Search results for: hydrological models

Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

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Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

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Authors: Al-Juhaishi Mohammed, Mikael Motelica-Heino, Fabrice Muller, Audrey Guirimand-Dufour, Christian Défarge

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This study aims at improving the urban hydrological cycle of the Orléans agglomeration (France) and understanding the relationship between physical and chemical parameters of urban surface runoff and the hydrological conditions. In particular water quality parameters such as pH, conductivity, total dissolved solids, major dissolved cations and anions, and chemical and biological oxygen demands were monitored for three types of urban water discharges (wastewater treatment plant output (WWTP), storm overflow and stormwater outfall) under two hydrologic scenarii (dry and wet weather). The first results were obtained over a period of five months.Each investigated (Ormes and l’Egoutier) outfall represents an urban runoff source that receives water from runoff roads, gutters, the irrigation of gardens and other sources of flow over the Earth’s surface that drains in its catchments and carries it to the Loire River. In wet weather conditions there is rain water runoff and an additional input from the roof gutters that have entered the stormwater system during rainfall. For the comparison the results La Chilesse is a storm overflow that was selected in our study as a potential source of waste water which is located before the (WWTP).The comparison of the physical-chemical parameters (total dissolved solids, turbidity, pH, conductivity, dissolved organic carbon (DOC), concentration of major cations and anions) together with the chemical oxygen demand (COD) and biological oxygen demand (BOD) helped to characterize sources of runoff waters in the different watersheds. It also helped to highlight the infiltration of wastewater in some stormwater systems that reject directly in the Loire River. The values of the conductivity measured in the outflow of Ormes were always higher than those measured in the other two outlets. The results showed a temporal variation for the Ormes outfall of conductivity from 1465 µS cm-1 in the dry weather flow to 650 µS cm-1 in the wet weather flow and also a spatial variation in the wet weather flow from 650 µS cm-1 in the Ormes outfall to 281 μS cm-1 in L’Egouttier outfall. The ultimate BOD (BOD28) showed a significant decrease in La Corne outfall from 210 mg L-1 in the wet weather flow to 75 mg L-1 in the dry weather flow because of the nutrient load that was transported by the runoff.

Keywords: BOD, COD, the Loire River, urban hydrology, urban dry and wet weather discharges, macronutrients

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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: Elina Bakhtieva

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The variety of available digital tools, strategies and activities might confuse and disorient even an experienced marketer. This applies in particular to B2B companies, which are usually less flexible in uptaking of digital technology than B2C companies. B2B companies are lacking a framework that corresponds to the specifics of the B2B business, and which helps to evaluate a company’s capabilities and to choose an appropriate path. A B2B digital marketing maturity model helps to fill this gap. However, modern marketing offers no widely approved digital marketing maturity model, and thus, some marketing institutions provide their own tools. The purpose of this paper is building an optimized B2B digital marketing maturity model based on a SWOT (strengths, weaknesses, opportunities, and threats) analysis of existing models. The current study provides an analytical review of the existing digital marketing maturity models with open access. The results of the research are twofold. First, the provided SWOT analysis outlines the main advantages and disadvantages of existing models. Secondly, the strengths of existing digital marketing maturity models, helps to identify the main characteristics and the structure of an optimized B2B digital marketing maturity model. The research findings indicate that only one out of three analyzed models could be used as a separate tool. This study is among the first examining the use of maturity models in digital marketing. It helps businesses to choose between the existing digital marketing models, the most effective one. Moreover, it creates a base for future research on digital marketing maturity models. This study contributes to the emerging B2B digital marketing literature by providing a SWOT analysis of the existing digital marketing maturity models and suggesting a structure and main characteristics of an optimized B2B digital marketing maturity model.

Keywords: B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis

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Authors: Majdi M. Alomari, Nafesah I. Alshdaifat, Mohammad S. Widyan

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Different countries have introduced different schemes and policies to counter global warming. The rationale behind the proposed policies and the potential barriers to successful implementation of the policies adopted by the countries were analyzed and estimated based on different models. It is argued that these models enhance the transparency and provide a better understanding to the policy makers. However, these models are underpinned with several structural and baseline assumptions. These assumptions, modeling features and future prediction of emission reductions and other implication such as cost and benefits of a transition to a low-carbon economy and its economy wide impacts were discussed. On the other hand, there are potential barriers in the form political, financial, and cultural and many others that pose a threat to the mitigation options.

