Sparse Modal Decomposition Method Addressing Underdetermined Vortex-Induced Vibration Reconstruction Problem for Marine Risers

When investigating the vortex-induced vibration(VIV)of marine risers,extrapolating the dynamic response on the entire length based on limited sensor measurements is a crucial step in both laboratory experiments and fatigue monitoring of real risers.The problem is conventionally solved using the modal decomposition method,based on the principle that the response can be approximated by a weighted sum of limited vibration modes.However,the method is not valid when the problem is underdetermined,i.e.,the number of unknown mode weights is more than the number of known measurements.This study proposed a sparse modal decomposition method based on the compressed sensing theory and the Compressive Sampling Matching Pursuit(Co Sa MP)algorithm,exploiting the sparsity of VIV in the modal space.In the validation study based on high-order VIV experiment data,the proposed method successfully reconstructed the response using only seven acceleration measurements when the conventional methods failed.A primary advantage of the proposed method is that it offers a completely data-driven approach for the underdetermined VIV reconstruction problem,which is more favorable than existing model-dependent solutions for many practical applications such as riser structural health monitoring.

Study of Axial Vibration of a Motor-Compressor System Using Operational Modal Analysis

A case study of excessive vibration on a motor-compressor system is presented in this paper.After barely two months of operation,the reciprocating compressor motor’s routine monitoring revealed excessive axial vibration amplitude.For this reason,the Operational Modal Analysis(OMA)was carried out in order to identify the pri-mary cause.According to the investigation,one of the harmonic components which was 18 times the motor’s running speed matched with a resonance frequency of 112 Hz.According to OMA study,the motor was vibrating in torsional motion because the compressor’s load had stimulated the entire motor-compressor unit at this reso-nance frequency.The analysis also demonstrates the bulging effect of the motor shaft’s axial vibration on the motor’s endplate.

Exploration and Practice of Database System Course Based on KAPI Teaching Modality Under the Emerging Engineering Education

Nowadays,it is extremely urgent for the software engineering education to cultivate the knowledge and ability of database talents in the era of big data.To this end,this paper proposes a talent training teaching modality that integrates knowledge,ability,practice,and innovation(KAPI)for Database System Course.The teaching modality contains three parts:top-level design,course learning process,and course assurance and evaluation.The top-level design sorts out the core knowledge of the course and determines a mixed online and offline teaching platform.The course learning process emphasizes the correspondence transformation relationship between core knowledge points and ability enhancement,and the course is practiced in the form of experimental projects to finally enhance students’innovation consciousness and ability.The assurance and evaluation of the course are based on the outcome-based education(OBE)orientation,which realizes the objective evaluation of students’learning process and final performance.The teaching results of the course in the past 2 years show that the KAPI-based teaching modality has achieved better results.Meanwhile,students are satisfied with the evaluation of the modality.The teaching modality in this paper helps to stimulate students’initiatives,and improve their knowledge vision and practical ability,and thus helps to cultivate innovative and high-quality engineering talents required by the emerging engineering education.

Generalized load graphical forecasting method based on modal decomposition

In a“low-carbon”context,the power load is affected by the coupling of multiple factors,which gradually evolves from the traditional“pure load”to the generalized load with the dual characteristics of“load+power supply.”Traditional time-series forecasting methods are no longer suitable owing to the complexity and uncertainty associated with generalized loads.From the perspective of image processing,this study proposes a graphical short-term prediction method for generalized loads based on modal decomposition.First,the datasets are normalized and feature-filtered by comparing the results of Xtreme gradient boosting,gradient boosted decision tree,and random forest algorithms.Subsequently,the generalized load data are decomposed into three sets of modalities by modal decomposition,and red,green,and blue(RGB)images are generated using them as the pixel values of the R,G,and B channels.The generated images are diversified,and an optimized DenseNet neural network was used for training and prediction.Finally,the base load,wind power,and photovoltaic power generation data are selected,and the characteristic curves of the generalized load scenarios under different permeabilities of wind power and photovoltaic power generation are obtained using the density-based spatial clustering of applications with noise algorithm.Based on the proposed graphical forecasting method,the feasibility of the generalized load graphical forecasting method is verified by comparing it with the traditional time-series forecasting method.

