Fingerprint Map Research Articles

A design of irregular grid map for large-scale Wi-Fi LAN fingerprint positioning systems.

The rapid growth of mobile communication and the proliferation of smartphones have drawn significant attention to location-based services (LBSs). One of the most important factors in the vitalization of LBSs is the accurate position estimation of a mobile device. The Wi-Fi positioning system (WPS) is a new positioning method that measures received signal strength indication (RSSI) data from all Wi-Fi access points (APs) and stores them in a large database as a form of radio fingerprint map. Because of the millions of APs in urban areas, radio fingerprints are seriously contaminated and confused. Moreover, the algorithmic advances for positioning face computational limitation. Therefore, we present a novel irregular grid structure and data analytics for efficient fingerprint map management. The usefulness of the proposed methodology is presented using the actual radio fingerprint measurements taken throughout Seoul, Korea.

An Analysis of Device-Free and Device-Based WiFi-Localization Systems

WiFi-based localization became one of the main indoor localization techniques due to the ubiquity of WiFi connectivity. However, indoor environments exhibit complex wireless propagation characteristics. Typically, these characteristics are captured by constructing a fingerprint map for the different locations in the area of interest. This finger print requires significant overhead in manual construction, and thus has been one of the major drawbacks of WiFi-based localization. In this paper, the authors present an automated tool for finger print constructions and leverage it to study novel scenarios for device-based and device-free WiFi-based localization that are difficult to evaluate in a real environment. In a particular, the authors examine the effect of changing the access points (AP) mounting location, AP technology upgrade, crowd effect on calibration and operation, among others; on the accuracy of the localization system. The authors present the analysis for the two classes of WiFi-based localization: device-based and device-free. The authors analysis highlights factors affecting the localization system accuracy, how to tune it for better localization, and provides insights for both researchers and practitioners.

Virtual 2D Positioning System by Using Wireless Sensors in Indoor Environment

A 2D location detection system is constructed by using Wireless Sensor Nodes (WSN) to create aVirtual Fingerprint map, specifically designed for use in an indoor environment. WSN technologies and programmable ZigBee wireless network protocols are employed. This system is based on radio-location fingerprinting technique. Both Linear taper functions and exponential taper functions are utilized with the received signal strength distributions between the fingerprint nodes to generate virtual fingerprint maps. Thus, areal and virtual combined fingerprint map is generated across the test area. K-nearest neighborhood algorithm has been implemented on virtual fingerprint maps, in conjunction with weight functions used to find the coordinates of the unknown objects. The system Localization accuracies of less than a grid space areproved in calculations.

GenomeFingerprinter: The Genome Fingerprint and the Universal Genome Fingerprint Analysis for Systematic Comparative Genomics

BackgroundNo attention has been paid on comparing a set of genome sequences crossing genetic components and biological categories with far divergence over large size range. We define it as the systematic comparative genomics and aim to develop the methodology.ResultsFirst, we create a method, GenomeFingerprinter, to unambiguously produce a set of three-dimensional coordinates from a sequence, followed by one three-dimensional plot and six two-dimensional trajectory projections, to illustrate the genome fingerprint of a given genome sequence. Second, we develop a set of concepts and tools, and thereby establish a method called the universal genome fingerprint analysis (UGFA). Particularly, we define the total genetic component configuration (TGCC) (including chromosome, plasmid, and phage) for describing a strain as a systematic unit, the universal genome fingerprint map (UGFM) of TGCC for differentiating strains as a universal system, and the systematic comparative genomics (SCG) for comparing a set of genomes crossing genetic components and biological categories. Third, we construct a method of quantitative analysis to compare two genomes by using the outcome dataset of genome fingerprint analysis. Specifically, we define the geometric center and its geometric mean for a given genome fingerprint map, followed by the Euclidean distance, the differentiate rate, and the weighted differentiate rate to quantitatively describe the difference between two genomes of comparison. Moreover, we demonstrate the applications through case studies on various genome sequences, giving tremendous insights into the critical issues in microbial genomics and taxonomy.ConclusionsWe have created a method, GenomeFingerprinter, for rapidly computing, geometrically visualizing, intuitively comparing a set of genomes at genome fingerprint level, and hence established a method called the universal genome fingerprint analysis, as well as developed a method of quantitative analysis of the outcome dataset. These have set up the methodology of systematic comparative genomics based on the genome fingerprint analysis.

