基于改进Node2vec算法的锅炉温度场分割方法研究

针对温度场特征参数差异引发的锅炉温度场分割准确性的问题,以维持温度场特征为目标,引入图结构表达场数据,通过改进Node2vec算法进行聚类分析,进而实现锅炉温度场的最佳分割。该方法基于多维度的特征信息对锅炉温度场实现分割,能够更准确地保留流场特征。在标准数据集上进行了实验验证,结果表明在具有多维度特征的数据集上,所提方法相比其他对比算法在分割效果方面有提升显著。最后将提出的方法用于分割电站锅炉温度场,结果表明该方法可以很好地捕捉温度场数据中的局部和全局特征,且结果具有较好的精确性。

Combining lymph node ratio to develop prognostic models for postoperative gastric neuroendocrine neoplasm patients

BACKGROUND Lymph node ratio(LNR)was demonstrated to play a crucial role in the prognosis of many tumors.However,research concerning the prognostic value of LNR in postoperative gastric neuroendocrine neoplasm(NEN)patients was limited.AIM To explore the prognostic value of LNR in postoperative gastric NEN patients and to combine LNR to develop prognostic models.METHODS A total of 286 patients from the Surveillance,Epidemiology,and End Results database were divided into the training set and validation set at a ratio of 8:2.92 patients from the First Affiliated Hospital of Soochow University in China were designated as a test set.Cox regression analysis was used to explore the relationship between LNR and disease-specific survival(DSS)of gastric NEN patients.Random survival forest(RSF)algorithm and Cox proportional hazards(CoxPH)analysis were applied to develop models to predict DSS respectively,and compared with the 8th edition American Joint Committee on Cancer(AJCC)tumornode-metastasis(TNM)staging.RESULTS Multivariate analyses indicated that LNR was an independent prognostic factor for postoperative gastric NEN patients and a higher LNR was accompanied by a higher risk of death.The RSF model exhibited the best performance in predicting DSS,with the C-index in the test set being 0.769[95%confidence interval(CI):0.691-0.846]outperforming the CoxPH model(0.744,95%CI:0.665-0.822)and the 8th edition AJCC TNM staging(0.723,95%CI:0.613-0.833).The calibration curves and decision curve analysis(DCA)demonstrated the RSF model had good calibration and clinical benefits.Furthermore,the RSF model could perform risk stratification and individual prognosis prediction effectively.CONCLUSION A higher LNR indicated a lower DSS in postoperative gastric NEN patients.The RSF model outperformed the CoxPH model and the 8th edition AJCC TNM staging in the test set,showing potential in clinical practice.

"Five steps four quadrants" modularized en bloc dissection technique for accessing hepatic hilum lymph nodes in laparoscopic pancreaticoduodenectomy

BACKGROUND Although en bloc dissection of hepatic hilum lymph nodes has many advantages in radical tumor treatment,the feasibility and safety of this approach for laparo-scopic pancreaticoduodenectomy(LPD)require further clinical evaluation and investigation.AIM To explore the application value of the"five steps four quadrants"modularized en bloc dissection technique for accessing hepatic hilum lymph nodes in LPD patients.METHODS A total of 52 patients who underwent LPD via the"five steps four quadrants"modularized en bloc dissection technique for hepatic hilum lymph nodes from April 2021 to July 2023 in our department were analyzed retrospectively.The patients'body mass index(BMI),preoperative laboratory indices,intraoperative variables and postoperative complications were recorded.The relationships between preoperative data and intraoperative lymph node dissection time and blood loss were also analyzed.RESULTS Among the 52 patients,36 were males and 16 were females,and the average age was 62.2±11.0 years.There were 26 patients with pancreatic head cancer,16 patients with periampullary cancer,and 10 patients with distal bile duct cancer.The BMI was 22.3±3.3 kg/m²,and the median total bilirubin(TBIL)concentration was 57.7(16.0-155.7)µmol/L.All patients successfully underwent the"five steps four quadrants"modularized en bloc dissection technique without lymph node clearance-related complications such as postoperative bleeding or lymphatic leakage.Correlation analysis revealed significant associations between preoperative BMI(r=0.3581,P=0.0091),TBIL level(r=0.2988,P=0.0341),prothrombin time(r=0.3018,P=0.0297)and lymph node dissection time.Moreover,dissection time was significantly correlated with intraoperative blood loss(r=0.7744,P<0.0001).Further stratified analysis demonstrated that patients with a preoperative BMI≥21.9 kg/m²and a TIBL concentration≥57.7μmol/L had significantly longer lymph node dissection times(both P<0.05).CONCLUSION The"five steps four quadrants"modularized en bloc dissection technique for accessing the hepatic hilum lymph node is safe and feasible for LPD.This technique is expected to improve the efficiency of hepatic hilum lymph node dissection and shorten the learning curve;thus,it is worthy of further clinical promotion and application.

