This chapter presents a re-understanding of the contents of our analog magnitude representations (e.g., approximate duration, distance, number). The approximate number system (ANS) is considered, which supports numerical representations that are widely described as fuzzy, noisy, and limited in their representational power. The contention is made that these characterizations are largely based on misunderstandings—that what has been called “noise” and “fuzziness” is actually an important epistemic signal of confidence in one’s estimate of the value. Rather than the ANS having noisy (...) or fuzzy numerical content, it is suggested that the ANS has exquisitely precise numerical content that is subject to epistemic limitations. Similar considerations will arise for other analog representations. The chapter discusses how this new understanding of ANS representations recasts the learnability problem for number and the conceptual changes that children must accomplish in the number domain. (shrink)

It is difficult to watch wild animals while they move, so often biologists analyse characteristics of animal movement paths. One common path characteristic used is tortuousity, measured using the fractal dimension (D). The typical method for estimating fractal D, the divider method, is biased and imprecise. The bias occurs because the path length is truncated. I present a method for minimising the truncation error. The imprecision occurs because sometimes the divider steps land inside the bends of curves, and sometimes they (...) miss the curves. I present three methods for minimising this variation and test the methods with simulated correlated random walks. The traditional divider method significantly overestimates fractal D when paths are short and the range of spatial scales is narrow. The best method to overcome these problems consists of walking the dividers forwards and backwards along the path, and then estimating the path length remaining at the end of the last divider step. (shrink)

Log-file data from computer-based assessments can provide useful collateral information for estimating student abilities. In turn, this can improve traditional approaches that only consider response accuracy. Based on the amounts of time students spent on 10 mathematics items from the PISA 2012, this study evaluated the overall changes in and measurement precision of ability estimates and explored country-level heterogeneity when combining item responses and time-on-task measurements using a joint framework. Our findings suggest a notable increase in precision with (...) the incorporation of response times and indicate differences between countries in how respondents approached items as well as in their response processes. Results also showed that additional information could be captured through differences in the modeling structure when response times were included. However, such information may not reflect the testing objective. (shrink)

Uchiyama et al. question heritability estimates in a convincing manner. We offer additional arguments to further bolster their claims, highlighting methodological issues in heritability coefficients' derivation, their misuse in various contexts, and their potential contributions to exacerbating common erroneous intuitions that have been shown to lead to deleterious social phenomena. We conclude that science should move away from using them.

Ground Representationism is the position that for each phenomenal feature there is a representational feature that accounts for it. Against this thesis, Ned Block (The Puzzle of Phenomenal Precision, 2015) has provided an intricate argument that rests on the notion of “phenomenal precision”: the phenomenal precision of a percept may change at a different rate from its representational counterpart. If so, there is then no representational feature that accounts for a specific change of this phenomenal feature. Therefore, (...) Ground Representationism cannot be generally true. -/- Although the notion of phenomenal precision is intuitive, it is admittedly in need of clarification. Here I reconstruct Block’s argument by suggesting a way of estimating phenomenal precision that is based on the assumption that parts of perceptual wholes can share phenomenal features independently of their place in the whole. Understood like this, the overall argument shows what it is supposed to show. -/- A more thorough look at the notion of phenomenal precision suggests tension with Block’s other work: in order to be non-trivial, we have to accept that some of our phenomenality is not concrete, but only generic. Such “solely generic phenomenology”, however, is a position mainly held by opponents to Block’s Access- vs. Phenomenal Consciousness-distinction. Interpreting phenomenal imprecision as constituted by introspective imprecision does not suffice as a way out. It seems that phenomenal precision is either trivial, self-contradictory, or incompatible with Block’s position elsewhere. So some additional elucidation on this crucial notion is needed. (shrink)

The problem of missingness in observational data is ubiquitous. When the confounders are missing at random, multiple imputation is commonly used; however, the method requires congeniality conditions for valid inferences, which may not be satisfied when estimating average causal treatment effects. Alternatively, fractional imputation, proposed by Kim 2011, has been implemented to handling missing values in regression context. In this article, we develop fractional imputation methods for estimating the average treatment effects with confounders missing at random. We show that the (...) fractional imputation estimator of the average treatment effect is asymptotically normal, which permits a consistent variance estimate. Via simulation study, we compare fractional imputation’s accuracy and precision with that of multiple imputation. (shrink)

The conflict of narrowness and precision in direct inference occurs if a body of evidence contains estimates for frequencies in a certain reference class and less precise estimates for frequencies in a narrower reference class. To develop a solution to this conflict, I draw on ideas developed by Paul Thorn and John Pollock. First, I argue that Kyburg and Teng’s solution to the conflict of narrowness and precision leads to unreasonable direct inference probabilities. I then show that Thorn’s (...) recent solution to the conflict leads to unreasonable direct inference probabilities. Based on my analysis of Thorn’s approach, I propose a natural distribution for a Bayesian analysis of the data directly obtained from studying members of the narrowest reference class. (shrink)

BackgroundIn precision medicine biomarkers stratify patients into groups that are offered different treatments, but this may conflict with the principle of equal treatment. While some patient characteristics are seen as relevant for unequal treatment and others not, it is known that they all may influence treatment decisions. How biomarkers influence these decisions is not known, nor is their ethical relevance well discussed.MethodsWe distributed an email survey designed to elicit treatment preferences from Norwegian doctors working with cancer patients. In a (...) forced-choice conjoint analysis pairs of hypothetical patients were presented, and we calculated the average marginal component effect of seven individual patient characteristics, to estimate how each of them influence doctors’ priority-setting decisions.ResultsA positive biomarker status increased the probability of being allocated the new drug, while older age, severe comorbidity and reduced physical function reduced the probability. Importantly, sex, education level and smoking status had no significant influence on the decision.ConclusionBiomarker status is perceived as relevant for priority setting decisions, alongside more well-known patient characteristics like age, physical function and comorbidity. Based on our results, we discuss a framework that can help clarify whether biomarker status should be seen as an ethically acceptable factor for providing unequal treatment to patients with the same disease. (shrink)

