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"abstract": "Image inpainting is the technique that's able to “repair” or “correct” the image by reconstructing missing regions of an image using AI algorithms. As the techniques of images inpainting become mature in recent years, the demand for image inpainting algorithms rises in the market. It can be used to fill out missing areas in a picture, denoise images, or even remove a specific object from an image. To this end, it is important to propose a survey for image inpainting method, which can provide a comprehensive introduction of this area. The reason for creating this paper is due to the lack of resources that conclude all the methods that are being used in image inpainting. As the field of image inpainting soars, researchers may need documents which explain all the methods that can be used to train their image inpainting models. In the paper, we gathered some most successful methods that are used by many researchers. We explained their model, methods they used, the results of the training, and the advantages of the approaches they used in their research.",
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"content": "Image inpainting is the technique that's able to “repair” or “correct” the image by reconstructing missing regions of an image using AI algorithms. As the techniques of images inpainting become mature in recent years, the demand for image inpainting algorithms rises in the market. It can be used to fill out missing areas in a picture, denoise images, or even remove a specific object from an image. To this end, it is important to propose a survey for image inpainting method, which can provide a comprehensive introduction of this area. The reason for creating this paper is due to the lack of resources that conclude all the methods that are being used in image inpainting. As the field of image inpainting soars, researchers may need documents which explain all the methods that can be used to train their image inpainting models. In the paper, we gathered some most successful methods that are used by many researchers. We explained their model, methods they used, the results of the training, and the advantages of the approaches they used in their research.",
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"abstract": "Energy efficiency is critical in the design and deployment of wireless sensor networks. Data compression is a significant approach to reducing energy consumption of data gathering in multi-hop sensor networks. Existing compression algorithms, however, only apply to either lossless or lossy compression, but not to both. This paper presents a unified algorithmic framework to both lossless and lossy data compression, thus effectively supporting the desirable flexibility of choosing either lossless or lossy compression in an on-demand fashion based on given applications. We analytically prove that the performance of the proposed framework for lossless compression is superior to or at least equivalent to that of traditional predictive coding schemes regardless of any entropy encoders used. We demonstrate the merits of our proposed framework in comparison with other recently proposed compression algorithms for wireless sensor networks including LEC, S-LZW and LTC using various real-world sensor data sets.",
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"abstract": "As light field images continue to increase in use and application, it becomes necessary to adapt existing image processing methods to this unique form of photography. In this paper we explore methods for applying neural style transfer to light field images. Feed-forward style transfer networks provide fast, high-quality results for monocular images, but no such networks exist for full light field images. Because of the size of these images, current light field data sets are small and are insufficient for training purely feed-forward style-transfer networks from scratch. Thus, it is necessary to adapt existing monocular style transfer networks in a way that allows for the stylization of each view of the light field while maintaining visual consistencies between views. To do this, we first generate disparity maps for each view given a single depth image for the light field. Then in a fashion similar to neural stylization of stereo images, we use disparity maps to enforce a consistency loss between views and to warp feature maps during the feed forward stylization. Unlike previous work, however, light fields have too many views to train a purely feed-forward network that can stylize the entire light field with angular consistency. Instead, the proposed method uses an iterative optimization for each view of a single light field image that backpropagates the consistency loss through the network. Thus, the network architecture allows for the incorporation of pre-trained fast monocular stylization network while avoiding the need for a large light field training set.",
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"abstract": "Recent advances have seen a surge of deep learning approaches for image super-resolution. Invariably, a network, e.g. a deep convolutional neural network (CNN) or auto-encoder is trained to learn the relationship between low and high-resolution image patches. Recognizing that a wavelet transform provides a \"coarse\" as well as \"detail\" separation of image content, we design a deep CNN to predict the \"missing details\" of wavelet coefficients of the low-resolution images to obtain the Super-Resolution (SR) results, which we name Deep Wavelet Super-Resolution (DWSR). Out network is trained in the wavelet domain with four input and output channels respectively. The input comprises of 4 sub-bands of the low-resolution wavelet coefficients and outputs are residuals (missing details) of 4 sub-bands of high-resolution wavelet coefficients. Wavelet coefficients and wavelet residuals are used as input and outputs of our network to further enhance the sparsity of activation maps. A key benefit of such a design is that it greatly reduces the training burden of learning the network that reconstructs low frequency details. The output prediction is added to the input to form the final SR wavelet coefficients. Then the inverse 2d discrete wavelet transformation is applied to transform the predicted details and generate the SR results. We show that DWSR is computationally simpler and yet produces competitive and often better results than state-of-the-art alternatives.",
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"abstract": "Spatial resolution is critical for observing and monitoring environmental phenomena. Acquiring high-resolution bathymetry data directly from satellites is not always feasible due to limitations on equipment, so spatial data scientists and researchers turn to single image super-resolution (SISR) methods that utilize deep learning techniques as an alternative method to increase pixel density. While super resolution residual networks (e.g., SR-ResNet) are promising for this purpose, several challenges still need to be addressed: (1) Earth data such as bathymetry is expensive to obtain and relatively limited in its data record amount; (2) certain domain knowledge needs to be complied with during model training; (3) certain areas of interest require more accurate measurements than other areas. To address these challenges, following the transfer learning principle, we study how to leverage an existing pre-trained super-resolution deep learning model, namely SR-ResNet, for high-resolution bathymetry data generation. We further enhance the SR-ResNet model to add corresponding loss functions based on domain knowledge. To let the model perform better for certain spatial areas, we add additional loss functions to increase the penalty of the areas of interest. Our experiments show our approaches achieve higher accuracy than most baseline models when evaluating using metrics including MSE, PSNR, and SSIM.",
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"abstract": "In the emerging commercial space industry there is a drastic increase in access to low cost satellite imagery. The price for satellite images depends on the sensor quality and revisit rate. This work proposes to bridge the gap between image quality and the price by improving the image quality via super-resolution (SR). Recently, a number of deep SR techniques have been proposed to enhance satellite images. However, none of these methods utilize the region-level context information, giving equal importance to each region in the image. This, along with the fact that most state-of-the-art SR methods are complex and cumbersome deep models, the time taken to process very large satellite images can be impractically high. We, propose to handle this challenge by designing an SR framework that analyzes the regional information content on each patch of the low-resolution image and judiciously chooses to use more computationally complex deep models to super-resolve more structure-rich regions on the image, while using less resource-intensive non-deep methods on non-salient regions. Through extensive experiments on a large satellite image, we show substantial decrease in inference time while achieving similar performance to that of existing deep SR methods over several evaluation measures like PSNR, MSE and SSIM.",
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"abstract": "The complexity of today's embedded systems forces designers to model and simulate systems and their components to explore the wide range of design choices. Such design space exploration is especially needed during the early design stages, where the design space is at its largest. Due to the exponential design space in real problems, evaluating and comparing every single point in the design space is infeasible. Therefore, heuristic search techniques, such as Evolutionary Algorithms (EA), are often used to search the design space for optimum design points using only a finite number of design-point evaluations. Understanding how the design space was searched by such searching algorithms and providing insight into the ¿landscape¿ of the design space, may be of invaluable importance to the designer, To this end, this paper presents a novel interactive visualization application, based on tree visualization, to understand the search dynamics of an evolutionary algorithm and to visualize where the optimum design points are located in the design space.",