基于Node.js的农业物联网应用平台设计

文章的研究目的在于提出基于Node.js的物联网应用平台设计方案,解决物联网实际运行过程中数据上传存在的问题,提出并设计一种基于Node.js的农业物联网应用平台,可以实现对农业生产环境参数的监测与控制。首先介绍农业物联网的背景与需求,明确研究目标,其次详细描述本平台的设计思路与架构,主要应用层平台软件的设计与实现。平台的实际应用显示,本平台能够在实现物联网常见功能的同时,支持更大的数据并发处理需求,对于农业物联网的应用特点有着更好的支持作用。

Analysis of the optimal target node to reduce seizure-like discharge in networks

Network approaches have been widely accepted to guide surgical strategy and predict outcome for epilepsy treatment.This study starts with a single oscillator to explore brain activity,using a phenomenological model capable of describing healthy and epileptic states.The ictal number of seizures decreases or remains unchanged with increasing the speed of oscillator excitability and in each seizure,there is an increasing tendency for ictal duration with respect to the speed.The underlying reason is that the strong excitability speed is conducive to reduce transition behaviors between two attractor basins.Moreover,the selection of the optimal removal node is estimated by an indicator proposed in this study.Results show that when the indicator is less than the threshold,removing the driving node is more possible to reduce seizures significantly,while the indicator exceeds the threshold,the epileptic node could be the removal one.Furthermore,the driving node is such a potential target that stimulating it is obviously effective in suppressing seizure-like activity compared to other nodes,and the propensity of seizures can be reduced 60%with the increased stimulus strength.Our results could provide new therapeutic ideas for epilepsy surgery and neuromodulation.

基于Node-RED的基建现场微气象监测与告警系统设计与实现

为了更好地满足输变电工程基建现场应用中对现场环境数据监测与告警的需求,本文设计实现了一种基于Node-RED的基建现场微气象监测与告警系统。该系统通过搭建基于Node-RED的监测预警服务,能够快速完成设备接入,实时监测PM2.5等各项微气象指标,并且能够通过自动执行预设的处置策略就地进行告警或将数据推送至相关平台。该系统可以有效提升基建现场环境监测与告警的效率,在推进电力基建领域的数字化、智能化转型方面具有显著意义。

Fifty-five cases of hepatic alveolar echinococcosis combined with lymph node metastasis:A retrospective study

