UWB radar sensor networks: Detection algorithms design and experimental analysis

In the last years radar sensor networks for localization and tracking in indoor environment have generated more and more interest, especially for anti-intrusion security systems. These networks often use Ultra Wide Band (UWB) technology, which consists in sending very short (few nanoseconds) impulse signals. This approach guarantees high resolution and accuracy and also other advantages such as low price, low power consumption and narrow-band interference (jamming) robustness. In this thesis the overall data processing (done in MATLAB environment) is discussed, starting from experimental measures from sensor devices, ending with the 2D visualization of targets movements over time and focusing mainly on detection and localization algorithms. Moreover, two different scenarios and both single and multiple target tracking are analyzed.

Simultaneous determination of 3-hydroxyanthranilic and cinnabarinic acid by high-performance liquid chromatography with photometric or electrochemical detection

A convenient and rapid method for the simultaneous determination by HPLC of 3-hydroxyanthranilic acid and the dimer derived by its oxidation, cinnabarinic acid, is described. Buffers or biological samples containing these two Trp metabolites were acidified to pH 2.0 and extracted with ethyl acetate with recoveries of 96.5 +/- 0.5 and 93.4 +/- 3.7% for 3-hydroxyanthranilic and cinnabarinic acid, respectively. The two compounds were separated on a reversed-phase (C18) column combined with ion-pair chromatography and detected photometrically or electrochemically. The method was applied successfully to biological systems in which formation of either 3-hydroxyanthranilic or cinnabarinic acid had been described previously. Thus, interferon-gamma-treated human peripheral blood mononuclear cells formed and released significant amounts of 3-hydroxyanthranilic acid into the culture medium and mouse liver nuclear fraction possessed high "cinnabarinic acid synthase" activity. In contrast, addition of 3-hydroxyanthranilic acid to human erythrocytes resulted in only marginal formation of cinnabarinic acid. We conclude that the method described is specific, sensitive, and suitable for the detection of the two Trp metabolites in biological systems.

The role of epistasis in the manifestation of heterosis: a systems-oriented approach

Heterosis is widely used in breeding, but the genetic basis of this biological phenomenon has not been elucidated. We postulate that additive and dominance genetic effects as well as two-locus interactions estimated in classical QTL analyses are not sufficient for quantifying the contributions of QTL to heterosis. A general theoretical framework for determining the contributions of different types of genetic effects to heterosis was developed. Additive x additive epistatic interactions of individual loci with the entire genetic background were identified as a major component of midparent heterosis. On the basis of these findings we defined a new type of heterotic effect denoted as augmented dominance effect di* that comprises the dominance effect at each QTL minus half the sum of additive x additive interactions with all other QTL. We demonstrate that genotypic expectations of QTL effects obtained from analyses with the design III using testcrosses of recombinant inbred lines and composite-interval mapping precisely equal genotypic expectations of midparent heterosis, thus identifying genomic regions relevant for expression of heterosis. The theory for QTL mapping of multiple traits is extended to the simultaneous mapping of newly defined genetic effects to improve the power of QTL detection and distinguish between dominance and overdominance.

The performance of computer-aided detection when analyzing prior mammograms of newly detected breast cancers with special focus on the time interval from initial imaging to detection

PURPOSE: The clinical role of CAD systems to detect breast cancer, which have not been on cancer containing mammograms not detected by the radiologist was proven retrospectively. METHODS: All patients from 1992 to 2005 with a histologically verified malignant breast lesion and a mammogram at our department, were analyzed in retrospect focussing on the time of detection of the malignant lesion. All prior mammograms were analyzed by CAD (CADx, USA). The resulting CAD printout was matched with the cancer containing images yielding to the radiological diagnosis of breast cancer. CAD performance, sensitivity as well as the association of CAD and radiological features were analyzed. RESULTS: 278 mammograms fulfilled the inclusion criteria. 111 cases showed a retrospectively visible lesion (71 masses, 23 single microcalcification clusters, 16 masses with microcalcifications, in one case two microcalcification clusters). 54/87 masses and 34/41 microcalcifications were detected by CAD. Detection rates varied from 9/20 (ACR 1) to 5/7 (ACR 4) (45% vs. 71%). The detection of microcalcifications was not influenced by breast tissue density. CONCLUSION: CAD might be useful in an earlier detection of subtle breast cancer cases, which might remain otherwise undetected.