Keywords: energy models, environmental policy instruments, mitigating CO2 emission, economic wide impact

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Authors: Temenuzhka Spasova, Nadya Yanakieva

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Snow modulates the hydrological cycle and influences the functioning of ecosystems and is a significant resource for many populations whose water is harvested from cold regions. Snow observations are important for validating climate models. The accumulation and rapid melt of snow are two of the most dynamical seasonal environmental changes on the Earth’s surface. The actuality of this research is related to the modern tendencies of the remote sensing application in the solution of problems of different nature in the ecological monitoring of the environment. The subject of the study is the dynamic during the different seasons on Livingstone Island, South Shetland Islands in Antarctica and on Svalbard in Arctic. The objects were analyzed and mapped according to the Еuropean Space Agency data (ESA), acquired by sensors Sentinel-1 SAR (Synthetic Aperture Radar), Sentinel 2 MSI and GIS. Results have been obtained for changes in snow coverage during the summer-winter transition and its dynamics in the two hemispheres. The data used is of high time-spatial resolution, which is an advantage when looking at the snow cover. The MSI images are with different spatial resolution at the Earth surface range. The changes of the environmental objects are shown with the SAR images and different processing approaches. The results clearly show that snow and snow melting can be best registered by using SAR data via hh- horizontal polarization. The effect of the researcher on aerospace data and technology enables us to obtain different digital models, structuring and analyzing results excluding the subjective factor. Because of the large extent of terrestrial snow coverage and the difficulties in obtaining ground measurements over cold regions, remote sensing and GIS represent an important tool for studying snow areas and properties from regional to global scales.

Keywords: climate changes, GIS, remote sensing, SAR images, snow coverage

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Authors: Dražen Cvitanić, Biljana Maljković

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This paper presents models for predicting operating speeds on tangent sections of two-lane rural roads developed on continuous speed data. The data corresponds to 20 drivers of different ages and driving experiences, driving their own cars along an 18 km long section of a state road. The data were first used for determination of maximum operating speeds on tangents and their comparison with speeds in the middle of tangents i.e. speed data used in most of operating speed studies. Analysis of continuous speed data indicated that the spot speed data are not reliable indicators of relevant speeds. After that, operating speed models for tangent sections were developed. There was no significant difference between models developed using speed data in the middle of tangent sections and models developed using maximum operating speeds on tangent sections. All developed models have higher coefficient of determination then models developed on spot speed data. Thus, it can be concluded that the method of measuring has more significant impact on the quality of operating speed model than the location of measurement.

Keywords: operating speed, continuous speed data, tangent sections, spot speed, consistency

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Authors: Razieh Arian, Hadi Adibi-Asl

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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine

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Authors: Rehab Abdulmajed, Amr Hamada, Ahmed Elsaid, Hisashi Hayakawa, Ayman Mahrous

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Solar emissions have a high impact on the Earth’s magnetic field, and the prediction of solar events is of high interest. Various techniques have been used in the prediction of solar wind using mathematical models, MHD models, and neural network (NN) models. This study investigates the coronal hole (CH) derived high-speed streams (HSSs) and their correlation to the CH area and create a neural network model to predict the HSSs. Two different algorithms were used to compare different models to find a model that best simulates the HSSs. A dataset of CH synoptic maps through Carrington rotations 1601 to 2185 along with Omni-data set solar wind speed averaged over the Carrington rotations is used, which covers Solar cycles (sc) 21, 22, 23, and most of 24.

Keywords: artificial neural network, coronal hole area, feed-forward neural network models, solar high speed streams

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Authors: Vasileiou Apostolos, Theodosiou Chrysa, Tsitroulis Ioannis, Maris Fotios

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The severity of extreme phenomena is due to their ability to cause severe damage in a small amount of time. It has been observed that floods affect the greatest number of people and induce the biggest damage when compared to the total of annual natural disasters. The detection of potential flood-prone areas constitutes one of the fundamental components of the European Natural Disaster Management Policy, directly connected to the European Directive 2007/60. The aim of the present paper is to develop a new methodology that combines geographical information, fuzzy logic and multi-criteria evaluation methods so that the most vulnerable areas are defined. Therefore, ten factors related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin were selected. Afterwards, two models were created to detect the areas pronest to flooding. The first model defined the gravitas of each factor using Analytical Hierarchy Process (AHP) and the final map of possible flood spots were created using GIS and Boolean Algebra. The second model made use of the fuzzy logic and GIS combination and a respective map was created. The application area of the aforementioned methodologies was in Ardas basin due to the frequent and important floods that have taken place these last years. Then, the results were compared to the already observed floods. The result analysis shows that both models can detect with great precision possible flood spots. As the fuzzy logic model is less time-consuming, it is considered the ideal model to apply to other areas. The said results are capable of contributing to the delineation of high risk areas and to the creation of successful management plans dealing with floods.

