Search results for: empirical modeling

Authors: Riad Benelmir, Muhammad Shoaib Ahmed Khan

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The socio-economic importance of the olive oil production is significant in the Mediterranean region, both in terms of wealth and tradition. However, the extraction of olive oil generates huge quantities of wastes that may have a great impact on land and water environment because of their high phytotoxicity. Especially olive mill wastewater (OMWW) is one of the major environmental pollutants in olive oil industry. This work projects to design a smart and sustainable integrated thermochemical catalytic processes of residues from olive mills by hydrothermal carbonization (HTC) of olive mill wastewater (OMWW) and fast pyrolysis of olive mill wastewater sludge (OMWS). The byproducts resulting from OMWW-HTC treatment are a solid phase enriched in carbon, called biochar and a liquid phase (residual water with less dissolved organic and phenolic compounds). HTC biochar can be tested as a fuel in combustion systems and will also be utilized in high-value applications, such as soil bio-fertilizer and as catalyst or/and catalyst support. The HTC residual water is characterized, treated and used in soil irrigation since the organic and the toxic compounds will be reduced under the permitted limits. This project’s concept includes also the conversion of OMWS to a green diesel through a catalytic pyrolysis process. The green diesel is then used as biofuel in an internal combustion engine (IC-Engine) for automotive application to be used for clean transportation. In this work, a theoretical study is considered for the use of heat from the pyrolysis non-condensable gases in a sorption-refrigeration machine for pyrolysis gases cooling and condensation of bio-oil vapors.

Keywords: biomass, olive oil extraction, adsorption cooling, pyrolisis

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Authors: Muhammad Umar Kiani, Muhammad Shahbaz

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Performance of any vehicle can be predicted by its design/modeling and optimization. Design optimization leads to efficient performance. Followed by horizontal launch, the air launch re-entry vehicle undergoes a launch maneuver by introducing a carefully selected angle of attack profile. This angle of attack profile is the basic element to complete a specified mission. Flight program of said vehicle is optimized under the constraints of the maximum allowed angle of attack, lateral and axial loads and with the objective of reaching maximum altitude. The main focus of this study is the endo-atmospheric phase of the ascent trajectory. A three degrees of freedom trajectory model is simulated in MATLAB. The optimization process uses evolutionary algorithm, because of its robustness and efficient capacity to explore the design space in search of the global optimum. Evolutionary Algorithm based trajectory optimization also offers the added benefit of being a generalized method that may work with continuous, discontinuous, linear, and non-linear performance matrix. It also eliminates the requirement of a starting solution. Optimization is particularly beneficial to achieve maximum advantage without increasing the computational cost and affecting the output of the system. For the case of launch vehicles we are immensely anxious to achieve maximum performance and efficiency under different constraints. In a launch vehicle, flight program means the prescribed variation of vehicle pitching angle during the flight which has substantial influence reachable altitude and accuracy of orbit insertion and aerodynamic loading. Results reveal that the angle of attack profile significantly affects the performance of the vehicle.

Keywords: endo-atmospheric, evolutionary algorithm, efficient performance, optimization process

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Authors: Jill Steel

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The interlinked issues of emotional wellbeing and attainment continue to dominate international educational discourse. Reading skills are particularly important to attainment in all areas of the curriculum, and illiteracy is associated with reduced wellbeing and life prospects, with serious ramifications for the wider economy and society. Research shows that reading attainment is influenced by reading motivation and frequency. Reading to Dogs (RTD) is increasingly applied to promote reading motivation and frequency in schools despite a paucity of empirical evidence, specifically examining the influence of RTD on emotional wellbeing and engagement with reading. This research aims to examine whether RTD is effective in promoting these positive outcomes among children aged eight to nine years. This study also aims to inform much needed regulation of the field and standards of practice, including both child and dog welfare. Therefore, ethical matters such as children’s inclusion and safety, as well as the rights and wellbeing of dogs infuse the study throughout. The methodological design is a mixed method longitudinal study. A UK wide questionnaire will be distributed to teachers between January and June 2020 to understand their perceptions of RTD. Following this, a randomised controlled trial (N = 100) will begin in August 2020 in two schools of a comparable demographic, with N= 50 in the intervention school, and N= 50 in a waiting list control school. Reading and wellbeing assessments will be conducted prior to and immediately post RTD, and four weeks after RTD to measure sustained changes. The reading assessments include New Group Reading Test, Motivation to Read Profile (Gambrell et al., 1995), as well as reading frequency and reading anxiety assessments specifically designed for the study. Wellbeing assessments include Goodman’s SDQ, (1997) and pupil self-reporting questionnaires specifically designed for the study. Child, class teacher, and parent questionnaires and interviews prior to, during and post RTD will be conducted to measure perceptions of the impact of RTD on mood and motivation towards reading. This study will make a substantial contribution to our understanding of the effectiveness of RTD and thus have consequences for the fields of education and anthrozoology.

