Interplay of laser power and pore characteristics in selective laser melting of ZK60 magnesium alloys:A study based on in-situ monitoring and image analysis

This study offers significant insights into the multi-physics phenomena of the SLM process and the subsequent porosity characteristics of ZK60 Magnesium(Mg)alloys.High-speed in-situ monitoring was employed to visualise process signals in real-time,elucidating the dynamics of melt pools and vapour plumes under varying laser power conditions specifically between 40 W and 60 W.Detailed morphological analysis was performed using Scanning-Electron Microscopy(SEM),demonstrating a critical correlation between laser power and pore formation.Lower laser power led to increased pore coverage,whereas a denser structure was observed at higher laser power.This laser power influence on porosity was further confirmed via Optical Microscopy(OM)conducted on both top and cross-sectional surfaces of the samples.An increase in laser power resulted in a decrease in pore coverage and pore size,potentially leading to a denser printed part of Mg alloy.X-ray Computed Tomography(XCT)augmented these findings by providing a 3D volumetric representation of the sample internal structure,revealing an inverse relationship between laser power and overall pore volume.Lower laser power appeared to favour the formation of interconnected pores,while a reduction in interconnected pores and an increase in isolated pores were observed at higher power.The interplay between melt pool size,vapour plume effects,and laser power was found to significantly influence the resulting porosity,indicating a need for effective management of these factors to optimise the SLM process of Mg alloys.

Influences of rainfall infiltration on stability of accumulation slope by in-situ monitoring test

In order to improve the understanding of the fundamental mechanism of rainfall infiltration induced landslides in accumulation slope and to clarify some important characteristics of slope performance,artificial rainfall simulation tests and field synthetic monitoring were carried out on a typical accumulation slope of Shangrui Freeway in Guizhou Province,China.The monitoring results show that the most accumulation landslides caused by rainfall infiltration are shallow relaxation failure,whose deformation zone lies within the top 0-4 m soil layer.The deformation of slope gradually reduces from the surface,where the greatest deformation lies in,to the deep part of slope.The average percentage of infiltration during the first 2 h is 86%,and then it reduces gradually with time because of the increase of the surface runoff.The average percentage of infiltration drop to a relatively stable value(50%)after 6 h.Rainfall infiltration causes obvious increase of pore-water pressure,which may result in a reduction of shear strength due to a decrease in effective stress and wetting-induced softening.The double-effect of rainfall infiltration is the main reason of rainfall infiltration induced landslides in accumulation slope.

In-situ monitoring of dynamic behavior of catalyst materials and reaction intermediates in semiconductor catalytic processes

Semiconductor photocatalysis, as a key part of solar energy utilization, has far-reaching implications for industrial, agricultural, and commercial development. Lack of understanding of the catalyst evolution and the reaction mechanism is a critical obstacle for designing efficient and stable photocatalysts. This review summarizes the recent progress of in-situ exploring the dynamic behavior of catalyst materials and reaction intermediates. Semiconductor photocatalytic processes and two major classes of in-situ techniques that include microscopic imaging and spectroscopic characterization are presented. Finally, problems and challenges in in-situ characterization are proposed, geared toward developing more advanced in-situ techniques and monitoring more accurate and realistic reaction processes, to guide designing advanced photocatalysts.

In-situ Monitoring the Setting Behavior of Foamed Concrete Using Ultrasonic Pulse Velocity Method

The applicability of ultrasonic pulse velocity （UPV） method to in-situ monitor setting and hardening process of foamed concrete （FC） was systematically investigated. The UPVs of various FC pastes were automatically and continuously measured by a specially designed ultrasonic monitoring apparatus （UMA）. Ultrasonic tests were performed on FC mixtures with different density （300, 500, 800 and 1 000 kg/m3）, and different fly ash contents （0%, 20%, 40% and 60%）. The influence of curing temperatures （20, 40, 60 and 80~C） was also studied. The experimental results show that three characteristic stages can be clearly identified during the setting process of an arbitrary FC paste： dormant stage, acceleration stage, and deceleration stage. Wet density, fly ash content, and curing temperature have great impact on setting behavior. A stepwise increase of the wet density results in shorter dormant stage and larger final UPV. Hydration reaction rate is obviously promoted with an increase in curing temperature. However, the addition fly ash retards the microstn,lcture formation. To aid in comparing with the ultrasonic results, the consistence spread test and Vicat needle test （VNT） were also conducted. A correlation between ultrasonic and VNT results was also established to evaluate the initial and final setting time of the FC mixtures. Finally, certain ranges of UPV with reasonable widths were suggested for the initial and final setting time, respectively.

