scholarly journals 10 Causal Models for Life: Physics, Life Science, Urbanism, Humanities.

2021 ◽  
Author(s):  
Dan Costa Baciu
Keyword(s):  
Cultural Studies ◽  
Life Science ◽  
Computer Systems ◽  
Nerve Cells ◽  
Causal Models ◽  
Causal Modeling ◽  
Digital Systems ◽  
Digital Signals ◽  
Unified Framework ◽  
Present Text

Creativity is found in artworks as well as in the color-ful feathers of paradise birds. Diversity is found in ecosystems as well as in cities. Digital signals are found in nerve cells as well as in computer systems. Can causal models explain why life is at once creative and diverse, and why it uses digital systems? This present text builds on common empirical observations as well as long accumulated modeling experience to develop a unified framework for causal modeling that applies to all sciences including physics, biology, and cultural studies. In this framework, life can be diverse, creative, and digital all at once.

scholarly journals Causal flow models for life

2021 ◽  
Author(s):  
Dan Costa Baciu
Keyword(s):  
Causal Models ◽  
Causal Modeling ◽  
Unified Framework ◽  
Flow Models ◽  
The City

Causality applies everywhere, and it is hard even to imagine a world in which it does not. Yet, one must acknowledge that life also is creative and diverse. Un-der these circumstances, the question emerges whether causal models can ex-plain life's creativity and diversity. Some life scientists say yes, yet many hu-manities scholars cast doubts or have posited that they have reached the end of theory. Here, I build on common empirical observations as well as long-accumulated modeling experience, and I review and further develop a unified framework for causal modeling that applies to all sciences including physics, biology, the sciences of the city, and the humanities.

scholarly journals Optimizing Consistency and Coverage in Configurational Causal Modeling

2021 ◽  
pp. 004912412199555
Author(s):  
Michael Baumgartner ◽  
Mathias Ambühl
Keyword(s):  
Model Selection ◽  
Causal Inference ◽  
Comparative Methods ◽  
Causal Models ◽  
Causal Modeling ◽  
Model Fit

Consistency and coverage are two core parameters of model fit used by configurational comparative methods (CCMs) of causal inference. Among causal models that perform equally well in other respects (e.g., robustness or compliance with background theories), those with higher consistency and coverage are typically considered preferable. Finding the optimally obtainable consistency and coverage scores for data [Formula: see text], so far, is a matter of repeatedly applying CCMs to [Formula: see text] while varying threshold settings. This article introduces a procedure called ConCovOpt that calculates, prior to actual CCM analyses, the consistency and coverage scores that can optimally be obtained by models inferred from [Formula: see text]. Moreover, we show how models reaching optimal scores can be methodically built in case of crisp-set and multi-value data. ConCovOpt is a tool, not for blindly maximizing model fit, but for rendering transparent the space of viable models at optimal fit scores in order to facilitate informed model selection—which, as we demonstrate by various data examples, may have substantive modeling implications.

scholarly journals Toward a Juris-cultural Studies of Human Rights

2021 ◽  
Vol 6 (SI) ◽  
pp. 3-14
Author(s):  
John Nguyet Erni
Keyword(s):  
Cultural Studies ◽  
New Media ◽  
Teaching And Learning ◽  
Legal Theory ◽  
Cultural Analysis ◽  
Court Case ◽  
Cultural Critique ◽  
Unified Framework ◽  
Legal Norms ◽  
National University

