• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.322-333
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• 2019

The purpose of the current study was to investigate the level of market size and market share of domestic research equipments for analyzing the difference of the number and amount of construction by the manufacturing countries in the basic and analytical science fields based on the information of the research equipment invested by the Korean government for the past 14 years. As of January 1 2019, from 2005 to 2018, 20,687 research facilities & equipments (main equipment with a construction cost of 30 million won or more) built in the basic and analytical science fields were selected for this study and their components, standard classification, number of construction, and amount of construction by country of manufacture were analyzed. Differences of the number and amount of construction among manufacturing countries were tested using a single sample chi-square test and one-way analysis of variance, followed by Bonferroni's post-hoc test. As a result of this study, the number of construction (p<.001) and construction amount (p<.05) were statistically different for each manufacturing country. The level of market size and market share was significantly different according to the equipment standard classification (p<.05). Therefore, differentiated strategies of the government and policy research projects will be required for each type of equipment and amount in order to support the policy for the localization of research equipment.

• Journal of KIBIM
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• v.10 no.1
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• pp.9-22
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• 2020

Recently, BIM has been extended to infrastructures such as roads and bridges, and the demand for BIM standard development for ports is increasing internationally. Due to the low level of utilization of classification system and drawing standards compared to other infrastructures, and the closed nature of national security facilities, ports have insufficient level of connection and sharing environment among external systems or users. In addition, since the standardization of data for port facilities is not made, it is still necessary to establish an independent DB for each system and to ensure interoperability of data between these systems since it does not have a shared environment among similar data. Therefore, the purpose of this study is to develop and verify IFC, the international standard for BIM, in order to cope with the BIM environment and to be commonly used in the design, construction, and maintenance of port facilities. To this end, we build a standard schema with port-specific Express Notation according to buildingSMART International's standard development methodology. First, domestic and international reference model standards were analyzed to derive components such as space and facilities of port facilities. Based on this, the components of the port facility were derived through the codification, categorization, and normalization process developed by the research team. This was extended based on the port BIM object classification system developed by the research team. Normalization results were verified by designers and associations. Then, IFC schema construction was based on Express-G data modeling based on IFC 4 * 2 Candidate, which is a bridge candidate standard based on IFC4 (ISO16739), and IFC 4 * 3 Draft, which is developed by buildingSMART International. The final schema was validated using the commercialized validation tool. In addition, in order to verify the structural verification of the port IFC schema, the transformation process was verified by converting the caisson model into a Part21 file. In the future, this result will not only be used as a delivery standard for port BIM products, but will also be applied as a linkage standard between systems and a common data format for port BIM platforms when BIM is used in the maintenance phase. In particular, it is expected to be used as a core standard for data exchange in the port maintenance stage.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.385-391
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• 2022

Quality evaluation of beef carcasses is an important issue in the livestock industry. Recently, through the AI monitor system based on artificial intelligence, the quality manager can receive help in making accurate decisions based on the analysis of beef carcass images or result information. This artificial intelligence dataset is an important factor in judging performance. Existing datasets may have different surface orientation or resolution. In this paper, we proposed a two-stage classification model that can efficiently manage the grades of beef carcass image using deep learning. And to overcome the problem of the various conditions of the image, a new dataset of 1,300 images was constructed. The recognition rate of deep network for 5-grade classification using the new dataset was 72.5%. Two-stage evaluation is a method to increase reliability by taking advantage of the large difference between grades 1++, 1+, and grades 1 and 2 and 3. With two experiments using the proposed two stage model, the recognition rates of 73.7% and 77.2% were obtained. As this, The proposed method will be an efficient method if we have a dataset with 100% recognition rate in the first stage.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.135-155
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• 2022

This study analyzes patent trends by deriving sub-technical fields of Organic Light-Emitting Diodes (OLEDs) industry, and analyzing technology value, originality, and diversity for each sub-technical field. To collect patent data, a set of international patent classification(IPC) codes related to OLED technology was defined, and OLED-related patents applied from 2005 to 2017 were collected using a set of IPC codes. Then, a large number of collected patent documents were classified into 12 major technologies using the Latent Dirichlet Allocation(LDA) topic model and trends for each technology were investigated. Patents related to touch sensor, module, image processing, and circuit driving showed an increasing trend, but virtual reality and user interface recently decreased, and thin film transistor, fingerprint recognition, and optical film showed a continuous trend. To compare the technological value, the number of forward citations, originality, and diversity of patents included in each technology group were investigated. From the results, image processing, user interface(UI) and user experience(UX), module, and adhesive technology with high number of forward citations, originality and diversity showed relatively high technological value. The results provide useful information in the process of establishing a company's technology strategy.

• Journal of Food Hygiene and Safety
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• v.38 no.4
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• pp.193-201
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• 2023

Antimicrobials in human medicine are classified by The World Health Organization (WHO) into three groups: critically important antimicrobials (CIA), highly important antimicrobials (HIA), and important antimicrobials (IA). CIA are antibiotic classes that satisfy two main criteria: that they are the sole or the only available limited therapeutic option to effectively treat severe bacterial infections in humans (Criterion 1), and infections where bacteria are transmitted to humans from non-human sources or have the potential to acquire resistance genes from non-human sources (Criterion 2). WHO emphasizes the need for cautious and responsible use of the CIA to mitigate risk and safeguard human health. Specific antimicrobials within the CIA with a high priority for management are reclassified as "highest priority critically important antimicrobials (HP-CIA)" and include the 3^rd generation of cephalosporins and the next generation of macrolides, quinolones, glycopeptides, and polymyxins. The CIA list is the scientific basis for risk assessment and risk management policies that warrant using antimicrobials to reduce antimicrobial resistance in several countries. In addition, the CIA list ensures food safety in the food industry, including for the popular food chain companies McDonald's and KFC. The continuous update of the CIA list reflects the advancement in research and emerging future challenges. Thus, active and deliberate evaluation of antimicrobial resistance and the construction of a list that reflects the specific circumstances of a country are essential to safeguarding food security.

