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"abstract": "With recent technological advances, graphics processing units (GPUs) are providing increasingly higher performance with improvement programmability. This paper investigates NVIDIA’s CUDA technology that enables data mining algorithm be parallelized effectively on GPU. The proposed algorithm exploits the computational power and the memory hierarchy of GPUs, using the shared memory to store frequently accessed data. Experimental results indicate that the speed of the computation through the GPU is considerably faster than through the CPU.",
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"abstractUrl": "/proceedings-article/rtss/2015/9507a273/12OmNqJZgBC",
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{
"abstractType": "Regular",
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{
"id": "proceedings/icpads/2011/4576/0/4576a316",
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"abstractUrl": "/proceedings-article/icpads/2011/4576a316/12OmNAnMuKm",
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{
"id": "proceedings/hpcc-icess/2012/4749/0/4749a453",
"title": "An Effective Approach for Implementing Sparse Matrix-Vector Multiplication on Graphics Processing Units",
"doi": null,
"abstractUrl": "/proceedings-article/hpcc-icess/2012/4749a453/12OmNBKEynM",
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{
"id": "proceedings/saahpc/2011/4448/0/4448a068",
"title": "Application of Graphics Processing Units (GPUs) to the Study of Non-linear Dynamics of the Exciton Bose-Einstein Condensate in a Semiconductor Quantum Well",
"doi": null,
"abstractUrl": "/proceedings-article/saahpc/2011/4448a068/12OmNBhpS80",
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"title": "Application Accelerators in High-Performance Computing, Symposium on",
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{
"id": "proceedings/icm/2011/4522/2/4522b396",
"title": "Numerical Simulation and Experimental Test on Muzzle Brake Efficiency",
"doi": null,
"abstractUrl": "/proceedings-article/icm/2011/4522b396/12OmNqIQSdz",
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"id": "proceedings/icm/2011/4522/2",
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{
"id": "proceedings/ispdc/2010/4120/0/4120a071",
"title": "Parallel Cycle Based Logic Simulation Using Graphics Processing Units",
"doi": null,
"abstractUrl": "/proceedings-article/ispdc/2010/4120a071/12OmNvnOwu9",
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"id": "proceedings/ispdc/2010/4120/0",
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"__typename": "RecommendedArticleType"
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{
"id": "proceedings/hpcmp-ugc/2009/3946/0/3946a278",
"title": "Ocean Wave Prediction Using Large-Scale Phase-Resolved Computations",
"doi": null,
"abstractUrl": "/proceedings-article/hpcmp-ugc/2009/3946a278/12OmNxZBSCY",
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"id": "proceedings/hpcmp-ugc/2009/3946/0",
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"abstract": "Dynamic programming (DP) is an important computational method for solving a wide variety of discrete optimization problems such as scheduling, string editing, packaging, and inventory management. In general, DP is classified into four categories based on the characteristics of the optimization equation. Because applications that are classified in the same category of DP have similar program behavior, the research community has sought to propose general solutions for parallelizing each category of DP. However, most existing studies focus on running DP on CPU-based parallel systems rather than on accelerating DP algorithms on the graphics processing unit (GPU). This paper presents the GPU acceleration of an important category of DP problems called nonserial polyadic dynamic programming (NPDP). In NPDP applications, the degree of parallelism varies significantly in different stages of computation, making it difficult to fully utilize the compute power of hundreds of processing cores in a GPU. To address this challenge, we propose a methodology that can adaptively adjust the thread-level parallelism in mapping a NPDP problem onto the GPU, thus providing sufficient and steady degrees of parallelism across different compute stages. We realize our approach in a real-world NPDP application -- the optimal matrix parenthesization problem. Experimental results demonstrate our method can achieve a speedup of 13.40 over the previously published GPU algorithm.",
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{
"abstractType": "Regular",
"content": "Dynamic programming (DP) is an important computational method for solving a wide variety of discrete optimization problems such as scheduling, string editing, packaging, and inventory management. In general, DP is classified into four categories based on the characteristics of the optimization equation. Because applications that are classified in the same category of DP have similar program behavior, the research community has sought to propose general solutions for parallelizing each category of DP. However, most existing studies focus on running DP on CPU-based parallel systems rather than on accelerating DP algorithms on the graphics processing unit (GPU). This paper presents the GPU acceleration of an important category of DP problems called nonserial polyadic dynamic programming (NPDP). In NPDP applications, the degree of parallelism varies significantly in different stages of computation, making it difficult to fully utilize the compute power of hundreds of processing cores in a GPU. To address this challenge, we propose a methodology that can adaptively adjust the thread-level parallelism in mapping a NPDP problem onto the GPU, thus providing sufficient and steady degrees of parallelism across different compute stages. We realize our approach in a real-world NPDP application -- the optimal matrix parenthesization problem. Experimental results demonstrate our method can achieve a speedup of 13.40 over the previously published GPU algorithm.",
