918 resultados para [JEL:P20] Economic Systems - Socialist Systems and Transitional Economies - General


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The main objective of this study is to revisit the fundamental postulations of autopoietic self-production wrapped within the autopoietic six-point key and to investigate whether or not firms as specific social systems can be treated as autopoietic unities. In order to do so firms have to be defined as simple and composite unities whereupon their boundaries have to be clearly identifiable. The test of social autopoiesis reveals that firms can be viewed as autopoietic social systems that exist in the communicative space with employees' firm-specific communicative sub-domains as their components. Furthermore, it is argued that the social reification of autopoiesis (autokoinopoiesis) in firms is quintessentially interconnected with physical autopoiesis of their employees (autophysiopoiesis). Discontiguous focus on productivity as firms' obvious physical implication may thus be upgraded by a very social nature of ideactivity, firms' only real survival force.

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Africa is thought to be the region most vulnerable to the impacts of climate variability and change. Agriculture plays a dominant role in supporting rural livelihoods and economic growth over most of Africa. Three aspects of the vulnerability of food crop systems to climate change in Africa are discussed: the assessment of the sensitivity of crops to variability in climate, the adaptive capacity of farmers, and the role of institutions in adapting to climate change. The magnitude of projected impacts of climate change on food crops in Africa varies widely among different studies. These differences arise from the variety of climate and crop models used, and the different techniques used to match the scale of climate model output to that needed by crop models. Most studies show a negative impact of climate change on crop productivity in Africa. Farmers have proved highly adaptable in the past to short- and long-term variations in climate and in their environment. Key to the ability of farmers to adapt to climate variability and change will be access to relevant knowledge and information. It is important that governments put in place institutional and macro-economic conditions that support and facilitate adaptation and resilience to climate change at local, national and transnational level.

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Building services are worth about 2% GDP and are essential for the effective and efficient operations of the building. It is increasingly recognised that the value of a building is related to the way it supports the client organisation’s ongoing business operations. Building services are central to the functional performance of buildings and provide the necessary conditions for health, well-being, safety and security of the occupants. They frequently comprise several technologically distinct sub-systems and their design and construction requires the involvement of numerous disciplines and trades. Designers and contractors working on the same project are frequently employed by different companies. Materials and equipment is supplied by a diverse range of manufacturers. Facilities managers are responsible for operation of the building service in use. The coordination between these participants is crucially important to achieve optimum performance, but too often is neglected. This leaves room for serious faults. The need for effective integration is important. Modern technology offers increasing opportunities for integrated personal-control systems for lighting, ventilation and security as well as interoperability between systems. Opportunities for a new mode of systems integration are provided by the emergence of PFI/PPP procurements frameworks. This paper attempts to establish how systems integration can be achieved in the process of designing, constructing and operating building services. The essence of the paper therefore is to envisage the emergent organisational responses to the realisation of building services as an interactive systems network.

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The transport of stratospheric air into the troposphere within deep convection was investigated using the Met Office Unified Model version 6.1. Three cases were simulated in which convective systems formed over the UK in the summer of 2005. For each of these three cases, simulations were performed on a grid having 4 km horizontal grid spacing in which the convection was parameterized and on a grid having 1 km horizontal grid spacing, which permitted explicit representation of the largest energy-containing scales of deep convection. Cross-tropopause transport was diagnosed using passive tracers that were initialized above the dynamically defined tropopause (2 potential vorticity unit surface) with a mixing ratio of 1. Although the synoptic-scale environment and triggering mechanisms varied between the cases, the total simulated transport was similar in all three cases. The total stratosphere-to-troposphere transport over the lifetime of the convective systems ranged from 25 to 100 kg/m2 across the simulated convective systems and resolutions, which corresponds to ∼5–20% of the total mass located within a stratospheric column extending 2 km above the tropopause. In all simulations, the transport into the lower troposphere (defined as below 3.5 km elevation) accounted for ∼1% of the total transport across the tropopause. In the 4 km runs most of the transport was due to parameterized convection, whereas in the 1 km runs the transport was due to explicitly resolved convection. The largest difference between the simulations with different resolutions occurred in the one case of midlevel convection considered, in which the total transport in the 1 km grid spacing simulation with explicit convection was 4 times that in the 4 km grid spacing simulation with parameterized convection. Although the total cross-tropopause transport was similar, stratospheric tracer was deposited more deeply to near-surface elevations in the convection-parameterizing simulations than in convection-permitting simulations.

