• Animal Bioscience
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• v.35 no.2_spc
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• pp.347-355
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• 2022

Among edible insects, black soldier fly (Hermetia illucens), yellow mealworm (Tenebrio molitor), and common housefly (Musca domestica) have been considered as an alternative protein source for pigs. Because they are easy to breed and grow in the organic wastes, and they have well-balanced nutritional value as a protein source for pigs. The black soldier fly larvae and mealworm could replace the fish meal in the diets for weaned pigs without adverse effects on growth performance and nutrient digestibility. Black soldier fly could also be included in the finishing pig's diet without any negative effects on the growth performance and pork quality of the market pigs. Insect products showed a greater standardized ileal digestibility value of amino acids than conventional animal proteins in growing pigs. Due to the limited amount of insect products used for pig feeding study, most previous pig studies have been conducted in weaned pigs. Thus, further study is needed about the optimal inclusion level of insect products in every phase diet from weaned pigs to sows. The use of insect products in swine diets has some challenges in terms of cost, supply, and safety. Lastly, intrinsic differences among insect species, processing method, and feeding phase should be taken into consideration for the use of insect products in the swine diets.

• Journal of Gastric Cancer
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• v.22 no.3
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• pp.169-183
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• 2022

Gastric cancer is prevalent in Korea and ranked as the third most common cancer in 2019, followed by lung and thyroid cancers. The National Cancer Screening Program (NCSP) for gastric cancer has been implemented in adults aged ≥ 40 since 1999 and involves endoscopic screening every 2 years. The beneficial effects of the current NCSP on early cancer detection, cost-effectiveness, and mortality reduction are evident. However, the screening program results in a large socioeconomic burden and the consumption of medical resources, as it focuses solely on secondary prevention (early detection) rather than primary prevention of cancer. Helicobacter pylori is defined as a group I carcinogen by the International Agency for Research on Cancer. Hence, its eradication has been suggested as an important primary gastric cancer prevention strategy. Well-designed randomized controlled trials involving high-risk groups (post-endoscopic resection of early gastric cancer and family history of gastric cancer) and long-term follow-up studies in the general population have provided high-quality evidence regarding the effects of H. pylori eradication on gastric cancer prevention. In this review, we discussed the evidences for a possible modification of the current gastric cancer secondary prevention strategy by introducing primary prevention through H. pylori eradication. Areas for future research to optimize primary prevention strategies were also suggested.

• Geomechanics and Engineering
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• v.29 no.3
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• pp.249-258
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• 2022

A disc cutter is an excavation tool on a tunnel boring machine (TBM) cutterhead; it crushes and cuts rock mass while the machine excavates using the cutterhead's rotational movement. Disc cutter wear occurs naturally. Thus, along with the management of downtime and excavation efficiency, abrasioned disc cutters need to be replaced at the proper time; otherwise, the construction period could be delayed and the cost could increase. The most common prediction models for TBM performance and for the disc cutter lifetime have been proposed by the Colorado School of Mines and Norwegian University of Science and Technology. However, design parameters of existing models do not well correspond to the field values when a TBM encounters complex and difficult ground conditions in the field. Thus, this study proposes a series of machine learning models to predict the disc cutter lifetime of a shield TBM using the excavation (machine) data during operation which is response to the rock mass. This study utilizes five different machine learning techniques: four types of classification models (i.e., K-Nearest Neighbors (KNN), Support Vector Machine, Decision Tree, and Staking Ensemble Model) and one artificial neural network (ANN) model. The KNN model was found to be the best model among the four classification models, affording the highest recall of 81%. The ANN model also predicted the wear rate of disc cutters reasonably well.

• Steel and Composite Structures
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• v.43 no.4
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• pp.501-509
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• 2022

Cracks are common defects in concrete structures. Thus far, crack inspection has been manually performed using the contact inspection method. This manpower-dependent method inevitably increases the cost and work hours. Various non-contact studies have been conducted to overcome such difficulties. However, previous studies have focused on developing a methodology for non-contact inspection or local quantitative detection of crack width or length on concrete surfaces. However, crack depth can affect the safety of concrete structures. In particular, although macrocrack depth is structurally fatal, it is difficult to find it with the existing method. Therefore, an experimental investigation based on non-contact infrared thermography and multivariate machine learning was performed in this study to estimate the hidden macrocrack depth. To consider practical applications for inspection, an experiment was conducted that considered the simulated piloting of an unmanned aerial vehicle equipped with infrared thermography equipment. The crack depths (10-60 mm) were comparatively evaluated using linear regression, gradient boosting, and random forest (AI regression methods).

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.171-176
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• 2023

What we have in common worldwide today is economic difficulties due to high inflation and uncertainty in the financial industry. The root cause of this is the war between Russia and Ukraine. The war between Russia and Ukraine is not simply a war between two countries. The United States and the European Union are providing military aid such as missiles to Ukraine, and Russia is attacking Ukraine by introducing UAVs (unmanned aerial vehicles) from Iran. A prominent weapon in this Russia-Ukraine war is the UAVs used in Russia. It is predicted that the form of war using UAVs will gradually expand in the future based on stealth. In addition, UAVs will continue to be used due to the fact that they can cause serious damage to the other country without harming their own lives, and because they have good cost-effectiveness. In this study, UAVs based on autonomous driving were studied. The target countries of the study include the United States, the European Union, China, and Iran, and the UAVs used in these countries have characteristics that can represent the world. In this study, the main specifications of major UAVs in use in major countries were investigated. In addition, the future technology and development direction were described through specifications and characteristics of UAVs currently in operation in major countries.

