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 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 Street context of various demographic groups in their daily mobility

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Ariel Salgado ◽  
Weixin Li ◽  
Fahad Alhasoun ◽  
Inés Caridi ◽  
Marta Gonzalez
Keyword(s):  
Geographical Information Systems ◽  
Building Blocks ◽  
Geographical Information ◽  
Unified Framework ◽  
Demographic Groups ◽  
Daily Mobility ◽  
Urban Science ◽  
Science Framework ◽  
The City ◽  
Racial Ethnic

AbstractWe present an urban science framework to characterize phone users’ exposure to different street context types based on network science, geographical information systems (GIS), daily individual trajectories, and street imagery. We consider street context as the inferred usage of the street, based on its buildings and construction, categorized in nine possible labels. The labels define whether the street is residential, commercial or downtown, throughway or not, and other special categories. We apply the analysis to the City of Boston, considering daily trajectories synthetically generated with a model based on call detail records (CDR) and images from Google Street View. Images are categorized both manually and using artificial intelligence (AI). We focus on the city’s four main racial/ethnic demographic groups (White, Black, Hispanic and Asian), aiming to characterize the differences in what these groups of people see during their daily activities. Based on daily trajectories, we reconstruct most common paths over the street network. We use street demand (number of times a street is included in a trajectory) to detect each group’s most relevant streets and regions. Based on their street demand, we measure the street context distribution for each group. The inclusion of images allows us to quantitatively measure the prevalence of each context and points to qualitative differences on where that context takes place. Other AI methodologies can further exploit these differences. This approach presents the building blocks to further studies that relate mobile devices’ dynamic records with the differences in urban exposure by demographic groups. The addition of AI-based image analysis to street demand can power up the capabilities of urban planning methodologies, compare multiple cities under a unified framework, and reduce the crudeness of GIS-only mobility analysis. Shortening the gap between big data-driven analysis and traditional human classification analysis can help build smarter and more equal cities while reducing the efforts necessary to study a city’s characteristics.

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 We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257534
Author(s):  
Andres Sevtsuk ◽  
Rounaq Basu ◽  
Bahij Chancey
Keyword(s):  
Built Environment ◽  
Urban Form ◽  
Weather Conditions ◽  
Data Availability ◽  
Pedestrian Flow ◽  
Development Activity ◽  
Flow Models ◽  
Urban Quality Of Life ◽  
Traffic Impact ◽  
The City

Cities are increasingly promoting walkability to tackle climate change, improve urban quality of life, and address socioeconomic inequities that auto-oriented development tends to exacerbate, prompting a need for predictive pedestrian flow models. This paper implements a novel network-based pedestrian flow model at a property-level resolution in the City of Melbourne. Data on Melbourne’s urban form, land-uses, amenities, and pedestrian walkways as well as weather conditions are used to predict pedestrian flows between different land-use pairs, which are subsequently calibrated against hourly observed pedestrian counts from automated sensors. Calibration allows the model extrapolate pedestrian flows on all streets throughout the city center based on reliable baseline observations, and to forecast how new development projects will change existing pedestrian flows. Longitudinal data availability also allows us to validate how accurate such predictions are by comparing model results to actual pedestrian counts observed in following years. Updating the built-environment data annually, we (1) test the accuracy of different calibration techniques for predicting foot-traffic on the city’s streets in subsequent years; (2) assess how changes in the built environment affect changes in foot-traffic; (3) analyze which pedestrian origin-destination flows explain observed foot-traffic during three peak weekday periods; and (4) assess the stability of model predictions over time. We find that annual changes in the built environment have a significant and measurable impact on the spatial distribution of Melbourne’s pedestrian flows. We hope this novel framework can be used by planners to implement “pedestrian impact assessments” for newly planned developments, which can complement traditional vehicular “traffic impact assessments”.

