Nursing Value Analysis and Risk Assessment of Acute Gastrointestinal Bleeding Using Multiagent Reinforcement Learning Algorithm

Gastrointestinal bleeding (GIB) indicates an issue in the digestive system. Blood can be found in feces or vomiting; however, it is not always visible, even if it makes the stool appear darkish or muddy. The bleeding can range in harshness from light to severe and can be dangerous. It is advised that nursing value analysis and risk assessment of patients with GIB is essential, but existing risk assessment techniques function inconsistently. Machine learning (ML) has the potential to increase risk evaluation. For evaluating risk in patients with GIB, scoring techniques are ineffective; a machine learning method would help. As a result, we present а unique machine learning-based nursing value analysis and risk assessment framework in this research to construct a model to evaluate the risk of hospital-based interventions or mortality in individuals with GIB and make a comparison to that of other rating systems. Initially, the dataset is collected, and preprocessing is done. Feature extraction is done using local binary patterns (LBP). Classification is performed using a fuzzy support vector machine (FSVM) classifier. For risk assessment and nursing value analysis, machine learning-based prediction using a multiagent reinforcement algorithm is employed. For improving the performance of the proposed system, we use spider monkey optimization (SMO) algorithm. The performance metrics like classification accuracy, area under the receiver-operating characteristic curve (AUROC), area under the curve (AUC), sensitivity, specificity, and precision are analyzed and compared with the traditional approaches. In individuals with GIB, the suggested technique had a good–excellent prognostic efficacy, and it outperformed other traditional models.

Qualitative Rating System for Drainability of Roadway Base Materials

Poor drainage of roadway base/subbase materials can lead to increased pore water pressure, reduction of strength and stiffness, and freeze-thaw damage. Base course drainability is dependent on physical properties of the material that affect its water flow and retention behavior including particle size distribution, fines content, density or porosity, the geometric and boundary conditions of the pavement system, and site-specific environmental conditions. Objectives of this project are to quantitatively assess permeability and water retention characteristics of representative roadway base materials, to derive predictive equations for indirect estimation of material properties that control drainability, and to develop and recommend rating systems for assessing more general base materials. Laboratory tests were conducted on 16 samples of materials used in or considered for use in roadway applications to determine grain size distribution, hydraulic conductivity, and soil-water characteristic curves. Results are correlated to grain size characteristics including percent gravel, percent fines, grain size indices (e.g., D10, D30), and unit weight. Procedures are provided to qualitatively assess drainability as “excellent,”“marginal,” or “poor,” from grain size, thereby offering a rationale to reduce pavement life cycle costs, improve safety, realize material cost savings, and reduce environmental impacts.

Quality of Educational Programs for Elementary School-Age Students With Autism

The purpose of this study was to assess the quality of educational programs for school-aged children with autism in the United States. Investigators completed the Autism Program Environment Quality Rating Systems-Preschool/Elementary (APERS-PE) in 60 elementary schools enrolling children with autism. The mean total rating scores were near the midpoint rating, indicating schools were providing educational program environments classified as adequate but not of high quality. Domains of the APERS-PE reflecting structural quality tended to be significantly above average and domains reflecting process quality tended to be significantly below average. With a few exceptions, inclusive and special education program did not differ significantly in total program quality ratings and reflected the same pattern of domain quality ratings.

Benchmark test for calculated default probability values derived from the application of rating-based models

Subject. This article deals with the issues of validation of the consistency of rating-based model forecasts. Objectives. The article aims to provide developers and validators of rating-based models with a practical fundamental test for benchmarking study of the estimated default probability values obtained as a result of the application of models used in the rating system. Methods. For the study, I used the classical interval approach to testing of statistical hypotheses focused on the subject area of calibration of rating systems. Results. In addition to the generally accepted tests for the correspondence of the predicted probabilities of default of credit risk objects to the historically realized values, the article proposes a new statistical test that corrects the shortcomings of the generally accepted ones, focused on "diagnosing" the consistency of the implemented discrimination of objects by the rating model. Examples of recognizing the reasons for a negative test result and negative consequences for lending are given while maintaining the current settings of the rating model. In addition to the bias in the assessment of the total frequency of defaults in the loan portfolio, the proposed method makes it possible to objectively reveal the inadequacy of discrimination against borrowers with a calibrated rating model, diagnose the “disease” of the rating model. Conclusions and Relevance. The new practical benchmark test allows to reject the hypothesis about the consistency of assessing the probability of default by the rating model at a given level of confidence and available historical data. The test has the advantage of practical interpretability based on its results, it is possible to draw a conclusion about the direction of the model correction. The offered test can be used in the process of internal validation by the bank of its own rating models, which is required by the Bank of Russia for approaches based on internal ratings.

Investigating the efficiency of the Asian handicap football betting market with ratings and Bayesian networks

Despite the massive popularity of the Asian Handicap (AH) football (soccer) betting market, its efficiency has not been adequately studied by the relevant literature. This paper combines rating systems with Bayesian networks and presents the first published model specifically developed for prediction and assessment of the efficiency of the AH betting market. The results are based on 13 English Premier League seasons and are compared to the traditional market, where the bets are for win, lose or draw. Different betting situations have been examined including a) both average and maximum (best available) market odds, b) all possible betting decision thresholds between predicted and published odds, c) optimisations for both return-on-investment and profit, and d) simple stake adjustments to investigate how the variance of returns changes when targeting equivalent profit in both traditional and AH markets. While the AH market is found to share the inefficiencies of the traditional market, the findings reveal both interesting differences as well as similarities between the two.

