University of Bremen

About: University of Bremen is a education organization based out in Bremen, Germany. It is known for research contribution in the topics: Population & Glacial period. The organization has 14563 authors who have published 37279 publications receiving 970381 citations. The organization is also known as: Universität Bremen.

A multilevel relaxation algorithm for simultaneous localization and mapping

Abstract: This paper addresses the problem of simultaneous localization and mapping (SLAM) by a mobile robot. An incremental SLAM algorithm is introduced that is derived from multigrid methods used for solving partial differential equations. The approach improves on the performance of previous relaxation methods for robot mapping, because it optimizes the map at multiple levels of resolution. The resulting algorithm has an update time that is linear in the number of estimated features for typical indoor environments, even when closing very large loops, and offers advantages in handling nonlinearities compared with other SLAM algorithms. Experimental comparisons with alternative algorithms using two well-known data sets and mapping results on a real robot are also presented.

Cigarette smoking and lung cancer – relative risk estimates for the major histological types from a pooled analysis of case-control studies

Abstract: Lung cancer is mainly caused by smoking, but the quantitative relations between smoking and histologic subtypes of lung cancer remain inconclusive. By using one of the largest lung cancer datasets ever assembled, we explored the impact of smoking on risks of the major cell types of lung cancer. This pooled analysis included 13,169 cases and 16,010 controls from Europe and Canada. Studies with population controls comprised 66.5% of the subjects. Adenocarcinoma (AdCa) was the most prevalent subtype in never smokers and in women. Squamous cell carcinoma (SqCC) predominated in male smokers. Age-adjusted odds ratios (ORs) were estimated with logistic regression. ORs were elevated for all metrics of exposure to cigarette smoke and were higher for SqCC and small cell lung cancer (SCLC) than for AdCa. Current male smokers with an average daily dose of >30 cigarettes had ORs of 103.5 (95% confidence interval (CI): 74.8-143.2) for SqCC, 111.3 (95% CI: 69.8-177.5) for SCLC and 21.9 (95% CI: 16.6-29.0) for AdCa. In women, the corresponding ORs were 62.7 (95% CI: 31.5-124.6), 108.6 (95% CI: 50.7-232.8) and 16.8 (95% CI: 9.2-30.6), respectively. Although ORs started to decline soon after quitting, they did not fully return to the baseline risk of never smokers even 35 years after cessation. The major result that smoking exerted a steeper risk gradient on SqCC and SCLC than on AdCa is in line with previous population data and biological understanding of lung cancer development.

An Architectural Approach Towards the Future Internet of Things

Abstract: Many of the initial developments towards the Internet of Things have focused on the combination of Auto-ID and networked infrastructures in businessto- business logistics and product life cycle applications. However, a future Internet of Things can provide a broader vision and also enable everyone to access and contribute rich information about things and locations. The success of social networks to share experience and personalised insights shows also great potential for integration with business-centric applications. The integration and interoperability with mainstream business software platforms can be enhanced and extended by real-time analytics, business intelligence and agent-based autonomous services. Information sharing may be rewarded through incentives, thus transforming the Internet of Things from a cost-focused experiment to a revenue-generating infrastructure to enable trading of enriched information and accelerate business innovation. Mash-ups and end-user programming will enable people to contribute to the Internet of Things with data, presentation and functionality. Things-generated physical world content and events from Auto-ID, sensors, actuators or meshed networks will be aggregated and combined with information from virtual worlds, such as business databases and Web 2.0 applications, and processed based on new business intelligence concepts. Direct action on the physical world will be supported through machine-interfaces and introduction of agile strategies. This chapter aims to provide a concept for a future architecture of the Internet of Things, including a definition, a review of developments, a list of key requirements and a technical design for possible implementation of the future Internet of Things. As open issues, the evaluation of usability by stakeholders in user-centric as well as business-centric scenarios is discussed and the need for quantifying costs and benefits for businesses, consumers, society and the environment is emphasised. Finally, guidelines are derived, for use by researchers as well as practitioners.