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}
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"fno": "4576a096",
"keywords": [
"Dynamic Programming",
"GPU",
"Parallel Computing",
"Parallelism",
"Optimization"
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{
"affiliation": null,
"fullName": "Chao-Chin Wu",
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{
"affiliation": null,
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{
"affiliation": null,
"fullName": "Heshan Lin",
"givenName": "Heshan",
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{
"affiliation": null,
"fullName": "Wu-chun Feng",
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{
"id": "proceedings/icpads/2012/4903/0/4903a045",
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{
"id": "proceedings/pact/1999/0425/0/04250303",
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"abstract": "It is well known that Lattice Boltzmann Method (LBM) makes great success in many computational physics fields. But contrasting with its application, the numerical theory in Lattice Boltzmann method makes a little development. We will try to do something in this aspect. In order to solve a two dimension Burgers equation, a lattice Boltz-mann scheme with BGK model is constructed. The maximum value principle is proved and the stability is obtained too. Numerical experiments show the second order convergent accuracy of the scheme.",
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"abstract": "Lattice Boltzmann algorihms are a mesoscopic representation of nonlinear continuum physics (like Navier-Stokes, magnetohydro dynamics (MHD), Gross- Pitaevskii equations) which are ideal for parallel supercomputers because they transform the difficult nonlinear convective macroscopic derivatives into purely local moments of distribution functions. The macroscopic nonlinearities are recovered by relaxation distribution functions in the collision operator whose dependence on the macroscopic velocity is algebraically nonlinear and thus purely local. Unlike standard computational fluid dynamics codes, there is no loss in parallelization in handling arbitrary geometric boundaries, e.g., using bounce-back rules from kinetic theory. By encoding detailed balance into the collision operator through the introduction of discrete H-function, the lattice Boltzmann algorithm can be made unconditionally stable for arbitrary high Reynolds numbers. It is shown that this approach is a special case of a quantum lattice Boltzmann algorithm that entangles local qubits through unitary collision operators and which is ideally parallelized on quantum computer architectures. Here we consider turbulence simulations using 2,048 PEs on a 1,6003-spatial grid. A connection is found between the rate of change of enstrophy and the onset of laminar-to- turbulent flows.",
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"content": "Lattice Boltzmann algorihms are a mesoscopic representation of nonlinear continuum physics (like Navier-Stokes, magnetohydro dynamics (MHD), Gross- Pitaevskii equations) which are ideal for parallel supercomputers because they transform the difficult nonlinear convective macroscopic derivatives into purely local moments of distribution functions. The macroscopic nonlinearities are recovered by relaxation distribution functions in the collision operator whose dependence on the macroscopic velocity is algebraically nonlinear and thus purely local. Unlike standard computational fluid dynamics codes, there is no loss in parallelization in handling arbitrary geometric boundaries, e.g., using bounce-back rules from kinetic theory. By encoding detailed balance into the collision operator through the introduction of discrete H-function, the lattice Boltzmann algorithm can be made unconditionally stable for arbitrary high Reynolds numbers. It is shown that this approach is a special case of a quantum lattice Boltzmann algorithm that entangles local qubits through unitary collision operators and which is ideally parallelized on quantum computer architectures. Here we consider turbulence simulations using 2,048 PEs on a 1,6003-spatial grid. A connection is found between the rate of change of enstrophy and the onset of laminar-to- turbulent flows.",
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"normalizedAbstract": "Lattice Boltzmann algorihms are a mesoscopic representation of nonlinear continuum physics (like Navier-Stokes, magnetohydro dynamics (MHD), Gross- Pitaevskii equations) which are ideal for parallel supercomputers because they transform the difficult nonlinear convective macroscopic derivatives into purely local moments of distribution functions. The macroscopic nonlinearities are recovered by relaxation distribution functions in the collision operator whose dependence on the macroscopic velocity is algebraically nonlinear and thus purely local. Unlike standard computational fluid dynamics codes, there is no loss in parallelization in handling arbitrary geometric boundaries, e.g., using bounce-back rules from kinetic theory. By encoding detailed balance into the collision operator through the introduction of discrete H-function, the lattice Boltzmann algorithm can be made unconditionally stable for arbitrary high Reynolds numbers. It is shown that this approach is a special case of a quantum lattice Boltzmann algorithm that entangles local qubits through unitary collision operators and which is ideally parallelized on quantum computer architectures. Here we consider turbulence simulations using 2,048 PEs on a 1,6003-spatial grid. A connection is found between the rate of change of enstrophy and the onset of laminar-to- turbulent flows.",