Developing Transportation Livability-Related Indicators for Green Urban Road Rating System in Taiwan

Although indicators in rating systems have been initiated to measure and promote the sustainability performance of roadway projects in some developed countries, applying those indicators to other regions/countries may still be difficult. In response to the United Nations’ sustainable development goals, local road agencies in Taiwan urgently need to establish systematic and quantifiable sustainable roadway strategies. As part of the project to develop a green urban road rating system in Taiwan, this study aims to develop transportation livability-related indicators (TLIs) and identify critical barriers to TLI application in Taiwan’s urban road system. To this end, the research employed an adaptive approach that integrates top-down and bottom-up approaches. The top-down approach included the comprehensive literature review and panel discussion to derive four TLIs and 21 corresponding requirements, and nine potential barriers to hold the indicator adoption. Four TLIs are pedestrian facilities, universal design, multimodal transportation, and utility facilities. The bottom-up approach used the Analytic Hierarchy Process (AHP) to assign weights to proposed indicators/requirements. Four critical barriers were also investigated through the Weighted Sum Model (WSM) method, namely unfavorable in-situ conditions, lack of stakeholders’ coordination, unsupported government policy and regulation, and limited budget and schedule. The findings can be beneficial to engineers and decisionmakers to enhance the livability standard of urban streets. The framework proposed in this research can be applied to other roadway characteristics aspects in different regions/countries.

Building information modelling and building sustainability assessment: a review

PurposeThe construction sector is increasingly engaged to explore the potential application of building information modelling (BIM) for the sustainability of the buildings. BIM can be applied conjugated to certification methods to evaluate the sustainability of the buildings, and it is known as building sustainability assessment (BSA). This article aims to explore applications of BIM in the sustainability analysis of buildings, including five types of BSA.Design/methodology/approachA literature review from 2009 to 2020 considering a combination of search terms related to BIM and BSA complemented the analysis. The bibliometric analysis indicates an increase in the number of publications on this topic of study in the last five years. A peak occurred in 2015 and 2020, with 51 and 66 publications, respectively.FindingsThe results showed that BIM contributes to achieving part of the sustainability requirements from BSA, especially quantitative requirements that are related to material and resources. However, a complete analysis between BIM and BSA is still a challenge since part of BSA's have a lack information in their requirements and BIM softwares present interoperability problems that difficult an integrated analysis to extract information directly from the software to attend BSA's requirements.Originality/valueThe results contribute to analysing the evolution of studies about BIM and to understand the limitation in the applicability with sustainability rating systems. Future directions of research indicate the necessity to improve the use of BIM in the sustainability analysis of the buildings, but with a good perspective regarding the application of BIM in material and resources requirements, and waste management in construction sites.

Global and national university rankings: A multivariate analysis

Introduction. In the context of globalisation and internationalisation of higher education, university rankings are becoming an important tool for assessing the quality of education received by students at various higher education institutions around the world. These processes actualise the issues of possibilities for practical use of methodologies for calculation of global and national university rankings.The aim of the study was to develop and apply a methodological approach to multivariate the analysis of Higher Education Institutions (HEIs) classification procedures, to construct and analyse aggregated indicators for global and national rating systems of higher education organisations, and to assess the relationship between them.Methodology and research methods. The current paper presents a system analysis of databases of rating systems and an aggregation of independent evaluations of global and national rankings of HEIs using the methodology of league table analysis based on mathematical apparatus of the voting theory. The dependence of global and national university rankings indicators was investigated using correlation, cluster, factor, regression (linear and polynomial) and dispersion methods of analysis.Results and scientific novelty. A comprehensive comparative analysis of ranking systems and their results was carried out. The authors solved the problem of aggregating multiple heterogeneous studies of global and national ranking systems with their qualitative and quantitative variety of criteria, indicators and methods of assessment. The correlation between the indicators of aggregated global and national rankings was revealed; the regression dependence of the integral national ranking with the results of the leading global rating systems was determined.Practical significance. The developed methodical approach is a convenient and effective mechanism for comprehensive monitoring of the members of educational process.

Key determinants of deposits volume using CAMEL rating system: The case of Saudi banks

CAMEL is considered one of the well-known banking rating systems used to build a proper bank ranking. In our paper, we investigate the CAMEL rating for Saudi banks, which is considered the second largest banking sector in GCC. The Saudi banking sector consists of 11 banks and is the leading sector in the Saudi stock index (TASI). In this research, we aim to determine the ranking of Saudi banks according to CAMEL composite and CAMEL overall ratings and explore the effects of these ratings on banks’ total deposits for the period from 2014 to 2018. The methodology involves four phases. In the first phase, we calculate the key financial ratios of CAMEL’s composites for each bank. In the second phase, we rank the banks from 1 to 11 to each one of CAMEL’s composites for each bank per year. In the third phase, we rank Saudi banks according to CAMEL composite and CAMEL overall. Finally, in the fourth phase, we run a regression model using CAMEL financial ratios rank as independent variable and banks’ total deposits as a dependent variable. Using the stepwise regression method, the results indicated that the best regression model has an adjusted R2 of 73.4% and a standard error of around 0.58. The results further indicated that capital measured by CAR, management as an efficiency ratio, earning with ROE proxy, and liquidity as loans to deposits have positive effects on banks’ total deposits. Meanwhile, earnings as net interest income to net revenue and liquidity calculated by CASA have a negative effect on banks’ total deposits. Finally, asset quality ratios and the rest of the ratios have no significant effect on banks’ total deposits.