In-situ monitoring plume,spattering behavior and revealing their relationship with melt flow in laser powder bed fusion of nickel-based superalloy

Laser powder bed fusion(LPBF)is a highly dynamic and complex physical process,and single-track de-fects tend to accumulate into non-negligible internal defects of parts.The nickel-based superalloy single track was fabricated by LPBF,and its plume and spattering behavior were monitored in situ and recorded in real time based on image recognition and tracking in this study.The relationship among laser energy density,melt flow,plume and spattering behavior during LPBF was discussed.Volumetric energy density had limitations as a design parameter for LPBF.However,we found that plume and spattering behavior can be used as real-time design parameters for the processing of LPBF parts and implemented the initial velocity statistics for LPBF single-track spattering based on the centroid extraction algorithm.The influ-ence of melt flow evolution paths on the spattering and plume behavior in three different melting modes was revealed,and a shift in plume behavior was found in the overlap region of the additive substrate.This study provides a new method for obtaining statistics of spattering-related physical quantities in the melting mode,which is beneficial for the development of processing methods to mitigate the instability of the LPBF process.

Real-Time Monitoring of Meteorological Data at In-Situ GCW Remediation Sites

To optimize the self-organization network, self-adaptation, real-time monitoring, remote management capability, and equipment reuse level of the meteorological station supporting the portable groundwater circulation wells, and to provide real-time and effective technical services and environmental data support for groundwater remediation, a real-time monitoring system design of the meteorological station supporting the portable groundwater circulation wells based on the existing equipment is proposed. A variety of environmental element information is collected and transmitted to the embedded web server by the intelligent weather transmitter, and then processed by the algorithm and stored internally, displayed locally, and published on the web. The system monitoring algorithm and user interface are designed in the CNWSCADA development environment to realize real-time processing and analysis of environmental data and monitoring, control, management, and maintenance of the system status. The PLC-controlled photovoltaic power generating panels and lithium battery packs are in line with the concept of energy saving and emission reduction, and at the same time, as an emergency power supply to guarantee the safety of equipment and data when the utility power fails to meet the requirements. The experiment proves that the system has the characteristics of remote control, real-time interaction, simple station deployment, reliable operation, convenient maintenance, and green environment protection, which is conducive to improving the comprehensive utilization efficiency of various types of environmental information and providing reliable data support, theoretical basis and guidance suggestions for the research of groundwater remediation technology and its disciplines, and the research and development of the movable groundwater cycling well monitoring system.

Application and management of continuous glucose monitoring in diabetic kidney disease

Diabetic kidney disease(DKD)is a common complication of diabetes mellitus that contributes to the risk of end-stage kidney disease(ESKD).Wide glycemic var-iations,such as hypoglycemia and hyperglycemia,are broadly found in diabetic patients with DKD and especially ESKD,as a result of impaired renal metabolism.It is essential to monitor glycemia for effective management of DKD.Hemoglobin A1c(HbA1c)has long been considered as the gold standard for monitoring glycemia for>3 months.However,assessment of HbA1c has some bias as it is susceptible to factors such as anemia and liver or kidney dysfunction.Continuous glucose monitoring(CGM)has provided new insights on glycemic assessment and management.CGM directly measures glucose level in interstitial fluid,reports real-time or retrospective glucose concentration,and provides multiple glycemic metrics.It avoids the pitfalls of HbA1c in some contexts,and may serve as a precise alternative to estimation of mean glucose and glycemic variability.Emerging studies have demonstrated the merits of CGM for precise monitoring,which allows fine-tuning of glycemic management in diabetic patients.Therefore,CGM technology has the potential for better glycemic monitoring in DKD patients.More research is needed to explore its application and management in different stages of DKD,including hemodialysis,peritoneal dialysis and kidney transplantation.

