Diversity Of Human Behavior Research Articles

Adaptive Leading Cruise Control in Mixed Traffic Considering Human Behavioral Diversity

Adaptive Leading Cruise Control in Mixed Traffic Considering Human Behavioral Diversity

Use of Mixed Methods in Social Sciences Research

The landscape of social sciences is inherently complex and multifaceted, demanding a comprehensive and nuanced approach to research methodologies. This paper highlights the significance of mixed methods research in addressing the intricate and dynamic nature of social phenomena. Mixed methods not only enhance the validity and reliability of research findings but also allow for a holistic understanding of social phenomena and empower researchers to explore the comprehensiveness and diversity of human experiences, behaviors, and interactions that the traditional single-method approach often falls short of. Furthermore, mixed methods facilitates the triangulation of data, enabling researchers to corroborate and validate results through diverse lenses, thereby fortifying the robustness of their conclusions. Mixed methods contribute to the development of more effective and informed social and public policy interventions. Adopting mixed methods in social science research is not merely a choice but a necessity for unlocking the full potential of inquiry and advancing our collective understanding of the complex social world.

AI-driven behavior biometrics framework for robust human activity recognition in surveillance systems

The integration of artificial intelligence (AI) into human activity recognition (HAR) in smart surveillance systems has the potential to revolutionize behavior monitoring. These systems analyze an individual’s physiological or behavioral features to continuously monitor and identify any unusual or suspicious activity in video streams, thereby improving security and surveillance measures. Traditional surveillance systems often rely on manual human monitoring, which is resource-intensive, error-prone, and time-consuming. To address these limitations, computer vision-based behavior biometrics has emerged as a solution for secure video surveillance applications. However, implementing automated HAR in real-world scenarios is challenging due to the diversity of human behavior, complex spatiotemporal patterns, varying viewpoints, and cluttered backgrounds. To tackle these challenges, an AI-based behavior biometrics framework is introduced that is based on a dynamic attention fusion unit (DAFU) followed by a temporal-spatial fusion (TSF) network to effectively recognize human activity in surveillance systems. In the first phase of the proposed framework, a lightweight EfficientNetB0 backbone is enhanced by the DAFU to extract human-centric salient features using a unified channel-spatial attention mechanism. In the second phase, the DAFU features with fixed sequence lengths are passed to the proposed TSF network to capture the temporal, spatial, and behavioral dependencies in video data streams. The integration of Echo-ConvLSTM in the TSF further enhances accuracy and robustness by combining temporal dependencies from the echo state network with spatial and temporal dependencies from the convolutional long short-term memory (ConvLSTM). The proposed AI-based behavior biometrics framework is evaluated using four publicly available HAR datasets (UCF101, HMDB51, UCF50, and YouTube Action), yielding higher accuracies of 98.734%, 80.342%, 98.987%, and 98.927%, which demonstrate the superior performance when compared with state-of-the-art (SOTA) methods.

FABRIC: A Framework for the Design and Evaluation of Collaborative Robots with Extended Human Adaptation

A limitation for collaborative robots (cobots) is their lack of ability to adapt to human partners, who typically exhibit an immense diversity of behaviors. We present an autonomous framework as a cobot’s real-time decision-making mechanism to anticipate a variety of human characteristics and behaviors, including human errors, toward a personalized collaboration. Our framework handles such behaviors in two levels: (1) short-term human behaviors are adapted through our novel Anticipatory Partially Observable Markov Decision Process (A-POMDP) models, covering a human’s changing intent (motivation), availability, and capability; (2) long-term changing human characteristics are adapted by our novel Adaptive Bayesian Policy Selection (ABPS) mechanism that selects a short-term decision model, e.g., an A-POMDP, according to an estimate of a human’s workplace characteristics, such as her expertise and collaboration preferences. To design and evaluate our framework over a diversity of human behaviors, we propose a pipeline where we first train and rigorously test the framework in simulation over novel human models. Then, we deploy and evaluate it on our novel physical experiment setup that induces cognitive load on humans to observe their dynamic behaviors, including their mistakes, and their changing characteristics such as their expertise. We conduct user studies and show that our framework effectively collaborates non-stop for hours and adapts to various changing human behaviors and characteristics in real-time. That increases the efficiency and naturalness of the collaboration with a higher perceived collaboration, positive teammate traits, and human trust. We believe that such an extended human-adaptation is a key to the long-term use of cobots.

