Detection Probability

Many factors affect the number of birds detected on point count surveys of breeding songbirds. The magnitude and importance of these factors are not well understood. We used a bird song simulation system to quantify the effects of detection distance, singing rate, species differences, and observer differences on detection probabilities of birds detected by ear. We simulated 40 point counts consisting of 10 birds per count for five primary species (Black-and-white Warbler Mniotilta varia, Black-throated Blue Warbler Dendroica caerulescens, Black-throated Green Warbler Dendroica virens, Hooded Warbler Wilsonia citrina, and Ovenbird Seiurus aurocapillus) over a range of 15 distances (34-143 m). Songs were played at low (two songs per count) and high (13-21 songs per count) singing rates. Detection probabilities averaged across observers ranged from 0.60 (Black-and-white Warbler) to 0.83 (Hooded Warbler) at the high singing rate and 0.41 (Black-and-white Warbler) to 0.67 (Hooded Warbler) at the low singing rate. Logistic regression analyses indicated that species, singing rate, distance, and observer were all significant factors affecting detection probabilities. Singing rate 3 species and singing rate 3 distance interactions were also significant. Simulations of expected counts, based on the best logistic model, indicated that observers detected between 19% (for the worst observer, lowest singing rate, and least detectable species) and 65% (for the best observer, highest singing rate, and most detectable species) of the true population. Detection probabilities on actual point count surveys are likely to vary even more because many sources of variability were controlled in our experiments. These findings strongly support the importance of adjusting measures of avian diversity or abundance from auditory point counts with direct estimates of detection probability.

The distribution of various evolutionary lineages of Apis mellifera subspecies in Africa is still controversial. We sampled honeybees from eight coastal locations and three Saharan oases in Libya and analyzed mtDNA variability with restriction fragment length polymorphisms and the sequence of the tRNAleu-cox2 intergenic region. Haplotypes belonging to the oriental O evolutionary lineage, including four which are newly described, were detected in all investigated locations. Haplotypes belonging to the European M lineage were rarely detected, probably reflecting the effect of sporadic importations. Honeybees belonging to the A lineage were detected in Al Aziziyah and Zlitan close to the Tunisian border. The distribution of the O lineage extends westward up to the border between Libya and Tunisia, a contact area between the O and A lineages. Various Libyan honeybee populations in Saharan oases are characterized by novel and unique haplotypes (O4, O5, O5 0 and O5 00 ). These might be natural relic populations that became isolated when the North African Sahara desert was still grassland (0.126-0.168 Myr ago).

We have developed a system for simulating the conditions of avian surveys in which birds are identifi ed by sound. The system uses a laptop computer to control a set of amplifi ed MP3 players placed at known locations around a survey point. The system can realistically simulate a known population of songbirds under a range of factors that aff ect detection probabilities. The goals of our research are to describe the sources and range of variability aff ecting point-count estimates and to fi nd applications of sampling theory and methodologies that produce practical improvements in the quality of bird-census data. Initial experiments in an open fi eld showed that, on average, observers tend to undercount birds on unlimited-radius counts, though the proportion of birds counted by individual observers ranged from 81% to 132% of the actual total. In contrast to the unlimited-radius counts, when data were truncated at a 50-m radius around the point, observers overestimated the total population by 17% to 122%. Results also illustrate how detection distances decline and identifi cation errors increase with increasing levels of ambient noise. Overall, the proportion of birds heard by observers decreased by 28 ± 4.7% under breezy conditions, 41 ± 5.2% with the presence of additional background birds, and 42 ± 3.4% with the addition of 10 dB of white noise. These fi ndings illustrate some of the inherent diffi culties in interpreting avian abundance estimates based on auditory detections, and why estimates that do not account for variations in detection probability will not withstand critical scrutiny.

Monitoring populations of elusive large carnivores like wolves (Canis lupus), which are often distributed at low density in widespread forested areas, is difficult or exceedingly expensive. Aiming to assess the power of two indirect monitoring methods, non-invasive genetic sampling and camera trapping, we designed a small-scale pilot study that was carried out from 2006 to 2008 in and around the Corno alle Scale Regional Park, Bologna, northern Italian Apennine. We collected 103 non-invasive samples (mainly scats) that were genotyped at 12 microsatellite loci and sexed using the ZFX gene. We identified 11 distinct wolf genotypes within the park and four wolf genotypes outside. Spatial locations and kinship analyses showed that the wolves belong to three different packs. The breeding pair of the 'Park' pack showed a complete turnover in the two sampling seasons. Two dogs, but no hybrids, were identified in the area. Up to five unbaited camera traps were activated (for 1,250 trapping-nights) close to recent wolf presence marks. We obtained 103 photos of wolves, documenting the reproduction events, the minimum number of adult and young wolves, and phenotype information each year. We obtained information on health conditions detecting probable sarcoptic mange in three individuals. Camera trapping also showed that the presence of wolves in a chase area during wild boar (Sus scrofa) hunting sessions was significantly higher in the nights just after a chase (P< 0.01, χ 2 test; P<0.07¸ exact Fisher test). The data obtained from genetics and camera trapping were consistent with one other, and in part complementary. The total cost of the study (c. 28,000 €) was moderate, suggesting that this integrated approach can be successfully used to monitor the structure and dynamics of local wolf packs.

