Search results for: conditional tabular GAN

Authors: Dafni Kalatzi Pantera

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How globalisation affects environmental activism? Existing research on this relationship focuses on the influence of the world polity on individuals’ willingness to participate in environmental movements. However, globalisation is a multidimensional process which promotes pro-environmental ideas through the world polity, but it also fosters economic growth which is considered antagonistic to the environment. This article models the way that globalisation as a whole affects individuals’ willingness to participate in environmental activism, and the main argument is that globalisation’s impact is conditional on political ideology. To test the above hypothesis, individual and country level data are used for European countries between 1981-2020. The results support the expectation of the article that although globalisation has a positive impact on individuals’ willingness to participate in environmental activism when it interacts with political ideology, its influence differs between ideological spectrums.

Keywords: environmental activism, globalisation, political ideology, world polity

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Authors: Daniel Mokatsanyane, Johnny Jansen Van Rensburg

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This paper is a concise introduction of the risk management on the water derivatives market. Water, a new commodity in the market, is one of the most important commodity on earth. As important to life and planet as crops, metals, and energy, none of them matters without water. This paper presents a brief overview of water as a tradable commodity via a new first of its kind futures contract on the Nasdaq Veles California Water Index (NQH2O) derivative instrument, TheGeneralised Autoregressive Conditional Heteroscedasticity (GARCH) statistical model will be the used to measure the water price volatility of the instrument and its performance since it’s been traded. describe the main products and illustrate their usage in risk management and also discuss key challenges with modeling and valuation of water as a traded commodity and finally discuss how water derivatives may be taken as an alternative asset investment class.

Keywords: water derivatives, commodity market, nasdaq veles california water Index (NQH2O, water price, risk management

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Authors: Chawarat Rotejanaprasert, Andrew Lawson

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Early detection of unusual health events depends on the ability to detect rapidly any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler (SKL) measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate (SCPO) within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study.

Keywords: Bayesian, spatial, temporal, surveillance, prospective

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Authors: Shao-Di Feng, Von-Wun Soo

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To generate symbolic music with specific emotions is a challenging task due to symbolic music datasets that have emotion labels are scarce and incomplete. This research aims to generate more refined emotions based on the training datasets that are only labeled with four quadrants in Russel’s 2D emotion model. We focus on the theory of Music Fadernet and map arousal and valence to the low-level attributes, and build a symbolic music generation model by combining transformer and GM-VAE. We adopt an in-attention mechanism for the model and improve it by allowing modulation by conditional information. And we show the music generation model could control the generation of music according to the emotions specified by users in terms of high-level linguistic expression and by manipulating their corresponding low-level musical attributes. Finally, we evaluate the model performance using a pre-trained emotion classifier against a pop piano midi dataset called EMOPIA, and by subjective listening evaluation, we demonstrate that the model could generate music with more refined emotions correctly.

Keywords: music generation, music emotion controlling, deep learning, semi-supervised learning

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Authors: Monsuru Oyenola Popoola, Oladapo Samson Abiola, Wusamotu Alao Adeniji

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The prevalent and incessant abandonment of road construction projects are alarming that it creates several negative effects to social, economic and environmental values of the project. The purpose of this paper is to investigate and determined the various causes and effects of abandoning road construction projects in Nigeria. Likert Scale questionnaire design was used to administered and analysed the data obtained for the stydy. 135 (Nr) questionnaires were completed and retrieved from the respondents, out of 200 (Nr) questionnaires sent out, representing a response rate of 67.5%. The analysis utilized the Relative Importance Index (R.I.I.) method and the results are presented in tabular form. The findings confirms that at least 20 factors were the causes of road projects abandonment in Nigeria with most including Leadership Instability, Improper Project Planning, Inconsistence in government policies and Design, Contractor Incompetence, Economy Instability and Inflation, Delay in remittance of money, Improper financial analysis, Poor risk management, Climatic Conditions, Improper Project Estimates etc. The findings also show that at least eight (8) effect were identified on the system, and these include; Waste of Financial Resources, Loss of economic value, Environmental degradation, Loss of economic value, Reduction in standard of living, Litigation and Arbitration, etc. The reflection is that allocating reasonable finance, developing appropriate and effective implementation plans and monitoring, evaluation and reporting on development project activities by key actors should enhance in resolving the problem of road projects abandonment.

