The application of computer in the quantitative analysis chemistry experiment is a chemistry experiment teaching applications software, developed by Visual Basic （6.0）, based on the content of quantitative analysis ...The application of computer in the quantitative analysis chemistry experiment is a chemistry experiment teaching applications software, developed by Visual Basic （6.0）, based on the content of quantitative analysis chemistry experiment of chemistry major in higher institute. This software has the function of the automatic processing the experimental data, the automatic generation of test report copies, and the automatic evaluation of students＇ experimental results, which solve the reliability, objectivity and accuracy problems of the students＇ experiment data processing and evaluation, and avoid interference with human factors. The software has the characteristic of the easy installation, the easy operation, the strong practicability, pertinence, the systematicness and the running stability, so it provides a platform in the quantitative analysis chemistry experiment for the students＇ assessment system of automatic processing, and it has a high popularization value. The project＇s technical route design is reasonable, the research method is correct, and the experimental data processing results are reliable, which has reached the leading domestic level in the quantitative analysis chemistry experiment teaching field of computer data processing. And this project has been through the achievements appraisal of Gansu Provincial Sci. ＆ Tech. Department.展开更多
According to the regulations of the People＇s Republic of China national standard as the basis, on the part of chemical industry product quality inspection and analysis of the implementation of computer management has...According to the regulations of the People＇s Republic of China national standard as the basis, on the part of chemical industry product quality inspection and analysis of the implementation of computer management has developed a set of software applications, the software in chemical products quality inspection and analysis of the means of management is an innovation. The software functions, can automatically process data, judge the product grade, quality analysis, objective and fair, convenient, fast, accurate, stable, practical, and easy to popularize.展开更多
We investigate the properties of the ponderomotive squeezing in an optomechanical system coupled to a charged nanomecbanical oscillator （NMO） nearby via Coulomb force. We find that the introduction of Coulomb intera...We investigate the properties of the ponderomotive squeezing in an optomechanical system coupled to a charged nanomecbanical oscillator （NMO） nearby via Coulomb force. We find that the introduction of Coulomb interaction allows the generation of squeezed output light from this system. Our numerical results show that the degree of squeezing can be tuned by the Coulomb coupling strength, the power of laser, and the frequencies of NMOs. Furthermore, the squeezing generated in our approach can be used to measure the Coulomb coupling strength.展开更多
In recent years,utilizing the low-rank prior information to construct a signal from a small amount of measures has attracted much attention.In this paper,a generalized nonconvex low-rank(GNLR) algorithm for magnetic r...In recent years,utilizing the low-rank prior information to construct a signal from a small amount of measures has attracted much attention.In this paper,a generalized nonconvex low-rank(GNLR) algorithm for magnetic resonance imaging(MRI)reconstruction is proposed,which reconstructs the image from highly under-sampled k-space data.In the algorithm,the nonconvex surrogate function replacing the conventional nuclear norm is utilized to enhance the low-rank property inherent in the reconstructed image.An alternative direction multiplier method(ADMM) is applied to solving the resulting non-convex model.Extensive experimental results have demonstrated that the proposed method can consistently recover MRIs efficiently,and outperforms the current state-of-the-art approaches in terms of higher peak signal-to-noise ratio(PSNR) and lower high-frequency error norm(HFEN) values.展开更多
As one of the most important mathematics-physics equations, heat equation has been widely used in engineering area and computing science research. Large-scale heat problems are difficult to solve due to computational ...As one of the most important mathematics-physics equations, heat equation has been widely used in engineering area and computing science research. Large-scale heat problems are difficult to solve due to computational intractability. The parallelization of heat equation is available to improve the simulation model efficiency. In order to solve the three-dimensional heat problems more rapidly, the OpenMP was adopted to parallelize the preconditioned conjugate gradient （PCG） algorithm in this paper. A numerical experiment on the three-dimensional heat equation model was carried out on a computer with four cores. Based on the test results, it is found that the execution time of the original serial PCG program is about 1.71 to 2.81 times of the parallel PCG program executed with different number of threads. The experiment results also demonstrate the available performance of the parallel PCG algorithm based on OpenMP in terms of solution quality and computational performance.展开更多
