Search results for: mathematical competence

Authors: Ebru Dural, M. Zulfu Asık

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Laminated glass is a kind of safety glass, which is made by 'sandwiching' two glass sheets and a polyvinyl butyral (PVB) interlayer in between them. When the glass is broken, the interlayer in between the glass sheets can stick them together. Because of this property, the hazards of sharp projectiles during natural and man-made disasters reduces. They can be widely applied in building, architecture, automotive, transport industries. Laminated glass can easily undergo large displacements even under their own weight. In order to explain their true behavior, they should be analyzed by using large deflection theory to represent nonlinear behavior. In this study, a nonlinear mathematical model is developed for the analysis of laminated glass cylindrical shell which is free in radial directions and restrained in axial directions. The results will be verified by using the results of the experiment, carried out on laminated glass cylindrical shells. The behavior of laminated composite cylindrical shell can be represented by five partial differential equations. Four of the five equations are used to represent axial displacements and radial displacements and the fifth one for the transverse deflection of the unit. Governing partial differential equations are derived by employing variational principles and minimum potential energy concept. Finite difference method is employed to solve the coupled differential equations. First, they are converted into a system of matrix equations and then iterative procedure is employed. Iterative procedure is necessary since equations are coupled. Problems occurred in getting convergent sequence generated by the employed procedure are overcome by employing variable underrelaxation factor. The procedure developed to solve the differential equations provides not only less storage but also less calculation time, which is a substantial advantage in computational mechanics problems.

Keywords: laminated glass, mathematical model, nonlinear behavior, PVB

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Authors: Nina Dziatzko, Christopher Stehr, Franziska Struve

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Intercultural competence as an explicit required skill nearly never appears in job advertisements in international or even global contexts. But especially those who have to deal with different nationalities and cultures in their everyday business need to have several intercultural competencies and further a global mind-set. This way the question arises how potential future global managers can be trained to learn these competencies. In this regard, it might be helpful to see if different types of intercultural trainings have different effects on those skills. This paper outlines lessons learned based on the evaluation of two different intercultural trainings for management students. The main differences between the observed intercultural trainings are the amount of theoretical input in relation to hands-on experiences, the number of trainers as well as the used methods to teach implicit cultural rules. Both groups contain management students with the willingness and perspective to work abroad or to work in international context. The research is carried out with a pre-training-survey and a post-training-survey which consists of questions referring the international context of the students and a self-estimation of 19 identified intercultural and global mind-set skills, such as: cosmopolitanism, empathy, differentiation and adaptability. Whereas there is no clear result which training gets overall a significant higher increase of skills, there is a clear difference between the focus of competencies trained by each of the intercultural trainings. This way this research provides a guideline for both academicals institutions as well as companies for the decision between different types of intercultural trainings, if the to be trained required skills are defined. Therefore the efficiency and the accuracy of fit of the education of future global managers get optimized.

Keywords: global mind-set, intercultural competencies, intercultural training, learning experiences

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Authors: Ekaterina Lukianchenko

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This article sums up a six-year experience of teaching English as a foreign language to over 900 university students at MGIMO (Moscow University of International Relations, Russia), all of them native speakers of Russian aged 16 to 23. By combining modern communicative approach to teaching with cognitive linguistics theories, one can deal more effectively with deeply rooted mistakes which particular students have of which conventional methods have failed to eliminate. If language items are understood as concepts and frames, and classroom activities as meaningful parts of language competence development, this might help to solve such problems as incorrect use of words, unsuitable register, and confused tenses - as well as logical or structural mistakes, and even certain psychological issues concerning essay writing. Along with classic teaching methods, such classroom practice includes plenty of interaction between students - playing special classroom games aimed at eliminating particular mistakes, working in pairs and groups, integrating all skills in one class. The main conclusions that the author of the experiment makes consist in an assumption that academic essay writing classes demand a balanced plan. This should not only include writing as such, but additionally feature elements of listening, reading, speaking activities specifically chosen according to the skills and language students will need to write the particular type of essay.

