• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.823-835
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• 2023

Recently, due to the increase in abnormal climate, rainfall intensity is increasing and drought periods are continuing. These environmental changes lead to prolonged drought conditions and difficulties in real-time recognition. In general, drought can be judged by the amount of precipitation and the number of days without rainfall. In determining the impact of drought, it is divided into meteorological drought, agricultural drought, and hydrological drought and evaluation is made using the drought index, but environmental drought evaluation is insufficient. The river water quality managed through the total water pollution cap system is vulnerable to the effects of such drought. In this study, we aim to determine the drought impact on river water quality and quantify the impact of prolonged drought on water quality. The impact of rain-free days and accumulated precipitation on river water quality was quantitatively evaluated. The Load Duration Curve (LDC), which is used to evaluate the water quality of rivers, was used to evaluate water pollution occurring at specific times. It has been observed that when the number of consecutive rainless days exceeds 14 days, the target water quality in the mid-basin is exceeded in over 60% of cases. The cumulative rainfall is set at 28 days as the criteria, with an annual average rainfall of 3%, which is 32.1 mm or less. It has been noted that changes in water quality in rivers occur when there are 14 or more rainless days and the cumulative rainfall over 28 days is 32.1 mm or less in the Gamcheon Mid-basin. Based on the results of this study, it aims to quantify the drought impact and contribute to the development of a drought water quality index for future environmental droughts.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1001-1006
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• 2023

Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

• Journal of Nutrition and Health
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• v.56 no.5
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• pp.455-468
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• 2023

Purpose: Abeliophyllum distichum (A.distichum) is a plant native to Korea. In this study, we investigated the mechanism of antioxidant and anti-inflammatory effects of the leaf extract of A.distichum. Methods: The antioxidant capacity of the A.distichum leaf extract was determined based on the total polyphenol content, 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assay, and the ferric reducing antioxidant power (FRAP) assay. The anti-inflammatory effects of the A.distichum leaf extract were evaluated by measuring the production of nitric oxide (NO) and the expression levels of proinflammatory cytokines including tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6 using the enzyme-linked immunosorbent assay (ELISA) and reverse transcription quantitative real-time PCR (RT-qPCR). In addition, the expression of heme oxygenase-1 (HO-1), nuclear transcription factor-erythroid 2 related factor (Nrf2), inducible nitric oxide synthase (iNOS), and cyclooxygenase 2 (COX-2), as well as the activation of nuclear factorkappa B (NF-ĸB) were examined using the western blot analysis. Results: The total polyphenol content of the A.distichum leaf extract was 329.89 ± 30.17 gallic acid equivalents mg/g and the DPPH and ABTS scavenging activities were 55% and 70%, respectively. Additionally, the FRAP value of the extract was 743.68 ± 116.59 mg/mL. After 12-hour treatment with the A.distichum leaf extract, there was a tendency for the Nrf2 expression to increase, and the expression of HO-1 was significantly elevated in the RAW264.7 cells. The A.distichum leaf extract treatment resulted in decreased levels of NO, TNF-α, IL-6, and IL-1β, as well as reduced expression of iNOS and COX-2, along with inhibition of NF-κB activation in lipopolysaccharide-stimulated RAW264.7 cells. Conclusion: These results suggest that the A.distichum leaf extract exerts antioxidative and anti-inflammatory effects by upregulating the expression of HO-1 and downregulating NF-κB activation.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.103-114
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• 2023

Augmented reality (AR) and virtual reality (VR) differ fundamentally, with AR overlaying computer-generated information onto the real world in a nonimmersive way. Despite extensive research on cybersickness in VR, its occurrence in AR has received less attention (Vovk et al., 2018). This study examines cybersickness and discomfort associated with AR usage, focusing on the impact of content intensity and exposure time. Participants viewed 30-minute racing simulation game clips through AR equipment, varying in racing speed to alter content intensity. Cybersickness was assessed subjectively using the Simulator sickness questionnaire (SSQ; Kennedy et al., 1993). Findings revealed a progressive increase in cybersickness with longer exposure, persisting even after removing the AR equipment. Contrarily, content intensity did not significantly influence cybersickness levels. Analysis of the SSQ subscales revealed higher oculomotor (O) scores compared to nausea (N) and disorientation (D), suggesting that discomfort primarily stemmed from oculomotor strain. The study highlights distinct differences in user experience between AR and VR, specifically in subjective responses.

