A framework for mining interesting high utility patterns with a strong frequency affinity

High utility pattern (HUP) mining is one of the most important research issues in data mining. Although HUP mining extracts important knowledge from databases, it requires long calculations and multiple database scans. Therefore, HUP mining is often unsuitable for real-time data processing schemes such as data streams. Furthermore, many HUPs may be unimportant due to the poor correlations among the items inside of them. Hence,the fast discovery of fewer but more important HUPs would be very useful in many practical domains. In this paper, we propose a novel framework to introduce a very useful measure, called frequency affinity, among the items in a HUP and the concept of interesting HUP with a strong frequency affinity for the fast discovery of more applicable knowledge. Moreover, we propose a new tree structure, utility tree based on frequency affinity (UTFA), and a novel algorithm, high utility interesting pattern mining (HUIPM), for single-pass mining of HUIPs from a database. Our approach mines fewer but more valuable HUPs, significantly reduces the overall runtime of existing HUP mining algorithms and is applicable to real-time data processing. Extensive performance analyses show that the proposed HUIPM algorithm is very efficient and scalable for interesting HUP mining with a strong frequency affinity.     

Effective periodic pattern mining in time series databases

The goal of analyzing a time series database is to find whether and how frequent a periodic pattern is repeated within the series. Periodic pattern mining is the problem that regards temporal regularity. However, most of the existing algorithms have a major limitation in mining interesting patterns of users interest, that is, they can mine patterns of specific length with all the events sequentially one after another in exact positions within this pattern. Though there are certain scenarios where a pattern can be flexible, that is, it may be interesting and can be mined by neglecting any number of unimportant events in between important events with variable length of the pattern. Moreover, existing algorithms can detect only specific type of periodicity in various time series databases and require the interaction from user to determine periodicity. In this paper, we have proposed an algorithm for the periodic pattern mining in time series databases which does not rely on the user for the period value or period type of the pattern and can detect all types of periodic patterns at the same time, indeed these flexibilities are missing in existing algorithms. The proposed algorithm facilitates the user to generate different kinds of patterns by skipping intermediate events in a time series database and find out the periodicity of the patterns within the database. It is an improvement over the generating pattern using suffix tree, because suffix tree based algorithms have weakness in this particular area of pattern generation. Comparing with the existing algorithms, the proposed algorithm improves generating different kinds of interesting patterns and detects whether the generated pattern is periodic or not. We have tested the performance of our algorithm on both synthetic and real life data from different domains and found a large number of interesting event sequences which were missing in existing algorithms and the proposed algorithm was efficient enough in generating and detecting periodicity of flexible patterns on both types of data.     

Input-parallel output-parallel configuration of boost half bridge DC-DC converter with control strategy

The concept of connecting two boost half bridge DC-DC converter modules in input-paral- lel output-parallel configuration is presented. The input-parallel-output-parallel （IPOP） converter consists of multiple boost half bridge （BHB） DC-DC converter modules which are connected in par- allel at the input and output side. This kind of converter is an attractive solution for high power ap- plications. The correlation between input current sharing （ICS） and output current sharing （OCS） of the IPOP converter basic modules is described. Two loop control strategies, consisting of input cur- rent loop and output voltage loop, have been developed to achieve equal ICS and OCS in this present work. The control strategy for the IPOP configuration of boost haft bridge DC-DC converter has been verified for different load conditions （half load and full load）, The IPOP system proposed here is comprising of two modules but it can be extended to three or more. The performance of the pro- posed system along with the control strategy is verified by simulation in MATLAB using Simpower tool. Finally the satisfactory simulation results are obtained.     

烯丙基酚氧树脂改性双马来酰亚胺体系的优化

通过环氧树脂与二烯丙基双酚A合成了一种烯丙基酚氧树脂,用以增韧双马来酰亚胺。在单因素试验的基础上,根据Box-Benhnken的中心组合试验设计原理,选取改性树脂体系组分为影响因子,应用响应面法进行3因素3水平的18组的设计试验,改性树脂性能(弯曲强度,冲击强度,热变形温度)为响应值,对改性树脂组分配比进行优化。结果表明,改性树脂组分配比BMI、DDS、APO、DABPA、DAP为2∶1∶0.2∶0.84∶0.1(物质的量比)时,综合2性能最好,此时改性双马树脂体系的冲击强度可达到21.4 k J/m,弯曲强度为200.5 MPa,热变形温度为195.8℃。     

A Novel Approach for Mining High‐Utility Sequential Patterns in Sequence Databases

Mining sequential patterns is an important research issue in data mining and knowledge discovery with broad applications. However, the existing sequential pattern mining approaches consider only binary frequency values of items in sequences and equal importance/significance values of distinct items. Therefore, they are not applicable to actually represent many real‐world scenarios. In this paper, we propose a novel framework for mining high‐utility sequential patterns for more real‐life applicable information extraction from sequence databases with non‐binary frequency values of items in sequences and different importance/significance values for distinct items. Moreover, for mining high‐utility sequential patterns, we propose two new algorithms: UtilityLevel is a high‐utility sequential pattern mining with a level‐wise candidate generation approach, and UtilitySpan is a high‐utility sequential pattern mining with a pattern growth approach. Extensive performance analyses show that our algorithms are very efficient and scalable for mining high‐utility sequential patterns.     

