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Remeshing Visual Hull Approximation By Displaced Butterfly Subdivision Surfaces, Jung Lee, Chang-Hun Kim, Sun-Jeong Kim
Remeshing Visual Hull Approximation By Displaced Butterfly Subdivision Surfaces, Jung Lee, Chang-Hun Kim, Sun-Jeong Kim
Applied Mathematics & Information Sciences
This paper proposes a new procedure for generating a displaced butterfly subdivision surface from multiple images. First, point geometry of the target object is recovered by combining LDC(Layered Depth Cube) surfel sampling scheme with the concept of visual hull based on the input images. Then the subdivision surface is generated approximating to the recovered point cloud. We use a variant displaced subdivision scheme, where scalar displacement, in the direction of a local normal, is computed via the MLS(Moving Least Squares) approximation. The resulting subdivision surface is a mesh with subdivision connectivity providing a high-quality and efficient approximation to the given …
Coupled Coincidence Point Results For Mixed (G,S)-Monotone Mapping And Applications, Habib Yazidi
Coupled Coincidence Point Results For Mixed (G,S)-Monotone Mapping And Applications, Habib Yazidi
Applied Mathematics & Information Sciences
We introduce the concept of mixed (G,S)-monotone mappings and prove coupled coincidence point theorems for such mappings satisfying a nonlinear contraction involving altering distance functions. Presented theorems extend, improve and generalize the recent results of Harjani, L´opez and Sadarangani [J. Harjani, B. L´opez and K. Sadarangani, Fixed point theorems for mixed monotone operators and applications to integral equations, Nonlinear Anal. 74 (2011) 1749-1760] and other existing results in the literature. As application, we present an existence theorem for solutions to a system of nonlinear integral equations.
Information Declassification For Multi-Threaded Programs, Hao Zhu, Yi Zhuang, Xiang Chen
Information Declassification For Multi-Threaded Programs, Hao Zhu, Yi Zhuang, Xiang Chen
Applied Mathematics & Information Sciences
Information declassification aims for trusted release of secret information to public environment. Existing security specifications and enforcement mechanisms of declassification policies have focused on sequential programs. This paper generalized the specification of gradually delimited release policy for sequential programs to the security condition suited for multi-threaded programs. This security condition restricts that the interleaving of low transition events may not depend on secret information, confines the content of information declassified in accord with the content allowed to be released, and controls the location of declassification only through the special release statement. Moreover, we proposed monitoring mechanisms of policy enforcement and …
A New Scalable Rfid Delegation Protocol, Xiuqing Chen, Tianjie Cao, Yu Guo
A New Scalable Rfid Delegation Protocol, Xiuqing Chen, Tianjie Cao, Yu Guo
Applied Mathematics & Information Sciences
The radio frequency identification (RFID) protocols are vulnerable to various attacks from an active or passive adversary. We shed light upon some existing security flaws in these delegation protocols. It is useful to mitigate many security weaknesses in such delegation protocols to promote the acceptance of RFID tags.We propose that a scalable RFID delegation protocol will be against traceability attacks with a stateful variant so that it provides the claimed security requirements. Compared with the previous schemes, we emphasize three critical distinctions in our protocol. First, the reader and the tag decrease one bitwise XOR of the message and reduce …
No-Reference Image Quality Assessment Through Sift Intensity, Tongfeng Sun, Shifei Ding, Xinzheng Xu
No-Reference Image Quality Assessment Through Sift Intensity, Tongfeng Sun, Shifei Ding, Xinzheng Xu
Applied Mathematics & Information Sciences
SIFT (Scale Invariant Feature Transform) points are scale-space extreme points, representing local minutiae structure features in the Gaussian scale space. SIFT intensity, as a novel no-reference metric, is feasible to assess various common distortions without the access to reference images. The metric introduces image preprocessing: neighborhood enhancement through contrast enhancement of adjacent pixels to reduce false SIFT points triggered by random signals; double-size image magnification through linear interpolation to amplify distortion effects to improve its sensitivity to image quality. SIFT intensity is defined as the number of SIFT points in a unit region and is calculated based on the first …
