Integration Technique Research Articles

Predefined-time stabilisation of stochastic low-order nonlinear systems with asymmetric output constraint

This paper researches the predefined-time stabilisation problem for a class of stochastic low-order nonlinear systems with asymmetric output constraint whose nonlinearities satisfy high-order and low-order growth conditions. By introducing a novel nonlinear transformation and utilising the adding a power integrator technique, a continuous state feedback controller is designed. The proposed control scheme can guarantee that the output constraint will not be violated almost surely and the trivial solution of the closed-loop system is stochastic predefined-time stable. Finally, two simulation examples are provided to demonstrate the effectiveness of this control method.

Power Quality Enhancement using Integrated Control Technique Quantum Calculus-based Least Mean Fourth and Optimized Fractional Order Proportional-Integral-Derivative

Power Quality Enhancement using Integrated Control Technique Quantum Calculus-based Least Mean Fourth and Optimized Fractional Order Proportional-Integral-Derivative

Occupational therapy in the Snoezelen® Room: Teachers’ and therapists’ knowledge and perceptions of the changes in children's behaviour and performance

Introduction: The Snoezelen® room, a multisensory environment (MSE), is often used in conjunction with sensory integrative techniques. Therefore, it may be of support in school-based occupational therapy intervention. Research has documented positive changes in children’s performance in the MSE. However, research to suggest that changes could be carried over to external environments is limited. This study aimed to investigate the knowledge and perception of teachers and therapists regarding changes in children's behaviour and performance after therapy in the Snoezelen® room. Methodology: A descriptive quantitative cross-sectional survey design by purposive sampling was used. Teachers and therapists working with children who received occupational therapy intervention in the Snoezelen® room participated. Results: Descriptive and inferential statistics were utilized to determine strong positive, significant correlations found between the total impact of the Snoezelen® room and the children’s level of arousal, as well as their behaviour and scholastic performance, as conveyed by 30 participants. After therapy in the Snoezelen® room, improvement in level of arousal was ranked as the biggest change, which appeared to improve for hours upon return to the classroom. Conclusion: Children’s arousal levels changed positively due to sensory input, which carried over to the external environment. Due to this, most teachers and therapists perceived that the Snoezelen® room positively changed behaviour and scholastic performance, through improved level of arousal. Implications for practice: The use of Snoezelen® rooms in schools, combined with sensory integration therapy (SIT), enhances children's self-regulation, which in turn positively impacts behaviour and academic performance. Strong, positive correlations were found between children's level of arousal and improvements in their behaviour and scholastic performance. Thus, Occupational therapy interventions in the Snoezelen® room significantly contribute to children’s ability to self-regulate, a key factor in achieving positive classroom behaviour and learning outcomes. Teachers and therapists perceive Snoezelen® rooms as beneficial, with 96.7% supporting their presence on school campuses to improve child behaviour through better self-regulation. Consistent with extensive research surrounding self-regulation of children, acquiring self-regulation skills in the early years lays the foundation for positive classroom behaviour and academic performance later.

Constrained Control of Autonomous Underwater Gliders Based on Disturbance Estimation and Tracking Back Calculation

ABSTRACTThis article presents an anti‐disturbance constrained control scheme for the pitch channel of autonomous underwater gliders subject to internal and external disturbances, as well as actuator saturation. First, the integral control technique is employed to develop a disturbance observer to estimate the overall effect of possible uncertainties and disturbances on the nominal vehicle model, which is referred to as the mismatched lumped disturbance. Then, a disturbance rejection control law is constructed based on the disturbance observer. Following that, a straightforward anti‐windup modification is proposed to handle potential input constraints by using the tracking back calculation technique. Specifically, the difference between saturated and unsaturated control input signals is utilized to create a feedback signal that addresses the disturbance observer input, thereby alleviating system windup during actuator saturation events. Furthermore, the stability of the overall closed‐loop system is established in term of the Lyapunov stability theorem, demonstrating that the tracking error is ultimately bounded. Compared with some existing anti‐windup control schemes, the suggested approach offers intuitive design guidelines, resulting in a simple controller that can be easily implemented. Finally, the effectiveness and robustness of the proposed control scheme are verified through simulation results.

