Narrow Results

SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a network model of human category learning. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g. it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes/attractors/rules. SUSTAIN has expanded the scope of findings that models of human category learning can address. This paper extends SUSTAIN to account for both supervised and unsupervised learning data through a common mechanism. The modified model, uSUSTAIN (unified SUSTAIN), is successfully applied to human learning data that compares unsupervised and supervised learning performances.¹⁸

We briefly present lag sequential analysis for behavioral streams, a commonly used method in psychology for quantifying the relationships between two nominal time series. Cross recurrence quantification analysis (CRQA) is shown as an extension of this technique, and we exemplify this nominal application of CRQA to eye-movement data in human interaction. In addition, we demonstrate nominal CRQA in a simple coupled logistic map simulation used in previous communication research, permitting the investigation of properties of nonlinear systems such as bifurcation and onset to chaos, even in the streams obtained by coarse-graining a coupled nonlinear model. We end with a summary of the importance of CRQA for exploring the relationship between two behavioral streams, and review a recent theoretical trend in the cognitive sciences that would be usefully informed by this and similar nonlinear methods. We hope this work will encourage scientists interested in general properties of complex, nonlinear dynamical systems to apply emerging methods to coarse-grained, nominal units of measure, as there is an immediate need for their application in the psychological domain.

Program partitioning is a task of splitting a large, complex software system into functionally independent program modules. It is a key step in program understanding, software maintenance and software reuse. Traditional program partitioning methods are nonlinear. In most cases, the computational efforts needed for partitioning a source program will increase exponentially with the size of the source program. The NP-hard complexity constitutes a computational barrier for partitioning legacy software systems properly and efficiently. In this paper, we propose a new method that can partition a source program into program modules within a timescale that is linear with the size of the program. Our method uses special heuristic knowledge, based on psychological analysis on human programming styles, to partition a source program into domain-oriented program modules. A case study on a legacy C program that consists of 92 functions is reported to demonstrate the efficiency and effectiveness of this method.

An innovative process that assists users in non-quantitative problem solving is presented. The process, called Ramic, employs the idea of psychological projection in an innovative way to help users focus, express and think through problems. Its applicability ranges from assisting with simple non-analytic decision-making to developing and assessing strategies.

In the virtual realm, harnessing the power of psychological projection for problem solving has been attempted in the form of a process called Sand Tray. Attempts at virtualization have garnered little traction potentially due to encumbrance of the interface. Ramic, in contrast, is innately set up for digital use through a relatively simple interface.

A key question this paper explores is how to quantitatively measure the value of Ramic in relation to the well-established process of Sand Tray. Even though these processes operate on qualitative problems, a preference analysis tool called conjoint analysis is used to build an experiment and derive specific user utilities for each process.

To perform the study, both processes required testing in the physical domain. A 32-person study is presented and indicates the Ramic projective process to have a 23% higher user utility than Sand Tray in the area of problem solving. As such, it presents an opportunity to explore a new way in which individuals can approach non-analytical problem solving and how computers can assist them in the task.

This paper integrates wavelet sound wave analysis with a fuzzy control method to develop a stage phobia analysis system for vocal performers in order to enhance the psychological efficiency of vocal performers and reduce the effect of stage phobia on vocal performance. To achieve howling signal filtering, the frequency sub-band with howling is reversed and then superimposed with the original signal in audio processing. Furthermore, this paper incorporates the actual requirements for processing the vocal audio spectrum and builds the corresponding practical modules. Furthermore, this paper integrates the research needs of vocal performers’ stage phobia to create system function modules, and investigates the psychological activities of vocal performers using the fuzzy control system, discovers the factors that influence stage performances, and improves the psychological output of vocal performers. Finally, this paper proposes experiments to test and evaluate the system’s results. The research findings indicate that the system described in this paper has a significant impact.

