An effective framework for finding similar cases of dengue from audio and text data using domain thesaurus and case base reasoning

Dengue, also known as break-bone fever, is a tropical disease transmitted by mosquitoes. If the similarity between dengue infected users can be identified, it can help government’s health agencies to manage the outbreak more effectively. To find similarity between cases affected by Dengue, user’s personal and health information are the two fundamental requirements. Identification of similar symptoms, causes, effects, predictions and treatment procedures, is important. In this paper, an effective framework is proposed which finds similar patients suffering from dengue using keyword aware domain thesaurus and case base reasoning method. This paper focuses on the use of ontology dependent domain thesaurus technique to extract relevant keywords and then build cases with the help of case base reasoning method. Similar cases can be shared with users, nearby hospitals and health organizations to manage the problem more adequately. Two million case bases were generated to test the proposed similarity method. Experimental evaluations of proposed framework resulted in high accuracy and low error rate for finding similar cases of dengue as compared to UPCC and IPCC algorithms. The framework developed in this paper is for dengue but can easily be extended to other domains also.     

An Alternative Approach to Poverty Analysis

A model of the household in which production and consumption activities are not separable is developed in order to provide micro-economic foundations for an alternative to the standard approach to poverty analysis. The alternative suggests that socio-economic groups and their respective livelihoods should be the basic building blocks for analysing poverty within a general equilibrium framework.     

From the kinetic theory of active particles to the modeling of social behaviors and politics

This paper deals with the modeling of complex social systems by methods of the mathematical kinetic theory for active particles. Specifically, a recent model by the last two authors is analyzed from the social sciences point of view. The model shows, despite its simplicity, some interesting features. In particular, this paper investigates the ability of the model to describe how a social politics and the disposable overall wealth may have a relevant influence towards the trend of the wealth distribution. The paper also outlines various research perspectives.     

从欧盟社会融入政策视角看我国农民工的城市融入问题

在全球化进程加剧的背景下,如何实现弱势群体的社会融入,已成为国际社会政策理论与实践研究的重大议题。本文阐释了欧盟国家关于社会排斥的基本概念及原因分析,社会融入的基本概念与理论模式、行动机制以及评估体系等相关研究,在此基础上,解析了我国农民工社会融入的基本条件、实践策略与理论模式,进而提出将农民工问题研究置于当代国际社会融入政策研究的背景下,将研究对象从农民工转变为乡—城移民,研究方法中加强社会融入的定量研究,通过政策行动与社区工作,发展并落实农民工社会融入政策体系。     

美国城市设计运作激励及对中国的启示

美国城市设计运作激励,是应对城市建设领域中资源私有制与治理公共性之间的矛盾,协调私人开发与社会整体发展方向之间偏差的城市设计操作方法.文章对美国这一方法的概念、内容及成因作出归纳与分析,并在结合我国国情的基础上,对运作激励在我国的发展作出思考.     

Comments on: “Structural vs. atheoretic approaches to econometrics” by Michael Keane

My comments on the keynote paper by Michael Keane.     

建设工程项目实施阶段后评价体系与方法探讨

建设工程项目实施阶段后评价的目的是为提高项目管理水平和对项目管理者进行客观公正的考核提供依据。项目实施阶段后评价的体系可按项目管理的内容和过程确定,应采用过程评价与效果评价相结合,分析评价与对比评价相结合,定性评价与定量评价相结合,业主方评价与承包方评价相结合,评价与建议相结合的方法。     

An Extreme Value Approach to Test the Effect of Price Limits on Volatility

Many stock exchanges around the world enforcing daily price limits on the amount asset prices can change to prevent the market from overreacting and to reduce volatility. Price limits are artificial boundaries set by market regulators who restrict price changes of a stock to a pre-specified range during a trading day or a single trading session. The primary aim of price limit rules is to stabilize the markets during panic trading, to moderate vitality by repressing excessive speculation, and to allow stocks to be traded at prices close to their fair value. However, their impact on the market is a somewhat unresolved issue （Harris, 1998）. Using a methodology of comparing volatility based on the extreme value technique, the authors empirically investigate the impact of price limits on the volatility of the Stock Exchange of Thailand. The empirical results support price limits advocates, suggesting that price limits rules moderate stock price volatility.     

The effects of supplier-to-buyer identification on operational performance—An empirical investigation of inter-organizational identification in automotive relationships

Over the past decade conceptual and empirical research in operations management has embraced the idea that collaborative supplier-buyer relationships are a source of competitive advantage for manufacturing firms. Anecdotal evidence from the Japanese and U.S. automotive industry and emerging research suggests that inter-organizational identification of suppliers with their buyers, termed supplier-to-buyer identification, is an unexplored factor of relational advantage. This study presents a model and empirical test that supplier-to-buyer identification fosters superior operational performance by enhancing trust, supplier relation-specific investments, and information exchange. Through a survey of 346 automotive supplier-buyer relationships, the findings show that supplier-to-buyer identification directly impacts supplier relationship-specific investments and information exchange, although most of the latter effect is mediated by trust. The findings also indicate that supplier relation-specific investments and information exchange play different but complementary roles in influencing operational performance. The results suggest new directions for supplier-buyer relationship research in operations management and important managerial implications.     

Forecasting national activity using lots of international predictors: An application to New Zealand

We assess the marginal predictive content of a large international dataset for forecasting GDP in New Zealand, an archetypal small open economy. We apply “data-rich” factor and shrinkage methods to efficiently handle hundreds of predictor series from many countries. The methods covered are principal components, targeted predictors, weighted principal components, partial least squares, elastic net and ridge regression. We find that exploiting a large international dataset can improve forecasts relative to data-rich approaches based on a large national dataset only, and also relative to more traditional approaches based on small datasets. This is in spite of New Zealand’s business and consumer confidence and expectations data capturing a substantial proportion of the predictive information in the international data. The largest forecasting accuracy gains from including international predictors are at longer forecast horizons. The forecasting performance achievable with the data-rich methods differs widely, with shrinkage methods and partial least squares performing best in handling the international data.