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

The spread of tuberculosis(TB),especially multidrug-resistant TB and extensively drug-resistant TB,has strongly motivated the research and development of new anti-TB drugs.New strategies to facilitate drug combinations,including pharmacokinetics-guided dose optimization and toxicology studies of first-and second-line anti-TB drugs have also been introduced and recommended.Liquid chromatography-mass spectrometry(LC-MS)has arguably become the gold standard in the analysis of both endo-and exo-genous compounds.This technique has been applied successfully not only for therapeutic drug monitoring(TDM)but also for pharmacometabolomics analysis.TDM improves the effectiveness of treatment,reduces adverse drug reactions,and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window.Based on TDM,the dose would be optimized individually to achieve favorable outcomes.Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs,aiding in the discovery of potential biomarkers for TB diagnostics,treatment monitoring,and outcome evaluation.This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades.Besides,we discussed the advantages and disadvantages of this technique in practical use.The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted.Lastly,we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies(pharmacometrics,drug and vaccine developments,machine learning/artificial intelligence,among others)to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

Fiber optic monitoring of an anti-slide pile in a retrogressive landslide

Anti-slide piles are one of the most important reinforcement structures against landslides,and evalu-ating the working conditions is of great significance for landslide mitigation.The widely adopted analytical methods of pile internal forces include cantilever beam method and elastic foundation beam method.However,due to many assumptions involved in calculation,the analytical models cannot be fully applicable to complex site situations,e.g.landslides with multi-sliding surfaces and pile-soil interface separation as discussed herein.In view of this,the combination of distributed fiber optic sensing(DFOS)and strain-internal force conversion methods was proposed to evaluate the working conditions of an anti-sliding pile in a typical retrogressive landslide in the Three Gorges reservoir area,China.Brillouin optical time domain reflectometry(BOTDR)was utilized to monitor the strain distri-bution along the pile.Next,by analyzing the relative deformation between the pile and its adjacent inclinometer,the pile-soil interface separation was profiled.Finally,the internal forces of the anti-slide pile were derived based on the strain-internal force conversion method.According to the ratio of calculated internal forces to the design values,the working conditions of the anti-slide pile could be evaluated.The results demonstrated that the proposed method could reveal the deformation pattern of the anti-slide pile system,and can quantitatively evaluate its working conditions.

Application of GNSS-PPP on Dynamic Deformation Monitoring of Offshore Platforms

The real-time dynamic deformation monitoring of offshore platforms under environmental excitation is crucial to their safe operation.Although Global Navigation Satellite System-Precise Point Positioning(GNSS-PPP)has been considered for this purpose,its monitoring accuracy is relatively low.Moreover,the influence of background noise on the dynamic monitoring accuracy of GNSS-PPP remains unclear.Hence,it is imperative to further validate the feasibility of GNSS-PPP for deformation monitoring of offshore platforms.To address these concerns,vibration table tests with different amplitudes and frequencies are conducted.The results demonstrate that GNSS-PPP can effectively monitor horizontal vibration displacement as low as±30 mm,which is consistent with GNSS-RTK.Furthermore,the spectral characteristic of background noise in GNSS-PPP is similar to that of GNSS-RTK(Real Time Kinematic).Building on this observation,an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)has been proposed to de-noise the data and enhance the dynamic monitoring accuracy of GNSS-PPP.Field monitoring application research is also undertaken,successfully extracting and analyzing the dynamic deformation of an offshore platform structure under environmental excitation using GNSS-PPP monitoring in conjunction with improved CEEMDAN de-noising.By comparing the de-noised dynamic deformation trajectories of the offshore platform during different periods,it is observed that the platform exhibits reversible alternating vibration responses under environmental excitation,with more pronounced displacement deformation in the direction of load action.The research results confirm the feasibility and potential of GNSS-PPP for dynamic deformation monitoring of offshore platforms.

