• Journal of Information Science Theory and Practice
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• v.11 no.1
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• pp.14-30
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• 2023

The purpose of this study is to compare research trends in the information and communication technology (ICT) field between North and South Korea and analyze the differences by using data mining. Frequency analysis, clustering, and network analysis were performed using keywords from seven South Korean and two North Korean ICT academic journals published for five years (2015-2019). In the case of South Korea (S. Korea), the frequency of research on image processing and wireless communication was high at 16.7% and 16.3%, respectively. North Korea (N. Korea) had a high frequency of research, in the order of 18.2% for image processing, 16.9% for computer/Internet applications/security, and 16.4% for industrial technology. N. Korea's natural language processing (NLP) sector was 11.9%, far higher than S. Korea's 0.7 percent. Student education is a unique subject that is not clustered in S. Korea. In order to promote exchanges between the two Koreas in the ICT field, the following specific policies are proposed. Joint research will be easily possible in the image processing sector, with the highest research rate in both Koreas. Technical cooperation of medical images is required. If S. Korea's high-quality image source is provided free of charge to N. Korea, research materials can be enriched. In the field of NLP, it calls for proposing exchanges such as holding a Korean language information conference, developing a Korean computer operating system. The field of student education encourages support for remote education contents and management know-how, as well as joint research on student remote evaluation.

• Fisheries and Aquatic Sciences
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• v.25 no.3
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• pp.151-157
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• 2022

Various approaches have been applied to transform aquaculture from a manual, labour-intensive industry to one dependent on automation technologies in the era of the fourth industrial revolution. Technologies associated with the monitoring of physical condition have successfully been applied in most aquafarm facilities; however, real-time biological monitoring systems that can observe fish condition and behaviour are still required. In this study, we used a video recorder placed on top of a fish tank to observe the swimming patterns of rock bream (Oplegnathus fasciatus), first one fish alone and then a group of five fish. Rock bream in the video samples were successfully identified using the you-only-look-once v3 algorithm, which is based on the Darknet-53 convolutional neural network. In addition to recordings of swimming behaviour under normal conditions, the swimming patterns of fish under abnormal conditions were recorded on adding an anaesthetic or lowering the salinity. The abnormal conditions led to changes in the velocity of movement (3.8 ± 0.6 cm/s) involving an initial rapid increase in speed (up to 16.5 ± 3.0 cm/s, upon 2-phenoxyethanol treatment) before the fish stopped moving, as well as changing from swimming upright to dying lying on their sides. Machine learning was applied to datasets consisting of normal or abnormal behaviour patterns, to evaluate the fish behaviour. The proposed algorithm showed a high accuracy (98.1%) in discriminating normal and abnormal rock bream behaviour. We conclude that artificial intelligence-based detection of abnormal behaviour can be applied to develop an automatic bio-management system for use in the aquaculture industry.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.11-19
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• 2022

In this paper, we propose a GoogleNet transfer learning and CNN-LSTM combination method to improve the time-series prediction performance for crack detection using crack data captured inside the sewer pipes. LSTM can solve the long-term dependency problem of CNN, so spatial and temporal characteristics can be considered at the same time. The predictive performance of the proposed method is excellent in all test variables as a result of comparing the RMSE(Root Mean Square Error) for time series sections using the crack data inside the sewer pipe. In addition, as a result of examining the prediction performance at the time of data generation, the proposed method was verified that it is effective in predicting crack detection by comparing with the existing CNN-only model. If the proposed method and experimental results obtained through this study are utilized, it can be applied in various fields such as the environment and humanities where time series data occurs frequently as well as crack data of concrete structures.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.1
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• pp.7-21
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• 2017

Multiple antenna techniques employed in fourth generation mobile communication systems are affected on their performance mostly by transmission environments and antenna configurations. The performance of the indoor LTE(Long-term Evolution) MIMO(multiple input multiple output) has been rigorously evaluated with considering various diversity transmission schemes and propagation conditions in the paper. Specifically, MAC TP(medium access control throughput) and LTE system parameters related to the MIMO technique are analyzed for several indoor propagation conditions. The performance comparison between multiple antenna diversity mode and single antenna mode has been derived as well. The results performed in the paper give the guideline on antenna configurations of polarization diversity in LTE 2×2 MIMO for various indoor channel environments, and possibly are exploited by network operators and antenna manufacturers.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.32-32
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• 2020

