Dual Problem Research Articles

SOLAR WIRELESS DYNAMIC ELECTRIC VEHICLE CHARGING SYSTEM

This paper details the making plans and design of a The Solar Wireless Dynamic Electric Vehicle Charging System, a solution to the dual problems of costly gasoline and dangerous emissions. The range of countries with electric cars on the road is gradually rising. In addition to assisting the surroundings, electric cars have validated useful in reducing down on transportation fees by means of substituting highly-priced gas with much greater less costly strength. Here, we create a novel and powerful solution to this problem by means of designing an electric powered vehicle dynamic charging infrastructure. There is no need to stop the car for charging due to the fact the EV can achieve this whilst it's far in movement, the device is powered with the The Solar Wireless Dynamic Electric Vehicle Charging System solar energy and there is no want for an additional power source. Key Words: Solar energy, Solar cell, Arduino Uno controller, Wireless charging, Electric vehicle, Dynamic charging.

On parametric semidefinite programming with unknown boundaries

In this paper, we study parametric semidefinite programs (SDPs) where the solution space of both the primal and dual problems change simultaneously. Given a bounded set, we aim to find the a priori unknown maximal permissible perturbation set within it where the semidefinite program problem has a unique optimum and is analytic with respect to the parameters. Our approach reformulates the parametric SDP as a system of partial differential equations (PDEs) where this maximal analytical permissible set (MAPS) is the set on which the system of PDEs is well-posed. A sweeping Euler scheme is developed to approximate this a priori unknown perturbation set. We prove local and global error bounds for this second-order sweeping Euler scheme and demonstrate the method in comparison to existing SDP solvers and its performance on several two-parameter and three-parameter SDPs for which the MAPS can be visualized.

Ohio START: An adaption of the National Sobriety Treatment and Recovery Teams model

BackgroundThe Sobriety Treatment and Recovery Teams (START) model is an evidence-supported intervention for families with at least one child under age 6 involved in the child welfare system due to substance misuse. The hallmark of the START model is early identification and linkage to addiction treatment services. To address the dual problem of heightened need for addiction treatment services and limited treatment availability in the wake of the opioid epidemic, Ohio’s adaptation extended the model to serve all eligible families regardless of the age of children in the household. ObjectiveTo investigate the delivery of the START model for parents and caregivers of older youth (age 6–18) only as compared to the population for which it was originally intended. MethodsWe used data from 40 counties and with parents as the unit of analysis (N = 714). We used multilevel models to estimate the relationship between the age of children in the home and 1) meeting fidelity for timely access to treatment services and 2) successful completion of the model. ResultsThere was no statistically significant difference in the likelihood of meeting fidelity requirement for timely access to treatment services, nor in successful completion for families with older children as compared to those with at least one child aged 0–5. ConclusionsThese results lend support to the use of the START model for all eligible families, regardless of the children’s ages. Future studies can examine more nuanced relationships to include the role of specific substances, child placement, and the role of family peer mentors.

Error estimates for finite element approximations of viscoelastic dynamics: The generalized Maxwell model

We prove error estimates for a finite element approximation of viscoelastic dynamics based on continuous Galerkin in space and time, both in energy norm and in L2 norm. The proof is based on an error representation formula using a discrete dual problem and a stability estimate involving the kinetic, elastic, and viscoelastic energies. To set up the dual error analysis and to prove the basic stability estimates, it is natural to formulate the problem as a first-order-in-time system involving evolution equations for the viscoelastic stress, the displacements, and the velocities. The equations for the viscoelastic stress can, however, be solved analytically in terms of the deviatoric strain velocity, and therefore, the viscoelastic stress can be eliminated from the system, resulting in a system for displacements and velocities.

Hybridization in meta-heuristic techniques for green layout design in the tyre manufacturing industry: An optimal analysis