The impact of traits in entrepreneurship has been subject to intense discussion. Apart from favorable traits fostering opportunity recognition, entrepreneurial orientation, venture performance, and other variables, a younger research stream also addresses the role of negative traits. Among them, the dark triad, comprising of narcissism, Machiavellianism, and psychopathy, have gained specific attention. This systematic literature review aims to structure the field, identify current research themes, and provide a better understanding of prior research outcomes. Our results show that dark triad research addresses entrepreneurial activity, opportunity recognition, entrepreneurial orientation, entrepreneurial leadership, the and entrepreneurial motives. Among the dark triad traits, narcissism is stressed most in research so far. It relates to firm performance, risk, and leadership behavior, whereas Machiavellianism and psychopathy relate to opportunity recognition and exploitation. We also identify several research gaps, which can be addressed in future research.

The following topics are under this section:

• Asia-Pacific — Stresses of parenting may negatively affect the parent-child relationship
• Asia-Pacific — Duke-NUS holds first regional ageing and health conference for policymakers and researchers in Singapore
• Asia-Pacific — Science, Tech, and policies convene for a sustainable future
• Asia-Pacific — Researchers uncover the mechanism behind cancer-causing E.coli toxin setting the path to new preventive measures for colorectal cancer
• Asia-Pacific — Novel technology to determine classification of cancer cells through DNA barcodes
• Asia-Pacific — Identification of specific proteins can aid in development of novel therapeutic targets for heart diseases
• Asia-Pacific — How evolutionarily conserved genetic material determines reproductive ability of plants
• Asia-Pacific — Scientists call for bolder actions to protect coral reefs
• Asia-Pacific — International research team develops breakthrough technology for auto-detection of heart disease
• Rest of the World — New clinical guidelines for patients at high risk of heart attacks, stroke
• Rest of the World — For gut microbes, not all types of fibre are created equal

Among Esther Thelen's most important contributions to developmental theory is that there is no single factor that has priority in driving development. In this paper, we discuss how this notion influenced our research on perceptual-motor development. We show that multiple factors constrain perceptual-motor development, but that a relatively minor change in one of them may lead to significant changes in the observed perceptual-motor behavior.

The ever-increasing amount of text generated by Twitter users contains a wealth of information about the users' state of mind. Over the years, researchers have tapped upon this resource and proposed a number of lexicons and techniques for analysing the polarity of sentiments expressed by tweets. However, we need to delve deeper to extract the emotions conveyed by them — a research direction that had not received adequate attention so far. Through this work we develop a novel Emotion Analysis lexicon that was compiled by integrating information from the domain of psychology, the lexical ontology WordNet, and a set of emoticons and slangs commonly used in web jargon. We use this lexicon to find the predominant emotions carried by tweets originating from three different cities and analysed how they evolve with time. We propose a mathematical characterisation of the evolution of emotion by introducing the concepts of Emotion Intensity and Emotion Trend and visualise them in the context of causative events. On analysis, we observed Joy to be the predominant emotion in all the three cities. However, we could discern significant differences in the responses, patterns of emotion swings and correlations between different emotion categories that reflected the uniqueness of each city.

The paper presents knowledge residence to be only in the mind and rejects the orthodox definition of the knowledge types which has been used till now by most knowledge management (KM) gurus and authors — in which knowledge exists inside and outside the human body — and presents an alternative model for such. Yet, unlike other papers that reject this classical view, this paper does not doubt the importance of the field nor underestimate the role of its originators. Alternatively, it emphasises the significance of KM and provides practical insights for its effectiveness. The paper concludes by addressing the importance of understanding the essence of knowledge in the public sector through proposing a pragmatic concept that could be easily applied. We have chosen a city that has an existing platform that can support the application of such concept — Dubai — especially with its current expanding endeavours towards “Connecting Minds, Creating the Future”, which is its Expo theme in 2020.

The Terasem Mind Uploading Experiment is a multi-decade test of the comparability of single person actual human consciousness as assessed by expert psychological review of their digitized interactions with same person purported human consciousness as assessed by expert psychological interviews of personality software that draws upon a database comprised of the original actual person's digitized interactions. The experiment is based upon a hypothesis that the paper analyzes for its conformance with scientific testability in accordance with the criteria set forth by Karl Popper. Strengths and weaknesses of both the hypothesis and the experiment are assessed in terms of other tests of digital consciousness, scientific rigor and good clinical practices. Recommendations for improvement include stronger parametrization of endpoint assessment and better attention to compliance with informed consent in the event there is emergence of software-based consciousness.

