Sampling stored-product insect pests : a comparison of four statistical sampling models for probability of pest detection

Background: Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult owing to species biology and behavioural characteristics. The design of robust sampling programmes should be based on an underlying statistical distribution that is sufficiently flexible to capture variations in the spatial distribution of the target species. Results: Comparisons are made of the accuracy of four probability-of-detection sampling models - the negative binomial model,1 the Poisson model,1 the double logarithmic model2 and the compound model3 - for detection of insects over a broad range of insect densities. Although the double log and negative binomial models performed well under specific conditions, it is shown that, of the four models examined, the compound model performed the best over a broad range of insect spatial distributions and densities. In particular, this model predicted well the number of samples required when insect density was high and clumped within experimental storages. Conclusions: This paper reinforces the need for effective sampling programs designed to detect insects over a broad range of spatial distributions. The compound model is robust over a broad range of insect densities and leads to substantial improvement in detection probabilities within highly variable systems such as grain storage.

Involvement of target contrast in visual masking location tasks deficients in myopia

Purpose: There have been few studies of visual temporal processing of myopic eyes. This study investigated the visual performance of emmetropic and myopic eyes using a backward visual masking location task. Methods: Data were collected for 39 subjects (15 emmetropes, 12 stable myopes, 12 progressing myopes). In backward visual masking, a target’s visibility is reduced by a mask presented in quick succession ‘after’ the target. The target and mask stimuli were presented at different interstimulus intervals (from 12 to 300 ms). The task involved locating the position of a target letter with both a higher (seven per cent) and a lower (five per cent) contrast. Results: Emmetropic subjects had significantly better performance for the lower contrast location task than the myopes (F2,36 = 22.88; p < 0.001) but there was no difference between the progressing and stable myopic groups (p = 0.911). There were no differences between the groups for the higher contrast location task (F2,36 = 0.72, p = 0.495). No relationship between task performance and either the magnitude of myopia or axial length was found for either task. Conclusions: A location task deficit was observed in myopes only for lower contrast stimuli. Both emmetropic and myopic groups had better performance for the higher contrast task compared to the lower contrast task, with myopes showing considerable improvement. This suggests that five per cent contrast may be the contrast threshold required to bias the task towards the magnocellular system (where myopes have a temporal processing deficit). Alternatively, the task may be sensitive to the contrast sensitivity of the observer.

Estimating the probability of an invalid match for matching using the rank transform

A fundamental problem faced by stereo matching algorithms is the matching or correspondence problem. A wide range of algorithms have been proposed for the correspondence problem. For all matching algorithms, it would be useful to be able to compute a measure of the probability of correctness, or reliability of a match. This paper focuses in particular on one class for matching algorithms, which are based on the rank transform. The interest in these algorithms for stereo matching stems from their invariance to radiometric distortion, and their amenability to fast hardware implementation. This work differs from previous work in that it derives, from first principles, an expression for the probability of a correct match. This method was based on an enumeration of all possible symbols for matching. The theoretical results for disparity error prediction, obtained using this method, were found to agree well with experimental results. However, disadvantages of the technique developed in this chapter are that it is not easily applicable to real images, and also that it is too computationally expensive for practical window sizes. Nevertheless, the exercise provides an interesting and novel analysis of match reliability.

Stepping accuracy and visuomotor control among older adults : effect of target contrast and refractive blur

Purpose: Older adults have increased visual impairment, including refractive blur from presbyopic multifocal spectacle corrections, and are less able to extract visual information from the environment to plan and execute appropriate stepping actions; these factors may collectively contribute to their higher risk of falls. The aim of this study was to examine the effect of refractive blur and target visibility on the stepping accuracy and visuomotor stepping strategies of older adults during a precision stepping task. Methods: Ten healthy, visually normal older adults (mean age 69.4 ± 5.2 years) walked up and down a 20 m indoor corridor stepping onto selected high and low-contrast targets while viewing under three visual conditions: best-corrected vision, +2.00 DS and +3.00 DS blur; the order of blur conditions was randomised between participants. Stepping accuracy and gaze behaviours were recorded using an eyetracker and a secondary hand-held camera. Results: Older adults made significantly more stepping errors with increasing levels of blur, particularly exhibiting under-stepping (stepping more posteriorly) onto the targets (p<0.05), while visuomotor stepping strategies did not significantly alter. Stepping errors were also significantly greater for the low compared to the high contrast targets and differences in visuomotor stepping strategies were found, including increased duration of gaze and increased interval between gaze onset and initiation of the leg swing when stepping onto the low contrast targets. Conclusions: These findings highlight that stepping accuracy is reduced for low visibility targets, and for high levels of refractive blur at levels typically present in multifocal spectacle corrections, despite significant changes in some of the visuomotor stepping strategies. These findings highlight the importance of maximising the contrast of objects in the environment, and may help explain why older adults wearing multifocal spectacle corrections exhibit an increased risk of falling.

