157,031 research outputs found

### Towards efficient SimRank computation on large networks

SimRank has been a powerful model for assessing the similarity of pairs of vertices in a graph. It is based on the concept that two vertices are similar if they are referenced by similar vertices. Due to its self-referentiality, fast SimRank computation on large graphs poses significant challenges. The state-of-the-art work [17] exploits partial sums memorization for computing SimRank in O(Kmn) time on a graph with n vertices and m edges, where K is the number of iterations. Partial sums memorizing can reduce repeated calculations by caching part of similarity summations for later reuse. However, we observe that computations among different partial sums may have duplicate redundancy. Besides, for a desired accuracy Ļµ, the existing SimRank model requires K = [logC Ļµ] iterations [17], where C is a damping factor. Nevertheless, such a geometric rate of convergence is slow in practice if a high accuracy is desirable. In this paper, we address these gaps. (1) We propose an adaptive clustering strategy to eliminate partial sums redundancy (i.e., duplicate computations occurring in partial sums), and devise an efficient algorithm for speeding up the computation of SimRank to 0(Kdn2) time, where d is typically much smaller than the average in-degree of a graph. (2) We also present a new notion of SimRank that is based on a differential equation and can be represented as an exponential sum of transition matrices, as opposed to the geometric sum of the conventional counterpart. This leads to a further speedup in the convergence rate of SimRank iterations. (3) Using real and synthetic data, we empirically verify that our approach of partial sums sharing outperforms the best known algorithm by up to one order of magnitude, and that our revised notion of SimRank further achieves a 5X speedup on large graphs while also fairly preserving the relative order of original SimRank scores

### Fe/Ni ratio in the Ant Nebula Mz 3

We have analyzed the [Fe II] and [Ni II] emission lines in the bipolar
planetary nebula Mz~3. We find that the [Fe II] and [Ni II] lines arise
exclusively from the central regions. Fluorescence excitation in the formation
process of these lines is negligible for this low-excitation nebula. From the
[Fe II]/[Ni II] ratio, we obtain a higher Fe/Ni abundance ratio with respect to
the solar value. The current result provides further supporting evidence for Mz
3 as a symbiotic Mira.Comment: 2 pages, 1 figure, to be published in the Proceedings of the IAU
Symposium 234: Planetary Nebulae in Our Galaxy and Beyond, eds. M.J. Barlow,
R.H. Mende

### The structure and magnetism of graphone

Graphone is a half-hydrogenated graphene. The structure of graphone is
illustrated as trigonal adsorption of hydrogen atoms on graphene at first.
However, we found the trigonal adsorption is unstable. We present an
illustration in detail to explain how a trigonal adsorption geometry evolves
into a rectangular adsorption geometry. We check the change of magnetism during
the evolution of geometry by evaluating the spin polarization of the
intermediate geometries. We prove and clarify that the rectangular adsorption
of hydrogen atoms on graphene is the most stable geometry of graphone and
graphone is actually antiferromagnetic.Comment: 11 pages, 4 figure

### Data Unfolding with Wiener-SVD Method

Data unfolding is a common analysis technique used in HEP data analysis.
Inspired by the deconvolution technique in the digital signal processing, a new
unfolding technique based on the SVD technique and the well-known Wiener filter
is introduced. The Wiener-SVD unfolding approach achieves the unfolding by
maximizing the signal to noise ratios in the effective frequency domain given
expectations of signal and noise and is free from regularization parameter.
Through a couple examples, the pros and cons of the Wiener-SVD approach as well
as the nature of the unfolded results are discussed.Comment: 26 pages, 12 figures, match the accepted version by JINS

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### China's energy consumption in the building sector: A Statistical Yearbook-Energy Balance Sheet based splitting method

China's energy consumption in the building sector (BEC) is not counted as a separate type of energy consumption, but divided and mixed in other sectors in China's statistical system. This led to the lack of historical data on China's BEC. Moreover, previous researches' shortages such as unsystematic research on BEC, various estimation methods with complex calculation process, and difficulties in data acquisition resulted in āheterogeneousā of current BEC in China. Aiming to these deficiencies, this study proposes a set of China building energy consumption calculation method (CBECM) by splitting out the building related energy consumption mixed in other sectors in the composition of China Statistical Yearbook-Energy Balance Sheet. Then, China's BEC from 2000 to 2014 are estimated using CBECM and compared with other studies. Results show that, from 2000 to 2014, China's BEC increased 1.7 times, rising from 301 to 814 million tons of standard coal consumed, with the BEC percentage of total energy consumption stayed relatively stable between 17.7% and 20.3%. By comparison, we find that our results are reliable and the CBECM has the following advantages over other methods: data source is authoritative, calculation process is concise, and it is easy to obtain time series data on BEC etc. The CBECM is particularly suitable for the provincial government to calculate the local BEC, even in the circumstance with statistical yearbook available only

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### Assessing the effects of technological progress on energy efficiency in the construction industry: A case of China

Energy-saving technologies in buildings have received great attention from energy efficiency researchers in the construction sector. Traditional research tends to focus on the energy used during building operation and in construction materials production, but it usually neglects the energy consumed in the building construction process. Very few studies have explored the impacts of technological progress on energy efficiency in the construction industry. This paper presents a model of the building construction process based on Cobb-Douglas production function. The model estimates the effects of technological progress on energy efficiency with the objective to examine the role that technological progress plays in energy savings in China's construction industry. The modeling results indicated that technological progress improved energy efficiency by an average of 7.1% per year from 1997 to 2014. Furthermore, three main technological progress factors (the efficiency of machinery and equipment, the proportion change of the energy structure, and research and development investment) were selected to analyze their effects on energy efficiency improvement. These positive effects were verified, and results show the effects of first two factors are significant. Finally, recommendations for promoting energy efficiency in the construction industry are proposed

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