• Animal Bioscience
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• v.37 no.7
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• pp.1246-1254
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• 2024

Objective: The goal of the current study was to investigate the impact of various concentrations of xylanase in energy-deficient corn-based diets on the growth performance, carcass characteristics, nutrient digestibility, and digesta viscosity in broilers from 7 to 35 days of age. Methods: A total of 280 seven-day-old Ross 308 broilers were randomly allocated to one of the five dietary treatments following a completely randomized design with 8 replicates and 7 birds per cage. The treatments were: i) positive control (PC, without xylanase); ii) NC-1 (80 kcal/kg ME reduced from PC); iii) NC-2 (100 kcal/kg ME reduced from PC); iv) NCX-1 (NC-1 + 2,000 U/kg xylanase); and v) NCX-2 (NC-2 + 3,000 U/kg xylanase). Body weight, weight gain, feed intake, and feed conversion ratio were determined weekly to evaluate growth performance. One bird per pen was sacrificed for ileal digesta collection to determine the viscosity and digestibility of energy, dry matter, crude protein on days 24 and 35, however breast and leg meat samples were obtained for proximate analysis (moisture, crude protein, fat, and ash) on day 35. Results: Birds fed diets supplemented with xylanase regardless of the amount had higher (p<0.05) body weights, daily gains, and improved feed efficiency compared to NC diets all throughout the experimental period. Feed intake was not affected (p>0.05) by the addition of xylanase. Moreover, lowered (p<0.05) viscosity of the ileal digesta were observed upon xylanase inclusion in the diets compared to the birds fed NC diets on day 24. Ileal nutrient digestibility and meat proximate composition were not affected (p>0.05) by xylanase. Conclusion: The present study indicated that the xylanase at 2,000 U/kg and 3,000 U/kg levels compensates for the 80 kcal/kg and 100 kcal/kg dietary energy levels, respectively, without having adverse effects on the growth performance, carcass characteristics, nutrient digestibility, and digesta viscosity of broilers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.196-207
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• 2023

As part of measures to address the climate crisis, buses are also being converted to electric and hydrogen buses. Local authorities need to prioritize carbon emissions when allocating newly introduced and converted electric and hydrogen buses, and as a method, consider the introduction of Low Emission Bus Zones (LEBZ) to propose the reduction of pollution from specific links. To introduce LEBZ, it is necessary to compare the carbon emissions before and after its implementation, yet there is a shortage of studies that focus solely on buses or analyze the effects of introducing LEBZ to specific links. In this paper, we utilized bus information system data to calculate and compare the effects of introducing LEBZ to bus priority lanes in Jeju. We categorized scenarios into five groups, with scenarios 1 through 4 involving the introduction of LEBZ, and scenario 5 designating cases where LEBZ was not introduced. Comparative results confirmed that in scenarios with LEBZ introduction, the reduction per km reached a maximum of 0.097t per km, whereas in cases without LEBZ, it amounted to 0.022t per km, demonstrating higher efficiency. It underscores the significance of conducting carbon emission calculations and comparing the effects of LEBZ introduction using bus information system data, which can be directly applied by local authorities to make informed and rational decisions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.403-421
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• 2023

As the number of underground structures has increased in recent decades, it has become crucial to predict geological hazards ahead of a tunnel face during tunnel construction. Consequently, this study developed a finite element (FE) numerical model to simulate electrical resistivity surveys in tunnel boring machine (TBM) operations for predicting mixed ground conditions in front of tunnel faces. The accuracy of the developed model was verified by comparing the numerical results not only with an analytical solution but also with experimental results. Using the developed model, a series of parametric studies were carried out to estimate the effect of geological conditions and sensor geometric configurations on electrical resistivity measurements. The results of these studies showed that both the interface slope and the difference in electrical resistivity between two different ground formations affect the patterns and variations in electrical resistivity observed during TBM excavation. Furthermore, it was revealed that selecting appropriate sensor spacing and optimizing the location of the electrode array were essential for enhancing the efficiency and accuracy of predictions related to mixed ground conditions. In conclusion, the developed model can serve as a powerful and reliable tool for predicting mixed ground conditions during TBM tunneling.

