Search results for: model transformation

Authors: Keerthi S. Shetty, Annappa Basava

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In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

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Authors: Elena Puica

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This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

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Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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Authors: Ana Rahma Yuniarti, Ki Moo Lim

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Slowed myocardial conduction velocity (CV) and shortened action potential duration (APD) due to some reason are associated with an increased risk of re-entrant excitation, predisposing to cardiac arrhythmia. That is because both of CV reduction and APD shortening induces shortening of wavelength. In this study, we investigated quantitatively the cardiac mechanical responses under various CV and APD using multi-scale computational model of the heart. The model consisted of electrical model coupled with the mechanical contraction model together with a lumped model of the circulatory system. The electrical model consisted of 149.344 numbers of nodes and 183.993 numbers of elements of tetrahedral mesh, whereas the mechanical model consisted of 356 numbers of nodes and 172 numbers of elements of hexahedral mesh with hermite basis. We performed the electrical simulation with two scenarios: 1) by varying the CV values with constant APD and 2) by varying the APD values with constant CV. Then, we compared the electrical and mechanical responses for both scenarios. Our simulation showed that faster CV and longer APD induced largest resultants wavelength and generated better cardiac pumping efficacy by increasing the cardiac output and consuming less energy. This is due to the long wave propagation and faster conduction generated more synchronous contraction of whole ventricle.

Keywords: conduction velocity, action potential duration, mechanical contraction model, circulatory model

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Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

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Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

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Authors: Yungtai Lo

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The current study follows an educational intervention on bottle-weaning to simultaneously evaluate the effect of the bottle-weaning intervention on reducing bottle use, daily milk intake from bottles, and daily energy intake in toddlers aged 11 to 13 months. A shared parameter model and a random effects model are used to jointly model bottle use, daily milk intake from bottles, and daily energy intake. We show in the two joint models that the bottle-weaning intervention promotes bottleweaning, and reduces daily milk intake from bottles in toddlers not off bottles and daily energy intake. We also show that the odds of drinking from a bottle were positively associated with the amount of milk intake from bottles and increased daily milk intake from bottles was associated with increased daily energy intake. The effect of bottle use on daily energy intake is through its effect on increasing daily milk intake from bottles that in turn increases daily energy intake.

Keywords: two-part model, semi-continuous variable, joint model, gamma regression, shared parameter model, random effects model

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Authors: T. M. Ismail, M. A. El-Salam

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A mathematical model study was carried out to investigate gasification of biomass fuels using high-temperature air and steam as a gasifying agent using high-temperature air up to 1000°C. In this study, a 2D computational fluid dynamics model was developed to study the gasification process in an updraft gasifier, considering drying, pyrolysis, combustion, and gasification reactions. The gas and solid phases were resolved using a Euler−Euler multiphase approach, with exchange terms for the momentum, mass, and energy. The standard k−ε turbulence model was used in the gas phase, and the particle phase was modeled using the kinetic theory of granular flow. The results show that the present model giving a promising way in its capability and sensitivity for the parameter effects that influence the gasification process.

Keywords: computational fluid dynamics, gasification, biomass fuel, fixed bed gasifier

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Authors: Dheyaa Wajid Abbood, Hanan Hussien Abood

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Stepped cascade has been utilized as a hydraulic structure for years. It has proven to be the least costly aeration system in replenishing dissolved oxygen. Numerical modeling of stepped cascade with end sill is very complicated and challenging because of the high roughness and velocity re circulation regions. Volume of fluid multiphase flow model (VOF) is used .The realizable k-ξ model is chosen to simulate turbulence. The computational results are compared with lab-scale stepped cascade data. The lab –scale model was constructed in the hydraulic laboratory, Al-Mustansiriya University, Iraq. The stepped cascade was 0.23 m wide and consisted of 3 steps each 0.2m high and 0.6 m long with variable end sill. The discharge was varied from 1 to 4 l/s. ANSYS has been employed to simulate the experimental data and their related results. This study shows that ANSYS is able to predict results almost the same as experimental findings in some regions of the structure.

