Comparing Sample-wise Learnability Across Deep Neural Network Models

Estimating the relative importance of each sample in a training set has important practical and theoretical value, such as in importance sampling or curriculum learning. This kind of focus on individual samples invokes the concept of sample-wise learnability: How easy is it to correctly learn each sample (cf. PAC learnability)? In this paper, we approach the sample-wise learnability problem within a deep learning context. We propose a measure of the learnability of a sample with a given deep neural network (DNN) model. The basic idea is to train the given model on the training set, and for each sample, aggregate the hits and misses over the entire training epochs. Our experiments show that the sample-wise learnability measure collected this way is highly linearly correlated across different DNN models (ResNet-20, VGG-16, and MobileNet), suggesting that such a measure can provide deep general insights on the data's properties. We expect our method to help develop better curricula for training, and help us better understand the data itself.Comment: Accepted to AAAI 2019 Student Abstrac

Proto-Model of an Infrared Wide-Field Off-Axis Telescope

We develop a proto-model of an off-axis reflective telescope for infrared wide-field observations based on the design of Schwarzschild-Chang type telescope. With only two mirrors, this design achieves an entrance pupil diameter of 50 mm and an effective focal length of 100 mm. We can apply this design to a mid-infrared telescope with a field of view of 8 deg X 8 deg. In spite of the substantial advantages of off-axis telescopes in the infrared compared to refractive or on-axis reflective telescopes, it is known to be difficult to align the mirrors in off-axis systems because of their asymmetric structures. Off-axis mirrors of our telescope are manufactured at the Korea Basic Science Institute (KBSI). We analyze the fabricated mirror surfaces by fitting polynomial functions to the measured data. We accomplish alignment of this two-mirror off-axis system using a ray tracing method. A simple imaging test is performed to compare a pinhole image with a simulated prediction.Comment: 14 pages, 16 figure

AMPK-Dependent Metabolic Regulation by PPAR Agonists

Comprehensive studies support the notion that the peroxisome proliferator-activated receptors, (PPARs), PPARα, PPARβ/δ, and PPARγ, regulate cell growth, morphogenesis, differentiation, and homeostasis. Agonists of each PPAR subtype exert their effects similarly or distinctly in different tissues such as liver, muscle, fat, and vessels. It is noteworthy that PPARα or PPARγ agonists have pharmacological effects by modulating the activity of AMPK, which is a key cellular energy sensor. However, the role of AMPK in the metabolic effects of PPAR agonists has not been thoroughly focused. Moreover, AMPK activation by PPAR agonists seems to be independent of the receptor activation. This intriguing action of PPAR agonists may account in part for the mechanistic basis of the therapeutics in the treatment of metabolic disease. In this paper, the effects of PPAR agonists on metabolic functions were summarized with particular reference to their AMPK activity regulation

Distribution, cell volume and extracellular enzyme activities of heterotrophic bacteria near the mouth of Keum River, Korea.

Article信州大学理学部附属諏訪臨湖実験所報告 9: 61-67(1995)departmental bulletin pape

DOO-RE: A dataset of ambient sensors in a meeting room for activity recognition

With the advancement of IoT technology, recognizing user activities with machine learning methods is a promising way to provide various smart services to users. High-quality data with privacy protection is essential for deploying such services in the real world. Data streams from surrounding ambient sensors are well suited to the requirement. Existing ambient sensor datasets only support constrained private spaces and those for public spaces have yet to be explored despite growing interest in research on them. To meet this need, we build a dataset collected from a meeting room equipped with ambient sensors. The dataset, DOO-RE, includes data streams from various ambient sensor types such as Sound and Projector. Each sensor data stream is segmented into activity units and multiple annotators provide activity labels through a cross-validation annotation process to improve annotation quality. We finally obtain 9 types of activities. To our best knowledge, DOO-RE is the first dataset to support the recognition of both single and group activities in a real meeting room with reliable annotations

Fabrication of Optical Switching Patterns with Structural Colored Microfibers

Structural color was generated using electrospinning and hydrothermal growth of zinc oxide (ZnO). An aligned seed layer was prepared by electrospinning, and the hydrothermal growth time control was adjusted to generate various structural colors. The structural color changed according to the angle of the incident light. When the light was parallel to the direction of the aligned nanofibers, no pattern was observed. This pattern is referred to as an "optical switching pattern." Replication using polydimethylsiloxane (PDMS) also enabled the generation of structural colors; this is an attractive approach for mass production. Additionally, the process is quite tunable because additional syntheses and etching can be performed after the patterns have been fabricated.11Ysciescopu

Role of G{alpha}12 and G{alpha}13 as Novel Switches for the Activity of Nrf2, a Key Antioxidative Transcription Factor

G{alpha}12 and G{alpha}13 function as molecular regulators responding to extracellular stimuli. NF-E2-related factor 2 (Nrf2) is involved in a protective adaptive response to oxidative stress. This study investigated the regulation of Nrf2 by G{alpha}12 and G{alpha}13. A deficiency of G{alpha}12, but not of G{alpha}13, enhanced Nrf2 activity and target gene transactivation in embryo fibroblasts. In mice, G{alpha}12 knockout activated Nrf2 and thereby facilitated heme catabolism to bilirubin and its glucuronosyl conjugations. An oligonucleotide microarray demonstrated the transactivation of Nrf2 target genes by G{alpha}12 gene knockout. G{alpha}12 deficiency reduced Jun N-terminal protein kinase (JNK)-dependent Nrf2 ubiquitination required for proteasomal degradation, and so did G{alpha}13 deficiency. The absence of G{alpha}12, but not of G{alpha}13, increased protein kinase C {delta} (PKC {delta}) activation and the PKC {delta}-mediated serine phosphorylation of Nrf2. G{alpha}13 gene knockout or knockdown abrogated the Nrf2 phosphorylation induced by G{alpha}12 deficiency, suggesting that relief from G{alpha}12 repression leads to the G{alpha}13-mediated activation of Nrf2. Constitutive activation of G{alpha}13 promoted Nrf2 activity and target gene induction via Rho-mediated PKC {delta} activation, corroborating positive regulation by G{alpha}13. In summary, G{alpha}12 and G{alpha}13 transmit a JNK-dependent signal for Nrf2 ubiquitination, whereas G{alpha}13 regulates Rho-PKC {delta}-mediated Nrf2 phosphorylation, which is negatively balanced by G{alpha}12