Oscar Camacho, Sebastian Vega, Marco Herrera
et al.
This paper proposes a novel control strategy for chemical processes by integrating fractional-order PID (FOPID) controllers with sliding mode control (SMC). Through the use of the enhanced flexibility and superior tuning capabilities of FOPID controllers over traditional PID schemes, the method replaces the classical discontinuous switching mechanism of SMC with a smooth fractional-order control action. The proposed hybrid approach is evaluated through simulations in two nonlinear systems, a mixing tank with variable time delay and a pH neutralization process, and experimentally validated using the TCLab device. Throughout three case studies, the method demonstrates improvements in performance and response between 40% and 10% compared to the other two SMC alternatives. Furthermore, the approach effectively reduces chattering, improves convergence speed, and improves robustness to measurement noise, contributing to extended actuator lifespan. This makes the proposed methodology particularly attractive for chemical process applications, offering a practical and accessible solution for plant operators by enabling the utilization of robust control techniques without requiring deep expertise in nonlinear control design.
This study addresses gaps in vocational trigonometry learning by integrating ethnomathematics and Tri-N pedagogy into an Android-based module to enhance mathematical literacy and engagement. Research and Development (R&D) with a 4D model (Define, Design, Develop, Disseminate) was applied. Data were collected from expert validation sheets and student response questionnaires, and analyzed using descriptive and quantitative methods. The module achieved high validity (85.6%) and strong student acceptance (82.22%), indicating practicality and suitability for classroom use. The integration of Tri-N stages with ethnomathematical contexts and mobile technology supports active learning and cultural relevance, contributing theoretically to contextual mathematics education and practically to digital learning innovations. The developed module is valid and practical for vocational trigonometry instruction. Future research should explore scalability and effectiveness through broader trials.
Keywords: Ethnomathematics, Tri-N Model, Android-Based Module, Vocational Education, Trigonometry
Ram M. Narayanan, Benjamin D. Simone, Daniel K. Watson
et al.
This study investigates the use of a custom-built 10 GHz continuous wave micro-Doppler radar system to analyze external vibrations of idling vehicles under various conditions. Scenarios included different gear engagements with one occupant and parked gear with up to four occupants. Motivated by security concerns, such as the threat posed by idling vehicles with multiple occupants, the research explores how micro-Doppler signatures can indicate vehicle readiness to move. Experiments focused on a mid-size SUV, with similar trends seen in other vehicles. Radar data were compared to in situ accelerometer measurements, confirming that the radar system can detect subtle frequency changes, especially during gear shifts. The system’s sensitivity enables it to distinguish variations tied to gear state and passenger load. Extracted features like frequency and magnitude show strong potential for use in machine learning models, offering a non-invasive, remote sensing method for reliably identifying vehicle operational states and occupancy levels in security or monitoring contexts. Spectrogram and PSD analyses reveal consistent tonal vibrations around 30 Hz, tied to engine activity, with harmonics at 60 Hz and 90 Hz. Gear shifts produce impulse signatures primarily below 20 Hz, and transient data show distinct peaks at 50, 80, and 100 Hz. Key features at 23 Hz and 45 Hz effectively indicate engine and gear states. Radar and accelerometer data align well, supporting the potential for remote sensing and machine learning-based classification.
Peristaltic flow in an annular region bounded by a concentric cylindrical tube is considered. The current study focuses on understanding enhancement of heat transfer in presence of nanoparticles. It also studies the effect of peristaltic motion on enhancement of heat transfer. The outer tube is subjected to a sinusoidal wave, and inner tube is rigid. Nanofluid has a variable viscosity which depends on temperature. Analytical solutions for temperature, velocity, and pressure gradient are evaluated and the effect of carbon nanotube is represented graphically. A method of regular perturbation is adopted to get an analytical solution. The impact of having single-walled carbon nanotubes (SNT) and multi-walled carbon nanotubes (MNT) on the parameters like pressure gradient, temperature, and velocity. Long wavelength approximation is assumed on a low Reynold’s flow. The impact of inner tube radius, amplitude of sinusoidal wave, and rate of flow on pressure gradient are analyzed for both SNT and MNT.
Kottakkaran Sooppy Nisar, Kalimuthu Kaliraj, Mohan Manjula
et al.
