• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.239-260
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• 2023

The underwater acoustic wireless communication networks are generally formed by the different autonomous underwater acoustic vehicles, and transceivers interconnected to the bottom of the ocean with battery deployed modems. Orthogonal frequency division multiplexing (OFDM) has become the most popular modulation technique in underwater acoustic communication due to its high data transmission and robustness over other symmetrical modulation techniques. To maintain the operability of underwater acoustic communication networks, the power consumption of battery-operated transceivers becomes a vital necessity to be minimized. The OFDM technology has a major lack of peak to average power ratio (PAPR) which results in the consumption of more power, creating non-linear distortion and increasing the bit error rate (BER). To overcome this situation, we have contributed our symmetry research into three dimensions. Firstly, we propose a machine learning-based underwater acoustic communication system through long short-term memory neural network (LSTM-NN). Secondly, the proposed LSTM-NN reduces the PAPR and makes the system reliable and efficient, which turns into a better performance of BER. Finally, the simulation and water tank experimental data results are executed which proves that the LSTM-NN is the best solution for mitigating the PAPR with non-linear distortion and complexity in the overall communication system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.462-462
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• 2022

Wetlands are one of the most vital natural habitats on the planet. India is incredibly blessed to have a number of multifunctional wetland ecosystems. Wetlands, in addition to their functional importance, can act as sources or sinks for greenhouse gases (GHGs) depending on their intrinsic factors. Carbon (CO2) and Methane (CH4) are the major greenhouse gases (GHG's) emitted in wetlands. It is demonstrated that, despite having 4.6 percent of its area covered by natural or man-made wetlands, being home to a large number of wetlands, and being the world's second largest cultivator of paddy, India's wetlands, including paddy fields that are intermittently flooded as typical wetlands, have been very poorly studied in terms of GHG emissions. The purpose of this paper is to examine the status of Indian wetlands and wetlands in terms of CH4 and CO2 emissions. The present study also reviews various literature to provide the equations, parameters that are required for estimating carbon and methane and some of the best strategies for conserving carbon in wetlands. The findings suggest that both non-manipulative and manipulative measures can be used to improve Carbon Sequestration (CS). Non-manipulative measures aim to improve CS by increasing the spatial extent of wetlands, whereas manipulative measures aim to change the characteristics of specific wetland components that influence CS. Uncertainty in carbon dynamics projections under changing environmental conditions is caused by a number of Knowledge gaps: i) There is a lack of knowledge on how organic matter mineralizes and partitions into carbon dioxide, methane, and dissolved organic carbon, ii) With the notable exception of methane dynamics, models that represent the dynamic interaction of processes and their controls have yet to be established. As a result, more research is needed to fully understand the importance of wetlands in terms of GHG emissions and carbon sequestration in India.

• 치위생과학회지
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• 제23권3호
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• pp.225-235
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• 2023

Background: This study aimed to analyze the effects of periodontal treatment and individual- and tooth-related factors on tooth extraction in people with disabilities. Methods: The Korea National Health Insurance claims data of individuals with disabilities aged 40~64 years with chronic periodontitis in 2008 were obtained. Of these, data on the disabled who underwent scaling/root plaining, subgingival curettage/periodontal surgery, or non-periodontal treatments, and data on their teeth were selected. The extraction of 716,688 teeth from 39,097 patients was tracked until 2018, and the patient- and tooth-level factors related to tooth loss were identified using a mixed-effect logistic regression analysis. Results: Data from approximately 17% of the teeth were extracted during a follow-up period of approximately 11 years. Among the tooth-level variables, scaling/root planing treatment at baseline and periodontal treatment during the follow-up period were associated with a lower risk of tooth loss (odds ratio=0.692 and 0.769, respectively, p<0.001). Non-vital teeth increased the risk of tooth loss by 3.159 times (p<0.001). Among the patient-level variables, females were less likely to have lost their teeth than males, and those with orthopedic impairment or brain lesions/mental disabilities, a higher age group, lower income level, or residents in medium/small cities or rural areas were more likely to have lost their teeth (p<0.001). Conclusion: Through approximately 11 years of follow-up, scaling or root planing, experience with periodontal treatment at least once, female sex, older age, lower income, smaller residential areas, type of disability, and pulp vitality were found to be associated with tooth loss in individuals with disabilities aged 40~64 years with chronic periodontitis. To prevent tooth loss in individuals with disabilities, it is necessary to establish a dental treatment plan that considers the timing of periodontal treatment and the characteristics of the patient and teeth.

