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ECGID: a human identification method based on adaptive particle swarm optimization and the bidirectional LSTM model Research Article

Yefei Zhang, Zhidong Zhao, Yanjun Deng, Xiaohong Zhang, Yu Zhang,zhangyf@hdu.edu.cn,zhaozd@hdu.edu.cn,yanjund@hdu.edu.cn,xhzhang@hdu.edu.cn,zy2009@hdu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 12,   Pages 1551-1684 doi: 10.1631/FITEE.2000511

Abstract: Physiological signal based biometric analysis has recently attracted attention as a means of meeting increasing privacy and security requirements. The real-time nature of an electrocardiogram (ECG) and the hidden nature of the information make it highly resistant to attacks. This paper focuses on three major bottlenecks of existing deep learning driven approaches: the lengthy time requirements for optimizing the hyperparameters, the slow and computationally intense identification process, and the unstable and complicated nature of ECG acquisition. We present a novel deep neural network framework for learning feature representations directly from ECG time series. The proposed framework integrates deep bidirectional long short-term memory (BLSTM) and . The overall approach not only avoids the inefficient and experience-dependent search for hyperparameters, but also fully exploits the spatial information of ordinal local features and the memory characteristics of a recognition algorithm. The effectiveness of the proposed approach is thoroughly evaluated in two ECG datasets, using two protocols, simulating the influence of electrode placement and acquisition sessions in identification. Comparing four recurrent neural network structures and four classical machine learning and deep learning algorithms, we prove the superiority of the proposed algorithm in minimizing overfitting and self-learning of time series. The experimental results demonstrated an average identification rate of 97.71%, 99.41%, and 98.89% in training, validation, and test sets, respectively. Thus, this study proves that the application of APSO and LSTM techniques to biometric can achieve a lower algorithm engineering effort and higher capacity for generalization.

Keywords： 心电图生物特征；个体身份识别；长短期记忆网络；自适应粒子群优化算法    

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Study on the molecular characteristic in phlegm-dampness constitution

Wang Qi,Dong Jing,Wu Hongdong,Wang Dongpo,Yao Shilin,Ren Xiaojuan

Strategic Study of CAE 2008, Volume 10, Issue 7,   Pages 100-103

Abstract:

To investigate the molecular mechanism for phlegm-dampness constitution,examining the genome DNA of peripheral blood cells of six phlegm-dampness constitution and six normal constitution by using Affymetrix GeneChip Mapping 500K Array.We had identified 442 genes with significant differences between the phlegm-dampness constitution and the normal constitution by using Affymetrix Gene Chip Human Genome U133 plus-2, base on research results of prophase, sieve the related gene and characteristics of single nucleotide polymorphisms( SNP) of phlegm-dampnessconstitution.5 related genes and 6 SNPs with significant differences were identified between the phlegm-dampness constitution and the normal constitution. Further biologianalysis on the genes identified between two constitution groups demonstrate that they are involved in enzyme activity,sterol transporter activity,participate in the biology process of lipid metabolism, cholesterol metabolic process,brown fat cell differentiation, gluconeogenesis and thermoregulation.These results indicate that the Molecular characteristic of phlegm-dampness constitution is related to metabolism disorder.

Keywords： phlegm-dampness constitution     Genechip Mapping Array     Molecular characteristic    

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A novel method based on convolutional neural networks for deriving standard 12-lead ECG from serial 3-lead ECG Regular Papers

Lu-di WANG, Wei ZHOU, Ying XING, Na LIU, Mahmood MOVAHEDIPOUR, Xiao-guang ZHOU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 3,   Pages 405-413 doi: 10.1631/FITEE.1700413

Abstract:

Reconstruction of a 12-lead electrocardiogram (ECG) from a serial 3-lead ECG has been researched in the past to satisfy the need for more wearing comfort and ambulatory situations. The accuracy and real-time performance of traditional methods need to be improved. In this study, we present a novel method based on convolutional neural networks (CNNs) for the synthesis of missing precordial leads. The results show that the proposed method receives better similarity and consumes less time using the PTB database. Particularly, the presented method shows outstanding performance in reconstructing the pathological ECG signal, which is crucial for cardiac diagnosis. Our CNN-based method is shown to be more accurate and time-saving for deployment in non-hospital situations to synthesize a standard 12-lead ECG from a reduced lead-set ECG recording. This is promising for real cardiac care.

