• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.350-357
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• 2023

Marine accidents frequently occur due to the unreasonable operation of ships excluded from ship departure control during marine special weather warnings within smooth water areas. Coastal wave buoys installed in smooth water areas are major reference indicators for ship departure control and can be seen as being directly connected to the safety of ships navigating smooth water areas and the coast. In this study, the location appropriateness of currently operating coastal wave buoys and additional installation in the smooth water areas were assessed by analyzing coastal marine accidents over the past 30 years (1991-2020), the main wind direction and wind speed of each major trading port, and the GICOMS ship track data in 2018. The study results showed that an additional coastal wave buoy should be installed at each of the major trading ports(Inchon Port, Pohang Port, Ulsan Port, and Busan Port) and that the location of the coastal wave buoy needs to be moved in the case of Busan Port. Based on various data analysis in this study, the suggestion for an additional installation and movement of the coastal wave buoy presented in this study is expected to contribute to improving the reliability of ship departure control and resolving safety blind spots.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.2
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• pp.156-162
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• 2024

Nerve conduction study (NCS) is an essential test for the diagnosis and follow-up of peripheral neuropathy. NCS can objectively quantify peripheral nerve function. NCS is affected by physiological factors such as height, age, body mass index, etc. Hence, the American Association of Neuromuscular & Electrodiagnosis Medicine (AANEM) is currently forming a Normal Data Task Force (NDTF) to present the normal value, but the number is significantly less. Currently, no research has been carried out on the correlation between nerve conduction speed and height and lower limb length in Koreans. Hence, this study sought to compare the nerve conduction velocity of the lower limbs according to the height and lower limb length. A total of 49 subjects were recruited. When the motor nerve conduction velocity and sensory nerve conduction velocity were compared according to the height and leg length, there was a statistically significant negative correlation of the peroneal and left tibial motor nerves with the height. Also, a statistically significant negative correlation was observed with the superficial peroneal sensory nerve and the sural nerve and the leg length. However, in this study, all the subject are in twentys age, whereas the NDTF is divided by age. Hence, additional studies involving subjects of various age groups are needed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.4
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• pp.340-347
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• 2024

In this study, an expert survey was conducted using the Delphi technique to select items and indicators for evaluation before installing educational facilities in the marine fisheries safety field, in which the educational infrastructure gap between regions is wide. Seven indicators were selected as geographic, social, and administrative factors. In order to objectively evaluate each indicator, evaluation indicators that could be evaluated using public data such as the "Comprehensive National Balanced Development Information System" and "National Statistical Portal" were developed. The Analytic Hierarchy Process (AHP) method was applied to select the weight for each indicator, resulting in 10 most important influencing factors on the selection of the location of educational facilities of the Marine Fisheries Safety Education Facilities: the distribution of marine officers, access to high-speed railways, the number of small ships less than 5 tons, access to highways interchange, the distribution of fishing boats, the close relationship of related industries, the planned new port, the distribution of commercial ports, the number of marine leisure riders, and the availability of long-term land leases in local government councils. The location evaluation index of marine and fishery safety education facilities developed in this study can be used to evaluate each region using national public data, and has the advantage of enabling objective evaluation. Therefore, it is judged that this evaluation index can be used to verify the feasibility of installing marine fisheries safety education facilities as well as other marine-related facilities.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.59-68
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• 2024

In this study, we proposed an efficient model that can detect and classify the drones and related devices based on radio frequency signals. In order to increase the applicability in the battlefield, proposed model was designed to be lightweight, to ensure rapid detection and high detection accuracy. Data preprocessing was performed by applying a Discrete Fourier Transform (DFT) that is faster than Hilbert-Huang Transform (HHT). We adopted the LightGBM model as the learning model, which can be easily used by non-professionals and guarantees excellent performance in terms of classification speed and accuracy. CardRF dataset was used to verify the performance of the proposed model. As a result of the experiment, the accuracy of 3 classes classification for detecting and classifying drones, WiFi, and Bluetooth device was 99.63% when the number of sample points was set to 100k and 99.40% when set to 500k during the data preprocessing with DFT. And, in the 10 classes classification for 6 drones, 2 Bluetooth devices, and 2 WiFi devices, the accuracy was 95.65% for 100k and 96.83% for 500k, confirming significantly improved detection performance compared to previous studies.

