Several studies have shown that our visual system may construct a “summary statistical representation” over groups of visual objects. Although there is a general understanding that human observers can accurately represent sets of a variety of features, many questions on how summary statistics, such as an average, are computed remain unanswered. This study investigated sampling properties of visual information used by human observers to extract two types of summary statistics of item sets, average and variance. We presented three models (...) of ideal observers to extract the summary statistics: a global sampling model without sampling noise, global sampling model with sampling noise, and limited sampling model. We compared the performance of an ideal observer of each model with that of human observers using statistical efficiency analysis. Results suggest that summary statistics of items in a set may be computed without representing individual items, which makes it possible to discard the limited sampling account. Moreover, the extraction of summary statistics may not necessarily require the representation of individual objects with focused attention when the sets of items are larger than 4. (shrink)

The study aims to identify the efficiency of the university education performance from the perspective of postgraduate and undergraduate students in international and Palestinian universities. The analytical descriptive approach was used for this purpose and the questionnaire was used as a main tool for data collection. The study community consists of: post graduate students, (23850) graduate students and (146355) undergraduate students. The sample of the study was 378 graduate students and 383 undergraduate students. The random stratified sample was used. (...) The Statistical Package of Social Sciences (SPSS) was also used for data analysis. The study reached a number of results, the most important of which are: The level of efficiency of educational performance in Palestinian and international universities from the point of view of postgraduate and undergraduate students was high. And that there are significant differences between the average views of the sample of the study on the efficiency of educational performance in Palestinian and international universities attributed to the University and to the benefit of international universities. The study concluded many recommendations, the most important of which is the necessity of continuing to develop e-learning strategies that affect the efficiency of educational performance and research commensurate with the university's position in the local and international community, which puts it on the best classification between local and international universities through e-learning. (shrink)

This study investigated visual statistical learning (VSL) in 24 deaf signers and 24 hearing non‐signers. Previous research with hearing individuals suggests that SL mechanisms support literacy. Our first goal was to assess whether VSL was associated with reading ability in deaf individuals, and whether this relation was sustained by a link between VSL and sign language skill. Our second goal was to test the Auditory Scaffolding Hypothesis, which makes the prediction that deaf people should be impaired in sequential processing (...) tasks. For the VSL task, we adopted a modified version of the triplet learning paradigm, with stimuli presented sequentially across space and time. Results revealed that measures of sign language skill (sentence comprehension/repetition) did not correlate with VSL scores, possibly due to the sequential nature of our VSL task. Reading comprehension scores (PIAT‐R) were a significant predictor of VSL accuracy in hearing but not deaf people. This finding might be due to the sequential nature of the VSL task and to a less salient role of the sequential orthography‐to‐phonology mapping in deaf readers compared to hearing readers. The two groups did not differ in VSL scores. However, when reading ability was taken into account, VSL scores were higher for the deaf group than the hearing group. Overall, this evidence is inconsistent with the Auditory Scaffolding Hypothesis, suggesting that humans can develop efficient sequencing abilities even in the absence of sound. (shrink)

The approaching ways in religious phenomenon quantitative studies are, most of the times, based only on the evolution of adherent flows and population structure from a religious point of view. In this pape, an integrated statistical indicators system will be designed. The main purpose of the system is to enhance the quality and coherence of the religious phenomenon. The most important indicators from the integrated system are: context indicators (political, economical, socio-cultural, demographical), basic indicators, level and structure indicators, participation (...) indicators, resource indicators (spiritual, human and pecuniary), quality, efficiency and outcomes (religious freedom, social connections, international relationships). Designing a complete, coherent system of indicators is necessary for a correct approach in studying the religious phenomenon. Statistical indicators can supply quantitative data for the operational description of the religious phenomenon. The indicators’ system makes possible not only a descriptive analysis but also some advanced statistical techniques (e.g. regression and correlation method). (shrink)

Rheumatoid arthritis is a progressive systemic autoimmune disease characterized by inflammation of the joints and surrounding tissues, which seriously affects the life of patients. The Sharp/van der Heijde method has been widely used in clinical evaluation for the RA disease. However, this manual method is time-consuming and laborious. Even if two radiologists evaluate a specific location, their subjective evaluation may lead to low inter-rater reliability. Here, we developed an efficient model powered by deep convolutional neural networks to solve these problems (...) and automated the overall scoring on hand X-rays. The depthwise separable convolution technique is used based on ResNet-50 due to the high resolution of hand X-rays. An inverted residual block is introduced to devise a ResNet-Dwise50 model to enhance the efficiency of the model. The model was trained and tested using bilateral posteroanterior images of 3818 patients. The experiment results show the ResNet-Dwise50 model achieved an MAE of 14.90 and RMSE of 22.01 while ensuring high efficiency. There was no statistical difference between the average scores given by two experienced radiologists and predicted scores from our model. (shrink)

This essay develops an account of health, the functional efficiency theory, which derives from Christopher Boorse's biostatistical theory. Like the BST, the functional efficiency theory is a nonevaluative view of health, but unlike the BST, it argues that the fundamental theoretical task is to distinguish levels of efficiency with which the parts and processes within organisms and within systems within organisms function. Which of these to label as healthy or pathological is of secondary importance. Because the (...) class='Hi'>statistical distributions that Boorse's account relies on are distributions of functional efficiency, the functional efficiency theory arguably complements rather than challenges the BST. (shrink)