Keywords: academic essay writing, creative teaching, cognitive linguistics, competency-based approach, communicative language teaching, frame, concept

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Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

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Authors: Orit Zeevy-Solovey

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Grammar has traditionally been taught for its own sake, emphasizing rules and drills. However, in recent years, more emphasis is given to communicative competence. Current research suggests that form-focused instruction is notably efficient when incorporated in a meaningful communicative context. It is maintained that writing tasks related to the students’ academic fields will encourage them to express themselves openly in topics that are close to their hearts, without feeling too uneasy about grammatical forms. The teacher can further reduce students’ apprehension of grammar by announcing that credit will be given for merely doing the task and that grammar mistakes will not affect the grade. Students’ linguistic errors can then be corrected by giving metalinguistic feedback which involves providing learners with some kind of explicit remark about the nature of the errors they have made. Research has also shown that learners’ developmental readiness is an important factor influencing the effectiveness of written corrective feedback. Larger effect sizes appear as the proficiency level is higher. The purposes of this paper are to demonstrate how grammar can be taught indirectly through writing tasks, and more specifically, how the use of metalinguistic written corrective feedback given to advanced English as a Foreign Language (EFL) students can raise their linguistic awareness. Since errors are not directly corrected, the students have to work out the corrections needed through exploring grammar books and websites. Longitudinal studies of metalinguistic written corrective feedback comparing the number of errors in students’ first and fourth compositions have shown a decrease in errors.

Keywords: EFL, linguistic awareness, metalinguistic corrective feedback, teaching grammar through writing

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Authors: Du T. Tran, Quyen T. L. Hoang

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The role of language learning strategies in second language acquisition has received increased attention across several disciplines in recent years. Language learning strategies have been shown to occur in many studies over the passing years with the aim of improving the efficiency of language learning. Following previous studies, this study endeavors to scrutinize language learning strategies employed by the students at Vo Minh Duc high school and the effect of motivation on students’ learning strategy choices. The responses are examined quantitatively and qualitatively to enhance their validity and reliability. Data are collected from 342 students’ responses to the questionnaire, interviews with ten teachers and fifteen students, and classroom observations. The findings reveal that students’ motivation has an enormous impact on the choice of language learning strategies. The results simultaneously show that students use many language learning strategies to enhance their communicative competence, but the most frequently used ones are cognitive and affective ones. Significant correlations among types of learning strategies and the influence of motivation on the choices of language learning strategies were consistent with previous studies. The study’s results are expected to be beneficial to teachers of English and students in terms of narrowing the gap between the students' language learning strategies and their teaching methodologies preferences and sketching out the best strategies to enhance students’ speaking skills. The implications of these findings and the importance of viewing learners holistically are discussed, and recommendations are made for ongoing research.

Keywords: learning strategies, speaking skills, memorization strategies, cognitive strategies, affective strategies

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Authors: Mst Ilme Faridatul, Bo Wu

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Multi-temporal urban land cover mapping is of paramount importance for monitoring urban sprawl and managing the ecological environment. For diversified urban activities, it is challenging to map land covers in a complex urban environment. Spectral indices have proved to be effective for mapping urban land covers. To improve multi-temporal urban land cover classification and mapping, we evaluate the performance of three spectral indices, e.g. modified normalized difference bare-land index (MNDBI), tasseled cap water and vegetation index (TCWVI) and shadow index (ShDI). The MNDBI is developed to evaluate its performance of enhancing urban impervious areas by separating bare lands. A tasseled cap index, TCWVI is developed to evaluate its competence to detect vegetation and water simultaneously. The ShDI is developed to maximize the spectral difference between shadows of skyscrapers and water and enhance water detection. First, this paper presents a comparative analysis of three spectral indices using Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM) and Operational Land Imager (OLI) data. Second, optimized thresholds of the spectral indices are imputed to classify land covers, and finally, their performance of enhancing multi-temporal urban land cover mapping is assessed. The results indicate that the spectral indices are competent to enhance multi-temporal urban land cover mapping and achieves an overall classification accuracy of 93-96%.

Keywords: land cover, mapping, multi-temporal, spectral indices

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Authors: Ragy Raafat Gaber Attaalla

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Despite having the greatest rates of mortality and morbidity in the world, low- and middle-income (LMIC) nations trail high-income nations in terms of the number of clinical trials, the number of qualified researchers, and the amount of research information specific to their people. Health inequities and the use of precision medicine may be hampered by a lack of local genomic data, clinical pharmacology and pharmacometrics competence, and training opportunities. These issues can be solved by carrying out health care infrastructure development, which includes data gathering and well-designed clinical pharmacology training in LMICs. It will be advantageous if there is international cooperation focused at enhancing education and infrastructure and promoting locally motivated clinical trials and research. This paper outlines various instances where clinical pharmacology knowledge could be put to use, including pharmacogenomic opportunities that could lead to better clinical guideline recommendations. Examples of how clinical pharmacology training can be successfully implemented in LMICs are also provided, including clinical pharmacology and pharmacometrics training programmes in Africa and a Tanzanian researcher's personal experience while on a training sabbatical in the United States. These training initiatives will profit from advocacy for clinical pharmacologists' employment prospects and career development pathways, which are gradually becoming acknowledged and established in LMICs. The advancement of training and research infrastructure to increase clinical pharmacologists' knowledge in LMICs would be extremely beneficial because they have a significant role to play in global health.

