Graphical Representation Of Model Research Articles

Towards a more accurate light transport model for non-line-of-sight imaging.

Non-line-of-sight (NLOS) imaging systems involve the measurement of an optical signal at a diffuse surface. A forward model encodes the physics of these measurements mathematically and can be inverted to generate a reconstruction of the hidden scene. Some existing NLOS imaging techniques rely on illuminating the diffuse surface and measuring the photon time of flight (ToF) of multi-bounce light paths. Alternatively, some methods depend on measuring high-frequency variations caused by shadows cast by occluders in the hidden scene. While forward models for ToF-NLOS and Shadow-NLOS have been developed separately, there has been limited work on unifying these two imaging modalities. Dove et al introduced a unified mathematical framework capable of modeling both imaging techniques [Opt. Express27, 18016 (2019)10.1364/OE.27.018016]. The authors utilize this general forward model, known as the two frequency spatial Wigner distribution (TFSWD), to discuss the implications of reconstruction resolution for combining the two modalities but only when the occluder geometry is known a priori. In this work, we develop a graphical representation of the TFSWD forward model and apply it to novel experimental setups with potential applications in NLOS imaging. Furthermore, we use this unified framework to explore the potential of combining these two imaging modalities in situations where the occluder geometry is not known in advance.

Revisiting Probabilistic Relation Analysis: Using Probabilistic Relation Graphs for Relational Similarity Analysis of Words in Short Texts

Relation graphs provide useful tools for structural and relational analyses of highly complex multi-component systems. Probabilistic relation graph models can represent relations between system components by their probabilistic links. These graph types have been widely used for the graphical representation of Markov models and bigram probabilities. This study presents an implication of relational similarities within probabilistic graph models of textual entries. The article discusses several utilization examples of two fundamental similarity measures in the probabilistic analysis of short texts. To this end, the construction of probabilistic graph models by using bigram probability matrices of textual entries is illustrated, and vector spaces of input word-vectors and output word-vectors are formed. In this vector space, the utilization of cosine similarity and mean squared error measures are demonstrated to evaluate the probabilistic relational similarity between lexeme pairs in short texts. By using probabilistic relation graphs of the short texts, relational interchangeability analyses of lexeme pairs are conducted, and confidence index parameters are defined to express the reliability of these analyses. Potential applications of these graphs in language processing and linguistics are discussed on the basis of the analysis results of example texts. The performance of the applied similarity measures is evaluated in comparison to the similarity index of the word2vec language model. Results of the comparative study in one of the illustrative examples reveal that synonyms with 0.18157 word2vec similarity value scored 1.0 cosine similarity value according to the proposed method.

Model-Based Transfer Reinforcement Learning Based on Graphical Model Representations.

Reinforcement learning (RL) plays an essential role in the field of artificial intelligence but suffers from data inefficiency and model-shift issues. One possible solution to deal with such issues is to exploit transfer learning. However, interpretability problems and negative transfer may occur without explainable models. In this article, we define Relation Transfer as explainable and transferable learning based on graphical model representations, inferring the skeleton and relations among variables in a causal view and generalizing to the target domain. The proposed algorithm consists of the following three steps. First, we leverage a suitable casual discovery method to identify the causal graph based on the augmented source domain data. After that, we make inferences on the target model based on the prior causal knowledge. Finally, offline RL training on the target model is utilized as prior knowledge to improve the policy training in the target domain. The proposed method can answer the question of what to transfer and realize zero-shot transfer across related domains in a principled way. To demonstrate the robustness of the proposed framework, we conduct experiments on four classical control problems as well as one simulation to the real-world application. Experimental results on both continuous and discrete cases demonstrate the efficacy of the proposed method.

ИССЛЕДОВАНИЕ ОСОБЕННОСТЕЙ ПЕРЕХОДНЫХ СОСТОЯНИЙ МОДЕЛИ ЖИЗНЕННОГО ЦИКЛА МОДИФИКАЦИИ

The article analyses models of product life cycle. The article describes the maturity levels of processes in accordance with GOST R ISO/IEC 15504-2-2009, as well as a graphical representation of models of maturity levels and attributes achieved at each stage. The result is a cumulative model, according to which it is possible to estimate, which indicator will contribute to creation of modification of the initial object and the beginning of a new iteration in the full life cycle, and, therefore, prevent moral and technological degradation.

