Human Dynamics Research Papers - Academia.edu (original) (raw)

2025, arXiv (Cornell University)

2025, Social Science and Medicine

In medical emergencies, phoning the ambulance service constitutes a high-stakes interaction. Call-takers rely on
callers to provide information about the patient so they can promptly recognise the medical problem and take
swift action to remedy it. When a language barrier exists between the call-taker and caller, this can add a further
challenge, given that third-party interpreters are rarely engaged, especially for time-critical conditions such as
cardiac arrest. Research in cardiac arrest calls has found that language barrier calls experience longer delays to
critical points such as recognition of cardiac arrest and commencement of resuscitation. This study aimed to
understand, in the absence of interpreters, the interactional challenges that emerged in language barrier
emergency calls, as parties worked to communicate the nature of the medical problem. Based on a critical
conversation analysis approach, we conducted fine-grained analysis of interactions in audio recordings and
transcripts of 33 language barrier calls from an Australian ambulance service in 2019. We found that call takers
regularly failed to recognise that the patient had a cardiac arrest. Non-fluent-English callers often provided vital
information about the patient, which could have led to cardiac arrest recognition by the call-taker, however such
information was missed if it was delivered in an unsolicited or atypical way. Opportunities to recognise cardiac
arrest were also missed when call-takers did not probe further after such information was provided or did not
provide enough interactional space for callers to complete their turns. We found that the main reason for delays
in recognising cardiac arrest was a lack of mutual understanding, which most of the time seemed to remain
unbeknownst to participants. The study makes recommendations for emergency medical dispatch centres to cater
for language barrier calls, with the goal of fostering a more inclusive prehospital care system and addressing
health disparities for non-fluent-English speakers.

2025, arXiv (Cornell University)

In social network markets, the act of consumer choice in these industries is governed not just by the set of incentives described by conventional consumer demand theory, but by the choices of others in which an individuals payoff is an explicit function of the actions of others. We observe two key empirical features of outcomes in social networked markets. First, a highly right-skewed, non-Gaussian distribution of the number of times competing alternatives are selected at a point in time. Second, there is turnover in the rankings of popularity over time. We show here that such outcomes can arise either when there is no alternative which exhibits inherent superiority in its attributes, or when agents find it very difficult to discern any differences in quality amongst the alternatives which are available so that it is as if no superiority exists. These features appear to obtain, as a reasonable approximation, in many social network markets. We examine the impact of network structure on both the rank-size distribution of choices at a point in time, and on the life spans of the most popular choices. We show that a key influence on outcomes is the extent to which the network follows a hierarchical structure. It is the social network properties of the markets, the meso-level structure, which determine outcomes rather than the objective attributes of the products.

2024, Frontiers in Physics

Citizen Science is research undertaken by professional scientists and members of the public collaboratively. Despite numerous benefits of citizen science for both the advancement of science and the community of the citizen scientists, there is still no comprehensive knowledge of patterns of contributions, and the demography of contributors to citizen science projects. In this paper we provide a first overview of spatiotemporal and gender distribution of citizen science workforce by analyzing 54 million classifications contributed by more than 340 thousand citizen science volunteers from 198 countries to one of the largest online citizen science platforms, Zooniverse. First we report on the uneven geographical distribution of the citizen scientist and model the variations among countries based on the socio-economic conditions as well as the level of research investment in each country. Analyzing the temporal features of contributions, we report on high “burstiness” of participation i...

2024, https://www.facebook.com/dario.ma.771/posts/pfbid02DdNbe19hBequzomiLJxobzUsXoxwnQ3WAkHCUsc7ev3n6YdRG2Ar6N8WV63pACWwl?notif\_id=1729344407618462&notif\_t=feedback\_reaction\_generic&ref=notif

L'ambra del Mar Baltico, una delle varietà più preziose e conosciute di questa resina fossile, ha affascinato l'umanità per millenni. Questo materiale organico, spesso chiamato "l'oro del Nord", si forma dall'indurimento della resina di... more

2024, Proceedings of the 21st Annual International Conference on Mobile Computing and Networking

