• Speech Sciences
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• v.11 no.3
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• pp.131-142
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• 2004

Speaker identification system basically functions by comparing spectral energy of an individual production model with that of an input signal. This study aimed to develop a new speaker identification system from two parameters from the spectral energy of numeric sounds: difference sum and correlation coefficient. A narrow-band spectrogram yielded more stable spectral energy across time than a wide-band one. In this paper, we collected empirical data from four male speakers and tested the speaker identification system. The subjects produced 18 combinations of three-digit numeric. sounds !en times each. Five productions of each three-digit number were statistically averaged to make a model for each speaker. Then, the remaining five productions were tested on the system. Results showed that when the threshold for the absolute difference sum was set to 1200, all the speakers could not pass the system while everybody could pass if set to 2800. The minimum correlation coefficient to allow all to pass was 0.82 while the coefficient of 0.95 rejected all. Thus, both threshold levels can be adjusted to the need of speaker identification system, which is desirable for further study.

• Journal of Gastric Cancer
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• v.21 no.3
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• pp.236-245
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• 2021

Purpose: The numeric N stage has replaced the topographic N stage in the current tumor node metastasis (TNM) staging in gastric carcinoma. However, the usefulness of the topographic N stage in the current TNM staging system is uncertain. We aimed to investigate the prognostic value of the topographic N stage in the current TNM staging system. Materials and Methods: We reviewed the data of 3350 patients with gastric cancer who underwent curative gastrectomy. The anatomic regions of the metastatic lymph nodes (MLNs) were classified into 2 groups: perigastric and extra-perigastric. The prognostic value of the anatomic region was analyzed using a multivariate prognostic model with adjustments for the TNM stage. Results: In patients with lymph node metastasis, extra-perigastric metastasis demonstrated significantly worse survival than perigastric metastasis alone (5-year survival rate, 39.6% vs. 73.1%, respectively, P<0.001). Extra-perigastric metastasis demonstrated significantly worse survival within the same pN stage; the multivariate analysis indicated that extra-perigastric metastasis was an independent poor prognostic factor (hazard ratio=1.33; 95% confidence interval=1.01-1.75). The anatomic region of the MLNs improved the goodness-of-fit (likelihood ratio statistics, 4.57; P=0.033) of the prognostic model using the TNM stage. Conclusions: The anatomic region of MLNs has an independent prognostic value in the numeric N stage in the current TNM staging of gastric carcinoma.

• Journal of Korean Society for Quality Management
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• v.42 no.4
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• pp.591-606
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• 2014

Purpose: The purpose of this study is to design an experimental simulation model for evaluating the UGV(Unmanned Ground Vehicle) effectiveness in a small unit combat scenario. Methods: We design and build a simulation model to evaluate the combat effectiveness of UGV in a small unit combat scenario. In order to build a simulation model, we used AnyLogic software tool which has functional advantages to describe agent-based simulation model. As for the combat scenario, we applied the typical engagement of mechanized unit equal or lower than battalion level. Analysis process follows the three phases. 1) Design an agent based conceptual medel in a small unit combat scenario. 2) Build a simulation medel using AnyLogic tool. 3) Analyze the simulation results and evaluate the UGV effectiveness. Results: The UGV effectiveness was measured and presented as a numeric values. Those numeric values were represented as a MOE(Measure of Effectiveness) which was the blue survival ratio. Conclusion: We developed an agent based simulation model which can provide a pattern of change how UGV effectiveness varied depending upon the number of UGV in a small unit combat scenario. We also found that the UGV effectiveness grows in the given scenario as the number of UGV increases.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.7
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• pp.67-75
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• 2005

It has been well-known that the Nonpoint Source (NPS) pollutions are the primary contributors to water quality degradation in the receiving water bodies as well as the Point Source (PS) pollutions. To develop an effective management practice for water quality improvement, pollutant loads must be first estimated. In many studies, the Numeric Integration (NI) method has been used because of its ease of application, irrespective of the total number of samples collected for each storm event. Thus, there have been needs for more accurate pollutant load estimation with a limited number of water quality samples. In this study, NI method and regression method using the USGS ESTIMATOR model were comparatively used to calculate the pollutant loads for the Wolgokri watershed, Gangwon Province. The $NO_{3}$-N, T-N, and T-P loads using NI method and ESTIMATOR model were 13.85 kg/ha, 45.92 kg/ha, and 1.887 kg/ha, and 11.93 kg/ha,43.20 kg/ha, and 1.650 kg/ha, respectively. The estimated loads using ESTIMATOR model were lower than those using NI method by $86\%$, $94\%$, and $87\%$. These discrepancies in the estimated loads using a different load estimation method could be explained in that the total number of samples were not sufficient enough for NI method. Thus, ESTIMATOR model is recommended for the frequently stream discharge and less frequently measured water quality data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.60-65
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• 2003

