238 research outputs found

    A fuzzy clustering model of information appliance

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    The purpose of this study is to propose a fuzzy clustering model of information appliances (IA). There are two sub-models, saying information appliance cluster engine (IACE) and user interactive model (UIM), in this model. The function of IACE is to process the users’ recognitions of IA devices. The UIM is the interface of IACE with the IA intelligent agents (IAIA). Via the proposed model, the IAIA can be more humanistic, and convenient for user. Also, via the implementation of this model, we can have the analysis of the optimal effectiveness

    Knowledge Discovery Model in Chinese Industrial News

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    With prevalence of Internet, users can easily retrieve the information what they want from Internet. Information explosion shows that efficient information summarization is aspired to all users. Therefore, an efficient knowledge management methodology becomes very important. Some technologies, such as text mining, for acquiring knowledge from huge amount of electronic documents are recognized as important technology in this field. This work focuses on text-mining applications on Chinese industrial news and knowledge discovery. We use information extract method to extract news into companies, event keyword, time, location, and person categories based on the characteristics of news. The set of five extracted categories is called information template. The templates are summarized by rule induction. We can discover unexpected knowledge from these summarized rules. We built an integrated industrial news text-mining model by using induction rule learner. This model is suitable to manipulate rules in bag-of-word form. Furthermore, we proposed interestingness to measure interesting strength of rules. The users can analyze the discovered rules based this measure. These are helpful to discover unexpected knowledge. It is meaningful to commercial activities if we can discover valuable rules. Besides industrial news application, we believe this model is suitable for knowledge discovery application in other fields

    Experimental analysis of fuzzy economic optimization

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    Group Decision Making for a Fuzzy Software Quality Assessment Model to Evaluate User Satisfaction

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    Information techniques have brought us tremendous benefit, whereas people are increasingly depended on lots of information systems. Therefore, how to establish an assessment model to choose a better software quality suitable for end-users is an important issue. This study is to present an algorithm of the group decision makers with crisp or fuzzy weights to tackle the integrated software quality for evaluating user satisfaction using fuzzy set theory, where the grades of quality and the grade of importance of quality items are assessed by linguistic values represented by triangular fuzzy numbers. The proposed algorithm is more flexible and useful than the ones that have presented before, since the weights against decision makers are considered

    Comorbidity and dementia: A nationwide survey in Taiwan

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    Background Comorbid medical diseases are highly prevalent in the geriatric population, imposing hardship on healthcare services for demented individuals. Dementia also complicates clinical care for other co-existing medical conditions. This study investigated the comorbidities associated with dementia in the elderly population aged 65 years and over in Taiwan. Methods We conducted a nationwide, population-based, cross-sectional survey; participants were selected by computerized random sampling from all 19 Taiwan counties between December 2011 and March 2013. After exclusion of incomplete or erroneous data, 8,456 subjects were enrolled. Of them, 6,183 were cognitively normal (control group), 1,576 had mild cognitive impairment (MCI), and 697 had dementia. We collected information about types of comorbidities (i.e., vascular risk factors, lung diseases, liver diseases, gastrointestinal diseases, and cancers), Charlson comorbidity index score, and demographic variables to compare subjects with normal cognition, MCI, and dementia. Results Regardless of the cognitive condition, over 60% of the individuals in each group had at least one comorbid disease. The proportion of subjects possessing at least three comorbidities was higher in those with cognitive impairment (MCI 20.9%, dementia 27.3%) than in control group (15%). Hypertension and diabetes mellitus were the most common comorbidities. The mean number of comorbidities and Charlson comorbidity index score were greater in MCI and dementia groups than in control group. Logistic regression demonstrated that the comorbidities significantly associated with MCI and dementia were cerebrovascular disease (OR 3.35, CI 2.62–4.28), cirrhosis (OR 3.29, CI 1.29–8.41), asthma (OR 1.56, CI 1.07–2.27), and diabetes mellitus (OR 1.24, CI 1.07–1.44). Conclusion Multiple medical comorbid diseases are common in older adults, especially in those with cognitive impairment. Cerebrovascular disease, cirrhosis, asthma, and diabetes mellitus are important contributors to cognitive deterioration in the elderly. Efforts to lower cumulative medical burden in the geriatric population may benefit cognitive function

    ABL Genomic Editing Sufficiently Abolishes Oncogenesis of Human Chronic Myeloid Leukemia Cells In Vitro and In Vivo

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    Chronic myelogenous leukemia (CML) is the most common type of leukemia in adults, and more than 90% of CML patients harbor the abnormal Philadelphia chromosome (Ph) that encodes the BCR-ABL oncoprotein. Although the ABL kinase inhibitor (imatinib) has proven to be very effective in achieving high remission rates and improving prognosis, up to 33% of CML patients still cannot achieve an optimal response. Here, we used CRISPR/Cas9 to specifically target the BCR-ABL junction region in K562 cells, resulting in the inhibition of cancer cell growth and oncogenesis. Due to the variety of BCR-ABL junctions in CML patients, we utilized gene editing of the human ABL gene for clinical applications. Using the ABL gene-edited virus in K562 cells, we detected 41.2% indels in ABL sgRNA_2-infected cells. The ABL-edited cells reveled significant suppression of BCR-ABL protein expression and downstream signals, inhibiting cell growth and increasing cell apoptosis. Next, we introduced the ABL gene-edited virus into a systemic K562 leukemia xenograft mouse model, and bioluminescence imaging of the mice showed a significant reduction in the leukemia cell population in ABL-targeted mice, compared to the scramble sgRNA virus-injected mice. In CML cells from clinical samples, infection with the ABL gene-edited virus resulted in more than 30.9% indels and significant cancer cell death. Notably, no off-target effects or bone marrow cell suppression was found using the ABL gene-edited virus, ensuring both user safety and treatment efficacy. This study demonstrated the critical role of the ABL gene in maintaining CML cell survival and tumorigenicity in vitro and in vivo. ABL gene editing-based therapy might provide a potential strategy for imatinib-insensitive or resistant CML patient
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