Authors: Tang, Xilang | Xiao, Mingqing | Liang, Yajun | Hu, Bin | Zhang, Lei
Article Type: Research Article
Abstract: Solenoid valves (SVs) are used as actuators in various applications, which are crucial parts in control system. Their failure may result in a system crash, so its health condition and reliability are related to the safety of an engineering system. In order to explore the basis of condition-based maintenance or replacement of SVs, it is necessary to develop a prognostic approach to predict its operation condition and remaining useful life (RUL). In this paper, a particle filter (PF) technique, an online tracking method, is proposed to make prognostics for SV. Moreover, the Brownian motion degradation model is proposed, and the …distortion of dynamic driven current curve is assumed as the indicator of degradation state. To validate the proposed PF-based prognostics method, a degradation experiment is designed. The result shows that the predicted degradation state accurately reflects the real time filtered degradation state of SV and a good RUL prediction can be calculated by this method. Show more
Keywords: Particle filter, prognostic, solenoid valve, remaining useful life, degradation experiment
DOI: 10.3233/JIFS-169608
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 523-532, 2018
Authors: Hu, Bin | Li, Tao Yun | Shen, GongTian | Wan, Benli
Article Type: Research Article
Abstract: The leakage magnetic field which induced by the inner surface groove during loading had been measured from the outer surface in geomagnetic environment. Compared the variation of the leakage magnetic field along the load with the location and development of the groove, it was found that two phenomena are relate to the magnetic field aberration. The relation can be described by the pink-pink value and the gradient of the magnetic field aberration. This result can be used to evaluate and monitor the inner defect by the magnetic field aberration characters.
Keywords: Leakage magnetic field, variation, inner surface groove, loading, geomagnetic environment
DOI: 10.3233/JAE-209474
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 64, no. 1-4, pp. 1531-1538, 2020
Authors: Shen, Gongtian | Hu, Bin | Gao, Guangxin | Li, Yuntao
Article Type: Research Article
Abstract: The dynamic variation of amplitude and gratitude of metal magnetic memory (MMM) signals for a crack on a crane crossbeam was investigated during loading from 0 to 80KN. The result shows that the amplitude and gratitude of MMMT signals slowly increase from 0 to 50KN, quickly increase from 50 to 70KN and rapidly decrease from 70 to 80KN. The crack emerged result in the peak to peak value rapidly increasing and the shape of MMM signals change to sharp. The stress released results in decreasing of the peak to peak of the amplitude and gratitude of MMM signals. MMM testing …method can be used to monitor the activity of surface crack or damage in steel structure. Show more
Keywords: Metal magnetic memory (MMM), crane, loading, crack, stress concentration
DOI: 10.3233/JAE-2010-1257
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 33, no. 3-4, pp. 1329-1334, 2010
Authors: Hu, Bin | Li, Luming | Chen, Xing | Zhong, Liqiang
Article Type: Research Article
Abstract: The environmental magnetic field, the stress distribution and the materials are the influencing factors of Magnetic Memory Method (MMM). In order to discover the influencing rule of environmental magnetic field, different even magnetic field is offered during the period of Magnetic Memory (MM) signals occurred. It was found that the environmental magnetic field can change the MM signals magnitude, can not change the curve's profile ordinarily. If the certain magnetic field offered, the curve will be reversed. So, if the environmental magnetic field was changed suitably, the best MM signals will be obtained. Three kinds of materials had been used …in experiments to investigate the difference and influencing rule. The result reveals that material is an important role which determines the value of MM signals on condition that the stress and environmental al magnetic field are the same.It was derived from the experimental data that the percent of C influences MM signals in a certain rule but not linear. Those results are different with the existing MMM and improve the MMM evaluation system. The environmental magnetic field function mechanism can be explained by the phenomena of these experiments. Show more
