Improved Detection Probability Research Articles

Slow hopping based cooperative sensing MAC protocol for cognitive radio networks

A slow hopping based cooperative sensing MAC (SHCS-MAC) protocol is proposed in order to improve aggregate throughput as well as achieve better coexistence with primary users (PUs) and other secondary users (SUs) in cognitive radio (CR) networks where each node has only one half-duplex radio. The proposed SHCS-MAC protocol includes indispensible CR-MAC features such as bootstrapping, multi-channel operation, cooperative sensing, and self-coexistence. Bootstrapping algorithm enables a new node to join a common hopping based network. Slow hopping based multi-channel (MC) operation improves aggregate throughput by enabling concurrent data exchange in different channels on common hopping sequence in which the slot duration can be flexibly selected. Furthermore, cooperative sensing protocol appropriate for the slow hopping based MC-MAC is devised to increase PU detection probability. The improved detection probability enables SUs to promptly evacuate from the channel in which a PU appears. Finally, self-coexistence algorithm is proposed to mitigate the performance degradation due to the interference among neighboring networks. By using extensive simulation and analysis, SHCS-MAC is shown to more efficiently increase network capacity, improve PU detection probability, and achieve self-coexistence with minimal radio cost.

DWT Blind Detection Algorithm of Digital Watermarking on still Image Based on KFDA

The algorithm of blind detection on DWT (Discrete Wavelet Transform) digital watermarking of still image is proposed to overcome the lower detection rate and higher false alarm rate problem. The algorithm utilizes KFDA (Kernel Fisher Discrimination Analysis) theory. With the help of research results of blind detection on DCT digital watermarking, the algorithm passes the test information by stochastic resonance system so as to amplify weak signals. Then the algorithm chooses suitable sample vector by computation. KFDA theory, a kind of learning machine with high precision is used to realize blind detection. Both theoretical analysis and simulation results show that the algorithm improves detection probability at low embedding strength. At the same time the algorithm also decreases false alarm rate.

Using container inspection history to improve interdiction logistics for illicit nuclear materials

Strengthening the United States' ability to prevent adversaries from smuggling nuclear materials into the country is a vital and ongoing issue. The prospect of additional countries, such as Iran, obtaining the know-how and equipment to produce these special nuclear materials in the near future underscores the need for efficient and effective inspection policies at ports and border crossings. In addition, the reduction of defense and homeland security budgets in recent years has made it increasingly important to accomplish the interdiction mission with fewer funds. Addressing these complications, in this article, we present a novel two-port interdiction model. We propose using prior inspection data as a low-cost way of increasing overall interdiction performance. We provide insights into two primary questions: first, how should a decision maker at a domestic port use detection data from the foreign port to improve the overall detection capability? Second, what are potential limitations to the usefulness of prior inspection data—is it possible that using prior data actually harms decision making at the domestic port? We find that a boundary curve policy (BCP) that takes into account both foreign and domestic inspection data can provide a significant improvement in detection probability. This BCP also proves to be surprisingly robust, even if adversaries are able to infiltrate shipments during transit. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 433-448, 2013

Gaussian versus Uniform Distribution for Intrusion Detection in Wireless Sensor Networks

In a Wireless Sensor Network (WSN), intrusion detection is of significant importance in many applications in detecting malicious or unexpected intruder(s). The intruder can be an enemy in a battlefield, or a malicious moving object in the area of interest. With uniform sensor deployment, the detection probability is the same for any point in a WSN. However, some applications may require different degrees of detection probability at different locations. For example, an intrusion detection application may need improved detection probability around important entities. Gaussian-distributed WSNs can provide differentiated detection capabilities at different locations but related work is limited. This paper analyzes the problem of intrusion detection in a Gaussian-distributed WSN by characterizing the detection probability with respect to the application requirements and the network parameters under both single-sensing detection and multiple-sensing detection scenarios. Effects of different network parameters on the detection probability are examined in detail. Furthermore, performance of Gaussian-distributed WSNs is compared with uniformly distributed WSNs. This work allows us to analytically formulate detection probability in a random WSN and provides guidelines in selecting an appropriate deployment strategy and determining critical network parameters.