Keywords: animal assisted intervention, reading to dogs, welfare, wellbeing

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Authors: Beeto W. C. Leung, Nicole C. Y. Lee

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It was well known that college students experienced a high level of stress and anxiety. College athletes, a special group of college students, may even encounter a higher level of pressure and distress due to their dual endeavors in academic and athletic settings. Due to the high demands and costs of mental health services, easily accessible, web-based self-help interventions are getting more popular. The aim of the present experimental study was to examine the potential intervention effect of a mindfulness-based self-help mobile App, called 'Smiling Mind', on mindfulness and psychological well-being. Forty-six college athletes, recruited from athletic teams of two local universities in Hong Kong, were randomly assigned to the Mindfulness App Group (MAG) and the Control Group (CG). All participants were administered the Mindful Attention Awareness Scale, Geriatric Depression Scale, and Perceived Stress Scale-10 before the study (Time 1, T1) and after the 4-week intervention (Time 2, T2). MAG was requested to use the app and follow the instructions every day for at least 5 days per week. Participants were also asked to record their daily app usage time. Results showed that, for MAG, from T1 to T2, mindfulness has been increased from 3.25 to 3.92; depressive symptoms and stress has been significantly decreased from 8.6 to 5.1 and 24.8 to 13.5 respectively while for the CG, mindfulness has been decreased slightly from 3.29 to 3.13; depressive symptoms and stress has been slightly increased from 7.1 to 7.3 and 24.1 to 27.1 respectively. Three mixed-design ANOVAs with time (T1, T2) as the within-subjects factor and intervention group (MAG, CG) as the between-subjects factor revealed a main effect of time on mindfulness, F(1, 41) = 10.28, p < 0.01, depressive symptoms, F(1, 41) = 6.55, p < 0.02 and stress, F(1, 41) = 16.96, p < 0.001 respectively. Both predicted interaction between time and intervention group on mindfulness, F(1, 41) = 26.6, p < 0.001, ηp 2 =0.39, depressive symptoms, F(1, 41) = 8.00, p < 0.01, ηp 2 =0.16 and Stress F(1, 41) = 49.3, p < 0.001, ηp 2 =0.55 were significant meaning that participants using the Mindfulness Mobile App in the intervention did experienced a significant increase in mindfulness and significant decrease in depressive symptoms and perceived level of stress after the 4-week intervention when compared with the control group. The present study provided encouraging empirical support for using Smiling Mind, a self-help mobile app, to promote mindfulness and mental health in a cost-effective way. Further studies should examine the potential use of Smiling Mind in different samples, including children and adolescence, as well as, investigate the lasting effects of using the app on other psychosocial outcomes such as emotional regulations.

Keywords: college athletes, experimental study, mindfulness mobile apps, psychological well-being

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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Authors: Sijuade A. A., Oguntoye J. P., Awodoye O. O., Adedapo O. A., Wahab W. B., Okediran O. O., Omidiora E. O., Olabiyisi S. O.

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Electronic voting systems have been introduced to improve the efficiency, accuracy, and transparency of the election process in many countries around the world, including Nigeria. However, concerns have been raised about the security and integrity of these systems. One way to address these concerns is through the implementation of electronic forensic election audit systems. This study aims to evaluate voters' intention to the adoption of electronic forensic election audit systems using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. In the study, the UTAUT model which is a widely used model in the field of information systems to explain the factors that influence individuals' intention to use a technology by integrating performance expectancy, effort expectancy, social influence, facilitating conditions, cost factor and privacy factor to voters’ behavioural intention was proposed. A total of 294 sample data were collected from a selected population of electorates who had at one time or the other participated in at least an electioneering process in Nigeria. The data was then analyzed statistically using Partial Least Square Structural Equation Modeling (PLS-SEM). The results obtained show that all variables have a significant effect on the electorates’ behavioral intention to adopt the development and implementation of an electronic forensic election audit system in Nigeria.

Keywords: election Audi, voters, UTAUT, performance expectancy, effort expectancy, social influence, facilitating condition social influence, facilitating conditions, cost factor, privacy factor, behavioural intention

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Authors: Thohaku Abdul Hadi, Hadyan Perdana Putra, Nugroho Wicaksono, Adhika Prajna Nandiwardhana, Onang Surya Nugroho, Heri Suryoatmojo, Soedibjo

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Access to electricity is now a basic requirement of mankind. Unfortunately, there are still many places around the world which have no access to electricity, such as small islands, where there could potentially be a factory, a plantation, a residential area, or resorts. Many of these places might have substantial potential for energy generation such us Photovoltaic (PV) and Wind turbine (WT), which can be used to generate electricity independently for themselves. Solar energy and wind power are renewable energy sources which are mostly found in nature and also kinds of alternative energy that are still developing in a rapid speed to help and meet the demand of electricity. PV and Wind has a characteristic of power depend on solar irradiation and wind speed based on geographical these areas. This paper presented a control methodology of hybrid small scale PV/Wind energy system that use a fuzzy logic controller (FLC) to extract the maximum power point tracking (MPPT) in different solar irradiation and wind speed. This paper discusses simulation and analysis of the generation process of hybrid resources in MPP and power conditioning unit (PCU) of Photovoltaic (PV) and Wind Turbine (WT) that is connected to the three-phase low voltage electricity grid system (380V) without battery storage. The capacity of the sources used is 2.2 kWp PV and 2.5 kW PMSG (Permanent Magnet Synchronous Generator) -WT power rating. The Modeling of hybrid PV/Wind, as well as integrated power electronics components in grid connected system, are simulated using MATLAB/Simulink.

