Linear Process Research Articles

Nonlinear optimal control for robotic exoskeletons with electropneumatic actuators

Nonlinear optimal control for robotic exoskeletons with electropneumatic actuators

Reaction mechanism, hygroscopic behavior, and properties of aluminum phosphate adhesive

The lack of basic research is a principal reason restricting the widespread application of aluminum phosphate adhesive, such as its reaction mechanism is not yet clear. Herein, we investigate the dissolution behavior of aluminum oxide (Al2O3) in acid aluminum phosphate (AAP) solution and the effects of Al2O3 addition, calcination temperature and phosphorus to aluminum (P/Al) ratio of the AAP solution on the thermal evolution, phase development and hygroscopic behavior of aluminum phosphate adhesive. The dissolution process of Al2O3 in AAP solution is controlled by external diffusion. The thermal evolution of aluminum phosphate adhesives is a complex process that is a function of Al2O3 addition and calcination temperature. Although it is a linear process, many of the reactions are largely coupled and occur simultaneously. The hygroscopic mechanism of aluminum phosphate adhesives is associated to the hydrophilicity of the hydroxyl groups (P–OH). Increasing the calcination temperature and the Al2O3 addition can improve the hygroscopicity resistance properties. Finally, the mechanical and dielectric properties of the quartz fiber cloth reinforced aluminum phosphate matrix composites (SiO2f/aluminum phosphate composites) were also investigated. The results demonstrate that the composites have the characteristics of light weight, high strength, and excellent dielectric properties, suggesting that they have attractive applications in radome materials.

Fundamental of Design Thinking and its Phases

Abstract: The practice of solving issues by putting the requirements of the customer first is known as "design thinking." Its foundation lies in the compassionate observation of people's interactions with their surroundings and the use of an experiential, iterative process to generate creative solutions. The "human-centered" nature of design thinking refers to the utilization of data showing how customers interact with a good or service, as opposed to how a company or other party anticipates such interactions. A product or service must be continuously improved by designers seeing how users interact with it in order to be really human-centered. In design thinking, this is the "iterative" phase. In place of incessant study or ruminating, it encourages moving fast to test prototypes. Unlike traditional problem solving, which is a linear process of identifying a problem and then finding solutions, design thinking only works if it is iterative. It's less of a way to arrive at a single solution, and more of a way to continually evolve your way of thinking and respond to consumer needs.

The weighted sum of powers in mean for estimating a change point in linear processes with random coefficients

The weighted sum of powers in mean for estimating a change point in linear processes with random coefficients

Opto-mechatronic dynamic characteristics in iron oxide-based nanofluid using spatial and frequency domain analysis

Iron oxide nanoparticles (IONPs) exhibit low toxicity and high chemical stability, attractive for developing of nanofluids (NFs) for advanced medical applications. This research focuses on the study of the optical, mechanical, and electrical dynamics of iron oxide–ethanol NFs. A novel sensitive methodology for analyzing the influence of nanoparticles (NPs) over the optical and electrical processes exhibited by IONFs is reported. The IONPs were synthesized by a microemulsion route and were characterized by transmission electron microscopy, scanning electron microscopy, and X-ray diffraction. The NPs exhibit a mean diameter of 30 nm and they were identified as Fe2O3. UV–Vis spectroscopy allows us determining the volume fraction of the fluid as a function of time. The assistance of a Michelson interferometer integrated with an image processing methodology was employed to explore the dynamics of the nanostructures. The percentage of NPs involved in linear and nonlinear dynamic fluid processes was estimated by taking a double-stage (spatial and frequency domains) Fast Fourier Transform in the interferometric pattern. A DC voltage source was used to study the electrical conductivity of the NF as it was being sedimented. The opto-mechatronic parameters were correlated, considering the volume fraction as the main variable to determine the optical and electrical characteristics. For the Fe2O3 NF, it is identified that the linear effects of sedimentation present a stronger impact on the optical properties, while the nonlinear interactions have more influence on the electrical conductivity. The main findings of this research have potential applications in rheological instrumentation to analyze complex effects using transient opto-mechatronic components.

