A comparative study of NdY-Fe-B magnet and NdCe-Fe-B magnet

Low cost and high abundance rare earth elements Y and Ce have attracted tremendous interests of the industrial and scientific societies for fabricating the highly cost-performance efficient rare earth permanent magnets. However, the effect of separate replacement of Nd by Y or Ce on the performances of NdFeB-type magnet under the same atomic ratio and preparation conditions is still unclear. In this work, we systematically investigated the magnetic properties, thermal stabilities and service performances of (Nd_0.8Y_0.2)_13.80Fe_balAl_0.24Cu_0.1B_6.04 (atomic fraction, denoted as 20Y) and (Nd_0.8Ce_0.2)_13.80Fe_balAl_0.24Cu_0.1B_6.04 (atomic fraction, denoted as 20Ce) magnets. The results demonstrate that the μ₀M_r, μ₀H_c and (BH)_max of 20Y magnet are respectively 1.325 T, 1.173 T and 343.467 kJ/m³, which are comprehensively higher than those of 20Ce magnet (μ₀M_r = 1.310 T, μ₀H_c = 0.948 T, (BH)_max = 321.105 kJ/m³). Moreover, the 20Y magnet has higher thermal stability compared with 20Ce magnet which is favorable for the magnetic performances at elevated temperatures. The investigation of microstructure and elemental distribution indicates that the excellent magnetic performances of NdY-Fe-B magnet can be attributed not only to the preferable intrinsic properties 4πM_s, H_a and T_c of Y₂Fe₁₄B, but also to the in-situ core–shell structure of the 2:14:1 matrix phase grain with Y-rich core and Nd-rich shell, along with the thicker grain boundary layer between the adjacent matrix phase grains in NdY-Fe-B magnet. Furthermore, the 20Y magnet exhibits better mechanical property and higher corrosion resistance than 20Ce magnet, which are helpful for prolonging the service life of the magnet in practical application.     

基于组合双向拍卖的云资源调度方法

针对跨数据中心的资源调度问题，提出了一种基于组合双向拍卖（PCDA）的资源调度方案。首先，将云资源拍卖分为三个部分：云用户代理报价、云资源提供商要价、拍卖代理组织拍卖；其次，在定义用户的优先级及任务紧迫度的基础上，在拍卖过程中估算每一个工作发生的服务等级协议（SLA）违规并以此计算云提供商的收益，同时每轮竞拍允许成交多项交易；最终达到根据用户等级合理分配云资源调度的效果。仿真实验结果表明该算法保证了竞拍成功率，与传统一次拍卖成交一项的组合双向拍卖方案相比，PCDA在竞拍时间段产生的能耗降低了35.00%，拍卖云提供商的利润提高了约38.84%。     

5G技术在医院智能服务中的应用

纵观当今的发展格局,是科学技术高速发展的时代。随着5G时代的来临,网络技术在各个领域中扮演着越来越重要的角色。特别是在医疗方面,为医院的日常工作奠定了坚实的基础。今天就5G网络技术在医院只能服务中的应用展开谈论。     

Model for practical prediction of natural carbonation in reinforced concrete: Part 1-formulation

A model is proposed for prediction of natural carbonation in reinforced concrete (RC) structures, and is potentially applicable to existing and new RC structures. The major components of the model comprise mathematical functions applied to predict the influence of concrete composition, and environmental factors on natural carbonation.This paper introduces the model concept and explains its structure including derivation, optimization and calibration. Over 163 data sets taken from a 10-year carbonation study were used in the model development and calibration. Only the experimental data that were based on outdoor natural exposure environment were employed in this research. Also in this study, the proposed model is compared with fib-Model Code 2010 using carbonation predictions generated from 346 data sets involving real world, highway structures. It is shown that the proposed model is comparably accurate and involves mainly basic tests with no major anticipated costs.     

增强现实中基于位置安全性的LBS位置隐私保护方法

为了解决基于位置的服务(LBS)和增强现实(AR)技术快速发展带来的用户位置隐私泄露的隐患,分析了现有的位置隐私保护方法的优缺点,提出基于位置安全性的位置隐私保护方法。将区域安全度和伪装区域引入该方法中,将提示某区域是否需要保护这一度量标准定义为区域安全度,非安全区域(即需要给予保护的区域)的区域安全度设置为1,安全区域(即不需要保护的区域)设置为0,通过扩大区域安全度和识别等级来计算位置安全度。实验结果表明,该方法与未引入位置安全性的方法相比降低了平均定位误差,提高了平均安全性,从而有效地保护了用户的位置隐私,提高了LBS的服务质量。     

