Search results for: ruin probability

Authors: Bi-Huei Tsai

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Previous studies on financial distress prediction choose the conventional failing and non-failing dichotomy; however, the distressed extent differs substantially among different financial distress events. To solve the problem, “non-distressed”, “slightly-distressed” and “reorganization and bankruptcy” are used in our article to approximate the continuum of corporate financial health. This paper explains different financial distress events using the two-stage method. First, this investigation adopts firm-specific financial ratios, corporate governance and market factors to measure the probability of various financial distress events based on multinomial logit models. Specifically, the bootstrapping simulation is performed to examine the difference of estimated misclassifying cost (EMC). Second, this work further applies macroeconomic factors to establish the credit cycle index and determines the distressed cut-off indicator of the two-stage models using such index. Two different models, one-stage and two-stage prediction models, are developed to forecast financial distress, and the results acquired from different models are compared with each other, and with the collected data. The findings show that the two-stage model incorporating financial ratios, corporate governance and market factors has the lowest misclassification error rate. The two-stage model is more accurate than the one-stage model as its distressed cut-off indicators are adjusted according to the macroeconomic-based credit cycle index.

Keywords: Multinomial logit model, corporate governance, company failure, reorganization, bankruptcy

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Authors: Elizabeth Spink

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Providing safe and affordable drinking water to low-income households in developing countries remains a challenge. Policy goals of increasing household piped-water access and cost recovery for utility providers are often at odds. Nonpayment of utility bills is frequently cited as a constraint to improving the quality of utility service. However, nonpayment is widely tolerated, and households often accumulate significant debt to the utility provider. This study examines the effect of enforcement of water bill payment through supply disconnections in Livingstone, Zambia. This research uses a dynamic model of household monthly payments and accumulation of arrears, which determine the probability of disconnection, and simulates the effect of exogenous changes in enforcement levels. This model is empirically tested using an event-study framework of exogenous increases in enforcement capacity that occur during administrative rezoning events, which reduce the number of households that one enforcement agent is responsible for. The results show that households are five percentage points more likely to make a payment in the months following a rezoning event, but disconnections for low-income households increase as well, resulting in little change in revenue collected by the water utility. The results suggest that high enforcement of water bill payments toward credit-constrained households may be ineffective and lead to reduced piped-water access.

Keywords: enforcement, nonpayment, piped-water access, water utilities

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Authors: Faith Fang Xi Ooi, Kam-Fong Lee

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Headlines are generally the summary of the content of news articles. With the added influence of hectic lifestyles, readers may rely solely on the headlines for information. In the media, what is reported concerning health issues are government responses and community involvement. There is a need for a call to action to curb health issues and not just reporting on what the government is doing about these health-related issues. In other words, linguistic elements of persuasive communicative function should be realized when reporting on health issues. Hence, this paper aims at identifying and analyzing the transitivity, Mood and Modality systems in two hundred news headlines from two Malaysian online news portals, namely The Star Online and New Straits Times. This study employs the purposive sampling method to obtain the news headlines on healthy eating using the search keyword ‘healthy eating’ and is based on Halliday’s Systemic Functional Linguistics (SFL) framework. The results show that the Material process dominates the process types along with its participants of Scope and Goal. The mood type that constitutes most of the headlines in the two newspapers is the declarative mood. Moreover, for Modality, the median Probability constitutes the highest in the headlines on healthy eating. This study contributes to the implications of being a source of reference for news writers and producers in constructing news headlines and for health campaign strategists to realize the persuasive appeals to influence behaviors and attitudes of the public towards healthy eating.

