The underlying factors of the perceived usefulness of using smart wearable devices for disaster applications

Smart wearable devices offer much potential to assist citizens in disasters. To the general public, however, using these devices for disaster applications is still a novel concept. In disasters, most people are reluctant to rely on unfamiliar technologies. Thus, for these devices to become truly useful in disasters, it is important to understand factors that affect their acceptance by the public. Previous studies show that perceived usefulness is a clear antecedent of people’s acceptance of smart wearable devices. However, the underlying factors that affect perceived usefulness itself are not clearly known. Thus, the aim of this study is to fill this gap, and by doing so, to derive some practical implications for solution developers and governments.This study used structural equation modelling to analyse survey data collected from 647 respondents in Japan. We found that the respondents’ perceived usefulness of the current applications of smart wearable devices was a strong predictor of their perceived usefulness of using these devices for disaster applications. Although indirect factors such as the ownership of ICT gadgets and the usage of social media also had some influences, most of their effects were mediated through increasing the respondents’ perceived usefulness of the current applications. In other words, through appreciating the functions of the current applications of smart wearable devices, people can visualise the usefulness of these devices in disaster situations. That being said, we found that in parallel, people also had concerns on the privacy issues of these devices. These findings shed light on the promotion and development of this fast growing technology for disaster applications.     

一种非实时系统灾备资源利用方法的研究

传统的灾备系统对于灾备资源未能充分利用,如何将庞大的灾备资源充分利用,避免资源的浪费一直备受关注。本文着重从一类非实时业务系统的灾备系统资源再利用研究和实现方面进行介绍和分析,在全面认识和分析灾备系统建设的特点基础上,阐述了针对非实时业务系统的灾备资源再利用的研究方向。     

Linux平台远程逻辑卷复制系统的灾难恢复策略

在存储管理中,数据保护是重要的一环.本文提出了一种基于Linux平台远程逻辑卷复制系统的灾难恢复策略,并论述了它的基本原理及实现方法.该灾难恢复策略保证了本地系统的数据卷在遭受灾难的情况下,可以被远程系统进行接管,并在适当时候根据远程数据卷实现本地数据的有效恢复,大大提高了数据保护能力,并在一定程度上降低了管理开销.     

Mobile Data Science and Intelligent Apps: Concepts,AI-Based Modeling and Research Directions

Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processing, as well as knowledge representation and expert systems, can be used to make the target mobile applications intelligent and more effective. In this paper, we present a comprehensive view on “mobile data science and intelligent apps” in terms of concepts and AI-based modeling that can be used to design and develop intelligent mobile applications for the betterment of human life in their diverse day-to-day situation. This study also includes the concepts and insights of various AI-powered intelligent apps in several application domains, ranging from personalized recommendation to healthcare services, including COVID-19 pandemic management in recent days. Finally, we highlight several research issues and future directions relevant to our analysis in the area of mobile data science and intelligent apps. Overall, this paper aims to serve as a reference point and guidelines for the mobile application developers as well as the researchers in this domain, particularly from the technical point of view.

     

信息系统灾难恢复计划研究

灾难发生时,需要有量化的、精确的方法从多个子灾难恢复计划中选择最优集合实现灾难恢复。该文采用最优化理论提出一个灾难恢复计划数学模型。模型表示系统中不同应用、设施、资源、子灾难恢复计划、预算等以及它们之间的关系,对资源进行分类,解决不同子灾难恢复计划之间的冲突。模型具有较少的主观参数,以实现客观评价灾难恢复计划,易于对灾难恢复计划进行精确、量化的分析。论文给出了模型的实施步骤与模型分析,实验验证了模型的正确性。     

SENDROM: Sensor networks for disaster relief operations management

SENDROM is a new sensor network architecture to manage the rescue operations after large scale disasters. This architecture mainly consists of sensor nodes deployed prior to a disaster and central nodes that can query sensor nodes. Central nodes are stored nearby the emergency operation centers and airports before a disaster. Following a disaster rescue teams are assigned one mobile central node and guided to a region based on the data in the SENDROM database. This paper explains the SENDROM architecture as well as our new task and data dissemination, localization of a detected person, and end-to-end reliable event transfer schemes introduced for SENDROM. Then it evaluates the performance of these schemes analytically and through simulation.     

