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Готові списки джерел за темами / Features of behavior / Статті в журналах

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Статті в журналах з теми "Features of behavior"

Автор: Grafiati

Опубліковано: 28 травня 2022

Оновлено: 31 липня 2025

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1

Kurbatova, T. N., and Yu A. Valova. "Psychological features and teenage sexual behavior." Psychology and Law 5, no. 4 (2015): 150–60. http://dx.doi.org/10.17759/psylaw.2015050413.

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The paper presents the results of an empirical study on the personality traits of sexually active teenagers. The research identified the personality traits of teenagers who are inclined to look for sexual relations. The research focused on the following: motivation and values, implicit representations about sexual contacts, parent-child relations, and self-concept. The study comprised 465 individuals including 405 school students aged 14-16 and 60 mothers of the teenagers examined. The results demonstrate that teenagers' refusal to begin sexual life, provided they have this opportunity (i.e. a

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2

Maitham, Ali Naji, Ahmed Salman Ghalib, and Jasim Fadhil Muthna. "Face recognition using selected topographical features." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (2020): 4695–700. https://doi.org/10.11591/ijece.v10i5.pp4695-4700.

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This paper represents a new features selection method to improve an existed feature type. Topographical (TGH) features provide large set of features by assigning each image pixel to the related feature depending on image gradient and Hessian matrix. Such type of features was handled by a proposed features selection method. A face recognition feature selector (FRFS) method is presented to inspect TGH features. FRFS depends in its main concept on linear discriminant analysis (LDA) technique, which is used in evaluating features efficiency. FRFS studies feature behavior over a dataset of images t

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3

Kovrigina, G. D. "Features of Prosocial Behavior." Humanitarian Vector 14, no. 2 (2019): 33–41. http://dx.doi.org/10.21209/1996-7853-2019-14-2-33-41.

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4

Родинова, Н. П., В. М. Остроухов, and А. Е. Ерзин. "Features of consumer behavior." Экономика и предпринимательство, no. 1(126) (March 12, 2021): 911–13. http://dx.doi.org/10.34925/eip.2021.126.01.178.

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В статье представлены модели потребительского поведения, принципы маркетинговой модели поведения потребителей, комплексная модель потребительского поведения, процесс принятия потребительского решения. The article presents the models of consumer behavior, the principles of the marketing model of consumer behavior, a complex model of consumer behavior, the process of making a consumer decision.

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5

Li, Sheliang, and Huaqi Chai. "Recognition of Teaching Features and Behaviors in Online Open Courses Based on Image Processing." Traitement du Signal 38, no. 1 (2021): 155–64. http://dx.doi.org/10.18280/ts.380116.

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High-quality online open courses have a wide audience. To further improve the quality of these courses, it is critical to analyze the teaching behaviors in class, which are the manifestation of the overall quality of the teacher. Considering the popularity of image processing-based behavior recognition in many disciplines, this paper explores deep into the teaching features and behaviors in online open courses based on image processing. Firstly, a coding scale was designed for teaching behaviors in online open courses. Next, the principle of optical flow solving was explained for teaching vide

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6

SKAKOVSKYI, Viacheslav. "FORMATION OF ECONOMIC BEHAVIOR OF ENTERPRISES: PROCESS AND FEATURES." Herald of Khmelnytskyi National University. Economic sciences 312, no. 6(2) (2022): 314–17. http://dx.doi.org/10.31891/2307-5740-2022-312-6(2)-52.

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The work considers the process of forming of economic behavior of enterprises on the basis of features of functioning of modern enterprises. It was determined that the process of forming an enterprise’s economic behavior strategy is characterized by a set of features: the level of development, regularity, uncertainty, the number of possible alternative solutions, which should be taken into account when forming economic behavior; information used in the formation of economic behavior; time horizons; interdependence; detail; assessment accuracy; degree of risk. Also the necessity of opening of f

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7

Donia, Manar M. F., Wessam H. El-Behaidy, and Aliaa A. A. Youssif. "Impulsive Aggression Break, Based on Early Recognition Using Spatiotemporal Features." Big Data and Cognitive Computing 7, no. 3 (2023): 150. http://dx.doi.org/10.3390/bdcc7030150.