• Genomics & Informatics
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• 제21권3호
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• pp.38.1-38.8
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• 2023

Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DEmiRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co- expression network. Next, four modules were selected based on the Z_summary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

• Asia pacific journal of information systems
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• 제34권1호
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• pp.150-190
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• 2024

This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.

• Animal Bioscience
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• 제37권8호
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• pp.1317-1332
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• 2024

Objective: Rare study of the non-coding and regulatory regions of the genome limits our ability to decode the mechanisms of fatty liver hemorrhage syndrome (FLHS) in chickens. Methods: Herein, we constructed the high-fat diet-induced FLHS chicken model to investigate the genome-wide active enhancers and transcriptome by H3K27ac target chromatin immunoprecipitation sequencing (ChIP-seq) and RNA sequencing (RNA-Seq) profiles of normal and FLHS liver tissues. Concurrently, an integrative analysis combining ChIP-seq with RNA-Seq and a comparative analysis with chicken FLHS, rat non-alcoholic fatty liver disease (NAFLD) and human NAFLD at the transcriptome level revealed the enhancer and super enhancer target genes and conservative genes involved in metabolic processes. Results: In total, 56 and 199 peak-genes were identified in upregulated peak-genes positively regulated by H3K27ac (Cor (peak-gene correlation) ≥0.5 and log2(FoldChange) ≥1) (PP) and downregulated peak-genes positively regulated by H3K27ac (Cor (peak-gene correlation) ≥0.5 and log2(FoldChange)≤-1) (PN), respectively; then we screened key regulatory targets mainly distributing in lipid metabolism (PCK1, APOA4, APOA1, INHBE) and apoptosis (KIT, NTRK2) together with MAPK and PPAR signaling pathway in FLHS. Intriguingly, PCK1 was also significantly covered in up-regulated super-enhancers (SEs), which further implied the vital role of PCK1 during the development of FLHS. Conclusion: Together, our studies have identified potential therapeutic biomarkers of PCK1 and elucidated novel insights into the pathogenesis of FLHS, especially for the epigenetic perspective.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권5호
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• pp.1317-1340
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• 2024

With the rapid development of information technology, people's demands on precise indoor positioning are increasing. Wireless sensor network, as the most commonly used indoor positioning sensor, performs a vital part for precise indoor positioning. However, in indoor positioning, obstacles and other uncontrollable factors make the localization precision not very accurate. Ultra-wide band (UWB) can achieve high precision centimeter-level positioning capability. Inertial navigation system (INS), which is a totally independent system of guidance, has high positioning accuracy. The combination of UWB and INS can not only decrease the impact of non-line-of-sight (NLOS) on localization, but also solve the accumulated error problem of inertial navigation system. In the paper, a fused UWB and INS positioning method is presented. The UWB data is firstly clustered using the Fuzzy C-means (FCM). And the Z hypothesis testing is proposed to determine whether there is a NLOS distance on a link where a beacon node is located. If there is, then the beacon node is removed, and conversely used to localize the mobile node using Least Squares localization. When the number of remaining beacon nodes is less than three, a robust extended Kalman filter with M-estimation would be utilized for localizing mobile nodes. The UWB is merged with the INS data by using the extended Kalman filter to acquire the final location estimate. Simulation and experimental results indicate that the proposed method has superior localization precision in comparison with the current algorithms.