Evaluation of surface defect detection in reinforced concrete bridge decks using terrestrial LiDAR

Routine bridge inspections require labor intensive and highly subjective visual interpretation to determine bridge deck surface condition. Light Detection and Ranging (LiDAR) a relatively new class of survey instrument has become a popular and increasingly used technology for providing as-built and inventory data in civil applications. While an increasing number of private and governmental agencies possess terrestrial and mobile LiDAR systems, an understanding of the technology’s capabilities and potential applications continues to evolve. LiDAR is a line-of-sight instrument and as such, care must be taken when establishing scan locations and resolution to allow the capture of data at an adequate resolution for defining features that contribute to the analysis of bridge deck surface condition. Information such as the location, area, and volume of spalling on deck surfaces, undersides, and support columns can be derived from properly collected LiDAR point clouds. The LiDAR point clouds contain information that can provide quantitative surface condition information, resulting in more accurate structural health monitoring. LiDAR scans were collected at three study bridges, each of which displayed a varying degree of degradation. A variety of commercially available analysis tools and an independently developed algorithm written in ArcGIS Python (ArcPy) were used to locate and quantify surface defects such as location, volume, and area of spalls. The results were visual and numerically displayed in a user-friendly web-based decision support tool integrating prior bridge condition metrics for comparison. LiDAR data processing procedures along with strengths and limitations of point clouds for defining features useful for assessing bridge deck condition are discussed. Point cloud density and incidence angle are two attributes that must be managed carefully to ensure data collected are of high quality and useful for bridge condition evaluation. When collected properly to ensure effective evaluation of bridge surface condition, LiDAR data can be analyzed to provide a useful data set from which to derive bridge deck condition information.

Land use/cover change using Remote Sensing and Geographic Information Systems : Pic Macaya National Park, Haiti

A post classification change detection technique based on a hybrid classification approach (unsupervised and supervised) was applied to Landsat Thematic Mapper (TM), Landsat Enhanced Thematic Plus (ETM+), and ASTER images acquired in 1987, 2000 and 2004 respectively to map land use/cover changes in the Pic Macaya National Park in the southern region of Haiti. Each image was classified individually into six land use/cover classes: built-up, agriculture, herbaceous, open pine forest, mixed forest, and barren land using unsupervised ISODATA and maximum likelihood supervised classifiers with the aid of field collected ground truth data collected in the field. Ground truth information, collected in the field in December 2007, and including equalized stratified random points which were visual interpreted were used to assess the accuracy of the classification results. The overall accuracy of the land classification for each image was respectively: 1987 (82%), 2000 (82%), 2004 (87%). A post classification change detection technique was used to produce change images for 1987 to 2000, 1987 to 2004, and 2000 to 2004. It was found that significant changes in the land use/cover occurred over the 17- year period. The results showed increases in built up (from 10% to 17%) and herbaceous (from 5% to 14%) areas between 1987 and 2004. The increase of herbaceous was mostly caused by the abandonment of exhausted agriculture lands. At the same time, open pine forest and mixed forest areas lost (75%) and (83%) of their area to other land use/cover types. Open pine forest (from 20% to 14%) and mixed forest (from18 to 12%) were transformed into agriculture area or barren land. This study illustrated the continuing deforestation, land degradation and soil erosion in the region, which in turn is leading to decrease in vegetative cover. The study also showed the importance of Remote Sensing (RS) and Geographic Information System (GIS) technologies to estimate timely changes in the land use/cover, and to evaluate their causes in order to design an ecological based management plan for the park.

A 5-year comparison of performance of sentinel and mandatory notification surveillance systems for measles in Switzerland

A sensitive, specific and timely surveillance is necessary to monitor progress towards measles elimination. We evaluated the performance of sentinel and mandatory-based surveillance systems for measles in Switzerland during a 5-year period by comparing 145 sentinel and 740 mandatory notified cases. The higher proportion of physicians who reported at least one case per year in the sentinel system suggests underreporting in the recently introduced mandatory surveillance for measles. Accordingly, the latter reported 2-36-fold lower estimates for incidence rates than the sentinel surveillance. However, these estimates were only 0.6-12-fold lower when we considered confirmed cases alone, which indicates a higher specificity of the mandatory surveillance system. In contrast, the sentinel network, which covers 3.5% of all outpatient consultations, detected only weakly and late a major national measles epidemic in 2003 and completely missed 2 of 10 cantonal outbreaks. Despite its better timeliness and greater sensitivity in case detection, the sentinel system, in the current situation of low incidence, is insufficient to perform measles control and to monitor progress towards elimination.