Versatile Method of Modeling Content and Structure of a Terminological Field

The paper introduces a new method for modeling a terminological field with its content and structure. The method is a foundation for a computer program able to evaluate students’ professional knowledge both in qualitative and quantitative aspects. The method includes several stages: processing the lexical content of a terminological field, revealing elements that structure this content, and graphical representation of the terminological field model. The list of methods included the thesaurus approach and the componential analysis of lexical meaning. The thesaurus approach detects the basic types of semantic relationships between lexical units within a terminological field. The componential analysis explicates elements that arrange these units. The model is represented as a tree graph structure, which is ideal for visualizing multi-level hierarchic structures. This graph consists of two types of elements: terms and structure units. The method is designed to be flexible and versatile so that it can be effectively applied to any terminological field. The method can be applied to a specific terminological field in order to build its model with particular regard to all characteristic features of its content and structure

Development of web-based dynamic nomogram to predict survival in patients with gastric cancer: a population-based study

Gastric cancer (GC) is the fifth most frequent malignancy worldwide and the third leading cause of cancer-associated mortality. The study’s goal was to construct a predictive model and nomograms to predict the survival of GC patients. This historical cohort study assessed 733 patients who underwent treatments for GC. The univariate and multivariable Cox proportional hazard (CPH) survival analyses were applied to identify the factors related to overall survival (OS). A dynamic nomogram was developed as a graphical representation of the CPH regression model. The internal validation of the nomogram was evaluated by Harrell’s concordance index (C-index) and time-dependent AUC. The results of the multivariable Cox model revealed that the age of patients, body mass index (BMI), grade of tumor, and depth of tumor elevate the mortality hazard of gastric cancer patients (P < 0.05). The built nomogram had a discriminatory performance, with a C-index of 0.64 (CI 0.61, 0.67). We constructed and validated an original predictive nomogram for OS in patients with GC. Furthermore, nomograms may help predict the individual risk of OS in patients treated for GC.

INFORMATION CONTENT OF HIGH-ORDER ASSOCIATIONS OF THE HUMAN GUT MICROBIOTA NETWORK.

The human gastrointestinal tract is an environment that hosts an ecosystem of microorganisms essential to human health. Vital biological processes emerge from fundamental inter- and intra-species molecular interactions that influence the assembly and composition of the gut microbiota ecology. Here we quantify the complexity of the ecological relationships within the human infant gut microbiota ecosystem as a function of the information contained in the nonlinear associations of a sequence of increasingly-specified maximum entropy representations of the system. Our paradigm frames the ecological state, in terms of the presence or absence of individual microbial ecological units that are identified by amplicon sequence variants (ASV) in the gut microenvironment, as a function of both the ecological states of its neighboring units and, in a departure from standard graphical model representations, the associations among the units within its neighborhood. We characterize the order of the system based on the relative quantity of statistical information encoded by high-order statistical associations of the infant gut microbiota.

Characteristics of mathematical modeling languages that facilitate model reuse in systems biology: a software engineering perspective

Reuse of mathematical models becomes increasingly important in systems biology as research moves toward large, multi-scale models composed of heterogeneous subcomponents. Currently, many models are not easily reusable due to inflexible or confusing code, inappropriate languages, or insufficient documentation. Best practice suggestions rarely cover such low-level design aspects. This gap could be filled by software engineering, which addresses those same issues for software reuse. We show that languages can facilitate reusability by being modular, human-readable, hybrid (i.e., supporting multiple formalisms), open, declarative, and by supporting the graphical representation of models. Modelers should not only use such a language, but be aware of the features that make it desirable and know how to apply them effectively. For this reason, we compare existing suitable languages in detail and demonstrate their benefits for a modular model of the human cardiac conduction system written in Modelica.

Prognostic Value of Preoperative Fibrinogen for Predicting Clinical Outcome in Patients with Nonmetastatic Colorectal Cancer.

