Assistive Device Art derives from the integration of Assistive Technology and Art, involving the mediation of sensorimotor functions and perception from both, psychophysical methods and conceptual mechanics of sensory embodiment. This paper describes the concept of ADA and its origins by observing the phenomena that surround the aesthetics of prosthesis-related art. It also analyzes one case study, the Echolocation Headphones, relating its provenience and performance to this new conceptual and psychophysical approach of tool design. This ADA tool is designed to (...) aid human echolocation. They facilitate the experience of sonic vision, as a way of reflecting and learning about the construct of our spatial perception. Echolocation Headphones are a pair of opaque goggles which disable the participant’s vision. This device emits a focused sound beam which activates the space with directional acoustic reflection, giving the user the ability to navigate and perceive space through audition. The directional properties of parametric sound provide the participant a focal echo, similar to the focal point of vision. This study analyzes the effectiveness of this wearable sensory extension for aiding auditory spatial location in three experiments; optimal sound type and distance for object location, perceptual resolution by just noticeable difference, and goal-directed spatial navigation for open pathway detection, all conducted at the Virtual Reality Lab of the University of Tsukuba, Japan. The Echolocation Headphones have been designed for a diverse participant base. They have both the potential to aid auditory spatial perception for the visually impaired and to train sighted individuals in gaining human echolocation abilities. Furthermore, this Assistive Device artwork instigates participants to contemplate on the plasticity of their sensorimotor architecture. (shrink)

Artificial Neural Networks have reached “grandmaster” and even “super-human” performance across a variety of games, from those involving perfect information, such as Go, to those involving imperfect information, such as “Starcraft”. Such technological developments from artificial intelligence (AI) labs have ushered concomitant applications across the world of business, where an “AI” brand-tag is quickly becoming ubiquitous. A corollary of such widespread commercial deployment is that when AI gets things wrong—an autonomous vehicle crashes, a chatbot exhibits “racist” behavior, automated credit-scoring processes (...) “discriminate” on gender, etc.—there are often significant financial, legal, and brand consequences, and the incident becomes major news. As Judea Pearl sees it, the underlying reason for such mistakes is that “... all the impressive achievements of deep learning amount to just curve fitting.” The key, as Pearl suggests, is to replace “reasoning by association” with “causal reasoning” —the ability to infer causes from observed phenomena. It is a point that was echoed by Gary Marcus and Ernest Davis in a recent piece for theNew York Times: “we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets—often using an approach known as ‘Deep Learning’—and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space, and causality.” In this paper, foregrounding what in 1949 Gilbert Ryle termed “a category mistake”, I will offer an alternative explanation for AI errors; it is not so much that AI machinery cannot “grasp” causality, but that AI machinery (qua computation) cannot understand anything at all. (shrink)

In the selection of job candidates who have the mental ability to become professional ATCOs, psychometric testing has been a ubiquitous activity in the ATM domain. To contribute to psychometric research in the ATM domain, we investigated the extent to which spatial orientation ability (SOA), as conceptualized in the spatial cognition and navigation literature, predicted air traffic conflict detection performance in a simulated free route airspace (FRA) environment. The implementation of free route airspace (FRA) over the past (...) few years, notably in Europe, have facilitated air traffic services by giving greater flexibility to aviation operators in planning and choosing preferred air routes that can lead to quicker arrivals. FRA offers enhanced system safety and efficiency, but these benefits can be outweighed by the introduction of air traffic conflicts that are geometrically more complex. Such conflicts can arise from increased number and distribution of conflict points, as well as from elevated uncertainty in aircraft maneuvering (for instance, during heading changes). Overall, these issues will make conflict detection more challenging for air traffic controllers (ATCOs). Consequently, there is a need to select ATCOs with suitably high levels of spatial orientation ability (SOA) to ensure flight safety under FRA implementation. In this study, we tested 20 participants who are eligible for ATCO job application, and found that response time-based performance on a newly developed, open access, computerized spatial orientation test (SOT) predicted time to loss of minimum separation (tLMS) performance on an air traffic conflict detection task (AT-CDT) we designed. We found this predictive relationship to be significant to a moderately large extent under scenarios with high air traffic density (raw regression coefficient = 0.58). Moreover, we demonstrated our AT-CDT as a valid test in terms of eliciting well-known mental workload and spatial learning effects. We explained these findings in light of similar or overlapping mental processes that were most likely activated optimally under task conditions featuring approximately equal numbers of outcome-relevant stimuli. We conclude by discussing the further application of the SOT to the selection of prospective ATCOs who can demonstrate high levels of conflict detection performance in FRA during training simulations. (shrink)

Recently, a number of experiments have emphasized the degree to which subjects fail to detect large changes in visual scenes. This finding, referred to as “change blindness,” is often considered surprising because many people have the intuition that such changes should be easy to detect. Levin, Momen, Drivdahl, and Simons documented this intuition by showing that the majority of subjects believe they would notice changes that are actually very rarely detected. Thus subjects exhibit a metacognitive error we refer to as (...) “change blindness blindness.” Here, we test whether CBB is caused by a misestimation of the perceptual experience associated with visual changes and show that it persists even when the pre- and postchange views are separated by long delays. In addition, subjects overestimate their change detection ability both when the relevant changes are illustrated by still pictures, and when they are illustrated using videos showing the changes occurring in real time. We conclude that CBB is a robust phenomenon that cannot be accounted for by failure to understand the specific perceptual experience associated with a change. (shrink)