Keywords: fuzzy MPPT, grid connected inverter, photovoltaic (PV), PMSG wind turbine

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: G. T. Ntuli

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This paper critically examines the gender dynamics of a Zulu girl child in her religio-cultural context from the postcolonial feminist perspective. As one of the former colonized ethnic groups in the South African context, the Zulu tribe used to have particular and contextual religio-cultural ways of a girl’s upbringing. This included traditional and cultural norms that any member of the community could not infringe without serious repercussions from the community members. However, the postcolonial social position of a girl child within this community became ambiguous and unpredictable due to colonial changes that enhanced gender dynamics that propelled tribal communities into deeper patriarchal structures. In the empirical study conducted within the Zulu context, which investigated the retrieval of ubuntombi (virginity) as a Zulu cultural heritage, identity and sex education as a path to adulthood, it was found that a Zulu girl child’s social position is geared towards double oppression due to gender dynamics that she experiences in her lifetime. It is these gender dynamics that are examined in this paper from the postcolonial feminist perspective. These gender dynamics are at play from the birth of a girl child, developmental stage to puberty and marriage rituals. These rituals and religio-cultural practices are meant to shape and mold a ‘good woman’ in the Zulu cultural context but social gender inequality that elevates males over females propel women social status into life denying peripheral positions. Consequently, in the place of a ‘good woman’ in the communal view, an oppressed and dehumanized woman becomes the outcome of such gender dynamics, more often treated with contempt, despised and violated in many demeaning ways. These do not only leave women economically and socio-politically impoverished, but also having to face violence of all kinds such as domestic, emotional, sexual and gender-based violence that are increasingly becoming a scourge in some of the sub-Saharan African countries including South Africa. It is for this reason that this paper becomes significant, not only within the Zulu context where the research was conducted, but also in all the countries that practice and promote patriarchal tendencies in the name of religio-cultural practices. There is a need for a different outlook as to what it means to be a ‘good woman’ in the cultural context, because if the goodness of a woman is determined by life denying cultural practices, such practices need to be deconstructed and discarded.

Keywords: feminist, gender dynamics, postcolonial, religio-cultural, Zulu girl child

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Marina Petrova

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Language policy issues related to the preservation and development of the native languages of the Russian peoples and the state languages of the national republics are increasingly becoming the focus of recent attention of educators and parents, public and national figures. Is it legal to teach the national language or the mother tongue as the state language? Due to that dispute language phobia moods easily evolve into xenophobia among the population. However, a civilized, intelligent multicultural personality can only be formed if the country develops bilingualism and multilingualism, and languages as a political tool help to find ‘keys’ to sufficiently closed national communities both within a poly-ethnic state and in internal relations of multilingual countries. The purpose of this study is to design and theoretically substantiate an efficient model of language education in the innovatively developing Republic of Sakha. 800 participants from different educational institutions of Yakutia worked at developing a multilingual model of education. This investigation is of considerable practical importance because researchers could build a methodical system designed to create conditions for the formation of a cultural language personality and the development of the multilingual communicative competence of Yakut youth, necessary for communication in native, Russian and foreign languages. The selected methodology of humane-personal and competence approaches is reliable and valid. Researchers used a variety of sources of information, including access to related scientific fields (philosophy of education, sociology, humane and social pedagogy, psychology, effective psychotherapy, methods of teaching Russian, psycholinguistics, socio-cultural education, ethnoculturology, ethnopsychology). Of special note is the application of theoretical and empirical research methods, a combination of academic analysis of the problem and experienced training, positive results of experimental work, representative series, correct processing and statistical reliability of the obtained data. It ensures the validity of the investigation’s findings as well as their broad introduction into practice of life-long language education.

Keywords: intercultural communication, language policy, multilingual and multicultural education, the Sakha Republic of Yakutia

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Authors: Badriah Alayidi, Emad Alyahya

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Background: Most people with Multiple Sclerosis (MS) report worsening balance as the condition progresses. Poor balance control is also well known to be a significant risk factor for both falling and fear of falling. The increased risk of falls with disease progression thus makes balance control an essential target of gait rehabilitation amongst people with MS. Intervention programs have developed various methods to improve balance control, and accumulating evidence suggests that exercise programs may help people with MS improve their balance. Among these methods, virtual reality (VR) is growing in popularity as a balance-training technique owing to its potential benefits, including better compliance and greater user happiness. However, it is not clear if a VR environment will induce different balance control mechanisms in MS as compared to healthy individuals or traditional environments. Therefore, this study aims to examine how individuals with MS control their balance in a VR setting. Methodology: The proposed study takes an empirical approach to estimate and determine the role of balance response in persons with MS using a VR environment. It will use primary data collected through patient observations, physiological and biomechanical evaluation of balance, and data analysis. Results: The preliminary systematic review and meta-analysis indicated that there was variability in terms of the outcome assessing balance response in people with MS. The preliminary results of these assessments have the potential to provide essential indicators of the progression of MS and contribute to the individualization of treatment and evaluation of the interventions’ effectiveness. The literature describes patients who have had the opportunity to experiment in VR settings and then used what they have learned in the real world, suggesting that this VR setting could be more appealing than conditional settings. The findings of the proposed study will be beneficial in estimating and determining the effect of VR on balance control in persons with MS. In previous studies, VR was shown to be an interesting approach to neurological rehabilitation, but more data are needed to support this approach in MS. Conclusions: The proposed study enables an assessment of balance and evaluations of a variety of physiological implications related to neural activity as well as biomechanical implications related to movement analysis.