This article provides a framework for comparing meritocratic and affirmative action admissions policies. The context of the analysis is admissions to public universities; admission rules are evaluated as part of the public investment problem faced by a state government. Meritocratic and affirmative admissions policies are compared in terms of their effects on the level and distribution of human capital. I argue that (a) meritocratic admissions are not necessarily efficient and (b) affirmative action policies may be efficiency enhancing relative to (...) meritocratic ones. Both these claims, as well as their negations, depend on features of individual behavior for which there is little empirical evidence. The implications of this absence of evidence are then explored, with a focus on policy evaluation when equality and efficiency are both desiderata. I argue that standard statistical decision theoretic approaches do not apply to the affirmative action case, even if equality and efficiency are rendered commensurable based on a scalar payoff function. In this context, I suggest that a presumption for equality-enhancing policies leads to support for affirmative action, but I emphasize the contingent nature of this conclusion. Key Words: affirmative action • meritocracy • college admissions • efficiency. (shrink)

This essay argues that what is central to Christopher Boorse’s biostatistical theory of disease as statistically subnormal part function (BST) are comparisons of the “functional efficiency” of parts and processes and that statistical considerations serve only to pick out a healthy level of functional efficiency. On this interpretation, the distinction between health and pathology is less important than comparisons of functional efficiency, which are entirely independent of statistical considerations. The clarifications or revisions of the BST (...) that this essay offers are friendly amendments that render moot some of the most prominent criticisms of Boorse’s account. (shrink)

We model happiness as a measurement tool used to rank alternative actions. Evolution favors a happiness function that measures the individual’s success in relative terms. The optimal function, in particular, is based on a time-varying reference point –or performance benchmark –that is updated over time in a statistically optimal way in order to match the individual’s potential. Habits and peer comparisons arise as special cases of such updating process. This updating also results in a volatile level of happiness that continuously (...) reverts to its long-term mean. Throughout, we draw a parallel with a problem of optimal incentives, which allows us to apply statistical insights from agency theory to the study of happiness. (shrink)

In order to extract the regularities underlying a continuous sensory input, the individual elements constituting the stream have to be encoded and their transitional probabilities (TPs) should be learned. This suggests that variance in statistical learning (SL) performance reflects efficiency in encoding representations as well as efficiency in detecting their statistical properties. These processes have been taken to be independent and temporally modular, where first, elements in the stream are encoded into internal representations, and then the (...) co‐occurrences between them are computed and registered. Here, we entertain a novel hypothesis that one unifying construct—the rate of information in the sensory input—explains learning performance. This theoretical approach merges processes related to encoding of events and those related to learning their regularities into a single computational principle. We present data from two large‐scale experiments with over 800 participants tested in support for this hypothesis, showing that rate of information in a visual stream clearly predicts SL performance, and that similar rate of information values leads to similar SL performance. We discuss the implications for SL theory and its relation to regularity learning. (shrink)

This article explores the intersection of philosophy and statistics by examining the philosophical assumptions underlying modern mathematical statistics from ontological and epistemological perspectives. Statistics holds interest for philosophers engaged with the problem of induction, as its mathematical apparatus serves as models for philosophical ideas. For instance, the much-discussed concepts of the uniformity of nature and natural kinds correspond to probability models and statistical models, which are fundamental to various statistical methods. Similarly, Dennett’s concept of a real pattern echoes (...) the spirit of various information criteria (such as AIC) used to determine the optimal level of complexity for maximizing a model’s predictive ability. Furthermore, the recent developments in machine learning models, such as deep learning, imply that these machines possess their own 'ontology,' which is potentially more complex and efficient at understanding the world than ours. This leads to a Quinean problem of radical translation between human and machine ontologies. We suggest that this issue is key to the successful application of AI technologies in our society. The other focus of this article is epistemology, where Bayesian and classical statistics are compared to internalist and externalist epistemologies, respectively. This comparison elucidates how and in what sense the statistical methods adopted in each camp are considered to justify scientific hypotheses and also sheds light on their epistemic problems. We conclude with a plea for more research and interdisciplinary dialogues between statistics and the philosophy of various traditions. (shrink)

The efficient coding hypothesis posits that sensory systems are tuned to the regularities of their natural input. The statistics of natural image databases have been the topic of many studies, which have revealed biases in the distribution of orientations that are related to neural representations as well as behavior in psychophysical tasks. However, commonly used natural image databases contain images taken with a camera with a planar image sensor and limited field of view. Thus, these images do not incorporate the (...) physical properties of the visual system and its active use reflecting body and eye movements. Here, we investigate quantitatively, whether the active use of the visual system influences image statistics across the visual field by simulating visual behaviors in an avatar in a naturalistic virtual environment. Images with a field of view of 120° were generated during exploration of a virtual forest environment both for a human and cat avatar. The physical properties of the visual system were taken into account by projecting the images onto idealized retinas according to models of the eyes' geometrical optics. Crucially, different active gaze behaviors were simulated to obtain image ensembles that allow investigating the consequences of active visual behaviors on the statistics of the input to the visual system. In the central visual field, the statistics of the virtual images matched photographic images regarding their power spectra and a bias in edge orientations toward cardinal directions. At larger eccentricities, the cardinal bias was superimposed with a gradually increasing radial bias. The strength of this effect depends on the active visual behavior and the physical properties of the eye. There were also significant differences between the upper and lower visual field, which became stronger depending on how the environment was actively sampled. Taken together, the results show that quantitatively relating natural image statistics to neural representations and psychophysical behavior requires not only to take the structure of the environment into account, but also the physical properties of the visual system, and its active use in behavior. (shrink)

In order to deal with high-dimensional distributed data, this article develops a novel and communication-efficient approach for sparse and high-dimensional data with the penalized quantile regression. In each round, the proposed method only requires the master machine to deal with a sparse penalized quantile regression which could be realized fastly by proximal alternating direction method of multipliers algorithm and the other worker machines to compute the subgradient on local data. The advantage of the proximal ADMM algorithm is that it could (...) make every parameter of iteration to have closed formula even in high-dimensional case, which greatly improves the speed of calculation. As for the communication efficiency, the proposed method does not sacrifice any statistical accuracy and provably improves the estimation error obtained by centralized method, provided the penalty levels are chosen properly. Moreover, the asymptotic properties of the proposed estimation and the convergence of the algorithm are convincible. Especially, it presents extensive experiments on both the numerical simulations and the HIV drug resistance data analysis, which all confirm the significant efficiency of our proposed method in quantile regression for distributed data by comparative and empirical analysis. (shrink)