Web-based intranet services and network management

Intranets are composed of a network of various devices, systems, and services supporting a wide variety of applications within an organization. Providing a secure, reliable, and efficient operating environment to support the organization's daily activities and its business is the most challenging task faced by operations and management staff today. Current management practices typically involve the use of separate, incompatible tools and techniques for managing networks, systems, and applications. What is needed desperately is a simple, uniform framework for managing not only networks but also systems and applications. Web-based management is a promising approach that can provide a truly integrated management solution. This article examines the key emerging technologies involved in Web-based management. The authors present an integrated architecture that can be used to manage all the networking and computing resources in an Intranet. Also presented are several specific examples where Web technology has been applied in managing different target resources for validating the architecture     

An ad hoc networking scheme in hybrid networks for emergency communications

This paper describes an ad hoc networking scheme and routing protocol for emergency communications. The objective of the network is to collect damage assessment information quickly and stably in a disaster. The network is configured with a hybrid wireless network, combining ad hoc networks and a cellular network to maintain connectivity between a base station (BS) and nodes even in a disaster. In the event that a direct link between the BS and a node is disconnected due to damage or obstacles, the node switches to the ad hoc mode, and accesses the BS via neighboring nodes by multihopping. The routing protocol proposed in this paper discovers and builds a route by way of monitoring neighbors’ communications instead of broadcasting a route request packet. The network employs a dedicated medium access control protocol based on TDM (Time Division Multiplexing) for multihopping in ad hoc networks to maintain accessibility and to perform a short delay. Experiments showed that approximately 90% of nodes are capable of reaching the BS within a few hops, even in conditions where only 20% of nodes maintain direct connections to the BS. In addition, the results showed that it is feasible for the network to operate in a short delay for delivering a packet to the BS. However, throughput is not retrieved sufficiently due to the restriction of the access protocol, whereas reachability does improve sufficiently. Therefore, the network is suitable for collecting damage assessment information and transmitting urgent traffic quickly and stably, while the data is restricted to a small amount.     

DistressNet: A disaster response system providing constant availability cloud-like services

Large scale disasters like the earthquake and tsunami in Japan (2011) cripple the local infrastructure. Proprietary systems and protocols used today for disaster response still lack data at the high spatial and temporal resolution needed to quickly save lives and to support disaster recovery efforts. Victims are rescued after days, if not weeks; digital coordination interfaces among responders are lacking, or are based on archaic methods (pencil, paper, paint on walls); the delay in receiving vast amounts of information from the field is bounded by the time used to physically transport tapes or hard drives. In this paper we present the design, implementation and evaluation of DistressNet, a system that provides services for emergency response applications. DistressNet integrates a variety of rapidly deployable, battery powered COTS devices into a secure framework. An optimal placement of networked components allows users to quickly and reliably store and retrieve data, in a “cloud”-like manner, from a local intermittently connected “fog”. High volumes of field data are available for emergency response personnel to view on interfaces like smartphones and tablets. DistressNet is a large academic effort, proposing open systems, instead of proprietary solutions. It has been developed in collaboration with Texas Task Force 1 and its components have been evaluated for over one year in outdoor deployments that required over 1500 man hours.     

NFVO容灾备份方案分析

NFVO，作为云管理的决策者，需要满足高可靠性要求，以确保单节点发生故障时不影响业务的正常运行。为提高资源利用率，建议NFVO采用N+1主备方式部署，同时对NFVO的容灾倒换机制进行了简单介绍     

云灾备中系统级管理技术的关键问题

文章指出云计算技术的核心在于对计算资源、存储资源和传输资源的系统级管理;云灾备的核心则在于利用云中海量资源,为用户提供系统级、数据级和业务级的灾难恢复服务和持续性服务。为了解决云灾备遇到的管理方面的挑战,文章有针对性地对云灾备管理中的最大化收益管理、高可用服务管理、业务连续服务管理、安全保障管理4个方面进行了分析和探讨。     

Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey

How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.     