• Phonetics and Speech Sciences
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• v.16 no.3
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• pp.79-86
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• 2024

Transformer models have shown remarkable performance in extracting meaningful information from sequential input data such as text and images, and are gaining attention as end-to-end models for speech recognition. This study compared the performances of the Transformer speech recognition model and its enhanced versions, the Conformer and E-Branchformer, when applied to Korean speech recognition. Using Korean speech data from AIHub, we prepared a training set of approximately 7,500 hours and evaluated the models using the ESPnet toolkit. Additionally, we compared syllables and subwords as recognition units and analyzed the performance differences with changes in the number of tokens using Byte Pair Encoding. The results showed that the E-Branchformer achieved the best performance in Korean speech recognition and Conformer outperformed Transformer but degraded in performance for long utterances owing to cross-attention alignment errors. We aimed to determine the optimal settings by analyzing the performance changes with subword token adjustments. This study comprehensively evaluated model accuracy and processing speed to maximize the efficiency of Korean speech recognition. This is expected to contribute to the training of large-scale Korean speech recognition models and improve Conformer recognition errors. Future research should include additional experiments with diverse Korean speech datasets and enhance the recognition performance through structural improvements in the Conformer.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.35-47
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• 2001

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.183-196
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• 2017

Objective: The purpose of this research was to assess the agreement between job physical risk factor analysis by ergonomists using ergonomic methods and physical examinations made by occupational physicians on the presence of musculoskeletal disorders of the upper extremities. Background: Ergonomics is the systematic application of principles concerned with the design of devices and working conditions for enhancing human capabilities and optimizing working and living conditions. Proper ergonomic design is necessary to prevent injuries and physical and emotional stress. The major types of ergonomic injuries and incidents are cumulative trauma disorders (CTDs), acute strains, sprains, and system failures. Minimization of use of excessive force and awkward postures can help to prevent such injuries Method: Initial data were collected as part of a larger study by the University of Utah Ergonomics and Safety program field data collection teams and medical data collection teams from the Rocky Mountain Center for Occupational and Environmental Health (RMCOEH). Subjects included 173 male and female workers, 83 at Beehive Clothing (a clothing plant), 74 at Autoliv (a plant making air bags for vehicles), and 16 at Deseret Meat (a meat-processing plant). Posture and effort levels were analyzed using a software program developed at the University of Utah (Utah Ergonomic Analysis Tool). The Ergonomic Epicondylitis Model (EEM) was developed to assess the risk of epicondylitis from observable job physical factors. The model considers five job risk factors: (1) intensity of exertion, (2) forearm rotation, (3) wrist posture, (4) elbow compression, and (5) speed of work. Qualitative ratings of these physical factors were determined during video analysis. Personal variables were also investigated to study their relationship with epicondylitis. Logistic regression models were used to determine the association between risk factors and symptoms of epicondyle pain. Results: Results of this study indicate that gender, smoking status, and BMI do have an effect on the risk of epicondylitis but there is not a statistically significant relationship between EEM and epicondylitis. Conclusion: This research studied the relationship between an Ergonomic Epicondylitis Model (EEM) and the occurrence of epicondylitis. The model was not predictive for epicondylitis. However, it is clear that epicondylitis was associated with some individual risk factors such as smoking status, gender, and BMI. Based on the results, future research may discover risk factors that seem to increase the risk of epicondylitis. Application: Although this research used a combination of questionnaire, ergonomic job analysis, and medical job analysis to specifically verify risk factors related to epicondylitis, there are limitations. This research did not have a very large sample size because only 173 subjects were available for this study. Also, it was conducted in only 3 facilities, a plant making air bags for vehicles, a meat-processing plant, and a clothing plant in Utah. If working conditions in other kinds of facilities are considered, results may improve. Therefore, future research should perform analysis with additional subjects in different kinds of facilities. Repetition and duration of a task were not considered as risk factors in this research. These two factors could be associated with epicondylitis so it could be important to include these factors in future research. Psychosocial data and workplace conditions (e.g., low temperature) were also noted during data collection, and could be used to further study the prevalence of epicondylitis. Univariate analysis methods could be used for each variable of EEM. This research was performed using multivariate analysis. Therefore, it was difficult to recognize the different effect of each variable. Basically, the difference between univariate and multivariate analysis is that univariate analysis deals with one predictor variable at a time, whereas multivariate analysis deals with multiple predictor variables combined in a predetermined manner. The univariate analysis could show how each variable is associated with epicondyle pain. This may allow more appropriate weighting factors to be determined and therefore improve the performance of the EEM.