Keywords: Magnetic memory method (MMM), influencing factors, stress concentration, environmental magnetic field, material
DOI: 10.3233/JAE-2010-1260
Citation: International Journal of Applied Electromagnetics and Mechanics, vol. 33, no. 3-4, pp. 1351-1357, 2010
Authors: Li, Zepeng | Huang, Rikui | Zhang, Yufeng | Zhu, Jianghong | Hu, Bin
Article Type: Research Article
Abstract: Knowledge Graph Embedding (KGE), which aims to embed the entities and relations of a knowledge gxraph into a low-dimensional continuous space, has been proven to be an effective method for completing a knowledge graph and improving the quality of the knowledge graph. The translation-based models represented by TransE, TransH, TransR and TransD have achieved great success in this regard. There is still potential for improvement in dealing with complex relations. In this paper, we find that the lack of flexibility in entity embedding limits the model’s ability to model complex relations. Therefore, we propose single-directional-flexible (sdf) models and multi-directional-flexible (mdf) …models to increase the flexibility and expressiveness of entity embeddings. These two methods can be applied to the TransD model and its variant models without increasing any time cost and space cost. We conduct experiments on benchmarks such as WN18 and FB15k. The experimental results show that the models significantly surpasses the classical translation models in both tasks of triplet classification and link prediction. In particular, for Hits@1 of link prediction of WN18, we get 71.7% after applying our method to TransD, which is much better than 24.1% of TransD. Show more
Keywords: Knowledge graph embedding, translation model, complex relation, single-directional-flexible model, multi-directional-flexible model
DOI: 10.3233/JIFS-211553
Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 2, pp. 3093-3105, 2023
Authors: Yue, Qi | Deng, Zhibin | Hu, Bin | Tao, Yuan
Article Type: Research Article
Abstract: The two-sided matching (TSM) decision-making is an interdisciplinary research field encompassing management science, behavioral science, and computer science, which are widely applied in various industries and everyday life, generating significant economic and social value. However, in the decision-making process of real-world TSM, the complexity of the decision-making problem and environment lead to the preference information provided by the two-sided agents being ambiguous and uncertain. The purpose of this study is to develop a new fair and stable matching methodology to resolve the TSM problem with multiple hesitant fuzzy element (HFE) information. The decision-making process is as follows. First, the TSM …problem with four kinds of HFEs is described. To solve this problem, the HFE value of each index is normalized and then is transformed into the closeness degree by using the bidirectional projection technology. Second, based on the closeness degree, the weight of each index is calculated by using the Critic method. Then, the agent satisfaction is obtained by aggregating the closeness and the weights. Next, a fair and stable TSM model to maximizing agent satisfactions under the constraints of one-to-one stable matching is constructed. The best TSM scheme can be obtained by solving the TSM model. Finally, an example of logistics technology cooperation is provided to verify the effectiveness and feasibility of the presented model and methodology. The proposed methodology develops a novel fuzzy information presentation tool and constructs a TSM model considering the fairness and stability, which is of great significance to investigate the TSM decision-making and the resolution of real-life TSM problems under the uncertain and fuzzy environments. One future research direction is to consider multiple psychological and behavioral factors of two-sided agents in TSM problems. Show more
Keywords: Two-sided matching, fairness and stability, hesitant fuzzy element (HFE), bidirectional projection technology, critic, multiobjective programming model
DOI: 10.3233/JIFS-232520
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3045-3069, 2024
Authors: Cui, Haibo | Wei, Xiaomei | Huang, Yu | Hu, Bin | Fang, Yaping | Wang, Jia
Article Type: Research Article