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"abstract": "In the present work surface electrocardiogram in lead II configuration has been chosen as the sample data as it has distinguished features for the accurate detection of the R-points for HRV analysis. The data used in the study is from ten normal patients for the duration of 8 minutes, at a sampling frequency of 500 Hz, using the DAS together with A/D converter, interfaced to a computer. The data for ten MI patients are selected from the European ST database. A high precision algorithm has been developed and implemented in MATLAB platform for the accurate detection of R-points. The conversion of these randomly occurring point processes into uniformly sampled signal is done by backward step interpolation technique. The sampled HRV signal is filtered by band pass filters at the LF (0.05 Hz - 0.15 Hz) and HF (0.15 Hz - 0.4 Hz) bands. The power spectrum of both bands of HRV signal has been estimated using FFT. The total power ratio and the peak power ratio of LF to HF band calculated for MI patients showed a drastic increase when compared to normal subjects. Also the total power in Ml patients has shown a drastic reduction",
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"abstract": "It is known that the perceived loudness of a tone signal by a human is spectrally masked by background noise. This masking effect causes not only a shift of just-audible sound pressure level of the tone, but also produces a masked loudness function having steeper slope than the unmasked one. This masking property of perceived loudness stimulates us to propose a new mel-scale-based feature extraction method with non-uniform spectral compression for speech recognition in noisy environments. In this method, the speech power spectrum is to undergo mel-scaled band-pass filtering, as in the standard MFCC front-end. However, the energies of the outputs of the filters are compressed by different root values defined by a compression function. This compression function is a function of the SNR in each filter band. Using this new scheme of SNR-dependent non-uniform spectral compression (SNSC) for mel-scaled filter-bank-based cepstral coefficients, substantial improvement is found for recognition in different noisy environments, as compared to the standard MFCC and features derived with cubic root spectral compression.",
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"title": "Magnetic Circuit Simulation and Analysis of Shear-Valve Mode MRF Damper",
"doi": null,
"abstractUrl": "/proceedings-article/icmeas/2021/976800a050/1zuuVD3H7Qk",
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"title": "2021 7th International Conference on Mechanical Engineering and Automation Science (ICMEAS)",
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"proceeding": {
"id": "1hHLm2dSyn6",
"title": "2019 2nd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)",
"acronym": "wcmeim",
"groupId": "1835484",
"volume": "0",
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"year": "2019",
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"article": {
"id": "1hHLtwUmSvm",
"doi": "10.1109/WCMEIM48965.2019.00012",
"title": "Simulation Analysis of Electromagnetic Vibration of Rotor Compressor Motor Based on Modal Superposition Method",
"normalizedTitle": "Simulation Analysis of Electromagnetic Vibration of Rotor Compressor Motor Based on Modal Superposition Method",
"abstract": "In order to study the electromagnetic vibration of the inverter compressor motor, a 6-pole 9-slot permanent magnet synchronous motor is taken as the research object. Firstly, the radial electromagnetic force wave generated by the air gap magnetic field of the motor under sine wave power supply is obtained by analytical method. Order and frequency distribution, and obtain the transient electromagnetic force on the stator core through electromagnetic software, simulate the modal of the motor stator assembly, obtain the low-order radial mode shape and frequency of the motor, and on this basis, we combines the electromagnetic force with the motor modal mesh to obtain the radial vibration response of the stator surface of the motor by modal superposition method, and conducts a bench test under the corresponding working conditions of the motor to measure the vibration spectrum of the motor. The results show that the simulation results are in good agreement with the test results, and the analysis process has important reference significance for predicting the electromagnetic vibration of different types of compressor motors.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In order to study the electromagnetic vibration of the inverter compressor motor, a 6-pole 9-slot permanent magnet synchronous motor is taken as the research object. Firstly, the radial electromagnetic force wave generated by the air gap magnetic field of the motor under sine wave power supply is obtained by analytical method. Order and frequency distribution, and obtain the transient electromagnetic force on the stator core through electromagnetic software, simulate the modal of the motor stator assembly, obtain the low-order radial mode shape and frequency of the motor, and on this basis, we combines the electromagnetic force with the motor modal mesh to obtain the radial vibration response of the stator surface of the motor by modal superposition method, and conducts a bench test under the corresponding working conditions of the motor to measure the vibration spectrum of the motor. The results show that the simulation results are in good agreement with the test results, and the analysis process has important reference significance for predicting the electromagnetic vibration of different types of compressor motors.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In order to study the electromagnetic vibration of the inverter compressor motor, a 6-pole 9-slot permanent magnet synchronous motor is taken as the research object. Firstly, the radial electromagnetic force wave generated by the air gap magnetic field of the motor under sine wave power supply is obtained by analytical method. Order and frequency distribution, and obtain the transient electromagnetic force on the stator core through electromagnetic software, simulate the modal of the motor stator assembly, obtain the low-order radial mode shape and frequency of the motor, and on this basis, we combines the electromagnetic force with the motor modal mesh to obtain the radial vibration response of the stator surface of the motor by modal superposition method, and conducts a bench test under the corresponding working conditions of the motor to measure the vibration spectrum of the motor. The results show that the simulation results are in good agreement with the test results, and the analysis process has important reference significance for predicting the electromagnetic vibration of different types of compressor motors.",
"fno": "504500a021",
"keywords": [
"Air Gaps",
"Assembling",
"Compressors",
"Electric Machine Analysis Computing",
"Invertors",
"Machine Insulation",
"Machine Testing",
"Modal Analysis",
"Rotors",
"Stators",
"Vibration Measurement",
"Electromagnetic Software",
"Motor Stator Assembly",
"Low Order Radial Mode Shape",
"Motor Modal Mesh",
"Radial Vibration Response",
"Modal Superposition Method",
"Vibration Spectrum",
"Electromagnetic Vibration Analysis",
"Compressor Motors",
"Rotor Compressor Motor",
"Inverter Compressor Motor",
"Air Gap Magnetic Field",
"Sine Wave Power Supply",
"Transient Electromagnetic Force",
"6 Pole 9 Slot Permanent Magnet Synchronous Motor",
"Stator Core",
"Radial Electromagnetic Force Wave Generation",
"Stators",
"Vibrations",
"Electromagnetic Forces",
"Permanent Magnet Motors",
"Analytical Models",
"Conferences",
"Mechanical Engineering",
"Inverter Compressor",
"Electromagnetic Vibration",
"Permanent Magnet Synchronous Motor",
"Modal Superposition Method",
"Radial Electromagnetic Force"
],
"authors": [
{
"affiliation": "Zhuhai Landa Compressor Co. , Ltd., China",
"fullName": "Mingxu Ren",
"givenName": "Mingxu",
"surname": "Ren",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Zhuhai Landa Compressor Co., Ltd., China",
"fullName": "Hui Shen",
"givenName": "Hui",
"surname": "Shen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Zhuhai Landa Compressor Co. , Ltd., China",
"fullName": "Wanjie Sun",
"givenName": "Wanjie",
"surname": "Sun",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Zhuhai Landa Compressor Co., Ltd., China",
"fullName": "Haishui Jin",
"givenName": "Haishui",
"surname": "Jin",
"__typename": "ArticleAuthorType"
}
],
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"pubDate": "2019-11-01T00:00:00",
"pubType": "proceedings",
"pages": "21-26",
"year": "2019",
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"isbn": "978-1-7281-5045-1",
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"doi": null,
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{
"proceeding": {
"id": "1pcSN7F2d7W",
"title": "2020 IEEE International Conference on Energy Internet (ICEI)",
"acronym": "icei",
"groupId": "1819924",
"volume": "0",
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"year": "2020",
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"article": {
"id": "1pcSOOtQo92",
"doi": "10.1109/ICEI49372.2020.00034",
"title": "Analysis of Influence of Uneven Air Gap of Hydrogenerator on Magnetic Field Strength and Rotor Magnetic Pole Stress Change",
"normalizedTitle": "Analysis of Influence of Uneven Air Gap of Hydrogenerator on Magnetic Field Strength and Rotor Magnetic Pole Stress Change",
"abstract": "The uneven air gap between the inner cavity of the stator and rotor's outer circle is one of the main vibration sources of large hydro-generator sets. Unbalanced magnetic tension between the stator and rotor forms a frequency-exciting disturbance force on the rotor and stator. In this paper, in order to explore the relationship between the uneven air gap and the magnetic field strength as well as electromagnetic stress, magnetic induction intensity of inner air-gap magnetic field of the generator and the stress on the rotor surface are analyzed for six working conditions of the hydroelectric generator, including centering and eccentricity of the rotor. The influence of the hydroelectric generator's air gap change rotor pole stress is studied with finite element software based on the structure of the generator.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The uneven air gap between the inner cavity of the stator and rotor's outer circle is one of the main vibration sources of large hydro-generator sets. Unbalanced magnetic tension between the stator and rotor forms a frequency-exciting disturbance force on the rotor and stator. In this paper, in order to explore the relationship between the uneven air gap and the magnetic field strength as well as electromagnetic stress, magnetic induction intensity of inner air-gap magnetic field of the generator and the stress on the rotor surface are analyzed for six working conditions of the hydroelectric generator, including centering and eccentricity of the rotor. The influence of the hydroelectric generator's air gap change rotor pole stress is studied with finite element software based on the structure of the generator.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The uneven air gap between the inner cavity of the stator and rotor's outer circle is one of the main vibration sources of large hydro-generator sets. Unbalanced magnetic tension between the stator and rotor forms a frequency-exciting disturbance force on the rotor and stator. In this paper, in order to explore the relationship between the uneven air gap and the magnetic field strength as well as electromagnetic stress, magnetic induction intensity of inner air-gap magnetic field of the generator and the stress on the rotor surface are analyzed for six working conditions of the hydroelectric generator, including centering and eccentricity of the rotor. The influence of the hydroelectric generator's air gap change rotor pole stress is studied with finite element software based on the structure of the generator.",