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.

scholarly journals The Effectiveness of Supervision on Islamic Education (PAI) Teacher's Performance of Junior High School (SMP) in Pangkalpinang

2019 ◽  
Vol 2 (1) ◽  
pp. 40-50
Author(s):  
Sri Mardiyah
Keyword(s):  
High School ◽  
Junior High School ◽  
Junior High ◽  
Islamic Education ◽  
Basic Principles ◽  
Flow Models ◽  
Qualitative Descriptive ◽  
The Many ◽  
The City

This paper is based on the many problems that occur in the implementation of the supervision of teaching junior high school Islamic education in the city of Pangkalpinang. Teaching supervision as a form of assistance and guidance to teachers to develop their abilities in the learning process has not been giving a significant impact in improving the quality of Islamic Education (PAI) learning. For this reason, a qualitative descriptive study was conducted on two state junior high schools that had different characters and qualities. Data and information are collected through unstructured interviews, unstructured observation, and documentation. Furthermore, the data is processed and analyzed descriptively through interactively as the Miles and Huberman flow models, namely data reduction, data display, and conclusion. The results of data analysis showed that the supervision of PAI teaching in these two schools was still administrative. As a result, teaching supervision tends to be a mere formality and the basic principles have not been properly implemented. Naturally, the supervision of PAI teaching has not had a significant impact on PAI teachers, both due to supervisory competence and teacher readiness. However, there are also factors that are felt to be quite supportive, such as the commitment of supervisors in the midst of the limited number and desire of teachers to develop. Furthermore, based on the disclosure of facts on this issue, it is expected to be the basis of evaluation and efforts to improve the implementation of teaching supervision in the Junior High School in Pangkalpinang City, especially in Islamic Education Subjects.

scholarly journals STREETGEN: IN-BASE PROCEDURAL-BASED ROAD GENERATION

2015 ◽  
Vol II-3/W5 ◽  
pp. 409-416 ◽  
Author(s):  
R. Cura ◽  
J. Perret ◽  
N. Paparoditis
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Input Data ◽  
State Of The Art ◽  
Geographic Information ◽  
Unified Framework ◽  
Cultural Activities ◽  
Simple Hypothesis ◽  
Gis Data ◽  
The City

Streets are large, diverse, and used for conflicting transport modalities as well as social and cultural activities. Proper planning is essential and requires data. Manually fabricating data that represent streets (street reconstruction) is error-prone and time consuming. Automatising street reconstruction is a challenge because of the diversity, size, and scale of the details (~ cm for cornerstone) required. The state-of-the-art focuses on roads and is strongly oriented by each application (simulation, visualisation, planning). We propose a unified framework that works on real Geographic Information System (GIS) data and uses a strong, yet simple hypothesis when possible to produce coherent street modelling at the city scale or street scale. Because it is updated only locally in subsequent computing, the result can be improved by adapting input data and the parameters of the model. We reconstruct the entire Paris streets in a few minutes and show how the results can be edited simultaneously by several concurrent users.

Hospitals: N.Y. Appellate Court Denies Move to Privatize Public Hospital

1999 ◽  
Vol 27 (2) ◽  
pp. 202-203
Author(s):  
Robert Chatham
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Public Health System ◽  
Municipal Hospital ◽  
The Public ◽  
Public Benefit ◽  
For Profit ◽  
Benefit Corporation ◽  
The City

The Court of Appeals of New York held, in Council of the City of New York u. Giuliani, slip op. 02634, 1999 WL 179257 (N.Y. Mar. 30, 1999), that New York City may not privatize a public city hospital without state statutory authorization. The court found invalid a sublease of a municipal hospital operated by a public benefit corporation to a private, for-profit entity. The court reasoned that the controlling statute prescribed the operation of a municipal hospital as a government function that must be fulfilled by the public benefit corporation as long as it exists, and nothing short of legislative action could put an end to the corporation's existence.In 1969, the New York State legislature enacted the Health and Hospitals Corporation Act (HHCA), establishing the New York City Health and Hospitals Corporation (HHC) as an attempt to improve the New York City public health system. Thirty years later, on a renewed perception that the public health system was once again lacking, the city administration approved a sublease of Coney Island Hospital from HHC to PHS New York, Inc. (PHS), a private, for-profit entity.

ASHA Convention 2013

ASHA Leader ◽  
2013 ◽  
Vol 18 (7) ◽  
pp. 46-48
Keyword(s):  
Ice Cream ◽  
Annual Convention ◽  
The City ◽  
Rich History

This year's Annual Convention features some sweet new twists like ice cream and free wi-fi. But it also draws on a rich history as it returns to Chicago, the city where the association's seeds were planted way back in 1930. Read on through our special convention section for a full flavor of can't-miss events, helpful tips, and speakers who remind why you do what you do.

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