• Journal of Environmental Impact Assessment
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• v.24 no.5
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• pp.456-471
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• 2015

Emission source term is one of the strong controlling factors for the air quality simulation capability, particularly over the urban area. Ulsan is an industrial area and frequently required to simulate for environmental assessment. In this study, two CAPSS (Clean Air Policy Support System) emission data; CAPSS-2003 and CAPSS-2010 in Ulsan, were employed as an input data for WRF-CMAQ air quality model for emission assessment. The simulated results were compared with observations for the local emission dominant synoptic conditions which had negative vorticities and lower geostrophic wind speed at 850hPa weather maps. The measurements of CO, $NO_2$, $SO_2$ and $PM_{10}$ concentrations were compared with simulations and the 'scaling factors' of emissions for CO, $NO_2$, $SO_2$, and $PM_{10}$ were suggested in in aggregative and quantitative manner. The results showed that CAPSS-2003 showed no critical discrepancies of CO and $NO_2$ observations with simulations, while $SO_2$ was overestimated by a factor of more than 12, while $PM_{10}$ was underestimated by a factor of more than 20 times. However, CAPSS-2010 case showed that $SO_2$ and $PM_{10}$ emission were much more improved than CAPSS-2003. However, $SO_2$ was still overestimated by a factor of more than 2, and $PM_{10}$ underestimated by a factor of 5, while there was no significant improvement for CO and $NO_2$ emission. The estimated factors identified in this study can be used as'scaling factors'for optimizing the emissions of air pollutants, particularly $SO_2$ and $PM_{10}$ for the realistic air quality simulation in Ulsan.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.17-24
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• 2011

Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.683-694
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• 2003

We present X-tree Diff, a change detection algorithm for tree-structured data. Our work is motivated by need to monitor massive volume of web documents and detect suspicious changes, called defacement attack on web sites. From this context, our algorithm should be very efficient in speed and use of memory space. X-tree Diff uses a special ordered labeled tree, X-tree, to represent XML/HTML documents. X-tree nodes have a special field, tMD, which stores a 128-bit hash value representing the structure and data of subtrees, so match identical subtrees form the old and new versions. During this process, X-tree Diff uses the Rule of Delaying Ambiguous Matchings, implying that it perform exact matching where a node in the old version has one-to one corrspondence with the corresponding node in the new, by delaying all the others. It drastically reduces the possibility of wrong matchings. X-tree Diff propagates such exact matchings upwards in Step 2, and obtain more matchings downwsards from roots in Step 3. In step 4, nodes to ve inserted or deleted are decided, We aldo show thst X-tree Diff runs on O(n), woere n is the number of noses in X-trees, in worst case as well as in average case, This result is even better than that of BULD Diff algorithm, which is O(n log(n)) in worst case, We experimented X-tree Diff on reat data, which are about 11,000 home pages from about 20 wev sites, instead of synthetic documets manipulated for experimented for ex[erimentation. Currently, X-treeDiff algorithm is being used in a commeercial hacking detection system, called the WIDS(Web-Document Intrusion Detection System), which is to find changes occured in registered websites, and report suspicious changes to users.