Important New Terms and Classifications in Uncertainty and Fuzzy Logic

Provides an abstract of the presentation and a brief professional biography of the presenter. The complete presentation was not made available for publication as part of the conference proceedings.

The theory of fuzzy logic, founded by Zadeh (1965), deals with the linguistic notion of graded membership, unlike the computational functions of the digital computer with bivalent propositions. Since mentation and cognitive functions of brains are based on relative grades of information acquired by the natural (biological) sensory systems, fuzzy logic has been used as a powerful tool for modeling human thinking and cognition (Gupta and Sinha, 1999, Gupta et al., 2003). The perceptions and actions of the cognitive process thus act on the graded information associated with fuzzy concepts, fuzzy judgment, fuzzy reasoning, and cognition. The most successful domain of fuzzy logic has been in the field of feedback control of various physical and chemical processes such as temperature, electric current, flow of liquid/gas, and the motion of machines (Gupta, 1994, Rao and Gupta, 1994, Sun and Jang, 1993, Gupta and Kaufmann, 1988, Kiszka et al., 1985, Berenji and Langari, 1992, Lee, 1990a,b). Fuzzy logic principles can also be applied to other areas. For example, these fuzzy principles have been used in the area such as fuzzy knowledge-based systems that use fuzzy IF-THEN rules, fuzzy software engineering, which may incorporate fuzziness in data and programs, and fuzzy database systems in the field of medicine, economics, and management problems. It is exciting to note that some consumer electronic and automotive industry products in the current market have used technology based on fuzzy logic, and the performance of these products has significantly improved (Al-Holou et al., 2002, Eichfeld et al., 1996).

In a recent article in Cancer, Cho and colleagues1 suggested that the Cancer of the Liver Italian Program (CLIP) system was the best prognostic system for predicting the survival of patients with hepatocellular carcinoma (HCC) who were undergoing transcatheter arterial chemoembolization, and further validation studies will be performed. We agree with the authors. Predicting mortality is an important component of the decision-making process, and scoring systems (Child-Pugh, CLIP, Model for Endstage Liver Disease, Barcelona Clinic Liver Cancer, etc) long have been accepted for establishing patient outcomes in HCC. Although these models perform well in predicting the mortality or morbidity in the original cohorts on which the models were developed, they may underestimate or overestimate mortality or morbidity in different populations.1 However, in the midst of such uncertainty, fuzzy logic may play an important role in the decision-making process. Fuzzy logic is the science of reasoning, thinking, and inference that recognizes and uses the real-world phenomenon that everything is a matter of degree. In the simplest terms, fuzzy-logic theory is an extension of binary theory that does not use crisp definitions and distinctions. Instead of assuming that everything must be defined in to black and white (binary view), fuzzy logic is a method that captures and uses the concept of fuzziness in a computationally effective manner. Neural networks and fuzzy logic are 2 complementary technologies. Neural networks can learn (ie, adapt) from data and feedback, but understanding the pattern learned by neural networks is difficult. Conversely, fuzzy rule-based models are easy to comprehend, because they use linguistic terms and the structure of if/then rules. Unlike neural networks, fuzzy logic does not come with a learning algorithm (ie, the system cannot learn from feedback). The combination of neural networks and fuzzy logic has created a new term, a neurofuzzy system. Neural networks, fuzzy systems, and the combination of both already have been applied successfully to computer-aided diagnosis—eg, detection of microcalcification, automatic detection of distorted plethysmogram pulses in neonates and pediatric patients, detection of erythematosquamous diseases, and lung-nodule detection—and have been useful for predicting the presence of prostate cancer.2 In conclusion, slight variations in population characteristics can change predictive values of the scoring systems. However, neurofuzzy systems can incorporate data from many clinical, biologic, and genetic variables and can provide better risk estimations for hepatocellular carcinoma. Mesut Tez MD*, Baris Zulfikaroglu MD , * Gazi University School of Medicine, Department of Surgery, Ankara, Turkey, Ankara Numune Hospital, Department of Fifth Surgery, Ankara, Turkey.

