Saving lives using social media: Analysis of the role of twitter for personal blood donation requests and dissemination

Social media has an impact on many aspects of human life ranging from sharing personal information to revolutionizing political systems of entire countries. One not so well studied aspect of social media is analyzing its usage and efficacy in healthcare, particularly in developing countries which lack state-of-the-art healthcare systems and processes. In such countries, social media may be used to facilitate patient-centric healthcare by involving the patient for fulfilling personal healthcare needs. This article provides an in-depth analysis of one such need, that is, how people use social media to request for blood donations. We study the request and dissemination behavior of people using social media to fulfill blood donation requests. We focus on twitter, and blood donation accounts in India. Our study reveals that each of the seven twitter accounts we studied have a large followership of more than 35,000 users on an average and receive a substantial number (more than 900) of donation requests in a day on an average. We analyze the requests in various ways to present an outlook for healthcare providers to make their systems more patient-centric through a better understanding of the needs of people requesting for blood donations. Our study also identifies areas where future social media enabled automated healthcare systems can focus on the needs of individual patients. These systems can provide support for saving more lives by reducing the gap between blood donors and the people in need.     

基于语义推理的文本信息关联关系分析技术

重点论述了文本信息中的知识发现及潜在关联分析技术。采用本体建模技术、信息抽取技术以及知识库上的语义推理技术等来完成并实现文本信息的关联关系发现和分析,最后给出了语义关联分析技术在文本信息处理系统中的应用,并简要描述了系统的处理流程。在信息处理领域的大数据环境下,该技术有利于信息分析人员快速获取关联线索,辅助完成信息挖掘,为指挥决策提供更全面的信息支持。     

Success factors in developing iHeart as a patient-centric healthcare system: A multi-group analysis

Coronary Heart Disease is the number one killer disease not only in Malaysia and Iran but also in many countries around the world. Though early diagnosis is critical for successful treatment of the disease, immediate reaction in cases of emergency is crucial significance in saving the lives of stricken. Previous studies on patient-centric healthcare indicate that both the patient’s whereabouts and the locality of the healthcare centers play a vital role at moment of crisis. Not only it is important for a patient to be able to find the nearest healthcare points, it is also necessary for the emergency centers to know the exact location of the patient seeking for help. To this end, a Location-Based Mobile Cardiac Emergency System (iHeart) is proposed, which is a patient-centric healthcare system, to monitor and track the patient via a wearable device and their mobile phones. Therefore, this study aims to find healthcare professional’s opinion and to find success factors of such a system before its full implementation. A survey was conducted in the form of questionnaire in Malaysia and Iran. In order to conduct the survey, a conceptual model was proposed based on DeLone and McLean Information Success Model. A total number of 323 data was collected from both countries. The results were analyzed using Structural Equation Modeling (SEM) with AMOS software. Multi-group comparison was applied to find differences in points of view from both countries. The results of this study revealed the success factors of iHeart before the full implementation. It was found that nationality plays a moderating role between some of the success factors and success of iHeart. The success of a patient-centric healthcare system is bound to the culture of a particular nation as well as to the technological advancements, facilities, and the needs of the target users, meaning that in order for a novel healthcare system to be publicly acknowledged and utilized; target users must be classified and assessed accordingly. The findings of the present study are highly beneficial to both patients suffering from Coronary Heart Disease and the healthcare providers that seek to utilize new patient-centric healthcare systems, devices, and electronic applications to rescue patients.     

Visualizing latent domain knowledge

Knowledge discovery and data mining commonly rely on finding salient patterns of association from a vast amount of data. Traditional citation analysis of scientific literature draws insights from strong citation patterns. Latent domain knowledge, in contrast to the mainstream domain knowledge, often consists of highly relevant but relatively infrequently cited scientific works. Visualizing latent domain knowledge presents a significant challenge to knowledge discovery and quantitative studies of science. We build upon a citation-based knowledge visualization procedure and develop an approach that not only captures knowledge structures from prominent and highly cited works, but also traces latent domain knowledge through low-frequency citation chains. We apply this approach to two cases: (1) identifying cross-domain applications of Pathfinder networks (PFNETs) and (2) clarifying the current status of scientific inquiry of a possible link between Bovine spongiform encephalopathy (BSE), also known as mad cow disease, and a new variant Creutzfeldt-Jakob disease (vCJD), a type of brain disease in humans     

