Passively Track WiFi Users with an Enhanced Particle Filter using Power-based Ranging

Passive positioning systems produce user location information for third-party providers of positioning services. Since the tracked wireless devices do not participate in the positioning process, passive positioning can only rely on simple, measurable radio signal parameters, such as timing or power information. In this work, we provide a passive tracking system for WiFi signals with an enhanced particle filter using fine-grained power-based ranging. Our proposed particle filter provides an improved likelihood function on observation parameters and is equipped with a modified coordinated turn model to address the challenges in a passive positioning system. The anchor nodes for WiFi signal sniffing and target positioning use software defined radio techniques to extract channel state information to mitigate multipath effects. By combining the enhanced particle filter and a set of enhanced ranging methods, our system can track mobile targets with an accuracy of 1.5m for 50% and 2.3m for 90% in a complex indoor environment. Our proposed particle filter significantly outperforms the typical bootstrap particle filter, extended Kalman filter and trilateration algorithms.

Shifts in microbial communities do not explain the response of grassland ecosystem function to plant functional composition and rainfall change

Ecosystem functioning in grasslands is regulated by a range of biotic and abiotic factors, and the role of microbial communities in regulating ecosystem function has been the subject of much recent scrutiny. However, there are still knowledge gaps regarding the impacts of rainfall and vegetation change upon microbial communities and the implications of these changes for ecosystem functioning. We investigated this issue using data from an experimental mesotrophic grassland study in south-east England, which had been subjected to four years of rainfall and plant functional composition manipulations. Soil respiration, nitrogen and phosphorus stocks were measured, and the abundance and community structure of soil microbes were characterised using quantitative PCR and multiplex-TRFLP analysis, respectively. Bacterial community structure was strongly related to the plant functional composition treatments, but not the rainfall treatment. However, there was a strong effect of both rainfall change and plant functional group upon bacterial abundance. There was also a weak interactive effect of the two treatments upon fungal community structure, although fungal abundance was not affected by either treatment. Next, we used a statistical approach to assess whether treatment effects on ecosystem function were regulated by the microbial community. Our results revealed that ecosystem function was influenced by the experimental treatments, but was not related to associated changes to the microbial community. Overall, these results indicate that changes in fungal and bacterial community structure and abundance play a relatively minor role in determining grassland ecosystem function responses to precipitation and plant functional composition change, and that direct effects on soil physical and chemical properties and upon plant and microbial physiology may play a more important role.

Minimized Extracorporeal Circulation does not impair cognitive brain function after coronary artery bypass grafting

Gebiet: Chirurgie Abstract: Minimized Extracorporeal Circulation does not impair cognitive brain function after coronary artery bypass grafting – – Objectives – Objective evaluation of the impact of minimized extracorporeal circulation (MECC) on perioperative cognitive brain function in coronary bypass grafting (CABG) by Electroencephalogram (EEG) P 300 wave event related potentials (ERP) and number connection test ( NCT) as metrics of cognitive function. – – Methods – Cognitive brain function was assessed in 31 patients with a mean age of 65y (Standard Deviation/SD 10) undergoing coronary artery bypass grafting (CABG) by the use of MECC with P300 auditory evoked potentials (peak latencies in milliseconds [ms]) directly prior to intervention, 7 days after and 3 month later. Number connection test (NCT), serving as method of control, was performed simultaneously in all patients. – – Results – Seven days following CABG, cognitive P300 evoked potentials were comparable to preoperative baseline values (vertex [Cz] 376 (SD 11) ms vs. 378 (18) ms, p=0.39, frontal [Fz] 377 (11) vs. 379 (21) ms, p=0.53). Cognitive brain function showed at 3 months compared to baseline values ([Cz] 376 (11) ms vs. 371 (14 ms) p=0.09, [Fz] 377 (11) ms vs. 371 (15) ms, p=0.04. Between the first postoperative measurement and 3 months later, significant improvement was observed ([Cz] 378 (18) ms vs. 371 (14) ms, p=0.03, [Fz] 379 (21) vs. 371 (15) ms, p=0.02). Similar clearly corresponding patterns could be obtained via number connection test. Results could be confirmed in repeated measures analysis of variance for Cz (p = 0.05) and (Fz) results (p = 0.04). – – Conclusions

A novel colourimetric technique to assess chewing function using two-coloured specimens: Validation and application

