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

The Concept of Public Interest Demonstrated in Korean Court Precedents

The concept of public interest is functioning as a topos in Korean public law discussions. However, no established definition of the term is presented in any books or papers on administrative law. An attempt to define a concrete and specified concept of public interest may turn out to be in vain because of the incommensurability of its value. In such case, the best way to get closer to the substance of the concept will be to search for the many and diverse ways the term public interest is used in real court precedents. This is because the court rulings are the result of many efforts to reach the best balancing point of conflicting interests. In Korean court precedents, many diverse explanations on public interest have been presented. For instance, the public interest has been illustrated as the interest of many and unspecified persons, general social welfare, environmental interest, the well functioning of state run organizations, interests related to traffic and transportation, interest related to education, the moral interest of our society, and interests related to basic human rights

Fundamental Chemistry Advances Toward the Development of Degradable Polymer-Based Nanoparticles for the Treatment of Infectious Diseases

Microorganisms, including bacteria, viruses, fungi, or parasites, give rise to infectious diseases, which can spread between people, and can even transfer from animals or insects to humans. Infectious diseases are common, sometimes fatal, health issues. To date, the treatment of infectious diseases has largely relied on antibiotics. However, the therapeutic outcomes of current treatments need to be enhanced due to the emergence of drug-resistant microorganisms and the decline in the development of new antibiotics. Nanotechnology could help improve the efficacy of currently available antibiotics via changing the pharmacokinetics and biodistribution of drugs, which could enhance bioavailability, reduce side effects, help overcome physical and biological barriers for the efficient delivery to the site of infection, and so on. This dissertation aims to explore a novel treatment method to treat infectious diseases using degradable polymer-based nanoparticles. In a first project, bacterial adhesin, FimHA-targeted polymeric nanoparticles were developed for the delivery of antimicrobials to bacteria hiding inside the cells by mimicking the bacterial mode of cell invasion in order to treat and eradicate recurrent urinary tract infections. Amidation between carboxylic acids located in the shell of the poly(acrylic acid)-block-polystyrene-based polymeric nanoparticles and primary amine groups of lysine residues on FimHA was employed as the conjugation method. We prepared FimHA-polymeric nanoparticle conjugates with varying amounts of adhesins on the surface without free and/or physically-associated proteins under the improved coupling conditions. In a second direction involving a series of projects, functional polycarbonates were developed in order to expand the pool of degradable polymers and their self-assembled nanostructures, which can be utilized as drug-delivery vehicles. Degradable polycarbonates were synthesized by metal-free organocatalytic ring-opening polymerization of cyclic carbonate monomers. Postpolymerization modifications were also employed to introduce new functionalities onto the same degradable polymer backbone. Water-soluble polycarbonate formed a hydrophilic shell domain of polymeric nanostructures, and reactive aldehyde- and vinyl ether-functionalized polycarbonates were synthesized and their potential for drug delivery systems were demonstrated. In a third direction, advanced mechanistic understanding of organocatalytic ring-opening polymerization (ROP), which is widely used for syntheses of degradable polymers, was gained by specialized NMR spectroscopy studies. The collection of 13C NMR data in real time during polymerization was enhanced via hyperpolarization of nuclear spins. The “living” characteristics of ring-opening polymerization enabled the observation of NMR resonances associated with an intermediate formed during ROP

The Protection of Private Information in the Internet under Tort Law in Korea: From the Perspectives of Three Major Legal Conceptions of Law

This paper is a follow-up paper of my previous paper on the issue of protection of private information in the Internet under tort law. In the previous paper, I reviewed the facts, legal issues, background information, and policy issues in the lineage II case, coming to the conclusion that the process of finding law by the judges in a new case which does not have any convention or precedent inevitably entails the policy makings of the judiciary. Based on the factual and legal foundations of the previous paper, in this paper, I made a new effort of analyzing the three major legal conceptions of modern jurisprudence from the perspective of finding the law in hard cases and applying the legal conceptions to solving the lineage II case. The three legal conceptions I referred are conventionalism, legal pragmatism, and integrity in law. By reviewing and comparing each of the three legal conceptions, I came to the conclusion that legal pragmatism is the most candid and suitable legal methodology in dealing with the recent private information leakage lawsuits in Korea

Emerging I&C Technologies Under the Shifting Regulatory Environment in South Korea