To stop or lessen factory pollution, many academics in the field of study have produced a vast array of strategies to achieve optimization goals. But, it is unable to follow a uniform solution for all production facilities. In this research work, green layout design (GLD) is proposed to minimize total material handling cost (TMHC) and CO2 emissions. The green facility layout refers to the facility layout with minimum CO2 emissions and to eliminate unnecessary energy dissipation from material handling equipments & production machineries, as well as plant re-layout in-term on material handling cost. In this study context, a Lagrangian relaxation model has been used at the allocation level. It computes a suboptimal solution to the dual problem in order to obtain a feasible solution. This enhanced algorithm method iteratively tries to minimize the gap between the dual and feasible solutions on minimal of TMHC and CO2 emission rate. It has been experimentally simulated using the MATLAB (Matrix Laboratory) application and upgraded adaptive salp swarm optimization (ASSO), dragon fly optimization (DFO) and Hybrid (combination) of ASSO-DFO evolutionary optimization techniques. The primary focus of this implementation is to control material handling between departments or cells, production flow between departments, energy consumption (electrical and gas consumption for production), and manpower utilization within and across departments. This research has chosen an existing and acceptable designs from targeted tyre manufacturing company in South India. The hybrid ASSO-DFO implementation TMHC differs from ABC by 60%, DFO by 65%, 58% with simulated annealing (SA), and ASSO by 48%. Emission rate decreased by 26% ABC, 21% DFO, and 24% SA & 18% with ASSO. An average of 50% decrease in TMHC and 25% reduction of CO2 emission rate in GLD have been achieved.

The ethically significant difference between dual use and slippery slope arguments, in relation to CRISPR-Cas9: philosophical considerations and ethical challenges

Biomedical research, on the one hand, contributes to important goals from generation of knowledge about the human body to the development and testing of therapeutics of all kinds. On the other hand, it can produce serious and sometimes unforeseeable consequences. In the ethical analysis of these two aspects of biomedical research, two important argumentative strategies play a major role. First, slippery slope arguments are used to warn of potential risks and to highlight knowledge-based limitations. Second, a dual-use problem describes the challenge that already established techniques can be used for both morally wrong and morally right purposes. These two argumentative strategies appear to share several similarities, which will be investigated in this article. For this purpose, the article will first provide clear working definitions for both types of argument. This lays the foundation for the further ethical analysis. In a second step, and in order to investigate the similarities and differences of the argumentative strategies with an example from current ethical debates, CRISPR-Cas9, a currently very promising tool of genome editing, will be examined. The extent to which the possible applications of this genome editing tool can be addressed by slippery slope arguments or the dual use problem will be investigated. For this purpose, selected studies involving the use of CRISPR-Cas9 will be examined. Based on this two-step, analytic and example-based comparison of slippery-slope argumentation and dual-use considerations, the article will detail the ethically relevant difference between the two argumentative strategies and at the same time contribute to the ongoing ethical debate about CRISPR-Cas9.

Sliding methods for dual fractional nonlinear divergence type parabolic equations and the Gibbons’ conjecture

Abstract In this paper, we consider the general dual fractional parabolic problem ∂ t α u ( x , t ) + L u ( x , t ) = f ( t , u ( x , t ) ) in R n × R . ${\partial }_{t}^{\alpha }u\left(x,t\right)+\mathcal{L}u\left(x,t\right)=f\left(t,u\left(x,t\right)\right) \text{in} {\mathbb{R}}^{n}{\times}\mathbb{R}.$ We show that the bounded entire solution u satisfying certain one-direction asymptotic assumptions must be monotone increasing and one-dimensional symmetric along that direction under an appropriate decreasing condition on f. Our result here actually solves a well-known problem known as Gibbons’ conjecture in the setting of the dual fractional parabolic equations. To overcome the difficulties caused by the nonlocal divergence type operator L $\mathcal{L}$ and the Marchaud time derivative ∂ t α ${\partial }_{t}^{\alpha }$ , we introduce several new ideas. First, we derive a general weighted average inequality corresponding to the nonlocal operator L $\mathcal{L}$ , which plays a fundamental bridging role in proving maximum principles in unbounded domains. Then we combine these two essential ingredients to carry out the sliding method to establish the Gibbons’ conjecture. It is worth noting that our results are novel even for a special case of L $\mathcal{L}$ , the fractional Laplacian (−Δ) s , and the approach developed in this paper will be adapted to a broad range of nonlocal parabolic equations involving more general Marchaud time derivatives and more general non-local elliptic operators.

Semi-Proximal ADMM for Primal and Dual Robust Low-Rank Matrix Restoration from Corrupted Observations

The matrix nuclear norm minimization problem has been extensively researched in recent years due to its widespread applications in control design, signal and image restoration, machine learning, big data problems, and more. One popular model is nuclear norm minimization with the l2-norm fidelity term, but it is only effective for those problems with Gaussian noise. A nuclear norm minimization problem with the l1-norm fidelity term has been studied in this paper, which can deal with the problems with not only non-Gaussian noise but also Gaussian noise or their mixture. Moreover, it also keeps the efficiency for the noiseless case. Given the nonsmooth proposed model, we transform it into a separated form by introducing an auxiliary variable and solve it by the semi-proximal alternating direction method of multipliers (sPADMM). Furthermore, we first attempt to solve its dual problem by sPADMM. Then, the convergence guarantees for the aforementioned algorithms are given. Finally, some numerical studies are dedicated to show the robustness of the proposed model and the effectiveness of the presented algorithms.