This special issue grew out of an advanced seminar on Cultural Studies that I guest-taught at the National University of Singapore in 2018, where there has been a long-time engagement with interdisciplinary teaching and learning in the field of Cultural Studies through NUS’s Asian Research Institute (and more recently through the university’s Department of Communication and New Media). The essays collected here represent a collection of sincere efforts to reframe political and ethical crises through a unified framework that can be called juris-cultural studies of law and rights. By “juris-cultural,” I refer to a genre of critical cultural analysis that investigates the mutually constitutive nature of law and culture, through dissecting “law as culture” in which cultural signifying practices are traceable to the presence or absence of legal norms, as well as through “culture as law” in which the contested meanings of cultural communities, their practices and politics, can shape or even dictate social norms and regulations. It is both a political language and a method that avoids separating law and culture but confronts their uneasy entanglements. The essays are united by a common critical method of combining critical legal theory with a cultural critique of law. Each essay centers on a particular court case, and performs critical reading of the legal logics and reasoning alongside a broader attention to social and cultural ideologies and power relations that overdetermine the outcome of the court judgment. The insights produced by such a method will hopefully present to readers an innovative approach adequate to the task of bringing the problems of rights, legal subjectivities, and critical justice squarely to the doorsteps of Cultural Studies.

Algorithms with Possibilities of Selflearning and Selfmodification

1983 ◽  
Vol 6 (1) ◽  
pp. 1-44
Author(s):  
Eugeniusz Eberbach
Keyword(s):  
Complex System ◽  
Elastic Properties ◽  
Digital Computer ◽  
Computer Systems ◽  
The State ◽  
Digital System ◽  
Digital Systems ◽  
Abstract Model ◽  
Tolerance Spaces ◽  
Variant Structure

This paper concerns a concept of selfperfecting and selflearning of digital computer systems. This idea is not new, but continuously in the state of elaborations. Such systems, i.e. with a possibility of selflearning and selfmodification would have undoubtedly greater possibilities and elastic properties in their behaviour than traditional digital systems. In the paper a digital system is treated as a complex system of algorithms. As an abstract model of real algorithms. so called Mazurkiewicz FC-algorithm is considered. FC-algorithms used in the paper have been extended to modifiable Fe-algorithms by adding a time-variant structure and the use of the notion of tolerance spaces. This structure allowed us to introduce a model of learning for modifiable FC-algorithms. Learning is understood as a goal directed process of changes of activities on the basis of experience.

MANAGING QUALITY AND NETWORK EFFECTS IN THE HIGH-TECH MARKET: THE CASE OF RESEARCH AND DEVELOPMENT TOOLS IN LIFE SCIENCE INDUSTRY

2012 ◽  
Vol 16 (02) ◽  
pp. 1250009 ◽  
Author(s):  
YANSONG HU ◽  
DAMIEN McLOUGHLIN
Keyword(s):  
Social Network ◽  
Research And Development ◽  
Network Effects ◽  
Life Science ◽  
Current Theory ◽  
Third Party ◽  
Network Effect ◽  
High Tech ◽  
Unified Framework ◽  
Development Tools

We seek to extend current theory on research and development (R&D) tools and create new insights by adopting a multi-disciplinary approach and drawing from literatures on quality and network effects in the high-tech market. More specifically, we use a unified framework on quality and network effects, and examine two forms of quality effects (third party quality reviews and company-advertised quality) and two types of network effects (network externalities effect and social network effect) in driving the popularity and success of R&D tools. By tracking two categories of R&D tools in the life science industry for a decade, our research provides a sharper understanding of R&D tools and therefore can help R&D tool producers to accelerate the market acceptance of their new tools, which should promote faster innovation and ultimately benefit the whole R&D community.

scholarly journals On the Expressiveness of some Runtime Validation Techniques

10.29007/j7qv ◽  
2018 ◽  
Author(s):  
Yliès Falcone ◽  
Jean-Claude Fernandez ◽  
Mounier Laurent
Keyword(s):  
Computer Systems ◽  
Runtime Verification ◽  
Unified Framework ◽  
The Real ◽  
Runtime Enforcement ◽  
Common Features ◽  
Abstract Level ◽  
Runtime Validation ◽  
Execution Environment