OBJECTIVES Chewing efficiency may be evaluated using cohesive specimen, especially in elderly or dysphagic patients. The aim of this study was to evaluate three two-coloured chewing gums for a colour-mixing ability test and to validate a new purpose built software (ViewGum©). METHODS Dentate participants (dentate-group) and edentulous patients with mandibular two-implant overdentures (IOD-group) were recruited. First, the dentate-group chewed three different types of two-coloured gum (gum1-gum3) for 5, 10, 20, 30 and 50 chewing cycles. Subsequently the number of chewing cycles with the highest intra- and inter-rater agreement was determined visually by applying a scale (SA) and opto-electronically (ViewGum©, Bland-Altman analysis). The ViewGum© software determines semi-automatically the variance of hue (VOH); inadequate mixing presents with larger VOH than complete mixing. Secondly, the dentate-group and the IOD-group were compared. RESULTS The dentate-group comprised 20 participants (10 female, 30.3±6.7 years); the IOD-group 15 participants (10 female, 74.6±8.3 years). Intra-rater and inter-rater agreement (SA) was very high at 20 chewing cycles (95.00-98.75%). Gums 1-3 showed different colour-mixing characteristics as a function of chewing cycles, gum1 showed a logarithmic association; gum2 and gum3 demonstrated more linear behaviours. However, the number of chewing cycles could be predicted in all specimens from VOH (all p<0.0001, mixed linear regression models). Both analyses proved discriminative to the dental state. CONCLUSION ViewGum© proved to be a reliable and discriminative tool to opto-electronically assess chewing efficiency, given an elastic specimen is chewed for 20 cycles and could be recommended for the evaluation of chewing efficiency in a clinical and research setting. CLINICAL SIGNIFICANCE Chewing is a complex function of the oro-facial structures and the central nervous system. The application of the proposed assessments of the chewing function in geriatrics or special care dentistry could help visualising oro-functional or dental comorbidities in dysphagic patients or those suffering from protein-energy malnutrition.

Effect of patient accrual patterns on power and size of log-rank test for time-to-event outcome in clinical trials

The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^

The causal relationships in mean and variance between stock returns and foreign institutional investment in India

This paper examines the causalities in mean and variance between stock returns and Foreign Institutional Investment (FII) in India. The analysis in this paper applies the Cross Correlation Function approach from Cheung and Ng (1996), and uses daily data for the timeframe of January 1999 to March 2008 divided into two periods before and after May 2003. Empirical results showed that there are uni-directional causalities in mean and variance from stock returns to FII flows irrelevant of the sample periods, while the reverse causalities in mean and variance are only found in the period beginning with 2003. These results point to FII flows having exerted an impact on the movement of Indian stock prices during the more recent period.

The Confucius institutes and China's soft power

The Confucius Institutes have been established by the Chinese government which operates them in collaboration with foreign universities and educational institutions in order to promote understanding of the Chinese language and culture. The first Confucius Institute opened its doors in Seoul, South Korea in 2004. Within the past seven years, 353 Confucius Institutes and 473 Confucius Classrooms have been established in 104 countries and regions. It is quite unusual for a language school to be able to make progress so rapidly. These developments raise a series of basic questions. First, what are the Confucius Institutes? What are their purpose and function? How have they been able to multiply so quickly? Are Confucius Institutes instruments of China's soft power? This article seeks to answer these questions by analyzing the details behind the establishment of Confucius Institutes, their organizational mechanism, and their activities. This paper concludes that due to insufficiency of cultural content and key concepts which can typify contemporary China, it is hard to see Confucius Institutes as China's soft power.

From irradiance to output power fluctuations: the pv plant as a low pass filter

The power generated by large grid-connected photovoltaic (PV) plants depends greatly on the solar irradiance. This paper studies the effects of the solar irradiance variability analyzing experimental 1-s data collected throughout a year at six PV plants, totaling 18 MWp. Each PV plant was modeled as a first order filter function based on an analysis in the frequency domain of the irradiance data and the output power signals. An empiric expression which relates the filter parameters and the PV plant size has been proposed. This simple model has been successfully validated precisely determining the daily maximum output power fluctuation from incident irradiance measurements.