Koopman operator-based multi-model for predictive control

AbstractThis work describes a new model structure developed for prediction in Model Predictive Control (MPC). The model has a multi-model structure in which independent sub-models are employed for the consecutive sampling instants. The model lifts process states into a high-dimensional space in which a linear process description is applied. Depending on the influence of the manipulated variables on lifted states, three general model versions are described and model identification algorithms are derived. As a result of the multi-model structure, model parameters are found analytically from computationally uncomplicated least squares problems using the Extended Dynamic Mode Decomposition algorithm, but the evolution of states over the horizon used in MPC is taken into account. Next, the MPC algorithm for the described model is derived. It requires solving online simple quadratic optimisation tasks. The effectiveness of three considered model configurations and three versions of the lifting functions is examined for a nonlinear DC motor benchmark. Their impact on model accuracy, complexity, possible control accuracy and MPC calculation time is thoroughly discussed. Finally, a more complex polymerisation reactor process is considered to showcase the practical applicability of the presented approach to modelling and MPC.

Opening up the narrow

It is vital to engage with professional learning and development (PLD) to be a teacher in Aotearoa New Zealand. In the way it has been enacted due to education policy, PLD has essentially become synonymous with teacher inquiry: to engage with PLD is to follow an inquiry cycle. Literature into what constitutes effective teacher PLD similarly endorses an inquiry approach. But teacher inquiry as interpreted by Ministry of Education neoliberal-influenced policy and procedures risks becoming a linear process abstracted away from the context and complexity of schools and teaching. Neoliberal influences on education policy have similarly supported input-output assumptions of PLD and have led to a narrowing effect. However, it is possible to open PLD up to be creative and subversive. If policy and procedure were to be decoupled, introducing greater flexibility, and refocused on the principles that underpin effective teacher PLD, then this creativity and transformation could be realised.

Analysis of remaining useful life of slope based on nonlinear wiener process

A remaining useful life (RUL) prediction model based on the nonlinear Wiener process is proposed to better tackle the life evaluation problem in the slope degradation process. Taking the displacement of the slope as its performance degradation index, and the nonlinear Wiener process is used to establish the RUL prediction model of the slope. For this model, the least squares method (LSM) is used to estimate the drift coefficients, the maximum likelihood estimation method (MLEM) is used to estimate the diffusion parameters, and then the probability density function (PDF) of the RUL of the slope is deduced and the RUL is predicted. The proposed model is verified by slope engineering examples. The results demonstrated that the RUL of the degradation model based on the nonlinear Wiener process has a greater prediction accuracy than the linear Wiener process. Because the various nonlinear functions have varying slope adaptations, and it can predict the RUL of a slope more accurately, which can provide more reliable preventive maintenance decisions.

Association between Oral Health and Depressive Symptoms in Chinese Older Adults: The Mediating Role of Dietary Diversity.

Diet is a modifiable factor in healthy population aging. Additionally, oral health and diet are important factors affecting depressive symptoms. To assess the mediating role of dietary diversity (DD) in oral health and depressive symptoms in older adults, we selected 8442 participants aged ≥ 65 years from the 2018 Chinese Longitudinal Health Longevity Survey (CLHLS) for a cross-sectional study. Depressive symptoms were determined based on scores on the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10). Dietary diversity scores (DDS) were established based on the frequency of intake of food groups. Oral health was measured by denture use and toothbrushing frequency. Stepwise multiple linear regression and PROCESS macros were used for mediated effects analysis and testing. The sample had a positive detection rate of 44.1% for depressive symptoms, 40.8% for denture use, and 41.9% for once-a-day toothbrushing. Denture use (ρ = -0.077, p < 0.01) and toothbrushing frequency (ρ = -0.115, p < 0.01) were negative predictors of depressive symptoms in older adults. DD significantly mediated the association between denture use (indirect effect -0.047; 95%CI: -0.068-0.028; p < 0.001), toothbrushing frequency (indirect effect -0.041; 95%CI: -0.054-0.030; p < 0.001), and depressive symptoms. Denture use and toothbrushing frequency not only directly reduce the risk of depressive symptoms in older adults, but also indirectly affect depressive symptoms through DD.