Keywords: healthy eating, modality, mood, news headlines, SFL

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Authors: Bidyadhar Dehury, Sanjay Kumar Mohanty

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According to the Right to Education Act of India, education is the fundamental right of all children of age group 6-14 year irrespective of their status. Using the unit level data from India Human Development Survey (IHDS), we tried to understand the inter-relationship between the level of poverty and the academic performance of the children aged 8-11 years. The level of multidimensional poverty is measured using five dimensions and 10 indicators using Alkire-Foster approach. The weighted deprivation score was obtained by giving equal weight to each dimension and indicators within the dimension. The weighted deprivation score varies from 0 to 1 and grouped into four categories as non-poor, vulnerable, multidimensional poor and sever multidimensional poor. The academic performance index was measured using three variables reading skills, math skills and writing skills using PCA. The bivariate and multivariate analysis was used in the analysis. The outcome variable was ordinal. So the predicted probabilities were calculated using the ordinal logistic regression. The predicted probabilities of good academic performance index was 0.202 if the child was sever multidimensional poor, 0.235 if the child was multidimensional poor, 0.264 if the child was vulnerable, and 0.316 if the child was non-poor. Hence, if the level of poverty among the children decreases from sever multidimensional poor to non-poor, the probability of good academic performance increases.

Keywords: multidimensional poverty, academic performance index, reading skills, math skills, writing skills, India

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Authors: Tahsien Mohamed Okasha

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We hypothesized that Post cardiac arrest patients with Glasgow coma scale (GCS) score of less than (8) and who will be exposed to therapeutic hypothermia protocol will exhibit improvement in their neurological performance. Purposive sample of 17 patients who were fulfilling the inclusion criteria during one year collected. The study carried out using Quasi-experimental research design. Four Tools used for data collection of this study: Demographic and medical data sheet, Post cardiac arrest health assessment sheet, Bedside Shivering Assessment Scale (BSAS), and Glasgow Pittsburgh cerebral performance category scale (CPC). Result: the mean age was X̅ ± SD = 53 ± 8.122 years, 47.1% were arrested because of cardiac etiology. 35.3% with initial arrest rhythm ventricular tachycardia (VT), 23.5% with ventricular fibrillation (VF), and 29.4% with A-Systole. Favorable neurological outcome was seen among 70.6%. There was significant statistical difference in WBC, Platelets, blood gases value, random blood sugar. Also Initial arrest rhythm, etiology of cardiac arrest, and shivering status were significantly correlated with cerebral performance categories score. therapeutic hypothermia has positive effects on neurological performance among post cardiac arrest patients with GCS score of less than (8). replication of the study on larger probability sample, with randomized control trial design. Further study for suggesting nursing protocol for patients undergoing therapeutic hypothermia.

Keywords: therapeutic hypothermia, neurological performance, after resuscitation from cardiac arrest., resuscitation

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Authors: Loai AbdAllah, Mahmoud Kaiyal

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Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

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Authors: Mandlenkosi Richard Mphatheni

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The Constitution of the Republic of South Africa (Act 108 of 1996 section 28(1) (d)) states, ‘Every child has the right to be protected from maltreatment, neglect, abuse, and degradation’. Qualitative research studied perceptions of the selected sample. Objectives of the research were to determine factors that influence perpetrators of sexual violence to target children, the risk factors of child sexual abuse, the effects of child sexual abuse on the development of the child, and the community prevention measures to minimize the risks of child sexual abuse. The research aimed to understand perspective and experiences of the Ngangelizwe community members on the problem of sexual violence against children and the perpetrator’s perceived motive for sexually abusing children. Convenience non-probability sampling technique was adopted to select 20 participants within the Ngangelizwe Township at Mthatha. Thematic analyses were used to analyse data. It was found that sexual abuse of children affects severely child and parents, while the community reported to be trivially affected by the sexual abuse of a child. The research revealed ignorance of some forms of sexual violence, as the commonly known form of sexual violence was rape. Therefore, ignorance of community members regarding various forms of sexual abuse means that such acts are either ignored, tolerated, or even regarded as acceptable. It thus means that community members cannot reject any actions or behaviour if they themselves are ignorant of what constitutes sexual violence. This study recommends that communities should be educated about different sexual offenses.

