Augmented Industrial Data-Driven Modeling Under the Curse of Dimensionality

The curse of dimensionality refers to the problem o increased sparsity and computational complexity when dealing with high-dimensional data.In recent years,the types and vari ables of industrial data have increased significantly,making data driven models more challenging to develop.To address this prob lem,data augmentation technology has been introduced as an effective tool to solve the sparsity problem of high-dimensiona industrial data.This paper systematically explores and discusses the necessity,feasibility,and effectiveness of augmented indus trial data-driven modeling in the context of the curse of dimen sionality and virtual big data.Then,the process of data augmen tation modeling is analyzed,and the concept of data boosting augmentation is proposed.The data boosting augmentation involves designing the reliability weight and actual-virtual weigh functions,and developing a double weighted partial least squares model to optimize the three stages of data generation,data fusion and modeling.This approach significantly improves the inter pretability,effectiveness,and practicality of data augmentation in the industrial modeling.Finally,the proposed method is verified using practical examples of fault diagnosis systems and virtua measurement systems in the industry.The results demonstrate the effectiveness of the proposed approach in improving the accu racy and robustness of data-driven models,making them more suitable for real-world industrial applications.

Three-Dimensional TIN Algorithm for Digital Terrain Modeling

The problem of taking an unorganized point cloud in 3D space and fitting a polyhedral surface to those points is both important and difficult. Aiming at increasing applications of full three dimensional digital terrain surface modeling, a new algorithm for the automatic generation of three dimensional triangulated irregular network from a point cloud is pro- posed. Based on the local topological consistency test, a combined algorithm of constrained 3D Delaunay triangulation and region-growing is extended to ensure topologically correct reconstruction. This paper also introduced an efficient neighbor- ing triangle location method by making full use of the surface normal information. Experimental results prove that this algo- rithm can efficiently obtain the most reasonable reconstructed mesh surface with arbitrary topology, wherein the automati- cally reconstructed surface has only small topological difference from the true surface. This algorithm has potential applica- tions to virtual environments, computer vision, and so on.

Three-dimensional numerical modeling of gravity anomalies based on Poisson equation in spacewavenumber mixed domain

In gravity-anomaly-based prospecting, the computational and memory requirements for practical numerical modeling are potentially enormous. Achieving an efficient and precise inversion for gravity anomaly imaging over large-scale and complex terrain requires additional methods. To this end, we have proposed a new topography-capable By performing a two-dimensional Fourier transform in the horizontal directions, threedimensional partial differential equations in the spatial domain were transformed into a group of independent, one-dimensional differential equations engaged with different wave numbers. These independent differential equations are highly parallel across different wave numbers. differential equations with different wave numbers, and the efficiency of solving fixedbandwidth linear equations was further improved by a chasing method. In a synthetic test, a prism model was used to verify the accuracy and reliability of the proposed algorithm by comparing the numerical solution with the analytical solution. We studied the computational precision and efficiency with and without topography using different Fourier transform methods. The results showed that the Guass-FFT method has higher numerical precision, while the standard FFT method is superior, in terms of computation time, for inversion and quantitative interpretation under complicated terrain.

Three-dimensional cell culture systems as an in vitro platform for cancer and stem cell modeling

Three-dimensional(3D)culture systems are becoming increasingly popular due to their ability to mimic tissue-like structures more effectively than the monolayer cultures.In cancer and stem cell research,the natural cell characteristics and architectures are closely mimicked by the 3D cell models.Thus,the 3D cell cultures are promising and suitable systems for various proposes,ranging from disease modeling to drug target identification as well as potential therapeutic substances that may transform our lives.This review provides a comprehensive compendium of recent advancements in culturing cells,in particular cancer and stem cells,using 3D culture techniques.The major approaches highlighted here include cell spheroids,hydrogel embedding,bioreactors,scaffolds,and bioprinting.In addition,the progress of employing 3D cell culture systems as a platform for cancer and stem cell research was addressed,and the prominent studies of 3D cell culture systems were discussed.