Chunking mechanisms in human learning

This paper discussed the external environmental conditions and humans’ internal cognition relating to the visual inspection process of actual mass productions. In visual inspection, human perception and recognition are indispensable to the detection and pass-fail discrimination of the defects, because only those form the discipline of the inspection. First, the effects of the external environment on the defect detection rate were evaluated based on the experimental results. Both defects’ features and environmental factors such as the display luminance and defects’ contrast and size are significant for the peripheral visual inspection. Some of the main effects reported in previous studies were verified again, and new interaction effects and whole factors became clear by quantitative analysis. The second was experiments and analyses of human perception and cognition of actual visual inspection targets. A wearable eye-tracker was used to observe experts and a beginner. The visual inspections by the experts were highly efficient because of their skilled perception at first glance and discrimination based on various industrial knowledge in addition to the defect’s appearance. The experts could stably detect a tiny and low-contrast defect on product images including much disturbing stimulus, and it is thought that their sensitivity and resolution were improved based on “attention” because they answered with high confidence. On the other hand, under the same situation, the number of the beginner’s focal points much increases, and processing speed deteriorates remarkably. Finally, some suggestions were summarized based on the results of the first and second topics about the environment of the visual inspection to raise the efficiency of defect detection and pass-fail judgement.

Objet Trouve, Holism, and Morphogenesis in Interactive Evolution Ron W. Noel (noelr1@rcn.com) WCSU, Department of Psychology, 181 White Street Danbury, CT 06810 Sylvia Acchione-Noel ( sylvia.acchione-noel@corporate.ge.com ) General Electric, JF Welch Leadership Development Center, Old Albany Post Road Ossining, NY 10562 Abstract Evolutionary systems are conceptualized as having four transfer functions between the two state spaces of genotype and phenotype. The four transfer functions are epigenesis, survival, mate selection, and genetic recombination. The treatment of these transfer functions is uneven at best. In particular, some complain that epigenesis, the formation of an entity from the original undifferentiated cell mass into tissues, is treated in a too simplistic manner to allow for system flexibility, or creativity. This paper reports on an interactive image evolving system that mimics the morphogenesis processes in epigenesis. System description, results, and theoretical implications are discussed. Introduction Interactive evolutionary systems seek to interface evolutionary programming to human preference in order to create systems capable of evolving artifacts that require a human expertise that hasn’t yet succumb to computation. A common area for this endeavor is the evolving of art, particularly image. The interfacing of human ability with machine computation requires resolving difficult issues in the arts, humanities, and sciences. Further, progress in the design of interactive evolutionary systems allows a glimpse into how very human abilities such as intuition, projection, and holistic perception interplay with the mechanics of machine computation. This paper reports on one such interactive evolutionary system that seeks to combine human perception with the genetic algorithm to evolve small holistic images. Humans lack the tremendous numerical computational speed of computers; yet they can process information holistically in an automatic, rapid, and natural manner. Machines possess tremendous computational capabilities; yet no algorithm exists to perform holistic processes as well as humans do. Ideally, a good interactive system would integrate the best human cognitive qualities with machine computational capabilities enabling the resultant hybrid system to outperform either of the two components alone. Evolutionary computation as an algorithm is well suited for the creation of an interactive imaging system. However, problems exist in implementation: How can evolutionary computation best support the holistic processes of human cognition? To answer this question requires an understanding of current theory regarding human holistic processes. Psychological Issues A well-known area in cognitive research that studies holistic processes is the recognition of objects and, in particular, the recognition of faces. Different perceptual encoding and representational processes have traditionally differentiated theories regarding the recognition of objects as compared to faces. However, the functional separation of these processes under all conditions of object recognition remains unclear (Bruce & Humphreys, 1994). Much of basic object recognition theory has been based on the decomposition of parts and the analysis of edge features (Marr & Nishihara, 1978; Biederman, 1987; Ullman, 1989). On the other hand, face recognition theory has been based on more holistic processes which utilize surface characteristics such as texture, color, and shading (Price & Humphreys, 1989). Some research suggests that the distinctions between object and face recognition begin to fade when one examines the object recognition processes of experts, who may utilize holistic processes similar to those found in face recognition (Diamond & Carey, 1986; Rhodes & McLean, 1990). The theory regarding holistic processing of faces can be separated into stronger and weaker stances (Bruce & Humphreys, 1994). Under the weaker stance, features may interact with each other through configural processes to form emergent properties or second-order relational features (Diamond & Carey, 1986). Under the stronger stance, face recognition is completely holistic; that is, its representation is non-decomposable in that no explicit description of features exists outside the context of the face (Tanaka & Farah, 1993). These stances provide two ways of approaching the development of an interactive system to support the holistic development of images: (1) A system which manipulates context-free features towards configuration, or (2) a system which develops the configuration of the image first, followed by more detailed development of features within the established context. We sought to design a recognition-driven system of the latter type, which would support the purely holistic development of images, including faces and objects. This system would function in a feature-free space to provide a

