Multi-Party Negotiation When Agents Have Subjective Estimates of Bargaining Powers

This paper presents a method for generating Pareto-optimal solutions in multi-party negotiations. In this iterative method, decision makers (DMs) formulate proposals that yield a minimum payoff to their opponents. Each proposal belongs to the efficient frontier, DMs try to adjust to a common one. In this setting, each DM is supposed to have a given bargaining power. More precisely each DM is supposed to have a subjective estimate of the power of the different parties. We study the convergence of the method, and provide examples where there is no possible agreement resulting from it.

Epipolar geometry estimation based on evolutionary agents

This paper presents a novel approach based on the use of evolutionary agents for epipolar geometry estimation. In contrast to conventional nonlinear optimization methods, the proposed technique employs each agent to denote a minimal subset to compute the fundamental matrix, and considers the data set of correspondences as a 1D cellular environment, in which the agents inhabit and evolve. The agents execute some evolutionary behavior, and evolve autonomously in a vast solution space to reach the optimal (or near optima) result. Then three different techniques are proposed in order to improve the searching ability and computational efficiency of the original agents. Subset template enables agents to collaborate more efficiently with each other, and inherit accurate information from the whole agent set. Competitive evolutionary agent (CEA) and finite multiple evolutionary agent (FMEA) apply a better evolutionary strategy or decision rule, and focus on different aspects of the evolutionary process. Experimental results with both synthetic data and real images show that the proposed agent-based approaches perform better than other typical methods in terms of accuracy and speed, and are more robust to noise and outliers.

A Universal Flow Regime Map for Horizontal Two-Phase Flow in Pipes

A new universal flow map has been developed for two-phase co-current flow. The map has been successfully tested against wide variety of data. Flow regime transition predictors suggested by other authors have been shown to be useful. New transitional models are proposed for the stratified to annular regimes, blow through slug and intermittent regimes.

The mouse and human IGSF6 (DORA) genes map to the inflammatory bowel disease 1 locus and are embedded in an intron of a gene of unknown function.

We have previously characterized IGSF6 (DORA), a novel member of the immunoglobulin superfamily (IGSF) from human and rat expressed in dendritic and myeloid cells. Using a probe from the open reading frame of the rat cDNA, we isolated a cosmid which contains the entire mouse gene. By comparative analysis and reverse transcriptase polymerase chain reaction, we defined the intron/exon structure and the mRNA of the mouse gene and, with respect to human BAC clones, the human gene. The genes span 10 kb (mouse) and 12 kb (human), with six exons arranged in a manner similar to other members of the IGSF. All intron/exon boundaries follow the GT-AG rule. Expression of the mouse Igsf6 gene is restricted to cells of the immune system, particularly macrophages. Northern blot revealed a single mRNA of 2.5 kb, in contrast to the human gene which is expressed as two mRNAs of 1 and 2.5 kb. The human and mouse genes were localized to a locus associated with inflammatory bowel disease. Analysis of the flanking regions of the Igsf6 gene revealed the presence of an unrelated gene, transcribed from the opposite strand of the DNA and oriented such that the Igsf6 gene is encoded entirely within an intron. An identical organization is seen in human. This gene of unknown function is transcribed and processed, contains homologues in Caenorhabditis elegans and prokaryotes, and is expressed in most organs in the mouse.

Simulation or measurement: the effect of radio map creation on indoor WLAN-based localisation accuracy

Indoor wireless network based client localisation requires the use of a radio map to relate received signal strength to specific locations. However, signal strength measurements are time consuming, expensive and usually require unrestricted access to all parts of the building concerned. An obvious option for circumventing this difficulty is to estimate the radio map using a propagation model. This paper compares the effect of measured and simulated radio maps on the accuracy of two different methods of wireless network based localisation. The results presented indicate that, although the propagation model used underestimated the signal strength by up to 15 dB at certain locations, there was not a signigicant reduction in localisation performance. In general, the difference in performance between the simulated and measured radio maps was around a 30 % increase in rms error