Formulation and Implicit Numerical Integration of a Kinematic Hardening Model for Unsaturated Soils

ABSTRACTCurrently, our understanding of material‐scale deterioration resulting from meteorologically induced variations in pore water pressure and its significant impact on infrastructure slopes is limited. To bridge this knowledge gap, we have developed an extended kinematic hardening constitutive model for unsaturated soils that refines our understanding of weather‐driven deterioration mechanisms in heterogeneous clay soils. This model has the capability of predicting the irrecoverable degradation of strength and stiffness that has been shown to occur when soils undergo wetting and drying cycles. The model is equipped with a fully coupled and hysteretic water retention curve and a hysteretic loading–collapse curve and has the capability to predict the irrecoverable degradation of strength and stiffness that occurs during cyclic loading of soils. Here, we employ a fully implicit stress integration technique and give particular emphasis to deriving a consistent tangent operator, which includes the linearisation of the retention curve. The proposed algorithm is evaluated for efficiency and performance by simulating various stress and strain‐driven triaxial paths, and the accuracy of the integration technique is evaluated through the use of convergence curves.

Isolation of highly polar galloyl glucoside tautomers from Saxifraga tangutica through preparative chromatography and assessment of their in vitro antioxidant activity

In this work, the rapid and efficient preparation of isolated galloyl glucoside tautomer free radical inhibitors was investigated using Saxifraga tangutica as a raw material. Four highly polar galloyl glucoside tautomers, 3-O-galloyl-α-d-glucose ⇌ 3-O-galloyl-β-d-glucose (Fr2-1-1), 2-O-galloyl-α-d-glucose ⇌ 2-O-galloyl-β-d-glucose (Fr2-1-2/2-1-3), 1-O-galloyl-β-d-glucose (Fr2-2-1), and 6-O-galloyl-α-d-glucose ⇌ 6-O-galloyl-β-d-glucose (Fr2-3-1/Fr2-3-2), were obtained via two-step medium-pressure liquid chromatography (with solid loading instead of conventional liquid injection) and one-step high-performance chromatography coupled with on-line RPLC-DPPH techniques for targeted isolation. This separation integration technique not only increases sample intake and reduces time cost but also visualizes each step of targeted separation. All four compounds were isolated from the plant for the first time. In vitro antioxidant activity assays by DPPH (1,1‑diphenyl-2-picrylhydrazyl) revealed that Fr2-1-2/Fr2-1-3 (IC50: 5.52 ± 0.32 μM), Fr2-2-1 (IC50: 7.22 ± 0.57 μM), and Fr2-3–1/Fr2-3-2 (IC50: 7.36 ± 0.25 μM) had superior free radical scavenging abilities and that both were superior to that of quercetin (IC50: 18.61 ± 3.55 μM). Oxidative stress assays revealed that Fr2-1-2/Fr2-1-3 significantly inhibited oxidative stress damage in H2O2-induced HepG2 cells, decreased the level of ROS (P < 0.01) and protected hepatocytes. Combined with the current results, gallic acid showed greater antioxidant activity when H atoms were replaced at d-glucose –OH (C-2) than at the other three sites [–OH (C-1), –OH (C-6) and –OH (C-3)].

The role of biomechanics in enhancing cognitive function and learning outcomes in English language teaching

Language learning, traditionally taught through memory and repetition, often overlooks the role of physical movement in enhancing cognitive and linguistic abilities. Theories like embodied cognition and motor learning suggest that cognitive functions are closely linked to physical actions. Research suggests that posture, gestures, and movement can improve language processing and comprehension. However, the practical integration of biomechanical principles into structured language teaching remains underexplored. Previous studies on gesture-based learning and movement-enhanced vocabulary acquisition indicate potential benefits but lack a comprehensive approach. This study introduces a series of biomechanical interventions in English language teaching, including posture training, movement-based vocabulary learning, sensory-motor integration, and kinesthetic learning techniques. A quasi-experimental design with 115 12–16-year-olds was used for 8 weeks. The experimental group received biomechanical interventions, and the control group received traditional teaching. Cognitive function and language outcomes were assessed pre-and post-assessment. The experimental group showed significant cognitive function improvements, with scores rising from 78.5 ± 5.6 to 89.3 ± 4.8, while the control group showed only a minor change (77.9 ± 5.8 to 80.7 ± 5.5, t = 4.56, p = 0.002, d = 1.78 In the experimental group, vocabulary scores increased from 85.6 ± 7.4 to 92.3 ± 6.2 (t = 3.22, p = 0.008, d = 1.03). Memory improvement correlated strongly with vocabulary acquisition (r = 0.68, p = 0.003). Also, engagement frequency increased (p = 0.004).