Purification and Characterization of a Urethanase from Penicillium variabile

Urethanase produced by Penicillium variabile was purified through ultrasonication, concentration by polyethylene glycol 20,000, and Superdex G-200 gel filtration chromatography. The molecular weight of urethanase was determined to be around 96 kDa by gel filtration. The purified enzyme showed a single band in SDS-PAGE with the molecular weight of ~13.7 kDa, which suggests that the enzyme has a multimeric structure composed of the same subunits. Peptide map fingerprinting analysis was then carried out by MALDI/TOF-TOF MS. Within the known sequences in NCBI, glucosamine-6-phosphate deaminase and 6-phosphogluconate dehydrogenase get high score as compared with urethanase. Sequence analysis informs that N-terminal sequence of urethanase is GTNTADNDAA. The Minchaelis constant (Km) and maximum reaction rate (Vm) of urethanase are 27.2 mmol/L and 156.25 μmol/L min, respectively.

군중-제공 신호지도 작성 및 위치 추적 시스템의 설계

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user`s position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.

Chemical fingerprinting and phylogenetic mapping of saponin congeners from three tropical holothurian sea cucumbers

Holothurians are sedentary marine organisms known to produce saponins (triterpene glycosides), secondary metabolites exhibiting a wide range of biological activities. In this paper, we investigated the saponin contents of semi-purified and membranolytic HPLC fractionated extracts from the body wall of three species of Holothuriidae as an attempt to examine its chemical diversity in relation to phylogenetic data. MALDI-FTICR MS and nano-HPLC-chip Q-TOF MS were used for mass profiling and isomer separation, respectively giving a unique chemical saponin fingerprint. Moreover, the methods used yield the highest number of congeners. However, saponin concentration, bioactivity and chemical diversity had no apparent relationship. MS fingerprint showed the presence of holothurinosides, which was observed for the first time in other Holothuria genera besides the basally positioned Holothuria forskali. This congener is proposed to be a primitive character that could be used for taxonomic purposes. The phylogenetic mapping also showed that the glycone part of the compound evolved from non-sulfated hexaosides to sulfated tetraosides, which have higher membranolytic activity and hydrophilicity, the two factors affecting the total ecological activity (i.e. chemical defense) of these compounds. This might be an adaptation to increase the fitness of the organism.

Development, characterization, genetic diversity and cross-species/genera transferability of ILP markers in rubber tree (Hevea brasiliensis)

To construct a linkage map enriched with tapping panel dryness (TPD)-related markers, we firstly utilized rubber tree ESTs associated with TPD to develop intron length polymorphism (ILP) markers. In this study, 52 new ILP markers were further developed. Together with the ILP markers previously reported, 102 ILP markers developed from TPD-related ESTs were analyzed within 39 Hevea germplasm in detail. The PCR success rate and polymorphism rate of ILP markers was 97.06 and 61.62 %, respectively. The results based on PCR amplification and sequence analyses provided the evidences on cross-species/genera transferability of rubber tree ILP markers. The average polymorphic information content (PIC) values of 39 Hevea germplasm were about 0.1719, indicating that the genetic base of Hevea germplasm selected in this study was very narrow. Among 39 Hevea germplasm, the PIC value of wild rubber tree accessions was the highest, followed by Hevea species and cultivated rubber tree clones. Based on the similarity coefficient of ILP markers, 39 Hevea germplasm were divided into three groups including cultivated clones, wild accessions and Hevea species, suggesting that the classification was generally related to the characterization of Hevea germplasm. The ILP markers developed in this study further enriches the number of molecular marker in rubber tree, and the ILP markers will have a wide application in DNA fingerprinting, genetic diversity, marker-assisted selection and genetic mapping, etc. Moreover, the ILP markers transferred cross-euphorbiaceae family might be utilized in cassava, castor bean and physic nut.

A computational method for detecting copy number variations using scale-space filtering

BackgroundAs next-generation sequencing technology made rapid and cost-effective sequencing available, the importance of computational approaches in finding and analyzing copy number variations (CNVs) has been amplified. Furthermore, most genome projects need to accurately analyze sequences with fairly low-coverage read data. It is urgently needed to develop a method to detect the exact types and locations of CNVs from low coverage read data.ResultsHere, we propose a new CNV detection method, CNV_SS, which uses scale-space filtering. The scale-space filtering is evaluated by applying to the read coverage data the Gaussian convolution for various scales according to a given scaling parameter. Next, by differentiating twice and finding zero-crossing points, inflection points of scale-space filtered read coverage data are calculated per scale. Then, the types and the exact locations of CNVs are obtained by analyzing the finger print map, the contours of zero-crossing points for various scales.ConclusionsThe performance of CNV_SS showed that FNR and FPR stay in the range of 1.27% to 2.43% and 1.14% to 2.44%, respectively, even at a relatively low coverage (0.5x ≤C ≤2x). CNV_SS gave also much more effective results than the conventional methods in the evaluation of FNR, at 3.82% at least and 76.97% at most even when the coverage level of read data is low. CNV_SS source code is freely available from http://dblab.hallym.ac.kr/CNV SS/.

