Suchergebnisse

Forests are now universally thought of as Complex Adaptive Systems. The adaptive capacity of these ecosystems is directly proportional to their resistance, resilience and adaptability/plasticity. These attributes are, in turn, a function of the degree of biocomplexity (compositional, structural and functional/relational) obtained by the system itself. Because a forest can reach a high level of complexity, an adequate three-dimensional physical space and a very long time span must be ensured. Managed forests are often limited in surface (due to physical or ecological fragmentation) and in height (due to too early and intense cuts, which does not allow the canopy to occupy all the available biospace) making them more simplified and therefore less resilient. As regards time, the diversity between human time and forest time is not often taken into account, attempting to accelerate, in an unnatural way, the growth and succession of the structural phases. Speed is the enemy of complexity, especially relational complexity, on which the ability of forests to respond to external disturbances is based. Global change and the new challenges for the planet's future require a decisive change in the criteria and methods of forest management, also considering the great value of ecosystems left to undisturbed natural evolution.

This research aims to analyze an organization's social impact under Social Resilience issue (Herb, 2005) by developing the regional development assessment based on ESG standard. In addition, the assessment is also related with Sustainable Development Goal No.11 (Sustainable cities and communities). The application context is using our regional development assessment to evaluate how an organization can interfere when a community suffers external disturbances. This content could be established a sustainable management to arrange concrete consequences from various aspects of perspectives. It is observed that the assessment indicates that how to evaluate social impact of organizations in the community and scientifically quantitate value for Social Resilience. The framework is based on ESG consisting of Environment, Social, and Governance. This estimate proceeds from testing a non-governmental organization (NGO) or a non-profit organization (NPO) interfering with the regions results in how much their influence is and how large a range of their influence is. The assessment was applied to analyze the region—Guangfu Village in Taichung City, Taiwan. The evaluation was not really phenomenal on the appearance under ESG standard. According to this study, the consequences from the assessment are described as below.Keywords: Social Resilience; ESG; Sustainable Development Goal

Nowadays, one of the main objectives in road transport is to decrease the number of accident victims. Rollover accidents caused nearly 33% of all deaths from passenger vehicle crashes. Roll Stability Control (RSC) systems prevent vehicles from untripped rollover accidents. The lateral load transfer is the main parameter which is taken into account in the RSC systems. This parameter is related to the roll angle, which can be directly measured from a dual-antenna GPS. Nevertheless, this is a costly technique. For this reason, roll angle has to be estimated. In this paper, a novel observer based on H∞ filtering in combination with a neural network (NN) for the vehicle roll angle estimation is proposed. The design of this observer is based on four main criteria: to use a simplified vehicle model, to use signals of sensors which are installed onboard in current vehicles, to consider the inaccuracy in the system model and to attenuate the effect of the external disturbances. Experimental results show the effectiveness of the proposed observer. ; This work is supported by the Spanish Government through the Project TRA2013-48030-C2-1-R, which is gratefully acknowledged.

ABSTRACTMuch of our present day perception of African agriculture is still indirectly based on the coloured accounts of the early explorers and administrators. It involves an often very static conception of 'traditional' African agriculture. Not only does this fail to dojustice to the rich and dynamic history of African agriculture, it has also led to an inappropriate research and development paradigm which treats African agriculture as a disrupted equilibrial system that needs readjustment to return to an equilibrial and productivestate. A diachronic study of African agricultural history reveals that many of our preconceptions of African society and agriculture are invalid: agriculturists are not inert, but respond in innovative and dynamic ways to the perturbations of their natural and socialenvironment. It appears that their survival is not so much dependent on the establishmentof a fine‐tuned equilibrium, but rather on the dynamic responses to these external disturbances. It is very likely that the agro‐ecosystems in large parts of Africa function mainly as non‐equilibrial (unstable), but nevertheless persistent systems. This has importantimplications for development interventions and agricultural research. It requires a shiftfrom a synchronic approach to a diachronic approach that is firmly based on an understaning of the past.

Extending phased array techniques to optical frequencies is challenging because of the considerably smaller wavelengths and the difficulty of stabilizing the optical path lengths of multiple emitters to this level of precision. This is especially true under real-world conditions where thermal and vibrational disturbances cause path length variations that are considerable in relation to the wavelength. Earlier attempts have relied on an external mechanism to sense and compensate for any unwanted variations in the outgoing beams. Here we propose and demonstrate a method that does not rely on any external components. The method combines a pseudo-random noise phase modulation scheme together with conventional heterodyne interferometry to simultaneously measure phase variations between emitters. This information is then used to control the relative phases between the emitters and compensate for any unwanted disturbance. Experimental results are presented that support the viability of this design. ; This work was supported by the Australian Government's Australian Space Research Program.