Numerical modelling of impact seismic sources using the stress glut theory

SUMMARY Meteorite impacts have proved to be a significant source of seismic signal on the Moon, and have now been recorded on Mars by InSight seismometers. Understanding how impacts produce seismic signal is key to the interpretation of this unique data, and to improve their identification in continuous seismic records. Here, we use the seismic Representation Theorem, and particularly the stress glut theory, to model the seismic motion resulting from impact cratering. The source is described by equivalent forces, some resulting from the impactor momentum transfer, and others from the stress glut, which represents the mechanical effect of plasticity and non linear processes in the source region. We condense these equivalent forces into a point-source with a time-varying single force and nine-component moment tensor. This analytical representation bridges the gap between the complex dynamics of crater formation, and the linear point-source representation classically used in seismology. Using the multiphysics modelling software HOSS, we develop a method to compute the stress glut of an impact, and the associated point-source from hypervelocity impact simulations. For a vertical and an oblique impact at 1000 m s−1, we show that the moment tensor presents a significant deviatoric component. Hence, the source is not an ideal isotropic explosion contrary to previous assumptions, and draws closer to a double couple for the oblique impact. The contribution of the point force to the seismic signal appears negligible. We verify this model by comparing two signals: (1) HOSS is coupled to SPECFEM3D to propagate the near-source signal elastically to remote seismic stations; (2) the point-source model derived from the stress-glut theory is used to generate displacements at the same distance. The comparison shows that the point-source model is accurately simulating the low-frequency impact seismic waveform, and its seismic moment is in trend with Lunar and Martian impact data. High-frequencies discrepancies exist, which are partly related to finite-source effects, but might be further explained by the difference in mathematical framework between classical seismology and HOSS’ numerical modelling.

It’s About What Happens in the Meantime: The Temporal Interplay of Individual and Collective Creativity

In creativity research, time is rarely conceptualized as a multidimensional phenomenon. Instead, it is conceived either as an external variable, for coordinating successive phases of an idea journey, interaction patterns, and moments of insight—or as an individual experience, encompassing aspects like stress or timelessness. Based on an ethnography of a music studio, I show how these temporalities coexist and how time is organized as a linear coordination process as well as an experience to enable and align individual and collective creativity. Time is thereby available in three dimensions, as planned time for linear sequencing of collective work steps, as assigned meantime for the spontaneous and parallel allocation of tasks to free time slots, and as idle meantime for indeterminate waiting periods afforded by the material temporality of artifacts and bodies. My findings elucidate that organizing the interplay of all three temporal dimensions favors both individual ideation in indeterminate situations of idleness and collective creative work on predefined tasks in planned phases and ad hoc structured situations. Importantly, I found how the time afforded by artifacts and bodies in creative work is key to enabling and aligning individual creative processes by providing opportunities for relaxation, defocusing, and humor during collective creative processes, based on coordinated interaction. My findings contribute to a social process perspective on creativity by reconsidering the role of individual experiences in creative collaboration from a temporal perspective. Funding: This research was supported by the Austrian Science Fund (FWF) [Grant 10.55776/I4884].

Kalman filter with impulse noised outliers: a robust sequential algorithm to filter data with a large number of outliers.

Impulse noised outliers are data points that differ significantly from other observations. They are generally removed from the data set through local regression or the Kalman filter algorithm. However, these methods, or their generalizations, are not well suited when the number of outliers is of the same order as the number of low-noise data (often called nominal measurement). In this article, we propose a new model for impulsed noise outliers. It is based on a hierarchical model and a simple linear Gaussian process as with the Kalman Filter. We present a fast forward-backward algorithm to filter and smooth sequential data and which also detects these outliers. We compare the robustness and efficiency of this algorithm with classical methods. Finally, we apply this method on a real data set from a Walk Over Weighing system admitting around 60 % of outliers. For this application, we further develop an (explicit) EM algorithm to calibrate some algorithm parameters.