"fno": "050000a147",
"keywords": [
"Air Gaps",
"Electromagnetic Induction",
"Finite Element Analysis",
"Hydroelectric Generators",
"Magnetic Fields",
"Rotors",
"Stators",
"Vibrations",
"Magnetic Induction Intensity",
"Hydroelectric Generator",
"Rotor Magnetic Pole Stress Change",
"Stator",
"Frequency Exciting Disturbance Force",
"Air Gap Magnetic Field Strength",
"Vibration Sources",
"Electromagnetic Stress",
"Rotor Eccentricity",
"Finite Element Software",
"Rotors",
"Magnetomechanical Effects",
"Air Gaps",
"Generators",
"Stress",
"Stators",
"Magnetic Fields",
"Hydro Power Generator",
"Eccentricity",
"Air Gap Magnetic Field",
"Stresses Analysis",
"FEM"
],
"authors": [
{
"affiliation": "The 54th Research Institute of China Electronics Technology Group Corporation,Antenna and Servo Department,Shijiazhuang,China",
"fullName": "Qi Sun",
"givenName": "Qi",
"surname": "Sun",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xi’an University of Technology,Xi’ an Thermal Power Research Institute Co. Ltd.,Xi’an,China",
"fullName": "Chenyuan Ma",
"givenName": "Chenyuan",
"surname": "Ma",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "The 54th Research Institute of China Electronics Technology Group Corporation,Antenna and Servo Department,Shijiazhuang,China",
"fullName": "Song Xiao",
"givenName": "Song",
"surname": "Xiao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xi’ an Thermal Power Research Institute Co. Ltd.,Xi’an,China",
"fullName": "Litao Niu",
"givenName": "Litao",
"surname": "Niu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xi’ an Thermal Power Research Institute Co. Ltd.,Xi’an,China",
"fullName": "Jianguo Pu",
"givenName": "Jianguo",
"surname": "Pu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xi’ an Thermal Power Research Institute Co. Ltd.,Xi’an,China",
"fullName": "Yiyang Wu",
"givenName": "Yiyang",
"surname": "Wu",
"__typename": "ArticleAuthorType"
}
],
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"pubDate": "2020-08-01T00:00:00",
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"pages": "147-151",
"year": "2020",
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{
"proceeding": {
"id": "1wiQJOF7bag",
"title": "2021 International Conference on Control Science and Electric Power Systems (CSEPS)",
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"article": {
"id": "1wiQKbmaMW4",
"doi": "10.1109/CSEPS53726.2021.00070",
"title": "Establishment of Electromagnetic Model of Permanent Magnet Synchronous Motor for Electric Machine Emulator",
"normalizedTitle": "Establishment of Electromagnetic Model of Permanent Magnet Synchronous Motor for Electric Machine Emulator",
"abstract": "For the motor model of the electric machine emulator (EME), the collected voltage at the terminal of the motor controller (MCU) is resolved into the current. The output characteristics of a permanent magnet synchronous motor can be expressed by its voltage equation, torque equation and motion equation. For the traditional motor model, parameters including inductance, resistance, flux linkage, and damping coefficient are regarded as constants. But these parameters are variable during actual motor operation. The thesis conducted an in-depth analysis of the electromagnetic characteristics and the influencing mechanism of permanent magnet synchronous motors (including iron core magnetic saturation and cross-coupling, air gap magnetic field harmonic effect). And an electromagnetic model of a permanent magnet synchronous motor that takes into account the non-sinusoidal air gap magnetic field and the iron core magnetic saturation in the electric machine emulator is built.",
"abstracts": [
{
"abstractType": "Regular",
"content": "For the motor model of the electric machine emulator (EME), the collected voltage at the terminal of the motor controller (MCU) is resolved into the current. The output characteristics of a permanent magnet synchronous motor can be expressed by its voltage equation, torque equation and motion equation. For the traditional motor model, parameters including inductance, resistance, flux linkage, and damping coefficient are regarded as constants. But these parameters are variable during actual motor operation. The thesis conducted an in-depth analysis of the electromagnetic characteristics and the influencing mechanism of permanent magnet synchronous motors (including iron core magnetic saturation and cross-coupling, air gap magnetic field harmonic effect). And an electromagnetic model of a permanent magnet synchronous motor that takes into account the non-sinusoidal air gap magnetic field and the iron core magnetic saturation in the electric machine emulator is built.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "For the motor model of the electric machine emulator (EME), the collected voltage at the terminal of the motor controller (MCU) is resolved into the current. The output characteristics of a permanent magnet synchronous motor can be expressed by its voltage equation, torque equation and motion equation. For the traditional motor model, parameters including inductance, resistance, flux linkage, and damping coefficient are regarded as constants. But these parameters are variable during actual motor operation. The thesis conducted an in-depth analysis of the electromagnetic characteristics and the influencing mechanism of permanent magnet synchronous motors (including iron core magnetic saturation and cross-coupling, air gap magnetic field harmonic effect). And an electromagnetic model of a permanent magnet synchronous motor that takes into account the non-sinusoidal air gap magnetic field and the iron core magnetic saturation in the electric machine emulator is built.",
"fno": "261800a315",
"keywords": [
"Air Gaps",
"Electric Machines",
"Machine Control",
"Magnetic Fields",
"Magnetic Flux",
"Permanent Magnet Motors",
"Synchronous Motors",
"Torque",
"Electric Machine Emulator",
"Motor Controller",
"Permanent Magnet Synchronous Motor",
"Torque Equation",
"Motion Equation",
"Traditional Motor Model",
"Actual Motor Operation",
"Iron Core Magnetic Saturation",
"Electromagnetic Model",
"Magnetic Flux",
"Magnetomechanical Effects",
"Magnetic Separation",
"Magnetic Cores",
"Rotors",
"Permanent Magnet Motors",
"Synchronous Motors",
"Permanent Magnet Synchronous Motor",
"Electric Machine Emulator",
"Electromagnetic Model",
"Electromagnetic Characteristics"
],
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"content": "The magnetic circuit structure in the damper is important for the design of the magnetorheological damper (MRD). This paper aims to explore the influence of various structural parameters in the magnetic circuit structure on shear-valve magnetorheological dampers. In order to establish the magnetic circuit structure model with different structural parameters and simulate the model with the finite element method, PAO-6, a polyolefin synthetic oil, was selected as the carrier liquid and the Carbonyl Iron Power whose average particle size is about 2 $\\mu$m was selected as the magnetic particles. Besides, some parameters of the magnetic circuit structure are set, including damping channel gap, cylinder wall thickness, coil slot length and depth as well as core thickness. Simulation results of different structural parameters are analyzed for comparing the variation of magnetic induction strength. The effects of different structural parameters on the performance of the MRD will be considered during the design, and the influence of the various structural parameters on the energy distribution of the magnetic field will be balanced to maximize the mechanical performance of the dampers.",
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"title": "2016 8th International Conference on Information Technology in Medicine and Education (ITME)",
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"article": {
"id": "12OmNBO3K3F",
"doi": "10.1109/ITME.2016.0081",
"title": "The Features of Lymph Node Metastasis of Differentiated Thyroid Carcinoma and the Choice of Lateral Neck Lymph Nodes Dissection",
"normalizedTitle": "The Features of Lymph Node Metastasis of Differentiated Thyroid Carcinoma and the Choice of Lateral Neck Lymph Nodes Dissection",
"abstract": "Objective: The clinicopathologic features of central area and lateral neck lymph nodes metastasis were retrospectively analyzed in order to better understand the characteristics of cervical lymph node metastasis, and provide an objective reasonable choice basis of surgical treatment cervical lymph node for the surgeons. Methods: All patients from January 2008 to July 2010 in our hospital were collected, 329 cases of resection of thyroid cancer and central lymph node dissection treatment of PTC were analyzed (Including 115 cases of lateral neck lymph nodes dissection at the same time). We then analyzed the correlation between the clinicopathological features of central lymph nodes and lateral lymph node metastasis. Results: The average age of 329 cases of patients was 43 years, male 66 cases, female 263 cases, tumor diameter average 1.11cm, the average number of tumors 1.76, 97 cases of bilateral, 232 cases of unilateral, 44.07% of central lymph node metastasis in 329, 57.39% of lateral lymph node metastasis in 115 cases of lateral neck lymph nodes dissection, 35.11% of central lymph node metastasis in 262 cases of patients with a clinincal negative result of central lymph nodes preoperative examination, 28.81% of lateral lymph node metastasis in 59 cases of patients with a negative result of lateral lymph nodes preoperative examination. (1) Papillary thyroid carcinoma those who were in the groups of male, >45 years old, associated with extrathyroidal invasion, the diameter >1cm, absence of other thyroid diseases, absence of nodular goiter had a higher rate of central lymph node metastasis (P=0.028, 0.003, 0.001, 0.000, 0.000, 0.001, espectively). And the group that Ultrasonography examination showed a positive result of central lymph nodes had a higher rate of central lymph node metastasis than the group that Ultrasonography showed a negative result (P=0.000). (2) Papillary thyroid carcinoma those who were in the groups of male, >45 years old, unilateral tumor had a higher rate of lateral lymph node metastasis (P=0.040, 0.008, 0.021, 0.000). And the group of central lymph node metastasis positive had a higher rate of lateral lymph node metastasis than the group of central lymph node metastasis negative (P=0.000). (3) Those clinically examination negative central lymph nodes metastasis papillary thyroid carcinoma who were in the groups of the diameter > 1cm, absence of other thyroid diseases, absence of nodular goiter had a higher rate of central lymph node metastasis(P=0.018, 0.001, 0.004). (4) Those cases with a negative result of lateral cervical lymph nodes examination whom in the group of central lymph node metastasis had a higher rate of lateral lymph node metastasis than the group of absence of central lymph node metastasis(P=0.027). Conclusions: There were certain associations between the central lymph nodes metastasis, lateral lymph node metastasis and clinicopathological features in thyroid papillary carcinoma patients. This is of important significance for clinical treatment choice.",