Infrared and Visible Camera Integration for Detection and Tracking of Small UAVs: Systematic Evaluation

Given the recent proliferation of Unmanned Aerial Systems (UASs) and the consequent importance of counter-UASs, this project aims to perform the detection and tracking of small non-cooperative UASs using Electro-optical (EO) and Infrared (IR) sensors. Two data integration techniques, at the decision and pixel levels, are compared with the use of each sensor independently to evaluate the system robustness in different operational conditions. The data are submitted to a YOLOv7 detector merged with a ByteTrack tracker. For training and validation, additional efforts are made towards creating datasets of spatially and temporally aligned EO and IR annotated Unmanned Aerial Vehicle (UAV) frames and videos. These consist of the acquisition of real data captured from a workstation on the ground, followed by image calibration, image alignment, the application of bias-removal techniques, and data augmentation methods to artificially create images. The performance of the detector across datasets shows an average precision of 88.4%, recall of 85.4%, and mAP@0.5 of 88.5%. Tests conducted on the decision-level fusion architecture demonstrate notable gains in recall and precision, although at the expense of lower frame rates. Precision, recall, and frame rate are not improved by the pixel-level fusion design.

Control of probability flow in Markov chain Monte Carlo-Nonreversibility and lifting.

The Markov chain Monte Carlo (MCMC) method is widely used in various fields as a powerful numerical integration technique for systems with many degrees of freedom. In MCMC methods, probabilistic state transitions can be considered as a random walk in state space, and random walks allow for sampling from complex distributions. However, paradoxically, it is necessary to carefully suppress the randomness of the random walk to improve computational efficiency. By breaking detailed balance, we can create a probability flow in the state space and perform more efficient sampling along this flow. Motivated by this idea, practical and efficient nonreversible MCMC methods have been developed over the past ten years. In particular, the lifting technique, which introduces probability flows in an extended state space, has been applied to various systems and has proven more efficient than conventional reversible updates. We review and discuss several practical approaches to implementing nonreversible MCMC methods, including the shift method in the cumulative distribution and the directed-worm algorithm.

Fast finite‐time stabilization of stochastic nonlinear systems with output constraints and an application to single‐link robot

AbstractThis article studies the fast finite‐time stabilization problem for stochastic nonlinear systems with asymmetric output constraints. To address the issue of slow convergence encountered in previous finite‐time control designs of stochastic nonlinear constrained systems, this paper extends the fast finite‐time stabilization mechanism to such systems. First, a novel asymmetric barrier Lyapunov function is employed to tackle the output constraint. Then, by adding a power integrator technique and the barrier Lyapunov function, a state‐feedback controller for stochastic nonlinear systems is explicitly designed using the backstepping method. The designed controller achieves fast finite‐time stability in probability of the stochastic nonlinear system while ensuring no violation of the output constraints. Finally, two examples are presented to demonstrate the effectiveness of the controller scheme.

Integrated Characterization of Expanding-Solvent Steam-Assisted Gravity Drainage (ES-SAGD) Processes by Using a Heat-Penetration Criterion within a Unified, Consistent, and Efficient Framework

Summary The hybrid solvent-steam injection [e.g., expanding-solvent steam-assisted gravity drainage (ES-SAGD)] is the most promising method to enhance heavy oil recovery; however, it is quite a challenge to reproduce the experimental measurements and in-situ observations because of the complicated multiphase flow behavior resulting from the coupled mass and heat transfer. In this work, an integrated technique has been developed and applied for the first time to dynamically and accurately characterize an ES-SAGD process within a unified, consistent, and efficient framework. By taking the competitive impact between heat energy and solvent dissolution, a generalized heat-penetration (HP) criterion has been derived and integrated with a numerical simulator to characterize the dynamics of solvent/steam chamber propagation conditioned to the production profiles during hybrid solvent-steam processes. This generalized HP criterion allows us to not only dynamically calculate temperature profiles beyond a solvent/steam chamber interface (SCI) but also accurately and pragmatically quantify mass and heat transfer inside the diluted oil drainage zone as well as the solvent/steam chamber. Also, comprehensive effects of the thermally sensitive co/countercurrent flows are examined with a series of multiphase relative permeabilities. Such an integrated technique has been successfully validated by reproducing the measured solvent/steam chambers in 3D physical ES-SAGD experiments. Good agreements between the simulated and measured production profiles (i.e., injection temperature, pressure, and flow rate) have been made throughout the entire production period. Not only have the measured solvent/steam chambers been reproduced but also sensitivity analyses have been performed to investigate the influences of multiphase flow behavior, solvent concentration, and grid dimension. It is found that the diffusion/dispersion coefficients and thermal properties are dependent on temperature and solvent concentrations, competitively affecting the calculated temperature distributions. Moreover, gas-liquid relative permeabilities can impose a significant impact on the SCI moving velocity as well as the oil drainage front. Such an integrated approach considerably reduces the simulation uncertainties and complexities, offering a straightforward and effective means of dynamically reproducing the observed solvent/steam chambers within a unified, consistent, and efficient framework.