Keywords: child sexual abuse, community, childhood attachment, adult attachment

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Authors: Kreso Ivandic, Filip Dodigovic, Damir Stuhec

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The paper deals with the proposed 'Material' and 'Action-resistance factor' design methods in designing the embedded retaining walls. The parametric analysis of evaluating the differences of the output values mutually and compared with classic approach computation was performed. There is a challenge with the criteria for choosing the proposed calculation design methods in Eurocode 7 with respect to current technical regulations and regular engineering practice. The basic criterion for applying a particular design method is to ensure minimum an equal degree of reliability in relation to the current practice. The procedure of combining the relevant partial coefficients according to design methods was carried out. The use of mentioned partial coefficients should result in the same level of safety, regardless of load combinations, material characteristics and problem geometry. This proposed approach of the partial coefficients related to the material and/or action-resistance should aimed at building a bridge between calculations used so far and pure probability analysis. The measure to compare the results was to determine an equivalent safety factor for each analysis. The results show a visible wide span of equivalent values of the classic safety factors.

Keywords: action-resistance factor design, classic approach, embedded retaining wall, Eurocode 7, limit states, material factor design

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Authors: Schadrack Mwizerwa

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The characterization and prediction of landslides are crucial for assessing geological hazards and mitigating risks to infrastructure and communities. This research aims to develop a probabilistic framework for analyzing excavation-induced landslides, which is fundamental for assessing geological hazards and mitigating risks to infrastructure and communities. The study uses Hermite polynomial chaos, a non-stationary random process, to analyze the stability of a slope and characterize the failure probability of a real landslide induced by highway construction excavation. The correlation within the data is captured using the Karhunen-Loève (KL) expansion theory, and the finite element method is used to analyze the slope's stability. The research contributes to the field of landslide characterization by employing advanced random field approaches, providing valuable insights into the complex nature of landslide behavior and the effectiveness of advanced probabilistic models for risk assessment and management. The data collected from the Baiyuzui landslide, induced by highway construction, is used as an illustrative example. The findings highlight the importance of considering the probabilistic nature of landslides and provide valuable insights into the complex behavior of such hazards.

Keywords: Hermite polynomial chaos, Karhunen-Loeve, slope stability, probabilistic analysis

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Authors: Ejaz Ahmed, Huang Yong

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The operation of aero engines has a critical importance in the vicinity of lean blowout (LBO) limits. Lefebvre’s model of LBO based on empirical correlation has been extended to flame volume concept by the authors. The flame volume takes into account the effects of geometric configuration, the complex spatial interaction of mixing, turbulence, heat transfer and combustion processes inside the gas turbine combustion chamber. For these reasons, flame volume based LBO predictions are more accurate. Although LBO prediction accuracy has improved, it poses a challenge associated with Vf estimation in real gas turbine combustors. This work extends the approach of flame volume prediction previously based on fuel iterative approximation with cold flow simulations to reactive flow simulations. Flame volume for 11 combustor configurations has been simulated and validated against experimental data. To make prediction methodology robust as required in the preliminary design stage, reactive flow simulations were carried out with the combination of probability density function (PDF) and discrete phase model (DPM) in FLUENT 15.0. The criterion for flame identification was defined. Two important parameters i.e. critical injection diameter (Dp,crit) and critical temperature (Tcrit) were identified, and their influence on reactive flow simulation was studied for Vf estimation. Obtained results exhibit ±15% error in Vf estimation with experimental data.

Keywords: CFD, combustion, gas turbine combustor, lean blowout

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Authors: Ms Azam Najafkouchak, David Todem, Dorothy Pathak, Pramod Pathak, Joseph Gardiner

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Propensity score (PS) methods have recently become the standard analysis as a tool for the causal inference in the observational studies where exposure is not randomly assigned, thus, confounding can impact the estimation of treatment effect on the outcome. For the binary outcome, the effect of treatment on the outcome can be estimated by odds ratios, relative risks, and risk differences. However, using the different PS methods may give you a different estimation of the treatment effect on the outcome. Several methods of PS analyses have been used mainly, include matching, inverse probability of weighting, stratification, and covariate adjusted on PS. Due to the dangers of discretizing continuous variables (exposure, covariates), the focus of this paper will be on how the variation in cut-points or boundaries will affect the average treatment effect (ATE) utilizing the stratification of PS method. Therefore, we are trying to avoid choosing arbitrary cut-points, instead, we continuously discretize the PS and accumulate information across all cut-points for inferences. We will use Monte Carlo simulation to evaluate ATE, focusing on two PS methods, stratification and covariate adjusted on PS. We will then show how this can be observed based on the analyses of the data from a case-control study of breast cancer, the Polish Women’s Health Study.

