• BMB Reports
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• v.38 no.5
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• pp.602-608
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• 2005

As a crucial transcription factor family, heat-shock factors were mainly analyzed and characterized in tomato and Arabidopsis. In this study, we isolated two putative heat shock factors OsHSF6 and OsHSF12 that interact specifically with heat-shock element (HSE) from Oryza sativa L by yeast one-hybrid method. The full-length cDNA of OsHSF6 and OsHSF12 have 1074bp and 920bp open reading frame (ORF), respectively. Analysis of the deduced amino acid sequences revealed that OsHSF6 was a class A heat shock factor (HSF) with all the conserved sequence elements characteristic of heat stress transcription factor, while OsHSF12 was a class B HSF with C-terminal domain (CTD) lacking of AHA motif. Bioinformatic analysis showed that the sequences and structures of two HSFs' DNA binding domain (DBD) had a high similarity with LpHSF24. The results of RT-PCR indicated OsHSF6 gene was expressed immediately after rice plants exposure to heat stress, and the transcription of OsHSF6 gene accumulated primarily in immature seeds, roots and leaves. However, we did not find the transcription of OsHSF12 gene in different organs and growth periods. Our results implied that OsHSF6 might be function as a HSF regulating early expression of stress genes in response to heat shock, and OsHSF12 might be act as a synergistic factor to regulate the expression of down-stream genes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.3
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• pp.451-458
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• 2022

In Korea, five major ports have been designated as sulfur oxide emission control areas to reduce air pollutant emissions, in accordance with Article 10 of the "Special Act on Port Air Quality" and Article 32 of the "Ship Pollution Prevention Regulations". As regulations against vessel-originated air pollutants (such as PM, CO2, NOx, and SOx) have been strengthened, the Ministry of Oceans and Fisheries(MOF) enacted rules that newly built public ships should adopt eco-friendly propulsion systems. However, particularly in diesel-electric hybrid propulsion systems,the demand for precise control schemes continues to grow as the fuel saving rate significantly varies depending on the control strategy applied. The conventional Power Take In-Power Take Off(PTI - PTO) mode control adopts a rule-based strategy, but this strategy is applied only in the low-load range and PTI mode; thus, an additional method is required to determine the optimal fuel consumption point. The proposed control method is designed to optimize fuel consumption by applying the equivalent consumption minimization strategy(ECMS) to the PTI - PTO mode by considering the characteristics of the specific fuel oil consumption(SFOC) of the engine in a diesel-electric hybrid propulsion system. To apply this method, a specific fishing vessel model operating on the Korean coast was selected to simulate the load operation environment of the ship. In this study, a 10.2% reduction was achieved in the MATLAB/SimDrive and SimElectric simulation by comparing the fuel consumption and CO2 emissions of the ship to which the conventional rule-based strategy was applied and that to which the ECMS was applied.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.420-426
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• 2022

Breast cancer is among the cancers that may be healed as the disease diagnosed at early times before it is distributed through all the areas of the body. The Automatic Analysis of Diagnostic Tests (AAT) is an automated assistance for physicians that can deliver reliable findings to analyze the critically endangered diseases. Deep learning, a family of machine learning methods, has grown at an astonishing pace in recent years. It is used to search and render diagnoses in fields from banking to medicine to machine learning. We attempt to create a deep learning algorithm that can reliably diagnose the breast cancer in the mammogram. We want the algorithm to identify it as cancer, or this image is not cancer, allowing use of a full testing dataset of either strong clinical annotations in training data or the cancer status only, in which a few images of either cancers or noncancer were annotated. Even with this technique, the photographs would be annotated with the condition; an optional portion of the annotated image will then act as the mark. The final stage of the suggested system doesn't need any based labels to be accessible during model training. Furthermore, the results of the review process suggest that deep learning approaches have surpassed the extent of the level of state-of-of-the-the-the-art in tumor identification, feature extraction, and classification. in these three ways, the paper explains why learning algorithms were applied: train the network from scratch, transplanting certain deep learning concepts and constraints into a network, and (another way) reducing the amount of parameters in the trained nets, are two functions that help expand the scope of the networks. Researchers in economically developing countries have applied deep learning imaging devices to cancer detection; on the other hand, cancer chances have gone through the roof in Africa. Convolutional Neural Network (CNN) is a sort of deep learning that can aid you with a variety of other activities, such as speech recognition, image recognition, and classification. To accomplish this goal in this article, we will use CNN to categorize and identify breast cancer photographs from the available databases from the US Centers for Disease Control and Prevention.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.447-452
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• 2024

