Smooth Action Research Articles

Who is an Agile leader? Technological vs. Non-technological Mindset Employees' Views

For an agile organization to be truly agile, it must be led by agile leaders to sustain its competitiveness and continuously identify opportunities for future growth and development. Technological and non-technological mindsets can see agile leadership differently. Therefore, this study aims to explore if there is any difference in the vision of who the agile leader is in the views of knowledge workers employed in the IT and other sectors. Using a qualitative definitional/interpretive approach supported by MAXQDA software, this study revealed that from the perspective of the technological mindset, key specific to this group characteristics are diligent risk management, technology usage focus, deep understanding of needs, efficiency, and efficacy, critical thinking skills, multitasking, information and knowledge sharing, responsibility, feeling, and constant focus on improvement. Whereas from the perspective of non-technological mindsets, key specific characteristics these mindsets notice are support for employee growth, dynamism and relevance of actions taken, perfect operation on managerial paradoxes, creativity, inclusion, empathy, and self-confidence. The common characteristics that are easy to notice in both mindset types are open-minded personality, the sequential habit of revisions, reflection, and re-framing, learning from experience, wise dynamic (smooth and accurate actions), perfect change implementation skills, adaptability skills, and a positive attitude towards challenges.

Model Predictive Control for Level Control of a Conical Tank

Conical tanks have a high application rate in industrial processes, especially in colloidal mills, chemical processes, and food processing. The use of conical tanks presents significant benefits because they contribute to sedimentation and reduce the accumulation of impurities compared to conventional cylindrical tanks. However, level control of a conical tank due to its shape requires advanced strategies to guarantee efficient control. In this research, a model predictive control (MPC) method was designed and implemented for the level control of a conical tank on a laboratory scale. To evaluate the performance of the controller, it was compared with a traditional proportional–integral (PI) controller, and the rise time, settling time, overshoot, and error in the steady state were analyzed when different set point changes were tested. In addition, the system was subjected to disturbances, and the MPC demonstrated better performance in a transient state, as well as smooth and stable action controls that allowed for an increase in the useful life of the actuator. In addition, an interactive graphical interface was developed that allowed a dynamic response in a real plant to be experienced; this provides an academic tool for designing control strategies before implementation in a real process.

Smooth actions of connected compact Lie groups with a free point are determined by two vector fields

Consider a smooth action G×M→M of a compact connected Lie group G on a connected manifold M. Assume the existence of a point of M whose isotropy group has a single element (a free point). Then we prove that there exist two complete vector field X,X1 such that their group of automorphisms equals G regarded as a group of diffeomorphisms of M (the existence of a free point implies that the action of G is effective). Moreover, some examples of effective actions with no free point where this result fails are exhibited.

Wind Energy Conversion System with Integrated Power Smoothing Capability based on an EVT-coupled Flywheel

This paper presents a wind energy conversion system that integrates, in a compact form, both generation and power smoothing functions. The system is based on a vertical axis wind turbine (VAWT) and a low-speed flywheel that are coupled by an electric variable transmission (EVT). The EVT performs a dual function by simultaneously injecting power to the grid and regulating the power flow to the flywheel to smooth the power fluctuation caused by wind turbulences. The main advantages of the presented generation/smoothing topology are integrating two machines (generator and motor) in the same physical structure and the reduced power demanded by the converter that feeds the flywheel’s rotor. A theoretical analysis is carried out to determine an appropriate control law and flywheel sizing to satisfy a desired attenuation of the power fluctuation. Simulation results show an effective smoothing action, as the power fluctuation is reduced to an adequate level. In addition, the validity of the flywheel sizing procedure is verified.

A data‐driven Bayesian approach for optimal dynamic product transitions

AbstractIn the processing industry, dynamic product transitions are essential for achieving high product quality, minimizing the use of raw materials and energy and reducing production costs. However, optimizing dynamic product transitions is a challenging task due to the complex dynamics of the process and the uncertainty in the measurements. In this article, a data‐driven Bayesian approach for optimal dynamic product transitions is proposed. The proposed approach is based on a dynamic optimization problem that is solved using a Bayesian optimization algorithm. One of the advantages of this approach for process optimization tasks is that it does not require a first‐principles dynamic mathematical model for drawing optimal solutions. The approach is applied to three case studies, and the results are comparable in performance quality with those obtained using a traditional gradient‐based optimization approach. The results show that the proposed approach is able to find optimal transition trajectories that meet the product composition requirements using smooth control actions. The approach is also able to cope with noisy measurements, which is an important feature in real‐world applications. The proposed approach has several advantages over traditional optimization approaches, including being data driven, able to cope with noisy measurements, computationally efficient, and it requires modest computational effort. Complex online optimal control problems can benefit from adopting a data‐driven Bayesian optimization scheme.