Multimodal Data-Driven Reinforcement Learning for Operational Decision-Making in Industrial Processes

Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and operating conditions in the industrial processes, existing data-driven methods cannot effectively adjust the operational variables. In addition, multimodal data such as images, audio.

Utilization of biomarkers for the prognostic prediction of cardiac arrest survivors using a multi-modal approach

International guidelines for post-cardiac arrest care recommend using multi-modal strategies to avoid the withdrawal of life-sustaining therapy(WLST)in patients with the potential for neurological recovery.[1]However,a clear methodology for multi-modal approaches has yet to be developed.Neuron-specific enolase(NSE)is currently the only recommended biomarker,and the European Resuscitation Council(ERC)and the European SocietyofIntensiveCareMedicine(ESICM)have proposed a cutoff value of 60μg/L at 48 and/or 72 h after the return of spontaneous circulation(ROSC)as a multimodal prognostic tool for predicting poor neurological outcomes.

Low-frequency oscillation of train-network system considering traction power supply mode

The low-frequency oscillation(LFO)has occurred in the train-network system due to the introduction of the power electronics of the trains.The modeling and analyzing method in current researches based on electrified railway unilateral power supply system are not suitable for the LFO analysis in a bilateral power supply system,where the trains are supplied by two traction substations.In this work,based on the single-input and single-output impedance model of China CRH5 trains,the node admittance matrices of the train-network system both in unilateral and bilateral power supply modes are established,including three-phase power grid,traction transformers and traction network.Then the modal analysis is used to study the oscillation modes and propagation characteristics of the unilateral and bilateral power supply systems.Moreover,the influence of the equivalent inductance of the power grid,the length of the transmission line,and the length of the traction network are analyzed on the critical oscillation mode of the bilateral power supply system.Finally,the theoretical analysis results are verified by the time-domain simulation model in MATLAB/Simulink.

Modal Frequency Prediction of Chladni Patterns Using Machine Learning

The introduction of machine learning (ML) in the research domain is a new era technique. The machine learning algorithm is developed for frequency predication of patterns that are formed on the Chladni plate and focused on the application of machine learning algorithms in image processing. In the Chladni plate, nodes and antinodes are demonstrated at various excited frequencies. Sand on the plate creates specific patterns when it is excited by vibrations from a mechanical oscillator. In the experimental setup, a rectangular aluminum plate of 16 cm x 16 cm and 0.61 mm thickness was placed over the mechanical oscillator, which was driven by a sine wave signal generator. 14 Chladni patterns are obtained on a Chladni plate and validation is done with modal analysis in Ansys. For machine learning, a large number of data sets are required, as captured around 200 photos of each modal frequency and around 3000 photos with a camera of all 14 Chladni patterns for supervised learning. The current model is written in Python language and model has one convolution layer. The main modules used in this are Tensor Flow Keras, NumPy, CV2 and Maxpooling. The fed reference data is taken for 14 frequencies between 330 Hz to 3910 Hz. In the model, all the images are converted to grayscale and canny edge detected. All patterns of frequencies have an almost 80% - 99% correlation with test sample experimental data. This approach is to form a directory of Chladni patterns for future reference purpose in real-life application. A machine learning algorithm can predict the resonant frequency based on the patterns formed on the Chladni plate.

Analysis of Commuting Modal Shift in Consideration of Social Interaction of Consciousness for Environment