• Biomolecules & Therapeutics
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• v.32 no.1
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• pp.154-161
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• 2024

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disorder that causes progressive paralysis. L-Citrulline is a nonessential neutral amino acid produced by L-arginine via nitric oxide synthase (NOS). According to previous studies, the pathogenesis of ALS entails glutamate toxicity, oxidative stress, protein misfolding, and neurofilament disruption. In addition, L-citrulline prevents neuronal cell death in brain ischemia; therefore, we investigated the change in the transport of L-citrulline under various pathological conditions in a cell line model of ALS. We examined the uptake of [¹⁴C]L-citrulline in wild-type (hSOD1wt/WT) and mutant NSC-34/ SOD1^G93A (MT) cell lines. The cell viability was determined via MTT assay. A transport study was performed to determine the uptake of [¹⁴C]L-citrulline. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis was performed to determine the expression levels of rat large neutral amino acid transported 1 (rLAT1) in ALS cell lines. Nitric oxide (NO) assay was performed using Griess reagent. L-Citrulline had a restorative effect on glutamate induced cell death, and increased [¹⁴C]L-citrulline uptake and mRNA levels of the large neutral amino acid transporter (LAT1) in the glutamate-treated ALS disease model (MT). NO levels increased significantly when MT cells were pretreated with glutamate for 24 h and restored by co-treatment with L-citrulline. Co-treatment of MT cells with L-arginine, an NO donor, increased NO levels. NSC-34 cells exposed to high glucose conditions showed a significant increase in [¹⁴C]L-citrulline uptake and LAT1 mRNA expression levels, which were restored to normal levels upon co-treatment with unlabeled L-citrulline. In contrast, exposure of the MT cell line to tumor necrosis factor alpha, lipopolysaccharides, and hypertonic condition decreased the uptake significantly which was restored to the normal level by co-treating with unlabeled L-citrulline. L-Citrulline can restore NO levels and cellular uptake in ALS-affected cells with glutamate cytotoxicity, pro-inflammatory cytokines, or other pathological states, suggesting that L-citrulline supplementation in ALS may play a key role in providing neuroprotection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.27-34
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• 2024

The direct and indirect damages caused by fires in underground utility tunnels have a great impact on society as a whole, so efforts are needed to prevent and manage them in advance. To this end, research is ongoing to prevent disasters such as fire flooding by applying digital twin technology to underground utility tunnels. A network is required to transmit the sensed signals from each sensor to the platform. In essence, it is necessary to analyze the application of wireless networks in the underground utility tunnel environments because the tunnel lacks the reception range of external wireless communication systems. Within the underground utility tunnels, electromagnetic interference caused by transmission and distribution cables, and diffuse reflection of signals from internal structures, obstacles, and metallic pipes such as water pipes can cause distortion or size reduction of wireless signals. To ensure real-time connectivity for remote surveillance and monitoring tasks through sensing, it is necessary to measure and analyze the wireless coverage in underground utility tunnels. Therefore, in order to build a wireless network environment in the underground utility tunnels. this study minimized the shaded area and measured the actual cavity environment so that there is no problem in connecting to the wireless environment inside the underground utility tunnels. We analyzed the data transmission rate, signal strength, and signal-to-noise ratio for each section of the terrain of the underground utility tunnels. The obtained results provide an appropriate wireless planning approach for installing wireless networks in underground utility tunnels.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.97-108
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• 2024

This research delves into the escalating concerns of accidents and fatalities in the construction industry over the recent five-year period, focusing on the development of a Safety Perception Model to augment safety measures. Given the rising percentage of elderly workers and the concurrent drop in productivity within the sector, there is a pronounced need for leveraging Fourth Industrial Revolution technologies to bolster safety protocols. The study comprises an in-depth analysis of statistical data regarding construction-related fatalities, aiming to shed light on prevailing safety challenges. Central to this investigation is the formulation of a Safety Perception Model tailored for small-scale construction projects. This model facilitates the quantification of safety risks by evaluating safety grades across construction sites. Utilizing the DWM1000 module, among an array of wireless communication technologies, the model enables the real-time tracking of worker locations and the assessment of safety levels on-site. Furthermore, the deployment of a safety management system allows for the evaluation of risk levels associated with individual workers. Aggregating these data points, the Safety Climate Index(SCLI) is calculated to depict the daily, weekly, and monthly safety climate of the site, thereby offering insights into the effectiveness of implemented safety measures and identifying areas for continuous improvement. This study is anticipated to significantly contribute to the systematic enhancement of safety and the prevention of accidents on construction sites, fostering an environment of improved productivity and strengthened safety culture through the application of the Safety Perception Model.