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A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

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Air distribution systems are one of the major electrical energy consumers in air-conditioned commercial buildings which maintain comfortable indoor thermal environment and air quality by supplying specified amounts of treated air into different zones. The sizes of air distribution lines affect energy efficiency of the distribution systems. Equal friction and static regain are two well-known approaches for sizing the air distribution lines. Concerns to life cycle cost of the air distribution systems, T and IPS methods have been developed. Hitherto, all these methods are based on static design conditions. Therefore, dynamic performance of the system has not been yet addressed; whereas, the air distribution systems are mostly performed in dynamic rather than static conditions. Besides, none of the existing methods consider any aspects of thermal comfort and environmental impacts. This study attempts to investigate the existing methods for sizing of the air distribution systems and proposes a dynamic approach for size optimisation of the air distribution lines by taking into account optimisation criteria such as economic aspects, environmental impacts and technical performance. These criteria have been respectively addressed through whole life costing analysis, life cycle assessment and deviation from set-point temperature of different zones. Integration of these criteria into the TRNSYS software produces a novel dynamic optimisation approach for duct sizing. Due to the integration of different criteria into a well- known performance evaluation software, this approach could be easily adopted by designers in busy nature of design. Comparison of this integrated approach with the existing methods reveals that under the defined criteria, system performance is improved up to 15% compared to the existing methods. This approach is interpreted as a significant step forward reaching to the net zero emission building in future.

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We consider two weakly coupled systems and adopt a perturbative approach based on the Ruelle response theory to study their interaction. We propose a systematic way of parameterizing the effect of the coupling as a function of only the variables of a system of interest. Our focus is on describing the impacts of the coupling on the long term statistics rather than on the finite-time behavior. By direct calculation, we find that, at first order, the coupling can be surrogated by adding a deterministic perturbation to the autonomous dynamics of the system of interest. At second order, there are additionally two separate and very different contributions. One is a term taking into account the second-order contributions of the fluctuations in the coupling, which can be parameterized as a stochastic forcing with given spectral properties. The other one is a memory term, coupling the system of interest to its previous history, through the correlations of the second system. If these correlations are known, this effect can be implemented as a perturbation with memory on the single system. In order to treat this case, we present an extension to Ruelle's response theory able to deal with integral operators. We discuss our results in the context of other methods previously proposed for disentangling the dynamics of two coupled systems. We emphasize that our results do not rely on assuming a time scale separation, and, if such a separation exists, can be used equally well to study the statistics of the slow variables and that of the fast variables. By recursively applying the technique proposed here, we can treat the general case of multi-level systems.

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A characterization of observability for linear time-varying descriptor systemsE(t)x(t)+F(t)x(t)=B(t)u(t), y(t)=C(t)x(t) was recently developed. NeitherE norC were required to have constant rank. This paper defines a dual system, and a type of controllability so that observability of the original system is equivalent to controllability of the dual system. Criteria for observability and controllability are given in terms of arrays of derivatives of the original coefficients. In addition, the duality results of this paper lead to an improvement on a previous fundamental structure result for solvable systems of the formE(t)x(t)+F(t)x(t)=f(tt).

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The concepts of on-line transactional processing (OLTP) and on-line analytical processing (OLAP) are often confused with the technologies or models that are used to design transactional and analytics based information systems. This in some way has contributed to existence of gaps between the semantics in information captured during transactional processing and information stored for analytical use. In this paper, we propose the use of a unified semantics design model, as a solution to help bridge the semantic gaps between data captured by OLTP systems and the information provided by OLAP systems. The central focus of this design approach is on enabling business intelligence using not just data, but data with context.