Keywords: low- and middle-income, clinical pharmacology, pharmacometrics, career development pathways

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Authors: Anna Wendolowska, Dorota Czyzowska

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An intimate relationship is a significant factor that influences romantic partners’ well-being. In the face of stress, avoidant partners often employ a defense-against-intimacy strategy, leading to reduced relationship satisfaction, intimacy, interdependence, and longevity. Dyadic coping can buffer the negative effects of stress on relational satisfaction. Emotional competence mediates the relationship between insecure attachment and intimacy. In the current study, the link between attachment, different forms of dyadic coping, and various aspects of relationship satisfaction was examined. Both partners completed the attachment style questionnaire, the well matching couple questionnaire, and the dyadic coping inventory. The data was analyzed using the actor–partner interdependence model. The results highlighted a negative association between insecure-avoidant attachment style and intimacy. The actor effects of avoidant attachment on relational intimacy for women and for men were significant, whilst the partner effects for both spouses were not significant. The emotion-focused common dyadic coping moderated the relationship between avoidance of attachment and the partner's sense of intimacy. After controlling for the emotion-focused common dyadic coping, the actor effect of attachment on intimacy for men was slightly weaker, and the actor effect for women turned out to be insignificant. The emotion-focused common dyadic coping weakened the negative association between insecure attachment and relational intimacy. The impact of adult attachment and dyadic coping significantly contributes to subjective relational well-being.

Keywords: adult attachment, dyadic coping, relational intimacy, relationship satisfaction

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Authors: Jingcheng Ma, Patricia B. Weisensee, Young H. Shin, Yujin Chang, Junjiao Tian, William P. King, Nenad Miljkovic

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Water droplet impact on surfaces is a ubiquitous phenomenon in both nature and industry. The transfer of mass, momentum and energy can be influenced by the time of contact between droplet and surface. In order to reduce the contact time, we study the influence of substrate motion prior to impact on the dynamics of droplet recoil. Using optical high speed imaging, we investigated the impact dynamics of macroscopic water droplets (~ 2mm) on rigid nanostructured superhydrophobic surfaces vibrating at 60 – 300 Hz and amplitudes of 0 – 3 mm. In addition, we studied the influence of the phase of the substrate at the moment of impact on total contact time. We demonstrate that substrate vibration can alter droplet dynamics, and decrease total contact time by as much as 50% compared to impact on stationary rigid superhydrophobic surfaces. Impact analysis revealed that the vibration frequency mainly affected the maximum contact time, while the amplitude of vibration had little direct effect on the contact time. Through mathematical modeling, we show that the oscillation amplitude influences the possibility density function of droplet impact at a given phase, and thus indirectly influences the average contact time. We also observed more vigorous droplet splashing and breakup during impact at larger amplitudes. Through semi-empirical mathematical modeling, we describe the relationship between contact time and vibration frequency, phase, and amplitude of the substrate. We also show that the maximum acceleration during the impact process is better suited as a threshold parameter for the onset of splashing than a Weber-number criterion. This study not only provides new insights into droplet impact physics on vibrating surfaces, but develops guidelines for the rational design of surfaces to achieve controllable droplet wetting in applications utilizing vibration.