Smooth and analytic actions of SL(n,R) and SL(n,Z) on closed n-dimensional manifolds

Smooth and analytic actions of SL(n,R) and SL(n,Z) on closed n-dimensional manifolds

Homotopy Sheaves on Generalised Spaces

We study the homotopy right Kan extension of homotopy sheaves on a category to its free cocompletion, i.e. to its category of presheaves. Any pretopology on the original category induces a canonical pretopology of generalised coverings on the free cocompletion. We show that with respect to these pretopologies the homotopy right Kan extension along the Yoneda embedding preserves homotopy sheaves valued in (sufficiently nice) simplicial model categories. Moreover, we show that this induces an equivalence between sheaves of spaces on the original category and colimit-preserving sheaves of spaces on its free cocompletion. We present three applications in geometry and topology: first, we prove that diffeological vector bundles descend along subductions of diffeological spaces. Second, we deduce that various flavours of bundle gerbes with connection satisfy (∞,2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(\\infty ,2)$$\\end{document}-categorical descent. Finally, we investigate smooth diffeomorphism actions in smooth bordism-type field theories on a manifold. We show how these smooth actions allow us to extract the values of a field theory on any object coherently from its values on generating objects of the bordism category.

Direct control of the endpoint of the manipulator under non-smooth uncertainty and reference trajectories

The problem of tracking the reference trajectory for the manipulator endpoint is considered under the following assumptions: the matrices of the mechanical system have uncertain parameters; external non-smooth disturbances act on the system; and only the vector of generalized coordinates of the manipulator is measured. This vector is uniquely recalculated into the vector of positions of the endpoint. A direct method for the synthesis of a tracking system is proposed, which does not require solving the inverse position problem. The manipulator model is represented in the canonical input-output form considering the vector of the endpoint. The input is a vector of generalized moments developed by the actuators. The complexity of regulation consists of the uncertainty of the input matrix. To stabilize tracking errors under these conditions, a method of linearization by dynamic feedback has been developed. For estimating mixed variables and disturbances, an observer of the minimum possible dynamic order is proposed. A cascade procedure for tuning S-shaped smooth and nonlinear (sigmoid) corrective actions of the observer is presented. This procedure provides an estimation of non-smooth disturbances in a given time with a given accuracy. To smooth primitive trajectories that define, as a first approximation, the desired movement of the endpoint in the workspace, tracking differentiators with sigmoid local feedbacks are used. To tune a tracking differentiator of arbitrary dimension, a decomposition procedure is developed. This procedure considers physical constraints on the velocity and higher derivatives of the manipulator endpoint. The variables of such a differentiator generate smoothed trajectories and their derivatives of any desired order. These trajectories become achievable for the robot. They are used in the tracking system of the control plant as new reference trajectories. The simulation results for a 3-link manipulator demonstrate the excellent performance of the proposed algorithms.

Classification of momentum proper exact Hamiltonian group actions and the equivariant Eliashberg cotangent bundle conjecture

Let G be a compact and connected Lie group. The Hamiltonian G-model functor maps the category of symplectic representations of closed subgroups of G to the category of exact Hamiltonian G-actions. Based on previous joint work with Y. Karshon, the restriction of this functor to the momentum proper subcategory on either side induces a bijection between the sets of isomorphism classes. This classifies all momentum proper exact Hamiltonian G-actions (of arbitrary complexity). As an extreme case, we obtain a version of the Eliashberg cotangent bundle conjecture for transitive smooth actions. As another extreme case, the momentum proper Hamiltonian G-actions on contractible manifolds are exactly the symplectic G-representations, up to isomorphism.

Smoothing finite‐order bilipschitz homeomorphisms of 3‐manifolds

AbstractWe show that, for , any action of a finite cyclic group by ‐bilipschitz homeomorphisms on a closed 3‐manifold is conjugated to a smooth action.