In causal inference, a variety of causal effect estimands have been studied, including the sample, uncensored, target, conditional, optimal subpopulation, and optimal weighted average treatment effects. Ad hoc methods have been developed for each estimand based on inverse probability weighting and on outcome regression modeling, but these may be sensitive to model misspecification, practical violations of positivity, or both. The contribution of this article is twofold. First, we formulate the generalized average treatment effect to unify these causal estimands as well (...) as their IPW estimates. Second, we develop a method based on Kernel optimal matching to optimally estimate GATE and to find the GATE most easily estimable by KOM, which we term the Kernel optimal weighted average treatment effect. KOM provides uniform control on the conditional mean squared error of a weighted estimator over a class of models while simultaneously controlling for precision. We study its theoretical properties and evaluate its comparative performance in a simulation study. We illustrate the use of KOM for GATE estimation in two case studies: comparing spine surgical interventions and studying the effect of peer support on people living with HIV. (shrink)

Evidence-Based Medicine (EBM) and Personalized Medicine (PM) share a common goal: reducing the gap between the results of biomedical research and their clinical application. PM is, however, often presented as a “new paradigm” for medicine, just as EBM was in the 1990s. It covers a wide variety of projects but the core idea that generally unites them is the ambition of better taking account of individual specificities than did EBM with its statistical and population-centred approach. In this article, I concentrate (...) on PM in cancerology, the essence of which is to target treatments based on the molecular profile of the patient. This targeting is made possible by gaining better knowledge about the molecular mechanisms of cancers. The classification of patients as a function of their molecular profile entails the creation of patient sub-groups. This creates a problem for the traditional evaluation of therapeutic treatment promoted by EBM, in particular the use of randomized trials using sizeable cohorts. But a better understanding of the mechanisms and the greater precision of treatments could reduce the need for these trials. Does PM thus represent the revenge of a physio-pathological and mechanistic culture in clinical research against the statistical and empirical one of EBM? My objective is to show how current practices of PM leads to epistemological changes in our estimation of what count as relevant types of information and proof in medicine, in particular in the field of therapeutic evaluation. I defend the idea that PM, far from obviating the need for statistical approaches and the search for correlations, ultimately poses new challenges for EBM. PM drives EBM to strengthen the articulation and the integration of statistical and mechanistic data with a view to providing a better service for each patient. (shrink)

The COVID-19 pandemic heavily influenced human life by constricting human social activity. Following the spread of the pandemic, humans did not have a choice but to change their lifestyles. There has been much change in the field of education, which has led to schools hosting online classes as an alternative to face-to-face classes. However, the concentration level is lowered in the online learning class, and the student’s learning rate decreases. We devise a framework for recognizing and estimating students’ concentration levels (...) to help lecturers. Previous studies have a limitation in that they classified attention levels using only discrete states. Due to the partial information from discrete states, the concentration levels could not be recognized well. This research aims to estimate more subtle levels as specified states by using a minimum amount of body movement data. The deep neural network is used to continuously recognize the human concentration model, and the concentration levels can be predicted and estimated by the Kalman filter. Using our framework, we successfully extracted the concentration levels, which can aid lecturers and can be expanded to other areas. To implement the framework, we recruited participants to take online classes. Data were collected and preprocessed using pose points, and an accuracy of 90.62 % was calculated by predicting the concentration level using the framework. Furthermore, the concentration level was approximated based on the Kalman filter. We found that webcams can be used to quantitatively measure student concentration when conducting online classes. Our framework is a great help for instructors to measure concentration levels, which can increase the learning efficiency. As a future work of this study, if emotion data and skin thermal data are comprehensively considered, a student’s concentration level can be measured more precisely. (shrink)

We explore the extent to which ancient Greek authors formulated concepts that approximate or encompass our modern notions of precision and accuracy. First, we focus on estimates and measurements of geographic features, astronomical times and positions, and weight. These raise further questions about whether the quantities reported were measured, estimated, or rounded. While ancient sources discuss the use of instruments, it is not always clear that the aim was to achieve what we would today regard as ‘precision’. Next, (...) we briefly consider round numbers, observing that they could carry symbolic meaning, while unrounded numbers could give an impression of hard-won achievement. Finally, we examine uses of the word akribeia. This is often translated as ‘precision’ or ‘exactness’, and Greek writers sometimes used akribeia to denote an ideal for their inquiries. A brief look at its uses by a number of Greek writers will on the one hand show the mismatch with our term ‘precision’, and on the other hand throw some light on the aims of Greek investigators. (shrink)

The common view of the transition between subitizing and numerosity estimation regimes is that there is a hard bound on the subitizing range, and beyond this range, people estimate. However, this view does not adequately address the behavioral signatures of enumeration under conditions of attentional load or in the immediate post-subitizing range. The possibility that there might exist a numerosity range where both processes of subitizing and estimation operate in conjunction has so far been ignored. Here, we investigate (...) this new proposal, that people strategically combine the processes of subitizing and estimation to maximize accuracy and precision, given time or attentional constraints. We present a process-level account of how subitizing and estimation can be combined through strategic deployment of attention to maximize the precision of perceived numerosity given time constraints. We then describe a computational model of this account and apply it in two experimental simulations to demonstrate how it can explain key findings in prior enumeration research. While recent modeling work has argued that the behavioral signatures of enumeration can best be explained through a single numerosity system with a single form of representation, we argue that our model demonstrates how the traditional two-systems view of numerical representation accounts for behavioral data through coordination with a unified attentional mechanism, rather than a unified representation. (shrink)

Bayesian non-parametric modeling has been developed and proven to be a powerful tool to analyze messy data with complex structures. Despite the increasing popularity of BNP modeling, it also faces challenges. One challenge is the estimation of the precision parameter in the Dirichlet process mixtures. In this study, we focus on a BNP growth curve model and investigate how non-informative prior, weakly informative prior, accurate informative prior, and inaccurate informative prior affect the model convergence, parameter estimation, and (...) computation time. A simulation study has been conducted. We conclude that the non-informative prior for the precision parameter is less preferred because it yields a much lower convergence rate, and growth curve parameter estimates are not sensitive to informative priors. (shrink)