Keywords: road construction, abandonment of road projects, climatic condition, project planning, contractor

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Authors: Giriraj Achari, Malay Bhattacharyya

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In this paper, the effectiveness of Copula Markov Switching Multifractal (MSM) models at forecasting Value-at-Risk of a two-stock portfolio is studied. The innovations are allowed to be drawn from distributions that can capture skewness and leptokurtosis, which are well documented empirical characteristics observed in financial returns. The candidate distributions considered for this purpose are Johnson-SU, Pearson Type-IV and α-Stable distributions. The two univariate marginal distributions are combined using the Student-t copula. The estimation of all parameters is performed by Maximum Likelihood Estimation. Finally, the models are compared in terms of accurate Value-at-Risk (VaR) forecasts using tests of unconditional coverage and independence. It is found that Copula-MSM-models with leptokurtic innovation distributions perform slightly better than Copula-MSM model with Normal innovations. Copula-MSM models, in general, produce better VaR forecasts as compared to traditional methods like Historical Simulation method, Variance-Covariance approach and Copula-Generalized Autoregressive Conditional Heteroscedasticity (Copula-GARCH) models.

Keywords: Copula, Markov Switching, multifractal, value-at-risk

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Authors: Ahmed Mozamel, Kemal Yildizli

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Due to mechanical energy losses and a competitive of minimizing these losses and increases the machine efficiency, the need for contactless gearing system has raised. In this work, one stage of mechanical planetary gear transmission system integrated with one stage of magnetic planetary gear system is designed as a two-stage hybrid gearbox system. The permanent magnets internal energy in the form of the magnetic field is used to create meshing between contactless magnetic rotors in order to provide self-system protection against overloading and decrease the mechanical loss of the transmission system by eliminating the friction losses. Classical methods, such as analytical, tabular method and the theory of elasticity are used to calculate the planetary gear design parameters. The finite element method (ANSYS Maxwell) is used to predict the behaviors of a magnetic gearing system. The concentric magnetic gearing system has been modeled and analyzed by using 2D finite element method (ANSYS Maxwell). In addition to that, design and manufacturing processes of prototype components (a planetary gear, concentric magnetic gear, shafts and the bearings selection) of a gearbox system are investigated. The output force, the output moment, the output power and efficiency of the hybrid gearbox system are experimentally evaluated. The viability of applying a magnetic force to transmit mechanical power through a non-contact gearing system is presented. The experimental test results show that the system is capable to operate continuously within the range of speed from 400 rpm to 3000 rpm with the reduction ratio of 2:1 and maximum efficiency of 91%.

Keywords: hybrid gearbox, mechanical gearboxes, magnetic gears, magnetic torque

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Authors: Fahad Abbasi

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Flow of electrically conducting nanofluids is of pivotal importance in countless industrial and medical appliances. Fluctuations in thermophysical properties of such fluids due to variations in temperature have not received due attention in the available literature. Present investigation aims to fill this void by analyzing the flow of copper-water nanofluid with temperature dependent viscosity past a Riga plate. Strong wall suction and viscous dissipation have also been taken into account. Numerical solutions for the resulting nonlinear system have been obtained. Results are presented in the graphical and tabular format in order to facilitate the physical analysis. An estimated expression for skin friction coefficient and Nusselt number are obtained by performing linear regression on numerical data for embedded parameters. Results indicate that the temperature dependent viscosity alters the velocity, as well as the temperature of the nanofluid and, is of considerable importance in the processes where high accuracy is desired. Addition of copper nanoparticles makes the momentum boundary layer thinner whereas viscosity parameter does not affect the boundary layer thickness. Moreover, the regression expressions indicate that magnitude of rate of change in effective skin friction coefficient and Nusselt number with respect to nanoparticles volume fraction is prominent when compared with the rate of change with variable viscosity parameter and modified Hartmann number.

Keywords: heat transfer, peristaltic flows, radially varying magnetic field, curved channel

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Authors: Krisada Lekdee, Sunee Sammatat, Nittaya Boonsit

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This paper proposes a GLMM with spatial and temporal effects for malaria data in Thailand. A Bayesian method is used for parameter estimation via Gibbs sampling MCMC. A conditional autoregressive (CAR) model is assumed to present the spatial effects. The temporal correlation is presented through the covariance matrix of the random effects. The malaria quarterly data have been extracted from the Bureau of Epidemiology, Ministry of Public Health of Thailand. The factors considered are rainfall and temperature. The result shows that rainfall and temperature are positively related to the malaria morbidity rate. The posterior means of the estimated morbidity rates are used to construct the malaria maps. The top 5 highest morbidity rates (per 100,000 population) are in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4, 97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82). According to the DIC criterion, the proposed model has a better performance than the GLMM with spatial effects but without temporal terms.