A Comparative Analysis of Fractal and Fractionalized Thermal Non-Equilibrium Model for Chaotic Convection Saturated by Porous Medium

The convective heat transfer is one of the most important mechanism of heat transference for controlling the chaotic characteristics in porous media. A comparative study of thermal non-equilibrium model is proposed for fractal porous under the consideration of chaotic convection. A novel chaos control is focused between fractal porous and fractional porous by means of newly proposed differential and integral techniques. The sensitivity analysis for chaos expansion and uncertainty quantification for the flow in heterogeneous media have been perceived to the problem of chaotic convection through numerical simulations. In order to approximate the propagation of chaos, two types of simulations have been carried out in terms of chaotic attractors through fractal and fractional approaches. For examining a variety of chaos under the numerical simulations in which fractal domain is varied and fractional domain is fixed, fractal domain is fixed and fractional domain is varied, and both fractal as well as fractional domain are varied. Finally, it is observed that the fractional and fractal memory effects have caused by interactions between uncertain parameters and disclosed the microstructures on the permeability of porous media.

Formulations and numerical techniques for computation of acoustic pressure and its gradient by integral method

Starting from the Ffowcs Williams-Hawkings surface integral formulation for a moving medium, the article proposes rather simple expressions for the radiated pressure and its gradient in the time domain, that are valid for solid or porous, fixed or moving integration surfaces. Moreover, these original expressions allow calculations with integration surfaces in supersonic motion (such as rotating surfaces around propellers or rotors). Versions dedicated to fixed integration surfaces are also proposed. The usual locally compact and the fully non-compact integration techniques are recalled, with, for both, a detailed description of efficient calculation algorithms. Particular attention is devoted to the order of precision of the calculations. The time derivation techniques and integration schemes used in this study lead to a theoretical second order that can easily be increased for the locally compact integration method. The results of these expressions and integration methods are compared to the analytical solution for the case of a fixed monopole and for that of a rotating monopole. They clearly show the benefit of the direct gradient calculation over a calculation by finite differences of the pressure around the observation point, particularly for broadband signals.

Numerical Treatment for the Caputo-Fabrizio Fractional Smoking Model using an Efficient Numerical Technique

Smoking is a prevalent social behavior widely practiced worldwide, especially in settings such as schools and some significant gatherings. Based on the World Health Organization (WHO), smoking is the third leading source of human mortality and the primary preventable cause of disease. This study introduces a highly efficient simulation technique to analyze and solve the Caputo-Fabrizio (CF) fractional smoking model. We numerically solve the fractional integral equations (FIEs) with Simpson’s 1/3 rule, an effective numerical integration technique. We concentrate on clarifying the stability/convergence of the proposed strategy. We juxtapose the outcomes derived using the Runge-Kutta method (RK4) with those obtained through the implemented methodology. The findings indicate that the used technique provides a simple and efficient instrument for simulating the solution of these models. The principal advantage of the proposed method is its dependence on a limited number of straightforward steps, devoid of long-term consequences or reliance on a perturbation parameter.

Management of Hybrid Hydropower and Floating Solar Systems at Num Ngum 1 in Lao PDR

The integration of a hybrid hydro-floating solar power (HPP-FPV) system is covered in this study with the goal of improving energy management and producing more electricity. The production capacity of the hybrid system is almost twice as high as that of the original HPP system, demonstrating its potential for higher energy generation. Because it forecasts weather and modifies electricity generation accordingly. The analysis highlights how crucial it is to make sure that the hybrid system's electricity generation doesn’t go beyond the current power grid's maximum transmission capacity. This is essential to preserving the consistency and caliber of the power that is provided. The research's overall goal of increasing the output of renewable energy through creative system integration and practical management techniques is captured in the abstract.

Fog Computing Enabled Adaptive Prognosis of Cutting Tool Remaining Life through Multi-source Data

Abstract Cutting tool remaining life during machining processes is essential for achieving sustainable production. Traditional prognosis methods are often crippled by the inability to adapt to diverse working conditions across the machining process lifecycle. This paper introduces a fog computing-enabled adaptive prognosis framework utilising multi-source data to address these challenges effectively. The key innovations include: (1) The proposed system integrates power and vibration data collected from LGMazak VTC-16A and IRON MAN QM200 machines. A standardised data fusion method combines multi-source data to enhance robustness and accuracy. (2) The transformer model is employed to improve prognosis accuracy of cutting tool remaining life, best accuracy of 98.24% and an average accuracy of 97.63% are achieved. (3) Finite Element Analysis (FEA) is incorporated to validate the model's predictions to validate reliability of deep learning model. (4) The fog computing optimisation mechanism based on the bees algorithm, which shows fitness value of 0.92 and convergence within 15 iterations. The proposed method reduces total data volume in cloud by 54.12%, prediction time by 33.64% and time complexity in the cloud layer by 4.62%. The effectiveness of fog computing in enhancing the operational efficiency and reliability of manufacturing systems is validated through advanced data integration and deep learning techniques.

