Individual Behavioral Characteristics Research Articles

Wild goose in the traditional worldview of the Buryats

The purpose of this study is to identify the image of the wild goose in the traditional worldview of the Buryats. The timeframe of this research covers the end of the 19th — middle of the 20th c., the period when the Buryats overall retained their set of mythological views. Geographically, the survey is focused on south-eastern Siberia, which includes ethnic Buryatia. The research is based on a variety of sources, including folklore, linguistic and ethnographic information. The structural-semiotic method has been chosen as the main technique of study, which allows determination of the symbolism that conveys the ideas about wild goose. It has been revealed that in minor genres of the Buryat folklore, the feminine nature of the wild goose is emphasized, and their anthroponymy mani-fests its gender differences. It has been found that, for the Buryats, the individual biological and behavioral char-acteristics of the goose were of a particular importance. It has also been determined that natural rhythms (the start of spring and the middle of autumn) were associated with the wild goose, as well as the first snowfall. At the same time, significant importance was attributed to its cry. Its image symbolized long distances and time. The motive of shapeshifting was also linked to it. This bird, both in shamanic and Buddhist traditions, was considered to be an assistant to the deity (the supreme celestial being among shamanists, and the White Elder among Bud-dhists). In the Buryat epics, it was endowed with a negative connotation. According to the traditional perceptions of some of the Cis-Baikal Buryats, the wild goose had a sacred status, and the interchangeability of images of a goose and another sacred bird — a swan — has been noted. The goose (precisely, the female goose) acted as a totem for a number of Cis-Baikal kins.

A survey on social network’s anomalous behavior detection

The onset of Web 3.0 has catalyzed the rapid advancement of social networking, transforming platforms into essential elements deeply embedded within the fabric of daily life. Researchers have proposed several methods for detecting anomalous behaviors in various scenarios. This article provides a comprehensive review of current research and the latest developments in anomalous behavior detection within social networks. We present a hierarchical three-layer categorization scheme based on the distinct characteristics of base-level detection technologies and various datasets. First, anomaly detection based on user behavioral characteristics can intuitively reflect deviations in individual behavior. However, it may overlook the overall network structure’s impact. Second, detecting anomalies within a network’s topological structure highlights structural significance, but may overlook the subtle nuances of individual behavior. Finally, the coordinated fusion method, which blends individual behavioral characteristics and the network’s topological structure, addresses the multifaceted nature of anomalies, yielding a more thorough and accurate anomaly detection strategy. This paper provides an overview and assesses the performance of three anomaly detection methods. Furthermore, we explore the challenges associated with social network anomaly detection and the potential pathways for further research.

A scoping review of web-based, interactive, personalized decision-making tools available to support breast cancer treatment and survivorship care.

We reviewed existing personalized, web-based, interactive decision-making tools available to guide breast cancer treatment and survivorship care decisions in clinical settings. The study was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews(PRISMA-ScR). We searched PubMed and related databases for interactive web-based decision-making tools developed to support breast cancer treatment and survivorship care from 2013 to 2023. Information on each tool's purpose, target population, data sources, individual and contextual characteristics, outcomes, validation, and usability testing were extracted. We completed a quality assessment for each tool using the International Patient Decision Aid Standard (IPDAS)instrument. We found 54 tools providing personalized breast cancer outcomes (e.g., recurrence) and treatment recommendations (e.g., chemotherapy) based on individual clinical (e.g., stage), genomic (e.g., 21-gene-recurrence score), behavioral (e.g., smoking), and contextual (e.g., insurance) characteristics. Forty-five tools were validated, and nine had undergone usability testing. However, validation and usability testing included mostly White, educated, and/or insured individuals. The average quality assessment score of the tools was 16 (range: 6-46; potential maximum: 63). There was wide variation in the characteristics, quality, validity, and usability of the tools. Future studies should consider diverse populations for tool development and testing. There are tools available to support personalized breast cancer treatment and survivorship care decisions in clinical settings. It is important for both cancer survivors and physicians to carefully consider the quality, validity, and usability of these tools before using them to guide care decisions.

