• Journal of Korean Society of Archives and Records Management
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• v.23 no.2
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• pp.49-67
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• 2023

In recent years, the film industry in South Korea has experienced a period of prosperity, evidenced by the numerous awards won at major international film festivals. Furthermore, growing global interest in K-content and the expansion of the OTT industry following the COVID-19 pandemic are providing favorable conditions for the development of the domestic film industry. Sound effects play a crucial role in conveying the atmosphere and emotions of a film, making them an essential element of film production. In response, the Jeonju IT & CT Industry Promotion Agency has been promoting the development of Korean-style sound effects since 2013. Furthermore, the agency launched an online service called the "K-Sound Library," a sound effect archive, in 2021. However, the service has not been widely utilized because of issues with the database's construction and the system's problems. Therefore, this study aims to identify the K-Sound Library's problems through interviews with sound effects specialists about the online service of the first sound effect archive in South Korea. Based on the interviews and analyses of foreign cases, the study suggests ways to improve the search services' usability and the sound effects classification system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1C
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• pp.1-8
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• 2008

Recently, there have been many construction projects on soft ground with growth of industry and economy. Therefore foundation piles of abutments and(or) buildings had been suffering from a lot of stability problems of inordinary displacement due to lateral flow of soft ground. Although many researches about lateral flow have been carried out, it is still difficult to assess the mechanism of lateral flow in soft ground quantitatively. And reasonable design method for judgement of lateral flow occurrence in soft ground is not established yet. In this study, six PNN (Probabilistic Neural Network) models were developed according to input variables and database compiled from Korea and Japan for the judgment of lateral flow occurrence. PNN models were compared with present empirical methods. It was found that the developed PNN models can give more precise and reliable judgment of lateral flow occurrence than empirical methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.157-167
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• 2006

During the first and second NGIS projects by the Korean government, The first one (1995~2000) was limited on constructing geographic information and the second (2001~2005) was focused on circulation and practical use of geoinformation from the result of the first project. In the latter half of 2nd NGIS project, However, the geographic information from the NGIS projects have not been renewed even though there were significant geographical changes. The accurate renewal of geoinformation is a matter of great importance to the next generation industry (e.g. LBS, Ubiquitous, Telematics). In this respect, it is time to update the geographic information in the latter half of the second NGIS project. Therefore, It is not only important to build an accurate geoinformation but also rapid and correct renewal of the geoinformation. NGII (National Geographic Information Institute) has been studying for improvement of digital map that was constructed by the result of the 1st NGIS project. Through the construction of clean digital map, NGII constructed Framework Data to three kinds of formats (NGI, NDA, NRL). Framework Data was contained to other database, and provided the reference system of location or contents for combining geoinformation. Framework Data is consist of Data Set, Data Model and UFID (Unique Feature Identifier). It will be achieved as national infrastructure data. This paper attempts to explore a method of the update to practical framework data with realtime geoinformation on feature's creation, modification and destruction managed by 'Feature management agency' using UFID's process. Furthermore, it suggests a method which can provide important data in order to plan the Framework update with the land change ratio.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.887-897
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• 2023

Leading waste disposal countries, such as Sweden, Switzerland, and the United Kingdom, conduct safety assessments across all stages of High-Level Radioactive Waste Deep Geological Disposal Facilities-from planning and site selection to construction, operation, closure, and post-closure management. As safety assessments are repeatedly performed at each stage, generating vast amounts of diverse data over extended periods, it is essential to construct a database for safety assessment and establish a data management system. In this study, the safety assessment data management systems of leading countries, were analyzed, categorizing them into 1) input and reference data for safety assessments, 2) guidelines for data management, 3) organizational structures for data management, and 4) computer systems for data management. While each country exhibited differences in specific aspects, commonalities included the classification of safety assessment input data based on disposal system components, the establishment of organizations to supply, use, and manage this data, and the implementation of quality management systems guided by instructions and manuals. These cases highlight the importance of data management systems and document management systems for securing the safety and enhancing the reliability of High-Level Radioactive Waste Disposal Facilities. To achieve this, the classification of input data that can be flexibly and effectively utilized, ensuring the consistency and traceability of input data, and establishing a quality management system for input data and document management are necessary.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.93-98
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• 2023

In paddy rice farming, water management is a critical task. To suppress weed emergence during the early stages of growth, fields are deeply flooded, and after transplantation, the water level is reduced to promote rooting and stimulate stem generation. Later, water is drained to prevent the production of sterile tillers. The adequacy of water supply is influenced by various factors such as field location, irrigation channels, soil conditions, and weather, requiring farmers to frequently check water levels and control the ingress and egress of water. This effort increases if the fields are scattered in remote locations. Automated irrigation systems have been considered to reduce labor and improve productivity. However, the net income from rice production in 2022 was about KRW 320,000/10a on average, making it financially unfeasible to implement high-cost devices or construct new infrastructure. This study focused on developing an IoT-Based irrigation valve that can be easily integrated into existing agricultural infrastructure without additional construction. The research was carried out in three main areas: Firstly, an irrigation valve was designed for quick and easy installation on existing agricultural pipes. Secondly, a power circuit was developed to connect a low-power Cat M1 communication modem with an Arduino Nano board for remote operation. Thirdly, a cloud-based platform was used to set up a server and database environment and create a web interface that users can easily access.