Three-dimensional fuzzy logic system for process modeling and control

The traditional fuzzy logic system （FLS） can only model and control the process in two-dimensional nature. Many of real-world systems are of multidimensional features, such as, thermal and fluid processes with spatiotemporal dynamics, biological systems, or decision-making processes that contain stochastic and imprecise uncertainties. These types of systems are difficult for the traditional FLS to model and control because they require a third dimension for spatial or probabilistic information. The type-2 fuzzy set provides the possibility to develop a three-dimensional fuzzy logic system for modeling and controlling these processes in three-dimensional nature.

In vitro three-dimensional cancer metastasis modeling:Past,present,and future

Metastasis is the leading cause of most cancer deaths, as opposed to dysregulated cell growth of the primary tumor. Molecular mechanisms of metastasis have been studied for decades and the findings have evolved our understanding of the progression of malignancy. However, most of the molecular mechanisms fail to address the causes of cancer and its evolutionary origin, demonstrating an inability to find a solution for complete cure of cancer. After being a neglected area of tumor biology for quite some time, recently several studies have focused on the impact of the tumor microenvironment on cancer growth. The importance of the tumor microenvironment is gradually gaining attention, particularly from the per- spective of biophysics. In vitro three-dimensional （3-D） metastatic models are an indispensable platform for investigating the tumor microenvironment, as they mimic the in vivo tumor tissue. In 3-D metastatic in vitro models, static factors such as the mechanical properties, biochemical factors, as well as dynamic factors such as cell-cell, cell-ECM interactions, and fluid shear stress can be studied quantitatively. With increasing focus on basic cancer research and drug development, the in vitro 3-D models offer unique advantages in fundamental and clinical biomedical studies.

Research on the Three-dimensional Modeling and Optimization of a Virtual Tower Crane Based on 3DS Max, Solidworks and EON Professional

Three-dimensional modeling of virtual hoisting machinery is the critical works to structure the system of virtual construction, and the foundation to realize intelligent and interactive virtual hoisting. Aimed at enhancing the requests of image quality and stability of the virtual construction scene, taking a tower crane for example. We studied the technology of three-dimensional modeling and optimization of a virtual tower crane, and a method named two-stage model optimization was put forward. This depended on the modeling stage using Solidworks and 3DS Max and the performance optimization stage in EON. The practice of software development indicates that the proposed methods of three-dimensional modeling and optimization could satisfy the performance request of virtual construction system and be popularized to other virtual system.

Three-Dimensional Pressure Modeling of South China Sea in High Temperature High Pressure Field

Yingqiong basin is a proven hydrocarbon-rich basin in South China Sea. There are a number of large exploration prospects in high temperature and over-pressured formations, especially in Yacheng Block of Qiongdongnan basin and Dongfang District of Yinggehai Basin. Owing to good exploration situation, we have already achieved proven geological reserves over 1000 × 108 m3. In recent years, a few drilled HPHT wells have confirmed that pressure predicted by conventional method was wildly inaccurate. From the view of regional stress, the accuracy of the pressure prediction will be substantially improved. Accurate pressure prediction and three-dimensional pressure modeling which are based on three-dimensional lithology modeling are the cornerstone to achieve exploration breakthrough. In this paper, the use of the triple constraint trend lithology model broke through the traditional method of seismic lithology prediction only by means of impedance threshold value. Compared with actual data and prediction, it confirms that three-dimensional pressure modeling method is reasonable and effective, and has a wide prospect of application.

Numerical Investigation of Thermal Behavior of CNC Machine Tool and Its Effects on Dimensional Accuracy of Machined Parts