Erich Neumann (1905-1960) was a student, close collaborator, and life-long friend of C. G. Jung's. He moved from Berlin to Palestine in 1934 where he endured WW11 with much distress. This provoked intense and depthful research into topics such as evil, consciousness, and creativity that would occupy his attention for the rest of his life- as well as challenge his friend's (Jung) thinking in many ways. His writings are still valuable and ever so pertinent for our understanding of human nature (...) and the changing developments that have resulted in "the eruption of the shadow and psychic chaos in today's world." (Jerome Bernstein) Eternal Echoes offers the reader an overview of Neumann's opus, which is large and multifaceted. Beginning with an introduction of Erich Neumann including a series of his active imagination watercolors, we see an intimate view into his internal process. The Jung-Neumann Correspondence examines evil as witnessed during WW11. The work Neumann focused on during this period resulted in his exploration of his own Roots of Jewish Consciousness, both Revelation and Apocalypse, and Hasidism. From there we move into an exploration of his exceptional and iconic books, The Origins and History of Consciousness, and The Great Mother, and two papers "Mass Man and the Phenomena of Recollectivation" and "Narcissism". Neumann continued his study of mythology and archetypes in Amor and Psyche: The Development of the Feminine. Later in Neumann's life, he wrote a number of books on creativity exploring its nature and source which began with his important early paper on "Mystical Man": Creative Man, Art and the Creative Unconscious, The Place of Creation. Neumann's works lead us back to our ground of being, where we live with opposites that are fiercely alive, impacting our lives and cultures. His writings are comprehensive, clear and steeped in deeply felt experiences that help to place us on firm ground. Since many of his themes and concepts are universal-beginning with archetypes, myths, and images-this book is not only pertinent to Jungian psychotherapists but anyone interested in understanding the profundity of human nature and its development. (shrink)

Accurate solar irradiance prediction plays an important role in ensuring the security and stability of renewable energy systems. Solar irradiance modeling is usually a time-dependent dynamic model. As a new kind of recurrent neural network, echo state network shows excellent performance in the field of time series prediction. However, the memory length of classical ESN is fixed and finite, which makes it hard to map sufficient features of solar irradiance with long-range dependency. Therefore, a novel deep echo state (...) network with variable memory pattern is proposed in this brief. VMP-DESN consists of multiple connected reservoirs in series, and there exist different types of memory modes in VMP-DESN. To remember more input history information in the states, the time delay links are added in each reservoir and between every two reservoirs. The VMP-DESN is more flexible to deal with different input signals due to its variable memory modes in the reservoir states. Additionally, the effect of different memory patterns on the VMP-DESN performance is discussed in detail, including the antidisturbance ability, memory capacity, and prediction accuracy. Finally, the effectiveness of VMP-DESN is evaluated by predicting the real solar irradiance task. (shrink)

While Karl Popper highly valued the ability to invent a bold new form of theoretical thought, he warned us at the same time of the need to be cautious in action. Ambitions that are utopian or revolutionary seemed to Popper always unacceptable. We must always be open to reforming our practices, but we must attempt this slowly and piecemeal. Every change that we make we must hold open to criticism. However, change must be conservative and anti-revolutionary. This is the (...) demand that while any one element of current culture may be criticised and rejected, it is important to do this work piecemeal and carefully. Only then does the audacity or boldness of rejecting a seemingly settled view amount to courage: for it reflects also significant conservation of values. Popper regarded no social change or scientific breakthrough as revolutionary. Even the process of conjecture and refutation, of trial and error, is a piecemeal method. Popper’s piecemeal method depicts Otto Neurath’s metaphor of not dismantling the whole ship except perhaps one plank at a time, replacing each plank as the effort goes on. Every step is as conservative as it is also bold, and that alone helps make it courageous. It is only through this conservatism, the piecemeal anti-revolutionary change, that people can become bold in how they experiment and replace some formerly received norm or idea. (shrink)

Internet-based health research is increasing, and often offers financial incentives but fraudulent behavior by participants can result. Specifically, eligible or ineligible individuals may enter the study multiple times and receive undeserved financial compensation. We review past experiences and approaches to this problem and propose several new strategies. Researchers can detect and prevent Internet research fraud in four broad ways: through the questionnaire/instrument ; through participants' non-questionnaire data and seeking external validation through computer information,, and 4) through study design. These approaches (...) each have pros and cons, and raise ethical, legal, and logistical questions, given that ethical tensions can emerge between preserving the integrity of research vs. protecting the privacy and confidentiality of study respondents. While past discussions concerning the ethics of online research have tended to focus on the participants' ability to trust the researchers, needs now arise to examine researchers' abilities to trust the participants. This analysis has several critical implications for future practice, policy, and research. (shrink)

ABSTRACTEmpathy involves a mapping between the emotions observed in others and those experienced in one’s self. However, effective social functioning also requires an ability to differentiate one’s...