Large monochromatic components in expansive hypergraphs

AbstractA result of Gyárfás [12] exactly determines the size of a largest monochromatic component in an arbitrary $r$ -colouring of the complete $k$ -uniform hypergraph $K_n^k$ when $k\geq 2$ and $k\in \{r-1,r\}$ . We prove a result which says that if one replaces $K_n^k$ in Gyárfás’ theorem by any ‘expansive’ $k$ -uniform hypergraph on $n$ vertices (that is, a $k$ -uniform hypergraph $G$ on $n$ vertices in which $e(V_1, \ldots, V_k)\gt 0$ for all disjoint sets $V_1, \ldots, V_k\subseteq V(G)$ with $|V_i|\gt \alpha$ for all $i\in [k]$ ), then one gets a largest monochromatic component of essentially the same size (within a small error term depending on $r$ and $\alpha$ ). As corollaries we recover a number of known results about large monochromatic components in random hypergraphs and random Steiner triple systems, often with drastically improved bounds on the error terms.Gyárfás’ result is equivalent to the dual problem of determining the smallest possible maximum degree of an arbitrary $r$ -partite $r$ -uniform hypergraph $H$ with $n$ edges in which every set of $k$ edges has a common intersection. In this language, our result says that if one replaces the condition that every set of $k$ edges has a common intersection with the condition that for every collection of $k$ disjoint sets $E_1, \ldots, E_k\subseteq E(H)$ with $|E_i|\gt \alpha$ , there exists $(e_1, \ldots, e_k)\in E_1\times \cdots \times E_k$ such that $e_1\cap \cdots \cap e_k\neq \emptyset$ , then the smallest possible maximum degree of $H$ is essentially the same (within a small error term depending on $r$ and $\alpha$ ). We prove our results in this dual setting.

A sublinear functional based approximated equivalence to optimality and duality for multiobjective programming in complex spaces

In this paper, we introduce a new approximation approach for a class of multiobjective programming problems in complex spaces and their duals. Using a sublinear functional, an approximated problem is constructed at a given feasible solution of the original problem. The equivalence between the solution of the considered multiobjective complex programming problem and its approximated problem is established by deriving the sufficiency theorem under the F-convexity assumption. An example showing this equivalence is also presented. Further, corresponding to the approximated problem, the Mond–Weir and Wolfe-type approximated dual problems are formulated. The duality results for the Mond–Weir and Wolfe-type dual problems are derived using the duality results established for the approximated Mond–Weir and Wolfe-type dual problems, respectively. The importance of the optimality conditions and proposed approximation approach is highlighted in a blind equalization problem in a communication system.

Computing the recession cone of a convex upper image via convex projection

It is possible to solve unbounded convex vector optimization problems (CVOPs) in two phases: (1) computing or approximating the recession cone of the upper image and (2) solving the equivalent bounded CVOP where the ordering cone is extended based on the first phase. In this paper, we consider unbounded CVOPs and propose an alternative solution methodology to compute or approximate the recession cone of the upper image. In particular, we relate the dual of the recession cone with the Lagrange dual of weighted sum scalarization problems whenever the dual problem can be written explicitly. Computing this set requires solving a convex (or polyhedral) projection problem. We show that this methodology can be applied to semidefinite, quadratic, and linear vector optimization problems and provide some numerical examples.

Scheduling with cardinality dependent unavailability periods

We consider non-preemptive scheduling problems on parallel identical machines where machines change their status from being available to being unavailable and vice versa along the time horizon. The particular form of unavailability we consider is when the starting time of each downtime depends upon the cardinality of the job subset processed on that machine since the previous downtime. We consider the problem of minimizing the makespan in such scenarios as well as its dual problem where we have a fixed common deadline of 1 and the goal is to minimize the number of machines for which there is a feasible schedule. We develop an EPTAS for the first variant and an AFPTAS for the second variant.

Prevalence of Selected Cardiovascular Risk Factors and Their Associated Factors among People Living with HIV/AIDS in India.

