is most consistent with their hypotheses. Applying the Leibnizian paradigm of scientific reasoning, GRAPHYP highlights infinitesimal learning pathways, as a ‘multiverse’ geometric graph in modeling possible search strategies answering research questions.

Modular ontology modeling

Reusing ontologies for new purposes, or adapting them to new use-cases, is frequently difficult. In our experiences, we have found this to be the case for several reasons: (i) differing representational granularity in ontologies and in use-cases, (ii) lacking conceptual clarity in potentially reusable ontologies, (iii) lack and difficulty of adherence to good modeling principles, and (iv) a lack of reuse emphasis and process support available in ontology engineering tooling. In order to address these concerns, we have developed the Modular Ontology Modeling (MOMo) methodology, and its supporting tooling infrastructure, CoModIDE (the Comprehensive Modular Ontology IDE – “commodity”). MOMo builds on the established eXtreme Design methodology, and like it emphasizes modular development and design pattern reuse; but crucially adds the extensive use of graphical schema diagrams, and tooling that support them, as vehicles for knowledge elicitation from experts. In this paper, we present the MOMo workflow in detail, and describe several useful resources for executing it. In particular, we provide a thorough and rigorous evaluation of CoModIDE in its role of supporting the MOMo methodology’s graphical modeling paradigm. We find that CoModIDE significantly improves approachability of such a paradigm, and that it displays a high usability.

Efficacy of a Novel Augmented Reality Navigation System Using 3D Computer Graphic Modeling in Endoscopic Transsphenoidal Surgery for Sellar and Parasellar Tumors

In endoscopic transsphenoidal skull base surgery, knowledge of tumor location on imaging and the anatomic structures is required simultaneously. However, it is often difficult to accurately reconstruct the endoscopic vision of the surgical field from the pre-surgical radiographic images because the lesion remarkably displaces the geography of normal anatomic structures. We created a precise three-dimensional computer graphic model from preoperative radiographic data that was then superimposed on a visual image of the actual surgical field and displayed on a video monitor during endoscopic transsphenoidal surgery. We evaluated the efficacy of this augmented reality (AR) navigation system in 15 consecutive patients with sellar and parasellar tumors. The average score overall was 4.7 [95% confidence interval: 4.58-4.82], which indicates that the AR navigation system was as useful as or more useful than conventional navigation in certain patients. In two patients, AR navigation was assessed as less useful than conventional navigation because perception of the depth of the lesion was more difficult. The developed system was more useful than conventional navigation for facilitating an immediate three-dimensional understanding of the lesion and surrounding structures.

Direct and indirect viral associations predict coexistence in wild plant virus communities

Viruses are a vastly underestimated component of biodiversity that occur as diverse communities across hierarchical scales from the landscape level to individual hosts. The integration of community ecology with disease biology is a powerful, novel approach that can yield unprecedented insights into the abiotic and biotic drivers of pathogen community assembly. Here, we sampled wild plant populations to characterize and analyze the diversity and co-occurrence structure of within-host virus communities and their predictors. Our results show that these virus communities are characterized by diverse, non-random coinfections. Using a novel graphical network modeling framework, we demonstrate how environmental heterogeneity influences the network of virus taxa and how the virus co-occurrence patterns can be attributed to non-random, direct statistical virus-virus associations. Moreover, we show that environmental heterogeneity changed virus association networks, especially through their indirect effects. Our results highlight a previously underestimated mechanism of how environmental variability can influence disease risks by changing associations between viruses that are conditional on their environment.

GEOMETRIC SIMULATION OF THE MOVEMENT PROCESS OF THE EXCAVATOR’S MILLING WORKING EQUIPMENT

The simulation of the process of movement of the milling working equipment of an excavator when digging a pipeline is discussed. The parameters of the repair and construction strip are calculated, the position of the coordinate systems of the excavator manipulator mechanism is established. A hypothesis has been put forward that the position of the excavator on the strip affects the volume of movement during digging, which increases energy consumption and reduces economic efficiency. The excavator manipulator is considered as a five-link mechanism. A kinematic scheme of the mechanism is given, on the basis of which a program based on the synthesis of movements along the velocity vector is created. The construction of the movement trajectory was carried out in such a way, that the output link was in a horizontal position throughout the entire movement process. The program was created using the Visual Lisp programming language built into the AutoCAD environment. The program made it possible to obtain graphic models of the movement of the excavator manipulator mechanism in its various positions, as well as to calculate the amount of movement. Based on the data obtained, a drawing by Radishchev was constructed, which reflected the dependence of the generalized coordinates of the excavator manipulator mechanism and the amount of movement on the depth of lowering of the working equipment. As a result, it was concluded that with the middle position of the excavator on the traffic lane, a smaller amount of traffic is provided, which means less energy consumption and a higher speed of work. The results of the conducted research can be used in the design of software and hardware systems for controlling moving objects, in particular, control systems for the motion of an excavator manipulator.