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"affiliation": "Department of Physics, The College of Williamand Mary, Williamsburg, VA",
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"affiliation": "US Air Force Research Laboratory (AFRL),Hanscom Field, MA",
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"affiliation": "Department of Mathematics and Science, RogersState University, Claremore, OK",
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"affiliation": "High Performance Computing Modernization Program, Mississippi State University, MS",
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"doi": null,
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"id": "trans/td/2022/03/09492751",
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"abstract": "It is studied about parallel algorithm of lattice boltzmann method. The data's",
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"affiliation": "IIT Madras",
"fullName": "Salman Siddique Khan",
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"fullName": "Adarsh V R",
"givenName": "Adarsh V",
"surname": "R",
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"affiliation": "Rice University",
"fullName": "Vivek Boominathan",
"givenName": "Vivek",
"surname": "Boominathan",
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"affiliation": "Rice University",
"fullName": "Jasper Tan",
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"fullName": "Ashok Veeraraghavan",
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"abstract": "We propose a novel framework for creating large-scale photorealistic datasets of indoor scenes, with ground truth geometry, material, lighting and semantics. Our goal is to make the dataset creation process widely accessible, transforming scans into photorealistic datasets with high-quality ground truth for appearance, layout, semantic labels, high quality spatially-varying BRDF and complex lighting, including direct, indirect and visibility components. This enables important applications in inverse rendering, scene understanding and robotics. We show that deep networks trained on the proposed dataset achieve competitive performance for shape, material and lighting estimation on real images, enabling photorealistic augmented reality applications, such as object insertion and material editing. We also show our semantic labels may be used for segmentation and multi-task learning. Finally, we demonstrate that our framework may also be integrated with physics engines, to create virtual robotics environments with unique ground truth such as friction coefficients and correspondence to real scenes. The dataset and all the tools to create such datasets will be made publicly available.<sup>1</sup>",
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"content": "We propose a novel framework for creating large-scale photorealistic datasets of indoor scenes, with ground truth geometry, material, lighting and semantics. Our goal is to make the dataset creation process widely accessible, transforming scans into photorealistic datasets with high-quality ground truth for appearance, layout, semantic labels, high quality spatially-varying BRDF and complex lighting, including direct, indirect and visibility components. This enables important applications in inverse rendering, scene understanding and robotics. We show that deep networks trained on the proposed dataset achieve competitive performance for shape, material and lighting estimation on real images, enabling photorealistic augmented reality applications, such as object insertion and material editing. We also show our semantic labels may be used for segmentation and multi-task learning. Finally, we demonstrate that our framework may also be integrated with physics engines, to create virtual robotics environments with unique ground truth such as friction coefficients and correspondence to real scenes. The dataset and all the tools to create such datasets will be made publicly available.<sup>1</sup>",
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"affiliation": "UC San Diego",
"fullName": "Zhengqin Li",
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"fullName": "Shen Sang",
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"fullName": "Sarah Wang",
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"fullName": "Meng Song",
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"fullName": "Yuhan Liu",
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"title": "A Survey of Solar Filament Detection Methods",
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"abstract": "Solar filament is one of the main features of the sun. As a forecasting aid for geomagnetic storms, also, it is the subject of space weather study. Many methods have been proposed to detect the solar filaments, but most of them are manual feature recognition techniques. In this paper, three kinds of automated detection methods for filaments are presented. They are respectively automated region growing procedure, a threshold and region growing combined method and Artificial Neural Network technique (ANN). The experimental results are presented and the advantages and disadvantages of these three methods are compared. Automated region growing method can represent more details of filaments, however, it is time-consuming and strongly dependents on the background cleaning procedures. Threshold and region growing combined method can effectively improve the speed of image processing, but it can't detect the filaments near the solar limb. ANN can resolve these drawbacks which exist in automated region growing procedure and it has the ability of recognizing multiplicative filaments.",