Music conditioned 2D hand gesture dance generation with HGS

AbstractIn recent years, the short video industry is booming. However, there are still many difficulties in the action generation of virtual characters. We observed that on the short video social platform, “hand gesture dance” is a very popular short video form. However, its development is limited by the professionalism of choreography. In order to solve these problems, we propose an intelligent choreography framework, which can generate new gesture sequences for unseen audio based on pairing data in the database. Our framework adopts multimodal method and obtains excellent results. In additional, we collected and produced the first and largest pair labeled hand gesture dance data set. Various experiments showed that our results not only generate smooth and rich action sequences, but also collect some semantic information contained in the audio.

A-foliations of codimension two on compact simply-connected manifolds

We show that a singular Riemannian foliation of codimension two on a compact simply-connected Riemannian (n+2)-manifold, with regular leaves homeomorphic to the n-torus, is given by a smooth effective n-torus action. This solves in the negative for the codimension 2 case a question about the existence of foliations by exotic tori on simply-connected manifolds.

Real-time adaptive sparse-identification-based predictive control of nonlinear processes

This study introduces a sparse identification-based model predictive control (MPC) framework that incorporates on-line updates of the sparse-identified model to account for nonlinear dynamics and model uncertainty in process systems. The methodology involves obtaining a nonlinear first-order ordinary differential equation model using sparse identification for nonlinear dynamics (SINDy), which is integrated into two control schemes: Lyapunov-based MPC (LMPC) for achieving steady-state operation and Lyapunov-based economic MPC (LEMPC) for achieving both closed-loop stability and optimal economic performance. To improve prediction accuracy, an on-line model update scheme is proposed for the SINDy models. Specifically, an error-trigger mechanism that utilizes prediction errors and then uses the most recent process data to update the parameters of the SINDy model in real-time is designed. By incorporating the error-triggered on-line model updates in the SINDy-based LMPC and LEMPC, the dynamic performance of the process is enhanced, ensuring closed-loop stability, optimality, and smooth control actions. Following theoretical results on the boundedness of the closed-loop states and detailed discussions on the selection criteria for parameters of the error-triggered SINDy update scheme, the effectiveness of the proposed methodology is demonstrated through a chemical process example with time-varying disturbances under the LEMPC framework.

Ethnic differences in hepatocellular carcinoma prevalence and therapeutic outcomes.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. The incidence of HCC is affected by genetic and non-genetic factors. Genetically, mutations in the genes, tumor protein P53 (TP53), catenin beta 1 (CTNNB1), AT-rich interaction domain 1A (ARIC1A), cyclin dependent kinase inhibitor 2A (CDKN2A), mannose 6-phosphate (M6P), smooth muscle action against decapentaplegic (SMAD2), retinoblastoma gene (RB1), cyclin D, antigen presenting cells (APC), AXIN1, and E-cadherin, have been shown to contribute to the occurrence of HCC. Non-genetic factors, including alcohol consumption, exposure to aflatoxin, age, gender, presence of hepatitis B (HBV), hepatitis C (HCV), and non-alcoholic fatty liver disease (NAFLD), increase the risk of HCC. The severity of the disease and its occurrence vary based on geographical location. Furthermore, men and minorities have been shown to be disproportionately affected by HCC, compared with women and non-minorities. Ethnicity has been reported to significantly affect tumorigenesis and clinical outcomes in patients diagnosed with HCC. Generally, differences in gene expression and/or the presence of comorbid medical diseases affect or influence the progression of HCC. Non-Caucasian HCC patients are significantly more likely to have poorer survival outcomes, compared to their Caucasian counterparts. Finally, there are a number of factors that contribute to the success rate of treatments for HCC. Assessment and treatment of HCC must be consistent using evidence-based guidelines and standardized outcomes, as well as international clinical practice guidelines for global consensus. Standardizing the assessment approach and method will enable comparison and improvement of liver cancer research through collaboration between researchers, healthcare providers, and advocacy groups. In this review, we will focus on discussing epidemiological factors that result in deviations and changes in treatment approaches for HCC.

