Search results for: random differential inclusion

Authors: M. Salmanzadeh

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In paper, we will deal with incompressible Couette flow, which represents an exact analytical solution of the Navier-Stokes equations. Couette flow is perhaps the simplest of all viscous flows, while at the same time retaining much of the same physical characteristics of a more complicated boundary-layer flow. The numerical technique that we will employ for the solution of the Couette flow is the Crank-Nicolson implicit method. Parabolic partial differential equations lend themselves to a marching solution; in addition, the use of an implicit technique allows a much larger marching step size than would be the case for an explicit solution. Hence, in the present paper we will have the opportunity to explore some aspects of CFD different from those discussed in the other papers.

Keywords: incompressible couette flow, numerical method, partial differential equation, Crank-Nicolson implicit

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Authors: Benniche Omar

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We are concerned with abstract fully nonlinear differential equations having the form y’(t)=Ay(t)+f(t,y(t)) where A is an m—dissipative operator (possibly multi—valued) defined on a subset D(A) of a Banach space X with values in X and f is a given function defined on I×X with values in X. We consider a graph K in I×X. We recall that K is said to be viable with respect to the above abstract differential equation if for each initial data in K there exists at least one trajectory starting from that initial data and remaining in K at least for a short time. The viability problem has been studied by many authors by using various techniques and frames. If K is closed, it is shown that a tangency condition, which is mainly linked to the dynamic, is crucial for viability. In the case when X is infinite dimensional, compactness and convexity assumptions are needed. In this paper, we are concerned with the notion of near viability for a given graph K with respect to y’(t)=Ay(t)+f(t,y(t)). Roughly speaking, the graph K is said to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)), if for each initial data in K there exists at least one trajectory remaining arbitrary close to K at least for short time. It is interesting to note that the near viability is equivalent to an appropriate tangency condition under mild assumptions on the dynamic. Adding natural convexity and compactness assumptions on the dynamic, we may recover the (exact) viability. Here we investigate near viability for a graph K in I×X with respect to y’(t)=Ay(t)+f(t,y(t)) where A and f are as above. We emphasis that the t—dependence on the perturbation f leads us to introduce a new tangency concept. In the base of a tangency conditions expressed in terms of that tangency concept, we formulate criteria for K to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)). As application, an abstract null—controllability theorem is given.

Keywords: abstract differential equation, graph, tangency condition, viability

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: M. O. Durojaye, J. T. Agee

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This paper is on the one-dimensional, positive temperature coefficient (PTC) thermistor model with a hyperbolic tangent function approximation for the electrical conductivity. The method of asymptotic expansion was adopted to obtain the steady state solution and the unsteady-state response was obtained using the method of lines (MOL) which is a well-established numerical technique. The approach is to reduce the partial differential equation to a vector system of ordinary differential equations and solve numerically. Our analysis shows that the hyperbolic tangent approximation introduced is well suitable for the electrical conductivity. Numerical solutions obtained also exhibit correct physical characteristics of the thermistor and are in good agreement with the exact steady state solutions.

Keywords: electrical conductivity, hyperbolic tangent function, PTC thermistor, method of lines

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Authors: Jian-Jun Shu

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It is common knowledge that many physical problems (such as non-linear shallow-water waves and wave motion in plasmas) can be described by the Korteweg-de Vries (KdV) equation, which possesses certain special solutions, known as solitary waves or solitons. As a marriage of the KdV equation and the classical Burgers (KdVB) equation, the Korteweg-de Vries-Burgers (KdVB) equation is a mathematical model of waves on shallow water surfaces in the presence of viscous dissipation. Asymptotic analysis is a method of describing limiting behavior and is a key tool for exploring the differential equations which arise in the mathematical modeling of real-world phenomena. By using variable transformations, the asymptotic expansion of the KdVB equation is presented in this paper. The asymptotic expansion may provide a good gauge on the validation of the corresponding numerical scheme.

