Human Behavior Patterns Research Articles

Analysis of Existing Techniques in Human Emotion and Behavioral Analysis using Deep Learning and Machine Learning Models

Abstract Artificial intelligence has become a pivotal force in the 21st-century information technology landscape, driving significant advancements in various fields. As AI continues to evolve, its capacity to understand and analyze human emotions and behaviors through machine learning has reached a new height. In practical applications, it is essential to intelligently capture the emotional information. Current research methods for studying human emotions and behaviors can be broadly classified into artificial and machine learning. Predominantly, emotion research leverages machine learning to enable AI to recognize facial expressions and perform emotion detection and feedback tasks. In the realm of human behavior research, vital structural information is extracted from limbs and skeletons for detailed analysis. Significant breakthroughs have been achieved by integrating AI technology with effective algorithms. However, existing detection mechanisms still suffer from varying degrees of error, primarily owing to imperfections in machine learning and algorithmic approaches to human emotions and behaviors, resulting in computational inaccuracies. This review explores the contributions and limitations of both machine and artificial learning in the current research landscape. This review proposes leveraging the working principles of wearable technology to develop a comprehensive detection framework for emotions and behaviors. This integrated approach aims to enhance the accuracy and reliability of AI in detecting human emotions and behaviors, thereby laying a solid foundation for future advancements in this field. By addressing the current challenges and refining methodologies, we can significantly improve AI's effectiveness of AI in understanding and interacting with human emotional and behavioral patterns.

Soft Biometrics for Authentication and Identification Hand Based on the Use of the Keyboard

Relevance. Nowadays, technological systems, artificial intelligence, the general availability of the Internet and penetration into the systems of banks, institutions and social networks have become a studied science and are accessible to all groups and ages. One of the main tasks was to provide a system for protecting confidential information from hackers, as well as easy access to authentication and identification of users. Biometric systems came to the fore, including mouse movement dynamics and keystroke dynamics, which reveal the typing style and mouse movement of each person. Soft biometrics is an interesting and inexpensive biometric method that does not require additional equipment. The system identifies a person based on the input information they enter in a special column. Hand identification dynamics falls into the category of behavioral soft biometrics, that is, the user's patterns reflect the individual program of actions that he follows when using the site.The goal of this article the purpose of this work is to improve the security level by creating a function that will strengthen the authentication system and improve the iron gate Методы исследования. In carrying out the work, methods of analysis and synthesis, theories of algorithms, laws of kinematics, neural networks, keystroke dynamics and soft biometrics were used.Results. A method for extracting dynamic characteristics of keystrokes is described. A neural network is created and a threshold value is determined for identifying the type of typing hand.Scientific novelty. Unlike known authentication methods, the proposed method is used to determine the typing hand on the keyboard through a neural network using the laws of kinematics, soft biometrics and extracting the dynamics of keystrokes in order to determine the value and accuracy of determining the type of typing hand.Significance. The proposed solution allows to increase the security of user authentication, increase the speed of implementation and reduce the cost. The results obtained in the work are positive and can be used in the near future. In turn, soft biometric measurements depend on human behavioral patterns, which complicates user falsification. It is difficult to imitate typing behavior, since it is ballistic (semi-autonomous), which makes behavioral information valuable as a soft and sensitive biometric method.

The interplay of time and space in human behavior: a sociological perspective on the TSCH model