High capacity, low power, short reach integrated silicon photonic interconnects

The architecture and component technology of a low power, high capacity, short reach optical interconnect are detailed. Measurements from high-performance 300 mm silicon photonics components that comprise the system are shown, along with a quantum-dot mode-locked laser 20-channel comb source with free space wall plug efficiencies up to 17%, advanced packaging techniques for 3D silicon photonic-electronic integration, and schematics for integrated electronics that control the photonic integrated circuits. Techniques for operating such a system in the presence of changing ambient temperature are addressed. Experiments on a 1 Tbps design are conducted with an optical link experiment indicating sub-picojoule/bit energy consumption at scale.

Blockchain and Digital Twins in Smart Industry 4.0: The Use Case of Supply Chain-A Review of Integration Techniques and Applications

The Fourth Industrial Revolution has transformed industries and supply chains by integrating advanced operations, tools, and logistics services. Despite these advancements, challenges persist, particularly in ensuring data dependability, security, and operational efficiency. Digital twins (DTs), which replicate real-world components and processes, have emerged as essential tools for enhancing predictive analytics, simulation, and product lifecycle management in Industry 4.0. However, traditional DT development relies on centralized systems, which are vulnerable to data tampering and security breaches, especially in the management of transaction logs and historical data. To address these challenges, this review provides a comprehensive analysis of the current state of integrating blockchain with DTs. Using a qualitative research methodology, including desk research, case studies, and interviews with industry experts, we analyze various blockchain-based DT applications across industries and specifically in supply chain management. The findings reveal that blockchain-enhanced DTs can significantly improve data integrity, traceability, and security, thus boosting operational efficiency and quality control in supply chains. Additionally, this study identifies key integration techniques and the role of blockchain in automating processes through smart contracts. This review provides insights into the practical implications of blockchain-based DTs, highlighting their potential to enhance the reliability and scalability of Industry 4.0 operations.

Special-point approach for optical absorption coefficient calculations on two-dimensional self-assemblies of type-II perovskite quantum dots

All-inorganic perovskite quantum dots with the usual cubic shape have emerged as a successful and low-cost alternative to electronically functional nanomaterials motivating various fields of applications, including high-efficiency photovoltaics. Here, we present an efficient and almost analytic approach for optical absorption coefficient calculation on self-assembled perovskite quantum dot films with type-II band alignment. The approach takes advantage of the special point technique for integration over the two-dimensional Brillouin zone, which minimizes the computational cost. The set of special wave-vector points is generated using the Monkhorst and Pack method. The optical absorption spectrum for phenyl-C60-butyric acid methyl ester (PCBM)/CsPbI3quantum dot films is computed, in good agreement with the experiment assuming a homogeneous linewidth of 50 meV and considering a ten special-point set. We show that light absorption in these systems is a cooperative optoelectronic property resulting from the quantum-mechanical coupling between perovskite nanocubes, leading to extended system states. The generality of this approach makes it suitable for calculating the optical absorption coefficient in a broad class of perovskite quantum dot systems.

Patient-centric knowledge graphs: a survey of current methods, challenges, and applications.

Patient-Centric Knowledge Graphs (PCKGs) represent an important shift in healthcare that focuses on individualized patient care by mapping the patient's health information holistically and multi-dimensionally. PCKGs integrate various types of health data to provide healthcare professionals with a comprehensive understanding of a patient's health, enabling more personalized and effective care. This literature review explores the methodologies, challenges, and opportunities associated with PCKGs, focusing on their role in integrating disparate healthcare data and enhancing patient care through a unified health perspective. In addition, this review also discusses the complexities of PCKG development, including ontology design, data integration techniques, knowledge extraction, and structured representation of knowledge. It highlights advanced techniques such as reasoning, semantic search, and inference mechanisms essential in constructing and evaluating PCKGs for actionable healthcare insights. We further explore the practical applications of PCKGs in personalized medicine, emphasizing their significance in improving disease prediction and formulating effective treatment plans. Overall, this review provides a foundational perspective on the current state-of-the-art and best practices of PCKGs, guiding future research and applications in this dynamic field.