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The study of human behaviors aims to gain a deeper perception of stimuli that control decision making. To describe, explain, predict, and control behavior, human behavior can be classified as either non-aggressive or anomalous behavior. Anomalous behavior is any unusual activity; impulsive aggressive, or violent behaviors are the most harmful. The detection of such behaviors at the initial spark is critical for guiding public safety decisions and a key to its security. This paper proposes an automatic aggressive-event recognition method based on effective feature representation and analysis. T

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8

Polskaya, N. A. "Features of Self-Injurious Behavior in Adolescence and Youth." Izvestiya of Saratov University. Philosophy. Psychology. Pedagogy 10, no. 1 (2010): 92–97. http://dx.doi.org/10.18500/1819-7671-2010-10-1-92-97.

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The research is aimed to studying features of self-injurious behaviour in adolescence and youth. This purpose makes us analyse such characteristics as self-attitude, coping behaviour, cases of psychological traumatization, deviant socialization and self-injurious behavior. Three types of self-injurious behavior: a deviant, a prosocial and a personality-dysfunctional one are defined.

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9

Zhang, Jun, ZhongCheng Wu, Fang Li, et al. "A Deep Learning Framework for Driving Behavior Identification on In-Vehicle CAN-BUS Sensor Data." Sensors 19, no. 6 (2019): 1356. http://dx.doi.org/10.3390/s19061356.

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Human driving behaviors are personalized and unique, and the automobile fingerprint of drivers could be helpful to automatically identify different driving behaviors and further be applied in fields such as auto-theft systems. Current research suggests that in-vehicle Controller Area Network-BUS (CAN-BUS) data can be used as an effective representation of driving behavior for recognizing different drivers. However, it is difficult to capture complex temporal features of driving behaviors in traditional methods. This paper proposes an end-to-end deep learning framework by fusing convolutional n

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10

Turgunboyev, Anvar Uzokboyevich. "CHARACTERISTIC FEATURES OF AUTOAGRESSIVE BEHAVIOR IN ADOLESCENTS." IQRO 1, no. 2 (2023): 64–75. https://doi.org/10.5281/zenodo.7616139.

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The problem of the study of autoaggressive behavior is one of the urgent problems of Psychiatry, medical psychology, medicine and jurisprudence Autoaggression is one of the forms of human behavior in an extreme situation, the nature and "severity" of which are the result of the addition of individual biological reactions of the body, personal psychological attitudes that occur under the influence of certain social conditions. Adolescents with autodestructive tendencies are a risk group because they consider spontaneous traumatic behaviors to be a way to deal with stress, tension and

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11

Wang, Yulin, Tao Song, Yichen Yang, and Zheng Hong. "Research on Multi-Scale Spatio-Temporal Graph Convolutional Human Behavior Recognition Method Incorporating Multi-Granularity Features." Sensors 24, no. 23 (2024): 7595. http://dx.doi.org/10.3390/s24237595.

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Aiming at the problem that the existing human skeleton behavior recognition methods are insensitive to human local movements and show inaccurate recognition in distinguishing similar behaviors, a multi-scale spatio-temporal graph convolution method incorporating multi-granularity features is proposed for human behavior recognition. Firstly, a skeleton fine-grained partitioning strategy is proposed, which initializes the skeleton data into data streams of different granularities. An adaptive cross-scale feature fusion layer is designed using a normalized Gaussian function to perform feature fus

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12

Yu, Youxin, Wenbo Zhu, Xiaoli Ma, et al. "Recognition of Sheep Feeding Behavior in Sheepfolds Using Fusion Spectrogram Depth Features and Acoustic Features." Animals 14, no. 22 (2024): 3267. http://dx.doi.org/10.3390/ani14223267.

