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相关概念视频

Applications of Stress01:04

Applications of Stress

400
Consider a structure made of a boom and a rod designed to support a load. These two components are connected by a pin and stabilized by brackets and pins. The boom and the rod are detached from their supports to assess the different stresses imposed on this structure, and a free-body diagram is drawn. Then, all the forces applied, including the load acting on the structure, are identified. The reaction forces exerted on both the boom and the rod are computed using the equilibrium equations.
The...
400
Stress Prevention and Stress Management Techniques V01:28

Stress Prevention and Stress Management Techniques V

63
A social support system is a structured network of personal relationships that provides assistance to individuals facing various challenges, offering a buffer against psychological and physical stressors. This network may consist of family members, friends, neighbors, colleagues, or other community members who provide resources and companionship. Social support can take many forms, including advice, emotional comfort, practical help, and companionship. Research indicates that these networks can...
63
Physiological Foundation of Stress01:24

Physiological Foundation of Stress

157
Stress triggers a coordinated physiological response involving the sympathetic nervous system (SNS) and the hypothalamic-pituitary-adrenal (HPA) axis. This dual activation ensures that the body is prepared for both immediate and prolonged stress management. The process begins with the perception of a stressor. This initial phase activates the SNS, leading to the rapid release of adrenaline (epinephrine) from the adrenal glands.
Role of the Sympathetic Nervous System
Adrenaline triggers the...
157
Stress Prevention and Stress Management Techniques IV01:26

Stress Prevention and Stress Management Techniques IV

62
Stress often leads to unhealthy habits like smoking, excessive drinking, and overeating, which offer short-term relief but ultimately increase long-term health risks. These behaviors create a cycle that temporarily lowers stress levels but can result in severe long-term health consequences. Breaking these habits is essential to reduce the risk of chronic diseases and improve overall well-being. Three primary changes that support better health include quitting smoking, reducing alcohol intake,...
62
Stress Prevention and Stress Management Techniques I01:26

Stress Prevention and Stress Management Techniques I

92
Stress prevention and management are crucial for maintaining well-being and building resilience. Techniques to manage stress include cultivating qualities like conscientiousness, a sense of personal control, and self-efficacy. Each of these traits significantly reduces stress and promotes healthier lifestyle choices and outcomes.
Conscientiousness
Conscientious individuals tend to be organized, responsible, and disciplined. They prioritize completing tasks and following structured routines,...
92
Stress Prevention and Stress Management Techniques II01:23

Stress Prevention and Stress Management Techniques II

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Personality types, particularly Type A and Type B, significantly influence how individuals respond to stress. These personality distinctions are marked by varying levels of ambition, competitiveness, and coping styles, all of which shape an individual's resilience to stressors.
Type A Personality: Driven and Easily Stressed
Individuals with Type A personalities are often highly competitive and ambitious and operate with a strong sense of urgency. Commonly labeled as...
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相关实验视频

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使用深度学习模型的新和高效的个性化压力检测技术

Ulligaddala Srinivasarao1, Gopisetty Rathnamma2, M Satish Kumar3

  • 1Department of CSE, GITAM (Deemed to be) University, Rudraram Village, Hyderabad, India. ulligaddalasrinu@gmail.com.

Scientific reports
|August 21, 2025
PubMed
概括

这项研究引入了一种有效的方法来检测社交媒体文字中的压力. 这种新的方法将高级文本表示与深度学习模型集成在一起,在压力检测中实现高精度.

关键词:
在深度莫吉快速文本福克斯优化剩余网络发芽的时间压力检测标记化

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科学领域:

  • 计算语言学
  • 人工智能
  • 心理学

背景情况:

  • 压力严重影响成人和老年人的健康,导致慢性疾病.
  • 由于复杂性和计算需求, 从社交媒体文本中检测压力存在挑战.
  • 现有的机器学习和深度学习模型面临长时间的培训时间和功能限制等局限性.

研究的目的:

  • 开发一种高效准确的社交媒体文本压力检测技术.
  • 在培训时间和功能利用方面克服现有方法的局限性.
  • 使用新型模型整合和优化来提高应力检测的准确性.

主要方法:

  • 集成先进的文本表示技术:FastText,字体表示的全球向量 (Glove),DeepMoji和XLNet.
  • 使用深度可分离卷积与残余网络 (DSC-ResNet) 进行精确的应力检测.
  • 使用混沌的Fennec Fox优化算法 (CFFO) 进行超参数调整.

主要成果:

  • 这种技术的准确性高达98.42%.
  • 精度,回忆力,特异性和F1分数分别为97. 58%,98. 12%,98. 28%和98. 38%.
  • 与现有技术相比,该模型表现出更高的性能.

结论:

  • 文本表示和DSC-ResNet的新型集成为压力检测提供了有效的解决方案.
  • 提出的方法有效地解决了先前方法的局限性,提供了高精度和性能.
  • 这项技术有望通过社交媒体分析在心理健康监测中应用.