Keywords: multiple sclerosis, virtual reality, postural control, balance

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Authors: Carla Idely Palencia-Aguilar

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Artificial wetlands play an important role at Guasca Municipality in Colombia, not only because they are used for the agroindustry, but also because more than 45 species were found, some of which are endemic and migratory birds. Remote sensing was used to determine the changes in the area occupied by water of artificial wetlands by means of Aster and Modis images for different time periods. Evapotranspiration was also determined by three methods: Surface Energy Balance System-Su (SEBS) algorithm, Surface Energy Balance- Bastiaanssen (SEBAL) algorithm, and Potential Evapotranspiration- FAO. Empirical equations were also developed to determine the relationship between Normalized Difference Vegetation Index (NDVI) versus net radiation, ambient temperature and rain with an obtained R2 of 0.83. Groundwater level fluctuations on a daily basis were studied as well. Data from a piezometer placed next to the wetland were fitted with rain changes (with two weather stations located at the proximities of the wetlands) by means of multiple regression and time series analysis, the R2 from the calculated and measured values resulted was higher than 0.98. Information from nearby weather stations provided information for ordinary kriging as well as the results for the Digital Elevation Model (DEM) developed by using PCI software. Standard models (exponential, spherical, circular, gaussian, linear) to describe spatial variation were tested. Ordinary Cokriging between height and rain variables were also tested, to determine if the accuracy of the interpolation would increase. The results showed no significant differences giving the fact that the mean result of the spherical function for the rain samples after ordinary kriging was 58.06 and a standard deviation of 18.06. The cokriging using for the variable rain, a spherical function; for height variable, the power function and for the cross variable (rain and height), the spherical function had a mean of 57.58 and a standard deviation of 18.36. Threatens of eutrophication were also studied, given the unconsciousness of neighbours and government deficiency. Water quality was determined over the years; different parameters were studied to determine the chemical characteristics of water. In addition, 600 pesticides were studied by gas and liquid chromatography. Results showed that coliforms, nitrogen, phosphorous and prochloraz were the most significant contaminants.

Keywords: DEM, evapotranspiration, geostatistics, NDVI

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Princess Ncube

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In the context of South Africa's banking sector, the prevention of bank failures is of paramount importance to ensure financial stability and economic growth. This paper focuses on the role of regulatory frameworks in safeguarding the resilience of South African banks and mitigating the risks of failures. It aims to assess the effectiveness of existing regulatory measures and proposes strategies to enhance the resilience of financial institutions in the country. The paper begins by examining the specific regulatory frameworks in place in South Africa, including capital adequacy requirements, stress testing methodologies, risk management guidelines, and supervisory practices. It delves into the evolution of these measures in response to lessons learned from past financial crises and their relevance in the unique South African banking landscape. Drawing on empirical evidence and case studies specific to South Africa, this paper evaluates the effectiveness of regulatory frameworks in preventing bank failures within the country. It analyses the impact of these frameworks on crucial aspects such as early detection of distress signals, improvements in risk management practices, and advancements in corporate governance within South African financial institutions. Additionally, it explores the interplay between regulatory frameworks and the specific economic environment of South Africa, including the role of macroprudential policies in preventing systemic risks. Based on the assessment, this paper proposes recommendations to strengthen regulatory frameworks and enhance their effectiveness in bank failure prevention in South Africa. It explores avenues for refining existing regulations to align capital requirements with the risk profiles of South African banks, enhancing stress testing methodologies to capture specific vulnerabilities, and fostering better coordination among regulatory authorities within the country. Furthermore, it examines the potential benefits of adopting innovative approaches, such as leveraging technology and data analytics, to improve risk assessment and supervision in the South African banking sector.