The Condorcet efficiency of a social choice procedure is usually defined as the probability that this procedure coincides with the majority winner (or majority ordering) in random samples, given a majority winner exists (or given the majority ordering is transitive). Consequently, it is in effect a conditional probability that two sample statistics coincide, given certain side conditions. We raise a different issue of Condorcet efficiencies: What is the probability that a social choice procedure applied to a sample matches with (...) the majority preferences of the population from which the sample was drawn? We investigate the canonical case where the sample statistic is itself also majority rule and the samples are drawn from real world distributions gathered from national election surveys in Germany, France, and the United States. We relate the results to the existing literature on majority cycles and social homogeneity. We find that these samples rarely display majority cycles, whereas the probability that a sample misrepresents the majority preferences of the underlying population varies dramatically and always exceeds the probability that the sample displays cyclic majority preferences. Social homogeneity plays a fundamental role in the type of Condorcet efficiency investigated here. (shrink)

This paper presents the progicnet programme. It proposes a general framework for probabilistic logic that can guide inference based on both logical and probabilistic input. After an introduction to the framework as such, it is illustrated by means of a toy example from psychometrics. It is shown that the framework can accommodate a number of approaches to probabilistic reasoning: Bayesian statistical inference, evidential probability, probabilistic argumentation, and objective Bayesianism. The framework thus provides insight into the relations between these approaches, (...) it illustrates how the results of different approaches can be combined, and it provides a basis for doing efficient inference in each of the approaches. (shrink)

A central problem in the cognitive sciences is identifying the link between consciousness and neural computation. The key features of consciousness—including the emergence of representative information content and the initiation of volitional action—are correlated with neural activity in the cerebral cortex, but not computational processes in spinal reflex circuits or classical computing architecture. To take a new approach toward considering the problem of consciousness, it may be worth re‐examining some outstanding puzzles in neuroscience, focusing on differences between the cerebral cortex (...) and spinal reflex circuits. First, the mammalian cerebral cortex exhibits exascale computational power, a feature that is not strictly correlated with the number of binary computational units; second, individual computational units engage in noisy coding, allowing random electrical events to gate signaling outcomes; third, this noisy coding results in the synchronous firing of statistically random populations of cells across the neural network, at a range of nested frequencies; fourth, the system grows into a more ordered state over time, as it encodes the predictive value gained through observation; and finally, the cerebral cortex is extraordinarily energy efficient, with very little free energy lost to entropy during the work of information processing. Here, I argue that each of these five key features suggest the mammalian brain engages in probabilistic computation. Indeed, by modeling the physical mechanisms of probabilistic computation, we may find a better way to explain the unique emergent features arising from cortical neural networks. (shrink)

Humans can seamlessly infer other people's preferences, based on what they do. Broadly, two types of accounts have been proposed to explain different aspects of this ability. The first account focuses on spatial information: Agents' efficient navigation in space reveals what they like. The second account focuses on statistical information: Uncommon choices reveal stronger preferences. Together, these two lines of research suggest that we have two distinct capacities for inferring preferences. Here we propose that this is not the case, (...) and that spatial-based and statistical-based preference inferences can be explained by the assumption that agents are efficient alone. We show that people's sensitivity to spatial and statistical information when they infer preferences is best predicted by a computational model of the principle of efficiency, and that this model outperforms dual-system models, even when the latter are fit to participant judgments. Our results suggest that, as adults, a unified understanding of agency under the principle of efficiency underlies our ability to infer preferences. (shrink)

Industry sustainability plays a vital role in shaping the environment for cultural and creative business development. However, considering the influence of the external environment and random factors on the technical efficiency of cultural and creative industries with the inherent defects of the traditional data envelopment analysis model; this manuscript analyzed the operating efficiency of 56 cultural and creative enterprises using the three-stage DEA model from 2012 to 2018. An analysis of the results shows that differences in efficiency (...) exist between stage one and stage three DEA. Furthermore, the environmental elements and statistical noise measured by the stochastic frontier analysis in stage two reveal positive and negative influences on the creative cultural enterprises at different stages. As a result, the overall efficiency of the listed cultural and creative industries was revealed to be low in China. Finally, this study suggested effective countermeasures and recommendations for better-operating efficiency systems for cultural and creative enterprises. (shrink)

Undoubtedly, the internet has become the most convenient and efficient communication and service delivery channel adopted by most government agencies, referred to as eGovernment. This study explores how eGovernment efficiency influences users’ subjective wellbeing, using trust as a covert stimulus with the capacity to alter individuals’ overt behavior. Covert and overt stimuli act as significant factors influencing the relationship between citizens and the online environment, moderated by socio-demographic characteristics. Using situation–organism–behavior–consequence theory, we propose a research model consisting of online (...) environment eGovernment efficiency influencing trust development, which in turn influences utilization, generating an impact on an individuals’ SWB. We followed the structural equation modeling approach to analyze the data survey N = 300, using Amos statistical techniques. Results reveal that the correlation between eGovernment efficiency and trust is positive and strong, trust and utilization is positive and moderate, and the correlation between utilization and SWB is positive and very strong. Stepwise regression analysis reveals that the control variables affect the relationship between eGovernment efficiency and trust. In the regression model: the highest education level explained 36% of the variance ; adding age increased the variance explained to 39%, and adding internet use frequency increased the variance explained to 41%. This study develops theoretical concepts of eGovernment use and how it affects citizens by indicating the psychological and behavioral situations as antecedents and mediators influencing SWB. It also provides practical suggestions for improving systems to correlate users’ feelings and behavior patterns to motivate trusting behavior, positively impacting users’ SWB to benefit citizens effectively. (shrink)

