A Data-Driven Approach for Modeling Agents

Agents are commonly created on a set of simple rules driven by theories, hypotheses, and assumptions. Such modeling premise has limited use of real-world data and is challenged when modeling real-world systems due to the lack of empirical grounding. Simultaneously, the last decade has witnessed the production and availability of large-scale data from various sensors that carry behavioral signals. These data sources have the potential to change the way we create agent-based models; from simple rules to driven by data. Despite this opportunity, the literature has neglected to offer a modeling approach to generate granular agent behaviors from data, creating a gap in the literature. This dissertation proposes a novel data-driven approach for modeling agents to bridge the research gap. The approach is composed of four detailed steps including data preparation, attribute model creation, behavior model creation, and integration. The connection between and within each step is established using data flow diagrams. The practicality of the approach is demonstrated with a human mobility model that uses millions of location footprints collected from social media. In this model, the generation of movement behavior is tested with five machine learning/statistical modeling techniques covering a large number of model/data configurations. Results show that Random Forest-based learning is the most effective for the mobility use case. Furthermore, agent attribute values are obtained/generated with machine learning and translational assignment techniques. The proposed approach is evaluated in two ways. First, the use case model is compared to another model which is developed using a state-of-the-art data-driven approach. The model’s prediction performance is comparable to the state-of-the-art model. The plausibility of behaviors and model structure in the use case model is found to be closer to real-world than the state-of-the-art model. This outcome indicates that the proposed approach produces realistic results. Second, a standard mobility dataset is used for driving the mobility model in place of social media data. Despite its small size, the data and model resembled the results gathered from the primary use case indicating the possibility of using different datasets with the proposed approach

A general epidemic model and its application to mask design considering different preferences towards masks

While most masks have a limited effect on personal protection, how effective are they for collective protection? How to enlighten the design of masks from the perspective of collective dynamics? In this paper, we assume three preferences in the population: (i) never wearing a mask; (ii) wearing a mask if and only if infected; (iii) always wearing a mask. We study the epidemic transmission in an open system within the Susceptible-Infected-Recovered (SIR) model framework. We use agent-based Monte Carlo simulation and mean-field differential equations to investigate the model, respectively. Ternary heat maps show that wearing masks is always beneficial in curbing the spread of the epidemic. Based on the model, we investigate the potential implications of different mask designs from the perspective of collective dynamics. The results show that strengthening the filterability of the mask from the face to the outside is more effective in most parameter spaces, because it acts on individuals with both preferences (ii) and (iii). However, when the fraction of individuals always wearing a mask achieves a critical point, strengthening the filterability from outside to the face becomes more effective, because of the emerging hidden reality that the infected individuals become too few to utilize the filterability from their face to outside fully.Comment: Complexity, 202

A Content Analysis-Based Approach to Explore Simulation Verification and Identify Its Current Challenges

Verification is a crucial process to facilitate the identification and removal of errors within simulations. This study explores semantic changes to the concept of simulation verification over the past six decades using a data-supported, automated content analysis approach. We collect and utilize a corpus of 4,047 peer-reviewed Modeling and Simulation (M&S) publications dealing with a wide range of studies of simulation verification from 1963 to 2015. We group the selected papers by decade of publication to provide insights and explore the corpus from four perspectives: (i) the positioning of prominent concepts across the corpus as a whole; (ii) a comparison of the prominence of verification, validation, and Verification and Validation (V&V) as separate concepts; (iii) the positioning of the concepts specifically associated with verification; and (iv) an evaluation of verification\u27s defining characteristics within each decade. Our analysis reveals unique characterizations of verification in each decade. The insights gathered helped to identify and discuss three categories of verification challenges as avenues of future research, awareness, and understanding for researchers, students, and practitioners. These categories include conveying confidence and maintaining ease of use; techniques\u27 coverage abilities for handling increasing simulation complexities; and new ways to provide error feedback to model users

Temporal and Spatiotemporal Investigation of Tourist Attraction Visit Sentiment on Twitter

In this paper, we propose a sentiment-based approach to investigate the temporal and spatiotemporal effects on tourists\u27 emotions when visiting a city\u27s tourist destinations. Our approach consists of four steps: data collection and preprocessing from social media; visitor origin identification; visit sentiment identification; and temporal and spatiotemporal analysis. The temporal and spatiotemporal dimensions include day of the year, season of the year, day of the week, location sentiment progression, enjoyment measure, and multi-location sentiment progression. We apply this approach to the city of Chicago using over eight million tweets. Results show that seasonal weather, as well as special days and activities like concerts, impact tourists\u27 emotions. In addition, our analysis suggests that tourists experience greater levels of enjoyment in places such as observatories rather than zoos. Finally, we find that local and international visitors tend to convey negative sentiment when visiting more than one attraction in a day whereas the opposite holds for out of state visitors