Keywords: average treatment effect, propensity score, stratification, covariate adjusted, monte Calro estimation, breast cancer, case_control study

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Authors: Amirhossein Chambari

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This article proposes a bi-objective model for the facility location problem subject to congestion (overcrowding). Motivated by implementations to locate servers in internet mirror sites, communication networks, one-server-systems, so on. This model consider for situations in which immobile (or fixed) service facilities are congested (or queued) by stochastic demand to behave as M/M/1/K queues. We consider for this problem two simultaneous perspectives; (1) Customers (desire to limit times of accessing and waiting for service) and (2) Service provider (desire to limit average facility idle-time). A bi-objective model is setup for facility location problem with two objective functions; (1) Minimizing sum of expected total traveling and waiting time (customers) and (2) Minimizing the average facility idle-time percentage (service provider). The proposed model belongs to the class of mixed-integer nonlinear programming models and the class of NP-hard problems. In addition, to solve the model, controlled elitist non-dominated sorting genetic algorithms (Controlled NSGA-II) and controlled elitist non-dominated ranking genetic algorithms (NRGA-I) are proposed. Furthermore, the two proposed metaheuristics algorithms are evaluated by establishing standard multiobjective metrics. Finally, the results are analyzed and some conclusions are given.

Keywords: bi-objective, facility location, queueing, controlled NSGA-II, NRGA-I

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Authors: Shahrzad Yektatalab, Agrin Mohammadi, Ladan Zarshenas

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Background: Misophonia is a severe emotional response to repetitive sounds. This disorder may limit a person's communication, reduce their ability, or disrupt their social and personal life. This study aims to determine the prevalence of Misophonia and its relationship with obsessive-compulsive disorder, anxiety, and depression in undergraduate students of XXX University of Medical Sciences. Methods: The present study is an analytical descriptive study conducted in October 2020. The study samples are 390 undergraduate students of XXX University of medical sciences. A relative and systematic sampling method was used. In this study, a demographic questionnaire, misophonia questionnaire (A score of 7 or higher is considered as misophonia), Beck anxiety questionnaire, Beck depression questionnaire, and Maudsley questionnaire were used, and the data were analyzed using SPSS 24 software. Due to the non-normality of the data, the Spearman correlation coefficient was used for analyzing data. The significance level was considered less than 0.05. Results: 23.8% of students have misophonia. Of the 390 participants in the study, 93 had experienced misophonia. Among these 93 students, 37 (39.8%) had obsessive-compulsive disorder, 8 (8.6%) had anxiety and 9 (9.7%) had depression. There was a significant and direct relationship between all variables (p <0.001), which means that with the increase of each disorder, the probability of an increase in other disorders increases. Conclusion: Due to the high prevalence of misophonia in students and its direct relationship with obsessive-compulsive disorder, anxiety, and depression, It is recommended that future studies be conducted to identify ways to prevent and reduce the incidence of misophonia.

Keywords: misophonia, obsessive-compulsive disorder, anxiety, depression

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Authors: Hadi Farahani, Mahsa Tahzibi, Laleh Golamrej Eliasi, Mohammad Torkashvand

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Iranian deafs are an under-researched population. The lack of research comes from the fact that if none, there are very few researchers capable of speaking sign language. The exclusion of this minority group from mainstream society often distorts the general understanding of prevalent issues of the deaf in Iran. The topic of this research was co-created through preliminary discussions with the Iranian deaf. Domestic violence then was picked up as an infrastructural issue impacting other dimensions of deaf lives such as work, education, and outside family relationships. For this purpose, we systematically searched the literature seeking a comprehensive questionnaire. We came across a 46-item standardized questionnaire measuring domestic violence in Iran. To adapt this questionnaire, we followed standard procedures reflected in another article. The inclusion criteria of the current research were married (had experienced living with a partner before) and +18-year-old deaf. Sampling was random and recruitment of the participants was through governmental or voluntary organizations for the deaf. 390 questionnaires then were analyzed through SPSS version 27. Analysis showed that the prevalence rate of domestic violence was 26% in general that emotional violence with 29% was the most prevalent type. Findings suggested that the more educated, and economically independent were the participants, the lower the probability of encountering domestic violence. Domestic violence within families where all members were deaf proved to be less usual than in families in which only the participant was deaf. Further interventional research is needed to assess how to empower the Iranian deaf regarding domestic violence.