An integrated method for compensating and correcting nonlinear error in five-axis machining utilizing cutter contacting point data

In current five-axis computer numerical control (CNC) machining, the use of minute linear path segments as an approximation for the ideal cutter contacting (CC) point trajectory is still prevalent. However, introducing rotation axes leads to a deviation of the actual CC point trajectory from the ideal, resulting in nonlinear errors. An integrated method is proposed in this paper for compensating and correcting both the contour error, associated with the approximation of the part surface by the ideal CC point trajectory and the nonlinear error of the CC point trajectory based on the information in the CC point data. By analyzing the spatial relationship between the tool posture and the CC point path during the five-axis linear interpolation process, two adjacent machining tool positions containing CC point data information are selected as the starting and ending points of the five-axis linear interpolation machining. The ideal tool center point and the actual CC point are calculated during the interpolation process, as well as the distance and the unit vector in the perpendicular direction between the actual CC point and the ideal CC point trajectory segment. In the comprehensive error compensation and correction phase, the obtained unit vectors are used as direction vectors for error compensation, and the tool center point during interpolation is first compensated and corrected. This ensures the actual CC point and the contour curve are on the same plane. The compensation direction for contour error is calculated using the start/end tool axis vectors and the ideal CC point trajectory vectors. The size of the contour error approximating the contour curve is calculated through the chord error. A second compensation and correction are applied to the tool center point for interpolation, ultimately achieving comprehensive compensation and correction of nonlinear errors. The data calculations were conducted in the MATLAB environment using actual machining data. After compensation and correction, the contour error was reduced by 76%, the nonlinear error of the CC point trajectory decreased to below 0.88 μm, and the comprehensive nonlinear error of the CC point trajectory was reduced from 19 to 1.5 μm, a reduction of 93%. This demonstrates significant practical value in enhancing the accuracy of five-axis CNC machining. Through actual machining verification, after using the method described in this paper, the average surface roughness decreased from 1.133 to 0.220 μm, and the maximum surface roughness decreased from 6.667 to 1.240 μm. This significantly demonstrates that the compensation and correction method proposed in this paper can significantly improve the surface quality of machined parts.

Contemporary Strategies for the Structural Design of Multi-Story Modular Timber Buildings: A Comprehensive Review

Modular timber construction embodies a pioneering and eco-friendly methodology within the building sector. With the notable progress made in manufacturing technologies and the advent of engineered wood products, timber has evolved into a promising substitute for conventional materials such as concrete, masonry, and steel. Beyond its structural attributes, timber brings environmental advantages, including its inherent capacity for carbon sequestration and a reduced carbon footprint compared to conventional materials. Timber’s lightweight nature, coupled with its versatility and efficiency in factory-based production, accelerates modular construction processes, providing a sustainable solution to the growing demands of the building industry. This work thoroughly explores contemporary modular construction using wood as the primary material. The investigation spans various aspects, from the fundamentals of modularity and the classification of modular timber solutions to considerations of layout design, structural systems, and stability at both the building and module levels. Moreover, inter-module joining techniques, MEP (mechanical, electrical, and plumbing) integration, and designs for disassembly are scrutinized. The investigation led to the conclusion that timber modular construction, drawing inspiration from the steel modular concept, consistently utilizes a structural approach based on linear members (timber frame, post-and-beam, etc.), incorporating stability configurations and diverse joint techniques. Despite the emphasis on modularization and prefabrication for adaptability, a significant portion of solutions still concentrate on the on-site linear assembly process of those linear members. Regarding modularity trends, the initial prevalence of 2D and 3D systems has given way to a recent surge in the utilization of post-and-beam structures, congruent with the ascending verticality of buildings. In contrast to avant-garde and bold trends, timber structures typically manifest as rectilinear, symmetric plans, characterized by regular and repetitive extrusions, demonstrating a proclivity for centrally located cores. This work aims to offer valuable insights into the current utilization of modular timber construction while identifying pivotal gaps for exploration. The delineation of these unexplored areas seeks to enable the advancement of modular timber projects and systems, fully leveraging the benefits provided by prefabrication and modularity.

