• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• Convergence Security Journal
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• v.24 no.1
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• pp.11-20
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• 2024

Recently, smart buildings that can efficiently manage energy using ICT technology and operate and control through the building automation system by collecting data from a large number of IoT sensors in real time are attracting attention. However, as data management is carried out through an open environment, the safety of smart buildings is threatened by the security vulnerability of the existing building automation protocol. Therefore, in this paper, we analyze the major data link technology of BACnet, which is used universally, and propose OWE-based efficient BACnet/SC that can ensure the reliability of data in a wireless environment. The proposed protocol enables safe communication even in an open network by applying OWE and provides the same level of security as BACnet/SC in a TLS environment. As a result, it reduces the connection process twice and reduces the average time required by 40%, enabling more efficient communication than before.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1273-1300
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• 2024

In the complex virtual environment of cyberspace, comprised of digital and communication networks, ensuring the security of information is being recognized as an ongoing challenge. The importance of 'Cyber Situation Awareness (CSA)' is being emphasized in response to this. CSA is understood as a vital capability to identify, understand, and respond to various cyber threats and is positioned at the heart of cyber security strategies from a defensive perspective. Critical industries such as finance, healthcare, manufacturing, telecommunications, transportation, and energy can be subjected to not just economic and societal losses from cyber threats but, in severe cases, national losses. Consequently, the importance of CSA is being accentuated and research activities are being vigorously undertaken. A systematic five-step approach to CSA is introduced against this backdrop, and a deep analysis of recent research trends, techniques, challenges, and future directions since 2019 is provided. The approach encompasses current situation and identification awareness, the impact of attacks and vulnerability assessment, the evolution of situations and tracking of actor behaviors, root cause and forensic analysis, and future scenarios and threat predictions. Through this survey, readers will be deepened in their understanding of the fundamental importance and practical applications of CSA, and their insights into research and applications in this field will be enhanced. This survey is expected to serve as a useful guide and reference for researchers and experts particularly interested in CSA research and applications.

• ALGAE
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• v.39 no.1
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• pp.17-30
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• 2024

Red macroalga Pyropia yezoensis is a high valuable cultivated marine crop. Its acclimation to cold stress is especially important for long cultivation period across winter in coasts of warm temperate zone in East Asia. In this study, the response of P. yezoensis thalli to low temperature was analyzed on physiology and transcriptome level, to explore its acclimation mechanism to cold stress. The results showed that the practical photosynthesis activity (indicated by Φ_PSII and qP) was depressed and pigment allophycocyanin content was decreased during the cold stress of 48 h. However, the F_v/F_m and non-photochemical quenching increased significantly after 24 h, and the average growth rate of thalli also rebounded from 24 to 48 h, indicating a certain extent of acclimation to cold stress. On transcriptionally, the low temperature promoted the expression of differentially expressed genes (DEGs) related to carbohydrate metabolism and energy metabolism, while genes related to photosynthetic system were depressed. The increased expression of DEGs involved in ribosomal biogenesis and lipid metabolism which could accelerate protein synthesis and enhance the degree of fatty acid unsaturation, might help P. yezoensis thallus cells to cope with cold stress. Further co-expression network analysis revealed differential expression trends along with stress time, and corresponding hub genes play important roles in the systemic acquired acclimation to cold stress. This study provides basic mechanisms of P. yezoensis acclimation to cold temperature and may aid in exploration of functional genes for genetic breeding of economic macroalgae.

• Journal of Radiation Industry
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• v.17 no.3
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• pp.225-232
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• 2023

In this study, poly(ethylene-co-vinyl acetate)/magnesium hydroxide (EVA/MDH) composites were prepared by electron beam crosslinking. EVA as a matrix resin and MDH as a flame retardant were melt-blended and compression molded to prepare EVA/MDH composites. The prepared EVA/MDH composites were electron beam-irradiated at various absorbed doses of 50~200kGy. The effects of electron beam irradiation on the gel content, tensile strength, elongation-at-break, thermal properties, and flame retardancy of the composites were investigated. The gel content and tensile strength increased, while the elongation-at-break decreased with an increase in the absorbed dose due to the formation of crosslinked network structures. In addition, the thermal stability and flame retardancy improved as the absorbed dose increased. Therefore, the EVA/MDH composites prepared in this study can be used as an insulation material for flame-retardant and heat-resistant wires and cables.