Keywords: analytical hierarchy process, flood prone areas, fuzzy logic, geographic information system

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Authors: Sibel Celik, Hüseyin Ergin

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The paper aims to find the best volatility forecasting model for stock markets in Turkey. For this purpose, we compare performance of different volatility models-both traditional GARCH model and high frequency based volatility models- and conclude that both in pre-crisis and crisis period, the performance of high frequency based volatility models are better than traditional GARCH model. The findings of paper are important for policy makers, financial institutions and investors.

Keywords: volatility, GARCH model, realized volatility, high frequency data

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Authors: Višnjica Vučetić, Mislav Anić, Jelena Bašić, Petra Sviličić, Ivana Tomašević

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The Agroclimatic Atlas of Croatia (Atlas) for the periods 1981–2010 and 1991–2020 is monograph of six chapters in digital form. Detailed descriptions of particular agroclimatological data are given in separate chapters as follows: agroclimatic indices based on air temperature (degree days, Huglin heliothermal index), soil temperature, water balance components (precipitation, potential evapotranspiration, actual evapotranspiration, soil moisture content, runoff, recharge and soil moisture loss) and fire weather indices. The last chapter is a description of the digital methods for the spatial interpolations (R and GIS). The Atlas comprises textual description of the relevant climate characteristic, maps of the spatial distribution of climatological elements at 109 stations (26 stations for soil temperature) and tables of the 30-year mean monthly, seasonal and annual values of climatological parameters at 24 stations. The Atlas was published in 2021, on the seventieth anniversary of the agrometeorology development at the Meteorological and Hydrological Service of Croatia. It is intended to support improvement of sustainable system of agricultural production and forest protection from fire and as a rich source of information for agronomic and forestry experts, but also for the decision-making bodies to use it for the development of strategic plans.

Keywords: agrometeorology, agroclimatic indices, soil temperature, water balance components, fire weather index, meteorological and hydrological service of Croatia

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Authors: Ashwini V. Chavan, Sukhanand S. Bhosale

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Challenges of weak soil subgrade are often resolved either by stabilization or reinforcing it. However, it is also practiced to reinforce the granular fill to improve the load-settlement behavior of over weak soil strata. The inclusion of reinforcement in the engineered granular fill provided a new impetus for the development of enhanced Soil-Structure Interaction (SSI) models, also known as mechanical foundation models or lumped parameter models. Several researchers have been working in this direction to understand the mechanism of granular fill-reinforcement interaction and the response of weak soil under the application of load. These models have been developed by extending available SSI models such as the Winkler Model, Pasternak Model, Hetenyi Model, Kerr Model etc., and are helpful to visualize the load-settlement behavior of a physical system through 1-D and 2-D analysis considering beam and plate resting on the foundation respectively. Based on the literature survey, these models are categorized as ‘Reinforced Pasternak Model,’ ‘Double Beam Model,’ ‘Reinforced Timoshenko Beam Model,’ and ‘Reinforced Kerr Model.’ The present work reviews the past 30+ years of research in the field of SSI models for reinforced foundation systems, presenting the conceptual development of these models systematically and discussing their limitations. Special efforts are taken to tabulate the parameters and their significance in the load-settlement analysis, which may be helpful in future studies for the comparison and enhancement of results and findings of physical models.

Keywords: geosynthetics, mathematical modeling, reinforced foundation, soil-structure interaction, ground improvement, soft soil

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Authors: Juan Manuel Sanchez-Cartas, Gonzalo Leon

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A price competition algorithm for ABMs based on game theory principles is proposed to deal with the simulation of theoretical market models. The algorithm is applied to the classical Hotelling’s model and to a two-sided market model to show it leads to the optimal behavior predicted by theoretical models. However, when theoretical models fail to predict the equilibrium, the algorithm is capable of reaching a feasible outcome. Results highlight that the algorithm can be implemented in other simulation models to guarantee rational users and endogenous optimal behaviors. Also, it can be applied as a tool of verification given that is theoretically based.

Keywords: agent-based models, algorithmic game theory, multi-sided markets, price optimization

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Authors: Phanida Phukoetphim, Asaad Y. Shamseldin

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In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand.