In silico Surveillance: evaluating outbreak detection with simulation models

BackgroundDetecting outbreaks is a crucial task for public health officials, yet gaps remain in the systematic evaluation of outbreak detection protocols. The authors’ objectives were to design, implement, and test a flexible methodology for generating detailed synthetic surveillance data that provides realistic geographical and temporal clustering of cases and use to evaluate outbreak detection protocols.MethodsA detailed representation of the Boston area was constructed, based on data about individuals, locations, and activity patterns. Influenza-like illness (ILI) transmission was simulated, producing 100 years of in silico ILI data. Six different surveillance systems were designed and developed using gathered cases from the simulated disease data. Performance was measured by inserting test outbreaks into the surveillance streams and analyzing the likelihood and timeliness of detection.ResultsDetection of outbreaks varied from 21% to 95%. Increased coverage did not linearly improve detection probability for all surveillance systems. Relaxing the decision threshold for signaling outbreaks greatly increased false-positives, improved outbreak detection slightly, and led to earlier outbreak detection.ConclusionsGeographical distribution can be more important than coverage level. Detailed simulations of infectious disease transmission can be configured to represent nearly any conceivable scenario. They are a powerful tool for evaluating the performance of surveillance systems and methods used for outbreak detection.

Improved detection probability of a radar target in the presence of multipath with prior knowledge of the environment

A new method to address radar target detection problems in multipath environments is considered. The novelty of the proposed method is that it exploits prior knowledge on the environment and combines it with ray-tracing electromagnetic modelling to determine some information about the possible multipath structure. This information is used to separate the environment into different regions based upon the behaviour of the multipath components. Specifically, as a case study, the authors consider a radar and a target in the presence of a perfectly reflecting planar surface. For this environment, three regions are determined based on the amount of overlap among the multipath components. For each region, receivers are designed exploiting the multipath structure. Thus, a different viewpoint to analyse radar detection problems is suggested. The two main results are the improvement in the target probability of detection, by properly accounting for the multipath and a priori determination of the best performing detector based upon the location of the target and the available signal-to-noise ratio.

Probability of Detection and Visual Count Error for Rafinesque's Big-eared Bat (Corynorhinus rafinesquii) and Southeastern myotis (Myotis austroriparius) in Tree Cavities

A common error in many studies is that a species may go undetected when they are actually present, thus leading to underestimates of the true population. Because imperfect detection can affect population estimates, we calculated detection probabilities of two rare bat species, Rafinesque's big-eared bats (Corynorhinus rafinesquii; RBEB) and southeastern myotis (Myotis austroriparius; SEM), when roosting in tree cavities. We used two methods: repeated surveys of the same tree cavity and a removal method where a tree cavity was eliminated from future surveys after a bat was detected. When repeated surveys were conducted, detection probabilities were 95% for each observer and 100% for two observers combined (n = 43). Using the removal method, each observer independently detected bats in tree cavities in 92% of inspections; whereas, combined observations of two surveyors improved detection probability to 99% (n = 27). We also evaluated count error for species identification and abundance using a two-observer method and compared it to digital infra-red imagery. Count errors were typically <4% and 38% when ≤20 bats and >20 bats were present, respectively, compared to digital images. When count errors occurred, most (64–73%) underestimated the number of bats present. Observers correctly identified species on 91% of occasions. Video recording tree cavities improved estimates of bat abundance and verified species composition. Repeated surveys and the removal method were similarly effective and suitable techniques for monitoring bat species occurrence; however, visual surveys were accurate for estimating abundance when number of bats was ≤20.

Presence detection using wideband audio-ultrasound sensor

A presence detection scheme is proposed for determining occupancy in indoor spaces using a wideband audio-ultrasound sensor. The scheme involves ultrasonic detection by processing the echoes due to transmission of a pulsed sinusoidal waveform, in combination with audio event detection at lower frequencies. The resulting binary detection results are then fused using an OR rule. The proposed scheme improves detection performance by determining occupancy under silent presence and still presence conditions. Experimental results are shown to validate the obtained improvement in probability of detection, while maintaining a given probability of false alarm.