2024, IEEE Access

Air travelers' behavior is closely related to the operational performance of any airport terminal. Much of previous research has focused on how airport operators balance the number of facilities in a terminal and the Level of Service (LOS), while the behavior of passengers is less considered. Not much is known, however, about passenger's behavior during the entire departure process in an airport. In this study, we analyze empirical departure passenger's data to gain an insight into the regular patterns of their activities in an airport. We find that there exist two distinguished temporal patterns during two discretionary periods-post check-in and pre-security check, post security check and pre-boarding. The time that departure passengers spend in these two periods is well approximated by a double power-law distribution and an exponential truncated power-law distribution respectively. The two distinguished distributions suggest that there may be different mechanisms underlying passengers' behavior as indicated by previous studies on human mobility. We introduce a stochastic model that considers traveling experience and time pressure to capture the decision dynamics of human behavior. Simulation results suggest that traveling experience and time pressure dominate passenger's decisions before and after security respectively. Our findings contribute to a better understanding of human dynamics, and also offer the potential for optimizing and simulation of airport terminal operation.

2024, Frontiers in Physics

2024, 2011 IEEE Consumer Communications and Networking Conference (CCNC)

Human dynamics in real-world social networks has been a long lasting topic of research. Recently, the rapid growing of online social networks with their data made accessible has given researchers a door of opportunity to study large-scale social networks. Facebook has been the largest, most influential, and fastest growing social network on the Internet to date. As Facebook's userbase is extremely diverse, spreading across different countries, races, ages, professions, and interests, to name a few, this network is a good model to study our society. In this paper, we present an analysis of a regional Facebook dataset, with attention given to the correlation among user connectivity, activity, and similarity.

2024, SAGE Open

Long-standing results in urban studies have shown correlation of population and population density to a city’s pace of life, empirically tested by examining whether individuals in bigger cities walk faster, spend less time buying stamps, or make greater numbers of telephone calls. Contemporary social media presents a new opportunity to test these hypotheses. This study examines whether users of the social media platform Twitter in larger and denser American cities tweet at a faster rate than their counterparts in smaller and sparser ones. Contrary to how telephony usage and productivity scale superlinearly with city population, the total volume of tweets in cities scales sublinearly. This is similar to the economies of scale in city infrastructures like gas stations. When looking at individuals, however, greater population density is associated with faster tweeting. The discrepancy between the ecological correlation and individual behavior is resolved by noting that larger cities ha...

2024, 2011 IEEE Consumer Communications and Networking Conference (CCNC)

2024, ArXiv

The results of this pilot are of great importance for the entire Dutch government, because we have developed a best practice with which administrators can really get started, and actually incorporate ethical values into the algorithms... more

2024, Що за животно е корпоративната култура и има ли тя почва у нас?

Тайната на Корпоративната Култура: Що за Животно е Тя и Има ли Почва У Нас? Корпоративната култура често е сравнявана с мистериозно същество от легендите – всички говорят за нея, но малцина са я видели в истинската ѝ форма. Тя може... more

2024, Frontiers in Human Dynamics

Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidelines are aimed at a variety of stakeholders, especially guiding practitioners toward more ethical and more robust applications of AI. In line with efforts of the EC, AI ethics scholarship focuses increasingly on converting abstract principles into actionable recommendations. However, the interpretation, relevance, and implementation of trustworthy AI depend on the domain and the context in which the AI system is used. The main contribution of this paper is to demonstrate how to use the general AI HLEG trustworthy AI guidelines in practice in...

2024, Communications Physics

The interactions among human beings represent the backbone of our societies. How people establish new connections and allocate their social interactions among them can reveal a lot of our social organisation. We leverage on a recent mathematical formalisation of the Adjacent Possible space to propose a microscopic model accounting for the growth and dynamics of social networks. At the individual’s level, our model correctly reproduces the rate at which people acquire new acquaintances as well as how they allocate their interactions among existing edges. On the macroscopic side, the model reproduces the key topological and dynamical features of social networks: the broad distribution of degree and activities, the average clustering coefficient and the community structure. The theory is born out in three diverse real-world social networks: the network of mentions between Twitter users, the network of co-authorship of the American Physical Society journals, and a mobile-phone-calls net...