Overview: 
 This document provides a summary of a practical method that can be used to compare handwriting (whether text-based or signatures) in the forensic environment. It is intended to serve as an approach to forensic handwriting examination for practitioners actively involved in casework, or for those interested in investigating general aspects of the practice of forensic handwriting examination (for example researchers, academics and legal professionals). The method proposed does not cover in detail all aspects of the examination of handwriting. It does, however, form the framework of forensic handwriting methodology in the government environment in Australia and New Zealand as represented by the Document Examination Specialist Advisory Group (DocSAG).
 It is noted from the outset that handwriting is examined using complex human perceptual and cognitive processes that can be difficult to accurately and validly describe in written form since, for the most part, these processes are hidden. What is presented here is the agreed general approach that DocSAG practitioners use in the majority of the comparisons that they carry out. The method is based around a flow diagram which structures the comparison process and provides the reader with a guide as to the significant landmark stages commonly worked through in practical handwriting examinations. Where decision points occur within the course of the method flow diagram a series of modules have been developed which describe the nature of the decision under consideration and address relevant theoretical and practical issues. Each module is, as far as is practical, independent of other modules in the method. This assists in facilitating changes in the process over time that may result from theoretical, practical or technological advances in the field.
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Introduction. The relevance of the research problem lies in the fact that in psychological science some theorists involved in the study of emotions believe that the states of emotional experience are unchanged. Since the principles of immutability and constancy of emotional experience are crucial for understanding consciousness, an important type of which in humans are emotions, since they influence their perceptual and cognitive processes and behavior.Purpose setting. There are unique classes of emotional phenomena, such as mood, feelings, which manifest themselves in the general background of events and persist after their completion. It is precisely such background experiences that are the basis of the emotional assessments studied in this work. Moral and aesthetic experiences associated with art, human cognition through art, ensure his development as a subject of moral relations to other people and to himself, contribute to changes in his moral experience and personal (including emotional) characteristics.Methodology and methods of the study was carried out on the basis of the study of philosophical, sociological, psychological and pedagogical scientific and methodological literature, which made it possible to develop the concept of psychological foundations. Results. Our research is educational in the management of emotions and feelings. The dynamic development of the results of our study of the emotional states of a personality, its experiences according to the author’s methods in the form of keeping an emotional diary since 1997, contributing to the self-development of a personality as a component of personal maturity, is presented.Conclusion. The practical value of the research within the framework of general psychology lies not only in the fact that the main directions for optimizing the process of emotional and moral development of a personality are identified, recommendations are substantiated for improving the specialization of people working with children, improving their professional skills, but also in developing a program for the psychological study of emotional and moral personality development (EMPD), diagnostics of specific and nonspecific emotional phenomena, which ensures timely correction of the EMPD process. The data obtained can be taken into account in schools and universities in the process of forecasting the moral atmosphere among adolescents and students, as well as the moral atmosphere of society in general.