Interspecific interactions among mesocarnivores can influence community dynamics and resource partitioning. Insights into these interactions can enhance understanding of local ecological processes that have impacts on pathogen transmission, such as the rabies lyssavirus. Host species ecology can provide an important baseline for disease management strategies especially in biologically diverse ecosystems and heterogeneous landscapes. We used a mesocarnivore guild native to the southwestern United States, a regional rabies
hotspot, that are prone to rabies outbreaks as our study system. Gray foxes (Urocyon cinereoargenteus), striped skunks (Mephitis mephitis), bobcats (Lynx rufus), and coyotes (Canis latrans) share large portions of their geographic ranges and can compete for resources, occupy similar niches, and influence population dynamics of each other. We deployed 80 cameras across two mountain ranges in Arizona, stratified by vegetation type. We used two-stage modeling to gain insight into species occurrence and co-occurrence patterns. There was strong evidence for the effects of elevation, season, and temperature impacting
detection probability of all four species, with understory height and canopy cover also influencing gray foxes and skunks. For all four mesocarnivores, a second stage multi-species co-occurrence model better explained patterns of detection than the single-species occurrence model. These four species are influencing the space use of each other and are likely competing for resources seasonally. We did not observe spatial partitioning between these competitors, likely due to an abundance of cover and food resources in the biologically diverse system we studied. From our results we can draw inferences on community dynamics to inform rabies management in a regional hotspot. Understanding environmental factors in disease hotspots can provide useful information to develop more reliable early-warning systems for viral outbreaks. We recommend that disease management focus on delivering oral vaccine baits onto the landscape when natural food resources are less abundant, specifically during the two drier seasons in Arizona (pre-monsoon spring and autumn) to maximize
intake by all mesocarnivores.

~H NMR spectroscopy assignments have been obtained for starch acetates using COSY and HOHAHA experiments by comparison with the spectra of amylose triacetate and of peracetylated malto-oligosaccharides (maltotriose, maltotetraose, maltoheptaose). These assignments are valuable for the location and evaluation of the substitution pattern in modified starches. The bulk of the l H NMR spectra of highly acetylated starch strongly resembles the spectrum of amylose triacetate in which all protons are identified and display distinct chemical shifts. The resolving power of the HOHAHA experiment allowed the distinction of minor spin systems. Beside these strong signals pertaining to an average 2,3,6-tri-O-acetyl-a-(1 ~ 4) linked o-glucopyranose unit in an infinite chain, the combination of COSY and HOHAHA experiments allowed the identification of these systems to the terminal, n-l, n-2, and to partially acetylated glucopyranosyl units. As an example, two different preparations of starch acetates with degrees of substitution 2.74 and 2.63 were examined. In one case, NMR demonstrates that the defects of acetylation are random on the polymeric chain (with corresponding signals for unacylated secondary hydroxyl positions at 6 3.61 and 3.40) while in another case, these signals are not detectable, probably due to the presence of clusters of non-acetylated residue forming solid-like zones.

Spectrum sensing is a key function of cognitive radio to prevent the harmful interference with licensed users and identify the available spectrum for improving the spectrum's utilization. However, detection performance in practice is often compromised with multipath fading, shadowing and receiver uncertainty issues. To mitigate the impact of these issues, cooperative spectrum sensing has been shown to be an effective method to improve the detection performance by exploiting spatial diversity. While cooperative gain such as improved detection performance and relaxed sensitivity requirement can be obtained, cooperative sensing can incur cooperation overhead. The overhead refers to any extra sensing time, delay, energy, and operations devoted to cooperative sensing and any performance degradation caused by cooperative sensing. In this paper, the stateof-the-art survey of cooperative sensing is provided to address the issues of cooperation method, cooperative gain, and cooperation overhead. Specifically, the cooperation method is analyzed by the fundamental components called the elements of cooperative sensing, including cooperation models, sensing techniques, hypothesis testing, data fusion, control channel and reporting, user selection, and knowledge base. Moreover, the impacting factors of achievable cooperative gain and incurred cooperation overhead are presented. The factors under consideration include sensing time and delay, channel impairments, energy efficiency, cooperation efficiency, mobility, security, and wideband sensing issues. The open research challenges related to each issue in cooperative sensing are also discussed.

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modelling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark-recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modelling analysis engine for spatial and habitat modelling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, stateof-the-art software that implements these methods is described that makes the methods accessible to practising ecologists.