• Journal of Korea Water Resources Association
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• v.57 no.6
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• pp.409-419
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• 2024

Climate change is already impacting sustainable water resource management. The influence of climate change on water supply from reservoirs has been generally assessed using climate change scenarios generated based on global climate models. However, inherent uncertainties exist due to the limitations of estimating climate change by assuming IPCC carbon emission scenarios. The decision scaling approach was applied to mitigate these issues in this study focusing on four reservoir watersheds: Chungju, Yongdam, Hapcheon, and Seomjingang reservoirs. The reservoir water supply reliablity was analyzed by combining the rainfall-runoff model (IHACRES) and the reservoir operation model based on HEC-ResSim. Water supply reliability analysis was aimed at ensuring the stable operation of dams, and its results ccould be utilized to develop either structural or non-structural water supply plans. Therefore, in this study, we aimed to assess potential risks that might arise during the operation of reserviors under various climate conditions. Using observed precipitation and temperature from 1995 to 2014, 49 climate stress scenarios were developed (7 precipitation scenarios based on quantiles and 7 temperature scenarios ranging from 0℃ to 6℃ at 1℃ intervals). Our study demonstrated that despite an increase in flood season precipitation leading to an increase in reservoir discharge, it had a greater impact on sustainable water management compared to the increase in non-flood season precipitation. Furthermore, in scenarios combining rainfall and temperature, the reliability of reservoir water supply showed greater variations than the sum of individual reliability changes in rainfall and temperature scenarios. This difference was attributed to the opposing effects of decreased and increased precipitation, each causing limitations in water and energy-limited evapotranspiration. These results were expected to enhance the efficiency of reservoir operation.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.167-182
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• 2024

The aim of this study is to empirically explore the operational spillover effect among companies within chaebol groups, prominent corporate conglomerates in South Korea. Chaebols are known for their horizontal and vertical integration, fostering close collaboration among their constituent companies from a supply chain standpoint. Existing literature highlights the sharing of tangible and intangible resources within chaebol structures, leading to increased efficiency by minimizing transaction costs through resource sharing. This research investigates whether operational management performance within chaebol structures can be transmitted through cooperative resource utilization. To achieve this objective, we categorize leading companies and affiliate companies within chaebols and examine whether the operational management performance of leading companies significantly influences that of affiliate companies. Data on conglomerates, as defined by the Korea Fair Trade Commission, were collected, along with information on companies within these groups. Subsequently, the company with the highest revenue within each group was identified as the leading company, while the remaining companies were designated as affiliate companies. Our analysis reveals a significant positive relationship between the performance of inventory and facility resource management of leading companies and that of affiliate companies. This study sheds light on the transfer of operational management performance within conglomerates from a managerial perspective, underscoring the importance of reinforcing cooperation systems within the chaebol group. Furthermore, this research contributes to the academic discourse by delineating conglomerates from an operational management perspective and empirically demonstrating the transfer effect of operational management performance.

• Korean Journal of Ecology and Environment
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• v.57 no.2
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• pp.61-74
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• 2024

Daemadeung, located in the estuary of the Nakdong River, is formed by sand dunes and possesses well-developed intertidal flats. This study aimed to investigate the habitat of benthic microalgae, photosynthetic pigments, and photosynthetic efficiency in the intertidal flats of Daemadeung from January to December 2011. The inorganic nitrogen content in the sediment pore water was primarily composed of ammonium, while nitrate + nitrite was dominant in the upper layer water. The concentration of chlorophyll a and fucoxanthin in the sediment surface was significantly higher than the mean of all the sediment layer. The average Fv/Fm of benthic microalgae during the entire survey period was 0.52±0.03, with the highest value (0.61±0.08) observed in February. The rETR_max showed a seasonal trend, being high from spring to early autumn (April to October) and low from winter to early spring (January to March, November, December), with the highest value (153.05±2.30 µmol electrons m^-2 s^-1) in July and the lowest (38.49±5.17 µmol electrons m^-2 s^-1) in January. The average Fv/Fm of diurnal microalgae was 0.48±0.03, with the highest value (0.61±0.08) observed at noon. The rETR_max showed a highest peak at noon (54.24±11.35 µmol electrons m^-2 s^-1) and reached its lowest point at 16:00 (26.17±4.75 µmol electrons m^-2 s^-1). These findings suggest that the productivity of benthic microalgae varies significantly depending on the survey time and sediment depth. Therefore, to quantify the productivity of benthic microalgae using Diving-PAM, surveys should be conducted based on tidal conditions, and simultaneous pigment analysis of sediment layers should also be performed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.4
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• pp.345-363
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• 2024