Abstract: Among human influenza viruses, strain A/H3N2 accounts for over a quarter of a million deaths annually. Antigenic variants of these viruses often render current vaccinations ineffective and lead to repeated infections. In this study, a computational model was developed to predict antigenic variants of the A/H3N2 strain. First, 18 critical antigenic amino acids in the hemagglutinin (HA) protein were recognized using a scoring method combining phi (ϕ) coefficient and information entropy. Next, a prediction model was developed by integrating multiple linear regression method with eight types of physicochemical changes in critical amino acid positions. When compared to other three known …models, our prediction model achieved the best performance not only on the training dataset but also on the commonly-used testing dataset composed of 31878 antigenic relationships of the H3N2 influenza virus. Show more
Keywords: Influenza A virus, H3N2, antigenic variant, multiple linear regression, physicochemical properties
DOI: 10.3233/BME-141201
Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3729-3735, 2014
Authors: Chen, Wanjiao | Hu, Bin | Zhang, Shuya | Zheng, Ying | Zhou, Zhong | Mai, Yifeng
Article Type: Research Article
Abstract: BACKGROUND: Accumulating evidence shows that the increase in blood viscosity (BV) is an independent risk factor for atherosclerosis and its related diseases, but as far as we know, there are few studies on the relationship between blood viscosity and carotid plaque severity. Therefore, we aimed to investigate the relationship between blood viscosity and the presence of carotid plaques, and further explore its relationship with the severity of carotid plaques. METHODS: We retrospectively analyzed the data of consecutive subjects in the physical examination center of the Affiliated Hospital of Ningbo University Medical College from January 2022 to May 2022. The parameters …of blood viscosity include the whole blood viscosity (WBV) at high, middle, and low shear rate, plasma viscosity (PV), hematocrit (HCT), rigidity “k”, rigidity index (RI), aggregation index (AI) and electrophoresis rate (ER), and standardized BV calculated by Quemada’s equation were included in the study. Carotid plaque score (CPS) was used to measure the severity of carotid artery disease, and participants were divided into mild, moderate, and severe groups according to the quartile of the score. Independent samples t -test and one-way ANOVA were used to compare normally distributed continuous variables between two or more independent groups, respectively. Binary logistic regression was used to evaluate the risk factors of carotid plaque. RESULTS: 314 men were enrolled in the study, of which 165 participants were diagnosed with Carotid artery plaque (CAP) (66.9%). Compared with the CAP- group, the WBV and PV of the CAP+group decreased, but the difference only existed in the PV (p = 0.001). However, standardized BV values (HCT set at 0.45) were higher in the CAP+group than in the CAP- group (3.8643±0.35431vs 3.9542±0.64871, p = 0.188). Regarding the rigidity and aggregation of RBC, the parameters including rigidity “k”, RI, AI and ER increased in the CAP+group compared with the CAP- group. The difference was statistically significant in k and ER (p = 0.04, p = 0.009). To assess the severity of carotid plaque, we divided the participants into mild, moderate, and severe groups by using the tertile of CPS value. The mild group was defined as CPS≤0.5 (n = 108), the moderate group as 0.5 < CPS≤1.7 (n = 105), and the severe group as CPS > 1.7 (n = 101). It was found that WBV and PV decreased with the increase of plaque severity, but the difference among the three groups was significant in PV (F = 8.073, p < 0.0001). In addition, with the severity of plaque from mild to severe, standardized BV gradually increased, which were 3.8611±0.34845, 3.8757±0.36637, 3.9007±0.38353 respectively. The difference between the groups was close to statistically significant (F = 2.438, p = 0.089). The values of parameters describing erythrocyte aggregation and rigidity increased among the mild, moderate, and severe groups. The difference was statistically significant in RBC rigidity “k” and ER of RBC (F = 3.863, p = 0.022; F = 5.897, p = 0.003, respectively). CONCLUSION: Increased blood viscosity is a risk factor for carotid plaque, but its increase may be hidden by decreased hematocrit. Therefore, it is necessary to comprehensively analyze various parameters of blood viscosity, such as the standardized BV calculated by Quemada’s equation, which may provide more useful reference value. Show more
Keywords: Carotid plaque, blood viscosity, hematocrit, Quemada’s equation
DOI: 10.3233/CH-221597