Keywords: asymptotic expansion, differential equation, Korteweg-de Vries-Burgers (KdVB) equation, soliton

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Authors: Joon Ho Kim, Tae Kwon Ha

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Effect of aging treatment on microstructural aspects of interfacial layers of the Cu/Al clad sheet produced by Differential Speed Rolling (DSR) process were studied by Electron Back Scattered Diffraction (EBSD). Clad sheet of Al/Cu has been fabricated by using DSR, which caused severe shear deformation between Al and Cu plate to easily bond to each other. Rolling was carried out at 100°C with speed ratio of 2, in which the total thickness reduction was 45%. Interface layers of clad sheet were analyzed by EBSD after subsequent annealing at 400°C for 30 to 120 min. With increasing annealing time, thickness of interface layer and fraction of high angle grain boundary were increased and average grain size was decreased.

Keywords: aluminium/copper clad sheet, differential speed rolling, interface layer, microstructure, annealing, electron back scattered diffraction

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Authors: Mehravar Javid, James Sexton, S. Taridashti, Joseph Dorer

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Objective: Intimacy is among the most important factors in marital relationships and includes different aspects. Communication skills can enable couples to promote their intimacy. This experimental study was conducted to measure the effectiveness of communication skills using Transactional Analysis (TA) on various dimensions of marital intimacy. Method: The participants in this study were female teachers. Analysis of covariance was recruited in the experimental group (n =15) and control group (n =15) with pre-test and post-test. Random assignment was applied. The experimental group received the Transactional Analysis training program for 9 sessions of 2 hours each week. The instrument was the Marital Intimacy Questionnaire, with 87 items and 9 subscales. Result: The findings suggest that training in Transactional Analysis significantly increased the total score of intimacy except spiritual intimacy on the post-test. Discussion: According to the obtained data, it is concluded that communication skills using Transactional Analysis (TA) training could increase intimacy and improve marital relationships. The study highlights the differential effects on emotional, rational, sexual, and psychological intimacy compared to physical, social/recreational, and relational intimacy over a 9-week period.

Keywords: communication skills, intimacy, marital relationships, transactional analysis

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Authors: B. Frączek

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The paper analyses the usage of the Internet by university students in Visegrad Countries (4V Countries) who study economic fields in their formal and informal financial education and captures the areas of untapped potential of Internet in educational processes. Higher education and training, technological readiness, and the financial market development are in the group of pillars, that are key for efficiency driven economies. These three pillars have become an inspiration to the research on using the Internet in the financial education among economic university students as the group of the best educated people in finance. The financial education is a process that allows for improving the level of financial literacy. In turn, the financial literacy it is the set of financial knowledge, skills, awareness and patterns influencing the financial decisions. The level of financial literacy influences the level of financial well-being of individuals, determines the scale of saving of households and at the same time gives the greater chance for sustainable and more predictable development of the financial market with the positive impact on economy. The financial literacy is necessary for each group of society but its appropriate level is desirable especially in respect of economics students as future participants of financial markets as well as the experts and advisors in financial decision making. The low level of financial literacy is the great problem of many target groups in both developing and developed countries and the financial education is seen as the best way of improving this situation. Also the financial inclusion plays the special role in enhancing the level of financial literacy in the aspect of education by practice as well as due to interrelation between level of financial literacy and degree of financial inclusion. Despite many initiatives under financial education, the level of financial literacy is still very low. Scientists still search for new ways of solving this problem. One of the proposal is more effective usage of the new technology in financial education, especially the Internet, because of the growing popularity of e-learning and the increasing number of Internet users, especially among young people who are called the Generation Net. Due to special role of the university students studying the economics fields for the future financial markets, students of four universities from Visegrad Countries (Czech Republic, Hungary, Poland and Slovakia) were invited to participate in the survey. The aim of the article is to present the level and ways of using the Internet technology in financial education and indicating the so far unused or underused opportunities.

