A New Measurement for International Fragmentation of the Production Process: An International Input-Output Approach

The paper investigates the possibility of constructing a new measurement for analysing international fragmentation of the production process. It asserts that the current usage of relevant data, whether the trade shares of parts and components or the index of Vertical Specialisation, is quite unsatisfactory for measuring the phenomenon, since they critically lack the overall perspective of the entire structure of production chains. 　The new measurement is formulated such that it captures every aspect of the vertical sequence of production linkages. It is based on the input-output model of Average Propagation Lengths, recently developed by Eric Dietzenbacher and others, which show the average number of production stages that are passed through for an exogenous change in one industry to affect another. By applying this model to the data of the Asian International Input-Output Tables, the index is able to measure the international dimension of production sharing and division of labour in East Asia.

Agglomeration versus Fragmentation:A Comparison of East Asia and Europe

Inspired by the observed contrasting patterns of industrial distribution in East Asia and Europe, this paper conducts an empirical clarification of the difference in spatial relationships among countries within a region for the electric machinery industry by use of spatial econometric analysis. The results indicate that, while production in the electric machinery industry in a country is positively correlated with that of neighboring countries in East Asia, there is no significant spatial correlation in Europe. Such a difference in spatial interdependence has important implications for economic development in those regions.

Production fragmentation, upstreamness, and value-added : evidence from factory Asia 1990-2005

We exploit the recent release of the 2005 Asian Input-Output Matrix to dress a picture of the geographic fragmentation of value added in Factory Asia from 1990 to 2005. We document 3 stylized facts. The first is that the average share of foreign value added embedded in production rose by about 7 percentage points between 1990 and 2005, from 9% to 16%. The second is that, contrary to popular belief, China's production embeds a smaller share of foreign value added than other Factory Asia countries'. Between 1990 and 2005 among Factory Asia countries China grew most after Japan as a source of value added to other countries' production. Third, country-industries at the upstream and downstream extremities of the supply chain embed a smaller share of foreign value added than those with intermediate levels of upstreamness.

Exploring differences between phonetic classes in Sleep Apnoea Syndrome Patients using automatic speech processing techniques

This work is part of an on-going collaborative project between the medical and signal processing communities to promote new research efforts on automatic OSA (Obstructive Apnea Syndrome) diagnosis. In this paper, we explore the differences noted in phonetic classes (interphoneme) across groups (control/apnoea) and analyze their utility for OSA detection

Introducing non-linear analysis into sustained speech characterization to improve sleep apnea detection

We present a novel approach for detecting severe obstructive sleep apnea (OSA) cases by introducing non-linear analysis into sustained speech characterization. The proposed scheme was designed for providing additional information into our baseline system, built on top of state-of-the-art cepstral domain modeling techniques, aiming to improve accuracy rates. This new information is lightly correlated with our previous MFCC modeling of sustained speech and uncorrelated with the information in our continuous speech modeling scheme. Tests have been performed to evaluate the improvement for our detection task, based on sustained speech as well as combined with a continuous speech classifier, resulting in a 10% relative reduction in classification for the first and a 33% relative reduction for the fused scheme. Results encourage us to consider the existence of non-linear effects on OSA patients' voices, and to think about tools which could be used to improve short-time analysis.

Soil fragmentation study applying different tillage systems

Runoff generation depends on rainfall, infiltration, interception, and surface depressional storage. Surface depressional storage depends on surface microtopography, usually quantified trough soil surface roughness (SSR). SSR is subject to spatial and temporal changes that create a high variability. In an agricultural environment, tillage operations produce abrupt changes in roughness. Subsequent rainfall gradually decreases roughness. Beside it, local variation in soil properties and hydrology cause its SSR to vary spatially at different scales. The methods commonly used to measure it involve collecting point elevations in regular grids using laser profilers or scanners, digital close range stereo-photogrammetry and terrestrial laser scanning or LIDAR systems. In this case, a laser-scanning instrument was used to obtain representative digital elevation models (DEMs) at a grid resolution of 7.2x7.2mm that cover an area of 0.9x0.9m. The DEMs were obtained from two study sites with different soils. The first study site was an experimental field on which five conventional tillage methods were applied. The second study site was a large olive orchard with trees planted at 7.5x5.0m and bare soils between rows. Here, three tillage treatments were applied. In this work we have evaluated the spatial variability of SSR at several scales studying differences in height calculated from points separated by incremental distances h were raised to power values q (from 0 to 4 in steps of 0.1). The q = 2 data were studied as a semivariogram model. The logarithm of average differences plotted vs. log h were characterized by their slope, ?(q). Structure functions [?(q) vs. q] were fitted showing that data had nonlinear structure functions typical of multiscale phenomena. Comparisson of the two types of soil in their respective structure functions are shown.

Improving automatic detection of obstructive sleep apnea through nonlinear analysis of sustained speech

We present a novel approach for the detection of severe obstructive sleep apnea (OSA) based on patients' voices introducing nonlinear measures to describe sustained speech dynamics. Nonlinear features were combined with state-of-the-art speech recognition systems using statistical modeling techniques (Gaussian mixture models, GMMs) over cepstral parameterization (MFCC) for both continuous and sustained speech. Tests were performed on a database including speech records from both severe OSA and control speakers. A 10 % relative reduction in classification error was obtained for sustained speech when combining MFCC-GMM and nonlinear features, and 33 % when fusing nonlinear features with both sustained and continuous MFCC-GMM. Accuracy reached 88.5 % allowing the system to be used in OSA early detection. Tests showed that nonlinear features and MFCCs are lightly correlated on sustained speech, but uncorrelated on continuous speech. Results also suggest the existence of nonlinear effects in OSA patients' voices, which should be found in continuous speech.