CSI-based sliding window fingerprinting method tailored for a signal blocking environment in VLP systems.

In visible light indoor positioning systems, the localization performance of the received signal strength (RSS)-based fingerprinting algorithm would drop dramatically due to the occlusion of the line-of-sight (LOS) signal caused by randomly moving people or objects. A sliding window fingerprinting (SWF) algorithm based on channel state information (CSI) is put forward to enhance the accuracy and robustness of indoor positioning in this work. The core idea behind SWF is to combine CSI with sliding matching. The sliding window is used to match the received CSI and the fingerprints in the database twice to obtain the optimal matching value and reduce the interference caused by the lack of the LOS signal. On this premise, in order to reflect the different contributions of various paths in CSI to the calculation of match values, a weighted sliding window fingerprinting (W-SWF) is also proposed for the purpose of further improving the accuracy of fingerprint matching. A 4 m × 4 m × 3 m indoor multipath scene with four LEDs is established to evaluate the positioning performance. The simulation results reveal that the mean errors of the proposed method are 0.20 cm and 1.43 cm respectively when the LOS signal of 1 or 2 LEDs is blocked. Compared with the traditional RSS algorithm, the weighted k-nearest neighbor (WKNN) algorithm, and the adaptive residual weighted k-nearest neighbor (ARWKNN) algorithm, the SWF algorithm achieves over 90% improvement in terms of mean error and root mean square error (RMSE).

RSS-based visible light positioning based on channel state information.

As a result of the influence of indoor multipath effects, visible light positioning (VLP) technology based on the received signal strength (RSS) has difficulty providing stable and highly accurate position estimation. In order to cope with this challenge, a trilateration-based positioning method using channel state information (CSI) is proposed. Two algorithms that can estimate the number of channel paths are studied, which are the prerequisites for the obtaining of an accurate ratio of received power of the line-of-sight (LOS) path to total received power. Unlike traditional trilateration positioning methods where total received power is used, the proposed method introduces CSI as a means of estimating the received power of the LOS path, which it uses for ranging. By reducing interference from the reflected paths in the received power, the proposed method has high-precision and high-reliability positioning capabilities. The positioning performance of the proposed method in an indoor environment with four LED bulbs and a single photodetector (PD) is evaluated through simulation. The simulation results demonstrate that the proposed method provides an average accuracy of 6.1 cm and a maximum positioning error of 17.7 cm in a cubic space with a size of 4 m×4 m×3 m. Compared to the existing least-squares (LS) method that uses total received power, the new method achieves approximately 83% improvement in the mean error of positioning and 81% in root mean square error (RMSE).

A new approach to entropy and similarity measure of vague soft sets.

We focus our discussion on the uncertainty measures of vague soft sets. We propose axiomatic definitions of similarity measure and entropy for vague soft sets. Furthermore, we present a new category of similarity measures and entropies for vague soft sets. The basic properties of these measures are discussed and the relationships among these measures are analyzed.

Updatable privacy-preserving K -nearest neighbor query in location-based s-ervice.

The K -nearest neighbor ( K -NN) query is an important query in location-based service (LBS), which can query the nearest k points to a given point, and provide some convenient services such as interest recommendations. Hence the privacy protection issue of K -NN query has been a popular research area, protecting the information of queries and the queried results, especially in the information era. However, most of existing schemes fail to consider the privacy protection of location points already stored on servers. Or some schemes support no update of location points. In this paper, we present an updatable and privacy-preserving K -NN query scheme to address the above two issues. Concretely, our scheme utilizes the K D-tree ( K -Dimensional tree) to store the location points of data owners in location service provider and encrypts the points with a distributed double-trapdoor public-key cryptosystem. Then, based on the Ciphertext Comparison Protocol and Ciphertext Euclidean Distance Calculation Protocol, our scheme can protect the privacy of location and query contents. Experimental analyses show our proposal supports some new location points for a fixed location service provider. Moreover, the queried results show a high accuracy of more than 95%.

Privacy-Preserving Multi-Class Support Vector Machine Model on Medical Diagnosis.