数据挖掘技术的方法和最新进展

随着大型数据库的不断涌现，不缺数据缺知识的矛盾日益突出。如何从浩如烟海的数据中发现隐藏的知识，创造更大的效益是一个迫切需要解决的课题。因此，知识发现和数据挖掘应运而生，成为一个新的研究领域。在此，介绍了数据仓库、知识发现和数据挖掘的基本概念，重点论述了数据挖掘技术的方法，并指出了研究方向。     

医学虚拟现实技术研究

医学虚拟现实技术(MedicalVirtual Reality Technology),作为一门新兴学科目前正在逐步形成之中,它是集医学,生物力学,机械学,材料学,计算机图形学,计算机视觉,数学分析,机械力学机器人等多学科为一体的新型交叉研究领域。而医学虚拟现实技术是一种悄然进入医疗教育领域的全新技术策略,它势将为未来医疗技术的发展提供了更为广泛的前景。     

基于二维查找表结构的SAR原始数据自适应频域压缩算法

该文针对实际SAR多普勒中心偏移及多普勒谱分裂问题,提出基于一维查找表的自适应多普勒非均匀压缩比分配方法,该方法结合一维量化编码查找表构成二维查找表结构的SAR原始数据自适应频域压缩算法。该文推导了SAR距离向回波频谱解析式,给出距离向非均匀压缩比分配通用方案。实际数据处理结果表明,该方法比传统频域类压缩算法具有更好的信噪比及鲁棒性。理论分析结果表明,其运算量提高很小,易于工程实现。     

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.     

Superconducting Electronics Research at CSIRO Australia-20 Years after Discovery of HTS

CSIRO has had a long-term research effort in superconductivity, in particular, since the discovery of HTS which promised big prospects. Significant progress has been made in research and development of HTS electronic devices and systems for practical applications such as mineral and exploration as well as some niche applications in emerging science and technology areas. This article presents an overview of the CSIRO research activities in HTS superconducting electronics since 1987, outlining the HTS junction and device technology as well as various application systems develop by the group.     

A Frequency Domain Method for Analyzing Period Doubling Bifurcations in Discrete-Time Systems

A frequency domain methodology for the approximation of period doubling bifurcations in discrete-time nonlinear systems is presented. The computation of a stability index, which characterizes the dynamical behavior of the emerging period-two orbit is also derived. The technique is applied to estimate the domain of attraction of the fixed point in an adaptive control system and to improve the dynamical behavior of a buck converter.     

Superconducting Electronics Research at CSIRO Australia ——20 Years after Discovery of HTS

CSIRO has had a long-term research effort in superconductivity, in particular, since the discovery of HTS which promised big prospects. Significant progress has been made in research and development of HTS electronic devices and systems for practical applications such as mineral and exploration as well as some niche applications in emerging science and technology areas. This article presents an overview of the CSIRO research activities in HTS supercon- ducting electronics since 1987, outlining the HTS junction and device technology as well as various application systems developed by the group.     

Superconducting Electronics Research at CSIRO Australia——20 Years after Discovery of HTS

CSIRO has had a long-term research effort in superconductivity, in particular, since the discovery of HTS which promised big prospects. Significant progress has been made in research and development of HTS electronic devices and systems for practical applications such as mineral and exploration as well as some niche applications in emerging science and technology areas. This article presents an overview of the CSIRO research activities in HTS supercon- ducting electronics since 1987, outlining the HTS junction and device technology as well as various application systems developed by the group.     