Personality and Learning Behavioral Characteristics as Predictors of Academic Achievement of Medical Students

This study investigates whether personality characteristics and learning behaviors can predict medical students’ academic achievement in Korea, specifically in terms of successfully completing medical school without delays or achieving a high grade point average (GPA) in their final year. In May 2018, 316 medical students took the Multi-Dimensional Learning Strategy Test, 2nd edition, which provided data on their personality and learning behavioral characteristics. Their final year’s GPA and any delays in completing medical school were ascertained by reviewing all electronic academic records of each semester they had been enrolled. The combination of personality and learning behavioral characteristics was significantly associated with completing medical school without delays, even after adjusting for sex and admission path. A multiple logistic regression analysis showed that the adjusted odds ratios and 95% confidence intervals for completing medical school without delays were 1.52 (95% confidence interval [CI], 0.83–2.78) and 3.64 (95% CI, 1.70–7.82) for “others” and “both high” categories, respectively, when compared with the “both low” category. For 235 students who completed medical school without delays, their learning behavioral characteristics (scores) were significantly associated with their final year’s GPA even after adjusting for sex, admission path, and personality characteristics (scores) as determined by the multiple linear regression analysis. This study suggests that individual personality and learning behavior characteristics are predictors of medical students’ academic achievement. Therefore, interventions such as personalized counseling programs should be provided in consideration of such student characteristics.

Relations Between Rape Myths and Behavioral and Personality Characteristics in Males Convicted of Rape

To date the relationships between rape myths and other psychological constructs within males who have committed rape have not been explored sufficiently. Considered as a risk factor for the perpetration of rape it seems significant to examine their association to individual behavioral and personality characteristics more in detail. Therefore, we analyzed the relations between self-reported rape myth acceptance and the self-evaluation of aggressiveness, assertiveness, hypersexuality, social anxiety, sexual anxiety, SCID personality characteristics and the external assessment of psychopathy within a sample of N=569 males convicted of rape. The results showed significant correlations with all constructs except sexual anxiety, antisocial personality and psychopathy. Furthermore, findings indicated the assignment of the relevant variables to two principal components: rape myths, aggressiveness, hypersexuality, paranoid and narcissistic personality (K1) on the one hand and psychopathy and antisocial personality (K2) on the other hand. Following the results, rape myths are contextualized within the investigated psychological constructs and their potential differentiation from psychopathy and antisocial personality is discussed.

Behavioural characteristics influencing walking speed of pedestrians over elevated facilities: A case study of India

Walking speed is an essential parameter used in determining pedestrians' walking behavioural characteristics, the performance of a pedestrian facility, the capacity of the system, and several traffic engineering policy-related applications. While several studies have focussed on understanding walking behavioural patterns over at-grade facilities, there is still a paucity of research on understanding the influence of pedestrians' individual and group behavioural characteristics on walking speed over elevated facilities. This study uses extensive video data collected from different foot-over bridges (FOBs) and skywalks to comprehensively understand walking speed characteristics and their variations over both elevated facilities. The results of the study demonstrated the importance of considering socio-demographic factors with the associative activities involved in walking, group characteristics, and land use type in the estimation of pedestrians’ walking speed. The outcome of the study results would provide relevant policy-related strategies to designers and planners for improving infrastructures, developing realistic crowd behavioural simulation models, and estimating overall crowd dynamics.

Improving Accuracy and Security of Identification by Multimodal Biometric Fusion: An Extensive Analysis

In the modern world, trustworthy and secure identity is essential for a number of uses, such as unlocking personal gadgets and gaining access to secure areas. Conventional techniques, such as PINs and passwords, have shown to be vulnerable to fraud and illegal access. These vulnerabilities have been addressed by the development of biometric authentication, which makes use of an individual's distinct physiological and behavioral characteristics. Unimodal biometric systems concentrate on a single feature, although they frequently face difficulties like noise and spoofing assaults. By merging characteristics from several modalities, multimodal biometric systems provide an answer and improve identification robustness and accuracy. In order to increase identification security and accuracy, this article investigates the combination of hand geometry, palm print, fingerprint, and facial biometrics. Different integration situations and modes of operation for multimodal biometric systems are examined, as well as various fusion methodologies. In summary, the paper ends with implications for biometric systems practitioners, academics, and policymakers as well as a discussion of relevant research topics.

