Enhanced permeability prediction in porous media using particle swarm optimization with multi-source integration

Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.

Data acquisition,analysis and applications of multi-sensor integration

This paper presents some key techniques for multi-sensor integration system, which is applied to the intelligent transportation system industry and surveying and mapping industry, e.g. road surface condition detection, digital map making. The techniques are synchronization control of multi-sensor, space-time benchmark for sensor data, and multi-sensor data fusion and mining. Firstly, synchronization control of multi-sensor is achieved through a synchronization control system which is composed of a time synchronization controller and some synchronization sub-controllers. The time synchronization controller can receive GPS time information from GPS satellites, relative distance information from distance measuring instrument and send space-time information to the synchronization sub-controller. The latter can work at three types of synchronization mode, i.e. active synchronization, passive synchronization and time service synchronization. Secondly, space-time benchmark can be established based on GPS time and global reference coordinate system, and can be obtained through position and azimuth determining system and synchronization control system. Thirdly, there are many types of data fusion and mining, e.g. GPS/Gyro/DMI data fusion, data fusion between stereophotogrammetry and PADS, data fusion between laser scanner and PADS, and data fusion between CCD camera and laser scanner. Finally, all these solutions presented in paper have been applied to two areas, i.e. land-bone intelligent road detection and measurement system and 3D measurement system based on unmanned helicopter. The former has equipped some highway engineering Co. , Ltd. and has been successfully put into use. The latter is an ongoing resealch.

Multi-broker architecture for large-scale dynamic heterogeneous information integration

In order to realize interoperability to a large number of autonomous and heterogeneous information sources with high efficiency, an agent-based multi-broker architecture （AMA）-HustEven, is constructed. A group of broker agents are designed to provide brokering services in a peer-to-peer （P2P） manner for the non- broker agents （user agents, resource agents, query agents）. Thus, the scalability and robustness of the system are enhanced. Ontology is also used by the broker agents for facilitating interoperability among all the agents in HustEven. Unlike any other AMAs, an interdomain ontology is built in this system to represent the relationships among the common concepts in the innerdomain ontologies. Therefore, a broker forwards the queries only to the other related brokers according to the interdomain ontology and the communication overhead among the brokers is reduced. Obviously, the application of the interdomain ontology enables a broker to fully take advantage of the multi-broker architecture. The experimental results show that the HustEven performs more efficiently than any other existing systems.

Silicon-based optoelectronic heterogeneous integration for optical interconnection

The performance of optical interconnection has improved dramatically in recent years.Silicon-based optoelectronic heterogeneous integration is the key enabler to achieve high performance optical interconnection,which not only provides the optical gain which is absent from native Si substrates and enables complete photonic functionalities on chip,but also improves the system performance through advanced heterogeneous integrated packaging.This paper reviews recent progress of silicon-based optoelectronic heterogeneous integration in high performance optical interconnection.The research status,development trend and application of ultra-low loss optical waveguides,high-speed detectors,high-speed modulators,lasers and 2D,2.5D,3D and monolithic integration are focused on.

Carbon nanotube integrated circuit technology:purification,assembly and integration

As the manufacturing process of silicon-based integrated circuits(ICs)approaches its physical limit,the quantum effect of silicon-based field-effect transistors(FETs)has become increasingly evident.And the burgeoning carbon-based semiconductor technology has become one of the most disruptive technologies in the post-Moore era.As one-dimensional nanomaterials,carbon nanotubes(CNTs)are far superior to silicon at the same technology nodes of FETs because of their excellent electrical transport and scaling properties,rendering them the most competitive material in the next-generation ICs technology.However,certain challenges impede the industrialization of CNTs,particularly in terms of material preparation,which significantly hinders the development of CNT-based ICs.Focusing on CNT-based ICs technology,this review summarizes its main technical status,development trends,existing challenges,and future development directions.