Low- and middle-income countries face the dual problem of infectious and non-infectious diseases. Persons living with HIV/AIDS (PLHIV) are also at risk of cardiovascular diseases. Hence, we did this study to determine the prevalence of cardiovascular risk factors (CVRF) among PLHIV and to find the factors associated with it. We carried out a cross-sectional analytical study among all adults aged ≥18 years registered at a facility-integrated anti-retroviral therapy center in Puducherry, India, from September 2016 to February 2018. After obtaining informed consent, we interviewed the participants to assess physical activity, alcohol, and tobacco use. We measured weight, height, abdominal circumference, and blood pressure, with biochemical investigations such as blood glucose and lipid profile. Of the total 316 adults PLHIV studied, the most common cardiovascular risk factor found was dyslipidemia (82.7%), followed by inadequate physical activity (74.4%). Other behavioral risk factors studied, such as current tobacco use and current alcohol use, showed a prevalence of 12.8% and 5.4%, respectively, among male participants. The prevalence of hypertension among adult PLHIV studied was 15.8%, and diabetes was 12.3%. In the multivariate analysis, diabetes, and hypertension were significantly associated with age and literacy. Obesity was found to be associated with diabetes and abdominal obesity with dyslipidemia. Dyslipidemia was the most common cardiovascular risk factor, followed by inadequate physical inactivity among PLHIV. Regular screening with blood glucose, blood pressure, and lipid profile, and timely cross-referrals can help in the early detection of CVRF among PLHIV and hence improve their quality of life through appropriate treatment.

Revitalising The Regulation of Zakat Institutions in Indonesia to Achieve Economic Justice

This research aims to provide a solution to the dual function problem of BAZNAS. The problem required the regulatory aspect improvement. Indentifiying national business governance issues, improving the regulation of Law No. 23/2011 on zakat management is crucial. The separation of the two functions of BAZNAS will also reduce the risk of misuse of zakat funds which can be significantly reduced, an independent regulator can conduct monitoring and auditing more effectively. This research uses qualitative method or conceptual review of secondary data through literature study approach. The purpose of the research is to help identify, analyze, and overcome problems and challenges faced in society. The results of the study to achieve economic justice through zakat, the BAZNAS institution needs to separate its function as implementer. To achieve economic justice through zakat, BAZNAS needs to separate its functions as implementer. This separation of functions for BAZNAS will also reduce the risk of misuse of zakat funds which can be reduced significantly. Meanwhile, regulations regarding zakat can be more optimally carried out by the Ministry of Religion independently in monitoring and auditing more effectively, thereby reducing the potential for abuse by implementers.

Research on dual robot collaboration method based on improved double ant colony algorithm

Purpose This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations. Design/methodology/approach A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy. Findings The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems. Originality/value This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

Limited packings: Related vertex partitions and duality issues

A k-limited packing partition (kLP partition) of a graph G is a partition of V(G) into k-limited packing sets. We consider the kLP partitions with minimum cardinality (with emphasis on k=2). The minimum cardinality is called kLP partition number of G and denoted by χ×k(G). This problem is the dual problem of k-tuple domatic partitioning as well as a generalization of the well-studied 2-distance coloring problem in graphs.We give the exact value of χ×2 for trees and bound it for general graphs. A section of this paper is devoted to the dual of this problem, where we give a solution to an open problem posed in 1998. We also revisit the total limited packing number in this paper and prove that the problem of computing this parameter is NP-hard even for some special families of graphs. We give some inequalities concerning this parameter and discuss the difference between 2TLP number and 2LP number with emphasis on trees.

Quantum annealing-driven branch and bound for the single machine total weighted number of tardy jobs scheduling problem

In the paper we present a new approach to solving NP-hard problems of discrete optimization adapted to the architecture of quantum processors (QPU, Quantum Processor Unit) implementing hardware quantum annealing. This approach is based on the use of the quantum annealing metaheuristic in the exact branch and bound algorithm to compute the lower and upper bounds of the objective function. To determine the lower bound, a new method of defining the Lagrange function for the dual problem (the generalized discrete knapsack problem) was used, the value of which is calculated on the QPU of a quantum machine. In turn, to determine the upper bound, we formulate an appropriate task in the form of binary quadratic programming with constraints.Despite the fact that the results generated by the quantum machine are probabilistic, the hybrid method of algorithm construction proposed in the paper, using alternately a CPU and QPU, guarantees the optimal solution. As a case study we consider the NP-hard single machine scheduling problem with minimizing the weighted number of tardy jobs. The performed computational experiments showed that optimal solutions were already obtained in the root of the solution tree, and the values of the lower and upper bounds differ by only a few percent.