• Journal of Animal Science and Technology
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• v.66 no.3
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• pp.567-576
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• 2024

Subclinical ketosis (SCK) is a prevalent metabolic disorder that occurs during the transition to lactation period. It is defined as a high blood concentration of ketone bodies (beta-hydroxybutyric acid f ≥ 1.2 mmol/L) within the first few weeks of lactation, and often presents without clinical signs. SCK is mainly caused by negative energy balance (NEB). The objective of this study is to identify single nucleotide polymorphisms (SNPs) associated with SCK using genome-wide association studies (GWAS), and to predict the biological functions of proximal genes using gene-set enrichment analysis (GSEA). Blood samples were collected from 112 Holstein cows between 5 and 18 days postpartum to determine the incidence of SCK. Genomic DNA extracted from both SCK and healthy cows was examined using the Illumina Bovine SNP50K BeadChip for genotyping. GWAS revealed 194 putative SNPs and 163 genes associated with those SNPs. Additionally, GSEA showed that the genes retrieved by Database for Annotation, Visualization, and Integrated Discovery (DAVID) belonged to calcium signaling, starch and sucrose, immune network, and metabolic pathways. Furthermore, the proximal genes were found to be related to germ cell and early embryo development. In summary, this study proposes several feasible SNPs and genes associated with SCK through GWAS and GSEA. These candidates can be utilized in selective breeding programs to reduce the genetic risk for SCK and subfertility in high-performance dairy cows.

• Clean Technology
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• v.30 no.3
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• pp.258-266
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• 2024

Rechargeable Li-SnO₂ batteries suffer from issues such as poor electronic/ionic conductivity and huge volume changes. In order to overcome these inherent limitations, this study designed a cell with a unique hierarchical structure, denoted as SnO₂@PCNF. The SnO₂@PCNF cell design incorporates in-situ generated SnO₂ nanoparticles strategically positioned within N-doped porous carbon nanofibers (PCNF). The in-situ generated SnO₂ nanoparticles can alleviate strains during cycling and shorten the pathway for the ions and electrons, improving the utilization of active materials. Moreover, the N-doped PCNF establishes a continuously conductive network to further increase the electrical conductivity and also buffers the significant volume changes that occur during charging and discharging. The resulting SnO₂@PCNF cell exhibits outstanding electrochemical performance and stable cycling characteristics. Notably, a reversible capacity of 520 mAh g^-1 was achieved after 100 cycles at 70 mA g^-1. Even under a higher current density of 1 A g^-1, the cell maintained a capacity retention of 393 mAh g^-1 after 1,000 cycles. These results highlight the SnO₂@PCNF cell's exceptional cycling stability and superior rate capability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.2028-2042
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• 1994

Properly defining signal and noise in a self-organizing system like ART(Adaptive Resonance Theory) neural network model raises a number of subtle issues. Pattern context must enter the definition so that input features, treated as irrelevant noise when they are embedded in a given input pattern, may be treated as informative signals when they are embedded in a different input pattern. The ATR automatically self-scales their computational units to embody context and learning dependent definitions of a signal and noise and there is no problem in categorizing input pattern that have features similar in nature. However, when we have imput patterns that have features that are different in size and nature, the use of only one vigilance parameter is not enough to differentiate a signal from noise for a good categorization. For example, if the value fo vigilance parameter is large, then noise may be processed as an informative signal and unnecessary categories are generated: and if the value of vigilance parameter is small, an informative signal may be ignored and treated as noise. Hence it is no easy to achieve a good pattern categorization. To overcome such problems, a Coupled-ART neural network capable of modularized categorization of patterns is proposed. The Coupled-ART has two layer of tightly coupled modules. the upper and the lower. The lower layer processes the global features of a pattern and the structural features, separately in parallel. The upper layer combines the categorized outputs from the lower layer and categorizes the combined output, Hence, due to the modularized categorization of patterns, the Coupled-ART classifies patterns more efficiently than the ART1 model.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.119-128
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• 2011