Keywords： Convolutional neural networks (CNNs)     Electrocardiogram (ECG) synthesis     E-health    

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Frequency-domain Analysis of ECG Signals

Tu Chengyuan,Zeng Yanjun,Li Shuxin

Strategic Study of CAE 2002, Volume 4, Issue 12,   Pages 66-70

Abstract:

A new simple approach to effectively detect QRS — T complexes in ECG curve is described, so as to easily get the P-wave (when AF does not happen) or the f-wave (when AF happens). By means of signal processing techniques such as the power spectrum function, the auto-correlation function and cross-correlation function, two kinds of ECG signals when AF does or does not happen were successively analyzed, showing the evident differences between them.

Keywords： ECG curve     P-wave     f-wave     AF (atrial fibrillation)     histogram     power spectrum     autocorrelation     cross-correlation    

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Characterization of the Gastric Mucosal Microbiota in Patients with Liver Cirrhosis and Its Associations with Gastrointestinal Symptoms Article

Yanfei Chen, Jing Guo, Chunlei Chen, Ding Shi, Daiqiong Fang, Feng Ji, Lanjuan Li

Engineering 2021, Volume 7, Issue 4,   Pages 507-514 doi: 10.1016/j.eng.2020.04.014

Abstract:

Several studies have indicated that the oral and gut microbiota may exhibit differences in patients with cirrhosis. Less is known about the microbiota in the stomach, which is located between the oral cavity and the intestinal tract. In this study, the gastric mucosal microbiota of patients with liver cirrhosis and controls were analyzed with 16S ribosomal RNA (rRNA) pyrosequencing. Cirrhotic patients had significantly
lower Helicobacter pylori (H. pylori) infection rates, as confirmed by both the histological method and the pyrosequencing method. In H. pylori-negative subjects, gastric bacterial communities of healthy and cirrhosis cohorts were clustered into four clusters based on bacterial compositions: Cluster_1 and Cluster_2 (mostly cirrhosis), Cluster_3 (mostly healthy), and Cluster_4 (around half of each). Compositional and functional differences were observed among these different clusters. At the genus level, Cluster_1 and Cluster_2 showed enrichment of Neisseria and Streptococcus, respectively. Functionally, Cluster_2 was characterized as depleted of genetic information processing, as well as of modules related to glycan biosynthesis and metabolism. Patients in Cluster_2 had more severe gastrointestinal symptoms and a higher rate of previous endoscopic variceal ligation (EVL) therapy than patients in other clusters. Our findings suggest that the colonization of both H. pylori and non-H. pylori is influenced in liver cirrhosis. Although the H. pylori-negative gastric mucosal microbiota showed considerable heterogeneity, associations between specific gastric microbiota and clinical characteristics could be observed. Previous EVL therapy might lead to a distinct structure of the gastric mucosal microbiota, thus aggravating the gastrointestinal symptoms in H. pylori-negative cirrhotic patients.

Keywords： Microbiome     Liver cirrhosis     Symptoms     Varices     Gastric endoscopy    

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The expression mode of hsa-miR-197 in uterine leiomyomas tissue and related bioinformatics analysis

Xu Qing,Fu Ziyi,Wu Xiaoli,Huangfu Yushuang and Ling Jing

Strategic Study of CAE 2014, Volume 16, Issue 5,   Pages 99-104

Abstract:

We performed Real-time PCR to detect the hsa-miR-197 expression levels in uterine leiomyomas tissues and paired normal myometrium separately；online databases including miRbase，UCSC，NCBI are employed to analysis the sequence conservation and genetic characteristics of hsa- miR- 197；miRNA databases such as miRanda，MirTarget2 and TargetScan are chosen to predict hsa- miR- 197 target genes；meanwhile，the intersection genes of these miRNA databases are chosen，and GO and Pathway analysis of these genes are carried out to explore the potential role of hsa-miR-197 playing in regulating the uterine leiomyomas occurrence and development. hsa-miR-197 functions in broad ground and participates in uterine leiomyomas multiple biology progress，which indicates that hsa- miR- 197 could regulate uterine leiomyomas occurrence and development.

