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Parkinson's disease (PD) and essential tremor (ET) are two kinds of tremor disorders which always confusing doctors in clinical diagnosis. Early experiments on structural MRI have already shown that Parkinson's disease can cause pathological changes in the brain region named Caudate_R (a part of Basal ganglia) while essential tremor cannot. Although there are many research work on the classification...
Online reviews are very important for lots of Web applications. Extracting opinion targets and opinion words from online reviews is one of the core works for review analysis and mining. The traditional extraction methods mainly include two categories: the pipeline-based methods and the propagation-based ones. The former extracts opinion targets and opinion words separately, which ignores the opinion...
Mass data generated from in-service radiographic product contain assignable information on Image Quality (IQ). Analyzing data from routine work might supplement the time-consuming Image Quality Assurance Test Procedure (IQATP) to evaluate IQ and to know product type performance on site, which can also locate risks and give manufacturer directions for the further actions as well. This article illustrates...
K-means clustering algorithm is an influential algorithm in data mining. The traditional K-means algorithm has sensitivity to the initial cluster centers, leading to the result of clustering depends on the initial centers excessively. In order to overcome this shortcoming, this paper proposes an improved K-means text clustering algorithm by optimizing initial cluster centers. The algorithm first calculates...
The big data computing era is coming to be a fact in all daily life. As data-intensive become a reality in many of scientific branches, finding an efficient strategy for massive data computing systems has become a multi-objective improvement. Processing these huge data on the distributed hardware clusters as Clouds needs a powerful computation model like Hadoop-MapReduce. In this paper, we studied...
The minimum number of required sensors problem in sweep coverage, one of the important coverage problems in WSN, using a small number of mobile sensor nodes to satisfy both POI (Point of Interest) coverage and data delivery is a dynamic coverage problem. To find the minimum number of mobile sensor nodes with a uniform speed to guarantee sweep coverage was proved to be a NP-hard problem. In this paper,...
Automatic Target Recognition (ATR) technology is of great significance in security inspection, while traditional object detection methods are proved not efficient in human body millimeter-wave images. In this paper, we propose a synthetic objection detection method for millimeter-wave images. We choose saliency, SIFT and HOG features to form image descriptors. According to sparse representation, the...
In order to recover high resolution image from their corresponding low-resolution counterparts for MR Images, this paper has proposed a super resolution reconstruction method to recover the low-resolution MR images based on convolution neural network. Based on the proposed network, the convolution operation and non-linear mapping are employed to adapt MR images naturally and leaning the end-to-end...
In this work, the proposed Intelligent Indoor Environment Monitoring System in Cloud (iDEMS) combines environmental sensors with ZigBee wireless sensor network technology to store and process environmental data in HBase. The environmental data collected by sensors will be stored and processed in the cloud using HBase, which supports storing large amounts of data, free to easily increase storage space...
With the progressive development of smart communities, security of smart community systems becomes an important issue. Role-Based Access control is a way to solve this problem. However, existing implementations of role-based access control are not fine-grained, and it takes no account of category information of the resources. As every resource in the model was authorized in the same way, such a model...
Against the background of data explosion and cloud computing, this paper investigates a branch of the cloud computing technology which is known as VDI (virtual desktop infrastructure). Users can access data and information via cloud desktops with the endpoint devices. The paper studies OpenStack - a famous open-source cloud platform which has been widely used, and introduces a secure, optimized and...
Recently, privacy protection attracts more and more research efforts especially for social network data. In the literature, most of existing approaches assume that social data are independent to each other which is not the case in the real world applications. In this paper, we are the first attempt to investigate the privacy protection issue when social data are correlated. We model the correlation...
Fast transferring and sharing large multimedia files on the mobile network is a challenge. Most users encounter a long delay before playing a file; so this creates a bad experience for users. One common mechanism is to buffer the file to the internal memory before playing it. Hence, playing a large media file without long delay or interruption is a dream. This paper proposed a new mechanism, named...
In many computer vision systems, one object can be described by multi-view data. Compared with individual view, multi-view data can contain complete and complementary information of the problem. But when views capture information which is uniquely but not complete enough to give an uniform learning performance, multi-view data may degrade the learning performance and it is therefore not an ideal solution...
Vertical elevators are commonly used in high-rise buildings. Elevator Group Control System(EGCS) is designed to dispatch elevator cars to meet the needs of customer's call in different floor. The optimization of EGCS is aiming at improving its transport capacity and service quality, which is a typical combinational optimization. Particle Swarm Optimization(PSO) is good at solving combinational optimization,...
A novel intraday algorithmic trading strategy is developed based on various machine learning techniques and paralleled computing architectures in this paper. The proposed binary classification framework can predict the price trends of Taiwan stock index futures after thirty minutes. Traditional learning-based approaches collect all samples during the training period as the learning materials. The...
Deep learning has been shown as a successful machine learning method for a variety of tasks, and its popularity results in numerous open-source deep learning software tools coming to public. Training a deep network is usually a very time-consuming process. To address the huge computational challenge in deep learning, many tools exploit hardware features such as multi-core CPUs and many-core GPUs to...
With more and more citizens traveling for life or work at night, there is a big gap between the demands and supplies for public transportation service in China. In this paper, we address the problem of night-bus stop planning by investigating the characteristics of taxi GPS trajectories and transactions, rather than leveraging subjective and costly surveys about citizen mobility patterns. There are...
The widespread use of internet provides extensive heterogeneous platforms for drug sales. The internet has greatly facilitated the development of merchandise sales, meanwhile, many fake drug sellers that has been strongly restricted in the market by law enforcement agencies build their own platforms for sales via the internet. In order to against the fake drug website, reduce time and human resource...
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