U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies

El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been developed to simulate and predict it.In some simplified coupled ocean-atmosphere models,the relationship between sea surface temperature(SST)anomalies and wind stress(τ)anomalies can be constructed by statistical methods,such as singular value decomposition(SVD).In recent years,the applications of artificial intelligence(AI)to climate modeling have shown promising prospects,and the integrations of AI-based models with dynamical models are active areas of research.This study constructs U-Net models for representing the relationship between SSTAs andτanomalies in the tropical Pacific;the UNet-derivedτmodel,denoted asτUNet,is then used to replace the original SVD-basedτmodel of an intermediate coupled model(ICM),forming a newly AI-integrated ICM,referred to as ICM-UNet.The simulation results obtained from ICM-UNet demonstrate their ability to represent the spatiotemporal variability of oceanic and atmospheric anomaly fields in the equatorial Pacific.In the ocean-only case study,theτUNet-derived wind stress anomaly fields are used to force the ocean component of the ICM,the results of which also indicate reasonable simulations of typical ENSO events.These results demonstrate the feasibility of integrating an AI-derived model with a physics-based dynamical model for ENSO modeling studies.Furthermore,the successful integration of the dynamical ocean models with the AI-based atmospheric wind model provides a novel approach to ocean-atmosphere interaction modeling studies.

A stable implicit nodal integration-based particle finite element method(N-PFEM)for modelling saturated soil dynamics

In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated soils.Our approach incorporates the nodal integration technique into a generalised Hellinger-Reissner(HR)variational principle,creating an implicit PFEM formulation.To mitigate the volumetric locking issue in low-order elements,we employ a node-based strain smoothing technique.By discretising field variables at the centre of smoothing cells,we achieve nodal integration over cells,eliminating the need for sophisticated mapping operations after re-meshing in the PFEM.We express the discretised governing equations as a min-max optimisation problem,which is further reformulated as a standard second-order cone programming(SOCP)problem.Stresses,pore water pressure,and displacements are simultaneously determined using the advanced primal-dual interior point method.Consequently,our numerical model offers improved accuracy for stresses and pore water pressure compared to the displacement-based PFEM formulation.Numerical experiments demonstrate that the N-PFEM efficiently captures both transient and long-term hydro-mechanical behaviour of saturated soils with high accuracy,obviating the need for stabilisation or regularisation techniques commonly employed in other nodal integration-based PFEM approaches.This work holds significant implications for the development of robust and accurate numerical tools for studying saturated soil dynamics.

Multi-feature integration kernel particle filtering target tracking

In light of degradation of particle filtering and robust weakness in the utilization of single feature tracking,this paper presents a kernel particle filtering tracking method based on multi-feature integration.In this paper,a new weight upgrading method is given out during kernel particle filtering at first,and then robust tracking is realized by integrating color and texture features under the framework of kernel particle filtering.Space histogram and integral histogram is adopted to calculate color and texture features respectively.These two calculation methods effectively overcome their own defectiveness,and meanwhile,improve the real timing for particle filtering.This algorithm has also improved sampling effectiveness,resolved redundant calculation for particle filtering and degradation of particles.Finally,the experiment for target tracking is realized by using the method under complicated background and shelter.Experiment results show that the method can reliably and accurately track target and deal with target sheltering situation properly.

Integrated importance measure for multi-state coherent systems of k level

To verify the effectiveness of the integrated importance measure （IIM） for multi-state coherent systems of k level, the definition and physical meaning of IIM are demonstrated. Then, the improvement potential and Δ-importance measures are generalized to multi-state coherent systems based on the system performance level, and the relationships between IIM and traditional importance measures are discussed. The characteristics of IIM are demonstrated in both series and parallel systems. Also, an application to an oil transportation system is given. The comparison results show that： （i） IIM has some useful properties that are not possessed by traditional importance measures; （ii） IIM is effective in evaluating the component role in multi-state systems when the component reliability and the failure rate are simultaneously considered.