The concept of spatiotemporal correlation, initially rooted in the domain of physics, has increasingly become of interest to scholars across various fields. This burgeoning interest is especially noted within the realm of human dynamics, where the examination of human behavior’s spatiotemporal aspects is emerging. The exploration into the nuanced ways in which human actions intertwine with geographical contexts is paramount. This paper delves into the Time-Space Characteristic Correlation of Human Behavior (TSCH) model, a pioneering framework that melds the intricacies of human behavior with geographic considerations through a micro-dynamic approach to population strategy, employing the mean-field limit method. This study scrutinizes the spatiotemporal dynamics of individual travel behaviors, focusing on specific traits such as sudden increases in activity (paroxysm B), behavioral memory (M), and the radius of gyration (Rg). The stability of these behavioral waves is evaluated through the application of the “db4” wavelet basis function, revealing stable fluctuations in population travel patterns that resonate deeply with regional characteristics. The model enables the computation of the overall cost burden of area visits for local residents, uncovering a power-law correlation between this cost and the spatial attractiveness of urban centers when analyzed at a collective level. Our findings underscore a profound linkage between the temporal and spatial patterns of human behavior at the urban scale. Furthermore, the TSCH model’s advancement facilitates a nuanced understanding of complex social issues, including urban development, public health management, and transportation systems optimization, offering valuable insights for sociological inquiry and practical application in addressing contemporary societal challenges.

Human behavior-driven epidemic surveillance in urban landscapes

We introduce a surveillance strategy specifically designed for urban areas to enhance preparedness and response to disease outbreaks by leveraging the unique characteristics of human behavior within urban contexts. By integrating data on individual residences and travel patterns, we construct a Mixing matrix that facilitates the identification of critical pathways that ease pathogen transmission across urban landscapes enabling targeted testing strategies. Our approach not only enhances public health systems’ ability to provide early epidemiological alerts but also underscores the variability in strategy effectiveness based on urban layout. We prove the feasibility of our mobility-informed policies by mapping essential mobility links to major transit stations, showing that few resources focused on specific stations yields a more effective surveillance than non-targeted approaches. This study emphasizes the critical role of integrating human behavioral patterns into epidemic management strategies to improve the preparedness and resilience of major cities against future outbreaks.

Impact of face trustworthiness on approach-avoidance behavior of adolescents with varied social anxiety traits

Approach/avoidance behavior is a basic human behavior pattern. However, more recent studies have demonstrated that this behavior pattern greatly differs among individuals. This heterogeneity has promoted research on exploring the predictive value of individual differences. Based on Person-Context Interaction Theory, the current study focused on the impact of face trustworthiness on adolescents’ approach/avoidance behavior with varied social anxiety traits. Results revealed that the avoidance behavior of highly anxiety individuals was affected by face trustworthiness, while in contrast, individuals with low levels of anxiety were only affected by face trustworthiness in their approach behavior. This indicates that adolescents tend to be more responsive to external influences in behaviors where they have greater proficiency, whereas external factors have a less significant impact on behaviors in which they lack skill. Results were also interpreted in terms of two independent social motivations, which may benefit the development of adolescents’ interpersonal relationships and the solution of extended problems caused by social problems.

Does ChatGPT have a typical or atypical theory of mind?

In recent years, the capabilities of Large Language Models (LLMs), such as ChatGPT, to imitate human behavioral patterns have been attracting growing interest from experimental psychology. Although ChatGPT can successfully generate accurate theoretical and inferential information in several fields, its ability to exhibit a Theory of Mind (ToM) is a topic of debate and interest in literature. Impairments in ToM are considered responsible for social difficulties in many clinical conditions, such as Autism Spectrum Disorder (ASD). Some studies showed that ChatGPT can successfully pass classical ToM tasks, however, the response style used by LLMs to solve advanced ToM tasks, comparing their abilities with those of typical development (TD) individuals and clinical populations, has not been explored. In this preliminary study, we administered the Advanced ToM Test and the Emotion Attribution Task to ChatGPT 3.5 and ChatGPT-4 and compared their responses with those of an ASD and TD group. Our results showed that the two LLMs had higher accuracy in understanding mental states, although ChatGPT-3.5 failed with more complex mental states. In understanding emotional states, ChatGPT-3.5 performed significantly worse than TDs but did not differ from ASDs, showing difficulty with negative emotions. ChatGPT-4 achieved higher accuracy, but difficulties with recognizing sadness and anger persisted. The style adopted by both LLMs appeared verbose, and repetitive, tending to violate Grice's maxims. This conversational style seems similar to that adopted by high-functioning ASDs. Clinical implications and potential applications are discussed.

