DeepStory: Video Story QA by Deep Embedded Memory Networks

Question-answering (QA) on video contents is a significant challenge for achieving human-level intelligence as it involves both vision and language in real-world settings. Here we demonstrate the possibility of an AI agent performing video story QA by learning from a large amount of cartoon videos. We develop a video-story learning model, i.e. Deep Embedded Memory Networks (DEMN), to reconstruct stories from a joint scene-dialogue video stream using a latent embedding space of observed data. The video stories are stored in a long-term memory component. For a given question, an LSTM-based attention model uses the long-term memory to recall the best question-story-answer triplet by focusing on specific words containing key information. We trained the DEMN on a novel QA dataset of children's cartoon video series, Pororo. The dataset contains 16,066 scene-dialogue pairs of 20.5-hour videos, 27,328 fine-grained sentences for scene description, and 8,913 story-related QA pairs. Our experimental results show that the DEMN outperforms other QA models. This is mainly due to 1) the reconstruction of video stories in a scene-dialogue combined form that utilize the latent embedding and 2) attention. DEMN also achieved state-of-the-art results on the MovieQA benchmark.Comment: 7 pages, accepted for IJCAI 201

Mathematical vibration modeling for an electrostatic precipitator system

The rapping acceleration of collecting plates in electrostatic precipitator system determines the dust- rapping performance of electromagnetic vibration exciter. To maximize the acceleration, the resonance phenomena needs to be driven by matching the mechanical natural frequency of the electrostatic precipitator system and the input frequency of electric current which energizes the electromagnetic vibrator. In this paper, the dust collecting plates and the electromagnetic vibration exciter in electrostatic precipitator system are vibration-modeled mathematically to characterize the resonance frequency. The effective mass and stiffness for each mode of the collecting plates are calculated using finite elements analysis and the natural frequency are computed by the method of least error square. In addition, the effective mass and stiffness of the exciter are computed. Then, the whole electrostatic precipitator system is analyzed. A frequency response analysis based on a sine sweep signal experiment is performed on a prototype for verification of calculated theoretical resonance frequency

Quantitative agreement of Dzyaloshinskii-Moriya interactions for domain-wall motion and spin-wave propagation

The magnetic exchange interaction is the one of the key factors governing the basic characteristics of magnetic systems. Unlike the symmetric nature of the Heisenberg exchange interaction, the interfacial Dzyaloshinskii-Moriya interaction (DMI) generates an antisymmetric exchange interaction which offers challenging opportunities in spintronics with intriguing antisymmetric phenomena. The role of the DMI, however, is still being debated, largely because distinct strengths of DMI have been measured for different magnetic objects, particularly chiral magnetic domain walls (DWs) and non-reciprocal spin waves (SWs). In this paper, we show that, after careful data analysis, both the DWs and SWs experience the same strength of DMI. This was confirmed by spin-torque efficiency measurement for the DWs, and Brillouin light scattering measurement for the SWs. This observation, therefore, indicates the unique role of the DMI on the magnetic DW and SW dynamics and also guarantees the compatibility of several DMI-measurement schemes recently proposed.Comment: 24 pages, 5 figure

Cases of ethical violation in research publications: through editorial decision making process

Purpose – To improve and strengthen existing publication and research ethics, KODISA has identified and presented various cases which have violated publication and research ethics and principles in recent years. The editorial office of KODISA has been providing and continues to provide advice and feedback on publication ethics to researchers during peer review and editorial decision making process. Providing advice and feedback on publication ethics will ensure researchers to have an opportunity to correct their mistakes or make appropriate decisions and avoid any violations in research ethics. The purpose of this paper is to identify different cases of ethical violation in research and inform and educate researchers to avoid any violations in publication and research ethics. Furthermore, this article will demonstrate how KODISA journals identify and penalize ethical violations and strengthens its publication ethics and practices. Research design, data and methodology – This paper examines different types of ethical violation in publication and research ethics. The paper identifies and analyzes all ethical violations in research and combines them into five general categories. Those five general types of ethical violations are thoroughly examined and discussed. Results – Ethical violations of research occur in various forms at regular intervals; in other words, unethical researchers tend to commit different types of ethical violations repeatedly at same time. The five categories of ethical violation in research are as follows: (1) Arbitrary changes or additions in author(s) happen frequently in thesis/dissertation related publications. (2) Self plagiarism, submitting same work or mixture of previous works with or without using proper citations, also occurs frequently, but the most common type of plagiarism is changing the statistical results and using them to present as the results of the empirical analysis; (3) Translation plagiarism, another ethical violation in publication, is difficult to detect but occurs frequently; (4) Fabrication of data or statistical analysis also occurs frequently. KODISA requires authors to submit the results of the empirical analysis of the paper (the output of the statistical program) to prevent this type of ethical violation; (5) Mashup or aggregator plagiarism, submitting a mix of several different works with or without proper citations without alterations, is very difficult to detect, and KODISA journals consider this type of plagiarism as the worst ethical violation. Conclusions – There are some individual cases of ethical violation in research and publication that could not be included in the five categories presented throughout the paper. KODISA and its editorial office should continue to develop, revise, and strengthen their publication ethics, to learn and share different ways to detect any ethical violations in research and publication, to train and educate its editorial members and researchers, and to analyze and share different cases of ethical violations with the scholarly community