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"content": "Solar filament is one of the main features of the sun. As a forecasting aid for geomagnetic storms, also, it is the subject of space weather study. Many methods have been proposed to detect the solar filaments, but most of them are manual feature recognition techniques. In this paper, three kinds of automated detection methods for filaments are presented. They are respectively automated region growing procedure, a threshold and region growing combined method and Artificial Neural Network technique (ANN). The experimental results are presented and the advantages and disadvantages of these three methods are compared. Automated region growing method can represent more details of filaments, however, it is time-consuming and strongly dependents on the background cleaning procedures. Threshold and region growing combined method can effectively improve the speed of image processing, but it can't detect the filaments near the solar limb. ANN can resolve these drawbacks which exist in automated region growing procedure and it has the ability of recognizing multiplicative filaments.",
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"affiliation": null,
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"abstract": "In this paper we introduce our preliminary research results for segmentation and labeling of 3-dimensional microscopy neuron image. We segment each of stacked 2-dimensional image slices using a partial differential equation (PDE) based algorithm and project previous slice segmentation result to the next slide as an initialization condition. Then we label neurons using an efficient connected component labeling algorithm. We show sample results obtained from real neuron image data",
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"abstract": "A new method, Global Newton-Raphson (GNR), for forward kinematics analysis of six degree–of-freedom (DOF) parallel robots is proposed, in order to obtain direct solutions of parallel robots in real time without divergence. The parallel robot can produce 3-DOF linear motions and 3-DOF angular motions, and feeds back positions of actuators measured by position sensors in real time. The GNR for the robot is built by Taylor series expansion and Newton-Raphson iteration with descent operator. Applying the GNR, the real generalized pose of moving platform is solved with respect to the base for a set of given positions of actuators. Accuracy and real time property of the GNR for the 6-DOF parallel robot are analyzed. The theoretical analysis indicated that the presented method can achieve the numerical convergent solution in real time with high accuracy, even the initial guesses are far from a solution.",
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"affiliation": "Macau University of Science and Technology",
"fullName": "Du Zhang",
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"title": "2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
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"title": "Comparison of dimensionality reduction methods for TCM symptom information",
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"abstract": "Objectives: To research a better method for reducing the dimensions of Traditional Chinese Medicine(TCM) symptom information by comparing Principal Component Analysis (PCA), Logistics Principal Component Analysis (LPCA) and Deep Belief network Autoencoder(DBA). All methods were applied to the pneumonic symptom dataset. Method: Mean-Square Error(MSE) was used to measure the performance of models. Heat maps were used to show the weight distributions of models which contained 10, 20 or 30 features. And Scatter plots were used to show the sample distributions which are described by 2 features. Results: In the 5-layer DBA network, MSE do not always decrease as the neuronal number of the 2nd layer increase, if the number is larger than 40. 5-layer DBA models have the best performance if the number of feature Z_$ \\lt 8$_Z. Else LPCA models have the minimal MSE. If the number of feature Z_$ \\gt 16$_Z, 3-layer DBA models are similar to 5-layer DBA models at MSE. Compared to PCA and LPCA, 3-layer DBA has the maximum range of weights and only a few variables in each feature have weights which significantly higher or lower than the other. In samples distributions, the features of 3-layer DBA and 5-layer DBA can divide the samples into different clusters more clearly than PCA and LPCA. Conclusion: LPCA and DBA can instead of PCA on dimensionality reduction for TCM symptom information. Compared with LPCA, DBAs features represent better with the same number of features and DBAs performance is better by building a multi-layer network when the feature number is small.",