Keywords： uterine leiomyomas     hsa-miR-197     bioinformatics analysis     target genes    

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Domain knowledge enhanced deep learning for electrocardiogram arrhythmia classification Research Article

Jie SUN,sunjie@nbut.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 1,   Pages 59-72 doi: 10.1631/FITEE.2100519

Abstract: Deep learning provides an effective way for automatic classification of s, but in , pure data-driven methods working as black-boxes may lead to unsatisfactory results. A promising solution is combining with deep learning. This paper develops a flexible and extensible framework for integrating with a deep neural network. The model consists of a deep neural network to capture the statistical pattern between input data and the ground-truth label, and a knowledge module to guarantee consistency with the . These two components are trained interactively to bring the best of both worlds. The experiments show that the is valuable in refining the neural network prediction and thus improves accuracy.

Keywords： Domain knowledge     Cardiac arrhythmia     Electrocardiogram (ECG)     Clinical decision-making    

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The status and outlook of wind power converters

Min Enze,Xie Wenhua

Strategic Study of CAE 2011, Volume 13, Issue 2,   Pages 13-15

Abstract:

The world recent activities in the fields of micro-algae biodiesel, cellulosic ethanol and biogasoline were reviewed; the challenges and measures taken were discussed. It was proposed that the first industrial demonstration unit for these micro-algae biodiesel, cellulosic ethanol and biogasoline should be built in China before 2015, based on raw material supply, R & D progress and international cooperation to lay the foundation for future development.

Keywords： bio-based automobile fuel     micro-algae biodiesel     cellulosic ethanol     biogasoline    

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Information schema constructs for instantiationand composition of system manifestation features Article

Shahab POURTALEBI, Imre HORVÁTH

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 9,   Pages 1396-1415 doi: 10.1631/FITEE.1601235

Abstract: Complementing our previous publications, this paper presentsthe information schema constructs (ISCs) that underpin the programmingof specific system manifestation feature (SMF) orientated informationmanagement and composing system models. First, we briefly present(1) the general process of pre-embodiment design with SMFs, (2) theprocedures of creating genotypes and phenotypes of SMFs, (3) the specificprocedure of instantiation of phenotypes of SMFs, and (4) the procedureof system model management and processing. Then, the chunks of informationneeded for instantiation of phenotypes of SMFs are discussed, andthe ISCs designed for instantiation presented. Afterwards, the informationmanagement aspects of system modeling are addressed. Methodologically,system modeling involves (1) placement of phenotypes of SMF in themodeling space, (2) combining them towards the desired architectureand operation, (3) assigning values to the parameters and checkingthe satisfaction of constraints, and (4) storing the system modelin the SMFs-based warehouse database. The final objective of the reportedresearch is to develop an SMFs-based toolbox to support modeling ofcyber-physical systems (CPSs).

Keywords： System manifestation features (SMFs)     Information schema constructs     Database schemata     SMF genotypes     SMF phenotypes     SMF instances     Software tool box     System-level design     Cyber-physical systems    

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Algorithm Design for Improving Feature Extraction Efficiency Based on KPCA

Xu Yong,Yangjingyu,Lu Jianfeng

Strategic Study of CAE 2005, Volume 7, Issue 10,   Pages 38-42

Abstract:

KPCA (kernel PCA) is derived from PCA. It can extract nonlinear feature components of samples. However, feature extraction for one sample requires that kernel functions between training samples and the sample be calculated in advance. So, the size of training sample set affects the efficiency of feature extraction. It is supposed that in feature space the eigenvectors may be linearly expressed by a part of training samples, called nodes. According to the supposition, an improved KPCA (IKPCA) algorithm is developed. IKPCA extracts feature components of one sample efficiently, only based on kernel functions between nodes and the sample. Experimental results show that IKPCA is very close to KPCA in performance, while with higher efficiency.

