Homo Sapiens, Homo Faber and Homo Dictyous. Creatively united by computing science

The present essay is a reflection inspired by the excellent book “Human Face of Computing” (editor Cristian S. Calude, published by Imperial College, Press, 2016) that is the outcome of a participatory exploration carried out by and insider (C. Calude) on the history of computing science with with its wide and deep ramification that are influencing all human activities. The book is based on interviews with outstanding researchers in computing science, mathematics, Internet, physics and technological sciences who have landmark contributions to computing science and are deeply interested in its applications, impact, uses and abuses in social life. The book explores the consequences of this field on the quality, production and democratization of knowledge

Impact of Membrane Computing and P Systems in ISI WoS. Celebrating the 65th Birthday of Gheorghe Păun

Membrane Computing is a branch of Computer Science initiated by Gheorghe Păun in 1998, in a technical report of Turku Centre for Computer Science published as a journal paper ("Computing with Membranes" in Journal of Computer and System Sciences) in 2000. Membrane systems, as Gheorghe Păun called the models he has introduced, are known nowadays as "P Systems" (with the letter P coming from the initial of the name of this research area "father"). This note is an overview of the impact in ISI WoS of Gheorghe Păun’s works, focused on Membrane Computing and P Systems field, on the occasion of his 65th birthday anniversary

Hollins Columns (1982 Feb 8)

Table of Contents: General Speakers Considers Spring Semester Refugees Flee Flood Campus Debates Equal Rights Amendment Insurance May Cover Flood Damages The Equal Rights Amendment Library Offers Films Conservative Paper Stirs Dartmouth The Dartmouth Review New Ideas Merit Hearing Controversial Speakers Needed At Hollins Points of View: General Speakers Fund: A Cause For Student Expression Student Endorses Ratification Abroaders\u27 Experience Unites Junior Class On The Spot French Dept. Sponsors Film N.Y. News Crossword Puzzle Students Discuss Reasons For Transferring Pol Sci Scholars Reveal Results Hollins E.R.A. Poll Results Theatre Arts Captures Blithe Spirit Hollins Celebrates City History Happy Valentines Day State Police Art Exhibit Emphasizes Spacehttps://digitalcommons.hollins.edu/newspapers/2151/thumbnail.jp

Ideologies of computer scientists and technologists (Correctness beyond reason)

Ideologies of computer scientists and technologist

Grigore C. Moisil: A Life Becoming a Myth

Grigore C. Mosil, Romanian mathematician, Professor at the University of Bucharest - Faculty of Mathematicsand Computer Science, member of the Romanian Academy, member of the Academy of Sciencesin Bologna and of the International Institute of Philosophy, Computer Pioneer Award of IEEE ComputerSociety (IEEE - 1996)

Supplementary schools as spaces of hope for a more inclusive world: Challenging exclusion and social injustice in multilingual London

Following a contextualisation of multilingual London, I will explore the ways in which many of London’s – and indeed the UK’s – language communities and the languages they speak suffer marginalisation and exclusion. Based on an exploration of language education policy, the article employs the construct of “monolingual habitus” (Gogolin 2002), which, whilst tending to monolingualise multilingualism, also offers insights into how the habitus might be shifted. Despite the structural forces at play, I argue that, through their supplementary schools, the language communities themselves can be conceived of as “spaces of hope”, able to challenge the constraints they encounter in order to ensure that their languages continue to be spoken and learnt. I support this argument by first considering their creative educational and cultural practices, and then the ways in which they act as spaces of resistance to the challenges they face. However, I also maintain that they have the potential to play a role in shifting the monolingual habitus beyond their communities, co-creating a more linguistically inclusive society. Further research is needed, however, to understand the processes that may be conducive to this shift and lead to a more inclusive and socially just world

Social conditions of outstanding contributions to computer science : a prosopography of Turing Award laureates (1966-2016)

