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Book ; Online ; Conference proceedings: Cyber Security

Yun, Xiaochun / Wen, Weiping / Lang, Bo / Yan, Hanbing / Ding, Li / Li, Jia / Zhou, Yu

15th International Annual Conference, CNCERT 2018, Beijing, China, August 14–16, 2018, Revised Selected Papers

(Communications in Computer and Information Science ; 970)

2019

Author's details	edited by Xiaochun Yun, Weiping Wen, Bo Lang, Hanbing Yan, Li Ding, Jia Li, Yu Zhou
Series title	Communications in Computer and Information Science ; 970
Keywords	Computer security
Subject code	005.8
Language	English
Size	1 Online-Ressource (X, 177 p. 80 illus., 38 illus. in color)
Publisher	Springer Singapore ; Imprint: Springer
Publishing place	Singapore
Document type	Book ; Online ; Conference proceedings
HBZ-ID	HT019992888
ISBN	978-981-13-6621-5 ; 9789811366208 ; 9789811366222 ; 981-13-6621-7 ; 9811366209 ; 9811366225
DOI	10.1007/978-981-13-6621-5
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Book ; Online ; Conference proceedings: Cyber Security

Lu, Wei / Wen, Qiaoyan / Zhang, Yuqing / Lang, Bo / Wen, Weiping / Yan, Hanbing / Li, Chao / Ding, Li / Li, Ruiguang / Zhou, Yu

17th China Annual Conference, CNCERT 2020, Beijing, China, August 12, 2020, Revised Selected Papers

(Communications in Computer and Information Science ; 1299)

2020

Author's details	edited by Wei Lu, Qiaoyan Wen, Yuqing Zhang, Bo Lang, Weiping Wen, Hanbing Yan, Chao Li, Li Ding, Ruiguang Li, Yu Zhou
Series title	Communications in Computer and Information Science ; 1299
Keywords	Computer security ; Computer communication systems ; Application software ; Architecture, Computer ; Data encryption (Computer science) ; Computer networks/Security measures
Subject code	005.8
Language	English
Size	1 Online-Ressource (X, 235 p. 108 illus., 70 illus. in color)
Edition	1st ed. 2020
Publisher	Springer Singapore ; Imprint: Springer
Publishing place	Singapore
Document type	Book ; Online ; Conference proceedings
HBZ-ID	HT020801395
ISBN	978-981-33-4922-3 ; 9789813349216 ; 9789813349230 ; 981-33-4922-0 ; 9813349212 ; 9813349239
DOI	10.1007/978-981-33-4922-3
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Book ; Online ; Conference proceedings: Cyber Security : 15th International Annual Conference, CNCERT 2018, Beijing, China, August 14-16, 2018, Revised Selected Papers

Yun, Xiaochun / Wen, Weiping / Lang, Bo / Yan, Hanbing / Ding, Li / Li, Jia / Zhou, Yu

2019

Keywords	Computer security ; Computer science
Size	1 electronic resource (177 pages)
Publisher	Springer Nature
Publishing place	Singapore
Document type	Book ; Online ; Conference proceedings
Note	English ; Open Access
HBZ-ID	HT021028895
ISBN	978-981-13-6621-5 ; 981-13-6621-7
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Book ; Online ; Conference proceedings: Cyber Security : 17th China Annual Conference, CNCERT 2020, Beijing, China, August 12, 2020, Revised Selected Papers

Lu, Wei / Wen, Qiaoyan / Zhang, Yuqing / Lang, Bo / Wen, Weiping / Yan, Hanbing / Li, Chao / Ding, Li / Li, Ruiguang / Zhou, Yu

2020

Keywords	Computer security ; Network hardware ; Information retrieval ; Systems analysis & design ; Coding theory & cryptology ; Network security ; Systems and Data Security ; Computer Communication Networks ; Information Systems Applications (incl. Internet) ; Computer System Implementation ; Cryptology ; Mobile and Network Security ; Data and Information Security ; Computer and Information Systems Applications ; communication channels (information theory) ; communication systems ; computer crime ; computer hardware ; computer networks ; computer security ; computer systems ; cryptography ; data communication systems ; data security ; databases ; network protocols ; network security ; sensors ; signal processing ; telecommunication networks ; telecommunication systems ; telecommunication traffic ; wireless telecommunication systems ; Internet searching ; Data encryption
Size	1 electronic resource (235 pages)
Publisher	Springer Nature
Document type	Book ; Online ; Conference proceedings
Note	English ; Open Access
HBZ-ID	HT021027688
ISBN	978-981-33-4922-3 ; 981-33-4922-0
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Multi-Objective Evolutionary Architecture Search for Parameterized Quantum Circuits.