We explore the ability to distinguish random from non-random events. Randomness is defined in terms of radioactive decay whereas non-randomness is quantified by excess repetitions (“repeat”) or alternations (“switch”) between successive bits. In the first four experiments no mention was made of randomness, probability, or related concepts in task instructions. We found superior performance in distinguishing random stimuli from repeat stimuli compared to switch stimuli. The last three experiments explicitly evoked the concept of randomness, thus allowing comparison of perceptual (...) and conceptual performance. The ability to identify random events from switch distracters was inferior to the ability to discriminate random from switch stimuli. In contrast, for repeat stimuli the concept of randomness appears to roughly coincide with perceptual discriminability. Finally, the ability to identify or produce stimuli as random did not co-vary with the ability to discriminate random from non-random stimuli. (shrink)

Recently, society and the accounting profession have become increasingly concerned with ethics. Accounting researchers have responded by attempting to investigate and analyze the ethical behavior of accountants. While the current state of ethical behavior among practitioners is important, the ability of accountants to detect ethical problems that may not be obvious should also be studied and understood. This study addresses three questions: (1) are auditors alert to ethical issues; (2) if so, how important do they perceive them to be; (...) and (3) what factors affect their sensitivity threshold and their perceptions of the importance of the issues?Most of the prior research in accounting ethics presents subjects with scenarios that contain an obvious ethical issue, and subjects realize that they are participating in an ethics study. In the present study, the ethical problems are integrated into general accounting situations in order to discover the sensitivity of accounting professionals to them. This study defines ethical sensitivity as the ability to interpret a given situation and to realize that a moral problem exists. (shrink)

This paper presents the design, development, and potential impact of Echoes of Union Depot, a virtual reality (VR) game aimed at promoting historic preservation and raising public awareness about El Paso's Union Depot, a building listed on the National Register of Historic Places Inventory. The game leverages the immersive capabilities of VR technology and 360° images to engage players in exploring the site's rich history and architectural evolution. Players assume the role of a time-traveling detective, guiding lost spirits to resolve (...) their past and move on. The paper outlines the development process, highlighting the use of 360° panoramic images and 3D Vista Virtual Tour Pro software to create an accessible and user-friendly experience that fosters historic preservation awareness and cultural appreciation. The study also discusses limitations and areas for future research, including expanding the scope to include other heritage sites, working with historians and cultural consultants for accurate representations, and evaluating the game's effectiveness in promoting awareness and fostering a sense of community pride. (shrink)

Plagiarism detection is the process of finding similarities on electronic based documents. Recently, this process is highly required because of the large number of available documents on the internet and the ability to copy and paste the text of relevant documents with simply Control+C and Control+V commands. The proposed solution is to investigate and develop an easy, fast, and multi-language support plagiarism detector with the easy of one click to detect the document plagiarism. This process will be done (...) with the support of intelligent system that can learn, change and adapt to the input document and make a cross-fast search for the content on the local repository and the online repository and link the content of the file with the matching content everywhere found. Furthermore, the supported document type that we will use is word, text and in some cases, the pdf files –where is the text can be extracting from them- and this made possible by using the DLL file from Word application that Microsoft provided on OS. The using of DLL will let us to not constrain on how to get the text from files; and will help us to apply the file on our Delphi project and walk throw our methodology and read the file word by word to grantee the best working scenarios for the calculation. In the result, this process will help in the uprising the documents quality and enhance the writer experience related to his work and will save the copyrights for the official writer of the documents by providing a new alternative tool for plagiarism detection problem for easy and fast use to the concerned Institutions for free. (shrink)

The ability to detect deception is one of the most intriguing features of our minds. Cognitive load can surprisingly increase the accuracy of detection when there is a substantial load compared to when the detection is performed without cognitive load. This effect was tested in two experiments. In the first experiment, the participants were asked to watch truth/lie videos while completing a concurrent task (N‐back in a 3‐back version; intuitive processing), providing verbal reasoning after watching each video (...) (deliberative processing), or watching the videos alone (control group). The cognitive load caused by the concurrent task led to a higher accuracy in deception detection compared to the other conditions. In the second experiment, we examined how this effect worked under various amounts of cognitive load. Participants watching truth/lie videos were assigned to one of three experimental conditions (N‐back in three versions: 1, 3, and 5‐back) or to a control group. The participants in the 3‐back and 5‐back conditions exhibited a significantly higher accuracy in deception detection than those in the 1‐back and control groups. Thus, the effect of increased accuracy in deception detection is due to cognitive load and is related to the amount of cognitive load present. (shrink)

In order to solve the problem of low accuracy of pedestrian detection of real traffic cameras and high missed detection rate of small target pedestrians, this paper combines autoencoding neural network and AdaBoost to construct a fast pedestrian detection algorithm. Aiming at the problem that a single high-level output feature map has insufficient ability to express pedestrian features and existing methods cannot effectively select appropriate multilevel features, this paper improves the traditional AdaBoost algorithm structure, that is, (...) the sample weight update formula and the strong classifier output formula are reset, and the two-input AdaBoost-DBN classification algorithm is proposed. Moreover, in view of the problem that the fusion video is not smoothly played, this paper considers the motion information of the video object, performs pixel interpolation by motion compensation, and restores the frame rate of the original video by reconstructing the dropped interframe image. Through experimental research, we can see that the algorithm constructed in this paper has a certain effect. (shrink)

For a better detection in Network information security monitoring system, the author proposes a method based on adaptive depth detection. A deep belief network was designed and implemented, and the intrusion detection system model was combined with a support vector machine. The data set adopts the NSL-KDD network communication data set, and this data set is authoritative in the security field. Redundant cleaning, data type conversion, normalization, and other processing operations are performed on the data set. Using (...) the data conversion method based on the probability mass function probability mass function coding, a standard data set with low redundancy and low dimensionality can be obtained. Research indicates that when the batch size reaches 64, the accuracy of the test set reaches its maximum value. As the batch size increases, the accuracy first increases and then decreases. When the batch size continues to increase, the model will inevitably fall into the local optimal state, resulting in the degradation of the detection performance of the system. In terms of the false alarm rate, the DBN-SVM model is also the highest; however, it is only 10.73%. Under the premise of increasing the detection rate, the false alarm rate is improved; for the overall detection performance of the model, it is within an acceptable range. In terms of accuracy, the DBN-SVM model also scored the highest. The accuracy rate is the ratio of normal and correct classification for intrusion detection. It can explain the detection ability of the model. In summary, the overall detection ability of the DBN-SVM model is the best. The good classification ability to use SVM is proved, and the classification of low-dimensional features is expected to increase the detection rate of the system. (shrink)