BACKGROUND Lymph node metastasis is a specific type of metastasis in hepatic alveolar echinococcosis(AE).Currently,there is a scarcity of describing the clinical characteristics and lymph node metastasis rules of patients with hepatic AE combined with lymph node metastasis and its mechanism and management are still controversial.Radical hepatectomy combined with regional lymph node dissection is a better treatment.AIM To analyse the clinical features of hepatic AE combined with lymph node metastasis to explore its treatment and efficacy.METHODS A total of 623 patients with hepatic AE admitted to the First Affiliated Hospital of Xinjiang Medical University from 1 January 2012 to 1 January 2022 were retrospectively analysed.Fifty-five patients with combined lymph node metastasis were analysed for their clinical data,diagnosis and treatment methods,follow-up efficacy,and characteristics of lymph node metastasis.Finally,we comparatively analysed the lymph node metastasis rates at different sites.Categorical variables are expressed as frequencies and percentages,and the analysis of difference was performed using theχ2 test.The Bonferroni method was used for pairwise comparisons when statistical differences existed between multiple categorical variables.RESULTS A lymph node metastasis rate of 8.8%(55/623)was reported in patients with hepatic AE,with a female predilection(69.1%)and a statistically significant sex difference(χ2=8.018,P=0.005).Of the 55 patients with lymph node metastasis,72.7%had a parasite lesion,neighbouring organ invasion,and metastasis stage of P3N1M0 and above,of which 67.3%,78.2%,and 34.5%of hepatic AE lesions invaded the bile ducts,blood vessels,and distant metastases,respectively.Detection rates of lymph node metastasis of 16.4%,21.7%,and 34.2%were reported for a preoperative abdominal ultrasound,magnetic resonance imaging,and computed tomography examinations.All patients were intraoperatively suspected with enlarged lymph nodes and underwent radical hepatectomy combined with regional lymph node dissection.After surgery,a routine pathological examination was conducted on the resected lymph nodes.A total of 106 positive lymph nodes were detected in six groups at various sites,including 51 single-group metastasis cases and four multi-group metastasis cases.When the metastasis rates at different sites were statistically analysed,we observed that the metastasis rate in the para-hepatoduodenal ligament lymph nodes was significantly higher than that of the other sites(χ^(2)=128.089,P=0.000<0.05).No statistical difference was observed in the metastasis rate between the five other groups.Clavien-Dindo grade IIIa complication occurred in 14 cases,which improved after administering symptomatic treatment.Additionally,lymph node dissection-related complications were not observed.Recurrence after 2 years was observed in one patient.CONCLUSION Lymph node metastasis is a rare form of metastasis in hepatic AE,which is more frequent in women.Parahepatoduodenal ligament lymph nodes are commonly observed.Radical hepatectomy combined with regional lymph node dissection is a safe,effective,and feasible treatment for liver AE combined with lymph node metastasis.

Robotic-assisted retroperitoneal lymph node dissection for stage II testicular cancer

Objective:To evaluate the perioperative as well as early oncological outcomes of patients undergoing robotic retroperitoneal lymph node dissection for treatment of testicular cancer.Methods:We conducted a prospective consecutive case series of patients undergoing robotic assisted retroperitoneal lymph node dissection for metastatic testicular cancer between May 2018 and July 2021 at our institution.Data were collected on patient and tumour characteristics,intraoperative and postoperative parameters,and functional and oncological outcomes.Descriptive statistics are presented.Results:Nineteen patients were identified;18(94.7%)completed the procedure robotically and one was converted to open surgery;78.9%of patients had stage≥IIB and 12(63.2%)patients had undergone prior chemotherapy.The median operative time was 300(interquartile range[IQR]240-315)min.Median blood loss was 100(IQR 50-175)mL.Median length of stay was 2(range 1-11)days.All robotically completed patients commenced diet and passed flatus on Day 1 and were discharged by Day 3.The median lymph node yield was 40.5(IQR 38-51)nodes.All patients undergoing nerve-sparing procedures recovered antegrade ejaculatory function.One patient had a Clavien-Dindo III complication(chylous ascites requiring drainage).At a median follow-up of 22.3(IQR 16.3-24.9)months,one patient developed retroperitoneal recurrence,which was successfully treated with second-line chemotherapy;no other patients have had recurrences.Conclusion:Robotic retroperitoneal lymph node dissection is a safe and feasible alternative to open surgery in appropriately selected patients,offering low morbidity.Early oncological outcomes are promising.Larger cohorts and longer follow-ups are required to validate our institution's findings.

Histological Risk Factors for Lymph Node Metastasis in pT1 Colorectal Cancer:Does Submucosal Invasion Depth Really Matter?