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The three decades of on-going executives’ concerns of how to achieve successful alignment between business and information technology shows the complexity of such a vital process. Most of the challenges of alignment are related to knowledge and organisational change and several researchers have introduced a number of mechanisms to address some of these challenges. However, these mechanisms pay less attention to multi-level effects, which results in a limited un-derstanding of alignment across levels. Therefore, we reviewed these challenges from a multi-level learning perspective and found that business and IT alignment is related to the balance of exploitation and exploration strategies with the intellec-tual content of individual, group and organisational levels.

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Mobile-to-mobile (M-to-M) communications are expected to play a crucial role in future wireless systems and networks. In this paper, we consider M-to-M multiple-input multiple-output (MIMO) maximal ratio combining system and assess its performance in spatially correlated channels. The analysis assumes double-correlated Rayleigh-and-Lognormal fading channels and is performed in terms of average symbol error probability, outage probability, and ergodic capacity. To obtain the receive and transmit spatial correlation functions needed for the performance analysis, we used a three-dimensional (3D) M-to-M MIMO channel model, which takes into account the effects of fast fading and shadowing. The expressions for the considered metrics are derived as a function of the average signal-to-noise ratio per receive antenna in closed-form and are further approximated using the recursive adaptive Simpson quadrature method. Numerical results are provided to show the effects of system parameters, such as distance between antenna elements, maximum elevation angle of scatterers, orientation angle of antenna array in the x–y plane, angle between the x–y plane and the antenna array orientation, and degree of scattering in the x–y plane, on the system performance. Copyright © 2011 John Wiley & Sons, Ltd.

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In this paper, we investigate the joint effects of high-power amplifier (HPA) nonlinearity, in-phase/quadrature-phase (I/Q) imbalance and crosstalk, on the performance of multiple-input multiple-output (MIMO) transmit beamforming (TB) systems, and propose a compensation method for the three impairments together. The performance of the MIMO TB system equipped with the proposed compensation scheme is evaluated in terms of average symbol error probability and capacity when transmissions are performed over uncorrelated Rayleigh fading channels. Numerical results are provided and show the effects on performance of several system parameters, namely, the HPA parameters, image-leakage ratio, crosstalk, numbers of antennas, length of pilot symbols and phase-shift keying modulation order.

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The financial crisis of 2007-2009 and the subsequent reaction of the G20 have created a new global regulatory landscape. Within the EU, change of regulatory institutions is ongoing. The research objective of this study is to understand how institutional changes to the EU regulatory landscape may affect corresponding institutionalized operational practices within financial organizations and to understand the role of agency within this process. Our motivation is to provide insight into these changes from an operational management perspective, as well as to test Thelen and Mahoney?s (2010) modes of institutional change. Consequently, the study researched implementations of an Investment Management System with a rules-based compliance module within financial organizations. The research consulted compliance and risk managers, as well as systems experts. The study suggests that prescriptive regulations are likely to create isomorphic configurations of rules-based compliance systems, which consequently will enable the institutionalization of associated compliance practices. The study reveals the ability of some agents within financial organizations to control the impact of regulatory institutions, not directly, but through the systems and processes they adopt to meet requirements. Furthermore, the research highlights the boundaries and relationships between each mode of change as future avenues of research.

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The objective of this article is to review the scientific literature on airflow distribution systems and ventilation effectiveness to identify and assess the most suitable room air distribution methods for various spaces. In this study, different ventilation systems are classified according to specific requirements and assessment procedures. This study shows that eight ventilation methods have been employed in the built environment for different purposes and tasks. The investigation shows that numerous studies have been carried out on ventilation effectiveness but few studies have been done regarding other aspects of air distribution. Amongst existing types of ventilation systems, the performance of each ventilation methods varies from one case to another due to different usages of the ventilation system in a room and the different assessment indices used. This review shows that the assessment of ventilation effectiveness or efficiency should be determined according to each task of the ventilation system, such as removal of heat, removal of pollutant, supply fresh air to the breathing zone or protecting the occupant from cross infection. The analysis results form a basic framework regarding the application of airflow distribution for the benefit of designers, architects, engineers, installers and building owners.