하나의 수계 또는 용수구역 내에서 작물생육기간 동안 지하수자원 수요량의 집중적인 증가로 인해 지역적 지하수 고갈이 발생하여 농작물 피해가 발생하고 있으며 과잉양수로 인한 지하수위 하강으로 사용자간 갈등도 빈번하다. 또한, 기후변화로 인해 극한기후인 가뭄의 잦은 발생은 이러한 현상을 가속화 한다. 지하수 산출성이 좋은 대수층의 공간적 분포는 복잡한 지질구조로 인해 균일하지 않으며 같은 대수층 내에서도 양수 위치에 따라 산출성은 다르게 나타난다. 이러한 지하수 수요와 공급 및 대수층 분포로 인한 지하수자원 불균형의 해소를 위해 지하수가 풍부한 지역에서 부족한 지역으로 지하수를 공급하는 방법을 적용할 수 있다. 이때 기술적용 지역의 지하수 사용 상황 및 공급 가능량을 정량적으로 평가하고 이를 기반으로 지하수 공급을 제어하는 것이 매우 중요하다. 지하수자원의 수요-공급 불균형이 발생할 때 즉각적으로 대응하기 위해서는 실시간으로 지하수 현황을 감시하고 이를 기반으로 공급 가능량을 산정할 필요가 있으며 이는 정보통신기술(Information and Communication Technology, ICT)에 기반한 관정연계관리체계(Well Network System, WNS)를 구성하는 기술 중 하나인 관정군집제어 기술로 구현될 수 있다. 수계 내에 설치된 기존의 양수정과 새롭게 추가된 관측정들을 4G LTE 네트워크를 통해 하나의 관정군으로 묶고 중앙 서버를 통한 자료 분석 및 양수 펌프 제어를 통해 대수층의 공급 능력과 사용자의 수요 현황에 따른 지하수자원의 체계적 분배를 구현하고자 하였다. 관정군집제어는 관정별 지하수위 및 양수정 양수량을 실시간으로 관측하고 이를 분석서버에 전송하여 해당 지하수계의 공급 가능량 및 인접관정 간섭 등을 분석하여 양수정의 펌프를 실시간으로 제어하고 양수된 지하수를 수요 지역으로 이송한다. 본 연구를 통해 관정군집제어 기술의 구현에 필요한 구성요소를 정의하고 이에 대한 구현 방법을 기술하여 WNS를 구성하는 하나의 요소기술 모델로 제시하고자 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.942-943
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• 2021

The present work proposes a classification system for the HEp-2 cell images using an unsupervised deep feature learning method. Unlike most of the state-of-the-art methods in the literature that utilize deep learning in a strictly supervised way, we propose here the use of the deep convolutional autoencoder (DCAE) as the principal feature extractor for classifying the different types of the HEp-2 cell images. The network takes the original cell images as the inputs and learns to reconstruct them in order to capture the features related to the global shape of the cells. A final feature vector is constructed by using the latent representations extracted from the DCAE, giving a highly discriminative feature representation. The created features will be fed to a nonlinear classifier whose output will represent the final type of the cell image. We have tested the discriminability of the proposed features on one of the most popular HEp-2 cell classification datasets, the SNPHEp-2 dataset and the results show that the proposed features manage to capture the distinctive characteristics of the different cell types while performing at least as well as the actual deep learning based state-of-the-art methods.

• IMMUNE NETWORK
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• v.24 no.1
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• pp.9.1-9.21
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• 2024

The cytokine IL-7 plays critical and nonredundant roles in T cell immunity so that the abundance and availability of IL-7 act as key regulatory mechanisms in T cell immunity. Importantly, IL-7 is not produced by T cells themselves but primarily by non-lymphoid lineage stromal cells and epithelial cells that are limited in their numbers. Thus, T cells depend on cell extrinsic IL-7, and the amount of in vivo IL-7 is considered a major factor in maximizing and maintaining the number of T cells in peripheral tissues. Moreover, IL-7 provides metabolic cues and promotes the survival of both naïve and memory T cells. Thus, IL-7 is also essential for the functional fitness of T cells. In this regard, there has been an extensive effort trying to increase the protein abundance of IL-7 in vivo, with the aim to augment T cell immunity and harness T cell functions in anti-tumor responses. Such approaches started under experimental animal models, but they recently culminated into clinical studies, with striking effects in re-establishing T cell immunity in immunocompromised patients, as well as boosting anti-tumor effects. Depending on the design, glycosylation, and the structure of recombinantly engineered IL-7 proteins and their mimetics, recombinant IL-7 molecules have shown dramatic differences in their stability, efficacy, cellular effects, and overall immune functions. The current review is aimed to summarize the past and present efforts in the field that led to clinical trials, and to highlight the therapeutical significance of IL-7 biology as a master regulator of T cell immunity.