Ding, Li / Spector, Lee

Entropy (Basel, Switzerland)

2023 Volume 25, Issue 1

Abstract: Recent work on hybrid quantum-classical machine learning systems has demonstrated success in utilizing parameterized quantum circuits (PQCs) to solve the challenging reinforcement learning (RL) tasks, with provable learning advantages over classical ... ...

Abstract	Recent work on hybrid quantum-classical machine learning systems has demonstrated success in utilizing parameterized quantum circuits (PQCs) to solve the challenging reinforcement learning (RL) tasks, with provable learning advantages over classical systems, e.g., deep neural networks. While existing work demonstrates and exploits the strength of PQC-based models, the design choices of PQC architectures and the interactions between different quantum circuits on learning tasks are generally underexplored. In this work, we introduce a Multi-objective Evolutionary Architecture Search framework for parameterized quantum circuits (MEAS-PQC), which uses a multi-objective genetic algorithm with quantum-specific configurations to perform efficient searching of optimal PQC architectures. Experimental results show that our method can find architectures that have superior learning performance on three benchmark RL tasks, and are also optimized for additional objectives including reductions in quantum noise and model size. Further analysis of patterns and probability distributions of quantum operations helps identify performance-critical design choices of hybrid quantum-classical learning systems.
Language	English
Publishing date	2023-01-03
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2014734-X
ISSN	1099-4300 ; 1099-4300
ISSN (online)	1099-4300
ISSN	1099-4300
DOI	10.3390/e25010093
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Fine-scale geographic difference of the endangered Big-headed Turtle (Platysternon megacephalum) fecal microbiota, and comparison with the syntopic Beale's Eyed Turtle (Sacalia bealei).

Fong, Jonathan J / Sung, Yik-Hei / Ding, Li

BMC microbiology

2024 Volume 24, Issue 1, Page(s) 71

Abstract: Background: Studies have elucidated the importance of gut microbiota for an organism, but we are still learning about the important influencing factors. Several factors have been identified in helping shape the microbiome of a host, and in this study we ...

Abstract	Background: Studies have elucidated the importance of gut microbiota for an organism, but we are still learning about the important influencing factors. Several factors have been identified in helping shape the microbiome of a host, and in this study we focus on two factors-geography and host. We characterize the fecal microbiota of the Big-headed Turtle (Platysternon megacephalum) and compare across a relatively fine geographic scale (three populations within an 8-km radius) and between two syntopic hosts (P. megacephalum and Sacalia bealei). Both species are endangered, which limits the number of samples we include in the study. Despite this limitation, these data serve as baseline data for healthy, wild fecal microbiotas of two endangered turtle species to aid in conservation management. Results: For geography, the beta diversity of fecal microbiota differed between the most distant sites. The genus Citrobacter significantly differs between sites, which may indicate a difference in food availability, environmental microbiota, or both. Also, we identify the common core microbiome for Platysternon across Hong Kong as the shared taxa across the three sites. Additionally, beta diversity differs between host species. Since the two species are from the same site and encounter the same environmental microbiota, we infer that there is a host effect on the fecal microbiota, such as diet or the recruitment of host-adapted bacteria. Lastly, functional analyses found metabolism pathways (KEGG level 1) to be the most common, and pathways (KEGG level 3) to be statistically significant between sites, but statistically indistinguishable between species at the same site. Conclusions: We find that fecal microbiota can significantly differ at a fine geographic scale and between syntopic hosts. Also, the function of fecal microbiota seems to be strongly affected by geographic site, rather than species. This study characterizes the identity and function of the fecal microbiota of two endangered turtle species, from what is likely their last remaining wild populations. These data of healthy, wild fecal microbiota will serve as a baseline for comparison and contribute to the conservation of these two endangered species.
MeSH term(s)	Animals ; Turtles ; Endangered Species ; Bacteria/genetics ; Gastrointestinal Microbiome ; Microbiota
Language	English
Publishing date	2024-02-29
Publishing country	England
Document type	Journal Article
ZDB-ID	2041505-9
ISSN	1471-2180 ; 1471-2180
ISSN (online)	1471-2180
ISSN	1471-2180
DOI	10.1186/s12866-024-03227-2
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Enhanced grip force estimation in robotic surgery: A sparrow search algorithm-optimized backpropagation neural network approach.