Keywords: deaf, domestic violence, economic violence, emotional violence, physical violence, sexual violence

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Authors: Guo Jinhong

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The purpose of this study is to explore the association between board member functions and information disclosure levels. Based on the literature variables, such as the characteristics of the board of directors in the past, a single comprehensive indicator is established as a substitute variable for board functions, and the information disclosure evaluation results published by the Securities and Foundation are used to measure the information disclosure level of the company. This study focuses on companies listed on the Taiwan Stock Exchange from 2006 to 2010 and uses descriptive statistical analysis, univariate analysis, correlation analysis and ordered normal probability (Ordered Probit) regression for empirical analysis. The empirical results show that there is a significant positive correlation between the function of board members and the level of information disclosure. This study also conducts a sensitivity test and draws similar conclusions, showing that boards with better board member functions have higher levels of information disclosure. In addition, this study also found that higher board independence, lower director shareholding pledge ratio, higher director shareholding ratio, and directors with rich professional knowledge and practical experience can help improve the level of information disclosure. The empirical results of this study provide strong support for the "relative regulations to improve the level of information disclosure" formulated by the competent authorities in recent years.

Keywords: function of board members, information disclosure, securities, foundation

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Authors: Hilda Fitria Lubis, Erna Sulistyawati

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Objective: The study aims to compare Leeway space averages between Moyers and Tanaka-Johnston's analysis of elementary school students from the Batak tribe in Medan City. Material and Methods: The study involved 106 students from the Batak tribe elementary school in Medan, comprising 53 male and 53 female students. The samples obtained were then printed on both jaws to obtain a working model, and the mesiodistal width of the four permanent biting teeth of the lower jaw and the amount of space available on the canine-premolar region, as well as the predicted mesiodistal number of the canine-premolar on the Moyers probability table with a 75% degree of confidence and the Tanaka-Johnston formula. Results: Using Moyers analysis, students at Batak Elementary School in Medan City have an average Leeway space value of 2 mm on the upper jaw and 2.78 mm on the lower jaw. The average Leeway spatial value using Tanaka-Johnston analysis in the Batak tribe in elementary school in Medan City is 1.33 mm on the top jaw and 2.39 mm on the bottom jaw. Conclusion: According to Moyers and Tanaka-Johnsnton's analysis of both the upper and lower jaws in elementary school students of the Batak tribe in Medan City, there is a significant difference between Leeway's average space.

Keywords: leeways space, batak tribe, genders, diagnosis

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Authors: N. E Okoligwe, Okezie A. Ihugba

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Few scholars disagrees that electricity consumption is an important supporting factor for economy growth. However, the relationship between electricity consumption and economy growth has different manifestation in different countries according to previous studies. This paper examines the causal relationship between electricity consumption and economic growth for Nigeria. In an attempt to do this, the paper tests the validity of the modernization or depending hypothesis by employing various econometric tools such as Augmented Dickey Fuller (ADF) and Johansen Co-integration test, the Error Correction Mechanism (ECM) and Granger Causality test on time series data from 1971-2012. The Granger causality is found not to run from electricity consumption to real GDP and from GDP to electricity consumption during the year of study. The null hypothesis is accepted at the 5 per cent level of significance where the probability value (0.2251 and 0.8251) is greater than five per cent level of significance because both of them are probably determined by some other factors like; increase in urban population, unemployment rate and the number of Nigerians that benefit from the increase in GDP and increase in electricity demand is not determined by the increase in GDP (income) over the period of study because electricity demand has always been greater than consumption. Consequently; the policy makers in Nigeria should place priority in early stages of reconstruction on building capacity additions and infrastructure development of the electric power sector as this would force the sustainable economic growth in Nigeria.