The domain of machine consciousness is a melting pot of computers, robots, neuropsychology, sociology and philosophy. This is both an opportunity and a serious risk of stagnation in entertaining but never-ending discussions that may prove useless concerning the construction of better machines. This paper analyzes this situation, defends an engineering approach to machine consciousness research and proposes a strategy focused on machine understanding to get out of the current impasse.

The year 2020 marked the 150th birth anniversary of the apostle of non-violence, Mahatma Gandhi and the 75th anniversary of the horrific nuclear attack on Japan. While Gandhi practiced and propagated non-violence, the atomic bombs dropped on the cities of Hiroshima and Nagasaki represented the most horrendous apocalyptic form of violence raising questions on the validity of Gandhian techniques. Gandhi not only condemned the nuclear attack stating that violence cannot bring peace but called employment of nuclear weapons as the most abominable use of science reiterating that only non-violence could save humanity from global nuclear suicide. Experts also assumed that the destructive power of nuclear weapons would ensure that the world will turn away from violence. However, again, Gandhi asked what would happen once the effect of disgust is over; whether the world will return to violence with renewed zeal? Nations have surely unlearnt lessons from World War II. Ever-rising number of nations are either developing or aspiring for nuclear weapons that are often brandished, even celebrated as sources of peace. As the world today looks at the beginning of the New Cold War between the United States and China, it is worth revisiting Gandhian premises of non-violence being intrinsic to human nature. Recent studies on the neurological basis of human behaviour seek to reinforce the science of non-violence with detailed biological and psychological indices. These show how non-violence is intrinsic to human nature and goes deeper into the animal kingdom. Their work continues to be neglected and negated by strategic studies resulting in rapacious international quest for ever more destructive power, all in the name of peace and security. No doubt, violence can never be eliminated, yet it has been and can be curbed and channelised by conscious use of non-violent techniques so convincingly propagated by Gandhi. This chapter seeks to investigate the psychology of Gandhian non-violence and access its implications and applicability for nuclear disarmament and non-violent world order.

Our understanding of an entrepreneurship varies by our interpretations. Since there is no widely accepted definition of entrepreneurship, there is a dilemma in the literature because we cannot first understand entrepreneurial behavior. The reason why there is no widely accepted definition of entrepreneurship is the competing antenarratives that influence entrepreneurial behavior. Entrepreneurial behavior manifests itself from three internal antenarratives that are the soul, individual psyche, and the collective unconscious. How you view the world will determine which of these antenarratives guide your interpretation and understanding of entrepreneurship and will lead to different types of behavior. Therefore, this chapter expands upon these three antenarratives to provide an outline and a deeper understanding of how entrepreneurial behavior manifests itself to orient the reader to what entrepreneurship means to them.

In recent years, quantum theory has been actively used in areas outside of physics, such as psychology, sociology, theory of decision-making, game theory, and others. In particular, quantum formalism (especially its probabilistic counterpart) is used to explain the paradoxes arising in cognitive psychology and decision making. Wang and Busemeyer invented a quantum model and approach as well as non-parametric equality (so-called QQ-equality), explaining the questions order effect. The primary objective of this note is to test the possibility to expand the Wang-Busemeyer model by considering questions which are mathematically represented by positive operator valued measures. We found that, for such observables, the QQ-equality can be violated. But, we also showed that, in principle, it is possible to reduce the expanded model to the original Wang-Busemeyer model by expanding the context of the questions.

We present a quantum-like (QL) model in that contexts (complexes of e.g. mental, social, biological, economic or even political conditions) are represented by complex probability amplitudes. This approach gives the possibility to apply the mathematical quantum formalism to probabilities induced in any domain of science. In our model quantum randomness appears not as irreducible randomness (as it is commonly accepted in conventional quantum mechanics, e.g. by von Neumann and Dirac), but as a consequence of obtaining incomplete information about a system. We pay main attention to the QL description of processing of incomplete information. Our QL model can be useful in cognitive, social and political sciences as well as economics and artificial intelligence. In this paper we consider in a more detail one special application — QL modeling of brain's functioning. The brain is modeled as a QL-computer.