With the rapid development of machine learning in the medical cloud system, cloud-assisted medical computing provides a concrete platform for remote rapid medical diagnosis services. Support vector machine (SVM), as one of the important algorithms of machine learning, has been widely used in the field of medical diagnosis for its high classification accuracy and efficiency. In some existing schemes, healthcare providers train diagnostic models with SVM algorithms and provide online diagnostic services to doctors. Doctors send the patient's case report to the diagnostic models to obtain the results and assist in clinical diagnosis. However, case report involves patients' privacy, and patients do not want their sensitive information to be leaked. Therefore, the protection of patient's privacy has become an important research direction in the field of online medical diagnosis. In this paper, we propose a privacy-preserving medical diagnosis scheme based on multi-class SVMs. The scheme is based on the distributed two trapdoors public key cryptosystem (DT-PKC) and Boneh-Goh-Nissim (BGN) cryptosystem. We design a secure computing protocol to compute the core process of the SVM classification algorithm. Our scheme can deal with both linearly separable data and nonlinear data while protecting the privacy of user data and support vectors. The results show that our scheme is secure, reliable, scalable with high accuracy.

Cost-benefit analysis of preventing nosocomial bloodstream infections among hemodialysis patients in Canada in 2004.

OBJECTIVES: Hemodialysis-associated bloodstream infection (BSI) is a significant public health problem because the number of hemodialysis patients in Canada had doubled from 1996 to 2005.Our study aimed to determine the costs of nosocomial BSIs in Canada and estimate the investment expenses for establishing infection control programs in general hospitals and conduct cost-benefit analysis. MATERIALS AND METHODS: The data from the Canadian Nosocomial Infection Surveillance Program was used to estimate the incidence rate of nosocomial BSI. We used Canadian Institute of Health Information data to estimate the extra costs of BSIs per stay across Canada in 2004. The cost of establishing and maintaining an infection control program in 1985 was estimated by the US Centers for Disease Control and Prevention and converted into 2004 Canadian costs. The possible 20% to 30% reduction of total nosocomial BSIs was hypothesized. RESULTS: A total of 2524 hemodialysis-associated BSIs were projected among 15,278 hemodialysis patients in Canada in 2004. The total annual costs to treat BSIs were estimated to be CDN$49.01 million. Total investment costs in prevention and human resources were CDN$8.15 million. The savings of avoidable medical costs after establishing infection control programs were CDN$14.52 million. The benefit/cost ratio was 1.0 to 1.8:1. CONCLUSION: Our study provides evidence that the economic benefit from implementing infection control programs could be expected to be well in excess of additional cost postinfection if the reduction of BSI can be reduced by 20% to 30%. Infection control offered double benefits: saving money while simultaneously improving the quality of care.

Risk of severe outcomes among patients admitted to hospital with pandemic (H1N1) influenza.

BACKGROUND: We describe the disease characteristics and outcomes, including risk factors for admission to intensive care unit (ICU) and death, of all patients in Canada admitted to hospital with pandemic (H1N1) influenza during the first five months of the pandemic. METHODS: We obtained data for all patients admitted to hospital with laboratory-confirmed pandemic (H1N1) influenza reported to the Public Health Agency of Canada from Apr. 26 to Sept. 26, 2009. We compared inpatients who had nonsevere disease with those who had severe disease, as indicated by admission to ICU or death. RESULTS: A total of 1479 patients were admitted to hospital with confirmed pandemic (H1N1) influenza during the study period. Of these, 1171 (79.2%) did not have a severe outcome, 236 (16.0%) were admitted to ICU and survived, and 72 (4.9%) died. The median age was 23 years for all of the patients, 18 years for those with a nonsevere outcome, 34 years for those admitted to ICU who survived and 51 years for those who died. The risk of a severe outcome was elevated among those who had an underlying medical condition and those 20 years of age and older. A delay of one day in the median time between the onset of symptoms and admission to hospital increased the risk of death by 5.5%. The risk of a severe outcome remained relatively constant over the five-month period. INTERPRETATION: The population-based incidence of admission to hospital with laboratory-confirmed pandemic (H1N1) influenza was low in the first five months of the pandemic in Canada. The risk of a severe outcome was associated with the presence of one or more underlying medical conditions, age of 20 years or more and a delay in hospital admission.

Numerical Study on Transient State of Inductive Fault Current Limiter Based on Field-Circuit Coupling Method.

As the capacity of the power grid continues to expand, high-level fault currents might be caused during a contingency, and the problem of short-circuit current over-limitation is imminent. The high-temperature superconducting (HTS) fault current limiter (FCL) is an effective method to solve this problem. In this paper, a transient numerical model for the process of limiting current in the inductive FCL is proposed. The model is based on the coupling of multiphysics finite element simulation and a circuit model. The voltage source is used as input, which can simulate the macroscopic characteristics in the process of limiting current, such as the voltage and current waveforms, and can also simulate microscopic characteristics, such as temperature, magnetic field, and electrodynamic force distribution. The short-circuit experimental data of an air core inductive superconducting fault current limiter (SFCL) prototype was compared with the simulation results to verify the reliability of the simulation.