Soon after the first COVID-19 positive case was detected in Wuhan, China, the virus spread around the globe, and in no time, it was declared as a global pandemic by the WHO. Testing, which is the first step in identifying and diagnosing COVID-19, became the first need of the masses. Therefore, testing kits for COVID-19 were manufactured for efficiently detecting COVID-19. However, due to limited resources in the densely populated countries, testing capacity even after a year is still a limiting (...) factor for COVID-19 diagnosis on a larger scale and contributes to a lag in disease tracking and containment. Due to this reason, we started this study to provide a better cost-effective solution for enhancing the testing capacity so that the maximum number of people could get tested for COVID-19. For this purpose, we utilized the approach of artificial neural networks (ANN) to acquire the relevant data on COVID-19 and its testing. The data were analyzed by using Machine Learning, and probabilistic algorithms were applied to obtain a statistically proven solution for COVID-19 testing. The results obtained through ANN indicated that sample pooling is not only an effective way but also regarded as a “Gold standard” for testing samples when the prevalence of the disease is low in the population and the chances of getting a positive result are less. We further demonstrated through algorithms that pooling samples from 16 individuals is better than pooling samples of 8 individuals when there is a high likelihood of getting negative test results. These findings provide ground to the fact that if sample pooling will be employed on a larger scale, testing capacity will be considerably increased within limited available resources without compromising the test specificity. It will provide healthcare units and enterprises with solutions through scientifically proven algorithms, thus, saving a considerable amount of time and finances. This will eventually help in containing the spread of the pandemic in densely populated areas including vulnerably confined groups, such as nursing homes, hospitals, cruise ships, and military ships. (shrink)

Infants have been described as 'statistical learners' capable of extracting structure (such as words) from patterned input (such as language). Here, we investigated whether prior knowledge influences how infants track transitional probabilities in word segmentation tasks. Are infants biased by prior experience when engaging in sequential statistical learning? In a laboratory simulation of learning across time, we exposed 9- and 10-month-old infants to a list of either disyllabic or trisyllabic nonsense words, followed by a pause-free speech stream composed (...) of a different set of disyllabic or trisyllabic nonsense words. Listening times revealed successful segmentation of words from fluent speech only when words were uniformly disyllabic or trisyllabic throughout both phases of the experiment. Hearing trisyllabic words during the pre-exposure phase derailed infants' abilities to segment speech into disyllabic words, and vice versa. We conclude that prior knowledge about word length equips infants with perceptual expectations that facilitate efficient processing of subsequent language input. (shrink)

Does the level of marketing activity in a country contribute to societal well-being or quality of life? Does economic efficiency also play a positive role in societal well-being? Does economic efficiency also moderate or mediate the marketing activity effect on societal well-being? Marketing activity refers to the pervasiveness of promotion expenditures and number of retail outlets per capita in a country. Economic efficiency refers to the extent to which the economy is unhampered by corruption, burdensome government regulation, (...) and a large informal economy. We used secondary data from the World Bank and other statistical sources to answer these questions. Our study findings suggest that both marketing activity and economic efficiency contribute positively to societal well-being, and that economic efficiency plays more of a mediator than moderator role between marketing activity and societal well-being. The public policy implication of this study is that increases in marketing activity and economic efficiency in countries characterized as low on both dimensions should significantly increase the quality of life in those countries. (shrink)

Humans have the ability to learn surprisingly complicated statistical information in a variety of modalities and situations, often based on relatively little input. These statistical learning (SL) skills appear to underlie many kinds of learning, but despite their ubiquity, we still do not fully understand precisely what SL is and what individual differences on SL tasks reflect. Here, we present experimental work suggesting that at least some individual differences arise from stimulus-specific variation in perceptual fluency: the ability to (...) rapidly or efficiently code and remember the stimuli that SL occurs over. Experiment 1 demonstrates that participants show improved SL when the stimuli are simple and familiar; Experiment 2 shows that this improvement is not evident for simple but unfamiliar stimuli; and Experiment 3 shows that for the same stimuli (Chinese characters), SL is higher for people who are familiar with them (Chinese speakers) than those who are not (English speakers matched on age and education level). Overall, our findings indicate that performance on a standard SL task varies substantially within the same (visual) modality as a function of whether the stimuli involved are familiar or not, independent of stimulus complexity. Moreover, test–retest correlations of performance in an SL task using stimuli of the same level of familiarity (but distinct items) are stronger than correlations across the same task with stimuli of different levels of familiarity. Finally, we demonstrate that SL performance is predicted by an independent measure of stimulus-specific perceptual fluency that contains no SL component at all. Our results suggest that a key component of SL performance may be related to stimulus-specific processing and familiarity. (shrink)

The study aimed to identify E- Learning strategies and their relation to the efficiency of research performance in foreign and Palestinian universities (University of Ottawa, Munster, Suez Canal, Al-Azhar, Islamic, Al-Aqsa). The analytical descriptive approach was used for this purpose, and relying on the questionnaire as a main tool for data collection. The study society is from the senior management, where the number of senior management in the universities in question is 206. The random stratified sample was selected and (...) (SPSS) was used for statistical data analysis. The study found a significant relationship between E- Learning strategies and the efficiency of research performance in universities. It also reached the participation of senior management in the research that develops the university performance in the Palestinian universities. The senior management indicated that they do not care to follow the policies of implementing the development of scientific research. While the senior management in foreign universities indicated that they are interested in following up the policies of implementing the development of scientific research. The study also showed that senior management in Palestinian universities does not care about providing the appropriate budget for E- Learning. The study recommended that the senior management of Palestinian universities should provide an E- Learning budget and encourage employees to continue using E- Learning strategies. The administration in the Palestinian universities should adopt and support outstanding research, and the need to encourage interest in the implementation of policies for the development of scientific research. (shrink)