Yan, Yongli / Sun, Tiansheng / Ren, Teng / Ding, Li

Mathematical biosciences and engineering : MBE

2024 Volume 21, Issue 3, Page(s) 3519–3539

Abstract: The absence of an effective gripping force feedback mechanism in minimally invasive surgical robot systems impedes physicians' ability to accurately perceive the force between surgical instruments and human tissues during surgery, thereby increasing ... ...

Abstract	The absence of an effective gripping force feedback mechanism in minimally invasive surgical robot systems impedes physicians' ability to accurately perceive the force between surgical instruments and human tissues during surgery, thereby increasing surgical risks. To address the challenge of integrating force sensors on minimally invasive surgical tools in existing systems, a clamping force prediction method based on mechanical clamp blade motion parameters is proposed. The interrelation between clamping force, displacement, compression speed, and the contact area of the clamp blade indenter was analyzed through compression experiments conducted on isolated pig kidney tissue. Subsequently, a prediction model was developed using a backpropagation (BP) neural network optimized by the Sparrow Search Algorithm (SSA). This model enables real-time prediction of clamping force, facilitating more accurate estimation of forces between instruments and tissues during surgery. The results indicate that the SSA-optimized model outperforms traditional BP networks and genetic algorithm-optimized (GA) BP models in terms of both accuracy and convergence speed. This study not only provides technical support for enhancing surgical safety and efficiency, but also offers a novel research direction for the design of force feedback systems in minimally invasive surgical robots in the future.
MeSH term(s)	Humans ; Animals ; Swine ; Robotic Surgical Procedures ; Equipment Design ; Pressure ; Neural Networks, Computer ; Hand Strength
Language	English
Publishing date	2024-03-29
Publishing country	United States
Document type	Journal Article
ZDB-ID	2265126-3
ISSN	1551-0018 ; 1551-0018
ISSN (online)	1551-0018
ISSN	1551-0018
DOI	10.3934/mbe.2024155
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Clinical Efficacy of Arthroscopic Transplantation of Palmaris Longus Tendon Combined with Early Accelerated Motion Rehabilitation After Scapholunate Ligament Reconstruction for Geissler Type IV Scapholunate Instability.

Ying, Qiuwen / Ding, Li / Gu, Fengming / Mi, Jingyi

Alternative therapies in health and medicine

2024

Abstract: Objective: The aim of this study is to investigate the clinical efficacy of early accelerated motion rehabilitation in treating wrist joint instability with Geissler IV scapholunate instability (SLI) using arthroscopic palmaris longus tendon ... ...

Abstract	Objective: The aim of this study is to investigate the clinical efficacy of early accelerated motion rehabilitation in treating wrist joint instability with Geissler IV scapholunate instability (SLI) using arthroscopic palmaris longus tendon transplantation in conjunction with scapholunate ligament reconstruction. Methods: From June 2019 to January 2022, seven patients with Geissler Type IV SLI underwent arthroscopic ligament reconstruction and repair surgery of the wrist joint, followed by early accelerated motion rehabilitation. Postoperative follow-up indicators included visual analogue scale (VAS) for pain assessment, DASH-CHINESE upper limb function score, Mayo wrist joint score, wrist joint range of motion, and grip strength. Surgical efficacy was evaluated based on these indicators. Results: All patients were followed up postoperatively, with a follow-up duration ranging from 6 to 20 months (mean: 15.3 months). No postoperative complications occurred, and significant improvements were observed in all measured parameters. Postoperative MRI results at one year indicated restoration of the anatomical structure of the scapholunate joint with good healing. Both VAS and DASH-CHINESE scores significantly decreased, and the differences between pre- and postoperative scores were statistically significant (P < .001). The preoperative Mayo wrist joint score was (47.857±21.380) points, with 2 cases rated as fair and 5 cases as poor. At the latest follow-up, the score was (84.286±6.726) points, with 2 cases rated as excellent, 2 cases as good, and 3 cases as fair. Wrist joint flexion-extension range, rotation range, and grip strength all significantly improved compared to the preoperative values, with statistically significant differences (P < .001). Conclusion: The combined approach of arthroscopic transplantation of the palmaris longus tendon and early accelerated motion rehabilitation shows satisfactory clinical outcomes in treating Geissler Type IV scapholunate instability of the wrist joint. This combined approach is of great significance in improving the patient's quality of life and wrist function and helps reduce pain symptoms. Furthermore, in future research, it is recommended to increase the sample size and prolong the observation period to further validate the efficacy.
Language	English
Publishing date	2024-01-31
Publishing country	United States
Document type	Journal Article
ZDB-ID	1225073-9
ISSN	1078-6791
ISSN	1078-6791
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 4504: Show issues

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Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

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Article ; Online: Machine learning-based models for prediction of the risk of stroke in coronary artery disease patients receiving coronary revascularization.