The growing prevalence of misleading information (i.e., bullshit) in society carries with it an increased need to understand the processes underlying many people’s susceptibility to falling for it. Here we report two studies (N = 412) examining the associations between one’s ability to detect pseudo-profound bullshit, confidence in one’s bullshit detection abilities, and the metacognitive experience of evaluating potentially misleading information. We find that people with the lowest (highest) bullshit detection performance overestimate (underestimate) their detection abilities (...) and overplace (underplace) those abilities when compared to others. Additionally, people reported using both intuitive and reflective thinking processes when evaluating misleading information. Taken together, these results show that both highly bullshit-receptive and highly bullshit-resistant people are largely unaware of the extent to which they can detect bullshit and that traditional miserly processing explanations of receptivity to misleading information may be insufficient to fully account for these effects. (shrink)

Studies of change detection suggest that people tend to overestimate their ability to detect visual changes. In a recent laboratory study of change detection and human intention, Beck et al., found that individuals have an inadequate understanding that intention can improve change detection performance and that its importance increases with scene complexity. We note that these findings may be specific to unfamiliar situations such as those generated routinely in studies of change detection. In two questionnaire (...) studies, we demonstrate that when participants consider real world scenarios such as driving, people are well aware that the intention to detect changes improves detection performance, especially in complex scenes. We suggest several reasons why change detection findings like Beck et al.’s do not generalize to real world situations. More broadly, we suggest a possible way to bridge the gap between lab and life. (shrink)

In Neal Stephenson’s fictional novel, Diamond Age (1995), the protagonist Nell acquires a prototype of what we might today recognise as a highly sophisticated e-reader with a voice-assistant. This e-reader, the “Young Lady’s Illustrated Primer”, uses artificial intelli- gence to serve as Nell’s personal teacher. What is key to the Primer is how it is designed to respond to Nell. The Primer has a theory of Nell – her needs, her real-world situation, her abilities – and it tailors its lessons (...) for her. The Primer is a highly personalised artificially intelligent device. For many readers – myself included – the Primer was a utopian vision of the bespoke digital tutors of the future. The appearance of new media and technologies in the early 2000s all pointed to the near-term reality of devices like Primers. The real-life experience of personalised digital media, though, is so far from Stephen- son’s vision that it is hard to imagine we will ever get there. Nell’s time with the Primer develops her intellectually, emotionally, and physically. Our “bespoke” media experience, by contrast, is more likely to turn us in on ourselves rather than guide us to live well in our societies. Personalised media is making us more like Narcissus: our consumption is driven by personal choices and automated algorithms that reflect what we already want to hear, see, and consume, and we are captivated. Central to our understanding of the problems with the personalisation of digital media are filter bubbles and echo chambers. These phenomena are used interchangeably by some, but in distinct ways by others. I take the position that filter bubbles and echo chambers are distinct phenomena, but ones that raise similar epistemic worries. I begin with a general discussion of filter bubbles and echo chambers, and I introduce the concept of “selective exposure” as central to both phenomena. There is minimal uniformity across uses of the terms “filter bubble” and “echo chamber”. Consequently, I divide the later discussion into two more precise topics: homophily and polarisation. I conclude with some future-looking comments about responsibility and the epistemic risks posed by digital personalisation. (shrink)

Critics of virtue reliabilism allege that the view cannot account for testimonial knowledge, as the acquisition of such knowledge is creditable to the testifier, not the recipient's cognitive abilities. I defend virtue reliabilism by attending to empirical work concerning human abilities to detect sincerity, certainty, and seriousness through bodily cues and properties of utterances. Then, I consider forms of testimony involving books, newspapers, and online social networks. I argue that, while discriminatory abilities directed at bodily cues and properties of utterances (...) are impotent in the face of such testimony, alternative abilities facilitate the acquisition of knowledge from these sources. (shrink)

Times of uncertainty and fear were brought on by Covid-19. The ongoing pandemic is a fruitful ground for fake news, as citizens try to find explanations that fit into their worldviews. This process polarizes society and creates echo chambers amplified by recommender systems. Our main goal is to detect anti-vaxxer echo chambers in Serbia by analyzing online reactions to the recent detention of prominent anti-vaxxer Dr. Jovana Stojkovic. A content analysis of online comments is deployed in anti-regime left-leaning, (...) anti-regime right-leaning, and pro-government media to explore attitudes towards a vaccination conspiracy theory, police action towards anti-vaxxers, and the government crisis response team. We clearly identify the anti-vaccine echo chamber among commentators of anti-regime right-leaning media (YouTube podcasts). Additionally, we describe attitudes expressed around issues related to vaccination. Limitations and implications for future research are discussed. (shrink)

Music training is associated with enhanced executive function but little is known about the extent to which harmonic aspects of musical training are associated with components of executive function. In the current study, an array of cognitive tests associated with one or more components of executive function, was administered to young adult musicians and non-musicians. To investigate how harmonic aspects of musical training relate to executive function, a test of the ability to compose a four-part harmony was developed and (...) administered to musicians. We tested the working hypothesis that musicians would outperform non-musicians on measures of executive function, and that among musicians, the ability to harmonize would correlate positively with measures of executive function. Results indicate that musicians outperformed non-musicians on the Tower of London task, a measure of planning and problem-solving. Group differences were not detected on tasks more selective for inhibitory control, conflict resolution, or working memory. Among musicians, scores on the harmony assessment were positively correlated with performance of the Tower of London task. Taken together, the current results support a strong relationship between musicianship and planning and problem solving abilities, and indicate that the ability to harmonize is associated with components of executive function contributing to planning and problem solving. (shrink)

