• Journal of Korean Tunnelling and Underground Space Association
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• v.8 no.3
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• pp.249-257
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• 2006

The spatial distribution of design parameters greatly affects tunnel behavior during and after construction, as well as in the long-term temporal responses. However, the tunnel design parameters commonly used in numerical modeling tend to be representative or average values of global-scale properties. Furthermore, the uncertainty and spatial variation of the design parameters increase as the tunnel scale increases. Consequently, the probability of failure also increases. In order to achieve structural stability in large-section tunnels, the design framework must take into consideration the quantitative effect of design parameter variations on tunnel behavior. Therefore, this paper suggests a statistical approach to numerical modeling to explore the effect of spatially distributed design parameters in a circular tunnel. Also, the effect of spatial variation in the lining strength is studied in this paper. The numerical results suggest that the deformation around the tunnel increases with an increase in the variation of the design parameters.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.9
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• pp.4433-4437
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• 2016

Background: Gastric cancer (GC) is the fifth most common cancer worldwide. Since development is usually asymptomatic, it is generally diagnosed at an advanced stage. The value of screening in patients with nonspecific symptoms for GC is controversial. Aim: The study aimed to evaluate whether hematological parameters (platelet count (PC), mean platelet volume (MPV), MPV/PC ratio, red blood cell distribution width (RDW), neutrophil to lymphocyte ratio (NLR), and platelet to lymphocyte ratio (PLR)) are useful markers to differentiate between gastric cancer patients and healthy individuals. Materials and Methods: Sixty-one patients with gastric cancer and sixty-one healthy individuals were enrolled to the survey and retrospective analysis of selected blood parameters were performed. Results: The mean values of PC, MPV, RDW, NLR, and PLR were significantly higher in GC patients compared to the control group. No statistical differences were observed in MPV/PC ratios. Likewise, no significant statistical differences were revealed in values of blood parameters among TNM stage groups. The RDW showed the highest diagnostic specificity and sensitivity. Conclusions: Hematological parameters: PC, MPV, RDW, NLR, PLR have diagnostic power and can discriminate patients with gastric cancer from patients without cancer. Blood parameters compared with clinical symptoms might alert physicians and patients and lead to performancce of upper gastrointestinal endoscopy, the gold standard in gastric cancer screening and therebly increase the early detection of cancer.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.100-107
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• 2015

Recently as the manufacturers want competitiveness in dynamically changing environment, they are trying a lot of efforts to be efficient with their production systems, which may be achieved by diminishing unplanned operation stops. The operation stops and maintenance cost are known to be significantly decreased by adopting proper maintenance strategy. Therefore, the manufacturers were more getting interested in scheduling of exact maintenance scheduling to keep smooth operation and prevent unexpected stops. In this paper, we proposedan integrated maintenance approach in injection molding manufacturing line. It consists of predictive and preventive maintenance approach. The predictive maintenance uses the statistical process control technique with the real-time data and the preventive maintenance is based on the checking period of machine components or equipment. For the predictive maintenance approach, firstly, we identified components or equipment that are required maintenance, and then machine parameters that are related with the identified components or equipment. Second, we performed regression analysis to select the machine parameters that affect the quality of the manufactured products and are significant to the quality of the products. By this analysis, we can exclude the insignificant parameters from monitoring parameters and focus on the significant parameters. Third, we developed the statistical prediction models for the selected machine parameters. Current models include regression, exponential smoothing and so on. We used these models to decide abnormal patternand to schedule maintenance. Finally, for other components or equipment which is not covered by predictive approach, we adoptedpreventive maintenance approach. To show feasibility we developed an integrated maintenance support system in LabView Watchdog Agent and SQL Server environment and validated our proposed methodology with experimental data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.9
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• pp.993-1000
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• 1992

Recently, many researchers have found that the speaker recognition rate is high when they perform the speaker recognition using statistical processing method of orthogonal parameter, which are derived from the analysis of speech signal and contain much of the speaker's identity. This method, however, has problems caused by vocalization speed or time varying feature of speed. Thus, to solve these problems, this paper proposes two methods of speaker recognition which combine DTW algorithm with the method using orthogonal parameters extracted from $Karthumem-Lo\'{e}ve$ Transform method which applies orthogonal parameters as feature vector to ETW algorithm and the other is the method which applies orthogonal parameters to the optimal path. In addition, we compare speaker recognition rate obtained from the proposed two method with that from the conventional method of statistical process of orthogonal parameters. Orthogonal parameters used in this paper are derived from both linear prediction coefficients and partial correlation coefficients of speech signal.