Keywords: multi-model combination, rainfall-runoff modeling, stochastic gradient boosting, bioinformatics

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Authors: Ahmad Alwosheel, Ahmed Alqaraawi

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This work proposes an unsupervised text-independent probabilistic approach to recognize Quran reciter voice. It is an accurate approach that works on real time applications. This approach does not require a prior information about reciter models. It has two phases, where in the training phase the reciters' acoustical features are modeled using Gaussian Mixture Models, while in the testing phase, unlabeled reciter's acoustical features are examined among GMM models. Using this approach, a high accuracy results are achieved with efficient computation time process.

Keywords: Quran, speaker recognition, reciter recognition, Gaussian Mixture Model

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: K. Debkowska

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The aim of this article is presenting the possibilities of using Fuzzy Set Qualitative Comparative Analysis (fsQCA) in researches concerning business models of enterprises. FsQCA is a bridge between quantitative and qualitative researches. It's potential can be used in analysis and evaluation of business models. The article presents the results of a study conducted on the basis of enterprises belonging to different sectors: transport and logistics, industry, building construction, and trade. The enterprises have been researched taking into account the components of business models and the financial condition of companies. Business models are areas of complex and heterogeneous nature. The use of fsQCA has enabled to answer the following question: which components of a business model and in which configuration influence better financial condition of enterprises. The analysis has been performed separately for particular sectors. This enabled to compare the combinations of business models' components which actively influence the financial condition of enterprises in analyzed sectors. The following components of business models were analyzed for the purposes of the study: Key Partners, Key Activities, Key Resources, Value Proposition, Channels, Cost Structure, Revenue Streams, Customer Segment and Customer Relationships. These components of the study constituted the variables shaping the financial results of enterprises. The results of the study lead us to believe that fsQCA can help in analyzing and evaluating a business model, which is important in terms of making a business decision about the business model used or its change. In addition, results obtained by fsQCA can be applied by all stakeholders connected with the company.

Keywords: business models, components of business models, data analysis, fsQCA

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Authors: Tadeusz Nowicki, Radosław Pytlak, Robert Waszkowski, Jerzy Bertrandt, Anna Kłos

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This paper presents methods for formal modeling of activities in the area of sanitary inspectors outbreak of food-borne diseases. The models allow you to measure the characteristics of the activities of sanitary inspection and as a result allow improving the performance of sanitary services and thus food security.

Keywords: food-borne disease, epidemic, sanitary inspection, mathematical models

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Authors: A. G. Kovalenko, Y. N. Amirgaliyev, A. U. Kalizhanova, L. S. Balgabayeva, A. H. Kozbakova, Z. S. Aitkulov

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It is known that statistical information on operation of the compound multisite system is often far from the description of actual state of the system and does not allow drawing any conclusions about the correctness of its operation. For example, from the world practice of operation of systems of water supply, water disposal, it is known that total measurements at consumers and at suppliers differ between 40-60%. It is connected with mathematical measure of inaccuracy as well as ineffective running of corresponding systems. Analysis of widely-distributed systems is more difficult, in which subjects, which are self-maintained in decision-making, carry out economic interaction in production, act of purchase and sale, resale and consumption. This work analyzed mathematical models of sellers, consumers, arbitragers and the models of their interaction in the provision of dispersed single-product market of perfect competition. On the basis of these models, the methods, allowing estimation of every subject’s operating options and systems as a whole are given.

Keywords: dispersed systems, models, hydraulic network, algorithms

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Authors: Anthony Usoro

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In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.

Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model

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Authors: Young Nam Jo, Moon Jeong Kang, Hong Hee Yoo

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Most human vibration models have been modeled as a multibody system consisting of some rigid bodies and spring-dampers. These models are developed for certain posture and conditions. So, the models cannot be used in vibration analysis in various posture and conditions. The purpose of this study is to develop a human vibration model that represent human vibration characteristics under various conditions by employing a musculoskeletal model. To do this, the human vibration model is developed based on biomechanical models. In addition, muscle models are employed instead of spring-dampers. Activations of muscles are controlled by PD controller to maintain body posture under vertical vibration is applied. Each gain value of the controller is obtained to minimize the difference of apparent mass and acceleration transmissibility between experim ent and analysis by using an optimization method.