• Animal Bioscience
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• v.37 no.8
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• pp.1345-1354
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• 2024

Objective: The objective of this study was to identify candidate genes that play important roles in skeletal muscle development in ducks. Methods: In this study, we investigated the transcriptional sequencing of embryonic pectoral muscles from two specialized lines: Liancheng white ducks (female) and Cherry valley ducks (male) hybrid Line A (LCA) and Line C (LCC) ducks. In addition, prediction of target genes for the differentially expressed mRNAs was conducted and the enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes signaling pathways were further analyzed. Finally, a protein-to-protein interaction network was analyzed by using the target genes to gain insights into their potential functional association. Results: A total of 1,428 differentially expressed genes (DEGs) with 762 being up-regulated genes and 666 being down-regulated genes in pectoral muscle of LCA and LCC ducks identified by RNA-seq (p<0.05). Meanwhile, 23 GO terms in the down-regulated genes and 75 GO terms in up-regulated genes were significantly enriched (p<0.05). Furthermore, the top 5 most enriched pathways were ECM-receptor interaction, fatty acid degradation, pyruvate degradation, PPAR signaling pathway, and glycolysis/gluconeogenesis. Finally, the candidate genes including integrin b3 (Itgb3), pyruvate kinase M1/2 (Pkm), insulin-like growth factor 1 (Igf1), glucose-6-phosphate isomerase (Gpi), GABA type A receptor-associated protein-like 1 (Gabarapl1), and thyroid hormone receptor beta (Thrb) showed the most expression difference, and then were selected to verification by quantitative real-time polymerase chain reaction (qRT-PCR). The result of qRT-PCR was consistent with that of transcriptome sequencing. Conclusion: This study provided information of molecular mechanisms underlying the developmental differences in skeletal muscles between specialized duck lines.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.8
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• pp.866-871
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• 2006

The nutrient recovery in phosphate crystallization process was investigated by using laboratory scale uptlow reactors, adopting sequencing batch type configuration. The industrial waste lime was used as potential cation source with magnesium salt($MgCl_2$) as control. The research was focused on its successful application in a novel integrated sludge treatment process, which is comprised of a high performance fermenter followed by a crystallization reactor. In the struvite precipitation test using synthetic wastewater first, which has the similar characteristics with the real fermentation effluent, the considerable nutrient removal(about 60%) in both ammonia and phosphate was observed within $0.5{\sim}1$ hr of retention time. The results also revealed that a minor amount(<5%) of ammonia stripping naturally occurred due to the alkaline(pH 9) characteristic in feed substrate. Stripping of $CO_2$ by air did not increase the struvite precipitation rate but it led to increased ammonia removal. In the second experiment using the fermentation effluent, the optimal dosage of magnesium salt for struvite precipitation was 0.86 g Mg $g^{-1}$ P, similar to the mass ratio of the struvite. The optimal dosage of waste lime was 0.3 g $L^{-1}$, resulting in 80% of $NH_4-N$ and 41% of $PO_4-P$ removal, at about 3 hrs of retention time. In the microscopic analysis, amorphous crystals were mainly observed in the settled solids with waste lime but prism-like crystals were observed with magnesium salt. Based on mass balance analysis for an integrated sludge treatment process(fermenter followed by crystallization reactor) for full-scale application(treatment capacity Q=158,880 $m^3\;d^{-1}$), nutrient recycle loading from the crystallization reactor effluent to the main liquid stream would be significantly reduced(0.13 g N and 0.19 g P per $m^3$ of wastewater, respectively). The results of the experiment reveal therefore that the reuse of waste lime, already an industrial waste, in a nutrient recovery system has various advantages such as higher economical benefits and sustainable treatment of the industrial waste.