Deformation monitoring of long-span railway bridges based on SBAS-InSAR technology

The deformation monitoring of long-span railway bridges is significant to ensure the safety of human life and property.The interferometric synthetic aperture radar(In SAR)technology has the advantage of high accuracy in bridge deformation monitoring.This study monitored the deformation of the Ganjiang Super Bridge based on the small baseline subsets(SBAS)In SAR technology and Sentinel-1A data.We analyzed the deformation results combined with bridge structure,temperature,and riverbed sediment scouring.The results are as follows:(1)The Ganjiang Super Bridge area is stable overall,with deformation rates ranging from-15.6 mm/yr to 10.7 mm/yr(2)The settlement of the Ganjiang Super Bridge deck gradually increases from the bridge tower toward the main span,which conforms to the typical deformation pattern of a cable-stayed bridge.(3)The sediment scouring from the riverbed cause the serious settlement on the bridge’s east side compared with that on the west side.(4)The bridge deformation negatively correlates with temperature,with a faster settlement at a higher temperature and a slow rebound trend at a lower temperature.The study findings can provide scientific data support for the health monitoring of long-span railway bridges.

Thermally Conductive and UV-EMI Shielding Electronic Textiles for Unrestricted and Multifaceted Health Monitoring

Skin-attachable electronics have garnered considerable research attention in health monitoring and artificial intelligence domains,whereas susceptibility to elec-tromagnetic interference(EMI),heat accumulation issues,and ultraviolet(UV)-induced aging problems pose significant constraints on their potential applications.Here,an ultra-elas-tic,highly breathable,and thermal-comfortable epidermal sensor with exceptional UV-EMI shielding performance and remarkable thermal conductivity is developed for high-fidelity monitoring of multiple human electrophysiological signals.Via filling the elastomeric microfibers with thermally conductive boron nitride nanoparticles and bridging the insulating fiber interfaces by plating Ag nanoparticles(NPs),an interwoven thermal con-ducting fiber network(0.72 W m^(-1) K^(-1))is constructed benefiting from the seamless thermal interfaces,facilitating unimpeded heat dissipation for comfort skin wearing.More excitingly,the elastomeric fiber substrates simultaneously achieve outstanding UV protection(UPF=143.1)and EMI shielding(SET>65,X-band)capabilities owing to the high electrical conductivity and surface plasmon resonance of Ag NPs.Furthermore,an electronic textile prepared by printing liquid metal on the UV-EMI shielding and thermally conductive nonwoven textile is finally utilized as an advanced epidermal sensor,which succeeds in monitoring different electrophysiological signals under vigorous electromagnetic interference.This research paves the way for developing protective and environmentally adaptive epidermal electronics for next-generation health regulation.

Technical development of operational in-situ marine monitoring and research on its key generic technologies in China

In China,operational in-situ marine monitoring is the primary means of directly obtaining hydrological,meteorological,and oceanographic environmental parameters across sea areas,and it is essential for applications such as forecast of marine environment,prevention and mitigation of disaster,exploitation of marine resources,marine environmental protection,and management of transportation safety.In this paper,we summarise the composition,development courses,and present operational status of three systems of operational in-situ marine monitoring,namely coastal marine automated network station,ocean data buoy and voluntary observing ship measuring and reporting system.Additionally,we discuss the technical development in these in-situ systems and achievements in the key generic technologies along with future development trends.