• IMMUNE NETWORK
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• v.23 no.4
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• pp.31.1-31.18
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• 2023

Evidence suggests that the human respiratory tract, as with the gastrointestinal tract, has evolved to its current state in association with commensal microbes. However, little is known about how the airway microbiome affects the development of airway immune system. Here, we uncover a previously unidentified mode of interaction between host airway immunity and a unique strain (AIT01) of Staphylococcus epidermidis, a predominant species of the nasal microbiome. Intranasal administration of AIT01 increased the population of neutrophils and monocytes in mouse lungs. The recruitment of these immune cells resulted in the protection of the murine host against infection by Pseudomonas aeruginosa, a pathogenic bacterium. Interestingly, an AIT01-secreted protein identified as GAPDH, a well-known bacterial moonlighting protein, mediated this protective effect. Intranasal delivery of the purified GAPDH conferred significant resistance against other Gram-negative pathogens (Klebsiella pneumoniae and Acinetobacter baumannii) and influenza A virus. Our findings demonstrate the potential of a native nasal microbe and its secretory protein to enhance innate immune defense against airway infections. These results offer a promising preventive measure, particularly relevant in the context of global pandemics.

• IMMUNE NETWORK
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• v.21 no.1
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• pp.5.1-5.22
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• 2021

Coronavirus disease 2019 (COVID-19) has developed as a pandemic, and it created an outrageous effect on the current healthcare and economic system throughout the globe. To date, there is no appropriate therapeutics or vaccines against the disease. The entire human race is eagerly waiting for the development of new therapeutics or vaccines against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Efforts are being taken to develop vaccines at a rapid rate for fighting against the ongoing pandemic situation. Amongst the various vaccines under consideration, some are either in the preclinical stage or in the clinical stages of development (phase-I, -II, and -III). Even, phase-III trials are being conducted for some repurposed vaccines like Bacillus Calmette-Guérin, polio vaccine, and measles-mumps-rubella. We have highlighted the ongoing clinical trial landscape of the COVID-19 as well as repurposed vaccines. An insight into the current status of the available antigenic epitopes for SARS-CoV-2 and different types of vaccine platforms of COVID-19 vaccines has been discussed. These vaccines are highlighted throughout the world by different news agencies. Moreover, ongoing clinical trials for repurposed vaccines for COVID-19 and critical factors associated with the development of COVID-19 vaccines have also been described.

• IMMUNE NETWORK
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• v.20 no.4
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• pp.33.1-33.19
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• 2020

We tested how adjuvants effect in a cancer vaccine model using an epitope derived from an autoactivation loop of membrane-type protease serine protease 14 (PRSS14; loop metavaccine) in mouse mammary tumor virus (MMTV)-polyoma middle tumor-antigen (PyMT) system and in 2 other orthotopic mouse systems. Earlier, we reported that loop metavaccine effectively prevented progression and metastasis regardless of adjuvant types and TH types of hosts in tail-vein injection systems. However, the loop metavaccine with Freund's complete adjuvant (CFA) reduced cancer progression and metastasis while that with alum, to our surprise, were adversely affected in 3 tumor bearing mouse models. The amounts of loop peptide specific antibodies inversely correlated with tumor burden and metastasis, meanwhile both T_H1 and T_H2 isotypes were present regardless of host type and adjuvant. Tumor infiltrating myeloid cells such as eosinophil, monocyte, and neutrophil were asymmetrically distributed among 2 adjuvant groups with loop metavaccine. Systemic expression profiling using the lymph nodes of the differentially immunized MMTV-PyMT mouse revealed that adjuvant types, as well as loop metavaccine can change the immune signatures. Specifically, loop metavaccine itself induces T_H2 and T_H17 responses but reduces T_H1 and T_reg responses regardless of adjuvant type, whereas CFA but not alum increased follicular T_H response. Among the myeloid signatures, eosinophil was most distinct between CFA and alum. Survival analysis of breast cancer patients showed that eosinophil chemokines can be useful prognostic factors in PRSS14 positive patients. Based on these observations, we concluded that multiple immune parameters are to be considered when applying a vaccine strategy to cancer patients.