Sliding Mode Control Of Grid Chaotic Oscillation Based On Immune Algorithm, Li Xiangqun, Liu Jianhua, Yang Longyue
Sliding Mode Control Of Grid Chaotic Oscillation Based On Immune Algorithm, Li Xiangqun, Liu Jianhua, Yang Longyue
Applied Mathematics & Information Sciences
The bifurcation and chaos phenomenon which exist in power grid are threats to the stable operation of power grid and the safety of people and equipment. In order to eliminate the chaos phenomena in power grid, a kind of non-singular terminal sliding mode (NTSM) variable structure control method based on immune algorithm is put forward. The second-order model of grid chaotic oscillation is built and to be controlled by non-singular terminal sliding mode variable structure controller. Meanwhile, the immune algorithm is introduced to optimize the sliding mode controller parameters. By means of simulation, the effectiveness of this method in the …
Information Entropy And Mutual Information-Based Uncertainty Measures In Rough Set Theory, Lin Sun, Jiucheng Xu
Information Entropy And Mutual Information-Based Uncertainty Measures In Rough Set Theory, Lin Sun, Jiucheng Xu
Applied Mathematics & Information Sciences
As an extension of the classical set theory, rough set theory plays a crucial role in uncertainty measurement. In this paper, concepts of information entropy and mutual information-based uncertainty measures are presented in both complete and incomplete information/decision systems. Then, some important properties of these measures are investigated, relationships among them are established, and comparison analyses with several representative uncertainty measures are illustrated as well. Theoretical analysis indicates that these proposed uncertainty measures can be used to evaluate the uncertainty ability of different knowledge in complete/incomplete decision systems, and then these results can be helpful for understanding the essence of …
Subspace Feature Analysis Of Local Manifold Learning For Hyperspectral Remote Sensing Images Classification, Ling Ding, Ping Tang, Hongyi Li
Subspace Feature Analysis Of Local Manifold Learning For Hyperspectral Remote Sensing Images Classification, Ling Ding, Ping Tang, Hongyi Li
Applied Mathematics & Information Sciences
Dimensionality reduction and segmentation have been used as methods to reduce the complexity of the representation of hyperspectral remote sensing images. In this study, a new object-oriented mapping approach is proposed based on nonlinear subspace feature analysis of hyperspectral remote sensing images. Nonlinear local manifold learning approaches for feature extraction were utilized to obtain subspace feature representation of hyperspectral remote sensing images. Afterwards, with a proper selection of parameters, the extracted subspace feature images were fed into the object-oriented system. Texture features derived from gray level co-occurrence matrix and wavelet filter with the use of SVM classifier at the pixel …
Energy Balanced Non-Uniform Distribution Node Scheduling Algorithm For Wireless Sensor Networks, Ma Shan-Shan, Qian Jian-Sheng
Energy Balanced Non-Uniform Distribution Node Scheduling Algorithm For Wireless Sensor Networks, Ma Shan-Shan, Qian Jian-Sheng
Applied Mathematics & Information Sciences
Node sleep scheduling is one of the most important methods to improve energy-constrained wireless sensor networks. Most existing approaches to solve this problem require sensors’ location information, which may be impractical considering high positioning costs. In this paper, an energy balanced non-uniform distribution node scheduling algorithm (EBNDNS) is proposed and evaluated. This method needs distance between sensors instead of location information. A simple non-uniform distribution strategy is also proposed. Combined with this strategy, simulation results show that EBNDNS can relieve the “energy-hole” problem for the multi-hop communication and significantly prolong the lifetime of networks.