Keywords: financial education, financial inclusion, financial literacy, internet and university education

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Authors: Y. J. Zhou, G. Lu

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In this paper, an analytical study is made for the dynamic behavior of human brain tissue under transient loading. In this analytical model the Mooney-Rivlin constitutive law is coupled with visco-elastic constitutive equations to take into account both the nonlinear and time-dependent mechanical behavior of brain tissue. Five ordinary differential equations representing the relationships of five main parameters (radial stress, circumferential stress, radial strain, circumferential strain, and particle velocity) are obtained by using the characteristic method to transform five partial differential equations (two continuity equations, one motion equation, and two constitutive equations). Analytical expressions of the attenuation properties for spherical wave in brain tissue are analytically derived. Numerical results are obtained based on the five ordinary differential equations. The mechanical responses (particle velocity and stress) of brain are compared at different radii including 5, 6, 10, 15 and 25 mm under four different input conditions. The results illustrate that loading curves types of the particle velocity significantly influences the stress in brain tissue. The understanding of the influence by the input loading cures can be used to reduce the potentially injury to brain under head impact by designing protective structures to control the loading curves types.

Keywords: analytical method, mechanical responses, spherical wave propagation, traumatic brain injury

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Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

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Authors: J. Fryt, K. Pietras, T. Smolen

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Intergenerational similarities in values may be effect of value transmission within families or socio-cultural trends prevailing at a specific point in time. According to salience hypothesis, salient family values may be transmitted more frequently. On the other hand, many value studies reveal that generational shift from social values (conservation and self-transcendence) to more individualistic values (openness to change and self-enhancement) suggest that value transmission and value change are two different processes. The first aim of our study was to describe similarities and differences in values of young women and their parents. The second aim was to determine which value similarities may be due to transmission within families. Ninety seven Polish women aged 19-25 and both their mothers and fathers filled in the Portrait Value Questionaire. Intergenerational similarities in values between women were found in strong preference for benevolence, universalism and self-direction as well as low preference for power. Similarities between younger women and older men were found in strong preference for universalism and hedonism as well as lower preference for security and tradition. Young women differed from older generation in strong preference for stimulation and achievement as well as low preference for conformity. To identify the origin of intergenerational similarities (whether they are the effect of value transmission within families or not), we used the comparison between correlations of values in family dyads (mother-daughter, father-daughter) and distribution of correlations in random intergenerational dyads (random mother-daughter, random father-daughter) as well as peer dyads (random daughter-daughter). Values representing conservation (security, tradition and conformity) as well as benevolence and power were transmitted in families between women. Achievement, power and security were transmitted between fathers and daughters. Similarities in openness to change (self-direction, stimulation and hedonism) and universalism were not stronger within families than in random intergenerational and peer dyads. Taken together, our findings suggest that despite noticeable generation shift from social to more individualistic values, we can observe transmission of parents’ salient values such as security, tradition, benevolence and achievement.

Keywords: value transmission, value change, intergenerational similarities, differences in values

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Authors: Sumara Khursheed, Jitendra Sharma

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The present work reports synthesis of nanocomposites (NCs) of phosphor (KCaVO4:Sm3+) embedded poly(methylmethacrylate) (PMMA) using solution casting method and their optical properties measurements for their possible application in making flexible luminescent films. X-ray diffraction analyses were employed to obtain the structural parameters as crystallinity, shape and size of the obtained NCs. The emission and excitation spectra were obtained using Photoluminescence spectroscopy to quantify the spectral properties of these fluorescent polymer/phosphor films. Optical energy gap has been estimated using UV-VIS spectroscopy while differential scanning calorimetry (DSC) was exploited to measure the thermal properties of the NC films in terms of their thermal stability, glass transition temperature and degree of crystallinity etc.

Keywords: nanocomposites, luminescence, XRD, differential scanning calorimetry, PMMA

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Authors: Sufyan Muhammad

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Recently, in achieving highly efficient but at the same time highly accurate solutions has become the major target of numerical analyst community. The concept is termed as compact schemes and has gained great popularity and consequently, we construct compact schemes for fourth order parabolic differential equations used to study vibrations in structures. For the superiority of newly constructed schemes, we consider range of examples. We have achieved followings i.e. (a) numerical scheme utilizes minimum number of stencil points (which means new scheme is compact); (b) numerical scheme is highly accurate (which means new scheme is reliable) and (c) numerical scheme is highly efficient (which means new scheme is fast).