Keywords: banks, resolution, liquidity, regulation

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Authors: Silvano Salvador, Maryam Zarrinderakht, Alan Martin

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Open pits, which are the result of mining, are filled by water over time until the water reaches the elevation of the local water table and generates mine pit lakes. There are several specific regulations about the water quality of pit lakes, and mining operations should keep the quality of groundwater above pre-defined standards. Therefore, an accurate, acceptable numerical model predicting pit lakes’ water balance and water quality is needed in advance of mine excavation. We carry on analyzing and developing the model introduced by Crusius, Dunbar, et al. (2002) for pit lakes. This model, called “PitMod”, simulates the physical and geochemical evolution of pit lakes over time scales ranging from a few months up to a century or more. Here, a lake is approximated as one-dimensional, horizontally averaged vertical layers. PitMod calculates the time-dependent vertical distribution of physical and geochemical pit lake properties, like temperature, salinity, conductivity, pH, trace metals, and dissolved oxygen, within each model layer. This model considers the effect of pit morphology, climate data, multiple surface and subsurface (groundwater) inflows/outflows, precipitation/evaporation, surface ice formation/melting, vertical mixing due to surface wind stress, convection, background turbulence and equilibrium geochemistry using PHREEQC and linking that to the geochemical reactions. PitMod, which is used and validated in over 50 mines projects since 2002, incorporates physical processes like those found in other lake models such as DYRESM (Imerito 2007). However, unlike DYRESM PitMod also includes geochemical processes, pit wall runoff, and other effects. In addition, PitMod is actively under development and can be customized as required for a particular site.

Keywords: pit lakes, mining, modeling, hydrology

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Authors: Annamária Käferné Rácz, Bence Jáger, Balázs Kövesdi, László Dunai

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Due to the numerous advantages of steel corrugated web girders, its application field is growing for bridges as well as for buildings. The global stability behavior of such girders is significantly larger than those of conventional I-girders with flat web, thus the application of the structural steel material can be significantly reduced. Design codes and specifications do not provide clear and complete rules or recommendations for the determination of the lateral torsional buckling (LTB) resistance of corrugated web girders. Therefore, the authors made a thorough investigation regarding the LTB resistance of the corrugated web girders. Finite element (FE) simulations have been performed to develop new design formulas for the determination of the LTB resistance of trapezoidally corrugated web girders. FE model is developed considering geometrical and material nonlinear analysis using equivalent geometric imperfections (GMNI analysis). The equivalent geometric imperfections involve the initial geometric imperfections and residual stresses coming from rolling, welding and flame cutting. Imperfection sensitivity analysis was performed to determine the necessary magnitudes regarding only the first eigenmodes shape imperfections. By the help of the validated FE model, an extended parametric study is carried out to investigate the LTB resistance for different trapezoidal corrugation profiles. First, the critical moment of a specific girder was calculated by FE model. The critical moments from the FE calculations are compared to the previous analytical calculation proposals. Then, nonlinear analysis was carried out to determine the ultimate resistance. Due to the numerical investigations, new proposals are developed for the determination of the LTB resistance of trapezoidally corrugated web girders through a modification factor on the design method related to the conventional flat web girders.

Keywords: corrugated web, lateral torsional buckling, critical moment, FE modeling

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Authors: Victor Counted

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Staying true to self is complicated. In most cases, we might not fully come to terms with this realities. Just like any journey, a self-discovery experience with the ‘self’, is like a rollercoaster ride. The researcher attempts to engage the reader in an empirical study on authenticity tendencies of African Christian Millennials. Hence, attempting the all-important question: What does it actually mean to be true to self for the African youth? A comprehensive, yet an unfinished business that applies the authenticity theory in its exploratory navigations to uncover the “lived world” of the participants who were part of this study. Using a mixed methods approach, the researcher will exhaustively give account to the authenticity tendencies and experiences of the respondents in the study by providing the reader with a unique narrative for understanding what it means to be true to oneself in Africa. At the quantitative study, the participants recorded higher scores on the Authenticity Scale (AS) authentic living, while showing a significant correlation within the subscales. Hypotheses were tested at the quantitative phase, which statistically supported gender and church affiliation as possible predictors for the authenticity orientations of the participants, while being a Christian native and race/ethnicity were not impact factors statistically. The results helped the researcher to develop the objectives behind the qualitative study, where only fifteen AS-authentic living participants were interviewed to understand why they scored high on authentic living, in order to understand what it means to be authentic. The hallmark of the qualitative case study exploration was the common coping mechanism of splitting adopted by the respondents to deal with their self-crisis as they tried to remain authentic to self, whilst self-regulating and self-investing the self to discover ‘self’. Specifically, the researcher observed the concurrent utilization of some kind of the religious-self by the respondents to regulate their self crisis, as they relate with self fragmenting through different splitting stages in hope for some kind of redemption. It was an explanation that led to the conclusion that being authentic is the new pieces. Authenticity is in fragments. This proposition led the researcher to introduce a hermeneutical support-system that will enable future researchers engage more critically and responsibly with their “living human documents” in order to inspire timely solutions that resolve the concerns of authenticity and wellbeing among Millennials in Africa.