The paper describes on the implementation of marine casualty prediction model that is one of the main part of Marine Casualty Forecasting System (MCFS). In this work, Cell Distributed Linear-In-the Parameter (CD-LIP) model is developed and compared with Baltic model using regression analysis of variance. As comparing, it is known that the proposed CD-LIP model has less residual than the Baltic model and, it gives best performance to the marine casualty numeric D/B of target area.

• Safety and Health at Work
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• v.3 no.2
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• pp.146-153
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• 2012

Objectives: The introduction of computerized numeric control (CNC) technology in manufacturing industries has revolutionized the production process, but there are some health and safety problems associated with these machines. The present study aimed to investigate the extent of postural discomfort in CNC machine operators, and the relationship of this discomfort to the display and control panel height, with a view to validate the anthropometric recommendation for the location of the display and control panel in CNC machines. Methods: The postural discomforts associated with CNC machines were studied in 122 male operators using Corlett and Bishop's body part discomfort mapping, subject information, and discomfort level at various time intervals from starting to end of a shift. This information was collected using a questionnaire. Statistical analysis was carried out using ANOVA. Results: Neck discomfort due to the positioning of the machine displays, and shoulder and arm discomfort due to the positioning of controls were identified as common health issues in the operators of these machines. The study revealed that 45.9% of machine operators reported discomfort in the lower back, 41.8% in the neck, 22.1% in the upper-back, 53.3% in the shoulder and arm, and 21.3% of the operators reported discomfort in the leg. Conclusion: Discomfort increased with the progress of the day and was highest at the end of a shift; subject age had no effect on patient tendency to experience discomfort levels.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.19-27
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• 2015

Technologies of wind power generation for development of alternative energy technology have been accumulated over the past 20 years. Wind power generation is environmentally friendly and economical because it uses the wind blowing in nature as energy resource. In order to operate wind power generation efficiently, it is necessary to accurately predict wind speed changing every moment in nature. It is important not only averagely how well to predict wind speed but also to minimize the largest absolute error between real value and prediction value of wind speed. In terms of generation operating plan, minimizing the largest absolute error plays an important role for building flexible generation operating plan because the difference between predicting power and real power causes economic loss. In this paper, we propose a method of wind speed prediction using numeric prediction algorithm-based wind speed forecast model made to analyze the wind speed forecast given by the Meteorological Administration and pattern value for considering seasonal property of wind speed as well as changing trend of past wind speed. The wind speed forecast given by the Meteorological Administration is the forecast in respect to comparatively wide area including wind generation farm. But it contributes considerably to make accuracy of wind speed prediction high. Also, the experimental results demonstrate that as the rate of wind is analyzed in more detail, the greater accuracy will be obtained.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.195-196
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• 2006

Recently, there are increasing need to make a synthetic assessment about oceanic data which is collected over the various scientific field, in addition to just gathering oceanic data. In this study, we made a basic map using satellite image, aerial photo, multi-beam data, geological stratum data etc. And as well we are producing comprehensive SVT(Scientific Visualization Toolkit) which can visualize various kinds of oceanic data. These oceanic data include both survey data such as tidal height, tide, current, wave, water temperature, salinity, oceanic weather data and numeric modelling results such as ocean hydrodynamic model, wave model, erosion/sediment model, thermal discharged coastal water model, ocean water quality model. In this process, we introduce GIS(Geographic Information System) concepts to reflect time and spatial characteristics of oceanic data.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.185-205
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• 2002

In this study, we consider infinite supply of raw materials and backlogged demands as given two boundary conditions. And we need not make any specific assumptions about the inter-arrival of external demand and service time distributions. Under these situations, the ultimate objective of this study is to prove the variability propagation principle in a pull serial line and is to measure it in terms of the first two moments of the inter-departure process subject to number of cards in each cell. Two preparations are required to achieve this objective : The one is to derive a true lower bound of variance of the inter-departure process. The other is to establish a constrained discrete minimax problem for the no backorder (backlogging) probabilities in each cell. We may get some fundamental results necessary to a completion for the proof through the necessary and sufficient conditions for existence of optimal solution of a constrained discrete minimax problem and the implicit function theorem. finally, we propose a numeric model to measure the variability propagation principle. Numeric examples show the validity and applicability of our study.