DOES PUBLIC R&D CROWD OUT PRIVATE R&D? A NOTE FROM TAIWAN, ROC

This paper tests the cointegration and causal relationship between aggregate public R&D and private R&D for Taiwan for the period 1979-2007 using a newly developed cointegration test proposed by Pesaran et al. (2001) and using a modified version of the Granger causality test due to Toda and Yamamoto (1995). The paper finds a long run cointegrating relationship between public and private R&D and a bi-directional causality where they complement each other. The Government of the ROC should continue to invest not only to stimulate private R&D but also to enable the country to compete more globally in technology-intensive products.Taiwan, Public and Private R&D, Bounds Test, Causality, Impulse Response

Network streaming and compression for mixed reality tele-immersion

Bulterman, D.C.A. [Promotor]Cesar, P.S. [Copromotor

Sero-prevalence status of foot and mouth disease in the North Western Amhara Regional State, Ethiopia

A cross-sectional survey was conducted on serum samples collected from North and South Gondar zones of North Western Amhara Regional State, Ethiopia to determine the sero-prevalence of foot and mouth diseases in bovine species. The samples were processed with the nonstructural protein (NSP) enzyme linked immunosorbent assay (ELISA) that can able to differentiate foot and mouth disease (FMD) naturally infected vaccinated animals. From the total sera tested, the overall sero-prevalence of foot and mouth disease in cattle at the North and South Gondar zones was 14.9% (86/578). The prevalence rate was high in North Gondar, 17.8% (66/370), as compared to 9.6% (20/208) in South Gondar and the difference was statistically significant (χ² =7.108, p=0.008). Highest sero-prevalence was observed at Metema (62.5%), Quara (46.7%) and Alefa Takusa (34.9%) districts of North Gondar zone, which are bordering with Sudan. The difference among the districts is also statistically significant (χ²=141.115, p=0.0001). There was also a significant association between seropositivity and age groups (χ²=9.483, P=0.009) but there was no significant association between the seropositivity and sex (χ²=0.623, p=0.430). This information on sero surveillance of foot and mouth disease in cattle is important for further epidemiological studies towards developing effective foot and mouth disease control strategies, particularly in these areas where animal movement is not restricted.Keywords: Cattle, Seroprevalence, FMD, North West Amhara Region, 3ABC ELIS

Binaural Spatialization for 3D immersive audio communication in a virtual world

Realistic 3D audio can greatly enhance the sense of presence in a virtual environment. We introduce a framework for capturing, transmitting and rendering of 3D audio in presence of other bandwidth savvy streams in a 3D Tele-immersion based virtual environment. This framework presents an efficient implementation for 3D Binaural Spatialization based on the positions of current objects in the scene, including animated avatars and on the fly reconstructed humans. We present a general overview of the framework, how audio is integrated in the system and how it can exploit the positions of the objects and room geometry to render realistic reverberations using head related transfer functions. The network streaming modules used to achieve lip-synchronization, high-quality audio frame reception, and accurate localization for binaural rendering are also presented. We highlight how large computational and networking challenges can be addressed efficiently. This represents a first step in adequate networking support for Binaural 3D Audio, useful for telepresence. The subsystem is successfully integrated with a larger 3D immersive system, with state of art capturing and rendering modules for visual data

Machine Learning Models Evaluation and Feature Importance Analysis on NPL Dataset

Predicting the probability of non-performing loans for individuals has a vital and beneficial role for banks to decrease credit risk and make the right decisions before giving the loan. The trend to make these decisions are based on credit study and in accordance with generally accepted standards, loan payment history, and demographic data of the clients. In this work, we evaluate how different Machine learning models such as Random Forest, Decision tree, KNN, SVM, and XGBoost perform on the dataset provided by a private bank in Ethiopia. Further, motivated by this evaluation we explore different feature selection methods to state the important features for the bank. Our findings show that XGBoost achieves the highest F1 score on the KMeans SMOTE over-sampled data. We also found that the most important features are the age of the applicant, years of employment, and total income of the applicant rather than collateral-related features in evaluating credit risk.Comment: 7 pages, 2 figures, Machine Learning for Development (ML4D) workshop at NeurIPS 202

Source coding for transmission of reconstructed dynamic geometry: a rate-distortion-complexity analysis of different approaches

Live 3D reconstruction of a human as a 3D mesh with commodity electronics is becoming a reality. Immersive applications (i.e. cloud gaming, tele-presence) benefit from effective transmission of such content over a bandwidth limited link. In this paper we outline different approaches for compressing live reconstructed mesh geometry based on distributing mesh reconstruction functions between sender and receiver. We evaluate rate-performance-complexity of different configurations. First, we investigate 3D mesh compression methods (i.e. dynamic/static) from MPEG-4. Second, we evaluate the option of using octree based point cloud compression and receiver side surface reconstruction

Foreign aid and tourism induced electricity consumption in the Turkish Republic of Northern Cyprus

The aim of this paper is to investigate the role of foreign aid and tourism in inducing electricity consumption in a tourism and a foreign aid dependent Turkish Republic of Northern Cyprus (TRNC) for the period 1977-2017. Applying the Autoregressive Distributive Lag (ARDL) approach to cointegration, we found that both foreign aid and tourism positively and significantly induce electricity consumption. Our results are robust to the Canonical Cointegrating Regression (CCR), the fully modified ordinary least squares (FMOLS) and the dynamic ordinary least squares (DOLS) long-run tests. We also found bidirectional causality between foreign aid and electricity consumption while unidirectional causality from tourism to electricity consumption. Both foreign aid and tourism induce electricity consumption indicating that they are both important sources of the growth of electricity consumption. However, since energy consumption is the main source of environmental degradation, the TRNC should develop an energy strategy that promotes environmental sustainability

Natural human interaction in virtual immersive environments

REVERIE (REal and Virtual Engagement in Realistic Immersive Environments [1]) targets novel research to address the demanding challenges involved with developing state-of-the-art technologies for online human interaction. The REVERIE framework enables users to meet, socialise and share experiences online by integrating cutting-edge technologies for 3D data acquisition and processing, networking, autonomy and real-time rendering. In this paper, we describe the innovative research that is showcased through the REVERIE integrated framework through richly defined use-cases which demonstrate the validity and potential for natural interaction in a virtual immersive and safe environment. Previews of the REVERIE demo and its key research components can be viewed at www.youtube.com/user/REVERIEFP7