Convergence and divergence dynamics in British and French business schools: how will the pressure for accreditation influence these dynamics?

This paper focuses on convergence and divergence dynamics among leading British and French business schools and explores how the pressure for accreditation influences these dynamics. We illustrate that despite historical differences in approaches to management education in Britain and France, these approaches have converged partly based on the influence of the American model of management education but more recently through the pursuit of accreditation, in particular from the Association to Advance Collegiate Schools of Business and the European Quality Improvement Standard. We explore these dynamics through the application of the resource-based view of the firm and institutional theory and suggest that, whilst achieving accreditation is a necessary precursor for international competition, it is no longer a form of competitive advantage. The pursuit of accreditation has fostered a form of competitive mimicry reducing national distinctiveness. The resource-based view of the firm suggests that the top schools need a more heterogeneous approach that is not easily replicable if they are to outperform the competitors. Consequently, the convergence of management education in Britain and France will become a new impetus for divergence. We assert that future growth and competitive advantage might be better achieved through the reassertion of national, regional and local cultural characteristics. © 2013 British Academy of Management.

A new algorithm to design minimal multi-functional observers for linear systems

Designing minimum possible order (minimal) observers for Multi-Input Multi-Output (MIMO) linear systems have always been an interesting subject. In this paper, a new methodology to design minimal multi-functional observers for Linear Time-Invariant (LTI) systems is proposed. The approach is applicable, and it also helps in regulating the convergence rate of the observed functions. It is assumed that the system is functional observable or functional detectable, which is less conservative than assuming the observability or detectability of the system. To satisfy the minimality of the observer, a recursive algorithm is provided that increases the order of the observer by appending the minimum required auxiliary functions to the desired functions that are going to be estimated. The algorithm increases the number of functions such that the necessary and sufficient conditions for the existence of a functional observer are satisfied. Moreover, a new methodology to solve the observer design interconnected equations is elaborated. Our new algorithm has advantages with regard to the other available methods in designing minimal order functional observers. Specifically, it is compared with the most common schemes, which are transformation based. Using numerical examples it is shown that under special circumstances, the conventional methods have some drawbacks. The problem partly lies in the lack of sufficient numerical degrees of freedom proposed by the conventional methods. It is shown that our proposed algorithm can resolve this issue. A recursive algorithm is also proposed to summarize the observer design procedure. Several numerical examples and simulation results illustrate the efficacy, superiority and different aspects of the theoretical findings.

Adaptive fuzzy multi-surface sliding control of multiple-input and multiple-output autonomous flight systems

In this study, we proposed an adaptive fuzzy multi-surface sliding control (AFMSSC) for trajectory tracking of 6 degrees of freedom inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). It is shown that an adaptive fuzzy logic-based function approximator can be used to estimate the system uncertainties and an iterative multi-surface sliding control design can be carried out to control flight. Using AFMSSC on MIMO autonomous flight systems creates confluent control that can account for both matched and mismatched uncertainties, system disturbances and excitation in internal dynamics. It is proved that the AFMSSC system guarantees asymptotic output tracking and ultimate uniform boundedness of the tracking error. Simulation results are presented to validate the analysis.

Global finite-time stabilisation for a class of stochastic nonlinear systems by output feedback

In this paper, the problem of global finite-time stabilisation by output feedback is considered for a class of stochastic nonlinear systems. First, based on homogeneous systems theory and the adding a power integrator technique, a homogeneous reduced order observer and control law are constructed in a recursive manner for the nominal system. Then, the homogeneous domination approach is used to deal with the nonlinearities in drift and diffusion terms; it is shown that the proposed output-feedback control law can guarantee that the closed-loop system is global finite-time stable in probability. Finally, simulation examples are carried out to demonstrate the effectiveness of the proposed control scheme.

Energy consumption and output: time series evidence from non-OECD developing countries