Web Service Composition Automation Based On Timed Automata, Hu Jingjing, Zhu Wei, Zhao Xing, Zhu Dongfeng
Web Service Composition Automation Based On Timed Automata, Hu Jingjing, Zhu Wei, Zhao Xing, Zhu Dongfeng
Applied Mathematics & Information Sciences
Web service composition is a new direction in the research of service computing. To promote the portfolio, the key problem is to achieve efficient and automatic composition process. We propose the web service composition model based on timed automata. In the computing framework, we design the formal model and its construction algorithm; provide a web service interface description language and composition automation engine. In order to validate its performance, using UPPAAL as the service composition simulator, realized the automation process from independent web services into composite ones. The experimental results verify the feasibility of automatic service composition and the effectiveness …
Real-Time Service Composition Algorithm Based On Semantic Web, Hu Jingjing, Ma Siying, Zhao Xing, Cao Yinyin
Real-Time Service Composition Algorithm Based On Semantic Web, Hu Jingjing, Ma Siying, Zhao Xing, Cao Yinyin
Applied Mathematics & Information Sciences
Real-time service composition needs to meet the time constraints precisely and enhanced the speed of combination computing quickly. To improve the accuracy of service selection, we establish a time ontology model and a set of inference rules, the search strategies through logic reasoning combined with the extended UDDI improve the search efficiency by 129% and accuracy by 161%. In the process of service composition, the improved simulated annealing algorithm (WSC-ISA) is proposed to implement the NP-hard problem of web service composition with QoS properties, which optimizes the solution by time priority and accepting deterioration solution in probability. Experiment results show …
Fsfp: Transfer Learning From Long Texts To The Short, Wei Fengmei, Zhang Jianpei, Chu Yan, Yang Jing
Fsfp: Transfer Learning From Long Texts To The Short, Wei Fengmei, Zhang Jianpei, Chu Yan, Yang Jing
Applied Mathematics & Information Sciences
Transfer learning is a method that studies how to identify the useful knowledge and skills in the previous tasks, and uses them to the new tasks or domains. At present, the research on transfer learning mostly focuses on the field of long texts. However, the source data should be given for the transportation from long texts to the short ones, and the priori probability distribution of the data should be given at the same time. In order to solve the problems, the algorithm which is called FSFP (Free Source selection Free Priori probability distribution) is proposed. It can transfer knowledge …
Quantitative Robust Declassification, Hao Zhu, Yi Zhuang, Xiang Chen
Quantitative Robust Declassification, Hao Zhu, Yi Zhuang, Xiang Chen
Applied Mathematics & Information Sciences
The previous declassification policies focus on qualitative analysis of security properties along different dimensions, lacking quantitative analysis of them. As a step in this direction, we relax restrictiveness of robustness of declassification from the quantitative aspect, and propose a definition of robustness rate of declassification, based on Shannon’s measure method of information lattice. We show our definition is equivalent to robust declassification when the value of robustness rate is equal to 1. Moreover, we make a theoretical and experimental analysis of robust rate about the laundering attack on average salary, respectively. The experimental results are consistent with the theoretical results …
Polynomial Smooth Twin Support Vector Machines, Shifei Ding, Huajuan Huang, Xinzheng Xu, Jian Wang
Polynomial Smooth Twin Support Vector Machines, Shifei Ding, Huajuan Huang, Xinzheng Xu, Jian Wang
Applied Mathematics & Information Sciences
Smoothing functions can transform the unsmooth twin support vector machines (TWSVM) into smooth ones, and thus better classification results can be obtained. It has been one of the key problems to seek a better smoothing function in this field for a long time. In this paper, a novel version for smooth TWSVM, termed polynomial smooth twin support vector machines (PSTWSVM), is proposed. In PSTWSVM, using the series expansion, a new class of polynomial smoothing is proposed, and then their important properties are discussed. It is shown that the approximation accuracy and smoothness rank of polynomial functions can be as high …
Mtsi Algorithm For Frequencies Estimation Of 2-D Superimposed Exponential Model In Multiplicative And Additive Noise Which Is Stationary, Jiawen Bian, Jing Xing, Huiming Peng, Hongwei Li
Mtsi Algorithm For Frequencies Estimation Of 2-D Superimposed Exponential Model In Multiplicative And Additive Noise Which Is Stationary, Jiawen Bian, Jing Xing, Huiming Peng, Hongwei Li
Applied Mathematics & Information Sciences
In this paper, the frequencies estimation of two-dimensional (2-D) superimposed exponential model in zero-mean multiplicative and additive noise which is stationary, is considered by a computationally efficient statistics based iterative algorithm. The model we considered is a more general evanescent part of stationary random field as well as an important model in statistical signal processing and texture classifications. It is observed that the estimator is consistent and works quite well in terms of biases and mean squared errors. Moreover, the asymptotic distribution of the estimators for the frequencies is multivariate normal and the estimators attain the same convergence rate as …
Information Entropy And Information Granulation-Based Uncertainty Measures In Incomplete Information Systems, Lin Sun, Jiucheng Xu, Tianhe Xu
Information Entropy And Information Granulation-Based Uncertainty Measures In Incomplete Information Systems, Lin Sun, Jiucheng Xu, Tianhe Xu
Applied Mathematics & Information Sciences
In this paper, concepts of information entropy and information granulation-based uncertainty measures are introduced in incomplete information/decision systems, and based on maximal consistent block technique, some variants of information entropy and information granulation are presented to measure the discernibility ability of an incomplete information system. Then, some important properties of them are discussed. From these properties, it can be shown that these proposed measures provide important approaches to measure the uncertainty ability of different knowledge in incomplete information/decision systems. And relationships among these measures are established as well. These results will be very helpful for understanding the essence of knowledge …
Solutions Of Konopelchenko-Dubrovsky Equation By Traveling Wave Hypothesis And Lie Symmetry Approach, Sachin Kumar, Amadou Hama, Anjan Biswas
Solutions Of Konopelchenko-Dubrovsky Equation By Traveling Wave Hypothesis And Lie Symmetry Approach, Sachin Kumar, Amadou Hama, Anjan Biswas
Applied Mathematics & Information Sciences
In this paper, the Konopelchenko-Dubrovsky equation will be studied by the aid of traveling wave hypothesis and Lie symmetry analysis. The traveling wave hypothesis will extract the 1-soliton solution while the Lie symmetry approach will retrieve other solutions to this equation.