Keywords: authenticity, self, identity, self-fragmentation, weak self integration, postmodern self, splitting

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Authors: Goksel Ezgi Guzey, Bihrat Onoz

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The scarcity of streamflow gauging stations and the increasing effects of global warming cause designing water management systems to be very difficult. This study is a significant contribution to assessing regional regression models for estimating streamflow. In this study, simulated meteorological data was related to the observed streamflow data from 1971 to 2020 for 33 stream gauging stations of the Euphrates-Tigris Basin. Ordinary least squares regression was used to predict flow for 2020-2100 with the simulated meteorological data. CORDEX- EURO and CORDEX-MENA domains were used with 0.11 and 0.22 grids, respectively, to estimate climate conditions under certain climate scenarios. Twelve meteorological variables simulated by two regional climate models, RCA4 and RegCM4, were used as independent variables in the ordinary least squares regression, where the observed streamflow was the dependent variable. The variability of streamflow was then calculated with 5-6 meteorological variables and watershed characteristics such as area and height prior to the application. Of the regression analysis of 31 stream gauging stations' data, the stations were subjected to a clustering analysis, which grouped the stations in two clusters in terms of their hydrometeorological properties. Two streamflow equations were found for the two clusters of stream gauging stations for every domain and every regional climate model, which increased the efficiency of streamflow estimation by a range of 10-15% for all the models. This study underlines the importance of homogeneity of a region in estimating streamflow not only in terms of the geographical location but also in terms of the meteorological characteristics of that region.

Keywords: hydrology, streamflow estimation, climate change, hydrologic modeling, HBV, hydropower

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Authors: Mauricio Cruz, Andrés Díaz García, Martha Isabel Gómez, Juan Carlos Serrato Bermúdez

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The disadvantages of using natural substrates in SSF processes have been well recognized and mainly are associated to gradual decomposition of the substrate, formation of agglomerates and decrease of porosity bed generating limitations in the mass and heat transfer. Additionally, in several cases, materials with a high agricultural value such as sour milk, beets, rice, beans and corn have been used. Thus, the use of economic inert supports (natural or synthetic) in combination with a nutrient suspension for the production of biocontrol microorganisms is a good alternative in SSF processes, but requires further studies in the fields of modeling and optimization. Therefore, the aim of this work is to compare the performance of two inert supports, a synthetic (polyurethane foam) and a natural one (rice husk), identifying the factors that have the major effects on the productivity of T. asperellum Th204 and the maximum specific growth rate in a PROPHYTA L05® fixed bed bioreactor. For this, the six factors C:N ratio, temperature, inoculation rate, bed height, air moisture content and airflow were evaluated using a fractional design. The factors C:N and air flow were identified as significant on the productivity (expressed as conidia/dry substrate•h). The polyurethane foam showed higher maximum specific growth rate (0.1631 h-1) and productivities of 3.89 x107 conidia/dry substrate•h compared to rice husk (2.83x106) and natural substrate based on rice (8.87x106) used as control. Finally, a quadratic model was generated and validated, obtaining productivities higher than 3.0x107 conidia/dry substrate•h with air flow at 0.9 m3/h and C:N ratio at 18.1.

Keywords: bioprocess, scale up, fractional design, C:N ratio, air flow

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Authors: Joonas Pääkkönen

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In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling

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Authors: Amani Abdallah, Isam Shahrour

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The quality of drinking water is a major concern of public health. The control of this quality is generally performed in the laboratory, which requires a long time. This type of control is not adapted for accidental pollution from sudden events, which can have serious consequences on population health. Therefore, it is of major interest to develop real-time innovative solutions for the detection of accidental contamination in drinking water systems This paper presents researches conducted within the SunRise Demonstrator for ‘Smart and Sustainable Cities’ with a particular focus on the supervision of the water quality. This work aims at (i) implementing a smart water system in a large water network (Campus of the University Lille1) including innovative equipment for real-time detection of abnormal events, such as those related to the contamination of drinking water and (ii) develop a numerical modeling of the contamination diffusion in the water distribution system. The first step included verification of the water quality sensors and their effectiveness on a network prototype of 50m length. This part included the evaluation of the efficiency of these sensors in the detection both bacterial and chemical contamination events in drinking water distribution systems. An on-line optical sensor integral with a laboratory-scale distribution system (LDS) was shown to respond rapidly to changes in refractive index induced by injected loads of chemical (cadmium, mercury) and biological contaminations (Escherichia coli). All injected substances were detected by the sensor; the magnitude of the response depends on the type of contaminant introduced and it is proportional to the injected substance concentration.

Keywords: distribution system, drinking water, refraction index, sensor, real-time

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Authors: Arjun G. Koppad

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The study was conducted in Joida taluk of Uttara Kannada district, Karnataka, India, to assess the land use land cover (LULC) and forest aboveground biomass using L band SAR data. The study area covered has dense, moderately dense, and sparse forests. The sampled area was 0.01 percent of the forest area with 30 sampling plots which were selected randomly. The point center quadrate (PCQ) method was used to select the tree and collected the tree growth parameters viz., tree height, diameter at breast height (DBH), and diameter at the tree base. The tree crown density was measured with a densitometer. Each sample plot biomass was estimated using the standard formula. In this study, the LULC classification was done using Freeman-Durden, Yamaghuchi and Pauli polarimetric decompositions. It was observed that the Freeman-Durden decomposition showed better LULC classification with an accuracy of 88 percent. An attempt was made to estimate the aboveground biomass using SAR backscatter. The ALOS-2 PALSAR-2 L-band data (HH, HV, VV &VH) fully polarimetric quad-pol SAR data was used. SAR backscatter-based regression model was implemented to retrieve forest aboveground biomass of the study area. Cross-polarization (HV) has shown a good correlation with forest above-ground biomass. The Multi Linear Regression analysis was done to estimate aboveground biomass of the natural forest areas of the Joida taluk. The different polarizations (HH &HV, VV &HH, HV & VH, VV&VH) combination of HH and HV polarization shows a good correlation with field and predicted biomass. The RMSE and value for HH & HV and HH & VV were 78 t/ha and 0.861, 81 t/ha and 0.853, respectively. Hence the model can be recommended for estimating AGB for the dense, moderately dense, and sparse forest.

