A New Weighting Scheme in Weighted Markov Model for Predicting the Probability of Drought Episodes

Drought is a complex stochastic natural hazard caused by prolonged shortage of rainfall. Several environmental factors are involved in determining drought classes at the specific monitoring station. Therefore, efficient sequence processing techniques are required to explore and predict the periodic information about the various episodes of drought classes. In this study, we proposed a new weighting scheme to predict the probability of various drought classes under Weighted Markov Chain (WMC) model. We provide a standardized scheme of weights for ordinal sequences of drought classifications by normalizing squared weighted Cohen Kappa. Illustrations of the proposed scheme are given by including temporal ordinal data on drought classes determined by the standardized precipitation temperature index (SPTI). Experimental results show that the proposed weighting scheme for WMC model is sufficiently flexible to address actual changes in drought classifications by restructuring the transient behavior of a Markov chain. In summary, this paper proposes a new weighting scheme to improve the accuracy of the WMC, specifically in the field of hydrology

Distribution planning in a weather-dependent scenario with stochastic travel times: a simheuristics approach

In real-life logistics, distribution plans might be affected by weather conditions (rain, snow, and fog), since they might have a significant effect on traveling times and, therefore, on total distribution costs. In this paper, the distribution problem is modeled as a multi-depot vehicle routing problem with stochastic traveling times. These traveling times are not only stochastic in nature but the specific probability distribution used to model them depends on the particular weather conditions on the delivery day. In order to solve the aforementioned problem, a simheuristic approach combining simulation within a biased-randomized heuristic framework is proposed. As the computational experiments will show, our simulation-optimization algorithm is able to provide high-quality solutions to this NP-hard problem in short computing times even for large-scale instances. From a managerial perspective, such a tool can be very useful in practical applications since it helps to increase the efficiency of the logistics and transportation operations.Peer ReviewedPostprint (published version

Distribution planning in a weather-dependent scenario with stochastic travel times: a simheuristics approach

In real-life logistics, distribution plans might be affected by weather conditions (rain, snow, and fog), since they might have a significant effect on traveling times and, therefore, on total distribution costs. In this paper, the distribution problem is modeled as a multi-depot vehicle routing problem with stochastic traveling times. These traveling times are not only stochastic in nature but the specific probability distribution used to model them depends on the particular weather conditions on the delivery day. In order to solve the aforementioned problem, a simheuristic approach combining simulation within a biased-randomized heuristic framework is proposed. As the computational experiments will show, our simulation-optimization algorithm is able to provide high-quality solutions to this NP-hard problem in short computing times even for large-scale instances. From a managerial perspective, such a tool can be very useful in practical applications since it helps to increase the efficiency of the logistics and transportation operations.Peer ReviewedPostprint (published version

Time-dependent reliability methodologies with saddlepoint approximation

Engineers always encounter time-dependent uncertainties that ubiquitously exist, such as the random deterioration of material properties and time-variant loads. Therefore the reliability of engineering systems becomes time-dependent. It is crucial to predict the time-dependent reliability in the design stage, given possible catastrophic consequences of a failure. Although extensive research has been conducted on reliability analysis, estimating the reliability accurately and efficiently is still challenging. The objective of this work is to develop accurate and efficient reliability methodologies for engineering design. The basic idea is the integration of traditional reliability methods with saddlepoint approximation (SPA), which can accurately approximate the tail distribution of a random variable. Four methods are proposed in this work. The first three methods deal with time-independent reliability while the last one estimates the time-dependent reliability. The first method combines SPA with first-order approximation and achieves higher accuracy over the traditional first-order reliability method when bimodal distributions are involved. The second method further improves the accuracy of reliability estimation by integrating SPA with the second-order approximation. The third method extends the second method into the reliability-based design for higher accuracy, and the high efficiency is maintained by an efficient algorithm for searching for an equivalent reliability index. The fourth method uses sequential efficient global optimization to convert a time-dependent problem into a time-independent counterpart. Then the second method is utilized to estimate the time-independent reliability after the conversion. The accuracy and effectiveness of the above methods are demonstrated by both numerical examples and engineering applications --Abstract, page iv

The structure of connotative dimensions judo and karate

The research was conducted in order to determine the specificity of conative dimensions of judo and karate athletes as well as their differences. To determine the specificity of the structure of the tested anthropological dimensions, the researchers tested 200 judo and karate athletes, members of judo and karate clubs in Serbia (about 100 judokas and about 100 karatekas), aged 18 to 27. For the assessment of conative characteristics, the researchers chose the measuring instrument CON6 to assess the following conative regulators: activity regulator, regulator of organic functions, regulator of defense reactions, regulator of attack reactions, system for coordination of regulatory functions, and the system for integration of regulatory functions. All the data in this study were processed at the Multidisciplinary Research Center, Faculty of Sport and Physical Education, University of Pristina through the system of data processing software programs DRSOFT developed by [ 19, 28, 17 ]. The algorithms and programs realized in this study are fully presented, and the results of the programs are analyzed

Statistical Approach in Analyzing of Advanced Metering Data in Power Distribution Grid

