Acoustic Scene Classification by Implicitly Identifying Distinct Sound Events

In this paper, we propose a new strategy for acoustic scene classification (ASC) , namely recognizing acoustic scenes through identifying distinct sound events. This differs from existing strategies, which focus on characterizing global acoustical distributions of audio or the temporal evolution of short-term audio features, without analysis down to the level of sound events. To identify distinct sound events for each scene, we formulate ASC in a multi-instance learning (MIL) framework, where each audio recording is mapped into a bag-of-instances representation. Here, instances can be seen as high-level representations for sound events inside a scene. We also propose a MIL neural networks model, which implicitly identifies distinct instances (i.e., sound events). Furthermore, we propose two specially designed modules that model the multi-temporal scale and multi-modal natures of the sound events respectively. The experiments were conducted on the official development set of the DCASE2018 Task1 Subtask B, and our best-performing model improves over the official baseline by 9.4% (68.3% vs 58.9%) in terms of classification accuracy. This study indicates that recognizing acoustic scenes by identifying distinct sound events is effective and paves the way for future studies that combine this strategy with previous ones.Comment: code URL typo, code is available at https://github.com/hackerekcah/distinct-events-asc.gi

A Compact and Discriminative Feature Based on Auditory Summary Statistics for Acoustic Scene Classification

One of the biggest challenges of acoustic scene classification (ASC) is to find proper features to better represent and characterize environmental sounds. Environmental sounds generally involve more sound sources while exhibiting less structure in temporal spectral representations. However, the background of an acoustic scene exhibits temporal homogeneity in acoustic properties, suggesting it could be characterized by distribution statistics rather than temporal details. In this work, we investigated using auditory summary statistics as the feature for ASC tasks. The inspiration comes from a recent neuroscience study, which shows the human auditory system tends to perceive sound textures through time-averaged statistics. Based on these statistics, we further proposed to use linear discriminant analysis to eliminate redundancies among these statistics while keeping the discriminative information, providing an extreme com-pact representation for acoustic scenes. Experimental results show the outstanding performance of the proposed feature over the conventional handcrafted features.Comment: Accepted as a conference paper of Interspeech 201

Flow characteristics and heat transfer performance in a Y-Fractal mini/microchannel heat sink

This article presents a combined experimental and computational study to investigate the flow and heat transfer in a Y-fractal microchannel. Experimental apparatus was newly built to investigate the effect of three different control factors, i.e., fluid flow rate, inlet temperature and heat flux, on the heat transfer characteristics of the microchannel. A standard k-Ɛ turbulence computational fluid dynamics (CFD) model was developed, validated and further employed to simulate the flow and heat transfer microchannel. A comparison between simulated results and the obtained experimental data was presented and discussed. Results showed that good agreement was achieved between the current simulated results and experimental data. Furthermore, an improved new design was suggested to further increase the heat transfer performance and create uniformity of temperature distribution.Peer reviewe

Performance analysis of a new deep super-cooling two-stage organic Rankine cycle

This document is the Accepted Manuscript version of the following article: Y. Yuan, G. Xu, Y. Quan, H. Wu, G. Song, W. Gong, and X. Luo, ‘Performance analysis of a new deep super-cooling two-stage organic Rankine cycle’, Energy Conversion and Management, Vol. 148: 305-316, September 2017. The final, definitive version is available online at doi:https://doi.org/10.1016/j.enconman.2017.06.006. Published by Elsevier.In this article, a new deep super-cooling two-stage organic Rankine cycle (DTORC) is proposed and evaluated at high temperature waste heat recovery in order to increase the power output. A thermodynamic model of recuperative organic rankine cycle (ORC) is also established for the purpose of comparison. Furthermore, a new evaluation index, effective heat source utilization, is proposed to reflect the relationship among the heat source, power output and consumption of the waste heat carrier. A simulation model is formulated and analysed under a wide range of operating conditions with the heat resource temperature fixed at 300℃. Hexamethyldisiloxane (MM) and R245fa are used as the working fluid for DTORC, and MM for ORC. In the current work, the comparisons of heat source utilization, net thermal efficiency as well as the total surface area of the heat exchangers between DTORC and RC are discussed in detail. Results show that the DTORC performs better than ORC at high temperature waste heat recovery and it could increase the power output by 150%. Moreover, the maximum net thermal efficiency of DTORC can reach to 23.5% and increased by 30.5% compared with that using ORC, whereas the total surface areas of the heat exchangers are nearly the same.Peer reviewe

Interaction Between Green Chemistry, United Nation Sustainable Development Goals (sdgs) And Public Health

The topic of sustainability has never ever been popular like today when people realized its significance. Launch of the United Nation Sustainable Development Goals built the blue print in environment, wealth, education and public health with sustainability, and development of green chemistry in concept and principles formation, research and innovation provided technical support in realizing these goals, and simultaneously tackle issues in public health. Three objects interact organically and form an integrated system

Three Essays on the Economics of Foreign Aid

Recent years have seen a burgeoning interest in the issue of foreign aid especially in the context of developmental economics. As foreign aid is designed to help those less-privileged nations with developmental objectives such as poverty reduction and/or economic growth, fundamental questions include whether aid has been effective and what motivates donors to provide aid. This dissertation is composed of three essays that examine different issues concerning foreign aid. First, I focus on the Millennium Development Goals (MDGs) and its impact on aid allocation among sectors. If specification of the MDGs affected aid flows, it should be observed that more financial resources were given after the MDGs were announced. Moreover, sectors associated with the MDGs should have received more aid. Second, researchers do not agree on the effect of aid on the recipient countries’ economic growth. I apply Social network theory to analyze the aid environment as a two-mode network. Network-based indicators are developed to capture aid connectivity and I find a positive relationship between the aid connectivity and the recipient countries’ average annual growth of GDP. Third, I look at two donors (South Korea and Turkey) who have transitioned from aid recipients to donors. Having experienced rapid economic development while receiving foreign assistance, these two nations may have a better understanding of how to make aid more effective for recipients. I then compared their aid allocation patterns with traditional donors

Lack of evidence of hepatitis in patients with oral lichen planus in China: a case control study

Background: China has been one of the countries with high prevalence of chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) liver disease. And lichen planus is an extrahepatic manifestation of patients with chronic HCV infection. This case-control study was conducted to investigate the relationship between oral lichen planus (OLP) and HBV/HCV infection in China. Material and Methods: A total of 776 patients, including 150 patients with OLP (Group OLP), 429 inpatients from the Trauma Ward of Oral and Maxillofacial Surgery Department (Group A), 110 patients with other oral mucosal diseases, but without a reported association with HCV infection (Group B) and 87 patients with oral lichenoid lesion (Group OLL), were compared with their seroprevalence of anti-HCV antibody (HCVAb), hepatitis B surface antigen (HBsAg) and the parameters of liver functions. Moreover, the clinical characteristics of OLP were also observed, such as gender, age, chief complaint, course of the disease, clinical type, sites involved and so on. Results: The positive rates of HCVAb and HBsAg in OLP patients were 0.7% and 4%, respectively. Neither HCVAb nor HBsAg was associated with OLP as demonstrated by both the univariate and the multivariate analyses. The clinical features and liver functions of OLP patients with negative or positive HBsAg were nearly the same. Conclusions: Our findings verify that there is no association between OLP and hepatitis and there is no need to run a screening test for HCV or HBV in OLP patients in Chin