The evolution of the technology standard alliance is examined using complex adaptive system theory. Taking TSA as a dynamic CAS, an echo model is constructed to depict the mechanism of its evolution, and a model is simulated on the NetLogo platform. The echo model includes a basic model, an extended model, and a three-layer echo model. The adhesive aggregation of agents is explained, and the three evolutionary stages of agents’ entry, migration, and exit are analyzed. Moreover, the (...) adaptability of agents in TSA is quantified. The results of simulation show the evolution of the TSA in relation to the two aspects of agent adhesion aggregation and agent resource interaction, and they demonstrate the dynamic and complex hierarchical structure of the TSA system. It is proposed that greater matching ability, moderate behavior income, and lower behavior cost are more conducive to the evolution and development of TSA. Additionally, the echo model is reconstructed to expand the range of application of CAS theory. (shrink)

Both psychoanalysis and modern detective fiction evolved into their modern form around the turn of 20th century. In several ways, their development reflected the turbulent time period: an era that saw increasing doubt over logic and reason as ways to govern the world and that questioned humanity's ability to redeem itself through progress and knowledge. Detective fiction was an attempt to solve the unexpected through logic and reasoning, while psychoanalysis was a way to make coherence out of a fragmented (...) presentation. The preceding period had marked a growing public concern over crime in urban areas that was fed into public consciousness by the burgeoning print industry. After the establishment of the world's .. (shrink)

The ability to recognize and correct errors in one's explanatory understanding is critically important for learning. However, little is known about the mechanisms that determine when and under what circumstances errors are detected and how they are corrected. The present study investigated thought experiments as a potential tool that can reveal errors and trigger belief revision in the service of error correction. Across two experiments, 1149 participants engaged in reasoning about force and motion (a domain with well‐documented misconceptions) in (...) a pre‐training—training—post‐training design. The two experiments manipulated the type of mental model manipulated in the thought experiments (i.e., whether participants reasoned about forces acting on their own bodies vs. on external objects), as well as the level of relational and argumentative reasoning about the outcomes of the thought experiments. The results showed that: (i) thought experiments can serve as a tool to elicit inconsistencies in one's representations; (ii) the level of relational and argumentative reasoning determines the level of belief revision in the service of error correction; and (iii) the type of mental model manipulated in a thought experiment determines its outcome and its potential to initiate belief revision. Thought experiments can serve as a valuable teaching and learning tool, and they can help us better understand the nature of error detection and correction systems. (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)

The ability of ordinary differential equations (ODEs) to simulate discrete machines with a universal computing power indicates a new source of difficulties for event detection problems. Indeed, nearly any kind of event detection is algorithmi- cally undecidable for infinite or finite half-open time intervals, and explicitly given “well-behaved” ODEs (see [18]). Practical event detection, however, usually takes place on finite closed time intervals. In this paper the undecidability of general event detection is extended to such (...) intervals. On the other hand, on finite closed time in- tervals event detection in a certain approximate sense is quite generally decidable, which partly saves the case for practicable event detection. The capability of simulat- ing universal Turing machines is still there, and is used to give complexity lower bounds in terms of accuracy of event detection. The ODEs used here are of course quite complicated, but not artificial, in that even from the point of view of practical event detection it would appear difficult to find criteria to exclude them. (shrink)

The biological function of human reasoning abilities cannot be to improve shared knowledge. This is at best a side effect. A more plausible function of argumentation, and thus of reasoning, is to advertise one's ability to detect lies and errors. Such selfish behavior is closer to what we should expect from a naturally selected competence.

The application of machine learning algorithms to healthcare data can enhance patient care while also reducing healthcare worker cognitive load. These algorithms can be used to detect anomalous physiological readings, potentially leading to expedited emergency response or new knowledge about the development of a health condition. However, while there has been much research conducted in assessing the performance of anomaly detection algorithms on well-known public datasets, there is less conceptual comparison across unsupervised and supervised performance on physiological data. Moreover, (...) while heart rate data are both ubiquitous and noninvasive, there has been little research specifically for anomaly detection of this type of data. Considering that heart rate data are indicative of both potential health complications and an individual’s physical activity, this is a rich source of largely overlooked data. To this end, we employed and evaluated five machine learning algorithms, two of which are unsupervised and the remaining three supervised, in their ability to detect anomalies in heart rate data. These algorithms were then evaluated on real heart rate data. Findings supported the effectiveness of local outlier factor and random forests algorithms in the task of heart rate anomaly detection, as each model generalized well from their training on simulated heart rate data to real world heart rate data. Furthermore, results support that simulated data can help configure algorithms to a degree of performance when real labeled data are not available and that this type of learning might be especially helpful in initial deployment of a system without prior data. (shrink)

Previous studies suggest that morphological awareness and word detection skills have facilitating roles in reading fluency; however, it is unknown whether they can interplay with each other in such roles. The present study explored the relationships of MA, word detection, and passage reading fluency across ages. In total, 180 Chinese primary and secondary school students, aged from 8.52 to 15.67 years, completed tasks for these aforementioned capacities. After controlling gender, non-verbal intelligence, and reading ability at the word (...) level, the results showed that the participants with higher scores for MA or word detection performed better in passage reading fluency. However, the predictive effect of word detection on reading fluency became weaker as the children became older. The interaction between MA and word detection was positive in younger children, whereas this interaction tended to be negative for older children. The results demonstrated a dynamic interplay between MA and word detection in contributing to passage reading fluency in Chinese children. While it has a positive interaction with word detection on reading fluency in younger children, MA may become a compensator in older children whose word detection skills are less effective in facilitating fluent reading. (shrink)