The impulsive fractional differential equation of the Sobolev type, including deviating arguments, is the subject of the study. The analytic semigroup and fixed point approaches serve the purpose of determining the existence of the approximations. The fractional power of a closed linear operator concept is used to show how the approximation converges. To arrive at a unique approach, an approximation strategy is used. Our main conclusions are defined using an example.
Nesta pesquisa é trilhado um caminho em busca de compreensões sobre o funcionamento do Ensino Médio em vigor a partir da Lei nº 13.415/2017. Objetiva-se responder: como as mudanças no Ensino Médio que são propostas nos documentos curriculares estão sendo desenvolvidas pelos professores e compreendidas pelos coordenadores pedagógicos da área de Ciências da Natureza e suas Tecnologias (CNT) das escolas de Ensino Médio da Rede Básica de Ensino do RS pertencentes à 14ª Coordenadoria Regional de Educação do Rio Grande do Sul (CRERS)? O corpus de análise é composto pelos dados obtidos através de respostas a um questionário semiestruturado, que foi disponibilizado na plataforma Google Forms a professores da área de Ciências da Natureza e suas Tecnologias e coordenadores que trabalham em escolas estaduais da 14ª CRERS. Sendo a Análise Textual Discursiva a metodologia de análise, que resultou em duas categorias: necessidades junto às mudanças no Ensino Médio e planejamento e desenvolvimento de atividades na área da CNT, as quais serão discutidas ao longo deste trabalho. Percebe-se que os olhares tanto do professor quanto do coordenador não destoam, mas demonstram as mesmas dúvidas diante das mudanças propostas. Mesmo que alguns tenham deixado claro que veem a importância destas mudanças, não as compreendem no todo. Sobre os estudantes, são discutidos apontamentos e respostas que mostram a diferença entre o protagonismo que lhes foi prometido e evidências de um processo antidemocrático.
Special aspects of education, Applied mathematics. Quantitative methods
In this paper, asymptotic formulae for solutions and Green's function of a boundary value problem are investigated when the equation and the boundary conditions contain a spectral parameter.
Whereas the extent of outbreak of COVID-19 is usually accessed via the number of reported cases and the number of patients succumbed to the disease, the officially recorded overall excess mortality numbers during the pandemic waves, which are significant and often followed the rise and fall of the pandemic waves, put a question mark on the above methodology. Gradually it has been recognized that estimating the size of the undiagnosed population (which includes asymptomatic cases and symptomatic cases but not reported) is also crucial. Here we used the classical mathematical SEIR model having an additional compartment, that is the undiagnosed group in addition to the susceptible, exposed, diagnosed, recovered and deceased groups, to link the undiagnosed COVID-19 cases to the reported excess mortality numbers and thereby try to know the actual size of the disease outbreak. The developed model wase successfully applied to relevant COVID-19 waves in USA (initial months of 2020), South Africa (mid of 2021) and Russia (2020–21) when a large discrepancy between the reported COVID-19 mortality and the overall excess mortality had been noticed.
We propose two enhancements of quasi-Newton methods used to accelerate coupling iterations for partitioned fluid-structure interaction. Quasi-Newton methods have been established as flexible, yet robust, efficient and accurate coupling methods of multi-physics simulations in general. The coupling library preCICE provides several variants, the so-called IQN-ILS method being the most commonly used. It uses input and output differences of the coupled solvers collected in previous iterations and time steps to approximate Newton iterations. To make quasi-Newton methods both applicable for parallel coupling (where these differences contain data from different physical fields) and to provide a robust approach for re-using information, a combination of information filtering and scaling for the different physical fields is typically required. This leads to good convergence, but increases the cost per iteration. We propose two new approaches—pre-scaling weight monitoring and a new, so-called QR3 filter, to substantially improve runtime while not affecting convergence quality. We evaluate these for a variety of fluid-structure interaction examples. Results show that we achieve drastic speedups for the pure quasi-Newton update steps. In the future, we intend to apply the methods also to volume-coupled scenarios, where these gains can be decisive for the feasibility of the coupling approach.
Evangelos Georganas, Dhiraj Kalamkar, Sasikanth Avancha
et al.
