Search results for: partial least squares regression

Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Shahadut Hossain, Jacek Wesolowski, Zahirul Hoque

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In many epidemiological and environmental studies covariate measurements are subject to the detection limit. In most applications, covariate measurements are usually truncated from below which is known as left-truncation. Because the measuring device, which we use to measure the covariate, fails to detect values falling below the certain threshold. In regression analyses, it causes inflated bias and inaccurate mean squared error (MSE) to the estimators. This paper suggests a response-based regression calibration method to correct the deleterious impact introduced by the covariate detection limit in the estimators of the parameters of simple logistic regression model. Compared to the maximum likelihood method, the proposed method is computationally simpler, and hence easier to implement. It is robust to the violation of distributional assumption about the covariate of interest. In producing correct inference, the performance of the proposed method compared to the other competing methods has been investigated through extensive simulations. A real-life application of the method is also shown using data from a population-based case-control study of non-Hodgkin lymphoma.

Keywords: environmental exposure, detection limit, left truncation, bias, ad-hoc substitution

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Authors: Kajal K. Patel, M. N. Mehta, T. R. Singh

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When water is injected in oil formatted area in secondary oil recovery process the instability occurs near common interface due to viscosity difference of injected water and native oil. The governing equation gives rise to the non-linear partial differential equation and its solution has been obtained by Homotopy analysis method with appropriate guess value of the solution together with some conditions and standard relations. The solution gives the average cross-sectional area occupied by the schematic fingers during the occurs of instability phenomenon. The numerical and graphical presentation has developed by using Maple software.

Keywords: capillary pressure, homotopy analysis method, instability phenomenon, viscosity

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Authors: Chien-Kuo Chang, You-Syuan Wu, Min-Chiu Wu, Chun-Wei Wang

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Epoxy resin is widely used in the insulation of high-voltage equipment such as transformers and insulating bushings due to its good electrical insulation properties. However, manufacturing defects will cause unpredictable accidents. Therefore, it is an important issue to determine the insulation state of equipment by measuring partial discharges. In this study, the needle-plane electrode structure was used to test the epoxy resin electrical treeing insulation deterioration phenomenon. During the test, we measured the partial discharge signal and then used the signal as the input data of the insulation status assessment system, which was developed in the past research. The experimental samples were made of transparent epoxy resin to facilitate the observation of changes, and were made in the distance of 1 cm and 1.5 cm of 5 sets. During the experiment, a magnifying glass with a total magnification of 2 times is set up to enlarge the picture and a time-lapse camera is used to record the changes of the experimental samples. In the experiment, we found that the electrical treeing phenomenon of the epoxy resin insulation deterioration process can be divided into several stages: initial dark tree, filamentary tree, reverse tree, and insulation breakdown, and simply observed each stage of electrical treeing. After substituting the partial discharge signal into the insulation status assessment system, it can be found that most experimental samples were assessed into the attention period in the middle of the test and into the risky period in the middle and late of the test. Compared to the attention period signal to the recorded film, there was no obvious correlation currently, but compared to the risky period signal, we can see that the experimental sample deformed due to the temperature rise caused by the larger and more frequent discharge. Besides, we also try to collect data about different types of PD by mixing high dielectric constant materials and changing the interior constitution of the sample. Recording data like PDIV、PDEV、RPDIV, the data that recorded can improve performance of various algorithm models.

Keywords: partial discharge, insulation deterioration, epoxy resin, electrical treeing

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Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

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Authors: Mezidi Amar

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In this research work, crack propagation at the interface of a composite beam is considered. The behavior of composite beams (CB) depends upon a law based on relationship between tangential or normal efforts with inelastic propagation. Throughout this study, composite beams are classified like composite beams with partial connection or sandwich beams of three layers. These structural systems are controlled by the same nature of differential equations regarding their behavior in the plane, as well as out-of-plane. Multi-layer elements with partial connection are typically met in the field of timber construction where the elements are assembled by joining. The formalism of the behavior in the plane and out-of-plane of these composite beams is obtained and their results concerning the engineering aspect or simple of interpretation are proposed for the case of composite beams made up of rectangular section and simply supported section. An apparent analytical peculiarity or paradox in the bending behavior of elastic–composite beams with interlayer slip, sandwich beam or other similar problems subjected to boundary moments exists. For a fully composite beam subjected to end moments, the partial composite model will render a non-vanishing uniform value for the normal force in the individual subelement. Obtained results are similar to those for the case of vibrations in the plane as well for the composite beams as for the sandwich beams where eigen-frequencies increase with related rigidity.