This paper focuses on the detection performances achievable in the presence of Low Probability of Intercept (LPI) radar signals. It well known that the radar community is widely investigating LPI waveforms to reduce the Range Advance Factor (RAF) obtainable with Electronic Support Measure (ESM) systems. Several filtering strategies for LPI signals processing are already available in open literature, but a

The aims of this study were to assess the prevalence of ketosis in type 1 diabetic patients with casual hyperglycemia (&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;250 mg/dl), to establish the relationship between glycemia and ketonemia during daily life, and to determine the utility of ketonemia. Capillary glycemia levels from 562 type 1 diabetic patients were recorded. Prevalence of casual hyperglycemia was 27.58%, and prevalence of asymptomatic ketonemia was 8.39%. Regarding blood ketone levels, 110 out of 155 patients (70.96%) had blood ketone levels of between 0 and 0.1 mmol/l and 32 out of 155 patients (20.63%) had blood ketone levels of between 0.2 and 0.4 mmol/l. Surprisingly, the mean glycemia levels in these subgroups did not differ and was consistently high (around 300 mg/dl), leading to the observation that even ketone levels considered as non-pathologic should probably be taken into account for a proper diabetes control. Some discrepancies between quantitative determination of ketonuria and qualitative determination of ketonemia were observed. That is in 20 patients with positive ketonuria, ketonemia was not detected, probably because ketosis was already resolved. Asymptomatic ketosis was observed in the hyperglycemic type 1 diabetic population, and metabolic control of these patients with a point of care device is recommended, together with a subsequent revision of insulin treatment. Furthermore, this study supports the opinion that the presence of ketosis, detected by beta-OHB levels, even below levels considered as pathologic, together with hyperglycemia, must be taken into account for proper monitoring and therapeutic control of diabetic patients.

The ISO 9001 (2000) define "Quality" as the ability of a set of inherent properties and characteristics of a product, system or process to fulfill requirements of customers and other interested parties. The "Plan de Calidad de Obra (PCO)" is an instrument that follows to get the necessary quality in Civil Works contracts. Graphical documentation generated during construction project elaboration or even during Civil Engineering works execution with planes, makes obligatory a meticulous treatment of this information that results transcendental in the consecution of the definitive products (projects or works) quality objective. In this work it's shown the principal graphical documentation procedures defined in the PCO attending to the edition, modification, distribution, storage, and other relevant aspects related to graphical information.

Magnetic anomaly detection is a good method for detecting ferromagnetic objects, particularly hidden targets. In this work, we address the detection of a moving ferromagnetic target using a static three-axis referenced magnetometer. The analysis and the results are also applicable to the converse case of a static ferromagnetic target and a moving three-axis referenced magnetometer. We use the three magnetometer outputs to build a total magnetic field of the target. This signal is decomposed into a set of orthonormal basis functions, out of which the dominant basis function is chosen as the detector. The detector provides output responses to any target magnetic moment orientation. We support the analysis by a computer simulation and real-world experimental results. The high detection probability and the simple implementation of the proposed method make it attractive for real-time applications.

In this article, we derive six distinct series representations of the generalized Nuttall Q-function. Interestingly, some of these expressions generalise some of the recent results on series representation of the Marcum Q-function since the Marcum Q-function is a special case of the Nuttall Qfunction. To the best of our knowledge, five of these representations are novel and the other one is included for the completeness of the article. The performances of these representations are compared using the magnitude of the truncation error which gives a measure of the accuracy and rate of convergence and allow us to show the strength of each representation. We then discussed the area of applications of our result. We showed that our Nuttall Q-function representations and their corresponding special case (Marcum Q-function) (though not limited to only these), can be used in (i) the computation of outage probability of wireless communication system with co-channel interferers, (ii) the evaluation of detection probability of energy detector over generalized fading channels in cognitive radio system, and (iii) the computation of cumulative distribution of selection diversity combining in correlated Nakagami-m fading channel. In all these areas of application, our solution has no restriction on any parameter of interest.

Elevated landslide rates in forested landscapes can adversely impact aquatic habitat and water quality and remove and/or degrade soil resources required for forest regeneration. As a result, understanding the associations between management actions, natural factors, and landslide rates is important information needed for land managers. An unusual and powerful storm in early December, 2007, caused record flooding and thousands of landslides across southwest Washington and northwest Oregon, USA, and provided a rare opportunity to examine the effects of both natural factors and forest management practices on landslide density. Landslide inventory data were collected from both aerial photos and systematic field surveys to provide a broad survey database that was used to develop estimates of landslide density and to examine associations between landslide density, precipitation, topography, and forest stand age across a 152,000 ha forested landscape in the Willapa Hills, Washington. We estimated the probability of detecting landslides on aerial photos for six strata defined by forest stand age and a broad range of rainfall intensity, expressed as percent of the 100-year, 24-h, maximum rainfall. Key findings are that landslide detection probability decreased with increasing stand age, but was similar across rainfall intensities. The overall fraction of field-detected landslides that were not detected on 1:12,000-scale aerial photos was 39%. Very few landslides occurred in the 0-100% of 100-year rainfall category, regardless of stand age or slope gradient class. At higher rainfall intensities, significantly higher landslide densities occurred on steep slopes (>70% gradient) compared to lower gradient slopes, as expected. Above 150% of 100-year rainfall, the density of landslides was 2-3 times larger in the 0-5 and 6-10 year stand age categories than in the 11-20, 21-30, 31-40, and 41+ categories. The effect of stand age was strongest at the highest rainfall intensities. Our results demonstrate that ground-based landslide inventory data are required in order to correct for detection bias from aerial photos, develop reasonable estimates of landslide density across environmental gradients such as rainfall magnitude and topography, and make unbiased interpretations of relationships between forest management associations and landslide occurrence. ß