This paper considers the problem of causal explanation in classical and statistical thermodynamics. It is argued that the irreversibility of macroscopic processes is explained in both formulations of thermodynamics in a teleological way that appeals to entropic or probabilistic consequences rather than to efficient-causal, antecedental conditions. This explanatory structure of thermodynamics is not taken to imply a teleological orientation to macroscopic processes themselves, but to reflect simply the epistemological limitations of this science, wherein consequences of heat-work asymmetries are either (...) macroscopically measurable (entropy) or calculable (probabilities), while efficient-causal relationships are obscure or indeterminable. (shrink)

This study came to complete the role that previous researchers began by focusing on strategic planning and linking it to an effective school administration in secondary public schools in Saudi Arabia to reach results and recommendations that may benefit principals, supervisors, and workers in the field of education. The study used the descriptive analytical approach and developed a questionnaire as an instrument, which was administered to 122 school principals from public schools in Saudi Arabia. The results concluded that the five (...) areas each received a very high relative weight, and this reinforces the importance of school principals using strategic planning in their schools because of its great benefit in increasing the effectiveness of school administration. The findings showed no statistically significant differences between the averages of the study sample’s estimates on the role of strategic planning in increasing the effectiveness of school administration due to years of experience, as all school principals need strategic planning because of its importance and because of its novelty, which limits the number of years of service. (shrink)

With the rise of the so-called military-entertainment complex, critical scholars note with alarm the integration of the political economies of entertainment companies and the military, in particular its potential influence on millions of young people who consume its concomitant films, toys and especially video games. Seen from a broad perspective, a potentially productive means of understanding the complexities of this sphere is through the lens of Michel Foucault’s notion of governmentality—a concept that ties together the actions and preferred outcomes of (...) the modern surveillance state with the microlevel actions of individual behavior. In this analytical framework, social norms are inculcated through subtle forms of coercion, where the state establishes the field of action in which state subjects ultimately perform self-discipline. This article argues that the first person shooter genre inculcates what I refer to as the governmentality of battlefield space: a form of discipline in which players adhere to gamic norms of performance—efficiency, proficiency, and masculine performativity—which are delineated by ludic structures and largely understood on terms which originate within the social ecology of gaming. The genre accomplishes this though disciplinary techniques such as informational verisimilitude, statistics, and masculinized “gamer” discourse, particularly during multiplayer instances, in which players constitute social understandings of what is “good” and “bad” play. It is on these terms that virtual combat performance and player performance become conflated in a kind of masculinized performance, which both adheres to and undermines traditional, hegemonic norms of (Western) military masculinity. This phenomenon transcends local social realities, and highlights the ways in which particular aspects of gaming and combat appear to have increasingly overlapping phenomenological and ontological qualities, working to produce a form of self-performance that may be required of tomorrow’s soldiers. (shrink)

Exploring how people represent natural categories is a key step toward developing a better understanding of how people learn, form memories, and make decisions. Much research on categorization has focused on artificial categories that are created in the laboratory, since studying natural categories defined on high-dimensional stimuli such as images is methodologically challenging. Recent work has produced methods for identifying these representations from observed behavior, such as reverse correlation (RC). We compare RC against an alternative method for inferring the structure (...) of natural categories called Markov chain Monte Carlo with People (MCMCP). Based on an algorithm used in computer science and statistics, MCMCP provides a way to sample from the set of stimuli associated with a natural category. We apply MCMCP and RC to the problem of recovering natural categories that correspond to two kinds of facial affect (happy and sad) from realistic images of faces. Our results show that MCMCP requires fewer trials to obtain a higher quality estimate of people’s mental representations of these two categories. (shrink)

The usage of new and progressive technologies brings with it new types of security threats and security incidents. Their number is constantly growing.The current trend is to move from reactive to proactive activities. For this reason, the organization should be aware of the current security situation, including the forecasting of the future state. The main goal of organizations, especially their security operation centres, is to handle events, identify potential security incidents, and effectively forecast the network security situation awareness (NSSA). In (...) this paper, we focus on increasing the efficiency of utilization of this part of cybersecurity. The paper’s main aim is to compare selected statistical models and models based on neural networks to find out which models are more suitable for NSSA forecasting. Based on the analysis provided in this paper, neural network methods prove a more accurate alternative than classical statistical prediction models in NSSA forecasting. In addition, the paper analyses the selection criteria and suitability of time series, which do not only reflect information about the total number of security events but represent a category of security event (e.g. recon scanning), port or protocol. (shrink)

Sentence boundary detection (SBD) represents an important first step in natural language processing since accurately identifying sentence boundaries significantly impacts downstream applications. Nevertheless, detecting sentence boundaries within legal texts poses a unique and challenging problem due to their distinct structural and linguistic features. Our approach utilizes deep learning models to leverage delimiter and surrounding context information as input, enabling precise detection of sentence boundaries in English legal texts. We evaluate various deep learning models, including domain-specific transformer models like LegalBERT and (...) CaseLawBERT. To assess the efficacy of our deep learning models, we compare them with a state-of-the-art domain-specific statistical conditional random field (CRF) model. After considering model size, F1-score, and inference time, we identify the Convolutional Neural Network Model (CNN) as the top-performing deep learning model. To further enhance performance, we integrate the features of the CNN model into the subsequent CRF model, creating a hybrid architecture that combines the strengths of both models. Our experiments demonstrate that the hybrid model outperforms the baseline model, achieving a 4% improvement in the F1-score. Additional experiments showcase the superiority of the hybrid model over SBD open-source libraries when confronted with an out-of-domain test set. These findings underscore the importance of efficient SBD in legal texts and emphasize the advantages of employing deep learning models and hybrid architectures to achieve optimal performance. (shrink)

