PMID- 35440942
OWN - NLM
STAT- MEDLINE
DCOM- 20220421
LR  - 20230804
IS  - 1687-5273 (Electronic)
IS  - 1687-5265 (Print)
VI  - 2022
DP  - 2022
TI  - The Use of Internet of Things and Cloud Computing Technology in the Performance 
      Appraisal Management of Innovation Capability of University Scientific Research 
      Team.
PG  - 9423718
LID - 10.1155/2022/9423718 [doi]
LID - 9423718
AB  - This study aims to speed up the progress of scientific research projects in 
      colleges and universities, continuously improve the innovation ability of 
      scientific research teams in colleges and universities, and optimize the current 
      management methods of performance appraisal of college innovation ability. 
      Firstly, the needs of the innovation performance evaluation system are analyzed, 
      and the corresponding innovation performance evaluation index system of 
      scientific research team is constructed. Secondly, the Internet of Things (IoT) 
      combines the Field Programmable Gate Array (FPGA) to build an innovation 
      capability performance appraisal management terminal. Thirdly, the lightweight 
      deep network has been built into the innovation ability performance assessment 
      management network of university scientific research teams, which relates to the 
      innovation performance assessment index system of scientific research teams. 
      Finally, the system performance is tested. The results show that the proposed 
      method has different degrees of compression for MobileNet, which can 
      significantly reduce the network computation and retain the original recognition 
      ability. Models whose Floating-Point Operations (FLOPs) are reduced by 70% to 90% 
      have 3.6 to 14.3 times fewer parameters. Under different pruning rates, the 
      proposed model has higher model compression rate and recognition accuracy than 
      other models. The results also show that the output of the results is closely 
      related to the interests of the research team. The academic influence score of 
      Team 1 is 0.17, which is the highest among the six groups in this experimental 
      study, indicating that Team 1 has the most significant academic influence. These 
      results provide certain data support and method reference for evaluating the 
      innovation ability of scientific research teams in colleges and universities and 
      contribute to the comprehensive development of efficient scientific research 
      teams.
CI  - Copyright (c) 2022 Siyu Meng and Xue Zhang.
FAU - Meng, Siyu
AU  - Meng S
AD  - College of Business Administration, Liaoning Technical University, Huludao, 
      Liaoning 125105, China.
FAU - Zhang, Xue
AU  - Zhang X
AUID- ORCID: 0000-0003-1094-5860
AD  - College of Business Administration, Liaoning Technical University, Huludao, 
      Liaoning 125105, China.
LA  - eng
PT  - Journal Article
PT  - Retracted Publication
DEP - 20220410
PL  - United States
TA  - Comput Intell Neurosci
JT  - Computational intelligence and neuroscience
JID - 101279357
SB  - IM
RIN - Comput Intell Neurosci. 2023 Jul 26;2023:9806856. PMID: 37538595
MH  - *Cloud Computing
MH  - Humans
MH  - *Internet of Things
MH  - Technology
MH  - Universities
PMC - PMC9013565
COIS- The authors declare that they have no conflicts of interest.
EDAT- 2022/04/21 06:00
MHDA- 2022/04/22 06:00
PMCR- 2022/04/10
CRDT- 2022/04/20 05:55
PHST- 2022/01/29 00:00 [received]
PHST- 2022/02/21 00:00 [revised]
PHST- 2022/03/09 00:00 [accepted]
PHST- 2022/04/20 05:55 [entrez]
PHST- 2022/04/21 06:00 [pubmed]
PHST- 2022/04/22 06:00 [medline]
PHST- 2022/04/10 00:00 [pmc-release]
AID - 10.1155/2022/9423718 [doi]
PST - epublish
SO  - Comput Intell Neurosci. 2022 Apr 10;2022:9423718. doi: 10.1155/2022/9423718. 
      eCollection 2022.