Measure Of Likelihood Research Articles

Multi-color Joint Probability Statistics Model-based Object Tracking System

<p>For continuous target following under complex scene, an objective following calculation in light of multi-shading joint likelihood investigation model was introduced. The calculation embraced shading histogram to speak to the actual factual trademark with Camshaft standard and completed exploratory research in such angles as multichannel joint shading highlights measurements, projection delineate weighted preparing, the following window size and position ascertaining, calculation handling component of course. It utilised red, green, blue, tint, luminance channel shading as the objective watched attributes, and planned the computation technique given the likelihood measurement to recognise any shading focus from the compound scene. It likewise settled the counting method for following window size and position which adjusted the multi-shading model. Utilizing weighting projection outline strategy, the foundation obstruction around the objective potential territory was dispensed with. Finally, more reasonable joining judgment and the calculation cycle tenets were advanced. After the test accreditation, the ongoing execution and recognition proportion introduce a decent outcome.</p>

Wrapped: An R package for circular data.

The Wrapped package computes the probability density function, cumulative distribution function, quantile function and also generates random samples for many univariate wrapped distributions. It also computes maximum likelihood estimates, standard errors, confidence intervals and measures of goodness of fit for nearly fifty univariate wrapped distributions. Numerical illustrations of the package are given.

GenoGeographer – A tool for genogeographic inference

Ancestry-informative markers (AIMs) are genetic markers that give information about the genogeographic ancestry of individuals. They are used for predicting the genogeographic origin of the investigated individual in crime and identification cases. When exploring the genogeographic origin of an AIMs profile, the likelihoods of the AIMs profile in various populations may be calculated. However, there might not be an apt population in the database of reference populations. The fact that the likelihood ratios (LR) of one population compared to other populations are large does not imply that any of the populations are relevant. This is because that even though the populations might be exclusive, they are not exhaustive in the sense that they cover all possible human populations.To handle this phenomena, we derive a likelihood ratio test (LRT), by which we can judge whether there is at least one population in our reference database that is “sufficiently close” to a profile's “true” genogeographic population. The LRT is a measure of absolute concordance between a profile and a population, rather than a relative measure of the profile's likelihood in two populations (the LR).The LRT is similar to a Fisher's exact test, which means that the varying sample sizes of the reference populations in the database is explicitly included in the calculations, and makes fewer assumptions than for LR calculations. The methodology has been implemented in an free open source interactive platform, GenoGeographer, that enables the forensic geneticist to make explorative analyses, produce various graphical outputs together with evidential weight computations.

Multi-attribute, multi-alternative models of choice: Choice, reaction time, and process tracing

The first aim of this research is to compare computational models of multi-alternative, multi-attribute choice when attribute values are explicit. The choice predictions of utility (standard random utility & weighted valuation), heuristic (elimination-by-aspects, lexicographic, & maximum attribute value), and dynamic (multi-alternative decision field theory, MDFT, & a version of the multi-attribute linear ballistic accumulator, MLBA) models are contrasted on both preferential and risky choice data. Using both maximum likelihood and cross-validation fit measures on choice data, the utility and dynamic models are preferred over the heuristic models for risky choice, with a slight overall advantage for the MLBA for preferential choice. The response time predictions of these models (except the MDFT) are then tested. Although the MLBA accurately predicts response time distributions, it only weakly accounts for stimulus-level differences. The other models completely fail to account for stimulus-level differences. Process tracing measures, i.e., eye and mouse tracking, were also collected. None of the qualitative predictions of the models are completely supported by that data. These results suggest that the models may not appropriately represent the interaction of attention and preference formation. To overcome this potential shortcoming, the second aim of this research is to test preference-formation assumptions, independently of attention, by developing the models of attentional sampling (MAS) model family which incorporates the empirical gaze patterns into a sequential sampling framework. An MAS variant that includes attribute values, but only updates the currently viewed alternative and does not contrast values across alternatives, performs well in both experiments. Overall, the results support the dynamic models, but point to the need to incorporate a framework that more accurately reflects the relationship between attention and the preference-formation process.

Association between urinary biomarkers of total sugars intake and measures of obesity in a cross-sectional study.