Urban overall and visible greenness and diabetes among older adults in China

Neighborhood greenness has been shown to reduce diabetes risk, however, no studies have compared the effects of overall greenness with visible greenness, which is crucial for understanding how greenness influences diabetes risk. Our study aims to explore the associations between greenness matrix and diabetes, as well as the potential effect modifications and mediating factors. We used logistic regressions to examine the cross-sectional associations of the satellite-based Normalized Difference Vegetation Index (NDVI) and street view-based Green View Index (GVI) with diabetes in 3,924 urban older adults enrolled in the 2017–2018 wave of Chinese Longitudinal Healthy Longevity Survey (CLHLS). We conducted the stratified analyses by age, sex, household income and education. Mediation analyses were also performed to see whether physical activity, BMI, air pollution, and social interaction mediate the associations. Significant associations with diabetes were only observed for NDVI but not for GVI. Participants in the highest quartile of NDVI and GVI had 52% (95 % CI: 48%, 63%) and 14% (-10%, 44%) lower odds of reporting having diabetes diagnosed by a doctor. The protective effects of NDVI were more pronounced in the young old (≥75–95 years) and high-education or high-income groups. No difference between males and females were observed. Air pollution (e.g., PM2.5, NO2 and O3) partially mediated the associations, but physical activity, BMI, and social interaction may not mediate the associations. Our findings indicate beneficial associations between overall greenness but not visible greenness surrounding residences with diabetes in older urban residents in China, especially for old adults with higher education or household income levels. Environmental factors (e.g., air pollution) but not individual behavioural characteristics are the potential underlying mechanisms.

Quantitative Model Study of the Psychological Recovery Benefit of Landscape Environment Based on Eye Movement Tracking Technology

From the perspective of landscape and human health, we use the Self-Rating Restoration Scale (SRRS) as a tool to explore the mental health restoration benefits brought by a landscape environment to individuals and explore the characteristics of individual movement behavior when viewing the landscape through the eye movement tracking technology. We selected average blink duration, average gaze length, average saccade amplitude, blink number, number of fixation points, saccade number, and average pupil diameter as experimental indicators for data monitoring. Based on the eye movement heat map obtained by data visualization processing and the results of correlation analysis, we summarized the eye movement behavior characteristics of individuals when viewing the restorative landscape. We try to construct a quantitative evaluation model of the landscape mental recovery benefit with the objective eye movement index as the independent variable through the method of curve estimation. The study results show that individual eye movement behavior is related to the landscape type and the level of psychological recovery is also different. (1)The more singular that the constituent elements are, the more widespread and concentrated the regional distribution of individual attention areas, and the relative psychological recovery benefit is relatively weak. The more complex that the constituent elements are, the more scattered and smaller the individual interest area, and the psychological recovery benefit is better. Brightly colored, dynamic landscapes are easier to form areas of interest to improve the psychological response to the human body. (2) The psychological recovery benefit of the landscape is directly proportional to the changing trend of the average blink duration, number of fixation points, and number of saccades and is inversely proportional to the changing trend of the average gaze length. (3) The objective eye movement index of average blink duration can quantitatively predict the psychological recovery benefit value of the landscape environment. The number of fixation points, the number of saccades, and the average fixation length could predict the psychological recovery benefits of the landscape, while the other indicators had no prediction effect.