Keywords: stepped cascade weir, aeration, multiphase flow model, ansys

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Authors: R. Monteiro, A. Abarca

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Large scale seismic risk assessment has become increasingly popular to evaluate the physical vulnerability of a given region to seismic events, by putting together hazard, exposure and vulnerability components. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), explains the steps and expected results for the development of an integrated seismic risk model for assessment of the vulnerability of residential buildings in Northern Algeria. For this purpose, the model foresees the consideration of an updated seismic hazard model, as well as ad-hoc exposure and physical vulnerability models for local residential buildings. The first results of this endeavor, such as the hazard model and a specific taxonomy to be used for the exposure and fragility components of the model are presented, using as starting point the province of Blida, in Algeria. Specific remarks and conclusions regarding the characteristics of the Northern Algerian in-built are then made based on these results.

Keywords: Northern Algeria, risk, seismic hazard, vulnerability

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Authors: M. Kharazmi, M. Zakeri, M. Packirisamy, J. Faraji

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Micro/Nanorobotics or manipulation of nanoparticles by Atomic Force Microscopic (AFM) is one of the most important solutions for controlling the movement of atoms, particles and micro/nano metrics components and assembling of them to design micro/nano-meter tools. Accurate modelling of manipulation requires identification of forces and mechanical knowledge in the Nanoscale which are different from macro world. Due to the importance of the adhesion forces and the interaction of surfaces at the nanoscale several friction models were presented. In this research, friction and normal forces that are applied on the AFM by using of the dynamic bending-torsion model of AFM are obtained based on Hurtado-Kim friction model (HK), Johnson-Kendall-Robert contact model (JKR) and Greenwood-Williamson roughness model (GW). Finally, the effect of standard deviation of asperities height on the normal load, friction force and friction coefficient are studied.

Keywords: atomic force microscopy, contact model, friction coefficient, Greenwood-Williamson model

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Authors: Pouya Molana, Zeinab Alimohammadi

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Determining wind wave characteristics is essential for implementing projects related to Coastal and Marine engineering such as designing coastal and marine structures, estimating sediment transport rates and coastal erosion rates in order to predict significant wave height (H_s), this study applies the third generation spectral wave model, Mike 21 SW, along with CEM model. For SW model calibration and verification, two data sets of meteorology and wave spectroscopy are used. The model was exposed to time-varying wind power and the results showed that difference ratio mean, standard deviation of difference ratio and correlation coefficient in SW model for H_s parameter are 1.102, 0.279 and 0.983, respectively. Whereas, the difference ratio mean, standard deviation and correlation coefficient in The Choice Experiment Method (CEM) for the same parameter are 0.869, 1.317 and 0.8359, respectively. Comparing these expected results it is revealed that the Choice Experiment Method CEM has more errors in comparison to MIKE 21 SW third generation spectral wave model and higher correlation coefficient does not necessarily mean higher accuracy.

Keywords: MIKE 21 SW, CEM method, significant wave height, difference ratio

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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: Ashley Wei-Ting Wang, Wen-Yau Hsu

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Objectives: The current study applies and expands the Tripartite Model to elaborate the link between non-suicidal self-injury (NSSI) and suicidal behavior. We propose a structural model of NSSI and suicidal risk, in which negative affect (NA) predicts both anxiety and depression, positive affect (PA) predicts depression only, anxiety is linked to NSSI, and depression is linked to suicidal risk. Method: Four hundreds and eighty seven undergraduates participated. Data were collected by administering self-report questionnaires. We performed hierarchical regression and structural equation modeling to test the proposed structural model. Results: The results largely support the proposed structural model, with one exception: anxiety was strongly associated with NSSI and to a lesser extent with suicidal risk. Conclusions: We conclude that the co-occurrence of NSSI and suicidal risk is due to NA and anxiety, and suicidal risk can be differentiated by depression. Further theoretical and practical implications are discussed.