Anti-cancer activity of flavonoids from Xinjiang Glycyrrhiza inflata Licorice on proliferation, cytotoxicity and apoptosis in cervical carcinoma cells

Glycyrrhiza inflata Licorice, as a traditional Chinese medicine, has long been used as therapeutic ingredients as anti-inflammatory, and anti-viral in many chronic diseases. Anti-cancer activity of licorice total flavonoids (LTFs) from Xinjiang G. inflata, on cervical carcinoma cells was investigated. LTFs were prepared from G. inflate. After determination of content by high-performance liquid chromatographic (HPLC), the finger print map was characterized by Electro Spray Mass Spectrometry. SiHa cervical carcinoma cells were treated with LTFs, and cell viability and cellular apoptosis were determined by both MTT method and flow cytometry. In the dose range of 0 to 500 μgml-1 LTFs, the cell viability dropped gradually with the LTFs treatment, the lowest level by MTT detection was 12%; in the dose range of 0 to 1000 μgml-1 LTFs, the ratio of cellular apoptosis induced by LTFs increased gradually, the highest level by flow cytometry detection was up to 78%. It can be concluded that LTFs had relatively high anti-cancer activity on cervical carcinoma cells including the inhibition of cell growth and viability by induction of cellular apoptosis. This work may provide important evidence for further screening and isolation of active ingredients of flavonoids as well as the development of new natural anti-cancer drugs. Key words: Xinjiang Glycyrrhiza inflata, licorice total flavonoids (LTFs), anti-cancer activity.

Unsupervised Construction of an Indoor Floor Plan Using a Smartphone

Indoor pedestrian tracking extends location-based services to indoor environments. Typical indoor positioning systems employ a training/positioning model using Wi-Fi fingerprints. While these approaches have practical results in terms of accuracy and coverage, they require an indoor map, which is typically not available to the average user and involves significant training costs. A practical indoor pedestrian tracking approach should consider the indoor environment without a pretrained database or floor plan. In this paper, we present an indoor pedestrian tracking system, called SmartSLAM, which automatically constructs an indoor floor plan and radio fingerprint map for anonymous buildings using a smartphone. The scheme employs odometry tracing using inertial sensors, an observation model using Wi-Fi signals, and a Bayesian estimation for floor-plan construction. SmartSLAM is a true simultaneous localization and mapping implementation that does not necessitate additional devices, such as laser rangefinders or wheel encoders. We implemented the scheme on off-the-shelf smartphones and evaluated the performance in our university buildings. Despite inherent tracking errors from noisy sensors, SmartSLAM successfully constructed indoor floor plans.

Prevalence and genotypic relatedness of carbapenem resistance among multidrug-resistant P. aeruginosa in tertiary hospitals across Thailand

BackgroundIncreased infection caused by multidrug resistant (MDR) Pseudomonas aeruginosa has raised awareness of the resistance situation worldwide. Carbapenem resistance among MDR (CR-MDR) P. aeruginosa has become a serious life-threatening problem due to the limited therapeutic options. Therefore, the objectives of this study were to determine the prevalence, the antibiotic susceptibility patterns and the relatedness of CR-MDR P. aeruginosa in tertiary hospitals across Thailand.MethodsMDR P. aeruginosa from eight tertiary hospitals across Thailand were collected from 2007–2009. Susceptibility of P. aeruginosa clinical isolates was determined according to the Clinical and Laboratory Standards Institute guideline. Selected CR-MDR P. aeruginosa isolates were genetically analyzed by pulsed-field gel electrophoresis.ResultsAbout 261 clinical isolates were identified as MDR P. aeruginosa and approximately 71.65% were found to be CR-MDR P. aeruginosa. The result showed that the meropenem resistance rate was the highest reaching over 50% in every hospitals. Additionally, the type of hospitals was a major factor affecting the resistance rate, as demonstrated by significantly higher CR-MDR rates among university and regional hospitals. The fingerprinting map identified 107 clones with at least 95% similarity. Only 4 clones were detected in more than one hospital.ConclusionsAlthough the antibiotic resistance rate was high, the spreading of CR-MDR was found locally. Specific strains of CR-MDR did not commonly spread from one hospital to another. Importantly, clonal dissemination ratio indicated limited intra-hospital transmission in Thailand.

위치기반 서비스 강화를 위한 최적 데이터 필터링 기법 및 측위 시스템 적용 모델

Focusing on the rapid market penetration of smart phones, the importance of LBS (Location Based Service) is drastically increased. However, traditional GPS method has critical weakness caused by limited availability, such as indoor environment. WPS is newly attractive method as a widely applicable positioning method. In WPS, RSSI (Received Signal Strength Indication) data of all Wi-Fi APs (Access Point) are measured and stored into a huge database. The stored RSSI data in database make single radio fingerprint map. By the radio fingerprint map, we can estimate the actual position of target point. The essential factor of radio fingerprint database is data integrity of RSSI. Because of millions of APs in urban area, RSSI measurement data are seriously contaminated. Therefore, we present the unified filtering method for RSSI measurement data. As the results of filtering, we can show the effectiveness of suggested method in practical positioning system of mobile operator.