• Smart Media Journal
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• v.12 no.7
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• pp.43-51
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• 2023

As online transactions increase, the image of clothing has a great influence on consumer purchasing decisions. The importance of image information for clothing materials has been emphasized, and it is important for the fashion industry to analyze clothing images and grasp the materials used. Textile materials used for clothing are difficult to identify with the naked eye, and much time and cost are consumed in sorting. This study aims to classify the materials of textiles from clothing images based on deep learning algorithms. Classifying materials can help reduce clothing production costs, increase the efficiency of the manufacturing process, and contribute to the service of recommending products of specific materials to consumers. We used machine vision-based deep learning algorithms ResNet and Vision Transformer to classify clothing images. A total of 760,949 images were collected and preprocessed to detect abnormal images. Finally, a total of 167,299 clothing images, 19 textile labels and 20 fabric labels were used. We used ResNet and Vision Transformer to classify clothing materials and compared the performance of the algorithms with the Top-k Accuracy Score metric. As a result of comparing the performance, the Vision Transformer algorithm outperforms ResNet.

• Journal of Navigation and Port Research
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• v.47 no.1
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• pp.25-36
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• 2023

To limit greenhouse gas emissions from ships, numerous environmental regulations and standards have been taken into effect. As a result, alternative fuels such as liquefied natural gas (LNG), liquefied petroleum gas (LPG), ammonia, and biofuels have been applied to ships. Most of these alternative fuels are low flashpoint fuels in the form of liquefied gas. Their use is predicted to continue to increase. Thus, management regulations for using low flash point fuel as a ship fuel are required. However, they are currently insufficient. In the case of LNG, ISO standards have been prepared in relation to bunkering. The Society for Gas as a Marine Fuel (SGMF), a non-governmental organization (NGO), has also prepared and published a guideline on LNG bunkering. The classification society also requires safety management areas to be designated according to bunkering methods and procedures for safe bunkering. Therefore, it is necessary to establish a procedure for setting a safety management area according to the type of fuel, environmental conditions, and leakage scenarios and verify it with a numerical method. In this study, as a feasibility study for establishing these procedures, application status and standards of the industry were reviewed. Classification guidelines and existing preceding studies were analyzed and investigated. Based on results of this study, a procedure for establishing a safety management area for bunkering in domestic ports of Korea can be prepared.

• Korean Journal of Radiology
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• v.25 no.7
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• pp.613-622
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• 2024

Objective: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). Materials and Methods: An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. Results: Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. Conclusion: The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.

• Journal of agriculture & life science
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• v.53 no.4
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• pp.93-101
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• 2019

Dog (Canis lupus familiaris) is a member of genius Canis that forms part of the wolf-like canids, and it has been evolved to diverse domestic breeds since 100 thousand years ago. Practical dog breed identification has been emerged to important part of pet industry such as genealogical certificates. From 11 dog breeds, 226 dogs and 23K SNP genotypes, we selected minimal SNPs of breed identification using machine learning algorithms including multiclass classification and feature selection. With 100 times of random choice of 70% data for training and 30% testing, we evaluated 9 classifiers' accuracies and 2 methods of feature selection. Linear SVM and PCA weighted feature selection showed the best accuracy of classification. Finally, we selected SNP markers and it could identify 11 breeds with approximately 90% accuracy, when having 40 SNP. This marker set is expected to be useful for dog breed and disease management by integration with disease markers.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.429-439
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• 2019

The objectives of this study were to gauge the extent of the forestry business through establishing the definition of forestry industry from the perspective of economic convergence and to analyze key components that affect each growth phase of a forestry business entity by classifying them. A total of 1,397 "sixth-sector industry" management entities were certified by the Ministry of Agriculture, Food, and Rural Affairs in South Korea from 2012-2017. Of these, 259 (18.5%) were in the forestry sector. In this study, the 259 forestry management entities were further classified into three phases based on sales distribution: entrance, development, and maturity. The entrance phase (<100 million KRW), development phase (>100 million and <1 billion KRW), and maturity phase (>1 billion KRW) constituted 33.2%, 55.4%, and 12.4% of the total 259 entities, respectively. The results showed that most of the management entities were either in the entrance or development phases, and only a small portion was in the maturity phase. To identify the key variables that affect each of the phases, chi-square analysis was used. We designed the "sixth-sector industry" type as an independent variable, whereas selected region, business organization, manager age group, forest product, processing type, and service type were designated as dependent variables. The results of the analysis showed that the processing and service types influenced all three developmental phases. Moreover, as the phase advanced, processing type showed a higher proportion of health-functional ingredients, such as powder or extract from forest products, which enable to develop and produce a variety of products. Service type also changed from simple experience to integrated experience tourism and finally to tourism education. Distribution and sales channel also turned out to be a significant factor during the development phase. This study provides the basic information needed to guide government support in the implementation of a formal forestry business through convergence as well as to increase the efficiency of business management.