53 resultados para tipped minimum wage


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European labour markets are increasingly divided between insiders in full-time permanent employment and outsiders in precarious work or unemployment. Using quantitative as well as qualitative methods, this thesis investigates the determinants and consequences of labour market policies that target these outsiders in three separate papers. The first paper looks at Active Labour Market Policies (ALMPs) that target the unemployed. It shows that left and right-wing parties choose different types of ALMPs depending on the policy and the welfare regime in which the party is located. These findings reconcile the conflicting theoretical expectations from the Power Resource approach and the insider-outsider theory. The second paper considers the regulation and protection of the temporary work sector. It solves the puzzle of temporary re-regulation in France, which contrasts with most other European countries that have deregulated temporary work. Permanent workers are adversely affected by the expansion of temporary work in France because of general skills and low wage coordination. The interests of temporary and permanent workers for re-regulation therefore overlap in France and left governments have an incentive to re-regulate the sector. The third paper then investigates what determines inequality between median and bottom income workers. It shows that non-inclusive economic coordination increases inequality in the absence of compensating institutions such as minimum wage regulation. The deregulation of temporary work as well as spending on employment incentives and rehabilitation also has adverse effects on inequality. Thus, policies that target outsiders have important economic effects on the rest of the workforce. Three broader contributions can be identified. First, welfare state policies may not always be in the interests of labour, so left parties may not always promote them. Second, the interests of insiders and outsiders are not necessarily at odds. Third, economic coordination may not be conducive to egalitarianism where it is not inclusive.

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Galactic cosmic rays (GCRs) are extremely difficult to shield against and pose one of the most severe long-term hazards for human exploration of space. The recent solar minimum between solar cycles 23 and 24 shows a prolonged period of reduced solar activity and low interplanetary magnetic field strengths. As a result, the modulation of GCRs is very weak, and the fluxes of GCRs are near their highest levels in the last 25 years in the fall of 2009. Here we explore the dose rates of GCRs in the current prolonged solar minimum and make predictions for the Lunar Reconnaissance Orbiter (LRO) Cosmic Ray Telescope for the Effects of Radiation (CRaTER), which is now measuring GCRs in the lunar environment. Our results confirm the weak modulation of GCRs leading to the largest dose rates seen in the last 25 years over a prolonged period of little solar activity.

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Solar outputs during the current solar minimum are setting record low values for the space age. Evidence is here reviewed that this is part of a decline in solar activity from a grand solar maximum and that the Sun has returned to a state that last prevailed in 1924. Recent research into what this means, and does not mean, for climate change is reviewed.

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Orthogonal internal coordinates are defined which have useful properties for constructing the potential energy functions of triatomic molecules with two or three minima on the surface. The coordinates are used to obtain ground state potentials of ClOO and HOF, both of which have three minima.

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Nonregular two-level fractional factorial designs are designs which cannot be specified in terms of a set of defining contrasts. The aliasing properties of nonregular designs can be compared by using a generalisation of the minimum aberration criterion called minimum G2-aberration.Until now, the only nontrivial designs that are known to have minimum G2-aberration are designs for n runs and m n–5 factors. In this paper, a number of construction results are presented which allow minimum G2-aberration designs to be found for many of the cases with n = 16, 24, 32, 48, 64 and 96 runs and m n/2–2 factors.

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Minimum aberration is the most established criterion for selecting a regular fractional factorial design of maximum resolution. Minimum aberration designs for n runs and n/2 less than or equal to m < n factors have previously been constructed using the novel idea of complementary designs. In this paper, an alternative method of construction is developed by relating the wordlength pattern of designs to the so-called 'confounding between experimental runs'. This allows minimum aberration designs to be constructed for n runs and 5n/16 less than or equal to m less than or equal to n/2 factors as well as for n/2 less than or equal to m < n.

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When Campylobacter jejuni cultures that had been grown in broth at 39degreesC were subcultured into fresh medium at 30degreesC, there was a transient period of growth followed by a decline in viable-cell numbers before growth resumed once more. We propose that this complex behavior is the net effect of the growth of inoculum cells followed by a loss of viability due to oxidative stress and the subsequent emergence of a spontaneously arising mutant population that takes over the culture.

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A fast Knowledge-based Evolution Strategy, KES, for the multi-objective minimum spanning tree, is presented. The proposed algorithm is validated, for the bi-objective case, with an exhaustive search for small problems (4-10 nodes), and compared with a deterministic algorithm, EPDA and NSGA-II for larger problems (up to 100 nodes) using benchmark hard instances. Experimental results show that KES finds the true Pareto fronts for small instances of the problem and calculates good approximation Pareto sets for larger instances tested. It is shown that the fronts calculated by YES are superior to NSGA-II fronts and almost as good as those established by EPDA. KES is designed to be scalable to multi-objective problems and fast due to its small complexity.

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A hybridised and Knowledge-based Evolutionary Algorithm (KEA) is applied to the multi-criterion minimum spanning tree problems. Hybridisation is used across its three phases. In the first phase a deterministic single objective optimization algorithm finds the extreme points of the Pareto front. In the second phase a K-best approach finds the first neighbours of the extreme points, which serve as an elitist parent population to an evolutionary algorithm in the third phase. A knowledge-based mutation operator is applied in each generation to reproduce individuals that are at least as good as the unique parent. The advantages of KEA over previous algorithms include its speed (making it applicable to large real-world problems), its scalability to more than two criteria, and its ability to find both the supported and unsupported optimal solutions.

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This paper proposes a new iterative algorithm for orthogonal frequency division multiplexing (OFDM) joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the relatively less studied problem of "overfitting" such that the iterative approach may converge to a trivial solution. Specifically, we apply a hard-decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the PHN, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical Simulations are also given to verify the proposed algorithm. (C) 2008 Elsevier B.V. All rights reserved.

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In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

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A beamforming algorithm is introduced based on the general objective function that approximates the bit error rate for the wireless systems with binary phase shift keying and quadrature phase shift keying modulation schemes. The proposed minimum approximate bit error rate (ABER) beamforming approach does not rely on the Gaussian assumption of the channel noise. Therefore, this approach is also applicable when the channel noise is non-Gaussian. The simulation results show that the proposed minimum ABER solution improves the standard minimum mean squares error beamforming solution, in terms of a smaller achievable system's bit error rate.