Statistically significant association between energy consumption and economic growth is now well established in the literature. However, it still remains an unsettled issue whether economic growth is the cause or effect of energy consumption. The importance of identifying the direction of causality emanates from its relevance in national policy-making issues regarding energy conservation. Energy conservationissue is more important when energy acts as a contributing factor in economic growth than when it is used as a result of higher economic growth. In this backdrop, it is justified to search causal relationship between energy consumption and national output (GDP) of those countries that are expected to have higher energy consumption in future. Evidence shows that countries classified as non-OECD Asia will have the highest growth in energy consumption (3.7 percent) over the period 2003-2030. This forecasted energy consumption in these countries will have significant policy implication in the area of energy conservation. Hence, the present paper attempts to identify the direction of causality between energy consumption and output in the context of six major energy dependent non-OECD Asian countries.However, since the traditional bivariate approach suffers from omitted variable problems (Stern 1993, Masih and Masih, 1996 and Asafu-Adjaye, 2000), this paper employs a trivariate demand side approach consisting of energy consumption, income and prices. The countries selected for this purpose are Bangladesh, China, India, Malaysia, Pakistan and Thailand. Moreover, according to the Energy Information Administration (EIA) data of 2005, these six countries contribute 81.35% of the energyconsumption by all non-OECD Asian countries (aggregate energy consumption of 2005 by all non-OECD Asian countries is 113.60 quadrillion BTU while for these six countries alone the consumption is 92.42 quadrillion BTU).

Testing for convergence in carbon dioxide emissions using a century of panel data

This paper tests the convergence in per-capita carbon dioxide emissions for a collection of developed and developing countries using data spanning the period 1870-2002. For this purpose, three recently developed panel unit root tests that permit for dependence among the individual countries are employed. The results lend strong support in favor of convergence for the panel as a whole. Estimates of the speed of this convergence is also provided. © 2007 Springer Science+Business Media B.V.

Tough decisions: Reproductive timing and output vary with individuals' physiology, behavior and past success in a social opportunistic breeder

This article is part of a Special Issue SBN 2014. Photoperiod and the hormonal response it triggers are key determinants of reproductive timing in birds. However, other cues and physiological traits may permit flexibility in the timing of breeding and perhaps facilitate adaptation to global change. Opportunistic breeders are excellent models to study the adaptive significance of this flexibility, especially at the individual level. Here, we sought to quantify whether particular male physiological and behavioral traits were linked to reproductive timing and output in wild-derived zebra finches. We repeatedly assessed male stress-induced corticosterone levels (CORT), basal metabolic rate (BMR), and activity before releasing them into outdoor aviaries and quantifying each pair's breeding timing, investment, and output over a seven-month period. Despite unlimited access to food and water, the colony breeding activity occurred in waves, probably due to interpair social stimulations. Pairs adjusted their inter-clutch interval and clutch size to social and temperature cues, respectively, but only after successful breeding attempts, suggesting a facultative response to external cues. When these effects were controlled for statistically or experimentally, breeding intervals were repeatable within individuals across reproductive attempts. In addition, males' first laying date and total offspring production varied with complex interactions between pre-breeding CORT, BMR and activity levels. These results suggest that no one trait is under selection but that, instead, correlational selection acts on hormone levels, metabolism, and behavior. Together our results suggest that studying inter-individual variation in breeding strategy and their multiple physiological and behavioral underpinnings may greatly improve our understanding of the mechanisms underlying the evolution of breeding decisions.

Eating marshmallows reduces ileostomy output: a randomized crossover trial

AIM: Anecdotally, many ostomates believe that eating marshmallows can reduce ileostomy effluent. There is a plausible mechanism for this, as the gelatine contained in marshmallows may thicken small bowel fluid, but there is currently no evidence that this is effective. METHOD: This was a randomized crossover trial. Adult patients with well-established ileostomies were included. Ileostomy output was measured for 1 week during which three marshmallows were consumed three times daily, and for one control week where marshmallows were not eaten. There was a 2-day washout period. Patients were randomly allocated to whether the control or intervention week occurred first. In addition, a questionnaire was administered regarding patient's subjective experience of their ileostomy function. RESULTS: Thirty-one participants were recruited; 28 completed the study. There was a median reduction in ileostomy output volume of 75 ml per day during the study period (P = 0.0054, 95% confidence interval 23.4-678.3) compared with the control week. Twenty of 28 subjects (71%) experienced a reduction in their ileostomy output, two had no change and six reported an increase. During the study period, participants reported fewer ileostomy bag changes (median five per day vs six in the control period, P = 0.0255). Twenty of 28 (71%) reported that the ileostomy effluent was thicker during the study week (P = 0.023). Overall 19 (68%) participants stated they would use marshmallows in the future if they wanted to reduce or thicken their ileostomy output. CONCLUSION: Eating marshmallows leads to a small but statistically significant reduction in ileostomy output.