New perspectives on the evolution of women's cooperation.

A holistic, evolutionary framework about human cooperation must incorporate information about women's cooperative behaviour. Yet, most empirical research on human cooperation has centered on men's behaviour or been derived from experimental studies conducted in western, industrialized populations. These bodies of data are unlikely to accurately represent human behavioural diversity. To address this gap and provide a more balanced view of human cooperation, this issue presents substantial new data and multi-disciplinary perspectives to document the complexity of women's cooperative behaviour. Research in this issue 1) challenges narratives about universal gender differences in cooperation, 2) reconsiders patrilocality and access to kin as constraints on women's cooperation, 3) reviews evidence for a connection between social support and women's health and 4) examines the phylogenetic roots of female cooperation. Here, we discuss the steps taken in this issue toward a more complete and evidence-based understanding of the role that cooperation plays in women's and girls' lives and in building human sociality. This article is part of the theme issue 'Cooperation among women: evolutionary and cross-cultural perspectives'.

Categorizing urban space based on visitor density and diversity: A view through social media data

Analyses of urban spaces have often stressed the importance of both the density and diversity of the people they attract. However, the diversity of people is a challenging concept to operationalize within the context of urban spaces, which is why many evaluations of urban space have relied primarily on density-based measures. We argue that a focus on only one of the two aspects misses important aspects of the variety of urban spaces in our cities. To address this, we design a methodology that evaluates both the density and diversity of human behavior in urban spaces based on geosocial media data. We operationalize density as the frequency of tweets from visitors to a particular location and diversity as the variety of the home neighborhoods of those visitors. Taking Singapore as a test case, we identify networks between the home neighborhoods of 28k Twitter users based on 2.2 million geolocated tweets collected between 2012 and 2016. Based on these data, we categorize the urban landscape of Singapore into four “performance” categories, namely High-Density/High-Diversity, High-Density/Low-Diversity, Low-Density/High-Diversity, and Low-Density/Low-Diversity. Our findings illustrate that this combined indicator provides useful nuance compared to differentiation between well and less performing spaces based on density alone. By enabling a categorization of urban spaces that fits closer to the diversity of human behavior in these spaces, human mobility data sets, such as the social media data we use, open the door to a practical evaluation of the design and planning of our heterogeneous urban environment.

Construction of public security indicators based on characteristics of shared group behavior patterns

PurposeHuman group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city interest points to construct urban security risk indicators. This paper combines traffic data and urban alarm data to analyze the safe travel characteristics of the urban population. The research results are helpful to explore the diversity of human group behavior, grasp the temporal and spatial laws and reveal regional security risks. It provides a reference for optimizing resource deployment and group intelligence analysis in emergency management.Design/methodology/approachBased on the dynamics index of group behavior, this paper mines the data of large shared bikes and ride-hailing in a big city of China. We integrate the urban interest points and travel dynamic characteristics, construct the urban traffic safety index based on alarm behavior and further calculate the urban safety index.FindingsThis study found significant differences in the travel power index among ride-sharing users. There is a positive correlation between user shared bike trips and the power-law bimodal phenomenon in the logarithmic coordinate system. It is closely related to the urban public security index.Originality/valueBased on group-shared dynamic index integrated alarm, we innovatively constructed an urban public safety index and analyzed the correlation of travel alarm behavior. The research results fully reveal the internal mechanism of the group behavior safety index and provide a valuable supplement for the police intelligence analysis.