Multi-Effect Evaporation Coupled with MVR Heat Pump Thermal Integration Distillation for Separating Salt Containing Methanol Wastewater

Due to the high energy consumption for separation of salt containing methanol wastewater, in this work, the multi-effect evaporation coupled with mechanical vapor recompression (MVR) heat pump and thermal integration technologies were raised for the first time. The ELECNRTL thermodynamic model is used to simulate and optimize the evaporation rectification process. Energy consumption and total annual cost (TAC) are taken as objective functions. The results show that multi-effect evaporation coupled with conventional distillation process can save energy consumption and TAC by 44.12% and 39.14%. The multi-effect evaporation coupled with distillation process based on MVR heat pump technology can save energy consumption and TAC by 55.27% and 47.49%, which is super to three-effect evaporation coupled with conventional distillation process. The three-effect evaporation coupled with MVR heat integration process can save energy consumption and TAC by 81.32% and 58.55%, which is more economical than other processes. It can be clearly seen that three-effect evaporation coupled with MVR heat integration process is more competitive to deal with the salt containing methanol wastewater.

An efficient method for train-track-substructure dynamic interaction analysis by implicit-explicit integration and multi-time-step solution

In this work,a method is put forward to obtain the dynamic solution efficiently and accurately for a large-scale train-track-substructure(TTS)system.It is called implicit-explicit integration and multi-time-step solution method(abbreviated as mI-nE-MTS method).The TTS system is divided into train-track subsystem and substruc-ture subsystem.Considering that the root cause of low effi-ciency of obtaining TTS solution lies in solving the alge-braic equation of the substructures,the high-efficient Zhai method,an explicit integration scheme,can be introduced to avoid matrix inversion process.The train-track system is solved by implicitly Park method.Moreover,it is known that the requirement of time step size differs for different sub-systems,integration methods and structural frequency response characteristics.A multi-time-step solution is pro-posed,in which time step size for the train-track subsystem and the substructure subsystem can be arbitrarily chosen once satisfying stability and precision demand,namely the time spent for m implicit integral steps is equal to n explicit integral steps,i.e.,mI=nE as mentioned above.The numeri-cal examples show the accuracy,efficiency,and engineering practicality of the proposed method.

Impacts of Integrated Multi-Trophic Aquaculture on Phytoplankton in Sanggou Bay

Integrated multi-trophic aquaculture(IMTA)has been considered as an ecofriendly culture system providing a potential solution to environmental risks caused by intensive monoculture system.However,the impact of IMTA on phytoplankton remains unclear.In this study,the spatial and temporal variations of phytoplankton in Sanggou Bay were investigated seasonally based on 21 sampling sites covering three cultivation zones(bivalve zone,IMTA zone,and kelp zone)and one control zone(without aquatic cultivation).In total,128 phytoplankton species,with diatoms and dinoflagellates as the dominant groups,were obtained across the whole year,and the mean Shannon diversity index(H')and species richness(SR)were determined as 1.39 and 9.39,respectively.The maximum chlorophyll a(Chl-a)(6.32μg L^(-1))and plankton diversity(H'of 1.97)occurred in summer and autumn,respectively.Compared to other zones,the bivalve zone displayed significantly higher Chl-a and lower H'in majority of time.Pairwise PERMANOVA analysis indicated that the phytoplankton assemblage in the bivalve zone was significantly different with the control and kelp zones,while the IMTA zone maintained close to other three zones.Based on generalized additive models,temperature,NO_(2)^(-)-N,N/P ratio,SiO_(3)^(2-)-Si,and salinity were determined as the key factors underlying Chl-a and phytoplankton diversity.Addi-tionally,the results of redundancy analysis further indicated that the phytoplankton assemblage in the bivalve zone is positively re-lated with nutrients such as NO_(3)^(-)-N and NH_(4)^(+)-N as well as water depth,while the phytoplankton assemblages in the kelp,control,and IMTA zones are associated with NO_(2)^(-)-N,SiO_(3)^(2-)-Si,and salinity.Taken all observations into consideration together,it can be inferred that IMTA can effectively reduce Chl-a level compared to bivalve monoculture by reducing the nutrients.However,the SR,H’,and species composition of phytoplankton are primarily determined by local environment factors such as temperature,water depth,salinity and SiO_(3)^(2-)-Si.