Keywords: forest, biomass, LULC, back scatter, SAR, regression

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Authors: Genevaive Melendres

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School administrators face the reality of teachers losing their engagement, or schools losing the teachers. This study is then conducted to identify a structural model that best predict work engagement of private secondary teachers in Davao City. Ninety-three teachers from four sectarian schools and 56 teachers from four non-sectarian schools were involved in the completion of four survey instruments namely Organizational Climate Questionnaire, Leader Behavior Descriptive Questionnaire, Organizational Commitment Scales, and Utrecht Work Engagement Scales. Data were analyzed using frequency distribution, mean, standardized deviation, t-test for independent sample, Pearson r, stepwise multiple regression analysis, and structural equation modeling. Results show that schools have high level of organizational climate dimensions; leaders oftentimes show work-oriented and people-oriented behavior; teachers have high normative commitment and they are very often engaged at their work. Teachers from non-sectarian schools have higher organizational commitment than those from sectarian schools. Organizational climate and leadership behavior are positively related to and predict work engagement whereas commitment did not show any relationship. This study underscores the relative effects of three variables on the work engagement of teachers. After testing network of relationships and evaluating several models, a best-fitting model was found between leadership behavior and work engagement. The noteworthy findings suggest that principals pay attention and consistently evaluate their behavior for this best predicts the work engagement of the teachers. The study provides value to administrators who take decisions and create conditions in which teachers derive fulfillment.

Keywords: leadership behavior, organizational climate, organizational commitment, private secondary school teachers, structural model on work engagement

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Authors: Szilvia Halmos

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Hungary was one of the first countries to sign and ratify the UN Convention on the Rights of Persons with Disabilities (hereinafter: CRPD). Consequently, Hungary assumed an obligation under international law to review the national law in the light of the Article 12 of the CRPD requiring the States parties to guarantee the equality of persons with disabilities in terms of legal capacity, and to replace the regimes of substitute decision-making by the instruments of supported decision-making. This article is often characterized as one of the key norms of the CRPD, since the legal autonomy of the persons with disabilities is an essential precondition of their participation in the social life on an equal basis with others, envisaged by the social paradigm of disability. This paper examines the impact of the CRPD on the relevant Hungarian national legal norms, with special focus on the relevant rules of the recently codified Civil Code. The employed research methodologies include (1) the specification of the implementation requirements imposed by the Article 12 of the CRPD, (2) the determination of the indicators of the appropriate implementation, (3) the critical analysis of compliance of the relevant Hungarian legal regulation with the indicators, (4) with respect to the relevant case law of the Hungarian Constitutional Court and ordinary courts, the European Court of Human Rights and the Committee of Rights of Persons with Disabilities and (5) to the available empirical figures on the functioning of substitute and supported decision-making regimes. It will be established that the new Civil Code has made large steps toward the equality of persons with disabilities in terms of legal capacity and the support model of decision-making by the introduction of some specific instruments of supported decision-making and the restriction of the application of guardianship. Nevertheless, the regulation currently in effect fails to represent some crucial principles of the Article 12 of the CRPD, such as the non-discrimination of persons with psycho-social disabilities, the support of the articulation of the will and preferences of the individual instead of his/her best interest in the course of decision-making. The changes in the practice of the substitute and the support model brought about by the new legal norms can also be assessed as significant, however, so far unsatisfactory. The number of registered supporters is rather low, and the preconditions of the effective functioning of the support (e.g. the proper training of the supporters) are not ensured.

Keywords: Article 12 of the UN CRPD, Hungarian law on legal capacity, persons with intellectual and psycho-social disabilities, supported decision-making

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Authors: Ibrahim Rassoul, E-K. Si Ahmed

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The growth, deformation, and detachment of fluid droplets adherent to solid substrates is a problem of fundamental interest with numerous practical applications. Specific interest in this proposal is the problem of a droplet on a fibrous, hydrophobic substrate subjected to body or external forces (gravity, convection). The past decade has seen tremendous advances in proton exchange membrane fuel cell (PEMFC) technology. However, there remain many challenges to bring commercially viable stationary PEMFC products to the market. PEMFCs are increasingly emerging as a viable alternative clean power source for automobile and stationary applications. Before PEMFCs can be employed to power automobiles and homes, several key technical challenges must be properly addressed. One technical challenge is elucidating the mechanisms underlying water transport in and removal from PEMFCs. On the one hand, sufficient water is needed in the polymer electrolyte membrane or PEM to maintain sufficiently high proton conductivity. On the other hand, too much liquid water present in the cathode can cause 'flooding' (that is, pore space is filled with excessive liquid water) and hinder the transport of the oxygen reactant from the gas flow channel (GFC) to the three-phase reaction sites. The aim of this work is to investigate the stability of a liquid water droplet emerging form a GDL pore, to gain fundamental insight into the instability process leading to detachment. The approach will combine analytical and numerical modeling with experimental visualization and measurements.

