Learning Character-level Compositionality with Visual Features

Previous work has modeled the compositionality of words by creating character-level models of meaning, reducing problems of sparsity for rare words. However, in many writing systems compositionality has an effect even on the character-level: the meaning of a character is derived by the sum of its parts. In this paper, we model this effect by creating embeddings for characters based on their visual characteristics, creating an image for the character and running it through a convolutional neural network to produce a visual character embedding. Experiments on a text classification task demonstrate that such model allows for better processing of instances with rare characters in languages such as Chinese, Japanese, and Korean. Additionally, qualitative analyses demonstrate that our proposed model learns to focus on the parts of characters that carry semantic content, resulting in embeddings that are coherent in visual space.Comment: Accepted to ACL 201

Building IT Change-Readiness Capabilities in the Mobile Service Delivery: A Case Study in the Exhibition Industry

The mobile technology is applied in more and more aspects in our life. It is used not only in communication, but also business activities. As the great progress of wireless transmission, commercial information can be delivered to one’s handheld devices immediately, no matter where he or she is. Many companies attempt to introduce such convenient technology as their new strategy to perform their real-time services. Individual-oriented information delivery is also a beneficial function for these companies. This research will examine the organization star-model to find out the critical factors how an organization successfully adopts mobile technology. In-depth interviews will be provided for validation

All the wiser: Fake news intervention using user reading preferences

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

Introductory Chapter: Land Use Change Ecosystem Services and Tropical Forests

Meteorology & climatolog

Role of interface morphology on the martensitic transformation in pure Fe

Using classical molecular dynamics simulations, we study austenite to ferrite phase transformation in iron, focusing on the role of interface morphology. We compare two different morphologies; a \textit{flat} interface in which the two phases are joined according to Nishiyama-Wasserman orientation relationship vs. a \textit{ledged} one, having steps similar to the vicinal surface. We identify the atomic displacements along a misfit dislocation network at the interface leading to the phase transformation. In case of \textit{ledged} interface, stacking faults are nucleated at the steps, which hinder the interface motion, leading to a lower mobility of the inter-phase boundary, than that of flat interface. Interestingly, we also find the temperature dependence of the interface mobility to show opposite trends in case of \textit{flat} vs. \textit{ledged} boundary. We believe that our study is going to present a unified and comprehensive view of martensitic transformation in iron with different interface morphology, which is lacking at present, as \textit{flat} and \textit{ledged} interfaces are treated separately in the existing literature.Comment: 10 pages, 9 figure

Theoretical study of the ammonia nitridation rate on an Fe (100) surface: A combined density functional theory and kinetic Monte Carlo study

Ammonia (NH[subscript 3]) nitridation on an Fe surface was studied by combining density functional theory (DFT) and kinetic Monte Carlo (kMC) calculations. A DFT calculation was performed to obtain the energy barriers (E[subscript b]) of the relevant elementary processes. The full mechanism of the exact reaction path was divided into five steps (adsorption, dissociation, surface migration, penetration, and diffusion) on an Fe (100) surface pre-covered with nitrogen. The energy barrier (E[subscript b]) depended on the N surface coverage. The DFT results were subsequently employed as a database for the kMC simulations. We then evaluated the NH[subscript 3] nitridation rate on the N pre-covered Fe surface. To determine the conditions necessary for a rapid NH[subscript 3] nitridation rate, the eight reaction events were considered in the kMC simulations: adsorption, desorption, dissociation, reverse dissociation, surface migration, penetration, reverse penetration, and diffusion. This study provides a real-time-scale simulation of NH[subscript 3] nitridation influenced by nitrogen surface coverage that allowed us to theoretically determine a nitrogen coverage (0.56 ML) suitable for rapid NH[subscript 3] nitridation. In this way, we were able to reveal the coverage dependence of the nitridation reaction using the combined DFT and kMC simulations.Korea (South). Ministry of Education, Science and Technology (MEST) (National Research Foundation of Korea. 2011-0028612