Extending phased array techniques to optical frequencies is challenging because of the considerably smaller wavelengths and the difficulty of stabilizing the optical path lengths of multiple emitters to this level of precision. This is especially true under real-world conditions where thermal and vibrational disturbances cause path length variations that are considerable in relation to the wavelength. Earlier attempts have relied on an external mechanism to sense and compensate for any unwanted variations in the outgoing beams. Here we propose and demonstrate a method that does not rely on any external components. The method combines a pseudo-random noise phase modulation scheme together with conventional heterodyne interferometry to simultaneously measure phase variations between emitters. This information is then used to control the relative phases between the emitters and compensate for any unwanted disturbance. Experimental results are presented that support the viability of this design. ; This work was supported by the Australian Government's Australian Space Research Program.

AbstractThe instability of human bipedalism demands that the brain accurately senses balancing self-motion and determines whether movements originate from self-generated actions or external disturbances. Here, we challenge the longstanding notion that this process relies on a single representation of the body and world to accurately perceive postural orientation and organize motor responses to control balance self-motion. Instead, we find that the conscious sense of balance can be distorted by the corrective control of upright standing. Using psychophysics, we quantified thresholds to imposed perturbations and balance responses evoking cues of self-motion that are (in)distinguishable from corrective balance actions. When standing immobile, participants clearly perceived imposed perturbations. Conversely, when freely balancing, participants often misattributed their own corrective responses as imposed motion because their balance system had detected, integrated, and responded to the perturbation in the absence of conscious perception. Importantly, this only occurred for perturbations encoded ambiguously with balance-correcting responses and that remained below the natural variability of ongoing balancing oscillations. These findings reveal that our balance system operates on its own sensorimotor principles that can interfere with causal attribution of our actions, and that our conscious sense of balance depends critically on the source and statistics of induced and self-generated motion cues.

Purpose: We are currently facing that business environment is not stable due to globalisation processes in economics, cyclical changes and other disturbing factors. Hence, it is necessary to search such reserves that would improve efficiency of the business entity. Design/Methodology/Approach: The main objective of these reserves is to buffer negative impacts of external disturbances on financial and economic sustainability of enterprises. One of methods designed to improve the enterprise efficiency involves application of controlling technologies. Findings: In the present article the authors examine results of statistical analysis of economic performance of more than 70 Russian and foreign enterprises. The authors also analyse economic performance according to the authors' integral indicator that shows effectiveness of implementation of the controlling system. Practical Implications: On the ground of this analysis, the authors determine the mean level of increase in efficiency of the enterprise's activity due to introduction of the controlling system. Originality/Value: The analysis proves that, on average, efficiency of the economic entity's operation increases by about 17%. ; South Ural State University is grateful for financial support of the Ministry of Education and Science of the Russian Federation (grant No 26.9677.2017/ВР). The work was supported by Act 211 Government of the Russian Federation, contract № 02.A03.21.0011. ; peer-reviewed

The popularity of Unmanned Aerial Vehicles (UAVs) has grown rapidly in many civil and military applications in the last few decades. Recent UAV applications include crop monitoring, terrain mapping and aerial photography, where one or several image sensors attached to the UAV provide important terrain information. A thrust vectoring aerial vehicle, a vehicle with the ability to change the direction of thrust generated while keeping the UAV body at a zero roll and pitch orientation, can serve well in such applications by allowing the sensors to capture stable image data without additional gimbals, reducing the payload and cost while increasing the flight endurance. Furthermore, thrust vectoring UAVs can perform fast forward flight as well as hover operations with non-zero pitch: features which can serve well in military applications. The first part of this research focuses on developing a comprehensive dynamic model and a low level attitude and position control structure for a tri-rotor UAV with thrust vectoring capability, namely the Vectored Thrust Aerial Vehicle. Nonlinear dynamics of UAVs require robust control methods to realize stable flight. Special attention needs to be given to wind gust disturbances, and parametric uncertainties. Sliding Mode Control , a type of Variable Structure Controller, has served well over the years in controlling UAVs and other dynamic systems. However, conventional Sliding Mode Control results in a high frequency switching behavior of the control signal. Furthermore, Sliding Mode Control does not focus on fast set-point regulation or tracking, which can be advantageous for UAVs and many other robotic systems. Taking these research gaps into account, this work presents an Adaptive Variable Structure Control method, which can acquire fast set-point regulation while maintaining robustness against external disturbances and uncertainties. The adaptive algorithm developed in this work is fundamentally different from current Adaptive Sliding Mode Control and other Variable Structure ...