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"content": "Objectives: To research a better method for reducing the dimensions of Traditional Chinese Medicine(TCM) symptom information by comparing Principal Component Analysis (PCA), Logistics Principal Component Analysis (LPCA) and Deep Belief network Autoencoder(DBA). All methods were applied to the pneumonic symptom dataset. Method: Mean-Square Error(MSE) was used to measure the performance of models. Heat maps were used to show the weight distributions of models which contained 10, 20 or 30 features. And Scatter plots were used to show the sample distributions which are described by 2 features. Results: In the 5-layer DBA network, MSE do not always decrease as the neuronal number of the 2nd layer increase, if the number is larger than 40. 5-layer DBA models have the best performance if the number of feature $ \\lt 8$. Else LPCA models have the minimal MSE. If the number of feature $ \\gt 16$, 3-layer DBA models are similar to 5-layer DBA models at MSE. Compared to PCA and LPCA, 3-layer DBA has the maximum range of weights and only a few variables in each feature have weights which significantly higher or lower than the other. In samples distributions, the features of 3-layer DBA and 5-layer DBA can divide the samples into different clusters more clearly than PCA and LPCA. Conclusion: LPCA and DBA can instead of PCA on dimensionality reduction for TCM symptom information. Compared with LPCA, DBAs features represent better with the same number of features and DBAs performance is better by building a multi-layer network when the feature number is small.",
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"normalizedAbstract": "Objectives: To research a better method for reducing the dimensions of Traditional Chinese Medicine(TCM) symptom information by comparing Principal Component Analysis (PCA), Logistics Principal Component Analysis (LPCA) and Deep Belief network Autoencoder(DBA). All methods were applied to the pneumonic symptom dataset. Method: Mean-Square Error(MSE) was used to measure the performance of models. Heat maps were used to show the weight distributions of models which contained 10, 20 or 30 features. And Scatter plots were used to show the sample distributions which are described by 2 features. Results: In the 5-layer DBA network, MSE do not always decrease as the neuronal number of the 2nd layer increase, if the number is larger than 40. 5-layer DBA models have the best performance if the number of feature -. Else LPCA models have the minimal MSE. If the number of feature -, 3-layer DBA models are similar to 5-layer DBA models at MSE. Compared to PCA and LPCA, 3-layer DBA has the maximum range of weights and only a few variables in each feature have weights which significantly higher or lower than the other. In samples distributions, the features of 3-layer DBA and 5-layer DBA can divide the samples into different clusters more clearly than PCA and LPCA. Conclusion: LPCA and DBA can instead of PCA on dimensionality reduction for TCM symptom information. Compared with LPCA, DBAs features represent better with the same number of features and DBAs performance is better by building a multi-layer network when the feature number is small.",
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"keywords": [
"Belief Networks",
"Data Mining",
"Learning Artificial Intelligence",
"Mean Square Error Methods",
"Medical Diagnostic Computing",
"Principal Component Analysis",
"TCM Symptom Information",
"Pneumonic Symptom Dataset",
"Sample Distributions",
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"Dimensionality Reduction Methods",
"LPCA",
"Mean Square Error",
"MSE",
"Deep Belief Network Autoencoder",
"Logistics Principal Component Analysis",
"Traditional Chinese Medicine Symptom Information",
"Principal Component Analysis",
"Dimensionality Reduction",
"Training",
"Neurons",
"Hospitals",
"Lung",
"Diseases",
"Symptom Information",
"Dimensionality Reduction",
"Traditional Chinese Medicine",
"Machine Learning"
],
"authors": [
{
"affiliation": "The Second Affiliated Hospital of Guangzhou University of Chinese Medicine Guangdong Provincial Data Center of Chinese Medicine, Guangzhou, China",
"fullName": "Haoyang Fu",
"givenName": "Haoyang",
"surname": "Fu",
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{
"affiliation": "Guangzhou University of Chinese Medicine, Guangzhou, China",
"fullName": "Jingbo Li",
"givenName": "Jingbo",
"surname": "Li",
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},
{
"affiliation": "The Second Affiliated Hospital of Guangzhou University of Chinese Medicine Guangdong Provincial Data Center of Chinese Medicine, Guangzhou, China",
"fullName": "Likeng Liang",
"givenName": "Likeng",
"surname": "Liang",
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"title": "2017 24th Asia-Pacific Software Engineering Conference (APSEC)",
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"article": {
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"doi": "10.1109/APSEC.2017.57",
"title": "What-If Model Construction and Validation of Web Systems Based on Log Mining",
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"abstract": "To maintain a complex modern web-based system, the what-if analysis is quite useful for predicting the impact of any workload growth or planned change on the performance of individual components, even the entire system. In this paper we propose an approach based on log mining to build what-if models of web-based systems and validate them by using OPNET simulation tool. Three contributions of this paper are: (1) the construction of what-if models based on log mining to automate the task of modeling and validation, (2) the technique to address complexity of user behaviors including users' browser caching, clustering of requests and users, etc., (3) and two real-life cases to evaluate the effectiveness and accuracy of this approach. The preliminary results show that the relative errors between logged data and simulation results are less than 18% in most cases including number of requests and network throughput.",
"abstracts": [
{
