993 resultados para Hard part


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The ways in which a society set standards of behaviour and of conduct for its members vary hugely. For example, accepted practices, recognised customs, spiritually or morally inspired norms, judicially declared rules, executively formulated edicts, formal legislative enactments or constitutionally embedded rights and duties. Whatever form they assume, these standards are the artificial construction of the human mind. Accordingly the law - whatever its form - can do no more and no less than regulate or set standards for human behaviour, human conduct, and human decision-making. The law cannot regulate the environment. It can only regulate human activities that impact directly or indirectly upon the environment. This applies as much to wetlands as components of the environment as it does to any other components of the environment or the environment at large. The capacity of the law to protect the environment and therefore wetlands is thus totally dependent upon the capacity of the law to regulate human behaviour, human conduct and human decision-making. At the same time the law needs to reflect the specific nature, functions and locations of wetlands. A wetland is an ecosystem by itself; it comprises a range of ecosystems within it; and it is part of a wider set of ecosystems. Hence, the significant ecological functions performed by wetlands. Then there are the benefits flowing to humans from wetlands. These may be social, economic, cultural, aesthetic, or a combination of some or of all of these. It is a challenge for a society acting through its legal system to find the appropriate balance between these ecological and these human values. But that is what sustainability requires.The ways in which a society set standards of behaviour and of conduct for its members vary hugely. For example, accepted practices, recognised customs, spiritually or morally inspired norms, judicially declared rules, executively formulated edicts, formal legislative enactments or constitutionally embedded rights and duties. Whatever form they assume, these standards are the artificial construction of the human mind. Accordingly the law - whatever its form - can do no more and no less than regulate or set standards for human behaviour, human conduct, and human decision-making. The law cannot regulate the environment. It can only regulate human activities that impact directly or indirectly upon the environment. This applies as much to wetlands as components of the environment as it does to any other components of the environment or the environment at large. The capacity of the law to protect the environment and therefore wetlands is thus totally dependent upon the capacity of the law to regulate human behaviour, human conduct and human decision-making. At the same time the law needs to reflect the specific nature, functions and locations of wetlands. A wetland is an ecosystem by itself; it comprises a range of ecosystems within it; and it is part of a wider set of ecosystems. Hence, the significant ecological functions performed by wetlands. Then there are the benefits flowing to humans from wetlands. These may be social, economic, cultural, aesthetic, or a combination of some or of all of these. It is a challenge for a society acting through its legal system to find the appropriate balance between these ecological and these human values. But that is what sustainability requires.

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In this Part 2 attention is turned towards the legal arrangements in nation states for managing wetlands. These national arrangements have effect within the international arrangements already mentioned and any regional arrangements that are relevant. However, each national system is a reflection of its own historical, cultural, political and constitutional background. It is the purpose of this Part 2 to review and assess the national approaches to wetlands management. This involves an analysis of a range of instruments. These are: constitutional rules; strategic rules; regulatory rules; and management rules. Each of these sets of rules performs different functions, assumes different forms and is differentially capable of enforcement.

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Nightclubs are businesses. Their business is pleasure; however pleasure has its price. People have become increasingly concerned about the problems of violence in society but why do higher levels of violence occur in nightclubs despite the established patterns of behaviour that dictates how we socialise and act? In response, researchers have focused on identifying social and situational factors that may contribute to violence from a government perspective, focusing on a variety of specific issues ranging from financial standpoints with effective target marketing strategies to legal obligations of supplying alcohol and abiding regulatory conditions. There is little research into specific design properties that can determine design standards to ensure/improve the physical design of nightclub environments to reduce patron violence. To address this gap, this current article aims to understand how people experience and respond to the physical environment of nightclubs and how these spaces influence their behaviour. The first section of this paper examines the background on nightclubs and theories concerning the influence of pleasure. The second section of this paper details the findings of existing studies that have examined the nightlife context and the various factors that influence patron violence. The main finding of this paper is that although alcohol likely plays a contributing role in aggressive patron behaviour, there is evidence that the relationship is moderated by a number of significant factors relating to the characteristics of the drinking environment such as: physical comfort; the degree of overall 'permissiveness‘ in the establishment; crowding; and physical environmental elements most influenced by day to-day management practices such as lighting, ventilation, cleanliness and seating arrangements. The findings from this paper have been used to develop a framework to guide exploratory research on how specific elements of the physical environment of nightclubs have an impact on elevated patron aggression and assault (Koleczko & Garcia Hansen, 2011).