Keywords: composite beam, behaviour, interface, deflection, propagation

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Authors: Edmund Kwablah, Anthony Amoah

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The merits associated with Foreign Direct Investment (FDI) inflows to host countries in Sub-Saharan Africa cannot be overemphasized. Against this background, countries have sought to design and implement strategic policies geared towards enhacing FDI and promoting economic growth. In this study, we used the Fully Modified Ordinary Least Squares technique and a panel data for Sub-Saharan African (SSA) countries spanning from 1998 to 2016. We hypothesize that FDI’s effect on economic growth is contingent on some absorptive capacities (e.g., financial market development and economic freedom) of the host country. We used financial market data that accounts for market fragility as a measure of financial market development and economic freedom data which uses the overall score of all the freedom indicators as a measure of economic freedom. Our results suggest that FDI has a statistically positive effect on economic growth when we account for host country’s absorptive capacities. However, a negative relationship will ensue if these absorptive capacities are not accounted for. We recommend that a developing continent like SSA should focus on identifying and building the relevant absorptive capacities that can translate the effect of FDI into a positive growth. This is because an economy with sound absorptive capacities reduces business risk and spur economic growth.

Keywords: FDI, absorptive capacity, economic growth, FMOLS, Fully Modified Ordinary Least Squares, SSA

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Authors: A. K. Jain, M. C. Paliwal

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The production of cement leads to the emission of large amounts of carbon-dioxide gas into the atmosphere which is a major contributor for the greenhouse effect and the global warming; hence it is mandatory either to quest for another material or partly replace it with some other material. According to the practical demonstrations and reports, Egg Shell Powder (ESP) can be used as a binding material for different field applications as it contains some of the properties of lime. It can partially replace the cement and further; it can be used in different proportion for enhancing the performance of cement. It can be used as a first-class alternative, for material reuse and waste recycling practices. Eggshell is calcium rich and analogous to limestone in chemical composition. Therefore, use of eggshell waste for partial replacement of cement in concrete is feasible. Different studies reveal that plasticity index of the soil can be improved by adding eggshell wastes in all the clay soil and it has wider application in construction projects including earth canals and earthen dams. The scarcity of aggregates is also increasing nowadays. Utilization of industrial waste or secondary materials is increasing in different construction applications. Coconut shell was successfully used in the construction industry for partial or full replacement for coarse aggregates. The use of coconut shell gives advantage of using waste material to partially replace the coarse aggregate. Studies carried on coconut shell indicate that it can partially replace the aggregate. It has good strength and modulus properties along with the advantage of high lignin content. It absorbs relatively low moisture due to its low cellulose content. In the paper, study carried out on eggshell powder and coconut shell will be discussed. Optimum proportions of these materials to be used for partial replacement of cement and aggregate will also be discussed.

Keywords: greenhouse, egg shell powder, binding material, aggregates, coconut shell, coarse aggregates

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Authors: Xiang Jianhong, Wang Cong, Wang Linyu

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With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal ECG, compressed sensing, joint sparse reconstruction, block sparse signal

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Authors: Raya Al Khayari, Rasha Al Jassim, Muna Al Balushi, Fatma Al Moqbali, Said El Hajjar

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This study utilizes linear regression analysis to investigate the correlation between user account passwords and the probability of civil ID exposure, offering statistical insights into civil ID security. The study employs multiple linear regression (MLR) analysis to further investigate the elements that influence consumers’ views of civil ID security. This aims to increase awareness and improve preventive measures. The results obtained from the MLR analysis provide a thorough comprehension and can guide specific educational and awareness campaigns aimed at promoting improved security procedures. In summary, the study’s results offer significant insights for improving existing security measures and developing more efficient tactics to reduce risks related to civil ID security in Oman. By identifying key factors that impact consumers’ perceptions, organizations can tailor their strategies to address vulnerabilities effectively. Additionally, the findings can inform policymakers on potential regulatory changes to enhance civil ID security in the country.