Keywords: Bayesian method, generalized linear mixed model (GLMM), malaria, spatial effects, temporal correlation

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Authors: Rachid Belhachemi, Pierre Rostan, Alexandra Rostan

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This paper develops a discrete-time option pricing model for index options. The model consists of two key ingredients. First, daily stock return innovations are driven by a continuous hidden threshold mixed skew-normal (HTSN) distribution which generates conditional non-normality that is needed to fit daily index return. The most important feature of the HTSN is the inclusion of a latent state variable with a continuum of states, unlike the traditional mixture distributions where the state variable is discrete with little number of states. The HTSN distribution belongs to the class of univariate probability distributions where parameters of the distribution capture the dependence between the variable of interest and the continuous latent state variable (the regime). The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. It has been shown empirically that this distribution outperforms its main competitor, the mixed normal (MN) distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence. Second, heteroscedasticity in the model is captured by a threeexogenous-factor GARCH model (GARCHX), where the factors are taken from the principal components analysis of various world indices and presents an application to option pricing. The factors of the GARCHX model are extracted from a matrix of world indices applying principal component analysis (PCA). The empirically determined factors are uncorrelated and represent truly different common components driving the returns. Both factors and the eight parameters inherent to the HTSN distribution aim at capturing the impact of the state of the economy on price levels since distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. The PCA identifies statistically independent factors affecting the random evolution of a given pool of assets -in our paper a pool of international stock indices- and sorting them by order of relative importance. The PCA computes a historical cross asset covariance matrix and identifies principal components representing independent factors. In our paper, factors are used to calibrate the HTSN-GARCHX model and are ultimately responsible for the nature of the distribution of random variables being generated. We benchmark our model to the MN-GARCHX model following the same PCA methodology and the standard Black-Scholes model. We show that our model outperforms the benchmark in terms of RMSE in dollar losses for put and call options, which in turn outperforms the analytical Black-Scholes by capturing the stylized facts known for index returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.

Keywords: continuous hidden threshold, factor models, GARCHX models, option pricing, risk-premium

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Authors: Kyugneun Lee, Ikjin Lee

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Parameter estimation with inverse problem often suffers from unfavorable conditions in the real world. Useless data and many input parameters make the problem complicated or insoluble. Data refinement and reformulation of the problem can solve that kind of difficulties. In this research, a method to solve the rank deficient inverse problem is suggested. A multi-physics system which has rank deficiency caused by response correlation is treated. Impeditive information is removed and the problem is reformulated to sequential estimations using Bayesian network (BN) and subset groups. At first, subset grouping of the responses is performed. Feature selection with singular value decomposition (SVD) is used for the grouping. Next, BN inference is used for sequential conditional estimation according to the group hierarchy. Directed acyclic graph (DAG) structure is organized to maximize the estimation ability. Variance ratio of response to noise is used to pairing the estimable parameters by each response.

Keywords: Bayesian network, feature selection, rank deficiency, statistical inverse analysis

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Authors: Neil Michael Walsh, Angelique Lombarts

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The authors propose that hospitality is ‘made’ (constituted and performed) in the encounters on the Silk-Routes. Inspired with an initial Derridean perspective on hospitality (the conditional/unconditional) and methodologically underpinned with a Delueuzian relational-rhizomatic approach, the authors contend that hospitality is (re)produced in the encounters of self/other, east/west (among others). Thus, in the spirit of performativity and using the temporal-spatial conduit of the Silk Routes (the sites of ethical, cultural, economic, and material interaction of such exchange), the authors concur that hospitality is produced at the moment in which it is performed. Key themes engaged as units of analysis become welcome, reception, hostility, (and so on) which the authors engage and examine –as they unfold- in the narratives and accounts and material legacies of those who travelled the Silk Routes between the 2nd and 18th Centuries. The preliminary results suggest that these earlier performative moments in hospitality-making on the silk routes continue to resonate and ‘form’ the hospitalities of today. Indeed, these acts of hospitality continue to reconstitute and are never a final state of affairs.