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In precision feeding, non-contact and pressure-free monitoring of sheep feeding behavior is crucial for health monitoring and optimizing production management. The experimental conditions and real-world environments differ when using acoustic sensors to identify sheep feeding behaviors, leading to discrepancies and consequently posing challenges for achieving high-accuracy classification in complex production environments. This study enhances the classification performance by integrating the deep spectrogram features and acoustic characteristics associated with feeding behavior. We conducted t

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13

Shestakovich, K. "Features of Organizational Behavior Staff." Bulletin of Science and Practice 5, no. 5 (2019): 370–75. http://dx.doi.org/10.33619/2414-2948/42/50.

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14

Isamutdinovna, Salakhutdinova Musharraf, and Musinova Rukhshona Yunusovna. "Modern features of suicidal behavior." ACADEMICIA: An International Multidisciplinary Research Journal 10, no. 5 (2020): 1965. http://dx.doi.org/10.5958/2249-7137.2020.00417.6.

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15

Krainikov, E., E. Prokopovich, Yu Zemlyakova, and S. Primachenko. "FEATURES OF TEENAGERS' DEVIANT BEHAVIOR." Bulletin of Taras Shevchenko National University of Kyiv. Series “Psychology”, no. 2 (9) (2018): 27–30. http://dx.doi.org/10.17721/bsp.2018.2(9).7.

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In order to investigate the problem, we conducted a psychodiagnostic study. During the implementation of the survey, the following tools were used: A. Bass – A. Darkey Questionnaire, Mini-Multifactor Test, Suicidal Risk Questionnaire (T.N. Razuvaeva Modification), Kimberley-Young Internet Addiction Test, Method for determining the tendencies to deviant behavior (A.Orel). The survey was conducted through the written face-to- face group survey of respondents. The resulting data was processed and summarized using statistical processing methods (SPSS v 23). The sample consisted of 78 adolescents (

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16

Marcih, Kristina Igorevna. "Features of parasportsmen’s coping behavior." Interactive science, no. 4 (June 20, 2016): 57–60. http://dx.doi.org/10.21661/r-80938.

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17

Zinovyeva, Tatyana Aleksandrovna. "GENDER FEATURES OF VERBAL BEHAVIOR." Theoretical & Applied Science 28, no. 08 (2015): 100–103. http://dx.doi.org/10.15863/tas.2015.08.28.17.

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18

Ovchinnikova, Julia E. "Psychological features of investment behavior." Theoretical and Practical Aspects of Management 2020, no. 8 (2020): 113–24. http://dx.doi.org/10.46486/0234-4505-2020-8-113-124.

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19

Fan, Qile, Penghang Yu, Zhiyi Tan, Bing-Kun Bao, and Guanming Lu. "BeFA: A General Behavior-driven Feature Adapter for Multimedia Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 11 (2025): 11634–44. https://doi.org/10.1609/aaai.v39i11.33266.

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Multimedia recommender systems focus on utilizing behavioral information and content information to model user preferences. Typically, it employs pre-trained feature encoders to extract content features, then fuses them with behavioral features. However, pre-trained feature encoders often extract features from the entire content simultaneously, including excessive preference-irrelevant details.We speculate that it may result in the extracted features not containing sufficient features to accurately reflect user preferences. To verify our hypothesis, we introduce an attribution analysis method

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20

Nitisha, Tyagi*1 &. Amit Asthana2. "A SURVEY PAPER FOR FACE RECOGNITION TECHNOLOGIES." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 4 (2018): 217–23. https://doi.org/10.5281/zenodo.1213071.

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The biometric is a study of human behavior and features. Face recognition is a technique of biometric. Various approaches are used for it. A survey for all these techniques is in this paper for analyzing various algorithms and methods. Face recognition is emerging branch of biometric for security as no faces can be defeated as a security approach. So, how we can recognize a face with the help of computers is given in this paper.  Face Recognition plays a major role in Biometrics. Feature selection is a measure issue in face recognition. This paper proposes a survey on face recognition. Th

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21

Мarchyshyna, YE, V. Melnyk, and M. Yaremchuk. "Features of safe and healthy behavior of ostrich care workers." Sučasne ptahìvnictvo, no. 5-6 (June 25, 2020): 18–25. http://dx.doi.org/10.31548/poultry2020.05-06.018.