BackgroundThe prognostic role of preoperative fibrinogen in colorectal cancer (CRC) patients remains controversial. Therefore, we assessed the predictive value of preoperative fibrinogen and developed a tool for predicting the survival of CRC patients.MethodsThis retrospective study evaluated 1869 patients who underwent curative resection for CRC. Univariate and multivariate survival analyses were conducted to identify the factors correlated with overall survival (OS) and cancer-specific survival (CSS). Nomograms were developed as a graphical representation of the Cox proportional hazards regression models. The performance of the nomograms was assessed by Harrell’s concordance index (c-index) and calibration plots.ResultsThe preoperative fibrinogen levels were correlated with age, tumor differentiation, tumor location, pT category, and TNM stage. In the multivariate analysis, elevated fibrinogen level was independently correlated with worse OS and CSS (OS: hazard ratio [HR] = 0.777, 95% confidence interval [95% CI] = 0.630–0.958, P = 0.018; CSS: HR = 0.757, 95% CI = 0.605–0.947, P = 0.015). The nomograms could predict outcomes with a c-index for OS and CSS of 0.79 and 0.81, respectively. The nomograms also had a good calibration.ConclusionPreoperative fibrinogen level was an independent marker of poor prognosis in patients with nonmetastatic CRC, and there was a threshold level for the use of fibrinogen as a prognostic factor. Furthermore, nomograms may help predict the individual risk of OS and CSS in patients treated for CRC.

A Visualization Template for the Graphical Representation of Sport Injury Antecedents and Consequences Models and Data.

A template for visually representing factors affecting and affected by the occurrence of sport injury is presented. The visualization template is designed to facilitate comparison among graphic depictions of models and data pertaining to the antecedents and consequences of sport injury. Innovative aspects and limitations of the visualization template are highlighted, and future applications of the visualization template are discussed.

Network planning methodology in the problem of adaptive learning of university students

The article proposes a methodology of network planning in the problem of adaptive learning of university students. The elements of network planning are briefly presented, the use of adaptive learning methods in the educational process is described. The learning process in the university is considered, and the possibilities of describing it using the formalism of network planning within some discipline are analyzed. The developed technique for assessing the performance of tasks is given. The process of interaction between a teacher and a student in the learning process is described in terms of assessing the sequence of this interaction and the parameters of the proposed algorithm. The developed model of the discipline in the form of a linear sequence of actions for the study of the discipline is presented. To reflect the efforts made to obtain a learning outcome, a graphical representation of the discipline's network model is given. The results of the use of network graphics in the educational process within one discipline are presented. The formulas used to assess the student when using this technique are described. Several variants of passing the academic discipline by a student are considered, analytical data obtained by comparing these variants are presented. A computer program designed to support the developed technique is presented. The results of using the proposed methodology for assessing the study of a discipline by a university student are analyzed. The study of the methodology presented in the article can be useful for both university teachers and students.

The Prediction of Saliency Map for Head and Eye Movements in 360 Degree Images

By recording the whole scene around the capturer, virtual reality (VR) techniques can provide viewers the sense of presence. To provide a satisfactory quality of experience, there should be at least 60 pixels per degree, so the resolution of panoramas should reach 21600 × 10800. The huge amount of data will put great demands on data processing and transmission. However, when exploring in the virtual environment, viewers only perceive the content in the current field of view (FOV). Therefore if we can predict the head and eye movements which are important behaviors of viewer, more processing resources can be allocated to the active FOV. But conventional saliency prediction methods are not fully adequate for panoramic images. In this paper, a new panorama-oriented model, to predict head and eye movements, is proposed. Due to the superiority of computation in the spherical domain, the spherical harmonics are employed to extract features at different frequency bands and orientations. Related low- and high-level features including the rare components in the frequency domain and color domain, the difference between center vision and peripheral vision, visual equilibrium, person and car detection, and equator bias are extracted to estimate the saliency. To predict head movements, visual mechanisms including visual uncertainty and equilibrium are incorporated, and the graphical model and functional representation for the switch of head orientation are established. Extensive experimental results on the publicly available database demonstrate the effectiveness of our methods.