AbstractResource‐based cities (RBCs) whose economies depend primarily on exploiting and processing natural resources usually have rigid, singular, and low‐end industrial structures, which often cripples their ability to cope with external disturbances such as international resource price fluctuations and economic downturns. This paper quantitatively analyzes the economic resilience of RBCs in China in terms of resistance and recoverability during the Asian financial crisis and the global financial crisis. Furthermore, it identifies the main factors affecting resilience. There are four main findings: First, RBCs were quickly and negatively impacted by the Asian financial crisis, which suggests that economic resistance was generally low during this period. In the recovery period, while the rate of recovery was slow at the beginning, economic recoverability improved after 2002. Economic resistance and recoverability were found to have a strong negative correlation. Second, at the beginning of the global financial crisis, the economic resistance of RBCs was generally high. However, after 2012, the number of cities that were severely affected by the economic crisis increased rapidly. Third, economic resistance varied across different types of RBCs. Coal‐based and forestry‐based cities had lower economic resistance, while oil & gas‐based cities were more resistant. RBCs in the Eastern region generally had low economic resistance, while the economic resilience of recessionary cities was also low. Finally, while factors affecting the economic resilience varied across the two economic cycles, we found that economic development, labor conditions and, most of all, the industrial structure had a statistically significant negative effect on economic resilience.

In tropical regions, the dynamics of social-ecological systems (SESs) associated with small producers is characterized by the close interrelation between land use, which is influenced by global, national and local drivers and livelihood development. Understanding the causes of land use dynamics is important, as it may reflect internal and/or external drivers that induce change and thus may be a critical process in achieving sustainable development. Furthermore, it is critical to understand the linkages and dependency between land use change and livelihood development. Smallholder livelihoods change and adapt continuously with land-use change. Insight into the dynamics of rural SESs is fundamental and requires a complex system's approach, as changes occur unpredictably, non-linearly and system responses are self-organizing and go through different phases of adaptive cycles. In this study, the ejido Laguna del Mante (LM), Valles, San Luis Potosi, Mexico is analyzed as a SES considering livelihoods and land use change. In particular, I addressed the underlying question as to "what were the causes of the spatio-temporal dynamics of land use and livelihoods?" and to "which degree were livelihoods adaptive to external disturbances such as climate change, land tenure change or fluctuations in soft commodity markets?". With diverse social-ecological methodologies including semi-structured interviews applied to key stakeholders, life history analysis applied to ejidatarios, and observational studies land use and livelihood dynamics were examined. The historical analysis of the LM-SES demonstrates that the original tropical forest system transformed into a high input livestock enterprise with the arrival of a politically and economically highly influential person. His unexpected death triggered the immediate full collapse of the SES ultimately leading to the foundation of the ejido LM. A cascade of economic (establishment of a local sugar factory, high price of sugarcane, subsidies) and social-political (privatization of ...

Semi-active suspensions have drawn particular attention due to their superior performance over the other types of suspensions. One of their advantages is that their damping coefficient can be controlled without the need for any external source of power. In this study, a handful of control approaches are implemented on a car models using MATLAB/Simulink. The investigated control methodologies are skyhook, groundhook, hybrid skyhook-groundhook, Acceleration Driven Damper, Power Driven Damper, H Robust Control, Fuzzy Logic Controller, and Inverse ANFIS. H Robust Control is an advanced method that guarantees transient performance and rejects external disturbances. It is shown that H with the proposed modification, has the best performance although its relatively high cost of computation could be potentially considered as a drawback. Also, the proposed Inverse ANFIS controller uses the power of fuzzy systems along with neural networks to help improve vehicle ride metrics significantly. In this study, a novel approach is introduced to analyze and fine-tune semi-active suspension control algorithms. In some cases, such as military trucks moving on off-road terrains, it is critical to keep the vehicle ride quality in an acceptable range. Semi-active suspensions are used to have more control over the ride metrics compared to passive suspensions and also, be more cost-effective compared to active suspensions. The proposed methodology will investigate the skyhook-groundhook hybrid controller. This is accomplished by conducting sensitivity analysis of the controller performance to varying vehicle/road parameters. This approach utilizes sensitivity analysis and one-at-a-time methodology to find and reach the optimum point of vehicle suspensions. Furthermore, real-time tuning of the mentioned controller will be studied. The online tuning will help keep the ride quality of the vehicle close to its optimum point while the vehicle parameters are changing. A quarter-car model is used for all simulations and analyses. ; Ph. D.