Problems of Value Orientation of Contemporary College Students and Countermeasures

Values, in fact, is the process of cultivating one’s own mind to correctly view money, fame, gain and loss. It serves as the core of human spiritual field and influences human values and behavioural patterns. Contemporary college students are a generation of attention, they have certain knowledge and ability, with the expressive desire of exploration and research. Among the values of college students, values influence all aspects. Therefore, under the condition of socialist market economy constantly tends to improve, the main work of colleges and universities is to deeply understand the current situation of college students’ values, and timely and effectively strengthen the ideological and moral education of college students, in order to cultivate talents and qualified citizens who can be used by the society.

Mix and Match: Characterizing Heterogeneous Human Behavior in AI-assisted Decision Making

AI-assisted decision-making systems hold immense potential to enhance human judgment, but their effectiveness is often hindered by a lack of understanding of the diverse ways in which humans take AI recommendations. Current research frequently relies on simplified, ``one-size-fits-all'' models to characterize an average human decision-maker, thus failing to capture the heterogeneity of people's decision-making behavior when incorporating AI assistance. To address this, we propose Mix and Match (M&M), a novel computational framework that explicitly models the diversity of human decision-makers and their unique patterns of relying on AI assistance. M&M represents the population of decision-makers as a mixture of distinct decision-making processes, with each process corresponding to a specific type of decision-maker. This approach enables us to infer latent behavioral patterns from limited data of human decisions under AI assistance, offering valuable insights into the cognitive processes underlying human-AI collaboration. Using real-world behavioral data, our empirical evaluation demonstrates that M&M consistently outperforms baseline methods in predicting human decision behavior. Furthermore, through a detailed analysis of the decision-maker types identified in our framework, we provide quantitative insights into nuanced patterns of how different individuals adopt AI recommendations. These findings offer implications for designing personalized and effective AI systems based on the diverse landscape of human behavior patterns in AI-assisted decision-making across various domains.

EBPVis: Visual Analytics of Economic Behavior Patterns in a Virtual Experimental Environment

AbstractExperimental economics is an important branch of economics to study human behaviours in a controlled laboratory setting or out in the field. Scientific experiments are conducted in experimental economics to collect what decisions people make in specific circumstances and verify economic theories. As a significant couple of variables in the virtual experimental environment, decisions and outcomes change with the subjective factors of participants and objective circumstances, making it a difficult task to capture human behaviour patterns and establish correlations to verify economic theories. In this paper, we present a visual analytics system, EBPVis, which enables economists to visually explore human behaviour patterns and faithfully verify economic theories, e.g. the vicious cycle of poverty and poverty trap. We utilize a Doc2Vec model to transform the economic behaviours of participants into a vectorized space according to their sequential decisions, where frequent sequences can be easily perceived and extracted to represent human behaviour patterns. To explore the correlation between decisions and outcomes, an Outcome View is designed to display the outcome variables for behaviour patterns. We also provide a Comparison View to support an efficient comparison between multiple behaviour patterns by revealing their differences in terms of decision combinations and time‐varying profits. Moreover, an Individual View is designed to illustrate the outcome accumulation and behaviour patterns of subjects. Case studies, expert feedback and user studies based on a real‐world dataset have demonstrated the effectiveness and practicability of EBPVis in the representation of economic behaviour patterns and certification of economic theories.