Optimization synthesis geopolymer based mixture metakaolin and fly ash activated by alkaline solution

The geopolymer materials have been widely studied because of their environmental positive impact and their potential use as a sustainable building material. It is in this context that this work has registered to optimize the synthesis geopolymer by improving their compressive strenght, from a mixture of three components, metakaolin, fly ash and activating alkaline solution. The methodology chosen in this study is a mixture design, in order to establish a models between two responses, setting time responses and the mechanical compressive strength, and the three constituents of the mixture, taking into account their interactions.The variance analysis of established models showed that Fisher experimental values are higher than critical value of Fisher-Snedecor, which allowed us to say that the factors used for modeling are significant overall. Thus, model validation showed that there is no difference statistically significant between the experimental and predicted values, which confirmed the validation of the established models, with very high values of determination coefficients (R2 = 95% for setting time and 96% for compressive strength). The graphical representation of models in the space of variables allowed us to determine the optimal constituent conditions, leading to a geopolymer with a compressive strength equal to 20.58 MPa.

Concerted hydrolysis mechanism of HIV-1 natural substrate against subtypes B and C-SA PR: insight through molecular dynamics and hybrid QM/MM studies

It is well known that understanding the catalytic mechanism of HIV-1 PR is the rationale on which its inhibitors were developed; therefore, a better understanding of the mechanism of natural substrate hydrolysis is important. Herein, the reaction mechanism of HIV-1 natural substrates with subtypes B and common mutant in South Africa (subtype C-SA) protease were studied through transition state modelling, using a general acid-general base (GA-GB) one-step concerted process. The activation free energies of enzyme-substrate complexes were compared based on their rate of hydrolysis using a two-layered ONIOM (B3LYP/6-31++G(d,p):AMBER) method. We expanded our computational model to obtain a better understanding of the mechanism of hydrolysis as well as how the enzyme recognises or chooses the cleavage site of the scissile bonds. Using this model, a potential substrate-based inhibitor could be developed with better potency. The calculated activation energies of natural substrates in our previous study correlated well with experimental data. A similar trend was observed for the Gag and Gag-Pol natural substrates in the present work for both enzyme complexes except for the PR-RT substrate. Natural bond orbital (NBO) analysis was also applied to determine the extent of charge transfer within the QM part of both enzymes considered and the PR-RT natural substrate. The result of this study shows that the method can be utilized as a dependable computational technique to rationalize lead compounds against specific targets.

Implementation bayes network based for classification study of completion

Many factors influence the completion of the study. However, it is likely that some variables are dependent on each other. Method Bayes Network is used because it can illustrate the cause-effect relationship between completion of study with the factors that allegedly influenced as a graphical model representation so that more easily understood. With empirical data, the presence or absence of relationships among factors is calculated using mutual information. If the structure of the network has been established then subsequently calculated the probability of relationship for each event. The probability value obtained is shown to obtain a complete causality diagram. The results of the research on the classification process using student data in 2012 with Bayes Network method resulted in an accuracy of 71.09%.

Stability of the Manual Ability Classification System in young children with cerebral palsy.

To examine the stability over time of the Manual Ability Classification System (MACS) levels in children with cerebral palsy (CP) aged 18 to 60months. This was a prospective longitudinal population-based study of 252 Australian children (160 males [63%] 92 females [37%]; mean age [SD] 41.7mo [14], range 17.2mo-69.2mo) with CP. Children were classified at 18months (n=70), 24 months (n=131), 30months (n=173), 36months (n=209), 48months (n=226), and 60months (n=221) of age. Stability of the MACS was examined using the proportion of specific positive agreement and transition proportions, which are measures of agreement. There were 1030 unique observations, with each of the 252 participants seen between two and six occasions (median=4). Average specific positive agreement over the study period was 76% for MACS level I, 67% for level II, 50% for level III, 51% for level IV, and 83% for level V. MACS levels I and V have the highest degree of stability, while levels III and IV have the lowest. We show how this may be explained by the proportion of children in each MACS level. Using measures of agreement rather than measures of reliability provides accurate information when measuring stability over time of an ordinal classification system. The relative stability of MACS levels can be explained by the proportion of children in each level. Children classified in Manual Ability Classification System (MACS) levels III and IV change levels at next assessment about 50% of the time. Children should be assessed with the MACS regularly, particularly those in levels III and IV. Stability within ordinal classification level categories can be predicted using a measurement error model. Transition proportions or specific agreement is recommended for reporting stability of ordinal classification systems.

