Reference unification and reference linking: Concept, functionalities and inhibiting elements. A case study of Chinese Science Citation Database

In comparing reference unification to reference linking, the authors found that reference linking yield similar result as that of reference unification. An investigative study was conducted by these authors at Chinese Science Citation Database (CSCD) of National Science Library (NSL) of the Chinese Academy of Sciences (CAS), it was found that there were three inhibiting elements in invoking a reference unification solution and the same is true for a reference linking solution. Firstly, it was difficult to define a minimum set of data elements for matching. Secondly, it had a problem of data inaccuracy and/or data incompleteness. Thirdly, it was hard to determine an appropriate linking result that produced the desired document for the user. Thus these authors suggest that getting Digital Object Identifier (DOI) for each journal article is a good way to bring about reference unification and also to improve metadata quality simultaneously at the same time. Therefore, DOI has a pivotal role to play in terms of bringing about reference unification and/or a reference linking.</p

Late Miocene-Quaternary Synchronous-But-Magnitude- Differentiated Episodic Rapid Uplifts of The NE Tibetan Plateau: A Synthesis From Flexural Basins

Abstract HKT-ISTP 2013 A

Significant late Jurassic counterclockwise rotations of the Yanshiping region, east North Qiangtang terrane, implication on Lhasa - Qiangtang initial collision

Abstract HKT-ISTP 2013 A

Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection

Dynamic time warping (DTW) is an effective dissimilarity measure in many time series applications. Despite its popularity, it is prone to noises and outliers, which leads to singularity problem and bias in the measurement. The time complexity of DTW is quadratic to the length of time series, making it inapplicable in real-time applications. In this paper, we propose a novel time series dissimilarity measure named RobustDTW to reduce the effects of noises and outliers. Specifically, the RobustDTW estimates the trend and optimizes the time warp in an alternating manner by utilizing our designed temporal graph trend filtering. To improve efficiency, we propose a multi-level framework that estimates the trend and the warp function at a lower resolution, and then repeatedly refines them at a higher resolution. Based on the proposed RobustDTW, we further extend it to periodicity detection and outlier time series detection. Experiments on real-world datasets demonstrate the superior performance of RobustDTW compared to DTW variants in both outlier time series detection and periodicity detection

The Weighted Support Vector Machine Based on Hybrid Swarm Intelligence Optimization for Icing Prediction of Transmission Line

Not only can the icing coat on transmission line cause the electrical fault of gap discharge and icing flashover but also it will lead to the mechanical failure of tower, conductor, insulators, and others. It will bring great harm to the people’s daily life and work. Thus, accurate prediction of ice thickness has important significance for power department to control the ice disaster effectively. Based on the analysis of standard support vector machine, this paper presents a weighted support vector machine regression model based on the similarity (WSVR). According to the different importance of samples, this paper introduces the weighted support vector machine and optimizes its parameters by hybrid swarm intelligence optimization algorithm with the particle swarm and ant colony (PSO-ACO), which improves the generalization ability of the model. In the case study, the actual data of ice thickness and climate in a certain area of Hunan province have been used to predict the icing thickness of the area, which verifies the validity and applicability of this proposed method. The predicted results show that the intelligent model proposed in this paper has higher precision and stronger generalization ability