"abstracts": [
{
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"content": "Objective: The clinicopathologic features of central area and lateral neck lymph nodes metastasis were retrospectively analyzed in order to better understand the characteristics of cervical lymph node metastasis, and provide an objective reasonable choice basis of surgical treatment cervical lymph node for the surgeons. Methods: All patients from January 2008 to July 2010 in our hospital were collected, 329 cases of resection of thyroid cancer and central lymph node dissection treatment of PTC were analyzed (Including 115 cases of lateral neck lymph nodes dissection at the same time). We then analyzed the correlation between the clinicopathological features of central lymph nodes and lateral lymph node metastasis. Results: The average age of 329 cases of patients was 43 years, male 66 cases, female 263 cases, tumor diameter average 1.11cm, the average number of tumors 1.76, 97 cases of bilateral, 232 cases of unilateral, 44.07% of central lymph node metastasis in 329, 57.39% of lateral lymph node metastasis in 115 cases of lateral neck lymph nodes dissection, 35.11% of central lymph node metastasis in 262 cases of patients with a clinincal negative result of central lymph nodes preoperative examination, 28.81% of lateral lymph node metastasis in 59 cases of patients with a negative result of lateral lymph nodes preoperative examination. (1) Papillary thyroid carcinoma those who were in the groups of male, >45 years old, associated with extrathyroidal invasion, the diameter >1cm, absence of other thyroid diseases, absence of nodular goiter had a higher rate of central lymph node metastasis (P=0.028, 0.003, 0.001, 0.000, 0.000, 0.001, espectively). And the group that Ultrasonography examination showed a positive result of central lymph nodes had a higher rate of central lymph node metastasis than the group that Ultrasonography showed a negative result (P=0.000). (2) Papillary thyroid carcinoma those who were in the groups of male, >45 years old, unilateral tumor had a higher rate of lateral lymph node metastasis (P=0.040, 0.008, 0.021, 0.000). And the group of central lymph node metastasis positive had a higher rate of lateral lymph node metastasis than the group of central lymph node metastasis negative (P=0.000). (3) Those clinically examination negative central lymph nodes metastasis papillary thyroid carcinoma who were in the groups of the diameter > 1cm, absence of other thyroid diseases, absence of nodular goiter had a higher rate of central lymph node metastasis(P=0.018, 0.001, 0.004). (4) Those cases with a negative result of lateral cervical lymph nodes examination whom in the group of central lymph node metastasis had a higher rate of lateral lymph node metastasis than the group of absence of central lymph node metastasis(P=0.027). Conclusions: There were certain associations between the central lymph nodes metastasis, lateral lymph node metastasis and clinicopathological features in thyroid papillary carcinoma patients. This is of important significance for clinical treatment choice.",
"__typename": "ArticleAbstractType"
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],
"normalizedAbstract": "Objective: The clinicopathologic features of central area and lateral neck lymph nodes metastasis were retrospectively analyzed in order to better understand the characteristics of cervical lymph node metastasis, and provide an objective reasonable choice basis of surgical treatment cervical lymph node for the surgeons. Methods: All patients from January 2008 to July 2010 in our hospital were collected, 329 cases of resection of thyroid cancer and central lymph node dissection treatment of PTC were analyzed (Including 115 cases of lateral neck lymph nodes dissection at the same time). We then analyzed the correlation between the clinicopathological features of central lymph nodes and lateral lymph node metastasis. Results: The average age of 329 cases of patients was 43 years, male 66 cases, female 263 cases, tumor diameter average 1.11cm, the average number of tumors 1.76, 97 cases of bilateral, 232 cases of unilateral, 44.07% of central lymph node metastasis in 329, 57.39% of lateral lymph node metastasis in 115 cases of lateral neck lymph nodes dissection, 35.11% of central lymph node metastasis in 262 cases of patients with a clinincal negative result of central lymph nodes preoperative examination, 28.81% of lateral lymph node metastasis in 59 cases of patients with a negative result of lateral lymph nodes preoperative examination. (1) Papillary thyroid carcinoma those who were in the groups of male, >45 years old, associated with extrathyroidal invasion, the diameter >1cm, absence of other thyroid diseases, absence of nodular goiter had a higher rate of central lymph node metastasis (P=0.028, 0.003, 0.001, 0.000, 0.000, 0.001, espectively). And the group that Ultrasonography examination showed a positive result of central lymph nodes had a higher rate of central lymph node metastasis than the group that Ultrasonography showed a negative result (P=0.000). (2) Papillary thyroid carcinoma those who were in the groups of male, >45 years old, unilateral tumor had a higher rate of lateral lymph node metastasis (P=0.040, 0.008, 0.021, 0.000). And the group of central lymph node metastasis positive had a higher rate of lateral lymph node metastasis than the group of central lymph node metastasis negative (P=0.000). (3) Those clinically examination negative central lymph nodes metastasis papillary thyroid carcinoma who were in the groups of the diameter > 1cm, absence of other thyroid diseases, absence of nodular goiter had a higher rate of central lymph node metastasis(P=0.018, 0.001, 0.004). (4) Those cases with a negative result of lateral cervical lymph nodes examination whom in the group of central lymph node metastasis had a higher rate of lateral lymph node metastasis than the group of absence of central lymph node metastasis(P=0.027). Conclusions: There were certain associations between the central lymph nodes metastasis, lateral lymph node metastasis and clinicopathological features in thyroid papillary carcinoma patients. This is of important significance for clinical treatment choice.",
"fno": "3906a333",
"keywords": [
"Lymph Nodes",
"Metastasis",
"Neck",
"Tumors",
"Surgery",
"Correlation",
"Lymph Node Metastasis",
"Thyroid Carcinoma"
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"affiliation": null,
"fullName": "Zhihui Sun",
"givenName": "Zhihui",
"surname": "Sun",
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"fullName": "Jia Liu",
"givenName": "Jia",
"surname": "Liu",
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{
"affiliation": null,
"fullName": "Peisong Wang",
"givenName": "Peisong",
"surname": "Wang",
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{
"affiliation": null,
"fullName": "Yanhua Li",
"givenName": "Yanhua",
"surname": "Li",
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{
"affiliation": null,
"fullName": "Zhi Lv",
"givenName": "Zhi",
"surname": "Lv",
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"affiliation": null,
"fullName": "Yi Han",
"givenName": "Yi",
"surname": "Han",
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{
"affiliation": null,
"fullName": "Guang Chen",
"givenName": "Guang",
"surname": "Chen",
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"title": "2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
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"title": "Robust 3D Features for Matching between Distorted Range Scans Captured by Moving Systems",
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"abstract": "Laser range sensors are often demanded to mount on a moving platform for achieving the good efficiency of 3D reconstruction. However, such moving systems often suffer from the difficulty of matching the distorted range scans. In this paper, we propose novel 3D features which can be robustly extracted and matched even for the distorted 3D surface captured by a moving system. Our feature extraction employs Morse theory to construct Morse functions which capture the critical points approximately invariant to the 3D surface distortion. Then for each critical point, we extract support regions with the maximally stable region defined by extremal region or disconnectivity. Our feature description is designed as two steps: 1) we normalize the detected local regions to canonical shapes for robust matching, 2) we encode each key point with multiple vectors at different Morse function values. In experiments, we demonstrate that the proposed 3D features achieve substantially better performance for distorted surface matching than the state-of-the-art methods.",
"abstracts": [
{
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"content": "Laser range sensors are often demanded to mount on a moving platform for achieving the good efficiency of 3D reconstruction. However, such moving systems often suffer from the difficulty of matching the distorted range scans. In this paper, we propose novel 3D features which can be robustly extracted and matched even for the distorted 3D surface captured by a moving system. Our feature extraction employs Morse theory to construct Morse functions which capture the critical points approximately invariant to the 3D surface distortion. Then for each critical point, we extract support regions with the maximally stable region defined by extremal region or disconnectivity. Our feature description is designed as two steps: 1) we normalize the detected local regions to canonical shapes for robust matching, 2) we encode each key point with multiple vectors at different Morse function values. In experiments, we demonstrate that the proposed 3D features achieve substantially better performance for distorted surface matching than the state-of-the-art methods.",
