Near-far resistant detection of CDMA signals via isolation bit insertion

This paper presents a novel scheme for near-far resistant CDMA detection: isolation bit insertion (IBI). At the transmitter, isolation bits are inserted into the information bit sequence before modulation, and a practical linear decorrelating detector (LDD) is obtained at the receiver. All the advantages that an LDD theoretically offers are retained and realised in practice.

One-shot near-far resistant CDMA detection in multipath fading channels-an O^3 BPSK based system

This paper applies O3BPSK (orthogonal on-off PSK) signaling scheme to multipath fading CDMA channels, for the purpose of near-far resistant detection in the reverse link. Based on the maximum multipath spreading delay, a minimum duration of “off” is suggested, with which the temporally adjacent bits (TABs) from different users at the receiver are decoupled. As a result, a Rake-type one-shot linear decorrelating detector (LDD) is obtained. Since no knowledge of echo amplitudes is needed, a blind detection can be realised.

A new signaling scheme for one-shot near-far resistant detection in DS/CDMA

This paper proposes a new signaling scheme: orthogonal on-off BPSK (O3BPSK), for near-far resistant detection in the asynchronous DS/CDMA systems (up-link). The temporally adjacent bits from different users in the received signals are decoupled by using the on-off signaling, and the original data rate is maintained with no increase in transmission rate by adopting an orthogonal structure. The detector at the receiver is a one-shot linear decorrelating detector, which depends upon neither hard-decision nor specific channel coding. Some computer simulations are shown to confirm the theoretical analysis.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover.

A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18% respectively.

Biolabeling with nanoparticles based on Y(2)O(3):Nd(3+) and luminescence detection in the near-infrared

Neodymium based fluorescence presents several advantages in comparison to conventional rare earth or enzyme-substrate based fluorescence emitting sources (e.g.Tb, HRP). Based on this fact we have herein explored a Nd-based fluoroimmunoassay. We efficiently detected the presence of an oxidized low-density lipoprotein (oxLDL) in human plasma a well-known marker for cardiovascular diseases, which causes around 30% of deaths worldwide. Conventional fluoroimmunoassay uses time-resolved luminescence techniques, with detection in the visible range, to eliminate the fluorescence background from the biological specimens. By using an immunoassay based on functionalized Y(2)O(3):Nd(3+) nanoparticles, where the excitation and emission processes in the Nd(3+) ion occur in the near-infrared (NIR) region, we have succeeded in eliminating the interferences from the biological fluorescence background, avoiding the use of time-resolved techniques. This yields higher emission intensity from the Nd(3+)-nanolabels and efficient detection of anti-oxidized low-density lipoproteins (anti-oxLDL) by Y(2)O(3):Nd(3+)-antibody-antigen conjugation, leading to a novel biolabeling method. (C) 2010 Elsevier B.V. All rights reserved.

The near babylonian speech confusion in early detection of psychosis

It is barely 15 years since, in 1996, the issue theme of Schizophrenia Bulletin (Vol 22, 2) “Early Detection, and Intervention in Schizophrenia” signified the commencement of this field of research. Since that time the field of early detection research has developed rapidly and it may be translated into clinical practice by the introduction of an Attenuated Psychosis Syndrome in Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, (DSM-5) (www.dsm5.org/ProposedRevisions/Pages/proposedrevision.aspx?rid=412#). Attenuated psychotic symptoms (APS) had first been suggested as a clinical predictor of first-episode psychosis by the Personal Assessment and Crisis Evaluation (PACE) Clinic group as part of the ultrahigh risk (UHR) criteria.1 The term ultrahigh risk became broadly accepted for this set of criteria for imminent risk of developing psychosis in the late 1990s. The use of the term “prodrome” for a state characterized by at-risk (AR) criteria was criticized as a retrospective concept inevitably followed by the full-blown disorder.1 Although alternative terms have been suggested, prodrome is still used in prospective studies (eg, prodromally symptomatic, potentially or putatively prodromal, prodrome-like state/symptoms). Some alternative suggestions such as prepsychotic state/symptoms, subthreshold psychotic symptoms, early psychosis, subsyndromal psychosis, hypopsychosis, or subpsychosis were short-lived. Other terms still in use include UHR, at-risk mental state (ARMS), AR, high risk, clinical high risk (CHR), or early and late AR state. Further, the term psychotic-like experiences (PLEs) has recently (re-)entered early detection research. …

Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis

The use of a common environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (RT-PCR) represent high specificity and sensitivity but are destructive and time-consuming, and require highly skilled experimenters. The feasibility of NIR hyperspectral imaging (HSI) is studied for the detection of peanut traces down to 0.01% by weight. A principal-component analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image, and the percentage of peanut adulteration was compared with the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01% and quantification of peanut adulteration from 10% to 0.1% with a coefficient of determination (r2) of 0.946. These results show the feasibility of using HSI systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality-control surveillance on food-product processing lines.

Near Real-Time Detection Of Pipe Bursts in Water Distribution Systems

The research work presented in the thesis describes a new methodology for the automated near real-time detection of pipe bursts in Water Distribution Systems (WDSs). The methodology analyses the pressure/flow data gathered by means of SCADA systems in order to extract useful informations that go beyond the simple and usual monitoring type activities and/or regulatory reporting , enabling the water company to proactively manage the WDSs sections. The work has an interdisciplinary nature covering AI techniques and WDSs management processes such as data collection, manipulation and analysis for event detection. Indeed, the methodology makes use of (i) Artificial Neural Network (ANN) for the short-term forecasting of future pressure/flow signal values and (ii) Rule-based Model for bursts detection at sensor and district level. The results of applying the new methodology to a District Metered Area in Emilia- Romagna’s region, Italy have also been reported in the thesis. The results gathered illustrate how the methodology is capable to detect the aforementioned failure events in fast and reliable manner. The methodology guarantees the water companies to save water, energy, money and therefore enhance them to achieve higher levels of operational efficiency, a compliance with the current regulations and, last but not least, an improvement of customer service.