Obesity is an important modifiable risk factor for chronic diseases. While there is increasing focus on the role of dietary sugars, there remains a paucity of data establishing the association between sugar intake and obesity in the general public. The objective of this study was to investigate associations of estimated sugar intake with odds for obesity in a representative sample of English adults. We used data from 434 participants of the 2005 Health Survey of England. Biomarkers for total sugar intake were measured in 24 h urine samples and used to estimate intake. Linear and logistic regression analyses were used to investigate associations between biomarker-based estimated intake and measures of obesity (body mass intake (BMI), waist circumference and waist-to-hip ratio) and obesity risk, respectively. Estimated sugar intake was significantly associated with BMI, waist circumference and waist-to-hip ratio; these associations remained significant after adjustment for estimated protein intake as a marker of non-sugar energy intake. Estimated sugar intake was also associated with increased odds for obesity based on BMI (OR 1.02; 95%CI 1.00–1.04 per 10g), waist-circumference (1.03; 1.01–1.05) and waist-to-hip ratio (1.04; 1.02–1.06); all OR estimates remained significant after adjusting for estimated protein intake. Our results strongly support positive associations between total sugar intake, measures of obesity and likelihood of being obese. It is the first time that such an association has been shown in a nationally-representative sample of the general population using a validated biomarker. This biomarker could be used to monitor the efficacy of public health interventions to reduce sugar intake.

Security analyst target prices as reference point and takeover completion

Based on prospect theory, we posit that security analysts’ target prices function as a reference point for takeover bids and affect deal completion. Using a sample of US takeovers from 1999 to 2014, we find a negative relation between target prices for a takeover target and the chances for successful deal completion. High degrees of target price dispersion indicate high reference points for some investors. Accordingly, we find low completion rates when target price dispersion is high. Our results hold for both ultimate deal completion and implied completion probability measured shortly after bids were announced as an alternative measure for completion likelihood.

Validity of the Braden Scale in grading pressure ulcers in trauma and burn patients

BackgroundPressure ulcers are a costly hospital-acquired condition in terms of clinical outcome and expense. The Braden Scale was developed in 1987 as a risk scoring method for pressure ulcers and uses six different risk factors: sensory perception, moisture, activity, mobility, nutrition, and friction and shear. A score of ≤18 is considered high risk. To date, research on the utility of the Braden Scale has focused on general medicine and nontrauma/burn surgery patients. We hypothesize that the Braden Scale does not accurately discriminate who will get a pressure ulcer among trauma and burn patients. MethodsWe collected data from medical records regarding documented Braden scores and presence of pressure ulcers regardless of staging. Patients with ulcers present on admission were excluded from analysis. For each patient, the lowest Braden score documented before the occurrence of the pressure ulcer was determined. A logistic regression was used to estimate odds ratios and associated 95% confidence intervals for the association between pressure ulcer likelihood and lowest Braden Scale measurement. To determine the discriminatory ability of the Braden Scale on pressure ulcer risk, four measures of performance (i.e., sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio) were calculated for four nonmutually exclusive groups: a Braden Scale measurement ≤18, ≤14, ≤12, and ≤9. ResultsFrom 2011 through 2014, a total of 2660 patients were admitted to the trauma/burn intensive care unit. Of these patients, 63 (2.3%) subsequently developed a pressure ulcer. A Braden Scale of ≤18 as the threshold for being at-risk of pressure ulcer had a sensitivity of 100% and specificity of 6%, whereas a Braden Scale of ≤9 had a sensitivity of 28.6% and a specificity of 90%. For all Braden Scale measurements, the positive likelihood ratio never reached the value of 10 that suggests high likelihood of an ulcer. ConclusionsThe Braden scale has mediocre discriminatory ability among the trauma/burn population. In addition, the low positive likelihood ratio suggests that the Braden scale may not be a useful clinical tool as it may result in unnecessary expenditure of time and personnel resources in preventing pressure ulcer formation.

