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Journal articles on the topic 'The Optimum Detection Probabilities'

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Author: Grafiati

Published: 11 September 2023

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1

Al-Ababneh, Nedal, and Hasan Aldiabat. "Optimum consultation for serial distributed detection systems." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (June 1, 2022): 2636. http://dx.doi.org/10.11591/ijece.v12i3.pp2636-2644.

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<p>This paper considers a distributed detection system which consists of sensors that are connected in series. The observations of each sensor in this system design are considered to be statistically independent of all other sensors. In contrast to the popular serial decision fusion systems, we assume that consultations are allowed in a serial manner between successive sensors that make up the system. In addition, the paper demonstrates the similarity between the proposed consulting serial system and the optimal serial one in terms of detection probabilities for a give probability of false alarm. However, it should be emphasized that the proposed system has the benefit of conditional nonrandom consultation among the sensors. Consequently, its survivability is higher than that of serial systems. Numerical evaluations for the cases of two and three sensors are provided and compared with those of the serial as well as the centralized schemes.</p>

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Friehe, Tim. "Optimal sanctions and endogeneity of differences in detection probabilities." International Review of Law and Economics 28, no. 2 (June 2008): 150–55. http://dx.doi.org/10.1016/j.irle.2008.02.004.

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Pateriya, Priyanka, Rakesh Singhai, and Piyush Shukla. "Design and Implementation of Optimum LSD Coded Signal Processing Algorithm in the Multiple-Antenna System for the 5G Wireless Technology." Wireless Communications and Mobile Computing 2022 (February 25, 2022): 1–12. http://dx.doi.org/10.1155/2022/7628814.

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The 5G system requires an optimum coding technique to achieve the high diversity gain, low bit error rate (BER), and low detection complexity. Various coding techniques were developed in recent times for improving the diversity performance of the MIMO systems. Space-time-coding (STC) is used to fulfill the requirement of handling large data flow in the 5G wireless communications. It is highly required to optimize the orthogonal nature of STC. The paper proposed a novel design of the optimum linearly scalable dispersion code (O-LSDC). In this paper, an optimum coefficient-based O-LSDC is designed based on the elementary matrix operations, unitary matrix normalization technique, and coefficient mapping strategy. Mapped coefficients are linearly solved for optimum value estimation. To find the optimum solution of the LSDC codes, five cases of LSDC are defined based on the scaling coefficients and then performance is evaluated against the BER vs. SNR. Evaluating the simulation results in terms of error probabilities for the five different orthonormal LSDC, this work simulates the system for multiple antennas using the Rayleigh fading MIMO system model. Also, evaluating the impact of the proposed LSDC over the BER performance for the varied number of Monte Carlo iterations, then the performance graph is plotted for multiple-antennas system. The proposed O-LSDC under Rayleigh fading channel using the M-PSK modulation enhances the performance of the 5G and beyond communication system in terms of BER and SNR.

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Solodov, A. A. "Optimal Poisson Cognitive System with Markov Learning Model." Open Education 25, no. 6 (December 27, 2021): 45–52. http://dx.doi.org/10.21686/1818-4243-2021-6-45-52.

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The aim of the study is to develop a mathematical model of the trained Markov cognitive system in the presence of discrete training and interfering random stimuli arising at random times at its input. The research method consists in the application of the simplest Markov learning model of Estes with a stochastic matrix with two states, in which the transition probabilities are calculated in accordance with the optimal Neуman-Pearson algorithm for detecting stimuli affecting the system. The paper proposes a model of the random appearance of images at the input of the cognitive system (in terms of learning theory, these are stimuli to which the system reacts). The model assumes an exponential distribution of the system’s response time to stimuli that is widely used to describe intellectual work, while their number is distributed according to the Poisson law. It is assumed that the cognitive system makes a decision about the presence or absence of a stimulus at its input in accordance with the Neуman-Pearson optimality criterion, i.e. maximizes the probability of correct detection of the stimulus with a fixed probability of false detection. The probabilities calculated in this way are accepted as transition probabilities in the stochastic learning matrix of the system. Thus, the following assumptions are accepted in the work, apparently corresponding to the behavior of the system assuming human reactions, i.e. the cognitive system.The images analyzed by the system arise at random moments of time, while the duration of time between neighboring appearances of images is distributed exponentially.The system analyzes the resulting images and makes a decision about the presence or absence of an image at its input in accordance with the optimal Neуman-Pearson algorithm that maximizes the probability of correct identification of the image with a fixed probability of false identification.The system is trainable in the sense that decisions about the presence or absence of an image are made sequentially on a set of identical situations, and the probability of making a decision depends on the previous decision of the system.The new results of the study are analytical expressions for the probabilities of the system staying in each of the possible states, depending on the number of steps of the learning process and the intensities of useful and interfering stimuli at the input of the system. These probabilities are calculated for an interesting case in which the discreteness of the appearance of stimuli in time is clearly manifested and the corresponding graphs are given. Stationary probabilities are also calculated, i.e. for an infinite number of training steps, the probabilities of the system staying in each of the states and the corresponding graph is presented.In conclusion, it is noted that the presented graphs of the behavior of the trained system correspond to an intuitive idea of the reaction of the cognitive system to the appearance of stimuli. Some possible directions of further research on the topic mentioned in the paper are indicated.