Keywords: non-suicidal self-injury, suicidal risk, anxiety, depression, the tripartite model, hierarchical relationship

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Authors: Shih-Kuei Lin

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The characterization of the arbitrage-free dynamics of interest rates is developed in this study under the presence of Markov jump risks, when the term structure of the interest rates is modeled through simple forward rates. We consider Markov jump risks by allowing randomness in jump sizes, independence between jump sizes and jump times. The Markov jump diffusion model is used to capture empirical phenomena and to accurately describe interest jump risks in a financial market. We derive the arbitrage-free model of simple forward rates under the spot measure. Moreover, the analytical pricing formulas for a cap and a floor are derived under the forward measure when the jump size follows a lognormal distribution. In our empirical analysis, we find that the LIBOR market model with Markov jump risk better accounts for changes from/to different states and different rates.

Keywords: arbitrage-free, cap and floor, Markov jump diffusion model, simple forward rate model, volatility smile, EM algorithm

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Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

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Authors: J. Fernandez, N. Aguilar, R. Fernandez de Canete, J. C. Ramos-Diaz

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In this paper, a simulation model of the glucose-insulin system for a patient undergoing diabetes Type 1 is developed by using a causal modeling approach under system dynamics. The OpenModelica simulation environment has been employed to build the so called causal model, while the glucose-insulin model parameters were adjusted to fit recorded mean data of a diabetic patient database. Model results under different conditions of a three-meal glucose and exogenous insulin ingestion patterns have been obtained. This simulation model can be useful to evaluate glucose-insulin performance in several circumstances, including insulin infusion algorithms in open-loop and decision support systems in closed-loop.

Keywords: causal modeling, diabetes, glucose-insulin system, diabetes, causal modeling, OpenModelica software

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Authors: Tareq Oshan

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Facility location and size decisions are important to any company because they affect profitability and success. However, warehouses are exposed to various risks of failure that affect their activity. This paper presents a mixed-integer non-linear mathematical model that can be used to determine optimal warehouse locations and sizes, which warehouses to fortify, and which branches should be assigned to specific warehouses when there is a risk of warehouse failure. Every branch is assigned to a fortified primary warehouse or a nonfortified primary warehouse and a fortified backup warehouse. The standard method and an introduced method, based on the average probabilities, for linearizing this mathematical model were used. A Canadian case study was used to demonstrate the developed mathematical model, followed by some sensitivity analysis.

Keywords: supply chain network design, fortified warehouse, mixed-integer mathematical model, warehouse failure risk

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Authors: T. M. L. Hoang, G. Tan, S. D. Bhowmik, B. Williams, A. Johnson, M. R. Karbaschi, Y. Cheng, H. Long, S. G. Mundree

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Iron deficiency is a worldwide problem affecting both developed and developing countries. Currently, two major approaches namely iron supplementation and food fortification have been used to combat this issue. These measures, however, are limited by the economic status of the targeted demographics. Iron biofortification through genetic modification to enhance the inherent iron content and bioavailability of crops has been employed recently. Several important crops such as rice, wheat, and banana were reported successfully improved iron content via this method, but there is no known study in legumes. Chickpea (Cicer arietinum) is an important leguminous crop that is widely consumed, particularly in India where iron deficiency anaemia is prevalent. Chickpea is also an ideal pulse in the formulation of complementary food between pulses and cereals to improve micronutrient contents. This project aims at generating enhanced ion accumulation and bioavailability chickpea through the exogenous expression of genes related to iron transport and iron homeostasis in chickpea plants. Iron-Regulated Transport (IRT) and Ferritin genes in combination were transformed into chickpea half-embryonic axis by agrobacterium–mediated transformation. Transgenic independent event was confirmed by Southern Blot analysis. T3 leaves and seeds of transgenic chickpea were assessed for iron contents using LA-ICP-MS (Laser Ablation – Inductively Coupled Plasma Mass Spectrometry) and ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometry). The correlation between transgene expression levels and iron content in T3 plants and seeds was assessed using qPCR. Results show that iron content in transgenic chickpea expressing the above genes significantly increased compared to that in non-transgenic controls.