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"fullName": "Xiangqi Huang",
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"title": "Automated Forgery Detection in Multispectral Document Images Using Fuzzy Clustering",
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"abstract": "Multispectral imaging allows for analysis of images in multiple spectral bands. Over the past three decades, airborne and satellite multispectral imaging have been the focus of extensive research in remote sensing. In the recent years, ground based multispectral imaging has gained an immense amount of interest in the fields ranging from computer vision and medical imaging to art, archaeology and computational forensics. The rich information content in multispectral images allows forensic experts to examine the chemical composition of forensic traces. Due to its rapid, non-contact and non-destructive characteristics, multispectral imaging is an effective tool for visualization, age estimation, detection and identification of forensic traces in document images. Ink mismatch is a key indicator of forgery in a document. Inks of different materials exhibit different spectral signature even if they have the same color. Multispectral analysis of questioned documents images allows identification and discrimination of visually similar inks. In this paper, an efficient automatic ink mismatch detection technique is proposed which uses Fuzzy C-Means Clustering to divide the spectral responses of ink pixels in handwritten notes into different clusters which relate to the unique inks used in the document. Sauvola's local thresholding technique is employed to efficiently segment foreground text from the document image. Furthermore, feature selection is used to optimize the performance of the proposed method. The presented method provides better ink discrimination results than state-of-the-art methods when tested on publicly available UWA Writing Inks Dataset.",
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"abstract": "Despite the rapid progress in style transfer, it is challenging of the color ink painting style transfer, because of the ambient characters of plane sense, freehand brushwork and local line sense. In this paper, we explore how to transfer flower photo to color ink painting. Unlike traditional image processing methods, we treat it as a generative problem by taking the advantages of CNN and GAN. Different from common neural style transfer methods, we propose a method that imitates the creation process of color ink painting. Specifically, we divide the task into two subtasks - line drawing extraction and image colorization. Instead of using edge detection algorithms, we take the line drawing as a kind of style and exploit CNN-based neural style transfer method to obtain line drawing. As for image colorization, we use the GAN-based neural style transfer method. Experimental results show that our method performs better than the one-stage neural style transfer methods.",
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"abstract": "In this paper, the classification models in machine learning were combined with hyperspectral imaging technology to identify different brands or different models of stamp-pad inks of the same brand. Spectral acquisition of stamp-pad ink was performed under a hyperspectral imager, and the acquired spectral data was combined with machine learning classification algorithms to build an identification model and predict the class of the delineated prediction samples. The algorithms employed include linear discriminant analysis (LDA), parameter selection of support vector machines based on grid search (grid-SVM) and parameter selection of support vector machines based on particle swarm optimization algorithm (PSO-SVM). After evaluating the identification models established by LDA, grid-SVM and PSO-SVM, the results show that PSO-SVM realizes the best classification results, with the accuracy for six different classes of stamp-pad inks of 96%, with further accuracy for a total of 10 various labels under each class of 95%, thereby achieving the discrimination of ink types that cannot be distinguished by conventional optical methods. Therefore, the model for the identification of stamp-pad ink types that are inaccessible by conventional optical methods was established. Ultimately, the identification of stamp-pad ink types can be realized by combing machine learning with hyperspectral imaging technology, providing a new, scientific and non-destructive examination method for seal examination, document addition and alteration, etc. It also provides an opportunity to build a new platform for the forensic science ink examination.",
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"abstract": "Ink classification is an active topic in historic and forensic document analysis. In this work, we compared the ink classification capabilities of five commonly used and wellproven similarity measures for classification of hyperspectral imaging (HSI). They are Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), Euclidean Distance (ED), Spectral Information Divergence (SID) and Binary Encoding (BE). These techniques were well explored in different fields of HSI; however, they are not investigated in the field of ink classification. This study reveals the ink classification capabilities of these similarity measures. A combination of different types and colors of inks from different manufactures were used to create sample text. The SAM obtained higher accuracy compared to other methods and also identified that, inks that have nearly similar spectral signatures, cause a decline in accuracies due to misclassification between similar classes.",
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"content": "Ink classification is an active topic in historic and forensic document analysis. In this work, we compared the ink classification capabilities of five commonly used and wellproven similarity measures for classification of hyperspectral imaging (HSI). They are Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), Euclidean Distance (ED), Spectral Information Divergence (SID) and Binary Encoding (BE). These techniques were well explored in different fields of HSI; however, they are not investigated in the field of ink classification. This study reveals the ink classification capabilities of these similarity measures. A combination of different types and colors of inks from different manufactures were used to create sample text. The SAM obtained higher accuracy compared to other methods and also identified that, inks that have nearly similar spectral signatures, cause a decline in accuracies due to misclassification between similar classes.",
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"abstract": "Qilianshan tunnel is a key project on Lanzhou-Xinjiang passenger dedicated line, located in Gansu province in the Northwest China. It is subjected to geo-stress in soft rock with rich water. Anisotropic mechanical-hydraulic coupling model was performed to investigate the energy density, effective stress and maximum shear stress, displacements and plastic zone of surrounding rock. Consequently, research results show that estimating pore water pressure distribution is important during construction. Energy, effective stress and the maximum shear stress accumulation zone occur and the peak value is located at 2.1 m from side wall. The displacement of crown is most and reaches to 7 cm which is less than ultimate displacement in teams of Code of Design on Tunnel of Railway. Extracted deformation ahead of working face is significantly affected when the distance is less than 8 m. Transversal plastic zone is mainly located at crown, shoulder and invert. The depth of it is 4 m. Pore water pressure and energy distribution ahead of working face increases firstly, and then it reduces. The peak value is located at 10 m ahead of working face. Not only does the analysis method fit for Qilianshan tunnel, but it can be a reference for similar geological engineering.",
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"title": "2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)",
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"title": "Mining Composite Spatio-Temporal Lifestyle Patterns from Geotagged Social Data",
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"abstract": "As social networks become increasingly integrated with their users’ daily lives, and users are willing to publicly share data about their offline activities on these networks, the resultant data offers a powerful tool to non-intrusively understand city dynamics as it captures human behaviour and interactions. In this paper, we derive lifestyle patterns from the Foursquare social network data, using matrix factorization and tensor decomposition as unsupervised methods to extract latent spatio-temporal behavior patterns. The extracted patterns offer precise definition of activity levels associated with specific lifestyles and showcase that users’ behaviors are a combination of several lifestyles, in contrast to traditional circadian topology theory which classifies individuals to a specific temporal pattern. The obtained patterns can provide deeper insights into city dynamics, the people within them and how society functions.",
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"content": "As social networks become increasingly integrated with their users’ daily lives, and users are willing to publicly share data about their offline activities on these networks, the resultant data offers a powerful tool to non-intrusively understand city dynamics as it captures human behaviour and interactions. In this paper, we derive lifestyle patterns from the Foursquare social network data, using matrix factorization and tensor decomposition as unsupervised methods to extract latent spatio-temporal behavior patterns. The extracted patterns offer precise definition of activity levels associated with specific lifestyles and showcase that users’ behaviors are a combination of several lifestyles, in contrast to traditional circadian topology theory which classifies individuals to a specific temporal pattern. The obtained patterns can provide deeper insights into city dynamics, the people within them and how society functions.",