Using a laboratory experiment, we examine whether voluntary sanctions induce subjects to coordinate more efficiently in a repeated minimum-effort game. While most groups first experience Pareto inferior coordination in a baseline treatment, the level of effort increases substantially once ex post sanctioning opportunities are introduced, that is, when one can assign costly punishment points to other group members to reduce their payoffs. We compare the effect of this voluntary punishment possibility with the effect of ex post costless communication, which in (...) contrast to the punishment treatment increases efforts only temporarily and fails to bring the players to higher payoff equilibria permanently. Our results indicate that decentralized sanctions can play an important role as a coordination device in Pareto-ranked coordination settings. They also suggest that the motivations behind voluntary sanctions may be more general than usually put forth in the literature on cooperation games. (shrink)

The predominant trends in the European prison system are population growth and overcrowding of correctional facilities. Recently, the level of criminal offences in Lithuania has been gradually increasing. Current statistics on repeated criminal offences and forecasts of recidivating crime are also pessimistic. The large number of convicts, the negative impact of isolation, the absence of a progressive correction system, the inadequacy of existing correctional measures, and the largely formal activity of penal institutions exacerbate the problems of ineffective resocialization of convicts (...) and resulting recidivism. Thus, the situation demands an examination of effective methods for the elimination of the above detriments. The article emphasizes the need for an essential modernization of the system of resocialization of convicts in Lithuania by transforming formal measures into real ones directed at the reform of behaviour and thinking. The article discusses new corrective measures widely used across the European Union and other countries, such as evaluation of individual risk for repeated criminal offence and implementation of appropriate behaviour-correction programmes on the basis of clearly defined criteria of effectiveness. Unfortunately such measures have not been implemented in Lithuania, either de jure or de facto. (shrink)

The paper provides a formal proof that efficient estimates of parameters, which vary as as little as possible when measurements are repeated, may be expected to provide more accurate predictions. The definition of predictive accuracy is motivated by the work of Akaike (1973). Surprisingly, the same explanation provides a novel solution for a well known problem for standard theories of scientific confirmation — the Ravens Paradox. This is significant in light of the fact that standard Bayesian analyses of the paradox (...) fail to account for the predictive utility of universal laws like All ravens are black. (shrink)

This paper proposes a nonlinear autoregressive neural network method for the investment performance evaluation of state-owned enterprises. It is different from the traditional method based on machine learning, such as linear regression, structural equation, clustering, and principal component analysis; this paper uses a regression prediction method to analyze investment efficiency. In this paper, we firstly analyze the relationship between diversified ownership reform, corporate debt leverage, and the investment efficiency of state-owned enterprises. Secondly, a set of investment efficiency (...) evaluation index system for SOE was constructed, and a nonlinear autoregressive neural network approach was used for verification. The data of A-share state-owned listed companies in Shanghai and Shenzhen stock exchanges from 2009 to 2018 are taken as a sample. The experimental results show that the output value from the NARNET is highly fitted to the actual data. Based on the neural network model regression analysis, this paper conducts a descriptive statistical analysis of the main variables and control variables of the evaluation indicators. It verifies the direct impact of diversified ownership reform on the investment efficiency of SOE and the indirect impact on the investment efficiency of SOE through corporate debt leverage. (shrink)

Nelson Goodman's new riddle of induction forcefully illustrates a challenge that must be confronted by any adequate theory of inductive inference: provide some basis for choosing among alternative hypotheses that fit past data but make divergent predictions. One response to this challenge is to distinguish among alternatives by means of some epistemically significant characteristic beyond fit with the data. Statistical learning theory takes this approach by showing how a concept similar to Popper's notion of degrees of testability is linked (...) to minimizing expected predictive error. In contrast, formal learning theory appeals to Ockham's razor, which it justifies by reference to the goal of enhancing efficient convergence to the truth. In this essay, I show that, despite their differences, statistical and formal learning theory yield precisely the same result for a class of inductive problems that I call strongly VC ordered, of which Goodman's riddle is just one example. (shrink)

Objective: Clock variance is an important statistic in many clinical and developmental studies. Existing methods require a large number of trials for accurate clock variability assessment, which is problematic in studies using clinical or either young or aged participants. Furthermore, these existing methods often implicitly convolute clock and memory processes, making it difficult to disentangle whether the clock or memory system are driving the observed deviations. Here we assessed whether twenty repeated productions of a well-engrained interval (1 second), a task (...) that does not incorporate memory updating nor the processing of feedback, could provide an accurate assessment of clock variability. Method: Sixty-eight undergraduate students completed two tasks: a 1-second production task in which they were asked to produce a 1-second duration by ending a tone by a keypress, and a multi-duration reproduction task. Durations presented in the reproduction task were tones lasting 1.17, 1.4 and 1.68 seconds. No feedback was presented in either task, and the order of presentation was counterbalanced between participants. Results: The observed central tendency in the reproduction task was better explained by models including the measures of clock variability derived from the 1-second production task than by models without it. Three clock variability measures were calculated for each participant (standard deviation, root mean squared residuals (RMSR) from an estimated linear slope, and RMSR scaled by mean production duration). The model including the scaled RMSR was prefered over the alternative models, and no notable effects of the order of presentation were observed. These results suggest that (1) measures of variability should account for drift, (2) the presentation of another timing task before a 1-second production task did not influence the assessment of the clock variability, and (3) the observed variability adheres to the scalar property and predicts temporal performance, and is thus a usable index of clock variability. Conclusion: This study shows that just 20 repeated productions of 1 second provide a reliable index of clock variability. As administering this task is fast and easy, it could prove to be useful in a large variety of developmental and clinical populations. (shrink)