A near real-time water surface detection method based on HSV transformation of MODIS multi-Spectral time series data

In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objective of this study is to develop and demonstrate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near-real-time. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. The validation of the algorithm showed very few omission errors and no commission errors. It demonstrates the ability of the proposed algorithm to perform as effectively as human interpretation of the images. The validation of the permanent water surface product with an independent dataset derived from high resolution imagery, showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed 27 is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties

Detection of high-velocity material from the wind-wind collision zone of Eta Carinae across the 2009.0 periastron passage

We report near-infrared spectroscopic observations of the Eta Carinae massive binary system during 2008-2009 using the CRIRES spectrograph mounted on the 8m UT 1 Very Large Telescope (VLT Antu). We detect a strong, broad absorption wing in He I lambda 10833 extending up to -1900 km s(-1) across the 2009.0 spectroscopic event. Analysis of archival Hubble Space Telescope/Space Telescope Imaging Spectrograph ultraviolet and optical data identifies a similar high-velocity absorption (up to -2100 km s(-1)) in the ultraviolet resonance lines of Si IV lambda lambda 1394, 1403 across the 2003.5 event. Ultraviolet resonance lines from low-ionization species, such as Si II lambda lambda 1527, 1533 and CII lambda lambda 1334, 1335, show absorption only up to -1200 km s(-1), indicating that the absorption with velocities -1200 to -2100 km s(-1) originates in a region markedly more rapidly moving and more ionized than the nominal wind of the primary star. Seeing-limited observations obtained at the 1.6m OPD/LNA telescope during the last four spectroscopic cycles of Eta Carinae (1989-2009) also show high-velocity absorption in He I lambda 10833 during periastron. Based on the large OPD/LNA dataset, we determine that material with velocities more negative than -900 km s(-1) is present in the phase range 0.976 <= phi <= 1.023 of the spectroscopic cycle, but absent in spectra taken at phi <= 0.947 and phi >= 1.049. Therefore, we constrain the duration of the high-velocity absorption to be 95 to 206 days (or 0.047 to 0.102 in phase). We propose that the high-velocity absorption component originates in shocked gas in the wind-wind collision zone, at distances of 15 to 45 AU in the line-of-sight to the primary star. With the aid of three-dimensional hydrodynamical simulations of the wind-wind collision zone, we find that the dense high-velocity gas is along the line-of-sight to the primary star only if the binary system is oriented in the sky such that the companion is behind the primary star during periastron, corresponding to a longitude of periastron of omega similar to 240 degrees-270 degrees. We study a possible tilt of the orbital plane relative to the Homunculus equatorial plane and conclude that our data are broadly consistent with orbital inclinations in the range i = 40 degrees-60 degrees.

Unsuccessful attacks dominate a drone-preying wasp's hunting performance near stingless bee nests

Bee males (drones) of stingless bees tend to congregate near entrances of conspecific nests, where they wait for virgin queens that initiate their nuptial flight. We observed that the Neotropical solitary wasp Trachypus boharti (Hymenoptera, Cabronidae) specifically preys on males of the stingless bee Scaptotrigona postica (Hymenoptera, Apidae); these wasps captured up to 50 males per day near the entrance of a single hive. Over 90% of the wasp attacks were unsuccessful; such erroneous attacks often involved conspecific wasps and worker bees. After the capture of non-male prey, wasps almost immediately released these individuals unharmed and continued hunting. A simple behavioral experiment showed that at short distances wasps were not specifically attracted to S. postica males nor were they repelled by workers of the same species. Likely, short-range prey detection near the bees' nest is achieved mainly by vision whereas close-range prey recognition is based principally on chemical and/or mechanical cues. We argue that the dependence on the wasp's visual perception during attack and the crowded and dynamic hunting conditions caused wasps to make many preying attempts that failed. Two wasp-density-related factors, wasp-prey distance and wasp-wasp encounters, may account for the fact that the highest male capture and unsuccessful wasp bee encounter rates occurred at intermediate wasp numbers.

Local search multiuser detection

In this work, a wide analysis of local search multiuser detection (LS-MUD) for direct sequence/code division multiple access (DS/CDMA) systems under multipath channels is carried out considering the performance-complexity trade-off. It is verified the robustness of the LS-MUD to variations in loading, E(b)/N(0), near-far effect, number of fingers of the Rake receiver and errors in the channel coefficients estimates. A compared analysis of the bit error rate (BER) and complexity trade-off is accomplished among LS, genetic algorithm (GA) and particle swarm optimization (PSO). Based on the deterministic behavior of the LS algorithm, it is also proposed simplifications over the cost function calculation, obtaining more efficient algorithms (simplified and combined LS-MUD versions) and creating new perspectives for the MUD implementation. The computational complexity is expressed in terms of the number of operations in order to converge. Our conclusion pointed out that the simplified LS (s-LS) method is always more efficient, independent of the system conditions, achieving a better performance with a lower complexity than the others heuristics detectors. Associated to this, the deterministic strategy and absence of input parameters made the s-LS algorithm the most appropriate for the MUD problem. (C) 2008 Elsevier GmbH. All rights reserved.