2024, Advances in Social Networks Analysis and Mining

Human mobility is differentiated by time scales. While the mechanism for long-time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analyzing the temporal and spatial trajectories of thousands of persons as individual networks. By using the concept of motifs from network theory only 17 unique networks are present in daily mobility, following simple rules. These networks, called here motifs, are sufficient to capture up to 90% of the population in surveys and mobile phone data sets for different countries. Each individual exhibits a characteristic motif, which seems to be stable over several months. Consequently, daily human mobility can be reproduced by an analytically tractable framework for Markov chains by modeling periods of high frequency trips followed by periods of lower activity as the key ingredient.

2024, Big Data Recommender Systems - Volume 2: Application Paradigms

2024

Background Intergenerational family farm transfer is increasingly viewed as crucial to the survival, continuity and future prosperity of the agricultural sector, traditional family farm model and broader sustainability of rural society. While financial incentives designed to stimulate and entice this complex and highly topical phenomenon are important, there are many more facets to the farm succession and retirement decision-making process, which for the most part have been neglected. This has resulted in the formulation and implementation of largely unsuccessful policy strategies, which do not give proper and due consideration to the senior generation's attachment to their farm and occupation. One such key example happened in the Republic of Ireland, where an Early Retirement Scheme (ERS 3, June 2007), requested farmers retiring under the scheme to 'cease agricultural activity forever'. Essentially, older farmers were asked to revise their selfperceptions upon retirement. Challenging this one-dimensional approach, this research sets aside economic enticements and delves deeper into the mind-set and mannerism of farmers in later life to inform more appropriate, 'farmer-sensitive' farm transfer policy directions. Aim This thesis consists of three interrelated journal articles. Each interconnected article explores the various human dynamics influencing and hindering the older generation's decision-making processes surrounding farm succession and retirement from a different theoretical base. Article 1 theoretically pioneers the use of Pierre Bourdieu's notion of symbolic capital to comprehend the psychodynamic and sociodynamic factors influencing the unwillingness and reluctance amongst older farmers towards relinquishing management and ownership of the family farm and retirement. Article 2 explores the micro-politics and hierarchical power dynamics at play within family farm households through the analytical lens of Pierre Bourdieu's concept of symbolic power, and the exercise of symbolic violence. Finally, article 3 applies Graham Rowles' concept of insideness as a theoretical framework to present an insightful, nuanced analysis of the deeply embedded attachment older farmers have with their farms.

2024

2024, Frontiers in Human Dynamics

2024, arXiv (Cornell University)

Z-inspection® is a registered trademark. The content of this work is open access distributed under the terms and conditions of the Creative Commons (Attribution-NonCommercial-ShareAlike CC BY-NC-SA) license The views expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations.

2024, IEEE Transactions on Mobile Computing

With the rapid growth of cell phone networks during the last decades, call detail records (CDR) have been used as approximate indicators for large scale studies on human and urban mobility. Although coarse and limited, CDR are a real marker of human presence. In this paper, we use more than 800 million of CDR to identify weekly patterns of human mobility through mobile phone data. Our methodology is based on the classification of individuals into six distinct presence profiles where we focus on the inherent temporal and geographical characteristics of each profile within a territory. Then, we use an event-based algorithm to cluster individuals and we identify 12 weekly patterns. We leverage these results to analyze population estimates adjustment processes and as a result, we propose new indicators to characterize the dynamics of a territory. Our model has been applied to real data coming from more than 1.6 million individuals and demonstrates its relevance. The product of our work can be used by local authorities for human mobility analysis and urban planning.

2023, Frontiers in Human Dynamics

2023, ISPRS international journal of geo-information

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

2023, Physical Review X

Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cellphone locations, [C. Song et al., Science 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one's conversation partners is defined as the degree to which one's next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by longtailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual's predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community-in the sense of an abundance of surrounding triangles-tend to have low predictability, and those bridging different communities tend to have high predictability.

2023, Journal of Physics A: Mathematical and Theoretical

Novel aspects of human dynamics and social interactions are investigated by means of mobile phone data. Using extensive phone records resolved in both time and space, we study the mean collective behavior at large scales and focus on the occurrence of anomalous events. We discuss how these spatiotemporal anomalies can be described using standard percolation theory tools. We also investigate patterns of calling activity at the individual level and show that the interevent time of consecutive calls is heavy-tailed. This finding, which has implications for dynamics of spreading phenomena in social networks, agrees with results previously reported on other human activities.