The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally induced positioning error compensation remains the most effective and practical method in this context. However, the efficiency of the compensation process depends on the quality of the model used to predict the thermal errors. The model should consistently reflect the relationships between temperature distribution in the MT structure and thermally induced positioning errors. A judicious choice of the number and location of temperature sensitive points to represent heat distribution is a key factor for robust thermal error modeling. Therefore, in this paper, the temperature sensitive points are selected following a structured thermomechanical analysis carried out to evaluate the effects of various temperature gradients on MT structure deformation intensity. The MT thermal behavior is first modeled using finite element method and validated by various experimentally measured temperature fields using temperature sensors and thermal imaging. MT Thermal behavior validation shows a maximum error of less than 10% when comparing the numerical estimations with the experimental results even under changing operation conditions. The numerical model is used through several series of simulations carried out using varied working condition to explore possible relationships between temperature distribution and thermal deformation characteristics to select the most appropriate temperature sensitive points that will be considered for building an empirical prediction model for thermal errors as function of MT thermal state. Validation tests achieved using an artificial neural network based simplified model confirmed the efficiency of the proposed temperature sensitive points allowing the prediction of the thermally induced errors with an accuracy greater than 90%.

Locating Error Considering Dimensional Errors Modeling for Multistation Manufacturing System

Multistation machining process is widely applied in contemporary manufacturing environment. Modeling of variation propagation in multistation machining process is one of the most important research scenarios. Due to the existence of multiple variation streams, it is challenging to model and analyze variation propagation in a multi-station system. Current approaches to error modeling for multistation machining process are not explicit enough for error control and ensuring final product quality. In this paper, a mathematic model to depict the part dimensional variation of the complex multistation manufacturing process is formulated. A linear state space dimensional error propagation equation is established through kinematics analysis of the influence of locating parameter variations and locating datum variations on dimensional errors, so the dimensional error accumulation and transformation within the multistation process are quantitatively described. A systematic procedure to build the model is presented, which enhances the way to determine the variation sources in complex machining systems. A simple two-dimensional example is used to illustrate the proposed procedures. Finally, an industrial case of multistation machining part in a manufacturing shop is given to testify the validation and practicability of the method. The proposed analytical model is essential to quality control and improvement for multistation systems in machining quality forecasting and design optimization.

Modeling and validating three dimensional human normal cervix and cervical cancer tissues in vitro

The use of three dimensional in vitro systems in cancer research is a promising path for developing effective anticancer therapies.The aim of this study was to engineer a functional 3-D in vitro model of normal and cancerous cervical tissue.Normal epithelial and immortalized cervical epithelial carcinoma cell lines were used to construct 3-D artificial normal cervical and cervical cancerous tissues.De-epidermised dermis（DED） was used as a scaffold for both models.Morphological analyses were conducted by using hematoxylin and eosin staining and characteristics of the models were studied by analyzing the expression of different structural cytokeratins and differential protein marker MAX dimerisation protein 1（Mad1） using immunohistochemical technique.Haematoxylin and eosin staining results showed that normal cervical tissue had multi epithelial layers while cancerous cervical tissue showed dysplastic changes.Immunohistochemistry staining revealed that for normal cervix model cytokeratin 10 was expressed in the upper stratified layer of the epithelium while cytokeratin 5 was expressed mainly in the middle and basal layer.Cytokeratin 19 was weakly expressed in a few basal cells.Cervical cancer model showed cytokeratin 19 expression in different epithelial layers and weak or no expression for cytokeratin 5 and cytokeratin 10.Madl expression was detected in some suprabasal cells.The 3-D in vitro models showed stratified epithelial layers and expressed the same types and patterns of differentiation marker proteins as seen in corresponding in vivo tissue in either normal cervical or cervical cancerous tissue.These findings imply that they can serve as functional normal and cervical cancer models.

Research on dynamic updating of three dimensional geological modeling based on the OO-Solid model

The dynamic updating of the model included: the change of space border,addi- tion and reduction of spatial component (disappearing,dividing and merging),the change of the topological relationship and synchronous dynamic updating of database.Firstly, arming at the deficiency of OO-Solid model in the aspect of dynamic updating,modeling primitives of OO-Solid model were modified.And then the algorithms of dynamic updating of 3D geological model with the node data,line data or surface data change were dis- cussed.The core algorithms was done by establishing space index,following the way of facing the object from bottom to top,namely the dynamic updating from the node to arc, and then to polygon,then to the face of the component and finally to the geological object. The research has important theoretical and practical values in the field of three dimen- sional geological modeling and is significant in the field of mineral resources.