Image feature optimization is an important means to deal with high-dimensional image data in image semantic understanding and its applications. We formulate image feature optimization as the establishment of a mapping...Image feature optimization is an important means to deal with high-dimensional image data in image semantic understanding and its applications. We formulate image feature optimization as the establishment of a mapping between highand low-dimensional space via a five-tuple model. Nonlinear dimensionality reduction based on manifold learning provides a feasible way for solving such a problem. We propose a novel globular neighborhood based locally linear embedding (GNLLE) algorithm using neighborhood update and an incremental neighbor search scheme, which not only can handle sparse datasets but also has strong anti-noise capability and good topological stability. Given that the distance measure adopted in nonlinear dimensionality reduction is usually based on pairwise similarity calculation, we also present a globular neighborhood and path clustering based locally linear embedding (GNPCLLE) algorithm based on path-based clustering. Due to its full consideration of correlations between image data, GNPCLLE can eliminate the distortion of the overall topological structure within the dataset on the manifold. Experimental results on two image sets show the effectiveness and efficiency of the proposed algorithms.展开更多
Uncovering shilling attackers hidden in recommender systems is very crucial to enhance the robustness and trustworthiness of product recommendation. Many shilling attack detection algorithms have been proposed so far,...Uncovering shilling attackers hidden in recommender systems is very crucial to enhance the robustness and trustworthiness of product recommendation. Many shilling attack detection algorithms have been proposed so far, and they exhibit complementary advantage and disadvantage towards various types of attackers. In this paper, we provide a thorough experimental comparison of several well-known detectors, including supervised C4.5 and NB, unsupervised PCA and MDS, semi-supervised HySAD methods, as well as statistical analysis methods. MovieLens 100K is the most widely-used dataset in the realm of shilling attack detection, and thus it is selected as the benchmark dataset. Meanwhile, seven types of shilling attacks generated by average-filling and random-filling model are compared in our experiments. As a result of our analysis, we show clearly causes and essential characteristics insider attackers that might determine the success or failure of different kinds of detectors.展开更多
文摘The application of computer in the quantitative analysis chemistry experiment is a chemistry experiment teaching applications software, developed by Visual Basic （6.0）, based on the content of quantitative analysis chemistry experiment of chemistry major in higher institute. This software has the function of the automatic processing the experimental data, the automatic generation of test report copies, and the automatic evaluation of students＇ experimental results, which solve the reliability, objectivity and accuracy problems of the students＇ experiment data processing and evaluation, and avoid interference with human factors. The software has the characteristic of the easy installation, the easy operation, the strong practicability, pertinence, the systematicness and the running stability, so it provides a platform in the quantitative analysis chemistry experiment for the students＇ assessment system of automatic processing, and it has a high popularization value. The project＇s technical route design is reasonable, the research method is correct, and the experimental data processing results are reliable, which has reached the leading domestic level in the quantitative analysis chemistry experiment teaching field of computer data processing. And this project has been through the achievements appraisal of Gansu Provincial Sci. ＆ Tech. Department.
文摘According to the regulations of the People＇s Republic of China national standard as the basis, on the part of chemical industry product quality inspection and analysis of the implementation of computer management has developed a set of software applications, the software in chemical products quality inspection and analysis of the means of management is an innovation. The software functions, can automatically process data, judge the product grade, quality analysis, objective and fair, convenient, fast, accurate, stable, practical, and easy to popularize.
基金Acknowledgment： The work is supported by the National Natural Science Foundation of China #60675006 and the National Key Technology R＆D Program during the l lth Five-Year Plan Period #2006BAI03A09.