M3SC:A Generic Dataset for Mixed Multi-Modal(MMM)Sensing and Communication Integration

The sixth generation(6G)of mobile communication system is witnessing a new paradigm shift,i.e.,integrated sensing-communication system.A comprehensive dataset is a prerequisite for 6G integrated sensing-communication research.This paper develops a novel simulation dataset,named M3SC,for mixed multi-modal(MMM)sensing-communication integration,and the generation framework of the M3SC dataset is further given.To obtain multimodal sensory data in physical space and communication data in electromagnetic space,we utilize Air-Sim and WaveFarer to collect multi-modal sensory data and exploit Wireless InSite to collect communication data.Furthermore,the in-depth integration and precise alignment of AirSim,WaveFarer,andWireless InSite are achieved.The M3SC dataset covers various weather conditions,multiplex frequency bands,and different times of the day.Currently,the M3SC dataset contains 1500 snapshots,including 80 RGB images,160 depth maps,80 LiDAR point clouds,256 sets of mmWave waveforms with 8 radar point clouds,and 72 channel impulse response(CIR)matrices per snapshot,thus totaling 120,000 RGB images,240,000 depth maps,120,000 LiDAR point clouds,384,000 sets of mmWave waveforms with 12,000 radar point clouds,and 108,000 CIR matrices.The data processing result presents the multi-modal sensory information and communication channel statistical properties.Finally,the MMM sensing-communication application,which can be supported by the M3SC dataset,is discussed.

Integrating Multi-Source Web Records into Relational Database

How to integrate heterogeneous semi-structured Web records into relational database is an important and challengeable research topic. An improved model of conditional random fields was presented to combine the learning of labeled samples and unlabeled database records in order to reduce the dependence on tediously hand-labeled training data. The pro- posed model was used to solve the problem of schema matching between data source schema and database schema. Experimental results using a large number of Web pages from diverse domains show the novel approach＇s effectiveness.

Waste Minimization Through Process Integration and Multi-objective Optimization

By avoiding or reducing the production of waste, waste minimization is an effective approach to solve the pollution problem in chemical industry. Process integration supported by multi-objective optimization provides a framework for process design or process retrofit by simultaneously optimizing on the aspects of environment and economics. Multi-objective genetic algorithm is applied in this area as the solution approach for the multi-objective optimization problem.

A novel self-alignment method for high precision silicon diffraction microlens arrays preparation and its integration with infrared focal plane arrays

Silicon(Si)diffraction microlens arrays are usually used to integrating with infrared focal plane arrays(IRFPAs)to improve their performance.The errors of lithography are unavoidable in the process of the Si diffrac-tion microlens arrays preparation in the conventional engraving method.It has a serious impact on its performance and subsequent applications.In response to the problem of errors of Si diffraction microlens arrays in the conven-tional method,a novel self-alignment method for high precision Si diffraction microlens arrays preparation is pro-posed.The accuracy of the Si diffractive microlens arrays preparation is determined by the accuracy of the first li-thography mask in the novel self-alignment method.In the subsequent etching,the etched area will be protected by the mask layer and the sacrifice layer or the protective layer.The unprotection area is carved to effectively block the non-etching areas,accurately etch the etching area required,and solve the problem of errors.The high precision Si diffraction microlens arrays are obtained by the novel self-alignment method and the diffraction effi-ciency could reach 92.6%.After integrating with IRFPAs,the average blackbody responsity increased by 8.3%,and the average blackbody detectivity increased by 10.3%.It indicates that the Si diffraction microlens arrays can improve the filling factor and reduce crosstalk of IRFPAs through convergence,thereby improving the perfor-mance of the IRFPAs.The results are of great reference significance for improving their performance through opti-mizing the preparation level of micro nano devices.

SOME PROPERTIES OF THE INTEGRATION OPERATORS ON THE SPACES F(p,q,s)

We study the closed range property and the strict singularity of integration operators acting on the spaces F(p,pα-2,s).We completely characterize the closed range property of the Volterra companion operator I_(g)on F(p,pα-2,s),which generalizes the existing results and answers a question raised in[A.Anderson,Integral Equations Operator Theory,69(2011),no.1,87-99].For the Volterra operator J_(g),we show that,for 0<α≤1,J_(g)never has a closed range on F(p,pα-2,s).We then prove that the notions of compactness,weak compactness and strict singularity coincide in the case of J_(g)acting on F(p,p-2,s).