Assessment of Post-Manoeuvre Observation Correlation Using Short-Arc Tracklets

Satellites maintain or establish their operational orbit by performing impulsive or continuous thrust maneuvers. When cataloging resident space objects, these rapid or slow orbital changes complicate a successful correlation. The new orbit remains uncertain and cannot be used for operations such as conjunction detection. This work outlines and assesses a method for the correlation of optical tracklets to already cataloged objects and the following orbit recovery. For that purpose, historic orbital data is analyzed to predict possible states after the maneuver using kernel density estimation. The resulting probability density function also provides a measure for the association likelihood of a new tracklet. The methods are tested with optical observations from the Zimmerwald observatory. Maneuver information and ephemerides are reported by the satellite operator and used as a reference.

An Extended QUALIFLEX Method Under Probability Hesitant Fuzzy Environment for Selecting Green Suppliers

For many companies, the selection of green suppliers has become a key strategic consideration due to regulatory requirements and market trends. In this paper, an extended qualitative flexible multiple (QUALIFLEX) method is used to solve problems regarding the selection of green suppliers using probability hesitant fuzzy information. First, a new Hausdorff distance between two probability hesitant fuzzy elements (PHFEs) is introduced, and the properties of the proposed distance are discussed. Second, a likelihood measurement for PHFEs is proposed based on the new Hausdorff distance; moreover, an extended QUALIFLEX is developed based on the likelihood measurement. Finally, the practicality and effectiveness of the proposed method is tested using a green supplier selection example; furthermore, a comparative analysis using probability hesitant fuzzy information is also performed.

On the Likelihood of God's Existence: An Econometric Perspective

This paper derives the measure of likelihood associated with the hypothesis of God's existence. is defined as an omnipotent, omniscient being. These words are given econometric definitions. The probability of an event is decomposed into its rationality (a measure of subjective preference) and nomicity (a measure of subjective influence). The likelihood of an event is thus a convolution of rationality and nomicity, as a function of the data. The existence of is thus represented as the state of perfect rationality (omniscience) and perfect nomicity (omnipotence). It is shown that this is the maximum likelihood model for any data set. Hence, the most statistically sound explanation of behavior is God wanted it that way. However, the ultimate purpose of econometrics is not explanation or prediction, it is to increase the utility of the agent using the analysis. As such, the theory that causes all behavior may not be economically useful, and is put aside for other theories/models with less likelihood but greater nomic value. The implications for the neoclassical approach to methodology are also considered.

Security Analyst Target Prices as Reference Point and Takeover Completion

Based on prospect theory, we posit that security analysts’ target prices function as a reference point for takeover bids and affect deal completion. Using a sample of US takeovers from 1999 to 2014, we find a negative relation between target prices for a takeover target and the chances for successful deal completion. High degrees of target price dispersion indicate high reference points for some investors. Accordingly, we find low completion rates when target price dispersion is high. Our results hold for both ultimate deal completion and implied completion probability measured shortly after bids were announced as an alternative measure for completion likelihood.

A wrist sensor and algorithm to determine instantaneous walking cadence and speed in daily life walking.

In daily life, a person's gait-an important marker for his/her health status-is usually assessed using inertial sensors fixed to lower limbs or trunk. Such sensor locations are not well suited for continuous and long duration measurements. A better location would be the wrist but with the drawback of the presence of perturbative movements independent of walking. The aim of this study was to devise and validate an algorithm able to accurately estimate walking cadence and speed for daily life walking in various environments based on acceleration measured at the wrist. To this end, a cadence likelihood measure was designed, automatically filtering out perturbative movements and amplifying the periodic wrist movement characteristic of walking. Speed was estimated using a piecewise linear model. The algorithm was validated for outdoor walking in various and challenging environments (e.g., trail, uphill, downhill). Cadence and speed were successfully estimated for all conditions. Overall median (interquartile range) relative errors were -0.13% (-1.72 2.04%) for instantaneous cadence and -0.67% (-6.52 6.23%) for instantaneous speed. The performance was comparable to existing algorithms for trunk- or lower limb-fixed sensors. The algorithm's low complexity would also allow a real-time implementation in a watch.

