• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.342-350
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• 2022

In this paper, actual drone noise samples are collected for speech processing in disaster environments to build noise-corrupted speech database, and speech enhancement performance is evaluated by applying spectrum subtraction and mask-based speech enhancement techniques. To improve the performance of VoiceFilter (VF), an existing deep neural network-based speech enhancement model, we apply the Self-Attention operation and use the estimated noise information as input to the Attention model. Compared to existing VF model techniques, the experimental results show 3.77%, 1.66% and 0.32% improvements for Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short-Time Objective Intelligence (STOI), respectively. When trained with a 75% mix of speech data with drone sounds collected from the Internet, the relative performance drop rates for SDR, PESQ, and STOI are 3.18%, 2.79% and 0.96%, respectively, compared to using only actual drone noise. This confirms that data similar to real data can be collected and effectively used for model training for speech enhancement in environments where real data is difficult to obtain.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.3
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• pp.263-276
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• 2023

The purpose of this study was to evaluate the performance of a model using You Only Look Once (YOLO) for object detection of proximal caries in periapical radiographs of children. A total of 2016 periapical radiographs in primary dentition were selected from the M6 database as a learning material group, of which 1143 were labeled as proximal caries by an experienced dentist using an annotation tool. After converting the annotations into a training dataset, YOLO was trained on the dataset using a single convolutional neural network (CNN) model. Accuracy, recall, specificity, precision, negative predictive value (NPV), F1-score, Precision-Recall curve, and AP (area under curve) were calculated for evaluation of the object detection model's performance in the 187 test datasets. The results showed that the CNN-based object detection model performed well in detecting proximal caries, with a diagnostic accuracy of 0.95, a recall of 0.94, a specificity of 0.97, a precision of 0.82, a NPV of 0.96, and an F1-score of 0.81. The AP was 0.83. This model could be a valuable tool for dentists in detecting carious lesions in periapical radiographs.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3C
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• pp.115-125
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by insitu test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network (NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. It was already found that NN model can come over the site dependency and prediction accuracy is greatly improved when compared with present theoretical and empirical models. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network (CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. Prediction results of CNN model are compared with those of conventional empirical and theoretical models and multi-layered neural network model, which has the optimized structure. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.594-609
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• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• 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.

• Korean journal of applied entomology
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• v.49 no.4
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• pp.375-384
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• 2010

We tried to establish the history of outbreaks and control methods of 'hwangchung' in Joseon Dynasty, uncovering the biological reality of the 'hwangchung' (called hwang or bihwang) analyzed through the Database program on 'the Annals of the Joseon Dynasty' and 'the Emollment of Haegoeje', two of the finest examples of classical historical records. The total number of articles on the outbreak of the hwangchung is 261 in the Annals of the Joseon Dynasty and 65 in the Emollment of Haegoeje. There were four peaks by hwangchung throughout the Joseon Era. Among them, the periods of King Taejo to King Sejong had the highest incidence. By comparing the number of records of the hwangchung from the Annals of the Joseon Dynasty with that in the Emollment of Haegoeje during the same period, results show the former was less than the latter, 35 vs 65. However, both records were relatively inconsistent with each other. Insect pests in forests as well as in agriculture were included in the biological identities of the hwangchung in the Joseon Dynasty periods, which is in accordance with those of Saigo's. The taxonomic identity could be confirmed in only 25 cases (9.5%) among the articles on hwangchung. It largely coincided with Paik's opinion: II in armyworm, nine in moth larva, one in rice stem borer, two in migratory locust, one in planthopper and one in rice-plant weevil. Therefore, it is not reasonable to regard hwangchung as a migratory locust or grasshopper only. The number of reports on the occurrence of hwangchung in the Annals of the Joseon Dynasty was 173 (66% of the total) and 47% of them were just simple reports, which means the report itself on the appearance of hwangchung was very significant. The reports on controlling insect pests were of low frequency, in 20% (34 cases) of the total reports, capturing insect pests or holding traditional ceremony called 'Poje'. Among them, only one case related to the treatment of seeds to prevent the damage by hwangchung was published in the King Sejong period. There were 37 discussions about changes and management of government policies due to disasters by hwangchung. They were mostly about relief or tax cut to the people who suffered damage and about cancellation of recruiting people to military training, constructing castles, and so on. It seems that not only the people but also the king was influenced by the hwangchung. In the case of King Seongjong, he referred to the stress of the prevention measure of locusts in 10 articles. The damage also had an effect on abdication in the reign of King Jeongjong.