Presence-absence data are used widely in analysis of wildlife-habitat relationships. Failure to detect a species' presence in an occupied habitat patch is a common sampling problem when the population size is small, individuals are difficult to sample, or sampling effort is limited. In this paper, the influence of non-detection of occurrence on parameter estimates of logistic regression models of wildlife-habitat relationships was assessed using analytical analysis and simulations. Two patterns of non-detection were investigated: (1) a random distribution of non-detection among occupied patches; and (2) a non-random distribution of nondetection in which the probability of detecting a species in an occupied patch covaried with measurable habitat variables. Our results showed that logistic regression models of wildlife-habitat relationships were sensitive to even low levels of non-detection in occupancy data. Both analytic and simulation studies show that non-detection yields bias in parameter estimation of logistic regression models. More importantly, the direction of bias was affected by the underlying pattern of non-detection and whether the habitat variable was positively or negatively related to occupancy. For a positive habitat coefficient, a random distribution of nondetection yielded negative bias in estimation, whereas linkage of the probability of non-detection to habitat covariates produced positive bias. For a negative habitat coefficient, the pattern was reversed, with a random distribution of non-detection leading to positive bias in estimation. A release-recapture livetrapping study of small mammals in central Indiana, USA, was used to illustrate the magnitude of non-detection in a typical field sampling protocol with varying levels of sampling intensity. Estimates of nondetection error ranged from 0 to 23% for seven species after 5 days of sampling. We suggest that for many sampling situations, relationships between probability of detection and habitat covariates need to be established to correctly interpret results of wildlifehabitat models. #

In this paper, we consider the problem of spectrum sensing in cognitive radio, where unlicensed (secondary) users are allowed to share the vacant frequency bands from the licensed (primary) users. We propose two cooperation protocols to improve the detection probability compared to an existing protocol. In the first protocol, secondary users with higher detection probability constantly act as relays to help those with lower detection probability, while in the second protocol, the help-oriented users choose to relay signals according to the decision made during the first time slot. Analytical studies are provided to demonstrate the enhanced performance of our proposed protocols. Finally, simulation examples are presented to corroborate our analytical results.

Large-scale, multispecies monitoring programs are widely used to assess changes in wildlife populations but they often assume constant,detectability,when,documenting,species,occurrence.,This assumption,is rarely,met,in practice,because,animal populations vary across time and space. As a result, detectability of a species can be influenced by a number of physical, biological, or anthropogenic factors (e.g., weather, seasonality, topography, biological rhythms, sampling methods). To evaluate some of these

Corridors are critical elements in the long-term conservation of wide-ranging species like the jaguar (Panthera onca). Jaguar corridors across the range of the species were initially identified using a GIS-based least-cost corridor model. However, due to inherent errors in remotely sensed data and model uncertainties, these corridors warrant field verification before conservation efforts can begin. We developed a novel corridor assessment protocol based on interview data and site occupancy modeling. We divided our pilot study area, in southeastern Nicaragua, into 71, 6 Â 6 km sampling units and conducted 160 structured interviews with local residents. Interviews were designed to collect data on jaguar and seven prey species so that detection/non-detection matrices could be constructed for each sampling unit. Jaguars were reportedly detected in 57% of the sampling units and had a detection probability of 28%. With the exception of white-lipped peccary, prey species were reportedly detected in 82-100% of the sampling units. Though the use of interview data may violate some assumptions of the occupancy modeling approach for determining 'proportion of area occupied', we countered these shortcomings through study design and interpreting the occupancy parameter, psi, as 'probability of habitat used'. Probability of habitat use was modeled for each target species using single state or multistate models. A combination of the estimated probabilities of habitat use for jaguar and prey was selected to identify the final jaguar corridor. This protocol provides an efficient field methodology for identifying corridors for easily-identifiable species, across large study areas comprised of unprotected, private lands.

The Integrated Probabilistic Data Association (IPDA) type filters provide estimates of the underlying target probability of existence /perceivability/visibility as well as track state maintenance. These quantities are conveniently used as track quality measures and can be used for track confirmation and termination. In this work five filters of this type are investigated and evaluated in a low elevation sea-surface target tracking scenario. The sea-surface induced multipath fading reduces the detection probability of the target at certain ranges which can lead to track loss. In this paper we evaluate the IPDA type filters in such scenario.