The role of Probabilistic Safety Assessment (PSA) has been supplementary and Risk-Informed Applications (RIAs) based on the insight from PSA has also been utilized limitedly in the licensing process for Nuclear Power Plants (NPPs) in South Korea. However, as the technical significance of PSA is getting increased, PSA has become a mandatory part of Safety Analysis Reports and Periodic Safety Review. It is worthwhile to highlight the role of emerging Instrumentation and Control (I&C) technologies including human-machine interface (HMI) in developing more credible and realistic PSA models. Particularly, it is expected that the information technology (i.e. software) embedded in digital I&C can adjust over- and under conservatism in analyzing risk. In this study, authors proposed the cases which would be able to significantly reduce risk if advanced I&C supported by information technologies is applied. In regard, the several enabling techniques and their effects are proposed. In order to improve the commercial competitiveness of NPPs, the need of collaboration and synergetic outcome of I&C, HMI and PSA should be emphasized

Rational Choice in Modern Administrative Law: With the Behavioral Economics Approach to the Two Major Cases in Korea

In modern regulatory state, the government has to deal with the so-called risk issues. We are all surrounded by many different types of risks like climate change, bird flu, mad cow disease, genetically modified food, nuclear energy, etc., just name a few. The reason why modern administrative law is under a big challenge in dealing with those risk issues is that the government has to make policy choice under uncertainty. Compared to the traditional role of state like police administration and social benefit administration, the role of government in risk administration is much complicated and dynamic. In this paper, I would like to address the issue of how people and governments in modern administrative state can reach rational choice in dealing with risk management. The idea of democracy is based upon the rational choice of each individual participating political process. However, if, for some reason, people cannot fully understand what is going on and what kind of options they have, then, it is not easy for them to make rational choice in expressing their political preferences. Which naturally brings about the difficulty of government in setting appropriate policy measures in modern administrative law. With the interdisciplinary contribution of psychology, economics, and law, we now know that there are several human behavioral biases that are affecting the process of rational choice of individuals in forming their political preferences. Availability heuristic, cascading effect, group polarization, framing effect, hindsight bias, etc. are the major examples of those behavioral biases. In this paper, I will try to show how those behavioral biases are affecting the process of individuals political preference formation, explain what should be the main concern of modern administrative law to minimize the adverse effects of those possible irrationality of people in building up social preference function, and provide my own view on those topics

Minority-Oriented Vicinity Expansion with Attentive Aggregation for Video Long-Tailed Recognition

A dramatic increase in real-world video volume with extremely diverse and emerging topics naturally forms a long-tailed video distribution in terms of their categories, and it spotlights the need for Video Long-Tailed Recognition (VLTR). In this work, we summarize the challenges in VLTR and explore how to overcome them. The challenges are: (1) it is impractical to re-train the whole model for high-quality features, (2) acquiring frame-wise labels requires extensive cost, and (3) long-tailed data triggers biased training. Yet, most existing works for VLTR unavoidably utilize image-level features extracted from pretrained models which are task-irrelevant, and learn by video-level labels. Therefore, to deal with such (1) task-irrelevant features and (2) video-level labels, we introduce two complementary learnable feature aggregators. Learnable layers in each aggregator are to produce task-relevant representations, and each aggregator is to assemble the snippet-wise knowledge into a video representative. Then, we propose Minority-Oriented Vicinity Expansion (MOVE) that explicitly leverages the class frequency into approximating the vicinity distributions to alleviate (3) biased training. By combining these solutions, our approach achieves state-of-the-art results on large-scale VideoLT and synthetically induced Imbalanced-MiniKinetics200. With VideoLT features from ResNet-50, it attains 18% and 58% relative improvements on head and tail classes over the previous state-of-the-art method, respectively.Comment: Accepted to AAAI 2023. Code is available at https://github.com/wjun0830/MOV

ShinyCore: An R/Shiny program for establishing core collection based on single nucleotide polymorphism data

Background: Managing and investigating all available genetic resources are challenging. As an alternative, breeders and researchers use core collection—a representative subset of the entire collection. A good core is characterized by high genetic diversity and low repetitiveness. Among the several available software, GenoCore uses a coverage criterion that does not require computationally expensive distance-based metrics. Results: ShinyCore is a new method to select a core collection through two phases. The first phase uses the coverage criterion to quickly attain a fixed coverage, and the second phase uses a newly devised score (referred to as the rarity score) to further enhance diversity. It can attain a fixed coverage faster than a currently available algorithm devised for the coverage criterion, so it will benefit users who have big data. ShinyCore attains the minimum coverage specified by a user faster than GenoCore, and it then seeks to add entries with the rarest allele for each marker. Therefore, measures of genetic diversity and distance can be improved. Conclusion: Although GenoCore is a fast algorithm, its implementation is difficult for those unfamiliar with R, ShinyCore can be easily implemented in Shiny with RStudio and an interactive web applet is available for those who are not familiar with programming languages