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设计更好的陷阱,还是理解人类境况:反思社会科学中的大数据现象
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作者 林之平〔美〕 刘建义(译) 《广州公共管理评论》 2016年第2期3-18,346,347,共18页
近年来“大数据”崛起,成为一种改变商业、科学和社会的“破坏性力量”。而对大数据及其价值,人们既抱有极大的热情和期盼,也存在质疑。在笔者看来,这种质疑源于对大数据利用目的的根本性混淆:是更好的科学,还是更好的工程?质疑者对摈... 近年来“大数据”崛起,成为一种改变商业、科学和社会的“破坏性力量”。而对大数据及其价值,人们既抱有极大的热情和期盼,也存在质疑。在笔者看来,这种质疑源于对大数据利用目的的根本性混淆:是更好的科学,还是更好的工程?质疑者对摈弃传统数据采集、分析方法,混淆相关、因果关系,建构单一解释力模型等做法提出了批评。然而,基于发展社会科学的考量,这些观点又有存在的价值。但笔者仍然认为,如果要利用大数据革新计算方法以改善效率,所设计的测量指标就应该是客观、公正的。那些听起来科学、有用的说法不一定能够优化工程工艺。厘清了科学与工程之间的异同,也就能够明白并解决围绕大数据产生的诸种论争,从而有助于设计测量贡献率的指标。 展开更多
关键词 大数据 计算社会科学 机器学习 数据挖掘 日志分析
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面向手持设备的电容传感器应用技巧
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作者 jimmy lin Albert Lee 《集成电路应用》 2010年第9期34-35,共2页
苹果iPhone让人们认识到了透明电容传感器的妙用,事实上,不透明的电容传感技术也有很大的发挥空间。在用电容传感器进行产品设计时也面临一些技术挑战,需要在开发初期加以解决。
关键词 电容传感器 传感器应用 手持设备 IPHONE 传感技术 开发初期 不透明 计时
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Characterization of Binding Sites of Eukaryotic Transcription Factors
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作者 Jiang Qian jimmy lin Donald J. Zack 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2006年第2期67-79,共13页
To explore the nature of eukaryotic transcription factor (TF) binding sites and determine how they differ from surrounding DNA sequences, we examined four features associated with DNA binding sites: G+C content, p... To explore the nature of eukaryotic transcription factor (TF) binding sites and determine how they differ from surrounding DNA sequences, we examined four features associated with DNA binding sites: G+C content, pattern complexity, palindromic structure, and Markov sequence ordering. Our analysis of the regulatory motifs obtained from the TRANSFAC databases using yeast intergenic sequences as background, revealed that these four features show variable enrichment in motif sequences. For example, motif sequences were more likely to have palindromic structure than were background sequences. In addition, these features were tightly localized to the regulatory motifs, indicating that they are a property of the motif sequences themselves and are not shared by the general promoter "environment" in which the regulatory motifs reside. By breaking down the motif sequences according to the TF classes to which they bind, more specific associations were identified. Finally, we found that some correlations, such as G+C content enrichment, were species-specific, while others, such as complexity enrichment, were universal across the species examined. The quantitative analysis provided here should increase our understanding of protein-DNA interactions and also help facilitate the discovery of regulatory motifs through bioinformatics. 展开更多
关键词 transcription factor PROMOTER gene regulation BIOINFORMATICS
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