Keywords: economic growth, electricity consumption, error correction mechanism, granger causality test

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Authors: Hye-Young Shin, Chan Kee Park

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Background: To compare the thinning patterns of the ganglion cell-inner plexiform layer (GCIPL) and peripapillary retinal nerve fiber layer (pRNFL) as measured using Cirrus high-definition optical coherence tomography (HD-OCT) in patients with visual field (VF) defects that respect the vertical meridian. Methods: Twenty eyes of eleven patients with VF defects that respect the vertical meridian were enrolled retrospectively. The thicknesses of the macular GCIPL and pRNFL were measured using Cirrus HD-OCT. The 5% and 1% thinning area index (TAI) was calculated as the proportion of abnormally thin sectors at the 5% and 1% probability level within the area corresponding to the affected VF. The 5% and 1% TAI were compared between the GCIPL and pRNFL measurements. Results: The color-coded GCIPL deviation map showed a characteristic vertical thinning pattern of the GCIPL, which is also seen in the VF of patients with brain lesions. The 5% and 1% TAI were significantly higher in the GCIPL measurements than in the pRNFL measurements (all P < 0.01). Conclusions: Macular GCIPL analysis clearly visualized a characteristic topographic pattern of retinal ganglion cell (RGC) loss in patients with VF defects that respect the vertical meridian, unlike pRNFL measurements. Macular GCIPL measurements provide more valuable information than pRNFL measurements for detecting the loss of RGCs in patients with retrograde degeneration of the optic nerve fibers.

Keywords: brain lesion, macular ganglion cell, inner plexiform layer, spectral-domain optical coherence tomography

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Authors: Sultan Ghaleb Aldaihani

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- The environment in which educational leadership takes place is becoming increasingly complex due to factors like globalization and rapid technological change. - This is creating a "leadership gap" where the complexity of the environment outpaces the ability of leaders to effectively respond. - Educational leadership involves guiding teachers and the broader school system towards improved student learning and achievement. 2. Implications of Artificial Intelligence (AI) in Educational Leadership: - AI has great potential to enhance education, such as through intelligent tutoring systems and automating routine tasks to free up teachers. - AI can also have significant implications for educational leadership by providing better information and data-driven decision-making capabilities. - Computer-adaptive testing can provide detailed, individualized data on student learning that leaders can use for instructional decisions and accountability. 3. Enhancing Decision-Making Processes: - Statistical models and data mining techniques can help identify at-risk students earlier, allowing for targeted interventions. - Probability-based models can diagnose students likely to drop out, enabling proactive support. - These data-driven approaches can make resource allocation and decision-making more effective. 4. Improving Efficiency and Productivity: - AI systems can automate tasks and change processes to improve the efficiency of educational leadership and administration. - Integrating AI can free up leaders to focus more on their role's human, interactive elements.

Keywords: Education, Leadership, Technology, Artificial Intelligence

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: Sumrina Kousar

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Objective: The aim of this study was to observe the effect of fortification of expressed human breast milk with olive oil and skimmed milk in improving weight gain in very low birth weight neonates and shortening their length of hospital stay. Study Design and place: A randomized controlled trial was carried out at the Combined Military Hospital Lahore from March 2018 to March 2019. Methods: Neonates admitted with very low birth weight and gestational age of < 34 weeks were included in the study. Sixty babies were enrolled using non-probability consecutive sampling; a random number table was used to allocate them into a fortification group and a control group. The control group received expressed milk alone, while olive oil 1 ml twice daily and skimmed milk 1 gram in every third feed were added to expressed milk in the fortification group. Data was analyzed on SPSS 20. Proportions were compared by applying the chi-square test. An independent sample t-test was applied for comparing means. A p-value of ≤ 0.05 was considered significant. Results: The study comprised of 60 neonates, with 30 in each of the groups. Weight gain was 24.83±5.63 in the fortification group and 11.72±3.95 in the control group (p =< 0.001). Mean hospital stay was 20.5716.511 in the fortification group and 27.678.89 in the control group (p =< 0.043). Conclusion: Olive oil and skimmed milk fortification of breast milk was effective for weight gain and reducing the length of hospital stay in very low birth weight neonates.