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"content": "To maintain a complex modern web-based system, the what-if analysis is quite useful for predicting the impact of any workload growth or planned change on the performance of individual components, even the entire system. In this paper we propose an approach based on log mining to build what-if models of web-based systems and validate them by using OPNET simulation tool. Three contributions of this paper are: (1) the construction of what-if models based on log mining to automate the task of modeling and validation, (2) the technique to address complexity of user behaviors including users' browser caching, clustering of requests and users, etc., (3) and two real-life cases to evaluate the effectiveness and accuracy of this approach. The preliminary results show that the relative errors between logged data and simulation results are less than 18% in most cases including number of requests and network throughput.",
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"normalizedAbstract": "To maintain a complex modern web-based system, the what-if analysis is quite useful for predicting the impact of any workload growth or planned change on the performance of individual components, even the entire system. In this paper we propose an approach based on log mining to build what-if models of web-based systems and validate them by using OPNET simulation tool. Three contributions of this paper are: (1) the construction of what-if models based on log mining to automate the task of modeling and validation, (2) the technique to address complexity of user behaviors including users' browser caching, clustering of requests and users, etc., (3) and two real-life cases to evaluate the effectiveness and accuracy of this approach. The preliminary results show that the relative errors between logged data and simulation results are less than 18% in most cases including number of requests and network throughput.",
"fno": "3681a505",
"keywords": [
"Data Mining",
"Internet",
"Workload Growth",
"Log Mining",
"OPNET Simulation Tool",
"Modeling Validation",
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"Logged Data",
"Model Construction",
"Web Systems",
"What If Model Construction",
"Complex Modern Web Based System",
"Network Throughput",
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"Unified Modeling Language",
"Predictive Models",
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"Tools",
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"What If Analysis",
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"Simulation",
"Web Based System",
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"User Clustering"
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"affiliation": null,
"fullName": "Jianpeng Hu",
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"fullName": "Linpeng Huang",
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"fullName": "Juan Huang",
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"fullName": "Tianqi Sun",
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"fullName": "Yingjun Ouyang",
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"abstract": "Data workers are non-professional data scientists who often use scripting languages like R, Python, or MATLAB, and employ an exploratory programming workflow. Current IDEs offer them two main programming modalities: script files and computational notebooks. To understand how these modalities impact work practice, we conducted a study with 21 data workers, and a subsequent larger survey with 62 respondents. Through interviews, walkthroughs, and screen recordings, we collected information about their workflows. Our analysis shows a tension between scripts and computational notebooks. Scripts are more common, better support storage and execution of previous analyses, but hinder experimentation. Notebooks better suit the actual data science workflow, but can become easily unorganized. We discuss how this dual nature of modality usage leads to several issues that affect data workers’ workflows, and discuss implications for the design of programming IDEs.",
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"abstract": "Data is everywhere and in everything we do. Most of the time, usable information is hidden in raw data and because of that, there is an increasing demand for people capable of working creatively with it. To fully understand how we can assist data science workers to become more productive in their jobs, we first need to understand who they are, how they work, what are the skills they hold and lack, and which tools they need. In this paper, we present the results of the analysis of several interviews conducted with data scientists. Our research allowed us to conclude that the heterogeneity between these professionals is still understudied, which makes the development of methodologies and tools more challenging and error prone. The results of this research are particularly useful for both the scientific community and industry to propose adequate solutions for these professionals.",
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"abstract": "Human-computer interaction (HCI) attracts more and more attention in automation, multimedia retrieval, computer system, universal computing. Meanwhile, it also poses new challenges to interaction design based on HCI in user experience, aesthetics, game design, and education]. This study aimed to analyze and assess literature published in the field of interaction design of HCI. <i>Methods:</i> Web of science was used to retrieve literature of interaction design. The study period was set from 1985 to 2020, a total of 3243 documents were published. Pyecharts were used to present geographical distribution of publications and VOSviewer was used for data visualization. <i>Results:</i> This article uses standard bibliometric indicators to demonstrate five main aspects: Publications growing, Geographical distribution of publications, citation analysis, research productivity, and author keywords clusters analyze. <i>Conclusion:</i> Through scientometrics analysis, it is found that the current research hotspots are mainly concentrated in 5 clusters: (a) UI for user-centered design, (b)HCI. (c)interaction design, (d)Intelligent interactive recognition research, (e)e-health and health information. According to the research frontier of interaction design research on HCI, researchers can get a clearer research status. Also, by showing the research fronts of interaction design of HCI, the scientometric analysis also highlights the research gap at the increasing importance of user health and the sustainability of interaction.",
