Social Welfare in One-Sided Matching Mechanisms

We study the Price of Anarchy of mechanisms for the well-known problem of one-sided matching, or house allocation, with respect to the social welfare objective. We consider both ordinal mechanisms, where agents submit preference lists over the items, and cardinal mechanisms, where agents may submit numerical values for the items being allocated. We present a general lower bound of $\Omega(\sqrt{n})$ on the Price of Anarchy, which applies to all mechanisms. We show that two well-known mechanisms, Probabilistic Serial, and Random Priority, achieve a matching upper bound. We extend our lower bound to the Price of Stability of a large class of mechanisms that satisfy a common proportionality property, and show stronger bounds on the Price of Anarchy of all deterministic mechanisms

Truthful Facility Assignment with Resource Augmentation: An Exact Analysis of Serial Dictatorship

We study the truthful facility assignment problem, where a set of agents with private most-preferred points on a metric space are assigned to facilities that lie on the metric space, under capacity constraints on the facilities. The goal is to produce such an assignment that minimizes the social cost, i.e., the total distance between the most-preferred points of the agents and their corresponding facilities in the assignment, under the constraint of truthfulness, which ensures that agents do not misreport their most-preferred points. We propose a resource augmentation framework, where a truthful mechanism is evaluated by its worst-case performance on an instance with enhanced facility capacities against the optimal mechanism on the same instance with the original capacities. We study a very well-known mechanism, Serial Dictatorship, and provide an exact analysis of its performance. Although Serial Dictatorship is a purely combinatorial mechanism, our analysis uses linear programming; a linear program expresses its greedy nature as well as the structure of the input, and finds the input instance that enforces the mechanism have its worst-case performance. Bounding the objective of the linear program using duality arguments allows us to compute tight bounds on the approximation ratio. Among other results, we prove that Serial Dictatorship has approximation ratio $g/(g-2)$ when the capacities are multiplied by any integer $g \geq 3$. Our results suggest that even a limited augmentation of the resources can have wondrous effects on the performance of the mechanism and in particular, the approximation ratio goes to 1 as the augmentation factor becomes large. We complement our results with bounds on the approximation ratio of Random Serial Dictatorship, the randomized version of Serial Dictatorship, when there is no resource augmentation

Distortion in Social Choice Problems: The First 15 Years and beyond

The notion of distortion in social choice problems has been defined to measure the loss in efficiency-typically measured by the utilitarian social welfare, the sum of utilities of the participating agents-due to having access only to limited information about the preferences of the agents. We survey the most significant results of the literature on distortion from the past 15 years, and highlight important open problems and the most promising avenues of ongoing and future work

What does it take to make integrated care work? A ‘cookbook’ for large-scale deployment of coordinated care and telehealth

The Advancing Care Coordination & Telehealth Deployment (ACT) Programme is the first to explore the organisational and structural processes needed to successfully implement care coordination and telehealth (CC&TH) services on a large scale. A number of insights and conclusions were identified by the ACT programme. These will prove useful and valuable in supporting the large-scale deployment of CC&TH. Targeted at populations of chronic patients and elderly people, these insights and conclusions are a useful benchmark for implementing and exchanging best practices across the EU. Examples are: Perceptions between managers, frontline staff and patients do not always match; Organisational structure does influence the views and experiences of patients: a dedicated contact person is considered both important and helpful; Successful patient adherence happens when staff are engaged; There is a willingness by patients to participate in healthcare programmes; Patients overestimate their level of knowledge and adherence behaviour; The responsibility for adherence must be shared between patients and health care providers; Awareness of the adherence concept is an important factor for adherence promotion; The ability to track the use of resources is a useful feature of a stratification strategy, however, current regional case finding tools are difficult to benchmark and evaluate; Data availability and homogeneity are the biggest challenges when evaluating the performance of the programmes

The distortion of distributed voting

Voting can abstractly model any decision-making scenario and as such it has been extensively studied over the decades. Recently, the related literature has focused on quantifying the impact of utilizing only limited information in the voting process on the societal welfare for the outcome, by bounding the distortion of voting rules. Even though there has been significant progress towards this goal, almost all previous works have so far neglected the fact that in many scenarios (like presidential elections) voting is actually a distributed procedure. In this paper, we consider a setting in which the voters are partitioned into disjoint districts and vote locally therein to elect local winning alternatives using a voting rule; the final outcome is then chosen from the set of these alternatives. We prove tight bounds on the distortion of well-known voting rules for such distributed elections both from a worst-case perspective as well as from a best-case one. Our results indicate that the partition of voters into districts leads to considerably higher distortion, a phenomenon which we also experimentally showcase using real-world data