~H NMR spectroscopy assignments have been obtained for starch acetates using COSY and HOHAHA experiments by comparison with the spectra of amylose triacetate and of peracetylated malto-oligosaccharides (maltotriose, maltotetraose, maltoheptaose). These assignments are valuable for the location and evaluation of the substitution pattern in modified starches. The bulk of the l H NMR spectra of highly acetylated starch strongly resembles the spectrum of amylose triacetate in which all protons are identified and display distinct chemical shifts. The resolving power of the HOHAHA experiment allowed the distinction of minor spin systems. Beside these strong signals pertaining to an average 2,3,6-tri-O-acetyl-a-(1 ~ 4) linked o-glucopyranose unit in an infinite chain, the combination of COSY and HOHAHA experiments allowed the identification of these systems to the terminal, n-l, n-2, and to partially acetylated glucopyranosyl units. As an example, two different preparations of starch acetates with degrees of substitution 2.74 and 2.63 were examined. In one case, NMR demonstrates that the defects of acetylation are random on the polymeric chain (with corresponding signals for unacylated secondary hydroxyl positions at 6 3.61 and 3.40) while in another case, these signals are not detectable, probably due to the presence of clusters of non-acetylated residue forming solid-like zones.

A number of strategies have been proposed for state-based class testing. An important proposal was made by Chow and adapted by Binder [3]: It consists in deriving test sequences covering all round-trip paths in a finite state machine (FSMs). Based on a number of (rather strong) assumptions, and for traditional FSMs, it can be demonstrated that all operation and transfer errors in the implementation can be uncovered. Through experimentation, this paper investigates this strategy when used in the context of UML statecharts. Based on a set of mutation operators proposed for object-oriented code we seed a significant number of faults in an implementation of a specific container class. We then investigate the effectiveness of four test teams at uncovering faults, based on the round-trip path strategy, and analyze the faults that seem to be difficult to detect. Our main conclusion is that the round-trip path strategy is reasonably effective at detecting faults (87% average as opposed to 69% for sizeequivalent, random test cases) but that a significant number of faults can only exhibit a high detection probability by augmenting the round-trip strategy with a traditional black-box strategy such as category-partition testing. This increases the number of test cases to run -and therefore the cost of testing-and a cost-benefit analysis weighting the increase of testing effort and the likely gain in fault detection is necessary.

Spectrum sensing is a key function of cognitive radio to prevent the harmful interference with licensed users and identify the available spectrum for improving the spectrum's utilization. However, detection performance in practice is often compromised with multipath fading, shadowing and receiver uncertainty issues. To mitigate the impact of these issues, cooperative spectrum sensing has been shown to be an effective method to improve the detection performance by exploiting spatial diversity. While cooperative gain such as improved detection performance and relaxed sensitivity requirement can be obtained, cooperative sensing can incur cooperation overhead. The overhead refers to any extra sensing time, delay, energy, and operations devoted to cooperative sensing and any performance degradation caused by cooperative sensing. In this paper, the stateof-the-art survey of cooperative sensing is provided to address the issues of cooperation method, cooperative gain, and cooperation overhead. Specifically, the cooperation method is analyzed by the fundamental components called the elements of cooperative sensing, including cooperation models, sensing techniques, hypothesis testing, data fusion, control channel and reporting, user selection, and knowledge base. Moreover, the impacting factors of achievable cooperative gain and incurred cooperation overhead are presented. The factors under consideration include sensing time and delay, channel impairments, energy efficiency, cooperation efficiency, mobility, security, and wideband sensing issues. The open research challenges related to each issue in cooperative sensing are also discussed.

In this paper we propose an online tracking algorithm for multiple manoeuvring targets using variable rate particle filters (VRPFs). Unlike conventional particle filters, VRPFs combined with an intrinsic dynamical model enables us to track the manoeuvring behaviour of an object even though only a single dynamical model is employed. Furthermore a Markov Random Field motion model is included for modelling target interactions. In this paper we propose to integrate a data-dependent importance sampling method with the framework to generate more representative state particles. A Poisson observation model is also used to model both targets and clutter measurements, avoiding the data association difficulties associated with traditional tracking approaches. Finally computer simulations demonstrate the potential of the proposed method for tracking multiple highly manoeuvrable targets in a hostile environment with high clutter density and low detection probability.

In this paper, non-duplex (i.e. without plasma nitriding) and duplex (Ti, Al)N and Cr-N coatings produced by ion plating are characterised by means of several analytical methods, such as glow discharge optical emission spectroscopy (GDOES), X-ray diffraction (XRD), surface profilometry, Knoop hardness measurements, scratch tests and scanning electron microscopy (SEM) on fractured and polished cross-sections. After the duplex treatment, an increase in surface roughness of hard PVD coatings could be detected, probably due to an effect of sputter etching by argon/nitrogen ions on the substrate surface during the plasma nitriding step. XRD results indicated that the coatings deposited with and without the plasma nitrided substrate exhibited different dominant phases, which can be attributed to the lower deposition temperatures used for producing the duplex (Ti, Al)N and Cr-N coatings. GDOES results indicated that both non-duplex and duplex (Ti, Al)N coatings had compositions close to Ti 0.50 Al 0.50 N. The non-duplex and duplex Cr-N coatings, however, showed different compositions, with the non-duplex Cr-N coatings displaying a two-layer structure. Finally, scratch tests indicated that the duplex coatings exhibited higher critical loads than their non-duplex counterparts, confirming that a plasma nitriding treatment prior to coating deposition increased the load-bearing capacity of steel substrates. The highest critical loads were recorded for the duplex (Ti, Al)N coating.

