Chinese investment in Taiwan: challenge or opportunity for Taiwan’s high-technology industrial development?

Cross-Strait economic activities are no longer one-directional. The Taiwanese government opened the doors to Chinese investment in 2009. The aim of this paper is to address the crucial question: What are the impacts of Chinese investment on Taiwan’s high-technology industrial development? Two further questions immediately follow: Will Chinese investment put Taiwanese industrial development at risk? Will an influx of Chinese investment provide a turning point for Taiwanese industry? The paper starts with a review of Chinese investment in Taiwan under the framework of the ECFA and then explains the justification for focusing on high-technology industry in Taiwan. It then outlines the main elements of Chinese outwards foreign direct investment (OFDI) before seeing to answer the above research questions. Fieldwork for this paper was conducted from December 2014 to March 2016. Interviewees include Chinese investors from Beijing, Shanghai and Kunshan, and consultants from a Taiwanese institute created to promote industrial development

Chinese investment in Taiwan: challenge or opportunity for Taiwan’s high-technology industrial development?

Cross-Strait economic activities are no longer one-directional. The Taiwanese government opened the doors to Chinese investment in 2009. The aim of this paper is to address the crucial question: What are the impacts of Chinese investment on Taiwan’s high-technology industrial development? Two further questions immediately follow: Will Chinese investment put Taiwanese industrial development at risk? Will an influx of Chinese investment provide a turning point for Taiwanese industry? The paper starts with a review of Chinese investment in Taiwan under the framework of the ECFA and then explains the justification for focusing on high-technology industry in Taiwan. It then outlines the main elements of Chinese outwards foreign direct investment (OFDI) before seeing to answer the above research questions. Fieldwork for this paper was conducted from December 2014 to March 2016. Interviewees include Chinese investors from Beijing, Shanghai and Kunshan, and consultants from a Taiwanese institute created to promote industrial development

Chinese Investment in Taiwan: A Challenge or an Opportunity for Taiwan?

Cross-Strait economic activities are no longer unidirectional. The Taiwanese government opened the doors to Chinese investment in 2009. This paper addresses the following crucial question: What is the impact of Chinese investment on Taiwan’s high-technology industrial development? Two further questions immediately follow: Will Chinese investment put Taiwanese industrial development at risk? Will an influx of Chinese investment lead to a turning point for Taiwanese industry? The paper first reviews Chinese investment in Taiwan under the framework of the Economic Cooperation Framework Agreement (ECFA) and then explains why we have chosen to focus here on the high-technology industry in Taiwan. It then outlines the main elements of Chinese outward foreign direct investment (OFDI) before seeking to answer the above research questions. Fieldwork for this paper was conducted from December 2014 to March 2016. Interviewees include Chinese investors, along with consultants from a Taiwanese institute created to promote industrial development

Landmark-Matching Transformation with Large Deformation Via n-dimensional Quasi-conformal Maps

We propose a new method to obtain landmark-matching transformations between n-dimensional Euclidean spaces with large deformations. Given a set of feature correspondences, our algorithm searches for an optimal folding-free mapping that satisfies the prescribed landmark constraints. The standard conformality distortion defined for mappings between 2-dimensional spaces is first generalized to the n-dimensional conformality distortion K(f) for a mapping f between n-dimensional Euclidean spaces (n ≥ 3). We then propose a variational model involving K(f) to tackle the landmark-matching problem in higher dimensional spaces. The generalized conformality term K(f) enforces the bijectivity of the optimized mapping and minimizes its local geometric distortions even with large deformations. Another challenge is the high computational cost of the proposed model. To tackle this, we have also proposed a numerical method to solve the optimization problem more efficiently. Alternating direction method with multiplier is applied to split the optimization problem into two subproblems. Preconditioned conjugate gradient method with multi-grid preconditioner is applied to solve one of the sub-problems, while a fixed-point iteration is proposed to solve another subproblem. Experiments have been carried out on both synthetic examples and lung CT images to compute the diffeomorphic landmark-matching transformation with different landmark constraints. Results show the efficacy of our proposed model to obtain a folding-free landmark-matching transformation between n-dimensional spaces with large deformations

Mapping and direct valuation: Do they give equivalent EQ-5D-5L index scores?