[Serum S100 protein and radiation-induced brain injury in astrocytoma patients].

OBJECTIVE: To study the value of serum S100 protein in the diagnosis of radiation-induced brain injury in astrocytoma patients. METHODS: Serum S100 protein levels were detected by enzyme-linked immunosorbent assay in 86 astrocytoma patients in the course of radiotherapy. RESULTS: The positivity rates of serum S100 protein before, in the middle of and after radiotherapy were 0, 9.3% (8/86) and 19.8% (17/86), respectively, showing significant differences (P<0.05) between these time points for measurement. CONCLUSION: High levels of serum S100 protein are associated with radiation-induced brain injury in astrocytoma patients and may serve as the marker for early diagnosis of the injury.

Improving the effectiveness of (-)-epigallocatechin gallate (EGCG) against rabbit atherosclerosis by EGCG-loaded nanoparticles prepared from chitosan and polyaspartic acid.

(-)-Epigallocatechin gallate (EGCG) is the major bioactive compound in green tea. Its effect is limited by the harsh environment of the gastrointestinal tract. The present study investigates how the effectiveness of EGCG is influenced by its encapsulation into self-assembled nanoparticles of chitosan (CS) and aspartic acid (PAA). Blank nanoparticles with a mean diameter of ca. 93 nm were prepared from 30-50 kDa PAA and 3-5 kDa CS with a mass rate of 1:1. EGCG was loaded in the nanoparticles to yield EGCG-CS-PAA nanoparticles with an average diameter of 102 nm, which were pH-responsive and demonstrated different EGCG release profiles in simulated gastrointestinal tract media. The average ratio (%) of lipid deposition for EGCG-CS-PAA nanoparticles administered orally to rabbits was 16.9 ± 5.8%, which was close to that of oral simvastatin (15.6 ± 4.1%). Orally administered EGCG alone yielded an average ratio of lipid deposit area of 42.1 ± 4.0%, whereas this value was 65.3 ± 10.8% for the blank nanoparticles. The effectiveness of EGCG against rabbit atherosclerosis was significantly improved by incorporating EGCG into the nanoformulation.

Blastocysts cloned from the Putian Black pig ear tissues frozen without cryoprotectant at -80 and -196 degrees Celsius for 3 yrs.

The Putian Black pig, as one of elite cultivars of endemic species in China, has been on the verge of extinction and urgently needs protection. Somatic cell nuclear transfer (SCNT) and noncryoprotected frozen tissue technology have successfully resurrected several mammalian species. Therefore, this study explored the primary feasibility of conserving this breed using a combination of both technologies. Skin tissues obtained from the ears of adult Putian Black boars were frozen without cryoprotectant at -20, -80, or -196 °C and stored for 3 yrs. Primary cell culture, passage and subculture were performed on frozen samples after being rapidly thawed at 39 °C and on fresh pig ear tissues (control). Cloned embryos were reconstructed using fibroblasts (from frozen and fresh tissues) with enucleated oocytes. Live cell lines were obtained from tissues frozen at -80 and at -196 °C and appeared to have normal proliferative activity after passage; furthermore, they directed cloned embryos to develop to the blastocyst stage after nuclear transfer. We concluded that the population of Putian Black pig might be increased in the future by transferring cloned blastocysts into synchronized recipient pigs.

Meconium: a matrix reflecting potential fetal exposure to organochlorine pesticides and its metabolites.

This study investigated the suitability of meconium as a matrix to reflect potential fetal exposure to organochlorine and its metabolites. With GC/MS methods, the process for separating and extracting meconium was explored repeatedly. The internal standard method and external standard method were introduced, and the ideal calibration curve (r=0.9885) for p,p'-DDE measurement was obtained with good validity and feasibility. Sixty samples collected during 1997-1998 from the Gynecological and Obstetrical Hospital, University of Rostock, were analyzed. We found three p,p'-DDE-positive samples and confirmed the results with mass spectrometry. Our findings, the first reported in the world, show that there exist residues organochlorine pesticide residue is present in human meconium 25 years after the use of organochlorine ceased. These results suggest that the pollution with organochlorine pesticides is a long-term global public health problem.