Ecological restoration of historical monuments (With a Focus on the Restoration of Chogha Zanbil)

Architecture has always been an art wherein one can observe the traces of human desires, goals, and behavioral patterns throughout history. Iran, a land of ancient heritage, is rich in architectural elements, historical spaces, and monuments, which not only hold a powerful presence in the realm of Iranian culture but also serve as a means to revive and expand historical and cultural connections with the past. This research employs a descriptive-analytical approach alongside field observations to address the subject of restoring historical monuments and its significance and necessity for preserving the historical fabric of Iranian architecture. The approach taken in this study is ecological restoration. We aim to illustrate not only the architectural characteristics and features of the unique earthen structure of Chogha Zanbil but also to assess the countless possibilities offered by this ecological method of preserving and maintaining historical structures. The findings indicate that the ecological restoration of the Chogha Zanbil ziggurat, on one hand, preserves the historical-cultural and religious authenticity of the site, and on the other hand, reflects the cultural relationship between the architectural space of the ziggurat and the surrounding environmental elements of these historical monuments.

Human navigation strategies and their errors result from dynamic interactions of spatial uncertainties

Goal-directed navigation requires continuously integrating uncertain self-motion and landmark cues into an internal sense of location and direction, concurrently planning future paths, and sequentially executing motor actions. Here, we provide a unified account of these processes with a computational model of probabilistic path planning in the framework of optimal feedback control under uncertainty. This model gives rise to diverse human navigational strategies previously believed to be distinct behaviors and predicts quantitatively both the errors and the variability of navigation across numerous experiments. This furthermore explains how sequential egocentric landmark observations form an uncertain allocentric cognitive map, how this internal map is used both in route planning and during execution of movements, and reconciles seemingly contradictory results about cue-integration behavior in navigation. Taken together, the present work provides a parsimonious explanation of how patterns of human goal-directed navigation behavior arise from the continuous and dynamic interactions of spatial uncertainties in perception, cognition, and action.

A Study on Spatiotemporal Dynamics and Spatial Dependence of Sound Source Perception in Fuzhou Historical and Cultural Districts

As a carrier of cultural characteristics of historic districts, the soundscape has unique advantages in shaping regional cultural personality, and mastering its spatiotemporal characteristics is crucial for preserving soundscape heritage with natural and humanistic environments as its kernel. Focusing on the Three Square and Seven Alleys historic and cultural district in Fuzhou, this paper analyzes the spatial and temporal patterns of the physical acoustic indicators of the soundscape, the spatial dependence of the sound source harmony, and the spatial relationship between the two. It was found that the physical acoustic indicators showed dynamic changes in spatial and temporal scales and reflect specific human activity and behavioral patterns; sound source harmony showed spatial autocorrelation in both global and local models, with prominent spatial characteristics; and the physical acoustic indicators may negatively affect soundscape perception. The study emphasizes the importance of the regional cultural connotation of soundscape in urban planning. It provides a scientific basis for the planning, designing, and managing of soundscape resources in historic and cultural districts and world heritage sites.

Visual Experimentation Research on Traditional Residential Courtyard Spaces Using Virtual Eye-Tracking Technology

Courtyard space serves as the soul of traditional residences in Southern China, representing a gem in traditional Chinese architecture. Courtyards play a multifaceted role in architecture, including functions such as lighting, ventilation, water collection, solar radiation, and environmental beautification. This paper, building upon previous research and theoretical foundations, takes three types of courtyards in "Kong House" as the research subjects. Through methods like data collection, literature analysis, questionnaire surveys, and eye-tracking experiments, the study investigates the spatial experience of courtyard spaces in traditional residences. It quantitatively validates the design theory of courtyard spaces, analyzes the similarities and differences in spatial experiences among comprehensive courtyards, landscape courtyards, and functional courtyards, and concludes the study. The experiments indicate that incorporating courtyard spaces in traditional residences can effectively influence human behavior patterns and perceptual choices. Comprehensive courtyards typically stimulate more exploration and lingering behaviors. The combination of virtual reality and eye-tracking experiments provides valuable visual information and statistical data for analyzing human behavior and evaluating traditional residential design schemes.