Friedrich Nietzsche's prophet Zarathustra famously declared that "man is the cruelest animal". It is a nice tagline for a show such as True Detective, which entertains people with the fetishized torture, rape, and murder of lost young women. The idea that humans are the cruelest animal is interesting in itself because it implies that nonhuman animals can and do possess this disposition to some degree. This makes perfect sense in naturalistic terms. Humans are, after all, predators. Since humans are by (...) far the most successful predator on the planet, it would be reasonable on this basis alone to claim that humans are the cruelest animal. Although Nietzsche would agree that the ability to positively enjoy suffering is an essential step in the social evolution of human beings, it is not how he represents the ultimate value of human cruelty. Rather, for Nietzsche, the human capacity for cruelty is the key to affirming life itself. (shrink)

Fake news detection involves predicting the likelihood that a particular news article is intentionally deceptive. Arabic FND started to receive more attention in the last decade, and many detection approaches demonstrated some ability to detect fake news on multiple datasets. However, most existing approaches do not consider recent advances in natural language processing, i.e., the use of neural networks and transformers. This paper presents a comprehensive comparative study of neural network and transformer-based language models used for Arabic (...) FND. We examine the use of neural networks and transformer-based language models for Arabic FND and show their performance compared to each other. We also conduct an extensive analysis of the possible reasons for the difference in performance results obtained by different approaches. The results demonstrate that transformer-based models outperform the neural network-based solutions, which led to an increase in the F1 score from 0.83 to 0.95, and it boosted the accuracy by 16% compared to the best in neural network-based solutions. Finally, we highlight the main gaps in Arabic FND research and suggest future research directions. (shrink)

Depression is a common mental health illness worldwide that affects our quality of life and ability to work. Although prior research has used EEG signals to increase the accuracy to identify depression, the rates of underdiagnosis remain high, and novel methods are required to identify depression. In this study, we built a model based on single-channel, dry-electrode EEG sensor technology to detect state depression, which measures the intensity of depressive feelings and cognitions at a particular time. To test the (...) accuracy of our model, we compared the results of our model with other commonly used methods for depression diagnosis, including the PHQ-9, Hamilton Depression Rating Scale, and House-Tree-Person drawing test, in three different studies. In study 1, we compared the results of our model with PHQ-9 in a sample of 158 senior high students. The results showed that the consistency rate of the two methods was 61.4%. In study 2, the results of our model were compared with HAM-D among 71 adults. We found that the consistency rate of state-depression identification by the two methods was 63.38% when a HAM-D score above 7 was considered depression, while the consistency rate increased to 83.10% when subjects showed at least one depressive symptom. In study 3, 68 adults participated in the study, and the results revealed that the consistency rate of our model and HTP drawing test was 91.2%. The results showed that our model is an effective means to identify state depression. Our study demonstrates that using our model, people with state depression could be identified in a timely manner and receive interventions or treatments, which may be helpful for the early detection of depression. (shrink)

Misleading information pervades marketing communications, and is a long-standing issue in business ethics. Regulators place a heavy burden on consumers to detect misleading information, and a number of studies have shown training can improve their ability to do so. However, the possible side effects have largely gone unexamined. We provide evidence for one such side-effect, whereby training consumers to detect a specific tactic (illegitimate endorsers), leaves them more vulnerable to a second tactic included in the same ad (a restrictive (...) qualifying footnote), relative to untrained controls. We update standard notions of persuasion knowledge using a goal systems approach that allows for multiple vigilance goals to explain such side-effects in terms of goal shielding, which is a generally adaptive process by which activation and/or fulfillment of a low-level goal inhibits alternative detection goals. Furthermore, the same goal systems logic is used to develop a more general form of training that activates a higher-level goal (general skepticism). This more general training improved detection of a broader set of tactics without the negative goal shielding side effect. (shrink)

Humans naturally perceive visual patterns in a global manner and are remarkably capable of extracting object shapes based on properties such as proximity, closure, symmetry, and good continuation. Notwithstanding the role of these properties in perceptual grouping, studies highlighted differences in disembedding performance across individuals, which are summarized by the field dependence dimension. Evidence suggests that age and educational attainment explain part of this variability, whereas the role of sex is still highly debated. Also, which stimulus features primarily influence inter-individual (...) variations in perceptual grouping has still to be fully determined. Building upon these premises, we assessed the role of age, education level, and sex on performance at the Leuven Embedded Figure Test—a proxy of disembedding abilities—in 391 cisgender individuals. We also investigated to what extent shape symmetry, closure, complexity, and continuation relate to task accuracy. Overall, target asymmetry, closure, and good continuation with the embedding context increase task difficulty. Simpler shapes are more difficult to detect than those with more lines, yet context complexity impairs the recognition of complex targets to a greater extent. Concerning demographic data, we confirm that age and educational attainment are significantly associated with disembedding abilities and reveal a perceptual advantage in males. In summary, our study further highlights the role of shape properties in disembedding performance and unveils sex differences not reported so far. (shrink)