Keywords: iron biofortification, chickpea, IRT, ferritin, Agrobacterium-mediated transformation, LA-ICP-MS, ICP-OES

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Authors: Malory Jonata

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Chlordecone (CLD) is an organochlorine pesticide used between 1971 and 1993 in both Guadeloupe and Martinique for the control of banana black weevil. The bishomocubane structure which characterizes this chemical compound led to high stability in organic matter and high persistence in the environment. Recently, researchers found that CLD can be degraded by isolated bacteria consortiums and, particularly, by bacteria such as Citrobacter sp 86 and Delsulfovibrio sp 86. Actually, six transformation product families of CLD are known. Moreover, the latest discovery showed that CLD was disappearing faster than first predicted in highly contaminated soil in Guadeloupe. However, the toxicity of transformation products is still unknown, and knowledge has to be deepened on the degradation ways and chemical characteristics of chlordecone and its transformation products. Microbial fuel cells (MFC) are electrochemical systems that can convert organic matter into electricity thanks to electroactive bacteria. These bacteria can exchange electrons through their membranes to solid surfaces or molecules. MFC have proven their efficiency as bioremediation systems in water and soils. They are already used for the bioremediation of several organochlorine compounds such as perchlorate, trichlorophenol or hexachlorobenzene. In this study, a three-electrodes system, inspired by MFC, is used to try to degrade chlordecone using bacteria from a mangrove swamp in Martinique. As we know, some mangrove bacteria are electroactive. Furthermore, the CLD rate seems to decline in mangrove swamp sediments. This study aims to prove that electroactive bacteria from a mangrove swamp in Martinique can degrade CLD thanks to a three-electrodes bioelectrochemical system. To achieve this goal, the tree-electrodes assembly has been connected to a potentiostat. The substrate used is mangrove water and sediments sampled in the mangrove swamp of La Trinité, a coastal city in Martinique, where CLD contamination has already been studied. Electroactive biofilms are formed by imposing a potential relative to Saturated Calomel Electrode using chronoamperometry. Moreover, their comportment has been studied by using cyclic voltametry. Biofilms have been studied under different imposed potentials, several conditions of the substrate and with or without CLD. In order to quantify the evolution of CLD rates in the substrate’s system, gas chromatography coupled with mass spectrometry (GC-MS) was performed on pre-treated samples of water and sediments after short, medium and long-term contact with the electroactive biofilms. Results showed that between -0,8V and -0,2V, the three-electrodes system was able to reduce the chemical in the substrate solution. The first GC-MS analysis result of samples spiked with CLD seems to reveal decreased CLD concentration over time. In conclusion, the designed bioelectrochemical system can provide the necessary conditions for chlordecone degradation. However, it is necessary to improve three-electrodes control settings in order to increase degradation rates. The biological pathways are yet to enlighten by biologicals analysis of electroactive biofilms formed in this system. Moreover, the electrochemical study of mangrove substrate gives new informations on the potential use of this substrate for bioremediation. But further studies are needed to a better understanding of the electrochemical potential of this environment.

Keywords: bioelectrochemistry, bioremediation, chlordecone, mangrove swamp

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Authors: M. J. Eichner, Y. S. Sarhan

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Overall study purpose has been the evaluation of ‘Vertical Villages’ as a new sustainable building typology, reducing significantly negative impacts of rapid urbanization processes in third world capital cities. Commonly in fast-growing cities, housing and job supply, educational and recreational opportunities, as well as public transportation infrastructure, are not accommodating rapid population growth, exposing people to high noise and emission polluted living environments with low-quality neighborhoods and a lack of recreational areas. Like many others, Egypt’s capital city Cairo, according to the UN facing annual population growth rates of up to 428.000 people, is struggling to address the general deterioration of urban living conditions. New settlements typologies and urban reconstruction approach hardly follow sustainable urbanization principles or socio-ecologic urbanization models with severe effects not only for inhabitants but also for the local environment and global climate. The authors prove that ‘Vertical Village’ buildings can offer a sustainable solution for increasing urban density with at the same time improving the living quality and urban environment significantly. Inserting them within high-density urban fabrics the ecologic and socio-cultural conditions of low-quality neighborhoods can be transformed towards districts, considering all needs of sustainable and social urban life. This study analyzes existing building typologies in Cairo’s «low quality - high density» districts Ard el Lewa, Dokki and Mohandesen according to benchmarks for sustainable residential buildings, identifying major problems and deficits. In 3 case study design projects, the sustainable transformation potential through ‘Vertical Village’ buildings are laid out and comparative studies show the improvement of the urban microclimate, safety, social diversity, sense of community, aesthetics, privacy, efficiency, healthiness and accessibility. The main result of the paper is that the disadvantages of density and overpopulation in developing countries can be converted with ‘Vertical Village’ buildings into advantages, achieving attractive and environmentally friendly living environments with multiple synergies. The paper is documenting based on scientific criteria that mixed-use vertical building structures, designed according to sustainable principles of low rise housing, can serve as an alternative to convert «low quality - high density» districts in megacities, opening a pathway for governments to achieve sustainable urban transformation goals. Neglected informal urban districts, home to millions of the poorer population groups, can be converted into healthier living and working environments.