Keywords: hospitality-genealogy, interactions, hospitality-making, Silk-Routes, rhizome, relationality

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Authors: Yongqin Zhang, John Lett

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Geospatial technologies have been increasingly used in agriculture for various applications and purposes in recent years. Unmanned aerial vehicles (drones) fit the needs of farmers in farming operations, from field spraying to grow cycles and crop health. In this research, we conducted a practical research project that used drone technology to design and map optimal locations and layouts of irrigation systems for agriculture farms. We flew a DJI Mavic 2 Pro drone to acquire aerial remote sensing images over two agriculture fields in Forest, Mississippi, in 2022. Flight plans were first designed to capture multiple high-resolution images via a 20-megapixel RGB camera mounted on the drone over the agriculture fields. The Drone Deploy web application was then utilized to develop flight plans and subsequent image processing and measurements. The images were orthorectified and processed to estimate the area of the area and measure the locations of the water line and sprinkle heads. Field measurements were conducted to measure the ground targets and validate the aerial measurements. Geospatial analysis and photogrammetric measurements were performed for the study area to determine optimal layout and quantitative estimates for irrigation systems. We created maps and tabular estimates to demonstrate the locations, spacing, amount, and layout of sprinkler heads and water lines to cover the agricultural fields. This research project provides scientific guidance to Mississippi farmers for a precision agricultural irrigation practice.

Keywords: drone images, agriculture, irrigation, geospatial analysis, photogrammetric measurements

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Authors: M. Kashiripoor

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Existing indicators for sustainable urban development do not identify the features of cities’ planning structures and their architecture. Iranian city has special relevance problem of assessing the conformity of their planning and development of the concept of sustainable development. Based on theoretical sources, the author concludes that, despite the existence of common indicators for sustainable development of settlements, specialized evaluation criteria city structure planning has not been developed. He is trying to fill this gap and put forward a system of indicators characterizing the level of development of the architectural-planning structure of the city. The proposed system of indicators is designed based on technical and economic urban standard indicators from different countries. Alternative designing systems and requirements of modern rating systems like LEED-ND comprise a criterion for evaluation of urban structures in accordance with principles of "Green" building and New Urbanism. Urban development trends are close in spirit of sustainable development and developed under its influence. The study allowed concluding that a system of indicators to identify the relevant architectural-planning structure of the city, requirements of sustainable development, should be adapted to the conditions of each country, particularly in Iran. The article attempts typology proposed indicators, which are presented in tabular form and are divided into two types: planning and spatial. This article discusses the known indicators of sustainable development and proposed specific system of indicators characterizing the level of development of architectural-planning structure of the city. This article examines indicators for evaluating level of city' planning structure development. The proposed system of indicators is derived from the urban planning standards and rating systems such as LEED-ND, BREEAM Community and CASBEE-UD.

Keywords: architectural-planning structure of cities, urban planning indicators, urban space indicators, urban development

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Authors: Promothes Saha

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Recently, transportation engineering industry members at the study university showed concern that students lacked the skills needed to solve real-world engineering problems using spreadsheet data analysis. In response to the concerns shown by industry members, this study investigated how to engage students in a better way by incorporating spreadsheet analysis during class - also, help them learn the course topics. Helping students link theoretical knowledge to real-world problems can be a challenge. In this effort, in-class activities and worksheets were redesigned to integrate with Excel to solve example problems using built-in tools including cell referencing, equations, data analysis tool pack, solver tool, conditional formatting, charts, etc. The effectiveness of this technique was investigated using students’ evaluations of the course, enrollment data, and students’ comments. Based on the data of those criteria, it is evident that the spreadsheet activities may increase student learning.

Keywords: civil, engineering, active learning, transportation

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Authors: Ajibola Isola, Shattri Mansor, Ojogbane Sani, Olugbemi Tope

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The cadastral map is the rationale behind city management planning and development. For years, cadastral maps have been produced by ground and photogrammetry platforms. Recent evolution in photogrammetry and remote sensing sensors ignites the use of Unmanned Aerial Vehicle systems (UAVs) for cadastral mapping. Despite the time-saving and multi-dimensional cost-effectiveness of the UAV platform, issues related to cadastral map accuracy are a hindrance to the wide applicability of UAVs' cadastral mapping. This study aims to present an approach leading to the generation and assessing the credibility of UAV cadastral mapping. Different sets of Red, Green, and Blue (RGB) photos were obtained from the Tarot 680-hexacopter UAV platform flown over the Universiti Putra Malaysia campus sports complex at an altitude range of 70 m, 100 m, and 250. Before flying the UAV, twenty-eight ground control points were evenly established in the study area with a real-time kinematic differential global positioning system. The second phase of the study utilizes an image-matching algorithm for photos alignment wherein camera calibration parameters and ten of the established ground control points were used for estimating the inner, relative, and absolute orientations of the photos. The resulting orthoimages are exported to ArcGIS software for digitization. Visual, tabular, and graphical assessments of the resulting cadastral maps showed a different level of accuracy. The results of the study show a gradual approach for generating UAV cadastral mapping and that the cadastral map acquired at 70 m altitude produced better results.

