• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.4
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• pp.313-332
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• 2014

With the increased creation, distribution, and use of image in context of the development of digital technologies and internet, research endeavors have accumulated drastically. As two dominant aspects of image retrieval have been considered content-based and concept-based image retrieval, concept-based image retrieval has been focused in the field of Library and Information Science. This study aims to systematically review the accumulated research of image retrieval from the perspective of LIS field. In order to achieve the purpose of this study, two data sets were prepared: a total of 282 image retrieval research papers from Web of Science, and a total of 35 image retrieval research from DBpia in Kore for comparison. For data analysis, systematic review methodology was utilized with bibliographic analysis of individual research papers in the data sets. The findings of this study demonstrated that two sub-areas, image indexing and description and image needs and image behavior, were dominant. Among these sub-areas, the results indicated that there were emerging areas such as collective indexing, image retrieval in terms of multi-language and multi-culture environments, and affective indexing and use. For the user-centered image retrieval research, college and graduate students were found prominent user groups for research while specific user groups such as medical/health related users, artists, and museum users were found considerably. With the comparison with the distribution of sub-areas of image retrieval research in Korea, considerable similarities were found. The findings of this study expect to guide research directions and agenda for future.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.49-60
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• 2019

With the appearance of self-driving cars and electric cars, the automobile industry is rapidly changing. In the midst of these changes, HMI studies are becoming more important as to how the driver obtains safety and convenience with controlling the vehicle. This study sought to understand how automobile manufacturers understand the driving situation, and how they define and limit driver interaction. For this, prior studies about HMI were reviewed and 15 participants performed an on-road study to drive vehicles from five manufacturers with using their interfaces. The results of the study confirmed that buttons and switches that are easily controlled by the user while driving were different from manufacturer to manufacturer. And there are some buttons that are more intensively controlled and others that are difficult to control while driving. It was able to derive 'selection and concentration' from Audi's vehicle, 'optimization of the driving ' from BMW's, 'simple and minimize' from Benz's vehicle, 'remove the manual distraction' from the vehicle of Lexus, and 'visual stability' from KIA's vehicle as the distinctive keywords for the HMI. This shows that each manufacturer has a different definition and interpretation of the driver's driving control area. This study has a distinct value in that it has identified the characteristics of vehicle-specific HMI in actual driving conditions, which is not apparent in appearance. It is expected that this research approach can be useful to see differences in interaction through actual driving despite changes in driving environment such as vehicle platooning and self-driving technology.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.543-559
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• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• Journal of Life Science
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• v.31 no.2
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• pp.248-255
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• 2021

Mammary gland tumors are one of the most common cancers in female dogs, and there are various types of cells depending on the tumor type. Complex carcinoma consists of a combination of luminal epithelial and myoepithelial cells with intra-tumoral heterogeneity. However, the origins of these tumor cells and their effects on the malignancies of tumors have not been identified. Recently, it has been reported that cancer stem cells, identified in several types of human tumors, are involved in tumor heterogeneity and may also contribute to malignancies such as tumor recurrence and metastasis. Interestingly, cancer stem cells share several abilities of self-renewal and cell differentiation into multiple types of cancer cells, but they have abnormal genetic mutation and signal transduction pathways to regulate the maintenance of stem cell characters. Moreover, it is known that these cell populations contribute to cell metastasis as well as cell resistance against chemo- and radio-therapeutics that promote tumor recurrence. The existence of cancer stem cells might explain the intra-tumoral heterogeneity and cancer aggressiveness during tumorigenesis in canine mammary gland tumors. This review summarizes the characteristics and types of canine mammary gland tumors, the definition of tumor stem cells, methods of isolation, and clinical significance.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.265-274
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• 2021

In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers' purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.

• Journal of Life Science
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• v.31 no.8
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• pp.771-777
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• 2021

Human endogenous retroviruses (HERVs) were inserted into the human genome millions of years ago but they are currently inactive and non-infectious due to recombinations, deletions, and mutations after insertion into the host genome. Nonetheless, recent studies have shown that HERV-derived elements are actually involved in physiological phenomena and certain diseases including cancers. Among the various physiological phenomena related to HERV-derived elements, it is necessary to focus on inflammatory response. HERV-derived elements have been reported to be directly involved in various inflammatory diseases, including autoimmune diseases such as rheumatoid arthritis, multiple sclerosis, amyotrophic lateral sclerosis, and Sjogren's syndrome. As a mechanism for regulating inflammation through HERV-derived elements, the possibility that HERV-derived elements may cause nonspecific innate immune processes and that HERV-derived RNA or proteins may cause selective signaling mechanisms through specific receptors can be considered. However, the mechanism through which HERV-derived elements regulate inflammatory response, such as how silent HERV elements are activated in inflammatory response and what factors and signaling mechanisms are involved in HERV-derived elements, have not been identified to date, making it difficult to study the onset of HERV-related inflammatory disease. In this review, we introduce HERV-related autoimmune diseases and propose the mechanisms of HERV-derived elements at the molecular level of HERV in inflammatory response.

