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In indoor environment, there are gross errors in random measured values of base station, which has effect on generalization ability of BP neural network and then results in low location accuracy. In order to improve location accuracy, location algorithm of BP Neural Network based on residual analysis is proposed, namely conducting pretreatment on measured values separately in training phase and location...
Supporting a large number of devices in LTE Machine-to-Machine (M2M) communications is a big challenge. The large number of devices will try to access radio resource in a short period of time which may result in severe congestion to the Radio Access Network (RAN). Hence, how to scatter the devices, which are always trying to access to a same eNBs (evolved Node B), to other eNBs has become an important...
Genre classification for musical documents is conventionally based on keywords, statistical features or low-level acoustic features. Such features are either lack of in-depth information of music content or incomprehensible for music professionals. This paper proposed a classification scheme based on the correlation analysis of the melodic patterns extracted from music documents. The extracted patterns...
Taking the data of Chinese real effective exchange rate (REER) as sample, the grey system Verhulst model is employed to investigate the changing tendencies innovatively. The forecasting result indicates that Chinese REER will depreciate with the improved accuracy of 97.35% by weakening operator. Only ten month data is employed, which overcomes the sample limitation of general statistical models and...
As the growth of economy and technology has become increasingly rapid, mental care is getting more important today. However, recent movements, such green technologies, place more emphasis on environmental issues but less on mental care. Therefore, this paper presents a newly emerging technology called orange computing for mental care applications. Orange computing refers to health, happiness, and...
In surveillance videos, cues such as head or body pose provide important information for analyzing people's behavior and interactions. In this paper we propose an approach that jointly estimates body location and body pose in monocular surveillance video. Our approach is based on tracks derived by multi-object tracking. First, body pose classification is conducted using sparse representation technique...
This chapter proposes a kind of caLibration algorithm to capture the number of pulses which aims to the caLibration of the meter field so as to achieve the accurate detection of power. In order to avoid the leakage of spectrum, it samples three-phase AC synchronously with the technology of digital phase-locked frequency multipLication. It describes the method of power correction in detail and decrease...
In BCI research community, support vector machine (SVM) is an effective method for motor imagery (MI)-based electroencephalographic (EEG) classification. However, the computation of decision function during SVM classification stage for a new EEG trial is time-consuming due to the large number of support vectors (SV). This paper proposes a new method to reduce the number of support vectors so that...
In this paper, we propose a new feature evaluation method that forms the basis for feature ranking and selection. The method starts by generating a number of feature subsets in a random fashion and evaluates features based on the derived subsets. It then proceeds in a number of stages. In each stage, it inputs the features whose ranks in the previous stage were above the median rank and re-evaluates...
We propose a novel method for detecting characteristic informative phenotype patterns from biomedical images. By building a metric space quantifying the difference between images, we learn the distributions of different classes, and then detect the characteristic regions using graph partition. We show that the detected regions are statistically significant. Our approach can also be used for designing...
The aim of this study is to develop a novel two-laser beam (TLB) stereolithography system and to optimize scanning path for shortening the fabrication time using adaptive crosshatch technique. In the development of TLB system, the wavelengths of the two semiconductor laser beams are determined to be 405 nm (blue light) and 532 nm (green light), respectively, according to the relative absorbance rate...
Surgical patients are usually at high risk of developing pressure ulcers after their operation. Usually, the pressure ulcers data sets are imbalanced. Therefore, this study aims to examine the real medical case of pressure ulcers with the use of support vector machines (SVMs). SVMs are used for forecasting and are a type of classification techniques. We utilize the measurement of sensitivity and specificity...
This paper presents a novel classified method that is called extension genetic algorithm (EGA). The new method is a combination of extension theory and genetic algorithm (GA). In the past, we used the extension method in some clustered problems. With the method, we had to rely on experiences to set rules on classical domain and weight, which caused to increase two tedious and complicated steps in...
Many types of shape descriptors have been proposed for 2D shape analysis, but most of them consist of component features that are not adapted to specific problems. This has two drawbacks. First, computation is wasted on the irrelevant components; second, the accuracy is impaired. This paper proposes an effective method that generates compact descriptors adapted to specific problems in hand, where...
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