Keywords: aerial mapping, orthomosaic, cadastral map, flying altitude, image processing

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Authors: D. Mokatsanyane, J. Jansen Van Rensburg

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This paper analyses the influence and impact of COVID-19 on major agricultural commodity prices in South Africa. According to a World Bank report, the agricultural sector in South Africa has been unable to reduce the domestic food crisis that has been occurring over the past years, hence the increased rate of poverty, which is currently at 55.5 percent as of April 2020. Despite the significance of this sector, empirical findings concluded that the agricultural sector now accounts for 1.88 percent of South Africa's gross domestic product (GDP). Suggesting that the agricultural sector's contribution to the economy has diminished. Despite the low contribution to GDP, this primary sector continues to play an essential role in the economy. Over the past years, multiple factors have contributed to the soaring commodities prices, namely, climate shocks, biofuel demand, demand and supply shocks, the exchange rate, speculation in commodity derivative markets, trade restrictions, and economic growth. The COVID-19 outbursts have currently disturbed the supply and demand of staple crops. To address the disruption, the government has exempted the agricultural sector from closure and restrictions on movement. The spread of COVID-19 has caused turmoil all around the world, but mostly in developing countries. According to Statistic South Africa, South Africa's economy decreased by seven percent in 2020. Consequently, this has arguably made the agricultural sector the most affected sector since slumped economic growth negatively impacts food security, trade, farm livelihood, and greenhouse gas emissions. South Africa is sensitive to the fruitfulness of global food chains. Restrictions in trade, reinforced sanitary control systems, and border controls have influenced food availability and prices internationally. The main objective of this study is to evaluate the behavior of agricultural commodity prices pre-and during-COVID to determine the impact of volatility drivers on these crops. Historical secondary data of spot prices for the top five major commodities, namely white maize, yellow maize, wheat, soybeans, and sunflower seeds, are analysed from 01 January 2017 to 1 September 2021. The timeframe was chosen to capture price fluctuations between pre-COVID-19 (01 January 2017 to 23 March 2020) and during-COVID-19 (24 March 2020 to 01 September 2021). The Generalised Autoregressive Conditional Heteroscedasticity (GARCH) statistical model will be used to measure the influence of price fluctuations. The results reveal that the commodity market has been experiencing volatility at different points. Extremely high volatility is represented during the first quarter of 2020. During this period, there was high uncertainty, and grain prices were very volatile. Despite the influence of COVID-19 on agricultural prices, the demand for these commodities is still existing and decent. During COVID-19, analysis indicates that prices were low and less volatile during the pandemic. The prices and returns of these commodities were low during COVID-19 because of the government's actions to respond to the virus's spread, which collapsed the market demand for food commodities.

Keywords: commodities market, commodity prices, generalised autoregressive conditional heteroscedasticity (GARCH), Price volatility, SAFEX

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Authors: I. Nyoman Mahayasa Adiputra

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Data in the field of health can be useful for the purposes of data analysis, one example of health data is disease data. Disease data is usually in a geographical plot in accordance with the area. Where the data was collected, in the city of Denpasar, Bali. Disease data report is still published in tabular form, disease information has not been mapped in GIS form. In this research, disease information in Denpasar city will be digitized in the form of a geographic information system with the smallest administrative area in the form of district. Denpasar City consists of 4 districts of North Denpasar, East Denpasar, West Denpasar and South Denpasar. In this research, we use Google fusion table technology for map digitization process, where this technology can facilitate from the administrator and from the recipient information. From the administrator side of the input disease, data can be done easily and quickly. From the receiving end of the information, the resulting GIS application can be published in a website-based application so that it can be accessed anywhere and anytime. In general, the results obtained in this study, divided into two, namely: (1) Geolocation of Denpasar and all of Denpasar districts, the process of digitizing the map of Denpasar city produces a polygon geolocation of each - district of Denpasar city. These results can be utilized in subsequent GIS studies if you want to use the same administrative area. (2) Dengue fever mapping in 2014 and 2015. Disease data used in this study is dengue fever case data taken in 2014 and 2015. Data taken from the profile report Denpasar Health Department 2015 and 2016. This mapping can be useful for the analysis of the spread of dengue hemorrhagic fever in the city of Denpasar.