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Schmidt, A., C. Kruse, F. Rottensteiner, U. Soergel, and C. Heipke. "NETWORK DETECTION IN RASTER DATA USING MARKED POINT PROCESSES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 10, 2016): 701–8. http://dx.doi.org/10.5194/isprs-archives-xli-b3-701-2016.

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We propose a new approach for the automatic detection of network structures in raster data. The model for the network structure is represented by a graph whose nodes and edges correspond to junction-points and to connecting line segments, respectively; nodes and edges are further described by certain parameters. We embed this model in the probabilistic framework of marked point processes and determine the most probable configuration of objects by stochastic sampling. That is, different graph configurations are constructed randomly by modifying the graph entity parameters, by adding and removing nodes and edges to/ from the current graph configuration. Each configuration is then evaluated based on the probabilities of the changes and an energy function describing the conformity with a predefined model. By using the Reversible Jump Markov Chain Monte Carlo sampler, a global optimum of the energy function is determined. We apply our method to the detection of river and tidal channel networks in digital terrain models. In comparison to our previous work, we introduce constraints concerning the flow direction of water into the energy function. Our goal is to analyse the influence of different parameter settings on the results of network detection in both, synthetic and real data. Our results show the general potential of our method for the detection of river networks in different types of terrain.

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Schmidt, A., C. Kruse, F. Rottensteiner, U. Soergel, and C. Heipke. "NETWORK DETECTION IN RASTER DATA USING MARKED POINT PROCESSES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 10, 2016): 701–8. http://dx.doi.org/10.5194/isprsarchives-xli-b3-701-2016.

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We propose a new approach for the automatic detection of network structures in raster data. The model for the network structure is represented by a graph whose nodes and edges correspond to junction-points and to connecting line segments, respectively; nodes and edges are further described by certain parameters. We embed this model in the probabilistic framework of marked point processes and determine the most probable configuration of objects by stochastic sampling. That is, different graph configurations are constructed randomly by modifying the graph entity parameters, by adding and removing nodes and edges to/ from the current graph configuration. Each configuration is then evaluated based on the probabilities of the changes and an energy function describing the conformity with a predefined model. By using the Reversible Jump Markov Chain Monte Carlo sampler, a global optimum of the energy function is determined. We apply our method to the detection of river and tidal channel networks in digital terrain models. In comparison to our previous work, we introduce constraints concerning the flow direction of water into the energy function. Our goal is to analyse the influence of different parameter settings on the results of network detection in both, synthetic and real data. Our results show the general potential of our method for the detection of river networks in different types of terrain.

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Valdez, Jose W., Kaya Klop-Toker, Michelle P. Stockwell, Loren Fardell, Simon Clulow, John Clulow, and Michael J. Mahony. "Differences in microhabitat selection patterns between a remnant and constructed landscape following management intervention." Wildlife Research 44, no. 3 (2017): 248. http://dx.doi.org/10.1071/wr16172.

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Context Achieving successful conservation outcomes in habitat creation and reintroductions requires an understanding of how species use their habitat and respond to these interventions. However, few initiatives directly compare microhabitat selection between remnant and managed habitats to measure effectiveness and evaluate outcomes. Probability of detection is also rarely included in studies on microhabitat use, which may lead to erroneous conclusions if detectability varies between variables. Methods In this study, we used the endangered green and golden bell frog (Litoria aurea) to compare differences in microhabitat-use patterns in both a remnant and a constructed habitat. A detectability study was also conducted to determine detection probabilities among microhabitats. Key results Aquatic vegetation was used more than expected in both the remnant and constructed habitats, and rock piles were utilised less than expected in the constructed habitat, despite their recommendation in most habitat templates. We found that detection probabilities altered the outcomes of abundance estimates for nearly all the measured microhabitat variables. Conclusions Future management for this species should focus on providing high proportions of aquatic vegetation. Furthermore, although rock piles have been utilised greatly in past L. aurea habitat creation, placing large rocks on a managed site is expensive and time consuming. Future management initiatives may need to focus on providing smaller proportion of rocks, which would be a more appropriate use of resources. Implications With conservation management projects increasing over the next few decades, understanding habitat use before implementing strategies should be a priority as it will provide important insights and inform decision-making for optimum habitat creation and restoration. Furthermore, accounting for detectability in microhabitat use studies is essential to avoid wrong conclusions that may negatively affect the success of ecological management strategies.

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Yang, Ling, Nathan L. Knight, Yong Li, and Chris Rizos. "Optimal Fault Detection and Exclusion Applied in GNSS Positioning." Journal of Navigation 66, no. 5 (May 17, 2013): 683–700. http://dx.doi.org/10.1017/s0373463313000155.