Change blindness, the surprising inability of people to detect significant changes between consecutively-presented visual displays, has recently been shown to affect tactile perception as well. Visual change blindness has been observed during saccades and eye blinks, conditions under which people’s awareness of visual information is temporarily suppressed. In the present study, we demonstrate change blindness for suprathreshold tactile stimuli resulting from the execution of a secondary task requiring bodily movement. In Experiment 1, the ability of participants to detect changes (...) between two sequentially-presented vibrotactile patterns delivered on their arms and legs was compared while they performed a secondary task consisting of either the execution of a movement with the right arm toward a visual target or the verbal identification of the target side. The results demonstrated that a motor response gave rise to the largest drop in perceptual sensitivity in detecting changes to the tactile display. In Experiment 2, we replicated these results under conditions in which the participants had to detect tactile changes while turning a steering wheel instead. These findings are discussed in terms of the role played by bodily movements, sensory suppression, and higher order information processing in modulating people’s awareness of tactile information across the body surface. (shrink)

Level measurements, thickness measurement or remote surface detection using ultrasonic pulse transit method require that the target surface be at 90 O to the incident beam so that reflected beam comes back at 180-degree angle to effectively use this method. This is perfectly true in case of flat, solid surface at right angle to the incident beam. But surface irregularities of a porous, non-smooth, uneven material such as snow cause penetration of incident wave into the surface, absorption of the (...) incident energy, scatter of energy in many directions and further attenuation of reflected signal making it difficult to detect the reflected echo. Such a received reflected echo is very low in amplitude and is heavily noise-ridden. The successful surface detection with excellent repeatability and accuracy without any false measurement in this case requires combination of physical acoustic, mechanical, hardware and software techniques together. In this paper we discuss the suitable physical, mechanical, electronics design to physically implement the theory of Arrayed Ultrasonic transducers to shape up the directional response, beam width and avoid interference to improve the chances of proper and sufficient reflection from the non-smooth, highly porous, uneven, non-planar irregular surface. (shrink)

GraphicalPatients with early- to middle-stage PD were enrolled for C-Gait assessment and traditional walking ability assessments. The correlation of C-Gait assessment and traditional walking tests were studied. Two models were established based on C-Gait assessment and traditional walking tests to explore the value of C-Gait assessment in predicting freezing of gait.ObjectiveEfficient methods for assessing walking adaptability in individuals with Parkinson’s disease are urgently needed. Therefore, this study aimed to assess C-Gait for detecting freezing of gait in patients with early- (...) to middle-stage PD.MethodPeople with PD diagnosis were recruited from April 2019 to November 2019 in Beijing Rehabilitation Hospital. The participants performed six items of walking adaptability on an instrumented treadmill augmented with visual targets and obstacles. The patient’s walking adaptability was evaluated by C-Gait assessment and traditional walking tests, and FOG-related indexes were collected as outcome measures. Two discriminant models were established by stepwise discriminant analysis; area under the receiver operating characteristic curve was used to validate the models.ResultIn total, 53 patients were included in this study. Most C-Gait assessment items had no or low correlations with traditional walking tests. The obstacle avoidance and speed of adaptation items could lead to FOG with high sensitivity. In addition, the C-Gait assessment model had slightly better discrimination of freezers from non-freezers compared with traditional walking test models ; specifically, obstacle avoidance and speed of adaptation have uniquely discriminant potential.ConclusionC-gait assessment could provide additional value to the traditional walking tests for PD. Gait adaptability assessment, as measured by C-Gait, may be able to help identify freezers in a PD population. (shrink)

Background: Detecting and classifying fish diseases is crucial for maintaining the health and sustainability of aquaculture systems. This study employs deep learning techniques, particularly Convolutional Neural Networks (CNNs), to automate the detection of various fish diseases using image data. Methods: The study utilizes a carefully curated dataset sourced from the Kaggle database, comprising images representing seven distinct types of fish diseases, along with images of healthy fish. Data preprocessing techniques, including resizing, rescaling, denoising, sharpening, and smoothing, are applied to (...) enhance image quality and facilitate accurate disease detection. Data augmentation is employed to increase the model's ability to generalize to unseen data. The CNN architecture is designed with cascading convolutional layers, ReLU activation functions, and pooling operations to extract high-level features associated with fish infections. The model architecture, implemented using the Keras Sequential API, includes convolutional layers, max pooling layers, and densely connected layers for classification. Results: Experimental results demonstrated promising performance across various disease categories, with high accuracy and balanced precision and recall values for most classes. The study also discussed the impact of climate change on fish disease incidence and underscores the importance of effective monitoring and management practices facilitated by technological innovations such as Big Data, IoT, sensors, and robotics in ensuring sustainable fisheries management. (shrink)

Faster R-CNN architecture is used to solve the problems of moving path uncertainty, changeable coverage, and high complexity in cold-air induced large-scale intensive temperature-reduction detection and classification, since those problems usually lead to path identification biases as well as low accuracy and generalization ability of recognition algorithm. In this paper, an improved recognition method of national ITR path in China based on faster R-CNN in complicated meteorological systems is proposed. Firstly, quality control of the original dataset of strong (...) cooling processes is carried out by means of data filtering. Then, according to the NITR standard and the characteristics of NITR, the NITR dataset in China is established by the intensive temperature-reduction areas located through spatial transformation. Meanwhile, considering that the selection of regularization parameters of Softmax classification method will cause the problem of probability calculation, support vector machine is used for path classification to enhance the confidence of classification. Finally, the improved faster R-CNN model is used to identify, classify, and locate the path of NITR events. The experimental results show that, compared to other models, the improved faster R-CNN algorithm greatly improves the performance of NITR’s path recognition, especially for the mixed NITR paths and single NITR paths. Therefore, the improved faster R-CNN model has fast calculation speed, high recognition accuracy, good robustness, and generalization ability of NITR path recognition. (shrink)

This paper looks at the attribution of the ability to lie and not at lying or lies. It also departs from more familiar approaches by focussing on the appraisal of an ability and not on the ability in itself. We believe that this attribution perspective is required to bring out the cognitive and intentional basis of the ability to lie.