EchoIA: A Cloud-Based Implicit Authentication Leveraging User Feedback

Implicit authentication (IA) transparently authenticates users by utilizing their behavioral data sampled from various sensors. Identifying the illegitimate user through constantly analyzing current users’ behavior, IA adds another layer of protection to the smart device. Due to the diversity of human behavior, existing research tends to utilize multiple features to identify users, which is less efficient. Irrelevant features may increase the system delay and reduce the authentication accuracy. However, dynamically choosing the best suitable features for each user (personal features) requires a massive calculation, making it infeasible in the real environment. In this paper, we propose EchoIA to find personal features with a small amount of calculation by leveraging user feedback derived from the correct rate of inputted passwords. By analyzing the feedback, EchoIA can deduce the true identities of current users and achieve a human-centered implicit authentication. In the authentication phase, our approach maintains transparency, which is the major advantage of IA. In the past two years, we conducted a comprehensive experiment to evaluate EchoIA. We compared it with four state-of-the-art IA schemes in the aspect of authentication accuracy and efficiency. The experiment results show that EchoIA has better authentication accuracy (93%) and less energy consumption (23-h battery lifetimes) than other IA schemes.

Environmental influences on human innovation and behavioural diversity in southern Africa 92-80 thousand years ago.

Africa's Middle Stone Age preserves sporadic evidence for novel behaviours among early modern humans, prompting a range of questions about the influence of social and environmental factors on patterns of human behavioural evolution. Here we document a suite of novel adaptations dating approximately 92-80 thousand years before the present at the archaeological site Varsche Rivier 003 (VR003), located in southern Africa's arid Succulent Karoo biome. Distinctive innovations include the production of ostrich eggshell artefacts, long-distance transportation of marine molluscs and systematic use of heat shatter in stone tool production, none of which occur in coeval assemblages at sites in more humid, well-studied regions immediately to the south. The appearance of these novelties at VR003 corresponds with a period of reduced regional wind strength and enhanced summer rainfall, and all of them disappear with increasing winter rainfall dominance after 80 thousand years before the present, following which a pattern of technological similarity emerges at sites throughout the broader region. The results indicate complex and environmentally contingent processes of innovation and cultural transmission in southern Africa during the Middle Stone Age.

Real-Time Stylized Humanoid Behavior Control through Interaction and Synchronization.

Restricted by the diversity and complexity of human behaviors, simulating a character to achieve human-level perception and motion control is still an active as well as a challenging area. We present a style-based teleoperation framework with the help of human perceptions and analyses to understand the tasks being handled and the unknown environment to control the character. In this framework, the motion optimization and body controller with center-of-mass and root virtual control (CR-VC) method are designed to achieve motion synchronization and style mimicking while maintaining the balance of the character. The motion optimization synthesizes the human high-level style features with the balance strategy to create a feasible, stylized, and stable pose for the character. The CR-VC method including the model-based torque compensation synchronizes the motion rhythm of the human and character. Without any inverse dynamics knowledge or offline preprocessing, our framework is generalized to various scenarios and robust to human behavior changes in real-time. We demonstrate the effectiveness of this framework through the teleoperation experiments with different tasks, motion styles, and operators. This study is a step toward building a human-robot interaction that uses humans to help characters understand and achieve the tasks.

Diversity in Psychological Research Activities: Quantitative Approach With Topic Modeling.