The main aim of this study was to analyze the patterns of changes in Approximate Number Sense precision from grade 1 to grade 9 in a sample of Russian schoolchildren. To fulfill this aim, the data from a longitudinal study of two cohorts of children were used. The first cohort was assessed at grades 1–5, and the second cohort was assessed at grades 5–9. ANS precision was assessed by accuracy and reaction time in a non-symbolic comparison test. The (...) patterns of change were estimated via mixed-effect growth models. The results revealed that in the first cohort, the average accuracy increased from grade 1 to grade 5 following a non-linear pattern and that the rate of growth slowed after grade 3. The non-linear pattern of changes in the second cohort indicated that accuracy started to increase from grade 7 to grade 9, while there were no changes from grade 5 to grade 7. However, the RT in the non-symbolic comparison test decreased evenly from grade 1 to grade 7, and the rate of processing non-symbolic information tended to stabilize from grade 7 to grade 9. Moreover, the changes in the rate of processing non-symbolic information were not explained by the changes in general processing speed. The results also demonstrated that accuracy and RT were positively correlated across all grades. These results indicate that accuracy and the rate of non-symbolic processing reflect two different processes, namely, the maturation and development of a non-symbolic representation system. (shrink)

How good are we at understanding what others communicate? It often seems to us, at least, that we understand quite well what others convey when speaking in a familiar language. However, a growing body of evidence from the psychology of language suggests that in various communicative settings comprehenders routinely form linguistic representations that are underdetermined, “sketchy”, “shallow” or imprecise, often without noticing it. The paper discusses some important consequences of this evidence. Following recent discussions in this strand of research, I (...) outline how the evidence is currently best interpreted as supporting a view on which operating at a certain level of imprecision and underdetermination is a functional feature of the system responsible for comprehension of linguistic utterances in humans. That this kind of imprecision and underdetermination is part and parcel of linguistic interactions, makes the exact success rate of comprehension particularly hard to estimate. This poses a unique and interesting challenge for assessing the quality of linguistic comprehension. Understanding what a speaker intended to convey with a linguistic utterance may be less transparent than it appears to us. I will discuss the extent to which this evidence may lead to pessimism about how good we are at comprehending what others communicate. However, as I will argue in the last part of the paper, in various cases language users can be sensitive to some types of imprecision and underdetermination in comprehension and make up for it by means of various forms of post hoc deliberation. I will describe some such clarificatory contexts and end by charting a map of important issues that require further investigation. (shrink)

Precise global solar radiation data are indispensable to the design, planning, operation, and management of solar radiation utilization equipment. Some examples prove that the uncertainty of the prediction of solar radiation provides more value than deterministic ones in the management of power systems. This study appraises the potential of random forest, V-support vector regression, and a resilient backpropagation artificial neural network for daily global solar radiation point prediction from average relative humidity, daily average temperature, and daily sunshine duration. To acquire (...) more accurate predictions of DGSR and examine the influence of historical DGSR on the performance of point prediction models, two different model inputs are considered: three meteorological variables and the lags of DGSR and three meteorological variables. Then, two interval prediction methods are developed by introducing the KDE to out-of-bag, introducing kernel density estimation to split conformal based on the three machine learning models. The two methods for interval prediction are denoted as OOB-KDE and SC-KDE. The mean absolute error, mean relative error, and Kendall rank correlation are used to assess the point prediction models. The performance of interval prediction methods is evaluated by the prediction interval coverage probability, prediction interval normalized average width, and coverage width criteria. The following conclusions are drawn from this study. First, the V-SVR model performs best with the lowest mean absolute error of 0.016 and mean relative error of 0.001. Second, the lags of DGSR improve the prediction accuracy by about 30%. Third, the OOB-KDE and SC-KDE methods improved the quality of the prediction interval. OOB-KDE improved CWC by 81%, and SC-KDE improved CWC by 99.99%. Fourth, the best interval prediction result is obtained using the SC-KDE method using the V-SVR model. The average difference between its PICP and prediction interval nominal coverage is only 3% of the PINC, and its PINAW is less than 0.007. (shrink)

The number-line estimation task has become one of the most important methods in numerical cognition research. Originally applied as a direct measure of spatial number representation, it became also informative regarding various other aspects of number processing and associated strategies. However, most of this work and associated conclusions concerns processing numbers in a symbolic format, by school children and older subjects. Symbolic number system is formally taught and trained at school, and its basic mathematical properties can easily be transferred (...) into a spatial format of an oriented number line. This triggers the question on basic characteristics of number line estimation before children get fully familiar with the symbolic number system, i.e., when they mostly rely on approximate system for non-symbolic quantities. In our three studies, we examine therefore how preschool children estimate position of non-symbolic quantities on a line, and how this estimation is related to the developing symbolic number knowledge and cultural directionality. The children were tested with the Give-a-number task, then they performed a computerized number-line task. In Experiment 1, lines bounded with sets of 1 and 20 elements going left-to-right or right-to-left were used. Even in the least numerically competent group, the linear model better fit the estimates than the logarithmic or cyclic power models. The line direction was irrelevant. In Experiment 2, a 1–9 left-to-right oriented line was used. Advantage of linear model was found at group level, and variance of estimates correlated with tested numerosities. In Experiment 3, a position-to-number procedure again revealed the advantage of the linear model, although the strategy of selecting an option more similar to the closer end of the line was prevalent. The precision of estimation increased with the mastery of counting principles in all three experiments. These results contradict the hypothesis of the log-to-linear shift in development of basic numerical representation, rather supporting the linear model with scalar variance. However, the important question remains whether the number-line task captures the nature of the basic numerical representation, or rather the strategies of mapping that representation to an external space. (shrink)

Construction cost estimation is one of the essential processes in construction management. Project cost is a complex engineering problem due to various factors affecting the construction industry. Accurate cost estimation is important in construction management and significantly impacts project performance. Artificial intelligence models have been effectively implemented in construction management studies in recent years owing to their capability to deal with complex problems. In this research, extreme gradient boosting is developed as an advanced input selector algorithm and coupled (...) with three AI models, including random forest, artificial neural network, and support vector machine for cost estimation. Datasets were gathered based on a survey conducted on 90 building projects in Iraq. Statistical indicators and graphical methods were used to evaluate the developed models. Several input predictors were used, and XGBoost highlighted inflation as the most crucial parameter. The results indicated that the best prediction was attained by XGBoost-RF using six input parameters, with r-squared and the mean absolute percentage error equal to 0.87 and 0.25, respectively. The comparison results revealed that all AI models showed good prediction performance when applied to datasets affected by more than two parameters. The outcomes of this research revealed an optimistic strategy that can help decision makers select the influencing parameters in the early phases of project management. Also, developing a prediction model with high precision results can assist the project’s estimators in decreasing the errors in the cost estimation process. (shrink)

