Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1:3m for mean accuracy and 2:2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Achievements and Challenges 20 Years after Beijing: A View from Switzerland

Despite being one of the world’s wealthiest countries and most modern economies, in Switzerland gender equality remains an elusive challenge. Paid maternity leave, legal abortion and an increase in women’s educational attainment are some of the milestones achieved since 1995, when the country was one of 189 states to adopt the Beijing Declaration and Platform for Action at the Fourth World Conference on Women. But while legal gender equality may be nearly achieved, much remains to be done to achieve gender equality in practice. Rigid gender stereotypes, wage discrimination, women’s heavy care burden, segregation in the workplace, violence against women, under-representation of women in political and economic decision making, and structural obstacles to reconciling family duties with employment still stand in the way of gender equality. In order to realize gender equality, government, employers, politicians and civil society all need to take concrete and coordinated actions. These range from changes in the educational sector, in the labour market and in the social security system to an active foreign policy that promotes women’s human rights.

Securing one's livelihood. Philanthropy in a mixed economy of welfare in the early 20th century

Since the late 19th century different social actors have played an important role in providing social security in Switzerland. Cooperatives, philanthropic organisations, social insurances, and the poor relief of the communes were all part of a "mixed economy of welfare". This article examines how the different actors in this "mixed economy" worked together, and asks what forms of help they supplied. It raises the question of whether a dichotomy between public and private forms of relief can be traced in the Swiss case. Did democratically legitimised processes of redistribution shape the social security system? Or was social security rather funded by private relief programs? The author argues that in the early 20th century, a complex public-private mix structured the Swiss welfare state and the poor often depended on both public and private funding. In this system, financially potent philanthropic organisations successfully contested the legal power of public actors.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranging and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Current patch test results with the European baseline series and extensions to it from the 'European Surveillance System on Contact Allergy' network, 2007-2008

The pattern of contact sensitization to the supposedly most important allergens assembled in the baseline series differs between countries, presumably at least partly because of exposure differences. Objectives. To describe the prevalence of contact sensitization to allergens tested in consecutive patients in the years 2007 and 2008, and to discuss possible differences.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Mobile competence network for community health workers in rural Myanmar: a supportive information system that facilitates the improvement of health services.

The goal of this project is the development of international cooperation for fostering solutions to provide better access to basic healthcare services.

B cells as a critical node in the microbiota-host immune system network.

Mutualism with our intestinal microbiota is a prerequisite for healthy existence. This requires physical separation of the majority of the microbiota from the host (by secreted antimicrobials, mucus, and the intestinal epithelium) and active immune control of the low numbers of microbes that overcome these physical and chemical barriers, even in healthy individuals. In this review, we address how B-cell responses to members of the intestinal microbiota form a robust network with mucus, epithelial integrity, follicular helper T cells, innate immunity, and gut-associated lymphoid tissues to maintain host-microbiota mutualism.

Cognitive-Behavioural Analysis System of Psychotherapy (CBASP), a drug, or their combination: differential therapeutics for persistent depressive disorder: a study protocol of an individual participant data network meta-analysis.

INTRODUCTION Despite important advances in psychological and pharmacological treatments of persistent depressive disorders in the past decades, their responses remain typically slow and poor, and differential responses among different modalities of treatments or their combinations are not well understood. Cognitive-Behavioural Analysis System of Psychotherapy (CBASP) is the only psychotherapy that has been specifically designed for chronic depression and has been examined in an increasing number of trials against medications, alone or in combination. When several treatment alternatives are available for a certain condition, network meta-analysis (NMA) provides a powerful tool to examine their relative efficacy by combining all direct and indirect comparisons. Individual participant data (IPD) meta-analysis enables exploration of impacts of individual characteristics that lead to a differentiated approach matching treatments to specific subgroups of patients. METHODS AND ANALYSIS We will search for all randomised controlled trials that compared CBASP, pharmacotherapy or their combination, in the treatment of patients with persistent depressive disorder, in Cochrane CENTRAL, PUBMED, SCOPUS and PsycINFO, supplemented by personal contacts. Individual participant data will be sought from the principal investigators of all the identified trials. Our primary outcomes are depression severity as measured on a continuous observer-rated scale for depression, and dropouts for any reason as a proxy measure of overall treatment acceptability. We will conduct a one-step IPD-NMA to compare CBASP, medications and their combinations, and also carry out a meta-regression to identify their prognostic factors and effect moderators. The model will be fitted in OpenBUGS, using vague priors for all location parameters. For the heterogeneity we will use a half-normal prior on the SD. ETHICS AND DISSEMINATION This study requires no ethical approval. We will publish the findings in a peer-reviewed journal. The study results will contribute to more finely differentiated therapeutics for patients suffering from this chronically disabling disorder. TRIAL REGISTRATION NUMBER CRD42016035886.