‘Adopt your city’: Post-political geographies and politics of urban philanthropy during austerity

Over the last decade, urban philanthropic giving has acquired an increased significance for cities, shaping urban agendas and affecting local decision-making. Contributing to the emerging geographical literature on the impact of philanthropy on urban governance as well as to scholarship on post-foundational geographies, I argue that urban philanthropic giving is related to a post-political regime of multi-stakeholder urban governance. Contrary to being a linear process of managerial consensus politics, the post-politicisation of urban governance emerges as a multidimensional and variegated process of mutations and adaptations. Drawing from Athens, Greece, in the austerity period, I trace the emergence of a new donor-based philanthrocapitalist regime of urban governance and I demonstrate that post-political governance can take diverse forms: from the well-described in existing literature inclusive partnership-based approach to more authoritarian consensus-based governance processes. The aim of the paper is not just to answer if philanthrocapitalism gives rise to a post-political condition or not, but to explore how it is making and remaking (post-political) urban governance of public spaces, urban politics and urban everyday life. In doing so, the paper focuses on Athens Partnership, an intermediate governance organisation that was established to manage and support donations from the private sector to local governments in Athens and explores the ways urban philanthropy impacts on urban governance. Overall, the paper brings forward a renewed, more enmeshed understanding of post-political urban governance through an analysis of the novel philanthrocapitalist regime that emerged in European cities in the context of the recent intersecting crises.

Integration and analysis of diverse healthcare data sources: A novel solution

Contemporary healthcare analytics requires informed decision-making through seamless integration, correlation, and curation of diverse data from sources like clinical trials, research publications, ubiquitous devices, and standard terminologies. Modern healthcare systems need to monitor temporal changes, manage key features, and deliver robust search capabilities, extending beyond electronic health records. However, existing systems lack readiness for comprehensive healthcare analytics tasks, necessitating a sophisticated solution. Our work introduces a groundbreaking comprehensive framework for managing, integrating, and processing continuously evolving healthcare data, with a focus on establishing an efficient architecture for data processing and ensuring interoperability and consistency. We incorporate a time dimension to capture critical changes for efficient data analysis and decision-making, extending from clinical trials to mapping clinical trial data to clinical research. Moreover, we curate disparate datasets, including trials, academic publications, standard medical terms, concepts, and ubiquitous device data. Employing highly efficient algorithms and methods, we optimize time and space complexity, validating the feasibility of our proposed solution. Our results demonstrate maximum linear change detection and update processing latency, showcasing efficiency compared to state-of-the-art methods. Additionally, our methods for profiling crucial entities in clinical trial data achieve consistent average accuracy, notably with the VSM model. This innovative approach significantly advances meeting dynamic requirements in contemporary healthcare analytics, particularly in clinical trials.

Linear growth determinants of under two years old children in Surabaya, Indonesia

BackgroundChildren under 2 years are in a crucial stage of child development, but they are also vulnerable to nutritional problems, one of which is linear growth faltering. Sociodemographic and health characteristics can influence the linear growth process. This study aimed to analyze the determinants of the linear growth of children under 2 years in four Community Health Centers in Surabaya, Indonesia. MethodA cross-sectional study of 160 parents with children under 2 years was done through consecutive sampling. Sociodemographic and health characteristics were assessed by questionnaires, anthropometric measurements, and secondary data from Maternal and Child Health Book (MCH). The linear growth of the children was identified using length-for-age z-score (LAZ). The data were analyzed using correlation test, One-way ANOVA, independent t-test, and multiple linear regression to see the influential factors. ResultsThe average LAZ for children under 2 years in four Surabaya City Health Centers areas was normal (−0.76 ± 1.70). Maternal height (p:0.001) and birth length (p:0.001) were significantly related to linear growth. The determinants of linear growth were birth length, maternal height, and history of exclusive breastfeeding, with the most considerable beta value of 0.231 on maternal height. ConclusionA maternal height primarily determines children under 2 years of linear growth. Parents with growth hormone deficiency were at risk of inheriting this gene to their children. Community Health Centers as health services can be more active in education and nutritional counseling for teenagers and prospective brides.