Objective After endoscopic resection of colorectal cancer with submucosal invasion(pT1 CRC),additional surgical treatment is recommended if deep submucosal invasion(DSI)is present.This study aimed to further elucidate the risk factors for lymph node metastasis(LNM)in patients with pT1 CRC,especially the effect of DSI on LNM.Methods Patients with pT1 CRC who underwent lymph node dissection were selected.The Chi-square test and multivariate logistic regression were used to analyze the relationship between clinicopathological characteristics and LNM.The submucosal invasion depth(SID)was measured via 4 methods and analyzed with 3 cut-off values.Results Twenty-eight of the 239 patients presented with LNM(11.7%),and the independent risk factors for LNM included high histological grade(P=0.003),lymphovascular invasion(LVI)(P=0.004),intermediate to high budding(Bd 2/3)(P=0.008),and cancer gland rupture(CGR)(P=0.008).Moreover,the SID,width of submucosal invasion(WSI),and area of submucosal invasion(ASI)were not significantly different.When one,two,three or more risk factors were identified,the LNM rates were 1.1%(1/95),12.5%(7/56),and 48.8%(20/41),respectively.Conclusion Indicators such as the SID,WSI,and ASI are not risk factors for LNM and are subjective in their measurement,which renders them relatively inconvenient to apply in clinical practice.In contrast,histological grade,LVI,tumor budding and CGR are relatively straightforward to identify and have been demonstrated to be statistically significant.It would be prudent to focus on these histological factors rather than subjective measurements.

Different lymph node staging systems for predicting the prognosis of colorectal neuroendocrine neoplasms

BACKGROUND Colorectal neuroendocrine neoplasms(NENs)are a rare malignancy that primarily arises from the diffuse distribution of neuroendocrine cells in the colon and rectum.Previous studies have pointed out that the status of lymph node may be used to predict the prognosis.AIM To investigate the predictive values of lymph node ratio(LNR),positive lymph node(PLN),and log odds of PLNs(LODDS)staging systems on the prognosis of colorectal NENs treated surgically,and compare their predictive values.METHODS This cohort study included 895 patients with colorectal NENs treated surgically from the Surveillance,Epidemiology,and End Results database.The endpoint was mortality of patients with colorectal NENs treated surgically.X-tile software was utilized to identify most suitable thresholds for categorizing the LNR,PLN,and LODDS.Participants were selected in a random manner to form training and testing sets.The prognosis of surgically treating colorectal NENs was examined using multivariate cox analysis to assess the associations of LNR,PLN,and LODDS with the prognosis of colorectal NENs.C-index was used for assessing the predictive effectiveness.We conducted a subgroup analysis to explore the different lymph node staging systems’predictive values.RESULTS After adjusting all confounding factors,PLN,LNR and LODDS staging systems were linked with mortality in patients with colorectal NENs treated surgically(P<0.05).We found that LODDS staging had a higher prognostic value for patients with colorectal NENs treated surgically than PLN and LNR staging systems.Similar results were obtained in the different G staging subgroup analyses.Furthermore,the area under the receiver operating characteristic curve values for LODDS staging system remained consistently higher than those of PLN or LNR,even at the 1-,2-,3-,4-,5-and 6-year follow-up periods.CONCLUSION LNR,PLN,and LODDS were found to significantly predict the prognosis of patients with colorectal NENs treated surgically.

A Layered Energy-Efficient Multi-Node Scheduling Mechanism for Large-Scale WSN

In recent years, target tracking has been considered one of the most important applications of wireless sensornetwork (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally criticalobjectives in this scenario. The existing mechanisms still have weaknesses in balancing the two demands. Theproposed heuristic multi-node collaborative scheduling mechanism (HMNCS) comprises cluster head (CH)election, pre-selection, and task set selectionmechanisms, where the latter two kinds of selections forma two-layerselection mechanism. The CH election innovatively introduces the movement trend of the target and establishesa scoring mechanism to determine the optimal CH, which can delay the CH rotation and thus reduce energyconsumption. The pre-selection mechanism adaptively filters out suitable nodes as the candidate task set to applyfor tracking tasks, which can reduce the application consumption and the overhead of the following task setselection. Finally, the task node selection is mathematically transformed into an optimization problem and thegenetic algorithm is adopted to form a final task set in the task set selection mechanism. Simulation results showthat HMNCS outperforms other compared mechanisms in the tracking accuracy and the network lifetime.