Keywords: civil-id disclosure, awareness, linear regression, multiple regression

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Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro

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In urban context, urban nodes such as amenity or hazard will certainly affect house price, while classic hedonic analysis will employ distance variables measured from each urban nodes. However, effects from distances to facilities on house prices generally do not represent the true price of the property. Distance variables measured on the same surface are suffering a problem called multicollinearity, which is usually presented as magnitude variance and mean value in regression, errors caused by instability. In this paper, we provided a theoretical framework to identify and gather the data with less bias, and also provided specific sampling method on locating the sample region to avoid the spatial multicollinerity problem in three distance variable’s case.

Keywords: hedonic regression, urban node, distance variables, multicollinerity, collinearity

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Authors: Abhinav Kumar Rajverma, Arun Kumar Misra, Abhijeet Chandra

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Family involvement in business is universal across countries, with varying characteristics. Firms of developed economies have diffused ownership structure; however, that of emerging markets have concentrated ownership structure, having resemblance with that of family firms. Optimization of dividend payout and leverage are very crucial for firm’s valuation. This paper studies dividend paying behavior of National Stock Exchange listed Indian firms from financial year 2007 to 2016. The final sample consists of 422 firms and of these more than 49% (207) are family firms. Results reveal that family firms pay lower dividend and are more leveraged compared to non-family firms. This unique data set helps to understand dividend behavior and capital structure of sample firms over a long-time period and across varying family ownership concentration. Using panel regression models, this paper examines factors affecting dividend payout and capital structure and establishes a link between the two using Two-stage Least Squares regression model. Profitability shows a positive impact on dividend and negative impact on leverage, confirming signaling and pecking order theory. Further, findings support bankruptcy theory as firm size has a positive relation with dividend and leverage and volatility shows a negative relation with both dividend and leverage. Findings are also consistent with agency theory, family ownership concentration has negative relation with both dividend payments and leverage. Further, the impact of family ownership control confirms the similar finding. The study further reveals that firms with high family ownership concentration (family control) do have an impact on determining the level of private benefits. Institutional ownership is not significant for dividend payments. However, it shows significant negative relation with leverage for both family and non-family firms. Dividend payout and leverage show mixed association with each other. This paper provides evidence of how varying level of family ownership concentration and ownership control influences the dividend policy and capital structure of firms in an emerging market like India and it can have significant contribution towards understanding and formulating corporate dividend policy decisions and capital structure for emerging economies, where majority of firms exhibit behavior of family firm.

Keywords: dividend, family firms, leverage, ownership structure

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Authors: Ali Safdari-Vaighani

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Pricing financial contracts on several underlying assets received more and more interest as a demand for complex derivatives. The option pricing under asset price involving jump diffusion processes leads to the partial integral differential equation (PIDEs), which is an extension of the Black-Scholes PDE with a new integral term. The aim of this paper is to show how basket option prices in the jump diffusion models, mainly on the Merton model, can be computed using RBF based approximation methods. For a test problem, the RBF-PU method is applied for numerical solution of partial integral differential equation arising from the two-asset European vanilla put options. The numerical result shows the accuracy and efficiency of the presented method.

Keywords: basket option, jump diffusion, ‎radial basis function, RBF-PUM

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Authors: Norshima Humaidi, Saif Hussein Abdallah Alghazo

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Cybersecurity threat have become a serious issue recently, and one of the cause is because human error, which is usually constituted by carelessness, ignorance, and failure to practice cybersecurity behaviour adequately. Using a data from a quantitative survey, Partial Least Squares-Structural Equation Modelling (PLS-SEM) analysis was used to determine the factors that affect cybersecurity protective behaviour (CPB). This study adapts cybersecurity protective behaviour model by focusing on two constructs that can enhance CPB: manager’s information security competencies (MISI) and procedural information security countermeasure (PCM) awareness. Theory of leadership competencies were adapted to measure user’s perception towards competencies among security managers/leader in the organization. Confirmatory factor analysis (CFA) testing shows that all the measurement items of each constructs were adequate in their validity individually based on their factor loading value. Moreover, each constructs are valid based on their parameter estimates and statistical significance. The quantitative research findings show that PCM awareness strongly influences CPB compared to MISI. Meanwhile, MISI was significantlyPCM awarenss. This study believes that the research findings can contribute to human behaviour in IS studies and are particularly beneficial to policy makers in improving organizations’ strategic plans in information security, especially in this new era. Most organizations spend time and resources to provide and establish strategic plans of information security; however, if employees are not willing to comply and practice information security behaviour appropriately, then these efforts are in vain.

