Gross substitutability of point-to-set correspondences

In this paper the notion of gross substitutability for the multi-valued case is studied. It is proved that, if in a pure exchange equilibrium model gross substitutability and some auxiliary conditions prevail, then (a) the set of equilibria is a Cartesian product of a convex set of equilibrium resource allocations and a convex cone of equilibrium prices; hence all equilibria are equiadvantageous for every trader; (b) the weak axiom of revealed preference holds in any equilibrium; (c) any equilibrium is stable with respect to reallocations of initial resources. Some situations in which Walras' law does not hold are considered as well.     

Equally important criteria and demanding aggregation

Within the class of weighted averages of ordered measurements on criteria of ‘equal importance’, we discuss aggregators that help assess to what extent ‘most’ criteria are satisfied, or a ‘good performance across the board’ is attained. All aggregators discussed are compromises between the simple mean and the very demanding minimum score. The weights of the aggregators are described in terms of the convex polytopes as induced by the characteristics of the aggregators, such as concavity. We take the barycentres of the polytopes as representative weights.     

Approximation of contractible valued correspondences by functions

Let X and Y be absolute neighborhood retracts (this is a large class of spaces) with X compact, and let F:X→Y be an upper hemicontinuous correspondence whose values are compact and contractible. It is shown that any neighborhood of the graph of F contains the graph of a continuous function f:X→Y. The relevance of this result to fixed point theory is indicated. It is also shown that if X is ‘locally infinite’, then F can be approximated in the stronger sense of the graph of f being close to the graph of F and every point in the graph of F being close to some point in the graph of f. A conjectured generalization of the main result is stated.     

多人合作对策中的费用均摊问题

对策论是运筹学的一个分支,是有关多人在竞争状态下的决策行为的数学理论。对策论按不同的分类方法有多种类别,如果局中人可以和其他局中人联合成一体统一行动与其他局中人对抗,这种对策称为多人合作对策。本文主要讨论多人对策中的一个例子。     

Notes and Comments: Stochastic demand correspondences and their aggregation properties

Abstract Mathematics Subject Classification (2000): 91B06, 91B16 Journal of Economic Literature Classification: D11     

Notes and Comments: Measures of risk attitude: correspondences between mean-variance and expected-utility approaches

Abstract The expected-utility (EU) approach brings great richness to the study of decision making in a large variety of stochastic environments. Research in the EU paradigm often starts from plausible assumptions on risk preferences or optimal responses to changes in the risk structure, and then investigates how such assumptions are reflected by properties of the von-Neumann-Morgenstern (vNM) utility functions underlying the EU concept. Building on Pratt’s (1964) analysis of risk aversion, several measures for risk attitude have been analyzed, including absolute prudence and temperance (Kimball (1990), Eeckhoudt, Goiller and Schlesinger (1996)), their relative and partial relative counterparts (Choi, Kim and Snow (2001), Honda (1985)) as well as extensions such as mixed risk aversion (Caballé and Pomansky (1996)). Mathematics Subject Classification (2000): 91B16, 91B06 Journal of Economic Literature Classification: D81, D82     

Cooperative distributed architecture for mashups

Since the advent of Web 2.0, personalised applications such as mashups have become widely popular. Mashups enable end-users to fetch data from distributed data sources, and refine it based on their personal needs. This high degree of personalisation that mashups offer comes at the expense of performance and scalability. These scalability challenges are exacerbated by the centralised architectures of current mashup platforms. In this paper, we address the performance and scalability issues by designing CoMaP – a distributed mashup platform. CoMaP’s architecture comprises of several cooperative mashup processing nodes distributed over the Internet upon which mashups can, fully or partially, be executed. CoMaP incorporates a dynamic and efficient scheme for deploying mashups on the processing nodes. Our scheme considers a number of parameters such as variations in link delays and bandwidths, and loads on mashup processing nodes. CoMaP includes effective and low-cost mechanisms for balancing loads on the processing nodes as well for handling node failures. Furthermore, we propose novel techniques that leverage keyword synonyms, ontologies and caching to enhance end-user experience. This paper reports several experiments to comprehensively study CoMaP’s performance. The results demonstrate CoMaP’s benefits as a scalable distributed mashup platform.     

