Domain-Specific Web Search with Keyword Spices

Domain-specific web search engines are effective tools for reducing the difficulty in acquiring information from the web. Existing methods for building domain-specific web search engines require human expertise or specific facilities. However, we can build a domain-specific search engine simply by adding domain specific keywords called "keyword spices" to the user's input query and forwarding it to a generalpurpose web search engine. Keyword spices can be effectively discovered from web documents using machine learning technologies. This paper will describe domain-specific web search engines that use keyword spices for locating cooking recipes, restaurants, and used cars. To fully automate the construction of domain-specific search engines, we also present trials of using web pages in an existing web directory as training examples

Predicate Classification Using Optimal Transport Loss in Scene Graph Generation

In scene graph generation (SGG), learning with cross-entropy loss yields biased predictions owing to the severe imbalance in the distribution of the relationship labels in the dataset. Thus, this study proposes a method to generate scene graphs using optimal transport as a measure for comparing two probability distributions. We apply learning with the optimal transport loss, which reflects the similarity between the labels in terms of transportation cost, for predicate classification in SGG. In the proposed approach, the transportation cost of the optimal transport is defined using the similarity of words obtained from the pre-trained model. The experimental evaluation of the effectiveness demonstrates that the proposed method outperforms existing methods in terms of mean Recall@50 and 100. Furthermore, it improves the recall of the relationship labels scarcely available in the dataset

Experimental Demonstration of Adaptive Quantum State Estimation

The first experimental demonstration of an adaptive quantum state estimation (AQSE) is reported. The strong consistency and asymptotic efficiency of AQSE have been mathematically proven [ A. Fujiwara J. Phys. A 39 12489 (2006)]. In this Letter, the angle of linear polarization of single photons, the phase parameter between the right and the left circularly polarization, is estimated using AQSE, and the strong consistency and asymptotic efficiency are experimentally verified. AQSE will provide a general useful method in both quantum information processing and metrology.Comment: 5pages, 4figure

Crowdsourcing chart digitizer : task design and quality control for making legacy open data machine-readable

Despite recent open data initiatives in many countries, a significant percentage of the data provided is in non-machine-readable formats like image format rather than in a machine-readable electronic format, thereby restricting their usability. Various types of software for digitizing data chart images have been developed. However, such software is designed for manual use and thus requires human intervention, making it unsuitable for automatically extracting data from a large number of chart images. This paper describes the first unified framework for converting legacy open data in chart images into a machine-readable and reusable format by using crowdsourcing. Crowd workers are asked not only to extract data from an image of a chart but also to reproduce the chart objects in a spreadsheet. The properties of the reproduced chart objects give their data structures, including series names and values, which are useful for automatic processing of data by computer. Since results produced by crowdsourcing inherently contain errors, a quality control mechanism was developed that improves accuracy by aggregating tables created by different workers for the same chart image and by utilizing the data structures obtained from the reproduced chart objects. Experimental results demonstrated that the proposed framework and mechanism are effective. The proposed framework is not intended to compete with chart digitizing software, and workers can use it if they feel it is useful for extracting data from charts. Experiments in which workers were encouraged to use such software showed that even if workers used it, the extracted data still contained errors. This indicates that quality control is necessary even if workers use software to extract data from chart images

Structural and kinetic modification of aqueous hydroxypropylmethylcellulose(HPMC) induced by electron beam irration

Electron beam was irradiated on 10% and 20% hydroxypropylmethylcellulose (HPMC) aqueous solutions with different doses to make gel films. As increasing dose, the gel fraction of the film increased sharply above a critical dose and then decreased gradually after passing a maximum. The scission/cross-linking ratio and the critical dose were determined using the Charlesby-Rosiak equation as 0.52 and 9 kGy for 10% gel and 0.43 and 14 kGy for 20% gel, respectively. The gel fraction for 20% HPMC film was lower at low dose and higher at high dose than that for 10% film. The behavior of the swelling ratio of the gel film was just opposite to that of the gel fraction. The cross-linking density of the gel estimated from the Flory theory linearly increased with irradiation dose at low dose, passed a maximum around 100 and 160 kGy for 10% and 20% films, respectively, and decreased at high dose. These results suggest the competition of scission and cross-linking induced by indirect effect of irradiation. Dielectric relaxation measurement by time domain reflectometry and RF impedance/material analyzer revealed two characteristic relaxations of chain motions around 100MHz and of orientation of free water around 20GHz. From the dose dependence of the relaxation parameters determined by fitting to a combined equation of Cole-Cole type and KWW type, a coupling of motions of HPMC molecules and water molecules was strongly suggested. The critical dose for gelation was coincident with the dose for the maximum of t h and the minimum of Deh together with the minimum of t m and the maximum of Dem, where t h and Deh denote the relaxation time and the relaxation strength for free water molecular motion and t m and Dem the corresponding ones for HPMC molecular motion. The characteristic behavior was discussed in terms of the increase of affinity between HPMC and water and the constrained molecular motion in the gel network

Variations of cosmic noise absorption (CNA) by energetic electron precipitation (EEP) and changes of the auroral morphology

The Tenth Symposium on Polar Science/Ordinary sessions: [OS] Space and upper atmospheric sciences, Wed. 4 Dec. / Institute of Statistics and Mathematics (ISM) Seminar room 2 (D304) (3rd floor

The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism

We present scalable hybrid-parallel algorithms for training large-scale 3D convolutional neural networks. Deep learning-based emerging scientific workflows often require model training with large, high-dimensional samples, which can make training much more costly and even infeasible due to excessive memory usage. We solve these challenges by extensively applying hybrid parallelism throughout the end-to-end training pipeline, including both computations and I/O. Our hybrid-parallel algorithm extends the standard data parallelism with spatial parallelism, which partitions a single sample in the spatial domain, realizing strong scaling beyond the mini-batch dimension with a larger aggregated memory capacity. We evaluate our proposed training algorithms with two challenging 3D CNNs, CosmoFlow and 3D U-Net. Our comprehensive performance studies show that good weak and strong scaling can be achieved for both networks using up 2K GPUs. More importantly, we enable training of CosmoFlow with much larger samples than previously possible, realizing an order-of-magnitude improvement in prediction accuracy.Comment: 12 pages, 10 figure

Sarcomere Imaging by Quantum Dots for the Study of Cardiac Muscle Physiology

We here review the use of quantum dots (QDs) for the imaging of sarcomeric movements in cardiac muscle. QDs are fluorescence substances (CdSe) that absorb photons and reemit photons at a different wavelength (depending on the size of the particle); they are efficient in generating long-lasting, narrow symmetric emission profiles, and hence useful in various types of imaging studies. Recently, we developed a novel system in which the length of a particular, single sarcomere in cardiomyocytes can be measured at ~30 nm precision. Moreover, our system enables accurate measurement of sarcomere length in the isolated heart. We propose that QDs are the ideal tool for the study of sarcomere dynamics during excitation-contraction coupling in healthy and diseased cardiac muscle