Statistical power is often a concern for clustered randomized control trials (RCTs) due to variance inflation from design effects and the high cost of adding study clusters (such as hospitals, schools, or communities). While covariate pre-specification can improve power for estimating regression-adjusted average treatment effects (ATEs), further precision gains can be achieved through covariate selection once primary outcomes have been collected. This article uses design-based methods underlying clustered RCTs to develop Lasso methods for the post-hoc selection of covariates for (...) ATE estimation that avoids a lack of transparency and model overfitting. Our focus is on two-stage estimators: in the first stage, Lasso estimation is conducted using data on cluster-level averages or sums, and in the second stage, standard ATE estimators are adjusted for covariates using the first-stage Lasso results. We discuss l 1 {l}_{1} consistency of the estimated Lasso coefficients, asymptotic normality of the ATE estimators, and design-based variance estimation. The nonparametric approach applies to continuous, binary, and discrete outcomes. We present simulation results and demonstrate the method using data from a federally funded clustered RCT testing the effects of school-based programs promoting behavioral health. (shrink)

It has been estimated that three species on the planet now go extinct every hour and that this rate is orders of magnitude higher than the planet has seen in previous catastrophic extinction events. We clearly are in the midst of a sixth extinction, and this one is different from the previous five. Why? This sixth extinction is caused by the activity of a single species—us. If there is any hope of ameliorating this extinction, it will entirely be up to (...) us, as the current stewards of this planet, to change the course. There are many challenges, though, to marshaling this effort. Two primary ones immediately come to mind. The first is that we simply haven't found the right biological tools to address this crisis. The second is that many humans on this planet don't even admit we have a problem. These are two very different problems. The first is primarily technological. Only recently has some of the more advanced biologically focused technology been available to conservation biology and extinction science. Humans are enthralled by cutting‐edge technology for the most part, and for the public, one of the more exciting possibilities in the realm of conservation biology is that some of the more charismatic species that have gone extinct might be resurrected through next‐generation technologies. While our discussion will articulate some weaknesses with the de‐extinction approach to conservation biology, we suggest that the “sexiness” of the technologies used in de‐extinction may simultaneously provide a definition of the techniques viable in conservation biology and afford a teachable moment. (shrink)

Adjusting for covariates is a well-established method to estimate the total causal effect of an exposure variable on an outcome of interest. Depending on the causal structure of the mechanism under study, there may be different adjustment sets, equally valid from a theoretical perspective, leading to identical causal effects. However, in practice, with finite data, estimators built on different sets may display different precisions. To investigate the extent of this variability, we consider the simplest non-trivial non-linear model of a v-structure (...) on three nodes for binary data. We explicitly compute and compare the variance of the two possible different causal estimators. Further, by going beyond leading-order asymptotics, we show that there are parameter regimes where the set with the asymptotically optimal variance does depend on the edge coefficients, a result that is not captured by the recent leading-order developments for general causal models. As a practical consequence, the adjustment set selection needs to account for the relative magnitude of the relationships between variables with respect to the sample size and cannot rely on purely graphical criteria. (shrink)

Multi-person pose estimation is a challenging problem. Bottom-up methods have been greatly studied because the prediction speed of top-down methods is related to the number of people in the input image, making these methods difficult to apply in real-time environments. To solve the problems of scale sensitivity and quantization error in bottom-up methods, it is necessary to have a model that can predict multi-scale keypoints and refine quantization error. To achieve this, we propose context feature and refined network for (...) multi-person pose estimation (CRNet), which can effectively solve the problems of scale sensitivity and quantization error in bottom-up methods. We use a multi-scale feature pyramid and context feature to achieve scale invariance of the network. We extract global and local features and then fuse them by attentional feature fusion (AFF) to obtain context feature that adapt to multi-scale keypoints. In addition, we propose an efficient refined network to solve the problem of quantization error and use multi-resolution supervised learning to further improve the prediction accuracy of CRNet. Comprehensive experiments are conducted on two benchmarks: COCO and MPII datasets. The average precision of CRNet reached 72.1 and 80.2%, respectively, surpassing most state-of-the-art methods. (shrink)

In prior research, signal detection theory has been widely utilized to assess metacognitive ability. However, the SDT metacognitive model requires the use of a two-alternative forced-choice task, while confidence must also be measured discretely. In our model, participants’ cognitive ability and their confidence in the cognitive task were used to estimate their metacognitive abilities. Therefore, in this study, a metacognitive model that can be applied to various cognitive tasks was developed. This model implements the item response theory and Q-learning models (...) to estimate cognitive ability; participants’ metacognitive ability is defined as the discrepancy between their confidence in their cognitive ability and their actual cognitive ability. The entire procedure was divided into two experiments. In experiment 1, two different cognitive tasks were used to estimate metacognitive ability and to examine overall discriminative and convergent validity. Notably, the parameters representing metacognitive ability did not correlate with cognitive ability but were positively correlated between the two tasks. In experiment 2, we performed a similar analysis using a different task to test the replicability of experiment 1. The results for experiment 2 were replicated for discriminative and convergent validity, albeit with weak results. Our metacognitive model exhibited high interpretability and versatility. (shrink)

This paper explores the various meanings of precision during the early modern period in Europe. In contrast with existing literature focused on assessing the precision of early instruments, this study delves into the intended significance of the term ‘precision’ as understood by historical figures such as J. Stöffler, P. Nunes or F. Mordente. By analysing a selection of instruments equipped with scales, both in their physical form and as they are described in instrument texts, several facets of (...) precision emerge. Some findings demonstrate that the precision of scales can be enhanced through corrections obtained from tables. In other cases, visual estimation is substituted with a method for obtaining values of multiple sexagesimal places. Furthermore, certain instruments designed to represent theoretical concepts achieve greater precision by incorporating the most intricate details of these notions. This investigation into lesser-known meanings of precision underscores the need of comprehensively exploring the concepts, the practices and the terminology surrounding precision that were in use over the fifteenth and sixteenth centuries. (shrink)