Development of a Hydrogen Refueling Station Design Tool

In the last couple of decades, there has been a growing concern in what effects fossil fuels are having on the environment, resulting in governments and governing organizations issuing stringent emission standards in an effort to curve their environmental damage. To meet these new standards, the transportation industry has been conducting research into alternative fuels, such as hydrogen, but one critical problem utilizing hydrogen is that there is almost no infrastructure. A network of hydrogen refueling stations similar to modern gasoline stations will be required to be constructed to meet future demand. The hydrogen refueling station model was created to aid in designing hydrogen facilities, thus accelerating their development while reducing design cost. A model was created using Simulink consisting of an electrolyzer that generates hydrogen, a compressor, numerous storage tanks, a dispensing unit that transfers hydrogen, and a vehicle component that consumes hydrogen fuel. The model was validated using data from existing hydrogen refueling stations, and the data obtained from testing the previous version of the hydrogen refueling station model to determine model accuracy and if the model has improved. The model has demonstrated that it can produce reasonable results for a station's performance and has improved compared to the previous version.     

Spherical volume-preserving Demons registration

In order to analyze the brain shift situation accurately, we need to register the medical image and analyze its deformation. In this paper, we introduce a framework with volume-preserving registration for brain shift analysis. First, a volume-preserving mapping is introduced for general manifolds supported by a rigorous continuous theory. The registration is then performed on the spherical tetrahedron mesh with MRI gray values. The registration can retain the equality of local volume elements while registering the manifold to a template at the same time. We use simulated brain shift data to test our method. The results show that our method can efficiently register the brain while preserving the volume of each vertex.     

Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloud

This research proposes ACARDS (Augmented-Context bAsed RecommenDation Service) framework that is able to utilize knowledge over the Linked Open Data (LOD) cloud to recommend context-based services to users. To improve the level of user satisfaction with the result of the recommendation, the ACARDS framework implements a novel recommendation algorithm that can utilize the knowledge over the LOD cloud. In addition, the noble algorithm is able to use new concepts like the enriched tags and the augmented tags that originate from the hashtags on the SNSs materials. These tags are utilized to recommend the most appropriate services in the user’s context, which can change dynamically. Last but not least, the ACARDS framework implements the context-based reshaping algorithm on the augmented tag cloud. In the reshaping process, the ACARDS framework can recommend the highly receptive services in the users’ context and their preferences. To evaluate the performance of the ACARDS framework, we conduct four kinds of experiments using the Instagram materials and the LOD cloud. As a result, we proved that the ACARDS framework contributes to increasing the query efficiency by reducing the search space and improving the user satisfaction on the recommended services.     

System for augmented human–robot interaction through mixed reality and robot training by non-experts in customer service environments

Human–robot interaction during general service tasks in home or retail environment has been proven challenging, partly because (1) robots lack high-level context-based cognition and (2) humans cannot intuit the perception state of robots as they can for other humans. To solve these two problems, we present a complete robot system that has been given the highest evaluation score at the Customer Interaction Task of the Future Convenience Store Challenge at the World Robot Summit 2018, which implements several key technologies: (1) a hierarchical spatial concepts formation for general robot task planning and (2) a mixed reality interface to enable users to intuitively visualize the current state of the robot perception and naturally interact with it. The results obtained during the competition indicate that the proposed system allows both non-expert operators and end users to achieve human–robot interactions in customer service environments. Furthermore, we describe a detailed scenario including employee operation and customer interaction which serves as a set of requirements for service robots and a road map for development. The system integration and task scenario described in this paper should be helpful for groups facing customer interaction challenges and looking for a successfully deployed base to build on.     

Comparison of OWAS,RULA and REBA for assessing potential work-related musculoskeletal disorders

This study compared three representative observational methods for assessing musculoskeletal loadings: Ovako Working Posture Analysis System (OWAS), Rapid Upper Limb Assessment (RULA), and Rapid Entire Body Assessment (REBA). The comparison was based on 209 cases of upper-body musculoskeletal disorders (MSDs) diagnosed by medical doctors. The most awkward/stressful posture in each participant's tasks was assessed using these techniques. Postural loadings were rated more highly by the RULA than by the OWAS and REBA (p < 0.01). The chi-square test and logistic regression analysis showed that only RULA grand score and action level, and REBA action level were associated with MSD work-relatedness (p < 0.01, p < 0.05, and p < 0.05, respectively). The percentage concordant values of the logistic model for the RULA grand score and action level were 52.4% and 44.8%, respectively, while the percentage concordant value for the REBA action level was 22.1%. Therefore, the RULA may be the best system for estimating the postural loads and work-relatedness of MSDs.Relevance to industryWork-related musculoskeletal disorders are the leading cause of workplace disability in the developed countries. For preventing the disorders, quantification of musculoskeletal loads is required.