A Time-based Passive Source Localization System for Narrow-band Signal

Time-based indoor localization has been investigated for several years but the accuracy of existing solutions is limited by several factors, e.g., imperfect synchronization, signal bandwidth and indoor environment. In this paper, we compare two time-based localization algorithms for narrow-band signals, i.e., multilateration and fingerprinting. First, we develop a new Linear Least Square (LLS) algorithm for Differential Time Difference Of Arrival (DTDOA). Second, fingerprinting is among the most successful approaches used for indoor localization and typically relies on the collection of measurements on signal strength over the area of interest. We propose an alternative by constructing fingerprints of fine-grained time information of the radio signal. We offer comprehensive analytical discussions on the feasibility of the approaches, which are backed up by evaluations in a software defined radio based IEEE 802.15.4 testbed. Our work contributes to research on localization with narrow-band signals. The results show that our proposed DTDOA-based LLS algorithm obviously improves the localization accuracy compared to traditional TDOA-based LLS algorithm but the accuracy is still limited because of the complex indoor environment. Furthermore, we show that time-based fingerprinting is a promising alternative to power-based fingerprinting.

A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration

Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.

Range-based Weighted-likelihood Particle Filter for RSS-based Indoor Tracking

Attractive business cases in various application fields contribute to the sustained long-term interest in indoor localization and tracking by the research community. Location tracking is generally treated as a dynamic state estimation problem, consisting of two steps: (i) location estimation through measurement, and (ii) location prediction. For the estimation step, one of the most efficient and low-cost solutions is Received Signal Strength (RSS)-based ranging. However, various challenges - unrealistic propagation model, non-line of sight (NLOS), and multipath propagation - are yet to be addressed. Particle filters are a popular choice for dealing with the inherent non-linearities in both location measurements and motion dynamics. While such filters have been successfully applied to accurate, time-based ranging measurements, dealing with the more error-prone RSS based ranging is still challenging. In this work, we address the above issues with a novel, weighted likelihood, bootstrap particle filter for tracking via RSS-based ranging. Our filter weights the individual likelihoods from different anchor nodes exponentially, according to the ranging estimation. We also employ an improved propagation model for more accurate RSS-based ranging, which we suggested in recent work. We implemented and tested our algorithm in a passive localization system with IEEE 802.15.4 signals, showing that our proposed solution largely outperforms a traditional bootstrap particle filter.

High-precision confocal reflection measurement for two dimensional refractive index mapping of optical fibers

We introduce a new fiber-optical approach for reflection based refractive index mapping. Our approach leads to improved stability and reliability over existing free-space confocal instruments and significantly cuts alignment efforts and reduces the number of components needed. Other than properly cleaved fiber end-faces, this setup requires no additional sample preparation. The instrument is calibrated by means of a set of samples with known refractive indices. The index steps of commercially available fibers are measured accurately down to < 10⁻³. The precision limit of the instrument is currently of the order of 10⁻⁴.

Democratic Legitimation of Trade Policy Tomorrow: TTIP, Democracy and Market in the Swiss Constitution

Free Trade Agreements (FTAs) are increasingly more concerned with regulatory convergence, rather than trade liberalisation through elimination of tariffs. This appears to result more often in so-called dynamic trade agreements, which still evolve after adoption. Further economic integration in democracies, however, depends on the support of the constituency. This article takes a closer look at the democratic legitimation of global economic integration in a case study on Switzerland. It finds that the current principles and institutions of democracy in Switzerland are unlikely to fully accommodate the new regulatory challenges of dynamic FTAs.

Evaluating the Trade-off Between Energy Efficiency and QoE in Wireless Mesh Networks

The increasing usage of wireless networks creates new challenges for wireless access providers. On the one hand, providers want to satisfy the user demands but on the other hand, they try to reduce the operational costs by decreasing the energy consumption. In this paper, we evaluate the trade-off between energy efficiency and quality of experience for a wireless mesh testbed. The results show that by intelligent service control, resources can be better utilized and energy can be saved by reducing the number of active network components. However, care has to be taken because the channel bandwidth varies in wireless networks. In the second part of the paper, we analyze the trade-off between energy efficiency and quality of experience at the end user. The results reveal that a provider's service control measures do not only reduce the operational costs of the network but also bring a second benefit: they help maximize the battery lifetime of the end-user device.