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In Global Navigation Satellite System (GNSS) positioning, it is standard practice to apply the Fault Detection and Exclusion (FDE) procedure iteratively, in order to exclude all faulty measurements and then ensure reliable positioning results. Since it is often only necessary to consider a single fault in a Receiver Autonomous Integrity Monitoring (RAIM) procedure, it would be ideal if a fault could be correctly identified. Thus, fault detection does not need to be applied in an iterative sense. One way of evaluating whether fault detection needs to be reapplied is to determine the probability of a wrong exclusion. To date, however, limited progress has been made in evaluating such probabilities. In this paper the relationships between different parameters are analysed in terms of the probability of correct and incorrect identification. Using this knowledge, a practical strategy for incorporating the probability of a wrong exclusion into the FDE procedure is developed. The theoretical findings are then demonstrated using a GPS single point positioning example.

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Lubis, Arif Ridho, Santi Prayudani, Muharman Lubis, and Al Khowarizmi. "Decision Making in the Tea Leaves Diseases Detection Using Mamdani Fuzzy Inference Method." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 3 (December 1, 2018): 1273. http://dx.doi.org/10.11591/ijeecs.v12.i3.pp1273-1281.

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The tea plants (Camellia Sinensis) are small tree species that use leaves and leaf buds to produce tea harvested through a monoculture system. It is an agriculture practice to cultivate one types of crop or livestock, variety or breed on a farm annually. Moreover, the emergence of pests, pathogens and diseases cause serious damages to tea plants significantly to its productivity and quality to optimum worst. All parts of the tea plant such as leaves, stems, roots, flowers and fruits are exposed to these harm lead to loss of yield 7 until 10% per year. The intensity of these attacks vary greatly on particular climate, the degree slope and the plant material used. Therefore, this study analyzes tea leaves as a common part used in recipes to create unique taste and flavor in tea production, especially in agro-industry. The decision making method used is Fuzzy Mamdani Inference as one of model with functional hierarchy with initial input based on established criteria. Fuzzy logic will provide tolerance to the set of value, so that small changes will not result in significant category differences, only affect the membership level on the variable value. Previous method using probabilities have shown 78% tea leaves have been attacked by category C (Gray Blight) while using Mamdani indicated 86% of tea leaves have been infected. In this case, this result pointed out that Fuzzy Mamdani Inferences have more optimal result compare to the previous method.

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El Jarroudi, Moussa, Louis Kouadio, Clive H. Bock, Mustapha El Jarroudi, Jürgen Junk, Matias Pasquali, Henri Maraite, and Philippe Delfosse. "A Threshold-Based Weather Model for Predicting Stripe Rust Infection in Winter Wheat." Plant Disease 101, no. 5 (May 2017): 693–703. http://dx.doi.org/10.1094/pdis-12-16-1766-re.

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Wheat stripe rust (caused by Puccinia striiformis f. sp. tritici) is a major threat in most wheat growing regions worldwide, which potentially causes substantial yield losses when environmental conditions are favorable. Data from 1999 to 2015 for three representative wheat-growing sites in Luxembourg were used to develop a threshold-based weather model for predicting wheat stripe rust. First, the range of favorable weather conditions using a Monte Carlo simulation method based on the Dennis model were characterized. Then, the optimum combined favorable weather variables (air temperature, relative humidity, and rainfall) during the most critical infection period (May-June) was identified and was used to develop the model. Uninterrupted hours with such favorable weather conditions over each dekad (i.e., 10-day period) during May-June were also considered when building the model. Results showed that a combination of relative humidity >92% and 4°C < temperature < 16°C for a minimum of 4 continuous hours, associated with rainfall ≤0.1 mm (with the dekad having these conditions for 5 to 20% of the time), were optimum to the development of a wheat stripe rust epidemic. The model accurately predicted infection events: probabilities of detection were ≥0.90 and false alarm ratios were ≤0.38 on average, and critical success indexes ranged from 0.63 to 1. The method is potentially applicable to studies of other economically important fungal diseases of other crops or in different geographical locations. If weather forecasts are available, the threshold-based weather model can be integrated into an operational warning system to guide fungicide applications.

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Santarossa, J. M., A. W. Stott, J. A. Woolliams, S. Brotherstone, E. Wall, and M. P. Coffey. "An economic evaluation of long-term sustainability in the dairy sector." Animal Science 79, no. 2 (October 2004): 315–25. http://dx.doi.org/10.1017/s1357729800090172.

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AbstractThis paper addresses the problem of assigning economic weights to heritable genetic traits of dairy cows while taking all implicit natural resource values into consideration. To do so, a deterministic bio-economic model of a dairy farm enterprise driven by input probabilities of oestrous detection and conception rates that act through the calving interval is constructed. The model further accounts for biologically limiting factors of both livestock and land within a neo-classical economics framework of profit maximization. Departing from the more customary approach of obtaining gross margins to calculate levels of return in the agricultural sector, we employ a natural resource economics methodology where returns are set against an economic point of reference specified as the value of natural assets' productivity and terminal assets' resale value. Introducing the impact of farming intensity on soil fertility enables us to obtain long-run variations in natural asset values as affected by tillage intensity. Results show that economic weights are not constant over the range of changes in genetic improvements due to the non-linearity of the system induced by diminishing marginal product of inputs and finite carrying capacity of resources employed. These values, while invariant to area farmed, are however subject to variations in resource quality and therefore will reflect the sensitivity of long-term sustainability of the system to managerial decisions on intensity of operation. Results further demonstrated that achieving optimum levels of output while precluding the impact of intensity on land productivity can seriously reduce the time horizon over which sustainability can be maintained. Inclusion of the implicit costs of land use on the other hand tended to suggest optimum levels of output below those identified when only considering accounting data.