A current issue in psycholinguistic research is whether the language difficulties exhibited by children with developmental language disorder [DLD, previously labeled specific language impairment ] are due to deficits in their abilities to pick up patterns in the sensory environment, an ability known as statistical learning, and the extent to which explicit learning mechanisms can be used to compensate for those deficits. Studies designed to test the compensatory role of explicit learning mechanisms in children with DLD are, however, scarce, (...) and the few conducted so far have led to inconsistent results. This work aimed to provide new insights into the role that explicit learning mechanisms might play on implicit learning deficits in children with DLD by resorting to a new approach. This approach involved not only the collection of event-related potentials, while preschool children with DLD [relative to typical language developmental controls] were exposed to a continuous auditory stream made of the repetition of three-syllable nonsense words but, importantly, the collection of ERPs when the same children performed analogous versions of the same auditory SL task first under incidental and afterward under intentional conditions. In each of these tasks, the level of predictability of the three-syllable nonsense words embedded in the speech streams was also manipulated to mimic natural languages closely. At the end of both tasks’ exposure phase, children performed a two-alternative forced-choice task from which behavioral evidence of SL was obtained. Results from the 2-AFC tasks failed to show reliable signs of SL in both groups of children. The ERPs data showed, however, significant modulations in the N100 and N400 components, taken as neural signatures of word segmentation in the brain, even though a detailed analysis of the neural responses revealed that only children from the TLD group seem to have taken advantage of the previous knowledge to enhance SL functioning. These results suggest that children with DLD showed deficits both in implicit and explicit learning mechanisms, casting doubts on the efficiency of the interventions relying on explicit instructions to help children with DLD to overcome their language difficulties. (shrink)

This article argues that actual entities come first; the statistical laws of nature are their effects, not their causes. Statistical laws are mentally abstracted from their habits and are only formal, not efficient, causes. They do not make anything happen or prevent anything from happening. They evolve or change as the habits of novel creatures evolve or change. They do not control or inform us about what any individual entity is doing, only about what masses of individuals on (...) average are doing. Thus, there is no way that traditional divine miracles could “violate” them. God has sufficient efficient-causal power to create our world ex nihilo, as in the Big Bang, and to prevent evils, which God does not do from love, justice, and moral goodness. Seven elements of a viable theodicy are outlined, the most important of which is divine justice. It would be unjust for God to prevent harms in some cases but not in all. In a universe in which God prevents all evils and thus directly controls everything, no creatures would take any responsibility for what they do. A loving and just God voluntarily and consistently limits the exercise of divine power so we can be free, responsible, and creative. (shrink)

Advocates of EBM deserve much credit for theirefforts to increase the use of scientificevidence and economic evaluation in medicaldecision making. But EBM advocates' rigidrequirements of certainty in the estimation ofintervention effects may run counter tosociety's interest in maximising the expectedbenefits from resource use in health care.Also, their dedication to efficiency may leadsome to overlook societal concerns for fairnessin resource allocation.

This article uses the “Green Credit Guidelines” issued in 2012 as a quasi-natural experiment, using the statistics of A-share listed companies from 2008 to 2017, using the PSM-DID model to examine the effect and mechanism of green credit policies on the investment efficiency of heavily polluting companies, and taking into consideration the heterogeneous influence of the financial ecological environment on the relationship between the two. The research indicates that, after the Green Credit Guidelines were promulgated, the investment efficiency (...) of heavy-polluting companies has been slightly improved compared with non-heavy-polluting companies and that the impact is more obvious in regions with better financial ecological environment. The research conclusions confirm the beneficial effects of the Green Credit Guidelines policy on the prudent investment of companies that cause serious pollution to the environment and improve investment efficiency, a provision of empirical evidence for financial leverage to drive the green economy transformation. (shrink)

Based on the review and research on the teleworking modality and the variables that impact it at the organizational level, such as quality of life, communication, organizational culture or productivity, a case study is proposed under the innovation and teleworking model of a company. Japanese automotive industry for the application of Multivariate Analysis techniques such as Principal Component Analysis and Linear Regression, in order to condense the information provided by multiple variables into principal components and validate the relationships and impact (...) that exist between them, thus determining the interdependence and correlation of the same with the telework variable, allowing to simplify the complexity of sample spaces with many dimensions. It was possible to identify the main components with the variables' own labels and the dependent and predictive variables of the case were statistically validated, through the use of the IBM SPSS. (shrink)

This essay demonstrates a previously unnoticed connection between formal and statistical learning theory with regard to Nelson Goodman’s new riddle of induction. Discussions of Goodman’s riddle in formal learning theory explain how conjecturing “all green” before “all grue” can enhance efficient convergence to the truth, where efficiency is understood in terms of minimizing the maximum number of retractions or “mind changes.” Vapnik-Chervonenkis (VC) dimension is a central concept in statistical learning theory and is similar to Popper’s notion (...) of degrees of testability. I show that for a class inductive problems of which Goodman’s riddle is one example, a reliable inductive method minimizes the maximum number of mind changes exactly if it always conjectures the hypothesis from the set with lowest VC dimension consistent with the data. I also discuss the relevance of these results to language invariance and curve fitting. (shrink)

