Recent Trends of Regional Development in China – Technological Portfolios and Economic Growth

This paper analyses recent patterns and trends of technological development in Chinese provinces. It reflects on characteristic distinctions between these regions’ portfolios of technological activity as well as the local matches between scientific, technological and economic efforts within them. Building on both theoretical and country specific literature, it suggests that, in China, the internal structure of technological activities might play a lesser role for economic development than in established market economies while their external embeddedness could be more important. Based on a comprehensive dataset, it identifies characteristic profiles and pathways of development among China’s provinces. With a view to those, its findings suggest a continued relevance of existing legacies but, equally, newly emerging industrial dynamism. While related variety is now present in many leading regions, the local match between technological and economic activities remains the most relevant discriminator between already well-developed provinces and those catching up with the leading group.

POSITIONAL ACCURACY ASSESSMENT OF THE OPENSTREETMAP BUILDINGS LAYER THROUGH AUTOMATIC HOMOLOGOUS PAIRS DETECTION: THE METHOD AND A CASE STUDY

OpenStreetMap (OSM) is currently the largest openly licensed collection of geospatial data. Being OSM increasingly exploited in a variety of applications, research has placed great attention on the assessment of its quality. This work focuses on assessing the quality of OSM buildings. While most of the studies available in literature are limited to the evaluation of OSM building completeness, this work proposes an original approach to assess the positional accuracy of OSM buildings based on comparison with a reference dataset. The comparison relies on a quasi-automated detection of homologous pairs on the two datasets. Based on the homologous pairs found, warping algorithms like e.g. affine transformations and multi-resolution splines can be applied to the OSM buildings to generate a new version having an optimal local match to the reference layer. A quality assessment of the OSM buildings of Milan Municipality (Northern Italy), having an area of about 180 km2, is then presented. After computing some measures of completeness, the algorithm based on homologous points is run using the building layer of the official vector cartography of Milan Municipality as the reference dataset. Approximately 100000 homologous points are found, which show a systematic translation of about 0.4 m on both the X and Y directions and a mean distance of about 0.8 m between the datasets. Besides its efficiency and high degree of automation, the algorithm generates a warped version of OSM buildings which, having by definition a closest match to the reference buildings, can be eventually integrated in the OSM database.

POSITIONAL ACCURACY ASSESSMENT OF THE OPENSTREETMAP BUILDINGS LAYER THROUGH AUTOMATIC HOMOLOGOUS PAIRS DETECTION: THE METHOD AND A CASE STUDY

OpenStreetMap (OSM) is currently the largest openly licensed collection of geospatial data. Being OSM increasingly exploited in a variety of applications, research has placed great attention on the assessment of its quality. This work focuses on assessing the quality of OSM buildings. While most of the studies available in literature are limited to the evaluation of OSM building completeness, this work proposes an original approach to assess the positional accuracy of OSM buildings based on comparison with a reference dataset. The comparison relies on a quasi-automated detection of homologous pairs on the two datasets. Based on the homologous pairs found, warping algorithms like e.g. affine transformations and multi-resolution splines can be applied to the OSM buildings to generate a new version having an optimal local match to the reference layer. A quality assessment of the OSM buildings of Milan Municipality (Northern Italy), having an area of about 180 km2, is then presented. After computing some measures of completeness, the algorithm based on homologous points is run using the building layer of the official vector cartography of Milan Municipality as the reference dataset. Approximately 100000 homologous points are found, which show a systematic translation of about 0.4 m on both the X and Y directions and a mean distance of about 0.8 m between the datasets. Besides its efficiency and high degree of automation, the algorithm generates a warped version of OSM buildings which, having by definition a closest match to the reference buildings, can be eventually integrated in the OSM database.

A Novel Adaptive Match Scheme for Parallel Mesh-Decomposition in OpenFOAM

A parallel multilevel k-way partitioning algorithm is used in OpenFOAM to perform parallel mesh-decomposition. Before the parallel decomposition procedure, mesh has to be pre-decomposed by the Simple method in OpenFOAM. Match-computation for the algorithms parallel coarsening phase is based on a kind of global match scheme which introduces large amount of communication overhead. However, the domains of the mesh generated by Simple maintain good locality and continuity, which makes it unnecessary to adopt global match scheme in the parallel coarsening phase. In this paper, a novel adaptive match scheme AMS is brought forward for the parallel multilevel k-way partitioning algorithm. An adaptive critical x is calculated firstly according to the scale of the mesh and the parallel degree. For the first x stages of the coarsening phase, a local match scheme is adopted in which vertexes are only allowed to match with their adjacent unmatched vertexes with heaviest edge-weight on their local processors. For the rest stages, the traditional global match scheme is introduced and match of two vertexes on different processors is allowed. AMS can efficiently reduce the communication overhead introduced by simply adopting global match scheme. The experiment is performed on mesh of LinearPTT application on Tianhe-1A. The results show that the parallel multilevel k-way paritioning algorithm based on AMS has a better performance than that based on traditional global match scheme.

A Novel Fingerprint Matching Algorithm Based on Compatible Multi-Area Alignment

Most minutiae-based matching algorithms consist of two phases, local match and global match. In the local phase, some corresponding pairs are obtained by comparing the affine-invariable features of minutiae. And then two images are aligned based on the candidate pairs. However, some spurious candidate pairs and the large nonlinear deformation in images lead to the failure in global match. In this paper, we proposed a novel minutiae-based matching scheme which insert a filtering step after the local match to discard the incompatible pairs and renovate the global match by dividing the whole image into small areas according to the location of the candidate pairs. Results on databases of FVC2004 validate our algorithm.

HYPLOSP: A KNOWLEDGE-BASED APPROACH TO PROTEIN LOCAL STRUCTURE PREDICTION

Local structure prediction can facilitate ab initio structure prediction, protein threading, and remote homology detection. However, the accuracy of existing methods is limited. In this paper, we propose a knowledge-based prediction method that assigns a measure called the local match rate to each position of an amino acid sequence to estimate the confidence of our method. Empirically, the accuracy of the method correlates positively with the local match rate; therefore, we employ it to predict the local structures of positions with a high local match rate. For positions with a low local match rate, we propose a neural network prediction method. To better utilize the knowledge-based and neural network methods, we design a hybrid prediction method, HYPLOSP (HYbrid method to Protein LOcal Structure Prediction) that combines both methods. To evaluate the performance of the proposed methods, we first perform cross-validation experiments by applying our knowledge-based method, a neural network method, and HYPLOSP to a large dataset of 3,925 protein chains. We test our methods extensively on three different structural alphabets and evaluate their performance by two widely used criteria, Maximum Deviation of backbone torsion Angle (MDA) and Q N , which is similar to Q3 in secondary structure prediction. We then compare HYPLOSP with three previous studies using a dataset of 56 new protein chains. HYPLOSP shows promising results in terms of MDA and Q N accuracy and demonstrates its alphabet-independent capability.