A Low Power BIST TPG for High Fault Coverage

A low hardware overhead scan based BIST test pattern generator (TPG) that reduces switching activities in circuit under test (CUTs) and also achieve very high fault coverage with reasonable length of test sequence is proposed. When the proposed TPG used to generate test patterns for test-per-scan BIST, it decreases the number transitions that occur during scan shifting and hence reduces the switching activity in the CUT. The proposed TPG does not require modifying the function logic and does not degrade system performance. The proposed BIST comprised of three TPGs: Low transition random TPG (LT-RTPG), 3- weight weighted random BIST (3-weight ERBIST) and Dual-speed LFSR (DS-LFSR). Test patterns generated by the LT-RTPG detect the easy-to-detect faults and remain the undetected faults can be detected by the WRBIST. The 3-weight WRBIST is used to reduce the test sequence lengths by improving detection probabilities of random pattern resistant faults (RPRF). The DS-LFSR consists of two LFSR's, slow LFSR and normal-speed LFSR. The DS-LFSR lowers the transition density at their circuit inputs.

EC-GMR Data Analysis for Inspection of Multilayer Airframe Structures

Eddy-current testing (ECT) is widely used in inspection of multilayer aircraft skin structures for the detection of cracks under fasteners (CUF). Detection of deep hidden CUF poses a major challenge in traditional ECT techniques largely because the weak eddy-current signal due to a subsurface crack is dominated by the strong signal from the aluminum or steel fastener. Giant magnetoresistive (GMR) sensors are finding increasing applications in directly measuring weak magnetic fields associated with induced eddy currents. The measured flux image at a fastener site is in general symmetric and an asymmetry is introduced by the presence of a subsurface crack, which is used for defect detection. This paper presents novel methods that employ the resident phase information, for improving detection probability of GMR signal analysis. Using computational model, the effectiveness of the proposed methods for enhancing detection of CUF is investigated. Results demonstrating the potential of these techniques for detection of second layer CUF are presented.

Effects of broadcasting calls during surveys to estimate density and occupancy of northern bobwhite

AbstractWe assessed the effects of using a broadcast caller during surveys and increasing survey duration to estimate northern bobwhite (Colinus virginianus) density and occupancy. From 15 May 2009 to 15 August 2009, we conducted repeat‐visit breeding bobwhite surveys at 180 sites in Delaware, USA. Increasing survey duration from 3 min to 7 min, or using a broadcast caller, improved detection probability for a single visit by 52% and 42%, respectively. However, density estimates when using a broadcast caller were biased high—≥3 times greater compared to passive‐listening surveys. Density estimates for 3‐min and 7‐min passive surveys were not different. Additionally, bobwhite occupancy was similar among all 3 survey treatments. Use of a broadcast caller to survey for bobwhites appears to violate the assumption of distance sampling that an individual is detected prior to movement. Use of a broadcast caller is inappropriate for determining density estimates through distance sampling, but may be appropriate for determining site occupancy. © 2011 The Wildlife Society.

Random or systematic sampling to detect a localised microbial contamination within a batch of food

Pathogenic microorganisms are known to be distributed heterogeneously in food products that are solid, semi-solid or powdered, like for instance peanut butter, cereals, or powdered milk. This complicates effective detection of the pathogens by sampling. Two-class sampling plans, which are deployed when the health hazard is severe and direct, specify how many samples have to be drawn. In order to take a representative sample, the sampling strategy is important, especially when the microorganisms are distributed heterogeneously or localised.This theoretical study shows the impact of random versus systematic sampling on the probability to detect localised microbial contamination in a batch of food. A statistical model was used to compare these sampling strategies. The microbial contamination was modelled as being present in one specific localised fraction of the batch in which the cells were randomly distributed, while no cells were present in the remaining part of the batch.The probability that the entire sampling scheme contains at least one cell was calculated for various numbers of samples drawn either randomly or systematically and was shown to depend on the size of the contaminated fraction, the microbial concentrations, and the number of samples drawn. The probability of detection was either equal or higher for systematic sampling as compared to random sampling. The maximal improvement in probability of detection was 0.37, when the sampling interval was equal to the size of the contaminated fraction, meaning that exactly one systematic sample hits the contaminated fraction. In those cases where the size of the contaminated fraction can be estimated, this study may assist in selecting the sampling strategy that is most optimal regarding probability of detection.