Recent advances in wireless data transmission technology have the potential to revolutionize clinical neuroscience. Today sensing-capable electrical stimulators, known as “bidirectional devices”, are used to acquire chronic brain activity from humans in natural environments. However, with wireless transmission come potential failures in data transmission, and not all available devices correctly account for missing data or provide precise timing for when data losses occur. Our inability to precisely reconstruct time-domain neural signals makes it difficult to apply subsequent neural signal processing techniques (...) and analyses. Here, our goal was to accurately reconstruct time-domain neural signals impacted by data loss during wireless transmission. Towards this end, we developed a method termed Periodic Estimation of Lost Packets. PELP leverages the highly periodic nature of stimulation artifacts to precisely determine when data losses occur. Using simulated stimulation waveforms added to human EEG data, we show that PELP is robust to a range of stimulation waveforms and noise characteristics. Then, we applied PELP to local field potential recordings collected using an implantable, bidirectional DBS platform operating at various telemetry bandwidths. By effectively accounting for the timing of missing data, PELP enables the analysis of neural time series data collected via wireless transmission—a prerequisite for better understanding the brain-behavior relationships underlying neurological and psychiatric disorders. (shrink)

A dynamic learning method is developed for an uncertain n-link robot with unknown system dynamics, achieving predefined performance attributes on the link angular position and velocity tracking errors. For a known nonsingular initial robotic condition, performance functions and unconstrained transformation errors are employed to prevent the violation of the full-state tracking error constraints. By combining two independent Lyapunov functions and radial basis function neural network approximator, a novel and simple adaptive neural control scheme is proposed for the dynamics of the (...) unconstrained transformation errors, which guarantees uniformly ultimate boundedness of all the signals in the closed-loop system. In the steady-state control process, RBF NNs are verified to satisfy the partial persistent excitation condition. Subsequently, an appropriate state transformation is adopted to achieve the accurate convergence of neural weight estimates. The corresponding experienced knowledge on unknown robotic dynamics is stored in NNs with constant neural weight values. Using the stored knowledge, a static neural learning controller is developed to improve the full-state tracking performance. A comparative simulation study on a 2-link robot illustrates the effectiveness of the proposed scheme. (shrink)

The food security of more than half of the world’s population depends on rice production which is one of the key objectives of precision agriculture. The traditional rice almanac used astronomical and climate factors to estimate yield response. However, this research integrated meteorological, agro-chemical, and soil physiographic factors for yield response prediction. Besides, the impact of those factors on the production of three major rice ecotypes has also been studied in this research. Moreover, this study found a different set (...) of those factors with respect to the yield response of different rice ecotypes. Machine learning algorithms named Extreme Gradient Boosting and Support Vector Regression have been used for predicting the yield response. The SVR shows better results than XGBoost for predicting the yield of the Aus rice ecotype, whereas XGBoost performs better for forecasting the yield of the Aman and Boro rice ecotypes. The result shows that the root mean squared error of three different ecotypes are in between 9.38% and 24.37% and that of R-squared values are between 89.74% and 99.13% on two different machine learning algorithms. Moreover, the explainability of the models is also shown in this study with the help of the explainable artificial intelligence model called Local Interpretable Model-Agnostic Explanations. (shrink)

The ArgumentWhile there has been muchattention given to experiment in modern science studies, there has been astoundingly little concern spared over the practice ofquanitataivemeasurment.Thus myths about the unreasonable effectiveness of mathematice in science still abound. This paper presents: An explicit mathematical model of the stabilization of quantitative constants in a mathematical science to rival older Bayesian and classical accounts;a framework for writing a history of pracitces with regard to treatment of quantitative measurement erroe; resourece for the comparative sociology of differing (...) discipliness in this regard;and a prolegonmena to a critique of orthodox economics and accounting theories. The key to all these diverse themes is the realization that no one individual alone is capable of fixing the magnitude of a quantitative error estimate, and therefore the social construction of error must be given a more precise meaning, an therefore the social construction of error must be given a more precise menaing, and that this occurs through the istrumentality of meta-analysis. (shrink)

In management research, theory testing confronts a paradox described by Meehl in which designing studies with greater methodological rigor puts theories at less risk of falsification. This paradox exists because most management theories make predictions that are merely directional, such as stating that two variables will be positively or negatively related. As methodological rigor increases, the probability that an estimated effect will differ from zero likewise increases, and the likelihood of finding support for a directional prediction boils down to a (...) coin toss. This paradox can be resolved by developing theories with greater precision, such that their propositions predict something more meaningful than deviations from zero. This article evaluates the precision of theories in management research, offers guidelines for making theories more precise, and discusses ways to overcome barriers to the pursuit of theoretical precision. (shrink)

Although memories are more retrievable if observers’ emotional states are consistent between encoding and retrieval, it is unclear whether the consistency of emotional states increases the likelihood of successful memory retrieval, the precision of retrieved memories, or both. The present study tested visual long-term memory for everyday objects while consistent or inconsistent emotional contexts between encoding and retrieval were induced using background grey-scale images from the International Affective Picture System. In the study phase, participants remembered colours of sequentially presented (...) objects in a negative or positive context. In the test phase, participants estimated the colours of previously studied objects in either negative versus neutral or positive versus neutral contexts. Note, IAPS images in the test phase were always visually different from those initially paired with the studied objects. We found that reinstating negative context and positive context at retrieval resulted in better mnemonic precision and a higher probability of successful retrieval, respectively. Critically, these effects could not be attributed to a negative or positive context at retrieval alone. Together, these findings demonstrated dissociable effects of emotion on the quantitative and qualitative aspects of visual long-term memory retrieval. (shrink)