Target Controllability of Multi-Layer Networks With High-Dimensional Nodes

This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion.

A Reputation-Based AODV Protocol for Blackhole and Malfunction Nodes Detection and Avoidance

Enhancing the security of Wireless Sensor Networks(WSNs)improves the usability of their applications.Therefore,finding solutions to various attacks,such as the blackhole attack,is crucial for the success of WSN applications.This paper proposes an enhanced version of the AODV(Ad Hoc On-Demand Distance Vector)protocol capable of detecting blackholes and malfunctioning benign nodes in WSNs,thereby avoiding them when delivering packets.The proposed version employs a network-based reputation system to select the best and most secure path to a destination.To achieve this goal,the proposed version utilizes the Watchdogs/Pathrater mechanisms in AODV to gather and broadcast reputations to all network nodes to build the network-based reputation system.To minimize the network overhead of the proposed approach,the paper uses reputation aggregator nodes only for forwarding reputation tables.Moreover,to reduce the overhead of updating reputation tables,the paper proposes three mechanisms,which are the prompt broadcast,the regular broadcast,and the light broadcast approaches.The proposed enhanced version has been designed to perform effectively in dynamic environments such as mobile WSNs where nodes,including blackholes,move continuously,which is considered a challenge for other protocols.Using the proposed enhanced protocol,a node evaluates the security of different routes to a destination and can select the most secure routing path.The paper provides an algorithm that explains the proposed protocol in detail and demonstrates a case study that shows the operations of calculating and updating reputation values when nodes move across different zones.Furthermore,the paper discusses the proposed approach’s overhead analysis to prove the proposed enhancement’s correctness and applicability.

“Half of the Node Records Are Forged?”: The Problemof Node Records Forgery in Ethereum Network

Ethereum, currently the most widely utilized smart contracts platform, anchors the security of myriad smartcontracts upon its own robustness. Its foundational peer-to-peer network facilitates a dependable node connectionmechanism, whereas an efficient data-sharing protocol constitutes as the bedrock of Blockchain network security.In this paper, we propose NodeHunter, an Ethereum network detector implemented through the application ofsimulation technology, which is capable of aggregating all node records within the network and the interconnectednessbetween them. Utilizing this connection information, NodeHunter can procure more comprehensive insightsfor network status analysis compared to preceding detection methodologies. Throughout a three-month period ofunbroken surveillance of the Ethereum network, we obtained an excess of two million node records along with overone hundred million node acquaintances. Analysis of the gathered data revealed that an alarming 49% or more ofthese node records were maliciously forged.

基于Node-red的云端智能生产线控制系统设计与实现

针对传统生产线在刚性生产过程中面临的成本过高、远程实施难、兼容性低等关键问题,基于目前中小企业的技术基础相对薄弱,无法将云计算平台、数据存储和处理等设备及技术运用到实际生产中的现状,本文利用西门子S7-1200 PLC作为核心控制器,基于Node-red平台设计了成本低、兼容性高的云端智能生产线监控系统,便于实现对于生产线的监视和控制,提高生产效率与产品质量。现场运行表明,该系统运行稳定,满足智能生产线的设计要求,同时具备部署成本低、兼容性高的突出优势。