The Pareto Frontier of Inefficiency in Mechanism Design

We study the trade-off between the Price of Anarchy (PoA) and the Price of Stability (PoS) in mechanism design, in the prototypical problem of unrelated machine scheduling. We give bounds on the space of feasible mechanisms with respect to the above metrics, and observe that two fundamental mechanisms, namely the First-Price (FP) and the Second-Price (SP), lie on the two opposite extrema of this boundary. Furthermore, for the natural class of anonymous task-independent mechanisms, we completely characterize the PoA/PoS Pareto frontier; we design a class of optimal mechanisms (formula presented) that lie exactly on this frontier. In particular, these mechanisms range smoothly, with respect to parameter (formula presented) across the frontier, between the First-Price (formula presented) and Second-Price (formula presented) mechanisms. En route to these results, we also provide a definitive answer to an important question related to the scheduling problem, namely whether non-truthful mechanisms can provide better makespan guarantees in the equilibrium, compared to truthful ones. We answer this question in the negative, by proving that the Price of Anarchy of all scheduling mechanisms is at least n, where n is the number of machines

Unplanned extubation in critically ill adults: Clinical review

Aims and objectives: To investigate and synthesize the evidence on the incidence and consequences of unplanned extubation (UE) in intensive care unit (ICU) patients, and on risk factors for UE. Background: ICU patients generally spend considerable time being intubated via the endotracheal route. Non-planned endotracheal tube removal, either deliberate or accidental, may pose significant safety risks for them. As UE is among the most studied critical incidents in the ICU, evaluation and summary of existing findings could provide important implications for clinical practice. Search strategies, inclusion and exclusion criteria: Observational studies published between 1990 and 2012 in English-language journals indexed by Cumulative Index for Nursing and Allied Health Literature (CINAHL), PubMed, Web of Science and the Cochrane Library were searched for studies on UE of critically ill adults. Thirty-three articles were considered eligible for inclusion. Conclusions: UE incidence varies considerably among reports, with self-extubation representing the majority of cases. Agitation, especially when combined with inadequate sedation, and decreased patient surveillance are the major risk factors for UE. Inexperienced personnel and improper tube fixation may also be important, while physical restraint use remains controversial. UE can be followed by serious complications, mainly aspiration, laryngeal oedema and increased risk for pneumonia. Need for re-intubation is a major determinant of patient outcomes. Implementation of educational or quality improvement programs is expected to advance personnel's knowledge about risk factors for UE, promote skills on safe, standardized procedures for patient care and increase compliance with them. Relevance to clinical practice: Identifying risk factors for UE and minimizing UE incidence through appropriate preventive strategies are prerequisites for improving nursing care quality and patient safety in the ICU. © 2012 The Authors. Nursing in Critical Care © 2012 British Association of Critical Care Nurses

Methodological and Technological Support for the Coordination of Smart Networks of SMEs

Part 2: Behaviour and CoordinationInternational audienceTo develop and to manufacture highly innovative, knowledge-intensive products, processes and services, small and medium-sized enterprises (SMEs) often rely on the help of partners to be able to apply new technologies, to open up market opportunities or to extend production capabilities. Therefore, collaboration in dynamic networks has become a major success factor for SMEs. However, in many cases, companies are lacking the appropriate resources and capabilities to effectively and efficiently coordinate such collaborative activities. This paper presents a set of adaptable and easy-to-use methods and tools that support SMEs in building up, operating and terminating knowledge-driven, ICT-enabled and organizationally embedded collaboration in Smart Networks. The effectiveness will be illustrated with examples from three SME networks in different industry sectors that have applied these methods and tools in their industrial practice

Practical machine learning based on cloud computing resources

Machine learning is a domain highly influenced by the rapid evolution of cloud computing and has reached a maturity point where a plethora of data processing capabilities is now widely available. The aim of the present study is to investigate the potential for building a common platform to support direct end-user application of machine learning algorithms across diverse scientific areas, emphasizing not only the suitability of appropriate tools, but also how results can be disseminated and utilized in a shared data environment. Three case studies are presented: i) quality evaluation metrics for tomographic image reconstruction in positron emission tomography (PET), ii) health impacts of surface UV radiation and iii) demographic determinants that influence the perception of fraud and corruption incidents within different industry sectors. Tests showed that commercially available cloud resources are over-sufficient to consolidate results from a variety of teams and applications and are able to contribute to the build-up of a valuable shared knowledge repository. The cloud service platform exploits machine learning models and helps automate the training and prediction process. The suggested approach makes optimization more efficient and supports the transition to a more sustainable global information environment by breaking knowledge silos. © 2019 Author(s)