As the remarkable achievements of generative artificial intelligence technology become increasingly visible, the issue of 'controllability' in artificial intelligence is emerging as a prominent global keyword. This comes at a time when existential threats, such as the possibility of machines dominating humans, are being raised. Accordingly, this study aims to establish the groundwork for shaping a social public sphere by closely examining the concept of control, the current status, and the global landscape of artificial intelligence. It seeks to address the innovative changes anticipated in future society, with artificial intelligence technology at its core. The study aims to derive implications for preparing countermeasures against social problems and unpredictable variables that may arise from the evolution of artificial intelligence technology. It also aims to present guidelines and strategic insights for the establishment of government regulations. Furthermore, the study seeks to uncover implications for the formation of social public discourse.

• Journal of Aerospace System Engineering
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• v.14 no.1
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• pp.44-53
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• 2020

In conjunction with the Fourth Industrial Revolution, the unmanned aerial vehicle industry is being developed to a new paradigm by combining advanced technologies such as AI, Big Data and the IoT. Aeronautical developed countries such as the U.S. are focusing their efforts on the development of the safer unmanned aerial vehicles. The Korea Aerospace Research Institute, as part of the national R&D project in 2011, had succeeded in developing the first vertical takeoff and landing (VTOL) UAS, called Smart-UAV. However, although the development technology of the VTOL UAS is possessed, developing and operating of the VTOL UAS for commercial or military use are limited. The type certification procedure of the VTOL UAS developed by domestic technology is stipulated in the Korean Aviation Safety Act, but the Korean VTOL UAS airworthiness standards (KAS) hsve not been established. Thus, this study investigated the development trends of the VTOL UAS in Korea and abroad and national certification systems and procedures, and benchmarked the special conditions for the VTOL aircraft, announced by the EASA on July 2, 2019, to establish standards for type certificate of the VTOL UAS in Korea.

• Solar Energy
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• v.17 no.4
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• pp.3-11
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• 1997

Because grain boundaries in polycrystalline silicon act as potential barriers and recombination centers for the photo-generated charge carriers, these defects degrade conversion effiency of solar cell. To reduce these effects of grain boundaries, we investigated various influencing factors such as thermal treatment, various grid pattern, selective wet etching for grain boundaries, buried contact metallization along grain boundaries, grid on metallic thin film. Pretreatment above $900^{\circ}C$ in $N_2$ atmosphere, gettering by $POCl_3$ and Al treatment for back surface field contributed to obtain a high quality poly-Si. To prevent carrier losses at the grain boundaries, we carried out surface treatment using Schimmel etchant. This etchant delineated grain boundaries of $10{\mu}m$ depth as well as surface texturing effect. A metal AI diffusion into grain boundaries on rear side reduced back surface recombination effects at grain boundaries. A combination of fine grid with finger spacing of 0.4mm and buried electrode along grain boundaries improved short circuit current density of solar cell. A ultra-thin Chromium layer of 20nm with transmittance of 80% reduced series resistance. This paper focused on the grain boundary effect for terrestrial applications of solar cells with low cost, large area, and high efficiency.

• Strategy21
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• s.44
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• pp.5-27
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• 2018