ALLEVIATING POVERTY THROUGH ENTREPRENEURSHIP: HOMO ENTREPRENEUR, ENTREPRENEURIAL CULTURE, AND STATE

<em>Creating economic well-being considers entrepreneurship as a basic factor. Improving entrepreneurship improves economic well-being/wealth at all levels of aggregation: individual, family, social community, state, and world civilization. Improving entrepreneurship means applying knowledge and understanding its causal factors. It is essentially a psychological, socio-cultural, and political-economic phenomenon. As a psychological/mental phenomenon, it can be recognized in individual conative (value), emotional-motivational, intellectual, and behavioral characteristics of people who start businesses (characteristics of enterprising persons/homo entrepreneur). As a social/cultural phenomenon, entrepreneurship recognizes social attitudes and behavior (culture), manifested as a mentality as a key success ingredient. As a political-economic phenomenon, it recognizes the importance of the political-economic situation, that is, in the actual resource support of state institutions, the absence of obstacles/disincentives for entrepreneurs, and in economic policies, practices, and habits that stimulate entrepreneurial ventures and economic growth. The results of the discussion about the individual, socio-cultural, and political-economic characteristics necessary for an entrepreneurial (creative) society have several outcomes. In the context of poverty alleviation, there is indicated the necessity of cultivating/internalizing: a) specific characteristics of entrepreneurs that make up an entrepreneurial person/homo entrepreneur, b) specific entrepreneurial values - cultural characteristics that form an entrepreneurial culture/mentality, and c) specific political-economic entrepreneurship prone characteristics/behavior of the state (state institutions) that form an entrepreneurial state. In such a context, management solutions for entrepreneurial/economic development improvement should suggest an integral strategy for poverty alleviation. Such a strategy should have different levels of aggregation from the individual to the global civilization of the human species.</em>

Using the H2O Automatic Machine Learning Algorithms to Identify Predictors of Web-Based Medical Record Nonuse Among Patients in a Data-Rich Environment: Mixed Methods Study.

With the advent of electronic storage of medical records and the internet, patients can access web-based medical records. This has facilitated doctor-patient communication and built trust between them. However, many patients avoid using web-based medical records despite their greater availability and readability. On the basis of demographic and individual behavioral characteristics, this study explores the predictors of web-based medical record nonuse among patients. Data were collected from the National Cancer Institute 2019 to 2020 Health Information National Trends Survey. First, based on the data-rich environment, the chi-square test (categorical variables) and 2-tailed t tests (continuous variables) were performed on the response variables and the variables in the questionnaire. According to the test results, the variables were initially screened, and those that passed the test were selected for subsequent analysis. Second, participants were excluded from the study if any of the initially screened variables were missing. Third, the data obtained were modeled using 5 machine learning algorithms, namely, logistic regression, automatic generalized linear model, automatic random forest, automatic deep neural network, and automatic gradient boosting machine, to identify and investigate factors affecting web-based medical record nonuse. The aforementioned automatic machine learning algorithms were based on the R interface (R Foundation for Statistical Computing) of the H2O (H2O.ai) scalable machine learning platform. Finally, 5-fold cross-validation was adopted for 80% of the data set, which was used as the training data to determine hyperparameters of 5 algorithms, and 20% of the data set was used as the test data for model comparison. Among the 9072 respondents, 5409 (59.62%) had no experience using web-based medical records. Using the 5 algorithms, 29 variables were identified as crucial predictors of nonuse of web-based medical records. These 29 variables comprised 6 (21%) sociodemographic variables (age, BMI, race, marital status, education, and income) and 23 (79%) variables related to individual lifestyles and behavioral habits (such as electronic and internet use, individuals' health status and their level of health concern, etc). H2O's automatic machine learning methods have a high model accuracy. On the basis of the performance of the validation data set, the optimal model was the automatic random forest with the highest area under the curve in the validation set (88.52%) and the test set (82.87%). When monitoring web-based medical record use trends, research should focus on social factors such as age, education, BMI, and marital status, as well as personal lifestyle and behavioral habits, including smoking, use of electronic devices and the internet, patients' personal health status, and their level of health concern. The use of electronic medical records can be targeted to specific patient groups, allowing more people to benefit from their usefulness.

Sedentary behaviour and traumatic dental injuries in adolescents: A population-based study.

Analyse factors associated with dental trauma in 12-year-old adolescents. An epidemiological survey was carried out in the five largest cities in the state of Mato Grosso do Sul, Brazil. Data on traumatic dental injuries (TDI) based on the World Health Organization (WHO), sociodemographic characteristics and individual clinical and behavioural characteristics in 615 adolescents were collected. Univariate and adjusted multilevel logistic regressions were performed to test the association of dental trauma with behavioural and sociodemographic factors. The study was approved by the Ethics Committee (CAAE number 85647518.4.0000.0021). The prevalence of TDI at 12 years was 3.4% (95% CI 1.8; 6.4). In the adjusted models, clinical characteristics of adolescents such as overjet >3 mm (OR = 1.51 [95% CI 1.00; 2.41]) were associated with trauma. Sociodemographic characteristics such as female sex (OR = 0.13 [95% CI 0.07; 0.25]), income above the poverty level (OR = 0.34 [95% CI 0.15; 0.78]), who declared themselves white (OR = 0.23 [95% CI 0.11; 0.47]) and with sedentary behaviour (OR = 0.69 [95% CI 0.59; 0.80]) were associated with trauma, as protective factors. Sociodemographic, behavioural and individual clinical characteristics were associated with TDI in adolescents. Oral health teams should focus on the most vulnerable groups, encouraging the use of mouthguards and access to treatment services.