Evaluación de las Prestaciones de una Red WiMAX Móvil en un Escenario de Alta Movilidad

The aim of this paper is to evaluate the performance of mobile WiMAX technology for users in a highly mobility scenario for an operating frequency of 3.5 GHz. By utilizing a modified version of the extended Erceg’s propagation model, based on the introduction of Rayleigh fading due to multipath, we have calculated the received desired power and the interference power to obtain the statistical signal-to-interference-plusnoise rate (as a function of mean value and variance of cochannel interference) and the user throughput. A rural scenario composed of a transmitting base station and users in moving vehicles along a cell sector is proposed. The obtained results about coverage and throughput have been simulated by a tool built in MATLAB

Stopping power dependence of nitrogen sputtering yields in copper nitride films under swift-ion irradiation: Exciton model approach

Nitrogen sputtering yields as high as 104 atoms/ion, are obtained by irradiating N-rich-Cu3N films (N concentration: 33 ± 2 at.%) with Cu ions at energies in the range 10?42 MeV. The kinetics of N sputtering as a function of ion fluence is determined at several energies (stopping powers) for films deposited on both, glass and silicon substrates. The kinetic curves show that the amount of nitrogen release strongly increases with rising irradiation fluence up to reaching a saturation level at a low remaining nitrogen fraction (5?10%), in which no further nitrogen reduction is observed. The sputtering rate for nitrogen depletion is found to be independent of the substrate and to linearly increase with electronic stopping power (Se). A stopping power (Sth) threshold of ?3.5 keV/nm for nitrogen depletion has been estimated from extrapolation of the data. Experimental kinetic data have been analyzed within a bulk molecular recombination model. The microscopic mechanisms of the nitrogen depletion process are discussed in terms of a non-radiative exciton decay model. In particular, the estimated threshold is related to a minimum exciton density which is required to achieve efficient sputtering rates.

High-peak-power pulse generation from a monolithic master oscillator power amplifier at 1.5 μm

We present an experimental study on the generation of high-peak-power short optical pulses from a fully integrated master-oscillator power-amplifier emitting at 1.5 μm. High-peak-power (2.7 W) optical pulses with short duration (100 ps) have been generated by gain switching the master oscillator under optimized driving conditions. The static and dynamic characteristics of the device have been studied as a function of the driving conditions. The ripples appearing in the power-current characteristics under cw conditions have been attributed to mode hopping between the master oscillator resonant mode and the Fabry-Perot modes of the entire device cavity. Although compound cavity effects have been evidenced to affect the static and dynamic performance of the device, we have demonstrated that trains of single-mode short optical pulses at gigahertz frequencies can be conveniently generated in these devices.

Bare-tether cathodic contact through thermoionic emission by low work-function materials

A new material, C12A7 : electride, which might present a work function as low as 0.6 eV and moderately high temperature stability, was recently proposed as coating for floating bare tethers. Arising from heating under space operation, current is emitted by thermionic emission along a thus coated cathodic segment. A preliminary study on the space-charge-limited (SCL) double layer in front of the cathodic segment is presented using Langmuir’s SCL electron current between cylindrical electrodes and orbital-motion-limited ion-collection sheath. A detailed calculation of current and bias profiles along the entire tether length is carried out with ohmic effects and the transition from SCL to full Richardson-Dushman emission included. Analysis shows that in the simplest drag mode, under typical orbital and tether conditions, thermionic emission leads to a short cathodic section and may eliminate the need for an active cathodic device and its corresponding gas feed requirements and power subsystem, which results in a truly “propellant-less” tether system for such basic applications as de-orbiting low earth orbit satellites.

Low work-function coating for an entirely propellantless bare electrodynamic tether

We present the possibility of a low work-function material, calcium aluminate electride, being used for a coating on a bare electrodynamic tether system. Analyses suggest that the coating would eliminate the need for an active cathodic device like a hollow cathode and, consequently, eliminate the need for an expellant to the hollow cathode, thus resulting in an electrodynamic tether system that requires no consumables. Applications include on-orbit power generation and deorbiting debris from low Earth orbit in a simple and trouble-free manner.

Statistical models for short-term wind power ramp forecasting

La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

Impact of N2 plasma power discharge on AlGaN/GaN HEMT performance

The effects of power and time conditions of in situ N2 plasma treatment, prior to silicon nitride (SiN) passivation, were investigated on an AlGaN/GaN high-electron mobility transistor (HEMT). These studies reveal that N2 plasma power is a critical parameter to control the SiN/AlGaN interface quality, which directly affects the 2-D electron gas density. Significant enhancement in the HEMT characteristics was observed by using a low power N2 plasma pretreatment. In contrast, a marked gradual reduction in the maximum drain-source current density (IDS max) and maximum transconductance (gm max), as well as in fT and fmax, was observed as the N2 plasma power increases (up to 40% decrease for 210 W). Different mechanisms were proposed to be dominant as a function of the discharge power range. A good correlation was observed between the device electrical characteristics and the surface assessment by atomic force microscopy and Kelvin force microscopy techniques.