Keywords: contact time, impact dynamics, oscillation, pear-shape droplet

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Authors: Carol Okigbo

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Mathematical problem solving has long been accorded an important place in mathematics curricula at every education level in both advanced and emerging economies. Its classroom approaches have varied, such as teaching for problem-solving, teaching about problem-solving, and teaching mathematics through problem-solving. It requires engaging in tasks for which the solution methods are not eminent, making sense of problems and persevering in solving them by exhibiting processes, strategies, appropriate attitude, and adequate exposure. Teachers play important roles in helping students acquire competency in problem-solving; thus, they are expected to be good problem-solvers and have proper conceptions of problem-solving. Studies show that teachers’ conceptions influence their decisions about what to teach and how to teach. Therefore, how teachers view their roles in teaching problem-solving will depend on their pedagogical conceptions of problem-solving. If teaching problem-solving is a major component of secondary school mathematics instruction, as recommended by researchers and mathematics educators, then it is necessary to establish teachers’ conceptions, what they do, and how they approach problem-solving. This study is designed to determine secondary school teachers’ conceptions regarding mathematical problem solving, its current situation, how teachers’ conceptions relate to their demographics, as well as the interaction patterns in the mathematics classroom. There have been many studies of mathematics problem solving, some of which addressed teachers’ conceptions using single-method approaches, thereby presenting only limited views of this important phenomenon. To address the problem more holistically, this study adopted an integrated mixed methods approach which involved a quantitative survey, qualitative analysis of open-ended responses, and ethnographic observations of teachers in class. Data for the analysis came from a random sample of 327 secondary school mathematics teachers in two Nigerian states - Anambra State and Enugu State who completed a 45-item questionnaire. Ten of the items elicited demographic information, 11 items were open-ended questions, and 25 items were Likert-type questions. Of the 327 teachers who responded to the questionnaires, 37 were randomly selected and observed in their classes. Data analysis using ANOVA, t-tests, chi-square tests, and open coding showed that the teachers had different conceptions about problem-solving, which fall into three main themes: practice on exercises and word application problems, a process of solving mathematical problems, and a way of teaching mathematics. Teachers reported that no period is set aside for problem-solving; typically, teachers solve problems on the board, teach problem-solving strategies, and allow students time to struggle with problems on their own. The result shows a significant difference between male and female teachers’ conception of problems solving, a significant relationship among teachers’ conceptions and academic qualifications, and teachers who have spent ten years or more teaching mathematics were significantly different from the group with seven to nine years of experience in terms of their conceptions of problem-solving.

Keywords: conceptions, education, mathematics, problem solving, teacher

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Authors: Alexandru-Ion Marinescu

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There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

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Authors: Hui-Chieh Li

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Circular economy promotes greater resource productivity and avoids pollution through greater recycling and re-use which bring benefits for both the environment and the economy. The concept is contrast to a linear economy which is ‘take, make, dispose’ model of production. A well-design reverse logistics service strategy could enhance the willingness of recycling of the users and reduce the related logistics cost as well as carbon emissions. Moreover, the recycle brings the manufacturers most advantages as it targets components for closed-loop reuse, essentially converting materials and components from worn-out product into inputs for new ones at right time and right place. This study considers demand-supply interaction, time-dependent recycle demand, time-dependent surplus value of recycled product and constructs models on recycle service strategy for the recyclable waste collector. A crucial factor in optimizing a recycle service strategy is consumer demand. The study considers the relationships between consumer demand towards recycle and product characteristics, surplus value and user behavior. The study proposes a recycle service strategy which differs significantly from the conventional and typical uniform service strategy. Periods with considerable demand and large surplus product value suggest frequent and short service cycle. The study explores how to determine a recycle service strategy for recyclable waste collector in terms of service cycle frequency and duration and vehicle type for all service cycles by considering surplus value of recycled product, time-dependent demand, transportation economies and demand-supply interaction. The recyclable waste collector is responsible for the collection of waste product for the manufacturer. The study also examines the impacts of utilization rate on the cost and profit in the context of different sizes of vehicles. The model applies mathematical programming methods and attempts to maximize the total profit of the distributor during the study period. This study applies the binary logit model, analytical model and mathematical programming methods to the problem. The model specifically explores how to determine a recycle service strategy for the recycler by considering product surplus value, time-dependent recycle demand, transportation economies and demand-supply interaction. The model applies mathematical programming methods and attempts to minimize the total logistics cost of the recycler and maximize the recycle benefits of the manufacturer during the study period. The study relaxes the constant demand assumption and examines how service strategy affects consumer demand towards waste recycling. Results of the study not only help understanding how the user demand for recycle service and product surplus value affects the logistics cost and manufacturer’s benefits, but also provide guidance such as award bonus and carbon emission regulations for the government.

Keywords: circular economy, consumer demand, product surplus value, recycle service strategy

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Authors: Sudhir Kumar Tewatia, Kanishck Tewatia, Anttriksh Tewatia

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Advancements in soil consolidation are discussed, and further improvements are proposed with particular reference to Tewatia’s Y-Y’ Approach, which is called the Settlement versus Rate of Settlement Approach in consolidation. A branch of calculus named Y-Y' (or y versus dy/dx) is suggested (as compared to the common X-Y', x versus dy/dx, dy/dx versus x or Newton-Leibniz branch) that solves some complicated/unsolved theoretical and practical problems in physical sciences (Physics, Chemistry, Mathematics, Biology, and allied sciences) and engineering in an amazingly simple and short manner, particularly when independent variable X is unknown and X-Y' Approach can’t be used. Complicated theoretical and practical problems in 1D, 2D, 3D Primary and Secondary consolidations with non-uniform gradual loading and irregularly shaped clays are solved with elementary school level Y-Y' Approach, and it is interesting to note that in X-Y' Approach, equations become more difficult while we move from one to three dimensions, but in Y-Y' Approach even 2D/3D equations are very simple to derive, solve, and use; rather easier sometimes. This branch of calculus will have a far-reaching impact on understanding and solving the problems in different fields of physical sciences and engineering that were hitherto unsolved or difficult to be solved by normal calculus/numerical/computer methods. Some particular cases from soil consolidation that basically creeps and diffusion equations in isolation and in combination with each other are taken for comparison with heat transfer. The Y-Y’ Approach can similarly be applied in wave equations and other fields wherever normal calculus works or fails. Soil mechanics uses mathematical analogies from other fields of physical sciences and engineering to solve theoretical and practical problems; for example, consolidation theory is a replica of the heat equation from thermodynamics with the addition of the effective stress principle. An attempt is made to give them mathematical analogies.