Keywords: central finite differences, compact schemes, Bernoulli's equations, finite differences

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Authors: Arcady Ponosov, Ramazan Kadiev

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Input-to-State Stability (ISS) is widely used in deterministic control theory but less known in the stochastic case. Roughly speaking, the theory explains when small perturbations of the right-hand sides of the system on the entire semiaxis cause only small changes in the solutions of the system, again on the entire semiaxis. This property is crucial in many applications. In the report, we explain how to define and study ISS for systems of linear stochastic differential equations with or without delays. The central result connects ISS with the property of Lyapunov stability. This relationship is well-known in the deterministic setting, but its stochastic version is new. As an application, a method of studying asymptotic Lyapunov stability for stochastic delay equations is described and justified. Several examples are provided that confirm the efficiency and simplicity of the framework.

Keywords: asymptotic stability, delay equations, operator methods, stochastic perturbations

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: Bharatendra Rai

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Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.

Keywords: degradation signal, drill-bit breakage, random forest, multinomial logistic regression

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Authors: Beata Jackowska-Zduniak

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We formulate and analyze a mathematical model describing dynamics of cancer growth under the influence of radiation therapy. The effect of this type of therapy is considered as an additional equation of discussed model. Numerical simulations show that delay, which is added to ordinary differential equations and represent time needed for transformation from one type of cells to the other one, affects the behavior of the system. The validation and verification of proposed model is based on medical data. Analytical results are illustrated by numerical examples of the model dynamics. The model is able to reconstruct dynamics of treatment of cancer and may be used to determine the most effective treatment regimen based on the study of the behavior of individual treatment protocols.

Keywords: mathematical modeling, numerical simulation, ordinary differential equations, radiation therapy

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Authors: Jiajia Yao, Guanlin Wu, Fang Liu, Junshuai Xue, Yue Hao

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This study reports on the epitaxial growth of a GaN-based resonant tunneling diode (RTD) structure with stable and repeatable double negative differential resistance (NDR) characteristics at room temperature on a c-plane GaN-on-sapphire template using plasma-assisted molecular beam epitaxy (PA-MBE) technology. In this structure, two independent AlN/GaN RTDs are epitaxially connected in series in the vertical growth direction through a silicon-doped GaN layer. As the collector electrode bias voltage increases, the two RTDs respectively align the ground state energy level in the quantum well with the 2DEG energy level in the emitter accumulation well to achieve quantum resonant tunneling and then reach the negative differential resistance (NDR) region. The two NDR regions exhibit similar peak current densities and peak-to-valley current ratios, which are 230 kA/cm² and 249 kA/cm², 1.33 and 1.38, respectively, for a device with a collector electrode mesa diameter of 1 µm. The consistency of the NDR is much higher than the results of on-chip discrete RTD device interconnection, resulting from the smaller chip area, fewer interconnect parasitic parameters, and less process complexity. The methods and results presented in this paper show the brilliant prospects of GaN RTDs in the development of multi-value logic digital circuits.

Keywords: MBE, AlN/GaN, RTDs, double NDR

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Y. A. Yahaya, Ahmad Tijjani Asabe

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This paper focuses on the formulation of 3-step hybrid Adams type method for the solution of first order differential equation (ODE). The methods which was derived on both grid and off grid points using multistep collocation schemes and also evaluated at some points to produced Block Adams type method and Adams moulton method respectively. The method with the highest order was selected to serve as the corrector. The convergence was valid and efficient. The numerical experiments were carried out and reveal that hybrid Adams type methods performed better than the conventional Adams moulton method.