In last period many distribution system operators (DSO) invest significant amount of money in smart metering system. Those investments are in part due to regulatory obligations and in part due to needs of DSO (utilities) for knowledge about electric energy consumption. Term electric energy consumption refers not only on real consumption of electric energy but also on data about peak power, unbalance, voltage profiles, power losses etc. Data which DSO can have depends on type of smart metering system. Further, smart meters as source of data can be implemented in transformer stations (TS) MV/LV and in LV grid at consumer level. Generally, smart meters can be placed in any node of distribution grid. As amount of smart meters is greater, the possibility of data analysis is greater. In this paper a smart metering system of J.P Elektroprivreda HZ HB d.d, Mostar, Bosnia and Herzegovina will be presented. One statistical approach for analyzing of advanced metering data of TS MV/LV will be presented. Statistical approach presented here is powerful tool for analyzing great amount of data from distribution grid in simple way. Main contribution of this paper is in using results obtained from statistical analysis of smart meter data in distribution grid analyzing and in maintenance/investment planning

An Analysis of the Link between Metacognitive Beliefs and Academic Health-oriented Lifestyle Preventive Behaviours Mediated by Self-efficacy during the COVID-19 Pandemic

[EN] The outbreak of the coronavirus and its ramifications, including lockdown and shutting down of many learning centers magnified the necessity of turning to virtual learning, has given rise to concerns about students learning and their reaction to the new teaching methods and the challenges they entail. The present study attempts to examine the link between metacognitive beliefs and behaviors that prevent health-oriented lifestyles through academic self-efficacy during the COVID-19 pandemic. The statistical sample consisted of 239 randomly selected undergraduate students of engineering at Azad University of Shahre-e Rey in the second semester of 1399-1400. The data were gathered using academic health-oriented life style test Salehzadeh et al. (2018) Academic Self-Efficacy Beliefs Questionnaire (ASEBQ), and Wells Metacognition Questionnaire-30 (MCQ-30). Findings of the study indicated that metacognitive beliefs are related to behaviors preventing academic health-oriented life style factors, such as learned helplessness and effort withdrawal, through self-efficacy. It is suggested that, According to the positive relationship that exists between metacognitive strategies and academic achievement. As well as these strategies are scalability learners need to be trained in skills such as self-regulation self- monitoring planning and goal setting. Until they dominate decided cognitive strategies and professors can also encourage students to use orientation by designing assignments, teaching study strategies, and using new teaching methods.Moradi, F.; Aghaei Sabet, S.; Soufi, S. (2022). An Analysis of the Link between Metacognitive Beliefs and Academic Health-oriented Lifestyle Preventive Behaviours Mediated by Self-efficacy during the COVID-19 Pandemic. Multidisciplinary Journal for Education, Social and Technological Sciences. 9(1):39-58. https://doi.org/10.4995/muse.2022.1687939589

A validation of the Visual Perceptual Aspects Test using a bifactor exploratory structural equation modelling approach

Visual perception is a psychological construct that describes the awareness of visual sensations and arise from the interactions of the individual or observer in the external environment together with the physiology of the observer’s visual system. A variety of theories of the development of visual perception have led to the development of different psychometric measures aimed at quantifying the cognitive construct. The Visual Perceptual Aspects Test was developed by Clutten (2009) to measure nine different constructs of visual perception. The original VPAT was validated using content and construct validity based on a Western Cape sample. However, to the researcher’s knowledge, a factor analysis had not yet been conducted on the VPAT to determine the factor validity of the test. Furthermore, no measures of validity or reliability had been conducted on the VPAT using a sample outside of the Western Cape. The aim of this research is to validate the hypothesised nine factor structure of the Visual Perceptual Aspects Test, using a confirmatory factor analysis, exploratory structural equation model, a bifactor confirmatory factor analysis and a bifactor exploratory structural equation model. The results of the analysis showed marginal model fit of the VPAT with the sample data, with sufficient levels of reliability for certain sub-tests. However, the VPAT did not meet significant levels of validity or reliability of the proposed model structure of the VPAT for the sample group of learners based in the Eastern Cape.PsychologyM.A. (Research Psychology

Blunt Force Trauma to the Ribs: Creating Predictive Models

Forensic anthropologists receive more requests for trauma analysis than any other aspect of the biological profile. Blunt force trauma to the ribs is some of the most common trauma recorded in a medical examiner’s setting, however the structural complexity of ribs make it difficult to move beyond descriptive documentation of injuries. The purpose of this study is to identify common rib fracture patterns, influential variables, and provide probabilistic statements to guide rib fracture interpretations. A sample of 1,415 deceased individuals with known blunt force trauma to the torso were collected from four geographically diverse medical examiner offices. Demographic data and fracture variables were recorded per individual. Frequency distributions, chi-squared tests, Kruskal-Wallis tests of independence, Dunn’s tests, and multiple correspondence analysis were employed to understand variable relationships. Conditional probabilities were calculated to provide probabilistic statements. Additionally, random forest analysis was conducted to classify location and type of fracture based on covariates. A total of 24, 853 fractures were recorded. The most common fractures were displaced and simple fractures on ribs three through seven in the anterolateral and posterolateral locations. The less common fracture patterns revealed significant relationships with demographic data and provided empirical evidence for previously untested statements. BMI had a significant relationship with location, such that fractures were more frequently recorded in lower ribs in individuals with a BMI category of obese. Age had a significant relationship with fracture type and fracture location in all analyses; younger individuals were more likely to have incomplete fractures and incur fractures anteriorly, and older individuals were more likely to have multi-fragmentary fractures. The current study indicates that rib fracture types and location are dependent on the demographics of the individual. Demographics, such as age and health of the individual inform the material properties and structural geometry of bone, which is how bone biomechanics are recommended to be incorporated into trauma analysis. Furthermore, the results from this research can be applied to motor vehicle safety research, experimental research avenues, and bioarcheological trauma analysis. Future rib fracture research should focus on including a more holistic view of an individual during the interpretation of fracture patterns