XIAP Restricts TNF- and RIP3-Dependent Cell Death and Inflammasome Activation

X-linked inhibitor of apoptosis protein (XIAP) has been identified as a potent regulator of innate immune responses, and loss-of-function mutations in XIAP cause the development of the X-linked lymphoproliferative syndrome type 2 (XLP-2) in humans. Using gene-targeted mice, we show that loss of XIAP or deletion of its RING domain lead to excessive cell death and IL-1β secretion from dendritic cells triggered by diverse Toll-like receptor stimuli. Aberrant IL-1β secretion is TNF dependent and requires RIP3 but is independent of cIAP1/cIAP2. The observed cell death also requires TNF and RIP3 but proceeds independently of caspase-1/caspase-11 or caspase-8 function. Loss of XIAP results in aberrantly elevated ubiquitylation of RIP1 outside of TNFR complex I. Virally infected Xiap−/− mice present with symptoms reminiscent of XLP-2. Our data show that XIAP controls RIP3-dependent cell death and IL-1β secretion in response to TNF, which might contribute to hyperinflammation in patients with XLP-2.

A mixed-integer linear programming approach to the optimization of event-bus schedules: a scheduling application in the tourism sector

This paper deals with “The Enchanted Journey,” which is a daily event tour booked by Bollywood-film fans. During the tour, the participants visit original sites of famous Bollywood films at various locations in Switzerland; moreover, the tour includes stops for lunch and shopping. Each day, up to five buses operate the tour. For operational reasons, however, two or more buses cannot stay at the same location simultaneously. Further operative constraints include time windows for all activities and precedence constraints between some activities. The planning problem is how to compute a feasible schedule for each bus. We implement a two-step hierarchical approach. In the first step, we minimize the total waiting time; in the second step, we minimize the total travel time of all buses. We present a basic formulation of this problem as a mixed-integer linear program. We enhance this basic formulation by symmetry-breaking constraints, which reduces the search space without loss of generality. We report on computational results obtained with the Gurobi Solver. Our numerical results show that all relevant problem instances can be solved using the basic formulation within reasonable CPU time, and that the symmetry-breaking constraints reduce that CPU time considerably.

Advanced morphological 3D magnetic resonance observation of cartilage repair tissue (MOCART) scoring using a new isotropic 3D proton-density, turbo spin echo sequence with variable flip angle distribution (PD-SPACE) compared to an isotropic 3D steady-state free precession sequence (True-FISP) and standard 2D sequences

To evaluate a new isotropic 3D proton-density, turbo-spin-echo sequence with variable flip-angle distribution (PD-SPACE) sequence compared to an isotropic 3D true-fast-imaging with steady-state-precession (True-FISP) sequence and 2D standard MR sequences with regard to the new 3D magnetic resonance observation of cartilage repair tissue (MOCART) score.

MQN-Mapplet: Visualization of Chemical Space with Interactive Maps of DrugBank, ChEMBL, PubChem, GDB-11, and GDB-13

The MQN-mapplet is a Java application giving access to the structure of small molecules in large databases via color-coded maps of their chemical space. These maps are projections from a 42-dimensional property space defined by 42 integer value descriptors called molecular quantum numbers (MQN), which count different categories of atoms, bonds, polar groups, and topological features and categorize molecules by size, rigidity, and polarity. Despite its simplicity, MQN-space is relevant to biological activities. The MQN-mapplet allows localization of any molecule on the color-coded images, visualization of the molecules, and identification of analogs as neighbors on the MQN-map or in the original 42-dimensional MQN-space. No query molecule is necessary to start the exploration, which may be particularly attractive for nonchemists. To our knowledge, this type of interactive exploration tool is unprecedented for very large databases such as PubChem and GDB-13 (almost one billion molecules). The application is freely available for download at www.gdb.unibe.ch.

First report of a multidrug-resistant Klebsiella pneumoniae of sequence type 11 causing sepsis in a free-ranging beaver (Castor fiber).

Klebsiella pneumoniae of sequence type (ST) 11 is a hyper-epidemic nosocomial clone spreading worldwide among humans and also emerging in pets. In this report, we describe a clinical case of fatal sepsis due to this multidrug-resistant (MDR) pathogen in a Eurasian beaver. The isolate showed resistance to six different classes of antimicrobials including third generation cephalosporins and fluoroquinolones. This is the first report describing the detection of a MDR K. pneumoniae ST11 in a free-ranging animal. Our finding highlights the potential for environmental dissemination of hyper-epidemic clones of K. pneumoniae and possible spread in wildlife and cause epizootics.