Interprofessional follow-up for people at risk of type 2 diabetes in primary healthcare – a randomized controlled trial with embedded qualitative interviews

Objective To examine the effects of an empowerment-based interprofessional lifestyle intervention program among people at risk of type 2 diabetes on knowledge, skills, and confidence in self-management, health, psychological well-being, and lifestyle characteristics, and to explore the participants’ perceptions of participating in the intervention. Design and methods In line with the Medical Research Council complex interventions research methods framework, we conducted a randomized controlled trial with embedded qualitative interviews in primary healthcare clinics in Norway between 2019–2021. Of the patients at risk (The Finnish Diabetes Risk Score Calculator (FINDRISC) ≥15 or Body Mass Index (BMI) ≥30) 142 accepted the invitation, and 14 participants from the intervention group participated in individual interviews after the 12-month follow-up. Our primary outcome was the Patient Activation Measure (PAM-13). Secondary outcomes were EQ-5D-5L, EQ-VAS, WHO-Overall health, WHO-Overall QOL, weight, height, waist circumference, and regularity of physical activity. We used thematic analysis to analyse the qualitative data. Results There was no clinically relevant differences of neither the primary nor the secondary endpoints between intervention and control group. As to the qualitative data, we identified two distinct features: ‘Meaningful perspectives on lifestyle changes’ and ‘Lifestyle change is not a linear process due to challenges faced along the way’ putting ownership of their choices in life into picture. Conclusion The negative results of the RCT stand in contrast to the findings given by the participants voices, perceiving the intervention as a key eye opener placing their health challenges in perspective. How to interpret these seemingly conflicting findings of participants being seen, heard, and understood, helping them to take more conscious ownership of their choices in life, and at the same time demonstrating no improvements in symptoms or measures, is a dilemma that needs further exploration. We should be careful to implement interventions that do not demonstrate any effects on the quantitative outcomes.

The entropy rate of Linear Additive Markov Processes.

This work derives a theoretical value for the entropy of a Linear Additive Markov Process (LAMP), an expressive but simple model able to generate sequences with a given autocorrelation structure. Our research establishes that the theoretical entropy rate of a LAMP model is equivalent to the theoretical entropy rate of the underlying first-order Markov Chain. The LAMP model captures complex relationships and long-range dependencies in data with similar expressibility to a higher-order Markov process. While a higher-order Markov process has a polynomial parameter space, a LAMP model is characterised only by a probability distribution and the transition matrix of an underlying first-order Markov Chain. This surprising result can be explained by the information balance between the additional structure imposed by the next state distribution of the LAMP model, and the additional randomness of each new transition. Understanding the entropy of the LAMP model provides a tool to model complex dependencies in data while retaining useful theoretical results. To emphasise the practical applications, we use the LAMP model to estimate the entropy rate of the LastFM, BrightKite, Wikispeedia and Reuters-21578 datasets. We compare estimates calculated using frequency probability estimates, a first-order Markov model and the LAMP model, also considering two approaches to ensure the transition matrix is irreducible. In most cases the LAMP entropy rates are lower than those of the alternatives, suggesting that LAMP model is better at accommodating structural dependencies in the processes, achieving a more accurate estimate of the true entropy.

Synergic action of linear dispersion, second-order nonlinearity, and third-order nonlinearity in shaping the spectral profile of a femtosecond pulse transporting in a lithium niobate crystal

We present a detailed theoretical and numerical analysis on the temporal-spectral-spatial evolution of a high-peak-power femtosecond laser pulse in two sets of systems: a pure lithium niobate (LN) plate and a periodically poled lithium niobate (PPLN) plate. We develop a modified unidimensional pulse propagation model that considers all the prominent linear and nonlinear processes and carried out the simulation process based on an improved split-step Fourier transformation method. We theoretically analyze the synergic action of the linear dispersion effect, the second-order nonlinearity (2nd-NL) second-harmonic generation (SHG) effect, and the third-order nonlinearity (3rd-NL) self-phase modulation (SPM) effect, and clarify the physical mechanism underlying the peculiar and diverse spectral broadening patterns previously reported in LN and PPLN thin plate experiments. Such analysis and discussion provides a deeper insight into the synergetic contribution of these linear and nonlinear effects brought about by the interaction of a femtosecond laser pulse with the LN nonlinear crystal and helps to draw a picture to fully understand these fruitful optical physical processes, phenomena, and laws.