Keywords: geographic information system, Google fusion table technology, delivery of disease data information, Denpasar city

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Authors: Kasirga Yildirak, Ismail Gur

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We propose a model to measure hail risk of an Agricultural Insurance portfolio. Hail is one of the major catastrophic event that causes big amount of loss to an insurer. Moreover, it is very hard to predict due to its strange atmospheric characteristics. We make use of parcel based claims data on apricot damage collected by the Turkish Agricultural Insurance Pool (TARSIM). As our ultimate aim is to compute the loadings assigned to specific parcels, we build a portfolio risk model that makes use of PD and the severity of the exposures. PD is computed by Spherical-Linear and Circular –Linear regression models as the data carries coordinate information and seasonality. Severity is mapped into integer brackets so that Probability Generation Function could be employed. Individual regressions are run on each clusters estimated on different criteria. Loss distribution is constructed by Panjer Recursion technique. We also show that one risk-one crop model can easily be extended to the multi risk–multi crop model by assuming conditional independency.

Keywords: hail insurance, spherical regression, circular regression, spherical clustering

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Aleksandra Tepic-Horecki, Zdravko Sumic

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In this paper, the influence of six different phytochemical content (phenols, carotenoids, chlorophyll a, chlorophyll b, chlorophyll a + b and vitamin C) on antioxidant potential of Murai and Levistro lettuce varieties was evaluated. Variable selection was made by generalized pair correlation method (GPCM) as a novel ranking method. This method is used for the discrimination between two variables that almost equal correlate to a dependent variable. Fisher’s conditional exact and McNemar’s test were carried out. Established multiple linear (MLR) models were statistically evaluated. As the best phytochemicals for the antioxidant potential prediction, chlorophyll a, chlorophyll a + b and total carotenoids content stand out. This was confirmed through both GPCM and MLR, predictive ability of obtained MLR can be used for antioxidant potential estimation for similar lettuce samples. This article is based upon work from the project of the Provincial Secretariat for Science and Technological Development of Vojvodina (No. 114-451-347/2015-02).

Keywords: antioxidant activity, generalized pair correlation method, lettuce, regression analysis

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Authors: Firano Zakaria, Filali Adib Fatine

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The issue f convergence in theoretical models (classical or Keynesian) has been widely discussed. The results of the work affirm that most countries are seeking to get as close as possible to a steady state in order to catch up with developed countries. In this paper, we have retested this question whether it is absolute or conditional. The results affirm that the degree of convergence of countries like Morocco is very low and income is still far from its equilibrium state. Moreover, the analysis of financial convergence, of the countries in our panel, states that the pace in this sector is more intense: countries are converging more rapidly in financial terms. The question arises as to why, with a fairly convergent financial system, growth does not respond, yet the financial system should facilitate this economic convergence. Our results confirm that the degree of information exchange between the financial system and the economic system did not change significantly between 1985 and 2017. This leads to the hypothesis that the financial system is failing to serve its role as a creator of information in developing countries despite all the reforms undertaken, thus making the existence of an economic demon in the Maxwell prevail.

Keywords: economic convergence, financial convergence, financial system, entropy

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Authors: Nael Y. Zabel, Maged E. Georgy, Moheeb E. Ibrahim

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A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. This paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords: expert system, knowledge management, pipeline projects, risk mismanagement

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Authors: Jorge M. Uribe

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We propose a methodology for setting the price of an insurance contract targeted to manage the risk associated with weather conditions that affect variable renewable energy generation. The methodology relies on conditional quantile regressions to estimate the weather risk of a solar panel. It is illustrated using real daily radiation and weather data for three cities in Spain (Valencia, Barcelona and Madrid) from February 2/2004 to January 22/2019. We also adapt the concepts of value at risk and expected short fall from finance to this context, to provide a complete panorama of what we label as weather risk. The methodology is easy to implement and can be used by insurance companies to price a contract with the aforementioned characteristics when data about similar projects and accurate cash flow projections are lacking. Our methodology assigns a higher price to an insurance product with the stated characteristics in Madrid, compared to Valencia and Barcelona. This is consistent with Madrid showing the largest interquartile range of operational deficits and it is unrelated to the average value deficit, which illustrates the importance of our proposal.