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Lofrano, Egidio, Marco Pingaro, Patrizia Trovalusci, and Achille Paolone. "Optimal Sensors Placement in Dynamic Damage Detection of Beams Using a Statistical Approach." Journal of Optimization Theory and Applications 187, no. 3 (October 16, 2020): 758–75. http://dx.doi.org/10.1007/s10957-020-01761-3.

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AbstractStructural monitoring plays a central role in civil engineering; in particular, optimal sensor positioning is essential for correct monitoring both in terms of usable data and for optimizing the cost of the setup sensors. In this context, we focus our attention on the identification of the dynamic response of beam-like structures with uncertain damages. In particular, the non-localized damage is described using a Gaussian distributed random damage parameter. Furthermore, a procedure for selecting an optimal number of sensor placements has been presented based on the comparison among the probability of damage occurrence and the probability to detect the damage, where the former can be evaluated from the known distribution of the random parameter, whereas the latter is evaluated exploiting the closed-form asymptotic solution provided by a perturbation approach. The presented case study shows the capability and reliability of the proposed procedure for detecting the minimum number of sensors such that the monitoring accuracy (estimated by an error function measuring the differences among the two probabilities) is not greater than a control small value.

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El Jarroudi, Moussa, Rachid Lahlali, Louis Kouadio, Antoine Denis, Alexandre Belleflamme, Mustapha El Jarroudi, Mohammed Boulif, Hamid Mahyou, and Bernard Tychon. "Weather-Based Predictive Modeling of Wheat Stripe Rust Infection in Morocco." Agronomy 10, no. 2 (February 15, 2020): 280. http://dx.doi.org/10.3390/agronomy10020280.

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Predicting infections by Puccinia striiformis f. sp. tritici, with sufficient lead times, helps determine whether fungicide sprays should be applied in order to prevent the risk of wheat stripe rust (WSR) epidemics that might otherwise lead to yield loss. Despite the increasing threat of WSR to wheat production in Morocco, a model for predicting WSR infection events has yet to be developed. In this study, data collected during two consecutive cropping seasons in 2018–2019 in bread and durum wheat fields at nine representative sites (98 and 99 fields in 2018 and 2019, respectively) were used to develop a weather-based model for predicting infections by P. striiformis. Varying levels of WSR incidence and severity were observed according to the site, year, and wheat species. A combined effect of relative humidity > 90%, rainfall ≤ 0.1 mm, and temperature ranging from 8 to 16 °C for a minimum of 4 continuous hours (with the week having these conditions for 5% to 10% of the time) during March–May were optimum to the development of WSR epidemics. Using the weather-based model, WSR infections were satisfactorily predicted, with probabilities of detection ≥ 0.92, critical success index ranging from 0.68 to 0.87, and false alarm ratio ranging from 0.10 to 0.32. Our findings could serve as a basis for developing a decision support tool for guiding on-farm WSR disease management, which could help ensure a sustainable and environmentally friendly wheat production in Morocco.

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Baker, Leanne F., Kyle J. Artym, and Heidi K. Swanson. "Optimal sampling methods for modelling the occupancy of Arctic grayling (Thymallus arcticus) in the Canadian Barrenlands." Canadian Journal of Fisheries and Aquatic Sciences 74, no. 10 (October 2017): 1564–74. http://dx.doi.org/10.1139/cjfas-2016-0429.

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In occupancy models, imperfect detectability of animals is usually corrected for by using temporally repeated surveys to estimate probability of detection. Substituting spatial replicates for temporal replicates could be an advantageous sampling strategy in remote Arctic regions, but may lead to serious violations of model assumptions. Using a case study of site occupancy of adfluvial young-of-year Arctic grayling (Thymallus arcticus) in Barrenland tundra streams, we assessed the reliability and efficiency of alternative sampling strategies: (i) randomly distributed versus sequential adjacent spatial replicates; (ii) visual versus electrofishing surveys; and (iii) spatial versus temporal replicates. Sequential, adjacent spatial replicates produced spatially autocorrelated data. Autocorrelation was relieved using randomly distributed spatial replicates, but using these randomly distributed spatial replicates introduced significant error into estimates of the probability of occupancy in streams. Models designed for spatially autocorrelated data could minimize this bias. Visual and electrofishing surveys produced comparable probabilities of detection. Spatially replicated surveys performed better than temporal replicates. The easiest and relatively most cost-effective sampling methods performed as well as, or better than, the more established, expensive, and logistically difficult alternatives for occupancy estimation.

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Micheyl, Christophe, and David P. Messing. "Likelihood ratio, optimal decision rules, and correct response probabilities in a signal detection theoretic, equal-variance Gaussian model of the observer in the 4IAX paradigm." Perception & Psychophysics 68, no. 5 (July 2006): 725–35. http://dx.doi.org/10.3758/bf03193696.