Keywords: human vibration analysis, hill type muscle model, PD control, whole-body vibration

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Authors: Saih Mohamed, Rouijaa Hicham, Ghammaz Abdelilah

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This paper presents circuit models to analyze the conducted susceptibility of multiconductor shielded cables in frequency domains using Branin’s method, which is referred to as the method of characteristics. These models, Which can be used directly in the time and frequency domains, take into account the presence of both the transfer impedance and admittance. The conducted susceptibility is studied by using an injection current on the cable shield as the source. Two examples are studied, a coaxial shielded cable and shielded cables with two parallel wires (i.e., twinax cables). This shield has an asymmetry (one slot on the side). Results obtained by these models are in good agreement with those obtained by other methods.

Keywords: circuit models, multiconductor shielded cables, Branin’s method, coaxial shielded cable, twinax cables

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Authors: Julia Zimmerman, Gaurav Savant

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This study aims to evaluate the efficacy of the U.S. Army Corp of Engineers’ River Analysis System (HEC-RAS) application to modeling the hydraulics of estuaries. HEC-RAS has been broadly used for a variety of riverine applications. However, it has not been widely applied to the study of circulation in estuaries. This report details the model development and validation of a combined 1D/2D unsteady flow hydraulic model using HEC-RAS for estuaries and they are associated with tidally influenced rivers. Two estuaries, Galveston Bay and Delaware Bay, were used as case studies. Galveston Bay, a bar-built, vertically mixed estuary, was modeled for the 2005 calendar year. Delaware Bay, a drowned river valley estuary, was modeled from October 22, 2019, to November 5, 2019. Water surface elevation was used to validate both models by comparing simulation results to NOAA’s Center for Operational Oceanographic Products and Services (CO-OPS) gauge data. Simulations were run using the Diffusion Wave Equations (DW), the Shallow Water Equations, Eulerian-Lagrangian Method (SWE-ELM), and the Shallow Water Equations Eulerian Method (SWE-EM) and compared for both accuracy and computational resources required. In general, the Diffusion Wave Equations results were found to be comparable to the two Shallow Water equations sets while requiring less computational power. The 1D/2D combined approach was valid for study areas within the 2D flow area, with the 1D flow serving mainly as an inflow boundary condition. Within the Delaware Bay estuary, the HEC-RAS DW model ran in 22 minutes and had an average R² value of 0.94 within the 2-D mesh. The Galveston Bay HEC-RAS DW ran in 6 hours and 47 minutes and had an average R² value of 0.83 within the 2-D mesh. The longer run time and lower R² for Galveston Bay can be attributed to the increased length of the time frame modeled and the greater complexity of the estuarine system. The models did not accurately capture tidal effects within the 1D flow area.

Keywords: Delaware bay, estuarine hydraulics, Galveston bay, HEC-RAS, one-dimensional modeling, two-dimensional modeling

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Authors: Sidique Gawusu, Xiaobing Zhang

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Turbulence models play a significant role in all computational fluid dynamics based modelling approaches. There is, however, no general turbulence model suitable for all flow scenarios. Therefore, a successful numerical modelling approach is only achievable if a more appropriate closure model is used. This paper evaluates different turbulence models in numerical modelling of oil-water flow within the Eulerian-Eulerian approach. A comparison among the obtained numerical results and published benchmark data showed reasonable agreement. The domain was meshed using structured mesh, and grid test was performed to ascertain grid independence. The evaluation of the models was made through analysis of velocity and pressure profiles across the domain. The models were tested for their suitability to accurately obtain a scalable and precise numerical experience. As a result, it is found that all the models except Standard-ω provide comparable results. The study also revealed new insights on flow in porous media, specifically oil reservoirs.

Keywords: turbulence modelling, simulation, multi-phase flows, water-flooding, heavy oil

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Authors: Katja Ignatieva, Patrick Wong

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We investigated the dynamics of high frequency energy prices, including crude oil and electricity prices. The returns of underlying quantities are modelled using various parametric models such as stochastic framework with jumps and stochastic volatility (SVCJ) as well as non-parametric alternatives, which are purely data driven and do not require specification of the drift or the diffusion coefficient function. Using different statistical criteria, we investigate the performance of considered parametric and nonparametric models in their ability to forecast price series and volatilities. Our models incorporate possible seasonalities in the underlying dynamics and utilise advanced estimation techniques for the dynamics of energy prices.