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The historical aspects, significance, peculiarities of ostrich behavior and occupational safety of ostrich farm workers are analyzed. It is noted that ostrich farming began in the world in the late XIXth century. The authors study the domestic and foreign practice of stausivnytstva. Describes the significant contribution of the industry in obtaining ostrich products – leather, meat, eggs, feathers. The value of staus products in comparison with other species of animals is noted. It is emphasized that during the care, feeding and observation of ostriches it is necessary to follow the establishe

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22

KARA, LEVENT BURAK, and THOMAS F. STAHOVICH. "Causal reasoning using geometric analysis." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 16, no. 5 (2002): 363–84. http://dx.doi.org/10.1017/s0890060402165036.

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We describe an approach that uses causal and geometric reasoning to construct explanations for the purposes of the geometric features on the parts of a mechanical device. To identify the purpose of a feature, the device is simulated with and without the feature. The simulations are then translated into a “causal-process” representation, which allows qualitatively important differences to be identified. These differences reveal the behaviors caused and prevented by the feature and thus provide useful cues about the feature's purpose. A clear understanding of the feature's purpose, however, requ

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23

Wang, Xiao Fei, Jun Hu, Yin Kuang, Wei Yu, and Rui Sun. "A Classification Method Based on Multi-Features for Abnormal Crowd Behaviors." Applied Mechanics and Materials 685 (October 2014): 501–6. http://dx.doi.org/10.4028/www.scientific.net/amm.685.501.

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An abnormal crowd behavior would harm social public security. Different abnormal crowd behaviors would bring about different harms and subject to different attentions of social public. The higher the harm of the abnormal crowd behavior was, the higher the attention of the social public would be. Therefore, in this paper, a classification method, using crowd density estimation and crowd intensity, is proposed for abnormal crowd behaviors. In order to describe the abnormal crowd behavior more reasonably, we shoot some videos. Finally, the effectiveness and accuracy of our method for abnormal beh

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24

Zhu, Xiaoliang, Yuanxin Ye, Liang Zhao, and Chen Shen. "MOOC Behavior Analysis and Academic Performance Prediction Based on Entropy." Sensors 21, no. 19 (2021): 6629. http://dx.doi.org/10.3390/s21196629.

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In recent years, massive open online courses (MOOCs) have received widespread attention owing to their flexibility and free access, which has attracted millions of online learners to participate in courses. With the wide application of MOOCs in educational institutions, a large amount of learners’ log data exist in the MOOCs platform, and this lays a solid data foundation for exploring learners’ online learning behaviors. Using data mining techniques to process these log data and then analyze the relationship between learner behavior and academic performance has become a hot topic of research.

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25

Guo, Yangyang, Yongliang Qiao, Salah Sukkarieh, Lilong Chai, and Dongjian He. "BiGRU-Attention Based Cow Behavior Classification Using Video Data for Precision Livestock Farming." Transactions of the ASABE 64, no. 6 (2021): 1823–33. http://dx.doi.org/10.13031/trans.14658.

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HighlightsBiGRU-attention based cow behavior classification was proposed.Key spatial-temporal features were captured for behavior representation.BiGRU-attention achieved &gt;82% classification accuracy on calf and adult cow datasets.The proposed method could be used for similar animal behavior classification.Abstract. Animal behavior consists of time series activities, which can reflect animals’ health and welfare status. Monitoring and classifying animal behavior facilitates management decisions to optimize animal performance, welfare, and environmental outcomes. In recent years, deep lea

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26

Hu, Ganglin, Jun Pang, and Xian Mo. "Effective attributed network embedding with information behavior extraction." PeerJ Computer Science 8 (July 8, 2022): e1030. http://dx.doi.org/10.7717/peerj-cs.1030.