Introduction. Improving control and supervisory activities on the basis of introducing risk-oriented approaches is an urgent area of public administration reforms both in Russia and abroad. Traditionally, assessing the effectiveness of this area is carried out on the basis of the state control intensity indicators (the number of inspections), and assessing risks in controlled areas is carried out on the basis of statistical indicators, partially dependent on state control bodies. To obtain a balanced assessment of the state control effectiveness (...) and efficiency, it is important to take into account other data sources reflecting the citizens’ and the business community position. The purpose of the study is to conduct a comprehensive assessment of the effectiveness and efficiency of sanitary and epidemiological surveillance on the basis of both statistical data and the results of sociological studies reflecting the position of citizens and business. Methods. The authors suggest their own methods for comprehensive assessment of the effectiveness and efficiency of state control. The scientific novelty of the study consists in a comprehensive assessment of the effectiveness and efficiency of sanitary and epidemiological surveillance, taking into account various data sources and making it possible to assess the progress of implementing the reform of state control in this area. Results. The results of the study indicate, in general, an increase in the effectiveness and budgetary efficiency of sanitary and epidemiological surveillance over the last years of the reform implementation. At the same time, at the level of intermediate and immediate results, there are multidirectional trends, and the growth in the total costs of business and the state is ahead of the growth in the results achieved. Conclusions. The use of the authors’ comprehensive methodology for assessing the effectiveness and efficiency of state control makes it possible to obtain reliable data characterizing the actual state of things in the area under consideration. Further improving the efficiency and effectiveness of sanitary and epidemiological surveillance requires expanding the scope of applying risk-oriented approaches and improving the quality of considering the appeals of the citizens who faced with risks of wrongdoing. (shrink)

Addressing fatigue is useful in a variety of scenarios and activities. Fatigue has recently been studied from a psychophysiological standpoint. As a result, the expression and impact of peripheral and central fatigue has been evaluated. Driving is one occupation where tiredness has disastrous consequences. BAlert is a smartphone app that approaches exhaustion with psychophysiological measures. More specifically, it evaluates the level of fatigue via heart rate variability data and the cognitive compromise via Stroop effect. The goal of this study is (...) to determine if there are gender differences in fatigue levels among professional drivers using the BAlert app. Statistically significant differences were found in the number of hours awake, in different parameters of HRV, in the level of stress, as well as in the cognitive response evaluated through the app. The results are discussed and their implications for the management of work fatigue are presented. (shrink)

Charles Murray describes himself as a libertarian, most notably in his short book, What it Means to be a Libertarian. He might more accurately have described himself as having libertarian tendencies. My reading of Simple Justice is that the views it espouses are far more traditionalist than libertarian. Neither traditionalist state-retribution nor modernist state-leniency is libertarian. Nor does either provide as just or efficient a response to crime as does libertarian restitution, including restitutive retribution. Here, I shall respond directly only (...) to Murray's views, rather than also deal with state-leniency. This is because I accept Murray's thesis, without endorsing his specific arguments for it, that state-leniency is disastrous as a response to crimes against persons and their justly acquired property. (shrink)

Discounting is a manifestation of behavioral impulsivity, which is closely related to self-regulation processes. The decision-making process for intertemporal choices is governed by the inhibition of impulses, which can influence both risk and time-related attitudes. This paper utilizes self-reported measures of risk, impatience, and impulsivity attitudes to examine their impact on the implicit discount rate used when weighing the current purchase cost against future energy savings of appliances. It analyzes and tests the interplay between these attitudes using specific functional forms (...) and causal models. The results highlight the role of risk, impatience and impulsivity on the discount rate and the biases that arise from omitting impulsive attitudes. In addition, other factors such as environmental and social preferences, attitudes, and financial constraints contribute to the implicit discount rate. (shrink)

BACKGROUND: There is growing interest in the ethics of cluster trials, but no literature on the uncertainties in defining communities in relation to the scientific notion of the cluster in collaborative biomedical research. METHODS: The views of participants in a community-based cluster randomised trial (CRT) in Mumbai, India, were solicited regarding their understanding and views on community. We conducted two focus group discussions with local residents and 20 semi-structured interviews with different respondent groups. On average, ten participants took part in (...) each focus group, most of them women aged 18-55. We conducted semi-structured interviews with ten residents (nine women and one man) lasting approximately an hour each and seven individuals (five men and two women) identified by residents as local leaders or decision-makers. In addition, we interviewed two Municipal Corporators (locally elected government officials involved in urban planning and development) and one representative of a political party located in a slum community. RESULTS: Residents' sense of community largely matched the scientific notion of the cluster, defined by the investigators as a geographic area, but their perceived needs were not entirely met by the trial. CONCLUSION: We examined whether the possibility of a conceptual mismatch between 'clusters' and 'communities' is likely to have methodological implications for a study or to lead to potential social disharmony because of the research interventions, arguing that it is important to take social factors into account as well as statistical efficiency when choosing the size and type of clusters and designing a trial. One method of informing such a design would be to use existing forums for community engagement to explore individuals' primary sense of community or social group and, where possible, to fit clusters around them. (shrink)

In this paper, we propose the introduction of a neutrosophic chi-square-test for consistency, incorporating neutrosophic statistics. Our aim is to modify the existing chi-square -test for consistency in order to analyze imprecise data. We present a novel test statistic for the neutrosophic chi-square -test for consistency, which accounts for the uncertainties inherent in the data. To evaluate the performance of the proposed test, we compare it with the traditional chi-square -test for consistency based on classical statistics. By conducting a comparative (...) analysis, we assess the efficiency and effectiveness of our proposed neutrosophic chi-square-test for consistency. Furthermore, we illustrate the application of the proposed test through a numerical example, demonstrating how it can be utilized in practical scenarios. Through this implementation, we aim to provide empirical evidence of the improved performance of our proposed test when compared to the traditional chi-square-test for consistency based on classical statistics. We anticipate that the proposed neutrosophic chi-square-test for consistency will outperform its classical counterpart, offering enhanced accuracy and reliability when dealing with imprecise data. This advancement has the potential to contribute significantly to the field of statistical analysis, particularly in situations where data uncertainty and imprecision are prevalent. (shrink)