The Implications of Interactions for Science and Philosophy

Reductionism has dominated science and philosophy for centuries. Complexity has recently shown that interactions---which reductionism neglects---are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply non-reductionism, non-materialism, non-predictability, non-Platonism, and non-nihilism. As alternatives to each of these, holism, informism, adaptation, contextuality, and meaningfulness are put forward, respectively. A worldview that includes interactions not only describes better our world, but can help to solve many open scientific, philosophical, and social problems caused by implications of reductionism.Comment: 12 pages, 2 figure

On microelectronic self-learning cognitive chip systems

After a brief review of machine learning techniques and applications, this Ph.D. thesis examines several approaches for implementing machine learning architectures and algorithms into hardware within our laboratory. From this interdisciplinary background support, we have motivations for novel approaches that we intend to follow as an objective of innovative hardware implementations of dynamically self-reconfigurable logic for enhanced self-adaptive, self-(re)organizing and eventually self-assembling machine learning systems, while developing this new particular area of research. And after reviewing some relevant background of robotic control methods followed by most recent advanced cognitive controllers, this Ph.D. thesis suggests that amongst many well-known ways of designing operational technologies, the design methodologies of those leading-edge high-tech devices such as cognitive chips that may well lead to intelligent machines exhibiting conscious phenomena should crucially be restricted to extremely well defined constraints. Roboticists also need those as specifications to help decide upfront on otherwise infinitely free hardware/software design details. In addition and most importantly, we propose these specifications as methodological guidelines tightly related to ethics and the nowadays well-identified workings of the human body and of its psyche

The Capabilities of Chaos and Complexity

To what degree could chaos and complexity have organized a Peptide or RNA World of crude yet necessarily integrated protometabolism? How far could such protolife evolve in the absence of a heritable linear digital symbol system that could mutate, instruct, regulate, optimize and maintain metabolic homeostasis? To address these questions, chaos, complexity, self-ordered states, and organization must all be carefully defined and distinguished. In addition their cause-and-effect relationships and mechanisms of action must be delineated. Are there any formal (non physical, abstract, conceptual, algorithmic) components to chaos, complexity, self-ordering and organization, or are they entirely physicodynamic (physical, mass/energy interaction alone)? Chaos and complexity can produce some fascinating self-ordered phenomena. But can spontaneous chaos and complexity steer events and processes toward pragmatic benefit, select function over non function, optimize algorithms, integrate circuits, produce computational halting, organize processes into formal systems, control and regulate existing systems toward greater efficiency? The question is pursued of whether there might be some yet-to-be discovered new law of biology that will elucidate the derivation of prescriptive information and control. “System” will be rigorously defined. Can a low-informational rapid succession of Prigogine’s dissipative structures self-order into bona fide organization

Physical pixels

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000.Includes bibliographical references (leaves 48-51).The picture element, or pixel, is a conceptual unit of representation for digital information. Like all data structures of the computer, pixels are invisible and therefore require an output device to be seen. The physical unit of display, or physical pixel, can be any form that makes the pixel visible. Pixels are often represented as the electronically addressable phosphors of a video monitor, but the potential for different visualizations inspires the development of novel phenotypes. Four new systems of physical pixels are presented: Nami, Peano, the Digital Palette and 20/20 Refurbished. In each case, the combination of material, hardware and software design results in a unique visualization of computation. The chief contribution of this research is the articulation of a mode of artistic practice in which custom units of representation integrate physical and digital media to engender a new art.by Kelly Bowman Heaton.S.M

UB Breakthroughs Spring 2014

The UB Breakthroughs newsletter for spring of 2014. This issue contains articles discussing professor Perle's study into chiropractic manipulation of the ankle and its effect on walking, Dr. Mahmood and Dr. Sobh’s work on facial recognition software, professor Lehman’s book about Tom Thumb, Dr. Li’s research into reduced gravity sample holder/manipulation tool for NASA’s Deep Space Geo-Lab, Dr. Robert Riggs’ research in Najaf, Iraq and its influence on global Shi’ite communities, Dr. Faezipour’s research into using smartphone technology to a Virtual Reality biofeedback tool for lung cancer and other breathing disorders, Dr. Gherasimova’s research into the semiconducting properties of germanium, professor Martignetti’s research into music education in inner-city schools, Dr. McAdam’s research into the relationship gap between IT and non-IT employees in a corporate environment, Dr. Ryan and Director Lopez’s research into substance abuse and HIV infection and group-level prevention programming for college students, Dr. Patra’s research into nanostructures to advance technology and medicine, and the collaboration of UB professors to create a new experimental course in New Product Commercialization for engineering, business, and design students

