Since data services are penetrating into our daily life rapidly, the mobile network becomes more complicated, and the amount of data transmission is more and more increasing. In this case, the traditional statistical ...Since data services are penetrating into our daily life rapidly, the mobile network becomes more complicated, and the amount of data transmission is more and more increasing. In this case, the traditional statistical methods for anomalous cell detection cannot adapt to the evolution of networks, and data mining becomes the mainstream. In this paper, we propose a novel kernel density-based local outlier factor(KLOF) to assign a degree of being an outlier to each object. Firstly, the notion of KLOF is introduced, which captures exactly the relative degree of isolation. Then, by analyzing its properties, including the tightness of upper and lower bounds, sensitivity of density perturbation, we find that KLOF is much greater than 1 for outliers. Lastly, KLOFis applied on a real-world dataset to detect anomalous cells with abnormal key performance indicators(KPIs) to verify its reliability. The experiment shows that KLOF can find outliers efficiently. It can be a guideline for the operators to perform faster and more efficient trouble shooting.展开更多
Epiphytic plant species are an important part of biological diversity. It is therefore essential to understand the distribution pattern and the factors influencing such patterns. The present study is aimed at observin...Epiphytic plant species are an important part of biological diversity. It is therefore essential to understand the distribution pattern and the factors influencing such patterns. The present study is aimed at observing the patterns of species richness, abundances and species composition of epiphytic orchids and ferns in two subtropical forests in Nepal. We also studied the relationship of host plants(Schima wallichii and Quercus lanata) and epiphyte species. Data were collected in Naudhara community forest(CF) and the national forest(NF) in Shivapuri Nagarjun National Park. The data were analyzed using univariate and multivariate tests. In total, we recorded 41 species of epiphytes(33 orchid and 8 fern species). Orchid species abundance is significantlyhigher in CF compared to NF. Orchid species richness and abundance increased with increasing southern aspect whereas it decreased with increasing canopy cover, and fern species richness increased with host bark roughness. Orchid abundance was positively correlated with increasing bark p H, stem size, tree age and tree height and negatively correlated with increasing steepness of the area. Likewise, fern abundances were high in places with high canopy cover, trees that were tall and big, but decreased with increasing altitude and southern aspect. The composition of the orchid and fern species was affected by altitude, aspect, canopy cover, DBH, number of forks and forest management types. We showed that the diversity of orchid and fern epiphytes is influenced by host characteristics as well as host types. The most important pre-requisite for a high epiphyte biodiversity is the presence of oldrespectively tall trees, independent of the recent protection status. This means:(i) for protection, e.g.in the frame of the national park declaration, such areas should be used which host such old tall trees;and(ii) also in managed forests and even in intensively used landscapes epiphytes can be protected by letting a certain number of trees be and by giving them space to grow old and tall.展开更多
To balance the convergence rate and steadystate error of blind source separation(BSS) algorithms, an efficient equivariant adaptive separation via independence(Efficient EASI) algorithm is proposed based on separating...To balance the convergence rate and steadystate error of blind source separation(BSS) algorithms, an efficient equivariant adaptive separation via independence(Efficient EASI) algorithm is proposed based on separating indicator, which was derived from the convergence condition of EASI, and can be used to evaluate the separation degree of separated signals. Furthermore, a nonlinear monotone increasing function between suitable step sizes and separating indicator is constructed to adaptively adjust step sizes, and forgetting factor is employed to weaken effects of data at the initial stage. Numerical case studies and experimental studies on a test bed with shell structures are provided to validate the efficiency improvement of the proposed method. This study can benefit for vibration & acoustic monitoring and control, and machinery condition monitoring and fault diagnosis.展开更多
基金supported by the National Basic Research Program of China (973 Program: 2013CB329004)
文摘Since data services are penetrating into our daily life rapidly, the mobile network becomes more complicated, and the amount of data transmission is more and more increasing. In this case, the traditional statistical methods for anomalous cell detection cannot adapt to the evolution of networks, and data mining becomes the mainstream. In this paper, we propose a novel kernel density-based local outlier factor(KLOF) to assign a degree of being an outlier to each object. Firstly, the notion of KLOF is introduced, which captures exactly the relative degree of isolation. Then, by analyzing its properties, including the tightness of upper and lower bounds, sensitivity of density perturbation, we find that KLOF is much greater than 1 for outliers. Lastly, KLOFis applied on a real-world dataset to detect anomalous cells with abnormal key performance indicators(KPIs) to verify its reliability. The experiment shows that KLOF can find outliers efficiently. It can be a guideline for the operators to perform faster and more efficient trouble shooting.
基金“Bauer-Stiftung und Glaser-Stiftung im Stifterverband für die Deutsche Wissenschaft” Project No. T237/24905/2013/Kg for the research grantgrant number 14-36098G of the Czech Science Foundation and the institutional support RVO 67985939
文摘Epiphytic plant species are an important part of biological diversity. It is therefore essential to understand the distribution pattern and the factors influencing such patterns. The present study is aimed at observing the patterns of species richness, abundances and species composition of epiphytic orchids and ferns in two subtropical forests in Nepal. We also studied the relationship of host plants(Schima wallichii and Quercus lanata) and epiphyte species. Data were collected in Naudhara community forest(CF) and the national forest(NF) in Shivapuri Nagarjun National Park. The data were analyzed using univariate and multivariate tests. In total, we recorded 41 species of epiphytes(33 orchid and 8 fern species). Orchid species abundance is significantlyhigher in CF compared to NF. Orchid species richness and abundance increased with increasing southern aspect whereas it decreased with increasing canopy cover, and fern species richness increased with host bark roughness. Orchid abundance was positively correlated with increasing bark p H, stem size, tree age and tree height and negatively correlated with increasing steepness of the area. Likewise, fern abundances were high in places with high canopy cover, trees that were tall and big, but decreased with increasing altitude and southern aspect. The composition of the orchid and fern species was affected by altitude, aspect, canopy cover, DBH, number of forks and forest management types. We showed that the diversity of orchid and fern epiphytes is influenced by host characteristics as well as host types. The most important pre-requisite for a high epiphyte biodiversity is the presence of oldrespectively tall trees, independent of the recent protection status. This means:(i) for protection, e.g.in the frame of the national park declaration, such areas should be used which host such old tall trees;and(ii) also in managed forests and even in intensively used landscapes epiphytes can be protected by letting a certain number of trees be and by giving them space to grow old and tall.
基金supported by the National Natural Science Foundation of China(Grant No.51305329)the China Postdoctoral Science Foundation(Grant No.2014T70911)+1 种基金the Doctoral Foundation of Education Ministry of China(Grant No.20130201120040)Basic Research Project of Natural Science in Shaanxi Province(Grant No.2015JQ5183)
文摘To balance the convergence rate and steadystate error of blind source separation(BSS) algorithms, an efficient equivariant adaptive separation via independence(Efficient EASI) algorithm is proposed based on separating indicator, which was derived from the convergence condition of EASI, and can be used to evaluate the separation degree of separated signals. Furthermore, a nonlinear monotone increasing function between suitable step sizes and separating indicator is constructed to adaptively adjust step sizes, and forgetting factor is employed to weaken effects of data at the initial stage. Numerical case studies and experimental studies on a test bed with shell structures are provided to validate the efficiency improvement of the proposed method. This study can benefit for vibration & acoustic monitoring and control, and machinery condition monitoring and fault diagnosis.