• Journal of Life Science
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• v.32 no.10
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• pp.812-820
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• 2022

Depression is a psychiatric disorder characterized by depressed mood, anhedonia, fatigue, and altered cognitive function, leading to a decline in daily functioning. In addition, depression is a serious and common mental illness not only in an individual's life but also in society, so it must be actively treated. Autophagy is involved in the pathophysiological mechanism of mental illness. According to a recent study, it is known that autophagy-induced apoptosis affects neuroplasticity and causes depression and that antidepressants regulate autophagy. Autophagy is a catabolic process that degradation and removes unnecessary organelles or proteins through a lysosome. And, it is essential for maintaining cellular homeostasis. Autophagy is activated in stress conditions, and depression is a stress-related disease. Stress causes damage to cellular homeostasis. Recently, although the role of autophagy mechanisms in neurons has been investigated, the autophagy of depression has not been fully studied. This review highlights the new evidence for the involvement of autophagy in the pathophysiological mechanisms and treatment of depression. To highlight the evidence, we present results from clinical and preclinical studies showing that autophagy is associated with depression. Understanding the relevance of autophagy to depression and the limitations of research suggest that autophagy regulation may provide a new direction for antidepressant development.

• Korean small business review
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• v.43 no.4
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• pp.27-57
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• 2021

How does authenticity influence the process that conducts a company's CSR Strategy? Authenticity, an internal/external alignment condition that an employee feels in relation to an organization, means the decision on how true and beneficial to employees through their experiences, such as thoughts and emotions. Also, it can be understood as a process of meaning formation between the organization's strategy to conduct CSR and the perception of employees conducting CSR. To prove the relation between authenticity and CSR clearly, we used various techniques like Text Mining, Topic Modeling and Semantic network analysis about O corporation's 657 review data, from 2015 to 2021. As a result of the analysis, we find out the special issues and types. The analysis shows that the issue concerning the 'external image' is the biggest characteristic of authenticity perception in other conditions. Furthermore, the types of authenticity perception evaluations are largely divided into acceptance and rejection, in detail, five categories. This study indicates that organizations should consider both external and internal conditions when establishing CSR strategies. In addition, it is necessary to be an interactive circular relationship between the organization and employee, collecting and reflecting employee's perceptions. Finally, this study proposes ways to overcome problems related to interaction.

• Journal of Life Science
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• v.32 no.5
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• pp.375-390
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• 2022

Influenza viruses are zoonotic respiratory pathogens, and influenza infections have caused a substantial burden on public health systems and the livestock industry. Although currently approved seasonal influenza vaccines have shown potent protection efficacy against antigenically well-matched strains, there are considerable unmet needs for the efficient control of viral infections. Enormous efforts have been made to develop broadly protective universal influenza vaccines to tackle the huge levels of genetic diversity and variability of influenza viruses. In addition, antiviral drugs have been considered important interventions for the treatment of viral infections. The viral neuraminidase inhibitor oseltamivir is the most widely used antiviral medication to treat influenza A and influenza B viruses. However, unsatisfactory clinical outcomes resulting from side effects and the emergence of resistant variants have led to greater attention being paid to plants as a natural resource for anti-influenza drugs. In particular, the recent COVID-19 pandemic has underpinned the need for safe and effective antiviral drugs with a broad spectrum of antiviral activity to prevent the rapid spread of viruses among humans. This review outlines the results of the antiviral activities of various natural products isolated from plants against influenza viruses. Special focus is paid to the virucidal effects and the immune-enhancing effects of antiviral natural products, since the products have broad applications as inactivating agents for the preparation of inactivated vaccines and vaccine adjuvants.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.81-90
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• 2021

There are various optimization problems in real world and research continues to solve them. An optimization problem is the problem of finding a combination of parameters that maximizes or minimizes the objective function. Harmony search is a population-based metaheuristic algorithm for solving optimization problems and it is designed to mimic the improvisation of jazz music. Harmony search has been actively applied to optimization problems in various fields such as civil engineering, computer science, energy, medical science, and water quality engineering. Harmony search has a simple working principle and it has the advantage of finding good solutions quickly in constrained optimization problems. Especially there are various application cases showing high accuracy with a low number of iterations by improving the solution through the empirical derivative. In this paper, we explain working principle of Harmony search and classify the leading research in recent 3 years, review them according to category, and suggest future research directions. The research is divided into review by field, algorithmic analysis and theory, and application to real world problems. Application to real world problems is classified according to the purpose of optimization and whether or not they are hybridized with other metaheuristic algorithms.