Simulation for Cybersecurity: State of the Art and Future Directions

In this article, we provide an introduction to simulation for cybersecurity and focus on three themes: (1) an overview of the cybersecurity domain; (2) a summary of notable simulation research efforts for cybersecurity; and (3) a proposed way forward on how simulations could broaden cybersecurity efforts. The overview of cybersecurity provides readers with a foundational perspective of cybersecurity in the light of targets, threats, and preventive measures. The simulation research section details the current role that simulation plays in cybersecurity, which mainly falls on representative environment building; test, evaluate, and explore; training and exercises; risk analysis and assessment; and humans in cybersecurity research. The proposed way forward section posits that the advancement of collecting and accessing sociotechnological data to inform models, the creation of new theoretical constructs, and the integration and improvement of behavioral models are needed to advance cybersecurity efforts

S-400s, Disinformation, and Anti-American Sentiment in Turkey

As social and political discourse in most countries becomes more polarized, anti-Americanism has risen not only in the Middle East and Latin America but also among the U.S. allies in Europe. Social media is one platform used to disseminate anti-American views in NATO countries, and its effectiveness can be magnified when mass media, public officials, and popular figures adopt these views. Disinformation, in particular, has gained recognition as a cybersecurity issue from 2016 onward, but disinformation can be manufactured domestically in addition to being part of a foreign influence campaign. In this paper, we analyze Turkish tweets using sentiment analysis techniques and compare the model\u27s results to the manual investigation based on qualitative research. We investigate institutional conditions, social and mass media control, and the state of political discourse in Turkey and focus on narratives pertaining to the purchase of S-400 missiles from Russia by Turkey, as well as the actors spreading these narratives, analyzing for popularity, narrative type, and bot-like behavior. Our findings suggest that although anti-American sentiment has held relatively steady in Turkey since 2003, the tightening of control over mass media networks in Turkey and the adoption of conspiratorial rhetoric by President Erdogan and his allies in the AKP from 2014 onward amplified anti-American sentiment and exacerbated negative sentiment on social media by pitting users against one another. This study and its findings are important because they highlight the importance of social and psychological components of cybersecurity. The ease by which disinformation efforts, influence operations, and other “softer” forms of cyber- and information warfare can be carried out means that they will only grow more common

A content analysis-based approach to explore simulation verification and identify its current challenges.

Verification is a crucial process to facilitate the identification and removal of errors within simulations. This study explores semantic changes to the concept of simulation verification over the past six decades using a data-supported, automated content analysis approach. We collect and utilize a corpus of 4,047 peer-reviewed Modeling and Simulation (M&S) publications dealing with a wide range of studies of simulation verification from 1963 to 2015. We group the selected papers by decade of publication to provide insights and explore the corpus from four perspectives: (i) the positioning of prominent concepts across the corpus as a whole; (ii) a comparison of the prominence of verification, validation, and Verification and Validation (V&V) as separate concepts; (iii) the positioning of the concepts specifically associated with verification; and (iv) an evaluation of verification's defining characteristics within each decade. Our analysis reveals unique characterizations of verification in each decade. The insights gathered helped to identify and discuss three categories of verification challenges as avenues of future research, awareness, and understanding for researchers, students, and practitioners. These categories include conveying confidence and maintaining ease of use; techniques' coverage abilities for handling increasing simulation complexities; and new ways to provide error feedback to model users

Compare of Structural and Functional Changes in Athletes, Hypertensive Patients and Healthy Sedentary Control Subjects

To asses cardiac structure and function in athletes, hypertensive patients and healthy sedentary control subjects by Doppler-echocardiographyOne hundred athletes, 45 hypertensive patients and 45 healthy sedentary control subjects volunteered to take part in the study, cardiac dimensions and function were determined by 2-D Doppler –echocardiography and were compared by One Way Anova test.There was not any significant relation in interventriculer septal thickness (IVST) between athletes and hypertensive patients (0,89±0.11-0,87±0.15). But there was a significant increase in athletes compared with sedentary subjects (0,89±0.11-0,77±0.14).there was a significant relation in deceleration time (DT) and in ratio of peak mitral velocity to mitral flow velocity at the time of atrial contraction (mEv/mAv) which is important for diastolic function compared three group (patients group has in favour of diastolic dysfunction, the other groups has normal limits of DT and mEv/mAv. Values of DT respectively athletes, patients, sedentary group (154±24, 240±54, 210±39). Values of mEv/mAv respectively athletes, patients, sedentary group (1.5±0.2, 1.1±0.2, 1.0±01).Although sedentary subject’s IVST was normal, athletes and hypertensive patients had increased IVST; but these increases did not impair diastolic function of heart also diastolic parameters in sedentary subjects was bigger than athletes

Supplemental Material - Leveraging newspapers to understand urban issues: A longitudinal analysis of urban shrinkage in Detroit

Supplemental Material for An artificial intelligence algorithm for analyzing globus pallidus necrosis after carbon monoxide intoxication by Na Jiang, Andrew T Crooks, Hamdi Kavak, Wenjing Wang in Environment and Planning B: Urban Analytics and City Science</p