Minimum Feature Selection For Epileptic Seizure Classification Using Wavelet-Based Feature Extraction And A Fuzzy Neural Network, Sang-Hong Lee, Joon S. Lim
Minimum Feature Selection For Epileptic Seizure Classification Using Wavelet-Based Feature Extraction And A Fuzzy Neural Network, Sang-Hong Lee, Joon S. Lim
Applied Mathematics & Information Sciences
This paper proposes a method that uses a wavelet transform (WT) and a fuzzy neural network to select the minimum number of features for classifying normal signals and epileptic seizure signals from the electroencephalogram (EEG) signals of people with epileptic symptoms and those of healthy people. WT was used to select the minimum number of features by creating detail coefficients and approximation coefficients from EEG signals. 40 initial features were obtained from the created wavelet coefficients using statistical methods, including frequency distributions and the amounts of variability in frequency distributions. We obtained 32 minimum features with the highest accuracy from …
Investment Decision Model Of Industrial Technologies And Innovation Strategic Alliance Regarding Conflict Based On Plant Growth Simulation Algorithm, Qing Zhou, Tong Li, Wei Yang, Lei Wang
Investment Decision Model Of Industrial Technologies And Innovation Strategic Alliance Regarding Conflict Based On Plant Growth Simulation Algorithm, Qing Zhou, Tong Li, Wei Yang, Lei Wang
Applied Mathematics & Information Sciences
Conflict is the key factor to affect investment and benefits of the industry technologies and innovation strategic alliance. This paper constructs an investment decision model of industry technology innovation strategic alliance by discussing the influence of the conflict on the alliance generic technology investment and the impact of member benefits. The results suggest that maximize revenue optimization of alliance generic technology investment and members can be realized through a investment portfolio of alliance members. Moderate conflict would promote alliance innovation performance effectively.
Two Driven Coupled Qubits In A Time Varying Magnetic Field: Exact And Approximate Solutions, E. I. Lashin, Gehad Sadiek, M. Sebawe Abdalla, Elham Aldufeery
Two Driven Coupled Qubits In A Time Varying Magnetic Field: Exact And Approximate Solutions, E. I. Lashin, Gehad Sadiek, M. Sebawe Abdalla, Elham Aldufeery
Applied Mathematics & Information Sciences
We study the dynamics of a two-qubit system coupled through time dependent anisotropic XYZ Heisenberg interaction in presence of a time varying non-uniform external magnetic field. Exact results are presented for the time evolution of the system under certain integrability conditions. Furthermore, the corresponding entanglement of the system is studied for different values of the involved parameters. We found that the time evolution and different properties of entanglement such as amplitude, frequency and profile can be finely tuned by the interplay of the characteristics of the time-dependent magnetic field and exchange coupling. Also we show how the discrete symmetries of …
A Fuzzy Decision Making Trial And Evaluation Laboratory Analysis Of Scm System Implementation, Ta-Ping Lu, Pei-Luen Patrick Rau, Tang-Zuo Liou, Yi-Hsin Yang
A Fuzzy Decision Making Trial And Evaluation Laboratory Analysis Of Scm System Implementation, Ta-Ping Lu, Pei-Luen Patrick Rau, Tang-Zuo Liou, Yi-Hsin Yang
Applied Mathematics & Information Sciences
This study has two phases. The first phase constructs a comprehensive model of key success factors (KSFs) for supply chain network management implementation in the semiconductor industry based on both a literature review and an expert review. The model has four dimensions: strategy, process, organization, and technology (SPOT), and 15 KSFs. The SPOT model can be a checklist for future projects. The second phase analyzed the complicated interrelationship among KSFs with Fuzzy Decision Making Trial and Evaluation Laboratory and discussed its managerial implications. Lastly, we provide two case studies to confirm the importance of the two most important factors.