During the past decade, novel Deep Learning (DL) algorithms, workloads and hardware have been developed to tackle a wide range of problems. Despite the advances in workload and hardware ecosystems, the programming methodology of DL systems is stagnant. DL workloads leverage either highly-optimized, yet platform-specific and inflexible kernels from DL libraries, or in the case of novel operators, reference implementations are built via DL framework primitives with underwhelming performance. This work introduces the Tensor Processing Primitives (TPP), a programming abstraction striving for efficient, portable implementation of DL workloads with high-productivity. TPPs define a compact, yet versatile set of 2D-tensor operators [or a virtual Tensor Instruction Set Architecture (ISA)], which subsequently can be utilized as building-blocks to construct complex operators on high-dimensional tensors. The TPP specification is platform-agnostic, thus, code expressed via TPPs is portable, whereas the TPP implementation is highly-optimized and platform-specific. We demonstrate the efficacy and viability of our approach using standalone kernels and end-to-end DL & High Performance Computing (HPC) workloads expressed entirely via TPPs that outperform state-of-the-art implementations on multiple platforms.
Taye Faniran, Aatif Ali, Matthew O. Adewole
et al.
Tuberculosis (TB) is an ailment caused by Mycobacterium tuberculosis. So, by the continuous spread of TB, this study presents a new mathematical model of TB that investigates the impact of smoking and contact rate on the transmission dynamics of the disease in a population. The basic reproduction number R0, of the model, is computed by employing the next generation matrix approach and the dynamical behavior of the model is explored in detail. Mathematical analysis reveals that the disease-free equilibrium solution is globally asymptotically stable when the associated basic reproduction number is less than unity. It is further shown that the model has a unique endemic equilibrium point, which is proved to exist when R0>1. The global asymptotic stability of the unique endemic equilibrium, when the associated basic reproduction number exceeds unity, is investigated through numerical simulations. Sensitivity analysis is carried out to identify key parameters that have the greatest influence on the transmission dynamics of TB in the population. The sensitivity results show that the top four parameters of the model, that have the most influence on R0of the model are the recruitment rate of smokers into the population, contact rate, progression rate to latent TB stage, and recovery rate of infectious individuals, with other key parameters influencing the outcome of the other output responses. Numerical experiments are performed to support the analytical findings. Numerical simulation of the model shows that, if the contact rate α=0.001, then R0is estimated to be 0.4611, which shows that TB dies out of the population. It further shows that, if the contact rate α=0.005, R0is estimated to be 2.3058, which indicates that TB establishes itself in the population. We observed from the above results that the smoking habit should be discouraged in society to reduce the prevalence of TB in the population.
Maíra Batistoni e Silva, Karolina Martins Almeida e Silva, Leila Cristina Aoyama Barbosa Souza
O uso de Questões Sociocientíficas (QSC) na educação em ciências tem aumentado nesta última década; entretanto aspectos pedagógicos, curriculares e do âmbito da formação de professores ainda tornam esta implantação um desafio. Neste trabalho analisamos propostas didáticas com o uso de QSC apresentadas nas sete edições do Encontro Nacional de Ensino de Biologia (2012-2018) para: i) caracterizar a relação conceitual entre QSC e Ciência, Tecnologia, Sociedade e Ambiente (CTSA) estabelecida nos trabalhos; ii) localizar as propostas didáticas nas diferentes correntes da Educação CTSA, e iii) caracterizar as dimensões conceituais das QSC abordadas. Por meio de análise de conteúdo do corpus selecionado, evidenciamos que a natureza das relações entre QSC e CTSA identificada é diversa e revela: i) indefinição do conceito de QSC no contexto de ensino; ii) que os objetivos educacionais se vincularam às correntes da Educação CTSA que pouco consideram aspectos éticos, morais e o engajamento dos estudantes em ações sociopolíticas; com isso iii) a relação entre ciência e tecnologia foi a única dimensão contemplada no conjunto das propostas. Por fim, apontamos aproximações e divergências entre a produção acadêmica e o planejamento didático com o uso de QSC e discutimos a necessidade de aprofundamento dos referenciais teóricos da área nas pesquisas e nos estudos que abordam QSC para contribuir com a construção adequada desse conceito e com a formação de professores no âmbito do ensino de biologia.