Improving detection probabilities for pests in stored grain

The presence of insects in stored grain is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspection of bulk grain commodities is essential to detect pests and thereby to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grain, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper, a sampling methodology is demonstrated that accounts for the heterogeneous distribution of insects in bulk grain. It is shown that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling programme to detect insects in bulk grain. The results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. It is also demonstrated that the probability of detecting pests in bulk grain increases as the number of subsamples increases, even when the total volume or mass of grain sampled remains constant. This study underlines the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models.

Improving Probability of Detection of Bolt Hole Eddy Current Inspection

Probability of detection (POD) of fatigue cracks and electric discharge machined (EDM) notches in 7075-T6 aluminum was evaluated for a bolt-hole eddy current inspection system. The POD study involved simulated bolt holes in coupons representative of wing areas on CC-130 and CP-140 aircraft. The data were obtained from 24 inspectors who inspected 468 coupons that contained a set of coupons with 45 EDM notches and 72 laboratory-grown fatigue cracks located at the inner surface corner of the bi-layer structures. A single point calibration based upon a 0.76 mm (0.030 inches) deep corner notch set to 20% of screen height (SH) was utilized. Large variability in detection capability between inspectors was observed. A portion of this variability was attributed to significant background noise on the order of 5% screen height (SH). Normalization of each inspector's data to signal amplitudes from notches at twice the depth (1.5 to 1.6 mm (0.060 inches)), close to 40% SH, reduced the relative variations and resulted in a 10–20% improvement in POD. These results indicate that calibration with signal responses from notches larger than that currently used would improve the POD for this inspection system and demonstrate the potential of using POD data to improve inspection systems.

An Intervehicular-Communication Protocol for Distributed Detection of Dangerous Vehicles

Recently, considerable research has been focused on applying ad hoc wireless networking technology to on-the-move vehicles. In this paper, we focus on distributed detection of dangerous vehicles on roads and highways. We propose the dangerous-vehicle-detection protocol (DVDP) to detect drivers who violate the permitted speed limit. In DVDP, each vehicle collects surrounding vehicles' identifications (IDs) and propagates warning information (including its position, speed, time, and collected IDs). This information is then forwarded hop-by-hop using ad hoc communications. A vehicle that receives this information will start to observe its surrounding vehicles. If surrounding vehicles are identified in the received warning information, it will estimate the speed of such vehicles. If the estimated speed exceeds the permitted speed, such vehicles are then marked as ?suspected vehicles,? and the updated warning information is further propagated. By repeating this process, the suspected vehicle (where other vehicles observe the speed violation) will ultimately be marked as a ?dangerous vehicle.? This judgment is then further propagated to warn others and to inform the traffic police. We evaluated the performance of DVDP using a simulator that performs both macroscopic and microscopic traffic simulation, taking into account realistic lane and speed models, mobility, position, and location errors. Simulation results revealed that DVDP's detection probability is greater than 80% when vehicle density is above 40 vehicles/min. When vehicle density is low, deployment of relay points can help to further improve detection probability. In addition, by utilizing vehicles in opposite lanes, detection probability can be further improved.

Estimation of survival and detection probabilities for multiple tagged salmon stocks with nested migration routes, using a large-scale telemetry array

Mark–recapture models for estimating survival and detection probabilities of tagged animals that migrate past successive receiver stations can incorporate multiple, linked stocks to improve detection probability estimates. When multiple release groups are analysed in a common framework, detection information can be shared to compensate for small sample sizes and provide generality beyond single-stock approaches. Methods for structuring complex detection history data and applying standard mark–recapture models are presented, allowing for information sharing among multiple stocks under nested migration route structures, where some portions of routes are shared with other stocks and other portions are unique. Possible biases from split-route migration patterns within a release group are described, along with a simple method of correcting these biases using stock-specific parameters that incorporate movement probabilities. Environmental covariates can be paired with stock-specific run timing data to model stock-specific detection probabilities that change seasonally. Finally, a method for assessing the redundancy of receivers on a multiple-receiver detection line is described, based on considerations of receiver line geometry. Examples are drawn from detection data of juvenile salmon on the Pacific Ocean Shelf Tracking Project (POST) array, but the methods presented here are transferable to other systems.