Model-Free Feature Screening via Maximal Information Coefficient (MIC) for Ultrahigh-Dimensional Multiclass Classification

It is common for datasets to contain both categorical and continuous variables. However, many feature screening methods designed for high-dimensional classification assume that the variables are continuous. This limits the applicability of existing methods in handling this complex scenario. To address this issue, we propose a model-free feature screening approach for ultra-high-dimensional multi-classification that can handle both categorical and continuous variables. Our proposed feature screening method utilizes the Maximal Information Coefficient to assess the predictive power of the variables. By satisfying certain regularity conditions, we have proven that our screening procedure possesses the sure screening property and ranking consistency properties. To validate the effectiveness of our approach, we conduct simulation studies and provide real data analysis examples to demonstrate its performance in finite samples. In summary, our proposed method offers a solution for effectively screening features in ultra-high-dimensional datasets with a mixture of categorical and continuous covariates.

Model-Free Ultra-High-Dimensional Feature Screening for Multi-Classified Response Data Based on Weighted Jensen-Shannon Divergence

In ultra-high-dimensional data, it is common for the response variable to be multi-classified. Therefore, this paper proposes a model-free screening method for variables whose response variable is multi-classified from the point of view of introducing Jensen-Shannon divergence to measure the importance of covariates. The idea of the method is to calculate the Jensen-Shannon divergence between the conditional probability distribution of the covariates on a given response variable and the unconditional probability distribution of the covariates, and then use the probabilities of the response variables as weights to calculate the weighted Jensen-Shannon divergence, where a larger weighted Jensen-Shannon divergence means that the covariates are more important. Additionally, we also investigated an adapted version of the method, which is to measure the relationship between the covariates and the response variable using the weighted Jensen-Shannon divergence adjusted by the logarithmic factor of the number of categories when the number of categories in each covariate varies. Then, through both theoretical and simulation experiments, it was demonstrated that the proposed methods have sure screening and ranking consistency properties. Finally, the results from simulation and real-dataset experiments show that in feature screening, the proposed methods investigated are robust in performance and faster in computational speed compared with an existing method.

A three-dimensional semi-implicit unstructured grid finite volume ocean model

A new three-dimensional semi-implicit finite-volume ocean model has been developed for simulating the coastal ocean circulation, which is based on the staggered C-unstructured non-orthogonal grid in the hor- izontal direction and z-level grid in the vertical direction. The three-dimensional model is discretized by the semi-implicit finite-volume method, in that the free-surface and the vertical diffusion are semi-implicit, thereby removing stability limitations associated with the surface gravity wave and vertical diffusion terms. The remaining terms in the momentum equations are discretized explicitly by an integral method. The partial cell method is used for resolving topography, which enables the model to better represent irregular topography. The model has been tested against analytical cases for wind and tidal oscillation circulation, and is applied to simulating the tidal flow in the Bohal Sea. The results are in good agreement both with the analytical solutions and measurement results.

A Novel Three-Dimensional Mouse Embryonic Implantation Model In Vitro

To regenerate three-dimensional endometrium in vitro as a novel model for studying the mechanism of implantation of embryos, the luminal epithelial cells and stromal cells of the rabbit uterus were separated and cultured in vitro. The type Ⅰ mouse tail collagen was used as scaffolding material. The stromal cells were inoculated in the type I mouse tail collagen, and the luminal epithelial cells were inoculated on the type i mouse tall collagen to regenerate the endometrium in vitro. The regenerated endometrium was cultured in DMEM-F/12 media containing 100 nmol L^-1 progesterone, 10 nM β-estradiol, and 10% fetal bovine serum （FBS） for 3 d. The media were then replaced with CZB containing 100 nM progesterone, 10 nmol L-1 β-estradiol, and 10% FBS, and the mouse blastulas were co-cultured with it. The results of scanning electronic micrography showed that the epithelial cells on the surface of the reconstructed endometrium were covered with numerous slender microvilli and some epithelial cells protruded pinopodes. After culturing for 12 h with the mouse blastula, the shedding, attachment, and implantation of the blastula were observed. The blastula can escape from zona pellucida and attach to the three-dimensional endometrium and is then implanted into it. This study showed that the reconstructed three-dimensional endometrium can serve as a robust embryo implantation model in vitro.