Keywords: fortification, olive oil, skimmed milk, weight gain

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Authors: Reshmita Nath

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In this study, we investigate the spatiotemporal characteristics of drought in India and its impact on agriculture during the summer season (April to September). For our analysis, we have used Standardized Precipitation Evapotranspiration Index (SPEI) datasets between 1982 and 2012 at six-month timescale. Based on the criteria SPEI<-1 we obtain the vulnerability map and have found that the Humid subtropical Upper Middle Gangetic Plain (UMGP) region is highly drought prone with an occurrence frequency of 40-45%. This UMGP region contributes at least 18-20% of India’s annual cereal production. Not only the probability, but the region becomes more and more drought-prone in the recent decades. Moreover, the cereal production in the UMGP has experienced a gradual declining trend from 2000 onwards and this feature is consistent with the increase in drought affected areas from 20-25% to 50-60%, before and after 2000, respectively. The higher correlation coefficient (-0.69) between the changes in cereal production and drought affected areas confirms that at least 50% of the agricultural (cereal) losses is associated with drought. While analyzing the individual impact of precipitation and surface temperature anomalies on SPEI (6), we have found that in the UMGP region surface temperature plays the primary role in lowering of SPEI. The linkage is further confirmed by the correlation analysis between the SPEI (6) and surface temperature rise, which exhibits strong negative values in the UMGP region. Higher temperature might have caused more evaporation and drying, which therefore increases the area affected by drought in the recent decade.

Keywords: drought, agriculture, SPEI, Indo-Gangetic plain

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Authors: Debasis Sarkar

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Clean development mechanism (CDM) can act as an effective instrument for mitigating climate change. This mechanism can effectively reduce the emission of CO2 and other green house gases (GHG). Construction of a mega infrastructure project like underground corridor construction for metro rail operation involves in consumption of substantial quantity of concrete which consumes huge quantity of energy consuming materials like cement and steel. This paper is an attempt to develop an integrated clean development mechanism and risk management approach for sustainable development for an underground corridor metro rail project in India during its construction phase. It was observed that about 35% reduction in CO2 emission can be obtained by adding fly ash as a part replacement of cement. The reduced emission quantity of CO2 which is of the quantum of about 21,646.36 MT would result in cost savings of approximately INR 8.5 million (USD 1,29,878).But construction and operation of such infrastructure projects of the present era are subject to huge risks and uncertainties throughout all the phases of the project, thus reducing the probability of successful completion of the project within stipulated time and cost frame. Thus, an integrated approach of combining CDM with risk management would enable the metro rail authorities to develop a sustainable risk mitigation measure framework to ensure more cost and energy savings and lesser time and cost over-run.

Keywords: clean development mechanism (CDM), infrastructure transportation, project risk management, underground metro rail

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Authors: Charity Ngoatle, Tebogo M. Mothiba, Mahlapahlapana J. Themane

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Misapprehension of medications instructions due to poor health literacy is common in diabetic patients, predominantly leading to suboptimal medication therapy caused by taking less than expected, or getting inadequate medication concentration. Globally, 50% of adults have been reported to have misunderstood medication instructions which could be the cause of not using medication as prescribed. Reading material has been found not to improve people’s knowledge to the extent where they would be informed and knowledgeable about their health. This, therefore, depicts that instructive materials alone cannot improve health literacy but further patient education is still needed to explain what the information really mean. The aim of this study was to investigate patients’ interpretation of prescribed medication instructions at Makanye Clinic in Limpopo Province, South Africa. The study used a mixed method approach. A non-probability purposive and simple random sampling strategies will be used to select ten (10) participants for the pilot study. Semi-structured interviews with a guide and self- administered structured questionnaires will be used to collect data. Tesch’s eight steps for qualitative data analysis and SPSS version 24 with descriptive statistics will be adopted. The preliminary findings from other studies show that: (a) poor health literacy negatively affect medication adherence, (b) general literacy influence health literacy, and (c) there are poor health outcomes and medication adverse effects due to poor medication comprehension.