What factors contribute to the acceptance of artificial intelligence? A systematic review

Artificial Intelligence (AI) agents are predicted to infiltrate most industries within the next decade, creating a personal, industrial, and social shift towards the new technology. As a result, there has been a surge of interest and research towards user acceptance of AI technology in recent years. However, the existing research appears dispersed and lacks systematic synthesis, limiting our understanding of user acceptance of AI technologies. To address this gap in the literature, we conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and meta-Analysis guidelines using five databases: EBSCO host, Embase, Inspec (Engineering Village host), Scopus, and Web of Science. Papers were required to focus on both user acceptance and AI technology. Acceptance was defined as the behavioural intention or willingness to use, buy, or try a good or service. A total of 7912 articles were identified in the database search. Sixty articles were included in the review. Most studies (n = 31) did not define AI in their papers, and 38 studies did not define AI for their participants. The extended Technology Acceptance Model (TAM) was the most frequently used theory to assess user acceptance of AI technologies. Perceived usefulness, performance expectancy, attitudes, trust, and effort expectancy significantly and positively predicted behavioural intention, willingness, and use behaviour of AI across multiple industries. However, in some cultural scenarios, it appears that the need for human contact cannot be replicated or replaced by AI, no matter the perceived usefulness or perceived ease of use. Given that most of the methodological approaches present in the literature have relied on self-reported data, further research using naturalistic methods is needed to validate the theoretical model/s that best predict the adoption of AI technologies.     

Self-determination and attitudes toward artificial intelligence: Cross-national and longitudinal perspectives

Artificial intelligence (AI) is becoming increasingly important in all domains of life. Therefore, it is crucial to understand individuals’ attitudes towards AI. This article investigated attitudes toward AI through two studies that are based on the self-determination theory and basic psychological needs (autonomy, competence, and relatedness). Study 1 used cross-sectional samples of adult populations aged 18–75 from Finland (N = 1,541), France (N = 1,561), Germany (N = 1,529), Ireland (N = 1,112), Italy (N = 1,530), and Poland (N = 1,533). Study 2 was based on a longitudinal two-wave sample of adults aged 18–80 from Finland (N = 828). Based on the robust regression analyses, Study 1 found that fulfillment of basic psychological needs was associated with higher AI positivity and lower AI negativity across Europe. According to the Study 2 results, based on hybrid multilevel regression models, autonomy and relatedness increased AI positivity and decreased AI negativity over time. The results provide robust evidence on the role of self-determination in attitudes towards AI. Self-determination is an important factor in AI acceptance and is becoming increasingly important considering the rapid development and adoption of AI solutions.     

Graph neural network-based virtual network function deployment optimization

Software-defined networking (SDN) and network function virtualization (NFV) help reduce the operating expenditure (OPEX) and capital expenditure (CAPEX) as well as increase the network flexibility and agility. However, since the network is more dynamic and heterogeneous than before, operators have problems to cope with the increased complexity of managing virtual networks and machines. This complexity is paired with strict time requirements for making management decisions; traditional mechanisms that rely on, for example, integer linear programming (ILP) models are no longer feasible. Machine learning has emerged as one of the possible solution to address network management problems to get near-optimal solutions in a short time. However, applying machine learning to network management is also not simple and has many challenges. Especially, understanding the network environment is an important problem for designing a machine learning model. In this paper, we proposed to use graph neural network (GNN) for virtual network function (VNF) management. The proposed model solves the complex VNF management problem in a short time and gets near-optimal solutions. We developed a model by taking into account various network environment conditions so that it can be applied in the actual network environment. Also, through in-depth experiments, we suggested the direction of the machine learning-based network management method.     