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"affiliation": "Xian Jiaotong Liverpool University,School of Advanced Technology,Suzhou,China",
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"affiliation": "Chemnitz University of Technology,Faculty of Electrical Engineering,Chemnitz,Germany",
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"content": "Numerous studies have shown that investment banking affiliations generate pressure on analysts to produce optimistic recommendations regarding affiliated stocks. By using a sample of listed companies in Taiwan, this study examined the stock trading of dealer departments, the portfolios of which contained stocks rated by an affiliated analyst. Controlling for various factors, including the dealer affiliation, we conducted a comparison to determine whether the trading behavior for a stock by an affiliated dealer department led to more optimistic analyst forecasts when paralleled to the consensus. If systematic evidence exists regarding dealer trading on the information of analysts' stock price forecasts, information processing is central to the role of the dealer. Therefore, the leakage of confidential information received by traded stocks could result in critical costs. Creating information asymmetry among investors could adversely affect the liquidity of public markets.",
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"abstract": "Putting investment in real estate or in stock? It is a hard decision for the investors to make. So based on the data from the year 1998 to 2007, this article sets up a gray-situation decision model, which shows that in the past 10 years the strategy of investing in real estate is the best, better than investing in stock and than investing in both simultaneously. This article believes that it is not only related to the prosperity of the real estate market for the past 10 years but also to the stock market which can not entitle the investors to gain “ durable income”. In China, it is the alternative effect and squeezable effect rather than the wealth effect that exist between the real estate market and the stock market.",
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"abstract": "the investment value of the stock in small and medium enterprise(SME) board in China need to be analyzed based on the actual data. The 38 stocks has existed above 5 years when Chinese Small and medium-sized enterprise board was founded in 2004, and their the market data is proper to be analyzed. The long-term investment values of the 38 stocks which are bought at the initial public offering price and are hold for more than 5 years is indicated by the difference between the stock market value add the sum of dividend and the initial investment cost, up to some fixed day. The analysis indicated that 94.74% of the 38 stocks have long-term investment value.",
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"abstract": "Previous researches show that investors are not completely rational. Overconfidence is one of the investors irrationalities that have drawn special attention from academics. This study adopts the method of [1] to investigate the relationship between the overconfidence and stock prices, risks and business cycle in the Taiwan stock market. We find that returns in the previous period are positively correlated with turnover rates of the current period, a result consistent with previous researches that investors in the Taiwan stock market exhibit overconfidence. In addition, investors are more likely to have more overconfidence in low-priced stocks than in high-priced stocks and more likely to have more overconfidence in high-risk stocks than low-risk stocks. Investors overconfidence is also more likely to occur in the bull market than in the bear market.",
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"content": "Previous researches show that investors are not completely rational. Overconfidence is one of the investors irrationalities that have drawn special attention from academics. This study adopts the method of [1] to investigate the relationship between the overconfidence and stock prices, risks and business cycle in the Taiwan stock market. We find that returns in the previous period are positively correlated with turnover rates of the current period, a result consistent with previous researches that investors in the Taiwan stock market exhibit overconfidence. In addition, investors are more likely to have more overconfidence in low-priced stocks than in high-priced stocks and more likely to have more overconfidence in high-risk stocks than low-risk stocks. Investors overconfidence is also more likely to occur in the bull market than in the bear market.",
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"title": "An augmented fama and french three-factor model using social interaction",
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"abstract": "We propose that social interaction is a potential risk factor in the asset pricing model of the stock market. “Panorama net” is a website for listed companies and investors to interact in China, which the data extracted from are used. Attention, talkativeness and warmness are constructed from them as a measurement of social interaction. We test whether the social interaction variables provide additional information in the asset pricing model proposed by Fama and French. Empirical results suggest that the social interaction is capable to influence stock return, but it performs differently across industries. In most industries which people are familiar with, such as health care and machinery, social interaction provides additional information; while in most stocks in industries far from daily life, it doesn't help to explain stock return. The results reveals that the social interaction is a potential risk factor in asset pricing model. It also helps listed companies and regulators to utilize interaction website in a better way.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose that social interaction is a potential risk factor in the asset pricing model of the stock market. “Panorama net” is a website for listed companies and investors to interact in China, which the data extracted from are used. Attention, talkativeness and warmness are constructed from them as a measurement of social interaction. We test whether the social interaction variables provide additional information in the asset pricing model proposed by Fama and French. Empirical results suggest that the social interaction is capable to influence stock return, but it performs differently across industries. In most industries which people are familiar with, such as health care and machinery, social interaction provides additional information; while in most stocks in industries far from daily life, it doesn't help to explain stock return. The results reveals that the social interaction is a potential risk factor in asset pricing model. It also helps listed companies and regulators to utilize interaction website in a better way.",
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"normalizedAbstract": "We propose that social interaction is a potential risk factor in the asset pricing model of the stock market. “Panorama net” is a website for listed companies and investors to interact in China, which the data extracted from are used. Attention, talkativeness and warmness are constructed from them as a measurement of social interaction. We test whether the social interaction variables provide additional information in the asset pricing model proposed by Fama and French. Empirical results suggest that the social interaction is capable to influence stock return, but it performs differently across industries. In most industries which people are familiar with, such as health care and machinery, social interaction provides additional information; while in most stocks in industries far from daily life, it doesn't help to explain stock return. The results reveals that the social interaction is a potential risk factor in asset pricing model. It also helps listed companies and regulators to utilize interaction website in a better way.",
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"Industries",
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"authors": [
{
"affiliation": "School of Information Science, Beijing Language and Culture University, Beijing, China",
"fullName": "Lin Huo",
"givenName": "Lin",
"surname": "Huo",
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{
"affiliation": "CEInet Data Co., Ltd. Beijing, China",
"fullName": "Xiaoli Sun",
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"abstract": "It is very useful to endow machines with the ability to understand users' personalized preferences. In this paper, we propose a novel methodology for discovering investors' personalized preferences in stock markets. Our work is able to estimate investors' personalized preferences for each stock and thus helpful for realizing investment recommendation, for instance through recommending real-time news or others' opinions on stocks preferred by the target user. Compared to conventional approaches, our method effectively incorporates stock movements for estimating investors' preference. By capturing stock-movement patterns influencing users' preferences, our method can find users with a similar investment philosophy and then increase the effect of preference prediction. An experimental evaluation with two real-world datasets demonstrates the effectiveness of our approach.",
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"title": "Deep Co-Investment Network Learning for Financial Assets",
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"abstract": "Most recent works model the market structure of the stock market as a correlation network of the stocks. They apply pre-defined patterns to extract correlation information from the time series of stocks. Without considering the influences of the evolving market structure to the market index trends, these methods hardly obtain the market structure models which are compatible with the market principles. Advancements in deep learning have shown their incredible modeling capacity on various finance-related tasks. However, the learned inner parameters, which capture the essence of the finance time series, are not further exploited about their representation in the financial fields. In this work, we model the financial market structure as a deep co-investment network and propose a Deep Co-investment Network Learning (DeepCNL) method. DeepCNL automatically learns deep co-investment patterns between any pairwise stocks, where the rise-fall trends of the market index are used for distance supervision. The learned inner parameters of the trained DeepCNL, which encodes the temporal dynamics of deep co-investment patterns, are used to build the co-investment network between the stocks as the investment structure of the corresponding market. We verify the effectiveness of DeepCNL on the real-world stock data and compare it with the existing methods on several financial tasks. The experimental results show that DeepCNL not only has the ability to better reflect the stock market structure that is consistent with widely-acknowledged financial principles but also is more capable to approximate the investment activities which lead to the stock performance reported in the real news or research reports than other alternatives.",