Virus purification, detection and removal

The biopharmaceutical industry has a growing demand and an increasing need to improve the current virus purification technologies, especially as more and more vaccines are produced from cell-culture derived virus particles. Downstream purification strategies can be expensive and account for 70% of the overall manufacturing costs. The economic pressure and purification processes can be particularly challenging when the virus to be purified is small, as in our model virus, porcine parvovirus (PPV). Our efforts are focused on designing an easy, economical, scalable and efficient system for virus purification, and we focused on aqueous two-phase systems. Industry acceptable standards for virus vaccine recovery can be as low as 30% due to demand of high final titer, virus transduction inhibitors and presence of empty or defective virus capsids as impurities. We have overcome these shortcomings by recovering a high 64% of infectious virus using an aqueous two-phase system. We used high molecular weight polymer and citrate salt to achieve a good yield and eliminated the major contaminant bovine serum albumin. Viruses are also studied for ensuring pure and safe drinking water. Low pressure microfiltrations are continuously being investigated for water filters as they allow high permeate flux and low fouling. Viruses such as PPV are small enough to pass through the microporous membranes. Control of viruses in water is crucial for public health and we have designed an affinity based membrane filter to capture virus. Nanofibers have a high surface to volume ratio providing a highly accessible surface area for virus adsorption. Chitosan an insoluble, biocompatible and biodegradable polymer was used for adsorbing trimer peptide WRW. About 0.2 μmoles of cysteine terminal WRW peptide was conjugated to amine terminal chitosan using maleimide conjugation chemistry. We achieved 90-99% virus removal from water adjusted to a neutral pH. The virus removal from affinity based chitosan was attributed to electrostatic and hydrophobic driven binding effect.

OUT-OF-STEP DETECTION BASED ON ZUBOV’S APPROXIMATION BOUNDARY METHOD

Disturbances in power systems may lead to electromagnetic transient oscillations due to mismatch of mechanical input power and electrical output power. Out-of-step conditions in power system are common after the disturbances where the continuous oscillations do not damp out and the system becomes unstable. Existing out-of-step detection methods are system specific as extensive off-line studies are required for setting of relays. Most of the existing algorithms also require network reduction techniques to apply in multi-machine power systems. To overcome these issues, this research applies Phasor Measurement Unit (PMU) data and Zubov’s approximation stability boundary method, which is a modification of Lyapunov’s direct method, to develop a novel out-of-step detection algorithm. The proposed out-of-step detection algorithm is tested in a Single Machine Infinite Bus system, IEEE 3-machine 9-bus, and IEEE 10-machine 39-bus systems. Simulation results show that the proposed algorithm is capable of detecting out-of-step conditions in multi-machine power systems without using network reduction techniques and a comparative study with an existing blinder method demonstrate that the decision times are faster. The simulation case studies also demonstrate that the proposed algorithm does not depend on power system parameters, hence it avoids the need of extensive off-line system studies as needed in other algorithms.

Reproducibility and accuracy of the ICDAS-II for occlusal caries detection

OBJECTIVES: The aim of this in vitro study was to assess the inter- and intra-examiner reproducibility and the accuracy of the International Caries Detection and Assessment System-II (ICDAS-II) in detecting occlusal caries. METHODS: One hundred and sixty-three molars were independently assessed twice by two experienced dentists using the 0- to 6-graded ICDAS-II. The teeth were histologically prepared and classified using two different histological systems [Ekstrand et al. (1997) Caries Research vol. 31, pp. 224-231; Lussi et al. (1999) Caries Research vol. 33, pp. 261-266] and assessed for caries extension. Sensitivity, specificity, accuracy and area under the ROC curve (A(z)) were obtained at D(2) and D(3) thresholds. Unweighted kappa coefficient was used to assess inter- and intra-examiner reproducibility. RESULTS: For the Ekstrand et al. histological classification the sensitivity was 0.99 and 1.00, specificity 1.00 and 0.69 and accuracy 0.99 and 0.76 at D(2) and D(3), respectively. For the Lussi et al. histological classification the sensitivity was 0.91 and 0.75, specificity 0.47 and 0.62 and accuracy 0.86 and 0.68 at D(2) and D(3), respectively. The A(z) varied from 0.54 to 0.73. The inter- and intra-examiner kappa values were 0.51 and 0.58, respectively. CONCLUSIONS: ICDAS-II presented good reproducibility and accuracy in detecting occlusal caries, especially caries lesions in the outer half of the enamel.

