• Journal of Sericultural and Entomological Science
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• v.13 no.2
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• pp.123-133
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• 1971

The author is the first man who tried to use an anesthetic on insect specially for silkworm in orde to evaluate the silkworm health and silk yielding ability and the obtained results are as followings. 1. The necessary ether vapor induction for narcosis on silkworms is varied by the glowth of the silkworm which the larger worm is, the longer induction is required. For instance, it was 2∼3 minutes for the worms of third day fifth instar silkworm in case use of ether anesthetic. 2. The longer anesthetic induction for silkworms, the longer recovery needs from anesthesia. In case five minutes ether vapor induction, silkworms recovered narcosis during in 5∼130 minutes which had varied very much by the health variation. 3. The ether induction caused silkworm to vomit digestive juice from a few per cent of the worms, but the chloroform induction showed majority of the worms to vomit the digestive juice out of mouth. So, the ether was found as better anesthetic for silkworms. 4. When ether induction last more than 20∼30 minutes, the recovered silkworms can eat mulberry, but when it gets more than three hours they can not eat mulberry. And when it last more than ten minutes, the silkworm may eat mulberry leaf, but they can not spinn cocoon properly. 5. In case five minutes ether induction for silkworms on third day fifth instar, the stronger variety is, the rallier recovered from narcosis. 6. The recovering duration from narcosis varies regarding with each worm health which shows Poisson′s distribution even in a same variety silkworm. 7. The female worms recover from narcosis earlier than male worms which means the female worm is stronger than male one. 8. The later recovered silkworm from narcosis spinned more rich cocoon silk and ended with smaller pupae weight. Such a tendency showed until at some recovery duration, then the silk yield droped down on the worms recovered in more longer duration. The author (Choe) had named such a relation curve as "Silk Yield Curve against Silkworm Health." 9. The silk yield or cocoon layer ratio had varied from 13 to 27% even in a same worm varity cocoon which showed serious variation and call attention carefulness for the duplication work of a variety silkworm eggs. 10. Not always the rich silk yielding worm is the best worm during the silkworm selection and it should be considered with the silkworm health evaluation. 11. At present situation, only specific breeding expert is allowed to join in the selection service because of need many years experience by use of visual observation, but the ether anesthesia method may help such an evaluation with more accuracy and easy way even for the people in fresh on the field. 12. The effect of the narcosis on the silkworm for the next generation or hybrid worm will be reported in next publication.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.81-90
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• 2009

It is inevitable for college students to be confused when they first face university education, which requires them to be self-reliant and responsible, after finishing their course of education, which is passive under control of period and environment, in primary, middle, and high schools. Introduction to college courses, which require students to be subjective and responsible, to be taken after chronically and environmentally controlled primary and secondary education, are but confusing. In this stage, college education should provide ground for educational system so that students can escape from repetitively enforced way of studying of fixed curriculums and study creatively and subjectively while befitting each individual's aptitude. For instance, in programming classes in engineering school, students scholastic achievements are closely interrelated with the professor's educational principles. A change in method of education, from one previously focused on theoretical contents to one centered on practices and experiments, can reap good results. Also, as the need arose for introduction of practice-focused evaluation system, from recognition-centered professor evaluating system to enablement of actively developing creative and self-reliant way of learning, we applied the Rublic System. It is a feedback system that all or most students become the evaluators, of which the indicators of evaluation such as category, standard, and score are public. We have looked into whether or not there has been an improvement in GPAs of students, and if there exists an improvement then what efforts should be made to solidify the system.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.73-82
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• 2022

Auto-scaling is one of the most important functions for cloud computing technology. Even if the number of users or service requests is explosively increased or decreased, system resources and service instances can be appropriately expanded or reduced to provide services suitable for the situation and it can improves stability and cost-effectiveness. However, since the policy is performed based on a single metric data at the time of monitoring a specific system resource, there is a problem that the service is already affected or the service instance that is actually needed cannot be managed in detail. To solve this problem, in this paper, we propose a method to predict system resource and service response time using a multivariate time series analysis model and establish an auto-scaling policy based on this. To verify this, implement it as a custom scheduler in the Kubernetes environment and compare it with the Kubernetes default auto-scaling method through experiments. The proposed method utilizes predictive data based on the impact between system resources and response time to preemptively execute auto-scaling for expected situations, thereby securing system stability and providing as much as necessary within the scope of not degrading service quality. It shows results that allow you to manage instances in detail.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• The Korean Journal of Franchise Management
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• v.3 no.1
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• pp.111-129
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• 2012