In late 1912, Fritz Goos at the Hamburg Physikalisches Staatslaboratorium discovered a systematic dependency of arc-spectra wavelengths on the length of the electric arc used and on its electric parameters, such as, for instance, the current employed. In early 1913, at Heinrich Kayser's better-equipped physical laboratory in Bonn, Goos was able to confirm these effects using a large concave Rowland grating. He was able to establish that variations of between 3 mm and 10 mm in the length of the arc (...) produced wavelength differences of up to 0.02 Å violet shift and -0.007 Å redshift respectively. Further inquiry also revealed a dependency of the wavelength on the region of the arc selected for spectrometric observation. All these surprising effects were soon collectively named ‘pole effect’.As is shown in this paper, the pole effect threatened the validity of the results of the entire research tradition of high-precision spectroscopy which, around 1910, had excelled in establishing several internally coherent systems of wavelength assignments. These wavelength catalogues had been established by spectroscopists such as Heinrich Kayser, Paul Eversheim and their co-workers in Bonn, by August Herman Pfund in Baltimore, and by Charles Fabry and Henri Buisson in Marseille under the aegis of the ‘International Union for Co-Operation in Solar Research’. They had all produced locally consistent, “homogeneous” systems of wavelengths with estimated errors sometimes smaller than 0.001 Å. However, long before 1913, strange non-local inconsistencies had emerged between these systems that were of much greater magnitude than the estimated error. The discovery of the pole effect opened up the possibility that variations in the arc parameters used in the measurements, which the different teams had hitherto not specified, were responsible for the systematic differences, in their respective sets of measurements, coming to up to 0.025 Å.This paper explores the interrelations between local knowledge production, the strategies for the establishment of local coherence, and the ways in which the community of physicists and spectroscopists handled a possible threat to this coherence after 1913. Around 1930, a general agreement was reached about the physical cause of the pole effect, namely Stark effects, caused in turn by intermolecular electric fields of ions in the arc. Much before 1930, however, the community had already succeeded in standardizing the instrumentation used in high-precision spectrometry and had conformed its research practice to such an extent that from 1917 on the pole effect could be routinely circumvented in high-precision spectrometry and interferometry. Thus, experimentation along with its instrumentation, indeed had ‘a life of its own’, independent of the many unsuccessful efforts to explain the pole effect theoretically. (shrink)

A Theory of Magnitude suggests that space, time, and quantities are processed through a generalized magnitude system. ATOM posits that task-irrelevant magnitudes interfere with the processing of task-relevant magnitudes as all the magnitudes are processed by a common system. Many behavioral and neuroimaging studies have found support in favor of a common magnitude processing system. However, it is largely unknown whether such cross-domain monotonic mapping arises from a change in the accuracy of the magnitude judgments or results from changes in (...) precision of the processing of magnitude. Therefore, in the present study, we examined whether large numerical magnitude affects temporal accuracy or temporal precision, or both. In other words, whether numerical magnitudes change our temporal experience or simply bias duration judgments. The temporal discrimination paradigm was used to present numerical magnitudes across varied durations. We estimated temporal accuracy and precision for each numerical magnitude. The results revealed that temporal accuracy for large numerical magnitude was significantly lower than that of small and identical magnitudes. This implies that the temporal duration was overestimated for large numerical magnitude compared to small and identical numerical magnitude, in line with ATOM’s prediction. However, no influence of numerical magnitude was observed on temporal precision. The findings of the present study suggest that task-irrelevant numerical magnitude selectively affects the accuracy of processing of duration but not duration discrimination itself. Further, we argue that numerical magnitude may not directly affect temporal processing but could influence via attentional mechanisms. (shrink)

This month the American Journal of Bioethics examines the intersectionality of medicine, ethics, and race. In “Race, Power, and COVID-19: A Call for Advocacy Within Bioethics,” Mithani and colleagu...

Virtue reliabilists argue that an agent can only gain knowledge if she responsibly employs a reliable belief-forming process. This in turn demands that she is either aware that her process is reliable or is sensitive to her process’s reliability in some other way. According to a recent argument in the philosophy of mind, sometimes a cognitive mechanism (i.e. precision estimation) can ensure that a belief-forming process is only employed when it’s reliable. If this is correct, epistemic responsibility can (...) sometimes be explained entirely on the subpersonal level. In this paper, I argue that the mechanism of precision estimation–the alleged new variety of epistemic responsibility–is a more ubiquitous phenomenon than epistemic responsibility. I show that precision estimation operates at levels that are not always concerned with the epistemic domain. Lastly, I broaden this argument to explain how all subpersonal epistemologies are likely to fall prey to the problem of demarcating cognitive agency and the problem of attributing beliefs. (shrink)

According to the free energy principle biological agents resist a tendency to disorder in their interactions with a dynamically changing environment by keeping themselves in sensory and physiological states that are expected given their embodiment and the niche they inhabit :127–138, 2010. doi: 10.1038/nrn2787). Why would a biological agent that aims at minimising uncertainty in its encounters with the world ever be motivated to seek out novelty? Novelty for such an agent would arrive in the form of sensory and physiological (...) states that are unexpected. Such an agent ought therefore to avoid novel and surprising interactions with the world one might think. Yet humans and many other animals find play and other forms of novelty-seeking and exploration hugely rewarding. How can this be understood in frameworks for studying the mind that emphasise prediction error minimisation? This problem has been taken up in recent research concerned with epistemic action—actions an agent engages in to reduce uncertainty. However that work leaves two questions unanswered, which it is the aim of our paper to address. First, no account has been given yet of why it should feel good to the agent to engage the world playfully and with curiosity. Second an appeal is made to precision-estimation to explain epistemic action, yet it remains unclear how precision-weighting works in action more generally, or active inference. We argue that an answer to both questions may lie in the bodily states of an agent that track the rate at which free energy is being reduced. The recent literature on the predictive brain has connected the valence of emotional experiences to the rate of change in the reduction of prediction error :e1003094, 2013. doi: 10.1371/journal.pcbi.1003094; Van de Cruys, in Metzinger and Wiese Philosophy and predictive processing, vol 24, MIND Group, Frankfurt am Main, 2017. doi: 10.15502/9783958573253). In this literature valenced emotional experiences are hypothesised to be identical with changes in the rate at which prediction error is reduced. Experiences are negatively valenced when overall prediction error increases and are positively valenced when the sum of prediction errors decrease. We offer an ecological-enactive interpretation of the concept of valence and its connection to rate of change of prediction error. We show how rate of change should be understood in terms of embodied states of affordance-related action readiness. We then go on to apply this ecological-enactive account of error dynamics to provide an answer to the first question we have raised: It may explain why it should feel good to an agent to be curious and playful. Our ecological-enactive account also allows us to show how error dynamics may provide an answer to the second question we have raised regarding how precision-weighting works in active inference. An agent that is sensitive to rates of error reduction can tune precision on the fly. We show how this ability to tune precision on the go can allow agents to develop skills for adapting better and better to the unexpected, and search out opportunities for resolving uncertainty and progressing in its learning. (shrink)