A framework for reconfigurable computing: task scheduling andcontext management

Dynamically reconfigurable architectures are emerging as a viable design alternative to implement a wide range of computationally intensive applications. At the same time, an urgent necessity has arisen for support tool development to automate the design process and achieve optimal exploitation of the architectural features of the system. Task scheduling and context (configuration) management become very critical issues in achieving the high performance that digital signal processing (DSP) and multimedia applications demand. This article proposes a strategy to automate the design process which considers all possible optimizations that can be carried out at compilation time, regarding context and data transfers. This strategy is general in nature and could be applied to different reconfigurable systems. We also discuss the key aspects of the scheduling problem in a reconfigurable architecture such as MorphoSys. In particular, we focus on a task scheduling methodology for DSP and multimedia applications, as well as the context management and scheduling optimizations     

Fault detection for a via etch process using adaptive multivariate methods

Multivariate process control charts like Hotelling T/sup 2/ and squared prediction error are gaining acceptance in the semiconductor industry to monitor the increasing amount of data available by modern process tools. These methods require models built based on the covariance matrix of a trainings data set. Slowly drifting manufacturing processes degrade this estimation for the covariance matrix creating false alarms. To overcome the problem, adaptive modeling schemes are considered. The tradeoff between sensitivity and false alarms for static and adaptive models applied to a via etching process is demonstrated. Possible improvements by incorporating domain knowledge are shown.     

Control and Communication Challenges in Networked Real-Time Systems

A current survey of the emerging field of networked control systems is provided. The aim is to introduce the fundamental issues involved in designing successful networked control systems, to provide a snapshot assessment of the current state of research in the field, to suggest useful future research directions, and to provide a broad perspective on recent fundamental results. Reflecting the goals of the Special Issue itself, this paper surveys relevant work from the areas of systems and control, signal processing, detection and estimation, data fusion, and distributed systems. We discuss appropriate network architectures, topics such as coding for robustly stable control in the presence of time-varying channel capacity, channels with fixed versus adaptively variable data width, issues in data rate problems in nonlinear feedback problems, and problems in routing for stability and performance. In surveying current research on networked control systems, we find that recent theoretical advances and target applications are intimately intertwined. The common goal of papers in the Special Issue which follows is to describe key aspects of this relationship. We also aim to provide a bridge between networked control systems and closely related contemporary work dealing with sensor networks and wireless communication protocols     

Efficient device‐to‐device discovery and access procedure for 5G cellular network

A large number of new data‐consuming applications are emerging, and many of them involve mobile users. In the next generation of wireless communication systems, device‐to‐device (D2D) communication is introduced as a new paradigm to offload the increasing traffic to the user equipment. Before the traffic transmission, D2D discovery and access procedure is the first important step which needs to be completed. In this paper, our goal is to design a device discovery and access scheme for the fifth generation cellular networks. We first present two types of device discovery and access procedures. Then we provide performance analysis based on the Markov process model. In addition, we present numerical simulation on the Vienna Matlab platform. The simulation results demonstrate the viability of the proposed scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

Indoor geolocation science and technology

This article presents an overview of the technical aspects of the existing technologies for wireless indoor location systems. The two major challenges for accurate location finding in indoor areas are the complexity of radio propagation and the ad hoc nature of the deployed infrastructure in these areas. Because of these difficulties a variety of signaling techniques, overall system architectures, and location finding algorithms are emerging for this application. This article provides a fundamental understanding of the issues related to indoor geolocation science that are needed for design and performance evaluation of emerging indoor geolocation systems     

Adaptive coding for time-varying channels using outdated fadingestimates

The idea of using knowledge of the current channel fading values to optimize the transmitted signal in wireless communication systems has attracted substantial research attention. However, the practicality of this adaptive signaling has been questioned due to the variation of the wireless channel over time, which results in a different channel at the time of data transmission than at the time of channel estimation. By characterizing the effects of fading channel variation on the adaptive signaling paradigm, it is demonstrated here that these misgivings are well founded, as the channel variation greatly alters the nature of the problem. The main goal of this paper is to employ this characterization of the effects of the channel variation to design adaptive signaling schemes that are effective for the time-varying channel. The design of uncoded adaptive quadrature amplitude modulation (QAM) systems is considered first, and it demonstrates the need to consider the channel variation in system design. This is followed by the main contribution of this paper; using only a single outdated fading estimate when neither the Doppler frequency nor the exact shape of the autocorrelation function of the channel fading process is known, adaptive trellis-coded modulation schemes are designed that can provide a significant increase in bandwidth efficiency over their nonadaptive counterparts on time-varying channels