Monitoring seismicity in the southern Sichuan Basin using a machine learning workflow

Monitoring seismicity in real time provides significant benefits for timely earthquake warning and analyses.In this study,we propose an automatic workflow based on machine learning(ML)to monitor seismicity in the southern Sichuan Basin of China.This workflow includes coherent event detection,phase picking,and earthquake location using three-component data from a seismic network.By combining Phase Net,we develop an ML-based earthquake location model called Phase Loc,to conduct real-time monitoring of the local seismicity.The approach allows us to use synthetic samples covering the entire study area to train Phase Loc,addressing the problems of insufficient data samples,imbalanced data distribution,and unreliable labels when training with observed data.We apply the trained model to observed data recorded in the southern Sichuan Basin,China,between September 2018 and March 2019.The results show that the average differences in latitude,longitude,and depth are 5.7 km,6.1 km,and 2 km,respectively,compared to the reference catalog.Phase Loc combines all available phase information to make fast and reliable predictions,even if only a few phases are detected and picked.The proposed workflow may help real-time seismic monitoring in other regions as well.

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

A Review: Biosensor Progression in Glucose Monitoring for Patients with Diabetes

Diabetes is a condition that can come to the surface at any point throughout a person’s life. Although Type 1 and Type 2 Diabetes have different triggers that cause them to arise, a person can experience similar complications from either if not monitored and treated accordingly. Through the Diabetes Control and Complications Trial, it was found that a significant way to monitor diabetes is through glucose levels in a person’s body. The research surrounding glucose monitoring dates to the mid-1800s, with the first successful reagent for glucose testing being developed in 1908. Since then, glucose sensing has become one of the most rapidly growing areas of research and development in biosensor technology, creating a competitive market for more advanced, accurate, and convenient glucose monitoring. This article reviews the history of biosensors used for glucose monitoring, and major advancements in biosensor technology to enhance performance and improve quality of life for patients with diabetes.

IoT-Enabled Plant Monitoring System with Power Optimization and Secure Authentication

Global food security is a pressing issue that affects the stability and well-being of communities worldwide.While existing Internet of Things(IoT)enabled plant monitoring systems have made significant strides in agricultural monitoring,they often face limitations such as high power consumption,restricted mobility,complex deployment requirements,and inadequate security measures for data access.This paper introduces an enhanced IoT application for agricultural monitoring systems that address these critical shortcomings.Our system strategically combines power efficiency,portability,and secure access capabilities,assisting farmers in monitoring and tracking crop environmental conditions.The proposed system includes a remote camera that captures images of surrounding plants and a sensor module that regularly monitors various environmental factors,including temperature,humidity,and soil moisture.We implement power management strategies to minimize energy consumption compared to existing solutions.Unlike conventional systems,our implementation utilizes the Amazon Web Services(AWS)cloud platform for reliable data storage and processing while incorporating comprehensive security measures,including Two-Factor Authentication(2FA)and JSON Web Tokens(JWT),features often overlooked in current agricultural IoT solutions.Users can access this secure monitoring system via a developed Android application,providing convenient mobile access to the gathered plant data.We validate our system’s advantages by implementing it with two potted garlic plants on Okayama University’s rooftop.Our evaluation demonstrates high sensor reliabil-ity,with strong correlations between sensor readings and reference data,achieving determination coefficients(R2)of 0.979 for temperature and 0.750 for humidity measurements.The implemented power management strategies extend battery life to 10 days on a single charge,significantly outperforming existing systems that typically require daily recharging.Furthermore,our dual-layer security implementation utilizing 2FA and JWT successfully protects sensitive agricultural data from unauthorized access.

Design and Construction of Automatic Monitoring System for Open-pit Coal Mine Slopes

[Objectives]To monitor the stability of open-pit coal mine slopes in real time and ensure the safety of coal mine production.[Methods]The automatic monitoring system of coal mine slope was explored in depth,and the core functions of the system were designed comprehensively.According to the design function of the automatic monitoring system,the slope automatic monitoring system was constructed.Besides,in accordance with the actual situation of the slope,the monitoring frequency of slopes was set scientifically,and the key indicators such as rainfall,deep displacement and surface displacement of the slopes were monitored in an all-round and multi-angle way.[Results]During the monitoring period,the overall condition of the slope remained good,and no landslides or other geological disasters occurred.At the same time,the overall rainfall in the slope area remained low.In terms of monitoring data,the horizontal displacement and settlement of the slopes increased first and then tended to be stable.Specifically,the maximum horizontal displacement during the monitoring period was 22.74 mm,while the maximum settlement was 18.65 mm.[Conclusions]The automatic slope monitoring system has obtained remarkable achievements in practical application.It not only improves the accuracy and efficiency of slope stability monitoring,but also provides valuable reference experience for similar projects.