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Network embedding has shown its effectiveness in many tasks, such as link prediction, node classification, and community detection. Most attributed network embedding methods consider topological features and attribute features to obtain a node embedding but ignore its implicit information behavior features, including information inquiry, interaction, and sharing. These can potentially lead to ineffective performance for downstream applications. In this article, we propose a novel network embedding framework, named information behavior extraction (IBE), that incorporates nodes’ topological feat

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27

Alkinani, Monagi H., Wazir Zada Khan, Quratulain Arshad, and Mudassar Raza. "HSDDD: A Hybrid Scheme for the Detection of Distracted Driving through Fusion of Deep Learning and Handcrafted Features." Sensors 22, no. 5 (2022): 1864. http://dx.doi.org/10.3390/s22051864.

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Traditional methods for behavior detection of distracted drivers are not capable of capturing driver behavior features related to complex temporal features. With the goal to improve transportation safety and to reduce fatal accidents on roads, this research article presents a Hybrid Scheme for the Detection of Distracted Driving called HSDDD. This scheme is based on a strategy of aggregating handcrafted and deep CNN features. HSDDD is based on three-tiered architecture. The three tiers are named as Coordination tier, Concatenation tier and Classification tier. We first obtain HOG features by u

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28

Yan Zhang, Yan Zhang, and Wei Wei Yan Zhang. "Research on the Application of Behavioral Image Feature Capture in Basketball Game Video." 網際網路技術學刊 25, no. 1 (2024): 157–65. http://dx.doi.org/10.53106/160792642024012501013.

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<p>In order to realize intelligent image recognition of foul behavior in basketball games, this paper designs a feature capture method of video foul behavior based on improved bilateral filtering algorithm. Adaptive bilateral filtering is used to denoise the video image, and the optical flow feature and HOG feature of the behavior in the denoised image are obtained by image combination feature extraction method, which is fused to a combined eigenvector. The combined features were taken as the target recognition samples, and the multi-back propagation neural network was used to identify t

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29

Zhang, Jian, Shengquan Liu, and Zhihua Liu. "Attribution classification method of APT malware based on multi-feature fusion." PLOS ONE 19, no. 6 (2024): e0304066. http://dx.doi.org/10.1371/journal.pone.0304066.

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In recent years, with the development of the Internet, the attribution classification of APT malware remains an important issue in society. Existing methods have yet to consider the DLL link library and hidden file address during the execution process, and there are shortcomings in capturing the local and global correlation of event behaviors. Compared to the structural features of binary code, opcode features reflect the runtime instructions and do not consider the issue of multiple reuse of local operation behaviors within the same APT organization. Obfuscation techniques more easily influen

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30

Hu, Jinli, Jueying Wu, Yangyang Sun, Xinyu Zhao, and Guang Hu. "Spatiotemporal Influence of Urban Park Landscape Features on Visitor Behavior." Sustainability 15, no. 6 (2023): 5248. http://dx.doi.org/10.3390/su15065248.

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The relationship between visitor behavior and the park landscape is complex. Influences of some park features on visitor behavior are unconfirmed and change with time and space, which always confuses landscape architects and park managers. These spatiotemporal dependent effects were less studied. To understand this influence, an empirical study was conducted in 10 representative parks across the West Lake Scenic Area in Hangzhou, China. A system for Observing Play and Recreation in Communities was applied to record visitor behavior on weekdays and weekends, which provides a non-contact approac

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31

Avdulova, Tat’yana P., and Anastasiya I. Antonikova. "PERSONALITY AND TIME PERSPECTIVE FEATURES IN ADOLESCENTS WITH EATING DISORDERS." RSUH/RGGU Bulletin. Series Psychology. Pedagogics. Education, no. 4 (2023): 103–21. http://dx.doi.org/10.28995/2073-6398-2023-4-103-121.

