Speech Perception in “Bubble” Noise: Korean Fricatives and Affricates By Native and Non-native Korean Listeners

The current study examines acoustic cues used by second language learners of Korean to discriminate between Korean fricatives and affricates in noise and how these cues relate to those used by native Korean listeners. Stimuli consist of naturally-spoken consonant-vowel-consonant-vowel (CVCV) syllables: /sɑdɑ/, /s*ɑdɑ/, /tʃɑdɑ/, /tʃhɑdɑ/, and /tʃ*ɑdɑ/. In this experiment, the “bubble noise” methodology of Mandel at al. (2016) was used to identify the time-frequency locations of important cues in each utterance, i.e., where audibility of the location is significantly correlated with correct identification of the utterance in noise. Results show that non-native Korean listeners can discriminate between Korean fricatives and affricates in noise after training with the specific utterances. However, the acoustic cues used by L2 Korean listeners are different from those used by native Korean listeners. There were explicit differences in the use of the acoustic cues between the two groups for identifying tenseness. The results of this study contribute to a better understanding of how second language learners of Korean process language. Furthermore, the current study helps us to better understand how people learning a second language process speech perception in noisy environments

Creating an evaluation system for a mobile application design to enhance usability and aesthetics

The purpose of this study is to create an evaluation system for a mobile application design meant to enhance usability and aesthetics. In order to best evaluate the design of a mobile application, designers need to have a thorough understanding of the content or subject of that mobile application. Therefore, in order to evaluate the appropriateness of the design of these examples of mobile applications stress was chosen as a topic for this case study. Stress is a fact of life. Experts say that stress is a natural bodily response to the demands placed on it: however, stress can cause health problems if left unmanaged. Thus, people under stress should manage their stress in appropriate ways. Along with the development of mobile technology, people came to use mobile applications anywhere at anytime. Mobile applications for stress reduction can be good tools that help people manage stress easily and effectively. The methodology includes a literature review and case studies with three existing mobile applications for stress reduction. These things are used to develop an evaluation matrix that allows for the analysis of mobile applications for stress reduction based on design principles, usability and aesthetics

Relationship between Moral Judgment Development and Political Attitude

2005The purposes of this study were to examine the emotional/political reactions to the terrorist attacks of September 11, 2001 in the USA and to look at the relationship among moral judgment development, attitude toward to human right and political reactions to terrorist attacks. The current study's results demonstrated that with respect to emotional responses to terrorist attacks, 'angry' and 'sad' appear at the same frequency while the least emotional response is 'confused'. Females report sadness more than males while males report anger more than females in a certain situation. With respect to political action choices to terrorist attack, males tend to consider a retaliatory response when they make political decision while females tend to consider more considerable ways in which we can overcome terrorist situation. Students who get higher moral judgment scores are less likely to insist that "we must fight back" while students who get lower moral judgment scores are less likely to insist that "we should not make hasty decisions." However it is not a significant difference, so we need to have more data and should explore in detail this relationship. In addition, people who have higher scores on attitude on human rights are more likely to consider innocent people's lives when they make political decisions. People who are more considering human rights tend to disagree with action choice 3 "we must fight back." Because the survey was administered to dentistry students in January 2002, their emotional responses and their political action choices could be different from what they thought right after the terrorist attack on September 11, 2001. Finally generalizability issue of the current study is discussed

Concrete delamination depth estimation using a noncontact mems ultrasonic sensor array and an optimization approach

In this study, we present a method to estimate the depth of near-surface shallow delamination in concrete using a noncontact micro-electromechanical system (MEMS) ultrasonic sensor array and an optimization-based data processing approach. The proposed approach updates the bulk wave velocities of the tested concrete element by solving an optimization problem using reference ultrasonic scanning data collected from a full-depth concrete region. Subsequently, the depth of concrete delamination is estimated by solving a separate optimization problem. Numerical simulations and laboratory experiments were conducted to evaluate the performance of the proposed ultrasonic data processing approach. The results demonstrated that the depth of shallow delamination in concrete structures could be accurately estimated