The Sensor technology and portable device capability able to collect recent user information and the information about the surrounding environment haven been highly developed. A user can be made use of various contents and the option is also extending with this technology development. In particular, the initial portable device had simply a call function, but now that has evolved into 'the 4th screen' which including movie, television, PC ability. also, in the past, a portable device to provided only the services of a SMS, in recent years, it provided to interactive video service, and it include technology which providing various contents. Also, it is rising as media which leading the consumption of contents, because it can be used anytime, anywhere. However, the contents available for the nature of user's handheld devices are limited. because it is very difficult for making the contents separately according to various device specification. To find a solution to this problem, the study on one contents from several device has been progressing. The contents conversion technology making use of the profile of device out of this study comes to the force and profile study has been progressing for this. Furthermore, Demand for a user is also increased and the study on the technology collecting, analyzing demands has been making active progress. And what is more, Grasping user's demands by making use of this technology and the study on the technology analyzing, providing contents has been making active progress as well. First of all, there is a method making good use of ZigBee, Bluetooth technology about the sensor for gathering user's information. ZigBee uses low-power digital radio for wireless headphone, wireless communication network, and being utilized for smart energy, automatic home system, wireless communication application and wireless sensor application. Bluetooth, as industry standards of PAN(Personal Area Networks), is being made of use of low power wireless device for the technology supporting data transmission such as drawing file, video file among Bluetooth device. With analyzing the collected information making use of this technology, it utilizes personalized service based on network knowledge developed by ETRI to service contents tailor-made for a user. Now that personalized service builds up network knowledge about user's various environments, the technology provides context friendly service constructed dynamically on the basis of this. The contents to service dynamically like this offer the contents that it converses with utilizing device profile to working well. Therefore, this paper suggests the system as follow. It collects the information, for example of user's sensitivity, context and location by using sensor technology, and generates the profile as a means of collected information as sensor. It collects the user's propensity to the information by user's input and event and generates profile in the same way besides the gathered information by sensor. Device transmits a generated profile and the profile about a device specification to proxy server. And proxy server transmits a profile to each profile management server. It analyzes profile in proxy server so that it selects the contents user demand and requests in contents server. Contents server receives a profile of user portable device from device profile server and converses the contents by using this. Original source code of contents convert into XML code using the device profile and XML code convert into source code available in user portable device. Thus, contents conversion process is terminated and user friendly system is completed as the user transmits optimal contents for user portable device.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.85-96
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• 2019

Solar radiation is an important variable for estimation of energy balance and water cycle in natural and agricultural ecosystems. A deep neural network (DNN) model has been developed in order to estimate the daily global solar radiation. Temperature and precipitation, which would have wider availability from weather stations than other variables such as sunshine duration, were used as inputs to the DNN model. Five-fold cross-validation was applied to train and test the DNN models. Meteorological data at 15 weather stations were collected for a long term period, e.g., > 30 years in Korea. The DNN model obtained from the cross-validation had relatively small value of RMSE ($3.75MJ\;m^{-2}\;d^{-1}$) for estimates of the daily solar radiation at the weather station in Suwon. The DNN model explained about 68% of variation in observed solar radiation at the Suwon weather station. It was found that the measurements of solar radiation in 1985 and 1998 were considerably low for a small period of time compared with sunshine duration. This suggested that assessment of the quality for the observation data for solar radiation would be needed in further studies. When data for those years were excluded from the data analysis, the DNN model had slightly greater degree of agreement statistics. For example, the values of $R^2$ and RMSE were 0.72 and $3.55MJ\;m^{-2}\;d^{-1}$, respectively. Our results indicate that a DNN would be useful for the development a solar radiation estimation model using temperature and precipitation, which are usually available for downscaled scenario data for future climate conditions. Thus, such a DNN model would be useful for the impact assessment of climate change on crop production where solar radiation is used as a required input variable to a crop model.