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Yu, Jinsong, Jie Yang, Diyin Tang, and Jing Dai. "An Optimal Burn-In Policy for Cellular Phone Lithium-Ion Batteries Using a Feature Selection Strategy and Relevance Vector Machine." Energies 11, no. 11 (November 2, 2018): 3021. http://dx.doi.org/10.3390/en11113021.

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The early detection of defective lithium-ion batteries in cellular phones is critical due to the rapid increase in popularity and mass production of cellular phones. It is essential for manufacturers to design an optimal burn-in policy to differentiate between normal and weak batteries in short cycles prior to shipping them to the marketplace. A novel approach to determine the optimal burn-in policy using a feature selection strategy and relevance vector machine (RVM) is proposed. The sequential floating forward search (SFFS) is used as the feature selection method to find an optimal feature subset from the entire sequence of the batteries’ quality characteristics while preserving the original variables. Given the selected feature subset, the RVM is applied to classify batteries into two groups and simultaneously obtain the posterior probabilities. To achieve better discrimination performance with less risk, a new characteristic is extracted from the discharge profile. Subsequently, an optimization cost model is developed by introducing a classification instability penalty to ensure the stability of the optimal number of burn-in cycles. A case study utilizing cellular phone lithium-ion batteries randomly selected from manufactured lots is presented to illustrate the proposed methodology. Furthermore, we conduct a comparison with the cumulative degradation (CD) method and non-cumulative degradation (NCD) method based on the Wiener process. The results show that our proposed burn-in test method performs better than comparable methods.

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Roy, Arunabha S., and S. M. Roy. "Optimum phase space probabilities from quantum tomography." Journal of Mathematical Physics 55, no. 1 (January 2014): 012102. http://dx.doi.org/10.1063/1.4854035.

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Schorlemmer, Danijel, Naoshi Hirata, Yuzo Ishigaki, Keiji Doi, Kazuyoshi Z. Nanjo, Hiroshi Tsuruoka, Thomas Beutin, and Fabian Euchner. "Earthquake Detection Probabilities in Japan." Bulletin of the Seismological Society of America 108, no. 2 (February 6, 2018): 702–17. http://dx.doi.org/10.1785/0120170110.

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Thoreson, Gregory G., and Erich A. Schneider. "Efficient calculation of detection probabilities." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 615, no. 3 (April 2010): 313–25. http://dx.doi.org/10.1016/j.nima.2010.02.003.

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20

Sarwate, D. V. "Computation of binary integration detection probabilities." IEEE Transactions on Aerospace and Electronic Systems 27, no. 6 (1991): 894–97. http://dx.doi.org/10.1109/7.104254.

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Shnidman, D. A. "Radar detection probabilities and their calculation." IEEE Transactions on Aerospace and Electronic Systems 31, no. 3 (July 1995): 928–50. http://dx.doi.org/10.1109/7.395246.

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Clayton, C. Andrew, John W. Hines, and Phyllis D. Elkins. "Detection limits with specified assurance probabilities." Analytical Chemistry 59, no. 20 (October 15, 1987): 2506–14. http://dx.doi.org/10.1021/ac00147a014.

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Hou, Xiu-ying, Norihiko Morinaga, and Toshihiko Namekawa. "Direct Evaluation of Radar Detection Probabilities." IEEE Transactions on Aerospace and Electronic Systems AES-23, no. 4 (July 1987): 418–24. http://dx.doi.org/10.1109/taes.1987.310875.

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White, Gary C. "Correcting wildlife counts using detection probabilities." Wildlife Research 32, no. 3 (2005): 211. http://dx.doi.org/10.1071/wr03123.

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One of the most pervasive uses of indices of wildlife populations is uncorrected counts of animals. Two examples are the minimum number known alive from capture and release studies, and aerial surveys where the detection probability is not estimated from a sightability model, marked animals, or distance sampling. Both the mark–recapture and distance-sampling estimators are techniques to estimate the probability of detection of an individual animal (or cluster of animals), which is then used to correct a count of animals. However, often the number of animals in a survey is inadequate to compute an estimate of the detection probability and hence correct the count. Modern methods allow sophisticated modelling to estimate the detection probability, including incorporating covariates to provide additional information about the detection probability. Examples from both distance and mark–recapture sampling are presented to demonstrate the approach.

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Duggins, Jonathan, Matthew Williams, Dong-Yun Kim, and Eric Smith. "Changepoint detection in SPI transition probabilities." Journal of Hydrology 388, no. 3-4 (July 2010): 456–63. http://dx.doi.org/10.1016/j.jhydrol.2010.05.030.

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Yu, Xiang, and Yu Qiao. "Enhanced Comprehensive Learning Particle Swarm Optimization with Dimensional Independent and Adaptive Parameters." Computational Intelligence and Neuroscience 2021 (February 5, 2021): 1–16. http://dx.doi.org/10.1155/2021/6628564.