Two-Stage Least Squares Based Iterative Identification Algorithm For Box-Jenkins Model, Jie Jia, Hua Huang, Yong Yang, Ke Lv, Feng Ding
Two-Stage Least Squares Based Iterative Identification Algorithm For Box-Jenkins Model, Jie Jia, Hua Huang, Yong Yang, Ke Lv, Feng Ding
Applied Mathematics & Information Sciences
In order to improve the parameters estimation precision, a two-stage least squares iterative algorithm for Box-Jenkins models is presented, which is based on the interactive estimation theory of the hierarchical identification and the auxiliary model. The main idea of the algorithm is to decompose a Box-Jenkins system into two subsystems so as to identify each subsystem, respectively. In our algorithm, the dimensions of the involved covariance matrices in each subsystem turn to be small. The simulation results indicate that the proposed algorithm is effective and has a high computational efficiency.
Mcdm Based On Reciprocal Judgment Matrix: A Comparative Study Of E-Vikor And E-Topsis Algorithmic Methods With Interval Numbers, Yajie Dou, Pengle Zhang, Jiang Jiang, Kewei Yang, Yingwu Chen
Mcdm Based On Reciprocal Judgment Matrix: A Comparative Study Of E-Vikor And E-Topsis Algorithmic Methods With Interval Numbers, Yajie Dou, Pengle Zhang, Jiang Jiang, Kewei Yang, Yingwu Chen
Applied Mathematics & Information Sciences
Interval number is a useful tool to handle the uncertainty brought by human factors in multi-criteria decision-making (MCDM) process. When faced with MCDM problems in real-world, the experts may be uncomfortable giving precise upper and lower bounds of the interval ratios on multi-criteria. Based on the reciprocal judgment matrices given by the experts through pairwise comparisons, the satisfaction degree of the multiple alternatives on single criterion is defined and the interval ratios was elicited by a linear programming model. The TOPSIS and VIKOR methods are extended with interval number and algorithmic E-VIKOR and E-TOPSIS methods are proposed. Finally, a numerical …
Wireless Sensor Networks Testbeds And State-Of-The-Art Multimedia Sensor Nodes, Muhammad Omer Farooq, Thomas Kunz
Wireless Sensor Networks Testbeds And State-Of-The-Art Multimedia Sensor Nodes, Muhammad Omer Farooq, Thomas Kunz
Applied Mathematics & Information Sciences
In recent years, Wireless Sensor Networks (WSNs) attracted researchers’ attention. This has led to advancements made in both hardware design and software components. The research at the hardware level has resulted in a variant of WSN called Wireless Multimedia Sensor Networks (WMSNs). WSNs have application in battlefields, industrial process monitoring, and environmental monitoring, to name but a few. Furthermore,WMSNs have the potential for real-time object detection and recognition. It can be used to locate misplaced items, assisted living, helping people with cognitive impairments, species detection, and providing real-time images for many other surveillance-based applications. Thus, such networks need to operate …
Modeling The Use Of Programming Languages: A Very Simple Approach, J. C. Chimal-Egu?A, A. Chavez-Valle
Modeling The Use Of Programming Languages: A Very Simple Approach, J. C. Chimal-Egu?A, A. Chavez-Valle
Applied Mathematics & Information Sciences
In this paper a very simple model for the dynamics of two programming languages is presented. Considering two programming languages X and Y respectively, it is possible to explain in relation to time the obsolescence of some programming languages and the future trend of those most used. Also, it is possible to quantify the level of popularity or decadence by using a parameter related with the use of language.With the aid of the model it is possible to predict future trends of languages, something very important when we have to take some decisions related to the investment in education related …
Evolutionary Instance Selection Algorithm Based On Takagi-Sugeno Fuzzy Model, Sang-Hong Lee, Joon S. Lim
Evolutionary Instance Selection Algorithm Based On Takagi-Sugeno Fuzzy Model, Sang-Hong Lee, Joon S. Lim
Applied Mathematics & Information Sciences
