岷江上游农林复合景观管理优先度评价

结合前期研究共辨识出10项景观管理影响因子,依据其作用的性质和特点,将其分为4大类参数,通过NetWeaver模型构建了基于模糊逻辑的优先度评价知识库,在EMDS(Ecosystem Management Decision Support system)和ARCGIS9.x环境下,对4类景观管理影响因子的优先度进行了评价。结果显示:1)可行性因子综合优先度评价结果为除ws3、ws6、ws8和ws9 4个子流域的优先度为低外,其余6个子流域优先度居于中等优先水平;2)有效性因子优先度综合评价结果,ws1、ws9和ws10 3个子流域优先度为强,ws8优先度最低,其余子流域为中等优先;3)景观综合结果除ws1~ws33个子流域属于强外,其余子流域优先度为低;4)所有影响因子的综合结果为ws8子流域优先度最低,其余部分优先度居于中等。

旱地作物需水量预报决策辅助系统

旱地作物需水量预报决策辅助系统是利用人工智能技术 ,在 Penman公式的基础上结合现有西北旱区的农学知识、模型以及经验进行系统集成而建立的智能化计算机软件系统 ,该系统是西北地区节水农业专家系统的一个子系统。在生产实践中可为陕西关中地区的冬小麦、夏玉米的栽培作出灌溉方案的决策咨询。

数据驱动的多Agent装备器材保障决策支持系统

为提高复杂网络环境和任务需求下器材保障的智能化水平,提出了一个数据驱动的多Agent器材保障决策支持系统DSS(decision support system),系统中的数据、模型以及Agent可分布在不同的网络节点上,高层Agent可由粒度更小的子Agent或Agent部件组合而成;系统中的各类智能Agent相互协作,共同完成异构数据集成、多维数据集构造、器材保障模型挖掘、复杂规划问题求解,以及保障方案自动生成等任务,从而有效降低了系统开发的难度,提高了Agent协作的灵活性。研究结果表明,该系统架构能够显著提升器材保障决策方案的质量和效率。

宏观经济的决策支持系统

本文介绍了一个用于宏观经济决策的决策支持系统的内容和特点。论述了处理经济系统时建立知识库系统的必要性。着重介绍了用于宏观经济的知识库系统以及建立在这个系统基础之上的整个决策支持系统的结构。最后简述了这个系统的发展方向。

基于面向对象方法的决策支持系统

决策支持系统(DSS-Decision Support Systems)作为信息系统的高级形式得到了广泛重视,但同时也面临着很多问题。本文仔细剖析了这些问题,讨论以面向对象OO(Object Oriented)的方法进行DSS设计,最后提出了一个基于OO方法的DSS结构。

交通战备保障方案决策系统的研究设计

阐述了一种交通战备保障方案实施决策支持系统，介绍了系统的数据库系统、模型库系统的设计.该系统主要针对突发事件，为交通战备保障方案的实施提供快速、有效的决策支持。

面向决策支持的综合地质信息系统功能开发和GIS应用

Synthetic Geology Information System(SGIS) is a part of the theory of Engineering Geomechanics-mate-Synthetics(EGMS), is also a development of its technical methodology. SGIS includes ways of geology engineering investigation, design, and construction. Although SGIS has an integrate theory frame, and some parts of it have gained great progress, the completion of SGIS is a continuous and accumulative process. This paper analyses the ways and principle of building knowledge database and model database, summarizes the experts' experience on exploration methods selection and the characters of exploration models, combining with the application of Decision Support System(DSS) in Decision support of Synthetic Exploration Methods for Railway engineering Geology. By the analysis of hierarchy structure of the model database, the effects of geology engineering factors on the selection of exploration methods are expressed. By the usage of fuzzy patterns recognize, hierarchy structure analysis, fuzzy collection closement analysis etc, the software of DSS for engineering design and construction are developed. At same time, by the development of Monitoring Data Analysis System and experiment data management system of Hydro-power project, this paper discussed the data management of science experiment of Hydro-power project by the usage of synthetic database and the usage of Geography Information System(GIS) and DSS technics. The technic of visual operation of data process and project monitoring system are presented. The intelligence algorithm of self-adoption is carried out to improve the data process and analysis of monitoring. Items of the project theoretical analysis and data process are designed in detail. All the theory and technical methods presented in this paper are one part of SGIS, in which the application of DSS and GIS, is an important step of the progress and completion of SGIS.

Probabilistic abductive computation of evidence collection strategies in crime investigation

J. Keppens, Q. Shen and B. Schafer. Probabilistic abductive computation of evidence collection strategies in crime investigation. Proceedings of the 10th International Conference on Artificial Intelligence and Law, pages 215-225.