The impact of inter-fraction set-up errors on the probability of pulmonary and cardiac complication in left-sided breast cancer patients

Purpose This study evaluated the impact of patient set-up errors on the probability of pulmonary and cardiac complications in the irradiation of left-sided breast cancer. Methods and Materials Using the CMS XiO Version 4.6 (CMS Inc., St Louis, MO) radiotherapy planning system's NTCP algorithm and the Lyman -Kutcher-Burman (LKB) model, we calculated the DVH indices for the ipsilateral lung and heart and the resultant normal tissue complication probabilities (NTCP) for radiation-induced pneumonitis and excess cardiac mortality in 12 left-sided breast cancer patients. Results Isocenter shifts in the posterior direction had the greatest effect on the lung V20, heart V25, mean and maximum doses to the lung and the heart. Dose volume histograms (DVH) results show that the ipsilateral lung V20 tolerance was exceeded in 58% of the patients after 1cm posterior shifts. Similarly, the heart V25 tolerance was exceeded after 1cm antero-posterior and left-right isocentric shifts in 70% of the patients. The baseline NTCPs for radiation-induced pneumonitis ranged from 0.73% - 3.4% with a mean value of 1.7%. The maximum reported NTCP for radiation-induced pneumonitis was 5.8% (mean 2.6%) after 1cm posterior isocentric shift. The NTCP for excess cardiac mortality were 0 % in 100% of the patients (n=12) before and after setup error simulations. Conclusions Set-up errors in left sided breast cancer patients have a statistically significant impact on the Lung NTCPs and DVH indices. However, with a central lung distance of 3cm or less (CLD <3cm), and a maximum heart distance of 1.5cm or less (MHD<1.5cm), the treatment plans could tolerate set-up errors of up to 1cm without any change in the NTCP to the heart.

Improving the estimation of probability of bidder participation in procurement auctions

Anticipating the number and identity of bidders has significant influence in many theoretical results of the auction itself and bidders’ bidding behaviour. This is because when a bidder knows in advance which specific bidders are likely competitors, this knowledge gives a company a head start when setting the bid price. However, despite these competitive implications, most previous studies have focused almost entirely on forecasting the number of bidders and only a few authors have dealt with the identity dimension qualitatively. Using a case study with immediate real-life applications, this paper develops a method for estimating every potential bidder’s probability of participating in a future auction as a function of the tender economic size removing the bias caused by the contract size opportunities distribution. This way, a bidder or auctioner will be able to estimate the likelihood of a specific group of key, previously identified bidders in a future tender.

On the probability of dizygotic twins being concordant for two alleles at multiple polymorphic loci

Accurate determination of same-sex twin zygosity is important for medical, scientific and personal reasons. Determination may be based upon questionnaire data, blood group, enzyme isoforms and fetal membrane examination, but assignment of zygosity must ultimately be confirmed by genotypic data. Here methods are reviewed for calculating average probabilities of correctly concluding a twin pair is monozygotic, given they share the same genotypes across all loci for commonly utilized multiplex short tandem repeat (STR) kits.

Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation

This article presents and evaluates Quantum Inspired models of Target Activation using Cued-Target Recall Memory Modelling over multiple sources of Free Association data. Two components were evaluated: Whether Quantum Inspired models of Target Activation would provide a better framework than their classical psychological counterparts and how robust these models are across the different sources of Free Association data. In previous work, a formal model of cued-target recall did not exist and as such Target Activation was unable to be assessed directly. Further to that, the data source used was suspected of suffering from temporal and geographical bias. As a consequence, Target Activation was measured against cued-target recall data as an approximation of performance. Since then, a formal model of cued-target recall (PIER3) has been developed [10] with alternative sources of data also becoming available. This allowed us to directly model target activation in cued-target recall with human cued-target recall pairs and use multiply sources of Free Association Data. Featural Characteristics known to be important to Target Activation were measured for each of the data sources to identify any major differences that may explain variations in performance for each of the models. Each of the activation models were used in the PIER3 memory model for each of the data sources and was benchmarked against cued-target recall pairs provided by the University of South Florida (USF). Two methods where used to evaluate performance. The first involved measuring the divergence between the sets of results using the Kullback Leibler (KL) divergence with the second utilizing a previous statistical analysis of the errors [9]. Of the three sources of data, two were sourced from human subjects being the USF Free Association Norms and the University of Leuven (UL) Free Association Networks. The third was sourced from a new method put forward by Galea and Bruza, 2015 in which pseudo Free Association Networks (Corpus Based Association Networks - CANs) are built using co-occurrence statistics on large text corpus. It was found that the Quantum Inspired Models of Target Activation not only outperformed the classical psychological model but was more robust across a variety of data sources.

