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

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

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

Mining Comparison Opinions from Chinese Online Reviews for Restaurant Competitive Analysis

Comparison is widely used by consumers during the process of product evaluation in order to emphasize their preference, which can contribute to a proxy for product competitiveness analysis. This paper proposes a novel method for mining comparative sentences based on the achievements of linguistic study. The definition of comparative sentence subcategory is put forward and a mixed rule pool containing both artificial rules and CSR is set up. Besides, an entity dictionary is used to re-check the identification result which can ensure precise identification and classification of comparative sentences. Real online comments are collected from Dianping.com as experimental data. The result shows that the proposed method outperforms baseline methods in terms of identification precision. Based on the result, features and opinions of comparative sentences are mined. We then conducted sentiment analysis to calculate the sentimental score of comparison relations. Finally, a feature competitive network of restaurants is constructed

Novel complete ensemble EMD with adaptive noise-based hybrid filtering for rolling bearing fault diagnosis

A feature extraction of fault bearing has attracted considerable attention in recent years. However, weak fault feature is difficult to extract under heavy background noise. To solve this problem, a novel multi-layer filtering method is proposed to filter out noise and extract weak fault feature. The first layer introduces a metric based on de-trended fluctuation analysis (DFA) to identify intrinsic mode function (IMF) that reflect period impulsive information for vibration signal adaptively. The second layer uses non-local mean (NLM) method as a pre-filter of the third layer to realize extraction of singular value decomposition (SVD) which reflect the most information of IMFs. The last layer introduces a relative energy difference criterion of a singular value to extract important feature of Hankel matrix of IMFs. The filtered signal is obtained by re-constructed signal from identified singular value of SVD. Experiment results on simulation and real vibration signals indicate that the hybrid filtering method removes heavy noise successfully and extract weak fault feature of rolling bearing effectively

Reaction dynamics for the Cl(2^2P) + XCl →\to XCl + Cl(2^2P) (X = H, D, Mu) reaction on a high-fidelity ground state potential energy surface

Globally accurate full-dimensional ground state potential energy surface (PES) for the Cl($^2$P) + XCl $\to$ HCl + Cl($^2$P) reaction, a prototypical heavy-light-heavy abstract reaction, is developed using permutation invariant polynomial neural network (PIP-NN) method and embedded atom neural network (EANN) method, with the corresponding total root mean square error (RMSE) being only 0.043 and 0.056 kcal/mol, respectively. The saddle point of this reaction system is found to be nonlinear. A full-dimensional approximate quantum mechanical method, ring-polymer molecular dynamics (RPMD) with Cayley propagator, is employed to calculate the thermal rate coefficients and kinetic isotopic effects of title reactions Cl($^2$P) + XCl $\to$ XCl + Cl($^2$P) (X = H, D, Mu) on both new PESs. The results reproduce the experimental results at high temperatures perfectly, but with moderate accuracy at lower temperatures. The similar kinetic behavior is supported by quantum dynamics using wave packet calculations as well.Comment: 23 pages,5 figure