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In this paper, a regional socialized service system of agriculture was constructed by using factor analysis and clustering analysis. The system included twenty one indicators of five categories. Furthermore, the statistical analysis software SPSS was used to evaluate the socialized agricultural service condition of western twelve provinces in China. The twelve provinces were divided into three classes...
This paper selected 12 evaluating index affecting customer satisfaction in the Taobao's third-party logistics service providers, used the principal component analysis (PCA), to find the main factors that affect customer satisfaction in the Taobao's third-party logistics service providers. The study has shown the main factors including the brand, the quality of the staff and reputation. This paper...
Remote sensing image fusion is a process that integrates the spatial detail of panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MS) image and produces a fused image that contain both high spatial and spectral details. In this paper, a new remote sensing image fusion method is proposed based on Statistical Univariate Finite Mixture Model (UFMM) in Shearlet Domain...
In multiuser MIMO systems, the required feedback rate per user increases linearly with the number of transmit antennas in order to achieve full multiplexing gain. When it comes to massive MIMO systems, the feedback overhead grows unacceptable. This motivates us to explore a novel feedback reduction scheme based on principal component analysis (PCA). The proposed PCA based feedback scheme exploits...
Many contemporary biomedical applications such as physiological monitoring, imaging, and sequencing produce large amounts of data that require new data processing and visualization algorithms. Algorithms such as principal component analysis (PCA), singular value decomposition and random projections (RP) have been proposed for dimensionality reduction. In this paper we propose a new random projection...
Various multispectral (MS) and panchromatic (PAN) fusion (or pan-sharpening) algorithms were developed to produce an enhanced MS image of high spatial resolution. Regarding the novelty in both the PAN and MS bands of the WV-2 imagery, the objective of this study is to assess the performance of nine state-of-the-art pan-sharpening methods for the WV-2 imagery, using both image quality indices and information...
An extension of group independent component analysis (GICA) is introduced, where multi-set canonical correlation analysis (MCCA) is combined with principal component analysis (PCA) for three-stage dimension reduction. The method is applied on naturalistic functional MRI (fMRI) images acquired during task-free continuous music listening experiment, and the results are compared with the outcome of the...
For the current applicable discussions on the idea of sample=overall in big data processing, this paper selects macro data from multi-source including influence factors of smart city from 17 districts and counties of Shanghai as an overall sample, and standardizes the data. Then, another sample is created from output of Principal Components Analysis (PCA). By comparing the two types of samples in...
The evaluation index system of rural services is structured as four dimensions: the scale of development, the speed of development, the structure of development and the environment of development. The developmental level of Chinese rural services relating 30 provinces has been evaluated based on principal component analysis method (PCA). The results of evaluation research indicated that the developmental...
As the number of cooking recipes posted on the Web increases, it becomes difficult to find a cooking recipe that a user needs. Moreover, even if it can be done, it is still difficult for users to arrange the cooking recipe, for example, by replacing ingredients with different ones. To deal with such problems, we propose a framework for typicality analysis of the combination of ingredients. The framework...
The following paper proposes a set of novel feature selection criteria that can be applied to kernel Principal Component Analysis (kPCA) outcome to derive discriminative feature spaces for complex classification problems, such as biometric recognition tasks. The proposed class-separation criteria that are used to evaluate distributions of samples, which are projected onto nonlinear most discriminative...
Peer-to-peer system is a promising solution to manage a large amount of data, but similarity search on peer-to-peer network with a restricted small number of messages is a challenging problem. Existing methods that can perform similarity search work only with low-dimensional data. We propose a method to transform the very high-dimensional data into low-dimensional vectors in order to perform similarity...
Hashing for image retrieval has attracted lots of attentions in recent years due to its fast computational speed and storage efficiency. Many existing hashing methods obtain the hashing functions through mapping neighbor items to similar codes, while ignoring the non-neighbor items. One exception is the Local Linear Spectral Hashing (LLSH), which introduces negative values into the local affinity...
Pansharpening techniques can be divided into component substitution (CS) and multi-resolution analysis (MRA) based methods. Generally, the CS methods result in fused images having high spatial quality but the fused images suffer from spectral distortions. On the other hand, images obtained using MRA techniques are not as sharp as CS methods but they are spectrally consistent. Both substitution and...
The accuracy of speech recognition systems, to a large extent, depends on the feature sets used for representing the recorded speech data. It has been a continuous process to derive better feature sets for more accurate speech recognition using ASR (Automatic Speech Recognition) systems. Many feature sets and their different combinations have been tried to achieve better accuracy but a feature set...
Seismic data size can be very large. High ratio compression is needed to keep data manageable without losing the detail of the traces inside the data. PCA is well known compression technique for high rate lossy compression. However, to keep seismic data lossless another lossless compression is needed to make the error as small as possible. To make the error as small as possible, we need to make the...
An ECG compression technique which achieves very low bit rates of is 12bps is presented. Principal Component Analysis (-PCA) is used prior to identifying non-linear relationships between the orthonormal eigenvectors. Polynomials are used to approximate higher index transformed coefficients from lower ones. Reconstruction is similar to that used in the Karhuneun-Loeve transform (KLT) technique but...
Security is the biggest challenge for the digital data of information systems and computer networks. Some systems are used for providing security to this data. Like these systems intrusion detection system (IDS) is used for providing security to computer networks and information systems. In IDS many systems uses number of techniques for providing accuracy by selecting complete features of dataset...
Humans often use the faces to recognize and similar recognition can enable automatically now by advancement in computing capabilities. The recognition process has now been matured into a science of sophisticated mathematical representation and matching process than early face recognition have been used simple geometric models. Face recognition has received a great deal of attention over the last few...
We are developing a new system called Computer-Aided Tracking and Motion Analysis with Ultrasound System (CAT & MAUS) to dynamically describe joint kinematics for pathology research on musculoskeletal conditions. It is essential to have computer-aided bony structure tracking in ultrasound (US) sequences in such a system for practical use. However, unlike CT or MRI imaging, the appearance of bony...
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