Manipulation via endowments in exchange markets with indivisible goods

We consider exchange markets with heterogeneous indivisible goods. We are interested in exchange rules that are efficient and immune to manipulations via endowments (either with respect to hiding or destroying part of the endowment or transferring part of the endowment to another trader). We consider three manipulability axioms: hiding-proofness, destruction-proofness, and transfer-proofness. We prove that no rule satisfying efficiency and hiding-proofness (which implies individual rationality) exists. For two-agent exchange markets with separable and responsive preferences, we show that efficient, individually rational, and destruction-proof rules exist. However, for separable preferences, no rule satisfies efficiency, individual rationality, and destruction-proofness. In the case of transfer-proofness the compatibility with efficiency and individual rationality for the two-agent case extends to the unrestricted domain. For exchange markets with separable preferences and more than two agents no rule satisfies efficiency, individual rationality, and transfer-proofness.

Priorities in the Location of Multiple Public Facilities

A collective decision problem is described by a set of agents, a profile of single-peaked preferences over the real line and a number k of public facilities to be located. We consider public facilities that do not su¤er from congestion and are non-excludable. We provide a characterization of the class of rules satisfying Pareto-efficiency, object-population monotonicity and sovereignty. Each rule in the class is a priority rule that selects locations according to a predetermined priority ordering among interest groups. We characterize each of the subclasses of priority rules that respectively satisfy anonymity, hiding-proofness and strategy-proofness. In particular, we prove that a priority rule is strategy-proof if and only if it partitions the set of agents into a fixed hierarchy. Alternatively, any such rule can be viewed as a collection of fixed-populations generalized peak-selection median rules (Moulin, 1980), that are linked across populations, in a way that we describe.

Individual versus group strategy-proofness: when do they coincide?

A social choice function is group strategy-proof on a domain if no group of agents can manipulate its final outcome to their own benefit by declaring false preferences on that domain. Group strategy-proofness is a very attractive requirement of incentive compatibility. But in many cases it is hard or impossible to find nontrivial social choice functions satisfying even the weakest condition of individual strategy-proofness. However, there are a number of economically significant domains where interesting rules satisfying individual strategy-proofness can be defined, and for some of them, all these rules turn out to also satisfy the stronger requirement of group strategy-proofness. This is the case, for example, when preferences are single-peaked or single-dipped. In other cases, this equivalence does not hold. We provide sufficient conditions defining domains of preferences guaranteeing that individual and group strategy-proofness are equivalent for all rules defined on the

On Strategy-proofness and symmetric single-peakedness

We characterize the class of strategy-proof social choice functions on the domain of symmetric single-peaked preferences. This class is strictly larger than the set of generalized median voter schemes (the class of strategy-proof and tops-only social choice functions on the domain of single-peaked preferences characterized by Moulin (1980)) since, under the domain of symmetric single-peaked preferences, generalized median voter schemes can be disturbed by discontinuity points and remain strategy-proof on the smaller domain. Our result identifies the specific nature of these discontinuities which allow to design non-onto social choice functions to deal with feasibility constraints.

Two necessary conditions for strategy-proofness: on what domains are they also sufficient?

A social choice function may or may not satisfy a desirable property depending on its domain of definition. For the same reason, different conditions may be equivalent for functions defined on some domains, while different in other cases. Understanding the role of domains is therefore a crucial issue in mechanism design. We illustrate this point by analyzing the role of different conditions that are always related, but not always equivalent to strategy-proofness. We define two very natural conditions that are necessary for strategy-proofness: monotonicity and reshuffling invariance. We remark that they are not always sufficient. Then, we identify a domain condition, called intertwinedness, that ensures the equivalence between our two conditions and that of strategy-proofness. We prove that some important domains are intertwined: those of single-peaked preferences, both with public and private goods, and also those arising in simple models of house allocation. We prove that other necessary conditions for strategy-proofness also become equivalent to ours when applied to functions defined on intertwined domains, even if they are not equivalent in general. We also study the relationship between our domain restrictions and others that appear in the literature, proving that we are indeed introducing a novel proposal.

Hiding the evidence: The State and spatial inequalities in health in Ireland

The Irish State has consistently reduced its production of publicly accessible disease / mortality maps over the last fifty years. State health statistics, and the small number of disease / mortality maps that have been produced in official publications, show a declining level of detail and are routinely out of date. Following a review of the production of disease / mortality maps in Ireland by the State and allied health agencies, two reasons are suggested for this decline. The first explanation relates to spatial inequalities in healthcare provision and to the absence of a health funding formulae in Ireland. The second explanation focuses on the potential politicisation of spatial inequalities in health status. Researchers in these fields are urged to disseminate information widely on spatial inequalities in healthcare provision, healthcare access and health status, both within and outside of the academic literature. Researchers in these fields are also urged to adopt an advocacy role on these issues, or to develop strategic alliances with such advocates.����

Steganalytic methods for the detection of histogram shifting data-hiding schemes

In this paper, some steganalytic techniques designed to detect the existence of hidden messages using histogram shifting methods are presented. Firstly, some techniques to identify specific methods of histogram shifting, based on visible marks on the histogram or abnormal statistical distributions are suggested. Then, we present a general technique capable of detecting all histogram shifting techniques analyzed. This technique is based on the effect of histogram shifting methods on the "volatility" of the histogram of differences and the study of its reduction whenever new data are hidden.

Subjectively adapted high capacity lossless image data hiding based on prediction errors

This article reports on a lossless data hiding scheme for digital images where the data hiding capacity is either determined by minimum acceptable subjective quality or by the demanded capacity. In the proposed method data is hidden within the image prediction errors, where the most well-known prediction algorithms such as the median edge detector (MED), gradient adjacent prediction (GAP) and Jiang prediction are tested for this purpose. In this method, first the histogram of the prediction errors of images are computed and then based on the required capacity or desired image quality, the prediction error values of frequencies larger than this capacity are shifted. The empty space created by such a shift is used for embedding the data. Experimental results show distinct superiority of the image prediction error histogram over the conventional image histogram itself, due to much narrower spectrum of the former over the latter. We have also devised an adaptive method for hiding data, where subjective quality is traded for data hiding capacity. Here the positive and negative error values are chosen such that the sum of their frequencies on the histogram is just above the given capacity or above a certain quality.

Reversible and high capacity data hiding in medical images

In this paper we introduce a highly efficient reversible data hiding system. It is based on dividing the image into tiles and shifting the histograms of each image tile between its minimum and maximum frequency. Data are then inserted at the pixel level with the largest frequency to maximize data hiding capacity. It exploits the special properties of medical images, where the histogram of their nonoverlapping image tiles mostly peak around some gray values and the rest of the spectrum is mainlyempty. The zeros (or minima) and peaks (maxima) of the histograms of the image tiles are then relocated to embed the data. The grey values of some pixels are therefore modified.High capacity, high fidelity, reversibility and multiple data insertions are the key requirements of data hiding in medical images. We show how histograms of image tiles of medical images can be exploited to achieve these requirements. Compared with data hiding method applied to the whole image, our scheme can result in 30%-200% capacity improvement and still with better image quality, depending on the medical image content. Additional advantages of the proposed method include hiding data in the regions of non-interest and better exploitation of spatial masking.

Steganalytic Methods for the Detection of Histogram Shifting Data Hiding Schemes

Peer-reviewed