Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

On-demand Virtual Neonatal Intensive Care units supporting rural, remote and urban healthcare with Bush Babies Broadband

Premature and ill term babies born in regional Australia must be moved to another hospital with Neonatal Intensive Care Unit (NICU) facilities. Transferred pre-term and critically ill term babies have higher mortality rates and much higher rates of long term disability than similar babies born in hospitals with NICU facilities. This paper details the Bush Babies Broadband project that aims to significantly improve the quality of treatment for babies born in rural, remote as well as urban areas by providing the first on-demand virtual NICU architecture in Australia. Real-time data collected from medical monitors and ventilators attached to the baby, audiovisual streams and static physiological data such as X-ray images are transmitted to the consulting Neonatologist to gain a better picture of the patient's condition than is currently available. The key contribution of this significant research is the infrastructure providing a mechanism for Neonatologists to receive information directly from a regional hospital, thereby preventing, in some cases, the immediate need to move the baby. A key benefit of this framework is that it is available to link regional hospitals with the supporting NICU Neonatologist ‘on demand’ eliminating the need to establish permanent point to point connections. This paper further describes the application of that architecture to a specific pilot connecting the Bathurst regional hospital with Neonatologists within the NICU at Nepean Hospital, Penrith Australia.     

Algorithms for Quantum Branching Programs Based on Fingerprinting

In the paper, we develop a method for constructing quantum algorithms for computing Boolean functions by quantum ordered read-once branching programs (quantum OBDDs). Our method is based on ˉngerprinting technique and representation of Boolean functions by their characteristic polynomials. We use circuit notation for branching programs for desired algorithms presentation. For several known functions our approach provides optimal QOBDDs. Namely we consider such functions as MODm, EQn, Palindromen, and PERMn (testing whether given Boolean matrix is the Permutation Matrix). We also propose a generalization of our method and apply it to the Boolean variant of the Hidden Subgroup Problem.     

A H-QoS-demand personalized home physiological monitoring system over a wireless multi-hop relay network for mobile home healthcare applications

For the elderly and chronic patients with cardiovascular disease who live alone, it is necessary to constantly monitor their physiological parameters, especially the electrocardiogram (ECG), to effectively prevent and control their health condition and even to provide urgent treatment or care while an emergency such as the abnormal variation of heart rate (HR) occurs. In this paper, a wireless in-home physiological monitoring system, based on multi-hop relay communications, which can ubiquitously and continuously monitor the patient's ECG at any time or any place at home without space limit and the “dead spot” due to the extended communication coverage by multi-hop wireless connectivity, is proposed. The system consists of a mobile-care device, which is responsible for capturing and wirelessly sending the patient's ECG data, a wireless multi-hop relay network (WMHRN) that is in charge of relaying the data sent by the former, and a residential gateway (RG), which is responsible for gathering and uploading the received ECG data to the remote care server through the Internet to carry out the patient's health condition monitoring and the management of pathological data. However, in order to assure that the ECG data can be effectively and timely forwarded, from the mobile-care device to the RG through the WMHRN, to meet the healthcare quality of service (H-QoS) demand for reliable and real-time end-to-end ECG transmission, the analysis of WMHRN latency in data-forwarding stage and the deployment consideration of wireless relay nodes are investigated in detail in this work. Moreover, an emergency alert service using short message service (SMS), based on the detection of abnormal variation of HR, is also used in the RG to further enhance the healthcare service quality. A prototype of this system has been developed and implemented. Finally, the experimental results are presented to verify the feasibility of the proposed system.     

一种基于概率校正和集成学习的肠癌肝转移预测模型

提出一种基于概率校正和集成学习的机器学习模型,用来预测患者肠癌肝转移的概率。首先将AdaBoost和Class-bal-anced SVM的概率结果进行校正,再将其结果和Logistic回归的预测结果进行集成,获得最终的预测结果。预测模型在复旦大学附属肿瘤医院的肠癌患者数据集上与其他算法如AdaBoost、Class-balanced SVM、Logistic回归算法进行了比较,结果显示该模型具有更好的AUC性能,更适合于医生的临床辅助诊断。模型的AUC性能在UCI数据集上进一步得到了验证。     

