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Code, data, and plots for a novel numerical approximation metric (i.e., FWD-GCA-based metric) of distortion in map projections.FWD-GCA-based metric was introduced in this study:Jin Yan, Tiansheng Xu, Ni Li, and Guanghong Gong. "Regression and Evaluation on a Forward Interpolated Version of the Great Circle Arcs���Based Distortion Metric of Map Projections" ISPRS International Journal of Geo-Information 10, no. 10: 649. https://doi.org/10.3390/ijgi10100649### Prerequisite ###Install dependencies in Julia:using PkgPkg.add("CSV")Pkg.add("DataFrames")Pkg.add("Proj4")Pkg.add("ForwardDiff")Install dependencies in Python:pip install numpy scipy matplotlib### Links to codes ###Julia code of GCA-based and the proposed FWD-GCA-based metrics:10.6084/m9.figshare.15022092Julia code of traditional differential-based metrics for more than 85 map projections:10.6084/m9.figshare.15022074Some auxiliary functions in Julia and Python for calculations, analyses, and plots.10.6084/m9.figshare.15022095### Links to data ###Approximately 200k sample points (CSV file) on sphere for evaluating differential-based, GCA, and FWD-GCA metrics:10.6084/m9.figshare.15022071Results (CSV format in ZIP files) of angular and area distortions for 200k sample points:[angular] 10.6084/m9.figshare.16681864[area] 10.6084/m9.figshare.16681867Coordinates of approximately 1 million 2-D sample points (CSV format in ZIP files) on projection plane for each map projection to draw plots:10.6084/m9.figshare.15035457### Links to plots ###Plots of area and angular distortions for all map projections we evaluated:[angular] 10.6084/m9.figshare.16681909[area] 10.6084/m9.figshare.16681912

Measuring, analyzing, reducing, and optimizing distortions in map projections is important in cartography. In this study, we introduced a novel image-based angular distortion metric based on the previous spherical great circle arcs-based metric. Images with predefined patterns were used to generate distorted images using mapping software. The generated distorted images with known patterns were then exploited to calculate the proposed angular distortion metric. The mapping software performed the underlying transformation of map projections. Therefore, there was no direct explicit dependence on the forward equations of the map projections in our proposed metric. However, there were fairly large computation errors in the ordinary image-based approach without special correction. To reduce the error, we introduced surface-fitting-based noise reduction in our approach. We established and solved systems of linear equations based on bivariate polynomial functions in the process of noise reduction. Sufficient experiments were made to validate the proposed image-based metric and the accompanying noise reduction approach. In the experiment, the NASA G.Projector was employed as the mapping software for evaluating more than 200 map projections. Experimental results demonstrated that the proposed image-based approach and surface fitting-based noise reduction are feasible and practical for the evaluation of the angular distortion of map projections.

In this paper, we propose an optimized modeling method based on hierarchical reconstruction for 3D building point cloud. In contrast to existing approaches, this method can make full use of the geometric information of the original building facade point cloud and roof point cloud, which will provide a more complete description for the model of buildings. Firstly, we segment and extract the facade and the roof point cloud of the building based on the difference in planar slices. Further, we use the P-Linkage algorithm to segment the facade point cloud into planar patches, and cluster the planar patches to layer the facade point cloud. Therefore, we reduce the complexity of reconstruction from three-dimensional to two-dimensional. Then we reconstruct the building facade based on the hierarchical reconstruction method and the building roof based on the block reconstruction method. Finally, we merge the facade model and roof model and clip unnecessary polygons, leading to the final model. We experiment with different data and the results compared with the commercial modeling software show that the method is feasible and can improve the three-dimensional building modeling effect.

Automatic recognition methods for non-stationary EEG data collected from EEG sensors play an essential role in neurological detection. The integrative approaches proposed in this study consists of Symlet wavelet processing, a gradient boosting machine, and a grid search optimizer for a three-level classification scheme for normal subjects, intermittent epilepsy, and continuous epilepsy. Fourth-order Symlet wavelets were adopted to decompose the EEG data into five time-frequency sub-bands, whose statistical features were computed and used as classification features. The grid search optimizer was used to automatically find the optimal parameters for training the classifier. The classification accuracy of the gradient boosting machine was compared with that of a support vector machine and a random forest classifier constructed according to previous descriptions. Multiple-index were used to evaluate the Symlet wavelet transform-gradient boosting machine-grid search optimizer classification scheme, which provided better classification accuracy and detection effectiveness than has recently reported in other work on three-level classification of EEG data.

