Human mobility synthesis using matrix and tensor factorizations

Human mobility prediction is of great advantage in route planning and schedule management. However, mobility data is a high-dimensional dataset in which multi-context prediction is difficult in a single model. Mobility data can usually be expressed as a home event, a work event, a shopping event and a traveling event. Previous works have only been able to learn and predict one type of mobility event and then integrate them. As the tensor model has a strong ability to describe high-dimensional information, we propose an algorithm to predict human mobility in tensors of location context data. Using the tensor decomposition method, we extract human mobility patterns with multiple expressions and then synthesize the future mobility event based on mobility patterns. The experiment is based on real-world location data and the results show that the tensor decomposition method has the highest accuracy in terms of prediction error among the three methods. The results also prove the feasibility of our multi-context prediction model.     

ECISER: Efficient Clip-art Image SEgmentation by Re-rasterization

Clip-art image segmentation is widely used as an essential step to solve many vision problems such as colorization and vectorization. Many of these applications not only demand accurate segmentation results, but also have little tolerance for time cost, which leads to the main challenge of this kind of segmentation. However, most existing segmentation techniques are found not sufficient for this purpose due to either their high computation cost or low accuracy. To address such issues, we propose a novel segmentation approach, ECISER, which is well-suited in this context. The basic idea of ECISER is to take advantage of the particular nature of cartoon images and connect image segmentation with aliased rasterization. Based on such relationship, a clip-art image can be quickly segmented into regions by re-rasterization of the original image and several other computationally efficient techniques developed in this paper. Experimental results show that our method achieves dramatic computational speedups over the current state-of-the-art approaches, while preserving almost the same quality of results.     

Determining the factors influencing students’ intention to use m-learning in Jordan higher education

M-learning is characterized as a powerful element of learning and education for facilitating the learning experiences. With enhanced and rapid advancements in technologies of ICTs (Information and Communication Technologies) and mobile, numerous innovative services and applications are being developed. Therefore, it becomes significant to investigate the factors influencing the intentions of m-learning to be used among the students of higher education institution. This study examines the “Technology Acceptance Model” (TAM), “Theory of Reasoned Action” (TRA) and “Unified Theory of Acceptance and Use of Technology” (UTAUT). The study is based on a survey being conducted across diverse groups of students, belonging to different communities and universities. The survey questionnaire was utilized for collecting the relevant data from 250 respondents. The results analyzed yields the impact that the proposed model of m-learning is comprehensive to study in the institutions of higher education.     

Development and monitoring of an integrated bioprocess for production of a potential malaria vaccine with Pichia pastoris

An engineered variant of the yeast Pichia pastoris was used to produce the potential malaria vaccine D1M1. This paper describes the implementation of an expanded bed adsorption chromatography step into a sequential cultivation process of the yeast in order to link protein expression, cell release, and product capture of the secreted protein in a fully automated plant. The process is operated with a semi-continuous strategy for an integrated production. Process improvements have been achieved using design of experiments. Resulting purities of product achieved up to 87% with recoveries of 51% in a single downstream operation. Furthermore, a multivariate analysis of historical batch data was used to develop a golden batch model for process monitoring.     

Low cycle fatigue behavior of a eutectic 80Au/20Sn solder alloy

The eutectic 80Au/20Sn solder alloy is widely used in high power electronics and optoelectronics packaging. In this study, low cycle fatigue behavior of a eutectic 80Au/20Sn solder alloy is reported. The 80Au/20Sn solder shows a quasi-static fracture characteristic at high strain rates, and then gradually transforms from a transgranular fracture (dominated by fatigue damage) to intergranular fracture (dominated by creep damage) at low strain rates with increasing temperature. Coffin-Manson and Morrow models are proposed to evaluate the low cycle fatigue behavior of the 80Au/20Sn solder. Besides, the 80Au/20Sn solder has enhanced fatigue resistance compared to the 63Sn/37Pb solder.     

Modelling of black carbon statistical distribution and return periods of extreme concentrations

Eight datasets of 1-h black carbon (BC) concentrations measured in Warsaw agglomeration (Poland), at urban background and sub-urban sites, and in Racibórz, a small town in Upper Silesia district (regional background site) were analyzed to evaluate BC levels, daily profiles and statistical distributions of concentrations in Central-Eastern European region. The observed mean levels ranged from 1483 ng m⁻³ in suburban site during summer to 3358 ng m⁻³ in regional background site in winter. Observed diurnal patterns were bimodal in the locations dominated by traffic emissions, but unimodal, with elevated evening peak in individually heated residential area. Three theoretical frequency distributions were applied to fit analyzed datasets separately. The lognormal distribution was the most appropriate to represent the middle-range values, while the high concentrations were satisfactorily predicted by the type I two-parameter exponential distribution which was used to estimate the return periods of extreme concentrations for winter months.     

一种实用的多数据库量子信息检索协议

针对目前量子私有信息检索不能适用与云存储的多数据库问题,基于现在成熟的量子密钥分发方法,提出了一种适合在多数据库环境下,实用的量子私有信息检索协议。对于不同大小的数据库,协议可通过调节参数θ和k,在保证数据库安全及用户隐私的情况下,完成信息的检索。性能分析结果表明,协议的通信复杂度低,检索成功率高、易于实施。     

Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.     

A Distribution‐freeCUSUMChart for Monitoring Variability of AutocorrelatedProcesses

We present a distribution‐free tabular cumulative sum chart for monitoring the variability of an autocorrelated process. A quantity known as the asymptotic variance parameter is employed as a measure of the variability, and a distribution‐free tabular cumulative sum chart is applied to variance estimates calculated from batches of nonoverlapping samples. The proposed chart is applicable to a stationary process with a general marginal distribution and a general autocorrelation structure. It also determines control limits analytically without trial‐and‐error simulations. The performance of the proposed chart is tested on stationary processes with both normal and nonnormal marginals with various autocorrelation structures. Copyright © 2014 John Wiley & Sons, Ltd.