Major depression is a prevalent mental disorder that leads to persistent negative mood and tremendous suffering in affected individuals. However, the biological realization of this disorder and associated symptom clusters remain poorly understood. Recently, phenomenological accounts of major depressive disorder and contributions to the emerging predictive processing account have provided valuable insights into the phenomenological and neuro-functional components that lead to manifestations of major depressive episodes. The purpose of this paper is to weave together these different strands of research to (...) develop a predictive processing account of major depressive disorder. In doing so, I will relate personal-level descriptions of associated phenomenal experiences to a sub-personal-level predictive processing account of the functional realization of major depression. I will argue that pervasive symptoms of the disorder, which include a diminished sense of agency, fatigue, social withdrawal, and rumination, are integrated by existential feelings of loss and impossibility. These phenomenal experiences, I will argue, are associated with dysfunctional processes of prediction error minimization, which are characterized by an overall decrease of the causal contributions of active inference and by distorted precision estimates. The emerging account promises to contribute to a better understanding of the complex processes that give rise to depressive experiences. (shrink)

This paper sketches an account that explains the elusive subjective quality of 'enduring substantiality' of the phenomenal self. It integrates a recent predictive processing account of the self by Chris Letheby and Philip Gerrans with key ideas of Michael Graziano's attention schema theory of consciousness. Similarly to the attention schema theory, the present account posits an internal model of ongoing attentional processing that supports attentional control. In terms of predictive processing, it is a dynamic model of precision estimates that (...) represents the salience of features, objects, and internal and external processes. The apparent substantiality of the self is then explained by a structural feature of this salience model: it binds different dimensions of salience by representations of higher-order dimensions of salience. The result of this salience binding is a phenomenally transparent 'salience object', which is represented as a cause of widespread changes in precision estimates, and results in a form of epistemic self-control. Phenomenologically, this goes along with the experience of the self as an attentional agent, and in this way creates the origin of our consciously experienced first-person perspective: I attend, I am. (shrink)

ABSTRACTThis study is a direct replication of gaze-liking effect using the same design, stimuli and procedure. The gaze-liking effect describes the tendency for people to rate objects as more likeable when they have recently seen a person repeatedly gaze toward rather than away from the object. However, as subsequent studies show considerable variability in the size of this effect, we sampled a larger number of participants than the original study to gain a more precise estimate of the gaze-liking effect size. (...) Our results indicate a much smaller standardised effect size than that of the original study. Our smaller effect size was not due to general insensitivity to eye-gaze effects because the same sample showed a clear gaze-cuing effect – faster reaction times when eyes looked toward vs away from target objects. We discuss the implications of our findings for future studies wishing to study the gaze-liking effect. (shrink)

It is shown that the postulation of a minimum length for the horizons of a black hole leads to lower bounds for the electric charges and magnetic moments of elementary particles. If the minimum length has the order of the Planck scale, these bounds are given, respectively, by the electronic charge and by \. The latter implies that the masses of fundamental particles are bounded above by the Planck mass, and that the smallest non-zero neutrino mass is \eV. A precise (...) estimation in agreement to the area quantisation of Loop Quantum Gravity predicts a mass for the lightest massive state in concordance with flavor oscillation measurements, and a Barbero–Immirzi parameter in accordance to horizon entropy estimations. (shrink)

While we cannot directly measure the psychological preferences of individuals, and the moral, emotional, and cognitive tendencies of people from the past, we can use cultural artifacts as a window to the zeitgeist of societies in particular historical periods. At present, an increasing number of digitized texts spanning several centuries is available for a computerized analysis. In addition, developments form historical economics have enabled increasingly precise estimations of sociodemographic realities from the past. Crossing these datasets offer a powerful tool to (...) test how the environment changes psychology and vice versa. However, designing the appropriate proxies of relevant psychological constructs is not trivial. The gold standard to measure psychological constructs in modern texts – Linguistic Inquiry and Word Count – has been validated by psychometric experimentation with modern participants. However, as a tool to investigate the psychology of the past, the LIWC is limited in two main aspects: it does not cover the entire range of relevant psychological dimensions and the meaning, spelling, and pragmatic use of certain words depend on the historical period from which the fiction work is sampled. These LIWC limitations make the design of custom tools inevitable. However, without psychometric validation, there is uncertainty regarding what exactly is being measured. To overcome these pitfalls, we suggest several internal and external validation procedures, to be conducted prior to diachronic analyses. First, the semantic adequacy of search terms in bags-of-words approaches should be verified by training semantic vector spaces with the historical text corpus using tools like word2vec. Second, we propose factor analyses to evaluate the internal consistency between distinct bag-of-words proxying the same underlying psychological construct. Third, these proxies can be externally validated using prior knowledge on the differences between genres or other literary dimensions. Finally, while LIWC is limited in the analysis of historical documents, it can be used as a sanity check for external validation of custom measures. This procedure allows a robust estimation of psychological constructs and how they change throughout history. Together with historical economics, it also increases our power in testing the relationship between environmental change and the expression of psychological traits from the past. (shrink)