The purpose of this paper is to look at USN's efforts to rebuild its combat power in the face of a reemergence of great powers competition, and to propose some recommendations for the ROKN. In addition to the plan to augment its fleet towards a 355-ships capacity, the USN is pursuing to improve exponentially combat lethality(quality) of its existing fleet by means of innovative science and technology. In other words, the USN is putting its utmost efforts to improve readiness of current forces, to modernize maintenance facilities such as naval shipyards, and simultaneously to invest in innovative weapons system R&D for the future. After all, the USN seems to pursue innovations in advanced military Science & Technology as the best way to ensure continued supremacy in the coming strategic competition between great powers. However, it is to be seen whether the USN can smoothly continue these efforts to rebuild combat strength vis-a-vis its new competition peers, namely China and Russian navy, due to the stringent fiscal constraints, originating, among others, from the 2011 Budget Control Act effective yet. Then, it seems to be China's unilateral and assertive behaviors to expand its maritime jurisdiction in the South China Sea that drives the USN's rebuild-up efforts of the future. Now, some changes began to be perceived in the basic framework of the hitherto regional maritime security, in the name of declining sea control of the USN as well as withering maritime order based on international law and norms. However, the ROK-US alliance system is the most excellent security mechanism upon which the ROK, as a trading power, depends for its survival and prosperity. In addition, as denuclearization of North Korea seems to take significant time and efforts to accomplish in the years to come, nuclear umbrella and extended deterrence by the US is still noting but indispensible for the security of the ROK. In this connection, the naval cooperation between ROKN and USN should be seen and strengthened as the most important deterrents to North Korean nuclear and missile threats, as well as to potential maritime provocation by neighboring countries. Based on these observations, this paper argues that the ROK Navy should try to expand its own deterrent capability by pursuing selective technological innovation in order to prevent this country's destiny from being dictated by other powers. In doing so, however, it may be too risky for the ROK to pursue the emerging, disruptive innovative technologies such as rail gun, hypersonic weapon... etc., due to enormous budget, time, and very thin chance of success. This paper recommends, therefore, to carefully select and extensively invest on the most cost-effective technological innovations, suitable in the operational environments of the ROK. In particular, this paper stresses the following six areas as most potential naval innovations for the ROK Navy: long range precision strike; air and missile defense at sea; ASW with various unmanned maritime system (UMS) such as USV, UUV based on advanced hydraulic acoustic sensor (Sonar) technology; network; digitalization for the use of AI and big data; and nuclear-powered attack submarines as a strategic deterrent.

• Korean Security Journal
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• no.42
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• pp.229-249
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• 2015

As the post-cold war era and globalization go on, national security problems which were not traditional national security problems such as terrorism, crime, environmental disasters, economic crises, cyber-terrorism, diseases, and energy problems threat humanity and nations and demands changes. Also, with the change, the concept of "big government" has emerged as the role of nation expanded. The modern society sees every country change from small government to big government in order to realize the establishment of welfare state. A comprehensive interpretation of security is needed in order to comprehensive protection of citizens beyond outside invasion such as crime, new disaster, terrorism. In Korea, incidents such as Cheonan-Ham, Yeonpeyong-Do, foot-and-mouth disease, Ddos terrorism, pirates hostages, mad cow disease, AI are happening and the humanitarian support for North Korea and the summit of South and North Korea are at a standstill. Also, National emergency management system, comprehensive emergency management center, countrol tower, national security system, cooperation with citizens, establishment of legal and institutional system are needed. The importance of this research is on the reestablishment of new national security and emergency management system according to the comparison between the national security and counter-terrorism system of Korea and that of the United States which is a leading country in this field. Also, the establishment of national emergency management act is needed as a statute for effective function as currently various laws and administrative organizations are dispersed.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.123-131
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• 2021

The Fourth Industrial Revolution was triggered by data-driven digital technologies such as AI and big data. There is a rapid movement to expand the scope of data utilization to the privacy area, which was considered only a protected area. Through the revision of the Data 3 Act, laws and systems were established that allow personal information to be freely transferred and utilized under their consent. But, it will be necessary to support the platform that encompasses the entire process from collecting personal information to managing and utilizing it. In this paper, we propose a platform model that can be applied to building mydata ecosystem using personal information. It describes the six essential functional requirements for building MyData platforms and the procedures and methods for implementing them. The six proposed essential features describe consent, sharing/downloading/ receipt of data, data collection and utilization, user authentication, API gateway, and platform services. We also illustrate the case of applying the MyData platform model to real-world, underprivileged mobility support services.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.58-64
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• 2021

As the number of registered vehicles increases, traffic congestion will worsen worse, which may act as an inhibitory factor for urban social and economic development. Through accurate traffic flow prediction, various AI techniques have been used to prevent traffic congestion. This paper uses the data from a VDS (Vehicle Detection System) as input variables. This study predicted traffic flow in five levels (free flow, somewhat delayed, delayed, somewhat congested, and congested), rather than predicting traffic flow in two levels (free flow and congested). The Catboost model, which is a machine-learning algorithm, was used in this study. This model predicts traffic flow in five levels and compares and analyzes the accuracy of the prediction with other algorithms. In addition, the preprocessed model that went through RandomizedSerachCv and One-Hot Encoding was compared with the naive one. As a result, the Catboost model without any hyper-parameter showed the highest accuracy of 93%. Overall, the Catboost model analyzes and predicts a large number of categorical traffic data better than any other machine learning and deep learning models, and the initial set parameters are optimized for Catboost.