© 2015 Luo et al. Objective: Utility values of health states defined by health-related quality of life instruments can be derived from either direct valuation ('valuation-derived') or mapping ('mapping-derived'). This study aimed to compare the utility-based EQ-5D-5L index scores derived from the two approaches as a means to validating the mapping function developed by van Hout et al for the EQ-5D-5L instrument. Methods: This was an observational study of 269 breast cancer patients whose EQ-5D-5L index scores were derived from both methods. For comparing discriminatory ability and responsiveness to change, multivariable regression models were used to estimate the effect sizes of various health indicators on the index scores. Agreement and test-retest reliability were examined using intraclass correlation coefficient (ICC). Whenever appropriate, the 90 % confidence intervals (90 % CI) were compared to predefined equivalence margins. Results: The mean difference in and ICC between the valuation- and mapping-derived EQ-5D-5L index scores were 0.015 (90 % CI = 0.006 to 0.024) and 0.915, respectively. Discriminatory ability and responsiveness of the two indices were equivalent in 13 of 15 regression analyses. However, the mapping-derived index score was lower than the valuation-derived index score in patients experiencing extreme health problems, and the test-retest reliability of the former was lower than the latter, for example, their ICCs differed by 0.121 (90 % CI = 0.051 to 0.198) in patients who reported no change in performance status in the follow-up survey. Conclusion: This study provided the first evidence supporting the validity of the mapping function for converting EQ-5D-5L profile data into a utility-based index score.published_or_final_versio

Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles

<p>Abstract</p> <p>Background</p> <p>The hierarchical clustering tree (HCT) with a dendrogram <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> and the singular value decomposition (SVD) with a dimension-reduced representative map <abbrgrp><abbr bid="B2">2</abbr></abbrgrp> are popular methods for two-way sorting the gene-by-array matrix map employed in gene expression profiling. While HCT dendrograms tend to optimize local coherent clustering patterns, SVD leading eigenvectors usually identify better global grouping and transitional structures.</p> <p>Results</p> <p>This study proposes a flipping mechanism for a conventional agglomerative HCT using a rank-two ellipse (R2E, an improved SVD algorithm for sorting purpose) seriation by Chen <abbrgrp><abbr bid="B3">3</abbr></abbrgrp> as an external reference. While HCTs always produce permutations with good local behaviour, the rank-two ellipse seriation gives the best global grouping patterns and smooth transitional trends. The resulting algorithm automatically integrates the desirable properties of each method so that users have access to a clustering and visualization environment for gene expression profiles that preserves coherent local clusters and identifies global grouping trends.</p> <p>Conclusion</p> <p>We demonstrate, through four examples, that the proposed method not only possesses better numerical and statistical properties, it also provides more meaningful biomedical insights than other sorting algorithms. We suggest that sorted proximity matrices for genes and arrays, in addition to the gene-by-array expression matrix, can greatly aid in the search for comprehensive understanding of gene expression structures. Software for the proposed methods can be obtained at <url>http://gap.stat.sinica.edu.tw/Software/GAP</url>.</p

Chinese investment in Taiwan: challenge or opportunity for Taiwan’s high-technology industrial development?

Cross-Strait economic activities are no longer one-directional. The Taiwanese government opened the doors to Chinese investment in 2009.The aim of this paper is to address the crucial question: What are the impacts of Chinese investment on Taiwan’s high-technology industrial development? Two further questions immediately follow: Will Chinese investment put Taiwanese industrial development at risk? Will an influx of Chinese investment provide a turning point for Taiwanese industry?The paper starts with a review of Chinese investment in Taiwan under the framework of the ECFA and then explains the justification for focusing on high-technology industry in Taiwan. It then outlines the main elements of Chinese outwards foreign direct investment (OFDI) before seeing to answer the above research questions.Fieldwork for this paper was conducted from December 2014 to March 2016. Interviewees include Chinese investors from Beijing, Shanghai and Kunshan, and consultants from a Taiwanese institute created to promote industrial development

Tea Verification Using Triplet Loss Convolutional Network

To solve tea image classification problems, this study focuses on triplet loss convolutional neural network to classify six high-mountain oolong tea classes. In the experiment, instead of using traditional deep learning training approach for local feature of tea images, an innovative image verification approach is proposed to learn the global feature of tea images by integrating the distributed tea leaves’ features of all tea sub-images and using a majority voting mechanism to do classification. The results show that the proposed approach can work for small sample size dataset and have higher accuracy than normal transfer learning approach. The average accuracy of the proposed approach achieves 99.54%