Japanese Sentiment Classification with Stacked Denoising Auto-Encoder using Distributed Word Representation

Traditional sentiment classification methods often require polarity dictionaries or crafted features to utilize machine learning. How-ever, those approaches incur high costs in the making of dictionaries and/or features, which hinder generalization of tasks. Ex-amples of these approaches include an ap-proach that uses a polarity dictionary that can-not handle unknown or newly invented words and another approach that uses a complex model with 13 types of feature templates. We propose a novel high performance sentiment classification method with stacked denoising auto-encoders that uses distributed word rep-resentation instead of building dictionaries or utilizing engineering features. The results of experiments conducted indicate that our model achieves state-of-the-art performance in Japanese sentiment classification tasks.

Natural Language Generation for Advertising: A Survey

Natural language generation methods have emerged as effective tools to help advertisers increase the number of online advertisements they produce. This survey entails a review of the research trends on this topic over the past decade, from template-based to extractive and abstractive approaches using neural networks. Additionally, key challenges and directions revealed through the survey, including metric optimization, faithfulness, diversity, multimodality, and the development of benchmark datasets, are discussed

Surface Plasmon Enhancement on Infrared Photodetection

AbstractInAsSb based infrared photodetector is an alternative to the existing HgCdTe, PbSnTe, and InSb counterparts, but its room temperature performance is still relatively poor. One of the ways to improve its performance is through surface plasmon, which provides near field confinement that leads to enhancement in light matter interaction. In this work, the role of each parameter of two dimensional metallic hole arrays in plasmonic enhancement is studied in details, such as the periodicity of hole array, hole diameter and metal film thickness. The plasmonic resonances and their corresponding electric field distributions are comprehensively studied in finite difference time domain simulation, which also would serve as a guide for designing surface plasmon enhanced InAsSb infrared detector with high quantum efficiency and signal-to-noise ratio

Microstructure and texture evolutions in FeCrAl cladding tube during pilger processing

The microstructure of FeCrAl cladding tubes depends on the fabricating process history. In this study, the microstructural characteristics of wrought FeCrAl alloys during industrial pilger processing into thin-walled tubes were investigated. The hot extruded tube showed ∼100 μm equiaxed grains with weak α∗-fiber in {h11}<1/h12> texture, while pilger rolling process change the microstructure to fragmented and elongated grains along the rolling direction. The pilgered textures could be predicted with the VPSC model. The inter-pass annealing at 800–850 \ub0C for 1 h results in recovery and recrystallization of the ferric matrix and restoration of ductility. The final finished tube shows fine recrystallized grains (∼11 μm) with dominant γ-fiber in three dimensions. Pilger rolling enhanced α-fiber while annealing reduced α-fiber and enhanced γ-fiber. Microstructural evolution in the Laves precipitates followed the sequence of faceted needle-like → spherical → faceted ellipsoidal. Thermomechanical processing resulted in cladding tubes with an area fraction of ∼5% and a number density of 5 7 10−11 m−2 in Laves precipitates, which is half that of the first-pilgered tube. Laves precipitates pin the grain boundaries to control the microstructure and prevent grain coarsening

Broker-supported and constraint-based infrastructure for collaborative systems

A collaborative system is much more complicated than a single user system due to a variety of collaboration capability, distribution features and interaction requirements. It is desirable for such a system to allow extensible sharing regardless of location and heterogeneity. Concurrent interactions with shared objects require facilities to provide real-time collaboration awareness and maintain system consistency. This thesis is a step towards developing generic models and enabling infrastructure to provide this support so as to ease the construction of collaborative systems. In this dissertation, we propose: (1) a hierarchical session model to provide a flexible sharing capability so that collaborations become extensible and integrable, (2) a distribution model to enable communication among heterogeneous collaboration participants or application clients/servers, and (3) an object-based constraint management model which supports constraint relationships among object methods as well as object data fields; it integrates constraint solving methods with concurrency control, so that the constraint relationships can be maintained even in a heterogeneous environment and under concurrent interactions. Based on these models, we have designed a broker-supported and constraint-based enabling infrastructure which includes the necessary facilities for collaboration control, distribution control, and interaction control in collaborative systems. We have further implemented our design in the Shastra distributed and collaborative environment. Applications developed in Shastra demonstrate how the models and the infrastructure facilitate the construction of collaborative systems

Brokered Collaborative Infrastructure for CSCW

We demonstrate the advantages of a distributed collaborative system for CSCW, and highlight the requirements of brokered support for such a system. We also demonstrate how we have augmented the infrastructure ofaprototype CSCW environment called SHASTRA to accommodate brokered collaboration. Several applications and possible scenarios of CSCW with brokered cooperative system are also presented. We describe how brokers can be used to exploit plurality and commonality of tasks in a cooperative setting, improving performance for the entire system