Probability kernel regression for WiFi localisation

Various methods have been developed for indoor localisation using WLAN signals. Algorithms that fingerprint the received signal strength indicators (RSSI) of WiFi for different locations can achieve tracking accuracies of the order of a few metres. RSSI fingerprinting suffers from two main limitations: first, as the signal environment changes, so does the fingerprint database, which requires regular updates; second, it has been reported that, in practice, certain devices record more complex (e.g bimodal) distributions of WiFi signals, precluding algorithms based on the mean RSSI. Mirowski et al. [2011. KL-divergence kernel regression for non-Gaussian fingerprint based localization. In: International conference on indoor positioning and indoor navigation, Guimaraes, Portugal] have recently introduced a simple methodology that takes into account the full distribution for computing similarities among fingerprints using the Kullback–Leibler (KL) divergence, and then performs localisation through kernel regression. Their algorithm provides a natural way of smoothing over time and motion trajectories and can be applied directly to histograms of WiFi connections to access points, ignoring RSSI distributions, hence removing the need for fingerprint recalibration. It has been shown to outperform nearest neighbours or Kalman and particle filtres, achieving up to 1 m accuracy in office environments. In this article, we focus on the relevance of Gaussian or non-Gaussian distributions for modelling RSSI distributions by considering additional probabilistic kernels for comparing Gaussian distributions and by evaluating them on three contrasting datasets. We discuss their limitations and formulate how the KL-divergence kernel regression algorithm bridges the gap with other WiFi localisation algorithms, notably Bayesian networks, support vector machines and K nearest neighbours. Finally, we revisit the assumptions on the fingerprint maps and overview practical WiFi localisation software implementation.

Construction of Human Nonimmune Library and Selection of scFvs Against IL-33

Interleukin (IL) 33 plays very important roles in inflammatory and allergic diseases. To select human single-chain Fv fragments (scFvs) against IL-33, a nonimmune phage library system was constructed. The full-length cDNA library was synthesized for amplification of the variable heavy chain (V(H)) and variable light chain (V(L)). By overlapping extension PCR for splicing V(H) and V(L), the full-length scFv library DNA were amplified and then transformed into Escherichia coli TG1. The scFv library was constructed successfully which contained 2.5×10(8) independent clones with full-length scFv inserts. The results of fingerprint maps of the scFvs by BstN I and DNA sequencing from the library at random proved that the library was diverse. The human IL-33 was amplified, expressed, and purified. The purified IL-33 with bioactivity was biotinylated and used as antigen for selection of scFv library by phage display. After three rounds of affinity selection, about 30 % of clones have specific binding activity with IL-33. Five of those with good binding activity were transformed into E. coli strain HB2151 for soluble expression. The selected scFvs were further identified by western blot and sequencing. Those selected scFvs could be used for further research of their effect on inflammatory and allergic diseases such as asthma by blockade of IL-33.

Proteomic approach to investigating the molecular integrity of rituximab when diluted in typical hospital conditions

BackgroundThe active substance of MabThera is rituximab. It is a genetically engineered chimeric mouse/human monoclonal antibody which binds specifically to the transmembrane antigen CD20. It is currently indicated for the...

TCH034 Proteomic approach to investigating the molecular integrity of infliximab after reconstitution and dilution in typical hospital conditions

BackgroundThe active substance of Remicade is infliximab. It is a chimeric human-murine monoclonal antibody directed against tumour necrosis factor α (TNFα), manufactured from a recombinant cell line. Remicade is presented...

Proteomic approach to investigating the molecular integrity of infliximab after reconstitution and dilution in typical hospital conditions

BackgroundThe active substance of Remicade is infliximab. It is a chimeric human-murine monoclonal antibody directed against tumour necrosis factor α (TNFα), manufactured from a recombinant cell line. Remicade is presented...

Analysis of the serum biomarkers in human knee osteoarthritis

Analysis of the serum biomarkers in human knee osteoarthritis

Isolation and characterization of novel microsatellite markers for Avena sativa (Poaceae) (oat)

A new set of microsatellite primers was developed for Avena sativa and characterized to assess the level of genetic diversity among cultivars and wild genotypes. Using an enrichment genomic library, 14 simple sequence repeat markers were identified. The loci of these markers were characterized and found to be polymorphic in size among 48 genotypes of oat from diverse geographical locations. The number of alleles per locus ranged from two to eight, while the observed heterozygosity ranged from 0.031 to 0.75. These newly identified microsatellite markers will facilitate genetic diversity studies, fingerprinting, and genetic mapping of oat. Moreover, these new primers for A. sativa will aid future studies of polyploidy and hybridization in other species in this genus.