Aplicação de MonetDB na avaliação de desempenho de bases de dados verticais

Dissertação apresentada à Universidade Fernando Pessoa como partes dos requisitos para a obtenção do grau de Mestre em Engenharia Informática, ramo de Sistemas de Informação e Multimédia

Context-aware real-time assistant architecture for pervasive healthcare

The aging population in many countries brings into focus rising healthcare costs and pressure on conventional healthcare services. Pervasive healthcare has emerged as a viable solution capable of providing a technology-driven approach to alleviate such problems by allowing healthcare to move from the hospital-centred care to self-care, mobile care, and at-home care. The state-of-the-art studies in this field, however, lack a systematic approach for providing comprehensive pervasive healthcare solutions from data collection to data interpretation and from data analysis to data delivery. In this thesis we introduce a Context-aware Real-time Assistant (CARA) architecture that integrates novel approaches with state-of-the-art technology solutions to provide a full-scale pervasive healthcare solution with the emphasis on context awareness to help maintaining the well-being of elderly people. CARA collects information about and around the individual in a home environment, and enables accurately recognition and continuously monitoring activities of daily living. It employs an innovative reasoning engine to provide accurate real-time interpretation of the context and current situation assessment. Being mindful of the use of the system for sensitive personal applications, CARA includes several mechanisms to make the sophisticated intelligent components as transparent and accountable as possible, it also includes a novel cloud-based component for more effective data analysis. To deliver the automated real-time services, CARA supports interactive video and medical sensor based remote consultation. Our proposal has been validated in three application domains that are rich in pervasive contexts and real-time scenarios: (i) Mobile-based Activity Recognition, (ii) Intelligent Healthcare Decision Support Systems and (iii) Home-based Remote Monitoring Systems.

The application of computer modelling to develop a methodology for ‘existing building’ upgrades to move towards carbon-neutral buildings

The retrofitting of existing buildings for decreased energy usage, through increased energy efficiency and for minimum carbon dioxide emissions throughout their remaining lifetime is a major area of research. This research area requires development to provide building professionals with more efficient building retrofit solution determination tools. The overarching objective of this research is to develop a tool for this purpose through the implementation of a prescribed methodology. This has been achieved in three distinct steps. Firstly, the concept of using the degree-days modelling method as an adequate means of basing retrofit decision upon was analysed and the results illustrated that the concept had merit. Secondly, the concept of combining the degree-days modelling method and the Genetic Algorithms optimisation method is investigated as a method of determining optimal thermal energy retrofit solutions. Thirdly, the combination of the degree-days modelling method and the Genetic Algorithms optimisation method were packaged into a building retrofit decision-support tool and named BRaSS (Building Retrofit Support Software). The results demonstrate clearly that, fundamental building information, simplified occupancy profiles and weather data used in a static simulation modelling method is a sufficient and adequate means to base retrofitting decisions upon. The results also show that basing retrofit decisions upon energy analysis results are the best means to guide a retrofit project and also to achieve results which are optimum for a particular building. The results also indicate that the building retrofit decision-support tool, BRaSS, is an effective method to determine optimum thermal energy retrofit solutions.

Knowledge-based IMRT treatment planning for prostate cancer.

PURPOSE: To demonstrate the feasibility of using a knowledge base of prior treatment plans to generate new prostate intensity modulated radiation therapy (IMRT) plans. Each new case would be matched against others in the knowledge base. Once the best match is identified, that clinically approved plan is used to generate the new plan. METHODS: A database of 100 prostate IMRT treatment plans was assembled into an information-theoretic system. An algorithm based on mutual information was implemented to identify similar patient cases by matching 2D beam's eye view projections of contours. Ten randomly selected query cases were each matched with the most similar case from the database of prior clinically approved plans. Treatment parameters from the matched case were used to develop new treatment plans. A comparison of the differences in the dose-volume histograms between the new and the original treatment plans were analyzed. RESULTS: On average, the new knowledge-based plan is capable of achieving very comparable planning target volume coverage as the original plan, to within 2% as evaluated for D98, D95, and D1. Similarly, the dose to the rectum and dose to the bladder are also comparable to the original plan. For the rectum, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are 1.8% +/- 8.5%, -2.5% +/- 13.9%, and -13.9% +/- 23.6%, respectively. For the bladder, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are -5.9% +/- 10.8%, -12.2% +/- 14.6%, and -24.9% +/- 21.2%, respectively. A negative percentage difference indicates that the new plan has greater dose sparing as compared to the original plan. CONCLUSIONS: The authors demonstrate a knowledge-based approach of using prior clinically approved treatment plans to generate clinically acceptable treatment plans of high quality. This semiautomated approach has the potential to improve the efficiency of the treatment planning process while ensuring that high quality plans are developed.