PROTOTYPICAL CASES FOR RETRIEVAL, REUSE, AND KNOWLEDGE MAINTENANCE IN BIOMEDICAL CASE-BASED REASONING

Representing biomedical knowledge is an essential task in biomedical informatics intelligent systems. Case-based reasoning (CBR) holds the promise to represent contextual knowledge in a way that was not possible before with traditional knowledge-based methods. One main issue in biomedical CBR is dealing with the rate of generation of new knowledge in biomedical fields, which often makes the content of a case base partially obsolete. This article proposes to make use of the concept of prototypical case to ensure that a CBR system would keep update with current research advances in the biomedical field. Prototypical cases have served various purposes in biomedical CBR systems, among which to organize and structure the memory, to guide the retrieval as well as the reuse of cases, and to serve as bootstrapping a CBR system memory when real cases are not available in sufficient quantity and/or quality. This paper emphasizes the different roles prototypical cases can play in CBR systems, and presents knowledge maintenance as a very important novel role for these prototypical cases.     

alt.metadata.health: Ontological Context for Data Use and Integration

Increasingly powerful computers and increased emphasis on evidence based decision making are creating a demand for merging and integrating data from different sources into a single data set. The demand for data is outstripping our ability to ensure data integrity, and sometimes analysis is performed on data that are not appropriate for the purposes they are used for. Here we describe problems that arise when data from different sources are merged, and we suggest that one way to add context to data so that users can make informed decisions about their ontological context is through ontology-based metadata. Examples of the problem are taken from health data with emphasis on difficulties in standardizing Emergency Room wait times. We describe eight fields that can be used to capture contextual metadata. These fields are captured using ethnographic methods from users and database stewards who frequently understand precisely how context and institutional usage have shaped interpretation of semantic fields. We argue that attaching a portable archive of ontological context to travel with data—based on information from users and developers—is a means of ensuring that data are integrated and compared in multiple contexts with greater integrity and more robust results.

基于格结构的概念代数研究

近年来,概念格作为一种有效的概念分析、表示与应用模型,被越来越多的领域所应用。概念代数是在概念 格理论基础上提出的一种新的代数系统。目前,概念代数系统还只是雏形,很多方面的内容还需要扩展与进一步的研 究。基于格结构的概念代数研究分别对Nilsson概念代数、Wille概念代数和认知信息学中的概念代数的基本概念与 内容进行了介绍,对各方法进行了分析与比较,并证明Nilsson概念代数是一种广义概念代数,为进一步的应用与研 究提供支持。     

Ontology-driven document enrichment: principles, tools and applications

In this paper, we present an approach to document enrichment, which consists of developing and integrating formal knowledge models with archives of documents, to provide intelligent knowledge retrieval and (possibly) additional knowledge-intensive services, beyond what is currently available using “standard” information retrieval and search facilities. Our approach is ontology-driven, in the sense that the construction of the knowledge model is carried out in a top-down fashion, by populating a given ontology, rather than in a bottom-up fashion, by annotating a particular document. In this paper, we give an overview of the approach and we examine the various types of issues (e.g. modelling, organizational and user interface issues) which need to be tackled to effectively deploy our approach in the workplace. In addition, we also discuss a number of technologies we have developed to support ontology-driven document enrichment and we illustrate our ideas in the domains of electronic news publishing, scholarly discourse and medical guidelines.     

Collaboration processes,outcomes, challenges and enablers of distributed clinical communities of practice

Modern healthcare's need for knowledge sharing and bridging the research–practice gap requires new forms of collaboration, in which clinicians of varying clinical and research expertise work together over geographical and organisational borders. To support such distributed communities of practice (CoPs), an understanding of their collaboration processes, outcomes, challenges and enablers is needed. The article examines these issues through a case study of a long-running CoP, the Swedish Oral Medicine Network (SOMNet). SOMNet's main form of collaboration is monthly telephone conference meetings centred on case consultations. Cases are submitted by the clinicians via a Web-based system. The methods used were interviews, observations, and a questionnaire. The work adds to previous research by studying a distributed CoP explicitly focused on supporting the transfer of scientific results from researchers to practitioners. We found that the regular meetings give a rhythm to the community. The centrality of cases means an immediate benefit for the submitter while the community is provided an authentic context for learning. SOMNet yields opportunities for help and learning for diverse expertise levels; the type of benefits is affected by the participant's degree of oral medicine knowledge and collaboration involvement. There are challenges in accommodating varying levels of expertise and encouraging those less experienced to participate. Enablers of the collaboration include the participation of experts, meeting facilitators and well-adapted ITs.