Keywords: instructions, diabetes mellitus, patients, prescribed medication

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Authors: Ali Jahanfar, Brajesh Dubey, Bahram Gharabaghi, Saber Bayat Movahed

Abstract:

Ever increasing population growth of major urban centers and environmental challenges in siting new landfills have resulted in a growing trend in design of mega-landfills some with extraordinary heights and dangerously steep slopes. Landfill failure mobility risk analysis is one of the most uncertain types of dynamic rheology models due to very large inherent variabilities in the heterogeneous solid waste material shear strength properties. The waste flow of three historic dumpsite and two landfill failures were back-analyzed using run-out modeling with DAN-W model. The travel distances of the waste flow during landfill failures were calculated approach by taking into account variability in material shear strength properties. The probability distribution function for shear strength properties of the waste material were grouped into four major classed based on waste material compaction (landfills versus dumpsites) and composition (high versus low quantity) of high shear strength waste materials such as wood, metal, plastic, paper and cardboard in the waste. This paper presents a probabilistic method for estimation of the spatial extent of waste avalanches, after a potential landfill failure, to create maps of vulnerability scores to inform property owners and residents of the level of the risk.

Keywords: landfill failure, waste flow, Voellmy rheology, friction coefficient, waste compaction and type

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Authors: C. V. Aravinda, H. N. Prakash

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In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.

Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages

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Authors: Érick Aragão Ribeiro, George André Pereira Thé, José Marques Soares

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Several problems in industrial supervision software development projects may lead to the delay or cancellation of projects. These problems can be avoided or contained by using identification methods, analysis and control of risks. These procedures can give an overview of the possible problems that can happen in the projects and what are the immediate solutions. Therefore, we propose a risk management method applied to the teaching and development of industrial supervision software. The method is developed through a literature review and previous projects can be divided into phases of management and have basic features that are validated with experimental research carried out by mechatronics engineering students and professionals. The management is conducted through the stages of identification, analysis, planning, monitoring, control and communication of risks. Programmers use a method of prioritizing risks considering the gravity and the possibility of occurrence of the risk. The outputs of the method indicate which risks occurred or are about to happen. The first results indicate which risks occur at different stages of the project and what risks have a high probability of occurring. The results show the efficiency of the proposed method compared to other methods, showing the improvement of software quality and leading developers in their decisions. This new way of developing supervision software helps students identify design problems, evaluate software developed and propose effective solutions. We conclude that the risk management optimizes the development of the industrial process control software and provides higher quality to the product.

Keywords: supervision software, risk management, industrial supervision, project management

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Authors: Sabyasachi Biswas, Indrajit Ghosh

Abstract:

The random and heterogeneous behavior of vehicles in India puts up a greater challenge for researchers. Stop-and-go modeling at signalized intersections under heterogeneous traffic conditions has remained one of the most sought-after fields. Vehicles are often caught up in the dilemma zone and are unable to take quick decisions whether to stop or cross the intersection. This hampers the traffic movement and may lead to accidents. The purpose of this work is to develop a stop and go prediction model that depicts the drivers’ decision during the yellow time at signalised intersections. To accomplish this, certain traffic parameters were taken into account to develop surrogate model. This research investigated the Stop and Go behavior of the drivers by collecting data from 4-signalized intersections located in two major Indian cities. Model was developed to predict the drivers’ decision making during the yellow phase of the traffic signal. The parameters used for modeling included distance to stop line, time to stop line, speed, and length of the vehicle. A Kriging base surrogate model has been developed to investigate the drivers’ decision-making behavior in amber phase. It is observed that the proposed approach yields a highly accurate result (97.4 percent) by Gaussian function. It was observed that the accuracy for the crossing probability was 95.45, 90.9 and 86.36.11 percent respectively as predicted by the Kriging models with Gaussian, Exponential and Linear functions.

Keywords: decision-making decision, dilemma zone, surrogate model, Kriging

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Authors: Zeyu Zhou, Xiaojun Bi

Abstract:

Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

Procedia PDF Downloads 229