The aim of this chapter is to refine some questions regarding AI, and to provide partial answers to them. We analyze the state of the art in designing intelligent systems that are able to mimic human complex activities, including acts based on artificial consciousness. The analysis is performed to contrast the human cognition and behavior to the similar processes in AI systems. The analysis includes elements of psychology, sociology, and communication science related to humans and lower level beings. The second part of this chapter is devoted to human-human and man-machine communication, as related to intelligence. We emphasize that the relational aspects constitute the basis for the perception, knowledge, semiotic and communication processes. Several consequences are derived. Subsequently, we deal with the tools needed to endow the machines with intelligence. We discuss the roles of knowledge and data structures. The results could help building "sensitive and intelligent" machines.

Underlying idea: A new hypothesis about how the mental state of psychosis may arise in the brain as a “linear” information processing pathology is briefly introduced. This hypothesis is proposed in the context of a complementary approach to psychiatry founded in the logical paradigm of chaos theory. To best understand the relation between chaos theory and psychiatry, the semantic structure of chaos theory is analyzed with the help of six general, and six specific, fundamental characteristics which can be directly inferred from empirical observations on chaotic systems. This enables a mathematically and physically stringent perspective on psychological phenomena which until now could only be grasped intuitively: Chaotic systems are in a general sense dynamic, intrinsically coherent, deterministic, recursive, reactive and structured: in a specific sense, self-organizing, unpredictable, nonreproducible, triadic, unstable and self-similar. To a great extent, certain concepts of chaos theory can be associated with corresponding concepts in psychiatry, psychology and psychotherapy, thus enabling an understanding of the human psyche in general as a (fractal) chaotic system and an explanation of certain mental developments, such as the course of schizophrenia, the course of psychosis and psychotherapy as chaotic processes.

General overview: A short comparison and contrast of classical and chaotic physical theory leads to four postulates and one hypothesis motivating a new, dynamic, nonlinear approach to classical, causal psychiatry: Process-Oriented PSYchiatry or “POPSY”, for short. Four aspects of the relationship between chaos theory and POPSY are discussed: (1) The first of these, namely, Identification of Chaos / Picture of Illness involves a definition of Chaos / Psychosis and a discussion of the 6 logical characteristics of each. This leads to the concept of dynamical disease (definition, characteristics and examples) and to the idea of “psychological disturbance as dynamical illness”. On the one hand, it is argued that the developmental course of psychosis is chaotic. On the other hand, we propose the hypothesis that the mental state of psychosis may be a linear information processing pathology. (2) The second aspect under discussion is the Assessment of Chaos / Diagnosis of Illness. In order to better understand how POPSY research treats this aspect, we take a look at the 3 different classes of (non-quantum) motion as models of 3 different possible courses of illness and outline present-day methods available for the quantitative assessment of chaotic (fractal) motion. (3) The third aspect, namely. Prediction of Chaos / Prognosis of Illness considers how each of these 3 classes of motion implies a different way of looking into the future: linear-causal, statistical and nonlinear-fractal, respectively (4) The fourth aspect of the relationship between chaos theory and POPSY, Control of Chaos / Treatment of Illness, is shown to have certain implications to complementary medicine. This paper completes with a short summary, conclusion and a closing remark.

With the advent of “Internet +” age, college students’ psychology is meeting more important changes than ever before. So how to improve the management level to the college students’ mental, build college students’ mental management mode to satisfy the needs of the times, strengthen college students’ psychological self-management ability and improve the psychological health level in the new period, these aspects become the important subjects to the college students’ ideological and political education work.

We show that (in contrast to rather common opinion) the domain of applications of the mathematical formalism of quantum mechanics is not restricted to physics. This formalism can be applied to the description of various quantum-like (QL) information processing. In particular, the calculus of quantum (and more general QL) probabilities can be used to explain some paradoxical statistical data which was collected in psychology and cognitive science. The main lesson of our study is that one should sharply distinguish the mathematical apparatus of QM from QM as a physical theory. The domain of application of the mathematical apparatus is essentially wider than quantum physics. Quantum-like representation algorithm, formula of total probability, interference of probabilities, psychology, cognition, decision making.