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The unified Parkinson's disease rating scale (UPDRS) is the most widely employed scale for tracking Parkinson's disease (PD) symptom progression. However, conventional way to achieve UPDRS, mainly based on the physical examinations of clinic patients performed by the trained medical staffs, involves the disadvantages of inconvenience and high medical expense. Hence, in this study, we try to explore...
Compressive sensing (CS) is a promising data acquisition and compression technology that can be used to reduce and balance the transmission cost in wireless sensor networks (WSNs). However, the transmission links are unreliable frequently and data loss is very common in wireless sensor networks. What's more, the reconstruction accuracy is reduced greatly due to unreliable links and data loss. In order...
Monitoring biomass over large geographic regions for changes in vegetation and cropping patterns is important for many applications. Changes in vegetation happen due to reasons ranging from climate change and damages to new government policies and regulations. Remote sensing imagery (multi-spectral and multi-temporal) is widely used in change pattern mapping studies. Existing bi-temporal change detection...
Noise and non-uniform gray level in underwater image cause the low segment precision, this paper presents a segmentation framework based on morphological component analysis (MCA) and fuzzy clustering with variational level set. The framework uses MCA method to sparse decompose the image into texture and cartoon parts. The cartoon part contains the mainly information with less noise, which is good...
Node localization is one of the important issues in wireless sensor networks. In order to lower the cost of a sensor network and improve localization accuracy and efficiency, we put forward a virtual cluster based mobile beacon aided localization algorithm (VCMBLA) in this paper. A multi-hop distance estimation method based on neighbor distribution (MDEND) is presented and a path planning strategy...
To overcome the problems of Euclidean distance based clustering algorithms, an efficient algorithm CES is proposed. A distance metric derived from the infinite norm is introduced to measure similarities between objects, through the distance metric, the neighbor searching is converted to the intersection of projection sets searching, which speed up the clustering processing. An efficient neighbor searching...
In this paper we present a new subspace clustering algorithm TGSCA for large dataset with noise. Experiments show that TGSCA can discover clusters both on entire space and subspace; the computation complexity is proximate linear with object's number, space dimension, and clusters' dimension respectively; it is not sensitive to noise; it can find both disjoint clusters or overlap clusters; it can find...
In recent years, Network Situation Awareness mainly concentrates on the security field, but therepsilas no research on Network Transmission Situation Awareness (NTSA). Comparing with traditional network management, NTSA(1) provides the comprehensive macroscopic view of network transmission status, strengthens the comprehension and control of network, and reduces the burden on administrators; (2) as...
As a large amount of data stored in spatial databases, people may like to find groups of data which share similar features. Thus cluster analysis becomes an important area of research in data mining. In the real world, there exist many physical obstacles such as rivers, lakes and highways, and their presence may affect the result of clustering substantially. However, most of clustering algorithms...
The aim of outlier detection was to find out abnormal data patterns concealed in abundant data sets which were sparse and isolate. Mine disaster occurred much more frequently in our country, so it was urgent to take out an effective method to prevent mine disaster and guarantee miner's life and property of the company. In this paper, we presented a new method-AHHDOD, it could not only find out the...
A major problem for many sensor network applications is determining the most efficient way of conserving the energy of the power source. Energy conservation is of prime importance for sensor networks. In this paper, a power saving hierarchical routing protocol PER is proposed for heterogeneous sensor network, optimized via cross-layer designs to save sensor's power. There are two kinds of nodes in...
In this paper, a new clustering algorithm MSC is proposed. Mathematics morphology theory is used to search clusters. A new mathematics morphological operator is introduced, which is more accurate than the ordinary operators: open and close. The scale space theory is integrated with mathematics morphology to get multi-scale and hierarchical clusters. Performance tests show that MSC can find clusters...
In this paper, a top-down search grid based algorithm is proposed to search all subspace that may contain clusters. Different from bottom-up search grid algorithms, the new approach starts from high-level subspace to low-level subspace, avoiding a lot of useless computation. Active spaces and grids are introduced to prune the search space, which reduces searching candidates dramatically. A new filter...
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