It is the matter for achievement of the low carbon transport system that the excessive use of private vehicles can be controlled appropriately.Not only improvement of service level of modes except private vehicle,but also consciousness for environmental problem of individual trip maker is important for eco-commuting promotion.On the other hand,consciousness for environment would be changed by influence of other person.Accordingly,it is aimed in the study that the structure of decision-making process for modal shift to the eco-commuting mode in the local city is described considering environmental consciousness and social interaction.For the purpose,the consciousness for the environment problem and the travel behavior of the commuter at the suburban area in the local city are investigated by the questionnaire survey.The covariance structure about the eco-consciousness is analyzed with the database of the questionnaire survey by structural equation modeling.As the result,it can be confirmed with the structural equation model that the individual environmental consciousness is strongly related with the intention of self-sacrifice and is influenced with the local interaction of the individual connections.On the other hand,the intention of modal shift for the commuting mode is analyzed with the database of the questionnaire survey.It can be found out that the environmental consciousness is not statistically significant for commuting mode choice with the present poor level of service of public transport.However,the intention of self-sacrifice for the prevention of the global warming is statistically confirmed as the factor of modal shift with the operation of eco-commuting bus service with the RP/SP integrated estimation method.As the result,the multi-agent simulation system with social interaction model for eco consciousness is developed to measure the effect of the eco-commuting promotion.For the purpose,the carbon dioxide emission is estimated based on traffic demand and road network condition in the traffic environment model.On the other hand,the relation between agents is defined based on the small world network.The proposed multi-agent simulation is applied to measure the effect of the eco-commuting promotion such as improvement of level of service on the public transport or education of eco-consciousness.The effect of the promotion plan can be observed with the proposed multi-agent system.Finally,it can be concluded that the proposed multi-agent simulation with social interaction for eco-consciousness is useful for planning of eco-commuting promotion.

Modal analysis of coupled vibration of belt drive systems

The modal method is applied to analyze coupled vibration of belt drive systems. A belt drive system is a hybrid system consisting of continuous belts modeled as strings as well as discrete pulleys and a tensioner arm. The characteristic equation of the system is derived from the governing equation. Numerical results demenstrate the effects of the transport speed and the initial tension on natural frequencies.

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

The problem of linear time-varying（LTV） system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the ＂frozen-time＂ assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stabilitypreserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system＇s stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam exper- imental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides anew way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model

The ChatGPT,a lite and conversational variant of Generative Pretrained Transformer 4(GPT-4)developed by OpenAI,is one of the milestone Large Language Models(LLMs)with billions of parameters.LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks,which profoundly impact various fields.This paper mainly discusses the future applications of LLMs in dentistry.We introduce two primary LLM deployment methods in dentistry,including automated dental diagnosis and cross-modal dental diagnosis,and examine their potential applications.Especially,equipped with a cross-modal encoder,a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations.We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application.While LLMs offer significant potential benefits,the challenges,such as data privacy,data quality,and model bias,need further study.Overall,LLMs have the potential to revolutionize dental diagnosis and treatment,which indicates a promising avenue for clinical application and research in dentistry.

ALGEBRAIC SEMANTICS OF SOME NORMAL QUANTIFIED MODAL SYSTEMS WITH THE BARCAN FORMULA

Let S be a propositional modal system and S~* be the quantification of S, then we can prove the algebraic semantic completeness theorem of the kind of Rasiowa-Sikorski for S~* by showing that S has the property (E)given in [1]. But except for a few cases, it is very difficult to show thara system S has the property (E). So for most quantified modal systems,

THE ALGEBRAIC AND KRIPKE'S SEMANTICS FOR QUANTIFIED MODAL SYSTEMS——THE CASE CONCERNING S5

In [1] and [2], the late modal logician E. J. Lemmon investigated the connexion between the algebraic and Kripke’s semantics for two series of modal propositional systems;he also pronounced in [1] that a third paper would be prepared to discuss the same connexion for quantifications of all the modal systems considered therein. Unfortunately, owing to his untimely death, this Paper did not come out. In this note we discuss the

MODAL SYNTHESIS METHOD FOR NORM COMPUTATION OF H_∞ DECENTRALIZED CONTROL SYSTEMS (II)

When using H_∞ techniques to design decentralized controllers for large systems, the whole system is divided into subsystems, which are analysed using H_∞ control theory before being recombined. An analogy was established with substructural analysis in structural mechanics, in which H_∞ decentralized control theory corresponds to substructural modal synthesis theory so that the optimal H_∞ norm of the whole system corresponds to the fundamental vibration frequency of the whole structure. Hence, modal synthesis methodology and the extended Wittrick_Williams algorithm were transplanted from structural mechanics to compute the optimal H_∞ norm of the control system. The orthogonality and the expansion theorem of eigenfunctions of the subsystems H_∞ control are presented in part (Ⅰ) of the paper. The modal synthesis method for computation of the optimal H_∞ norm of decentralized control systems and numerical examples are presented in part (Ⅱ).