The development process of a complex project involves many tasks, organizations and persons. Therefore, how to assign tasks reasonably to the corresponding organizations or persons will substantially affect the project development results. Based on the summary of the main factors that influence the decision-making behaviors, this paper analyzes the characteristics of tasks and persons. Firstly, the importance of tasks is defined and prioritized. Secondly, this paper identified the cooperative inertia factors. Then the person cooperation model is established. Furthermore, the task assignment algorithm based on the organizational evolution model is proposed. Finally, the simulation results demonstrate the rationality of the proposed task assignment model. It can be employed to perform the quantitative analysis of tasks assignment and help managers make decisions.

This paper presents a modeling framework for product lifecycle information. Although being widely used in enterprises’ virtual product data management, Product Lifecycle Management (PLM) systems are unable to manage the modeling and simulation aspects of virtual products. To reinforce the sharing and management of the product lifecycle information, especially the simulation data, a product’s four-dimensional (4D) view model (PLIM) is established, which includes geometry view, task view, virtual prototype system view and lifecycle view. To provide efficient and effective simulation information, the prototype system view is then studied in detail. Finally, to validate the feasibility of the modeling framework, a prototype system is developed based on an application example, with the demonstration of 4D product lifecycle information model (PLIM).

Purpose – The purpose of this paper is to introduce a new method of ontology‐based digital product data exchange. The digital product data are enriched with virtual prototype (VP) model information and the designed exchange process is discussed. Additionally, an algorithm enabling the ontology‐based data exchange method among missile guide systems is proposed and analyzed.Design/methodology/approach – Semantic sevice‐oriented architecture (SSOA) is an innovative integration architecture for digital product information integration and process integration. In digital product ontology layer of SSOA, a new method of ontology‐based product data exchange is proposed. Compared with traditional information exchange, the method adds the VP's information to general digital products' information. The VP's information is described by building VP static structure ontology and dynamic behavior ontology. The exchange process of the novel method is discussed in detail. Finally, an example illustrating the data exchange a...

How to predict and change organizational performance has been a focus problem drawing economists and managers’ attention for a long time. The Big-five Factor theory is very popular among psychologists and ABMS (Agent-Based Modeling and Simulation) method is widely used in Systems Science. By integrating Big-five Factor and ABMS, we proposed a model to predict organizational performance. Fuzzy rules were built up to describe one-on-one cooperation in the five dimensions of personalities and an unsymmetrical network model was established to depict cooperation relationships between team members. What is more, a series of cases was studied and the result was proved to be rational.

One of the most important problems of airplane infrared simulation is to establish the simulation model accurately based on real-time status. This paper analyses the three main sources of infrared signatures in airplane: airplane-skin, nozzle components and exhaust plume. By reckoning environment radiation, aerodynamic heating, heat transferring and hot engine casing principle, a synthetic simulation method was used, especially a new infrared engine model for airplane was firstly proposed with airplane's working status as the input. Then atmospheric transmittance is analyzed through Modetran4 with various influential factors such as atmospheric aerosol and geometric path considered. Finally the simulation results obtained have been analyzed with respect to different work status and view angle parameters, which will have an important effect on infrared image simulation system in military simulation system.

In this paper, Computer Generated Forces (CGF) behavior modeling was studied from the viewpoint of associate data mining, for the large quantity of data, rules and models in its process. Because CGF behavior models data source was the combination of staticDB and dynamic data stream, the paper advanced the methods of item truncation and aim-pattern restriction. Through pretreatment, coding, searching frequent pattern, generating associate rules of the CGF behavior modeling data, then decision could be made according as these rules. Application of the two methods improves on the classical aprior algorithm, also improves efficiency of searching frequent items and credibility of CGF's decision. Finally, the application of associate rules mining in air-combat is studied in detail. As the simulation shows, comparing with the traditional matching-rule decision, associate rule mining has higher efficiency on condition with guaranteeing reliability of decision.