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"content": "Human-computer interaction (HCI) attracts more and more attention in automation, multimedia retrieval, computer system, universal computing. Meanwhile, it also poses new challenges to interaction design based on HCI in user experience, aesthetics, game design, and education]. This study aimed to analyze and assess literature published in the field of interaction design of HCI. <i>Methods:</i> Web of science was used to retrieve literature of interaction design. The study period was set from 1985 to 2020, a total of 3243 documents were published. Pyecharts were used to present geographical distribution of publications and VOSviewer was used for data visualization. <i>Results:</i> This article uses standard bibliometric indicators to demonstrate five main aspects: Publications growing, Geographical distribution of publications, citation analysis, research productivity, and author keywords clusters analyze. <i>Conclusion:</i> Through scientometrics analysis, it is found that the current research hotspots are mainly concentrated in 5 clusters: (a) UI for user-centered design, (b)HCI. (c)interaction design, (d)Intelligent interactive recognition research, (e)e-health and health information. According to the research frontier of interaction design research on HCI, researchers can get a clearer research status. Also, by showing the research fronts of interaction design of HCI, the scientometric analysis also highlights the research gap at the increasing importance of user health and the sustainability of interaction.",
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"normalizedAbstract": "Human-computer interaction (HCI) attracts more and more attention in automation, multimedia retrieval, computer system, universal computing. Meanwhile, it also poses new challenges to interaction design based on HCI in user experience, aesthetics, game design, and education]. This study aimed to analyze and assess literature published in the field of interaction design of HCI. Methods: Web of science was used to retrieve literature of interaction design. The study period was set from 1985 to 2020, a total of 3243 documents were published. Pyecharts were used to present geographical distribution of publications and VOSviewer was used for data visualization. Results: This article uses standard bibliometric indicators to demonstrate five main aspects: Publications growing, Geographical distribution of publications, citation analysis, research productivity, and author keywords clusters analyze. Conclusion: Through scientometrics analysis, it is found that the current research hotspots are mainly concentrated in 5 clusters: (a) UI for user-centered design, (b)HCI. (c)interaction design, (d)Intelligent interactive recognition research, (e)e-health and health information. According to the research frontier of interaction design research on HCI, researchers can get a clearer research status. Also, by showing the research fronts of interaction design of HCI, the scientometric analysis also highlights the research gap at the increasing importance of user health and the sustainability of interaction.",
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"abstract": "The reluctance changing principle of resolver is divided into two kinds: one is varying reluctance through coupling area and the other is the air gap. The mechanical eccentricity makes much more influence on the precision of the one pair pole reluctance resolver. In this article, one pair pole axial flux reluctance resolver with new magnetic structure is put forward, which has the compensating character inside its two side air gap. The prototype has both the exciting windings and signal windings in its stator, which are vertical to each other. There is no winding in its rotor and one inclined ring is set in it. The character of the EMF in signal windings is got using FEM. At the same time, one 4-pole reluctance resolver's zero error analysis is put forward by using FEM. The result of the FEM analysis is coinciding with supposing of the analytical method well and this will offer us the basic parameters for the further analysis in the future.",
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"content": "The reluctance changing principle of resolver is divided into two kinds: one is varying reluctance through coupling area and the other is the air gap. The mechanical eccentricity makes much more influence on the precision of the one pair pole reluctance resolver. In this article, one pair pole axial flux reluctance resolver with new magnetic structure is put forward, which has the compensating character inside its two side air gap. The prototype has both the exciting windings and signal windings in its stator, which are vertical to each other. There is no winding in its rotor and one inclined ring is set in it. The character of the EMF in signal windings is got using FEM. At the same time, one 4-pole reluctance resolver's zero error analysis is put forward by using FEM. The result of the FEM analysis is coinciding with supposing of the analytical method well and this will offer us the basic parameters for the further analysis in the future.",
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