Detection of type III secretion genes as a general indicator of bacterial virulence

Type III secretion systems of Gram-negative bacteria are specific export machineries for virulence factors which allow their translocation to eukaryotic cells. Since they correlate with bacterial pathogenicity, their presence is used as a general indicator of bacterial virulence. By comparing the genetic relationship of the major type III secretion systems we found the family of genes encoding the inner-membrane channel proteins represented by the Yersinia enterocolitica lcrD (synonym yscV) and its homologous genes from other species an ideal component for establishing a general detection approach for type III secretion systems. Based on the genes of the lcrD family we developed gene probes for Gram-negative human, animal and plant pathogens. The probes comprise lcrD from Y. enterocolitica, sepA from enteropathogenic Escherichia coli, invA from Salmonella typhimurium, mxiA from Shigella sonnei, as well as hrcV from Erwinia amylovora. In addition we included as a control probe the flhA gene from E. coli K-12 to validate our approach. FlhA is part of the flagellar export apparatus which shows a high degree of similarity with type III secretions systems, but is not involved in pathogenicity. The probes were evaluated by screening a series of pathogenic as well as non-pathogenic bacteria. The probes detected type III secretion in pathogens where such systems were either known or were expected to be present, whereas no positive hybridization signals could be found in non-pathogenic Gram-negative bacteria. Gram-positive bacteria were devoid of known type III secretion systems. No interference due to the genetic similarity between the type III secretion system and the flagellar export apparatus was observed. However, potential type III secretion systems could be detected in bacteria where no such systems have been described yet. The presented approach provides therefore a useful tool for the assessment of the virulence potential of bacterial isolates of human, animal and plant origin. Moreover, it is a powerful means for a first safety assessment of poorly characterized strains intended to be used in biotechnological applications.

Distributed sensor failure detection in sensor networks

We investigate the problem of distributed sensors' failure detection in networks with a small number of defective sensors, whose measurements differ significantly from the neighbor measurements. We build on the sparse nature of the binary sensor failure signals to propose a novel distributed detection algorithm based on gossip mechanisms and on Group Testing (GT), where the latter has been used so far in centralized detection problems. The new distributed GT algorithm estimates the set of scattered defective sensors with a low complexity distance decoder from a small number of linearly independent binary messages exchanged by the sensors. We first consider networks with one defective sensor and determine the minimal number of linearly independent messages needed for its detection with high probability. We then extend our study to the multiple defective sensors detection by modifying appropriately the message exchange protocol and the decoding procedure. We show that, for small and medium sized networks, the number of messages required for successful detection is actually smaller than the minimal number computed theoretically. Finally, simulations demonstrate that the proposed method outperforms methods based on random walks in terms of both detection performance and convergence rate.

A technique for continuous detection of drill liquid in ice cores

When drilling ice cores deeper than ∼100 m, drill liquid is required to maintain ice-core quality and to limit borehole closure. Due to high-pressure air bubbles in the ice, the ice core can crack during drilling and core retrieval, typically at 600–1200 m depth in Greenland. Ice from this 'brittle zone' can be contaminated by drill liquid as it seeps through cracks into the core. Continuous flow analysis (CFA) systems are routinely used to analyse ice for chemical impurities, so the detection of drill liquid is important for validating accurate measurements and avoiding potential instrument damage. An optical detector was constructed to identify drill liquid in CFA tubing by ultraviolet absorption spectroscopy at a wavelength of 290 nm. The set-up was successfully field-tested in the frame of the NEEM ice-core drilling project in Greenland. A total of 27 cases of drill liquid contamination were identified during the analysis of 175 m of brittle zone ice. The analyses most strongly affected by drill liquid contamination include insoluble dust particles, electrolytic conductivity, ammonium, hydrogen peroxide and sulphate. This method may also be applied to other types of drill liquid used at other drill sites.