Detecting gravitational wave emission from the known accreting neutron stars

Detection of gravitational waves from accreting neutron stars (NSs) in our galaxy, due to ellipticity or internal oscillation, would be a breakthrough in our understanding of compact objects and explain the absence of NSs rotating near the break-up limit. Direct detection, however, poses a formidable challenge. Using the current data available on the properties of the accreting NSs in Low Mass X-Ray Binaries (LMXBs), we quantify the detectability for the known accreting NSs, considering various emission scenarios and taking into account the negative impact of parameter uncertainty on the data analysis process. Only a few of the persistently bright NSs accreting at rates near the Eddington limit are detectable by Advanced LIGO if they are emitting gravitational waves at a rate matching the torque from accretion. A larger fraction of the known population is detectable if the spin and orbital parameters are known in advance, especially with the narrow-band Advanced LIGO. We identify the most promising targets, and list specific actions that would lead to significant improvements in detection probability. These include astronomical observations (especially for unknown orbital periods), improvements in data analysis algorithms and capabilities, and further detector development.

Study on the long-distance target apperception techniques for underwater vehicles

The limited physical size for autonomous underwater vehicles (AUV) or unmanned underwater vehicles (UUV) makes it difficult to acquire enough space gain for localizing long-distance targets. A new technique about long-distance target apperception with passive synthetic aperture array for underwater vehicles is presented. First, a synthetic aperture-processing algorithm based on the FFT transform in the beam space (BSSAP) is introduced. Then, the study on the flank array passive long-distance apperception techniques in the frequency scope of 11–18 kHz is implemented from the view of improving array gains, detection probability and augmenting detected range under a certain sea environment. The results show that the BSSAP algorithm can extend the aperture effectively and improve detection probability. Because of the augment of the transmission loss, the detected range has the trend of decline with the increase of frequency under the same target source level. The synthesized array could improve the space gain by nearly 7 dB and SNR is increased by about 5 dB. The detected range is enhanced to nearly 2 km under the condition of 108–118 dB of the target source level for AUV system in measurement interval of nearly 1 s.

Detection Probability Improvement for Nondestructive Evaluation Using a Magnetic Camera

It is important to estimate the intensity distribution of a magnetic field as a possible magnetic method in an industrial nondestructive evaluation application. A magnetic camera provides the distribution of a quantitative magnetic field with homogeneous lift-off and same spatial resolution. Magnetic flux leakage near a crack on the specimen can be amplified by using a 3- dimensional magnetic fluid, that is to say a magnetic lens. This study introduces the experimental consideration of the effects of magnetic lenses for concentrating of magnetic flux. The experimental results showed that the magnetic fluid has a sufficient lens effect for magnetic camera and effect of improvement in probability of detection.

Detection enhancement using multiple time-reversed guide sources in shallow water

Detection in a monostatic, broadband, active sonar system in shallow water is degraded by propagation-induced spreading. Improved detection has previously been achieved in the 3- to 3.5-kHz range by using the information in time-reversed one-way transmissions from multiple spatially separated guide sources. Detection results in the wider 500- to 3500-Hz band from an experiment south of the Hudson Canyon off the coast of New Jersey are presented in this talk. The target as well as the guide source was an echo repeater positioned at various water depths and ranges. Various subapertures of the 64-element NRL source receiver array were used to transmit 0.25-s LFMs and detect their echoes. The guide source data is analyzed to show the amount of information content depending on aperture and bandwidth. The improvement in probability of detection using multiple guide-source signals is compared with a baseline probability using matched filtering. Improvement in detection as a function of the number of guide sources and their range is also discussed. [Work supported by ONR.]