Keywords: sustainable, architecture, urbanization, urban transformation, vertical village

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Authors: K. M. Anusha, R. Krishnaveni

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Crossing a decade of the 21st century, the paradigm of human resources can be seen evolving with the strategic gene induced into it. There seems to be a radical shift descending as the corporate sector calls on its HR team to become strategic rather than administrative. This transferal eventually requires the metrics employed by these HR teams not to be just operationally reactive but to be aligned to an evidence-based strategic thinking. Realizing the growing need for a prescriptive metric model for effective HR analytics, this study has designed a conceptual framework for a basic metric model that can assist IT-HRM professionals to transition to a practice of evidence-based decision-making to enhance organizational performance.

Keywords: metric model, evidence based HR, HR analytics, strategic HR practices, IT sector

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Authors: Nikolaos Reppas, Yilin Gui

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A dual-porosity finite element-code will be presented for the stability analysis of the wellbore during CO₂ injection. An elastoplastic damage response will be considered to the model. The Finite Element Method (FEM) will be validated using experimental results from literature or from experiments that are planned to be undertaken at Newcastle University. The main target of the research paper is to present a constitutive model that can help industries to safely store CO₂ in geological rock formations and forecast any changes on the surrounding rock of the wellbore. The fully coupled elastoplastic damage Thermo-Hydraulic-Mechanical (THM) model will determine the pressure and temperature of the injected CO₂ as well as the size of the radius of the wellbore that can make the Carbon Capture and Storage (CCS) procedure more efficient.

Keywords: carbon capture and storage, Wellbore stability, elastoplastic damage response for rock, constitutive THM model, fully coupled thermo-hydraulic-mechanical model

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Authors: N. Guo, C. Xu, Z. C. Yang

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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

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Authors: Jin Sung Kim, Hoon Huh

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The material properties of OFHC copper film was investigated with the High-Speed Material Micro Testing Machine (HSMMTM) at the high strain rates. The rate-dependent stress-strain curves from the experiment and the Johnson-Cook curve fitting showed large discrepancies as the plastic strain increases since the constitutive model implies no rate-dependent strain hardening effect. A new constitutive model was proposed in consideration of rate-dependent strain hardening effect. The strain rate hardening term in the new constitutive model consists of the strain rate sensitivity coefficients of the yield strength and strain hardening.

Keywords: rate dependent material properties, dynamic constitutive model, OFHC copper film, strain rate

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Authors: M. Ndaw, G. Mendy, S. Ouya

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Risk management in banking sector is a key issue linked to financial system stability and its importance has been elevated by technological developments and emergence of new financial instruments. In this paper, we improve the model previously defined for quantifying internal control impact on banking risks by automatizing the residual criticality estimation step of FMECA. For this, we defined three equations and a maturity coefficient to obtain a mathematical model which is tested on all banking processes and type of risks. The new model allows an optimal assessment of residual criticality and improves the correlation rate that has become 98%.

