Gray Classes Research Articles

College multimedia teaching system devise and application evaluation

Aiming at multimedia teaching system is one of the important links in the current information construction and teaching quality evaluation of colleges and universities. Design multimedia teaching system, on the one hand, from the perspective of software design for other users to provide reference; on the other hand, according to the multilevel gray system evaluation theory, making multimedia teaching evaluation, to determine the index value; index weight; sample matrix; evaluation of gray classes, etc., for the evaluation of teachers’ multimedia teaching skills to make a comprehensive evaluation, make originally not quantitative evaluation, multimedia teaching more scientific and more reasonable and more accurate quantitative evaluation, through actual application, good results have been achieved.

Privacy-preserving deep learning algorithm for big personal data analysis

For privacy-preserving analysing of big data, a deep learning method is proposed. The method transforms the sensitive part of the personal information into non-sensitive data. To implement this process, two-stage architecture is proposed. The modified sparse denoising autoencoder and CNN models have been used in the architecture. Modified sparse denoising autoencoder performs transformation of data and CNN classifies the transformed data. In order to achieve low loss in data transformation, the sparsification parameter is added to the objective function of the autoencoder by the Kullback–Leibler divergence function. Here, the efficiency evaluation of the model is conducted by the MSE (mean squared error) loss function. In order to evaluate the accuracy of the transformation process, the features derived from the sparse denoising autoencoder algorithm fed to the input of the deep CNN algorithm and the classification of the reconstructed data is classified to the Black (0), White (1) and Gray (2) classes. Since here conducted the transformation of the Black class data to the Gray class data, in the classification stage, the CNN algorithm is classified the Black class data as the Gray class with 0.99 accuracy. The comparison of the proposed method with simple autoencoder is provided and experiments conducted on Cleveland medical dataset extracted from the Heart Disease dataset, Arrhythmia and Skoda datasets showed that the proposed method outperforms other conventional methods.

Wearing Comfort and Electromagnetic Shielding Effectiveness for Shielding Fabrics Based on Grey Cluster Analysis

In this paper, the comprehensive property of shielding fabrics was analyzed by the mathematic method-grey cluster analysis. Eight samples of shielding fabrics were selected as research objects in the experiment. The electromagnetic shielding effectiveness in different frequencies and wearing comfort, including tensile and bending property, abrasive resistance, permeability and color fastness were measured and then analyzed. Grey cluster analysis was carried out to evaluate the comprehensive property of the chosen samples by eight clustering objects and nine clustering indexes. In the process of data operation, MATLAB7.0 was used to calculate experimental results due to its high efficiency and accuracy. According to cluster analysis results, the eight samples were divided into three gray classes, namely, 2#, 5# belonging to “first-rate”, 4# and 7# belonging to “medium” and 1#, 3#, 6#,8# belonging to “low-rate”.

Electromagnetic shielding effectiveness and wearing comfort of radiation protection fabrics based on gray clustering analysis

In this study, the comprehensive property of several radiation protection fabrics was analyzed by gray clustering analysis (GCA). Nine samples of chemical plating, silver fiber, and stainless steel fiber were selected as the research objects. The electromagnetic shielding effectiveness in different frequencies and wearing comfort, including tensile and bending property, air transmission and abrasive resistance, was investigated. GCA was carried out to evaluate the comprehensive property of samples by nine clustering objects and seven clustering indexes. In the process of data operation, MATLAB7.0 was used to calculate experimental results due to its high efficiency and accuracy. The results of clustering analysis demonstrated that nine samples can be divided into three gray classes, namely, 4# and 5# belonging to “first-rate”; 1#, 3#, and 6# belonging to “medium”; and 2#, 7#, 8#, and 9# belonging to “low-rate”.

Research on the Gray Hierarchy Evaluation Model Based on Multimedia System and English Teaching Evaluation

Network technology and multimedia are gaining momentum. They accelerate the reform of the educational sector. Traditional educational mode is integrated with new technology and a multimedia network education system is taking shape. As a result, traditional English teaching system has experienced a progressed reform. The evaluation of English teaching system in multimedia network is for the purpose of measuring the level and efficacy of the integrated new multimedia technology. This paper studies the English teaching system in multimedia network, adopts Analytic Hierarchy Process (AHP) to conclude 1 first-class index, 5 second-class indexes and 21 three-class indexes. It employs the Grey Evaluation and Matlab software for the comprehensive evaluation of 30 teaching systems and classifies the results by gray classes. By studying the evaluation principle of English teaching system in multimedia network, this paper intends to provide the algorithm with theoretical foundations so that the system can better serve students.