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Comprehensive learning particle swarm optimization (CLPSO) and enhanced CLPSO (ECLPSO) are two literature metaheuristics for global optimization. ECLPSO significantly improves the exploitation and convergence performance of CLPSO by perturbation-based exploitation and adaptive learning probabilities. However, ECLPSO still cannot locate the global optimum or find a near-optimum solution for a number of problems. In this paper, we study further bettering the exploration performance of ECLPSO. We propose to assign an independent inertia weight and an independent acceleration coefficient corresponding to each dimension of the search space, as well as an independent learning probability for each particle on each dimension. Like ECLPSO, a normative interval bounded by the minimum and maximum personal best positions is determined with respect to each dimension in each generation. The dimensional independent maximum velocities, inertia weights, acceleration coefficients, and learning probabilities are proposed to be adaptively updated based on the dimensional normative intervals in order to facilitate exploration, exploitation, and convergence, particularly exploration. Our proposed metaheuristic, called adaptive CLPSO (ACLPSO), is evaluated on various benchmark functions. Experimental results demonstrate that the dimensional independent and adaptive maximum velocities, inertia weights, acceleration coefficients, and learning probabilities help to significantly mend ECLPSO’s exploration performance, and ACLPSO is able to derive the global optimum or a near-optimum solution on all the benchmark functions for all the runs with parameters appropriately set.

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Fletcher, Robert J., and Richard L. Hutto. "Estimating Detection Probablities of River Birds using Double Surveys." Auk 123, no. 3 (July 1, 2006): 695–707. http://dx.doi.org/10.1093/auk/123.3.695.

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AbstractWe describe a method for surveying birds in river habitats that allows for rapid assessment across broad spatial scales and estimation of detection probabilities. Our river survey approach incorporates a double-survey technique, whereby observers in two canoes simultaneously survey birds along a river reach. Data are in the form of a two-sample mark-recapture history, and covariates suspected of influencing detection probabilities can be included in the modeling process and evaluated using information-theoretic approaches. We provide an example using the method along the Madison and upper Missouri rivers in Montana. Overall, detection probabilities for each observer ranged from 57% to 89%, and combined detection probabilities (the likelihood of at least one observer detecting an individual) were consistently high (88% across all species). Detection probabilities across species were positively correlated with body mass. Detection probabilities for some species were influenced by observer, river conditions, and whether species were in groups or alone; groups were more detectable, and individuals in slow-flowing and wide sections of river were more detectable. Boat-based double surveys are a viable method for estimating detection probabilities of birds in river habitats, and double surveys should be considered in other aquaticEstimaciones de Probabilidades de Detección de Aves de Río Utilizando Muestreos Dobles systems.

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Picinbono, B., and P. Duvaut. "Optimum quantization for detection." IEEE Transactions on Communications 36, no. 11 (1988): 1254–58. http://dx.doi.org/10.1109/26.8934.

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McIntyre, T., T. L. Majelantle, D. J. Slip, and R. G. Harcourt. "Quantifying imperfect camera-trap detection probabilities: implications for density modelling." Wildlife Research 47, no. 2 (2020): 177. http://dx.doi.org/10.1071/wr19040.

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Abstract ContextData obtained from camera traps are increasingly used to inform various population-level models. Although acknowledged, imperfect detection probabilities within camera-trap detection zones are rarely taken into account when modelling animal densities. AimsWe aimed to identify parameters influencing camera-trap detection probabilities, and quantify their relative impacts, as well as explore the downstream implications of imperfect detection probabilities on population-density modelling. MethodsWe modelled the relationships between the detection probabilities of a standard camera-trap model (n=35) on a remotely operated animal-shaped soft toy and a series of parameters likely to influence it. These included the distance of animals from camera traps, animal speed, camera-trap deployment height, ambient temperature (as a proxy for background surface temperatures) and animal surface temperature. We then used this detection-probability model to quantify the likely influence of imperfect detection rates on subsequent population-level models, being, in this case, estimates from random encounter density models on a known density simulation. Key resultsDetection probabilities mostly varied predictably in relation to measured parameters, and decreased with an increasing distance from the camera traps and speeds of movement, as well as heights of camera-trap deployments. Increased differences between ambient temperature and animal surface temperature were associated with increased detection probabilities. Importantly, our results showed substantial inter-camera (of the same model) variability in detection probabilities. Resulting model outputs suggested consistent and systematic underestimation of true population densities when not taking imperfect detection probabilities into account. ConclusionsImperfect, and individually variable, detection probabilities inside the detection zones of camera traps can compromise resulting population-density estimates. ImplicationsWe propose a simple calibration approach for individual camera traps before field deployment and encourage researchers to actively estimate individual camera-trap detection performance for inclusion in subsequent modelling approaches.

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Anily, S., and A. Federgruen. "Simulated annealing methods with general acceptance probabilities." Journal of Applied Probability 24, no. 3 (September 1987): 657–67. http://dx.doi.org/10.2307/3214097.

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Heuristic solution methods for combinatorial optimization problems are often based on local neighborhood searches. These tend to get trapped in a local optimum and the final result is often heavily dependent on the starting solution. Simulated annealing methods attempt to avoid these problems by randomizing the procedure so as to allow for occasional changes that worsen the solution. In this paper we provide probabilistic analyses of different designs of these methods.