Keywords: calculus, clay, consolidation, creep, diffusion, heat, settlement

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Authors: Rafat Alwazna

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Translation teaching is a particular activity that includes translators and interpreters training either inside or outside institutionalised settings, such as universities. It can also serve as a means of teaching other fields, such as foreign languages. Translation teaching began in the twentieth century. Teachers of translation hold the responsibilities of educating students, developing their translation competence and training them to be professional translators. The activity of translation teaching involves various tasks, including curriculum design, course delivery, material writing as well as application and implementation. The present paper addresses translation teaching during COVID-19 outbreak, seeking to find out the challenges encountered by translation teachers in online translation teaching and the discoveries/solutions arrived at to resolve them. The paper makes use of a comprehensive questionnaire, containing closed-ended and open-ended questions to elicit both quantitative as well as qualitative data from about sixty translation teachers who have been teaching translation at BA and MA levels during COVID-19 outbreak. The data shows that about 40% of the participants evaluate their online translation teaching experience during COVID-19 outbreak as enjoyable and exhilarating. On the contrary, no participant has evaluated his/her online translation teaching experience as being not good, nor has any participant evaluated his/her online translation teaching experience as being terrible. The data also presents that about 23.33% of the participants evaluate their online translation teaching experience as very good, and the same percentage applies to those who evaluate their online translation teaching experience as good to some extent. Moreover, the data indicates that around 13.33% of the participants evaluate their online translation teaching experience as good. The data also demonstrates that the majority of the participants have encountered obstacles in online translation teaching and have concurrently proposed solutions to resolve them.

Keywords: online translation teaching, electronic learning platform, COVID-19 outbreak, challenges, solutions

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Authors: Prakash Singh, Piet Maphodisa Kgohlo

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Knowledge-worker productivity is one of the biggest leadership challenges facing all organizations in the twenty-first century. It cannot be denied that knowledge-worker productivity affects all organizations. The work and the workforce are both undergoing greater changes currently than at any time, since the beginning of the industrial revolution two centuries ago. Employees welcome collegial teaming (CT) as an innovative way to develop their work-integrated learning competencies. Human resource development policies must evoke the symbiotic relationship between CT and work-integrated learning, seeing that employees need to be endowed with the competence to move from one skill to another, as each one becomes obsolete, and to simultaneously develop their cognitive and emotional intelligence. The outcome of this relationship must culminate in the development of highly productive knowledge-workers. While this study focuses on teachers, the conceptual framework and the findings of this research can be beneficial for any organization, public or private sector, business or non-business. Therefore, in this quantitative study, the benefits of CT are considered in developing human resources to sustain knowledge-worker productivity. The ANOVA p-values reveal that the majority of teachers agree that CT can empower them to overcome the challenges of managing curriculum change. CT can equip them with continuous and sustained learning, growth and improvement, necessary for knowledge-worker productivity. This study, therefore, confirms that CT benefits all workers, immaterial of their age, gender or experience. Hence, this exploratory research provides a new perspective of CT in addressing knowledge-worker productivity when organizational change alters the vision of the organization.

Keywords: collegial teaming, human resource development, knowledge-worker productivity, work-integrated learning

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Authors: B. S.Akhmetov, S. T. Akhmetova, D. N. Nadeyev, V. Yu. Yegorov, V. V. Smogoonov

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Estimated probabilities of errors of the first and second kind for nonideal biometrics-neural transducers 256 outputs, the construction of nomograms based error probability of 'own' and 'alien' from the mathematical expectation and standard deviation of the normalized measures Hamming.

Keywords: modeling, errors, probability, biometrics, neural network, authentication

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Authors: A. Elragig, S. Townley, H. Dreiwi

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In this paper we introduce a bacteria-leukocyte model with bacteria chemotaxsis. We assume that bacteria develop a tactic defense mechanism as a response to Leukocyte phagocytosis. We explore the effect of this tactic motion on Turing space in two parameter spaces. A fine tuning of bacterial chemotaxis shows a significant effect on developing a non-uniform steady state.