• Advances in nano research
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• v.12 no.1
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• pp.49-63
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• 2022

Nanocatalysts are usually used in the synthesis of petrochemical products, fine chemicals, biofuel production, and automotive exhaust catalysis. Due to high activity and stability, recyclability, and cost-effectiveness, nanocatalysts are a key area in green chemistry. On the other hand, water as a common by-product or undesired element in a range of nanocatalyzed processes may be promoting the deactivation of catalytic systems. The advancement in the field of hydrophobicity in nanocatalysis could relatively solves these problems and improves the efficiency and recyclability of nanocatalysts. Some recent developments in the synthesis of novel nanocatalysts with tunable hydrophilic-hydrophobic character have been reviewed in this article and followed by highlighting their use in catalyzing several processes such as glycerolysis, Fenton, oxidation, reduction, ketalization, and hydrodesulfurization. Zeolites, carbon materials, modified silicas, surfactant-ligands, and polymers are the basic components in the controlling hydrophobicity of new nanocatalysts. Various characterization methods such as N2 adsorption-desorption, scanning and transmission electron microscopy, and contact angle measurement are critical in the understanding of hydrophobicity of materials. Also, in this review, it has been shown that how the hydrophobicity of nanocatalyst is affected by its structure, textural properties, and surface acidity, and discuss the important factors in designing catalysts with high efficiency and recyclability. It is useful for chemists and chemical engineers who are concerned with designing novel types of nanocatalysts with high activity and recyclability for environmentally friendly applications.

• Transactions of Materials Processing
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• v.32 no.3
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• pp.122-128
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• 2023

As electric vehicles (EV) have increasingly replaced the conventional vehicles with internal combustion engines (ICE), most of automotive makers are actively devoting to the technology development of EV parts. Accordingly, the manufacturing process for power source has been also shifting from engine/transmission to EV motor/reducer system. However, lack of experience in developing the EV motor still remains as a technical challenge. In this paper, we employed the forming simulation based on finite element modeling to solve this problem. In particular, in order to increase the accuracy of the forming simulation, we introduced the elastic-plastic constitutive model parameters for polymer-copper hybrid wire by investigating the individual strain-stress curves, and elastic modulus of polymer and copper. Then, the reliability of modeling procedure was confirmed by comparing the simulated results with experiments. Finally, the identified mechanical properties and finite element modeling were applied to a hairpin forming process, which involves multiple deformation paths such as bending, pressing, widening, and twisting. The proposed numerical approach can replace common experience or experiment based trials by reducing production time and cost in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.95-95
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• 2023

Common hydrological problems of developing countries include poor data management, insufficient measuring devices and ungauged watersheds, leading to small or unreliable data availability. This has greatly affected the adoption of artificial intelligence techniques for flood risk mitigation and damage control in several developing countries. While climate datasets have recorded resounding applications, but they exhibit more uncertainties than ground-based measurements. To encourage AI adoption in developing countries with small ground-based dataset, we propose data augmentation for regression tasks and compare performance evaluation of different AI models with and without data augmentation. More focus is placed on simple models that offer lesser computational cost and higher accuracy than deeper models that train longer and consume computer resources, which may be insufficient in developing countries. To implement this approach, we modelled and predicted streamflow data of the Asa River Watershed located in Ilorin, Kwara State Nigeria. Results revealed that adequate hyperparameter tuning and proper model selection improve streamflow prediction on small water dataset. This approach can be implemented in data-scarce regions to ensure timely flood intervention and early warning systems are adopted in developing countries.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.536-542
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• 2022

Cost overruns, schedule delays, and a shortage of skilled labor are common problems the construction industry is currently experiencing. Modularization and standardization strategies have the potential to resolve the various problems mentioned above and have been applied for various construction applications for a long time. However, the level of modularization remains low, and modular construction projects have not been getting the full benefits. Thus, this review investigated the cutting-edge technologies currently being utilized to develop the modular construction field. For this paper, qualified research papers were identified using predetermined keywords from previous related research papers. Identified literature was then filtered and analyzed. According to the included reviews, several technologies are being developed for modular construction. For example, automated design and monitoring systems for modularization were developed. In addition, research labs are utilizing robotic arms for modular construction to achieve a high level of completion in the construction industry, as is seen in the manufacturing industry. Despite these efforts, more research and development are necessary because some automation technologies still require manual activities. Thus, there is great potential for further development of modularization techniques, and further research is recommended to achieve high levels of modularization.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.722-728
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• 2000

This study of field control machine in the recycled vinyl rail is gantry crane type and promoting agricultural automatization through self-controlled spraying, harvesting and conveyance. In addition to, that control machine could get a cost and labor reduction effect through automatization and make better environment by preventing farmers from agrichemical damage, accidents and recycling wasted vinyl. That machine is able to be divided as traveling, spraying, harvesting and conveyance sections. In driving section consists of girder frame, carrier, rail, control system, driving system, working machine, rail and loading device for working machine. This machine has following advantages to be able to bring a big innovation in the agricultural industry. I) Accurate performance is able to be done by proper positioning due to based on the rails. 2) The soil is not made hard like heavy tractor 3) The wheel is not sank into the soil and slipped well under rain like heavy tractor. Therefore, weather and soil situation could not affect working condition. 4) Complete unmanned control and 24hours-working are available due to traveling on the rails. 5) It could use various energy resources like not only liquid fuel but also solar, common electronic power due to traveling on the rails.