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相关概念视频

Attribution Theory00:56

Attribution Theory

13.8K
Behavior is a product of both the situation (e.g., cultural influences, social roles, and the presence of bystanders) and of the person (e.g., personality characteristics). Subfields of psychology tend to focus on one influence or behavior over others. Situationism is the view that our behavior and actions are determined by our immediate environment and surroundings. In contrast, dispositionism holds that our behavior is determined by internal factors (Heider, 1958).
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Fundamental Attribution Error01:14

Fundamental Attribution Error

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According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
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Attribution01:26

Attribution

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In social interactions, individuals frequently seek to understand the motivations and causes behind others' behaviors. This fundamental aspect of social perception, known as attribution, plays a crucial role in shaping interpersonal relationships and guiding future actions. Attribution refers to the cognitive process through which people infer the reasons behind others' behaviors, allowing them to assess character traits, intentions, and situational influences.Attribution Theory and Its...
282
Personal Choice and Fate Attributions01:19

Personal Choice and Fate Attributions

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Some individuals interpret life events as a consequence of their personal choices and actions, while others believe that outcomes are dictated by fate or destiny. This divergence in perspective has been examined in psychological and cross-cultural studies, particularly in relation to religious faith and cultural beliefs about causality.Fate and Personal ResponsibilityPeople who emphasize personal responsibility view events as direct consequences of their decisions. For instance, breaking a leg...
171
Equation of Motion: General Plane motion01:22

Equation of Motion: General Plane motion

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In the context of a rigid body's movement within a general plane, it is important to understand that this motion is typically triggered by external forces or couple moments exerted onto it. This principle can be explained through Newton's second law, which stipulates the translational motion of the body's center of mass along each axis.
Moreover, the body's center of mass experiences a rotational effect as a result of these couple moments. This rotation can be articulated as the...
575
Theory of Attribution I: Correspondent Inference Theory01:15

Theory of Attribution I: Correspondent Inference Theory

547
Correspondent inference theory, proposed by Jones and Davis in 1965, seeks to explain how individuals infer stable personality traits from observed behaviors. It suggests that people attribute actions to underlying dispositions rather than external circumstances, particularly when the behavior appears intentional and socially significant.Voluntary Behavior and Dispositional AttributionAccording to this theory, individuals are more likely to attribute behavior to personal traits when it appears...
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Updated: Jan 31, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
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SENTINEL-DL:一种法医框架,用于使用运动传感器数据进行设备归属.

Attaullah Buriro1, Abdul Baseer Buriro2, Tahir Ahmad3

  • 1School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK. attaullah.buriro@essex.ac.uk.

Scientific reports
|January 29, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了SENTINEL-DL,这是一个新的法医框架,使用加速度计数据将运动证据与特定的智能手机和智能手表模型联系起来. 它在设备关联方面实现了高精度,增强了数字取证.

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相关实验视频

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Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
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科学领域:

  • 数字法医学数字法医学
  • 传感器数据分析数据分析
  • 机器学习 机器学习

背景情况:

  • 数字证据分析通常依赖于存储在设备上的数据.
  • 将基于运动的证据与特定设备模型联系起来是一个挑战.
  • 现有的法医方法可能缺乏强大的设备指纹识别功能.

研究的目的:

  • 引入SENTINEL-DL,这是一个新的法医框架,用于使用运动传感器数据进行设备关联.
  • 为了利用加速仪的内在运动信号进行法医分析.
  • 为了增强数字指纹和法医认证的动作证据.

主要方法:

  • 利用内置的3D加速度计来对抗改的内在运动特征进行分析.
  • 采用机器学习模型,包括随机森林 (RF),深度神经网络 (DNN) 和卷积神经网络 (CNN).
  • 将未知的传感数据与设备配置文件的参考数据库进行匹配.

主要成果:

  • 智能手机的真实阳性率 (TPR) 为93.99%,智能手表的真实阳性率为92.65%.
  • 报告了智能手机的虚假接受率 (FAR) 为0.66%,智能手表的虚假接受率为1.22%.
  • 智能手机的总准确率为98.76%,智能手表的总准确率为98.97%.

结论:

  • SENTINEL-DL为分析运动传感器证据提供了一种轻量级和可靠的解决方案.
  • 该框架提供有效的数字指纹和法医认证支持.
  • 运动传感器数据可以显著改善设备指纹和法医验证方法.