High-intensity spatial-mode steerable frequency up-converter toward on-chip integration

Integrated photonic devices are essential for on-chip optical communication,optical-electronic systems,and quantum information sciences.To develop a high-fidelity interface between photonics in various frequency domains without disturbing their quantum properties,nonlinear frequency conversion,typically steered with the quadratic(χ2)process,should be considered.Furthermore,another degree of freedom in steering the spatial modes during theχ2 process,with unprecedent mode intensity is proposed here by modulating the lithium niobate(LN)waveguide-based inter-mode quasi-phasematching conditions with both temperature and wavelength parameters.Under high incident light intensities(25 and 27.8 dBm for the pump and the signal lights,respectively),mode conversion at the sum-frequency wavelength with sufficient high output power(−7–8 dBm)among the TM01,TM10,and TM00 modes is realized automatically with characterized broad temperature(ΔT≥8°C)and wavelength windows(Δλ≥1 nm),avoiding the previous efforts in carefully preparing the signal or pump modes.The results prove that high-intensity spatial modes can be prepared at arbitrary transparent wavelength of theχ2 media toward on-chip integration,which facilitates the development of chip-based communication and quantum information systems because spatial correlations can be applied to generate hyperentangled states and provide additional robustness in quantum error correction with the extended Hilbert space.

Multi-Bandgap Monolithic Metal Nanowire Percolation Network Sensor Integration by Reversible Selective Laser-Induced Redox

Active electronics are usually composed of semiconductor and metal electrodes which are connected by multiple vacuum deposition steps and photolithography patterning.However,the presence of interface of dissimilar material between semiconductor and metal electrode makes various problems in electrical contacts and mechanical failure.The ideal electronics should not have defective interfaces of dissimilar materials.In this study,we developed a novel method to fabricate active electronic components in a monolithic seamless fashion where both metal and semiconductor can be prepared from the same monolith material without creating a semiconductor-metal interface by reversible selective laser-induced redox(rSLIR)method.Furthermore,rSLIR can control the oxidation state of transition metal(Cu)to yield semiconductors with two different bandgap states(Cu_(2)O and CuO with bandgaps of 2.1 and 1.2 eV,respectively),which may allow multifunctional sensors with multiple bandgaps from the same materials.This novel method enables the seamless integration of single-phase Cu,Cu_(2)O,and CuO,simultaneously while allowing reversible,selec-tive conversion between oxidation states by simply shining laser light.Moreover,we fabricated a flexible monolithic metal-semiconduc-tor-metal multispectral photodetector that can detect multiple wavelengths.The unique monolithic characteristics of rSLIR process can provide next-generation electronics fabrication method overcoming the limitation of conventional photolithography methods.

Digital Twin Technology of Human-Machine Integration in Cross-Belt Sorting System

The Chinese express delivery industry processes nearly 110 billion items in 2022,averaging an annual growth rate of 200%.Among the various types of sorting systems used for handling express items,cross-belt sorting systems stand out as the most crucial.However,despite their high degree of automation,the workload for operators has intensified owing to the surging volume of express items.In the era of Industry 5.0,it is imperative to adopt new technologies that not only enhance worker welfare but also improve the efficiency of cross-belt systems.Striking a balance between efficiency in handling express items and operator well-being is challenging.Digital twin technology offers a promising solution in this respect.A realization method of a human-machine integrated digital twin is proposed in this study,enabling the interaction of biological human bodies,virtual human bodies,virtual equipment,and logistics equipment in a closed loop,thus setting an operating framework.Key technologies in the proposed framework include a collection of heterogeneous data from multiple sources,construction of the relationship between operator fatigue and operation efficiency based on physiological measurements,virtual model construction,and an online optimization module based on real-time simulation.The feasibility of the proposed method was verified in an express distribution center.