Denial of Service attacks constitute one of the greatest problem in network security. Monitoring traffic is one of the main techniques used in order to find out the existence of possible outliers in the traffic patterns. In this paper, we propose an approach that detects Denial of Service attacks using Emergent Self-Organizing Maps. The approach is based on classifying "normal" traffic against "abnormal" traffic in the sense of Denial of Service attacks. The approach permits the automatic classification of events that are contained in logs and visualization of network traffic. Extensive simulations show the effectiveness of this approach compared to previously proposed approaches regarding false alarms and detection probabilities.

Recent concern over global amphibian population declines has highlighted a need for more extensive, rigorous monitoring programs. Two sources of variation, spatial variation and variation in detection probability, make the design and implementation of effective monitoring programs difficult. We used Pollock's robust design in a 3-year capture-recapture study to estimate detection probability and temporary emigration for Plethodon salamanders in Great Smoky Mountains National Park (Tennessee/North Carolina), USA. We used 12 competing models to determine the importance of temporary emigration, and we explored temporal and behavioral effects on conditional capture probabilities. The top 4 models all included random temporary emigration, and Akaike model weights indicated that this parameter was the most important. Models that contained behavioral effects in capture probabilities were selected more often than models with equal capture probabilities for marked and previously unmarked individuals. The "best" model contained random emigration and behavioral effects and was selected 4 times as often as any other model. When we included Markovian emigration, the probability of emigrating from the surface usually was less than the probability of remaining an emigrant (73% of site-years). Markovian emigration estimates often were similar and always had overlapping confidence intervals, thus the Markovian model rarely was chosen over the random emigration models (only 9.6% of site-years). Our study is the first to formally estimate temporary emigration in terrestrial salamander populations, and our results verify that significant proportions of terrestrial salamander populations are subterranean. We determined that the probability of capturing salamanders on the surface may also vary temporally within a sampling season. Therefore, we caution against using unadjusted count indices to compare salamander populations over time or space unless detection probabilities are estimated. Temporary emigration models will improve abundance estimates when a large proportion of the population is unavailable for capture during a given sampling period.

Spectrum sensing is a key function of cognitive radio to prevent the harmful interference with licensed users and identify the available spectrum for improving the spectrum's utilization. However, detection performance in practice is often compromised with multipath fading, shadowing and receiver uncertainty issues. To mitigate the impact of these issues, cooperative spectrum sensing has been shown to be an effective method to improve the detection performance by exploiting spatial diversity. While cooperative gain such as improved detection performance and relaxed sensitivity requirement can be obtained, cooperative sensing can incur cooperation overhead. The overhead refers to any extra sensing time, delay, energy, and operations devoted to cooperative sensing and any performance degradation caused by cooperative sensing. In this paper, the stateof-the-art survey of cooperative sensing is provided to address the issues of cooperation method, cooperative gain, and cooperation overhead. Specifically, the cooperation method is analyzed by the fundamental components called the elements of cooperative sensing, including cooperation models, sensing techniques, hypothesis testing, data fusion, control channel and reporting, user selection, and knowledge base. Moreover, the impacting factors of achievable cooperative gain and incurred cooperation overhead are presented. The factors under consideration include sensing time and delay, channel impairments, energy efficiency, cooperation efficiency, mobility, security, and wideband sensing issues. The open research challenges related to each issue in cooperative sensing are also discussed.

This paper describes the construction and optimization of a Langmuir-Taylor detector for lithium, using a rhenium ribbon. The absolute detection probability of this very sensitive detector is measured and the dependence of this probability with oxygen pressure and surface temperature is studied. Sources of background signal and their minimization are also discussed in details. And a comparison between our data concerning the response time of the detector and literature values is given. A theoretical analysis has been made: this analysis supports the validity of the Saha-Langmuir law to relate the ionization probability to the work function. Finally, the rapid variations of the work function with oxygen pressure and temperature are explained by a chemical equilibrium model.

We present a single-photon avalanche diode (SPAD) with a wide spectral range fabricated in an advanced 180 nm CMOS process. The realized SPAD achieves 20 % photon detection probability (PDP) for wavelengths ranging from 440 nm to 820 nm at an excess bias of 4 V, with 30 % PDP at wavelengths from 520 nm to 720 nm. Dark count rates (DCR) are at most 5 kHz, which is 30 Hz/μm2, at an excess bias of 4V when we measure 10 μm diameter active area structure. Afterpulsing probability, timing jitter, and temperature effects on DCR are also presented.