Accuracy of FreeStyle Libre flash glucose monitoring in patients with type 2 diabetes who migrated from highlands to plains

BACKGROUND The FreeStyle Libre flash glucose monitoring(FGM)system entered the Chinese market in 2017 to complement the self-monitoring of blood glucose.Due to its increased usage in clinics,the number of studies investigating its accuracy has increased.However,its accuracy has not been investigated in highland populations in China.AIM To evaluate measurements recorded using the FreeStyle Libre FGM system compared with capillary blood glucose measured using the enzyme electrode method in patients with type 2 diabetes(T2D)who had migrated within 3 mo from highlands to plains.METHODS Overall,68 patients with T2D,selected from those who had recently migrated from highlands to plains(within 3 mo),were hospitalized at the Department of Endocrinology from August to October 2017 and underwent continuous glucose monitoring(CGM)with the FreeStyle Libre FGM system for 14 d.Throughout the study period,fingertip capillary blood glucose was measured daily using the enzyme electrode method(Super GL,China),and blood glucose levels were read from the scanning probe during fasting and 2 h after all three meals.Moreover,the time interval between reading the data from the scanning probe and collecting fingertip capillary blood was controlled to<5 min.The accuracy of the FGM system was evaluated according to the CGM guidelines.Subsequently,the factors influencing the mean absolute relative difference(MARD)of this system were analyzed by a multiple linear regression method.RESULTS Pearson’s correlation analysis showed that the fingertip and scanned glucose levels were positively correlated(R=0.86,P=0.00).The aggregated MARD of scanned glucose was 14.28±13.40%.Parker's error analysis showed that 99.30%of the data pairs were located in areas A and B.According to the probe wear time of the FreeStyle Libre FGM system,MARD_(1 d) and MARD_(2-14 d) were 16.55%and 14.35%,respectively(t=1.23,P=0.22).Multiple stepwise regression analysis showed that MARD did not correlate with blood glucose when the largest amplitude of glycemic excursion(LAGE)was<5.80 mmol/L but negatively correlated with blood glucose when the LAGE was≥5.80 mmol/L.CONCLUSION The FreeStyle Libre FGM system has good accuracy in patients with T2D who had recently migrated from highlands to plains.This system might be ideal for avoiding the effects of high hematocrit on blood glucose monitoring in populations that recently migrated to plains.MARD is mainly influenced by glucose levels and fluctuations,and the accuracy of the system is higher when the blood glucose fluctuation is small.In case of higher blood glucose level fluctuations,deviation in the scanned glucose levels is the highest at extremely low blood glucose levels.

A Fuzzy Trust Management Mechanism with Dynamic Behavior Monitoring for Wireless Sensor Networks

Traditional wireless sensor networks(WSNs)are typically deployed in remote and hostile environments for information collection.The wireless communication methods adopted by sensor nodes may make the network highly vulnerable to various attacks.Traditional encryption and authentication mechanisms cannot prevent attacks launched by internal malicious nodes.The trust-based security mechanism is usually adopted to solve this problem in WSNs.However,the behavioral evidence used for trust estimation presents some uncertainties due to the open wireless medium and the inexpensive sensor nodes.Moreover,how to efficiently collect behavioral evidences are rarely discussed.To address these issues,in this paper,we present a trust management mechanism based on fuzzy logic and a cloud model.First,a type-II fuzzy logic system is used to preprocess the behavioral evidences and alleviate uncertainty.Then,the cloud model is introduced to estimate the trust values for sensor nodes.Finally,a dynamic behavior monitoring protocol is proposed to provide a balance between energy conservation and safety assurance.Simulation results demonstrate that our trust management mechanism can effectively protect the network from internal malicious attacks while enhancing the energy efficiency of behavior monitoring.