Multi-output interval type-2 fuzzy logic system for protein secondary structure prediction

A new multi-output interval type-2 fuzzy logic system (MOIT2FLS) is introduced for protein secondary structure prediction in this paper. Three outputs of the MOIT2FLS correspond to three structure classes including helix, strand (sheet) and coil. Quantitative properties of amino acids are employed to characterize twenty amino acids rather than the widely used computationally expensive binary encoding scheme. Three clustering tasks are performed using the adaptive vector quantization method to construct an equal number of initial rules for each type of secondary structure. Genetic algorithm is applied to optimally adjust parameters of the MOIT2FLS. The genetic fitness function is designed based on the Q3 measure. Experimental results demonstrate the dominance of the proposed approach against the traditional methods that are Chou-Fasman method, Garnier-Osguthorpe-Robson method, and artificial neural network models.

Hybrid technique of ant colony and particle swarm optimization for short term wind energy forecasting

Wind farms are producing a considerable portion of the world renewable energy. Since the output power of any wind farm is highly dependent on the wind speed, the power extracted from a wind park is not always a constant value. In order to have a non-disruptive supply of electricity, it is important to have a good scheduling and forecasting system for the energy output of any wind park. In this paper, a new hybrid swarm technique (HAP) is used to forecast the energy output of a real wind farm located in Binaloud, Iran. The technique consists of the hybridization of the ant colony optimization (ACO) and particle swarm optimization (PSO) which are two meta-heuristic techniques under the category of swarm intelligence. The hybridization of the two algorithms to optimize the forecasting model leads to a higher quality result with a faster convergence profile. The empirical hourly wind power output of Binaloud Wind Farm for 364 days is collected and used to train and test the prepared model. The meteorological data consisting of wind speed and ambient temperature is used as the inputs to the mathematical model. The results indicate that the proposed technique can estimate the output wind power based on the wind speed and the ambient temperature with an MAPE of 3.513%.

A framework for convergence of cloud services and Internet of things

Today, Cloud Computing and the Internet of things are two "major forces" that drive the development of new Information Technology (IT) solutions. Many Internet of things (IoT) based large-scale applications rely on a cloud platform for data processing and storage. However, big data generated or collected by large-scale geo-distributed devices needs to be transferred to the cloud, often becoming a bottleneck for the system. In this paper, we propose a framework that integrates popular cloud services with a network of loT devices. In the framework, novel methods have been designed for reliable and efficient data transportation. This framework provides a convergence of cloud services and devices that will ease the development of loT based, cloud-enabled applications. We have implemented a prototype of the framework to demonstrate the convergence of popular cloud services and IoT technologies.

On unknown-input functional observability of linear systems

Finding the least possible order of a stable Unknown-Input Functional Observer (UIFO) has always been a challenge in observer design theory. A practical recursive algorithm is proposed in this technical note to design a minimal multi-functional observer for multi-input multi-output (MIMO) linear time-invariant (LTI) systems with unknown-inputs. The concept of unknown-input functional observability is introduced,and it is used as a certificate of the convergence of our algorithm. The proposed procedure looks for a number of additional auxiliary functions to be augmented to the original functions desired for reconstruction. The resulting UIFO is proper, and minimal (of minimum possible order). Moreover, the algorithm does not need the system to be unknown-input observable. A numerical example shows the procedure as well as the effectiveness of the proposed algorithm.

Nonlinear adaptive excitation controller design for multimachine power systems

This paper presents a nonlinear adaptive excitation control scheme to enhance the dynamic stability of multimachine power systems. The proposed controller is designed based on the adaptive backstepping technique where the mechanical power input to the generators and the damping coefficient of each generator are considered as unknown. These unknown quantities are estimated through the adaption laws. The adaption laws are obtained from the formulation of Lyapunov functions which guarantee the convergence of different physical quantities of generators such as the relative speed, terminal voltage, and electrical power output. The proposed scheme is evaluated by applying a three-phase short-circuit fault at one of the key transmission lines in an 11-bus test power system and compared with an existing backstepping controller and conventional power system stabilizer (CPSS). Simulation results show that the proposed scheme is much more effective than existing controllers.

Nonlinear controller design for vehicle-to-grid systems with output LCL filters

This paper presents a nonlinear controller design for vehicle-to-grid (V2G) systems with LCL output filters. The V2G systems are modeled with LCL output filters in order to eliminate harmonics for improving power qualities and the nonlinear controller is designed based on the feedback linearization. The feasibility of using the appropriate feedback linearization approaches, either partial or exact, is also investigated through the feedback linearizability of V2G systems. In this paper, partial feedback linearization is used to design the controller with a capability of sharing both active and reactive power in V2G systems. The performance of the proposed controller controller is evaluated on a single-phase full-bridge converter-based V2G system with an LCL output filter and compared to that of without any filter. Simulation results clearly demonstrate the harmonic elimination capabilities of the proposed V2G structure with the proposed control scheme.