Lin, Lulu / Ding, Li / Fu, Zhongguo / Zhang, Lijiao

PloS one

2024 Volume 19, Issue 2, Page(s) e0296402

Abstract: Background: To construct several prediction models for the risk of stroke in coronary artery disease (CAD) patients receiving coronary revascularization based on machine learning methods.: Methods: In total, 5757 CAD patients receiving coronary ... ...

Abstract	Background: To construct several prediction models for the risk of stroke in coronary artery disease (CAD) patients receiving coronary revascularization based on machine learning methods. Methods: In total, 5757 CAD patients receiving coronary revascularization admitted to ICU in Medical Information Mart for Intensive Care IV (MIMIC-IV) were included in this cohort study. All the data were randomly split into the training set (n = 4029) and testing set (n = 1728) at 7:3. Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO) regression model were applied for feature screening. Variables with Pearson correlation coefficient<9 were included, and the regression coefficients were set to 0. Features more closely related to the outcome were selected from the 10-fold cross-validation, and features with non-0 Coefficent were retained and included in the final model. The predictive values of the models were evaluated by sensitivity, specificity, area under the curve (AUC), accuracy, and 95% confidence interval (CI). Results: The Catboost model presented the best predictive performance with the AUC of 0.831 (95%CI: 0.811-0.851) in the training set, and 0.760 (95%CI: 0.722-0.798) in the testing set. The AUC of the logistic regression model was 0.789 (95%CI: 0.764-0.814) in the training set and 0.731 (95%CI: 0.686-0.776) in the testing set. The results of Delong test revealed that the predictive value of the Catboost model was significantly higher than the logistic regression model (P<0.05). Charlson Comorbidity Index (CCI) was the most important variable associated with the risk of stroke in CAD patients receiving coronary revascularization. Conclusion: The Catboost model was the optimal model for predicting the risk of stroke in CAD patients receiving coronary revascularization, which might provide a tool to quickly identify CAD patients who were at high risk of postoperative stroke.
MeSH term(s)	Humans ; Coronary Artery Disease/complications ; Coronary Artery Disease/surgery ; Cohort Studies ; Stroke/epidemiology ; Stroke/etiology ; Area Under Curve ; Machine Learning
Language	English
Publishing date	2024-02-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0296402
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Automatically detecting OSAHS patients based on transfer learning and model fusion.

Ding, Li / Peng, Jianxin / Song, Lijuan / Zhang, Xiaowen

Physiological measurement

2024

Abstract: Snoring is the most typical symptom of obstructive sleep apnea hypopnea syndrome (OSAHS) that can be used to develop a non-invasive approach for automatically detecting OSAHS patients. In this work, a model based on transfer learning and model fusion was ...

Abstract	Snoring is the most typical symptom of obstructive sleep apnea hypopnea syndrome (OSAHS) that can be used to develop a non-invasive approach for automatically detecting OSAHS patients. In this work, a model based on transfer learning and model fusion was applied to classify simple snorers and OSAHS patients. Three kinds of basic models were constructed based on pretrained Visual Geometry Group-16 (VGG16), Pretrained Audio Neural Networks (PANN), and Mel-frequency Cepstral Coefficient (MFCC). The XGBoost was used to select features based on feature importance, the max voting strategy was applied to fuse these basic models and leave-one-subject-out cross validation was used to evaluate the proposed model. The results show that the fused model embedded with top-5 VGG16 features and top-5 PANN features can correctly identify OSAHS patients (AHI>5) with 100% accuracy. The proposed fused model provides a good classification performance with lower computational cost and higher robustness that makes detecting OSAHS patients at home possible.
Language	English
Publishing date	2024-05-09
Publishing country	England
Document type	Journal Article
ZDB-ID	1149545-5
ISSN	1361-6579 ; 0967-3334
ISSN (online)	1361-6579
ISSN	0967-3334
DOI	10.1088/1361-6579/ad4953
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 1559: Show issues

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ab Jg. 2022: Lesesaal (EG)

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