2023

Introduzione Le ricerche di superficie e gli scavi condotti dall'insegnamento di Topografia Antica della Sapienza-Università di Roma nell'ultimo decennio nel bacino di Piediluco hanno permesso il rinvenimento di alcuni ornamenti in ambra 1 dal sito di Paduli 2 e Ara Marina (fig. 1). Si tratta di un vago troncopiramidale schiacciato (da Paduli), un bottone sferico e una placchetta multiforata (entrambi da Ara Marina, già identificato come Podere Colle D'Agnano 3). I materiali si inquadrano tra il Bronzo Tardo gli inizi dell'età del ferro.

2023, Frontiers in human dynamics

2023, Physical Review E

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. Here we provide direct evidence that for five human activity patterns, such as email and letter based communications, web browsing, library visits and stock trading, the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. We show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experiencing very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. We discuss two queueing models that capture human activity. The first model assumes that there are no limitations on the number of tasks an individual can hadle at any time, predicting that the waiting time of the individual tasks follow a heavy tailed distribution P (τw) ∼ τ −α w with α = 3/2. The second model imposes limitations on the queue length, resulting in a heavy tailed waiting time distribution characterized by α = 1. We provide empirical evidence supporting the relevance of these two models to human activity patterns, showing that while emails, web browsing and library visitation display α = 1, the surface mail based communication belongs to the α = 3/2 universality class. Finally, we discuss possible extension of the proposed queueing models and outline some future challenges in exploring the statistical mechanisms of human dynamics. These findings have important implications not only for our quantitative understanding of human activity patterns, but also for resource management and service allocation in both communications and retail.

2023, Frontiers in human dynamics

2023, PLOS Digital Health

Explainability for artificial intelligence (AI) in medicine is a hotly debated topic. Our paper presents a review of the key arguments in favor and against explainability for AI-powered Clinical Decision Support System (CDSS) applied to a concrete use case, namely an AI-powered CDSS currently used in the emergency call setting to identify patients with life-threatening cardiac arrest. More specifically, we performed a normative analysis using socio-technical scenarios to provide a nuanced account of the role of explainability for CDSSs for the concrete use case, allowing for abstractions to a more general level. Our analysis focused on three layers: technical considerations, human factors, and the designated system role in decision-making. Our findings suggest that whether explainability can provide added value to CDSS depends on several key questions: technical feasibility, the level of validation in case of explainable algorithms, the characteristics of the context in which the sy...

2023, Frontiers in Human Dynamics

2023, PLOS Digital Health

2023, Frontiers in Human Dynamics

2023, Journal of Physics A: Mathematical and Theoretical

2023

The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate team formation, especially teams distributed across space and time. Parameters of human teams that effect system performance can be captured in this model. Human centered aspects of networks, such as differences in operational tempo (sense of urgency), priorities (common goal), and team history (knowledge of the other team members), can be incorporated. The information captured in ...

2023, Frontiers in Human Dynamics

2023, arXiv (Cornell University)

2023, 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)

Human dynamic models are useful in design of physical human-robot and human-robot-environment interaction: informing choice of robot impedance, motivating relaxations to passivity-based safety constraints, and allowing online inference to user intent. Designing for performance objectives such as stable well-damped contact transitions also requires nominal models, but the use of human models in controller design is limited. Established approaches to identify human dynamics apply position or force perturbation and measure the corresponding response, mostly to validate neuromuscular hypotheses on motor control, which raises questions about their transferability to human-led collaboration. Here, human dynamics are identified in a task which closely resembles the final application, where the human leads the robot into contact with a (virtual) wall. This paper investigates the impact of human dynamics on coupled system behavior, and establishes a general framework for identification in humanled scenarios, making consideration of unmeasured human input. Experiments with different stiffness environments allow inference to human dynamics, and characterize the range of human dynamics which can be modulated by the user.

