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The human brain is one of the most complex systems that have been investigated and modeled. In order to explore its functions thoroughly, scientists have developed various ways of acquiring and analysing the brain signal. Recently, graph and network theory has gained great popularity in modeling the brain connectivity of different brain areas. In this paper, we propose a fast community detection algorithm...
Influence maximization specifies a set of nodes that maximizes the influences in social networks. The influence maximization problem due to its importance in targeted marketing has been explored by many researchers. All proposed algorithms are not scalable and are too time consuming for large-scale social network. In this paper, an efficient and fast algorithm called ComPath+ is proposed for influence...
This paper presents a novel method for robust face recognition, termed non-negative sparse low-rank representation classification (NSLRRC). NSLRRC seeks a sparse, low-rank and non-negative matrix over all training samples. Sparse constraint makes representation vector discriminative, while low-rank matrix will expose the global structures of data. Meanwhile, non-negative representation vectors guarantee...
In this paper, we propose a robust edge indicator employing two eigenvalues of nonlocal structure tensor matrix. In our method, a new nonlocal structure tensor is first constructed. This structure tensor is robust to noise, which inherits from nonlocal means algorithm. Furthermore, based on the constructed nonlocal structure tensor, a new and edge indicator is built, which can effectively differentiate...
In this work, a electric filed mills(EFMs) network and lightning locating system(LLS) data during June, July and August of 2013&2014, were chosen and processed for lightning warning. We set a region of 10km radius from the EFM sites as the area of concern (AOC), and a second region extending 20km outward, as the warning area (WA). We use a running average to smooth the electric field (EF) to lessen...
Spectral graph theory can characterize the global properties and extract structural information of a graph. The normalized Laplacian matrix of a graph has positive or zero eigenvalues, and the largest eigenvalues is less than or equal to 2. In this paper, the internal rules of the eigenvalues of the normalized Laplacian matrix will be proposed. The range of the eigenvalues is further narrowed and...
Smartphones have become ubiquitous in our society. With a large number of users spending more time and sharing more personal data with these devices, it would be beneficial to gain some understanding of data security. This paper presents different security issues regarding applications of Android systems which are one of the most popular mobile operating systems. The research also sheds a light on...
Chronic pain is a disease that the patients suffers a lot in their daily life and it is difficult to be released completely. It is difficult to manage because pain can come anytime and it is unpredictable. However, the pain can be represented by the pain related behaviors such as guiding and abrupt actions. In this paper, we will develop a machine learning based system that can detect the pain related...
To achieve the effective plant leaf classification using manifold learning, the local geometry structure of plant leaves is able to be preserved effectively and a discriminant manifold-based projection should be learned to capture the dominant structure features better. We firstly use Gabor filter to model the texture of plant leaf images as the samples. Then for the high-dimensional features, we...
In current education, it is difficult for a teacher to know the engagement of each student, the contents that students cannot understand and the reason why students cannot perform sufficiently in the quizzes and exams. To study student engagement in classroom, we digitize materials used in lectures, including textbooks and collect event logs of tablets used by students. By analyzing these logs, we...
The detailed designs, technologies and implementations of cloud storage are presented, including the multi-tenant concurrency, separated framework between buffer and business etc. Master/Workers partition algorithm is adopted to improve the reading and writing efficiency for big data in the cloud storage. A cross-platform interface is provided by using RESTful API. Meta files and their permissions...
This position paper introduces a new paradigm in human friendly computing and systems such that the shape, material and touch of a device case significantly matter. While casing has been considered as an auxiliary, that for mobile devices such as smart-phones becomes quite critical for their use. Since casing is an important part of user experiences of mobile devices, we believe that its integrity...
We propose a method to extract frequent sub-sequences from sequential input. Especially, we aim to extract three or more symbols from sequential input. In our former research, we could extract only two symbols. To extract three or more symbols, we propose a learning method and structure of self-organizing spiking neural network. The learning method is based on STDP rule. An output-layer of neural...
In this paper, a short-term load forecasting method which considers the different load characteristics in different periods is proposed. Firstly, we use parallel K-Means algorithm to cluster the daily load curves with 96 points of electricity customer to obtain some date groups with different load characteristics. Then for each date group, we use the daily load curves in the group to build load forecasting...
During usage of data warehouse systems, queries are the most frequent operations over data. Among the queries, range queries are a typical type, which locate range of data according to some timestamp, location, or other attributes falling in a range of lower bound and upper bound. To accelerate range queries, people use different kinds of index schemes to index the data for later use. Indexes supporting...
To increase work efficiency of administration transaction, we have designed the Information-based management system of CHS. The system includes four subsidiary systems: The administration management handing system, evaluating system, searching system and statistics analytical system. The administration management handling system includes the application system of the CHS station(center), the examine...
This paper presents a new improved ViBe algorithm approach to accelerate the ghost suppression, which is a robust and efficient background subtraction algorithm for video sequences. The ViBe has the advantages of faster processing speed and lighter computation load compared with other algorithms. For the sake of the real-time performance of the background modeling, it only uses the first frame to...
Analyzing characteristics of customers' electricity consumption behavior is helpful to improve the management level of demand side energy efficiency. In this paper, a method for analyzing the customers' electricity consumption behavior based on the massive data is proposed. Firstly, clustering algorithm is used to cluster daily load curves of the main power grid in the past one year, then under the...
As the amount of data grows exponentially, active storage was proposed as an alternative solution in order to mitigate the I/O performance problem in distributed cluster system. It moves appropriate computation to the location in which data is stored and hence reduces the amount of data transferred. Prior research has investigated and deployed the concept in different forms. However, balancing the...
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