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

Korean value systems and managerial practices

Human beings are by nature sociocultural creatures. Our behavior is influenced not only by traditional value systems but also by contemporary education and training. In the same manner, the managerial practices of Korean managers are strongly influenced by the norms and value systems of the traditional Korean society. But, as the society changes from an agrarian society to an industrialized one, so does the behavior of Korean managers. This chapter focuses on the process of this change. More specifically, it will look at the effects of traditional value systems and those of industrialization on Korean managerial practices

Crossmodal Attentive Skill Learner

This paper presents the Crossmodal Attentive Skill Learner (CASL), integrated with the recently-introduced Asynchronous Advantage Option-Critic (A2OC) architecture [Harb et al., 2017] to enable hierarchical reinforcement learning across multiple sensory inputs. We provide concrete examples where the approach not only improves performance in a single task, but accelerates transfer to new tasks. We demonstrate the attention mechanism anticipates and identifies useful latent features, while filtering irrelevant sensor modalities during execution. We modify the Arcade Learning Environment [Bellemare et al., 2013] to support audio queries, and conduct evaluations of crossmodal learning in the Atari 2600 game Amidar. Finally, building on the recent work of Babaeizadeh et al. [2017], we open-source a fast hybrid CPU-GPU implementation of CASL.Comment: International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2018, NIPS 2017 Deep Reinforcement Learning Symposiu

Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network

Methods based on convolutional neural network (CNN) have demonstrated tremendous improvements on single image super-resolution. However, the previous methods mainly restore images from one single area in the low resolution (LR) input, which limits the flexibility of models to infer various scales of details for high resolution (HR) output. Moreover, most of them train a specific model for each up-scale factor. In this paper, we propose a multi-scale super resolution (MSSR) network. Our network consists of multi-scale paths to make the HR inference, which can learn to synthesize features from different scales. This property helps reconstruct various kinds of regions in HR images. In addition, only one single model is needed for multiple up-scale factors, which is more efficient without loss of restoration quality. Experiments on four public datasets demonstrate that the proposed method achieved state-of-the-art performance with fast speed

Juvenile idiopathic arthritis: Diagnosis and differential diagnosis

Juvenile idiopathic arthritis (JIA) is comprised of a heterogeneous group of several disease subtypes that are characterized by the onset of arthritis before the age of 16 years and has symptoms lasting at least 6 weeks. The previous classification of JIA included seven different categories, whereas its current classification was compiled by the International League of the Association for Rheumatology, and replaced the previous terms of "juvenile chronic arthritis" and "juvenile rheumatoid arthritis," which were used in Europe or North America, respectively, with the single nomenclature of JIA. As mentioned above, JIA is defined as arthritis of unknown etiology that manifests itself before the age of 16 years and persists for at least 6 weeks, while excluding other known conditions. The clinical symptoms of JIA can be quite variable. Several symptoms that are characteristic of arthritis are not necessarily diagnostic of JIA and may have multiple etiologies that can be differentiated with careful examination of patient history. The disease may develop over days or sometimes weeks, thereby making the diagnosis difficult at the time of presentation. To make a clinical diagnosis of JIA, the first step is to exclude arthritis with known etiologies. Of note, late treatment due to excessive delay of diagnosis can cause severe damage to joints and other organs and impair skeletal maturation. Therefore, early detection of JIA is critical to ensure prompt treatment and to prevent long-term complications including the likelihood of disability in childhood

Metabolomics profiling: a potential tool for predicting immunoglobulin A nephropathy progression

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