MODELING THE DEFAULT RISK OF CARD LOANS CONSIDERING INDIVIDUAL BEHAVIOR CHARACTERISTICS BASED ON BANK ACCOUNT DEPOSIT AND WITHDRAWAL DATA

In general, banks keep management costs for card loans down because the amounts are smaller than those of corporate loans. Therefore, they are not sufficiently managed after the money is lent. This study analyzes the deposit and withdrawal data of bank accounts used by card loan borrowers and proposes a default risk management technique. A previous study analyzed bank account data for screening applicants for card loans, and constructed a model to evaluate default risk. However, to the best of our knowledge, there are no studies that analyze bank account data to determine measures for managing the default risk while lending money with a card loan or construct a management model. In addition to the explanatory variables used in the screening model, we employ some variables observable after lending money that are related to individual behavior characteristics, such as number of borrowings and contract repayment rate, and analyze their relationships with default. We construct a logit model using these variables and examine the model using approximately 60 million observations. The result shows that the accuracy ratios exceed 50%, and the model is effective in practice. We also confirm the robustness of the results through cross-validation and an out-of-sample test.

Classification Of Hand Images by Person, Age and Gender with The Median Robust Extended Local Binary Model

Biometric technologies try to automatically recognize individuals by considering the physiological and behavioral characteristics of individuals. Although the methods used here are very diverse, the personal qualities used also vary. Facial features, finger and vein prints, iris, retina, ear, hand, and finger recognition are only some of the physiological features. It may be preferred to use one or more of these personal features to reduce the margin of error that may arise depending on the security level in the applications used. Biometric recognition systems have varying requirements in security systems applications. Fingerprint and iris recognition work well in applications that require high security levels, while applications that require low security levels are not suitable due to privacy concerns. On the other hand, identification from hand images is more accepted based on the idea that it does not have a very high distinctiveness. But it is sufficient for medium security applications. Apart from these, palm images have many advantages such as reliability, stability, user-friendliness, non-intrusiveness, and flexible use. In this study, it is aimed to identify people, determine their ages, and determine their gender by using both upper surface and inner surface images of right-left hand data of hand shape. For this purpose, images of both the inner surface of the hand (10) and the outer surface of the hand (10) of 100 different people were collected. This was done separately for the right and left hands, and a total of 3955 images were obtained. The features of these images were extracted using the Median Robust Extended Local Binary Model (MRELBP). Images are classified for person, age and gender. The results were 91.4%, 85.9% and 92.6%, respectively.

The Effects of Winter Parks in Cold Regions on Cognition Recovery and Emotion Improvement of Older Adults: An Empirical Study of Changchun Parks.

Urban parks are one of the primary settings for older adults to exercise, and their health benefits have been confirmed by a large number of studies. However, with the increased social attention to mental health, there is not enough research on the short-term mental health recovery of older adults in parks. Meanwhile, the health recovery effects of winter parks in special climate areas have not been well explored. This study aimed to explore the effects of winter parks in cold regions on the short-term mental health recovery of older adults and the potential predictors of these effects, including individual status, park characteristics, and behavioral characteristics. This study divided short-term mental health recovery into cognitive recovery and emotional improvement, and selected the digit span test and 10 kinds of emotional expression as the experimental methods, recruited 92 older adults from 6 parks in Changchun, and compared the pre-test and post-test results for evaluation. The results showed that winter parks in cold cities still had short-term cognitive recovery and emotional improvement effects on older adults. The main park characteristic factors affecting the overall cognitive recovery were the evergreen vegetation area and the existence of structures, and that which affected the overall emotional improvement was the main pathway length. Furthermore, individual conditions, including gender, age, physical health, living and customary conditions, and park characteristics, including park type, park area, main pathway length, square area, equipment area, evergreen vegetation area, the presence of water, and structures, all related to short-term mental health recovery effects. Among behavioral characteristics, stay time in parks and MVPA (Moderate and Vigorous Physical Activity) times were also related to certain effects, but behavior type was not.

