Browsing by Author "Huang, Chien-Hsun"

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A Novel Modified Particle Swarm Optimization for Forecasting Financial Time Series
(2009)
Chen, An-Pin
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Huang, Chien-Hsun
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Hsu, Yu-Chia
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
Time series has been widely applied in the real world, traditional methods can hardly solve the dynamic environment issue resulting from the assumption of stationary process Many traditional models and artificial intelligence technologies had been developed under this assumption, and adapted the dynamic environment based on the time-varying characteristic But these models still has drawback of dividing the time series Into training set and testing set when developing the models It means the time-varying characteristic of these two sets did not be considered, and it might cause spurious regression phenomenon and result in misleading the statistic analysis In order to forecast dynamic time series, a model which can consider the dynamic environment and conquer the out-of-sample problem is necessary Particle swarm optimization (PSO) has the characteristics of fast-convergence and avoiding local optimal, also has been widely used in the time series forecasting In this research, we proposed a modified PSO to consider the dynamic environment issue and use the advantage of PSO to forecast the dynamic financial time series
Gut microbiome changes in overweight male adults following bowel preparation
(2018-12-31)
Chen, Hui-Mei
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Chen, Chung-Chu
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Chen, Chien-Chi
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Wang, Shen-Chih
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Wang, Chun-Lin
BackgroundHuman gut microbiome has an essential role in human health and disease. Although the major dominant microbiota within individuals have been reported, the change of gut microbiome caused by external factors, such as antibiotic use and bowel cleansing, remains unclear. We conducted this study to investigate the change of gut microbiome in overweight male adults after bowel preparation, where none of the participants had been diagnosed with any systemic diseases.MethodsA total of 20 overweight, male Taiwanese adults were recruited, and all participants were omnivorous. The participants provided fecal samples and blood samples at three time points: prior to bowel preparation, 7days after colonoscopy, and 28days after colonoscopy. The microbiota composition in fecal samples was analyzed using 16S ribosome RNA gene amplicon sequencing.ResultsOur results demonstrated that the relative abundance of the most dominant bacteria hardly changed from prior to bowel preparation to 28days after colonoscopy. Using the ratio of Prevotella to the sum of Prevotella and Bacteroides in the fecal samples at baseline, the participants were separated into two groups. The fecal samples of the Type 1 group was Bacteroides-dominant, and that of the Type 2 group was Prevotella-dominant with a noticeable presence Bacteroides. Bulleidia appears more in the Type 1 fecal samples, while Akkermensia appears more in the Type 2 fecal samples. Of each type, the gut microbial diversity differed slightly among the three collection times. Additionally, the Type 2 fecal microbiota was temporarily susceptible to bowel cleansing. Predictive functional analysis of microbial community reveals that their activities for the mineral absorption metabolism and arachidonic acid metabolism differed significantly between the two types. Depending on their fecal type, the variance of triglycerides and C-reactive protein also differed between the two types of participants.ConclusionsDepending upon the fecal type, the microbial diversity and the predictive functional modules of microbial community differed significantly after bowel preparation. In addition, blood biochemical markers presented somewhat associated with fecal type. Therefore, our results might provide some insights as to how knowledge of the microbial community could be used to promote health through personalized clinical treatment.
High numerical-aperture microlens fabricated by focused ion beam milling
(2007-01-01)
Chiu, Yi
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Huang, Chien-Hsun
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Hsu, Ying-Chien
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電控工程研究所
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Institute of Electrical and Control Engineering
The focusing objective lens is a key component in the optical pick-up head. In this paper, focused ion beam milling is used to fabricate a NA 0.65 microlens in the silicon nitride film suspended on a silicon substrate. The measured NA is 0.64 and the focused spot size is 0.64 mu m.
High numerical-aperture microlens fabricated by focused ion beam milling - art. no. 66200L
(2007)
Chiu, Yi
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Huang, Chien-Hsun
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Hsu, Ying-Chien
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電控工程研究所
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Institute of Electrical and Control Engineering
The focusing objective lens is a key component in the optical pick-up head. In this paper, focused ion beam milling is used to fabricate a NA 0.65 microlens in the silicon nitride film suspended on a silicon substrate. The measured NA is 0.64 and the focused spot size is 0.64 mu m.
Incorporating significant amino acid pairs and protein domains to predict RNA splicing-related proteins with functional roles
(2014-01-01)
Hsu, Justin Bo-Kai
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Huang, Kai-Yao
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Weng, Tzu-Ya
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Huang, Chien-Hsun
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Lee, Tzong-Yi
Machinery of pre-mRNA splicing is carried out through the interaction of RNA sequence elements and a variety of RNA splicing-related proteins (SRPs) (e.g. spliceosome and splicing factors). Alternative splicing, which is an important post-transcriptional regulation in eukaryotes, gives rise to multiple mature mRNA isoforms, which encodes proteins with functional diversities. However, the regulation of RNA splicing is not yet fully elucidated, partly because SRPs have not yet been exhaustively identified and the experimental identification is labor-intensive. Therefore, we are motivated to design a new method for identifying SRPs with their functional roles in the regulation of RNA splicing. The experimentally verified SRPs were manually curated from research articles. According to the functional annotation of Splicing Related Gene Database, the collected SRPs were further categorized into four functional groups including small nuclear Ribonucleoprotein, Splicing Factor, Splicing Regulation Factor and Novel Spliceosome Protein. The composition of amino acid pairs indicates that there are remarkable differences among four functional groups of SRPs. Then, support vector machines (SVMs) were utilized to learn the predictive models for identifying SRPs as well as their functional roles. The cross-validation evaluation presents that the SVM models trained with significant amino acid pairs and functional domains could provide a better predictive performance. In addition, the independent testing demonstrates that the proposed method could accurately identify SRPs in mammals/plants as well as effectively distinguish between SRPs and RNA-binding proteins. This investigation provides a practical means to identifying potential SRPs and a perspective for exploring the regulation of RNA splicing.
Specific heat capacity of molten salt-based alumina nanofluid
(2013-06-21)
Lu, Ming-Chang
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Huang, Chien-Hsun
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機械工程學系
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Department of Mechanical Engineering
There is no consensus on the effect of nanoparticle (NP) addition on the specific heat capacity (SHC) of fluids. In addition, the predictions from the existing model have a large discrepancy from the measured SHCs in nanofluids. We show that the SHC of the molten salt-based alumina nanofluid decreases with reducing particle size and increasing particle concentration. The NP size-dependent SHC is resulted from an augmentation of the nanolayer effect as particle size reduces. A model considering the nanolayer effect which supports the experimental results was proposed.