The study on three-dimensional numerical model and fronts of the Jiulong Estuary and the Xiamen Bay

Applying the methods of on-site observation and dynamic model, the research on the fronts at the Jiulong Estuary has been carried out, during which spatial and temporal distribution, dynamic characteristics and formation mechanism of salinity fronts are analyzed and discussed. The research shows that the estuarine fronts mainly lie in the area from the Jiyu Islet to the Haimen Island, outside of Yuweizai to Hulishan cross-section, the near coast of Yuweizai and the south of the Songyu-Gulangyu Channel. The fronts in the former two regions are formed directly by plume, while the one near the coast of Yuweizai is a tidal intrusion front caused by flood current and the one at the south of the Songyu-Gulangyu Channel is the result of current shear transformation. Under normal circumstances, fresh water of the Jiulong River mainly influences the inside of the Xiamen Bay, and when it is in typhoon seasons, plume front can affect the Taiwan Strait and has an effect on the biogeochemical Drocesses in the strait.

A DESIGN OF THREE-DIMENSIONAL SPATIAL DATA MODEL AND ITS DATA STRUCTURE IN GEOLOGICAL EXPLORATION ENGINEERING

The key to develop 3-D GISs is the study on 3-D data model and data structure. Some of the data models and data structures have been presented by scholars. Because of the complexity of 3-D spatial phenomenon, there are no perfect data structures that can describe all spatial entities. Every data structure has its own advantages and disadvantages. It is difficult to design a single data structure to meet different needs. The important subject in the3-D data models is developing a data model that has integrated vector and raster data structures. A special 3-D spatial data model based on distributing features of spatial entities should be designed. We took the geological exploration engineering as the research background and designed an integrated data model whose data structures integrats vector and raster data byadopting object-oriented technique. Research achievements are presented in this paper.

Mechanism Modeling and Simulation Based on Dimensional Deviation

To analyze the effects on motion characteristics of mechanisms of dimensional variations, a study on random dimensional deviation generation techniques for 3D models on the basis of the present mechanical modeling software was carried out, which utilized the redeveloped interfaces provided by the modeling software to develop a random dimensional deviation generation system with certain probability distribution characteristics. This system has been used to perform modeling and simulation of the specific mechanical time delayed mechanism under multiple deviation varieties, simulation results indicate the dynamic characteristics of the mechanism are influenced significantly by the dimensional deviation in the tolerance distribution range, which should be emphasized in the design.

A Three-Dimensional Water Quality Model and Its Application to Jiaozhou Bay, China

A three-dimensional coupled physical and water quality model was developed and applied to the Jiaozhou Bay to study water quality involving nutrients, biochemical oxygen demand, dissolved oxygen, and phytoplankton that are closely related to eutrophication process. The physical model is a modified ECOM-si version with inclusion of flooding/draining processes over the intertidal zone. The water quality model is based on WASP5 which quantifies processes governing internal nutrients cycling, dissolved oxygen balance and phytoplankton growth. The model was used to simulate the spatial distribution and the temporal variation of water quality in the Jiaozhou Bay for the period of May 2005 to May 2006. In addition, the effect of reduction of riverine nutrients load was simulated and evaluated. The simulated results show that under the influence of nutrients discharged from river, the concentrations of nutrients and phytoplankton were higher in the northwest and northeast of the bay, and decreased from the inner bay to the outer. Affected by strong tidal mixing, the concentrations of all state variables were vertically homogeneous except in the deeper regions where a small gradient was found. Obvious seasonal variation of phytoplankton biomass was found, which exhibited two peaks in March and July, respectively. The variation of riverine waste loads had remarkable impact on nutrients concentration in coastal areas, but slightly altered the distribution in the center of the bay.