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A single-police forensic system based on rights protection law enforcement task
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Science & Technology Review | 2020, 38(21) : 192 - 196
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Science & Technology Review | 2020, 38(21): 192-196
Exclusive: System Engineering
A single-police forensic system based on rights protection law enforcement task
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GU Yu, HE He, SHI Yuhao
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    System Engineering Research Institute, China State Shipbuilding Corporation Limited, Beijing 100094, China
Published: 2020-11-13 doi: 10.3981/j.issn.1000-7857.2020.21.024
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At present, police have only a single means of evidence collection in the process of law enforcement and can neither analyze and deal with evidence effectively in real time nor provide effective support for investigation and arrest of law enforcement tasks. To solve these problems, we propose a single police law enforcement system based on rights protection law enforcement tasks. We adopt network architecture, integrate advanced forensic equipment and transmission equipment and apply deep learning algorithm to the evidence processing system to construct a systematic single police law enforcement system based on single police evidence collection and multiple police cooperative evidence collection. We use system engineering method to design the system and the operation process. In the design process, we put forward key technologies such as information integration, command assistant decision making and feature extraction.
law enforcement and evidence collection  /  single police law enforcement system  /  systems engineering
GU Yu, HE He, SHI Yuhao. A single-police forensic system based on rights protection law enforcement task[J]. Science & Technology Review, 2020 , 38 (21) : 192 -196 . DOI: 10.3981/j.issn.1000-7857.2020.21.024
Year 2020 volume 38 Issue 21
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doi: 10.3981/j.issn.1000-7857.2020.21.024
  • Receive Date:2020-04-16
  • Online Date:2020-11-17
  • Published:2020-11-13
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  • Received:2020-04-16
  • Revised:2020-07-16
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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