• 대한임상검사과학회지
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• 제52권2호
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• pp.119-127
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• 2020

선행 연구에서 동맥경화와 폐기능이상과 연관성이 있었다. 맥압은 동맥경화의중요한 예측이지만 아직까지 폐기능이상과 맥압의 연관성은 불분명하다. 따라서, 본 연구는 대한민국 비흡연 성인을 대상으로 맥압과 폐기능장애(예측 강제 폐활량, 예측 강제 날숨량 1초율)의 관련성을 알아보고자 실시하였다. 본 연구는 2013년부터 2015년까지 3년간의 대한민국 국민건강영양조사자료에서 비흡연 성인(6,857명)을 대상으로 실시하였다. 본 연구의 주요 결과는 맥압과 폐기능장애에 대한 관련 변수를 보정한 후의 결과에서, 정상 맥압(pulse pressure, PP≤60 mmHg)에 비하여 고맥압(PP>60 mmHg; 1.337 [95% confidence interval (CI), 1.049~1.703)에서 제한성 폐질환(restrictive pulmonary disease, RPD; the predicted FVC<80.0% with FEV₁/FVC≥70.0%)의 교차비(odds ratio, OR)가 유의하게 높았다. 추가적으로, 정상맥압에 비하여 고맥압(1.339 [95% CI, 1.093~1.642])에서 폐쇄성 폐질환(obstructive pulmonary disease, OPD; FEV₁/FVC<70.0%)의 교차비가 유의하게 높았다. 결론적으로, 대한민국 비흡연 성인에서 제한성 폐질환 및 폐쇄성 폐질환은 고맥압과 유의한 관계가 있었다.

• 한국응급구조학회지
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• 제15권2호
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• pp.101-108
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• 2011

Purpose: Cardiopulmonary resuscitation (CPR) prevents tissue necrosis of the brain and cardiac muscle in the cardiac arrest patient and requires exact skills in order to increase survival rate. Through comparison of the training effects of feedback manikin and non-feedback manikin, this study present the effective CPR device to CPR instructors. Method: This CPR course for 80 students by using Resusci Anne $SkillReporter^{TM}$ (RASR; Laerdal Medical, Stavanger, Norway) and Actar 911 $Squadron^{TM}$ (A911; Vital Signs, New Jersey, USA) held on December 22, 2009. Thirty seven students and two assistants were placed in one laboratory, there were five RASR manikins which provide the LED performance indicator, not the metronome. Forty two students and two assistants were placed in the other laboratory, there were 20 A911 manikins which don't provide any feedback indicator. Chest compression scores and ventilation compression scores obtaining from two groups were analysed statistically by using independent t-test. Results: Chest compression scores, average depth (mm) was 37.5 in RASR and 41.80 A911 (p=.004), too depth (#) was 2.8 in RASR and 19.4 A911 (p=.005), average number per min (#/min) was 64.4 in RASR and 68.2 A911 (p=.038), wrong hand position (#/min) was 10.9 in RASR and 30.8 A911 (p=.040). Four items that showed better scores in group RASR had statistically significant difference. Ventilation compression scores, percent correct (%) was 40.6 in RASR and 20.6 A911 (p<.001), number correct (#) was 4.7 in RASR and 2.1 A911 (p=.002), too fast (#) was 0.9 in RASR and 2.9 A911 (p=.003), average volume (ml) was 536.5 in RASR and 707.1 A911 (p=.011). Also, three items that showed better scores in group RASR had statistically significant difference. Conclusions: Regarding the positive effect of CPR training feedback, comparison between the real-time visual feedback manikin (RASR) and the non-feedback manikin (A911) showed that RASR had better results than A911 in chest compression except average number per min (it means that we need harder chest manikin) and ventilation. Verification of the training effect in the real world such as CPR outcomes is also necessary. A proper application of manikin in training circumstances and research on retention of CPR skills will be needed.