Grid partition of geometry model in finite element analysis results in massive redundant geometry points, comprising of point cloud, which is tend to be rendered in various aspects to analyze result in the post-processing. In order to deal with point cloud in real-time application, a novel algorithm is presented to simplify the redundant data and reconstruct the surface of geometry model from point cloud. First, points inside the model is removed by using element connection flag to reduce geometry data, and then local coplanar points is linked to a contour to construct a surface element to reduce geometry points further, finally the constructed surface elements are divide into different groups by using topology relationship to build up surfaces of geometry model. The point cloud of finite element analysis result is greatly reduced and geometry model surface is accurately reconstructed based on reduced point cloud by using the algorithm.

Ant colony optimization(ACO) provides an effective way to solve combinatorial optimization problem. However, with the complexity of the problem increasing, the ACO algorithm needs considerable computational time and resources to improve the good quality of solution, and this rarely satisfies the requirement of real-time computing in M&S (Modeling and Simulation) area. Parallel implementation of ACO can reduce the computational time obviously for the large scale combinatorial optimization problem, and much of the previous work in this field focuses on parallel implementation using MPI which is executed on clusters. Meanwhile, great emphasis is placed on multi-core computing technology with the development of multi-processor architecture and multi-core architecture. A new parallel ant colony optimization (PACO) algorithm is proposed, which applies two kinds of typical multi-core computing technologies, the well-known OpenMP and the recently introduced TBB (Threading Building Blocks) library by Intel Corporation, to solve target assignment problem(TAP). Effectiveness and efficiency of proposed algorithm is validated by studying the convergence speed, problem size scalability and thread size scalability of it.

The Model Driven Architecture (MDA) concept and key technology were discussed, including modeling technology, model transformation technology and model template. A MDA framework using UML for Platform Independent Model (PIM) and XML for Platform Specific Model (PSM) was proposed for simulation system development. The main technology of the MDA framework was introduced, which included PIM modeling guideline, PIM validity checking, PSM template, corresponding relation, symbol dictionary, CODE template and other key technologies. A MDA tool oriented simulation system was built based on the MDA framework. The tool has realized MDA process, where models in simulation system representing static and dynamic behaviors could be transformed from PIM to codes of different platforms. The MDA tool has been used in the transportation system simulation, the simulation models of different MDA periods are given, and the feasibility of applying MDA tool in the simulation system model development is verified.

A dasiageneralized optimal game theorypsila (GOGT) is proposed for the first time to establish special modeling and nonlinear decision-making, some principles and algorithms are also deduced from GOGT model. Junior and senior models derived from the main principles are respectively used to simulate models with multi-granularities and complicated decision-making problems. Crucial equation appending random disturbance holds the uniform scenario of Junior. A virtual 3D system of dynamic stars, moon and their mirror images in water is presented according to junior model. An armor CGF with multi-granularities is provided to testify the feasibility of senior model. Damage-summarizing and dynamic algorithm of aggregation is discussed using generalized mathematics expectation and fuzzy mathematics. Finally, an intelligent observer in large-scale 3D battlefield was designed using synthetic model. Quantitative parameters of nature, sense and complexity were presented The weighted 9-observational mode decision-making equation and observational target competition method are all calculated by advanced GOG models combining virtual and acoustical weights.

Based on musical acoustics, psychoacoustics, architectural acoustics, room acoustics and digital audio technology, Using geometrics and psychoacoustics, an underline sound remodeling method was proposed by compressor, amplifier, exciter and equalizer, etc. Frequency spectrum analyzing was realized by FFT discrete transform and Hamming window function. Compressor ratio was calculated by advanced algorithm in large scaled sound clips. Equivalent absorption coefficient algorithm optimized complications of material absorption coefficients. Integral weights were calculated in 24 octave band of audible domain which contributed to the balanced algorithm reported for the first time. RT time (reverberation time) was computed by the equivalent absorption coefficient with advanced Sabine function. Frequency spectrum and formant data samples were summarized according to different state variables, RT time and compressor ratio. A BP network was realized by several equalizer parameters adjusting. 20 groups of top 3 relative formants (60 data) corresponding to different thrusts of motor engines were proposed for the net training and the output layer of the BP network was realized by 3, 4 and 6 nerval cells. Network with 4 nerval cells was analyzed to be effective in both runtime spectrum curve matching and computing efficiency.