How to Meet the Diverse Needs of Consumers: Big Data Mining based on Online Review

This article applied Word2vec and image mining on OCRs analysis. Data from Dianping.com showed that in Beijing, good taste is the primary factor for customers to choose a restaurant. Unlike the general opinion, careers and locations have little influence on cuisine choice in Beijing. Hot pot is the most popular one all over the city. Warm color, medium dark light and saturation with certain amount of grey are three key aspects for an enjoyable dining environment. Offline mouth to mouth recommendation is the most useful way to spread a restaurants reputation. So making the antecedent consumer satisfy is the most applied way to appeal new ones. This findings can help restaurant owners to run a better business and promote the satisfactory

Neural control for constrained human-robot interaction with human motion intention estimation and impedance learning

In this paper, an impedance control strategy is proposed for a rigid robot collaborating with human by considering impedance learning and human motion intention estimation. The least square method is used in human impedance identification, and the robot can adjust its impedance parameters according to human impedance model for guaranteeing compliant collaboration. Neural networks (NNs) are employed in human motion intention estimation, so that the robot follows the human actively and human partner costs less control effort. On the other hand, the full-state constraints are considered for operational safety in human-robot interactive processes. Neural control is presented in the control strategy to deal with the dynamic uncertainties and improve the system robustness. Simulation results are carried out to show the effectiveness of the proposed control design

Human-robot co-carrying using visual and force sensing

In this paper, we propose a hybrid framework using visual and force sensing for human-robot co-carrying tasks. Visual sensing is utilized to obtain human motion and an observer is designed for estimating control input of human, which generates robot's desired motion towards human's intended motion. An adaptive impedance-based control strategy is proposed for trajectory tracking with neural networks (NNs) used to compensate for uncertainties in robot's dynamics. Motion synchronization is achieved and this approach yields a stable and efficient interaction behavior between human and robot, decreases human control effort and avoids interference to human during the interaction. The proposed framework is validated by a co-carrying task in simulations and experiments

The effect of pulsed electromagnetic field on the bone volume of human being

AbstractPulsed electromagnetic fields (PEMF) devices have been used clinically to slow down osteoporosis and accelerate the healing of bone fractures for many years. However the underlying mechanism by which bone remodeling under PEMF is regulated remains poorly understood. In this paper, a mathematical model of bone cell population of bone remodeling under PEMF at cellular level is developed to address this issue for the first time. Based on this model and control theory, parametric study of control mechanism is carried out and a number of possible control mechanisms are identified. These findings would help further understanding of bone remodeling under PEMF and potential therapies and pharmacological developments in clinical trials

Food protein-stabilized nanoemulsions as potential delivery systems for poorly water-soluble drugs: preparation, in vitro characterization, and pharmacokinetics in rats

Nanoemulsions stabilized by traditional emulsifiers raise toxicological concerns for long-term treatment. The present work investigates the potential of food proteins as safer stabilizers for nanoemulsions to deliver hydrophobic drugs. Nanoemulsions stabilized by food proteins (soybean protein isolate, whey protein isolate, β-lactoglobulin) were prepared by high-pressure homogenization. The toxicity of the nanoemulsions was tested in Caco-2 cells using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide viability assay. In vivo absorption in rats was also evaluated. Food protein-stabilized nanoemulsions, with small particle size and good size distribution, exhibited better stability and biocompatibility compared with nanoemulsions stabilized by traditional emulsifiers. Moreover, β-lactoglobulin had a better emulsifying capacity and biocompatibility than the other two food proteins. The pancreatic degradation of the proteins accelerated drug release. It is concluded that an oil/water nanoemulsion system with good biocompatibility can be prepared by using food proteins as emulsifiers, allowing better and more rapid absorption of lipophilic drugs

Maximum likelihood estimation of reviewers' acumen in central review setting: categorical data

Successfully evaluating pathologists' acumen could be very useful in improving the concordance of their calls on histopathologic variables. We are proposing a new method to estimate the reviewers' acumen based on their histopathologic calls. The previously proposed method includes redundant parameters that are not identifiable and results are incorrect. The new method is more parsimonious and through extensive simulation studies, we show that the new method relies less on the initial values and converges to the true parameters. The result of the anesthetist data set by the new method is more convincing