航天高光谱遥感应用研究进展(特邀)

近年来随着高光谱成像技术的快速发展,航天高光谱遥感数据在各领域应用研究中取得了良好的发展与突破。文中回顾了国内外航天高光谱成像技术的发展历程,介绍了有代表性的航天高光谱成像仪的主要应用技术指标,较为系统地总结和分析了近五年来航天高光谱遥感数据在国土资源、农林遥感、海洋湖泊遥感、城市环境、灾害监测及其他方面等各领域的最新应用研究进展。对基于AI技术的高光谱信息提取与应用、基于高光谱遥感的多源数据融合与应用以及面向深空探测领域的高光谱数据分析与应用等发展趋势做了展望,未来航天高光谱成像仪技术的进一步突破和应用研究需求的牵引将会推动高光谱应用领域更大范围的创新与发展。     

基于射频卡的保安巡更系统的研制开发

介绍了一种基于射频卡及其读写器进行二次开发而成的.方便实用的保安巡更系统由PC微机、单片机、射频卡及其读写器等部分组成,完成了巡更资料的采集、传输、管理等功能.该系统既可以加强对保安人员的监督管理,又可以省去管理人员查岗麻烦,同时也适应了各部门逐步普及计算机管理、提高管理水平的要求,具有很好的实用和推广意义.     

Ontology Development for Designing and Managing Dynamic Business Process Networks

Recent advances in flexible process design and deployment technologies, such as web services and flexible workflow systems, promise the development of flexible intra- and inter-organizational business process networks with potential economic benefits. However, exploiting this potential requires the development of scalable process-management technologies that provide a consistent viewpoint and common language (for describing properties of the process network) to all stakeholders involved in its management. Current approaches to managing such networks requires one to use a babel of languages (in the formal sense) at different levels of abstraction. The development of explicit process ontologies is one of the potentially viable approaches to provide an unified view. In this paper, we discuss the need for process ontologies, propose a task-based ontological framework synthesizing recent research in the fields of AI planning and software engineering, and illustrate the need to link declarative and procedural process representations. We illustrate the use of this ontological framework for managing processes in developing applications for integrating information from disparate information sources in multiple domains. Further, based on this experience, we discuss potential benefits and areas for future research.     

30 GHz SiGe active inductor with voltage controlled Q

An active inductor (AI) based on a cascade gyrator for 30 GHz applications implemented with a 0.25 μm in SiGe technology is presented. The gyrator converts not only a key capacitor into an inductor, but also an added resistor, into a negative resistor. This gyrator-RC has its losses compensated by the negative resistor improving the active inductor Q factor. Changing the bias voltage and current allows to obtain a variable AI. A study of a cascade gyrator AI topology is done to understand the circuit behavior and key elements. For this purpose, an AI impedance model is introduced and discussed. An improved AI with the added resistor replaced by a voltage controlled mosfet resistor is proposed. This extra control voltage allows the variable AI quality factor fine tuning. Schematic and circuit extracted from layout simulations are presented, and compared with the measured results of two prototypes of the AIs (one with a fixed resistor and other with a voltage controlled resistor). A prototype of a high pass filter using the AI with fine Q control was fabricated. Non-linear simulations for different input signal levels were performed and compared with measurements. Also discussion on the non-linear models accuracy is performed.     

交通2.0——智慧交通的关键

基于"Web 2.0"、"City 2.0"、"政府2.0"等概念,提出了"交通2.0"概念,并建立了系统模型。该系统模型包括众筹数据和开放数据两个维度,众筹数据通过收集公众从智能手机、车载终端、Web 2.0网站上传的交通数据,获取现有检测系统不能提供的实时数据,并及时解决公众使用交通系统过程中发现的问题;开放数据通过开放公共数据,催化公众把开放的数据做出各种相互补充相互竞争的应用和服务,形成可持续的全面解决方案和创新的生态环境。该系统模型通过云计算、大数据处理、手机应用等技术做到了聚合众筹数据,提供开放数据以催化产生创新的交通应用和服务以完善现有交通设施和管理制度,并给将来的交通规划提供数据支撑和科学决策支持。智慧交通项目集成"交通2.0"后,实践表明奠定众筹数据和开放数据两个渠道,使公众能够积极地参与到交通生态链的完善和智慧化过程中来,是真正实现从"智能"到"智慧"的关键,是智慧交通系统产生活力的源泉。