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Anily, S., and A. Federgruen. "Simulated annealing methods with general acceptance probabilities." Journal of Applied Probability 24, no. 03 (September 1987): 657–67. http://dx.doi.org/10.1017/s0021900200031387.

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Heuristic solution methods for combinatorial optimization problems are often based on local neighborhood searches. These tend to get trapped in a local optimum and the final result is often heavily dependent on the starting solution. Simulated annealing methods attempt to avoid these problems by randomizing the procedure so as to allow for occasional changes that worsen the solution. In this paper we provide probabilistic analyses of different designs of these methods.

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Kluever, Bryan M., Eric M. Gese, and Steven J. Dempsey. "The influence of road characteristics and species on detection probabilities of carnivore faeces." Wildlife Research 42, no. 1 (2015): 75. http://dx.doi.org/10.1071/wr14244.

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Context Determining reliable estimates of carnivore population size and distributions are paramount for developing informed conservation and management plans. Traditionally, invasive sampling has been employed to monitor carnivores, but non-invasive sampling has the advantage of not needing to capture the animal and is generally less expensive. Faeces sampling is a common non-invasive sampling technique and future use is forecasted to increase due to the low costs and logistical ease of sampling, and more advanced techniques in landscape and conservation genetics. For many species, faeces sampling often occurs on or alongside roads. Despite the commonality of road-based faeces sampling, detectability issues are often not addressed. Aim We sought to test whether faeces detection probabilities varied by species – coyote (Canis latrans) versus kit fox (Vulpes macrotis) – and to test whether road characteristics influenced faeces detection probabilities. Methods We placed coyote and kit fox faeces along roads, quantified road characteristics, and then subsequently conducted ‘blind’ road-based faeces detection surveys in Utah during 2012 and 2013. Technicians that surveyed the faeces deposition transects had no knowledge of the locations of the placed faeces. Key results Faeces detection probabilities for kit foxes and coyotes were 45% and 74%, respectively; larger faeces originated from coyotes and were more readily detected. Misidentification of placed faeces was rare and did not differ by species. The width of survey roads and the composition of a road’s surface influenced detection probabilities. Conclusion We identified factors that can influence faeces detection probabilities. Not accounting for variable detection probabilities of different species or not accounting for or reducing road-based variables influencing faeces detection probabilities could hamper reliable counts of mammalian faeces, and could potentially reduce precision of population estimates derived from road-based faeces deposition surveys. Implications We recommend that wildlife researchers acknowledge and account for imperfect faeces detection probabilities during faecal sampling. Steps can be taken during study design to improve detection probabilities, and during the analysis phase to account for variable detection probabilities.

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Gao, Hongsheng, and Peter J. Smith. "Exact SINR Calculations for Optimum Linear Combining in Wireless Systems." Probability in the Engineering and Informational Sciences 12, no. 2 (April 1998): 261–81. http://dx.doi.org/10.1017/s0269964800005180.

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This paper presents an exact derivation of the statistical distribution of the signal to interference-plus-noise ratio (SINR) for optimum linear combining in wireless systems with multiple cochannel interferes, Rayleigh fading, and additive white Gaussian noise. The distribution of the SINR is shown to be remarkably simple and leads to bounds on the bit error rate and outage probabilities which are tighter, simpler, and more robust than any previous results. The simplicity of the SINR distribution permits extremely fast computation of outage probabilities for any number of interference channels and diversity levels. Hence for wireless systems it enables performance studies to be performed over a much wider range of conditions, such as shadow fading, specific channel allocation methods, etc. Previously such studies were extremely limited due to the intensive computational requirements of simulating these systems.

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Helstrom, C. W. "Detection probabilities for correlated Rayleigh fading signals." IEEE Transactions on Aerospace and Electronic Systems 28, no. 1 (1992): 259–67. http://dx.doi.org/10.1109/7.135451.

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Kulatilake, Pinnaduwa H. S. W., and Shoung Ouyang. "Target Detection Probabilities for Continuous Line Search." Journal of Computing in Civil Engineering 1, no. 1 (January 1987): 1–19. http://dx.doi.org/10.1061/(asce)0887-3801(1987)1:1(1).

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Ghosh, Shalini, and F. Joel Ferguson. "Detection probabilities of interconnect breaks: an analysis." Integration 38, no. 3 (January 2005): 451–65. http://dx.doi.org/10.1016/j.vlsi.2004.07.003.

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Wu, Zhaole, Xin Wang, Wenyi Fang, Longzhao Liu, Shaoting Tang, Hongwei Zheng, and Zhiming Zheng. "Community detection based on first passage probabilities." Physics Letters A 390 (February 2021): 127099. http://dx.doi.org/10.1016/j.physleta.2020.127099.

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Jennelle, Christopher S., Evan G. Cooch, Michael J. Conroy, and Juan Carlos Senar. "STATE-SPECIFIC DETECTION PROBABILITIES AND DISEASE PREVALENCE." Ecological Applications 17, no. 1 (January 2007): 154–67. http://dx.doi.org/10.1890/1051-0761(2007)017[0154:sdpadp]2.0.co;2.