• Korean Journal of Ecology and Environment
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• v.56 no.3
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• pp.268-279
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• 2023

Nowadays, artificial intelligence model approaches such as machine and deep learning have been widely used to predict variations of water quality in various freshwater bodies. In particular, many researchers have tried to predict the occurrence of cyanobacterial blooms in inland water, which pose a threat to human health and aquatic ecosystems. Therefore, the objective of this study were to: 1) review studies on the application of machine learning models for predicting the occurrence of cyanobacterial blooms and its metabolites and 2) prospect for future study on the prediction of cyanobacteria by machine learning models including deep learning. In this study, a systematic literature search and review were conducted using SCOPUS, which is Elsevier's abstract and citation database. The key results showed that deep learning models were usually used to predict cyanobacterial cells, while machine learning models focused on predicting cyanobacterial metabolites such as concentrations of microcystin, geosmin, and 2-methylisoborneol (2-MIB) in reservoirs. There was a distinct difference in the use of input variables to predict cyanobacterial cells and metabolites. The application of deep learning models through the construction of big data may be encouraged to build accurate models to predict cyanobacterial metabolites.

• Korean Journal of Plant Resources
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• v.37 no.2
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• pp.171-202
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• 2024

If the plant genetic resources and information-sharing systems held by arboretums worldwide are effectively utilized, it is believed that a conservation system for plant diversity in the currently inaccessible North Korean region could be established. This study was conducted to review the scientific names of plants native to North Korea but not to South Korea and to assess the status of genetic resources held in domestic and international arboretums. To compile a list and status of North Korean plant's genetic resources, updated checklists of vascular plants in Korean Peninsula and online plant information databases were consulted to compile synonym, distribution range, and other related information. A total of 486 taxa (449 species, 13 subspecies, 21 varieties, 1 forma and 2 hybrids) from 236 genera and 64 families, representing 12.34% of the total native flora of the Korean Peninsular were presented in the North Korea plant list, and the presence of rare, endemic and northern lineage species was confirmed. It was found that 384 taxa from 190 genera, 53 families of North Korean plants are held as genetic resources in 333 arboretums and plant research institutions across 46 countries and 5 continents worldwide. This study is expected to contribute to the construction and application of a species list for plants native to the Korean Peninsula.

• The Journal of the Acoustical Society of Korea
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• v.25 no.5
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• pp.213-221
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• 2006

Phone segmentation of speech waveform is especially important for concatenative text to speech synthesis which uses segmented corpora for the construction of synthetic units. because the quality of synthesized speech depends critically on the accuracy of the segmentation. In the beginning. the phone segmentation was manually performed. but it brings the huge effort and the large time delay. HMM-based approaches adopted from automatic speech recognition are most widely used for automatic segmentation in speech synthesis, providing a consistent and accurate phone labeling scheme. Even the HMM-based approach has been successful, it may locate a phone boundary at a different position than expected. In this paper. we categorized adjacent phoneme pairs and analyzed the mismatches between hand-labeled transcriptions and HMM-based labels. Then we described the dominant error patterns that must be improved for the speech synthesis. For the experiment. hand labeled standard Korean speech DB from ETRI was used as a reference DB. Time difference larger than 20ms between hand-labeled phoneme boundary and auto-aligned boundary is treated as an automatic segmentation error. Our experimental results from female speaker revealed that plosive-vowel, affricate-vowel and vowel-liquid pairs showed high accuracies, 99%, 99.5% and 99% respectively. But stop-nasal, stop-liquid and nasal-liquid pairs showed very low accuracies, 45%, 50% and 55%. And these from male speaker revealed similar tendency.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.244-252
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• 2023

The timeliness and accuracy of test results are crucial factors for clinicians to decide and promptly administer effective and targeted antimicrobial therapy, especially in life-threatening infections or when vital organs and functions, such as sight, are at risk. Further research is needed to refine and optimize matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based assays to obtain accurate and reliable results in the shortest time possible. MALDI-TOF MS-based bacterial identification focuses primarily on techniques for isolating and purifying pathogens from clinical samples, the expansion of spectral libraries, and the upgrading of software. As technology advances, many MALDI-based microbial identification databases and systems have been licensed and put into clinical use. Nevertheless, it is still necessary to develop MALDI-TOF MS-based antimicrobial-resistance analysis for comprehensive clinical microbiology characterization. The important applications of MALDI-TOF MS in clinical research include specific application categories, common analytes, main methods, limitations, and solutions. In order to utilize clinical microbiology laboratories, it is essential to secure expertise through education and training of clinical laboratory scientists, and database construction and experience must be maximized. In the future, MALDI-TOF mass spectrometry is expected to be applied in various fields through the use of more powerful databases.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.2
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• pp.11-21
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• 2000

Tunnelling has been created as a great extent in view of less land space available because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities. In tunnelling, it is often faced that measures are obliged to be taken without confirmation for such abnormality as diverged movement of surrounding rock mass, growing crack of shotcrete and yielding of rockbolts. In this case, it is usually said that the judgments of experienced engineers for the selection of measure are importance and allowed us to get over the situations in many construction sites. But decrease of such experienced engineers need us to develop the new system to assist the selection of measures for the abnormality without any experiences of similar tunnelling sites. In this study, After a lot of tunnelling reinforcement methods were surveyed and the detail application were studied, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.