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"content": "Most recent works model the market structure of the stock market as a correlation network of the stocks. They apply pre-defined patterns to extract correlation information from the time series of stocks. Without considering the influences of the evolving market structure to the market index trends, these methods hardly obtain the market structure models which are compatible with the market principles. Advancements in deep learning have shown their incredible modeling capacity on various finance-related tasks. However, the learned inner parameters, which capture the essence of the finance time series, are not further exploited about their representation in the financial fields. In this work, we model the financial market structure as a deep co-investment network and propose a Deep Co-investment Network Learning (DeepCNL) method. DeepCNL automatically learns deep co-investment patterns between any pairwise stocks, where the rise-fall trends of the market index are used for distance supervision. The learned inner parameters of the trained DeepCNL, which encodes the temporal dynamics of deep co-investment patterns, are used to build the co-investment network between the stocks as the investment structure of the corresponding market. We verify the effectiveness of DeepCNL on the real-world stock data and compare it with the existing methods on several financial tasks. The experimental results show that DeepCNL not only has the ability to better reflect the stock market structure that is consistent with widely-acknowledged financial principles but also is more capable to approximate the investment activities which lead to the stock performance reported in the real news or research reports than other alternatives.",
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"affiliation": "Central Univ. of Finance & Econ., Beijing, China",
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"affiliation": "Dept. of Comput. Sci., Univ. of Illinois at Chicago, Chicago, IL, USA",
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"abstract": "Optical flow is a widely used technique for extracting flow information from video images. While it is useful for estimating temporary movement in video images, it only captures one aspect of extracting dominant flow information from a sequence of video images. In this paper, we propose a novel flow extraction approach called causal flow, which can estimate the dominant causal relationships among nearby pixels. We assume flows in video images as pixel-to-pixel information transfer, whereas the optical flow measures the relative motion of pixels. Causal flow is based on Granger causality test, which measures causal influence based on prediction via vector autoregression, and is widely used in economics and brain science. The experimental results demonstrate that causal flow can extract dominant flow information which cannot be obtained by current methods.",
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"title": "Causal Extraction from the Literature of Pressure Injury and Risk Factors",
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"abstract": "Literature for evidence on factors that put an individual at risk of pressure injury usually focused on identifying independent pressure injury risk factors. It is hard to find how important each factor is through the literature. By extracting casual relations, we can tackle the vast volume of causal knowledge and establish causal graphs. In this paper, we aim to use an unsupervised learning model to extract causal relations between pressure injury and risk factors. The workflow includes data preprocessing, causality determination, causality verification, and knowledge graph drawing. We conduct extensive experiments on a medical literature data set of 10,000 abstracts crawling from Pubmed and compare the knowledge graph we draw with the latest international guideline to verify the accuracy. We study 12 pressure injury risk factors and finally extract 10 relations between pressure injury and risk factors with the correct ratio 8/10, and 17 relations in the risk factor pairs with the correct ratio 16/17. The average credibility of extracting relations between pressure injury and risk factors is 0.7317, and 0.8983 for extracting relations of the 17 risk factor pairs. It indicates that the proposed method of extracting causal relations from the literature of pressure injury has a high degree of credibility.",
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"content": "Literature for evidence on factors that put an individual at risk of pressure injury usually focused on identifying independent pressure injury risk factors. It is hard to find how important each factor is through the literature. By extracting casual relations, we can tackle the vast volume of causal knowledge and establish causal graphs. In this paper, we aim to use an unsupervised learning model to extract causal relations between pressure injury and risk factors. The workflow includes data preprocessing, causality determination, causality verification, and knowledge graph drawing. We conduct extensive experiments on a medical literature data set of 10,000 abstracts crawling from Pubmed and compare the knowledge graph we draw with the latest international guideline to verify the accuracy. We study 12 pressure injury risk factors and finally extract 10 relations between pressure injury and risk factors with the correct ratio 8/10, and 17 relations in the risk factor pairs with the correct ratio 16/17. The average credibility of extracting relations between pressure injury and risk factors is 0.7317, and 0.8983 for extracting relations of the 17 risk factor pairs. It indicates that the proposed method of extracting causal relations from the literature of pressure injury has a high degree of credibility.",
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"keywords": [
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"Data Mining",
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"affiliation": "Hefei University of Technology,Key Laboratory of Knowledge Engineering with Big Data of the Ministry of Education, School of Computer Science and Information Engineering,Hefei,China",
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"affiliation": "Hefei University of Technology,Key Laboratory of Knowledge Engineering with Big Data of the Ministry of Education, School of Computer Science and Information Engineering,Hefei,China",
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"abstract": "Comfortable locomotion in VR based games is crucial. Simulation sickness, caused by fast optical movement, lag or mismatch in forces, threatens this comfort and fosters a negative attitude towards further VR experiences. The design of the locomotion interface has a direct impact on the likelihood of inducing sickness. General paradigms and guidelines are being adopted by the game development community, but more data is needed. We use both subjective and objective methods to compare two common modes of travel, teleportation and driving along a fixed track. Our results show that teleportation causes fewer symptoms of sickness and leaves a more positive impression of VR.",
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"content": "Comfortable locomotion in VR based games is crucial. Simulation sickness, caused by fast optical movement, lag or mismatch in forces, threatens this comfort and fosters a negative attitude towards further VR experiences. The design of the locomotion interface has a direct impact on the likelihood of inducing sickness. General paradigms and guidelines are being adopted by the game development community, but more data is needed. We use both subjective and objective methods to compare two common modes of travel, teleportation and driving along a fixed track. Our results show that teleportation causes fewer symptoms of sickness and leaves a more positive impression of VR.",
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"content": "Most existing Virtual Reality (VR) locomotion interfaces are designed for ground-based locomotion, limiting the degrees of freedom (DoF) during movement as they would in the real world. However, an optimized three-dimensional travel technique is required for certain virtual scenes such as flying and diving. This study evaluated three different interface types: Slider, Teleport, and Point-Tug, that were created based on existing ground-based locomotion methods in order to investigate the features required for three-dimensional (3D) movement. We conducted a within-subjects study with 3D navigation tasks and evaluated the performance when navigating a virtual environment using three different 3D locomotion interfaces. The results show that Slider, which allows users to move continuously, has an advantage over the others, and interfaces such as teleportation, which are widely used in ground-based locomotion, are likely to be perceived differently in 3D locomotion.",
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"affiliation": "Osaka University,Japan",
"fullName": "Donghae Lim",
"givenName": "Donghae",
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"affiliation": "Osaka University,Japan",
"fullName": "Shizuka Shirai",
"givenName": "Shizuka",
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"affiliation": "Augusta University,United States",
"fullName": "Jason Orlosky",
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"affiliation": "Osaka Institute of Technology,Japan",
"fullName": "Photchara Ratsamee",
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"proceeding": {
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"abstract": "We experimentally assessed the relative contributions of tactual and auditory information to multisensory (i.e., bimodal) judgments of surface roughness using a rigid probe. Participants judged the magnitude of surface roughness and their corresponding confidence in three modality conditions: touch-only, audition-only (i.e., touch-produced sounds only) and touch+audition. The results indicated that touch cues were weighted 62% and auditory cues 38% in the bimodal judgments. Participants also proved to be more confident of their judgments in the bimodal condition. Implications for the creation of virtual roughness presented through uni- vs. multimodal interfaces is also addressed.",