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Royle, J. Andrew. "Site Occupancy Models with Heterogeneous Detection Probabilities." Biometrics 62, no. 1 (September 28, 2005): 97–102. http://dx.doi.org/10.1111/j.1541-0420.2005.00439.x.

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Stager, Paul, and Donald Hameluck. "Estimating Detection Probabilities Fdr Search and Rescue." Proceedings of the Human Factors Society Annual Meeting 30, no. 3 (September 1986): 312–16. http://dx.doi.org/10.1177/154193128603000326.

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In planning visual search, operations, the allocation of Search and Rescue (SAR) resources may be dependent on the statistical probability that a missing aircraft or crash site can be detected if it is within given geographical areas. The present study was undertaken in order to relate probability of detection (POD) to the relevant environmental or contextual variables. Multidimensional scaling (MDS) and cluster analysis were used to determine the basic stimulus dimensions and characteristics that define different categories of search area. A simulated visual search task generated POD data for representative aerial views that contained synthetic crash sites. POD was a function of target contrast and terrain exposure. Limited field trials have indicated that data from the static visual displays were capable of providing reasonable estimates of detection in dynamic visual search.

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Markowsky, George. "Bounding fault detection probabilities in combinational circuits." Journal of Electronic Testing 2, no. 4 (November 1991): 315–23. http://dx.doi.org/10.1007/bf00135227.

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Hilton, Harry H. "OPTIMUM VISCOELASTIC DESIGNER MATERIALS FOR MINIMIZING FAILURE PROBABILITIES DURING COMPOSITE CURING." Journal of Thermal Stresses 26, no. 6 (June 2003): 547–57. http://dx.doi.org/10.1080/713855956.

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Oliver, C. J., D. Blacknell, and R. G. White. "Optimum edge detection in SAR." IEE Proceedings - Radar, Sonar and Navigation 143, no. 1 (1996): 31. http://dx.doi.org/10.1049/ip-rsn:19960219.

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Yarotskii, V. A. "Optimum detection of magnetic dipoles." Measurement Techniques 35, no. 10 (October 1992): 1190–94. http://dx.doi.org/10.1007/bf00977481.

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Verma, R. C., C. Schmid, and K. Mikolajczyk. "Face detection and tracking in a video by propagating detection probabilities." IEEE Transactions on Pattern Analysis and Machine Intelligence 25, no. 10 (October 2003): 1215–28. http://dx.doi.org/10.1109/tpami.2003.1233896.

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Theeuwes, Jules. "Unemployment and Labour Market Transition Probabilities." Recherches économiques de Louvain 52, no. 3-4 (December 1986): 209–25. http://dx.doi.org/10.1017/s0770451800082890.

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I. ANALYSING UNEMPLOYMENT: A RESEARCH PROGRAMThere are many kinds of unemployment. An average economist should be able to enumerate at least a dozen without forward notice. This embarrassing abundance of definitions gives a clear indication of the trouble we have pinning unemployment down.Unemployment is generally considered to be an undesirable quantity in a market economy. Although not all of it. Part of it is unavoidable and even considered necessary for an efficient matching of jobs and workers. In this sense one could define —although this would not be easy— an optimal quantity of unemployment taking into account the institutions and stochastics of the labour market. Unemployment under and above this optimum would be inefficient. The next question is: can one avoid too much or too little unemployment through policy measures at reasonable costs? There is no definite answer to that. A lot of heated discussion in macroeconomics focusses on this subject.

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TRENTADUE, F., and G. C. MARANO. "OPTIMUM RELIABILITY BASED DESIGN CRITERIA FOR ELASTIC STRUCTURES SUBJECT TO RANDOM DYNAMIC LOADS." International Journal of Structural Stability and Dynamics 06, no. 04 (December 2006): 437–56. http://dx.doi.org/10.1142/s021945540600212x.

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In this work a new method for the optimal design of generic elastic structures, subject to random dynamic loads, is proposed. Elastic structures are described as deterministic multi-degree of freedom systems in which the structural failure probability, referred to as a first crossing passage problem, is minimized. The proposed method is here applied to optimize the shape of a vertical column with an extra-mass located at the free top end, subject to a base acceleration modeled as a Gaussian, stationary, filtered stochastic process. The elastic threshold crossing probabilities are determined in a finite number of column sections and the objective function is assumed to be a measure of these probabilities. Finally, this measure is minimized under a constant weight constraint (or even under more general conditions).

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LONGORIA, MEREDITH P., and FLOYD W. WECKERLY. "Estimating Detection Probabilities from Sign of Collared Peccary." Journal of Wildlife Management 71, no. 2 (April 2007): 652–55. http://dx.doi.org/10.2193/2005-613.

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Pagano, Anthony M., and Todd W. Arnold. "Detection Probabilities for Ground-Based Breeding Waterfowl Surveys." Journal of Wildlife Management 73, no. 3 (April 2009): 392–98. http://dx.doi.org/10.2193/2007-411.

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Nogueira, Ana Rita, Carlos Abreu Ferreira, and João Gama. "Improving acute kidney injury detection with conditional probabilities." Intelligent Data Analysis 22, no. 6 (December 12, 2018): 1355–74. http://dx.doi.org/10.3233/ida-173626.

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