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The work presents the results of a study in the relationship between eating behaviors and the temporal perspective of personality, as well as the personality characterological features among older adolescents. Using the Dutch Eating Questionnaire (DEBQ) the authors identifie restrictive, emotive and external eating behaviors. The characteristics of adolescents are analyzed on the basis of the modified A. Lichko PDO questionnaire. The temporal perspective of personality is considered in accordance with the model of F. Zimbardo. Significant bilateral positive links were found between the orienta

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32

Bai, Qiang, Ronghua Gao, Qifeng Li, Rong Wang, and Hongming Zhang. "Recognition of the behaviors of dairy cows by an improved YOLO." Intelligence & Robotics 4, no. 1 (2024): 1–19. http://dx.doi.org/10.20517/ir.2024.01.

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The physiological well-being of dairy cows is intimately tied to their behavior. Detecting aberrant dairy cows early and reducing financial losses on farms are both possible with real-time and reliable monitoring of their behavior. The behavior data of dairy cows in real environments have dense occlusion and multi-scale issues, which affect the detection results of the model. Therefore, we focus on both data processing and model construction to improve the results of dairy cow behavior detection. We use a mixed data augmentation method to provide the model with rich cow behavior features. Simu

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33

Abduazizova, Durdona Abduzuhurovna, and Malika Abduzuhurovna Solieva. "NATIONAL FEATURES OF GENDER CHRONEMIC COMMUNICATIVE BEHAVIOR IN DIFFERENT LINGUA-CULTURES." CURRENT RESEARCH JOURNAL OF PHILOLOGICAL SCIENCES 02, no. 09 (2021): 59–65. http://dx.doi.org/10.37547/philological-crjps-02-09-13.

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The article is devoted to the national peculiarities of gender-specific communicative behavior of the British, Uzbeks and Chinese. The author considers the correlation of gender national values of different linguistic cultures in their chronemic behavior with linear and cyclic time models. Gender features affect not only the perception of time by representatives of linguistic cultures, but also the language. It is due to such gender characteristics that the communication of people from different linguistic cultures is largely due to differences in their ideas about time. Representatives of lin

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34

Abduazizova, Durdona Abduzuhurovna, and Malika Abduzuhurovna Solieva. "NATIONAL FEATURES OF GENDER CHRONEMIC COMMUNICATIVE BEHAVIOR IN DIFFERENT LINGUA-CULTURES." CURRENT RESEARCH JOURNAL OF PHILOLOGICAL SCIENCES 02, no. 09 (2021): 59–65. http://dx.doi.org/10.37547/philological-crjps-02-09-13.

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Анотація:

The article is devoted to the national peculiarities of gender-specific communicative behavior of the British, Uzbeks and Chinese. The author considers the correlation of gender national values of different linguistic cultures in their chronemic behavior with linear and cyclic time models. Gender features affect not only the perception of time by representatives of linguistic cultures, but also the language. It is due to such gender characteristics that the communication of people from different linguistic cultures is largely due to differences in their ideas about time. Representatives of lin

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35

Zmaga, A., and I. Martyniuk. "Features of coping behavior at students." Humanitarian studios: pedagogics, psychology, philosophy 1, no. 100 (2020): 27–34. http://dx.doi.org/10.31548/hspedagog2020.01.027.

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The article deals with the theoretical and methodological basis of the study of coping strategies in the student age. It is noted that the importance of coping behavior is to solve the following important tasks in stressful situations: to find the meaning of the situation, to confront the stressor, to maintain relations with those who could be a potential helper in solving the crisis, to maintain emotional balance, to maintain the image of self,social identity and self-belief. Emphasis is placed on the following coping behavior strategies: solving a problem, managing one’s emotions, avoiding a

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36

Tkach, B. "Neuropsychological features personalities with deviant behavior." Fundamental and applied researches in practice of leading scientific schools 27, no. 3 (2018): 201–6. http://dx.doi.org/10.33531/farplss.2018.3.24.

