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.     

Intelligent Information‐Centric Networking routing scheme under imprecise information

Information‐Centric Networking (ICN) has been accepted to overcome some weaknesses of the current Internet architecture, showing that “what is being exchanged” is more important than “who are exchanging information.” Given the inadequate considerations on Quality of Service (QoS) and energy saving in ICN routing, we propose in this paper a routing algorithm to enhance the two aspects. At first, on one hand, Cauchy distribution is used as a fuzzy model to evaluate users' QoS requirements, such as bandwidth, delay, and error rate; on the other hand, we formulate energy saving problem to evaluate the green quality of routing algorithm. Then, we design a link selection approach by considering QoS and energy saving, which belongs to a multi‐objective decision problem resolved by intelligent drops algorithm. Finally, we implement the proposed algorithm and compare it with the famous adaptive forwarding mechanism in terms of some significant metrics, and the experimental results reveal that the proposed algorithm is more efficient.     

Research on the identification performance of UHF RFID system considering the correlation of cascaded channel

The identification rate of UHF RFID system was restricted by multipath propagation effects.The system identification performance was studied considering the correlation coefficient between forward and reverse channels.Based on the generalized Rician fading channel model,the analytical expression of identification rate was derived under independent,full correlation and correlation cases.Compared with the existing analysis,the proposed uniform calculation formula of identification rate was for any correlation coefficient and kinds of channel conditions.The numerical computation and Monte-carlo simulations show that the influences of different correlation coefficients,channel conditions,sensitivity and distance on the identification rate.     

基于MF-R和AWS密钥管理机制的物联网健康监测大数据分析系统

带有传感器的可穿戴式医疗设备不断生成大量数据，由于数据的复杂性，难以通过处理和分析大数据来找到有价值的决策信息。为了解决这个问题，提出了一种新的物联网体系结构，用于存储和处理医疗应用的可扩展传感器数据（大数据）。所提出的架构主要由两个子架构组成：Meta Fog重定向（MF-R）架构和AWS密钥管理机制。MF-R架构使用Apache Pig和Apache HBase等大数据技术来收集和存储不同传感器设备生成的传感器数据，并利用卡尔曼滤波消除噪声。AWS密钥管理机制使用密钥管理方案，目的是保护云中的数据，防止未经授权的访问。当数据存储在云中时，所提出的系统能够使用随机梯度下降算法和逻辑回归来开发心脏病的预测模型。仿真实验表明，和其他几种算法相比，提出的算法具有更小的误差，且在吞吐量、准确度等方面具有一定的优越性。     

A design of experiments investigation into dry separation using a Knelson Concentrator

Enhanced gravity, or centrifugal, separators have revolutionised gold processing over the past decades, significantly increasing the recovery of fine (−100 μm) free gold. One of the main drawbacks of centrifugal gravity concentrators is the large volume of water required (even if it is all recycled). With water becoming an ever increasingly important “commodity”, reducing this is of importance both from an environmental and a monetary point of view. This work investigated operating a laboratory scale Knelson Concentrator with a dry feed and using air as the fluidising medium. The feed used was a synthetic mixture of tungsten and quartz, used to mimic a gold ore. The response surface method and central composite design techniques were used to design the experiments and to model the results, with the experimental variables being the bowl speed (G-Level), air fluidising pressure and the feed rate. The models corresponded well to the experimental results, indicating that for this experimental setup, the optimal conditions were a bowl G-Level of 40 G, a feed rate of 220 g/min and an air fluidising pressure of 8 psi.     

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.     

Improved method for roadside barrier length of need modeling using real-world trajectories

The 2011 AASHTO Roadside Design Guide (RDG) contains perhaps the most widely used procedure for choosing an appropriate length of need (LON) for roadside barriers. However, this procedure has several limitations. The procedure uses a highly simplified model of vehicle departure, and the procedure does not allow designers to specify an explicit level of protection. A new procedure for choosing LON that addresses these limitations is presented in this paper. This new procedure is based on recent, real-world road departure trajectories and uses this departure data in a more realistic way. The new procedure also allows LON to be specified for a precisely known level of protection – a level which can be based on number of crashes, injury outcomes or even estimated crash cost – while still remaining straightforward and quick to use like the 2011 RDG procedure.     

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.