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Through K-nearest neighbor algorithm based on k-d tree, the noises in the disordered and three-dimensional point cloud are removed. The value of the k in the K-nearest neighbor algorithm is discussed in detail. By three-dimensional projection, the dimension of k-d tree is reduced. So efficiency of de-noising is improved. The original depth image corresponding with the point cloud data is converted...
Traditional data mining approaches offers simply statistical analysis with discovery of hidden knowledge and frequent patterns. It succeeded in finding the correlation among items by statistical significance but could not provide additional parameter to knowledge discovery. In contrast to traditional approach, use of profit significance as a measure to calculate new support and confidence established...
In real life applications, enormous wealth of data generates from online and offline sources and is incremental in nature. Data Mining has become accustomed to specifying constraints from incremental data that is indeed an answer to important task such as to generate frequent pattern. The goal of the pattern mining process is to discover all the patterns from the data sources where all the patterns...
MOOCs have refined the way of teaching where the electronic devices can provide knowledge on the go, which says that knowledge is omnipresent. The connectivism is a technique where the knowledge is contained in the electronic media, which can be delivered as per the requirement. The use of Face detection with Haar based algorithms help to track the current status of the user and perform the teaching...
As a fast search algorithm for motion estimation, the unsymmetrical-cross multi-hexagon-grid Search (UMHexagonS) is widely used in H.264. However, the research found that there were some shortages in this algorithm, such as the computational complexity. Based on this, we improve the UMHexagonS algorithm to reduce the computation. By partitioning the search range, we can only search the prediction...
Electrocardiogram (ECG) is the recording of electric activity of heart. The abnormal ECGs are called arrhythmias. In this paper, we propose the algorithm to detect the arrhythmias based on heart rate variability. Heart rate variability in normal ECGs and arrhythmias is detected by taking five ECG beats from each ECG. We investigate the consecutive RR peak interval to detect heart rate variation in...
With the rapid increase of the network bandwidth, to process high throughput regular expressions with hardware has become inevitable. This paper presents a novel NFA-based algorithm. In this paper, two theorems were proved and were used to prove the correctness of the algorithm. Our approach was based on three basic modules to construct NFA that can be easily reused in a FPGA or ASIC. The quantitative...
Transferring data from source node to destination is the most important task in the wireless sensor network. Main drawback for the any wireless sensor networks is limited energy available to nodes because of the small size of the batteries they use as source of power. Balancing the route of the data transfer is one of the technique that can be used to minimized sensor nodes energy consumption during...
In engineering design processes, there are many cases where feasibility has to be checked. Some applications, such as radiation therapy, can be formulated as linear feasibility problems. In addition, a feasible point is required to start many other algorithms. In this paper, we propose an interior point method for linear feasibility problems. This algorithm is suitable for problems that are large...
The data generated from both men and machines are exponentially multiplying the size and the structural definition of the data. Such a voluminous, dynamic and unstructured data termed as Big Data is analyzed and maintained and can be used for various purposes and applications. Big Data is generated from sources like social media, cyber physical system and business entities. This enormous data generation...
With the phenomenal increase in digital data, it is inefficient to run the traditional clustering algorithms on separate servers. To deal with this problem, researchers are migrating to distribute environment to implement the traditional clustering algorithms, more specifically K-means clustering. In traditional K Means Clustering, the problem of instability caused by the random initial centers exists...
There is no absolute shortest path by using a bi-objective model to solve the optimal path problem. Based on the flight and train schedules, we establish the transfer time reliability model in the transfer station according to the reliability theory, as well as combine this model with the bi-objective optimal path optimization model. The improved PRDFS D algorithm is used to calculate the path set...
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