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In article presents the casual structure of deviant behavior, created on the basis of complex and systematic neuropsychological research. Neuropsychological research is proposed to be carried out together with Eye tracking and EEG, to eliminate the subjectivity element in interpreting diagnostic results. Three components of the symptom-complex of the mental stage of deviation are formed. It is shown that the primary symptom complex is represented by minimal disruption of the functioning in anterior part of brain: the orbitofrontal cortex part prefrontal cortex; dorsolateral prefrontal cortex;

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Lapina, Iryna. "Features of young people's consumer behavior." Організаційна психологія Економічна психологія 33, no. 3-4 (2024): 137–44. http://dx.doi.org/10.31108/2.2024.3.33.12.

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Introduction. Young people's consumer behavior has a considerable social significance. Young people’s consumer ideology sets consumer standards for the future through youth's socialization. Young people are characterized by certain features related to their age, life experience, and socialization phase, and their consumer behavior has a number of peculiar manifestations, which need serious research. Aim: to analyze the features of and factors in young people's consumer behavior. Methods: theoretical analysis and systematization of psychological knowledge, online survey using a questionnaire. R

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Moldovan, Adela R., and Daniel David. "Features of automaticity in eating behavior." Eating Behaviors 13, no. 1 (2012): 46–48. http://dx.doi.org/10.1016/j.eatbeh.2011.09.006.

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Zafeiriou, Lazaros, Mihalis A. Nicolaou, Stefanos Zafeiriou, Symeon Nikitidis, and Maja Pantic. "Probabilistic Slow Features for Behavior Analysis." IEEE Transactions on Neural Networks and Learning Systems 27, no. 5 (2016): 1034–48. http://dx.doi.org/10.1109/tnnls.2015.2435653.

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Wojtan, Chris, and Greg Turk. "Fast viscoelastic behavior with thin features." ACM Transactions on Graphics 27, no. 3 (2008): 1–8. http://dx.doi.org/10.1145/1360612.1360646.

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Belyh, N. A., and A. Yu Zhuleva. "Features of eating behavior in adolescents." Profilakticheskaya meditsina 26, no. 8 (2023): 69. http://dx.doi.org/10.17116/profmed20232608169.

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Gordeliy, Elizaveta, and Pierre Bérest. "Characteristic features of salt-cavern behavior." International Journal of Rock Mechanics and Mining Sciences 173 (January 2024): 105607. http://dx.doi.org/10.1016/j.ijrmms.2023.105607.

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Kulakhmetov, Abdusattor B., and Davron K. Muminov. "FEATURES OF DEVIANT BEHAVIOR IN ADOLESCENCE." Deutsche internationale Zeitschrift für zeitgenössische Wissenschaft 88 (September 18, 2024): 59–60. https://doi.org/10.5281/zenodo.13786038.

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The article analyzes sociological approaches to the analysis of deviations and deviant behavior. The sociocultural aspect of deviations and deviant behavior of adolescents is considered. Forms defined deviations among adolescents in modern conditions.

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Peng, Shuyun, Xiaopei Zhang, Luoyu Zhou, and Peng Wang. "YOLO-CBD: Classroom Behavior Detection Method Based on Behavior Feature Extraction and Aggregation." Sensors 25, no. 10 (2025): 3073. https://doi.org/10.3390/s25103073.

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Classroom behavior can effectively reflect learning states, and thus classroom behavior detection is crucial for improving teaching methods and enhancing teaching quality. To address issues such as severe occlusions and large scale variations in student behavior detection, this paper proposes a classroom behavior detection model, named YOLO-CBD (YOLOv10s Classroom Behavior Detection). Firstly, BiFormer attention is introduced to redesign the Efficientv2 network, leading to a novel backbone network for efficient feature extraction of student classroom behaviors. The proposed attention module en

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Wang, Jiarong, Qianran Sun, and Caiqiu Zhou. "Insider Threat Detection Based on Deep Clustering of Multi-Source Behavioral Events." Applied Sciences 13, no. 24 (2023): 13021. http://dx.doi.org/10.3390/app132413021.