Keywords： KPCA(Kernel PCA)     IKPCA(Improved KPCA)     feature extraction     feature space    

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Reservoir development characteristics and predication technologies of large Puguang-Yuanba Gas Field

Guo Xusheng,Guo Tonglou,Huang Renchun,Chen Zuqing

Strategic Study of CAE 2010, Volume 12, Issue 10,   Pages 82-90

Abstract:

Based on reef and shoal facies reservoir development characteristics and main controlling factors in Puguang-Yuanba area, the "three step processes method of the facies controlled the reservoir"  comprehensive prediction technology of ultra-deep carbonate rock was established, which was under the guidance of sedimentary facies analysis, on the basis of forward modeling and the seismic facies analysis, and by the phase-controlled multi-parameter reservoir inversion as core.

Keywords： Puguang Gas Field     Yuanba Gas Field     platform edge     organic reefs     shoals     attribute analysis     the three step processes method of the facies controlled the reservoir    

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Information schema constructs for defining warehouse databases of genotypes and phenotypes of system manifestation features Article

Shahab POURTALEBI,Imre HORVÁTH

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 9,   Pages 862-884 doi: 10.1631/FITEE.1600997

Abstract: Our long-term objective is to develop a software toolbox for pre-embodiment design of complex and heterogeneous systems, such as cyber-physical systems. The novelty of this toolbox is that it uses system manifestation features (SMFs) for transdisciplinary modeling of these systems. The main challenges of implementation of the toolbox are functional design- and language-independent computational realization of the warehouses, and systematic development and management of the various evolving implements of SMFs (genotypes, phenotypes, and instances). Therefore, an information schema construct (ISC) based approach is proposed to create the schemata of the associated warehouse databases and the above-mentioned SMF implements. ISCs logically arrange the data contents of SMFs in a set of relational tables of varying semantics. In this article we present the ISCs necessary for creation of genotypes and phenotypes. They increase the efficiency of the database development process and make the data relationships transparent. Our follow-up research focuses on the elaboration of the SMF instances based system modeling methodology.

Keywords： Cyber-physical systems     Software toolbox     Pre-embodiment design     System manifestation features (SMFs)     Warehouses     Database schemata     SMF genotypes     SMF phenotypes     SMF instances     Information schema constructs    

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Development Strategy of Microbial Safety Industry

Song Zhongjian, Li Man, Hu Liangbin, Wang Chunming, Lu Xi, Liu Kaihui, Zhang Lijia, Yu Yan, Wu Qingping

Strategic Study of CAE 2021, Volume 23, Issue 5,   Pages 79-85 doi: 10.15302/J-SSCAE-2021.05.010

Abstract:

Microbial safety is crucial for China’s social and economic development in the new era, and it is an important support for national food security, public health, and social stability. In this article, we analyze the development needs and current status of the microbial safety industry considering the policy environment in China. Subsequently, we clarify the domestic and global development patterns of the industry and summarize the challenges faced by the innovation and application of pathogenic microorganism detection and control technologies in China. Furthermore, we propose a development plan for building China’s microbial safety industry. To explore a high-quality development path, China should build innovation platforms and a large scientific database regarding microbial safety, enhance personnel development for this industry, encourage leading enterprises to develop according to standards and regulations, and strengthen major system innovation and engineering technology research in the microbial safety field.

Keywords： microbial safety     microbial detection     microbial diagnosis     microbial prevention and control     nucleic acid detection    

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Afeature selection approach based on a similarity measure for software defect prediction Article

Qiao YU, Shu-juan JIANG, Rong-cun WANG, Hong-yang WANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1744-1753 doi: 10.1631/FITEE.1601322

Abstract: Software defect prediction is aimed to find potential defects based on historical data and software features. Software features can reflect the characteristics of software modules. However, some of these features may be more relevant to the class (defective or non-defective), but others may be redundant or irrelevant. To fully measure the correlation between different features and the class, we present a feature selection approach based on a similarity measure (SM) for software defect prediction. First, the feature weights are updated according to the similarity of samples in different classes. Second, a feature ranking list is generated by sorting the feature weights in descending order, and all feature subsets are selected from the feature ranking list in sequence. Finally, all feature subsets are evaluated on a k-nearest neighbor (KNN) model and measured by an area under curve (AUC) metric for classification performance. The experiments are conducted on 11 National Aeronautics and Space Administration (NASA) datasets, and the results show that our approach performs better than or is comparable to the compared feature selection approaches in terms of classification performance.