Chapter 12 - We Have Time Requirements

Event-Related Potentials (ERPs) and Cognitive Processing

Learning and memory can be defined as the processes by which we acquire information about our environment and experiences, to be used later in similar situations. These cognitive processes are important for behaviors crucial to survival, such as finding food and shelter, assessing risk, and behaving appropriately in social contexts. Research provides insights into how hormones influence animal and human cognition. Here, we focus on the sex hormones, which influence both learning or acquisition and memory consolidation through two mechanisms: (i) the genomic pathways, acting longer-term to modulate gene transcription, protein expression, and structural changes implicated in establishing memory traces; and (ii) rapid pathways in which receptor activation initiates cell signaling cascades and more immediate neural responses. Investigating the roles of sex hormones in learning and memory enhances our understanding of neural networks involved in different types of learning, in ways that may be applied to human health and cognition.

Considerable effort has been and is currently being concentrated on improving the speech quality at low and very low bit rates. Recently new models of LPC excitation have been devised, which are able to yield good quality speech by exploiting our knowledge of the human speech production and perception processes. Unfortunately, these models generally require too much computational load to be easily implemented on currently available hardware. This paper describes an efficient speech coder, capable of providing acceptable quality speech, within the limitations of both low bit rate (approximately 2.4 kbit/s) and real-time implementation. The coder is based upon pattern classification and cluster analysis with perceptually-meaningful error minimization criteria. Our main objective is improving the excitation representation in a linear predictive coding scheme and, hence, the subjective quality of synthesized speech signals.

Action video game players (AVGPs) outperform nonvideo game players (NVGPs) on a wide variety of attentional tasks, mediating benefits to perceptual and cognitive decision processes. A key issue in the literature is the extent to which such benefits transfer beyond cognition. Using steady-state visual evoked potentials (SSVEP) as a neural measure of attentional resource allocation, we investigated whether the attentional benefit of AVGPs generalizes to the processing of rapidly presented facial emotions. AVGPs (n = 36) and NVGPs (n = 32) performed a novel, attention-demanding emotion discrimination task, requiring the identification of a target emotion in one of two laterally presented streams of emotional faces. The emotional faces flickered at either 2.0 Hz or 2.5 Hz. AVGPs outperformed NVGPs at detecting the target emotions regardless of the type of emotion. Correspondingly, attentional modulation of the SSVEP at parieto-occipital recording sites was larger in AVGPs compared with NVGPs. This difference appeared to be driven by a larger response to attended information, as opposed to a reduced response to irrelevant distractor information. Exploratory analyses confirmed that this novel paradigm elicited the expected pattern of event-related potentials associated with target detection and error processing. These components did not, however, differ between groups. Overall, the results indicate enhanced discrimination of facial emotions in AVGPs arising from enhanced attentional processing of emotional information. This presents evidence for the attentional advantage of AVGPs to extend beyond perceptual and cognitive processes.

Scientific research into human cognition is well established by decades of rigorous behavioral experimentation, studies of the human brain, and computer simulations. All of these converge to provide scientific insights into perception, judgment, and decision making (Dror & Thomas, 2005; Kosslyn & Koenig, 1995). Many of these theoretical insights play an important role in our understanding of how humans behave in the real world. The scientific research has important bearings on how human perception, judgment, and decision making can be enhanced, as well as how both lay people and experts can (and do) make mistakes. Bridging scientific theory to the real world can assist our understanding of human performance and error and help us evaluate the reliability of humans. Furthermore, it has implications on how to minimize such error through proper selection and training, best practices, and utilizing technology (Dror, 2007, in press). In this chapter, scientific findings about human cognition are discussed and linked to practical issues in the real world of investigations.

Functional magnetic resonance imaging (fMRI) provides a safe, noninvasive method for measuring neural function and relating it to behavior and cognitive processes. The fMRI procedure is being increasingly employed to answer questions about how and where information is processed in the brain to guide behavior. This general overview of fMRI centers on practical concerns for researchers wishing to use fMRI to answer their own questions about the relationship between brain and behavior.In this chapter we review the basic principles of fMRI‐based cognitive neuroscience, focusing on (a) the history and development of fMRI for observing neural function, (b) the nature of the fMRI signal and its relation to neural activation and cognitive processes, (c) the types of questions that can be addressed using fMRI, (d) concerns for experimental design and statistical analysis, and (e) advanced approaches for fMRI‐based meta‐analysis. The strengths and limitations of fMRI are discussed relative to how this method can best be used to elucidate the complex relationship between cognition and neural processes.