Future development strategies for KODISA journals: overview of 2016 and strategic plans for the future

Purpose – With the rise of the fourth industrial revolution, it has converged with the existing industrial revolution to give shape to increased accessibility of knowledge and information. As a result, it has become easier for scholars to actively pursue and compile research in various fields. This current study aims to focus and assess the current standing of KODISA: the Journal of Distribution Science (JDS), International Journal of Industrial Distribution & Business (IJIDB), the East Asian Journal of Business Management (EAJBM), the Journal of Asian Finance, Economics and Business (JAFEB) in a rapidly evolving era. Novel strategies for creating the future vision of KODISA 2020 will also be examined. Research design, data, and methodology – The current research will analyze published journals of KODISA in order to offer a vision for the KODISA 2020 future. In part 1, this paper will observe the current address of the KODISA journal and its overview of past achievements. Next, part 2 will discuss the activities that will be needed for journals of KODISA, JDS, IJIDB, EAJBM, JAFEB to branch out internationally and significant journals will be statistically analyzed in part 3. The last part 4 will offer strategies for the continued growth of KODISA and visions for KODISA 2020. Results – Among the KODISA publications, IJIDB was second, JDS was 23rd (in economic publications of 54 journals), and EAJBM was 22nd (out of 79 publications in management field journals). This shows the high quality of the KODISA publication journals. According to 2016 publication analysis, JDS, IJIDB, etc. each had 157 publications, 15 publications, 16 publications, and 28 publications. In the case of JDS, it showed an increase of 14% compared to last year. Additionally, JAFEB showed a significant increase of 68%. This shows that compared to other journals, it had a higher rate of paper submission. IJIDB and EAJBM did not show any significant increases. In JDS, it showed many studies related to the distribution, management of distribution, and consumer behavior. In order to increase the status of the KODISA journal to a SCI status, many more international conferences will open to increase its international recognition levels. Second, the systematic functions of the journal will be developed further to increase its stability. Third, future graduate schools will open to foster future potential leaders in this field and build a platform for innovators and leaders. Conclusions – In KODISA, JDS was first published in 1999, and has been registered in SCOPUS February 2017. Other sister publications within the KODISA are preparing for SCOPUS registration as well. KODISA journals will prepare to be an innovative journal for 2020 and the future beyond

On the Explanation of Factors Affecting E-Commerce Adoption

The Internet has grown at a remarkable pace since the emergence of the World Wide Web in the early 1990s. While electronic commerce (e-Commerce) has become an important issue with the growth of the Internet, there has been insufficient empirical research concerning its adoption by Internet users. In this paper, we propose the e-Commerce Adoption Model (e-CAM), which attempts to examine important factors that predict a consumerís online purchasing behavior. e-CAM integrates the technology acceptance model with the theories of perceived risk to explain the adoption of e-Commerce. Specifically, we examine the impact of the following factors on the consumerís purchasing behavior: perceived ease of use, perceived usefulness, perceived risk with products/services, and perceived risk in the context of online transaction. We test the e-CAM model using the structural equation modeling technique. Most of the causal relationships between the constructs postulated by our model are well supported, accounting for 33.4% of the total variance in e-Commerce adoption. In sum, our study finds that all of the antecedent constructs directly and/or indirectly affect the consumerís adoption of e-Commerce. Therefore, the findings suggest that firms providing products/services through e- Commerce should consider these contextual factors in order to facilitate consumersí adoption behavior

Towards the Human Global Context: Does the Vision-Language Model Really Judge Like a Human Being?

As computer vision and NLP make progress, Vision-Language(VL) is becoming an important area of research. Despite the importance, evaluation metrics of the research domain is still at a preliminary stage of development. In this paper, we propose a quantitative metric "Equivariance Score" and evaluation dataset "Human Puzzle" to assess whether a VL model is understanding an image like a human. We observed that the VL model does not interpret the overall context of an input image but instead shows biases toward a specific object or shape that forms the local context. We aim to quantitatively measure a model's performance in understanding context. To verify the current existing VL model's capability, we sliced the original input image into pieces and randomly placed them, distorting the global context of the image. Our paper discusses each VL model's level of interpretation on global context and addresses how the structural characteristics influenced the results

