Methods of forensic facial reconstruction and human identification: historical background, significance, and limitations

Guleria, Ankita; Krishan, Kewal; Sharma, Vishal; Kanchan, Tanuj

doi:10.1007/s00114-023-01838-9

Cited by 4 publications

(2 citation statements)

References 54 publications

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“…As a result of the differences present among individuals due to variations in their professions and lifestyles, different individuals may form unique microbial fingerprints. Such fingerprints may then provide a theoretical basis for tracking the origin of these microorganisms in forensic microbiology, and thus can be analyzed to achieve individual identifications (Guleria et al, 2023). The human microbiome, which encompasses the fungi, bacteria and viruses living in and on individuals and their surrounding environment, contributes significantly to the genetic content and, in this way, is unique to each individual.…”

Section: Review 21 Current Status Of Forensic Microbiomes For Use In ...mentioning

confidence: 99%

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification

Yang,

Wang,

Zhai

et al. 2024

Front. Microbiol.

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Forensic microbiome research is a field with a wide range of applications and a number of protocols have been developed for its use in this area of research. As individuals host radically different microbiota, the human microbiome is expected to become a new biomarker for forensic identification. To achieve an effective use of this procedure an understanding of factors which can alter the human microbiome and determinations of stable and changing elements will be critical in selecting appropriate targets for investigation. The 16S rRNA gene, which is notable for its conservation and specificity, represents a potentially ideal marker for forensic microbiome identification. Gene sequencing involving 16S rRNA is currently the method of choice for use in investigating microbiomes. While the sequencing involved with microbiome determinations can generate large multi-dimensional datasets that can be difficult to analyze and interpret, machine learning methods can be useful in surmounting this analytical challenge. In this review, we describe the research methods and related sequencing technologies currently available for application of 16S rRNA gene sequencing and machine learning in the field of forensic identification. In addition, we assess the potential value of 16S rRNA and machine learning in forensic microbiome science.

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Section: Review 21 Current Status Of Forensic Microbiomes For Use In ...mentioning

confidence: 99%

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification

Yang,

Wang,

Zhai

et al. 2024

Front. Microbiol.

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show abstract

“…Ahn and Chen [6] highlight how countries have recognized the importance of artificial intelligence in building digital governments, particularly in terms of optimizing government operations and capitalizing on new product values in Chinese economy. Guleria et al [7] delve into the practicality and versatility of ChatGPT for court investigations and address the ethical and legal concerns surrounding its usage. Furthermore, Xu et al [8] provide an in-depth exploration of chatbot applications in the medical field, including cancer diagnosis, screening, treatment, patient monitoring, support, and management.…”

Section: Introductionmentioning

confidence: 99%

Exploring Public Response to ChatGPT With Sentiment Analysis and Knowledge Mapping

Zhou,

Liang,

Fang

et al. 2024

IEEE Access

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Information about artificial intelligence generated content (AIGC) has attracted great attention from the public. ChatGPT has gained attention from many countries due to its powerful functionality and efficiency. However, there are still many countries, such as China, that refuse to introduce ChatGPT into their own countries. This article aims to study the attention that ChatGPT has attracted in China, further investigate the reasons for the obstruction of ChatGPT's dissemination, and provide prospects and suggestions for the global development of artificial intelligence. First, we apply the Latent Dirichlet Allocation (LDA) topic modeling algorithm to analyze the 28,122 web tweets and comments from China regarding ChatGPT. The results show that there are more negative emotions compared to positive and neutral emotions. The attention on ChatGPT rapidly increased twice between March and May 2023. We find the audience interest and concern words ： "improvement", "company" and "technology". The analysis reveals three main themes: social, technological, and educational. Additionally, we conduct knowledge mapping to analyze the publication time, research hotspots, and subject distribution of Chinese scholars' literature. In conclusion, this paper highlights several key issues that need to be addressed for the further advancement of AIGC, including the evolution of job roles, the changing technological landscape, the pursuit of artificial general intelligence, and ethical concerns.

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FAST-Net: A Coarse-to-fine Pyramid Network for Face-Skull Transformation

Zhao,

Ma,

Cui

et al. 2023

Lecture Notes in Computer Science

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Methods of forensic facial reconstruction and human identification: historical background, significance, and limitations

Cited by 4 publications

References 54 publications

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification

Exploring Public Response to ChatGPT With Sentiment Analysis and Knowledge Mapping

FAST-Net: A Coarse-to-fine Pyramid Network for Face-Skull Transformation

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