The thesis deals with the design and implementation of an Adaptive Flight Control technique for Unmanned Aerial Vehicles (UAVs). The application of UAVs has been increasing exponentially in the last decade both in Military and Civilian fronts. These UAVs fly at very low speeds and Reynolds numbers, have nonlinear coupling, and tend to exhibit time varying characteristics. In addition, due to the variety of missions, they fly in uncertain environments exposing themselves to unpredictable external disturbances. The successful completion of the UAV missions is largely dependent on the accuracy of the control provided by the flight controllers. Thus there is a necessity for accurate and robust flight controllers. These controllers should be able to adapt to the changes in the dynamics due to internal and external changes. From the available literature, it is known that, one of the better suited adaptive controllers is the model based controller. The design and implementation of model based adaptive controller is discussed in the thesis. A critical issue in the design and application of model based control is the online identification of the UAV dynamics from the available sensors using the onboard processing capability. For this, proper instrumentation in terms of sensors and avionics for two platforms developed at UNSW@ADFA is discussed. Using the flight data from the remotely flown platforms, state space identification and fuzzy identification are developed to mimic the UAV dynamics. Real time validations using Hardware in Loop (HIL) simulations show that both the methods are feasible for control. A finer comparison showed that the accuracy of identification using fuzzy systems is better than the state space technique. The flight tests with real time online identification confirmed the feasibility of fuzzy identification for intelligent control. Hence two adaptive controllers based on the fuzzy identification are developed. The first adaptive controller is a hybrid indirect adaptive controller that utilises the ...

Change and Continuity in the Orientation of OECD Countries' Macroeconomic Policies Jean-Paul Fitoussi, Jacques Le Cacheux The current world economic situation is obviously the inheritance of the various shocks and structural changes that occurred over the past fifteen years. However, whereas these shocks had had similar consequences on the major OECD countries until the end of the seventies, they seem to have been followed by very diverse evolutions since then. Especially when compared with the United States, Europe is experiencing slow growth, together with negative net job creation, having opted for orthodox financial policies and seemingly over-indulging in disinflation. One is then led to ask the following question : May it be that, on top of the various « external » disturbances that adversely affected employment in European countries, an internal event — some institutional change — happened, which would make the current situation the result of choice ? According to this hypothesis, slow growth, stagnating productive investment, and high unemployment in Europe in the eighties would result partly from a change in policy-makers' preferences : not only have disinflation and external balance become priorities, but policies, facts and rhetoric converge to show that employment and economic growth can no longer be considered as objectives for macroeconomic policy-making. This paper tries to substantiate this hypothesis by putting recent developments into historical perspective, and by confronting governments' discourse on economic policy objectives with actually implemented policies, with changing economic doctrines, and with the actual performances of the various economies. When looking at the past twenty-five years, two major impressions emerge : that of continuity, for the most part, in Japan and the United States ; that of a break, radical in some respects, in Europe at the turn of the decade. One may hold the view that the choices were constrained, and that European governments did their best to master the ...

Abstract
To estimate the reaction of economies to political interventions or external disturbances, input–output (IO) tables—constructed by aggregating data into industrial sectors—are extensively used. However, economic growth, robustness, and resilience crucially depend on the detailed structure of nonaggregated firm-level production networks (FPNs). Due to nonavailability of data, little is known about how much aggregated sector-based and detailed firm-level-based model predictions differ. Using a nearly complete nationwide FPN, containing 243,399 Hungarian firms with 1,104,141 supplier–buyer relations, we self-consistently compare production losses on the aggregated industry-level production network (IPN) and the granular FPN. For this, we model the propagation of shocks of the same size on both, the IPN and FPN, where the latter captures relevant heterogeneities within industries. In a COVID-19 inspired scenario, we model the shock based on detailed firm-level data during the early pandemic. We find that using IPNs instead of FPNs leads to an underestimation of economic losses of up to 37%, demonstrating a natural limitation of industry-level IO models in predicting economic outcomes. We ascribe the large discrepancy to the significant heterogeneity of firms within industries: we find that firms within one sector only sell 23.5% to and buy 19.3% from the same industries on average, emphasizing the strong limitations of industrial sectors for representing the firms they include. Similar error levels are expected when estimating economic growth, CO2 emissions, and the impact of policy interventions with industry-level IO models. Granular data are key for reasonable predictions of dynamical economic systems.