Node Sociability Based Intelligent Routing for Post-Disaster Emergency Networks

In a post-disaster environment characterized by frequent interruptions in communication links,traditional wireless communication networks are ineffective.Although the“store-carry-forward”mechanism characteristic of Delay Tolerant Networks(DTNs)can transmit data from Internet of things devices to more reliable base stations or data centres,it also suffers from inefficient data transmission and excessive transmission delays.To address these challenges,we propose an intelligent routing strategy based on node sociability for post-disaster emergency network scenarios.First,we introduce an intelligent routing strategy based on node intimacy,which selects more suitable relay nodes and assigns the corresponding number of message copies based on comprehensive utility values.Second,we present an intelligent routing strategy based on geographical location of nodes to forward message replicas secondarily based on transmission utility values.Finally,experiments demonstrate the effectiveness of our proposed algorithm in terms of message delivery rate,network cost ratio and average transmission delay.

The Effect of Key Nodes on theMalware Dynamics in the Industrial Control Network

As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.

An Optimal Node Localization in WSN Based on Siege Whale Optimization Algorithm

Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging andfundamental operations in various monitoring or tracking applications because the network deploys a large areaand allocates the acquired location information to unknown devices. The metaheuristic approach is one of themost advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditionalmethods that often suffer from computational time problems and small network deployment scale. This studyproposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on thesiege mechanism (SWOA) for node localization inWSN. The objective function is modeled while communicatingon localized nodes, considering variables like delay, path loss, energy, and received signal strength. The localizationapproach also assigns the discovered location data to unidentified devices with the modeled objective functionby applying the SWOA algorithm. The experimental analysis is carried out to demonstrate the efficiency of thedesigned localization scheme in terms of various metrics, e.g., localization errors rate, converges rate, and executedtime. Compared experimental-result shows that theSWOA offers the applicability of the developed model forWSNto perform the localization scheme with excellent quality. Significantly, the error and convergence values achievedby the SWOA are less location error, faster in convergence and executed time than the others compared to at least areduced 1.5% to 4.7% error rate, and quicker by at least 4%and 2% in convergence and executed time, respectivelyfor the experimental scenarios.

Deep learning-based automatic pipeline system for predicting lateral cervical lymph node metastasis in patients with papillary thyroid carcinoma using computed tomography:A multi-center study

Objective:The assessment of lateral lymph node metastasis(LLNM)in patients with papillary thyroid carcinoma(PTC)holds great significance.This study aims to develop and evaluate a deep learning-based automatic pipeline system(DLAPS)for diagnosing LLNM in PTC using computed tomography(CT).Methods:A total of 1,266 lateral lymph nodes(LLNs)from 519 PTC patients who underwent CT examinations from January 2019 to November 2022 were included and divided into training and validation set,internal test set,pooled external test set,and prospective test set.The DLAPS consists of an auto-segmentation network based on RefineNet model and a classification network based on ensemble model(ResNet,Xception,and DenseNet).The performance of the DLAPS was compared with that of manually segmented DL models,the clinical model,and Node Reporting and Data System(Node-RADS).The improvement of radiologists’diagnostic performance under the DLAPS-assisted strategy was explored.In addition,bulk RNA-sequencing was conducted based on 12 LLNs to reveal the underlying biological basis of the DLAPS.Results:The DLAPS yielded good performance with area under the receiver operating characteristic curve(AUC)of 0.872,0.910,and 0.822 in the internal,pooled external,and prospective test sets,respectively.The DLAPS significantly outperformed clinical models(AUC 0.731,P<0.001)and Node-RADS(AUC 0.602,P<0.001)in the internal test set.Moreover,the performance of the DLAPS was comparable to that of the manually segmented deep learning(DL)model with AUCs ranging 0.814−0.901 in three test sets.Furthermore,the DLAPSassisted strategy improved the performance of radiologists and enhanced inter-observer consistency.In clinical situations,the rate of unnecessary LLN dissection decreased from 33.33%to 7.32%.Furthermore,the DLAPS was associated with the cell-cell conjunction in the microenvironment.Conclusions:Using CT images from PTC patients,the DLAPS could effectively segment and classify LLNs non-invasively,and this system had a good generalization ability and clinical applicability.

Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.