Formulation development and optimization of alpha ketoglutarate nanoparticles for cyanide poisoning

The purpose of this research work was to formulate and evaluate alpha ketoglutarate nanoparticles as dry powder inhaler for treatment of cyanide poisoning. Non-polymeric particles were prepared by nano-precipitation technique using various stabilizers. Selection of co-solvent and stabilizer was a key to produce stabilized particles. A combination of lutrol F68 and PVA as a crystal growth inhibitor seems to be best in achieving minimum particle size of 110.2 nm. On the basis of preliminary trials a Box-Behnken statistical design was employed to study the effect of independent variables, drug concentration (X₁), stirring speed (X₂), stirring time (X₃), PVA concentration (X₄), poloxomer concentration (X₅) and volume of co-solvent (X₆) on average particle size. Particle size varied from 110 to 875 nm depending upon the significant terms. Optimized formulation was predicted at drug concentration (50 μg/ml), stirring speed (640 rpm), stirring time (1 min), PVA concentration (1%), poloxomer concentration (1.69%) and volume of co-solvent (30 ml) with 104.6% experimental validity. The nanosized particles were further characterized by X-ray diffraction (XRD), Differential Scanning Calorimetry (DSC), Nuclear Magnetic Resonance (NMR) and Fourier Transform Infrared Spectroscopy (FT-IR) analysis. The results of particle characterization indicate that there was no physical disparity when compared with the commercial α-KG sample.     

大规模MIMO系统下的低复杂度迫零预编码技术

针对大规模天线技术导致传统迫零(zero-forcing,ZF)预编码复杂度上升的问题,提出了一种低复杂度预编码技术.首先利用对称超松弛迭代(semi-iteration symmetric successive overrelaxation method,SSOR)技术优化信道矩阵求逆复杂度的问题;然后利用切比雪夫半...     

Improved thermosets obtained from diglycidyl ether of bisphenol A/4,4′‐diaminodiphenylsulfone based on a new epoxy‐terminated hyperbranched polymer

A new hyperbranched polymer (HBP) with a flexible aromatic skeleton and terminal epoxy groups was synthesized to improve the toughness of diglycidyl ether of bisphenol A. The HBP was characterized using nuclear magnetic resonance, Fourier transfer infrared spectroscopy and gel permeation chromatography. The effect of HBP on the thermomechanical and mechanical properties of modified epoxy systems was studied. For evaluating the efficiency of the modified epoxy systems, composite samples using glass fiber cloth were molded and tested. Using dynamic mechanical analysis, a slight reduction in glass transition temperature (T_g) with increasing HBP content was observed. Analysis of fracture surfaces revealed a possible effect of HBP as a toughener and showed no phase separation in the modified resin systems. The results showed that the addition of 15 phr HBP maximized the toughness of the modified resin systems with 215 and 40% increases in impact and flexural strengths, respectively. T_g and heat resistance of cured modified resin systems decreased slightly with an increase in HBP content and, at 15 phr HBP, only a 2.6% decrease in thermomechanical properties was observed. Meanwhile, a molded composite with HBP showed improved mechanical properties and retention rate at 150 °C as compared to that made with neat resin. © 2015 Society of Chemical Industry     

Physiological and Nutraceutical Perspectives of Fructan

Functional and nutraceutical foods have captured the global market owing to trends and perceptions of consumers on the natural products and diet-health linkages. Health promoting potential of such foods has been attributed to the presence of essential bioactive moieties. Wheat, being staple food in many parts of the world, gained substantial attention of researchers particularly for the extraction of various functional components. Among these, fructan oligosaccharides in nature bestow quality of baked products and provide protection against various physiological disorders. Addition of fructan in various baked products enhances softness and color, especially in bread, and also imparts textural improvement. Moreover, fructans boost mineral absorption, hypocholesterolemic, and hypoglycemic perspectives, bifidogenic nature and controlling cancer insurgence. The benefits allied with fructan are mainly dose and time dependent. In this context, its industrial applications for vulnerable groups are increasing worldwide.