Recent cultural studies have discussed universality and diversity in human behavior using numerous samples investigated worldwide. We aimed to quantitatively extend this discussion to various research activities in psychology in terms of geographic regions and time trends. Most psychology departments have specialists in various fields of psychology. Further, research institutions in all regions typically aim to provide systematic and balanced research education. Nevertheless, most researchers recognize universal features and patterns of diversity in research activities in psychology in terms of regional differences and time trends. However, these arguments remain intuitive and vague, and no studies have conducted quantitative analyses. To this end, we conducted topic modeling for the abstracts of psychological articles with the regions of author affiliations and publication periods as covariates. The results showed that the topic proportions related to basic research were high in North-Central America, whereas those related to clinical research were high in Europe. Interestingly, the regional differences shown by topic modeling were not observed in the frequency analysis of keywords, indicating that topic modeling revealed implicit characteristics. Moreover, we observed an increasing trend of neuroscience topics across publication periods. However, this trend was not valid for the psychology journal Psychological Science. Taken together, our results suggest diversity of geographic regions and periods in research activities in psychology. More importantly, our findings indicate that universality holds neither for human behavior nor research activities on human mental processes.

Genetics on the neurodiversity spectrum: Genetic, phenotypic and endophenotypic continua in autism and ADHD

How we ought to diagnose, categorise and respond to spectrum disabilities such as autism and Attention Deficit/Hyperactivity Disorder (ADHD) is a topic of lively debate. The heterogeneity associated with ADHD and autism is described as falling on various continua of behavioural, neural, and genetic difference. These continua are varyingly described either as extending into the general population, or as being continua within a given disorder demarcation. Moreover, the interrelationships of these continua are likewise often vague and subject to diverse interpretations.In this paper, I explore geneticists' and self-advocates’ perspectives concerning autism and ADHD as continua. These diagnoses are overwhelmingly analysed as falling on a continuum or continua of underlying traits, which supports the notion of “the neurodiversity spectrum”, i.e., a broader swath of human neural and behavioural diversity on which some concentrations of different functioning are diagnosed. I offer a taxonomy of conceptions of the genetic, phenotypic, and endophenotypic dimensionality within and beyond these diagnostic categories, and suggest that the spectrum of neurodiversity is characteristically endophenotypic.

Cross-cultural, developmental psychology: integrating approaches and key insights

Abstract Like psychology more broadly, developmental psychology has long suffered from a narrow focus on children from WEIRD societies—or those that are Western, Educated, Industrialized, Rich, and Democratic. In this review, we discuss how developmental scientists have sought to correct this bias through two complementary approaches: one centered on detailed, ethnographic investigations of child development within populations (increasing the depth of our understanding) and one focused on larger, multi-site studies that test children on standardized tasks across populations (increasing breadth). We review key papers from each of these approaches, describe how they are currently practiced, and discuss their strengths and weaknesses. Next, we highlight exemplary papers from the adult literature that offer useful insights, namely the importance of formal modeling and a greater focus on studying variation at multiple levels of analysis. We end by outlining best practices for future waves of cross-cultural, developmental science. Overall, we argue that a more integrated perspective, combining the strengths of the breadth & depth approaches, can help better elucidate the developmental origins of human behavioral diversity.

Behavioural diversity in fishing—Towards a next generation of fishery models

AbstractDespite improved knowledge and stricter regulations, numerous fish stocks remain overharvested. Previous research has shown that fisheries management may fail when the models and assessments used to inform management are based on unrealistic assumptions regarding fishers' decision‐making and responses to policies. Improving the understanding of fisher behaviour requires addressing its diversity and complexity through the integration of social science knowledge into modelling. In our paper, we review and synthesize state‐of‐the‐art research on both social science's understanding of fisher behaviour and the representation of fisher decision‐making in scientific models. We then develop and experiment with an agent‐based social–ecological fisheries model that formalizes three different fishing styles. Thereby we reflect on the implications of our incorporation of behavioural diversity and contrast it with the predominant assumption in fishery models: fishing practices being driven by rational profit maximizing. We envision a next generation of fisheries models and management that account for social scientific knowledge on individual and collective human behaviours. Through our agent‐based model, we demonstrate how such an integration is possible and propose a scientific approach for reducing uncertainty based on human behavioural diversity in fisheries. This study serves to lay the foundations for a next generation of social–ecological fishery models that account for human behavioural diversity and social and ecological complexity that are relevant for a realistic assessment and management of fishery sustainability problems.