Special aspects of education, Applied mathematics. Quantitative methods
Abstract There has been an increasing interest in analyzing the structure of domestic and global supply chains/networks in the past decade. Concerns about potential (systemic) risks resulting from overdependence on global supply networks have been magnified during the lockdowns triggered by the COVID-19 pandemic in the last year. Strengthening local and/or domestic networks may be an adequate approach to overcome the severe economic implications of this overdependence, but it also rises the question of how one can measure the strength of domestic supply/production networks and design an appropriate structure. The objective of this paper is to propose a method for measurement and to provide a first-cut analysis with this method on a sample of economies. Building on ecological network analysis, we borrow the Finn cycling index from its toolbox and show a ranking of countries with respect to the strength of their domestic production networks based on this index. The results suggest that the countries are very heterogeneous both in terms of the level of cycling index and its sectoral decomposition. Using panel-econometric techniques, we point out the role of the openness and structural asymmetry in shaping this strength, also controlling for other macroeconomic characteristics of the economies. The estimates reveal that openness has a negative, while asymmetry has a positive effect on this index, but other country-specific characteristics also play a role in shaping the systemic operation of national economies as measured by the Finn cycling index.
Research of travel distance on single - depot position in warehouse is tremendous. This study focuses more on the effect of two-depot position on travel distance in order picking problem (OPP) by using the concept of traveling salesman problem (TSP) and exact method – Branch and Bound (B\&B) algorithm. The total distance of one-depot position is shorter than two-depot position for single and double block warehouses and the difference is less than 5%. The total distance is also compared with approximate methods – SA and TS which show that the differences are less than 5%. The sequence of location visit for one depot and two depot is similar about two third from the total location visits. For order picking problem that has more than 25 location visits, one need to consider to apply approximate approach to get the solution faster even the difference will be higher from exact approach when the number of location visit or aisle increases.
Sherif A. Zaid, Hani Albalawi, Khaled S. Alatawi
et al.
The electric vehicle (EV) is one of the most important and common parts of modern life. Recently, EVs have undergone a big development thanks to the advantages of high efficiency, negligible pollution, low maintenance, and low noise. Charging stations are very important and mandatory services for electric vehicles. Nevertheless, they cause high stress on the electric utility grid. Therefore, renewable energy-sourced charging stations have been introduced. They improve the environmental issues of the electric vehicles and support remote area operation. This paper proposes the application of fuzzy control to an isolated charging station supplied by photovoltaic power. The system is modeled and simulated using Matlab/Simulink. The simulation results indicate that the disturbances in the solar insolation do not affect the electric vehicle charging process at all. Moreover, the controller perfectly manages the stored energy to compensate for the solar energy variations. Additionally, the system response with the fuzzy controller is compared to that with the PI controller. The comparison shows that the fuzzy controller provides an improved response.
Principal component analysis (PCA) has been a powerful tool for high-dimensional data analysis. It is usually redesigned to the incremental PCA algorithm for processing streaming data. In this paper, we propose a subspace type incremental two-dimensional PCA algorithm (SI2DPCA) derived from an incremental updating of the eigenspace to compute several principal eigenvectors at the same time for the online feature extraction. The algorithm overcomes the problem that the approximate eigenvectors extracted from the traditional incremental two-dimensional PCA algorithm (I2DPCA) are not mutually orthogonal, and it presents more efficiently. In numerical experiments, we compare the proposed SI2DPCA with the traditional I2DPCA in terms of the accuracy of computed approximations, orthogonality errors, and execution time based on widely used datasets, such as FERET, Yale, ORL, and so on, to confirm the superiority of SI2DPCA.
More than eighty percent of pancreatic cancer involves ductal adenocarcinoma with an abundant desmoplastic extracellular matrix surrounding the solid tumor entity. This aberrant tumor microenvironment facilitates a strong resistance of pancreatic cancer to medication. Although various therapeutic strategies have been reported to be effective in mice with pancreatic cancer, they still need to be tested quantitatively in wider animal-based experiments before being applied as therapies. To aid the design of experiments, we develop a cell-based mathematical model to describe cancer progression under therapy with a specific application to pancreatic cancer. The displacement of cells is simulated by solving a large system of stochastic differential equations with the Euler–Maruyama method. We consider treatment with the PEGylated drug PEGPH20 that breaks down hyaluronan in desmoplastic stroma followed by administration of the chemotherapy drug gemcitabine to inhibit the proliferation of cancer cells. Modeling the effects of PEGPH20 + gemcitabine concentrations is based on Green’s fundamental solutions of the reaction–diffusion equation. Moreover, Monte Carlo simulations are performed to quantitatively investigate uncertainties in the input parameters as well as predictions for the likelihood of success of cancer therapy. Our simplified model is able to simulate cancer progression and evaluate treatments to inhibit the progression of cancer.