Keywords: cybersecurity, protection behaviour, information security, information security competencies, countermeasure awareness

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Authors: Milica Karadžić, Lidija Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Anamarija Mandić, Aleksandar Oklješa, Andrea Nikolić, Marija Sakač, Katarina Penov Gaši

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Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology).

Keywords: artificial neural networks, chemometrics, global sensitivity analysis, liquid chromatography, steroids

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Authors: Oluremi I. Bamgbade, Oluwayomi Babatunde

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Governments and nonprofits have been in the support of sustainability as the goal of businesses especially in the construction industry because of its considerable impacts on the environment, economy, and society. However, to measure the degree to which an organisation is being sustainable or pursuing sustainable growth can be difficult as a result of the clear sustainability strategy required to assume their commitment to the goal and competitive advantage. This research investigated the influence of organisational culture and organisational structure in achieving sustainable construction among South African construction firms. A total of 132 consultants from the nine provinces in South Africa participated in the survey. The data collected were initially screened using SPSS (version 21) while Partial Least Squares Structural Equation Modeling (PLS-SEM) algorithm and bootstrap techniques were employed to test the hypothesised paths. The empirical evidence also supported the hypothesised direct effects of organisational culture and organisational structure on sustainable construction. Similarly, the result regarding the relationship between organisational culture and organisational structure was supported. Therefore, construction industry can record a considerable level of construction sustainability and establish suitable cultures and structures within the construction organisations. Drawing upon organisational control theory, these findings supported the view that these organisational internal factors have a strong contingent effect on sustainability adoption in construction project execution. The paper makes theoretical, practical and methodological contributions within the domain of sustainable construction especially in the context of South Africa. Some limitations of the study are indicated, suggesting opportunities for future research.

Keywords: organisational culture, organisational structure, South African construction firms, sustainable construction

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Authors: Arun Goel

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The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free over-fall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, support vector machine (Polynomial and rbf) models, and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free over-fall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: air entrainment rate, dissolved oxygen, weir, SVM, regression

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Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

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Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution

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Authors: Muhammad Kashif

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The primary aim of this paper is to investigate the influence of financial technology (FinTech) on sustainable finance. The sample for this study spans from 2010 to 2021, encompassing data from 89 countries worldwide. The study employed two-stage least squares (2SLS) regression approach with the instrumental variables and validated the findings using a two-step system generalized method of moments (GMM). The findings indicate that fintech has a significant favorable impact on sustainable finance. While other factors such as institutional quality, socio-economic condition, and renewable energy have a significant and beneficial influence on the trajectory of sustainable finance, except globalization's impact is positive but insignificant. Furthermore, fintech is crucial in driving the transition toward a sustainable future characterized by a lower carbon economy. The study found that fintech has extensive application across various sectors of sustainable finance and has substantial potential to create long-term positive effects on sustainable finance. Fintech can integrate extensively with other technologies to facilitate diversified growth in sustainable finance. Additionally, this study highlights fintech-related trends and research opportunities in sustainable finance, showing how these can promote each other worldwide with important policy implications for countries looking to advance sustainable finance through technology.

Keywords: sustainable development goals (SDGs), financial technology (FinTech), genuine savings index (GSI), financial stability index, sustainable finance

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Authors: Zerroug Abdelhamid, Danielle Chassoux

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Various models are given to simulate homogeneous or heterogeneous cancerous tumors and extract in each case the boundary. The fractal dimension is then estimated by least squares method and compared to some previous methods.

Keywords: simulation, cancerous tumor, Markov fields, fractal dimension, extraction, recovering

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Authors: Mehmet Alpaslan Köroğlu, Musa Hakan Arslan, Muslu Kazım Körez

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Basic objective of this study is to create a regression analysis method that can estimate the length of a plastic hinge which is an important design parameter, by making use of the outcomes of (lateral load-lateral displacement hysteretic curves) the experimental studies conducted for the reinforced square concrete columns. For this aim, 170 different square reinforced concrete column tests results have been collected from the existing literature. The parameters which are thought affecting the plastic hinge length such as cross-section properties, features of material used, axial loading level, confinement of the column, longitudinal reinforcement bars in the columns etc. have been obtained from these 170 different square reinforced concrete column tests. In the study, when determining the length of plastic hinge, using the experimental test results, a regression analysis have been separately tested and compared with each other. In addition, the outcome of mentioned methods on determination of plastic hinge length of the reinforced concrete columns has been compared to other methods available in the literature.