Drivers of technology substitution : successive generations of high tech products

Principal Topic High technology consumer products such as notebooks, digital cameras and DVD players are not introduced into a vacuum. Consumer experience with related earlier generation technologies, such as PCs, film cameras and VCRs, and the installed base of these products strongly impacts the market diffusion of the new generation products. Yet technology substitution has received only sparse attention in the diffusion of innovation literature. Research for consumer durables has been dominated by studies of (first purchase) adoption (c.f. Bass 1969) which do not explicitly consider the presence of an existing product/technology. More recently, considerable attention has also been given to replacement purchases (c.f. Kamakura and Balasubramanian 1987). Only a handful of papers explicitly deal with the diffusion of technology/product substitutes (e.g. Norton and Bass, 1987: Bass and Bass, 2004). They propose diffusion-type aggregate-level sales models that are used to forecast the overall sales for successive generations. Lacking household data, these aggregate models are unable to give insights into the decisions by individual households - whether to adopt generation II, and if so, when and why. This paper makes two contributions. It is the first large-scale empirical study that collects household data for successive generations of technologies in an effort to understand the drivers of adoption. Second, in comparision to traditional analysis that evaluates technology substitution as an ''adoption of innovation'' type process, we propose that from a consumer's perspective, technology substitution combines elements of both adoption (adopting the new generation technology) and replacement (replacing the generation I product with generation II). Based on this proposition, we develop and test a number of hypotheses. Methodology/Key Propositions In some cases, successive generations are clear ''substitutes'' for the earlier generation, in that they have almost identical functionality. For example, successive generations of PCs Pentium I to II to III or flat screen TV substituting for colour TV. More commonly, however, the new technology (generation II) is a ''partial substitute'' for existing technology (generation I). For example, digital cameras substitute for film-based cameras in the sense that they perform the same core function of taking photographs. They have some additional attributes of easier copying and sharing of images. However, the attribute of image quality is inferior. In cases of partial substitution, some consumers will purchase generation II products as substitutes for their generation I product, while other consumers will purchase generation II products as additional products to be used as well as their generation I product. We propose that substitute generation II purchases combine elements of both adoption and replacement, but additional generation II purchases are solely adoption-driven process. Extensive research on innovation adoption has consistently shown consumer innovativeness is the most important consumer characteristic that drives adoption timing (Goldsmith et al. 1995; Gielens and Steenkamp 2007). Hence, we expect consumer innovativeness also to influence both additional and substitute generation II purchases. Hypothesis 1a) More innovative households will make additional generation II purchases earlier. 1 b) More innovative households will make substitute generation II purchases earlier. 1 c) Consumer innovativeness will have a stronger impact on additional generation II purchases than on substitute generation II purchases. As outlined above, substitute generation II purchases act, in part like a replacement purchase for the generation I product. Prior research (Bayus 1991; Grewal et al 2004) identified product age as the most dominant factor influencing replacements. Hence, we hypothesise that: Hypothesis 2: Households with older generation I products will make substitute generation II purchases earlier. Our survey of 8,077 households investigates their adoption of two new generation products: notebooks as a technology change to PCs, and DVD players as a technology shift from VCRs. We employ Cox hazard modelling to study factors influencing the timing of a household's adoption of generation II products. We determine whether this is an additional or substitute purchase by asking whether the generation I product is still used. A separate hazard model is conducted for additional and substitute purchases. Consumer Innovativeness is measured as domain innovativeness adapted from the scales of Goldsmith and Hofacker (1991) and Flynn et al. (1996). The age of the generation I product is calculated based on the most recent household purchase of that product. Control variables include age, size and income of household, and age and education of primary decision-maker. Results and Implications Our preliminary results confirm both our hypotheses. Consumer innovativeness has a strong influence on both additional purchases (exp = 1.11) and substitute purchases (exp = 1.09). Exp is interpreted as the increased probability of purchase for an increase of 1.0 on a 7-point innovativeness scale. Also consistent with our hypotheses, the age of the generation I product has a dramatic influence for substitute purchases of VCR/DVD (exp = 2.92) and a strong influence for PCs/notebooks (exp = 1.30). Exp is interpreted as the increased probability of purchase for an increase of 10 years in the age of the generation I product. Yet, also as hypothesised, there was no influence on additional purchases. The results lead to two key implications. First, there is a clear distinction between additional and substitute purchases of generation II products, each with different drivers. Treating these as a single process will mask the true drivers of adoption. For substitute purchases, product age is a key driver. Hence, implications for marketers of high technology products can utilise data on generation I product age (e.g. from warranty or loyalty programs) to target customers who are more likely to make a purchase.

Kindergarten students' understanding of probability concepts

This study explored kindergarten students’ intuitive strategies and understandings in probabilities. The paper aims to provide an in depth insight into the levels of probability understanding across four constructs, as proposed by Jones (1997), for kindergarten students. Qualitative evidence from two students revealed that even before instruction pupils have a good capacity of predicting most and least likely events, of distinguishing fair probability situations from unfair ones, of comparing the probability of an event in two sample spaces, and of recognizing conditional probability events. These results contribute to the growing evidence on kindergarten students’ intuitive probabilistic reasoning. The potential of this study for improving the learning of probability, as well as suggestions for further research, are discussed.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.