Keywords: chemotaxis-diffusion driven instability, bacterial chemotaxis, mathematical biology, ecology

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Authors: Vladimir Isakov, Evgeniy Rykov, Lubov Magerramova, Nikolay Emmaussky

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For the manufacture of critical hollow products, a laser narrow-seam welding scheme based on the supply of a laser beam into the inner cavity has been developed. The report presents the results of comprehensive studies aimed at creating a sealed weld that repeats the geometric shape of the inner cavity using a rotary mirror. Laser welding of hard-to-reach places requires preliminary modeling of the process to identify defect-free modes performed at the highest possible welding speed. Optimization of the technological modes of the welded joint with a ratio of the seam width to its depth equal to 1/5 of the thickness of the Ni superalloy 6.0 mm was performed using the Verhulst limited growth model in a discrete representation. This mathematical model in the form of a recurrence relation made it possible to numerically investigate the entire variety of laser melting modes: chaotic; self-oscillating; stationary and attenuated. The control parameters and the parameter of the order to which other variables of the technological system of laser welding are subordinated are established. In it, the coefficient of relative heat capacity of the melt bath was used as a control parameter, characterizing the competition between the heat input by the laser and the heat sink into the surrounding metal. The parameter of the order of the narrow–seam laser welding process, in this interpretation, is a dimensionless value of the penetration depth, which is an argument of the function of the desired logistic equation. Experimental studies of narrow-seam welding were performed using a copper, water-cooled mirror by radiation from a powerful fiber laser. The obtained results were used to validate the evolutionary mathematical model of the laser welding process.

Keywords: laser welding, internal cavity, limited growth model, ni-superalloy

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Authors: Nir Wittenberg, Moshe Farhi

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This mixed-methods study examines the integration of artificial intelligence (AI) tools in a first-year social work course to assess their potential for enhancing professional knowledge and skills. The incorporation of digital technologies, such as AI, in social work interventions, training, and research has increased, with the expectation that AI will become as commonplace as email and mobile phones. However, policies and ethical guidelines regarding AI, as well as empirical evaluations of its usefulness, are lacking. As AI is gradually being adopted in the field, it is prudent to explore AI thoughtfully in alignment with pedagogical goals. The outcomes assessed include professional identity, course satisfaction, and motivation. AI offers unique reflective learning opportunities through personalized simulations, feedback, and queries to complement face-to-face lessons. For instance, AI simulations provide low-risk practices for situations such as client interactions, enabling students to build skills with less stress. However, it is essential to recognize that AI alone cannot ensure real-world competence or cultural sensitivity. Outcomes related to student learning, experience, and perceptions will help to elucidate the best practices for AI integration, guiding faculty, and advancing pedagogical innovation. This strategic integration of selected AI technologies is expected to diversify course methodology, improve learning outcomes, and generate new evidence on AI’s educational utility. The findings will inform faculty seeking to thoughtfully incorporate AI into teaching and learning.

Keywords: artificial intelligence (AI), social work education, students, developing a professional identity, ethical considerations

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Authors: Sonia Arradaza-Pajaron

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College students are expected to engage in an on-the-job training or internship for completion of a course requirement prior to graduation. In this scenario, they are exposed to the real world of work outside their training institution. To find out their readiness both emotionally and academically, this study has been conducted. A descriptive-correlational research design was employed and random sampling technique method was utilized among 265 randomly selected third year college students of PIT, SY 2014-15. A questionnaire on Emotional Intelligence (bearing the four components namely; emotional literacy, emotional quotient competence, values and beliefs and emotional quotient outcomes) was fielded to the respondents and GWA was extracted from the school automate. Data collected were statistically treated using percentage, weighted mean and Pearson-r for correlation. Results revealed that respondents’ emotional intelligence level is moderately high while their academic performance is good. A high significant relationship was found between the EI component; Emotional Literacy and their academic performance while only significant relationship was found between Emotional Quotient Outcomes and their academic performance. Therefore, if EI influences academic performance significantly when correlated, a possibility that their OJT performance can also be affected either positively or negatively. Thus, EI can be considered predictor of their academic and academic-related performance. Based on the result, it is then recommended that the institution would try to look deeply into the consideration of embedding emotional intelligence as part of the (especially on Emotional Literacy and Emotional Quotient Outcomes of the students) college curriculum. It can be done if the school shall have an effective Emotional Intelligence framework or program manned by qualified and competent teachers, guidance counselors in different colleges in its implementation.