Keywords： Software defect prediction     Feature selection     Similarity measure     Feature weights     Feature ranking list    

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Microbial Medicine Industry: Current Status and Future Trends

Yu Qing, Huang Tingting, Deng Zixin

Strategic Study of CAE 2021, Volume 23, Issue 5,   Pages 69-78 doi: 10.15302/J-SSCAE-2021.05.009

Abstract:

The microbial sourced natural products possess diverse structures and excellent activities, implying great potentials for clinical application. This study systematically analyzes the current status of the microbial medicine industry in China and summarizes the development trends of the industry from the aspects of microbial strain resource utilization, excellent strain screening, fermentation process optimization, strain engineering, and new microbial medicine development. This aims to facilitate major breakthroughs and industrial upgrades for China’s microbial medicine industry. Although China’s microbial medicine industry has solid resource and technical foundations, it still lags behind the international advanced level. Considering the opportunities and challenges, we propose several suggestions for promoting China’s microbial medicine industry: constructing large-scale scientific facilities for microbial medicine, strengthening basic research and independent technology development, establishing a talent cultivation system, and formulating systematic industrial incentives.

Keywords： microbial medicine     development trend     biological activity     microbial metabolism     synthetic biology    

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Title Author Date Type Operation

ECGID: a human identification method based on adaptive particle swarm optimization and the bidirectional LSTM model

Yefei Zhang, Zhidong Zhao, Yanjun Deng, Xiaohong Zhang, Yu Zhang,zhangyf@hdu.edu.cn,zhaozd@hdu.edu.cn,yanjund@hdu.edu.cn,xhzhang@hdu.edu.cn,zy2009@hdu.edu.cn

Journal Article

Study on the molecular characteristic in phlegm-dampness constitution

Wang Qi,Dong Jing,Wu Hongdong,Wang Dongpo,Yao Shilin,Ren Xiaojuan

Journal Article

A novel method based on convolutional neural networks for deriving standard 12-lead ECG from serial 3-lead ECG

Lu-di WANG, Wei ZHOU, Ying XING, Na LIU, Mahmood MOVAHEDIPOUR, Xiao-guang ZHOU

Journal Article

Frequency-domain Analysis of ECG Signals

Tu Chengyuan,Zeng Yanjun,Li Shuxin

Journal Article

Characterization of the Gastric Mucosal Microbiota in Patients with Liver Cirrhosis and Its Associations with Gastrointestinal Symptoms

Yanfei Chen, Jing Guo, Chunlei Chen, Ding Shi, Daiqiong Fang, Feng Ji, Lanjuan Li

Journal Article

The expression mode of hsa-miR-197 in uterine leiomyomas tissue and related bioinformatics analysis

Xu Qing,Fu Ziyi,Wu Xiaoli,Huangfu Yushuang and Ling Jing

Journal Article

Domain knowledge enhanced deep learning for electrocardiogram arrhythmia classification

Jie SUN,sunjie@nbut.edu.cn

Journal Article

The status and outlook of wind power converters

Min Enze,Xie Wenhua

Journal Article

Information schema constructs for instantiationand composition of system manifestation features

Shahab POURTALEBI, Imre HORVÁTH

Journal Article

Algorithm Design for Improving Feature Extraction Efficiency Based on KPCA

Xu Yong,Yangjingyu,Lu Jianfeng

Journal Article

Reservoir development characteristics and predication technologies of large Puguang-Yuanba Gas Field

Guo Xusheng,Guo Tonglou,Huang Renchun,Chen Zuqing

Journal Article

Information schema constructs for defining warehouse databases of genotypes and phenotypes of system manifestation features

Shahab POURTALEBI,Imre HORVÁTH

Journal Article

Development Strategy of Microbial Safety Industry

Song Zhongjian, Li Man, Hu Liangbin, Wang Chunming, Lu Xi, Liu Kaihui, Zhang Lijia, Yu Yan, Wu Qingping

Journal Article

Afeature selection approach based on a similarity measure for software defect prediction

Qiao YU, Shu-juan JIANG, Rong-cun WANG, Hong-yang WANG

Journal Article

Microbial Medicine Industry: Current Status and Future Trends

Yu Qing, Huang Tingting, Deng Zixin

Journal Article