Domestic franchise industry is a promising business to more than 10% per year growth rate and emerging as core of retail. In addition, due to the socio-cultural phenomena, including the retirement of the baby-boom generation, the growth of the franchise industry for some time expected to continue. But Domestic franchise reveals that limits to ensure for new franchisees because that few industries are concentrated to advance for franchisor and franchisees. Franchisors that within the industry came to a saturated, are for the growth and expansion of business into new industries to deploy as second, third brand. But reality is that the more success rather than failure. Therefore, in this study is a new brand development approach and case study results it focus on the BEERBARKET's successful story of INTO FRANCHISE SYSTEMS, INC. Case analysis results of this study, are reveled that franchise headquarters derived through research methods and research information, environmental survey and analysis should be continuously and objectively. Thus, based on the derived contents, the new brand Biz-Model should be established for recognition from the industry and customers. Ability to respond sensitively to changes in the environment and business activities can be associated with linking franchise headquarters belonging to the saturated competitive environment more is needed. Through proactively respond Franchise New business launching instance that BEERBARKET's successful story of INTO FRANCHISE SYSTEMS, INC. suggests the need to study about how to respond to environmental changes.

• Steel and Composite Structures
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• v.48 no.2
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• pp.163-177
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• 2023

Complex and intricate preparation techniques, the imperative for utmost precision and sensitivity in instrumentation, premature sample failure, and fragile specimens collectively contribute to the arduous task of measuring the fracture toughness of concrete in the laboratory. The objective of this research is to introduce and refine an equation based on the gene expression programming (GEP) method to calculate the fracture toughness of reinforced concrete, thereby minimizing the need for costly and time-consuming laboratory experiments. To accomplish this, various types of reinforced concrete, each incorporating distinct ratios of fibers and additives, were subjected to diverse loading angles relative to the initial crack (α) in order to ascertain the effective fracture toughness (Keff) of 660 samples utilizing the central straight notched Brazilian disc (CSNBD) test. Within the datasets, six pivotal input factors influencing the Keff of concrete, namely sample type (ST), diameter (D), thickness (t), length (L), force (F), and α, were taken into account. The ST and α parameters represent crucial inputs in the model presented in this study, marking the first instance that their influence has been examined via the CSNBD test. Of the 660 datasets, 460 were utilized for training purposes, while 100 each were allotted for testing and validation of the model. The GEP model was fine-tuned based on the training datasets, and its efficacy was evaluated using the separate test and validation datasets. In subsequent stages, the GEP model was optimized, yielding the most robust models. Ultimately, an equation was derived by averaging the most exemplary models, providing a means to predict the Keff parameter. This averaged equation exhibited exceptional proficiency in predicting the Keff of concrete. The significance of this work lies in the possibility of obtaining the Keff parameter without investing copious amounts of time and resources into the CSNBD test, simply by inputting the relevant parameters into the equation derived for diverse samples of reinforced concrete subject to varied loading angles.

• Journal of Space Technology and Applications
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• v.3 no.2
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• pp.101-117
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• 2023

Active debris removal, a technology that approaches and removes space debris in orbit, and the on-orbit service, a technology for extending the mission life of satellites by fuel charging or by exchanging the battery, are gaining interest with the growth of the space community. SaTReC plans to develop a satellite capable of capturing and removing Korean satellites orbiting in space after the end of their missions. In contrast to the previously launched satellites by Korea, which were mainly intended to observe Earth and the space environment, rendezvous/docking technologies, as required in the future during, for instance, space exploration missions, will be implemented and demonstrated. In this paper, an orbital transition method for next-generation small satellites that will capture and remove space debris will be introduced. It is assumed that a small satellite with a mass of approximately 200 kg will be injected into the mission orbit through Korea Space Launch Vehicle-II in 2027. Because the satellite must access the target using a minimum amount of fuel, an approaching technology using Earth's J2 perturbation force has been developed. This method is expected to enable space debris removal missions for relatively lightweight satellites and to serve as the basis for carrying out a new type of space exploration in what is termed the 'Newspace' era.