Dynamic Models with Sigmoid Corrections to Generation of an Achievable 4D-Trajectory for a UAV and Estimating Wind Disturbances

For an unmanned aerial vehicle (UAV) of an aircraft type, the problems of planning achievable trajectories as well as robust control under wind disturbances are considered. A computationally simple method for compiling a primary non-smooth 4D trajectory is proposed. Its segments connect the given waypoints and determine the desired average velocity in various sections. Instead of time-consuming methods of analytical smoothing of broken path joints using polynomials, a tracking differentiator with S-shaped smooth and limited sigmoid corrective actions is developed. This virtual dynamic model provides natural smoothing of the primary trajectory considering the design constraints on the velocity, acceleration, and thrust of the UAV. The tracking differentiator variables create an achievable trajectory and are used to synthesize the UAV tracking system. To compensate for the action of wind disturbances on the UAV, a disturbance observer is developed. It is a replica of the equations of the control plant model, which are directly affected by external uncontrolled disturbances. These algorithms also use sigmoid corrections. Unlike standard disturbances observers, this approach does not require the development of a dynamic model of external disturbances and does not assume their smoothness. The effectiveness of the developed algorithms was confirmed by numerical simulation.

Superconformal Film Growth: From Smoothing Surfaces to Interconnect Technology.

ConspectusElectronics manufacturing involves Cu electrodeposition to form 3D circuitry of arbitrary complexity. This ranges from nanometer-wide interconnects between individual transistors to increasingly large multilevel intermediate and global scale on-chip wiring. At larger scale, similar technology is used to form micrometer-sized high aspect ratio through-silicon vias (TSV) that facilitate chip stacking and multilevel printed circuit board (PCB) metallization. Common to all of these applications is void-free Cu filling of lithographically defined trenches and vias. While line-of-sight physical vapor deposition processes cannot accomplish this feat, the combination of surfactants and electrochemical or chemical vapor deposition enables preferential metal deposition within recessed surface features known as superfilling. The same superconformal film growth processes account for the long-reported but poorly understood smoothing and brightening action provided by certain electroplating additives. Prototypical surfactant additives for superconformal Cu deposition from acid-based CuSO4 electrolytes include a combination of halide, polyether suppressor, sulfonate-terminated disulfide, and/or thiol accelerator and possibly a N-bearing cationic leveler. Many competitive and coadsorption dynamics underlie functional operation of the additives. Upon immersion, Cu surfaces are rapidly covered by a saturated halide layer that makes the interface more hydrophobic, thereby supporting the formation of a polyether suppressor layer. Also, halide serves as a cosurfactant supporting the adsorption of amphiphilic molecular disulfide species on the surface while inhibiting copper sulfide formation and incorporation into the growing deposit. Furthermore, the dangling hydrophilic sulfonate end group of the accelerator enables activated metal deposition by hindering polyether suppressor assembly. A common thread in superconformal feature filling is additive-derived positive feedback of the metal deposition reaction within recessed or re-entrant regions. For submicrometer features or optically rough surfaces, area reduction that accompanies the motion of concave surface segments results in the most strongly bound adsorbates' enrichment, which for the suppressor-accelerator systems is the sulfonate-terminated disulfide accelerator species. The superfilling and smoothing process is quantitatively captured by the curvature-enhanced adsorbate coverage mechanism. For larger features, such as TSV, whose depths approach the thickness of the hydrodynamic boundary layer, significant compositional and electrical gradients couple with the metal deposition process to give a negative differential resistance and related nonlinear effects on morphological evolution. For certain suppressor-only electrolytes, remarkable bottom-up feature filling occurs where metal deposition disrupts inhibiting adsorbates at the bottom of the TSV or overruns the ability of the suppressor to form due to kinetic or transport limitations. Because the electrical response to changes in interface chemistry is more rapid than mass transport processes, deposition on planar substrates proceeds by bifurcation into passive and active zones, generating Turing patterns. On patterned substrates, active zone development is biased toward the most recessed regions. The distinction between packaging and on-chip metallization will be blurred as the dimensions of the former merge with those of early day on-chip 3D metallization.