Keywords: columns, plastic hinge length, regression analysis, reinforced concrete

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Authors: M. Hemam, M. Djezzar, T. Djouad

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We are interested in the problem of building an ontology in a heterogeneous organization, by taking into account different viewpoints and different terminologies of communities in the organization. Such ontology, that we call multi-viewpoint ontology, confers to the same universe of discourse, several partial descriptions, where each one is relative to a particular viewpoint. In addition, these partial descriptions share at global level, ontological elements constituent a consensus between the various viewpoints. In order to provide response elements to this problem we define a multi-viewpoints knowledge model based on viewpoint and ontology notions. The multi-viewpoints knowledge model is used to formalize the multi-viewpoints ontology in description logics language.

Keywords: description logic, knowledge engineering, ontology, viewpoint

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Authors: Shahadut Hossain

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Measurement errors in continuous covariates and/or misclassifications in categorical covariates are common in epidemiological studies. Regression analysis ignoring such mismeasurements seriously biases the estimated main and interaction effects of covariates on the outcome of interest. Thus, adjustments for such mismeasurements are necessary. In this research, we propose a Bayesian parametric framework for eliminating deleterious impacts of covariate mismeasurements in logistic regression. The proposed adjustment method is unified and thus can be applied to any generalized linear and non-linear regression models. Furthermore, adjustment for covariate mismeasurements requires validation data usually in the form of either gold standard measurements or replicates of the mismeasured covariates on a subset of the study population. Initial investigation shows that adequacy of such adjustment depends on the sizes of main and validation samples, especially when prevalences of the categorical covariates are low. Thus, we investigate the impact of main and validation sample sizes on the adjusted estimates, and provide a general guideline about these sample sizes based on simulation studies.

Keywords: measurement errors, misclassification, mismeasurement, validation sample, Bayesian adjustment

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Authors: Kun-Peng Jin, Jin Liang, Ti-Jun Xiao

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In this work, we are concerned with the dynamic behaviors of solutions to some coupled systems with infinite memory, which consist of two partial differential equations where only one partial differential equation has damping. Such coupled systems are good mathematical models to describe the deformation and stress characteristics of some viscoelastic materials affected by temperature change, external forces, and other factors. By using the theory of operator semigroups, we give wellposedness results for the Cauchy problem for these coupled systems. Then, with the help of some auxiliary functions and lemmas, which are specially designed for overcoming difficulties in the proof, we show that the solutions of the coupled systems decay to zero in a strong way under a few basic conditions. The results in this dynamic analysis of coupled systems are generalizations of many existing results.

Keywords: dynamic analysis, coupled system, infinite memory, damping.

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Authors: Abbasali Abouei Mehrizi, Hao Wang

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The thin film region is so important in heat transfer process due to its low thermal resistance. On the other hand, the dynamic contact angle is crucial boundary condition in numerical simulations. While different modeling contains different assumption of the microscopic contact angle, none of them has experimental evidence for their assumption, and the contact line movement mechanism still remains vague. The experimental investigation in complete wetting is more popular than partial wetting, especially in nanoscale resolution when there is sharp variation in thin film profile in partial wetting. In the present study, an experimental investigation of water film morphology near the triple phase contact line during the condensation is performed. The state-of-the-art tapping-mode atomic force microscopy (TM-AFM) was used to get the high-resolution film profile goes down to 2 nm from the contact line. The droplet was put in saturated chamber. The pristine silicon wafer was used as a smooth substrate. The substrate was heated by PI film heater. So the chamber would be over saturated by droplet evaporation. By turning off the heater, water vapor gradually started condensing on the droplet and the droplet advanced. The advancing speed was less than 20 nm/s. The dominant results indicate that in contrast to nonvolatile liquid, the film profile goes down straightly to the surface till 2 nm from the substrate. However, small bending has been observed below 20 nm, occasionally. So, it can be claimed that for the low condensation rate the microscopic contact angle equals to the optically detectable macroscopic contact angle. This result can be used to simplify the heat transfer modeling in partial wetting. The experimental result of the equality of microscopic and macroscopic contact angle can be used as a solid evidence for using this boundary condition in numerical simulation.

