A Study of recent classification algorithms and a novel approach for biosignal data classification

Analyzing and understanding human biosignals have been important research areas that have many practical applications in everyday life. For example, Brain Computer Interface is a research area that studies the connection between the human brain and external systems by processing and learning the brain signals called Electroencephalography (EEG) signals. Similarly, various assistive robotics applications are being developed to interpret eye or muscle signals in humans in order to provide control inputs for external devices. The efficiency for all of these applications depends heavily on being able to process and classify human biosignals. Therefore many techniques from Signal Processing and Machine Learning fields are applied in order to understand human biosignals better and increase the efficiency and success of these applications. This thesis proposes a new classifier for biosignal data classification utilizing Particle Swarm Optimization Clustering and Radial Basis Function Networks (RBFN). The performance of the proposed classifier together with several variations in the technique is analyzed by utilizing comparisons with the state of the art classifiers such as Fuzzy Functions Support Vector Machines (FFSVM), Improved Fuzzy Functions Support Vector Machines (IFFSVM). These classifiers are implemented on the classification of same biological signals in order to evaluate the proposed technique. Several clustering algorithms, which are used in these classifiers, such as K-means, Fuzzy c-means, and Particle Swarm Optimization (PSO), are studied and compared with each other based on clustering abilities. The effects of the analyzed clustering algorithms in the performance of Radial Basis Functions Networks classifier are investigated. Strengths and weaknesses are analyzed on various standard and EEG datasets. Results show that the proposed classifier that combines PSO clustering with RBFN classifier can reach or exceed the performance of these state of the art classifiers. Finally, the proposed classification technique is applied to a real-time system application where a mobile robot is controlled based on person\u27s EEG signal

Sandspur, Vol 98 No 23, April 15, 1992

Rollins College student newspaper, written by the students and published at Rollins College. The Sandspur started as a literary journal.https://stars.library.ucf.edu/cfm-sandspur/2730/thumbnail.jp

East-West Paths to Unconventional Computing

Unconventional computing is about breaking boundaries in thinking, acting and computing. Typical topics of this non-typical field include, but are not limited to physics of computation, non-classical logics, new complexity measures, novel hardware, mechanical, chemical and quantum computing. Unconventional computing encourages a new style of thinking while practical applications are obtained from uncovering and exploiting principles and mechanisms of information processing in and functional properties of, physical, chemical and living systems; in particular, efficient algorithms are developed, (almost) optimal architectures are designed and working prototypes of future computing devices are manufactured. This article includes idiosyncratic accounts of ‘unconventional computing’ scientists reflecting on their personal experiences, what attracted them to the field, their inspirations and discoveries.info:eu-repo/semantics/publishedVersio

A theoretical and practical approach to a persuasive agent model for change behaviour in oral care and hygiene

There is an increased use of the persuasive agent in behaviour change interventions due to the agent‘s features of sociable, reactive, autonomy, and proactive. However, many interventions have been unsuccessful, particularly in the domain of oral care. The psychological reactance has been identified as one of the major reasons for these unsuccessful behaviour change interventions. This study proposes a formal persuasive agent model that leads to psychological reactance reduction in order to achieve an improved behaviour change intervention in oral care and hygiene. Agent-based simulation methodology is adopted for the development of the proposed model. Evaluation of the model was conducted in two phases that include verification and validation. The verification process involves simulation trace and stability analysis. On the other hand, the validation was carried out using user-centred approach by developing an agent-based application based on belief-desire-intention architecture. This study contributes an agent model which is made up of interrelated cognitive and behavioural factors. Furthermore, the simulation traces provide some insights on the interactions among the identified factors in order to comprehend their roles in behaviour change intervention. The simulation result showed that as time increases, the psychological reactance decreases towards zero. Similarly, the model validation result showed that the percentage of respondents‘ who experienced psychological reactance towards behaviour change in oral care and hygiene was reduced from 100 percent to 3 percent. The contribution made in this thesis would enable agent application and behaviour change intervention designers to make scientific reasoning and predictions. Likewise, it provides a guideline for software designers on the development of agent-based applications that may not have psychological reactance