2023, arXiv (Cornell University)

We present a study of the reciprocity of human behaviour based on mobile phone usage records. The underlying question is whether human relationships are mutual, in the sense that both are equally active in keeping up the relationship, or is it on the contrary typical that relationships are lopsided, with one party being significantly more active than the other. We study this question with the help of a mobile phone data set consisting of all mobile phone calls between 5.3 million customers of a single mobile phone operator. It turns out that lopsided relations are indeed quite common, to the extent that the variation cannot be explained by simple random deviations or by variations in personal activity. We also show that there is no non-trivial correlation between reciprocity and local network density.

2023, Advances in Physics: X

In the post year 2000 era the technologies that facilitate human communication have rapidly multiplied. While the adoption of these technologies has hugely impacted the behaviour and sociality of people, specifically in urban but also in rural environments, their 'digital footprints' on different data bases have become an active area of research. The existence and accessibility of such large population-level datasets, has allowed scientists to study and model innate human tendencies and social patterns in an unprecedented way that complements traditional research approaches like questionnaire studies. In this review, we focus on data analytics and modelling researchalong the lines of Social Physicsas it has been carried out using the mobile phone datasets to get insight into the various aspects of human sociality, burstiness in communication, mobility patterns, and daily rhythms.

2023, Scientific Reports

The dynamics of close relationships is important for understanding the migration patterns of individual life-courses. The bottom-up approach to this subject by social scientists has been limited by sample size, while the more recent top-down approach using large-scale datasets suffers from a lack of detail about the human individuals. We incorporate the geographic and demographic information of millions of mobile phone users with their communication patterns to study the dynamics of close relationships and its effect in their life-course migration. We demonstrate how the close age-and sex-biased dyadic relationships are correlated with the geographic proximity of the pair of individuals, e.g., young couples tend to live further from each other than old couples. In addition, we find that emotionally closer pairs are living geographically closer to each other. These findings imply that the life-course framework is crucial for understanding the complex dynamics of close relationships and their effect on the migration patterns of human individuals. H uman societies have successfully been described in the framework of social networks based on dyadic relationships 1. In recent years, a number of social networks have been characterised in terms of smallworld properties 2 , broad distributions of the number of neighbours 3 , assortative mixing 4 or homophily 5 , and community structure 6. This is partially due to recent access to large-scale highly-resolved digital datasets on human dynamics and social interaction 7. Mobile phone datasets in particular have provided a unique opportunity to study the structure and dynamics of human relationships 8-13. Although the lack of detail about individuals often undermines the importance of large-scale studies based on anonymised datasets, limited geographic and demographic information of mobile phone users has successfully been used, e.g., in studies of age and sex biases in social relationships 14,15. It is important to stress that humans are embedded not only in social networks but also in geographic space 16,17. People move and migrate for a number of reasons. For example, people leave their parental home for education or employment, to get married, to rear a family, or they can move due to divorce and separation 18. In these life-course events, close relationships play a crucial role in shaping migrational patterns. Human mobility patterns have recently been studied by using the datasets of time-resolved location of mobile phone users 19-22. These datasets are limited to periods of a few years at most, so far allowing only cross-sectional analysis. In contrast, the longitudinal approach adopted by social scientists has been used to investigate long-term migration patterns over the human lifespan 23,24 , but suffers from the fact that sample size is invariably limited. Large-scale mobile phone datasets can be used to understand the role of close relationships in the life-course migration, by exploiting geographic and demographic information of mobile phone users. Frequency of contact between a pair of individuals has been established as a reliable index of emotional closeness in relationships, and the frequency of contact by telephone and other digital media like email and text message is known to correlate significantly with the frequency of face-to-face contact 25-27. Thus one can assume that most of important relationships of individuals are captured by mobile phone communication records, and that the level of emotional closeness in a relationship is reflected in the strength of communication. We also assume that the life-course migration patterns are reflected in the age-and sex-dependent geographic correlations of users. In other words, even though our mobile phone dataset of users of all age groups is necessarily cross-sectional, we can use them to gain insights into longitudinal, life-course migration patterns.

2023, Neurocomputing

In this work we propose a new experimental paradigm in the context of human motor control. Human subjects track a target with a mouse-pointer on a computer screen while the underlying dynamics is similar to a stick-balancing problem. This approach gives wide control over system parameters. We show that there are two scaling regions in the power spectrum of the distance r between mouse and target and ÿnd a power law in the laminar phases distribution of r. We propose a model for this dynamics and compare the model results to the experimental ÿndings.