OpenWorm: overview and recent advances in integrative biological simulation of Caenorhabditis elegans

The adoption of powerful software tools and computational methods from the software industry by the scientific research community has resulted in a renewed interest in integrative, large-scale biological simulations. These typically involve the development of computational platforms to combine diverse, process-specific models into a coherent whole. The OpenWorm Foundation is an independent research organization working towards an integrative simulation of the nematode Caenorhabditis elegans, with the aim of providing a powerful new tool to understand how the organism's behaviour arises from its fundamental biology. In this perspective, we give an overview of the history and philosophy of OpenWorm, descriptions of the constituent sub-projects and corresponding open-science management practices, and discuss current achievements of the project and future directions. This article is part of a discussion meeting issue ‘Connectome to behaviour: modelling C. elegans at cellular resolution’

Agricultural land systems : modelling past, present and future regional dynamics

This thesis arises from the understanding of how the integration of concepts, tools, techniques, and methods from geographic information science (GIS) can provide a formalised knowledge base for agricultural land systems in response to future agricultural and food system challenges. To that end, this thesis focuses on understanding the potential application of GIS-based approaches and available spatial data sources for modelling regional agricultural land-use and production dynamics in Portugal. The specific objectives of this thesis are addressed in seven chapters in Parts II through V, each corresponding to one scientific article that was either published or is being considered for publication in peer-reviewed international scientific journals. In Part II, Chapter 2 summarises the body of knowledge and provides the context for the contribution of this thesis within the scientific domain of agricultural land systems. In Part III, Chapters 3 and 4 explore remotely sensed and Volunteered Geographic Information (VGI) data, multitemporal and multisensory approaches, and a variety of statistical methods for mapping, quantifying, and assessing regional agricultural land dynamics in the Beja district. In Part IV, Chapters 5–7 explore the CA-Markov model, Markov chain model, machine learning, and model-agnostic approach, as well as a set of spatial metrics and statistical methods for modelling the factors and spatiotemporal changes of agricultural land use in the Beja district. In Part V, Chapter 8 explores an area-weighting GIS-based technique, a spatiotemporal data cube, and statistical methods to model the spatial distribution across time for regional agricultural production in Portugal. The case studies in the thesis contribute practical and theoretical knowledge by demonstrating the strengths and limitations of several GIS-based approaches. Together, the case studies demonstrate the underlying principles that underpin each approach in a way that allows us to infer their potentiality and appropriateness for modelling regional agricultural land-use and production dynamics, stimulating further research along this line. Generally, this thesis partly reflects the state-of-art of land-use modelling and contribute significantly to the introduction of advances in agricultural system modelling research and land-system science

Considerations in designing a cybernetic simple 'learning' model; and an overview of the problem of modelling learning

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Learning is viewed as a central feature of living systems and must be manifested in any artifact that claims to exhibit general intelligence. The central aims of the thesis are twofold: (1) - To review and critically assess the empirical and theoretical aspects of learning as have been addressed in a multitude of disciplines, with the aim of extracting fundamental features and elements. (2) - To develop a more systematic approach to the cybernetic modelling of learning than has been achieved hitherto. In pursuit of aim (1) above the following discussions are included: Historical and Philosophical backgrounds; Natural learning, both physiological and psychological aspects; Hierarchies of learning identified in the evolutionary, functional and developmental senses; An extensive section on the general problem of modelling of learning and the formal tools, is included as a link between aims (1) and (2). Following this a systematic and historically oriented study of cybernetic and other related approaches to the problem of modelling of learning is presented. This then leads to the development of a state-of-the-art general purpose experimental cybernetic learning model. The programming and use of this model is also fully described, including an elaborate scheme for the manifestation of simple learning