分布式通信流分析系统的实现

文章介绍了通信流分析以及匿名通信的研究现状,并分析了现在研究通信流分析所采用的几种流分析工具,指出他们对于匿名通信的通信流分析的不足之处,最后,提出了适应于匿名通信的分布式通信流分析系统的实现方法。     

中间件与多层分布式体系技术

传统两层模式已无法适应开放系统中实现大规模的关键业务的要求，以交易中间件为基础框架的多层分布式体系应运而生，它支持分布计算，提供跨网络、硬件和OS平台的透明性的应用或服务的交互、且支持标准的协议、接口等。     

中间件与多层分布式体系技术

传统两层模式已无法适应开放系统中实现大规模的关键业务的要求,以交易中间件为基础框架的多层分布式体系应运而生,它支持分布计算,提供跨网络、硬件和OS平台的透明性的应用或服务的交互、且支持标准的协议、接口等。     

Optimal pollution control with distributed delays

We present a model of optimal stock pollution control with general distributed delays in the stock accumulation dynamics. Using generic functional forms and a distribution structure covering a wide range of distributions, we solve analytically the complex dynamic system that arises from the introduction of these distributed delays. From a theoretical standpoint, our contribution extends the dynamic optimization literature that focused on single discrete delays and develops an original method to address control problems written as mixed type functional differential equations with general kernels. Our results show the qualitative impact of acknowledging these distributed delays on the optimal pollution paths dynamics. We study analytically the properties of the dynamics and we identify the conditions for the occurrence of limit cycles. This theoretical work contributes to the design of efficient environmental policies in the presence of complex delays.     

Online distributed learning in wind power forecasting

Forecasting wind power generation up to a few hours ahead is of the utmost importance for the efficient operation of power systems and for participation in electricity markets. Recent statistical learning approaches exploit spatiotemporal dependence patterns among neighbouring sites, but their requirement of sharing confidential data with third parties may limit their use in practice. This explains the recent interest in distributed, privacy preserving algorithms for high-dimensional statistical learning, e.g. with auto-regressive models. The few approaches that have been proposed are based on batch learning. However, these approaches are potentially computationally expensive and do not allow for the accommodation of nonstationary characteristics of stochastic processes like wind power generation. This paper closes the gap between online and distributed optimisation by presenting two novel approaches that recursively update model parameters while limiting information exchange between wind farm operators and other potential data providers. A simulation study compared the convergence and tracking ability of both approaches. In addition, a case study using a large dataset from 311 wind farms in Denmark confirmed that online distributed approaches generally outperform existing batch approaches while preserving privacy such that agents do not have to actively share their private data.     

Density estimation for randomly distributed circular objects

Summary Nearest neighbour methods traditionally used to estimate density of a sessile biological population treat individuals as points. The present paper suggests distance-based density estimators which treat individuals as circles with variable areas. Distribution of distance between a sample point and thek-th (k = 1, 2, 3, …) nearest circle is derived. Maximum likelihood estimator of density is obtained from a random sample of point tok-th order distances. Assuming a skewed distribution for the circle radius, moment estimators of density and mean circle area are derived.     

Orchestrating distributed data governance in open social innovation

Open Social Innovation (OSI) involves the collaboration of multiple stakeholders to generate ideas, and develop and scale solutions to make progress on societal challenges. In an OSI project, stakeholders share data and information, utilize it to better understand a problem, and combine data with digital technologies to create digitally-enabled solutions. Consequently, data governance is essential for orchestrating an OSI project to facilitate the coordination of innovation. Because OSI brings multiple stakeholders together, and each stakeholder participates voluntarily, data governance in OSI has a distributed nature. In this essay we put forward a framework consisting of three dimensions allowing an inquiry into the effectiveness of such distributed data governance: (1) openness (i.e., freely sharing data and information), (2) accountability (i.e., willingness to be held responsible and provide justifications for one's conduct) and (3) power (i.e., resourceful actors' ability to impact other stakeholder's actions). We apply this framework to reflect on the OSI project #WirVsVirus (“We versus virus” in English), to illustrate the challenges in organizing effective distributed data governance, and derive implications for research and practice.     

An adaptive distributed localisation in wireless sensor network

Many applications of wireless sensor networks (WSN) in industry can benefit from fine-grained localisation. In this paper, we propose an accurate, distributed localisation method which uses connectivity measurements to localise sensor nodes in WSN. The proposed method is based on a manifold learning embedding algorithm that adaptively emphasises the most accurate range measurements and naturally accounts for communication constraints within the WSN. Each node adaptively chooses a neighbourhood of sensor, updates its position estimate by minimising a local cost function and then passes this update to neighbouring sensors. Simulation results demonstrate that the proposed method is more robust to measurement errors than previous proposals and it can achieve comparable results using many fewer anchor nodes than previous methods.     

Recent developments of the autoregressive distributed lag modelling framework

We review the literature on the autoregressive distributed lag (ARDL) model, from its origins in the analysis of autocorrelated trend stationary processes to its subsequent applications in the analysis of cointegrated non-stationary time series. We then survey several recent extensions of the ARDL model, including asymmetric and non-linear generalisations of the ARDL model, the quantile ARDL model, the pooled mean group dynamic panel data model and the spatio-temporal ARDL model.     

配电自动化系统中分布式终端的设计与应用

文章通过对配电终端市场的功能需求分析,设计出了具有故障自动检测与识别功能、提供稳定的工作电源、能够适应户外恶劣条件等功能的智能终端装置,并通过系统调试、现场使用,验证其可靠性。