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"content": "We experimentally assessed the relative contributions of tactual and auditory information to multisensory (i.e., bimodal) judgments of surface roughness using a rigid probe. Participants judged the magnitude of surface roughness and their corresponding confidence in three modality conditions: touch-only, audition-only (i.e., touch-produced sounds only) and touch+audition. The results indicated that touch cues were weighted 62% and auditory cues 38% in the bimodal judgments. Participants also proved to be more confident of their judgments in the bimodal condition. Implications for the creation of virtual roughness presented through uni- vs. multimodal interfaces is also addressed.",
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"affiliation": "Queen's University",
"fullName": "S.J. Lederman",
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{
"affiliation": "Queen's University",
"fullName": "T. Morgan",
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{
"affiliation": "Queen's University",
"fullName": "C. Hamilton",
"givenName": "C.",
"surname": "Hamilton",
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{
"affiliation": "Carnegie Mellon University",
"fullName": "R.L. Klatzky",
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"doi": "10.1109/VR.2009.4811061",
"title": "A VR Multimodal Interface for Small Artifacts in the Gold Museum",
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"abstract": "The Gold Museum, in Bogota, Colombia, displays the largest collection of pre-Hispanic gold artifacts in the world and it has been renovated recently. With funds from the Colombian Government, we have created a multimodal experience that allows visitors to touch, hear, and see small artifacts. Here we present a description of this demo, its functionality, and technical requirements.",
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"content": "The Gold Museum, in Bogota, Colombia, displays the largest collection of pre-Hispanic gold artifacts in the world and it has been renovated recently. With funds from the Colombian Government, we have created a multimodal experience that allows visitors to touch, hear, and see small artifacts. Here we present a description of this demo, its functionality, and technical requirements.",
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"affiliation": "Universid de los Andes, Colombia, e-mail: jua-bord@uniandes.edu.co",
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"affiliation": "Museo del Oro, Colombia, e-mail: elondola@banrep.gov.co",
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"affiliation": "Universidad de los Andes, Colombia, e-mail: dieg-res@uniandes.edu.co",
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"affiliation": "Universidad Nacional de,Colombia, e-mail: faprietoo@unal.edu.co",
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"title": "Studying the Role of Self and External Touch in the Appropriation of Dysmorphic Hands",
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"abstract": "In Virtual Reality, self-touch (ST) stimulation is a promising method of sense of body ownership (SoBO) induction that does not require an external effector. However, its applicability to dysmorphic bodies has not been explored yet and remains uncertain due to the requirement to provide incongruent visuomotor sensations. In this, paper, we studied the effect of ST stimulation on dysmorphic hands via haptic retargeting, as compared to a classical external-touch (ET) stimulation, on the SoBO. Our results indicate that ST can induce similar levels of dysmorphic SoBO than ET stimulation, but that some types of dysmorphism might decrease the ST stimulation accuracy due to the nature of the re-targeting that they induce.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In Virtual Reality, self-touch (ST) stimulation is a promising method of sense of body ownership (SoBO) induction that does not require an external effector. However, its applicability to dysmorphic bodies has not been explored yet and remains uncertain due to the requirement to provide incongruent visuomotor sensations. In this, paper, we studied the effect of ST stimulation on dysmorphic hands via haptic retargeting, as compared to a classical external-touch (ET) stimulation, on the SoBO. Our results indicate that ST can induce similar levels of dysmorphic SoBO than ET stimulation, but that some types of dysmorphism might decrease the ST stimulation accuracy due to the nature of the re-targeting that they induce.",
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"abstract": "The Property prediction of apparel textile based on the model of yarn structure is important. Especially, the prediction is important for the Kansei performance of textile products. It is necessary to create a model of the textile structure for predicting the physical properties of textiles. In this study the textile structure model is created based on the actual operation of the loom. The structural model of the textiles is composed of the yarn model. In this case, Breen's particle model was used for the yarn model. In this study, by the above method, we created several models of fabrics. As a result, different fabric models are found to have a representation according to the characteristics of the structure of each thread. This method shows the possibility of simulating the characteristics of various fabrics made from yarn with different characteristics.",
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"title": "An interactive tool for yarn strength prediction using support vector regression",
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"abstract": "Cotton, popularly known as White Gold has been an important commercial crop of National significance due to the immense influence of its rural economy. Transfer of technology to identify the quality of fibre is gaining importance. The physical characteristics of cotton such as fiber length, length distribution, trash value, color grade, strength, shape, tenacity, density, moisture absorption, dimensional stability, resistance, thermal reaction, count, etc., contributes to determine the quality of cotton and in turn yarn strength. In this paper yarn strength prediction has been modeled using regression. Support Vector regression, the supervised machine learning technique has been employed for predicting the yarn strength. The trained model was evaluated based on mean squared error and correlation coefficient and was found that the prediction accuracy of SVR based model, the intelligence reasoning method is higher compared with the traditional statistical regression, the least square regression model.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Cotton, popularly known as White Gold has been an important commercial crop of National significance due to the immense influence of its rural economy. Transfer of technology to identify the quality of fibre is gaining importance. The physical characteristics of cotton such as fiber length, length distribution, trash value, color grade, strength, shape, tenacity, density, moisture absorption, dimensional stability, resistance, thermal reaction, count, etc., contributes to determine the quality of cotton and in turn yarn strength. In this paper yarn strength prediction has been modeled using regression. Support Vector regression, the supervised machine learning technique has been employed for predicting the yarn strength. The trained model was evaluated based on mean squared error and correlation coefficient and was found that the prediction accuracy of SVR based model, the intelligence reasoning method is higher compared with the traditional statistical regression, the least square regression model.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Cotton, popularly known as White Gold has been an important commercial crop of National significance due to the immense influence of its rural economy. Transfer of technology to identify the quality of fibre is gaining importance. The physical characteristics of cotton such as fiber length, length distribution, trash value, color grade, strength, shape, tenacity, density, moisture absorption, dimensional stability, resistance, thermal reaction, count, etc., contributes to determine the quality of cotton and in turn yarn strength. In this paper yarn strength prediction has been modeled using regression. Support Vector regression, the supervised machine learning technique has been employed for predicting the yarn strength. The trained model was evaluated based on mean squared error and correlation coefficient and was found that the prediction accuracy of SVR based model, the intelligence reasoning method is higher compared with the traditional statistical regression, the least square regression model.",
"fno": "05460714",
"keywords": [
"Cotton",
"Crops",
"Inference Mechanisms",
"Interactive Systems",
"Learning Artificial Intelligence",
"Mean Square Error Methods",
"Production Engineering Computing",
"Regression Analysis",
"Support Vector Machines",
"Tensile Strength",
"Textile Fibres",
"Yarn",
"Interactive Tool",
"Yarn Strength Prediction",
"Support Vector Regression",
"Cotton",
"White Gold",
"Commercial Crop",
"Rural Economy",
"Fibre Quality",
"Fiber Length",
"Length Distribution",
"Trash Value",
"Color Grade",
"Supervised Machine Learning",
"Mean Squared Error",
"Correlation Coefficient",
"Intelligence Reasoning",
"Yarn",
"Predictive Models",
"Cotton",
"Thermal Resistance",
"Gold",
"Crops",
"Shape",
"Moisture",
"Absorption",
"Thermal Stability",
"Support Vector Machine",
"Support Vector Regression",
"Yarn Strength",
"Least Square Regression"
],
"authors": [
{
"affiliation": null,
"fullName": "Selvanayaki M.",
"givenName": "Selvanayaki",
"surname": "M.",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Vijaya M.S.",
"givenName": "Vijaya",
"surname": "M.S.",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Jamuna K.S.",
"givenName": "Jamuna",
"surname": "K.S.",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Karpagavalli S.",
"givenName": "Karpagavalli",
"surname": "S.",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icmlc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2010-02-01T00:00:00",
"pubType": "proceedings",
"pages": "335-339",
"year": "2010",
"issn": null,
"isbn": "978-1-4244-6006-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
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