Visual Experimentation Research on Traditional Residential Courtyard Spaces Using Virtual Eye-Tracking Technology

Courtyard space serves as the soul of traditional residences in Southern China, representing a gem in traditional Chinese architecture. Courtyards play a multifaceted role in architecture, including functions such as lighting, ventilation, water collection, solar radiation, and environmental beautification. This paper, building upon previous research and theoretical foundations, takes three types of courtyards in "Kong House" as the research subjects. Through methods like data collection, literature analysis, questionnaire surveys, and eye-tracking experiments, the study investigates the spatial experience of courtyard spaces in traditional residences. It quantitatively validates the design theory of courtyard spaces, analyzes the similarities and differences in spatial experiences among comprehensive courtyards, landscape courtyards, and functional courtyards, and concludes the study. The experiments indicate that incorporating courtyard spaces in traditional residences can effectively influence human behavior patterns and perceptual choices. Comprehensive courtyards typically stimulate more exploration and lingering behaviors. The combination of virtual reality and eye-tracking experiments provides valuable visual information and statistical data for analyzing human behavior and evaluating traditional residential design schemes.

Acoustic analysis and control measures for noise in university: a case study of Adrar University, Algeria

The purpose of this research is to investigate the complex dynamics of noise pollution at the University of Adrar-Algeria, with a particular emphasis on the impact that the dry desert climate has on the acoustic environment of the campus. With the goal of cultivating an environment that is characterised by tranquilly, comfort, and optimal conditions for attention, learning, and practical engagement, the research attempts to achieve the goal of enhancing the existing discourse on noise management inside academic institutions. The inquiry makes use of a methodical approach in order to investigate the many climatological characteristics that are unique to the desert climate and that lead to increased noise levels within the university grounds. In addition, the research investigates the ways in which noise emissions from various sources alter inside the confines of Adrar University, taking into account the ways in which the harsh desert climate influences the parameters that control these emissions. The investigation of human behaviour patterns is relevant to this investigation. In particular, the investigation will focus on instances of protracted assemblage in air-conditioned places, which correlates with increased noise levels. In light of the fact that noise control is an essential component of the academic environment, the research being conducted at the University of Adrar includes the collection of questionnaires, the administration of on-site sound measurements, and the creation of an all-encompassing noise map. The findings shed light on the climatic factors that are primarily responsible for the excessive amount of noise that exceeds the standards that are suggested by the World Health Organisation (WHO).

PERANAN WHATSAPP SEBAGAI MEDIA PENEGUHAN IMAN BAGI UMAT DI LINGKUNGAN BENEDIKTUS PAROKI SANTA MARIA DIANGKAT KE SURGA PALUR

This research was motivated by rapid technological developments that can change patterns of human behavior, especially in terms of praying online. This study aims to determine the role of WhatsApp as a medium of faith confirmation for people in the St. Benedict, Parish of Santa Maria Assumption Palur, Karanganyar. Data collection was carried out by observation, interviews, community meetings, and questionnaires. This research was conducted using a mixed approach between qualitative and quantitative, but leaning more towards qualitative. The collected data was validated by means of triangulation. The results of this study indicate that most people feel that WhatsApp has a role as a medium for strengthening the people's faith. They feel affirmed and think that WhatsApp is able to find God through social media. Meanwhile, there are some people who feel that WhatsApp is less helpful when it comes to praying because it is considered less solemn. The people hope that WhatsApp can be used as a means of strengthening faith through what is shared by the people.

Classic Performing Arts Supply Chain Modeling in Covid 19 Protocol to Support D.I Yogyakarta Cultural Tourism Using Soft System Methodology