Keywords: adam-moulton type (amt), corrector method, off-grid, block method, convergence analysis

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Authors: Pedro A. Medina-Rios, Marly Yolie Quintana-Daza

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Having the opportunity to communicate in a social, academic and work context is very relevant for any individual and more for a deaf person when oral language is not their natural language, and written language is their second language. Currently, in Colombia, there is not a specialized dictionary for our best knowledge in sign language archiving. Archival is one of the areas that the deaf community has a greater chance of performing. Nourishing new signs in dictionaries for deaf people extends the possibility that they have the appropriate signs to communicate and improve their performance. The aim of this work was to illustrate the importance of designing pedagogical and technological strategies of knowledge management, for the academic inclusion of deaf people through proposals of lexicon in Colombian sign language (LSC) in the area of archival. As a method, the analytical study was used to identify relevant words in the technical area of the archival and its counterpart with the LSC, 30 deaf people, apprentices - students of the Servicio Nacional de Aprendizaje (SENA) in Documentary or Archival Management programs, were evaluated through direct interviews in LSC. For the analysis tools were maintained to evaluate correlation patterns and linguistic methods of visual, gestural analysis and corpus; besides, methods of linear regression were used. Among the results, significant data were found among the variables socioeconomic stratum, academic level, labor location. The need to generate new signals on the subject of the file to improve communication between the deaf person, listener and the sign language interpreter. It is concluded that the generation of new signs to nourish the LSC dictionary in archival subjects is necessary to improve the labor inclusion of deaf people in Colombia.

Keywords: archival, inclusion, deaf, thesaurus

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Authors: Alpana Agarwal, Akhil Sharma

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This work presents a fully differential CMOS amplifier consisting of two self-biased gain boosted inverter stages, that provides an alternative to the power hungry operational amplifier. The self-biasing avoids the use of external biasing circuitry, thus reduces the die area, design efforts, and power consumption. In the present work, regulated cascode technique has been employed for gain boosting. The Miller compensation is also applied to enhance the phase margin. The circuit has been designed and simulated in 1.8 V 0.18 µm CMOS technology. The simulation results show a high DC gain of 100.7 dB, Unity-Gain Bandwidth of 107.8 MHz, and Phase Margin of 66.7^o with a power dissipation of 286 μW and makes it suitable candidate for the high resolution pipelined ADCs.

Keywords: CMOS amplifier, gain boosting, inverter-based amplifier, self-biased inverter

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Authors: Andriy Didenko, Zanin Kavazovic

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Engineering students often have certain difficulties in mastering major theoretical concepts in mathematical courses such as differential equations. Student projects were proposed to motivate students’ learning and can be used as a tool to promote students’ interest in the material. Authors propose a student project that includes the use of Microsoft Excel. This instructional tool is often overlooked by both educators and students. An integral component of the experimental part of such a project is the exploration of an interactive spreadsheet. The aim is to assist engineering students in better understanding of Euler’s method. This method is employed to numerically solve first order differential equations. At first, students are invited to select classic equations from a list presented in a form of a drop-down menu. For each of these equations, students can select and modify certain key parameters and observe the influence of initial condition on the solution. This will give students an insight into the behavior of the method in different configurations as solutions to equations are given in numerical and graphical forms. Further, students could also create their own equations by providing functions of their own choice and a variety of initial conditions. Moreover, they can visualize and explore the impact of the length of the time step on the convergence of a sequence of numerical solutions to the exact solution of the equation. As a final stage of the project, students are encouraged to develop their own spreadsheets for other numerical methods and other types of equations. Such projects promote students’ interest in mathematical applications and further improve their mathematical and programming skills.

Keywords: student project, Euler's method, spreadsheet, engineering education

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Authors: Nursel Koyuncu, Nihal Ata Tutkun

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Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

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Authors: YingWei Tan, XueFeng Ding

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Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: Ladan Maijama’a, Jibril D. Jiya, Ejike C. Anene

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This paper presents Differential Evolution Algorithm (DEA) based Variable Structure Position Control (VSPC) of Laboratory DC servomotor (LDCSM). DEA is employed for the optimal tuning of Variable Structure Control (VSC) parameters for position control of a DC servomotor. The VSC combines the techniques of Sliding Mode Control (SMC) that gives the advantages of small overshoot, improved step response characteristics, faster dynamic response and adaptability to plant parameter variations, suppressed influences of disturbances and uncertainties in system behavior. The results of the simulation responses of the VSC parameters adjustment by DEA were performed in Matlab Version 2010a platform and yield better dynamic performance compared with the untuned VSC designed.