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Violence in nightclubs is a serious problem that has the Australian government launching multimillion dollar drinking campaigns. Research on nightclub violence has focused on identifying contributing social and environmental factors, with many concentrating on a variety of specific issues ranging from financial standpoints with effective target marketing strategies to legal obligations of supplying alcohol and abiding regulatory conditions. Moreover, existing research suggests that there is no single factor that directly affects the rate violence in licensed venues. As detailed in the review paper of Koleczko and Garcia Hansen (2011), there is little research about the physical environment of nightclubs and which specific design properties can be used to determine design standards to ensure/improve the physical design of nightclub environments to reduce patron violence. This current study seeks to address this omission by reporting on a series of interviews with participants from management and design domains. Featured case studies are both located in Fortitude Valley, a Mecca for party-goers and the busiest nightclub district in Queensland. The results and analysis support the conclusions that a number of elements of the physical environment influence elevated patron aggression and assault.

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A number of learning problems can be cast as an Online Convex Game: on each round, a learner makes a prediction x from a convex set, the environment plays a loss function f, and the learner’s long-term goal is to minimize regret. Algorithms have been proposed by Zinkevich, when f is assumed to be convex, and Hazan et al., when f is assumed to be strongly convex, that have provably low regret. We consider these two settings and analyze such games from a minimax perspective, proving minimax strategies and lower bounds in each case. These results prove that the existing algorithms are essentially optimal.

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We present new expected risk bounds for binary and multiclass prediction, and resolve several recent conjectures on sample compressibility due to Kuzmin and Warmuth. By exploiting the combinatorial structure of concept class F, Haussler et al. achieved a VC(F)/n bound for the natural one-inclusion prediction strategy. The key step in their proof is a d=VC(F) bound on the graph density of a subgraph of the hypercube—one-inclusion graph. The first main result of this report is a density bound of n∙choose(n-1,≤d-1)/choose(n,≤d) < d, which positively resolves a conjecture of Kuzmin and Warmuth relating to their unlabeled Peeling compression scheme and also leads to an improved one-inclusion mistake bound. The proof uses a new form of VC-invariant shifting and a group-theoretic symmetrization. Our second main result is an algebraic topological property of maximum classes of VC-dimension d as being d-contractible simplicial complexes, extending the well-known characterization that d=1 maximum classes are trees. We negatively resolve a minimum degree conjecture of Kuzmin and Warmuth—the second part to a conjectured proof of correctness for Peeling—that every class has one-inclusion minimum degree at most its VC-dimension. Our final main result is a k-class analogue of the d/n mistake bound, replacing the VC-dimension by the Pollard pseudo-dimension and the one-inclusion strategy by its natural hypergraph generalization. This result improves on known PAC-based expected risk bounds by a factor of O(log n) and is shown to be optimal up to a O(log k) factor. The combinatorial technique of shifting takes a central role in understanding the one-inclusion (hyper)graph and is a running theme throughout

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We study the rates of growth of the regret in online convex optimization. First, we show that a simple extension of the algorithm of Hazan et al eliminates the need for a priori knowledge of the lower bound on the second derivatives of the observed functions. We then provide an algorithm, Adaptive Online Gradient Descent, which interpolates between the results of Zinkevich for linear functions and of Hazan et al for strongly convex functions, achieving intermediate rates between [square root T] and [log T]. Furthermore, we show strong optimality of the algorithm. Finally, we provide an extension of our results to general norms.

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We consider the problem of prediction with expert advice in the setting where a forecaster is presented with several online prediction tasks. Instead of competing against the best expert separately on each task, we assume the tasks are related, and thus we expect that a few experts will perform well on the entire set of tasks. That is, our forecaster would like, on each task, to compete against the best expert chosen from a small set of experts. While we describe the "ideal" algorithm and its performance bound, we show that the computation required for this algorithm is as hard as computation of a matrix permanent. We present an efficient algorithm based on mixing priors, and prove a bound that is nearly as good for the sequential task presentation case. We also consider a harder case where the task may change arbitrarily from round to round, and we develop an efficient approximate randomized algorithm based on Markov chain Monte Carlo techniques.