The performing arts are a unique and complex industry. To enjoy performing arts products, a customer must come to the rooms where the performance takes place. Performance products can be categorized as service products that do not have a physical form. Every performing arts performance always involves many works of art with a high level of coordination. The flow of materials and information (supply chain) moves very quickly within the limitations of space and time. Because the success of performing arts is influenced by many factors and actors, a performing arts manager must be able to manage the performing arts supply chain well.The Corona Virus Disease 19 (Covid-19) pandemic which has hit almost all corners of the world has formed new patterns of human behavior in working and interacting. Likewise, organizing and enjoying performing arts will look different compared to before the Covid-19 outbreak. The implementation of health protocols is needed to minimize the spread of the virus which has infected more than 13.2 billion people throughout the world.The performing arts supply chain policy model in the Covid-19 protocol to support cultural tourism in D.I Yogyakarta can be implemented by following the Joint Decree Guidelines of the Minister of Education and the Minister of Tourism and Economy dated 02 July 2020. Each actor must pay attention to the technical guidelines for preventing and controlling corona virus disease 2019. Each actor guarantees the hygiene of their respective performing arts equipment. Each actor maintains the form and duration of physical contact and pays attention to health protocols in activities throughout the performing arts supply chain. The performing arts model during the pandemic is realized in regulations that are in accordance with the technical guidelines for preventing and controlling the 2019 corona virus disease.

A Novel Approach to Combinatorial Problems: Binary Growth Optimizer Algorithm.

The set-covering problem aims to find the smallest possible set of subsets that cover all the elements of a larger set. The difficulty of solving the set-covering problem increases as the number of elements and sets grows, making it a complex problem for which traditional integer programming solutions may become inefficient in real-life instances. Given this complexity, various metaheuristics have been successfully applied to solve the set-covering problem and related issues. This study introduces, implements, and analyzes a novel metaheuristic inspired by the well-established Growth Optimizer algorithm. Drawing insights from human behavioral patterns, this approach has shown promise in optimizing complex problems in continuous domains, where experimental results demonstrate the effectiveness and competitiveness of the metaheuristic compared to other strategies. The Growth Optimizer algorithm is modified and adapted to the realm of binary optimization for solving the set-covering problem, resulting in the creation of the Binary Growth Optimizer algorithm. Upon the implementation and analysis of its outcomes, the findings illustrate its capability to achieve competitive and efficient solutions in terms of resolution time and result quality.

Utilizing enhanced deep learning methods for residential burglary detection via analysis of human behavior patterns

Utilizing enhanced deep learning methods for residential burglary detection via analysis of human behavior patterns

Behind the waterfall - Interdisciplinary results from Holley Shelter and their implications for understanding human behavioral patterns at the end of the Middle Stone Age in southern Africa

Holley Shelter is a Middle (MSA) and Later Stone Age (LSA) site in KwaZulu-Natal, South Africa. The rock shelter is located at the intersection of three ecosystems, in a strip of the Savanna Biome between the Grassland and Indian Ocean Coastal Belt Biomes. Initial excavations in the 1950s by Gordon Cramb yielded large amounts of unifacial points and splintered pieces, as well as organic remains associated with MSA occupations. Our comparative techno-typological evaluation of this material in 2015 suggested the occupations may date to early MIS 3. We then initiated new excavations at the site using modern field methods and controlled sampling for lithic and organic material. Following the initial round of interdisciplinary analysis, we herein report the first absolute ages for Holley Shelter, a detailed technological analysis of new lithic material from the uppermost MSA layers at the site, and a preliminary study of the associated faunal remains. A set of 12 14C dates place these occupations within a constricted chronological period dated to ∼36,000–34,000 cal. BP that overlaps with the so-called ‘final MSA’. The hornfels-dominated lithic assemblages are characterized by diverse core technologies oriented toward the production of laminar products, which include bladelets and abundant splintered pieces. The zooarchaeological analysis documents an emphasis on open grasslands that provided the bulk of the animal prey exploited by the inhabitants of the shelter, with a preference for medium-sized antelopes. Three bone retouchers, a rare occurrence in southern African MSA contexts, were identified in the faunal assemblage. The archaeological deposits at Holley Shelter reflect short-term, potentially seasonal, and specialized occupations that could be influenced by its ecological position. The archaeological material exhibits marked discrepancies with other well-dated final MSA assemblages such as those from Sibhudu, Umbeli Belli, Sibebe and Border Cave. This illustrates considerable variability and a complex spatio-temporal patterning of behavioral adaptations and cultural traditions at the end of the MSA in southern Africa.