Keywords: advancing, condensation, microscopic contact angle, partial wetting

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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Authors: Madeleine Gadd, Rose How, Edward Mathews, John Buchanan, Vicky Cottrell, Andre Coetzee, Karuna Katti

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Introduction: Triphallia, a congenital anomaly describing the presence of three distinct penile shafts, has been reported only once in the literature. This case report describes the serendipitous discovery of the first reported human case of partial orthotopic triphallia during cadaveric dissection. Case Summary: Despite the normal appearance of external genitalia on examination, the dissection of a 78-year-old male revealed a remarkable anatomical variation: two small supernumerary penises situated in a transverse orientation postero inferiorly to the primary penis. The main and the larger supernumerary penile shafts displayed their own corpora cavernosa and glans penis, sharing a single urethra, which coursed through the secondary penis prior to its passage through the primary penis. The smallest of the supernumerary penises was similar in dimension to the secondary penis, at 3.7cm long and 1.2cm wide (compared to the secondary penis at 3.8cm long and 1.3cm wide). However, it lacked a urethra and a typical arrangement of the corpora cavernosa and spongiosum, making this a case of partial triphallia rather than true triphallia. Conclusion: This case report provides a comprehensive anatomical description of partial triphallia in a cadaver, shedding light on the morphology, embryology, and clinical implications of this anomaly. This case report underscores the importance of meticulous anatomical dissections, particularly since, without dissection, this anatomical variation would have remained undiscovered. Although we can only speculate the functional implications of this condition, understanding such anatomical variations contributes to both knowledge of human anatomy and clinical management, should the condition be encountered in living individuals.

Keywords: triphallia, diphallia, congenital abnormalities, genitourinary abnormalities, urology

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Authors: Mikiyas Adugna

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Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

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Authors: Debajyoti Choudhuri, Ratan Kumar Giri, Shesadev Pradhan

Abstract:

The perturbed nonlinear Schrodinger equation involving the p-biharmonic and the p-Laplacian operators involving a real valued parameter and a continuous real valued potential function defined over the N- dimensional Euclidean space has been considered. By the variational technique, an existence result pertaining to a nontrivial solution to this non-linear partial differential equation has been proposed. Further, by the Concentration lemma, the concentration of solutions to the same problem defined on the set consisting of those elements where the potential function vanishes as the real parameter approaches to infinity has been addressed.

Keywords: p-Laplacian, p-biharmonic, elliptic PDEs, Concentration lemma, Sobolev space

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Authors: Amanda Rithieli Pereira Dos Santos, Rute Quelvia De Faria, Álvaro De Oliveira Cardoso, Anderson Rodrigo Da Silva, Érica Leão Fernandes Araújo

Abstract:

The study of the kinetics of drying has great importance for the mathematical modeling, allowing to know about the processes of transference of heat and mass between the products and to adjust dryers managing new technologies for these processes. The present work had the objective of studying the kinetics of drying of soybean seeds and adjusting different statistical models to the experimental data varying cultivar and temperature. Soybean seeds were pre-dried in a natural environment in order to reduce and homogenize the water content to the level of 14% (b.s.). Then, drying was carried out in a forced air circulation oven at controlled temperatures of 38, 43, 48, 53 and 58 ± 1 ° C, using two soybean cultivars, BRS 8780 and Sambaíba, until reaching a hygroscopic equilibrium. The experimental design was completely randomized in factorial 5 x 2 (temperature x cultivar) with 3 replicates. To the experimental data were adjusted eleven statistical models used to explain the drying process of agricultural products. Regression analysis was performed using the least squares Gauss-Newton algorithm to estimate the parameters. The degree of adjustment was evaluated from the analysis of the coefficient of determination (R²), the adjusted coefficient of determination (R² Aj.) And the standard error (S.E). The models that best represent the drying kinetics of soybean seeds are those of Midilli and Logarítmico.

Keywords: curve of drying seeds, Glycine max L., moisture ratio, statistical models

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