In this study, we propose evolutionary instance selection based on the Takagi-Sugeno (T-S) fuzzy model. The previous neural network with weighted fuzzy membership functions (NEWFM) supports feature selection; thus, it enables the selection of minimum features with the highest performance. The enhanced NEWFM supports a weighted mean defuzzification in the T-S fuzzy model with a confidence interval in the normal distribution; thus, it enables the selection of minimum instances with the highest performance. The enhanced NEWFM has two stages; feature selection is performed in the first stage, whereas instance selection is performed in the second stage. The performance of the …
A Novel Road Extraction Algorithm For High Resolution Remote Sensing Images, Teng Xinpeng, Song Shunlin, Zhan Yongzhao
A Novel Road Extraction Algorithm For High Resolution Remote Sensing Images, Teng Xinpeng, Song Shunlin, Zhan Yongzhao
Applied Mathematics & Information Sciences
Automatic road extraction from the high resolution remote sensing images is of great importance in intelligent transportation and image processing. Hence, in this paper, an effective road extraction algorithm for high resolution remote sensing images based on the circular projection transformation is proposed. The main idea of the proposed algorithm lies in that the road extraction results are obtained by selecting a suitable initial template, and then search the matched templates through moving the initial template in two directions. Firstly, the circular projection vector of the initial template is achieved by calculating the circular projection value at a specific radius. …
Extended One-Step Methods For Solving Delay- Differential Equations, F. Ibrahim, A. A. Salama, A. Ouazzi, S. Turek
Extended One-Step Methods For Solving Delay- Differential Equations, F. Ibrahim, A. A. Salama, A. Ouazzi, S. Turek
Applied Mathematics & Information Sciences
We discuss extended one-step methods of order three for the numerical solution of delay-differential equations. A convergence theorem and the numerical studies regarding the convergence factor of these methods are given. Also, we investigate the stability properties of these methods. The results of the theoretical studies are illustrated by numerical examples.
Solitons, Shock Waves, Conservation Laws And Bifurcation Analysis Of Boussinesq Equation With Power Law Nonlinearity And Dual Dispersion, Anjan Biswas, Ming Song, Houria Triki, Abdul H. Kara, Bouthina S. Ahmed, Andre Strong
Solitons, Shock Waves, Conservation Laws And Bifurcation Analysis Of Boussinesq Equation With Power Law Nonlinearity And Dual Dispersion, Anjan Biswas, Ming Song, Houria Triki, Abdul H. Kara, Bouthina S. Ahmed, Andre Strong
Applied Mathematics & Information Sciences
This paper obtains the soliton solutions to the Boussinesq equation with the effect of surface tension being taken into account. The power law nonlinearity is considered. Three integration tools are adopted in order to extract the soliton solutions. They are the traveling wave hypothesis, ansatz method and the semi-inverse variational principle. Finally, the Lie symmetry approach is adopted to extract the conservation laws of this equation.
Steganography In Audio Files By Hermite Transform, Sandra L. Gomez-Coronel, Boris Escalante-Ram?Rez, Marco A. Acevedo-Mosqueda, Ma. Elena Acevedo Mosqueda
Steganography In Audio Files By Hermite Transform, Sandra L. Gomez-Coronel, Boris Escalante-Ram?Rez, Marco A. Acevedo-Mosqueda, Ma. Elena Acevedo Mosqueda
Applied Mathematics & Information Sciences
This work proposes the use of the Hermite Transform (HT) for imprinting audio files with hidden information. One of the most important aspects of this kind of concealment derives from the amount of data that a host file (audio, images, data, or video) can hold. In this particular case, both the host and the hidden files are audio files. The amount of information that can be hiddenwith the suggested technique-occupies half the length of the host file. Furthermore, the use of the Hermite Transform on audio files helps improve the algorithm performance. Experimental results show that our proposal is efficient …