Finding a moral compass . . . without a compass

Weiss, Kenneth M.

doi:10.1002/evan.21462

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…The biologist would maintain that domesticated mammals feel in the same way as humans (Weiss, 2016). Take the example of the dog awaiting with impatience the return of his master.…”

Section: Eroticism and Ethicsmentioning

confidence: 99%

Eroticism: Why It Still Matters

Fellmann¹

2016

PSYCH

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This article is about Eroticism as a key-concept in the psychological understanding of the human mind. The meaning of the term can be defined as follows: Eroticism is the way humans experience sexuality as a self-sufficient mental activity. Sexuality underlies different social rules in varying cultural contexts and may lead to different ways of thinking, but there is no evidence that cultural diversity actually leads to fundamentally different ways of feeling. The constant disposition for recreational rather than procreational sex makes eroticism a medium of human creativity. In this sense, eroticism is considered a central factor in the process of hominisation. The crucial cognitive competence which makes for the uniqueness of our species is due to the transformation of sexuality into eroticism and its disposition for social learning. In the animal kingdom, sex contributes to the welfare of the horde, while in human society eroticism contributes to individual self-recognition and paves the way to moral awareness. Methodologically, I plead for a cooperation of psychological and anthropological research, each utilizing and combining the complementary aspects of both approaches.

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“…The biologist would maintain that domesticated mammals feel in the same way as humans (Weiss, 2016). Take the example of the dog awaiting with impatience the return of his master.…”

Section: Eroticism and Ethicsmentioning

confidence: 99%

Eroticism: Why It Still Matters

Fellmann¹

2016

PSYCH

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“…In particular, few people seek medical treatment in the early stage of COPD and undergo CT scans simultaneously. Transfer learning [9] may solve the above problems. Since radiomics was proposed to mine more information from medical images using advanced feature analysis in 2007 [10], it has been widely used to analyze lung disease imaging [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Multi-Layer Perceptron Classifier with the Proposed Combined Feature Vector of 3D CNN Features and Lung Radiomics Features for COPD Stage Classification

Yang,

Zeng,

Chen

et al. 2023

Journal of Healthcare Engineering

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Computed tomography (CT) has been regarded as the most effective modality for characterizing and quantifying chronic obstructive pulmonary disease (COPD). Therefore, chest CT images should provide more information for COPD diagnosis, such as COPD stage classification. This paper proposes a features combination strategy by concatenating three-dimension (3D) CNN features and lung radiomics features for COPD stage classification based on the multi-layer perceptron (MLP) classifier. First, 465 sets of chest HRCT images are automatically segmented by a trained ResU-Net, obtaining the lung images with the Hounsfield unit. Second, the 3D CNN features are extracted from the lung region images based on a truncated transfer learning strategy. Then, the lung radiomics features are extracted from the lung region images by PyRadiomics. Third, the MLP classifier with the best classification performance is determined by the 3D CNN features and the lung radiomics features. Finally, the proposed combined feature vector is used to improve the MLP classifier’s performance. The results show that compared with CNN models and other ML classifiers, the MLP classifier with the best classification performance is determined. The MLP classifier with the proposed combined feature vector has achieved accuracy, mean precision, mean recall, mean F1-score, and AUC of 0.879, 0.879, 0.879, 0.875, and 0.971, respectively. Compared to the MLP classifier with the 3D CNN features selected by Lasso, our method based on the MLP classifier has improved the classification performance by 5.8% (accuracy), 5.3% (mean precision), 5.8% (mean recall), 5.4% (mean F1-score), and 2.5% (AUC). Compared to the MLP classifier with lung radiomics features selected by Lasso, our method based on the MLP classifier has improved the classification performance by 5.0% (accuracy), 5.1% (mean precision), 5.0% (mean recall), 5.1% (mean F1-score), and 2.1% (AUC). Therefore, it is concluded that our method is effective in improving the classification performance for COPD stage classification.

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Traffic Condition Classification Model Based on Traffic‐Net

Cao

Chen

Zhong

et al. 2023

Computational Intelligence and Neuroscience

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The classification and detection of traffic status plays a vital role in the urban smart transportation system. The classification and mastery of the traffic status at different time periods and sections will help the traffic management department to optimize road management and implement rescue in real time. Travelers can follow the traffic conditions. We choose the best route to effectively improve travel efficiency and safety. However, due to factors such as weather, time of day, lighting, and sample labeling costs, the existing classification methods are insufficient in real time and detection accuracy to meet application requirements. In order to solve this problem, this article aims to effectively transfer and apply the pretrained model learned on large-scale image data sets to small-sample road traffic data sets. By sharing common visual features, model weight parameter migration, and fine-tuning, the road is finally optimized. Traffic conditions classification is based on Traffic-Net. Experiments show that the method in this article can not only obtain a prediction accuracy of more than 96% but also can effectively reduce the model training time and meet the needs of practical applications.

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Finding a moral compass . . . without a compass

Cited by 3 publications

References 14 publications

Eroticism: Why It Still Matters

Eroticism: Why It Still Matters

Multi-Layer Perceptron Classifier with the Proposed Combined Feature Vector of 3D CNN Features and Lung Radiomics Features for COPD Stage Classification

Traffic Condition Classification Model Based on Traffic‐Net

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