Keywords: insurance, weather, vre, risk

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Authors: Sofia Sehli, Zainab El Ouafi, Casey Eddington, Soumaya Jbara, Kasambula Arthur Shem, Islam El Jaddaoui, Ayorinde Afolayan, Olaitan I. Awe, Allissa Dillman, Hassan Ghazal

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The ability to promptly sequence whole genomes at a relatively low cost has revolutionized the way we study the microbiome. Microbiologists are no longer limited to studying what can be grown in a laboratory and instead are given the opportunity to rapidly identify the makeup of microbial communities in a wide variety of environments. Analyzing whole genome sequencing (WGS) data is a complex process that involves multiple moving parts and might be rather unintuitive for scientists that don’t typically work with this type of data. Thus, to help lower the barrier for less-computationally inclined individuals, TAXAPRO was developed at the first Omics Codeathon held virtually by the African Society for Bioinformatics and Computational Biology (ASBCB) in June 2021. TAXAPRO is an advanced metagenomics pipeline that accurately assembles organelle genomes from whole-genome sequencing data. TAXAPRO seamlessly combines WGS analysis tools to create a pipeline that automatically processes raw WGS data and presents organism abundance information in both a tabular and graphical format. TAXAPRO was evaluated using COVID-19 patient gut microbiome data. Analysis performed by TAXAPRO demonstrated a high abundance of Clostridia and Bacteroidia genera and a low abundance of Proteobacteria genera relative to others in the gut microbiome of patients hospitalized with COVID-19, consistent with the original findings derived using a different analysis methodology. This provides crucial evidence that the TAXAPRO workflow dispenses reliable organism abundance information overnight without the hassle of performing the analysis manually.

Keywords: metagenomics, shotgun metagenomic sequence analysis, COVID-19, pipeline, bioinformatics

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Authors: Tariq Aziz, Suresh Kumar, Vikesh Kumar, Sheraz Mustafa, Jhanzeb Marwat

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The paper provides an updated version of volatility spillover among the equity markets of South Asian countries, including Pakistan, India, Srilanka, and Bangladesh. The analysis uses both symmetric and asymmetric Generalized Autoregressive Conditional Heteroscedasticity models to investigate volatility persistence and leverage effect. The bivariate EGARCH model is used to test for volatility transmission between two equity markets. Weekly data for the period February 2013 to August 2019 is used for empirical analysis. The findings indicate that the leverage effect exists in the equity markets of all the countries except Bangladesh. The volatility spillover from the equity market of Bangladesh to all other countries is negative and significant whereas the volatility of the equity market of Sri-Lanka does influence the volatility of any other country’s equity market. Indian equity market influence only the volatility of the Sri-Lankan equity market; and there is bidirectional volatility spillover between the equity markets of Pakistan and Bangladesh. The findings are important for policy-makers and international investors.

Keywords: volatility spillover, volatility persistence, garch, egarch

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Authors: Alhage Drammeh

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The research is on the occurrence of certain diseases among children in rural and far-flung parts of the Gambia and the extent to which they are caused by lack of access to clean water. A baseline survey was used to discover, describe, and explain the actual processes. The paper explains the purpose of the research, which is majorly to improve the health condition of children, especially those living in rural communities. The paper also gives a brief overview of the socio-economic situation of The Gambia, emphasizing its status as a Least Developed Country (LDC) and the majority of its population living below the poverty line, with women and children hardest hit. The research used as case studies of two rural communities in the Gambia -Basse Dampha Kunda Village and Foni Besse. Data was collected through oral interviews and medical tests conducted among people in both villages, with an emphasis on children. The demographic detail of those tested is tabulated for a clearer understanding. The results were compared, revealing that skin rashes, hepatitis, and certain other diseases are more prevalent in communities lacking access to safe drinking water. These results were also presented in a tabular form. The study established how some policy failures and neglect on the part of the Government of The Gambia are imperiling the health of many rural dwellers in the country, the most glaring being that the research team was unable to test water samples collected from the two communities, as there are no laboratory reagents for testing water anywhere in The Gambia. Many rural communities lack basic amenities, especially clean and potable water, as well as health facilities. The study findings also highlighted the need for healthcare providers and medical NGOs to voice the plight of rural dwellers and collaborate with the government to set up health facilities in rural areas of The Gambia.