Keywords: differential evolution algorithm, laboratory DC servomotor, sliding mode control, variable structure control

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Authors: Olga V. Kharchenko

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Applicability of a KTA crystal-based laser system with optical parametric oscillators (OPO) generation to lidar sounding of the atmosphere in the spectral range 3–4 µm is studied in this work. A technique based on differential absorption lidar (DIAL) method and differential optical absorption spectroscopy (DOAS) is developed for lidar sounding of trace atmospheric gases (TAG). The DIAL-DOAS technique is tested to estimate its efficiency for lidar sounding of atmospheric trace gases.

Keywords: atmosphere, lidar sounding, DIAL, DOAS, trace gases, nonlinear crystal

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Authors: Motahar Reza, Rajni Chahal, Neha Sharma

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This article addresses the boundary layer flow and heat transfer of Casson fluid over a nonlinearly permeable stretching surface with chemical reaction in the presence of variable magnetic field. The effect of thermal radiation is considered to control the rate of heat transfer at the surface. Using similarity transformations, the governing partial differential equations of this problem are reduced into a set of non-linear ordinary differential equations which are solved by finite difference method. It is observed that the velocity at fixed point decreases with increasing the nonlinear stretching parameter but the temperature increases with nonlinear stretching parameter.

Keywords: boundary layer flow, nonlinear stretching, Casson fluid, heat transfer, radiation

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Authors: Denisa Denglerova, Radim Sip

Abstract:

Academic sources as well as international agreements and national documents define inclusion in terms of several criteria: equal opportunities, fulfilling individual needs, development of human resources, community participation. In order for these criteria to be met, the community must be cohesive. Community cohesion, which is a relatively new concept, is not determined by homogeneity, but by the acceptance of diversity among the community members and utilisation of its positive potential. This brings us to a central category of inclusion - appreciating diversity and using it to a positive effect. However, school diversity is a real phenomenon, which schools need to tackle more and more often. This is also indicated by the number of publications focused on diversity in schools. These sources present recent analyses of using identity as a tool of coping with the demands of a diversified society. The aim of this study is to identify and describe in detail the processes taking place in selected schools, which contribute to their pro-inclusive character. The research is designed around a multiple case study of three pro-inclusive schools. Paradigmatically speaking, the research is rooted in situational epistemology. This is also related to the overall framework of interpretation, for which we are going to use innovative methods of situational analysis. In terms of specific research outcomes this will manifest itself in replacing the idea of “objective theory” by the idea of “detailed cartography of a social world”. The cartographic approach directs both the logic of data collection and the choice of methods of their analysis and interpretation. The research results include detection of the following sensitive concepts: Key persons. All participants can contribute to promoting an inclusion-friendly environment; however, some do so with greater motivation than others. These could include school management, teachers with a strong vision of equality, or school counsellors. They have a significant effect on the transformation of the school, and are themselves deeply convinced that inclusion is necessary. Accordingly, they select suitable co-workers; they also inspire some of the other co-workers to make changes, leading by example. Employees with strongly opposing views gradually leave the school, and new members of staff are introduced to the concept of inclusion and openness from the beginning. Manifestations of school openness in working with diversity on all important levels. By this we mean positive manipulation with diversity both in the relationships between “traditional” school participants (directors, teachers, pupils) and school-parent relationships, or relationships between schools and the broader community, in terms of teaching methods as well as ways how the school culture affects the school environment. Other important detected concepts significantly helping to form a pro-inclusive environment in the school are individual and parallel classes; freedom and responsibility of both pupils and teachers, manifested on the didactic level by tendencies towards an open curriculum; ways of asserting discipline in the school environment.

Keywords: inclusion, diversity, education, sensitive concept, situational analysis

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