Risk assessment of rainstorm and flood disasters in China between 2004 and 2009 based on gray fixed weight cluster analysis

Rainstorm and flood disasters frequently occur in China, causing heavy losses for people’s lives and property and reducing the capability of sustainable development of the national and local economy. In this study, the risks of the rainstorm and flood disasters are assessed for the Chinese mainland, excluding Hong Kong, Macao, and Taiwan and also employ the historical data of seven indicators, including the affected area of crops, the affected population, the direct economic loss, and etc., from 2004 to 2009. Based on the large 1,302 historical sample data, the impact of rainstorm and flood disasters were analyzed using the methodology of gray fixed weight cluster analysis according to disaster losses, which were divided into the three gray classes of high, medium, and low. The regional differences of the risk assessment of the rainstorm and flood disasters are discussed, and the dynamical risk zoning map is conducted. The results show a consistent conclusion with the actual losses of rainstorm and flood disasters over each administrative district, which can provide more scientific evidence for the relevant departments of disaster prevention and mitigation.

Effect of long-term treatment with raloxifene on mammary density in postmenopausal women

To evaluate in a group of postmenopausal women the effects of long-term raloxifene treatment on breast density using a digitized analysis of mammograms and on insulinlike growth factor-1 (IGF-1), insulinlike growth factor binding protein-3 (IGFBP-3), and sex hormone-binding globulin (SHBG) plasma levels. Seventy healthy postmenopausal women with normal body weight were enrolled in this study and were divided into two groups based on their bone status, evaluated by dual-energy x-ray at the lumbar spine (L2-4). Fifty women (chronological age 52.4 +/- 4.1 y, menopausal age 42.1 +/- 3.9 y), in whom the L2-4 T score was less than -2.5 SD, were treated with raloxifene HCl 60 mg/day orally for 2 years. The other 20 women (chronological age 53.6 +/- 3.5 y, age at menopause 43.1 +/- 3.6 y), in whom the L2-4 T score ranged between -1 and -2.5 SD, were enrolled as controls. All 70 women received calcium (1 g/d orally) and cholecalciferol (880 UI/d orally) supplementation. Moreover, all women followed a normocaloric and personalized diet. All women had mammography at baseline and after 2 years of therapy. The mammographic images on traditional support (radiography) were acquired by using a film scanner and were then elaborated by means of ad hoc software. Moreover, assessments of IGF-1, IGFBP-3, and SHBG plasma levels were obtained at baseline and after 24 months. After 24 months of therapy, there was a significant variation in the raloxifene-treated group with respect to baseline in the distribution of gray classes of radiographic images. In particular, an attenuation of graphic trace with a reduction of the areas with the lowest and most elevated gray classes was observed. In the control group, no significant variations of graphic traces were observed. Moreover, raloxifene treatment significantly reduced IGF-1 and increased IGFBP-3 and SHBG plasma levels at 24 months. During follow-up, IGF-1, IGFPB-3, and SHBG levels did not change significantly in the control group. Long-term treatment with raloxifene in a population of postmenopausal women is able to reduce breast density. Such an effect could perhaps explain the reduction in the incidence of mammary carcinoma observed in the Multiple Outcomes of Raloxifene Evaluation study probably due to the direct antiestrogenic activity of raloxifene on mammalian tissue and/or its indirect activity increasing SHBG levels or modifying the IGF-1/IGFBP-3 ratio.

An evaluation of seasat SAR imagery for urban analysis

Digitally processed Seasat SAR imagery of the Denver, Colorado, area is analyzed with regard to the types of urban data that can be detected and/or inferred from satellite-borne L-band systems. Black-and-white images of the scene were generated at three scales to determine the advantages and detail discernible at each level of display. The large-scale imagery was density-sliced to evaluate the feasibility of producing a semiautomated land-cover classification from the SAR data. Gray level classes were assigned colors to aid interpretation and subsequently compared with the black-and-white images to assess the contribution of each technique and benefits of combining the data from both procedures.