Non-redundant sequential association rule mining based on closed sequential patterns

In many applications, e.g., bioinformatics, web access traces, system utilisation logs, etc., the data is naturally in the form of sequences. People have taken great interest in analysing the sequential data and finding the inherent characteristics or relationships within the data. Sequential association rule mining is one of the possible methods used to analyse this data. As conventional sequential association rule mining very often generates a huge number of association rules, of which many are redundant, it is desirable to find a solution to get rid of those unnecessary association rules. Because of the complexity and temporal ordered characteristics of sequential data, current research on sequential association rule mining is limited. Although several sequential association rule prediction models using either sequence constraints or temporal constraints have been proposed, none of them considered the redundancy problem in rule mining. The main contribution of this research is to propose a non-redundant association rule mining method based on closed frequent sequences and minimal sequential generators. We also give a definition for the non-redundant sequential rules, which are sequential rules with minimal antecedents but maximal consequents. A new algorithm called CSGM (closed sequential and generator mining) for generating closed sequences and minimal sequential generators is also introduced. A further experiment has been done to compare the performance of generating non-redundant sequential rules and full sequential rules, meanwhile, performance evaluation of our CSGM and other closed sequential pattern mining or generator mining algorithms has also been conducted. We also use generated non-redundant sequential rules for query expansion in order to improve recommendations for infrequently purchased products

Research on 4-dimensional Systems without Equilibria with Application

Recently chaos-based encryption has been obtained more and more attention. Chaotic systems without equilibria may be suitable to be used to design pseudorandom number generators (PRNGs) because there does not exist corresponding chaos criterion theorem on such systems. This paper proposes two propositions on 4-dimensional systems without equilibria. Using one of the propositions introduces a chaotic system without equilibria. Using this system and the generalized chaos synchronization (GCS) theorem constructs an 8-dimensional discrete generalized chaos synchronization (8DBDGCS) system. Using the 8DBDGCS system designs a 216-word chaotic PRNG. Simulation results show that there are no significant correlations between the key stream and the perturbed key streams generated via the 216-word chaotic PRNG. The key space of the chaotic PRNG is larger than 21275. As an application, the chaotic PRNG is used with an avalanche-encryption scheme to encrypt an RGB image. The results demonstrate that the chaotic PRNG is able to generate the avalanche effects which are similar to those generated via ideal chaotic PRNGs

Spatial Heterogeneity of Climate Change Effects on Dominant Height of Larch Plantations in Northern and Northeastern China

Determining the response of dominant height growth to climate change is important for understanding adaption strategies. Based on 550 permanent plots from a national forest inventory and climate data across seven provinces and three climate zones, we developed a climate-sensitive dominant height growth model under a mixed-effects model framework. The mean temperature of the wettest quarter and precipitation of the wettest month were found to be statistically significant explanatory variables that markedly improved model performance. Generally, future climate change had a positive effect on stand dominant height in northern and northeastern China, but the effect showed high spatial variability linked to local climatic conditions. The range in dominant height difference between the current climate and three future BC-RCP scenarios would change from ´0.61 m to 1.75 m (´6.9% to 13.5%) during the period 2041–2060 and from ´1.17 m to 3.28 m (´9.1% to 41.0%) during the period 2061–2080 across provinces. The impacts of climate change on stand dominant height decreased as stand age increased. Forests in cold and warm temperate zones had a smaller decrease in dominant height, owing to climate change, compared with those in the mid temperate zone. Overall, future climate change could impact dominant height growth in northern and northeastern China. As spatial heterogeneity of climate change affects dominant height growth, locally specific mitigation measures should be considered in forest management

QDR-Tree: An Efcient Index Scheme for Complex Spatial Keyword Query

With the popularity of mobile devices and the development of geo-positioning technology, location-based services (LBS) attract much attention and top-k spatial keyword queries become increasingly complex. It is common to see that clients issue a query to find a restaurant serving pizza and steak, low in price and noise level particularly. However, most of prior works focused only on the spatial keyword while ignoring these independent numerical attributes. In this paper we demonstrate, for the first time, the Attributes-Aware Spatial Keyword Query (ASKQ), and devise a two-layer hybrid index structure called Quad-cluster Dual-filtering R-Tree (QDR-Tree). In the keyword cluster layer, a Quad-Cluster Tree (QC-Tree) is built based on the hierarchical clustering algorithm using kernel k-means to classify keywords. In the spatial layer, for each leaf node of the QC-Tree, we attach a Dual-Filtering R-Tree (DR-Tree) with two filtering algorithms, namely, keyword bitmap-based and attributes skyline-based filtering. Accordingly, efficient query processing algorithms are proposed. Through theoretical analysis, we have verified the optimization both in processing time and space consumption. Finally, massive experiments with real-data demonstrate the efficiency and effectiveness of QDR-Tree

Catalytic hydrodeoxygenation of pyrolysis oil over nickel-based catalysts under H2/CO2 atmosphere

Background Renewable feedstocks and bio-refinery concepts are the key to a successful transition to a sustainable chemical industry. One conceivable refinery concept is based on pyrolysis oils from biomass, though these oils are quite difficult to handle. A well investigated approach to upgrade pyrolysis oil and turn it into a valuable products is catalytic hydrodeoxygenation (HDO). However, this process has to be optimized and new ideas are needed to make the hydrodeoxygenation process attractive sustainable and economically competitive. With regard to the many successful applications of gas-expanded liquids in heterogeneous catalysis, the expansion of pyrolysis oil with carbon dioxide was applied in the context of a hydrodeoxygenation reaction. The catalyst used for HDO was Ni/Al2O3 (nickel loading 20 %wt). Results The influence of CO2 on the viscosity was found to be quite strong at low temperature. At 52 °C and a CO2 pressure of 0.5 MPa the viscosity is reduced by 30 %. With 4.0 MPa of CO2 the viscosity decreases by 60 %. With supercritical CO2 a volume expansion of 5 % was observed. The hydrodeoxygenation showed best results at 340 °C and autogenous pressure. The experiments were started at a total pressure of 8.0 MPa at room temperature (H2 + CO2), with a respective partial pressure of CO2 of 0 MPa, 2.0 MPa or 4.0 MPa. A deoxygenation degree of around 70 % could be reached (dry basis) under each atmosphere. The analysis of the upgraded products by different techniques indicated a slight decrease of hydrogenation with increasing the pressure of CO2. Conclusions Despite we observed a change in the physical properties when expanding the pyrolysis oil with CO2, no real improvement of the catalytic hydrodeoxygenation reaction (e.g. deoxygenation degree) could be found yet. Possible reasons for the absence of gas-expanded liquid effects could be the polar nature of the used pyrolysis oil and the high temperature. We assume that a viscous and more tar-like, but less polar pyrolysis oil will be more influenced. Gas-expansion with CO2 tends to be less effective with polar liquids due to the unpolar nature of CO2. The only observed effect in our actual system was a decrease of the hydrogenation with decreasing partial pressure of hydroge