Keywords: stochastic volatility, affine jump-diffusion models, high frequency data, model specification, markov chain monte carlo

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Authors: Serin Darwish, Hakim Saibi, Amir Gabr

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The United Arab Emirates (UAE) is situated within an arid zone where the climate is arid and the recharge of the groundwater is very low. Groundwater is the primary source of water in the United Arab Emirates. However, rapid expansion, population growth, agriculture, and industrial activities have negatively affected these limited water resources. The shortage of water resources has become a serious concern due to the over-pumping of groundwater to meet demand. In addition to the deficit of groundwater, the UAE has one of the highest per capita water consumption rates in the world. In this study, a combination of time-lapse measurements of microgravity and depth to groundwater level in selected wells in Al Ain city was used to estimate the variations in groundwater storage. Al-Ain is the second largest city in Abu Dhabi Emirates and the third largest city in the UAE. The groundwater in this region has been overexploited. Relative gravity measurements were acquired using the Scintrex CG-6 Autograv. This latest generation gravimeter from Scintrex Ltd provides fast, precise gravity measurements and automated corrections for temperature, tide, instrument tilt and rejection of data noise. The CG-6 gravimeter has a resolution of 0.1μGal. The purpose of this study is to measure the groundwater storage changes in the shallow aquifers based on the application of microgravity method. The gravity method is a nondestructive technique that allows collection of data at almost any location over the aquifer. Preliminary results indicate a possible relationship between microgravity and water levels, but more work needs to be done to confirm this. The results will help to develop the relationship between monthly microgravity changes with hydrological and hydrogeological changes of shallow phreatic. The study will be useful in water management considerations and additional future investigations.

Keywords: Al-Ain, arid region, groundwater, microgravity

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Authors: Nahlah Abbas, Saleh A. Wasimi, Nadhir Al-Ansari

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The Greater Zab and Lesser Zab are the major tributaries of Tigris River contributing the largest flow volumes into the river. The impacts of climate change on water resources in these basins have not been well addressed. To gain a better understanding of the effects of climate change on water resources of the study area in near future (2049-2069) as well as in distant future (2080-2099), Soil and Water Assessment Tool (SWAT) was applied. The model was first calibrated for the period from 1979 to 2004 to test its suitability in describing the hydrological processes in the basins. The SWAT model showed a good performance in simulating streamflow. The calibrated model was then used to evaluate the impacts of climate change on water resources. Six general circulation models (GCMs) from phase five of the Coupled Model Intercomparison Project (CMIP5) under three Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5, and RCP 8.5 for periods of 2049-2069 and 2080-2099 were used to project the climate change impacts on these basins. The results demonstrated a significant decline in water resources availability in the future.

Keywords: Tigris River, climate change, water resources, SWAT

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Authors: Nice Vasconcelos Coimbra, Fábio dos Santos Gonçalves, Marisa Nascimento, Ellen Cristine Giese

Abstract:

The development of chemical routes for the recovery and separation of rare earth elements (REE) is seen as a priority and strategic action by several countries demanding these elements. Among the possibilities of alternative routes, the biosorption process has been evaluated in our laboratory. In this theme, the present work attempts to assess and fit the solution equilibrium data in Langmuir, Freundlich and DKR isothermal models, based on the biosorption results of the lanthanum and samarium elements by Bacillus subtilis immobilized on calcium alginate gel. It was observed that the preference of adsorption of REE by the immobilized biomass followed the order Sm (III)> La (III). It can be concluded that among the studied isotherms models, the Langmuir model presented better mathematical results than the Freundlich and DKR models.

Keywords: rare earth elements, biosorption, Bacillus subtilis, adsorption isotherm models

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Authors: Mahmoud Aly, Mohamed Ismail, Mohamed Badereldin, Amro Mostafa

Abstract:

Introduction: The models of soul houses were appeared in the prehistory, old kingdom, and middle kingdom period. They represented the imagination of the deceased about his house in the afterlife, some of these soul houses were two floors, and the study will examine five models of soul houses which were discovered near Saqqara site by an Egyptian mission. These models had been transferred to The Grand Egyptian Museum (GEM) to be ready to display at the new museum. We focus upon five models of soul houses (GEM Numbers, 1276,1280,1281,1282,8711) they related to the old kingdom period. These models were all made of pottery, the five models have oval shape and were decorated with relief. Methodology: The study will focus on the development of soul houses during the different periods in ancient Egypt and the kinds of offerings which will reflect the economic situation in the Egyptian society and kinds of oils which were famous in ancient Egypt. Conclusion: This research focuses on the function of soul house and the kind of offerings which were put in it, This study will be useful for the heritage and ancient civilizations, specially when we talk about opening new museums like The Grand Egyptian Museum, which will display a new collection of soul houses.

Keywords: archaeology study, grand egyptian museum, relief, soul houses

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