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With the continuous advancement of enterprise digitization, insider threats have become one of the primary cybersecurity concerns for organizations. Therefore, it is of great significance to develop an effective insider threat detection mechanism to ensure the security of enterprises. Most methods rely on artificial feature engineering and input the extracted user behavior features into a clustering-based unsupervised machine learning model for insider threat detection. However, feature extraction is independent of clustering-based unsupervised machine learning. As a result, user behavior feat

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Bhavya, Rajeev*1 &. Mohammed Malik C. K2. "PERSONALITY AND SOCIAL NETWORK MENTAL DISORDER PREDICTION VIA TWITTER ANALYSIS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY Metanoia 19 (April 4, 2019): 6–11. https://doi.org/10.5281/zenodo.2629143.

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With the rise in popularity of social networking, various types of social network mental disorders (SNMDs), such as Cyber-Relationship Addiction, Information Overload, and Net Compulsion, has shown up on the surface. Symptoms of these mental disorders are usually observed passively, resulting in delayed clinical intervention. From the studies it was observed that the core reason for some of this addictive behavior was depression. In this paper we propose a machine learning framework, enhanced with sentimental analysis that exploits features extracted from social network data, to accurately ide

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Wei, Jiaxuan, Shuang Yu, and Yu Wang. "Intelligent Driving Behavior Recognition and Legal Liability Issues Using Deep Learning Convolutional Networks." International Journal of Information Technologies and Systems Approach 18, no. 1 (2025): 1–20. https://doi.org/10.4018/ijitsa.382479.

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This work aimed to develop a driving behavior recognition and liability assistance determination method applicable to practical traffic safety management and criminal liability determination scenarios. First, an improved deep neural network was designed, which integrated multi-scale 3D convolutional structures and attention mechanisms to efficiently extract driving behavior features from both spatial and temporal dimensions. Next, a subset of six typical driving behaviors was constructed based on the Drive&Act public dataset, followed by sample labeling and feature preprocessing. Finally,

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STAHOVICH, THOMAS F., and LEVENT BURAK KARA. "A representation for comparing simulations and computing the purpose of geometric features." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 15, no. 2 (2001): 189–201. http://dx.doi.org/10.1017/s0890060401152042.

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We present a new representation that allows a rigid-body dynamic simulation to be described as a set of “causal-processes.” A causal-process is an interval of time during which both the behavior and the causes of the behavior remain qualitatively uniform. The representation consists of acyclic, directed graphs that are isomorphic to the flow of causality through the kinematic chain. Forces are the carriers of causality in this domain; thus they are central to the representation. We use this representation to compute the purposes of the geometric features on the parts of a device. To compute th

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Ding, Damin, Yueyang Zhao, Jingru Zhang, et al. "A New Method of Classroom Behavior Recognition Based on WS-FC SLOWFAST." International Journal of Gaming and Computer-Mediated Simulations 17, no. 1 (2025): 1–28. https://doi.org/10.4018/ijgcms.371423.

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With the growing integration of deep learning and educational informatization, applying artificial intelligence to classroom behavior analysis has garnered significant attention. This article specifies 14 types of classroom behaviors and their classification criteria. By clipping and frame extraction from surveillance videos, target detection, manual annotation, temporal association, and other operations, a multi-label behavior dataset was created. This article also proposes a Weakly supervised fine-grained classification SlowFast SlowFast behavior recognition algorithm, which improves the acc

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Seo, H. J., H. R. Wang, Y. S. Woo, et al. "Factors related to suicidal behavior in korean patients with bipolar disorder: The effect of mixed features on suicidality." European Psychiatry 33, S1 (2016): s270—s271. http://dx.doi.org/10.1016/j.eurpsy.2016.01.710.

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IntroductionThe aim of the present study was to investigate various risk factors of suicidal behaviors, including the mixed features specifier, in Korean patients with bipolar disorder.MethodsWe retrospectively reviewed medical charts from 2005 to 2014. A total of 334 patients diagnosed with bipolar disorder using the DSM-IV TR were enrolled. Subjects were categorized into two groups according to their history of suicidal behavior and the demographic and clinical characteristics of the groups were compared, including the mixed features specifier. We re-evaluated the index episode using DSM-5 c

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