Republican Monsters: The Cultural Construction of American Positivist Criminology, 1767-1920

This dissertation examines the history of and cultural influences on positivist criminology in the United States. From Benjamin Rush to the present day, the U.S. has produced an extensive corpus of empirical and theoretical studies that seeks to discern an objective, scientifically-grounded basis for criminal behavior. American positivist criminology has drawn on numerous subfields and theories, including rational choice / economic theory, biology, and psychology, but in all cases, maintains that a purely scientific explanation of offending is possible. This study proceeds from the perspective that divisions between scientific and non-scientific thought are untenable. Drawing on scholarship in literary criticism and sociology, I argue that positivist criminology confronts an inherent contradiction in purporting to develop a purely scientific account of phenomena that are defined by the moral and cultural sentiments of a society. I thus hypothesize that positivist criminology is in fact reliant on the irrational and fictive cultural tropes and images of crime that it claims to exorcize. The dissertation proceeds by reviewing the literature on the history of criminology, developing a set of functional types or tropes for character analysis, and then examining four separate periods in the development of scientific criminology: eighteenth century studies of rational action, nineteenth century studies of defective reasoning, early twentieth century studies of race and crime, and the development of scientifically informed criminalistics programs. Each of these cases captures a different period and focus in the development of scientific criminology. In threading continuity between these cases, I show how criminological positivism is consistently reliant on culturally informed tropes and characters to render itself sensible and coherent

Agency and structure in Zygmunt Bauman’s Modernity and the Holocaust.

The article explores how in Modernity and the Holocaust to his liquid turn\ud writings Zygmunt Bauman’s work assumes that people live in a deterministic\ud world. Bauman fails to distinguish agency as an analytical category in its own\ud right and as such fails to capture self-determination, agential control and moral\ud responsibility. All of Bauman’s work is based upon the assumption that the\ud individual loses their autonomy and the ability to judge the moral content of their\ud actions because of adiaphortic processes external to themselves as individuals\ud giving rise to agentic state in which the individual is unable to exercise their\ud agency. In contrast to the argument in Modernity and the Holocaust this article\ud suggests that the Nazis developed a distinct communitarian ethical code rooted\ud in self-control that encouraged individuals to overcome their personal feeling\ud states, enabling them to engage in acts of cruelty to people defined as outside\ud of the community. In his post-2000 work where the emphasis is on the process\ud of liquefaction there is the same undervaluing of human agency in the face of\ud external forces reflected in Bauman’s concepts of ambivalence, fate and swarm

What Makes Complex Systems Complex?

This paper explores some of the factors that make complex systems complex. We first examine the history of complex systems. It was Aristotle’s insight that how elements are joined together helps determine the properties of the resulting whole. We find (a) that scientific reductionism does not provide a sufficient explanation; (b) that to understand complex systems, one must identify and trace energy flows; and (c) that disproportionate causality, including global tipping points, are all around us. Disproportionate causality results from the wide availability of energy stores. We discuss three categories of emergent phenomena—static, dynamic, and adaptive—and recommend retiring the term emergent, except perhaps as a synonym for creative. Finally, we find that virtually all communication is stigmergic

Computational Optimizations for Machine Learning

The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity

Nerd Ecology: Defending the Earth with Unpopular Culture

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. Drawing on a wide range of examples from literature, comics, film, television and digital media, Nerd Ecology is the first substantial ecocritical study of nerd culture’s engagement with environmental issues. Exploring such works as Star Trek, Tolkien’s Lord of the Rings, The Matrix, Joss Whedon’s Buffy the Vampire Slayer and Firefly, the fiction of Thomas Pynchon, The Hunger Games, and superhero comics such as Green Lantern and X-Men, Anthony Lioi maps out the development of nerd culture and its intersections with the most fundamental ecocritical themes. In this way Lioi finds in the narratives of unpopular culture - narratives in which marginalised individuals and communities unite to save the planet - the building blocks of a new environmental politics in tune with the concerns of contemporary ecocritical theory and practice

The Montclarion, March 18, 1999

Student Newspaper of Montclair State Universityhttps://digitalcommons.montclair.edu/montclarion/1840/thumbnail.jp