Securing Passive Objects in Mobile Ad-Hoc Peer-to-Peer Networks

Security and privacy in mobile ad-hoc peer-to-peer environments are hard to attain, especially when working with passive objects (without own processing power, e.g. RFID tags). This paper introduces a method for integrating such objects into a peer-to-peer environment without infrastructure components while providing a high level of privacy and security for peers interacting with objects. The integration is done by associating public keys to passive objects, which can be used by peers to validate proxies (peers additionally acting on behalf of objects). To overcome the problem of limited storage capacity on small embedded objects, ECC keys are used.     

On-Line Dial-a-Ride Problems Under a Restricted Information Model

In on-line dial-a-ride problems servers are traveling in some metric space to serve requests for rides which are presented over time. Each ride is characterized by two points in the metric space, a source, the starting point of the ride, and a destination, the endpoint of the ride. Usually it is assumed that at the release of a request, complete information about the ride is known. We diverge from this by assuming that at the release of a ride, only information about the source is given. At visiting the source, the information about the destination will be made available to the servers. For many practical problems, our model is closer to reality. However, we feel that the lack of information is often a choice, rather than inherent to the problem: additional information can be obtained, but this requires investments in information systems. In this paper we give mathematical evidence that for the problem under study it pays to invest.     

双享空间的幽默合辑

Extract荷兰Den Bosh的一怕老建筑,最近迎来自己的新生。那是座建于20世纪的双层Loft,在设计师Roderick Vos的改造下,它的空间一半被用于零售展示,一半用于办公思考。它模糊了设计师与顾客、艺术与生活的界限,令每一位到访者都能在幽默而单纯的氛围中,领略双享空间的专业设计精神。     

Lung Cancer Assistant: a hybrid clinical decision support application for lung cancer care

Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments.     

Direct comparison of Eulerian–Eulerian and Eulerian–Lagrangian simulations for particle-laden vertical channel flow

Particle-laden flows in a vertical channel were simulated using an Eulerian–Eulerian, Anisotropic Gaussian (EE-AG) model. Two sets of cases varying the overall mass loading were done using particle sizes corresponding to either a large or small Stokes number. Primary and turbulent statistics were extracted from these results and compared with counterparts collected from Eulerian–Lagrangian (EL) simulations. The statistics collected from the small Stokes number particle cases correspond well between the two models, with the EE-AG model replicating the transition observed using the EL model from shear-induced turbulence to relaminarization to cluster-induced turbulence as the mass loading increased. The EE-AG model was able to capture the behavior of the EL simulations only at the largest particle concentrations using the large Stokes particles. This is due to the limitations involved with employing a particle-phase Eulerian model (as opposed to a Lagrangian representation) for a spatially intermittent system that has a low particle number concentration.