The Relationship Between Tool Use and Prey Availability in Chimpanzees (Pan troglodytes schweinfurthii) of Northern Democratic Republic of Congo

A key feature of human behavioral diversity is that it can be constrained by cultural preference (“cultural override”); that is, population-specific preferences can override resource availability. Here we investigate whether a similar phenomenon can be found in one of our closest relatives, as well as the potential impacts of ecological differences on feeding behavior. Our study subjects were different subpopulations of Eastern chimpanzees (Pan troglodytes schweinfurthii) occupying two very different habitats, moist tropical lowland forests vs. moist tropical forest–savanna mosaic on opposite sides of a major river. Given differences in encounter rates of different kinds of tool sites on both sides of the Uele River, we predicted that these subpopulations would differ in their likelihood of using tools to prey on two insect species despite similar availability. In surveys conducted over a 9-year period at 19 different survey regions in northern Democratic Republic of Congo (10 in lowland forest and 9 in mosaic), we collected and analyzed data on chimpanzee tool-assisted exploitation of insects. To determine the availability of insect species eaten by the chimpanzees, we counted insects and their mounds on transects and recces at 12 of these sites. For stick tools used to harvest epigaeic Dorylus and ponerine ants, we evaluated seasonal, geographical, and prey-availability factors that might influence their occurrence, using nest encounter rate as a proxy to control for chimpanzee abundance. Across the 19 survey regions spanning both sides of the Uele, we found little difference in the availability of epigaeic Dorylus and ponerine ants. Despite this, tool encounter rates for epigaeic Dorylus, but not ponerine, ants were significantly higher in the mosaic to the north of the Uele. Furthermore, we found no evidence for termite fishing anywhere, despite the availability of Macrotermes mounds throughout the region and the fact that chimpanzees at a number of other study sites use tools to harvest these termites. Instead, the chimpanzees of this region used a novel percussive technique to harvest two other types of termites, Cubitermes sp. and Thoracotermes macrothorax. This mismatch between prey availability and predation is consistent with cultural override, but given the different habitats on the two sides of the Uele River, we cannot fully rule out the influence of ecological factors. Comparing our findings with those of similar studies of other chimpanzee populations promises to contribute to our understanding of the evolution of behavioral diversity in humans and our closest cousins.

Information encountering re-encountered

PurposeIn order to understand the totality, diversity and richness of human information behavior, increasing research attention has been paid to examining serendipity in the context of information acquisition. However, several issues have arisen as this research subfield has tried to find its feet; we have used different, inconsistent terminology to define this phenomenon (e.g. information encountering, accidental information discovery, incidental information acquisition), the scope of the phenomenon has not been clearly defined and its nature was not fully understood or fleshed-out.Design/methodology/approachIn this paper, information encountering (IE) was proposed as the preferred term for serendipity in the context of information acquisition.FindingsA reconceptualized definition and scope of IE was presented, a temporal model of IE and a refined model of IE that integrates the IE process with contextual factors and extends previous models of IE to include additional information acquisition activities pre- and postencounter.Originality/valueBy providing a more precise definition, clearer scope and richer theoretical description of the nature of IE, there was hope to make the phenomenon of serendipity in the context of information acquisition more accessible, encouraging future research consistency and thereby promoting deeper, more unified theoretical development.

Żołnierz na wojnie i po wojnie. Problematyka zachowań ludzkich

Artykuł stanowi wprowadzenie do studium zachowań ludzkich na wojnie i po wojnie. Dotyczy wyłącznie zachowań żołnierzy. Stare żołnierskie porzekadło mówi, że żołnierz na wojnie robi to, czego nauczył się w czasie pokoju. Wojna jest nieubłaganym, surowym weryfikatorem poziomu wyszkolenia dowództw i sztabów oraz wojsk. Autor skupił swą uwagę na problematyce zjawiska kryzysu pierwszego dnia wojny, relacjach międzyludzkich, oswajaniu śmierci, stresie bojowym, roli dowódców, problemach z przystosowaniem żołnierzy do funkcjonowania po powrocie z wojny. Starał się ukazać różnorodność ludzkich zachowań, wskazując na pozytywne i pożądane cechy, piętnując zjawiska negatywne.