Keywords: academic performance, emotional intelligence, college students, academic success

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Authors: Ming Liu, Zhihui Sun, Xiaoning Zhang

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This paper studies a deterministic container transportation problem, jointly optimizing the berth allocation, quay crane assignment and yard storage allocation at container ports. The problem is formulated as an integer program to coordinate the decisions. Because of the large scale, it is then transformed into a set partitioning formulation, and a framework of branchand- price algorithm is provided to solve it.

Keywords: branch-and-price, container terminal, joint scheduling, maritime logistics

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Authors: Abderrahim Elmoataz

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More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

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Authors: Ahmed Ali Torad

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Background: Breast feeding maintains the maternal fetal immunological link, favours the transmission of immune-competence from the mother to her infant and is considered an important contributory factor to the neo natal immune defense system. Purpose: This study was conducted to investigate the effect of relaxation techniques on immunological properties of breast milk. Subjects and Methods: Thirty breast feeding mothers with a single, mature infant without any complications participated in the study. Subjects will be recruited from outpatient clinic of obstetric department of El Kasr El-Aini university hospital in Cairo. Mothers were randomly divided into two equal groups using coin toss method: Group (A) (relaxation training group) (experimental group): It will be composed of 15 women who received relaxation training program in addition to breast feeding and nutritional advices and Group (B) (control group): It will be composed of 15 women who received breast feeding and nutritional advices only. Results: The results showed that mean mother’s age was 28.4 ± 3.68 and 28.07 ± 4.09 for group A and B respectively, there were statistically significant differences between pre and post values regarding cortisol level, IgA level, leucocyte count and infant’s weight and height and there is only statistically significant differences between both groups regarding post values of all immunological variables (cortisol – IgA – leucocyte count). Conclusion: We could conclude that there is a statistically significant effect of relaxation techniques on immunological properties of breast milk.

Keywords: relaxation, breast, milk, immunology, lactation

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Authors: Pawan Kumar Gupta, Sumana Ghosh

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Parkinson's Disease (PD) is a long-term neurodegenerative movement disorder of the central nervous system with vast symptoms related to the motor system. The common symptoms of PD are tremor, rigidity, bradykinesia/akinesia, and postural instability, but the clinical symptom includes other motor and non‐motor issues. The motor symptoms of the disease are consequence of death of the neurons in a region of the midbrain known as substantia nigra pars compacta, leading to decreased level of a neurotransmitter known as dopamine. The cause of this neuron death is not clearly known but involves formation of Lewy bodies, an abnormal aggregation or clumping of the protein alpha-synuclein in the neurons. Unfortunately, there is no cure for PD, and the management of this disease is challenging. Therefore, it is critical for a patient to be diagnosed at early stages. A limited choice of drugs is available to improve the symptoms, but those become less and less effective over time. Apart from that, with rapid growth in the field of science and technology, other methods such as multi-area brain stimulation are used to treat patients. In order to develop advanced techniques and to support drug development for treating PD patients, an accurate mathematical model is needed to explain the underlying relationship of dopamine secretion in the brain with the hand tremors. There has been a lot of effort in the past few decades on modeling PD tremors and treatment effects from a computational point of view. These models can effectively save time as well as the cost of drug development for the pharmaceutical industry and be helpful for selecting appropriate treatment mechanisms among all possible options. In this review paper, an effort is made to investigate studies on PD modeling and analysis and to highlight some of the key advances in the field over the past centuries with discussion on the current challenges.

Keywords: Parkinson's disease, deep brain stimulation, tremor, modeling

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Authors: Rashid S. Mohammad, Shicheng Zhang, Xinzhe Zhao

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In tight oil reservoirs, wettability alteration has generally been considered as an effective way to remove fracturing fluid retention on the surface of the fracture and consequently improved oil production. However, there is a lack of a reliable productivity prediction model to show the relationship between the wettability and oil production in tight oil well. In this paper, a new oil productivity prediction model of immiscible oil-water flow and miscible CO₂-oil flow accounting for wettability is developed. This mathematical model is established by considering two different length scales: nonporous network and propped fractures. CO₂ flow diffuses in the nonporous network and high velocity non-Darcy flow in propped fractures are considered by taking into account the effect of wettability alteration on capillary pressure and relative permeability. A laboratory experiment is also conducted here to validate this model. Laboratory experiments have been designed to compare the water saturation profiles for different contact angle, revealing the fluid retention in rock pores that affects capillary force and relative permeability. Four kinds of brines with different concentrations are selected here to create different contact angles. In water-wet porous media, as the system becomes more oil-wet, water saturation decreases. As a result, oil relative permeability increases. On the other hand, capillary pressure which is the resistance for the oil flow increases as well. The oil production change due to wettability alteration is the result of the comprehensive changes of oil relative permeability and capillary pressure. The results indicate that wettability is a key factor for fracturing fluid retention removal and oil enhancement in tight reservoirs. By incorporating laboratory test into a mathematical model, this work shows the relationship between wettability and oil production is not a simple linear pattern but a parabolic one. Additionally, it can be used for a better understanding of optimization design of fracturing fluids.