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

Current Management and Future Strategies of Gastric Cancer

The overall prognosis of gastric cancer has gradually improved over the past decades with growing awareness of potential carcinogens, surveillance programs and early diagnosis, as well as advances in surgical techniques and multimodality treatments. Nevertheless, the outcome of advanced stage disease still remains poor with currently available treatments, and a worldwide consensus on the standard management thereof has not been established. To improve prognosis and quality of life in gastric cancer patients, both standardization and individualization of managements are imperative. Diagnostic tests and surgical procedures need to be further sophisticated and standardized based on more recent evidences from ongoing and future randomized controlled trials, while comprehensive management should be individualized to each patient. Future challenges lie with how to optimize personalized therapies by deciphering biological complexity of gastric cancer and incorporating molecular biomarkers in clinical practice to forecast prognosis and to guide targeted therapeutics in adjunct to current standards of care

Effect of Cooking on Radiation-induced Chemical Markers in Beef and Pork during Storage

Raw and cooked beef and pork loins were irradiated at 0 or 5 25 kGy. The radiation induced marker compounds, such as hydrocarbons, 2-alkylcyclobutanones and sulfur volatiles, were determined after 0 and 6 months of frozen storage. Two hydrocarbons [8-heptadecene (C17:1), 6,9- heptadecadiene (C17:2)] and two 2-alkylcyclobutanones [2- dodecylcyclobutanone (DCB), 2-tetradecylcyclobutanone (TCB)] were detected only in irradiated raw and cooked meats. Although pre-cooked irradiated meats produced more hydrocarbons and 2-alkylcyclobutanones than the irradiated cooked ones, the amounts of individual hydrocarbons and 2- alkylcyclobutanones, such as 8-heptadecene, 6,9- heptadecadiene, DCB, and TCB, were sufficient enough to detect whether the meat was irradiated or not. Dimethyl disulfide and dimethyl trisulfide were also detected only in irradiated meats, but dimethyl trisulfide disappeared after 6 months of frozen storage under oxygen-permeable packaging conditions. The results indicated that 8- heptadecene, 6,9-heptadecadiene, DCB, TCB and dimethyl disulfide, even though they were decreased with storage, could be used as marker compounds for the detection of irradiated beef and pork regardless of cooking under the frozen conditions for 6 months

t3t^3-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence

The variational autoencoder (VAE) typically employs a standard normal prior as a regularizer for the probabilistic latent encoder. However, the Gaussian tail often decays too quickly to effectively accommodate the encoded points, failing to preserve crucial structures hidden in the data. In this paper, we explore the use of heavy-tailed models to combat over-regularization. Drawing upon insights from information geometry, we propose $t^3$VAE, a modified VAE framework that incorporates Student's t-distributions for the prior, encoder, and decoder. This results in a joint model distribution of a power form which we argue can better fit real-world datasets. We derive a new objective by reformulating the evidence lower bound as joint optimization of KL divergence between two statistical manifolds and replacing with $\gamma$-power divergence, a natural alternative for power families. $t^3$VAE demonstrates superior generation of low-density regions when trained on heavy-tailed synthetic data. Furthermore, we show that $t^3$VAE significantly outperforms other models on CelebA and imbalanced CIFAR-100 datasets.Comment: ICLR 2024; 27 pages, 7 figures, 8 table

Evaluation of Radiation-induced Compounds in Irradiated Raw or Cooked Chicken Meat during Storage

The concentrations of hydrocarbons, 2-alkylcyclobutanones, and sulfur volatiles in irradiated (0, 5 kGy) chicken meats (raw, pre-cooked, and irradiatedcooked) were analyzed after 0 and 6 months of frozen storage (-40°C) under oxygen permeable packaging conditions. Two hydrocarbons [8-heptadecene (C17:1) and 6,9-heptadecadiene (C17:2)], two 2-alkylcyclobutanones [2-dodecylcyclobutanone (DCB) and 2-tetradecylcyclobutanone (TCB)], and dimethyl disulfide were determined as radiation-induced detection markers in the irradiated raw and cooked chicken meats. Although, irradiated-cooked samples produced less hydrocarbons and 2-alkylcyclobutanones than pre-cooked irradiated ones, the amount of individual hydrocarbons or 2-alkylcyclobutanones was still sufficient enough to detectradiation treatment even after 6 months of storage at -40°C. Among sulfur volatiles, only dimethyl disulfide were found in meat after 6 months of storage indicating it has potential to be used an irradiation detection marker for frozen-stored meats under oxygen permeable packaging conditions