2023, PLoS ONE

The number of people using online social networks in their everyday life is continuously growing at a pace never saw before. This new kind of communication has an enormous impact on opinions, cultural trends, information spreading and even in the commercial success of new products. More importantly, social online networks have revealed as a fundamental organizing mechanism in recent country-wide social movements. In this paper, we provide a quantitative analysis of the structural and dynamical patterns emerging from the activity of an online social network around the ongoing May 15th (15M) movement in Spain. Our network is made up by users that exchanged tweets in a time period of one month, which includes the birth and stabilization of the 15M movement. We characterize in depth the growth of such dynamical network and find that it is scale-free with communities at the mesoscale. We also find that its dynamics exhibits typical features of critical systems such as robustness and power-law distributions for several quantities. Remarkably, we report that the patterns characterizing the spreading dynamics are asymmetric, giving rise to a clear distinction between information sources and sinks. Our study represents a first step towards the use of data from online social media to comprehend modern societal dynamics.

2023, Transactions of the Institute of Systems, Control and Information Engineers

Coupled human balancing tasks, performed by a pair of artificial controllers and a pair of human subjects, have been studied by the present authors based on the coupled inverted pendula (CIP) model. On the contrary, in this paper, we examine another type of combination, the artificial controller and the human subject. We experimentally estimate Lyapunov and sub-Lyapunov exponents of balancing errors of the system of human subject and artificial controller, in which the human subject is in cooperation with the artificial controller having several different feedback gains. The result implies that the human subject seems to try to make the artificial controller minimally or neutrally stable.

2023, IEEE Transactions on Technology and Society

The ethical and societal implications of artificial intelligence systems raise concerns. In this article, we outline a novel process based on applied ethics, namely, Z-Inspection , to assess if an AI system is trustworthy. We use the definition of trustworthy AI given by the high-level European Commission's expert group on AI. Z-Inspection is a general inspection process that can be applied to a variety of domains where AI systems are used, such as business, healthcare, and public sector, among many others. To the best of our knowledge, Z-Inspection is the first process to assess trustworthy AI in practice.

2023, Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems

The rapid pace of urbanization and socioeconomic development encourage people to spend more time together and therefore monitoring of human dynamics is of great importance, especially for facilities of elder care and involving multiple activities. Traditional approaches are limited due to their high deployment costs and privacy concerns (e.g., camera-based surveillance or sensor-attachmentbased solutions). In this work, we propose to provide a fine-grained comprehensive view of human dynamics using existing WiFi infrastructures often available in many indoor venues. Our approach is low-cost and device-free, which does not require any active human participation. Our system aims to provide smart human dynamics monitoring through participant number estimation, human density estimation and walking speed and direction derivation. A semisupervised learning approach leveraging the non-linear regression model is developed to significantly reduce training efforts and accommodate different monitoring environments. We further derive participant number and density estimation based on the statistical distribution of Channel State Information (CSI) measurements. In addition, people's walking speed and direction are estimated by using a frequency-based mechanism. Extensive experiments over 12 months demonstrate that our system can perform fine-grained effective human dynamic monitoring with over 90% accuracy in estimating participants number, density, and walking speed and direction at various indoor environments.

2023, Frontiers in Human Dynamics

Armed conflict and forced migration are associated with an increase in intimate partner violence (IPV) against women. Yet as risks of IPV intensify, familiar options for seeking help dissipate as families and communities disperse and seek refuge in a foreign country. The reconfiguration of family and community systems, coupled with the presence of local and international humanitarian actors, introduces significant changes to IPV response pathways. Drawing from intensive fieldwork, this article examines response options available to women seeking help for IPV in refugee camps against the backdrop of efforts to localize humanitarian assistance. This study employed a qualitative approach to study responses to IPV in three refugee camps: Ajuong Thok (South Sudan), Dadaab (Kenya), and Domiz (Iraqi Kurdistan). In each location, data collection activities were conducted with women survivors of IPV, members of the general refugee community, refugee leaders, and service providers. The sample...