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Acquisition is the first step in the signal processing section of a Global Positioning System (GPS) receiver. It detects the presence of a GPS signal in the signals received by the antenna and provides estimates of code phase and Doppler to the tracking loops. The acquisition process depends upon the precorrelation bandwidth, analog-to-digital conversion (ADC), sampling frequency and predetection integration time. A GPS software receiver was developed to perform acquisition and tracking of GPS signals. A GPS front-end data logger was used to collect digitized intermediate frequency (IF) data which provides input to the software receiver which performs acquisition, fine frequency estimation and tracking of GPS signals. Different acquisition schemes were implemented in the software receiver and can be chosen to acquire signals depending on the GPS signal conditions. The aim of this paper is to analyze various parameters of the acquisition process and their effects. Circular convolution and modified circular convolution schemes were considered during the analysis. The various parameters analyzed are the sampling frequency, predetection integration period and false detection probability. A GPS simulator (STR 6560) was used to generate GPS signals and the Signal Tap was used to collect data for various analyses. This allowed for the use of real GPS signals rather than simulating them in software with assumptions. These analyses provide a better understanding of acquisition parameters and allow their proper selection.

A generalized likelihood ratio test (GLRT) statistic is proposed for detection of heart rate turbulence (HRT), where a set of Karhunen-Loève basis functions models HRT. The detector structure is based on the extended integral pulse frequency modulation model that accounts for the presence of ectopic beats and HRT. This new test statistic takes a priori information regarding HRT shape into account, whereas our previously presented GLRT detector relied solely on the energy contained in the signal subspace. The spectral relationship between heart rate variability (HRV) and HRT is investigated for the purpose of modeling HRV "noise" present during the turbulence period, the results suggesting that the white noise assumption is feasible to pursue. The performance was studied for both simulated and real data, leading to results which show that the new GLRT detector is superior to the original one as well as to the commonly used parameter turbulence slope (TS) on both types of data. Averaging ten ventricular ectopic beats, the estimated detection probability of the new detector, the previous detector, and TS were found to be 0.83, 0.35, and 0.41, respectively, when the false alarm probability was held fixed at 0.1.

Dispersive Raman spectra of six copal resins, that were purchased in local markets in Mexico, are presented. The spectra were interpreted and compared with each other. For all these spectra, the relative intensity of the Raman band at approximately 1645 cm (1 , attributed to the exomethylene n

Results are reported from a search for low-multiplicity neutrino bursts in the Sudbury Neutrino Observatory (SNO). Such bursts could indicate detection of a nearby core-collapse supernova explosion. The data were taken from Phase I (), when NaCl was added to the target. The search was a blind analysis in which the potential backgrounds were estimated and analysis cuts were developed to eliminate such backgrounds with 90% confidence before the data were examined. The search maintained a greater than 50% detection probability for standard supernovae occuring at a distance of up to 60 kpc for Phase I and up to 70 kpc for Phase II. No low-multiplicity bursts were observed during the data-taking period.

According to the standard economic perspective, criminal activities vary with the 'price' of crime, which depends on the severity of punishment and the detection probability. An alternative view claims that crime is also in uenced by social interaction phenomena, such as 'peer pressure' or 'neighbourhood e ects'. Detecting social interaction in the ÿeld is fraught with di culties, however. In this paper, we argue that given its extensive control possibilities, experiments are well suited to show the potential existence of social interaction e ects. We present an experimental study where people can engage in 'criminal' activities. We ÿnd support for the importance of social interaction: On average subjects steal the more, the more others steal. This behaviour can be interpreted in terms of reciprocity.

Bearings-only tracking (BOT) using a single maneuvering platform has been studied extensively in the past. However, only a few studies exist in the open literature that deal with measurement origin uncertainty. Most publications are concerned with finding the best filtering approach, since BOT is inherently nonlinear, or finding the optimal maneuver strategy for the sensor platform to improve observability. We consider measurement origin uncertainty due to the existence of multiple targets in the surveillance region, non-unity detection probability, and false alarms. Our algorithm uses the multiframe assignment (MFA) to solve the data association problem, and filtering is performed using the unscented Kalman filter (UKF). We employ both the modified and log polar coordinate systems. Simulation results show that the proposed algorithm is very effective in terms of tracking accuracy and track maintenance capability, especially when formulated in the log polar coordinate system.

Point-count surveys are o en used to collect data on the abundance and distribution of birds, generally as an index of relative abundance. Valid comparison of these indices assumes that the detection process is comparable over space and time. These restrictive assumptions can be eliminated by estimating detection probabilities directly. We generalize a recently proposed removal model for estimating detection probabilities using a time-of-detection approach, which can account for more sources of variation in point-count data. This method is specifi cally designed to account for variation in detection probabilities associated with singing rates of birds. Our model accounts for both availability bias and detection bias by modeling the combined probability that a bird sings during the count, and the probability that it is detected given that it sings. The model requires dividing the count into several intervals and recording detections of individual birds in each interval. We develop maximum-likelihood estimators for this approach and provide a full suite of models based on capture-recapture models, including covariate models. We present two examples of this method: one for four species of songbirds surveyed in Great Smoky Mountains National Park using three unequal intervals, and one for the Pearly-eyed Thrasher (Margarops fuscatus) surveyed in Puerto Rico using four equal intervals. Models incorporating individual heterogeneity were selected for all data sets using information-theoretic model-selection techniques. Detection probabilities varied among count-time intervals, which suggests that birds may be responding to observers. We recommend applying this method to surveys with four or more equal intervals to reduce assumptions and to take full advantage of standard capture-recapture so ware. The time-of-detection approach provides a bett er understanding of the detection process, especially when singing rates of individual birds aff ect detection probabilities.