Keywords: risk, control, banking, FMECA, criticality

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Authors: Fernando P. Silva, Valter J. S. Leite, Erivelton G. Nepomuceno

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In this paper, a nonlinear controller design for an omnidirectional mobile is presented. The robot controller consists of an inner-loop controller and an outer-loop controller, the first is designed using state feedback (robust allocation) and the second controller is designed based on Robust Multi Inversion (RMI) approach. The objective of RMI controller is rendering the robust inversion of the dynamic, when the model is affected by uncertainties. A model nonlinear MIMO of an omni-directional robot (small-league of Robocup) is used to simulate the RMI approach. The parameters of linear and nonlinear model are varied to cause modelling uncertainties among the model and the real model (real system) generating an error in inner-loop controller signal that must be compensated by RMI controller. The simulation test results show that the RMI is capable of compensating the uncertainties and keep the system stable and controlled under uncertainties.

Keywords: robust multi inversion, omni-directional robot, robocup, nonlinear control

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Authors: Farzad Khajavi, Farzaneh Jalilfar, Faranak Jafari, Leila Shokrani

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Formulation of gliclazide in the form of extended-release tablet in 30 and 60 mg dosage forms was performed using hypromellose (HPMC K4M) as a retarding agent. Drug-release profiles were investigated in comparison with references Diamicron MR 30 and 60 mg tablets. The effect of size of powder particles, the amount of hypromellose in formulation, hardness of tablets, and also the effect of halving the tablets were investigated on drug release profile. A mathematical model which describes hypromellose behavior in initial times of drug release was proposed for the estimation of hypromellose content in modified-release gliclazide 60 mg tablet. This model is based on erosion of hypromellose in dissolution media. The model is applicable to describe release profiles of insoluble drugs. Therefore, by using dissolved amount of drug in initial times of dissolution and the model, the amount of hypromellose in formulation can be predictable. The model was used to predict the HPMC K4M content in modified-release gliclazide 30 mg and extended-release quetiapine 200 mg tablets.

Keywords: Gliclazide, hypromellose, drug release, modified-release tablet, mathematical model

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Authors: Maryam Aloshan, Imam Mohammad Ibn Saud, Ahmad Khudair

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This study assesses the data governance maturity of nonprofit organizations in Riyadh, Saudi Arabia, using the National Data Maturity Index (NDI) framework developed by the Saudi Data and Artificial Intelligence Authority (SDAIA). Employing a survey designed around the NDI model, data maturity levels were evaluated across 14 dimensions using a 5-point Likert scale. The results reveal a spectrum of maturity levels among the organizations surveyed: while some medium-sized associations reached the ‘Defined’ stage, others, including large associations, fell within the ‘Absence of Capabilities’ or ‘Building’ phases, with no organizations achieving the advanced ‘Established’ or ‘Pioneering’ levels. This variation suggests an emerging recognition of data governance but underscores the need for targeted interventions to bridge the maturity gap. The findings point to a significant opportunity to elevate data governance capabilities in Saudi nonprofits through customized capacity-building initiatives, including training, mentorship, and best practice sharing. This study contributes valuable insights into the digital transformation journey of the Saudi nonprofit sector, aligning with national goals for data-driven governance and organizational efficiency.

Keywords: nonprofit organizations-national data maturity index (NDI), Saudi Arabia- SDAIA, data governance, data maturity

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

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Authors: Amin Noor, Roslinda Nazar, Norihan Md. Arifin

Abstract:

In this paper, a numerical and theoretical study has been performed for the stagnation-point boundary layer flow and heat transfer towards a shrinking sheet in a nanofluid. The mathematical nanofluid model in which the effect of the nanoparticle volume fraction is taken into account is considered. The governing nonlinear partial differential equations are transformed into a system of nonlinear ordinary differential equations using a similarity transformation which is then solved numerically using the function bvp4c from Matlab. Numerical results are obtained for the skin friction coefficient, the local Nusselt number as well as the velocity and temperature profiles for some values of the governing parameters, namely the nanoparticle volume fraction Φ, the shrinking parameter λ and the Prandtl number Pr. Three different types of nanoparticles are considered, namely Cu, Al2O3 and TiO2. It is found that solutions do not exist for larger shrinking rates and dual (upper and lower branch) solutions exist when λ < -1.0. A stability analysis has been performed to show which branch solutions are stable and physically realizable. It is also found that the upper branch solutions are stable while the lower branch solutions are unstable.

Keywords: heat transfer, nanofluid, shrinking sheet, stability analysis, stagnation-point flow

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