A Phyto Pharmacological Comparitive Review on Curcuma Species

Since the dawn of time, medicinal plants have been employed by local populations as a source of healing throughout the healthcare system to demonstrate their efficacy. Some of the results have sparked the development of plant-based medications. The most intricate of interactions would be the investigation of how plants work. This essay examines the function of contemporary pharmacology in relation to a variety of plant derived medicines that has been used for millennia and were know to ancient civilizations. The skill of pharmacists and doctors to engage to the challenges that have arose with the propagation of professional services in the assistance of mans life has increased as a result of wisdom of the development of ideas related to the use of herbal medicines as well as the evolution of awareness. It has been noticed that the plant contained antibacterial, antioxidant, analgesic antifungal, antiasthmatic ,smooth pain reliever, locomotor depressant, anti convulsant and muscle relaxing actions as well as anti inflammatory characteristics. It is now thought of as a useful source of distinctive natural compounds for the creation of medicines against different diseases. According to phytochemical studies, the main chemical components of Curcuma aromatica and Curcuma caesia are terpenoids, flavonoids, phenolic compounds, tannins, inorganic compounds, organic acids and anthocyanin.

Foot trajectory and gait planning of quadruped robot

Foot trajectory and gait planning is one of the important research fields of foot robot. The eighth order polynomial is used to plan the trajectory of each joint of the robot leg, so that the Angle, angular velocity and angular acceleration curves of each joint during leg movement can be smooth and continuous, so as to improve the smooth and quick action of the leg movement. Through MATLAB simulation and robot experiment, it is proved that the eight-order polynomial can keep the legs of the robot continuously and smoothly in the process of movement, reduce the impact of the mutation of the joint movement on the legs of the robot, so that the running trajectory of the robot can be optimized to a certain extent.

Spatial Downscaling of Forest Above-Ground Biomass Distribution Patterns Based on Landsat 8 OLI Images and a Multiscale Geographically Weighted Regression Algorithm

Forest above-ground biomass (AGB) is an excellent indicator for the health status and carbon sink potential of forest ecosystems, as well as the effectiveness of sustainable forest management practices. However, due to the strong heterogeneity of forest structures, acquiring high-accuracy and high-resolution AGB distributions over wide regions is often prohibitively expensive. To fill the resulting gap, this paper uses part of Lishui city, Zhejiang province as the study area, based on 168 forest sample observations, and proposes a novel integrated framework that combines a multi-scale geographically weighted regression (MGWR) with the co-kriging algorithm to refine the spatial downscaling of AGB. Specifically, optimal predictor variable sets identified by random forest importance ranking, multiple stepwise regression, and Pearson VIF methods were first assessed based on their total explanatory power (R square), followed by reconfirmation of the optimal predictor variable set based on the non-stationarity impact of each variable’s action scale (bandwidth) on the output pattern of AGB downscaling. The AGB downscaling statistical algorithms included MGWR, GWR, random forest (RF), and the ordinary least square (OLS), and their downscaling performances were quantitatively compared to determine the best downscaling method. Ultimately, the downscaled AGB pattern was produced using the best method, which was further refined by considering the spatial autocorrelation in AGB samples by implementing a co-kriging interpolation analysis of the predicted AGB downscaling residuals. The results indicated that the variable set selected by random forest importance ranking had the strongest explanatory power, with a validation R square of 0.58. This was further confirmed by the MGWR analysis which showed that the set of variables produced a more spatially smooth downscaled AGB pattern. Among the set of optimal variables, elevation and aspect affected AGB at local scales, representing a strong spatial heterogeneity. Some textural features and spectral features showed a smooth action scale relative to AGB, showing insignificant spatial scale processes. In the study area with complex terrain, using aspect as a covariant, the co-kriging (CK) model achieved a higher simulation accuracy for the MGWR-predicted AGB residuals than the ordinary kriging model. Overall, the proposed MGWR-CK model, with a final validation R square value of 0.62, effectively improved the spatial distribution characteristics and textural details of AGB mapping without the additional costs of procuring finer satellite images and GIS-based features. This will contribute to the accurate assessment of carbon sinks and carbon stock changes in subtropical forest ecosystems globally.

$Z_2^k$-actions with connected fixed point set

In this paper we describe the equivariant cobordism classification of smooth actions $(M^m,\phi)$ of the group $G=\mathbb{Z}_2^k$ on closed smooth $m$-dimensional manifolds $M^m$, for which the fixed point set of the action is a connected manifold of dimension n and $2^k n - 2^{k-1} \leq m < 2^k n$. Here, $\mathbb{Z}_2^k$ is considered as the group generated by $k$ commuting smooth involutions defined on $M^m$. This generalizes a previous result of 2008 of the second author, who obtained this type of classification for $k=2$ and $m=4n-1$ or $m=4n-2$.