THE MODAL FEATURES OF THE VIBRATION SYSTEMS OF THE WEAKLY- VISCOELASTIC MATERIAL STRUCTURES

This paper discusses the modal features of weakly-viscoelastic material structures both for single-modulus and multi-modulus materials. It is the eigenvalues of these structures that are the roots of a series of rational fraction polynomial equations. A theorem about the roots of these equations is proved in the paper. Based on it, some important conclusions about the modal features of the weakly viscoelastic material structures are given according to their dynamic behaviors.

Development of a software platform for bridge modal and damage identification based on ambient excitation

Modal and damage identification based on ambient excitation can greatly improve the efficiency of high-speed railway bridge vibration detection.This paper first describes the basic principles of stochastic subspace identification,peak-picking,and frequency domain decomposition method in modal analysis based on ambient excitation,and the effectiveness of these three methods is verified through finite element calculation and numerical simulation,Then the damage element is added to the finite element model to simulate the crack,and the curvature mode difference and the curvature mode area difference square ratio are calculated by using the stochastic subspace identification results to verify their ability of damage identification and location.Finally,the above modal and damage identification techniques are integrated to develop a bridge modal and damage identification software platform.The final results show that all three modal identification methods can accurately identify the vibration frequency and mode shape,both damage identification methods can accurately identify and locate the damage,and the developed software platform is simple and efficient.

An Analysis on the BRICS TALK from the Perspective of Modality System

The tenth BRICS Summit was held in Johannesburg,South Africa in 2018,which attracted attention from the whole world.Especially,it is of great importance to the BRICS nations,for it is the first ten years of BRICS,which marks its growth.Meanwhile,this year the Trump administration imposed more strict policies on protectionism.Particularly,the trade war between China and the United States is so intensive.China,as the core member of BRICS has great clout on BRICS,so the trade war between China and US also arouse a heat discussion among the BRICS nations.During the Summit,CGTN invited experts from the five BRICS nations to discuss related topics.Systemic Functional Linguistics,as one of the most influential branches of Linguistics,was firstly established by M.A.K.Halliday,and it has been greatly developed over the past decades.Interpersonal meaning is one of the three meta-functions,which focuses on how addressers use language to communicate,establish and maintain relationships with addressees,and express their opinions.Mood and modality are two basic resources to the realization of interpersonal meaning.Mood is used to represent the interaction of the language users,while modality reflects the utterers’attitudes and judgments.The paper discusses the three aspects of modality:modal operators,modal adjuncts and metaphors of modality.The paper applies the modality system to the analysis of the transcript of BRICS TALK.The author selects the experts’speeches on the trade war between China and US as the data.The research questions are as followed:(1)the characteristics of the modality resources appeared in their talks;(2)the BRICS nations attitudes and stance on trade war and America’s protectionism.

Multi-modal human-machine interface of a telerobotic system for remote arc welding

In telerobotic system for remote welding, human-machine interface is one of the most important factor for enhancing capability and efficiency. This paper presents an architecture design of human-machine interface for welding telerobotic system： welding multi-modal human-machine interface. The human-machine interface integrated several control modes, which are namely shared control, teleteaching, supervisory control and local autonomous control. Space mouse, panoramic vision camera and graphics simulation system are also integrated into the human-machine interface for welding teleoperation. Finally, weld seam tracing and welding experiments of U-shape seam are performed by these control modes respectively. The results show that the system has better performance of human-machine interaction and complexity environment welding.

Sensitivity analysis and dynamic modification of modal parameter in mechanical transmission system

Sensitivity analysis is one of the effective methods in the dynamic modification. The sensitivity of the modal parameters such as the natural frequencies and mode shapes in undamped free vibration of mechanical transmission system is analyzed in this paper.In particular,the sensitivities of the modal parameters to physical parameters of shaft system such as the inertia and stiffness are given.A calculation formula for dynamic modification is presented based on the analysis of modal parameter.With a mechanical transmission system as an example, the sensitivities of natural frequencies and modes shape are calculated and analyzed. Furthermore, the dynamic modification is also carried out and a good result is obtained.