Steel pipe reinforced grouting method has been widely used to strengthen the crown of tunnel face and prevent groundwater leakage during tunnel excavation. Various injection procedures without sealing have recently been suggested to enhance efficiency. There are two representative injection methods. One is simultaneous injection in segmented batches, and the other is multiple injection using the external packer. The pros and cons of each method were discussed in terms of construction duration and equipment. However, it has yet to be discussed how the injection procedure affects the grout diffusion range in the ground. This study aims to evaluate the grout diffusion range quantitatively by considering the practical grouting sequences. The grout viscosity was measured by laboratory testing. Then, the numerical modeling was structured using the commercial computational fluid dynamics software. Finally, the grout diffusion range affected by the injection procedure and ground conditions was evaluated by performing the numerical parametric study. The results showed that the injection method highly affected the grout diffusion range, especially for inhomogeneous soil. Consequently, it is anticipated that the proper method of steel pipe reinforced grouting will be suggested.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.687-692
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• 2024

The energy crisis is emerging as a serious problem around the world. In the case of Korea, there is great interest in energy efficiency research related to industrial complexes, which use more than 53% of total energy and account for more than 45% of greenhouse gas emissions in Korea. One of the studies is a study on saving energy through sharing facilities between factories using the same utility in an industrial complex called a virtual energy network plant and through transactions between energy producing and demand factories. In such energy-saving research, data collection is very important because there are various uses for data, such as analysis and prediction. However, existing systems had several shortcomings in reliably collecting time series data. In this study, we propose an intelligent IIoT platform to improve it. The intelligent IIoT platform includes a preprocessing system to identify abnormal data and process it in a timely manner, classifies abnormal and missing data, and presents interpolation techniques to maintain stable time series data. Additionally, time series data collection is streamlined through database optimization. This paper contributes to increasing data usability in the industrial environment through stable data collection and rapid problem response, and contributes to reducing the burden of data collection and optimizing monitoring load by introducing a variety of chatbot notification systems.

• The Journal of Bigdata
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• v.9 no.1
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• pp.31-47
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• 2024

With the advancement of artificial intelligence, the travel and hospitality industry is also adopting AI and machine learning technologies for various purposes. In the tourism industry, demand forecasting is recognized as a very important factor, as it directly impacts service efficiency and revenue maximization. Demand forecasting requires the consideration of time-varying data flows, which is why statistical techniques and machine learning models are used. In recent years, variations and integration of existing models have been studied to account for the diversity of demand forecasting data and the complexity of the natural world, which have been reported to improve forecasting performance concerning uncertainty and variability. This study also proposes a new model that integrates various machine-learning approaches to improve the accuracy of hotel sales demand forecasting. Specifically, this study proposes a new time series forecasting model based on XGBoost that selectively utilizes a local model by clustering with DTW K-means and a global model using the entire data to improve forecasting performance. The hotel demand forecasting model that selectively utilizes global and regional models proposed in this study is expected to impact the growth of the hotel and travel industry positively and can be applied to forecasting in other business fields in the future.

• The Journal of Bigdata
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• v.8 no.2
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• pp.73-82
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• 2023

With 78% of current fisheries workers being elderly, there's a pressing need to address labor shortages. Consequently, active research on smart aquaculture technologies, centered on object detection and tracking algorithms, is underway. These technologies allow for fish size analysis and behavior pattern forecasting, facilitating the development of real-time monitoring and automated systems. Our study utilized video data from cameras outside aquaculture facilities and implemented fish detection and tracking algorithms. We aimed to tackle high maintenance costs due to underwater conditions and camera corrosion from ammonia and pH levels. We evaluated the performance of a real-time system using YOLOv7 for fish detection and the SORT algorithm for movement tracking. YOLOv7 results demonstrated a trade-off between Recall and Precision, minimizing false detections from lighting, water currents, and shadows. Effective tracking was ascertained through re-identification. This research holds promise for enhancing smart aquaculture's operational efficiency and improving fishery facility management.