Fingerprint image enhancement using multiple filters.

Biometrics is the measurement of an individual's distinctive physical and behavioral characteristics. In comparison to traditional token-based or knowledge-based forms of identification, biometrics such as fingerprints, are more reliable. Fingerprint images recorded digitally can be affected by scanner noise, incorrect finger pressure, condition of the finger's skin (wet, dry, or abraded), or physical material it is scanned from. Image enhancement algorithms applied to fingerprint images remove noise elements while retaining relevant structures (ridges, valleys) and help in the detection of fingerprint features (minutiae). Amongst the most common image enhancement filters is the Gabor filter, however, given their restricted maximum bandwidth as well as limited range of spectral information, it falls short. We put forward a novel method of fingerprint image enhancement using a combination of a diffusion-coherence filter and a 2D log-Gabor filter. The log-Gabor overcomes the limitations of the Gabor filter while Coherence Diffusion mitigates noise elements within fingerprint images. Implementation is done on the FVC image database and assessed via visual comparison with coherence diffusion used disjointedly and with the Gabor filter.

Contextual and individual factors associated with self-reported tooth loss among adults and elderly residents in rural riverside areas: A cross-sectional household-based survey.

Tooth loss is an oral health condition with high prevalence and negative impact on quality of life. It is the result of the history of oral diseases and their treatment as well as provision of dental care and access to dental services. Socioeconomic characteristics are determinants of tooth loss and living in rural areas is also a risk factor for its incidence. To identify contextual and individual factors associated with self-reported tooth loss among adults and elderly people living in rural riverside areas. A cross-sectional household-based survey was conducted in 2019 with rural riverside communities on the left bank of the Rio Negro River, Manaus, Amazonas. These communities are covered by a fluvial health team and two riverside health teams. Interviews were conducted in a representative random sample of dwellers aged ≥ 18 years, using electronic forms to obtain information on oral health conditions, demographic and socioeconomic characteristics, and use of and access to health services. The outcome was self-reported tooth loss. After the descriptive analysis of the data, a multilevel Poisson regression analysis was performed to estimate the prevalence ratio for the outcome. Variables with p-value ≤0.20 in the bivariate analyses were included in the multiple analysis considering the hierarchy between individual and contextual variables in the multilevel model. Variables with p-value ≤0.10 were kept in the final model and the significance level adopted was 0.05. 603 individuals from 357 households were assessed (mean age 44.1 years). The average number of missing teeth was 11.2 (±11.6); 27.4% of individuals had lost more than 20 teeth (non-functional dentition) and 12.1% were completely edentulous. Contextual characteristic of primary healthcare offered was associated with the outcome. The tooth loss was lower in territories covered by riverside health teams. At individual level, tooth loss was greater in older individuals who had experienced dental pain over the past six months and whose sugar consumption was high. Black or brown individuals, individuals whose household income was higher, those who were on the Bolsa Família cash transfer program, those who consulted a dentist over the past year, and those who reported satisfaction with their teeth/oral health reported less tooth loss. Tooth loss was associated with contextual territorial factors related to the healthcare service and individual demographic, behavioral, socioeconomic, and service-related characteristics as well as self-perceived oral health conditions. The findings suggest that actions focused on the oral health of these populations involve not only changes in the healthcare service organization, but also intersectoral policies that contribute to reducing social inequalities.

