A hybrid multi-criteria decision-making method for cloud adoption: Evidence from the healthcare sector

The purpose of this paper is to investigate the main determinants (criteria as well as sub-criteria) influencing the adoption decision of cloud computing (CC) in the healthcare sector. In the present study, qualitative interviews and the Delphi method are used to find the relevance of identified determinants (criteria and sub-criteria) from literature. Further, an integrated hybrid approach of interpretive structural modeling, analytic hierarchy process, and Technique for Order Preference by Similarity to Ideal Solution (ISM-AHP-TOPSIS) have been employed to identify interrelationships among criteria, rank critical criteria as well as subcriteria, and find the most suitable cloud service provider (CSP) respectively. This study analyses seven criteria and twenty-one sub-criteria that offers a roadmap to decision-makers before CC-adoption (CCA). The analysis of ISM and AHP revealed technology as the most critical and human-environment as the least critical criteria. The vital sub-criteria associated with each criterion are Management Strategic Planning (under Organisation), Government Policy (External Environment), Security (Technology), Financing of IT in Hospital (Economic), Perceived Visibility (Social), and Attitude of Colleagues about Cloud Computing (Human Environment). The results from TOPSIS revealed CSP5 being the most suitable service provider followed by CSP2. Finally, this research makes methodological contribution in terms of an integrated hybrid method, to select a suitable CSP for the healthcare sector and the theoretical contribution in terms of criteria & sub-criteria. This article answers an important question, i.e., whether the benefits of CCA outweighs its barriers, thereby exploring the potential (and future) of CC for the advancement of healthcare provision.     

云计算在智慧医院信息服务中的应用

随着医疗服务体系的发展和进步,越来越多的医院开始将云计算技术引入信息服务系统,使医院信息化建设得到了迅速发展。文章分析了云计算技术的特点及其在智能医院信息服务中的应用和影响,以期促进该技术在未来的发展和推广。     

Should medium-sized contractors still implement home-made information technologies on construction sites?

Despite the increasing dissemination of the Building Information Modeling (BIM) approach, many firms are still far from BIM and are only starting to adopt information technologies. We conducted an ethnographic action research with an industrial partner that implements information technologies on its construction sites, with a strong preference for home-made applications. Results show that the development of such applications faces difficulties and that multiple iterations and versions are necessary before achieving the expected goals because the required competencies are lacking among internal development teams. Moreover, initial needs evolve considerably throughout the application’s development and evaluation process. However, notwithstanding the difficulties encountered during the different application development phases, the industrial partner believes the decision to be worthwhile because of the desire to have internal control over the project data and the need to consider certain specificities related to business processes.     

基于火箭遥测的地面站接收信号情况预估方法

火箭尾焰造成的信号衰减是地面测量点位选择重点考虑的问题,通常采用传统β角确定火箭尾焰对遥测地面站接收信号的影响程度。针对新型固体火箭发射中β角分析法对遥测地面站接收信号情况预测不准确的问题,文中在分析影响遥测地面站信号接收因素的基础上,提出了一种采用信号衰减方向性预估遥测地面站接收信号情况的模型。通过分析火箭遥测实测飞行姿态、位置以及地面遥测设备实际跟踪信号情况确定了模型参数,并通过实例计算证明了该方法优的优越性。     

多流多科目实时数据处理算法的设计与实现

随着飞行试验测试技术的快速发展,单架次需要处理的试飞科目越来越多,而多科目处理参数分布在不同的网络流中,这对机载实时数据处理的效率带来严峻的挑战。利用“合并-处理-分流”的方法,设计一种多流多科目网络数据实时处理算法。该算法将多科目处理参数按照参数名、采样率等信息进行整合形成合并参数列表；在实时处理时根据合并参数信息实时处理多网络流中的数据,并将处理结果存储在数据缓存中；最后将多科目数据进行分流即可得到处理结果。测试结果表明,该算法可实际应用于多流多科目数据处理中,大幅提高实时处理的效率,同时可以得到准确的数据处理结果。     