• Journal of Korean Home Economics Education Association
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• v.20 no.1
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• pp.45-62
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• 2008

The purpose of this study was to investigate middle school home economics(HE) teachers' perception and needs on self supervision related to HE subject matter, Using the methods of survey and interview, 177 samples were collected. For collected surveys, mean value, standard deviation, frequency, percentage analysis were performed by using an SPSS/Win (ver10.1) program. The results of this study were as follows. First, the middle school HE teachers recognized that self supervision related to HE subject matter was absolutely needed to expand the improvement of techniques for teaching instructions and the width of knowledge on the studies on textbook. Second, the middle school HE teachers recognized the necessary parts of self supervision related to HE subject matter as HE teaching-learning methods, the studies on textbook contents, and HE education philosophy in order. Third, the middle school HE teachers recognized that it would be helpful in improving their HE class and expertise in order of field survey, participation in various training programs, utilization of mass media, participation in societies for researches and meetings and information sharing with co-teachers among the types of self supervision. Fourth, the middle school HE teachers needed the reduction in miscellaneous duties, less pressure for time, restoration of teachers' desire, support of physical resources (improvement of various environments such as classrooms and special rooms), economic support and various support programs (expanding the opportunities to participate in training and society and establishment of a database for relevant materials, etc.) to facilitate self supervision. As such, the middle school HE teachers' overall recognition on HE-related self supervision became significantly higher. To enhance the HE-related expertise, however, it would be necessary to conduct concrete and active support for HE education, philosophical area and the studies on textbook contents as well as the teaching-learning methods for HE in which teachers' demand was high. In addition, the HE teachers wanted to have an easy and quick access to various HE-related data; therefore, it would be urgent to summarize scattered relevant data and support the HE teachers more systematically.

• The Korean Journal of Air & Space Law and Policy
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• v.32 no.2
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• pp.101-127
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• 2017

Even with the most advanced aviation technology benefits, aircraft accidents are constantly occurring while air passenger transportation volume is expected to double in the next 15 years. Since it is not possible to secure aviation safety only by the post aircraft accident safety action of accident investigations, it has been recognized and consensus has been formed that proactive and predictive prevention measures are necessary. In this sense, the aviation safety management system (SMS) was introduced in 2008 and has been carried out in earnest since 2011. SMS is a proactive and predictive aircraft accident preventive measure, which is a mechanism to eliminate the fundamental risk factors by approaching organizational factors beyond technological factors and human factors related to aviation safety. The methodology is to collect hazards in all the sites required for aircraft operations, to build a database, to analyze the risks, and through managing risks, to keep the risks acceptable or below. Therefore, the improper implementation of SMS indicates that the aircraft accident prevention is insufficient and it is to be directly connected with the aircraft accident. Reports of duty performance related hazards including their own errors are essential and most important in SMS. Under the policy of just culture for voluntary reporting, the guarantee of information providers' anonymity, non-punishment and non-blame should be basically secured, but to this end, under-reporting is stagnant due to lack of trust in their own organizations. It is necessary for the accountable executive(CEO) and senior management to take a leading role to foster the safety culture initiating from just culture with the safety consciousness, balancing between safety and profit for the organization. Though a Ministry of Land, Infrastructure and Transport's order, "Guidance on SMS Implementation" states the training required for the accountable executive(CEO) and senior management, it is not legally binding. Thus it is suggested that the SMS training completion certificates of accountable executive(CEO) and senior management be included in SMS approval application form that is legally required by "Korea Aviation Safety Program" in addition to other required documents such as a copy of SMS manual. Also, SMS related items are missing in the aircraft accident investigation, so that organizational factors in association with safety culture and risk management are not being investigated. This hinders from preventing future accidents, as the root cause cannot be identified. The Aircraft Accident Investigation Manuals issued by ICAO contain the SMS investigation wheres it is not included in the final report form of Annex 13 to the Convention on International Civil Aviation. In addition, the US National Transportation Safety Board(NTSB) that has been a substantial example of the aircraft accident investigation for the other accident investigation agencies worldwide does not appear to expand the scope of investigation activities further to SMS. For these reasons, it is believed that investigation agencies conducting their investigations under Annex 13 do not include SMS in the investigation items, and the aircraft accident investigators are hardly exposed to SMS investigation methods or techniques. In this respect, it is necessary to include the SMS investigation in the organization and management information of the final report format of Annex 13. In Korea as well, in the same manner, SMS item should be added to the final report format of the Operating Regulation of the Aircraft and Railway Accident Investigation Board. If such legal and institutional improvement methods are complemented, SMS will serve the purpose of aircraft accident prevention effectively and contribute to the improvement of aviation safety in the future.

