Accurately mapping urban vegetation carbon density is challenging because of complex landscapes and mixed pixels. In this study, a novel methodology was proposed that combines a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), to map the forest carbon density of Shenzhen City of Chi...

Transform coding (TC) is an efficient and effective vector quantization approach where the resulting compact representation can be the basis for a more elaborate hierarchical framework for sub-linear approximate search. However, as compared to the state-of-the-art product quantization methods, there is a significant performance gap in terms of matching accuracy. One of the main shortcomings of ...

The main objective of this study was to evaluate the effectiveness of adding feature variables, such as forest type information and topographicand climatic-environmental factors to satellite image data, on the accuracy of stand volume estimates made with the k-nearest neighbor (k-NN) technique in southwestern Japan. Data from the Forest Resources Monitoring Survey—a national plot sampling surve...

This paper presents a new approach to measuring similarity over massive time-series data. Our approach is built on two principles: one is to parallelize the large amount computation using a scalable cloud serving system, called TimeCloud. The another is to benefit from the filter-and-refinement approach for query processing, such that similarity computation is efficiently performed over approxi...

Abstract— Feature selection is an indispensable pre-processing step when mining huge datasets that can significantly improve the overall system performance. Therefore in this paper we focus on a hybrid approach of feature selection. This method falls into two phases. The filter phase select the features with highest information gain and guides the initialization of search process for wrapper ph...

background and aims: since using city power for welding process is not allowed, diesel generators are used as a power supply in construction industries. they could be introduced as a main source of noise pollution. the purposes of this study were to assess and control noise pollution produced by construction diesel generators in hamadan, iran. methods: in this descriptive, cross-sectional study...

an efficient cluster head selection algorithm in wireless sensor networks is proposed in this paper. the implementation of the proposed algorithm can improve energy which allows the structured representation of a network topology. according to the residual energy, number of the neighbors, and the centrality of each node, the algorithm uses fuzzy inference systems to select cluster head. the alg...

Data reduction is a common pre-processing step for k-nearest neighbor classification (kNN). The existing prototype selection methods implement different criteria for selecting relevant points to use in classification, which constitutes a selection bias. This study examines the nature of the instance selection bias in intrinsically high-dimensional data. In high-dimensional feature spaces, hubs ...

This paper presents a new hybrid classifier that combines the probability based Bayesian Network paradigm with the Nearest Neighbor distance based algorithm. The Bayesian Network structure is obtained from the data by using the K2 structural learning algorithm. The Nearest Neighbor algorithm is used in combination with the Bayesian Network in the deduction phase. For those data bases in which s...

In this paper a framework “Temporal-Vector Trajectory Learning” (TVTL) for human action recognition is proposed. In this framework, the major concept is that we would like to add the temporal information into the action recognition process. Base on this purpose, there are three kinds of temporal information, LTM, DTM, and TTM, being proposed. With the three kinds of proposed temporal informatio...