Runtime validation techniques have been proposed as artifacts to detect and/or correct unforeseen behaviours of computer systems.Their common features is to give only partial validation results, based on a restricted set of system executions produced in the real execution environment. A key issue is thus to better understand which kind of properties can (or cannot) be validated using such techniques.We focus on three techniques known as runtime verification, property-oriented testing, and runtime enforcement. We present these approaches at an abstract level and in a unified framework, and we discuss their respective ability to deal with properties on infinite execution sequences, that are commonly encountered in many application domains.

scholarly journals Combining Reinforcement Learning and Causal Models for Robotics Applications

2021 ◽  
Author(s):  
Arquímides Méndez-Molina
Keyword(s):  
Reinforcement Learning ◽  
Learning Task ◽  
Learning Processes ◽  
Causal Models ◽  
Causal Modeling ◽  
Application Area ◽  
Service Robotics ◽  
Preliminary Results ◽  
Starting Point ◽  
Good Starting Point

The relation between Reinforcement learning (RL) and Causal Modeling(CM) is an underexplored area with untapped potential for any learning task. In this extended abstract of our Ph.D. research proposal, we present a way to combine both areas to improve their respective learning processes, especially in the context of our application area (service robotics). The preliminary results obtained so far are a good starting point for thinking about the success of our research project.

scholarly journals Time and causality in the social sciences

2021 ◽  
pp. 0961463X2110294
Author(s):  
Guillaume Wunsch ◽  
Federica Russo ◽  
Michel Mouchart ◽  
Renzo Orsi
Keyword(s):  
Social Sciences ◽  
Causal Structure ◽  
Causal Models ◽  
Causal Modeling ◽  
Temporal Information ◽  
Causal Mechanism ◽  
Generative Process ◽  
The Social ◽  
Causal Ordering ◽  
Modeling Strategy

This article deals with the role of time in causal models in the social sciences. The aim is to underline the importance of time-sensitive causal models, in contrast to time-free models. The relation between time and causality is important, though a complex one, as the debates in the philosophy of science show. In particular, an outstanding issue is whether one can derive causal ordering from time ordering. The article examines how time is taken into account in demography and in economics as examples of social sciences in which considerations about time may diverge. We then present structural causal modeling as a modeling strategy that, while not essentially based on temporal information, can incorporate it in a more or less explicit way. In particular, we argue that temporal information is useful to the extent that it is placed in a correct causal structure, thus further corroborating the causal mechanism or generative process explaining the phenomenon under consideration. Despite the fact that the causal ordering of variables is more relevant than the temporal order for explanatory purposes, in establishing causal ordering the researcher should nevertheless take into account the time-patterns of causes and effects, as these are often episodes rather than single events. For this reason in particular, it is time to put time at the core of our causal models.

A unified framework for the performability evaluation of fault-tolerant computer systems

1993 ◽  
Vol 42 (3) ◽  
pp. 312-326 ◽  
Author(s):  
K.R. Pattipati ◽  
Y. Li ◽  
H.A.P. Blom
Keyword(s):  
Fault Tolerant ◽  
Computer Systems ◽  
Unified Framework

Education in the Digital Age: A Driving Force or a Lost Place

i-com ◽  
2021 ◽  
Vol 20 (3) ◽  
pp. 263-277
Author(s):  
Michael Herczeg
Keyword(s):  
Higher Education ◽  
Driving Force ◽  
Teaching And Learning ◽  
Computer Systems ◽  
Interactive Media ◽  
Digital Age ◽  
Constructivist Learning ◽  
Digital Systems ◽  
Educational Technologies

Abstract Teaching and learning using computer systems has a long tradition. This contribution will discuss major challenges and changes of the last 20 years to derive consequences and ideas for the next 20 years. The development of digital educational technologies will be outlined and the deficiencies and potentials of learning with digital systems and environments will be discussed. Finally, a media framework that enables for post-constructivist learning in the 21st century will be presented. The contribution focuses on interactive media in the context of schools, laying the foundation for digital competences for higher education and workplaces.

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