Citation: Clinical Hemorheology and Microcirculation, vol. 83, no. 4, pp. 351-358, 2023
Authors: Zheng, Weihao | Yao, Zhijun | Hu, Bin | Gao, Xiang | Cai, Hanshu | Moore, Philip | and for the Alzheimer’s Disease Neuroimaging Initiative
Article Type: Research Article
Abstract: Brain network occupies an important position in representing abnormalities in Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Currently, most studies only focused on morphological features of regions of interest without exploring the interregional alterations. In order to investigate the potential discriminative power of a morphological network in AD diagnosis and to provide supportive evidence on the feasibility of an individual structural network study, we propose a novel approach of extracting the correlative features from magnetic resonance imaging, which consists of a two-step approach for constructing an individual thickness network with low computational complexity. Firstly, multi-distance combination is utilized for …accurate evaluation of between-region dissimilarity; and then the dissimilarity is transformed to connectivity via calculation of correlation function. An evaluation of the proposed approach has been conducted with 189 normal controls, 198 MCI subjects, and 163 AD patients using machine learning techniques. Results show that the observed correlative feature suggests significant promotion in classification performance compared with cortical thickness, with accuracy of 89.88% and area of 0.9588 under receiver operating characteristic curve. We further improved the performance by integrating both thickness and apolipoprotein E ɛ 4 allele information with correlative features. New achieved accuracies are 92.11% and 79.37% in separating AD from normal controls and AD converters from non-converters, respectively. Differences between using diverse distance measurements and various correlation transformation functions are also discussed to explore an optimal way for network establishment. Show more
Keywords: Alzheimer’s disease, combined distance, correlation calculation function, cortical thickness network, magnetic resonance imaging, mild cognitive impairment
DOI: 10.3233/JAD-150311
Citation: Journal of Alzheimer's Disease, vol. 48, no. 4, pp. 995-1008, 2015
Authors: Piao, Sirong | Chen, Keliang | Wang, Na | Bao, Yifang | Liu, Xueling | Hu, Bin | Lu, Yucheng | Yang, Liqin | Geng, Daoying | Li, Yuxin
Article Type: Research Article
Abstract: Background: Structural-functional connectivity (SC– FC) coupling is related to various cognitive functions and more sensitive for the detection of subtle brain alterations. Objective: To investigate whether decoupling of SC-FC was detected in mild cognitive impairment (MCI) patients on a modular level, the interaction effect of aging and disease, and its relationship with network efficiency. Methods: 73 patients with MCI and 65 healthy controls were enrolled who underwent diffusion tensor imaging and resting-state functional MRI to generate structural and functional networks. Five modules were defined based on automated anatomical labeling 90 atlas, including default mode network (DMN), frontoparietal attention network (FPN), …sensorimotor network (SMN), subcortical network (SCN), and visual network (VIS). Intra-module and inter-module SC-FC coupling were compared between two groups. The interaction effect of aging and group on modular SC-FC coupling was further analyzed by two-way ANCOVA. The correlation between the coupling and network efficiency was finally calculated. Results: In MCI patients, aberrant intra-module coupling was noted in SMN, and altered inter-module coupling was found in the other four modules. Intra-module coupling exhibited significant age-by-group effects in DMN and SMN, and inter-module coupling showed significant age-by-group effects in DMN and FPN. In MCI patients, both positive or negative correlations between coupling and network efficiency were found in DMN, FPN, SCN, and VIS. Conclusion: SC-FC coupling could reflect the association of SC and FC, especially in modular levels. In MCI, SC-FC coupling could be affected by the interaction effect of aging and disease, which may shed light on advancing the pathophysiological mechanisms of MCI. Show more
Keywords: Connectome, functional connectivity, mild cognitive impairment, structural connectivity, structural-functional coupling
DOI: 10.3233/JAD-220837
Citation: Journal of Alzheimer's Disease, vol. 92, no. 4, pp. 1439-1450, 2023