• Journal of Hospice and Palliative Care
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• v.3 no.2
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• pp.126-135
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• 2000

Purpose : To evaluate the present status of bereavement care in Korean hospice service as a basic database for the effective bereavement care. Method : The data were collected two sets from September to October, 1999 and from November to December, 2000, 55 hospice institutions identified by the Hospice Education Institution, College of Nursing, Catholic University were contacted for a telephone survey. The researchers conducted telephone interviews with hospice administrators for 10 to 30 minutes. Result : 1) Among the 55 Korean Hospice institutions, 38 institutions(69.1%) provided bereavement services. 2) The contents of bereavement services consisted of telephone call 28 institutions(74.5%), bereaved family meeting 26 institutions(69.4%), home visiting 22 institutions(57.9%), mail 16 institutions(42.1%), personal counselling 7 institutions(18.4%). 3) The 26 hospice institutions(68.4%) which provided meetings for bereaved families met with the following frequency : Annually is 11 institutions(42.3%), biannually 6 institutions(23.1%), monthly 6 institutions(23.1%) and bimonthly 3 institutions(11.5%). 4) Only 4 hospice institutions(10.5%) used the assessment tool to screen for high risk of bereaved. 5) The major difficulties of current bereavement services were low attendance for the bereaved family meeting, shortage of professional managers and volunteers, limited accessibility to hospice institutions, little social awareness for the bereaved, and financial difficulties. 6) The hospice administrators expressed the need for the development of bereavement program, the education program for the bereavement services, trained professionals, the sufficient provision of human resource and financial support for more effective bereavement services. Conclusion : Although many hospice institutions(69.1%) provided bereavement services, they generally lacked capable bereavement professionals and various individualized bereavement services. In conclusion, it is required to develop the specified bereavement program and the training program for the staff and volunteers, so as to provide customized bereavement services based on individual needs. Further research will be necessary to evaluate the effects of customized bereavement services in Korea before applying to practice.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.281-290
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• 2020

With the spread of smartphones, services that want to use personalized data are increasing. In particular, healthcare-related services deal with a variety of data, and data visualization techniques are used to effectively show this. As data visualization techniques are used, interactions in visualization are also naturally emphasized. In the PC environment, since the interaction for data visualization is performed with a mouse, various filtering for data is provided. On the other hand, in the case of interaction in a mobile environment, the screen size is small and it is difficult to recognize whether or not the interaction is possible, so that only limited visualization provided by the app can be provided through a button touch method. In order to overcome the limitation of interaction in such a mobile environment, we intend to enable data visualization interactions through conversations with chatbots so that users can check individual data through various visualizations. To do this, it is necessary to convert the user's query into a query and retrieve the result data through the converted query in the database that is storing data periodically. There are many studies currently being done to convert natural language into queries, but research on converting user queries into queries based on visualization has not been done yet. Therefore, in this paper, we will focus on query generation in a situation where a data visualization technique has been determined in advance. Supported interactions are filtering on task x-axis values and comparison between two groups. The test scenario utilized data on the number of steps, and filtering for the x-axis period was shown as a bar graph, and a comparison between the two groups was shown as a line graph. In order to develop a natural language processing model that can receive requested information through visualization, about 15,800 training data were collected through a survey of 1,000 people. As a result of algorithm development and performance evaluation, about 89% accuracy in classification model and 99% accuracy in query generation model was obtained.