Bioinspired interactive neuromorphic devices

The performance of conventional computer based on von Neumann architecture is limited due to the physical separation of memory and processor. By synergistically integrating various sensors with synaptic devices, recently emerging interactive neuromorphic devices can directly sense/store/process various stimuli information from external environments and implement functions of perception, learning, memory, and computation. In this review, we present the basic model of bioinspired interactive neuromorphic devices and discuss the performance metrics. Next, we summarize the recent progress and development of bioinspired interactive neuromorphic devices, which are classified into neuromorphic tactile systems, visual systems, auditory systems, and multisensory system. They are discussed in detail from the aspects of materials, device architectures, operating mechanisms, synaptic plasticity, and potential applications. Additionally, the bioinspired interactive neuromorphic devices that can fuse multiple/mixed sensing signals are proposed to address more realistic and sophisticated problems. Finally, we discuss the pros and cons regarding to the computing neurons and integrating sensory neurons and deliver the perspectives on interactive neuromorphic devices at the material, device, network, and system levels. It is believed the neuromorphic devices can provide promising solutions to next generation of interactive sensation/memory/computation toward the development of multimodal, low-power, and large-scale intelligent systems endowed with neuromorphic features.     

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method. In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.      

Parallel Multipopulation Differential Evolutionary Particle Swarm Optimization for Voltage and Reactive Power Control

This paper presents parallel multipopulation differential evolutionary particle swarm optimization (DEEPSO) for voltage and reactive power control (VQC). The problem can be formulated as a mixed integer nonlinear optimization problem and various evolutionary computation techniques have been applied to the problem including PSO, differential evolution (DE), and DEEPSO. Since VQC is one of the online controls, speed‐up of computation is required. Moreover, there is still room for improvement in solution quality. This paper applies parallel multipopulation DEEPSO in order to speed up the calculation and improve solution quality. The proposed method is applied to IEEE 30, 57, and 118 bus systems. The results indicate that the proposed method can realize fast computation and minimize more active power losses than the conventional evolutionary computation techniques.     

波前传感器电铸镍层应力实时检测精度评估

目的 搭建电铸应力实时检测平台，评估其测量精度，并探明电化学沉积过程中镍层平均内应力的变化规律。方法 采用横向剪切波前传感器搭建电铸应力实时检测平台，通过测量在铸层应力作用下电铸基底弯曲的曲率半径，利用Stoney公式计算铸层平均应力。采用参考球面反射镜评估横向剪切波前传感器曲率半径的测量精度，并在0.5 A/dm2电流密度下进行电铸应力实时检测实验，对铸层平均应力测量极限进行评估，同时对检测误差进行分析。结果 横向波前传感器曲率半径测量精度为99.22%，在0.5 A/dm2电流密度下，所搭建的铸层应力实时检测平台可测量的最小厚度为5.1 μm，由曲率测量波动带来的应力检测误差为1.3 MPa。实验测得铸层平均应力随铸层厚度的增加而变大，当铸层厚度达到30 μm左右，铸层平均应力趋于稳定，应力大小为79.7 MPa。同时发现，当铸层厚度小于30 μm时，沿电铸基底长度方向的铸层平均应力明显大于宽度方向铸层平均应力，随铸层厚度的增加，两个方向的应力大小趋于等值。结论 采用横向剪切波前传感器搭建的电铸应力检测平台，能有效对铸层应力进行高精度的实时测量，为精密电铸过程中应力变化规律的研究提供了检测技术基础。     

基于一种云计算数据保护的多级加密算法的应用研究

云计算是分布式计算技术的一种,其最基本的概念是透过网络将庞大的计算处理程序自动分拆成无数个较小的子程序,再交由多部服务器所组成的庞大系统经搜寻、计算分析之后将处理结果回传给用户。云计算中的数据泄漏已经成为云计算的巨大威胁,据不完全统计数据,仅在2019年1年,大约有超40亿条信息被泄露。这些信息涵盖科技、医疗、政府、金融、教育、制造等十几个领域数百个行业,数据泄露已经成为云计算中数据安全的巨大威胁。主要提出了一种多级加密算法,能更好地保护云计算中的数据,并能以极小的成本在云计算中得到应用。