Objective: This paper reviewed and examined the quality of all the qualitative evaluation studies indexed by two key search terms of “qualitative” and “evaluation” in the Social Work Abstracts database from 1990 t...Objective: This paper reviewed and examined the quality of all the qualitative evaluation studies indexed by two key search terms of “qualitative” and “evaluation” in the Social Work Abstracts database from 1990 to 2003 against a number of criteria typically adopted in the field of qualitative research. The review led to a dissatisfactory finding of the low quality of many qualitative evaluation studies due to their insensitivity to the following issues: philosophical basis of the study, auditability (detailed documentation of the participants and data collecting procedure), biases (acknowledgement of biases and preoccupation, and steps to deal with them), credibility or trustworthiness (triangulation, peer checking and participant verification of the findings), consistency (reliability consciousness and audit trails), and critical interpretation of the data (alternative explanations, disconfirming evidence, and limitations of the study). It was recommended that researchers be cautious when utilizing findings from the published qualitative evaluation studies; that social workers be sensitive to the issue of quality when conducting qualitative evaluation studies; that researchers be critical when judging the qualitative evaluation studies in social work; that researchers develop a clear set of guidelines for qualitative studies; that social work training institutes design qualified qualitative research courses; that a database of social work in China be established; that researchers be engaged in more qualitative studies that demonstrate high quality; that myths in qualitative research be debunked; and that adequate training for social workers on qualitative evaluation studies be provided.展开更多
Based on the intelligent decision support system, a new method was presented to defense the catastrophic infectious disease such as SARS, Bird Flu, etc.. By using All Set theory, the decision support system (DSS) mode...Based on the intelligent decision support system, a new method was presented to defense the catastrophic infectious disease such as SARS, Bird Flu, etc.. By using All Set theory, the decision support system (DSS) model can be built to analyze the noise information and forecast the trend of the catastrophe then to give the method or policy to defend the disease. The model system is composed of four subsystems: the noise analysis subsystem, forecast and simulation subsystem, diagnosis subsystem and second recovery subsystem. They are discussed briefly in this paper.This model can be used not only for SARS but also for other paroxysmal accidences.展开更多
To overcome the failure in eliminating suspicious patterns or association rules existing in traditional association rules mining, we propose a novel method to mine item-item and between-set correlated association rule...To overcome the failure in eliminating suspicious patterns or association rules existing in traditional association rules mining, we propose a novel method to mine item-item and between-set correlated association rules. First, we present three measurements: the association, correlation, and item-set correlation measurements. In the association measurement, the all-confidence measure is used to filter suspicious cross-support patterns, while the all-item-confidence measure is applied in the correlation measurement to eliminate spurious association rules that contain negatively correlated items. Then, we define the item-set correlation measurement and show its corresponding properties. By using this measurement, spurious association rules in which the antecedent and consequent item-sets are negatively correlated can be eliminated. Finally, we propose item-item and between-set correlated association rules and two mining algorithms, I&ISCoMine_AP and I&ISCoMine_CT. Experimental results with synthetic and real retail datasets show that the proposed method is effective and valid.展开更多
文摘Objective: This paper reviewed and examined the quality of all the qualitative evaluation studies indexed by two key search terms of “qualitative” and “evaluation” in the Social Work Abstracts database from 1990 to 2003 against a number of criteria typically adopted in the field of qualitative research. The review led to a dissatisfactory finding of the low quality of many qualitative evaluation studies due to their insensitivity to the following issues: philosophical basis of the study, auditability (detailed documentation of the participants and data collecting procedure), biases (acknowledgement of biases and preoccupation, and steps to deal with them), credibility or trustworthiness (triangulation, peer checking and participant verification of the findings), consistency (reliability consciousness and audit trails), and critical interpretation of the data (alternative explanations, disconfirming evidence, and limitations of the study). It was recommended that researchers be cautious when utilizing findings from the published qualitative evaluation studies; that social workers be sensitive to the issue of quality when conducting qualitative evaluation studies; that researchers be critical when judging the qualitative evaluation studies in social work; that researchers develop a clear set of guidelines for qualitative studies; that social work training institutes design qualified qualitative research courses; that a database of social work in China be established; that researchers be engaged in more qualitative studies that demonstrate high quality; that myths in qualitative research be debunked; and that adequate training for social workers on qualitative evaluation studies be provided.
文摘Based on the intelligent decision support system, a new method was presented to defense the catastrophic infectious disease such as SARS, Bird Flu, etc.. By using All Set theory, the decision support system (DSS) model can be built to analyze the noise information and forecast the trend of the catastrophe then to give the method or policy to defend the disease. The model system is composed of four subsystems: the noise analysis subsystem, forecast and simulation subsystem, diagnosis subsystem and second recovery subsystem. They are discussed briefly in this paper.This model can be used not only for SARS but also for other paroxysmal accidences.
基金Project supported by the National Natural Science Foundation of China (Nos. 10876036 and 70871111)the Ningbo Natural Science Foundation, China (No. 2010A610113)
文摘To overcome the failure in eliminating suspicious patterns or association rules existing in traditional association rules mining, we propose a novel method to mine item-item and between-set correlated association rules. First, we present three measurements: the association, correlation, and item-set correlation measurements. In the association measurement, the all-confidence measure is used to filter suspicious cross-support patterns, while the all-item-confidence measure is applied in the correlation measurement to eliminate spurious association rules that contain negatively correlated items. Then, we define the item-set correlation measurement and show its corresponding properties. By using this measurement, spurious association rules in which the antecedent and consequent item-sets are negatively correlated can be eliminated. Finally, we propose item-item and between-set correlated association rules and two mining algorithms, I&ISCoMine_AP and I&ISCoMine_CT. Experimental results with synthetic and real retail datasets show that the proposed method is effective and valid.