文摘We investigate the properties of the ponderomotive squeezing in an optomechanical system coupled to a charged nanomecbanical oscillator （NMO） nearby via Coulomb force. We find that the introduction of Coulomb interaction allows the generation of squeezed output light from this system. Our numerical results show that the degree of squeezing can be tuned by the Coulomb coupling strength, the power of laser, and the frequencies of NMOs. Furthermore, the squeezing generated in our approach can be used to measure the Coulomb coupling strength.
基金National Natural Science Foundations of China(Nos.61362001,61365013,51165033)the Science and Technology Department of Jiangxi Province of China(Nos.20132BAB211030,20122BAB211015)+1 种基金the Jiangxi Advanced Projects for Postdoctoral Research Funds,China(o.2014KY02)the Innovation Special Fund Project of Nanchang University,China(o.cx2015136)
文摘In recent years,utilizing the low-rank prior information to construct a signal from a small amount of measures has attracted much attention.In this paper,a generalized nonconvex low-rank(GNLR) algorithm for magnetic resonance imaging(MRI)reconstruction is proposed,which reconstructs the image from highly under-sampled k-space data.In the algorithm,the nonconvex surrogate function replacing the conventional nuclear norm is utilized to enhance the low-rank property inherent in the reconstructed image.An alternative direction multiplier method(ADMM) is applied to solving the resulting non-convex model.Extensive experimental results have demonstrated that the proposed method can consistently recover MRIs efficiently,and outperforms the current state-of-the-art approaches in terms of higher peak signal-to-noise ratio(PSNR) and lower high-frequency error norm(HFEN) values.
文摘As one of the most important mathematics-physics equations, heat equation has been widely used in engineering area and computing science research. Large-scale heat problems are difficult to solve due to computational intractability. The parallelization of heat equation is available to improve the simulation model efficiency. In order to solve the three-dimensional heat problems more rapidly, the OpenMP was adopted to parallelize the preconditioned conjugate gradient （PCG） algorithm in this paper. A numerical experiment on the three-dimensional heat equation model was carried out on a computer with four cores. Based on the test results, it is found that the execution time of the original serial PCG program is about 1.71 to 2.81 times of the parallel PCG program executed with different number of threads. The experiment results also demonstrate the available performance of the parallel PCG algorithm based on OpenMP in terms of solution quality and computational performance.
基金Project (No 2008AA01Z132) supported by the National High-Tech Research and Development Program of China
文摘Image feature optimization is an important means to deal with high-dimensional image data in image semantic understanding and its applications. We formulate image feature optimization as the establishment of a mapping between highand low-dimensional space via a five-tuple model. Nonlinear dimensionality reduction based on manifold learning provides a feasible way for solving such a problem. We propose a novel globular neighborhood based locally linear embedding (GNLLE) algorithm using neighborhood update and an incremental neighbor search scheme, which not only can handle sparse datasets but also has strong anti-noise capability and good topological stability. Given that the distance measure adopted in nonlinear dimensionality reduction is usually based on pairwise similarity calculation, we also present a globular neighborhood and path clustering based locally linear embedding (GNPCLLE) algorithm based on path-based clustering. Due to its full consideration of correlations between image data, GNPCLLE can eliminate the distortion of the overall topological structure within the dataset on the manifold. Experimental results on two image sets show the effectiveness and efficiency of the proposed algorithms.
文摘Uncovering shilling attackers hidden in recommender systems is very crucial to enhance the robustness and trustworthiness of product recommendation. Many shilling attack detection algorithms have been proposed so far, and they exhibit complementary advantage and disadvantage towards various types of attackers. In this paper, we provide a thorough experimental comparison of several well-known detectors, including supervised C4.5 and NB, unsupervised PCA and MDS, semi-supervised HySAD methods, as well as statistical analysis methods. MovieLens 100K is the most widely-used dataset in the realm of shilling attack detection, and thus it is selected as the benchmark dataset. Meanwhile, seven types of shilling attacks generated by average-filling and random-filling model are compared in our experiments. As a result of our analysis, we show clearly causes and essential characteristics insider attackers that might determine the success or failure of different kinds of detectors.