SUMMARYDuring the 1970s, widespread scientific interest in the risks of climate change prompted John A. Eddy, an astrophysicist with the National Center for Atmospheric Research in Boulder, CO, to investigate whether sunspots could be used to predict future climate changes. Methodologically, Eddy’s investigations were uniquely historical in nature. By interrogating old manuscripts of solar observations since the early seventeenth century, he identified what appeared to be a correlation between the so-called Maunder Minimum – a virtual cessation of sunspots between 1645 (...) and 1715 – and severely cold temperatures during the Little Ice Age. While he could not identify the physical mechanisms that governed solar-climate relationships, this historical episode fostered his curiosity. Fortuitously, Eddy’s solar-climate research coincided with efforts to use satellites to monitor and record variations in solar energy output, which in context constituted a significant development in managing environmental and technological risk.But using the Maunder Minimum to advance the frontiers of knowledge about solar-terrestrial relationships was not Eddy’s only – or even primary – motivation. In the mid-1840s, German astronomer Heinrich Schwabe discovered what appeared to be a decadal sunspot cycle, the existence of which inspired generations of astrophysicists to more precisely estimate its length as well as determine its underlying causes. Eddy, however, came to believe that the astronomical community failed to consider the implications of subsequent evidence suggesting that Schwabe's solar cycle was not an enduring characteristic of the sun. Instead, he reasoned that evidence offered by nineteenth-century European astronomers Gustav Sporer and Edward Maunder in the 1880s and 1890s had been entirely overlooked. But rather than arguing that their evidence was overlooked in error, Eddy identified what he cast as a conspiracy of wilful ignorance on the part of a staid and conservative astronomical community. By utilizing Eddy's private hand-written notes as they appeared in undergraduate lectures, public speeches and academic talks, as well as his appreciation for the seminal views of sociologist of science Thomas Kuhn, I show that Eddy sought to rectify this injustice by proposing a contrasting vision of science as an interdisciplinary, collaborative and creative process of exploring the ignored areas between scientific disciplines. (shrink)

Results of a comprehensive simulation study are reported investigating the effects of sample size, test length, number of attributes and base rate of mastery on item parameter recovery and classification accuracy of four DCMs. Effects were evaluated using bias and RMSE computed between true parameters and estimated parameters. Effects of simulated factors on attribute assignment were also evaluated using the percentage of classification accuracy. More precise estimates of item parameters were obtained with larger sample size and longer test length. Recovery (...) of item parameters decreased as the number of attributes increased from three to five but base rate of mastery had a varying effect on the item recovery. Item parameter and classification accuracy were higher for DINA and DINO models. (shrink)

When used in conjunction with the current floorplan and the optimization technique in circuit design engineering, this research allows for the evaluation of design parameters that can be used to reduce congestion during integrated circuit fabrication. Testing the multiple alternative consequences of IC design will be extremely beneficial in this situation, as will be demonstrated further below. If the importance of placement and routing congestion concerns is underappreciated, the IC implementation may experience significant nonlinear problems throughout the process as a (...) result of the underappreciation of placement and routing congestion concerns. The use of standard optimization techniques in integrated circuit design is not the most effective strategy when it comes to precisely estimating nonlinear aspects in the design of integrated circuits. To this end, advanced tools such as Xilinx VIVADO and the ICC2 have been developed, in addition to the ICC1 and VIRTUOSO, to explore for computations and recover the actual parameters that are required to design optimal placement and routing for well-organized and ordered physical design. Furthermore, this work employs the perimeter degree technique to measure routing congestion in both horizontal and vertical directions for a silicon chip region and then applies the technique to lower the density of superfluous routing. Recently, a metaheuristic approach to computation has increased in favor, particularly in the last two decades. It is a classic graph theory problem, and it is also a common topic in the field of optimization. However, it does not provide correct information about where and how nodes should be put, despite its popularity. Consequently, in conjunction with the optimized floorplan data, the optimized model created by the Improved Harmonic Search Optimization algorithm undergoes testing and investigation in order to estimate the amount of congestion that occurs during the routing process in VLSI circuit design and to minimize the amount of congestion that occurs. (shrink)

En faisant dialoguer Paul Ricœur, Judith Butler, Emmanuel Levinas et Annie Léchenet, je montre comment l’œuvre de Ricœur offre des ressources intéressantes pour articuler une double exigence des discours féministes, à savoir une exigence de justice et une exigence de reconnaissance. Cet article se propose de montrer plus précisément comment l’herméneutique du sujet ricœurien, qui place l’estime de soi au cœur d’une recherche de la vie bonne, avec et pour les autres, dans des institutions justes, peut offrir un intérêt particulier (...) pour la recherche féministe. En liant plus particulièrement les notions de promesse et d’estime de soi, l’article suggère que Ricœur nous aide à élaborer un concept qui semble implicite dans le féminisme, celui de fidélité à soi. (shrink)

Unsupervised learning techniques, e.g. clustering, is useful for obtaining a summary of a dataset. However, its application to large databases can be computationally expensive. Alternatively, useful information can also be retrieved from its subsets in a more efficient yet effective manner. This paper addresses the problem of finding a small subset of minority instances whose distribution significantly differs from that of the majority. Generally, such a subset can substantially overlap with the majority, which is problematic for conventional estimation of (...) distribution. This paper proposes a new approach for estimating a minority distribution based on Information Theoretic Framework, an extension of the Rate Distortion Theory for unsupervised learning tasks. Specifically, the proposed method estimates parameters which maximize the divergence between the minority and majority distributions, penalizes the redundancy of data expression based on the mutual information between the observed and hidden variables, and employs a hard assignment approximation to avoid computation of trivial conditional probabilities. The algorithm of the proposed method has no problem-dependent parameter and its time and space complexities are linear to the size of the minority subset. Experiments using artificial datasets show the proposed method yields significantly high precision and sensitivity in detecting minority subsets which substantially overlaps with the majority. The proposed method also substantially outperforms one-class classification and mixture estimation methods in real-world benchmark datasets for text and satellite imagery classification. (shrink)

Estimating whether the Earth’s biota is in the middle of a crisis relies heavily on comparisons between present and past data about biodiversity or biodiversity surrogates. Although the past is a crucial source of information to assess the severity of the current biodiversity crisis, substantive conceptual and methodological questions remain about how paleodiversity and biodiversity are to be properly compared. I argue that to justify claims of a current biodiversity crisis is harder than it appears. More precisely, I claim that (...) paleodiversity measurements are incommensurable with contemporary measurements, given the different ways that biodiversity is conceptualized and operationalized. I conclude by proposing three possible ways of overcoming this incommensurability problem. (shrink)