• Advances in Energy Research
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• v.8 no.2
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• pp.95-110
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• 2022

Wind energy can be utilized for the generation of electricity, due to significant wind potential at different parts of the world, some countries have already been generating of electricity through wind. Pakistan is still well behind and has not yet made any appreciable effort for the same. The objective of this work was to add some new strategies to calculate Weibull parameters and assess wind energy potential. A new approach calculates Weibull parameters; we also developed an alternate formula to calculate shape parameters instead of the gamma function. We obtained k (shape parameter) and c (scale parameter) for two-parameter Weibull distribution using five statistical methods for five different cities in Pakistan. Maximum likelihood method, Modified Maximum likelihood Method, Method of Moment, Energy Pattern Method, Empirical Method, and have been to calculate and differentiate the values of (shape parameter) k and (scale parameter) c. The performance of these five methods is estimated using the Goodness-of-Fit Test, including root mean square error, mean absolute bias error, mean absolute percentage error, and chi-square error. The daily 10-minute average values of wind speed data (obtained from energydata.info) of different cities of Pakistan for the year 2016 are used to estimate the Weibull parameters. The study finds that Hyderabad city has the largest wind potential than Karachi, Quetta, Lahore, and Peshawar. Hyderabad and Karachi are two possible sites where wind turbines can produce reasonable electricity.

• Journal of Welding and Joining
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• v.22 no.1
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• pp.58-64
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• 2004

The control of the weld bead shape is important in laser welding of the small parts. The effects of laser welding parameters on the weld bead shape in the pulsed Nd:YAG laser welding of STS 304L material were investigated. Shielding gas type, flow rate, pumping voltage, pulse frequency, pulse width, focal position and overlap distance were selected as laser welding parameters. Experiments were designed and conducted using the Taguchi method which was a statistical experimental method. The weld bead width, penetration, area and aspect ratio were measured and analysed as the weld bead shape properties and the welding parameters were optimized to maximize the weld aspect ratio. Weld aspect ratio were greatly affected by the pulse width, pumping voltage and pulse frequency, and somewhat by the overlap distance, and little by the shielding gas type, flow rate and focal position. A confirmation experiment were conducted using the optimized welding parameters.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.107-117
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• 1999

A comparison of a neural network approach with the conventional statistical methods, multiple regression and band ratio analyses, for the estimation of water quality parameters in presented in this paper. The Landsat TM image of Lake Daechung acquired on March 18, 1996 and the thirty in-situ sampling data sets measured during the satellite overpass were used for the comparison. We employed a three-layered and feedforward network trained by backpropagation algorithm. A cross validation was applied because of the small number of training pairs available for this study. The neural network showed much more successful performance than the conventional statistical analyses, although the results of the conventional statistical analyses were significant. The superiority of a neural network to statistical methods in estimating water quality parameters is strictly because the neural network modeled non-linear behaviors of data sets much better.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.6
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• pp.698-705
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• 2008

When electromagnetic waves propagate through atmosphere, waves are affected by various factors. Atmosphere normally consists of different molecular species, water vapours, rain, fog, snow and small suspended particles called aerosols. The distributions of atmosphere molecules, water vapours, rain rate, snowfall and aerosol are dependent on geometrical regions or environment. In order to predict propagation characteristics in atmospheric environment, statistical analysis of the relevant parameters such as temperature, humidity, atmospheric pressure, wind speed, areosol and rainfall is crucial. In this paper, we performed a long-term statistical analysis for the atmospheric parameters in domestic environments and analyzed the propagation characteristics through atmosphere based on that.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.8
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• pp.643-650
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• 2014

Gear transmission system is widely applied in engineering. As the problem of contact fatigue, wear, lubrication failure etc, the condition of gear teeth contacts will be worse. The vibration and sound signals in the gear system will be affected by the some failures like scuffing, abrasive wear and spalling due to the deterioration of gear teeth surface. By studying the estimation of specific film thickness, measurement of reduction in tooth thickness, visual examination of wear mechanisms on the gear teeth and their effects on the statistical parameters of vibration and sound signals, the research obtained the satisfactory results on accessing the surface fatigue wear in a spur gear system. The paper utilizes the relationship between statistical parameters obtained from sound signals and Stribeck curve to confirm the hypothesis of dependency of surface fatigue wear, specific film thickness.

• International Journal of Quality Innovation
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• v.7 no.3
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• pp.107-115
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• 2006

Control charts are important tools of statistical quality control. In 1956, Duncan first proposed the economic design of $\bar{x}-control$ charts to control normal process means and insure that the economic design control chart actually has a lower cost, compared with a Shewhart control chart. An moving average (MA) control chart is more effective than a Shewhart control chart in detecting small process shifts and is considered by some to be simpler to implement than the CUSUM. An economic design of MA control chart has also been proposed in 2005. The weaknesses to only the economic design are poor statistics because it dose not consider type I or type II errors and average time to signal when selecting design parameters for control chart. This paper provides a construction of an economic-statistical model to determine the optimal parameters of an MA control chart to improve economic design. A numerical example is employed to demonstrate the model's working and its sensitivity analysis is also provided.