Three Recipes for Better 3D Pseudo-GTs of 3D Human Mesh Estimation in the Wild

Recovering 3D human mesh in the wild is greatly challenging as in-the-wild (ITW) datasets provide only 2D pose ground truths (GTs). Recently, 3D pseudo-GTs have been widely used to train 3D human mesh estimation networks as the 3D pseudo-GTs enable 3D mesh supervision when training the networks on ITW datasets. However, despite the great potential of the 3D pseudo-GTs, there has been no extensive analysis that investigates which factors are important to make more beneficial 3D pseudo-GTs. In this paper, we provide three recipes to obtain highly beneficial 3D pseudo-GTs of ITW datasets. The main challenge is that only 2D-based weak supervision is allowed when obtaining the 3D pseudo-GTs. Each of our three recipes addresses the challenge in each aspect: depth ambiguity, sub-optimality of weak supervision, and implausible articulation. Experimental results show that simply re-training state-of-the-art networks with our new 3D pseudo-GTs elevates their performance to the next level without bells and whistles. The 3D pseudo-GT is publicly available in https://github.com/mks0601/NeuralAnnot_RELEASE.Comment: Published at CVPRW 202

Broussonetia papyrifera Root Bark Extract Exhibits Anti-inflammatory Effects on Adipose Tissue and Improves Insulin Sensitivity Potentially Via AMPK Activation

The chronic low-grade inflammation in adipose tissue plays a causal role in obesity-induced insulin resistance and its associated pathophysiological consequences. In this study, we investigated the effects of extracts of Broussonetia papyrifera root bark (PRE) and its bioactive components on inflammation and insulin sensitivity. PRE inhibited TNF-alpha-induced NF-kappa B transcriptional activity in the NF-kappa B luciferase assay and pro-inflammatory genes' expression by blocking phosphorylation of I kappa B and NF-kappa B in 3T3-L1 adipocytes, which were mediated by activating AMPK. Ten-week-high fat diet (HFD)-fed C57BL6 male mice treated with PRE had improved glucose intolerance and decreased inflammation in adipose tissue, as indicated by reductions in NF-kappa B phosphorylation and pro-inflammatory genes' expression. Furthermore, PRE activated AMP-activated protein kinase (AMPK) and reduced lipogenic genes' expression in both adipose tissue and liver. Finally, we identified broussoflavonol B (BF) and kazinol J (KJ) as bioactive constituents to suppress pro-inflammatory responses via activating AMPK in 3T3-L1 adipocytes. Taken together, these results indicate the therapeutic potential of PRE, especially BF or KJ, in metabolic diseases such as obesity and type 2 diabetes

VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception

AI alignment refers to models acting towards human-intended goals, preferences, or ethical principles. Given that most large-scale deep learning models act as black boxes and cannot be manually controlled, analyzing the similarity between models and humans can be a proxy measure for ensuring AI safety. In this paper, we focus on the models' visual perception alignment with humans, further referred to as AI-human visual alignment. Specifically, we propose a new dataset for measuring AI-human visual alignment in terms of image classification, a fundamental task in machine perception. In order to evaluate AI-human visual alignment, a dataset should encompass samples with various scenarios that may arise in the real world and have gold human perception labels. Our dataset consists of three groups of samples, namely Must-Act (i.e., Must-Classify), Must-Abstain, and Uncertain, based on the quantity and clarity of visual information in an image and further divided into eight categories. All samples have a gold human perception label; even Uncertain (severely blurry) sample labels were obtained via crowd-sourcing. The validity of our dataset is verified by sampling theory, statistical theories related to survey design, and experts in the related fields. Using our dataset, we analyze the visual alignment and reliability of five popular visual perception models and seven abstention methods. Our code and data is available at \url{https://github.com/jiyounglee-0523/VisAlign}