The social network has become the primary medium of rumor propagation. Moreover, manual identification of rumors is extremely time-consuming and laborious. It is crucial to identify rumors automatically. Machine learning technology is widely implemented in the identification and detection of misinformation on social networks. However, the traditional machine learning methods profoundly rely on feature engineering and domain knowledge, and the learning ability of temporal features is insufficient. Furthermore, the features used by the deep learning method based on natural (...) language processing are heavily limited. Therefore, it is of great significance and practical value to study the rumor detection method independent of feature engineering and effectively aggregate heterogeneous features to adapt to the complex and variable social network. In this paper, a deep neural network- based feature aggregation modeling method is proposed, which makes full use of the knowledge of propagation pattern feature and text content feature of social network event without feature engineering and domain knowledge. The experimental results show that the feature aggregation model has achieved 94.4% of accuracy as the best performance in recent works. (shrink)

A key component of the susceptibility to cognitive biases is the ability to monitor for conflict between intuitively cued “heuristic” answers and logical principles. While there is evidence that pe...

My starting point is a fundamental paradox that lies at the heart of the slow demise of the Roman Republic: why does the system collapse when, as many scholars have noted, there is nothing that suggests that there was ever an intention by anyone to overthrow the Republic? Understanding this paradox is key to identifying what Rome might have to say to us today. What changes in the final decades of the Roman Republic is a declining view of the (...) class='Hi'>ability of political institutions to project the community into the future. This change is due to important alterations in the norms that provide the background context by which individuals working through institutions can get things done. The changes in these norms not only disable these institutions, making them seem less capable of projecting the community into the future, but also make possible alterations in the political framework that might have been inconceivable before. In particular, one sees the elevation of individuals who offer solutions by promising to bypass those ineffective and unresponsive institutions. (shrink)

Prior studies suggest that psychological difficulties arise from higher trait rejection sensitivity (RS)—heightened vigilance and differential detection of social rejection cues and defensive response to. On the other hand, from an evolutionary perspective, rapid and efficient detection of social rejection cues can be considered beneficial. We conducted a survey and an electrophysiological experiment to reconcile this seeming contradiction. We compared the effects of RS and rejection detection capability (RDC) on perceived interpersonal experiences (Study 1) and on neurocognitive (...) processes in response to cues of social rejection (disgusted faces; Study 2). We found that RS and RDC were not significantly related, although RS was positively related to perceived social rejection experiences and RDC was positively related to perceived social inclusion experiences. Event-related brain potentials (ERPs) revealed that higher RS was related to cognitive avoidance (i.e., P1) and heightened motivated attention (i.e., late positive potential: LPP), but not to facial expression encoding (i.e., N170) toward disgusted faces. On the other hand, higher RDC was related to heightened N170 amplitude, but not to P1 and LPP amplitudes. These findings imply that sensitivity to rejection is apparently distinct from the ability to detect social rejection cues and instead reflects intense vigilance and defensive response to those cues. We discussed an alternative explanation of the relationship between RS and RDC from a signal detection perspective. (shrink)

Interactions between humans and bots are increasingly common online, prompting some legislators to pass laws that require bots to disclose their identity. The Turing test is a classic thought experiment testing humans’ ability to distinguish a bot impostor from a real human from exchanging text messages. In the current study, we propose a minimal Turing test that avoids natural language, thus allowing us to study the foundations of human communication. In particular, we investigate the relative roles of conventions and (...) reciprocal interaction in determining successful communication. Participants in our task could communicate only by moving an abstract shape in a 2D space. We asked participants to categorize their online social interaction as being with a human partner or a bot impostor. The main hypotheses were that access to the interaction history of a pair would make a bot impostor more deceptive and interrupt the formation of novel conventions between the human participants. Copying their previous interactions prevents humans from successfully communicating through repeating what already worked before. By comparing bots that imitate behavior from the same or a different dyad, we find that impostors are harder to detect when they copy the participants’ own partners, leading to less conventional interactions. We also show that reciprocity is beneficial for communicative success when the bot impostor prevents conventionality. We conclude that machine impostors can avoid detection and interrupt the formation of stable conventions by imitating past interactions, and that both reciprocity and conventionality are adaptive strategies under the right circumstances. Our results provide new insights into the emergence of communication and suggest that online bots mining personal information, for example, on social media, might become indistinguishable from humans more easily. (shrink)

The presence of vegetation on railway tracks threatens track safety and longevity. However, vegetation inspections in Sweden are currently being carried out manually. Manually inspecting vegetation is very slow and time consuming. Maintaining an even quality standard is also very difficult. A machine vision-based approach is therefore proposed to emulate the visual abilities of the human inspector. Work aimed at detecting vegetation on railway tracks has been split into two main phases. The first phase is aimed at detecting vegetation on (...) the tracks using appropriate image analysis techniques. The second phase is aimed at detecting the rails in the image to determine the cover of vegetation that is present between the rails as opposed to vegetation present outside the rails. Results achieved in the current work indicate that the machine vision approach has performed reasonably well in detecting the presence/absence of vegetation on railway tracks when compared with a human operator. (shrink)