What Causes Unethical Behavior? A Meta‐Analysis to Set an Agenda for Public Administration Research

AbstractThis article uses meta‐analysis to synthesize 137 experiments in 73 articles on the causes of unethical behavior. Results show that exposure to in‐group members who misbehave or to others who benefit from unethical actions, greed, egocentrism, self‐justification, exposure to incremental dishonesty, loss aversion, challenging performance goals, or time pressure increase unethical behavior. In contrast, monitoring of employees, moral reminders, and individuals’ willingness to maintain a positive self‐view decrease unethical conduct. Findings on the effect of self‐control depletion on unethical behavior are mixed. Results also present subgroup analyses and several measures of study heterogeneity and likelihood of publication bias. The implications are of interest to both scholars and practitioners. The article concludes by discussing which of the factors analyzed should gain prominence in public administration research and uncovering several unexplored causes of unethical behavior.

Scene Image Retrieval Based on Manifold Structures of Canonical Images

Image retrieval methods have been dramatically developed in the last decade. In this paper, we propose a novel method for image retrieval based on manifold structures of canonical images. Firstly, we present the image normalization process to find a set of canonical images that anchors the probabilistic distributions around the real data manifolds to learn the representations that better encode the manifold structures in general high-dimensional image space. In addition, we employ the canonical images as the centers of the conditional multivariate Gaussian distributions. This approach allows to learn more detailed structures of the partial manifolds resulting in improved representation of the high level properties of scene images. Furthermore, we use the probabilistic framework of the extended model to retrieve images based on the similarity measure of reciprocal likelihood of pairs of images and the sum of likelihood of one of two images based on the other’s best distributions. We estimate our method using SUN database. In the experiments on scene image retrieval, the proposed method is efficient, and exhibits superior capabilities compared to other methods, such as GIST.

Deformable Patch-based NCC Measure for Visual Tracking

This paper tries to solve the visual tracking problem in a simple and intuitive way. In particular, we extend the traditional NCC measure with deformable part-based models (DPM) to get a new image similarity measurement and feed it into the particle filtering framework for visual object tracking. The proposed target model consists of a root template and a set of patch templates. The root is the whole target image, and patches are sub-regions of the target image. NCC responses are calculated for the root template with test images, and every patch template with their corresponding sub-regions of test images. The likelihood between the target and a test image is calculated by integrating all template responses. Instead of directly accumulating all responses, we employ the idea of DPM that combines global and local responses using an elastic model to get a robust image likelihood measure. We also explore an exhaustive patch representation mechanism by introducing the dense NCC feature map. The proposed feature map enables the usage of all patches in the target region for target description and similarity measure. Finally, we provide both qualitative and quantitative experiments against state-of-the-arts on the TB50 dataset. Experimental results show that the proposed similarity measure is effective for visual tracking under challenging scenarios.

Enhancing Safety Risk Management with Quantitative Measures

At the airfield in hub airports, many activities occur that involve a range of participants, including various-size aircraft, ground vehicles, and workers. The safety management system is FAA's approach for systematically managing aviation safety. A major component of the safety management system is safety risk management (SRM), which entails analysis, assessment, and control of safety risks, including risks on the airfield. Current SRM has few specific safety models to estimate the likelihood or frequency of risks. This paper presents an example for development and incorporation of safety models into SRM. Specifically, it discusses safety models for runway incursion that use the following variables: total and general aviation operations, length of runway by type, number of taxiway intersections, snowfall, precipitation, number of hot spots, and construction activity. Categorization and processing of data were significant because each variable used could take on multiple forms, and some types of data involved review of airfield diagrams. The data used were from 137 U.S. hub airports for 2009 through 2014. For modeling, the negative multinomial distribution was used because it proved suitable for representing overdispersed data such as runway incursion frequency. Performance of the models was assessed through the goodness-of-fit measures of log likelihood, overdispersion, and cumulative residual plots. Models were developed for five severity categories of runway incursions and three types of surface events. The safety modeling approach presented here can serve as a foundation for development of other safety models that can be integrated into SRM to enable quantitative analysis of safety risks.

