7,064 research outputs found
The selfish signifier: meaning, virulence and transmissibility in a management fashion
Purpose. Management fashions can be, and have been, conceptualized as narrative elements competing for replication and resources in the wider managerial discourse. Most wax and wane through a life cycle. Some achieve an extended place and even a transition to quasi permanent institutions. Facilities / Facility Management (FM) is one such example.
Design/methodology/approach. The case draws FMâs history since 1968 and asks whether it is compatible with recent and classic (Darwin 1871) thoughts on cultural evolution as a selection process between competing discourses.
Findings. Several properties of that history are argued as compatible with the theoretical stance taken particularly the mutation of the syntactic content to suit local circumstances and the dilution of the termâs intent. Success attributes in the selective competition include contingency, securing an organizational home and mutability (what was represented became, more operational, less virulent but in the process more transmissible). In spreading globally the signifier / meme FM also proved mutatable to local managerial discourses.
Originality/value The study supports a developing paradigm that it is possible to view organizations as ecologies of variously, memes, signifiers, narratives, representations or discourses. All five terms are shown to have been used to make similar significations by different authors. It shows how a natural history of narrative memes can be constructed
The Institute for Fiscal Studies Report: English Council Funding: Whatâs Happened and Whatâs Next?
The article reviews the recent Institute for Fiscal Studies (IfFS) report, English Council Funding: Whatâs Happened and Whatâs Next. The article provides an overview of the main themesand ïŹndings of the report which examines the consequences of a sustained period of austerity for English local government and the impact of austerity on certain key council services.The article explores what the report has to say about the way councils have responded to reductions in government funding and the strategies they have developed to protect certain frontline services. The article reviews the suggestions made in the IfFS report for changing English local government funding and ïŹnds that they reïŹect a form of centralist thinking which lacks a radical edge when it comes to reform
Stability and Performance Verification of Optimization-based Controllers
This paper presents a method to verify closed-loop properties of
optimization-based controllers for deterministic and stochastic constrained
polynomial discrete-time dynamical systems. The closed-loop properties amenable
to the proposed technique include global and local stability, performance with
respect to a given cost function (both in a deterministic and stochastic
setting) and the gain. The method applies to a wide range of
practical control problems: For instance, a dynamical controller (e.g., a PID)
plus input saturation, model predictive control with state estimation, inexact
model and soft constraints, or a general optimization-based controller where
the underlying problem is solved with a fixed number of iterations of a
first-order method are all amenable to the proposed approach.
The approach is based on the observation that the control input generated by
an optimization-based controller satisfies the associated Karush-Kuhn-Tucker
(KKT) conditions which, provided all data is polynomial, are a system of
polynomial equalities and inequalities. The closed-loop properties can then be
analyzed using sum-of-squares (SOS) programming
A Parametric Non-Convex Decomposition Algorithm for Real-Time and Distributed NMPC
A novel decomposition scheme to solve parametric non-convex programs as they
arise in Nonlinear Model Predictive Control (NMPC) is presented. It consists of
a fixed number of alternating proximal gradient steps and a dual update per
time step. Hence, the proposed approach is attractive in a real-time
distributed context. Assuming that the Nonlinear Program (NLP) is
semi-algebraic and that its critical points are strongly regular, contraction
of the sequence of primal-dual iterates is proven, implying stability of the
sub-optimality error, under some mild assumptions. Moreover, it is shown that
the performance of the optimality-tracking scheme can be enhanced via a
continuation technique. The efficacy of the proposed decomposition method is
demonstrated by solving a centralised NMPC problem to control a DC motor and a
distributed NMPC program for collaborative tracking of unicycles, both within a
real-time framework. Furthermore, an analysis of the sub-optimality error as a
function of the sampling period is proposed given a fixed computational power.Comment: 16 pages, 9 figure
An Alternating Trust Region Algorithm for Distributed Linearly Constrained Nonlinear Programs, Application to the AC Optimal Power Flow
A novel trust region method for solving linearly constrained nonlinear
programs is presented. The proposed technique is amenable to a distributed
implementation, as its salient ingredient is an alternating projected gradient
sweep in place of the Cauchy point computation. It is proven that the algorithm
yields a sequence that globally converges to a critical point. As a result of
some changes to the standard trust region method, namely a proximal
regularisation of the trust region subproblem, it is shown that the local
convergence rate is linear with an arbitrarily small ratio. Thus, convergence
is locally almost superlinear, under standard regularity assumptions. The
proposed method is successfully applied to compute local solutions to
alternating current optimal power flow problems in transmission and
distribution networks. Moreover, the new mechanism for computing a Cauchy point
compares favourably against the standard projected search as for its activity
detection properties
Analytics and complexity: learning and leading for the future
There is growing interest in the application of learning analytics to manage, inform and improve learning and teaching within higher education. In particular, learning analytics is seen as enabling data-driven decision making as universities are seeking to respond a range of significant challenges that are reshaping the higher education landscape. Experience over four years with a project exploring the use of learning analytics to improve learning and teaching at a particular university has, however, revealed a much more complex reality that potentially limits the value of some analytics-based strategies. This paper uses this experience with over 80,000 students across three learning management systems, combined with literature from complex adaptive systems and learning analytics to identify the source and nature of these limitations along with a suggested path forward
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