The Turing Award, commonly described as computer science's highest award and equivalent of the Nobel prize in that discipline, has now been awarded for half a century. In the following, we describe the social regularities that underlie and the conditions that embed these high achievements in computer science innovation. We find, contrary to a meritocratic ideal of one's only abilities determining success or recognition within sciences, that several characteristics of scientists, exogenous and non-exogenous alike to their scientific work and identities, are of overbearing or disproportionate importance in defining academic acknowledgement. We find in particular that nationality or birth place, gender and one's network have a big role in making Turing Award laureates. As do social origins, with a significant portion of Turing Award winners coming primarily from middle- and upper-class family backgrounds, especially households with significant cultural capital i.e. one or both parents hold an advanced degree or are engaged in an academic profession). Reviewing the data before us, we were also unable to ignore the non-participation of visible minorities and non-white computer scientists to the body of Turing Award recipients. In short, place of birth, nationality, gender, social background, "race" and networks play a role in making Turing Award laureates. This paper also explores the ways in which a social history or sociology of computer science and the wider technology sector may unfold in the future, by discussing theoretical implications, methods and sources

The Interrogative Force of the Individual and Societal Memories of the Armenian Genocide Versus Long-Term Denial

Mega-violent actions against individuals, communities and nations, such as genocides under different forms, leave traces that can be located at various levels of social complexity from individual to societal (including global) levels and become part of the memorization, remembering and commemorative processes. I assume that the individual and societal memories of genocide form a dynamic field that nurtures the interrogative force that opposes the denial of any genocide. The interrogative force is activated by the wide range of cognitive dissonances that emerge at all levels of social complexity between the memories about any genocide and its denial by various individual and collective actors. The study explores the interrogative force of individual and societal memories in the case of the genocide suffered by the Armenians. Individual and societal memories are approached within the wider context provided by traces (physical, archeological, human remains, written, oral and iconic records), memories, remembering and commemorative processes. The study uses findings of previous research on various records and the technique of self- inquiry that gives to the participants the possibility to generate their own questions about the Genocide suffered by the Armenians. The study suggests that the interrogative force opposes denial and it increases as more individual and collective actors from different levels of social complexity are entering into the field of inquiry due to multiple cognitive dissonances that are identified during a long-term denial of genocide

Deep Multi Temporal Scale Networks for Human Motion Analysis

The movement of human beings appears to respond to a complex motor system that contains signals at different hierarchical levels. For example, an action such as ``grasping a glass on a table'' represents a high-level action, but to perform this task, the body needs several motor inputs that include the activation of different joints of the body (shoulder, arm, hand, fingers, etc.). Each of these different joints/muscles have a different size, responsiveness, and precision with a complex non-linearly stratified temporal dimension where every muscle has its temporal scale. Parts such as the fingers responds much faster to brain input than more voluminous body parts such as the shoulder. The cooperation we have when we perform an action produces smooth, effective, and expressive movement in a complex multiple temporal scale cognitive task. Following this layered structure, the human body can be described as a kinematic tree, consisting of joints connected. Although it is nowadays well known that human movement and its perception are characterised by multiple temporal scales, very few works in the literature are focused on studying this particular property. In this thesis, we will focus on the analysis of human movement using data-driven techniques. In particular, we will focus on the non-verbal aspects of human movement, with an emphasis on full-body movements. The data-driven methods can interpret the information in the data by searching for rules, associations or patterns that can represent the relationships between input (e.g. the human action acquired with sensors) and output (e.g. the type of action performed). Furthermore, these models may represent a new research frontier as they can analyse large masses of data and focus on aspects that even an expert user might miss. The literature on data-driven models proposes two families of methods that can process time series and human movement. The first family, called shallow models, extract features from the time series that can help the learning algorithm find associations in the data. These features are identified and designed by domain experts who can identify the best ones for the problem faced. On the other hand, the second family avoids this phase of extraction by the human expert since the models themselves can identify the best set of features to optimise the learning of the model. In this thesis, we will provide a method that can apply the multi-temporal scales property of the human motion domain to deep learning models, the only data-driven models that can be extended to handle this property. We will ask ourselves two questions: what happens if we apply knowledge about how human movements are performed to deep learning models? Can this knowledge improve current automatic recognition standards? In order to prove the validity of our study, we collected data and tested our hypothesis in specially designed experiments. Results support both the proposal and the need for the use of deep multi-scale models as a tool to better understand human movement and its multiple time-scale nature

Reinventing the Social Scientist and Humanist in the Era of Big Data

This book explores the big data evolution by interrogating the notion that big data is a disruptive innovation that appears to be challenging existing epistemologies in the humanities and social sciences. Exploring various (controversial) facets of big data such as ethics, data power, and data justice, the book attempts to clarify the trajectory of the epistemology of (big) data-driven science in the humanities and social sciences