En los últimos años la actividad ganadera en el municipio de Ixiamas al norte de La Paz, Bolivia, se ha incrementado exponencialmente, lo que ha generado una mayor sobreposición de espacios de uso entre actividades humanas y presencia de animales silvestres. Entre los principales conflictos que se generan en la zona están aquellos que resultan del ataque de jaguares (Panthera onca) al ganado vacuno. En este sentido, conocer la sobreposición entre los espacios utilizados por el jaguar y la actividad ganadera tiene implicancia directa para generar acciones de mitigación de conflictos entre jaguares y ganaderos. Para esto, evaluamos el uso del espacio potencial por el jaguar en zonas ganaderas, mediante la estimación de la probabilidad de ocupación (V) y la probabilidad de detección (p). Se evaluaron dos transectos de 600m en cada unidad de muestreo, cuadrículas de 1x1km?. Se establecieron un total de 74 cuadrículas, de las cuales en 33 se detectaron la presencia del jaguar. Construimos modelos de ocupación utilizando el programa PRESENCE 12.7, empleando un análisis de una especie-una estación con probabilidad de autocorrelación espacial. Estimamos la probabilidad uso de espacio basado en una matriz de presencia/ausencia de rastros indirectos de jaguar (ej. huellas, heces) respecto a ocho covariables de sitio (cantidad de bosque, riqueza de especies presa, distancia a caminos principales/secundarios, centros poblados, capital municipal, ríos y predios) y tres covariables de muestreo (#personas que realizaron el muestreo, tiempo desde la última lluvia y tipo de sustrato) estimadas para cada cuadricula. Los resultados sugieren un W=0.71+0.10 y p=0.61+0.2. Siendo el mejor modelo para la estimación del espacio de uso potencial (Cobertura de Bosque), Al#personas que realizaron el muestreo y tiempo desde la última lluvia) con un AIC=313.59. Con este modelo explicativo, estimamos el uso de espacio potencial del jaguar en toda la región ganadera, obteniendo un mapa con cinco niveles de espacios de uso potencial. Luego, a este se sobrepuso un mapa con la representación del espacio geográfico de estancias ganaderas en el área de estudio. Nuestros resultados sugieren que al menos el 50% de estancias ganaderas presentes en la zona (n=62) se encuentran en lugares de mayor uso potencial por el jaguar. Es así que, nuestros resultados nos permitieron identificar las áreas con mayor probabilidad de conflicto con jaguar, con lo cual es posible generar recomendaciones de mitigación del conflicto a las diferentes estancias presentes en la zona.

ORIGINAL PAPER Monitoring wolves (Canis lupus) by non-invasive genetics ... Abstract Monitoring populations of elusive large carni-vores like wolves (Canis lupus), which are often distributed at low density in widespread forested areas, is difficult or exceedingly expensive. ...

⎯ In this paper, we analyze the performance of the encoding and the modulation processes in the downlink and uplink of the EPCglobal Gen2 system through the analysis and simulation. Furthermore, the synchronization issues on time and frequency domain and the preamble architecture are evaluated. Through the simulation in the uplink, we find that the detection probability of FM0 and Miller coding approaches 1 at 13dB E b /N 0 .

In this paper we present an online approach for joint detection and tracking for multiple targets using variable rate particle filters (VRPFs). Unlike conventional models and particle filters, the proposed method utilises the applied forces (tangential and radial components) to model target motions and does not assume the hidden state to change at the same rate as the observations. In effect not only does the proposed method enable us to model parsimoniously the manoeuvring behaviours of targets with a single dynamical model but it also provides a more efficient framework for recursive estimation of the targets' positions since much fewer states will be estimated. In addition, a target detection/termination module will be integrated in the proposed method in which a track initiation, termination, or maintenance move is randomly executed using Bayesian Monte Carlo methods. To model a more realistic observation environment Poisson process is chosen for all target originating and spurious measurements. Unlike other observation models, the proposed model does not require extensive computation for data association between active targets and observations, prior to target state estimation, as a result. To improve the quality of the particles we adopt a data-dependent importance sampling strategy in which the latest observations are involved when new particles are updated. This enables the target states to be updated as new observations arrive while keeping the number of states sufficiently low to track the manoeuvres of the targets. Computer simulations demonstrate the potential of the proposed method for detecting and tracking multiple highly manoeuverable targets in a hostile environment with high clutter density and low detection probability.

An appmach for estimahg the Mure probability of tubes containing through-wall axial cracks has already been proposed by the authors. It is baaed on probabilistic fracture mechanics and accounts for scatter in tube geometry and material properties, scatter in residual and operational strwrees responsible for crack propagation end chcterktics of nondestauctive examidon and ptuggbg prooehaes (e.g., datection probabiity, s i i g accuracy, human errors). Results of Pretimirrarytests demonstrated wide applicability of this approach and triggered some improvements.