Protocol for the "Implementation, adoption, and utility of family history in diverse care settings" study.

BACKGROUND: Risk assessment with a thorough family health history is recommended by numerous organizations and is now a required component of the annual physical for Medicare beneficiaries under the Affordable Care Act. However, there are several barriers to incorporating robust risk assessments into routine care. MeTree, a web-based patient-facing health risk assessment tool, was developed with the aim of overcoming these barriers. In order to better understand what factors will be instrumental for broader adoption of risk assessment programs like MeTree in clinical settings, we obtained funding to perform a type III hybrid implementation-effectiveness study in primary care clinics at five diverse healthcare systems. Here, we describe the study's protocol. METHODS/DESIGN: MeTree collects personal medical information and a three-generation family health history from patients on 98 conditions. Using algorithms built entirely from current clinical guidelines, it provides clinical decision support to providers and patients on 30 conditions. All adult patients with an upcoming well-visit appointment at one of the 20 intervention clinics are eligible to participate. Patient-oriented risk reports are provided in real time. Provider-oriented risk reports are uploaded to the electronic medical record for review at the time of the appointment. Implementation outcomes are enrollment rate of clinics, providers, and patients (enrolled vs approached) and their representativeness compared to the underlying population. Primary effectiveness outcomes are the percent of participants newly identified as being at increased risk for one of the clinical decision support conditions and the percent with appropriate risk-based screening. Secondary outcomes include percent change in those meeting goals for a healthy lifestyle (diet, exercise, and smoking). Outcomes are measured through electronic medical record data abstraction, patient surveys, and surveys/qualitative interviews of clinical staff. DISCUSSION: This study evaluates factors that are critical to successful implementation of a web-based risk assessment tool into routine clinical care in a variety of healthcare settings. The result will identify resource needs and potential barriers and solutions to implementation in each setting as well as an understanding potential effectiveness. TRIAL REGISTRATION: NCT01956773.

The IGNITE network: a model for genomic medicine implementation and research.

BACKGROUND: Patients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility. METHODS: To address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.ignite-genomics.org ) Network, comprised of six projects and a coordinating center, was established in 2013 to support the development, investigation and dissemination of genomic medicine practice models that seamlessly integrate genomic data into the electronic health record and that deploy tools for point of care decision making. IGNITE site projects are aligned in their purpose of testing these models, but individual projects vary in scope and design, including exploring genetic markers for disease risk prediction and prevention, developing tools for using family history data, incorporating pharmacogenomic data into clinical care, refining disease diagnosis using sequence-based mutation discovery, and creating novel educational approaches. RESULTS: This paper describes the IGNITE Network and member projects, including network structure, collaborative initiatives, clinical decision support strategies, methods for return of genomic test results, and educational initiatives for patients and providers. Clinical and outcomes data from individual sites and network-wide projects are anticipated to begin being published over the next few years. CONCLUSIONS: The IGNITE Network is an innovative series of projects and pilot demonstrations aiming to enhance translation of validated actionable genomic information into clinical settings and develop and use measures of outcome in response to genome-based clinical interventions using a pragmatic framework to provide early data and proofs of concept on the utility of these interventions. Through these efforts and collaboration with other stakeholders, IGNITE is poised to have a significant impact on the acceleration of genomic information into medical practice.

Las infraestructuras de recarga y el despegue del vehículo eléctrico.

Este trabajo revisa la evolución y estado actual de la automoción eléctrica; analiza las ventajas ambientales, de eficiencia energética y de costes del motor eléctrico frente al de combustión interna; y presenta como limitaciones para el uso del vehículo eléctrico, el desarrollo actual de las baterías recargables y la lenta implantación de electrolineras. Con el objetivo de contribuir al desarrollo de una actividad económica respetuosa con el medio ambiente y basada en nuevas tecnologías, se proyecta, a partir de experiencias previas, una instalación de puntos de recarga para una ciudad de 50.000 habitantes con un parque de 100 vehículos eléctricos que dispone de dos plazas de recarga rápida (poste trifásico 400V CA), siete plazas de recarga lenta (postes monofásicos 230V CA) y de 50 módulos fotovoltaicos que producen diariamente la energía equivalente a la recarga lenta de un vehículo en los meses fríos y de dos en los meses cálidos.