Parsimonious graphical dependence models constructed from vines

AbstractMultivariate models with parsimonious dependence have been used for a large number of variables, and have mainly been developed for multivariate Gaussian. Graphical dependence model representations include Bayesian networks, conditional independence graphs, and truncated vines. The class of Gaussian truncated vines is a subset of Gaussian Bayesian networks and Gaussian conditional independence graphs, but has an extension to non‐Gaussian dependence with (i) combinations of continuous and discrete random variables with arbitrary univariate margins, and (ii) accommodation of latent variables. To illustrate the importance of graphical models with latent variables that do not rely on the Gaussian assumption, the combined factor‐vine structure is presented and applied to a data set of stock returns. The Canadian Journal of Statistics 46: 532–555; 2018 © 2018 Société statistique du Canada

IMPLEMENTATION OF ACOUSTIC PROCESSES SIMULATION ON THE BASIS OF UNREAL ENGINE 4 SOFTWARE PLATFORM

The stages of development of the software simulator of acoustic oscillations are outlined. The main theoretical foundations laid down in the software product during development are given. The assumptions made within the framework of the theoretical framework for the purpose of optimizing the algorithm are stated. Elements of algorithmic logic and technical base within which development was carried out are presented. The main elements on the basis of which the classes of the software product are built are indicated and characterized. The program classes realized within the development process are characterized and described. The listings of the developed classes in Unreal Engine Blueprint format are given. The commentary for each listing is provided. Screenshots of implemented software for direct and transverse wave scenarios (direct and oblique sensor) are provided. Qualitative parameters of the correspondence of the obtained simulation model to real samples are characterized. Graphical representation of simulated testing model is given. The shortcomings of the received model are characterized and ways of their elimination are considered.

Desenvolvimento e Avaliação de um Perfil UML para Modelagem de Jogos Educacionais Digitais

UML (Unified Modeling Language) is a general purpose language for software modeling, moreover, is the language most known and used for graphical representation of models. Just the elements preexisting in the UML (Unified Modeling Language) may not be sufficient to facilitate understanding of specific domain models. An example of specific problem domain is the Digital Educational Games (DEGs). In this paper, we describe the UP4EG, a UML profile for DEGs modeling, using UML class diagrams. The UP4EG gathers many stereotypes and tagged values divided into six packages that represent the main elements that a DEG should present. From an experimental study on the proposed profile with computer science students, it was realized that number of errors and the time spent for the identification of the main elements of a DEG can be improved when this profile is used in the modeling of this type of software.

A Conceptual Framework for Detecting Cheating in Online and Take‐Home Exams

ABSTRACTSelecting the right methodology to use for detecting cheating in online exams requires considerable time and effort due to a wide variety of scholarly publications on academic dishonesty in online education. This article offers a cheating detection framework that can serve as a guideline for conducting cheating studies. The necessary theories and related statistical models are arranged into three phases/sections within the framework to allow cheating studies to be completed in a sufficiently quick and precise manner. This cheating detection framework includes commonly used models in each phase and addresses the collection and analysis of the needed data. The model's level of complexity ascends progressively from a graphical representation of data and descriptive statistical models to more advanced inferential statistics, correlation analysis, regression analysis, and the optional comparison method and the Goldfeld‐Quandt Test for heteroskedasticity. An instructor receiving positive results on the possibility of cheating in Phases 1 or 2 can avoid using more advanced models in Phase 3. Tests conducted on sample courses showed that models in Phases 1 and 2 of the proposed framework provided results effectively for over 70% of the test groups, saving users further time and effort. High‐tech systems and low‐cost recommendations that can mitigate cheating are discussed. This framework will be beneficial in guiding instructors who are converting from the traditionally proctored in‐class exam to a take‐home or online exam without authentication or proctoring. In addition, it can serve as a powerful deterrent that will alleviate the concerns that an institution's stakeholders might have about the reliability of their programs.