• KOREAN JOURNAL OF CROP SCIENCE
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• v.32 no.2
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• pp.224-233
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• 1987

Most of the japonica rice varieties preferred for high eating quality are liable to lodging even under moderate rate of nitrogen application. This lodging liability has been a critical limit even for proper evaluation of physio-logical characteristics of those varieties exhibitable under higher nitrogen levels. Use of recent inhibitors of gibberellin biosynthesis such as ‘Pac1obutrazol’ may allow us to overcome this barrier. The responses of four high eating quality varieties to nitrogen application to the level of 150kg N per ha were evaluated with and without use of Paclobutrazol in comparison with a non-lodging, improved short japonica, Dongjin and a non-lodging, high yielding indica x japonica Milyang 23. The four were Damageum (the best eating quality in the 1930s), Nongrim 6 (the best in the 1960s), Chuchung (the best since 1970s), Koshihikari (the best in Japan since 1960s). As expected increased application of nitrogen increased plant height, length of the 3rd internode, and lodg-ing liability, being measured as culm breaking load, in all varieties tested and caused actual lodging in the fiel from the 50kg Nfha level in Damageum and Koshihikari and at the level of l50kg Nfha in Nongrim 6. Applica-tion of Pac1obutrazol (0.6%G) 15 days before heading reduced plant height, length of the 3rd internode and lodging liability being measured as culm breaking load in all varieties tested. However, the application of Pac1obutrazol during active tillering stage resulted in decreased culm breaking load in Damageum, Nongrim 6, and Koshihikari in spite of the decreased plant height and culm length as in the other varieties. Maximum yield was obtained with 100kg Nand 30kg Pac1obutrazol at 15 days before heading in Nongrim 6, 150kg N and 30kg Pac1obutrazol at 15 days before heading in Damageum, and 150kg N and 20kg Paclobutrazol at 20 days after transplanting plus 30kg Paclobutrazol at 15 days before heading in the variety Koshinhikari and Chuchung. Under a sensory evaluation of cooked rice, the four high eating quality varieties were not different in rank and Paclobutrazol treated rice was not distinguished from the untreated in eating quality.

• Journal of Popular Narrative
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• v.25 no.1
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• pp.217-247
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• 2019

This research paper intends to examine the intertextuality of Klaus Mann's novel Mephisto (1936) and István Szabó's film Mephisto (1981) and how the derivative contents (i.e., film) accepted and improved the schematic aesthetics of conviction in original contents (i.e., novel). In general, the aesthetics of conviction is applied to criticize the state socialism of the artists of the Third Reich or the ideology of the artists of East Germany from a biased ethical perspective. Mephisto is also based on the aesthetics of conviction. Thus, it would be meaningful to examine the characteristic similarity and difference between Klaus Mann's real antagonist (i.e., Gustaf Gründgens) and fictional antagonist (i.e., Hendrik Höfgen) from a historical critical perspective. In this process, an aesthetic distance between the real and fictional antagonists would be secured through the internal criticism in terms of intertextuality. In this respect, the film aesthetics of István Szabó are deemed to overcome the schematic limit of the original novel. The conviction in both the novel and film of Mephisto pertains to the belief and stance of a person who compromised with the state socialism of Nazi Germany, i.e., succumbed to the irresistible history. Klaus Mann denounced Mephisto's character Höfgen (i.e., Gründgens in reality) as an "Mephisto with evil spirits" from the perspective of exile literature. For such denunciation, Klaus Mann used various means such as satire, caricature, sarcasm, parody and irony. However, his novel is devoid of introspection and "utopianism", and thus could be considered to allow personal rights to be disregarded by the freedom of art. On the contrary, István Szabó employed the two different types of evil (evil of Mephisto and evil of Faust) from a dualistic perspective (instead of a dichotomous perspective of good and evil) by expressing the character of Höfgen like both Mephisto and Hamlet (i.e., "Faust with both good and evil spirits). However, Szabó did not present the mixed character of "Mephisto and Hamlet (Faust)" only as an object of pity. Rather, Szabó called for social responsibility by showing a much more tragic end. As such, the novel Mephisto is more like the biography of an individual, and the film Mephisto is more like the biography of a generation. The aesthetics of conviction of Mephisto appears to overcome biased historical and textual perspectives through the irony of intertextuality between the novel and the film. Even if history is an irresistible "fate" to an individual, human dignity cannot be denied because it is the "value of life". The issue of conviction is not only limited to the times of Nazi Germany. It can also be raised with the ideology of the modern and contemporary history of Korea. History is so deeply rooted that it should not be criticized merely from a dichotomous perspective. When it comes to the relationship between history and individual life, a neutral point of view is required. Hopefully, this research paper will provide readers with a significant opportunity for finding out their "inner Mephisto" and "inner Hamlet."

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.471-480
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• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• Maritime Security
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• v.7 no.1
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• pp.31-60
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• 2023

This study proposes a new convergence weapon system that combines the covert placement and detection abilities of a self-propelled mobile mine with the rapid tracking and attack abilities of supercavitating rocket torpedoes. This innovative system has been designed to counter North Korea's new underwater weapon, 'Haeil'. The concept behind this convergence weapon system is to maximize the strengths and minimize the weaknesses of each weapon type. Self-propelled mobile mines, typically placed discreetly on the seabed or in the water, are designed to explode when a vessel or submarine passes near them. They are generally used to defend or control specific areas, like traditional sea mines, and can effectively limit enemy movement and guide them in a desired direction. The advantage that self-propelled mines have over traditional sea mines is their ability to move independently, ensuring the survivability of the platform responsible for placing the sea mines. This allows the mines to be discreetly placed even deeper into enemy lines, significantly reducing the time and cost of mine placement while ensuring the safety of the deployed platforms. However, to cause substantial damage to a target, the mine needs to detonate when the target is very close - typically within a few yards. This makes the timing of the explosion crucial. On the other hand, supercavitating rocket torpedoes are capable of traveling at groundbreaking speeds, many times faster than conventional torpedoes. This rapid movement leaves little room for the target to evade, a significant advantage. However, this comes with notable drawbacks - short range, high noise levels, and guidance issues. The high noise levels and short range is a serious disadvantage that can expose the platform that launched the torpedo. This research proposes the use of a convergence weapon system that leverages the strengths of both weapons while compensating for their weaknesses. This strategy can overcome the limitations of traditional underwater kill-chains, offering swift and precise responses. By adapting the weapon acquisition criteria from the Defense force development Service Order, the effectiveness of the proposed system was independently analyzed and proven in terms of underwater defense sustainability, survivability, and cost-efficiency. Furthermore, the utility of this system was demonstrated through simulated scenarios, revealing its potential to play a critical role in future underwater kill-chain scenarios. However, realizing this system presents significant technical challenges and requires further research.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.