Socio-cultural definition of intercultural dialogue in the concept of Mary Douglas

The research is aimed at uncovering the distinctiveness of the culture types (or communities) identified by Mary Douglas, and at determining the extent of inner willingness for intercultural communication of the representatives of those culture types. The authors are motivated by the inadequacy of the prevailing in modern intellectual discourse division of societies into "open" and “closed" ones. In particular, they emphasize that the global tendency of societies towards openness should have led to an emergence of Kant's citizen of the world, but instead it led to an increase of cultural intolerance and an exacerbation of intercultural conflicts. In view of this, the typology of societies conceptualized in Karl Popper's works needs significant reexamination, expansion, and clarification; the intellectual work of Mary Douglas accomplishes this goal in its own way. Mary Douglas's scientific work, in particular her concept of “grid/group" can become a theoretical foundation for the study of problems and contradictions of intercultural communication. The "cultural map”, proposed by the researcher, makes it possible to determine the level of openness of the representatives of a certain cultural environment to intercultural communication, and to predict its effectiveness and its consequences. In addition, the concept of “grid/group”, developed by the researcher, can become a useful theoretical basis for the study of "cultural intelligence”. Evaluation of social structuring and categorization from the standpoint of Durkheim's approach enabled Mary Douglas to demonstrate the particulars of formation and maintenance of cultural boundaries by means of ritual and to form an original "cultural map", identifying four extreme types of social communities with a clear internal structure. The latter organizes the social and cultural experience of each member of the community, determining the characteristics of his or her behavior, including the willingness for intercultural interaction. In the works of Mary Douglas, it manifests itself not only and not so much as an individual’s personal mood, but as a specific and predetermined social program of interaction with representatives of other cultural environments, that is, a kind of mental directive. It determines the characteristics of individual behavior of each person; meaning, it becomes a schematic marker of a person's cultural affiliation, thus facilitating the understanding of cultural differences and motivation of a person in a group.

청소년 자살 위험과 정서·행동 특성에 관한 연구

The purpose of this study is to understand the effect of youth emotional and behavioral characteristics on suicide risk and to understand the vulnerability of risk groups. The dependent variable was set as suicide risk, including suicidal thoughts, plans, and attempts, and the independent variable was set as general characteristics, risk factors for school violence, emotional and behavioral factors, and personality factors. First, as a result of identifying the difference between each variable according to general characteristics using the T-test and the ANOVA, the risk of suicide and the risk of female students in emotional and behavioral problems were high. In the relationship between drug abuse, self-esteem, and parents, male students were high, and the difference in suicide risk according to grades was not significant. Second, in identifying suicide risk influencing factors using multiple regression analysis, grades and self-esteem were high, and the more positive the parent relationship, the lower the risk of suicide. Factors that increase the risk of suicide were psychological burden (733), mood problems (.327), drug abuse (.174), and Internet dependence (146). Third, as a result of analyzing the differences by group using cross-analysis, the groups with a high proportion of suicide risk were identified as the management group of psychological burden, mood problems, anxiety problems, poor self-control, drug abuse management group, and Internet dependence. Fourth, in the analysis of suicide risk using logistic regression analysis, the risk of suicide was high in the first year of middle school and first year of high school, and the risk of suicide was found to be high in the mood problem management group, drug abuse management group, anxiety problem management group, Internet dependence management group, low self-esteem group, and low community conscious group. Youth suicide risk is complex due to the interaction of individual personality, emotional and behavioral characteristics, and social environmental factors, so intervention in cooperation programs by local communities is necessary rather than individual approaches of risk groups

Graph method for driving behavior optimization based on “SAF-ECO” description of behavior characteristics

Considering the fact that driving behavior data possesses characteristics of strong real-time, poor stability, and continuous change, this study proposes the Individual Driving Behavior Graph Construction Method (DBGCM), which visually presents the time trajectory of driving behavior to explore safety-ecological (SAF-ECO) characteristics of individual drivers. The results can be applied in the analysis of driving safety ecology and as a reference for driving behavior optimization. This study is based on the micro-driving behavior data collected by the on-board diagnostic devices (OBD), which can create a graph on individual driver behavior characteristics via nodes and time axis as its elements. Additionally, the method of Longest Common Subsequence (LCSS) is proposed to identify the similarity among different driving behavior graphs. The data results of taxi drivers under different SAF-ECO levels lead to the conclusion that the driving behavior characteristics graph analysis is consistent with the SAF-ECO classification. The similarity of graphs among “safe and non-eco” drivers is higher than that within other categories. Finally, the research discusses in detail the data requirements, method verification, and future applications. The reasonable coupling characteristic description of “SAF-ECO” driving behavior is conducive to the enhancement of drivers’ self-management ability, driving education, and customization for drivers.