Keywords: wettability, relative permeability, fluid retention, oil production, unconventional and tight reservoirs

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Authors: N. Gharbi

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Constraint Satisfaction problems are mathematical problems that are often used to model many real-world problems for which we look if there exists a solution satisfying all its constraints. Table constraints are important for modeling parts of many problems since they list all combinations of allowed or forbidden values. However, they admit practical limitations because they are sometimes too large to be represented in a direct way. In this paper, we present a survey of the different categories of the proposed approaches to compress table constraints in order to reduce both space and time complexities.

Keywords: constraint programming, compression, data mining, table constraints

Procedia PDF Downloads 326

Authors: Mansour Mohammadpour

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Data transformation refers to the modification of any point in a data set by a mathematical function. When applying transformations, the measurement scale of the data is modified. Data transformations are commonly employed to turn data into the appropriate form, which can serve various functions in the quantitative analysis of the data. This study addresses the investigation of the use of data transformations in Data Envelopment Analysis (DEA). Although data transformations are important options for analysis, they do fundamentally alter the nature of the variable, making the interpretation of the results somewhat more complex.

Keywords: data transformation, data envelopment analysis, undesirable data, negative data

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Authors: Benjamin Castillo, Luis Pastenes, Fernando Cordova

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The pathogen growth in animal source foods is a common problem in the food industry, causing monetary losses due to the spoiling of products or food intoxication outbreaks in the community. In this sense, the quality of the product is reflected by the population of deteriorating agents present in it, which are mainly bacteria. The factors which are likely associated with freshness in animal source foods are temperature and processing, storage, and transport times. However, the level of deterioration of products depends, in turn, on the characteristics of the bacterial population, causing the decomposition or spoiling, such as pH level and toxins. Knowing the growth dynamics of the agents that are involved in product contamination allows the monitoring for more efficient processing. This means better quality and reasonable costs, along with a better estimation of necessary time and temperature intervals for transport and storage in order to preserve product quality. The objective of this project is to design a secondary model that allows measuring the impact on temperature bacterial growth and the competition for pH adequacy and release of bacteriocins in order to describe such phenomenon and, thus, estimate food product half-life with the least possible risk of deterioration or spoiling. In order to achieve this objective, the authors propose an analysis of a three-dimensional ordinary differential which includes; logistic bacterial growth extended by the inhibitory action of bacteriocins including the effect of the medium pH; change in the medium pH levels through an adaptation of the Luedeking-Piret kinetic model; Bacteriocin concentration modeled similarly to pH levels. These three dimensions are being influenced by the temperature at all times. Then, this differential system is expanded, taking into consideration the variable temperature and the concentration of pulsed bacteriocins, which represent characteristics inherent of the modeling, such as transport and storage, as well as the incorporation of substances that inhibit bacterial growth. The main results lead to the fact that temperature changes in an early stage of transport increased the bacterial population significantly more than if it had increased during the final stage. On the other hand, the incorporation of bacteriocins, as in other investigations, proved to be efficient in the short and medium-term since, although the population of bacteria decreased, once the bacteriocins were depleted or degraded over time, the bacteria eventually returned to their regular growth rate. The efficacy of the bacteriocins at low temperatures decreased slightly, which equates with the fact that their natural degradation rate also decreased. In summary, the implementation of the mathematical model allowed the simulation of a set of possible bacteria present in animal based products, along with their properties, in various transport and storage situations, which led us to state that for inhibiting bacterial growth, the optimum is complementary low constant temperatures and the initial use of bacteriocins.

Keywords: bacterial growth, bacteriocins, mathematical modelling, temperature

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Authors: H. Ghodbane, A. A. Taleb, O. Kraa

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This paper presents geometric design of induction heating system. The objective of this design is to improve the temperature distribution in the load. The study of such a device requires the use of models or modeling representation, physical, mathematical, and numerical. This modeling is the basis of the understanding, the design, and optimization of these systems. The optimization technique is to find values of variables that maximize or minimize the objective function.

Keywords: optimization, modeling, geometric design system, temperature increase

Procedia PDF Downloads 530