Flexibility in Cognitive Functioning: The Play of Paradox

Interactions among motivation, cognitive functioning, and affect shape much of the diversity in human behavior. This study aims to synthesize the literature on these interactions through a narrative review and highlights how a particular class of motivations leads to paradoxical effects. The literature review was conducted by following a rigorous search protocol to identify and filter the research on the topic. A synthesis of the pertinent research suggests that motivation, cognitive functioning, and affect interact cyclically to give rise to behavioral diversity. More importantly, affective and motivational influences lead to flexibility in cognitive functioning. This flexibility in information search and processing gives rise to paradoxical effects in the case of a class of motivations called, desires. Regulation of affect helps tone down these paradoxical effects. To conclude, few implications to theory and practice are discussed.

Life-LCA: assessing the environmental impacts of a human being—challenges and perspectives

The life-cycle assessment (LCA) method is typically applied to products, but the potential and demand for extending its use also to other applications are high. In this respect, this paper proposes an LCA concept to be used for the assessment of human beings as new study objects, namely Life-LCA. Key challenges of such a new approach and potential solutions for those are identified and discussed. The Life-LCA concept was developed based on a detailed desktop research. Several Life-LCA-specific challenges were identified and categorized under three research questions. One of these questions focusses on the conceptual design of a Life-LCA method while the others are addressing operational issues, which are the definition of the new study system and the practical assessment of complex human consumption behaviors. Methodological solutions are proposed, e.g., based on suggestions provided in the existing methods product LCA and organizational LCA (O-LCA). Conceptual challenges arise from the general diversity, complexity, and temporal development of human lives and consumption behaviors. We introduce Life-LCA as a two-dimensional method that covers both, the new human life cycle (dimension 1) and the life cycle of the consumed products (dimension 2). Furthermore, the two types Individual Life-LCA and Lifestyle-LCA are differentiated. Especially, the definition of a general system boundary for Life-LCA and data collection and evaluation face many operational challenges. For example, the social behavior of human beings is a new factor to be considered which causes new allocation problems in LCA. Moreover, the high demand for aggregated LCA data requires specific rules for data collection and evaluation as well as a new bottom-up product clustering scheme. Life-LCA, either used for the assessment of individual lives or lifestyles, has the potential to raise environmental awareness of people by making their specific environmental impacts comprehensively measurable and thus, tangible. However, many challenges need to be solved in future interdisciplinary research to develop a robust and applicable method. This paper conceptualizes such an approach and proposes solutions that can serve as a framework for ongoing method development.

What is cumulative cultural evolution?

In recent years, the phenomenon of cumulative cultural evolution (CCE) has become the focus of major research interest in biology, psychology and anthropology. Some researchers argue that CCE is unique to humans and underlies our extraordinary evolutionary success as a species. Others claim to have found CCE in non-human species. Yet others remain sceptical that CCE is even important for explaining human behavioural diversity and complexity. These debates are hampered by multiple and often ambiguous definitions of CCE. Here, we review how researchers define, use and test CCE. We identify a core set of criteria for CCE which are both necessary and sufficient, and may be found in non-human species. We also identify a set of extended criteria that are observed in human CCE but not, to date, in other species. Different socio-cognitive mechanisms may underlie these different criteria. We reinterpret previous theoretical models and observational and experimental studies of both human and non-human species in light of these more fine-grained criteria. Finally, we discuss key issues surrounding information, fitness and cognition. We recommend that researchers are more explicit about what components of CCE they are testing and claiming to demonstrate.