Sensitivity and uncertainty-based evaluation and simulation of MIKE SHE model in Guishui River Basin, Beijing, China

In the process of building a hydrological model, some basin feature parameters are expressed inaccurately. It is an important way to construct models and estimate the uncertainty parameters for evaluating the uncertainty of the overall output. In this paper, an uncertainty-based study was calibrated and evaluated the comprehensive distributed model MIKE SHE to hydrological data in the Guishui River Basin, Beijing of China. The generalised likelihood uncertainty estimation (GLUE) method was used to quantify uncertainties originating from the use of discharge observations and the presence of equifinal solutions. Monte Carlo sampling is randomly generated to 10,000 parameter sets during GLUE calibration. MIKE SHE parameter sets are identified and 5% and 95% uncertainty bounds for monthly streamflow are calculated. The behavioural values of nine individual parameters for MIKE SHE were explored against the likelihood measure values. The results show that more than 50% observations in calibration period fell within the corresponding uncertainty bounds, suggesting a similar level of model performance. The simulation results are corresponded better with the measured flow, but still need to be improved for higher accuracy. There are some relative sensitive and insensitive parameters in the result of uncertainty analysis.

Parameter Uncertainty Estimation by Using the Concept of Ideal Data in GLUE Approach

The hydrological uncertainty about NASH model parameters is investigated and addressed in the paper through “ideal data” concept by using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology in an application to the small Yanduhe research catchment in Yangtze River, China. And a suitable likelihood measure is assured here to reduce the uncertainty coming from the parameters relationship. “Ideal data” is assumed to be no error for the input-output data and model structure. The relationship between parameters k and n of NASH model is clearly quantitatively demonstrated based on the real data and it shows the existence of uncertainty factors different from the parameter one. Ideal data research results show that the accuracy of data and model structure are the two important preconditions for parameter estimation. And with suitable likelihood measure, the parameter uncertainty could be decreased or even disappeared. Moreover it is shown how distributions of predicted discharge errors are non-Gaussian and vary in shape with time and discharge under the single existence of parameter uncertainty or under the existence of all uncertainties.

Enclosure Transform for Interest Point Detection From Speckle Imagery

We present a fast enclosure transform (ET) to localize complex objects of interest from speckle imagery. This approach explores the spatial confinement on regional features from a sparse image feature representation. Unrelated, broken ridge features surrounding an object are organized collaboratively, giving rise to the enclosureness of the object. Three enclosure likelihood measures are constructed, consisting of the enclosure force, potential energy, and encloser count. In the transform domain, the local maxima manifest the locations of objects of interest, for which only the intrinsic dimension is known a priori. The discrete ET algorithm is computationally efficient, being on the order of O(MN) using N measuring distances across an image of M ridge pixels. It involves easy and few parameter settings. We demonstrate and assess the performance of ET on the automatic detection of the prostate locations from supra-pubic ultrasound images. ET yields superior results in terms of positive detection rate, accuracy and coverage.

A multi-attribute methodology for the prioritisation of oil contaminated sites in the Niger Delta.

The Ogoniland region of the Niger Delta contains a vast number of sites contaminated with petroleum hydrocarbons that originated from Nigeria's active oil sector. The United Nations Environment Programme (UNEP) reported on this widespread contamination in 2011, however, wide-scale action to clean-up these sites has yet to be initiated. A challenge for decision makers responsible for the clean-up of these sites has been the prioritisation of sites to enable appropriate allocation of scarce resources. In this study, a risk-based multi-criteria decision analysis framework was used to prioritise high-risk sites contaminated with petroleum hydrocarbons in the Ogoniland region of Nigeria. The prioritisation method used a set of risk-based attributes that took into account chemical and ecological impacts, as well as socio-economic impacts, providing a holistic assessment of the risk. Data for the analysis was taken from the UNEP Environmental Assessment of Ogoniland, where over 110 communities were assessed for oil-contamination. Results from our prioritisation show that the highest-ranking sites were not necessarily the sites with the highest observed level of hydrocarbon contamination. This differentiation was due to our use of proximity as a surrogate measure for likelihood of exposure. Composite measures of risk provide a more robust assessment, and can enrich discussions about risk management and the allocation of resources for the clean-up of affected sites.