Keywords: jaundice, skin rashes, children, rural communities, the Gambia, causes

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Authors: Malik SS, Masood N, Mubarik S, Khadim TM

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Introduction: Xeroderma pigmentosum group G (XPG) gene plays a crucial role in the correction of UV-induced DNA damage through nucleotide excision repair pathway. Single nucleotide polymorphisms in XPG gene have been reported to be associated with different cancers. Current case-control study was designed to evaluate the relationship between one of the most frequently found XPG (rs1047768 T>C) polymorphism and breast cancer risk. Methodology: A total of 200 individuals were screened for this polymorphism including 100 pathologically confirmed breast cancer cases and age-matched 100 controls. Genotyping was carried out using Tetra amplification-refractory mutation system (ARMS) PCR and results were confirmed by gel electrophoresis. Results: Conditional logistic regression analysis showed significant association between TC genotype (OR: 8.9, CI: 2.0 – 38.7) and increased breast cancer risk. Although homozygous CC genotype was more frequent in patients as compared to controls, but it was statistically non-significant (OR: 3.9, CI: 0.4 – 35.7). Conclusion: In conclusion, XPG (rs1047768 T>C) polymorphism may contribute towards increased risk of breast cancer but other polymorphisms may also be evaluated to elucidate their role in breast cancer.

Keywords: XPG, breast cancer, NER, ARMS-PCR

Procedia PDF Downloads 161

Authors: Jan Henrik Wosnitza

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The logistic regression has developed into a standard approach for estimating conditional probabilities in a wide range of applications including credit risk prediction. The article at hand contributes to the current literature on logistic regression fourfold: First, it is demonstrated that the binary logistic regression automatically meets its model assumptions under very general conditions. This result explains, at least in part, the logistic regression's popularity. Second, the requirement of homoscedasticity in the context of binary logistic regression is theoretically substantiated. The variances among the groups of defaulted and non-defaulted obligors have to be the same across the level of the aggregated default indicators in order to achieve linear logits. Third, this article sheds some light on the question why nonlinear logits might be superior to linear logits in case of a small amount of data. Fourth, an innovative methodology for estimating correlations between obligor-specific log-odds is proposed. In order to crystallize the key ideas, this paper focuses on the example of credit risk prediction. However, the results presented in this paper can easily be transferred to any other field of application.

Keywords: correlation, credit risk estimation, default correlation, homoscedasticity, logistic regression, nonlinear logistic regression

Procedia PDF Downloads 394

Authors: Ana B. Vivas, Antonia Ypsilanti, Aristea I. Ladas, Angeles F. Estevez

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Mild Cognitive Impairment (MCI) is considered an intermediate stage between normal and pathological aging, as a substantial percentage of people diagnosed with MCI converts later to dementia of the Alzheimer’s type. Memory is of the first cognitive processes to deteriorate in this condition. In the present study we employed the differential outcomes procedure (DOP) to improve visuospatial memory in a group of participants with MCI. The DOP requires the structure of a conditional discriminative learning task in which a correct choice response to a specific stimulus-stimulus association is reinforced with a particular reinforcer or outcome. A group of 10 participants with MCI, and a matched control group had to learn and keep in working memory four target locations out of eight possible locations where a shape could be presented. Results showed that participants with MCI had a statistically significant better terminal accuracy when a unique outcome was paired with a location (76% accuracy) as compared to a non differential outcome condition (64%). This finding suggests that the DOP is useful in improving working memory in MCI patients, which may delay their conversion to dementia.

Keywords: mild cognitive impairment, working memory, differential outcomes, cognitive process

Procedia PDF Downloads 434

Authors: Josip Visković, Josip Arnerić, Ante Rozga

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Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modelling time varying volatility are GARCH type models. When financial returns exhibit sudden jumps that are due to structural breaks, standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance. In such situations models in which the parameters are allowed to change over time are more appropriate. This paper compares different GARCH models in terms of their ability to describe structural changes in returns caused by financial crisis at stock markets of six selected central and east European countries. The empirical analysis demonstrates that Markov regime switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility when sudden switching occurs in response to financial crisis.

Keywords: central and east European countries, financial crisis, Markov switching GARCH model, transition probabilities

Procedia PDF Downloads 201