A randomized sparse Kaczmarz solver for sparse signal recovery via minimax‐concave penalty

The randomized sparse Kaczmarz (RSK) method is an algorithm used to calculate sparse solutions for the basis pursuit problem. In this paper, we propose an algorithm framework for computing sparse solutions of linear systems, which includes the sparse Kaczmarz and sparse block Kaczmarz algorithms. In order to overcome the limitations of the penalty, we design an effective and new randomized sparse Kaczmarz algorithm (RSK‐MCP) based on the non‐convex minimax‐concave penalty (MCP) in sparse signal reconstruction. Additionally, we prove that the RSK‐MCP algorithm is equivalent to the randomized coordinate descent method for the corresponding dual problem. Based on this result, we demonstrate that the RSK‐MCP algorithm exhibits linear convergence, meaning it converges to a sparse solution of the MCP model when the regularization of MCP is a strongly convex function. Numerical experiments indicate that the RSK‐MCP algorithm outperforms RSK‐L1 in terms of both efficiency and accuracy.

Multijoints and Factorisation

We solve the dual multijoint problem and prove the existence of so-called factorisations for arbitrary fields and multijoints of kj\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$k_j$$\\end{document}-planes. More generally, we deduce a discrete analogue of a theorem due in essence to Bourgain and Guth. Our result is a universal statement which describes a property of the discrete wedge product without any explicit reference to multijoints and is stated as follows: Suppose that k1+…+kd=n\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$k_1 + \\ldots + k_d = n$$\\end{document}. There is a constant C=C(n)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$C=C(n)$$\\end{document} so that for any field F\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathbb {F}$$\\end{document} and for any finitely supported function S:Fn→R≥0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$S : \\mathbb {F}^n \\rightarrow \\mathbb {R}_{\\ge 0}$$\\end{document}, there are factorising functions skj:Fn×Gr(kj,Fn)→R≥0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$s_{k_j} : \\mathbb {F}^n\ imes {{\\,\\mathrm{{Gr}}\\,}}(k_j, \\mathbb {F}^n)\\rightarrow \\mathbb {R}_{\\ge 0}$$\\end{document} such that V1∧⋯∧VdSpd≤∏j=1dskjp,Vj,\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\begin{aligned} \\left( V_1 \\wedge \\cdots \\wedge V_d\\right) S\\left( p\\right) ^d \\le \\prod _{j=1}^d s_{k_j}\\left( p, V_j\\right) , \\end{aligned}$$\\end{document}for every p∈Fn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p\\in \\mathbb {F}^n$$\\end{document} and every tuple of planes Vj∈Gr(kj,Fn)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V_j\\in {{\\,\\mathrm{{Gr}}\\,}}(k_j, \\mathbb {F}^n)$$\\end{document}, and ∑p∈πjs(p,e(πj))=CSd,\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\begin{aligned} \\sum _{p\\in \\pi _j} s(p, e(\\pi _j)) =C \\left| \\left| S\\right| \\right| _d, \\end{aligned}$$\\end{document}for every kj\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$k_j$$\\end{document}-plane πj⊂Fn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi _j\\subset \\mathbb {F}^n$$\\end{document}, where e(πj)∈Gr(kj,Fn)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$e(\\pi _j)\\in {{\\,\\mathrm{{Gr}}\\,}}(k_j,\\mathbb {F}^n)$$\\end{document}, is the translate of πj\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi _j$$\\end{document} that contains the origin and ∧\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\wedge $$\\end{document} denotes the discrete wedge product.

Factors affecting implementation of digital lean in healthcare in the post-COVID world – mixed-method approach

PurposeDigital lean implementation can solve the dual problem of stagnating quality and rising costs in healthcare. Although technology adoption in healthcare has increased in the post-COVID world, value unlocking using technology needs a well-thought-out approach to achieve success. This paper provides a prescriptive framework for successfully implementing digital lean in healthcare.Design/methodology/approachThis study uses a mixed-method approach to achieve three research objectives. Whilst it uses a narrative review to identify the enablers, it uses qualitative thematic analysis techniques to categorise them into factors. The study utilises the delphi method for the thematic grouping of the enablers in the broader groups. The study used an advanced ordinal priority approach (OPA) to prioritise these factors. Finally, the study uses concordance analysis to assess the reliability of group decision-making.FindingsThe study found that 20 identified enablers are rooted in practice factors, followed by human resource management (HRM) factors, customer factors, leadership factors and technology factors. These results further counter the myth that technology holds the utmost significance in implementing digital lean in healthcare and found the equal importance of factors related to people, customers, leadership and best practices such as benchmarking, continuous improvement and change management.Originality/valueThe study is the first of its kind, providing the prescriptive framework for implementing digital lean in healthcare. The findings are useful for healthcare professionals and health policymakers.