• 한국노년학
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• v.29 no.1
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• pp.21-35
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• 2009

The aim of this study is to make clear the characteristics of elderly comsumer behaviors and to provide information for the organ and company preparing aging friendly industry. This information is actual data which analyzed elderly consumer behaviors according to sociology of Population criterion. The first survey was conducted to 600 elderly about the degree of products preference, the criterion of products selection, actual purchaser, the preferring medium. To compare elderly consumer behaviors to young consumer behaviors, the second survey was conducted to 400 elderly and young persons. The results are in following. First, the crucial factors of elderly consumers making select products is the function of products. Second, when planning marketing for elderly consumers, company needs to investigate factors affecting elderly consumers behaviors, for instance the educational level, a monthly income level, age, sex, and so on. Third, elderly consumers were the most interested in health products. Specially, male elderly consumers in leisure sports and tour products. Fourth, elderly consumers is active for economic respect and independent for social respect.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.57-57
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• 2022

In many areas of the world, salt damage and drought have had a negative impact on human survival due to a decrease in agricultural productivity. For instance, about 50% of agricultural land will be affected by salt damage by 2050. Biostimulants such as plant extracts can not only increase the nutrient utilization efficiency of plants, but also promote plant growth and increase resistance to abiotic or biotic stress. Therefore, the objective of this study was to determine how selected plant extracts might reduce levels of stress caused by drought and salt and to better understand the physiological response mechanisms of rice plants. In this study, we used Soybean leaves, Soybean stems and Allium tuberosum, Allium cepa, Hizikia fusiforme, and Gracilaria verrucosa extracts were used. These extracts had been used in previous studies and were found to be effective. The materials were dried in a dry oven at 50℃ for 5 days and ground using a blender. Each 50 g of materials was put in 1 L of distilled water, stirred for 24 hours, filtered using 4 layers of mirocloth, and then concentrated using a concentrator. Rice (cv. Hopumbyeo) seeds were immersed and germinated, and then sown in seedbeds filled with commercial soil. In drought experiments, three rice seedlings at 1 week after seeding was transplanted into 100 ml cups filled with commercial soils and grown until the 4-leaf stage. For this experiment, the soil weight in a cup was equalized, and water was allowed to become 100% saturated and then drained for 24 hours. Thereafter, plant extracts at 3% concentrations were applied to the soils. For NaCl treatments, rice plants at 17 days after seeding were treated with either 100 mM NaCl or plant extracts at 1%+ 100 mM NaCl combinations in the growth chamber. Leaf injury, relative water content, photosynthetic efficiency, and chlorophyll contents were measured at 3, 5, and 6 days after treatments. Shoot fresh weight of rice under drought conditions increased 28-37% in response to treatments of Soybean leaf, Soybean stem, Allium tuberosum, Allium cepa, Hizikia fusiforme, and Gracilaria verrucosa extracts at 3% when compared with control plants. Shoot fresh weight of rice subjected to 100 mM NaCl treatments also increased by 6-24% in response to Soybean leaf, Soybean stem, Allium tuberosum, Allium cepa, Hizikia fusiforme, and Gracilaria verrucosa extracts at 3% when compared with control plants. Compared to the control, rice plants treated with these six extracts and subjected to drought conditions had significantly higher relative water content, Fv/Fm, total chlorophyll and total carotenoids than control plants. With the exception of relative water contents, rice plants treated with the six extracts and subjected to salt stress (100 mM NaCl treatments) had significantly higher Fv/Fm, total chlorophyll and total carotenoids than control plants. However, the type of extract used did not produce significant difference in these parameters. Thus, all the plant extracts used in this study could mitigate drought and NaCl stresses and could also contribute substantially to sustainable crop production.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.33-43
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• 2024

This research assessed the applicability of the You Only Look Once (YOLO)v8 and DeepLabv3+ models for the effective detection of compost heaps, identified as a significant source of non-point source pollution. Utilizing high-resolution imagery acquired through Unmanned Aerial Vehicles(UAVs), the study conducted a comprehensive comparison and analysis of the quantitative and qualitative performances. In the quantitative evaluation, the YOLOv8 model demonstrated superior performance across various metrics, particularly in its ability to accurately distinguish the presence or absence of covers on compost heaps. These outcomes imply that the YOLOv8 model is highly effective in the precise detection and classification of compost heaps, thereby providing a novel approach for assessing the management grades of compost heaps and contributing to non-point source pollution management. This study suggests that utilizing UAVs and deep learning technologies for detecting and managing compost heaps can address the constraints linked to traditional field survey methods, thereby facilitating the establishment of accurate and effective non-point source pollution management strategies, and contributing to the safeguarding of aquatic environments.