Keywords: polymer electrolyte fuel cell, water droplet, gas diffusion layer, contact angle, surface tension

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Authors: Marko Batic, Nikola Tomasevic, Sanja Vranes

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One of the strongholds in the ubiquitous efforts related to the energy conservation and energy efficiency improvement is represented by the retrofit of high energy consumers in buildings. In general, HVAC systems represent the highest energy consumers in buildings. However they usually suffer from mal-operation and/or malfunction, causing even higher energy consumption than necessary. Various Fault Detection and Diagnosis (FDD) systems can be successfully employed for this purpose, especially when it comes to the application at a single device/unit level. In the case of more complex systems, where multiple devices are operating in the context of the same building, significant energy efficiency improvements can only be achieved through application of comprehensive FDD systems relying on additional higher level knowledge, such as their geographical location, served area, their intra- and inter- system dependencies etc. This paper presents a comprehensive FDD system that relies on the utilization of common knowledge repository that stores all critical information. The discussed system is deployed as a test-bed platform at the two at Fiumicino and Malpensa airports in Italy. This paper aims at presenting advantages of implementation of the knowledge base through the utilization of ontology and offers improved functionalities of such system through examples of typical queries and reasoning that enable derivation of high level energy conservation measures (ECM). Therefore, key SPARQL queries and SWRL rules, based on the two instantiated airport ontologies, are elaborated. The detection of high level irregularities in the operation of airport heating/cooling plants is discussed and estimation of energy savings is reported.

Keywords: airport ontology, knowledge management, ontology modeling, reasoning

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Authors: Pavan K. Emani, Shashank Kothari, V. S. Phanikanth

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The ultimate load analysis of RC pile groups has assumed a lot of significance under liquefying soil conditions, especially due to post-earthquake studies of 1964 Niigata, 1995 Kobe and 2001 Bhuj earthquakes. The present study reports the results of numerical simulations on pile groups subjected to monotonically increasing lateral loads under design amounts of pile axial loading. The soil liquefaction has been considered through the non-linear p-y relationship of the soil springs, which can vary along the depth/length of the pile. This variation again is related to the liquefaction potential of the site and the magnitude of the seismic shaking. As the piles in the group can reach their extreme deflections and rotations during increased amounts of lateral loading, a precise modeling of the inelastic behavior of the pile cross-section is done, considering the complete stress-strain behavior of concrete, with and without confinement, and reinforcing steel, including the strain-hardening portion. The possibility of the inelastic buckling of the individual piles is considered in the overall collapse modes. The model is analysed using Riks analysis in finite element software to check the post buckling behavior and plastic collapse of piles. The results confirm the kinds of failure modes predicted by centrifuge test results reported by researchers on pile group, although the pile material used is significantly different from that of the simulation model. The extension of the present work promises an important contribution to the design codes for pile groups in liquefying soils.

Keywords: collapse load analysis, inelastic buckling, liquefaction, pile group

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Authors: Teresa Kupczyk, Selçuk Mustafa Özcan, Joanna Kubicka

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The paper presents results of specialist literature analysis concerning learning outcomes and student satisfaction as a factor of the necessary change in the Polish higher education system. The objective of the empirical research was to determine students’ assessment of learning outcomes, satisfaction of their expectations, as well as their satisfaction with lectures and practical classes held in the traditional form, e-learning and video-conference. The assessment concerned effectiveness of time spent at classes, usefulness of the delivered knowledge, instructors’ preparation and teaching skills, application of tools, studies curriculum, its adaptation to students’ needs and labour market, as well as studying conditions. Self-assessment of learning outcomes was confronted with assessment by lecturers. The indirect objective of the research was also to identify how students assessed their activity and commitment in acquisition of knowledge and their discipline in achieving education goals. It was analysed how the studies held affected the students’ willingness to improve their skills and assessment of their perspectives at the labour market. To capture the changes underway, the research was held at the beginning, during and after completion of the studies. The study group included 86 students of two editions of full-time studies majoring in Management and specialising in “Mega-event organisation”. The studies were held within the EU-funded project entitled “Responding to challenges of new markets – innovative managerial education”. The results obtained were analysed statistically. Average results and standard deviations were calculated. In order to describe differences between the studied variables present during the process of studies, as well as considering the respondents’ gender, t-Student test for independent samples was performed with the IBM SPSS Statistics 21.0 software package. Correlations between variables were identified by calculation of Pearson and Spearman correlation coefficients. Research results suggest necessity to introduce some changes in the teaching system applied at Polish higher education institutions, not only considering the obtained outcomes, but also impact on students’ willingness to improve their qualifications constantly, improved self-assessment among students and their opportunities at the labour market.

Keywords: higher education, learning outcomes, students, change

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